Remote Sensing based modelling of Annual Surface Mass Balances of Chhota Shigiri Glacier, Western Himalayas, India

NASA Astrophysics Data System (ADS)

Chandrasekharan, Anita; Ramsankaran, Raaj

2017-04-01

The current study aims at modelling glacier mass balances over Chhota Shigiri glacier (32.28o N; 77.58° E) in Himachal Pradesh, India using the Equilibrium Line Altitude (ELA) gradient approach proposed by Rabatel et al. (2005). The model requires yearly ELA, average mass balance and mass balance gradient to estimate annual mass balance of a glacier which can be obtained either through field measurements or remote sensing observations. However, in view of the general scenario of lack of field data for Himalayan glaciers, in this study the model has been applied only using the inputs derived through multi-temporal satellite remote sensing observations thus eliminating the need for any field measurements. Preliminary analysis show that the obtained results are comparable with the observed field mass balance. The results also demonstrate that this approach with remote sensing inputs has potential to be used for glacier mass balance estimations provided good quality multi-temporal remote sensing dataset are available.

Sense of Cohesion among Community Activists Engaging in Volunteer Activity

ERIC Educational Resources Information Center

Levy, Drorit; Itzhaky, Haya; Zanbar, Lea; Schwartz, Chaya

2012-01-01

The present article attempts to shed light on the direct and indirect contribution of personal resources and community indices to Sense of Cohesion among activists engaging in community volunteer work. The sample comprised 481 activists. Based on social systems theory, three levels of variables were examined: (1) inputs, which included personal…

Wireless Computing Architecture III

DTIC Science & Technology

2013-09-01

MIMO Multiple-Input and Multiple-Output MIMO /CON MIMO with concurrent hannel access and estimation MU- MIMO Multiuser MIMO OFDM Orthogonal...compressive sensing \\; a design for concurrent channel estimation in scalable multiuser MIMO networking; and novel networking protocols based on machine...Network, Antenna Arrays, UAV networking, Angle of Arrival, Localization MIMO , Access Point, Channel State Information, Compressive Sensing 16

Load power device, system and method of load control and management employing load identification

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

Yang, Yi; Luebke, Charles John; Schoepf, Thomas J.

A load power device includes a power input, at least one power output for at least one load, a plurality of sensors structured to sense voltage and current at the at least one power output, and a processor. The processor provides: (a) load identification based upon the sensed voltage and current, and (b) load control and management based upon the load identification.

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.

Combining Space-Based and In-Situ Measurements to Track Flooding in Thailand

NASA Technical Reports Server (NTRS)

Chien, Steve; Doubleday, Joshua; Mclaren, David; Tran, Daniel; Tanpipat, Veerachai; Chitradon, Royal; Boonya-aaroonnet, Surajate; Thanapakpawin, Porranee; Khunboa, Chatchai; Leelapatra, Watis;

Global versus local mechanisms of temperature sensing in ion channels.

PubMed

Arrigoni, Cristina; Minor, Daniel L

2018-05-01

Ion channels turn diverse types of inputs, ranging from neurotransmitters to physical forces, into electrical signals. Channel responses to ligands generally rely on binding to discrete sensor domains that are coupled to the portion of the channel responsible for ion permeation. By contrast, sensing physical cues such as voltage, pressure, and temperature arises from more varied mechanisms. Voltage is commonly sensed by a local, domain-based strategy, whereas the predominant paradigm for pressure sensing employs a global response in channel structure to membrane tension changes. Temperature sensing has been the most challenging response to understand and whether discrete sensor domains exist for pressure and temperature has been the subject of much investigation and debate. Recent exciting advances have uncovered discrete sensor modules for pressure and temperature in force-sensitive and thermal-sensitive ion channels, respectively. In particular, characterization of bacterial voltage-gated sodium channel (BacNa V ) thermal responses has identified a coiled-coil thermosensor that controls channel function through a temperature-dependent unfolding event. This coiled-coil thermosensor blueprint recurs in other temperature sensitive ion channels and thermosensitive proteins. Together with the identification of ion channel pressure sensing domains, these examples demonstrate that "local" domain-based solutions for sensing force and temperature exist and highlight the diversity of both global and local strategies that channels use to sense physical inputs. The modular nature of these newly discovered physical signal sensors provides opportunities to engineer novel pressure-sensitive and thermosensitive proteins and raises new questions about how such modular sensors may have evolved and empowered ion channel pores with new sensibilities.

Use of Landsat and environmental satellite data in evapotranspiration estimation from a wildland area

NASA Technical Reports Server (NTRS)

Khorram, S.; Smith, H. G.

1979-01-01

A remote sensing-aided procedure was applied to the watershed-wide estimation of water loss to the atmosphere (evapotranspiration, ET). The approach involved a spatially referenced databank based on both remotely sensed and ground-acquired information. Physical models for both estimation of ET and quantification of input parameters are specified, and results of the investigation are outlined.

Tool actuation and force feedback on robot-assisted microsurgery system

NASA Technical Reports Server (NTRS)

Das, Hari (Inventor); Ohm, Tim R. (Inventor); Boswell, Curtis D. (Inventor); Steele, Robert D. (Inventor)

2002-01-01

An input control device with force sensors is configured to sense hand movements of a surgeon performing a robot-assisted microsurgery. The sensed hand movements actuate a mechanically decoupled robot manipulator. A microsurgical manipulator, attached to the robot manipulator, is activated to move small objects and perform microsurgical tasks. A force-feedback element coupled to the robot manipulator and the input control device provides the input control device with an amplified sense of touch in the microsurgical manipulator.

A New MEMS Gyroscope Used for Single-Channel Damping

PubMed Central

Zhang, Zengping; Zhang, Wei; Zhang, Fuxue; Wang, Biao

2015-01-01

The silicon micromechanical gyroscope, which will be introduced in this paper, represents a novel MEMS gyroscope concept. It is used for the damping of a single-channel control system of rotating aircraft. It differs from common MEMS gyroscopes in that does not have a drive structure, itself, and only has a sense structure. It is installed on a rotating aircraft, and utilizes the aircraft spin to make its sensing element obtain angular momentum. When the aircraft is subjected to an angular rotation, a periodic Coriolis force is induced in the direction orthogonal to both the angular momentum and the angular velocity input axis. This novel MEMS gyroscope can thus sense angular velocity inputs. The output sensing signal is exactly an amplitude-modulation signal. Its envelope is proportional to the input angular velocity, and the carrier frequency corresponds to the spin frequency of the rotating aircraft, so the MEMS gyroscope can not only sense the transverse angular rotation of an aircraft, but also automatically change the carrier frequency over the change of spin frequency, making it very suitable for the damping of a single-channel control system of a rotating aircraft. In this paper, the motion equation of the MEMS gyroscope has been derived. Then, an analysis has been carried to solve the motion equation and dynamic parameters. Finally, an experimental validation has been done based on a precision three axis rate table. The correlation coefficients between the tested data and the theoretical values are 0.9969, 0.9872 and 0.9842, respectively. These results demonstrate that both the design and sensing mechanism are correct. PMID:25942638

Enhancing PTFs with remotely sensed data for multi-scale soil water retention estimation

NASA Astrophysics Data System (ADS)

Jana, Raghavendra B.; Mohanty, Binayak P.

2011-03-01

SummaryUse of remotely sensed data products in the earth science and water resources fields is growing due to increasingly easy availability of the data. Traditionally, pedotransfer functions (PTFs) employed for soil hydraulic parameter estimation from other easily available data have used basic soil texture and structure information as inputs. Inclusion of surrogate/supplementary data such as topography and vegetation information has shown some improvement in the PTF's ability to estimate more accurate soil hydraulic parameters. Artificial neural networks (ANNs) are a popular tool for PTF development, and are usually applied across matching spatial scales of inputs and outputs. However, different hydrologic, hydro-climatic, and contaminant transport models require input data at different scales, all of which may not be easily available from existing databases. In such a scenario, it becomes necessary to scale the soil hydraulic parameter values estimated by PTFs to suit the model requirements. Also, uncertainties in the predictions need to be quantified to enable users to gauge the suitability of a particular dataset in their applications. Bayesian Neural Networks (BNNs) inherently provide uncertainty estimates for their outputs due to their utilization of Markov Chain Monte Carlo (MCMC) techniques. In this paper, we present a PTF methodology to estimate soil water retention characteristics built on a Bayesian framework for training of neural networks and utilizing several in situ and remotely sensed datasets jointly. The BNN is also applied across spatial scales to provide fine scale outputs when trained with coarse scale data. Our training data inputs include ground/remotely sensed soil texture, bulk density, elevation, and Leaf Area Index (LAI) at 1 km resolutions, while similar properties measured at a point scale are used as fine scale inputs. The methodology was tested at two different hydro-climatic regions. We also tested the effect of varying the support scale of the training data for the BNNs by sequentially aggregating finer resolution training data to coarser resolutions, and the applicability of the technique to upscaling problems. The BNN outputs are corrected for bias using a non-linear CDF-matching technique. Final results show good promise of the suitability of this Bayesian Neural Network approach for soil hydraulic parameter estimation across spatial scales using ground-, air-, or space-based remotely sensed geophysical parameters. Inclusion of remotely sensed data such as elevation and LAI in addition to in situ soil physical properties improved the estimation capabilities of the BNN-based PTF in certain conditions.

Method and system to estimate variables in an integrated gasification combined cycle (IGCC) plant

DOEpatents

Kumar, Aditya; Shi, Ruijie; Dokucu, Mustafa

2013-09-17

System and method to estimate variables in an integrated gasification combined cycle (IGCC) plant are provided. The system includes a sensor suite to measure respective plant input and output variables. An extended Kalman filter (EKF) receives sensed plant input variables and includes a dynamic model to generate a plurality of plant state estimates and a covariance matrix for the state estimates. A preemptive-constraining processor is configured to preemptively constrain the state estimates and covariance matrix to be free of constraint violations. A measurement-correction processor may be configured to correct constrained state estimates and a constrained covariance matrix based on processing of sensed plant output variables. The measurement-correction processor is coupled to update the dynamic model with corrected state estimates and a corrected covariance matrix. The updated dynamic model may be configured to estimate values for at least one plant variable not originally sensed by the sensor suite.

Development of smart piezoelectric transducer self-sensing, self-diagnosis and tuning schemes for structural health monitoring applications

NASA Astrophysics Data System (ADS)

Lee, Sang Jun

Autonomous structural health monitoring (SHM) systems using active sensing devices have been studied extensively to diagnose the current state of aerospace, civil infrastructure and mechanical systems in near real-time and aims to eventually reduce life-cycle costs by replacing current schedule-based maintenance with condition-based maintenance. This research develops four schemes for SHM applications: (1) a simple and reliable PZT transducer self-sensing scheme; (2) a smart PZT self-diagnosis scheme; (3) an instantaneous reciprocity-based PZT diagnosis scheme; and (4) an effective PZT transducer tuning scheme. First, this research develops a PZT transducer self-sensing scheme, which is a necessary condition to accomplish a PZT transducer self-diagnosis. Main advantages of the proposed self-sensing approach are its simplicity and adaptability. The necessary hardware is only an additional self-sensing circuit which includes a minimum of electric components. With this circuit, the self-sensing parameters can be calibrated instantaneously in the presence of changing operational and environmental conditions of the system. In particular, this self-sensing scheme focuses on estimating the mechanical response in the time domain for the subsequent applications of the PZT transducer self-diagnosis and tuning with guided wave propagation. The most significant challenge of this self-sensing comes from the fact that the magnitude of the mechanical response is generally several orders of magnitude smaller than that of the input signal. The proposed self-sensing scheme fully takes advantage of the fact that any user-defined input signals can be applied to a host structure and the input waveform is known. The performance of the proposed self-sensing scheme is demonstrated by theoretical analysis, numerical simulations and various experiments. Second, this research proposes a smart PZT transducer self-diagnosis scheme based on the developed self-sensing scheme. Conventionally, the capacitance change of the PZT wafer is monitored to identify the abnormal PZT condition because the capacitance of the PZT wafer is linearly proportional to its size and also related to the bonding condition. However, temperature variation is another primary factor that affects the PZT capacitance. To ensure the reliable transducer self-diagnosis, two different self-diagnosis features are proposed to differentiate two main PZT wafer defects, i.e., PZT debonding and PZT cracking, from temperature variations and structural damages. The PZT debonding is identified using two indices based on time reversal process (TRP) without any baseline data. Also, the PZT cracking is identified by monitoring the change of the generated Lamb wave power ratio index with respect to the driving frequency. The uniqueness of this self-diagnosis scheme is that the self-diagnosis features can differentiate the PZT defects from environmental variations and structural damages. Therefore, it is expected to minimize false-alarms which are induced by operational or environmental variations as well as structural damages. The applicability of the proposed self-diagnosis scheme is verified by theoretical analysis, numerical simulations, and experimental tests. Third, a new methodology of guided wave-based PZT transducer diagnosis is developed to identify PZT transducer defects without using prior baseline data. This methodology can be applied when a number of same-size PZT transducers are attached to a target structure to form a sensor network. The advantage of the proposed technique is that abnormal PZT transducers among intact PZT transducers can be detected even when the system being monitored is subjected to varying operational and environmental conditions or changing structural conditions. To achieve this goal, the proposed diagnosis technique utilizes the linear reciprocity of guided wave propagation between a pair of surface-bonded PZT transducers. Finally, a PZT transducer tuning scheme is being developed for selective Lamb wave excitation and sensing. This is useful for structural damage detection based on Lamb wave propagation because the proper transducer size and the corresponding input frequency can be is crucial for selective Lamb wave excitation and sensing. The circular PZT response model is derived, and the energy balance is included for a better prediction of the PZT responses because the existing PZT response models do not consider any energy balance between Lamb wave modes. In addition, two calibration methods are also suggested in order to model the PZT responses more accurately by considering a bonding layer effect. (Abstract shortened by UMI.)

A motion sensing-based framework for robotic manipulation.

PubMed

Deng, Hao; Xia, Zeyang; Weng, Shaokui; Gan, Yangzhou; Fang, Peng; Xiong, Jing

2016-01-01

To data, outside of the controlled environments, robots normally perform manipulation tasks operating with human. This pattern requires the robot operators with high technical skills training for varied teach-pendant operating system. Motion sensing technology, which enables human-machine interaction in a novel and natural interface using gestures, has crucially inspired us to adopt this user-friendly and straightforward operation mode on robotic manipulation. Thus, in this paper, we presented a motion sensing-based framework for robotic manipulation, which recognizes gesture commands captured from motion sensing input device and drives the action of robots. For compatibility, a general hardware interface layer was also developed in the framework. Simulation and physical experiments have been conducted for preliminary validation. The results have shown that the proposed framework is an effective approach for general robotic manipulation with motion sensing control.

Distributed optical fiber vibration sensor based on Sagnac interference in conjunction with OTDR.

PubMed

Pan, Chao; Liu, Xiaorui; Zhu, Hui; Shan, Xuekang; Sun, Xiaohan

2017-08-21

A real-time distributed optical fiber vibration sensing prototype based on the Sagnac interference in conjunction with the optical time domain reflectometry (OTDR) was developed. The sensing mechanism for single- and multi-points vibrations along the sensing fiber was analyzed theoretically and demonstrated experimentally. The experimental results show excellent agreement with the theoretical models. It is verified that single-point vibration induces a significantly abrupt and monotonous power change in the corresponding position of OTDR trace. As to multi-points vibrations, the detection of the following vibration is influenced by all previous ones. However, if the distance between the adjacent two vibrations is larger than half of the input optical pulse width, abrupt power changes induced by them are separate and still monotonous. A time-shifting differential module was developed and carried out to convert vibration-induced power changes to pulses. Consequently, vibrations can be located accurately by measuring peak or valley positions of the vibration-induced pulses. It is demonstrated that when the width and peak power of input optical pulse are set to 1 μs and 35 mW, respectively, the position error is less than ± 0.5 m in a sensing range of more than 16 km, with the spatial resolution of ~110 m.

Realization of 2:1 MUX using Mach Zhender Interferometer structure and its application in selection of output signal of MOEMS pressure and temperature sensor

NASA Astrophysics Data System (ADS)

Jindal, Sumit Kumar; Raghuwanshi, Sanjeev Kumar

2016-03-01

In this paper we have initially designed a circular diaphragm based MOEMS pressure sensor and a thermistor based temperature sensor. This has been done by the help of externally modulated LiNbO3 Mach Zhender Interferometer (MZI) which senses the input voltage signal and modulates it to give an output in the form of intensity of light. This output is then calibrated to understand the proper relation between the input applied and output measured. The next aspect has been the use of MZI to work as a 2:1 MUX where two input lines are -pressure signal and temperature signal. The arrangement of MZI is then modulated in such a way that based on the requirement it chooses the proper input signal and sends it to the output port for the measurement. The design has been simulated in Opti-BPM software.

Sensitivity of geographic information system outputs to errors in remotely sensed data

NASA Technical Reports Server (NTRS)

Ramapriyan, H. K.; Boyd, R. K.; Gunther, F. J.; Lu, Y. C.

1981-01-01

The sensitivity of the outputs of a geographic information system (GIS) to errors in inputs derived from remotely sensed data (RSD) is investigated using a suitability model with per-cell decisions and a gridded geographic data base whose cells are larger than the RSD pixels. The process of preparing RSD as input to a GIS is analyzed, and the errors associated with classification and registration are examined. In the case of the model considered, it is found that the errors caused during classification and registration are partially compensated by the aggregation of pixels. The compensation is quantified by means of an analytical model, a Monte Carlo simulation, and experiments with Landsat data. The results show that error reductions of the order of 50% occur because of aggregation when 25 pixels of RSD are used per cell in the geographic data base.

Experimental image alignment system

NASA Technical Reports Server (NTRS)

Moyer, A. L.; Kowel, S. T.; Kornreich, P. G.

1980-01-01

A microcomputer-based instrument for image alignment with respect to a reference image is described which uses the DEFT sensor (Direct Electronic Fourier Transform) for image sensing and preprocessing. The instrument alignment algorithm which uses the two-dimensional Fourier transform as input is also described. It generates signals used to steer the stage carrying the test image into the correct orientation. This algorithm has computational advantages over algorithms which use image intensity data as input and is suitable for a microcomputer-based instrument since the two-dimensional Fourier transform is provided by the DEFT sensor.

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

PubMed

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

2006-08-01

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

Probability-based constrained MPC for structured uncertain systems with state and random input delays

NASA Astrophysics Data System (ADS)

Lu, Jianbo; Li, Dewei; Xi, Yugeng

2013-07-01

This article is concerned with probability-based constrained model predictive control (MPC) for systems with both structured uncertainties and time delays, where a random input delay and multiple fixed state delays are included. The process of input delay is governed by a discrete-time finite-state Markov chain. By invoking an appropriate augmented state, the system is transformed into a standard structured uncertain time-delay Markov jump linear system (MJLS). For the resulting system, a multi-step feedback control law is utilised to minimise an upper bound on the expected value of performance objective. The proposed design has been proved to stabilise the closed-loop system in the mean square sense and to guarantee constraints on control inputs and system states. Finally, a numerical example is given to illustrate the proposed results.

The wavelength-tunable tapered surface plasmon resonance fiber sensor based on separated input-output channels

NASA Astrophysics Data System (ADS)

Chen, Shimeng; Liu, Yun; Gao, Xiaotong; Liu, Xiuxin; Peng, Wei

2014-11-01

We present a wavelength-tunable tapered optics fiber surface Plasmon resonance (SPR) sensor by polishing the end faces of multimode fibers(MMF).Two hard plastic clad optical fibers joint closely and are used as the light input and output channels. Their end faces are polished to produce two oblique planes, which are coated with gold film to be the sensing surface and the front mirror. The presence of the tapered geometry formed by the two oblique planes in the orthogonal directions makes it possible to adjust incident angle through changing the tilt angles of the two end faces, so as to achieve tuning the SPR coupling wavelength-angle pair. Compared with previous researches based a tapered optic fiber probe, we report the approach theoretically increase the signal noise ratio (SNR) by separating incident and emergent light propagating in the different coordinate fiber. Since fabricating the sensing surface and the front mirror on the two fibers to replace one single fiber tip, there is more incident light can reach the sensing surface and satisfy SPR effective. In addition, this improvement in structure has advantages of large grinding and sensing area, which can lead to high sensitivity and simple manufacture process of the sensor. Experimental measurement demonstrates the sensor has a favorable SPR resonanceabsorption and the ability of measuring refractive index (RI) of aqueous solution. This novel tapered SPR sensor has the potential to be applied to the biological sensing field.

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.

Supervised spike-timing-dependent plasticity: a spatiotemporal neuronal learning rule for function approximation and decisions.

PubMed

Franosch, Jan-Moritz P; Urban, Sebastian; van Hemmen, J Leo

2013-12-01

How can an animal learn from experience? How can it train sensors, such as the auditory or tactile system, based on other sensory input such as the visual system? Supervised spike-timing-dependent plasticity (supervised STDP) is a possible answer. Supervised STDP trains one modality using input from another one as "supervisor." Quite complex time-dependent relationships between the senses can be learned. Here we prove that under very general conditions, supervised STDP converges to a stable configuration of synaptic weights leading to a reconstruction of primary sensory input.

Forecasting tidal marsh elevation and habitat change through fusion of Earth observations and a process model

USGS Publications Warehouse

Byrd, Kristin B.; Windham-Myers, Lisamarie; Leeuw, Thomas; Downing, Bryan D.; Morris, James T.; Ferner, Matthew C.

2016-01-01

Reducing uncertainty in data inputs at relevant spatial scales can improve tidal marsh forecasting models, and their usefulness in coastal climate change adaptation decisions. The Marsh Equilibrium Model (MEM), a one-dimensional mechanistic elevation model, incorporates feedbacks of organic and inorganic inputs to project elevations under sea-level rise scenarios. We tested the feasibility of deriving two key MEM inputs—average annual suspended sediment concentration (SSC) and aboveground peak biomass—from remote sensing data in order to apply MEM across a broader geographic region. We analyzed the precision and representativeness (spatial distribution) of these remote sensing inputs to improve understanding of our study region, a brackish tidal marsh in San Francisco Bay, and to test the applicable spatial extent for coastal modeling. We compared biomass and SSC models derived from Landsat 8, DigitalGlobe WorldView-2, and hyperspectral airborne imagery. Landsat 8-derived inputs were evaluated in a MEM sensitivity analysis. Biomass models were comparable although peak biomass from Landsat 8 best matched field-measured values. The Portable Remote Imaging Spectrometer SSC model was most accurate, although a Landsat 8 time series provided annual average SSC estimates. Landsat 8-measured peak biomass values were randomly distributed, and annual average SSC (30 mg/L) was well represented in the main channels (IQR: 29–32 mg/L), illustrating the suitability of these inputs across the model domain. Trend response surface analysis identified significant diversion between field and remote sensing-based model runs at 60 yr due to model sensitivity at the marsh edge (80–140 cm NAVD88), although at 100 yr, elevation forecasts differed less than 10 cm across 97% of the marsh surface (150–200 cm NAVD88). Results demonstrate the utility of Landsat 8 for landscape-scale tidal marsh elevation projections due to its comparable performance with the other sensors, temporal frequency, and cost. Integration of remote sensing data with MEM should advance regional projections of marsh vegetation change by better parameterizing MEM inputs spatially. Improving information for coastal modeling will support planning for ecosystem services, including habitat, carbon storage, and flood protection.

Considerations and techniques for incorporating remotely sensed imagery into the land resource management process.

NASA Technical Reports Server (NTRS)

Brooner, W. G.; Nichols, D. A.

1972-01-01

Development of a scheme for utilizing remote sensing technology in an operational program for regional land use planning and land resource management program applications. The scheme utilizes remote sensing imagery as one of several potential inputs to derive desired and necessary data, and considers several alternative approaches to the expansion and/or reduction and analysis of data, using automated data handling techniques. Within this scheme is a five-stage program development which includes: (1) preliminary coordination, (2) interpretation and encoding, (3) creation of data base files, (4) data analysis and generation of desired products, and (5) applications.

Adding Remote Sensing Data Products to the Nutrient Management Decision Support Toolbox

NASA Technical Reports Server (NTRS)

Lehrter, John; Schaeffer, Blake; Hagy, Jim; Spiering, Bruce; Blonski, Slawek; Underwood, Lauren; Ellis, Chris

2011-01-01

Some of the primary issues that manifest from nutrient enrichment and eutrophication (Figure 1) may be observed from satellites. For example, remotely sensed estimates of chlorophyll a (chla), total suspended solids (TSS), and light attenuation (Kd) or water clarity, which are often associated with elevated nutrient inputs, are data products collected daily and globally for coastal systems from satellites such as NASA s MODIS (Figure 2). The objective of this project is to inform water quality decision making activities using remotely sensed water quality data. In particular, we seek to inform the development of numeric nutrient criteria. In this poster we demonstrate an approach for developing nutrient criteria based on remotely sensed chla.

Single-Event Effect Testing of the Linear Technology LTC6103HMS8#PBF Current Sense Amplifier

NASA Technical Reports Server (NTRS)

Yau, Ka-Yen; Campola, Michael J.; Wilcox, Edward

2016-01-01

The LTC6103HMS8#PBF (henceforth abbreviated as LTC6103) current sense amplifier from Linear Technology was tested for both destructive and non-destructive single-event effects (SEE) using the heavy-ion cyclotron accelerator beam at Lawrence Berkeley National Laboratory (LBNL) Berkeley Accelerator Effects (BASE) facility. During testing, the input voltages and output currents were monitored to detect single event latch-up (SEL) and single-event transients (SETs).

Sparse Polynomial Chaos Surrogate for ACME Land Model via Iterative Bayesian Compressive Sensing

NASA Astrophysics Data System (ADS)

Sargsyan, K.; Ricciuto, D. M.; Safta, C.; Debusschere, B.; Najm, H. N.; Thornton, P. E.

2015-12-01

For computationally expensive climate models, Monte-Carlo approaches of exploring the input parameter space are often prohibitive due to slow convergence with respect to ensemble size. To alleviate this, we build inexpensive surrogates using uncertainty quantification (UQ) methods employing Polynomial Chaos (PC) expansions that approximate the input-output relationships using as few model evaluations as possible. However, when many uncertain input parameters are present, such UQ studies suffer from the curse of dimensionality. In particular, for 50-100 input parameters non-adaptive PC representations have infeasible numbers of basis terms. To this end, we develop and employ Weighted Iterative Bayesian Compressive Sensing to learn the most important input parameter relationships for efficient, sparse PC surrogate construction with posterior uncertainty quantified due to insufficient data. Besides drastic dimensionality reduction, the uncertain surrogate can efficiently replace the model in computationally intensive studies such as forward uncertainty propagation and variance-based sensitivity analysis, as well as design optimization and parameter estimation using observational data. We applied the surrogate construction and variance-based uncertainty decomposition to Accelerated Climate Model for Energy (ACME) Land Model for several output QoIs at nearly 100 FLUXNET sites covering multiple plant functional types and climates, varying 65 input parameters over broad ranges of possible values. This work is supported by the U.S. Department of Energy, Office of Science, Biological and Environmental Research, Accelerated Climate Modeling for Energy (ACME) project. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Utility of Satellite Remote Sensing for Land-Atmosphere Coupling and Drought Metrics

NASA Technical Reports Server (NTRS)

Roundy, Joshua K.; Santanello, Joseph A.

2017-01-01

Feedbacks between the land and the atmosphere can play an important role in the water cycle and a number of studies have quantified Land-Atmosphere (L-A) interactions and feedbacks through observations and prediction models. Due to the complex nature of L-A interactions, the observed variables are not always available at the needed temporal and spatial scales. This work derives the Coupling Drought Index (CDI) solely from satellite data and evaluates the input variables and the resultant CDI against in-situ data and reanalysis products. NASA's AQUA satellite and retrievals of soil moisture and lower tropospheric temperature and humidity properties are used as input. Overall, the AQUA-based CDI and its inputs perform well at a point, spatially, and in time (trends) compared to in-situ and reanalysis products. In addition, this work represents the first time that in-situ observations were utilized for the coupling classification and CDI. The combination of in-situ and satellite remote sensing CDI is unique and provides an observational tool for evaluating models at local and large scales. Overall, results indicate that there is sufficient information in the signal from simultaneous measurements of the land and atmosphere from satellite remote sensing to provide useful information for applications of drought monitoring and coupling metrics.

Utility of Satellite Remote Sensing for Land-Atmosphere Coupling and Drought Metrics

PubMed Central

Roundy, Joshua K.; Santanello, Joseph A.

2018-01-01

Feedbacks between the land and the atmosphere can play an important role in the water cycle and a number of studies have quantified Land-Atmosphere (L-A) interactions and feedbacks through observations and prediction models. Due to the complex nature of L-A interactions, the observed variables are not always available at the needed temporal and spatial scales. This work derives the Coupling Drought Index (CDI) solely from satellite data and evaluates the input variables and the resultant CDI against in-situ data and reanalysis products. NASA’s AQUA satellite and retrievals of soil moisture and lower tropospheric temperature and humidity properties are used as input. Overall, the AQUA-based CDI and its inputs perform well at a point, spatially, and in time (trends) compared to in-situ and reanalysis products. In addition, this work represents the first time that in-situ observations were utilized for the coupling classification and CDI. The combination of in-situ and satellite remote sensing CDI is unique and provides an observational tool for evaluating models at local and large scales. Overall, results indicate that there is sufficient information in the signal from simultaneous measurements of the land and atmosphere from satellite remote sensing to provide useful information for applications of drought monitoring and coupling metrics. PMID:29645012

Cybernetic group method of data handling (GMDH) statistical learning for hyperspectral remote sensing inverse problems in coastal ocean optics

NASA Astrophysics Data System (ADS)

Filippi, Anthony Matthew

For complex systems, sufficient a priori knowledge is often lacking about the mathematical or empirical relationship between cause and effect or between inputs and outputs of a given system. Automated machine learning may offer a useful solution in such cases. Coastal marine optical environments represent such a case, as the optical remote sensing inverse problem remains largely unsolved. A self-organizing, cybernetic mathematical modeling approach known as the group method of data handling (GMDH), a type of statistical learning network (SLN), was used to generate explicit spectral inversion models for optically shallow coastal waters. Optically shallow water light fields represent a particularly difficult challenge in oceanographic remote sensing. Several algorithm-input data treatment combinations were utilized in multiple experiments to automatically generate inverse solutions for various inherent optical property (IOP), bottom optical property (BOP), constituent concentration, and bottom depth estimations. The objective was to identify the optimal remote-sensing reflectance Rrs(lambda) inversion algorithm. The GMDH also has the potential of inductive discovery of physical hydro-optical laws. Simulated data were used to develop generalized, quasi-universal relationships. The Hydrolight numerical forward model, based on radiative transfer theory, was used to compute simulated above-water remote-sensing reflectance Rrs(lambda) psuedodata, matching the spectral channels and resolution of the experimental Naval Research Laboratory Ocean PHILLS (Portable Hyperspectral Imager for Low-Light Spectroscopy) sensor. The input-output pairs were for GMDH and artificial neural network (ANN) model development, the latter of which was used as a baseline, or control, algorithm. Both types of models were applied to in situ and aircraft data. Also, in situ spectroradiometer-derived Rrs(lambda) were used as input to an optimization-based inversion procedure. Target variables included bottom depth z b, chlorophyll a concentration [chl- a], spectral bottom irradiance reflectance Rb(lambda), and spectral total absorption a(lambda) and spectral total backscattering bb(lambda) coefficients. When applying the cybernetic and neural models to in situ HyperTSRB-derived Rrs, the difference in the means of the absolute error of the inversion estimates for zb was significant (alpha = 0.05). GMDH yielded significantly better zb than the ANN. The ANN model posted a mean absolute error (MAE) of 0.62214 m, compared with 0.55161 m for GMDH.

Survey of in-situ and remote sensing methods for soil moisture determination

NASA Technical Reports Server (NTRS)

Schmugge, T. J.; Jackson, T. J.; Mckim, H. L.

1981-01-01

General methods for determining the moisture content in the surface layers of the soil based on in situ or point measurements, soil water models and remote sensing observations are surveyed. In situ methods described include gravimetric techniques, nuclear techniques based on neutron scattering or gamma-ray attenuation, electromagnetic techniques, tensiometric techniques and hygrometric techniques. Soil water models based on column mass balance treat soil moisture contents as a result of meteorological inputs (precipitation, runoff, subsurface flow) and demands (evaporation, transpiration, percolation). The remote sensing approaches are based on measurements of the diurnal range of surface temperature and the crop canopy temperature in the thermal infrared, measurements of the radar backscattering coefficient in the microwave region, and measurements of microwave emission or brightness temperature. Advantages and disadvantages of the various methods are pointed out, and it is concluded that a successful monitoring system must incorporate all of the approaches considered.

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.

Remote Sensing of Complex Flows by Doppler Wind Lidar: Issues and Preliminary Recommendations

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

Clifton, Andrew; Boquet, Matthieu; Burin Des Roziers, Edward

Remote sensing of winds using lidar has become popular and useful in the wind energy industry. Extensive experience has been gained with using lidar for applications including land-based and offshore resource assessment, plant operations, and turbine control. Prepared by members of International Energy Agency Task 32, this report describes the state of the art in the use of Doppler wind lidar for resource assessment in complex flows. The report will be used as input for future recommended practices on this topic.

The application of remote sensing techniques to inter and intra urban analysis

NASA Technical Reports Server (NTRS)

Horton, F. E.

1972-01-01

This is an effort to assess the applicability of air and spaceborne photography toward providing data inputs to urban and regional planning, management, and research. Through evaluation of remote sensing inputs to urban change detection systems, analyzing an effort to replicate an existing urban land use data file using remotely sensed data, estimating population and dwelling units from imagery, and by identifying and evaluating a system of urban places ultilizing space photography, it was determined that remote sensing can provide data concerning land use, changes in commercial structure, data for transportation planning, housing quality, residential dynamics, and population density.

Single-Input and Multiple-Output Surface Acoustic Wave Sensing for Damage Quantification in Piezoelectric Sensors.

PubMed

Pamwani, Lavish; Habib, Anowarul; Melandsø, Frank; Ahluwalia, Balpreet Singh; Shelke, Amit

2018-06-22

The main aim of the paper is damage detection at the microscale in the anisotropic piezoelectric sensors using surface acoustic waves (SAWs). A novel technique based on the single input and multiple output of Rayleigh waves is proposed to detect the microscale cracks/flaws in the sensor. A convex-shaped interdigital transducer is fabricated for excitation of divergent SAWs in the sensor. An angularly shaped interdigital transducer (IDT) is fabricated at 0 degrees and ±20 degrees for sensing the convex shape evolution of SAWs. A precalibrated damage was introduced in the piezoelectric sensor material using a micro-indenter in the direction perpendicular to the pointing direction of the SAW. Damage detection algorithms based on empirical mode decomposition (EMD) and principal component analysis (PCA) are implemented to quantify the evolution of damage in piezoelectric sensor material. The evolution of the damage was quantified using a proposed condition indicator (CI) based on normalized Euclidean norm of the change in principal angles, corresponding to pristine and damaged states. The CI indicator provides a robust and accurate metric for detection and quantification of damage.

Remote Sensing Systems Optimization for Geobase Enhancement

DTIC Science & Technology

2003-03-01

through feedback from base users, as well as the researcher’s observations. 3.1 GeoBase and GIS Learning GeoBase and Geographic Information System ...Abstract The U.S. Air Force is in the process of implementing GeoBase, a geographic information system (GIS), throughout its worldwide installations...Geographic Information System (GIS). A GIS is a computer database that contains geo-spatial information . It is the principal tool used to input, view

An information system design for watershed-wide modeling of water loss to the atmosphere using remote sensing techniques

NASA Technical Reports Server (NTRS)

Khorram, S.

1977-01-01

Results are presented of a study intended to develop a general location-specific remote-sensing procedure for watershed-wide estimation of water loss to the atmosphere by evaporation and transpiration. The general approach involves a stepwise sequence of required information definition (input data), appropriate sample design, mathematical modeling, and evaluation of results. More specifically, the remote sensing-aided system developed to evaluate evapotranspiration employs a basic two-stage two-phase sample of three information resolution levels. Based on the discussed design, documentation, and feasibility analysis to yield timely, relatively accurate, and cost-effective evapotranspiration estimates on a watershed or subwatershed basis, work is now proceeding to implement this remote sensing-aided system.

A review of sensing technologies for small and large-scale touch panels

NASA Astrophysics Data System (ADS)

Akhtar, Humza; Kemao, Qian; Kakarala, Ramakrishna

2017-06-01

A touch panel is an input device for human computer interaction. It consists of a network of sensors, a sampling circuit and a micro controller for detecting and locating a touch input. Touch input can come from either finger or stylus depending upon the type of touch technology. These touch panels provide an intuitive and collaborative workspace so that people can perform various tasks with the use of their fingers instead of traditional input devices like keyboard and mouse. Touch sensing technology is not new. At the time of this writing, various technologies are available in the market and this paper reviews the most common ones. We review traditional designs and sensing algorithms for touch technology. We also observe that due to its various strengths, capacitive touch will dominate the large-scale touch panel industry in years to come. In the end, we discuss the motivation for doing academic research on large-scale panels.

Bioinspired active whisker sensor for robotic vibrissal tactile sensing

NASA Astrophysics Data System (ADS)

Ju, Feng; Ling, Shih-Fu

2014-12-01

A whisker transducer (WT) inspired by rat’s vibrissal tactile perception is proposed based on a transduction matrix model characterizing the electro-mechanical transduction process in both forward and backward directions. It is capable of acting as an actuator to sweep the whisker and simultaneously as a sensor to sense the force, motion, and mechanical impedance at whisker tip. Its validity is confirmed by numerical simulation using a finite element model. A prototype is then fabricated and its transduction matrix is determined by parameter identification. The calibrated WT can accurately sense mechanical impedance which is directly related to stiffness, mass and damping. Subsequent vibrissal tactile sensing of sandpaper texture reveals that the real part of mechanical impedance sensed by WT is correlated with sandpaper roughness. Texture discrimination is successfully achieved by inputting the real part to a k-means clustering algorithm. The mechanical impedance sensing ability as well as other features of the WT such as simultaneous-actuation-and-sensing makes it a good solution to robotic tactile sensing.

Simultaneous G-Quadruplex DNA Logic.

PubMed

Bader, Antoine; Cockroft, Scott L

2018-04-03

A fundamental principle of digital computer operation is Boolean logic, where inputs and outputs are described by binary integer voltages. Similarly, inputs and outputs may be processed on the molecular level as exemplified by synthetic circuits that exploit the programmability of DNA base-pairing. Unlike modern computers, which execute large numbers of logic gates in parallel, most implementations of molecular logic have been limited to single computing tasks, or sensing applications. This work reports three G-quadruplex-based logic gates that operate simultaneously in a single reaction vessel. The gates respond to unique Boolean DNA inputs by undergoing topological conversion from duplex to G-quadruplex states that were resolved using a thioflavin T dye and gel electrophoresis. The modular, addressable, and label-free approach could be incorporated into DNA-based sensors, or used for resolving and debugging parallel processes in DNA computing applications. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Natural Resource Information System. Volume 1: Overall description

NASA Technical Reports Server (NTRS)

1972-01-01

A prototype computer-based Natural Resource Information System was designed which could store, process, and display data of maximum usefulness to land management decision making. The system includes graphic input and display, the use of remote sensing as a data source, and it is useful at multiple management levels. A survey established current decision making processes and functions, information requirements, and data collection and processing procedures. The applications of remote sensing data and processing requirements were established. Processing software was constructed and a data base established using high-altitude imagery and map coverage of selected areas of SE Arizona. Finally a demonstration of system processing functions was conducted utilizing material from the data base.

Efficient two-dimensional compressive sensing in MIMO radar

NASA Astrophysics Data System (ADS)

Shahbazi, Nafiseh; Abbasfar, Aliazam; Jabbarian-Jahromi, Mohammad

2017-12-01

Compressive sensing (CS) has been a way to lower sampling rate leading to data reduction for processing in multiple-input multiple-output (MIMO) radar systems. In this paper, we further reduce the computational complexity of a pulse-Doppler collocated MIMO radar by introducing a two-dimensional (2D) compressive sensing. To do so, we first introduce a new 2D formulation for the compressed received signals and then we propose a new measurement matrix design for our 2D compressive sensing model that is based on minimizing the coherence of sensing matrix using gradient descent algorithm. The simulation results show that our proposed 2D measurement matrix design using gradient decent algorithm (2D-MMDGD) has much lower computational complexity compared to one-dimensional (1D) methods while having better performance in comparison with conventional methods such as Gaussian random measurement matrix.

Crankshaft position sensing with combined starter alternator

DOEpatents

Brandenburg, Larry Raymond; Miller, John Michael

2000-06-13

A crankshaft position sensing apparatus for use with an engine (16) having a combined starter/alternator assembly (18). The crankshaft position sensing apparatus includes a tone ring (38) with a sensor (36) and bandpass filter (46), having a cylinder identification input from a camshaft sensor (48), and a gain limiter (54). The sensing apparatus mounts near the rotor (30) of the combined starter/alternator assembly (18). The filtered crankshaft position signal can then be input into a vehicle system controller (58) and an inner loop controller (60). The starter/alternator assembly (18) in combination with an internal combustion engine is particularly useful for a hybrid electric vehicle system.

NASA Earth Science Research Results for Improved Regional Crop Yield Prediction

NASA Astrophysics Data System (ADS)

Mali, P.; O'Hara, C. G.; Shrestha, B.; Sinclair, T. R.; G de Goncalves, L. G.; Salado Navarro, L. R.

2007-12-01

National agencies such as USDA Foreign Agricultural Service (FAS), Production Estimation and Crop Assessment Division (PECAD) work specifically to analyze and generate timely crop yield estimates that help define national as well as global food policies. The USDA/FAS/PECAD utilizes a Decision Support System (DSS) called CADRE (Crop Condition and Data Retrieval Evaluation) mainly through an automated database management system that integrates various meteorological datasets, crop and soil models, and remote sensing data; providing significant contribution to the national and international crop production estimates. The "Sinclair" soybean growth model has been used inside CADRE DSS as one of the crop models. This project uses Sinclair model (a semi-mechanistic crop growth model) for its potential to be effectively used in a geo-processing environment with remote-sensing-based inputs. The main objective of this proposed work is to verify, validate and benchmark current and future NASA earth science research results for the benefit in the operational decision making process of the PECAD/CADRE DSS. For this purpose, the NASA South American Land Data Assimilation System (SALDAS) meteorological dataset is tested for its applicability as a surrogate meteorological input in the Sinclair model meteorological input requirements. Similarly, NASA sensor MODIS products is tested for its applicability in the improvement of the crop yield prediction through improving precision of planting date estimation, plant vigor and growth monitoring. The project also analyzes simulated Visible/Infrared Imager/Radiometer Suite (VIIRS, a future NASA sensor) vegetation product for its applicability in crop growth prediction to accelerate the process of transition of VIIRS research results for the operational use of USDA/FAS/PECAD DSS. The research results will help in providing improved decision making capacity to the USDA/FAS/PECAD DSS through improved vegetation growth monitoring from high spatial and temporal resolution remote sensing datasets; improved time-series meteorological inputs required for crop growth models; and regional prediction capability through geo-processing-based yield modeling.

Irrigation scheduling by ET and soil water sensing

USDA-ARS?s Scientific Manuscript database

Irrigation scheduling is the process of deciding when, where and how much to irrigate, usually with the goal of optimizing economic return on investment in land, equipment, inputs and personnel. This hour-long seminar presents methods of irrigation scheduling based, on the one hand on estimates of t...

Multi-Source Autonomous Response for Targeting and Monitoring of Volcanic Activity

NASA Technical Reports Server (NTRS)

Davies, Ashley G.; Doubleday, Joshua R.; Tran, Daniel Q.

2014-01-01

The study of volcanoes is important for both purely scientific and human survival reasons. From a scientific standpoint, volcanic gas and ash emissions contribute significantly to the terrestrial atmosphere. Ash depositions and lava flows can also greatly affect local environments. From a human survival standpoint, many people live within the reach of active volcanoes, and therefore can be endangered by both atmospheric (ash, debris) toxicity and lava flow. There are many potential information sources that can be used to determine how to best monitor volcanic activity worldwide. These are of varying temporal frequency, spatial regard, method of access, and reliability. The problem is how to incorporate all of these inputs in a general framework to assign/task/reconfigure assets to monitor events in a timely fashion. In situ sensing can provide a valuable range of complementary information such as seismographic, discharge, acoustic, and other data. However, many volcanoes are not instrumented with in situ sensors, and those that have sensor networks are restricted to a relatively small numbers of point sensors. Consequently, ideal volcanic study synergistically combines space and in situ measurements. This work demonstrates an effort to integrate spaceborne sensing from MODIS (Terra and Aqua), ALI (EO-1), Worldview-2, and in situ sensing in an automated scheme to improve global volcano monitoring. Specifically, it is a "sensor web" concept in which a number of volcano monitoring systems are linked together to monitor volcanic activity more accurately, and this activity measurement automatically tasks space assets to acquire further satellite imagery of ongoing volcanic activity. A general framework was developed for evidence combination that accounts for multiple information sources in a scientist-directed fashion to weigh inputs and allocate observations based on the confidence of an events occurrence, rarity of the event at that location, and other scientists' inputs. The software framework uses multiple source languages and is a general framework for combining inputs and incrementally submitting observation requests/reconfigurations, accounting for prior requests. The autonomous aspect of operations is unique, especially in the context of the wide range of inputs that includes manually inputted electronic reports (such as the Air Force Weather Advisories), automated satellite-based detection methods (such as MODVOLC and GOESVOLC), and in situ sensor networks.

Automatic archaeological feature extraction from satellite VHR images

NASA Astrophysics Data System (ADS)

Jahjah, Munzer; Ulivieri, Carlo

2010-05-01

Archaeological applications need a methodological approach on a variable scale able to satisfy the intra-site (excavation) and the inter-site (survey, environmental research). The increased availability of high resolution and micro-scale data has substantially favoured archaeological applications and the consequent use of GIS platforms for reconstruction of archaeological landscapes based on remotely sensed data. Feature extraction of multispectral remotely sensing image is an important task before any further processing. High resolution remote sensing data, especially panchromatic, is an important input for the analysis of various types of image characteristics; it plays an important role in the visual systems for recognition and interpretation of given data. The methods proposed rely on an object-oriented approach based on a theory for the analysis of spatial structures called mathematical morphology. The term "morphology" stems from the fact that it aims at analysing object shapes and forms. It is mathematical in the sense that the analysis is based on the set theory, integral geometry, and lattice algebra. Mathematical morphology has proven to be a powerful image analysis technique; two-dimensional grey tone images are seen as three-dimensional sets by associating each image pixel with an elevation proportional to its intensity level. An object of known shape and size, called the structuring element, is then used to investigate the morphology of the input set. This is achieved by positioning the origin of the structuring element to every possible position of the space and testing, for each position, whether the structuring element either is included or has a nonempty intersection with the studied set. The shape and size of the structuring element must be selected according to the morphology of the searched image structures. Other two feature extraction techniques were used, eCognition and ENVI module SW, in order to compare the results. These techniques were applied to different archaeological sites in Turkmenistan (Nisa) and in Iraq (Babylon); a further change detection analysis was applied to the Babylon site using two HR images as a pre-post second gulf war. We had different results or outputs, taking into consideration the fact that the operative scale of sensed data determines the final result of the elaboration and the output of the information quality, because each of them was sensitive to specific shapes in each input image, we had mapped linear and nonlinear objects, updating archaeological cartography, automatic change detection analysis for the Babylon site. The discussion of these techniques has the objective to provide the archaeological team with new instruments for the orientation and the planning of a remote sensing application.

Operational Retrievals of Evapotranspiration: Are we there yet?

NASA Astrophysics Data System (ADS)

Neale, C. M. U.; Anderson, M. C.; Hain, C.; Schull, M.; Isidro, C., Sr.; Goncalves, I. Z.

2017-12-01

Remote sensing based retrievals of evapotranspiration (ET) have progressed significantly over the last two decades with the improvement of methods and algorithms and the availability of multiple satellite sensors with shortwave and thermal infrared bands on polar orbiting platforms. The modeling approaches include simpler vegetation index (VI) based methods such as the reflectance-based crop coefficient approach coupled with surface reference evapotranspiration estimates to derive actual evapotranspiration of crops or, direct inputs to the Penman-Monteith equation through VI relationships with certain input variables. Methods that are more complex include one-layer or two-layer energy balance approaches that make use of both shortwave and longwave spectral band information to estimate different inputs to the energy balance equation. These models mostly differ in the estimation of sensible heat fluxes. For continental and global scale applications, other satellite-based products such as solar radiation, vegetation leaf area and cover are used as inputs, along with gridded re-analysis weather information. This presentation will review the state-of-the-art in satellite-based evapotranspiration estimation, giving examples of existing efforts to obtain operational ET retrievals over continental and global scales and discussing difficulties and challenges.

A novel input-parasitic compensation technique for a nanopore-based CMOS DNA detection sensor

NASA Astrophysics Data System (ADS)

Kim, Jungsuk

2016-12-01

This paper presents a novel input-parasitic compensation (IPC) technique for a nanopore-based complementary metal-oxide-semiconductor (CMOS) DNA detection sensor. A resistive-feedback transimpedance amplifier is typically adopted as the headstage of a DNA detection sensor to amplify the minute ionic currents generated from a nanopore and convert them to a readable voltage range for digitization. But, parasitic capacitances arising from the headstage input and the nanopore often cause headstage saturation during nanopore sensing, thereby resulting in significant DNA data loss. To compensate for the unwanted saturation, in this work, we propose an area-efficient and automated IPC technique, customized for a low-noise DNA detection sensor, fabricated using a 0.35- μm CMOS process; we demonstrated this prototype in a benchtop test using an α-hemolysin ( α-HL) protein nanopore.

A comprehensive evaluation of input data-induced uncertainty in nonpoint source pollution modeling

NASA Astrophysics Data System (ADS)

Chen, L.; Gong, Y.; Shen, Z.

2015-11-01

Watershed models have been used extensively for quantifying nonpoint source (NPS) pollution, but few studies have been conducted on the error-transitivity from different input data sets to NPS modeling. In this paper, the effects of four input data, including rainfall, digital elevation models (DEMs), land use maps, and the amount of fertilizer, on NPS simulation were quantified and compared. A systematic input-induced uncertainty was investigated using watershed model for phosphorus load prediction. Based on the results, the rain gauge density resulted in the largest model uncertainty, followed by DEMs, whereas land use and fertilizer amount exhibited limited impacts. The mean coefficient of variation for errors in single rain gauges-, multiple gauges-, ASTER GDEM-, NFGIS DEM-, land use-, and fertilizer amount information was 0.390, 0.274, 0.186, 0.073, 0.033 and 0.005, respectively. The use of specific input information, such as key gauges, is also highlighted to achieve the required model accuracy. In this sense, these results provide valuable information to other model-based studies for the control of prediction uncertainty.

Research and Development in the Computer and Information Sciences. Volume 1, Information Acquisition, Sensing, and Input: A Selective Literature Review.

ERIC Educational Resources Information Center

Stevens, Mary Elizabeth

The series, of which this is the initial report, is intended to give a selective overview of research and development efforts and requirements in the computer and information sciences. The operations of information acquisition, sensing, and input to information processing systems are considered in generalized terms. Specific topics include but are…

The Relation between Teachers' Math Talk and the Acquisition of Number Sense within Kindergarten Classrooms

ERIC Educational Resources Information Center

Boonen, Anton J. H.; Kolkman, Meijke E.; Kroesbergen, Evelyn H.

2011-01-01

The aim of the present study was to investigate the relation between teachers' math talk and the acquisition of number sense within kindergarten classrooms. The mathematical language input provided by 35 kindergarten teachers was examined with 9 different input categories. The results of this study indicate that the role of each of these math talk…

Subranging scheme for SQUID sensors

NASA Technical Reports Server (NTRS)

Penanen, Konstantin I. (Inventor)

2008-01-01

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

Self-organizing sensing and actuation for automatic control

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

Cheng, George Shu-Xing

A Self-Organizing Process Control Architecture is introduced with a Sensing Layer, Control Layer, Actuation Layer, Process Layer, as well as Self-Organizing Sensors (SOS) and Self-Organizing Actuators (SOA). A Self-Organizing Sensor for a process variable with one or multiple input variables is disclosed. An artificial neural network (ANN) based dynamic modeling mechanism as part of the Self-Organizing Sensor is described. As a case example, a Self-Organizing Soft-Sensor for CFB Boiler Bed Height is presented. Also provided is a method to develop a Self-Organizing Sensor.

Carbon nanotube thin film strain sensor models assembled using nano- and micro-scale imaging

NASA Astrophysics Data System (ADS)

Lee, Bo Mi; Loh, Kenneth J.; Yang, Yuan-Sen

2017-07-01

Nanomaterial-based thin films, particularly those based on carbon nanotubes (CNT), have brought forth tremendous opportunities for designing next-generation strain sensors. However, their strain sensing properties can vary depending on fabrication method, post-processing treatment, and types of CNTs and polymers employed. The objective of this study was to derive a CNT-based thin film strain sensor model using inputs from nano-/micro-scale experimental measurements of nanotube physical properties. This study began with fabricating ultra-low-concentration CNT-polymer thin films, followed by imaging them using atomic force microscopy. Image processing was employed for characterizing CNT dispersed shapes, lengths, and other physical attributes, and results were used for building five different types of thin film percolation-based models. Numerical simulations were conducted to assess how the morphology of dispersed CNTs in its 2D matrix affected bulk film electrical and electromechanical (strain sensing) properties. The simulation results showed that CNT morphology had a significant impact on strain sensing performance.

An analytical model for subsurface irradiance and remote sensing reflectance in deep and shallow case-2 waters.

PubMed

Albert, A; Mobley, C

2003-11-03

Subsurface remote sensing signals, represented by the irradiance re fl ectance and the remote sensing re fl ectance, were investigated. The present study is based on simulations with the radiative transfer program Hydrolight using optical properties of Lake Constance (German: Bodensee) based on in-situ measurements of the water constituents and the bottom characteristics. Analytical equations are derived for the irradiance re fl ectance and remote sensing re fl ectance for deep and shallow water applications. The input of the parameterization are the inherent optical properties of the water - absorption a(lambda) and backscattering bb(lambda). Additionally, the solar zenith angle thetas, the viewing angle thetav , and the surface wind speed u are considered. For shallow water applications the bottom albedo RB and the bottom depth zB are included into the parameterizations. The result is a complete set of analytical equations for the remote sensing signals R and Rrs in deep and shallow waters with an accuracy better than 4%. In addition, parameterizations of apparent optical properties were derived for the upward and downward diffuse attenuation coefficients Ku and Kd.

A Novel Technique for Maximum Power Point Tracking of a Photovoltaic Based on Sensing of Array Current Using Adaptive Neuro-Fuzzy Inference System (ANFIS)

NASA Astrophysics Data System (ADS)

El-Zoghby, Helmy M.; Bendary, Ahmed F.

2016-10-01

Maximum Power Point Tracking (MPPT) is now widely used method in increasing the photovoltaic (PV) efficiency. The conventional MPPT methods have many problems concerning the accuracy, flexibility and efficiency. The MPP depends on the PV temperature and solar irradiation that randomly varied. In this paper an artificial intelligence based controller is presented through implementing of an Adaptive Neuro-Fuzzy Inference System (ANFIS) to obtain maximum power from PV. The ANFIS inputs are the temperature and cell current, and the output is optimal voltage at maximum power. During operation the trained ANFIS senses the PV current using suitable sensor and also senses the temperature to determine the optimal operating voltage that corresponds to the current at MPP. This voltage is used to control the boost converter duty cycle. The MATLAB simulation results shows the effectiveness of the ANFIS with sensing the PV current in obtaining the MPPT from the PV.

Using Remote Sensing to Estimate Crop Water Use to Improve Irrigation Water Management

NASA Astrophysics Data System (ADS)

Reyes-Gonzalez, Arturo

Irrigation water is scarce. Hence, accurate estimation of crop water use is necessary for proper irrigation managements and water conservation. Satellite-based remote sensing is a tool that can estimate crop water use efficiently. Several models have been developed to estimate crop water requirement or actual evapotranspiration (ETa) using remote sensing. One of them is the Mapping EvapoTranspiration at High Resolution using Internalized Calibration (METRIC) model. This model has been compared with other methods for ET estimations including weighing lysimeters, pan evaporation, Bowen Ratio Energy Balance System (BREBS), Eddy Covariance (EC), and sap flow. However, comparison of METRIC model outputs to an atmometer for ETa estimation has not yet been attempted in eastern South Dakota. The results showed a good relationship between ETa estimated by the METRIC model and estimated with atmometer (r2 = 0.87 and RMSE = 0.65 mm day-1). However, ETa values from atmometer were consistently lower than ET a values from METRIC. The verification of remotely sensed estimates of surface variables is essential for any remote-sensing study. The relationships between LAI, Ts, and ETa estimated using the remote sensing-based METRIC model and in-situ measurements were established. The results showed good agreement between the variables measured in situ and estimated by the METRIC model. LAI showed r2 = 0.76, and RMSE = 0.59 m2 m -2, Ts had r2 = 0.87 and RMSE 1.24 °C and ETa presented r2= 0.89 and RMSE = 0.71 mm day -1. Estimation of ETa using energy balance method can be challenging and time consuming. Thus, there is a need to develop a simple and fast method to estimate ETa using minimum input parameters. Two methods were used, namely 1) an energy balance method (EB method) that used input parameters of the Landsat image, weather data, a digital elevation map, and a land cover map and 2) a Kc-NDVI method that use two input parameters: the Landsat image and weather data. A strong relationship was found between the two methods with r2 of 0.97 and RMSE of 0.37 mm day -1. Hence, the Kc-NDVI method performed well for ET a estimations, indicating that Kc-NDVI method can be a robust and reliable method to estimate ETa in a short period of time. Estimation of crop evapotranspiration (ETc) using satellite remote sensing-based vegetation index such as the Normalized Difference Vegetation Index (NDVI). The NDVI was calculated using near-infrared and red wavebands. The relationship between NDVI and tabulated Kc's was used to generate Kc maps. ETc maps were developed as an output of Kc maps multiplied by reference evapotranspiration (ETr). Daily ETc maps helped to explain the variability of crop water use during the growing season. Based on the results we can conclude that ETc maps developed from remotely sensed multispectral vegetation indices are a useful tool for quantifying crop water use at regional and field scales.

A nonlinear strategy for sensor based vehicle path control

NASA Technical Reports Server (NTRS)

Mayr, R.

1994-01-01

A method of transverse control which makes use of nonlinear formulations is presented. The strategy is utilized to stabilize a vehicle. The vehicle is autonomously guided and takes its control inputs from an optical sensing system. Additionally, the velocity of the vehicle is dictated by a longitudinal controller, which is also discussed.

Practical robotic self-awareness and self-knowledge

NASA Astrophysics Data System (ADS)

Gage, Douglas W.

2011-05-01

The functional software components of an autonomous robotic system express behavior via commands to its actuators, based on processed inputs from its sensors; we propose an additional set of "cognitive" capabilities for robotic systems of all types, based on the comprehensive logging of all available data, including sensor inputs, behavioral states, and outputs sent to actuators. A robot should maintain a "sense" of its own (piecewise) continuous existence through time and space; it should in some sense "get a life," providing a level of self-awareness and self-knowledge. Self-awareness includes the ability to survive and work through unexpected power glitches while executing a task or mission. Selfknowledge includes an extensive world model including a model of self and the purpose context in which it is operating (deontics). Our system must support proactive self-test, monitoring, and calibration, and maintain a "personal" health/repair history, supporting system test and evaluation by continuously measuring performance throughout the entire product lifecycle. It will include episodic memory, and a system "lifelog," and will also participate in multiple modes of Human Robotic interaction (HRI).

New developments of a knowledge based system (VEG) for inferring vegetation characteristics

NASA Technical Reports Server (NTRS)

Kimes, D. S.; Harrison, P. A.; Harrison, P. R.

1992-01-01

An extraction technique for inferring physical and biological surface properties of vegetation using nadir and/or directional reflectance data as input has been developed. A knowledge-based system (VEG) accepts spectral data of an unknown target as input, determines the best strategy for inferring the desired vegetation characteristic, applies the strategy to the target data, and provides a rigorous estimate of the accuracy of the inference. Progress in developing the system is presented. VEG combines methods from remote sensing and artificial intelligence, and integrates input spectral measurements with diverse knowledge bases. VEG has been developed to (1) infer spectral hemispherical reflectance from any combination of nadir and/or off-nadir view angles; (2) test and develop new extraction techniques on an internal spectral database; (3) browse, plot, or analyze directional reflectance data in the system's spectral database; (4) discriminate between user-defined vegetation classes using spectral and directional reflectance relationships; and (5) infer unknown view angles from known view angles (known as view angle extension).

Robust adaptive fuzzy tracking control for pure-feedback stochastic nonlinear systems with input constraints.

PubMed

Wang, Huanqing; Chen, Bing; Liu, Xiaoping; Liu, Kefu; Lin, Chong

2013-12-01

This paper is concerned with the problem of adaptive fuzzy tracking control for a class of pure-feedback stochastic nonlinear systems with input saturation. To overcome the design difficulty from nondifferential saturation nonlinearity, a smooth nonlinear function of the control input signal is first introduced to approximate the saturation function; then, an adaptive fuzzy tracking controller based on the mean-value theorem is constructed by using backstepping technique. The proposed adaptive fuzzy controller guarantees that all signals in the closed-loop system are bounded in probability and the system output eventually converges to a small neighborhood of the desired reference signal in the sense of mean quartic value. Simulation results further illustrate the effectiveness of the proposed control scheme.

Novel image compression-encryption hybrid algorithm based on key-controlled measurement matrix in compressive sensing

NASA Astrophysics Data System (ADS)

Zhou, Nanrun; Zhang, Aidi; Zheng, Fen; Gong, Lihua

2014-10-01

The existing ways to encrypt images based on compressive sensing usually treat the whole measurement matrix as the key, which renders the key too large to distribute and memorize or store. To solve this problem, a new image compression-encryption hybrid algorithm is proposed to realize compression and encryption simultaneously, where the key is easily distributed, stored or memorized. The input image is divided into 4 blocks to compress and encrypt, then the pixels of the two adjacent blocks are exchanged randomly by random matrices. The measurement matrices in compressive sensing are constructed by utilizing the circulant matrices and controlling the original row vectors of the circulant matrices with logistic map. And the random matrices used in random pixel exchanging are bound with the measurement matrices. Simulation results verify the effectiveness, security of the proposed algorithm and the acceptable compression performance.

Metabolic sensing neurons and the control of energy homeostasis.

PubMed

Levin, Barry E

2006-11-30

The brain and periphery carry on a constant conversation; the periphery informs the brain about its metabolic needs and the brain provides for these needs through its control of somatomotor, autonomic and neurohumoral pathways involved in energy intake, expenditure and storage. Metabolic sensing neurons are the integrators of a variety of metabolic, humoral and neural inputs from the periphery. Such neurons, originally called "glucosensing", also respond to fatty acids, hormones and metabolites from the periphery. They are integrated within neural pathways involved in the regulation of energy homeostasis. Unlike most neurons, they utilize glucose and other metabolites as signaling molecules to regulate their membrane potential and firing rate. For glucosensing neurons, glucokinase acts as the rate-limiting step in glucosensing while the pathways that mediate responses to metabolites like lactate, ketone bodies and fatty acids are less well characterized. Many metabolic sensing neurons also respond to insulin and leptin and other peripheral hormones and receive neural inputs from peripheral organs. Each set of afferent signals arrives with different temporal profiles and by different routes and these inputs are summated at the level of the membrane potential to produce a given neural firing pattern. In some obese individuals, the relative sensitivity of metabolic sensing neurons to various peripheral inputs is genetically reduced. This may provide one mechanism underlying their propensity to become obese when exposed to diets high in fat and caloric density. Thus, metabolic sensing neurons may provide a potential therapeutic target for the treatment of obesity.

Remote sensing based crop type mapping and evapotranspiration estimates at the farm level in arid regions of the globe

NASA Astrophysics Data System (ADS)

Ozdogan, M.; Serrat-Capdevila, A.; Anderson, M. C.

2017-12-01

Despite increasing scarcity of freshwater resources, there is dearth of spatially explicit information on irrigation water consumption through evapotranspiration, particularly in semi-arid and arid geographies. Remote sensing, either alone or in combination with ground surveys, is increasingly being used for irrigation water management by quantifying evaporative losses at the farm level. Increased availability of observations, sophisticated algorithms, and access to cloud-based computing is also helping this effort. This presentation will focus on crop-specific evapotranspiration estimates at the farm level derived from remote sensing in a number of water-scarce regions of the world. The work is part of a larger effort to quantify irrigation water use and improve use efficiencies associated with several World Bank projects. Examples will be drawn from India, where groundwater based irrigation withdrawals are monitored with the help of crop type mapping and evapotranspiration estimates from remote sensing. Another example will be provided from a northern irrigation district in Mexico, where remote sensing is used for detailed water accounting at the farm level. These locations exemplify the success stories in irrigation water management with the help of remote sensing with the hope that spatially disaggregated information on evapotranspiration can be used as inputs for various water management decisions as well as for better water allocation strategies in many other water scarce regions.

Flexible Sensory Platform Based on Oxide-based Neuromorphic Transistors

NASA Astrophysics Data System (ADS)

Liu, Ning; Zhu, Li Qiang; Feng, Ping; Wan, Chang Jin; Liu, Yang Hui; Shi, Yi; Wan, Qing

2015-12-01

Inspired by the dendritic integration and spiking operation of a biological neuron, flexible oxide-based neuromorphic transistors with multiple input gates are fabricated on flexible plastic substrates for pH sensor applications. When such device is operated in a quasi-static dual-gate synergic sensing mode, it shows a high pH sensitivity of ~105 mV/pH. Our results also demonstrate that single-spike dynamic mode can remarkably improve pH sensitivity and reduce response/recover time and power consumption. Moreover, we find that an appropriate negative bias applied on the sensing gate electrode can further enhance the pH sensitivity and reduce the power consumption. Our flexible neuromorphic transistors provide a new-concept sensory platform for biochemical detection with high sensitivity, rapid response and ultralow power consumption.

Flexible Sensory Platform Based on Oxide-based Neuromorphic Transistors

PubMed Central

Liu, Ning; Zhu, Li Qiang; Feng, Ping; Wan, Chang Jin; Liu, Yang Hui; Shi, Yi; Wan, Qing

2015-01-01

Inspired by the dendritic integration and spiking operation of a biological neuron, flexible oxide-based neuromorphic transistors with multiple input gates are fabricated on flexible plastic substrates for pH sensor applications. When such device is operated in a quasi-static dual-gate synergic sensing mode, it shows a high pH sensitivity of ~105 mV/pH. Our results also demonstrate that single-spike dynamic mode can remarkably improve pH sensitivity and reduce response/recover time and power consumption. Moreover, we find that an appropriate negative bias applied on the sensing gate electrode can further enhance the pH sensitivity and reduce the power consumption. Our flexible neuromorphic transistors provide a new-concept sensory platform for biochemical detection with high sensitivity, rapid response and ultralow power consumption. PMID:26656113

Comparison of Uncalibrated Rgbvi with Spectrometer-Based Ndvi Derived from Uav Sensing Systems on Field Scale

NASA Astrophysics Data System (ADS)

Bareth, G.; Bolten, A.; Gnyp, M. L.; Reusch, S.; Jasper, J.

2016-06-01

The development of UAV-based sensing systems for agronomic applications serves the improvement of crop management. The latter is in the focus of precision agriculture which intends to optimize yield, fertilizer input, and crop protection. Besides, in some cropping systems vehicle-based sensing devices are less suitable because fields cannot be entered from certain growing stages onwards. This is true for rice, maize, sorghum, and many more crops. Consequently, UAV-based sensing approaches fill a niche of very high resolution data acquisition on the field scale in space and time. While mounting RGB digital compact cameras to low-weight UAVs (< 5 kg) is well established, the miniaturization of sensors in the last years also enables hyperspectral data acquisition from those platforms. From both, RGB and hyperspectral data, vegetation indices (VIs) are computed to estimate crop growth parameters. In this contribution, we compare two different sensing approaches from a low-weight UAV platform (< 5 kg) for monitoring a nitrogen field experiment of winter wheat and a corresponding farmers' field in Western Germany. (i) A standard digital compact camera was flown to acquire RGB images which are used to compute the RGBVI and (ii) NDVI is computed from a newly modified version of the Yara N-Sensor. The latter is a well-established tractor-based hyperspectral sensor for crop management and is available on the market since a decade. It was modified for this study to fit the requirements of UAV-based data acquisition. Consequently, we focus on three objectives in this contribution: (1) to evaluate the potential of the uncalibrated RGBVI for monitoring nitrogen status in winter wheat, (2) investigate the UAV-based performance of the modified Yara N-Sensor, and (3) compare the results of the two different UAV-based sensing approaches for winter wheat.

Urban land use: Remote sensing of ground-basin permeability

NASA Technical Reports Server (NTRS)

Tinney, L. R.; Jensen, J. R.; Estes, J. E.

1975-01-01

A remote sensing analysis of the amount and type of permeable and impermeable surfaces overlying an urban recharge basin is discussed. An effective methodology for accurately generating this data as input to a safe yield study is detailed and compared to more conventional alternative approaches. The amount of area inventoried, approximately 10 sq. miles, should provide a reliable base against which automatic pattern recognition algorithms, currently under investigation for this task, can be evaluated. If successful, such approaches can significantly reduce the time and effort involved in obtaining permeability data, an important aspect of urban hydrology dynamics.

Natural Resource Information System, remote sensing studies

NASA Technical Reports Server (NTRS)

Leachtenauer, J.; Hirsch, R.; Williams, V.; Tucker, R.

1972-01-01

Potential applications of remote sensing data were reviewed, and available imagery was interpreted to provide input to a demonstration data base. A literature review was conducted to determine the types and qualities of imagery required to satisfy identified data needs. Ektachrome imagery available over the demonstration areas was reviewed to establish the feasibility of interpreting cultural features, range condition, and timber type. Using the same imagery, a land use map was prepared for the demonstration area. The feasibility of identifying commercial timber areas using a density slicing technique was tested on multispectral imagery available for a portion of the demonstration area.

Development of MODIS data-based algorithm for retrieving sea surface temperature in coastal waters.

PubMed

Wang, Jiao; Deng, Zhiqiang

2017-06-01

A new algorithm was developed for retrieving sea surface temperature (SST) in coastal waters using satellite remote sensing data from Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Aqua platform. The new SST algorithm was trained using the Artificial Neural Network (ANN) method and tested using 8 years of remote sensing data from MODIS Aqua sensor and in situ sensing data from the US coastal waters in Louisiana, Texas, Florida, California, and New Jersey. The ANN algorithm could be utilized to map SST in both deep offshore and particularly shallow nearshore waters at the high spatial resolution of 1 km, greatly expanding the coverage of remote sensing-based SST data from offshore waters to nearshore waters. Applications of the ANN algorithm require only the remotely sensed reflectance values from the two MODIS Aqua thermal bands 31 and 32 as input data. Application results indicated that the ANN algorithm was able to explaining 82-90% variations in observed SST in US coastal waters. While the algorithm is generally applicable to the retrieval of SST, it works best for nearshore waters where important coastal resources are located and existing algorithms are either not applicable or do not work well, making the new ANN-based SST algorithm unique and particularly useful to coastal resource management.

Dataset on the mean, standard deviation, broad-sense heritability and stability of wheat quality bred in three different ways and grown under organic and low-input conventional systems.

PubMed

Rakszegi, Marianna; Löschenberger, Franziska; Hiltbrunner, Jürg; Vida, Gyula; Mikó, Péter

2016-06-01

An assessment was previously made of the effects of organic and low-input field management systems on the physical, grain compositional and processing quality of wheat and on the performance of varieties developed using different breeding methods ("Comparison of quality parameters of wheat varieties with different breeding origin under organic and low-input conventional conditions" [1]). Here, accompanying data are provided on the performance and stability analysis of the genotypes using the coefficient of variation and the 'ranking' and 'which-won-where' plots of GGE biplot analysis for the most important quality traits. Broad-sense heritability was also evaluated and is given for the most important physical and quality properties of the seed in organic and low-input management systems, while mean values and standard deviation of the studied properties are presented separately for organic and low-input fields.

Image Mining in Remote Sensing for Coastal Wetlands Mapping: from Pixel Based to Object Based Approach

NASA Astrophysics Data System (ADS)

Farda, N. M.; Danoedoro, P.; Hartono; Harjoko, A.

2016-11-01

The availably of remote sensing image data is numerous now, and with a large amount of data it makes “knowledge gap” in extraction of selected information, especially coastal wetlands. Coastal wetlands provide ecosystem services essential to people and the environment. The aim of this research is to extract coastal wetlands information from satellite data using pixel based and object based image mining approach. Landsat MSS, Landsat 5 TM, Landsat 7 ETM+, and Landsat 8 OLI images located in Segara Anakan lagoon are selected to represent data at various multi temporal images. The input for image mining are visible and near infrared bands, PCA band, invers PCA bands, mean shift segmentation bands, bare soil index, vegetation index, wetness index, elevation from SRTM and ASTER GDEM, and GLCM (Harralick) or variability texture. There is three methods were applied to extract coastal wetlands using image mining: pixel based - Decision Tree C4.5, pixel based - Back Propagation Neural Network, and object based - Mean Shift segmentation and Decision Tree C4.5. The results show that remote sensing image mining can be used to map coastal wetlands ecosystem. Decision Tree C4.5 can be mapped with highest accuracy (0.75 overall kappa). The availability of remote sensing image mining for mapping coastal wetlands is very important to provide better understanding about their spatiotemporal coastal wetlands dynamics distribution.

Characterization of time-resolved fluorescence response measurements for distributed optical-fiber sensing.

PubMed

Sinchenko, Elena; Gibbs, W E Keith; Davis, Claire E; Stoddart, Paul R

2010-11-20

A distributed optical-fiber sensing system based on pulsed excitation and time-gated photon counting has been used to locate a fluorescent region along the fiber. The complex Alq3 and the infrared dye IR-125 were examined with 405 and 780 nm excitation, respectively. A model to characterize the response of the distributed fluorescence sensor to a Gaussian input pulse was developed and tested. Analysis of the Alq3 fluorescent response confirmed the validity of the model and enabled the fluorescence lifetime to be determined. The intrinsic lifetime obtained (18.2±0.9 ns) is in good agreement with published data. The decay rate was found to be proportional to concentration, which is indicative of collisional deactivation. The model allows the spatial resolution of a distributed sensing system to be improved for fluorophores with lifetimes that are longer than the resolution of the sensing system.

Compressed Sensing in On-Grid MIMO Radar.

PubMed

Minner, Michael F

2015-01-01

The accurate detection of targets is a significant problem in multiple-input multiple-output (MIMO) radar. Recent advances of Compressive Sensing offer a means of efficiently accomplishing this task. The sparsity constraints needed to apply the techniques of Compressive Sensing to problems in radar systems have led to discretizations of the target scene in various domains, such as azimuth, time delay, and Doppler. Building upon recent work, we investigate the feasibility of on-grid Compressive Sensing-based MIMO radar via a threefold azimuth-delay-Doppler discretization for target detection and parameter estimation. We utilize a colocated random sensor array and transmit distinct linear chirps to a small scene with few, slowly moving targets. Relying upon standard far-field and narrowband assumptions, we analyze the efficacy of various recovery algorithms in determining the parameters of the scene through numerical simulations, with particular focus on the ℓ 1-squared Nonnegative Regularization method.

Structural sensing of interior sound for active control of noise in structural-acoustic cavities.

PubMed

Bagha, Ashok K; Modak, S V

2015-07-01

This paper proposes a method for structural sensing of acoustic potential energy for active control of noise in a structural-acoustic cavity. The sensing strategy aims at global control and works with a fewer number of sensors. It is based on the established concept of radiation modes and hence does not add too many states to the order of the system. Acoustic potential energy is sensed using a combination of a Kalman filter and a frequency weighting filter with the structural response measurements as the inputs. The use of Kalman filter also makes the system robust against measurement noise. The formulation of the strategy is presented using finite element models of the system including that of sensors and actuators so that it can be easily applied to practical systems. The sensing strategy is numerically evaluated in the framework of Linear Quadratic Gaussian based feedback control of interior noise in a rectangular box cavity with a flexible plate with single and multiple pairs of piezoelectric sensor-actuator patches when broadband disturbances act on the plate. The performance is compared with an "acoustic filter" that models the complete transfer function from the structure to the acoustic domain. The sensing performance is also compared with a direct estimation strategy.

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.

RF Spectrum Sensing Based on an Overdamped Nonlinear Oscillator Ring for Cognitive Radios.

PubMed

Tang, Zhi-Ling; Li, Si-Min; Yu, Li-Juan

2016-06-09

Existing spectrum-sensing techniques for cognitive radios require an analog-to-digital converter (ADC) to work at high dynamic range and a high sampling rate, resulting in high cost. Therefore, in this paper, a spectrum-sensing method based on a unidirectionally coupled, overdamped nonlinear oscillator ring is proposed. First, the numerical model of such a system is established based on the circuit of the nonlinear oscillator. Through numerical analysis of the model, the critical condition of the system's starting oscillation is determined, and the simulation results of the system's response to Gaussian white noise and periodic signal are presented. The results show that once the radio signal is input into the system, it starts oscillating when in the critical region, and the oscillating frequency of each element is fo/N, where fo is the frequency of the radio signal and N is the number of elements in the ring. The oscillation indicates that the spectrum resources at fo are occupied. At the same time, the sampling rate required for an ADC is reduced to the original value, 1/N. A prototypical circuit to verify the functionality of the system is designed, and the sensing bandwidth of the system is measured.

A cloud-based home health care information sharing system to connect patients with home healthcare staff -A case report of a study in a mountainous region.

PubMed

Nomoto, Shinichi; Utsumi, Momoe; Sasayama, Satoshi; Dekigai, Hiroshi

2017-01-01

We have developed a cloud system, the e-Renraku Notebook (e-RN) for sharing of home care information based on the concept of "patient-centricity". In order to assess the likelihood that our system will enhance the communication and sharing of information between home healthcare staff members and home-care patients, we selected patients who were residing in mountainous regions for inclusion in our study. We herein report the findings.Eighteen staff members from 7 medical facilities and 9 patients participated in the present study.The e-RN was developed for two reasons: to allow patients to independently report their health status and to have staff members view and respond to the information received. The patients and staff members were given iPads with the pre-installed applications and the information being exchanged was reviewed over a 54-day period.Information was mainly input by the patients (61.6%), followed by the nurses who performed home visits (19.9%). The amount of information input by patients requiring high-level nursing care and their corresponding staff member was significantly greater than that input by patients who required low-level of nursing care.This patient-centric system in which patients can independently report and share information with a member of the healthcare staff provides a sense of security. It also allows staff members to understand the patient's health status before making a home visit, thereby giving them a sense of security and confidence. It was also noteworthy that elderly patients requiring high-level nursing care and their staff counterpart input information in the system significantly more frequently than patients who required low-level care.

Vibration monitoring via nano-composite piezoelectric foam bushings

NASA Astrophysics Data System (ADS)

Bird, Evan T.; Merrell, A. Jake; Anderson, Brady K.; Newton, Cory N.; Rosquist, Parker G.; Fullwood, David T.; Bowden, Anton E.; Seeley, Matthew K.

2016-11-01

Most mechanical systems produce vibrations as an inherent side effect of operation. Though some vibrations are acceptable in operation, others can cause damage or signal a machine’s imminent failure. These vibrations would optimally be monitored in real-time, without human supervision to prevent failure and excessive wear in machinery. This paper explores a new alternative to currently-used machine-monitoring equipment, namely a piezoelectric foam sensor system. These sensors are made of a silicone-based foam embedded with nano- and micro-scale conductive particles. Upon impact, they emit an electric response that is directly correlated with impact energy, with no electrical power input. In the present work, we investigated their utility as self-sensing bushings on machinery. These sensors were found to accurately detect both the amplitude and frequency of typical machine vibrations. The bushings could potentially save time and money over other vibration sensing mechanisms, while simultaneously providing a potential control input that could be utilized for correcting vibrational imbalance.

Distinguishing Representations as Origin and Representations as Input: Roles for Individual Neurons.

PubMed

Edwards, Jonathan C W

2016-01-01

It is widely perceived that there is a problem in giving a naturalistic account of mental representation that deals adequately with the issue of meaning, interpretation, or significance (semantic content). It is suggested here that this problem may arise partly from the conflation of two vernacular senses of representation: representation-as-origin and representation-as-input. The flash of a neon sign may in one sense represent a popular drink, but to function as a representation it must provide an input to a 'consumer' in the street. The arguments presented draw on two principles - the neuron doctrine and the need for a venue for 'presentation' or 'reception' of a representation at a specified site, consistent with the locality principle. It is also argued that domains of representation cannot be defined by signal traffic, since they can be expected to include 'null' elements based on non-firing cells. In this analysis, mental representations-as-origin are distributed patterns of cell firing. Each firing cell is given semantic value in its own right - some form of atomic propositional significance - since different axonal branches may contribute to integration with different populations of signals at different downstream sites. Representations-as-input are patterns of local co-arrival of signals in the form of synaptic potentials in dendrites. Meaning then draws on the relationships between active and null inputs, forming 'scenarios' comprising a molecular combination of 'premises' from which a new output with atomic propositional significance is generated. In both types of representation, meaning, interpretation or significance pivots on events in an individual cell. (This analysis only applies to 'occurrent' representations based on current neural activity.) The concept of representations-as-input emphasizes the need for an internal 'consumer' of a representation and the dependence of meaning on the co-relationships involved in an input interaction between signals and consumer. The acceptance of this necessity provides a basis for resolving the problem that representations appear both as distributed (representation-as-origin) and as local (representation-as-input). The key implications are that representations in the brain are massively multiple both in series and in parallel, and that individual cells play specific semantic roles. These roles are discussed in relation to traditional concepts of 'gnostic' cell types.

Distinguishing Representations as Origin and Representations as Input: Roles for Individual Neurons

PubMed Central

Edwards, Jonathan C. W.

2016-01-01

It is widely perceived that there is a problem in giving a naturalistic account of mental representation that deals adequately with the issue of meaning, interpretation, or significance (semantic content). It is suggested here that this problem may arise partly from the conflation of two vernacular senses of representation: representation-as-origin and representation-as-input. The flash of a neon sign may in one sense represent a popular drink, but to function as a representation it must provide an input to a ‘consumer’ in the street. The arguments presented draw on two principles – the neuron doctrine and the need for a venue for ‘presentation’ or ‘reception’ of a representation at a specified site, consistent with the locality principle. It is also argued that domains of representation cannot be defined by signal traffic, since they can be expected to include ‘null’ elements based on non-firing cells. In this analysis, mental representations-as-origin are distributed patterns of cell firing. Each firing cell is given semantic value in its own right – some form of atomic propositional significance – since different axonal branches may contribute to integration with different populations of signals at different downstream sites. Representations-as-input are patterns of local co-arrival of signals in the form of synaptic potentials in dendrites. Meaning then draws on the relationships between active and null inputs, forming ‘scenarios’ comprising a molecular combination of ‘premises’ from which a new output with atomic propositional significance is generated. In both types of representation, meaning, interpretation or significance pivots on events in an individual cell. (This analysis only applies to ‘occurrent’ representations based on current neural activity.) The concept of representations-as-input emphasizes the need for an internal ‘consumer’ of a representation and the dependence of meaning on the co-relationships involved in an input interaction between signals and consumer. The acceptance of this necessity provides a basis for resolving the problem that representations appear both as distributed (representation-as-origin) and as local (representation-as-input). The key implications are that representations in the brain are massively multiple both in series and in parallel, and that individual cells play specific semantic roles. These roles are discussed in relation to traditional concepts of ‘gnostic’ cell types. PMID:27746760

A layered abduction model of perception: Integrating bottom-up and top-down processing in a multi-sense agent

NASA Technical Reports Server (NTRS)

Josephson, John R.

1989-01-01

A layered-abduction model of perception is presented which unifies bottom-up and top-down processing in a single logical and information-processing framework. The process of interpreting the input from each sense is broken down into discrete layers of interpretation, where at each layer a best explanation hypothesis is formed of the data presented by the layer or layers below, with the help of information available laterally and from above. The formation of this hypothesis is treated as a problem of abductive inference, similar to diagnosis and theory formation. Thus this model brings a knowledge-based problem-solving approach to the analysis of perception, treating perception as a kind of compiled cognition. The bottom-up passing of information from layer to layer defines channels of information flow, which separate and converge in a specific way for any specific sense modality. Multi-modal perception occurs where channels converge from more than one sense. This model has not yet been implemented, though it is based on systems which have been successful in medical and mechanical diagnosis and medical test interpretation.

Cognitive Processes in Intelligence Analysis: A Descriptive Model and Review of the Literature

DTIC Science & Technology

1979-12-01

vision, hearing , touch,) tion’frquenly ncouterIntefernce In column 2 are the means by which allresulting from unavoidable confusion on reqenty couner... auditory , touch, or senses and makes It available to the muscular sense Inputs outside rest of the cognitive structure, while at awareness and attention...or Ie, the visual to the auditory . change in the sensory Input. The buffer p Shas several characteristics: (The reader may be able to recap- ture

Hypothesis on human eye perceiving optical spectrum rather than an image

NASA Astrophysics Data System (ADS)

Zheng, Yufeng; Szu, Harold

2015-05-01

It is a common knowledge that we see the world because our eyes can perceive an optical image. A digital camera seems a good example of simulating the eye imaging system. However, the signal sensing and imaging on human retina is very complicated. There are at least five layers (of neurons) along the signal pathway: photoreceptors (cones and rods), bipolar, horizontal, amacrine and ganglion cells. To sense an optical image, it seems that photoreceptors (as sensors) plus ganglion cells (converting to electrical signals for transmission) are good enough. Image sensing does not require ununiformed distribution of photoreceptors like fovea. There are some challenging questions, for example, why don't we feel the "blind spots" (never fibers exiting the eyes)? Similar situation happens to glaucoma patients who do not feel their vision loss until 50% or more nerves died. Now our hypothesis is that human retina initially senses optical (i.e., Fourier) spectrum rather than optical image. Due to the symmetric property of Fourier spectrum the signal loss from a blind spot or the dead nerves (for glaucoma patients) can be recovered. Eye logarithmic response to input light intensity much likes displaying Fourier magnitude. The optics and structures of human eyes satisfy the needs of optical Fourier spectrum sampling. It is unsure that where and how inverse Fourier transform is performed in human vision system to obtain an optical image. Phase retrieval technique in compressive sensing domain enables image reconstruction even without phase inputs. The spectrum-based imaging system can potentially tolerate up to 50% of bad sensors (pixels), adapt to large dynamic range (with logarithmic response), etc.

CHARACTERISTIC LENGTH SCALE OF INPUT DATA IN DISTRIBUTED MODELS: IMPLICATIONS FOR MODELING GRID SIZE. (R824784)

EPA Science Inventory

The appropriate spatial scale for a distributed energy balance model was investigated by: (a) determining the scale of variability associated with the remotely sensed and GIS-generated model input data; and (b) examining the effects of input data spatial aggregation on model resp...

Solid Waste Landfill Site Selection in the Sense of Environment Sensitive Sustainable Urbanization: Izmir, Turkey Case

NASA Astrophysics Data System (ADS)

TÜdeş, Şule; Kumlu, Kadriye Burcu Yavuz

2017-10-01

Each stage of the planning process should be based on the natural resource protection, in the sense of environmental sensitive and sustainable urban planning. Values, which are vital for the continuity of the life in the Earth, as soil, water, forest etc. should be protected from the undesired effects of the pollution and the other effects caused by the high urbanization levels. In this context, GIS-MCDM based solid waste landfill site selection is applied for Izmir, Turkey, where is a significant attraction place for tourism. As Multi criteria Decision Making (MCDM) technique, Analytical Hierarchy Process (AHP) is used. In this study, geological, tectonically and hydrological data, as well as agricultural land use, slope, distance to the settlement areas and the highways are used as inputs for AHP analysis. In the analysis stage, those inputs are rated and weighted. The weighted criteria are evaluated via GIS, by using weighted overlay tool. Therefore, an upper-scale analysis is conducted and a map, which shows the alternative places for the solid waste landfill sites, considering the environmental protection and evaluated in the context of environmental and urban criteria, are obtained.

A gold nanocluster-based fluorescent probe for simultaneous pH and temperature sensing and its application to cellular imaging and logic gates.

PubMed

Wu, Yun-Tse; Shanmugam, Chandirasekar; Tseng, Wei-Bin; Hiseh, Ming-Mu; Tseng, Wei-Lung

2016-06-07

Metal nanocluster-based nanomaterials for the simultaneous determination of temperature and pH variations in micro-environments are still a challenge. In this study, we develop a dual-emission fluorescent probe consisting of bovine serum albumin-stabilized gold nanoclusters (BSA-AuNCs) and fluorescein-5-isothiocyanate (FITC) as temperature- and pH-responsive fluorescence signals. Under single wavelength excitation the FITC/BSA-AuNCs exhibited well-separated dual emission bands at 525 and 670 nm. When FITC was used as a reference fluorophore, FITC/BSA-AuNCs showed a good linear response over the temperature range 1-71 °C and offered temperature-independent spectral shifts, temperature accuracy, activation energy, and reusability. The possible mechanism for high temperature-induced fluorescence quenching of FITC/BSA-AuNCs could be attributed to a weakening of the Au-S bond, thereby lowering the charge transfer from BSA to AuNCs. Additionally, the pH- and temperature-responsive properties of FITC/BSA-AuNCs allow simultaneous temperature sensing from 21 to 41 °C (at intervals of 5 °C) and pH from 6.0 to 8.0 (at intervals of 0.5 pH unit), facilitating the construction of two-input AND logic gates. Three-input AND logic gates were also designed using temperature, pH, and trypsin as inputs. The practicality of using FITC/BSA-AuNCs to determine the temperature and pH changes in HeLa cells is also validated.

Spatial heterogeneity of leaf area index across scales from simulation and remote sensing

NASA Astrophysics Data System (ADS)

Reichenau, Tim G.; Korres, Wolfgang; Montzka, Carsten; Schneider, Karl

2016-04-01

Leaf area index (LAI, single sided leaf area per ground area) influences mass and energy exchange of vegetated surfaces. Therefore LAI is an input variable for many land surface schemes of coupled large scale models, which do not simulate LAI. Since these models typically run on rather coarse resolution grids, LAI is often inferred from coarse resolution remote sensing. However, especially in agriculturally used areas, a grid cell of these products often covers more than a single land-use. In that case, the given LAI does not apply to any single land-use. Therefore, the overall spatial heterogeneity in these datasets differs from that on resolutions high enough to distinguish areas with differing land-use. Detailed process-based plant growth models simulate LAI for separate plant functional types or specific species. However, limited availability of observations causes reduced spatial heterogeneity of model input data (soil, weather, land-use). Since LAI is strongly heterogeneous in space and time and since processes depend on LAI in a nonlinear way, a correct representation of LAI spatial heterogeneity is also desirable on coarse resolutions. The current study assesses this issue by comparing the spatial heterogeneity of LAI from remote sensing (RapidEye) and process-based simulations (DANUBIA simulation system) across scales. Spatial heterogeneity is assessed by analyzing LAI frequency distributions (spatial variability) and semivariograms (spatial structure). Test case is the arable land in the fertile loess plain of the Rur catchment near the Germany-Netherlands border.

Prototyping sensor network system for automatic vital signs collection. Evaluation of a location based automated assignment of measured vital signs to patients.

PubMed

Kuroda, T; Noma, H; Naito, C; Tada, M; Yamanaka, H; Takemura, T; Nin, K; Yoshihara, H

2013-01-01

Development of a clinical sensor network system that automatically collects vital sign and its supplemental data, and evaluation the effect of automatic vital sensor value assignment to patients based on locations of sensors. The sensor network estimates the data-source, a target patient, from the position of a vital sign sensor obtained from a newly developed proximity sensing system. The proximity sensing system estimates the positions of the devices using a Bluetooth inquiry process. Using Bluetooth access points and the positioning system newly developed in this project, the sensor network collects vital sign and its 4W (who, where, what, and when) supplemental data from any Bluetooth ready vital sign sensors such as Continua-ready devices. The prototype was evaluated in a pseudo clinical setting at Kyoto University Hospital using a cyclic paired comparison and statistical analysis. The result of the cyclic paired analysis shows the subjects evaluated the proposed system is more effective and safer than POCS as well as paper-based operation. It halves the times for vital signs input and eliminates input errors. On the other hand, the prototype failed in its position estimation for 12.6% of all attempts, and the nurses overlooked half of the errors. A detailed investigation clears that an advanced interface to show the system's "confidence", i.e. the probability of estimation error, must be effective to reduce the oversights. This paper proposed a clinical sensor network system that relieves nurses from vital signs input tasks. The result clearly shows that the proposed system increases the efficiency and safety of the nursing process both subjectively and objectively. It is a step toward new generation of point of nursing care systems where sensors take over the tasks of data input from the nurses.

No Evidence of Narrowly Defined Cognitive Penetrability in Unambiguous Vision

PubMed Central

Lammers, Nikki A.; de Haan, Edward H.; Pinto, Yair

2017-01-01

The classical notion of cognitive impenetrability suggests that perceptual processing is an automatic modular system and not under conscious control. Near consensus is now emerging that this classical notion is untenable. However, as recently pointed out by Firestone and Scholl, this consensus is built on quicksand. In most studies claiming perception is cognitively penetrable, it remains unclear which actual process has been affected (perception, memory, imagery, input selection or judgment). In fact, the only available “proofs” for cognitive penetrability are proxies for perception, such as behavioral responses and neural correlates. We suggest that one can interpret cognitive penetrability in two different ways, a broad sense and a narrow sense. In the broad sense, attention and memory are not considered as “just” pre- and post-perceptual systems but as part of the mechanisms by which top-down processes influence the actual percept. Although many studies have proven top-down influences in this broader sense, it is still debatable whether cognitive penetrability remains tenable in a narrow sense. The narrow sense states that cognitive penetrability only occurs when top-down factors are flexible and cause a clear illusion from a first person perspective. So far, there is no strong evidence from a first person perspective that visual illusions can indeed be driven by high-level flexible factors. One cannot be cognitively trained to see and unsee visual illusions. We argue that this lack of convincing proof for cognitive penetrability in the narrow sense can be explained by the fact that most research focuses on foveal vision only. This type of perception may be too unambiguous for transient high-level factors to control perception. Therefore, illusions in more ambiguous perception, such as peripheral vision, can offer a unique insight into the matter. They produce a clear subjective percept based on unclear, degraded visual input: the optimal basis to study narrowly defined cognitive penetrability. PMID:28740471

Displacement Theories for In-Flight Deformed Shape Predictions of Aerospace Structures

NASA Technical Reports Server (NTRS)

Ko, William L.; Richards, W. L.; Tran, Van t.

2007-01-01

Displacement theories are developed for a variety of structures with the goal of providing real-time shape predictions for aerospace vehicles during flight. These theories are initially developed for a cantilever beam to predict the deformed shapes of the Helios flying wing. The main structural configuration of the Helios wing is a cantilever wing tubular spar subjected to bending, torsion, and combined bending and torsion loading. The displacement equations that are formulated are expressed in terms of strains measured at multiple sensing stations equally spaced on the surface of the wing spar. Displacement theories for other structures, such as tapered cantilever beams, two-point supported beams, wing boxes, and plates also are developed. The accuracy of the displacement theories is successfully validated by finite-element analysis and classical beam theory using input-strains generated by finite-element analysis. The displacement equations and associated strain-sensing system (such as fiber optic sensors) create a powerful means for in-flight deformation monitoring of aerospace structures. This method serves multiple purposes for structural shape sensing, loads monitoring, and structural health monitoring. Ultimately, the calculated displacement data can be visually displayed to the ground-based pilot or used as input to the control system to actively control the shape of structures during flight.

Realizing parameterless automatic classification of remote sensing imagery using ontology engineering and cyberinfrastructure techniques

NASA Astrophysics Data System (ADS)

Sun, Ziheng; Fang, Hui; Di, Liping; Yue, Peng

2016-09-01

It was an untouchable dream for remote sensing experts to realize total automatic image classification without inputting any parameter values. Experts usually spend hours and hours on tuning the input parameters of classification algorithms in order to obtain the best results. With the rapid development of knowledge engineering and cyberinfrastructure, a lot of data processing and knowledge reasoning capabilities become online accessible, shareable and interoperable. Based on these recent improvements, this paper presents an idea of parameterless automatic classification which only requires an image and automatically outputs a labeled vector. No parameters and operations are needed from endpoint consumers. An approach is proposed to realize the idea. It adopts an ontology database to store the experiences of tuning values for classifiers. A sample database is used to record training samples of image segments. Geoprocessing Web services are used as functionality blocks to finish basic classification steps. Workflow technology is involved to turn the overall image classification into a total automatic process. A Web-based prototypical system named PACS (Parameterless Automatic Classification System) is implemented. A number of images are fed into the system for evaluation purposes. The results show that the approach could automatically classify remote sensing images and have a fairly good average accuracy. It is indicated that the classified results will be more accurate if the two databases have higher quality. Once the experiences and samples in the databases are accumulated as many as an expert has, the approach should be able to get the results with similar quality to that a human expert can get. Since the approach is total automatic and parameterless, it can not only relieve remote sensing workers from the heavy and time-consuming parameter tuning work, but also significantly shorten the waiting time for consumers and facilitate them to engage in image classification activities. Currently, the approach is used only on high resolution optical three-band remote sensing imagery. The feasibility using the approach on other kinds of remote sensing images or involving additional bands in classification will be studied in future.

Discharge prediction in the Upper Senegal River using remote sensing data

NASA Astrophysics Data System (ADS)

Ceccarini, Iacopo; Raso, Luciano; Steele-Dunne, Susan; Hrachowitz, Markus; Nijzink, Remko; Bodian, Ansoumana; Claps, Pierluigi

2017-04-01

The Upper Senegal River, West Africa, is a poorly gauged basin. Nevertheless, discharge predictions are required in this river for the optimal operation of the downstream Manantali reservoir, flood forecasting, development plans for the entire basin and studies for adaptation to climate change. Despite the need for reliable discharge predictions, currently available rainfall-runoff models for this basin provide only poor performances, particularly during extreme regimes, both low-flow and high-flow. In this research we develop a rainfall-runoff model that combines remote-sensing input data and a-priori knowledge on catchment physical characteristics. This semi-distributed model, is based on conceptual numerical descriptions of hydrological processes at the catchment scale. Because of the lack of reliable input data from ground observations, we use the Tropical Rainfall Measuring Mission (TRMM) remote-sensing data for precipitation and the Global Land Evaporation Amsterdam Model (GLEAM) for the terrestrial potential evaporation. The model parameters are selected by a combination of calibration, by match of observed output and considering a large set of hydrological signatures, as well as a-priori knowledge on the catchment. The Generalized Likelihood Uncertainty Estimation (GLUE) method was used to choose the most likely range in which the parameter sets belong. Analysis of different experiments enhances our understanding on the added value of distributed remote-sensing data and a-priori information in rainfall-runoff modelling. Results of this research will be used for decision making at different scales, contributing to a rational use of water resources in this river.

Remote Sensing/gis Integration for Site Planning and Resource Management

NASA Technical Reports Server (NTRS)

Fellows, J. D.

1982-01-01

The development of an interactive/batch gridded information system (array of cells georeferenced to USGS quad sheets) and interfacing application programs (e.g., hydrologic models) is discussed. This system allows non-programer users to request any data set(s) stored in the data base by inputing any random polygon's (watershed, political zone) boundary points. The data base information contained within this polygon can be used to produce maps, statistics, and define model parameters for the area. Present/proposed conditions for the area may be compared by inputing future usage (land cover, soils, slope, etc.). This system, known as the Hydrologic Analysis Program (HAP), is especially effective in the real time analysis of proposed land cover changes on runoff hydrographs and graphics/statistics resource inventories of random study area/watersheds.

Learning consensus in adversarial environments

NASA Astrophysics Data System (ADS)

Vamvoudakis, Kyriakos G.; García Carrillo, Luis R.; Hespanha, João. P.

2013-05-01

This work presents a game theory-based consensus problem for leaderless multi-agent systems in the presence of adversarial inputs that are introducing disturbance to the dynamics. Given the presence of enemy components and the possibility of malicious cyber attacks compromising the security of networked teams, a position agreement must be reached by the networked mobile team based on environmental changes. The problem is addressed under a distributed decision making framework that is robust to possible cyber attacks, which has an advantage over centralized decision making in the sense that a decision maker is not required to access information from all the other decision makers. The proposed framework derives three tuning laws for every agent; one associated with the cost, one associated with the controller, and one with the adversarial input.

Influence of multi-source and multi-temporal remotely sensed and ancillary data on the accuracy of random forest classification of wetlands in northern Minnesota

USGS Publications Warehouse

Corcoran, Jennifer M.; Knight, Joseph F.; Gallant, Alisa L.

2013-01-01

Wetland mapping at the landscape scale using remotely sensed data requires both affordable data and an efficient accurate classification method. Random forest classification offers several advantages over traditional land cover classification techniques, including a bootstrapping technique to generate robust estimations of outliers in the training data, as well as the capability of measuring classification confidence. Though the random forest classifier can generate complex decision trees with a multitude of input data and still not run a high risk of over fitting, there is a great need to reduce computational and operational costs by including only key input data sets without sacrificing a significant level of accuracy. Our main questions for this study site in Northern Minnesota were: (1) how does classification accuracy and confidence of mapping wetlands compare using different remote sensing platforms and sets of input data; (2) what are the key input variables for accurate differentiation of upland, water, and wetlands, including wetland type; and (3) which datasets and seasonal imagery yield the best accuracy for wetland classification. Our results show the key input variables include terrain (elevation and curvature) and soils descriptors (hydric), along with an assortment of remotely sensed data collected in the spring (satellite visible, near infrared, and thermal bands; satellite normalized vegetation index and Tasseled Cap greenness and wetness; and horizontal-horizontal (HH) and horizontal-vertical (HV) polarization using L-band satellite radar). We undertook this exploratory analysis to inform decisions by natural resource managers charged with monitoring wetland ecosystems and to aid in designing a system for consistent operational mapping of wetlands across landscapes similar to those found in Northern Minnesota.

High efficient optical remote sensing images acquisition for nano-satellite: reconstruction algorithms

NASA Astrophysics Data System (ADS)

Liu, Yang; Li, Feng; Xin, Lei; Fu, Jie; Huang, Puming

2017-10-01

Large amount of data is one of the most obvious features in satellite based remote sensing systems, which is also a burden for data processing and transmission. The theory of compressive sensing(CS) has been proposed for almost a decade, and massive experiments show that CS has favorable performance in data compression and recovery, so we apply CS theory to remote sensing images acquisition. In CS, the construction of classical sensing matrix for all sparse signals has to satisfy the Restricted Isometry Property (RIP) strictly, which limits applying CS in practical in image compression. While for remote sensing images, we know some inherent characteristics such as non-negative, smoothness and etc.. Therefore, the goal of this paper is to present a novel measurement matrix that breaks RIP. The new sensing matrix consists of two parts: the standard Nyquist sampling matrix for thumbnails and the conventional CS sampling matrix. Since most of sun-synchronous based satellites fly around the earth 90 minutes and the revisit cycle is also short, lots of previously captured remote sensing images of the same place are available in advance. This drives us to reconstruct remote sensing images through a deep learning approach with those measurements from the new framework. Therefore, we propose a novel deep convolutional neural network (CNN) architecture which takes in undersampsing measurements as input and outputs an intermediate reconstruction image. It is well known that the training procedure to the network costs long time, luckily, the training step can be done only once, which makes the approach attractive for a host of sparse recovery problems.

Charge modeling of ionic polymer-metal composites for dynamic curvature sensing

NASA Astrophysics Data System (ADS)

Bahramzadeh, Yousef; Shahinpoor, Mohsen

2011-04-01

A curvature sensor based on Ionic Polymer-Metal Composite (IPMC) is proposed and characterized for sensing of curvature variation in structures such as inflatable space structures in which using low power and flexible curvature sensor is of high importance for dynamic monitoring of shape at desired points. The linearity of output signal of sensor for calibration, effect of deflection rate at low frequencies and the phase delay between the output signal and the input deformation of IPMC curvature sensor is investigated. An analytical chemo-electro-mechanical model for charge dynamic of IPMC sensor is presented based on Nernst-Planck partial differential equation which can be used to explain the phenomena observed in experiments. The rate dependency of output signal and phase delay between the applied deformation and sensor signal is studied using the proposed model. The model provides a background for predicting the general characteristics of IPMC sensor. It is shown that IPMC sensor exhibits good linearity, sensitivity, and repeatability for dynamic curvature sensing of inflatable structures.

Hydrological Relevant Parameters from Remote Sensing - Spatial Modelling Input and Validation Basis

NASA Astrophysics Data System (ADS)

Hochschild, V.

2012-12-01

This keynote paper will demonstrate how multisensoral remote sensing data is used as spatial input for mesoscale hydrological modeling as well as for sophisticated validation purposes. The tasks of Water Resources Management are subject as well as the role of remote sensing in regional catchment modeling. Parameters derived from remote sensing discussed in this presentation will be land cover, topographical information from digital elevation models, biophysical vegetation parameters, surface soil moisture, evapotranspiration estimations, lake level measurements, determination of snow covered area, lake ice cycles, soil erosion type, mass wasting monitoring, sealed area, flash flood estimation. The actual possibilities of recent satellite and airborne systems are discussed, as well as the data integration into GIS and hydrological modeling, scaling issues and quality assessment will be mentioned. The presentation will provide an overview of own research examples from Germany, Tibet and Africa (Ethiopia, South Africa) as well as other international research activities. Finally the paper gives an outlook on upcoming sensors and concludes the possibilities of remote sensing in hydrology.

Low-voltage analog front-end processor design for ISFET-based sensor and H+ sensing applications

NASA Astrophysics Data System (ADS)

Chung, Wen-Yaw; Yang, Chung-Huang; Peng, Kang-Chu; Yeh, M. H.

2003-04-01

This paper presents a modular-based low-voltage analog-front-end processor design in a 0.5mm double-poly double-metal CMOS technology for Ion Sensitive Field Effect Transistor (ISFET)-based sensor and H+ sensing applications. To meet the potentiometric response of the ISFET that is proportional to various H+ concentrations, the constant-voltage and constant current (CVCS) testing configuration has been used. Low-voltage design skills such as bulk-driven input pair, folded-cascode amplifier, bootstrap switch control circuits have been designed and integrated for 1.5V supply and nearly rail-to-rail analog to digital signal processing. Core modules consist of an 8-bit two-step analog-digital converter and bulk-driven pre-amplifiers have been developed in this research. The experimental results show that the proposed circuitry has an acceptable linearity to 0.1 pH-H+ sensing conversions with the buffer solution in the range of pH2 to pH12. The processor has a potential usage in battery-operated and portable healthcare devices and environmental monitoring applications.

Method and system for spatially variable rate application of agricultural chemicals based on remotely sensed vegetation data

NASA Technical Reports Server (NTRS)

Lewis, Mark David (Inventor); Seal, Michael R. (Inventor); Hood, Kenneth Brown (Inventor); Johnson, James William (Inventor)

2007-01-01

Remotely sensed spectral image data are used to develop a Vegetation Index file which represents spatial variations of actual crop vigor throughout a field that is under cultivation. The latter information is processed to place it in a format that can be used by farm personnel to correlate and calibrate it with actually observed crop conditions existing at control points within the field. Based on the results, farm personnel formulate a prescription request, which is forwarded via email or FTP to a central processing site, where the prescription is prepared. The latter is returned via email or FTP to on-side farm personnel, who can load it into a controller on a spray rig that directly applies inputs to the field at a spatially variable rate.

Method and apparatus for spatially variable rate application of agricultural chemicals based on remotely sensed vegetation data

NASA Technical Reports Server (NTRS)

Hood, Kenneth Brown (Inventor); Johnson, James William (Inventor); Seal, Michael R. (Inventor); Lewis, Mark David (Inventor)

2004-01-01

Remotely sensed spectral image data are used to develop a Vegetation Index file which represents spatial variations of actual crop vigor throughout a field that is under cultivation. The latter information is processed to place it in a format that can be used by farm personnel to correlate and calibrate it with actually observed crop conditions existing at control points within the field. Based on the results, farm personnel formulate a prescription request, which is forwarded via email or FTP to a central processing site, where the prescription is prepared. The latter is returned via email or FTP to on-side farm personnel, who can load it into a controller on a spray rig that directly applies inputs to the field at a spatially variable rate.

Classification of Active Microwave and Passive Optical Data Based on Bayesian Theory and Mrf

NASA Astrophysics Data System (ADS)

Yu, F.; Li, H. T.; Han, Y. S.; Gu, H. Y.

2012-08-01

A classifier based on Bayesian theory and Markov random field (MRF) is presented to classify the active microwave and passive optical remote sensing data, which have demonstrated their respective advantages in inversion of surface soil moisture content. In the method, the VV, VH polarization of ASAR and all the 7 TM bands are taken as the input of the classifier to get the class labels of each pixel of the images. And the model is validated for the necessities of integration of TM and ASAR, it shows that, the total precision of classification in this paper is 89.4%. Comparing with the classification with single TM, the accuracy increase 11.5%, illustrating that synthesis of active and passive optical remote sensing data is efficient and potential in classification.

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.

Thermal Infrared Remote Sensing for Analysis of Landscape Ecological Processes: Current Insights and Trends. Chapter 3

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Luvall, Jeffrey C.

2014-01-01

NASA or NOAA Earth-observing satellites are not the only space-based TIR platforms. The European Space Agency (ESA), the Chinese, and other countries have in orbit or plan to launch TIR remote sensing systems. Satellite remote sensing provides an excellent opportunity to study land-atmosphere energy exchanges at the regional scale. A predominant application of TIR data has been in inferring evaporation, evapotranspiration (ET), and soil moisture. In addition to using TIR data for ET and soil moisture analysis over vegetated surfaces, there is also a need for using these data for assessment of drought conditions. The concept of ecological thermodynamics provides a quantification of surface energy fluxes for landscape characterization in relation to the overall amount of energy input and output from specific land cover types.

Absolute radiometric calibration of advanced remote sensing systems

NASA Technical Reports Server (NTRS)

Slater, P. N.

1982-01-01

The distinction between the uses of relative and absolute spectroradiometric calibration of remote sensing systems is discussed. The advantages of detector-based absolute calibration are described, and the categories of relative and absolute system calibrations are listed. The limitations and problems associated with three common methods used for the absolute calibration of remote sensing systems are addressed. Two methods are proposed for the in-flight absolute calibration of advanced multispectral linear array systems. One makes use of a sun-illuminated panel in front of the sensor, the radiance of which is monitored by a spectrally flat pyroelectric radiometer. The other uses a large, uniform, high-radiance reference ground surface. The ground and atmospheric measurements required as input to a radiative transfer program to predict the radiance level at the entrance pupil of the orbital sensor are discussed, and the ground instrumentation is described.

Equity Theory Ratios as Causal Schemas.

PubMed

Arvanitis, Alexios; Hantzi, Alexandra

2016-01-01

Equity theory approaches justice evaluations based on ratios of exchange inputs to exchange outcomes. Situations are evaluated as just if ratios are equal and unjust if unequal. We suggest that equity ratios serve a more fundamental cognitive function than the evaluation of justice. More particularly, we propose that they serve as causal schemas for exchange outcomes, that is, they assist in determining whether certain outcomes are caused by inputs of other people in the context of an exchange process. Equality or inequality of ratios in this sense points to an exchange process. Indeed, Study 1 shows that different exchange situations, such as disproportional or balanced proportional situations, create perceptions of give-and-take on the basis of equity ratios. Study 2 shows that perceptions of justice are based more on communicatively accepted rules of interaction than equity-based evaluations, thereby offering a distinction between an attribution and an evaluation cognitive process for exchange outcomes.

Equity Theory Ratios as Causal Schemas

PubMed Central

Arvanitis, Alexios; Hantzi, Alexandra

2016-01-01

Equity theory approaches justice evaluations based on ratios of exchange inputs to exchange outcomes. Situations are evaluated as just if ratios are equal and unjust if unequal. We suggest that equity ratios serve a more fundamental cognitive function than the evaluation of justice. More particularly, we propose that they serve as causal schemas for exchange outcomes, that is, they assist in determining whether certain outcomes are caused by inputs of other people in the context of an exchange process. Equality or inequality of ratios in this sense points to an exchange process. Indeed, Study 1 shows that different exchange situations, such as disproportional or balanced proportional situations, create perceptions of give-and-take on the basis of equity ratios. Study 2 shows that perceptions of justice are based more on communicatively accepted rules of interaction than equity-based evaluations, thereby offering a distinction between an attribution and an evaluation cognitive process for exchange outcomes. PMID:27594846

RF Spectrum Sensing Based on an Overdamped Nonlinear Oscillator Ring for Cognitive Radios

PubMed Central

Tang, Zhi-Ling; Li, Si-Min; Yu, Li-Juan

2016-01-01

Existing spectrum-sensing techniques for cognitive radios require an analog-to-digital converter (ADC) to work at high dynamic range and a high sampling rate, resulting in high cost. Therefore, in this paper, a spectrum-sensing method based on a unidirectionally coupled, overdamped nonlinear oscillator ring is proposed. First, the numerical model of such a system is established based on the circuit of the nonlinear oscillator. Through numerical analysis of the model, the critical condition of the system’s starting oscillation is determined, and the simulation results of the system’s response to Gaussian white noise and periodic signal are presented. The results show that once the radio signal is input into the system, it starts oscillating when in the critical region, and the oscillating frequency of each element is fo/N, where fo is the frequency of the radio signal and N is the number of elements in the ring. The oscillation indicates that the spectrum resources at fo are occupied. At the same time, the sampling rate required for an ADC is reduced to the original value, 1/N. A prototypical circuit to verify the functionality of the system is designed, and the sensing bandwidth of the system is measured. PMID:27294928

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

NASA Astrophysics Data System (ADS)

Saha, Ardhendu; Datta, Arijit; Kaman, Surjit

2018-03-01

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

Parallel consensual neural networks.

PubMed

Benediktsson, J A; Sveinsson, J R; Ersoy, O K; Swain, P H

1997-01-01

A new type of a neural-network architecture, the parallel consensual neural network (PCNN), is introduced and applied in classification/data fusion of multisource remote sensing and geographic data. The PCNN architecture is based on statistical consensus theory and involves using stage neural networks with transformed input data. The input data are transformed several times and the different transformed data are used as if they were independent inputs. The independent inputs are first classified using the stage neural networks. The output responses from the stage networks are then weighted and combined to make a consensual decision. In this paper, optimization methods are used in order to weight the outputs from the stage networks. Two approaches are proposed to compute the data transforms for the PCNN, one for binary data and another for analog data. The analog approach uses wavelet packets. The experimental results obtained with the proposed approach show that the PCNN outperforms both a conjugate-gradient backpropagation neural network and conventional statistical methods in terms of overall classification accuracy of test data.

A Hybrid Semi-Digital Transimpedance Amplifier With Noise Cancellation Technique for Nanopore-Based DNA Sequencing.

PubMed

Hsu, Chung-Lun; Jiang, Haowei; Venkatesh, A G; Hall, Drew A

2015-10-01

Over the past two decades, nanopores have been a promising technology for next generation deoxyribonucleic acid (DNA) sequencing. Here, we present a hybrid semi-digital transimpedance amplifier (HSD-TIA) to sense the minute current signatures introduced by single-stranded DNA (ssDNA) translocating through a nanopore, while discharging the baseline current using a semi-digital feedback loop. The amplifier achieves fast settling by adaptively tuning a DC compensation current when a step input is detected. A noise cancellation technique reduces the total input-referred current noise caused by the parasitic input capacitance. Measurement results show the performance of the amplifier with 31.6 M Ω mid-band gain, 950 kHz bandwidth, and 8.5 fA/ √Hz input-referred current noise, a 2× noise reduction due to the noise cancellation technique. The settling response is demonstrated by observing the insertion of a protein nanopore in a lipid bilayer. Using the nanopore, the HSD-TIA was able to measure ssDNA translocation events.

A Multi-Component Automated Laser-Origami System for Cyber-Manufacturing

NASA Astrophysics Data System (ADS)

Ko, Woo-Hyun; Srinivasa, Arun; Kumar, P. R.

2017-12-01

Cyber-manufacturing systems can be enhanced by an integrated network architecture that is easily configurable, reliable, and scalable. We consider a cyber-physical system for use in an origami-type laser-based custom manufacturing machine employing folding and cutting of sheet material to manufacture 3D objects. We have developed such a system for use in a laser-based autonomous custom manufacturing machine equipped with real-time sensing and control. The basic elements in the architecture are built around the laser processing machine. They include a sensing system to estimate the state of the workpiece, a control system determining control inputs for a laser system based on the estimated data and user’s job requests, a robotic arm manipulating the workpiece in the work space, and middleware, named Etherware, supporting the communication among the systems. We demonstrate automated 3D laser cutting and bending to fabricate a 3D product as an experimental result.

Electronic circuit provides accurate sensing and control of dc voltage

NASA Technical Reports Server (NTRS)

Loftus, W. D.

1966-01-01

Electronic circuit used relay coil to sense and control dc voltage. The control relay is driven by a switching transistor that is biased to cutoff for all input up to slightly less than the threshold level.

Regional yield predictions of malting barley by remote sensing and ancillary data

NASA Astrophysics Data System (ADS)

Weissteiner, Christof J.; Braun, Matthias; Kuehbauch, Walter

2004-02-01

Yield forecasts are of high interest to the malting and brewing industry in order to allow the most convenient purchasing policy of raw materials. Within this investigation, malting barley yield forecasts (Hordeum vulgare L.) were performed for typical growing regions in South-Western Germany. Multisensoral and multitemporal Remote Sensing data on one hand and ancillary meteorological, agrostatistical, topographical and pedological data on the other hand were used as input data for prediction models, which were based on an empirical-statistical modeling approach. Since spring barley production is depending on acreage and on the yield per area, classification is needed, which was performed by a supervised multitemporal classification algorithm, utilizing optical Remote Sensing data (LANDSAT TM/ETM+). Comparison between a pixel-based and an object-oriented classification algorithm was carried out. The basic version of the yield estimation model was conducted by means of linear correlation of Remote Sensing data (NOAA-AVHRR NDVI), CORINE land cover data and agrostatistical data. In an extended version meteorological data (temperature, precipitation, etc.) and soil data was incorporated. Both, basic and extended prediction systems, led to feasible results, depending on the selection of the time span for NDVI accumulation.

Electric current locator

DOEpatents

King, Paul E [Corvallis, OR; Woodside, Charles Rigel [Corvallis, OR

2012-02-07

The disclosure herein provides an apparatus for location of a quantity of current vectors in an electrical device, where the current vector has a known direction and a known relative magnitude to an input current supplied to the electrical device. Mathematical constants used in Biot-Savart superposition equations are determined for the electrical device, the orientation of the apparatus, and relative magnitude of the current vector and the input current, and the apparatus utilizes magnetic field sensors oriented to a sensing plane to provide current vector location based on the solution of the Biot-Savart superposition equations. Description of required orientations between the apparatus and the electrical device are disclosed and various methods of determining the mathematical constants are presented.

Engineering integrated digital circuits with allosteric ribozymes for scaling up molecular computation and diagnostics.

PubMed

Penchovsky, Robert

2012-10-19

Here we describe molecular implementations of integrated digital circuits, including a three-input AND logic gate, a two-input multiplexer, and 1-to-2 decoder using allosteric ribozymes. Furthermore, we demonstrate a multiplexer-decoder circuit. The ribozymes are designed to seek-and-destroy specific RNAs with a certain length by a fully computerized procedure. The algorithm can accurately predict one base substitution that alters the ribozyme's logic function. The ability to sense the length of RNA molecules enables single ribozymes to be used as platforms for multiple interactions. These ribozymes can work as integrated circuits with the functionality of up to five logic gates. The ribozyme design is universal since the allosteric and substrate domains can be altered to sense different RNAs. In addition, the ribozymes can specifically cleave RNA molecules with triplet-repeat expansions observed in genetic disorders such as oculopharyngeal muscular dystrophy. Therefore, the designer ribozymes can be employed for scaling up computing and diagnostic networks in the fields of molecular computing and diagnostics and RNA synthetic biology.

Assessment of the use of space technology in the monitoring of oil spills and ocean pollution: Executive summary

NASA Technical Reports Server (NTRS)

Alvarado, U. R. (Editor)

1980-01-01

The adequacy of current technology in terms of stage of maturity, of sensing, support systems, and information extraction was assessed relative to oil spills, waste pollution, and inputs to pollution trajectory models. Needs for advanced techniques are defined and the characteristics of a future satellite system are determined based on the requirements of U.S. agencies involved in pollution monitoring.

Mapping the Risks of Malaria, Dengue and Influenza Using Satellite Data

NASA Astrophysics Data System (ADS)

Kiang, R. K.; Soebiyanto, R. P.

2012-07-01

It has long been recognized that environment and climate may affect the transmission of infectious diseases. The effects are most obvious for vector-borne infectious diseases, such as malaria and dengue, but less so for airborne and contact diseases, such as seasonal influenza. In this paper, we examined the meteorological and environmental parameters that influence the transmission of malaria, dengue and seasonal influenza. Remotely sensed parameters that provide such parameters were discussed. Both statistical and biologically inspired, processed based models can be used to model the transmission of these diseases utilizing the remotely sensed parameters as input. Examples were given for modelling malaria in Thailand, dengue in Indonesia, and seasonal influenza in Hong Kong.

Visible-infrared remote-sensing model and applications for ocean waters. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Lee, Zhongping

1994-01-01

Remote sensing has become important in the ocean sciences, especially for research involving large spatial scales. To estimate the in-water constituents through remote sensing, whether carried out by satellite or airplane, the signal emitted from beneath the sea surface, the so called water-leaving radiance (L(w)), is of prime importance. The magnitude of L(w) depends on two terms: one is the intensity of the solar input, and the other is the reflectance of the in-water constituents. The ratio of the water-leaving radiance to the downwelling irradiance (E(d)) above the sear surface (remote-sensing reflectance, R(sub rs)) is independent of the intensity of the irradiance input, and is largely a function of the optical properties of the in-water constituents. In this work, a model is developed to interpret r(sub rs) for ocean water in the visible-infrared range. In addition to terms for the radiance scattered from molecules and particles, the model includes terms that describe contributions from bottom reflectance, fluorescence of gelbstoff or colored dissolved organic matter (CDOM), and water Raman scattering. By using this model, the measured R(sub rs) of waters from the West Florida Shelf to the Mississippi River plume, which covered a (concentration of chlorophyll a) range of 0.07 - 50 mg/cu m, were well interpreted. The average percentage difference (a.p.d.) between the measured and modeled R(sub rs) is 3.4%, and, for the shallow waters, the model-required water depth is within 10% of the chart depth. Simple mathematical simulations for the phytoplankton pigment absorption coefficient (a(sub theta)) are suggested for using the R(sub rs) model. The inverse problem of R(sub rs), which is to analytically derive the in-water constituents from R(sub rs) data alone, can be solved using the a(sub theta) functions without prior knowledge of the in-water optical properties. More importantly, this method avoids problems associated with a need for knowledge of the shape and value of the chlorophyll-specific absorption coefficient. The simulation was tested for a wide range of water types, including waters from Monterey Bay, the West Florida Shelf, and the Mississippi River plume. Using the simulation, the R(sub rs)-derived in-water absorption coefficients were consistent with the values from in-water measurements (r(exp 2) greater than 0.94, slope approximately 1.0). In the remote-sensing applications, a new approach is suggested for the estimation of primary production based on remote sensing. Using this approach, the calculated primary production (PP) values based upon remotely sensed data were very close to the measured values for the euphotic zone (r(exp 2) = 0.95, slope 1.26, and 32% average difference), while traditional, pigment-based PP model provided values only one-third the size of the measured data. This indicates a potential to significantly improve the accuracy of the estimation of primary production based upon remote sensing.

Synthetic Biology Platform for Sensing and Integrating Endogenous Transcriptional Inputs in Mammalian Cells.

PubMed

Angelici, Bartolomeo; Mailand, Erik; Haefliger, Benjamin; Benenson, Yaakov

2016-08-30

One of the goals of synthetic biology is to develop programmable artificial gene networks that can transduce multiple endogenous molecular cues to precisely control cell behavior. Realizing this vision requires interfacing natural molecular inputs with synthetic components that generate functional molecular outputs. Interfacing synthetic circuits with endogenous mammalian transcription factors has been particularly difficult. Here, we describe a systematic approach that enables integration and transduction of multiple mammalian transcription factor inputs by a synthetic network. The approach is facilitated by a proportional amplifier sensor based on synergistic positive autoregulation. The circuits efficiently transduce endogenous transcription factor levels into RNAi, transcriptional transactivation, and site-specific recombination. They also enable AND logic between pairs of arbitrary transcription factors. The results establish a framework for developing synthetic gene networks that interface with cellular processes through transcriptional regulators. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.

An Interactive Web-Based Analysis Framework for Remote Sensing Cloud Computing

NASA Astrophysics Data System (ADS)

Wang, X. Z.; Zhang, H. M.; Zhao, J. H.; Lin, Q. H.; Zhou, Y. C.; Li, J. H.

2015-07-01

Spatiotemporal data, especially remote sensing data, are widely used in ecological, geographical, agriculture, and military research and applications. With the development of remote sensing technology, more and more remote sensing data are accumulated and stored in the cloud. An effective way for cloud users to access and analyse these massive spatiotemporal data in the web clients becomes an urgent issue. In this paper, we proposed a new scalable, interactive and web-based cloud computing solution for massive remote sensing data analysis. We build a spatiotemporal analysis platform to provide the end-user with a safe and convenient way to access massive remote sensing data stored in the cloud. The lightweight cloud storage system used to store public data and users' private data is constructed based on open source distributed file system. In it, massive remote sensing data are stored as public data, while the intermediate and input data are stored as private data. The elastic, scalable, and flexible cloud computing environment is built using Docker, which is a technology of open-source lightweight cloud computing container in the Linux operating system. In the Docker container, open-source software such as IPython, NumPy, GDAL, and Grass GIS etc., are deployed. Users can write scripts in the IPython Notebook web page through the web browser to process data, and the scripts will be submitted to IPython kernel to be executed. By comparing the performance of remote sensing data analysis tasks executed in Docker container, KVM virtual machines and physical machines respectively, we can conclude that the cloud computing environment built by Docker makes the greatest use of the host system resources, and can handle more concurrent spatial-temporal computing tasks. Docker technology provides resource isolation mechanism in aspects of IO, CPU, and memory etc., which offers security guarantee when processing remote sensing data in the IPython Notebook. Users can write complex data processing code on the web directly, so they can design their own data processing algorithm.

Method and apparatus for wavefront sensing

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

Bahk, Seung-Whan

A method for performing optical wavefront sensing includes providing an amplitude transmission mask having a light input side, a light output side, and an optical transmission axis passing from the light input side to the light output side. The amplitude transmission mask is characterized by a checkerboard pattern having a square unit cell of size .LAMBDA.. The method also includes directing an incident light field having a wavelengthmore » $$ \\lamda $$ to be incident on the light input side and propagating the incident light field through the amplitude transmission mask. The method further includes producing a plurality of diffracted light fields on the light output side and detecting, at a detector disposed a distance L from the amplitude transmission mask, an interferogram associated with the plurality of diffracted light fields.« less

Phase detector for three-phase power factor controller

NASA Technical Reports Server (NTRS)

Nola, F. J. (Inventor)

1984-01-01

A phase detector for the three phase power factor controller (PFC) is described. The phase detector for each phase includes an operational amplifier which senses the current phase angle for that phase by sensing the voltage across the phase thyristor. Common mode rejection is achieved by providing positive feedback between the input and output of the voltage sensing operational amplifier. this feedback preferably comprises a resistor connected between the output and input of the operational amplifier. The novelty of the invention resides in providing positive feedback such that switching of the operational amplifier is synchronized with switching of the voltage across the thyristor. The invention provides a solution to problems associated with high common mode voltage and enables use of lower cost components than would be required by other approaches.

Technology for organization of the onboard system for processing and storage of ERS data for ultrasmall spacecraft

NASA Astrophysics Data System (ADS)

Strotov, Valery V.; Taganov, Alexander I.; Konkin, Yuriy V.; Kolesenkov, Aleksandr N.

2017-10-01

Task of processing and analysis of obtained Earth remote sensing data on ultra-small spacecraft board is actual taking into consideration significant expenditures of energy for data transfer and low productivity of computers. Thereby, there is an issue of effective and reliable storage of the general information flow obtained from onboard systems of information collection, including Earth remote sensing data, into a specialized data base. The paper has considered peculiarities of database management system operation with the multilevel memory structure. For storage of data in data base the format has been developed that describes a data base physical structure which contains required parameters for information loading. Such structure allows reducing a memory size occupied by data base because it is not necessary to store values of keys separately. The paper has shown architecture of the relational database management system oriented into embedment into the onboard ultra-small spacecraft software. Data base for storage of different information, including Earth remote sensing data, can be developed by means of such database management system for its following processing. Suggested database management system architecture has low requirements to power of the computer systems and memory resources on the ultra-small spacecraft board. Data integrity is ensured under input and change of the structured information.

Dynamic protein assembly by programmable DNA strand displacement.

PubMed

Chen, Rebecca P; Blackstock, Daniel; Sun, Qing; Chen, Wilfred

2018-04-01

Inspired by the remarkable ability of natural protein switches to sense and respond to a wide range of environmental queues, here we report a strategy to engineer synthetic protein switches by using DNA strand displacement to dynamically organize proteins with highly diverse and complex logic gate architectures. We show that DNA strand displacement can be used to dynamically control the spatial proximity and the corresponding fluorescence resonance energy transfer between two fluorescent proteins. Performing Boolean logic operations enabled the explicit control of protein proximity using multi-input, reversible and amplification architectures. We further demonstrate the power of this technology beyond sensing by achieving dynamic control of an enzyme cascade. Finally, we establish the utility of the approach as a synthetic computing platform that drives the dynamic reconstitution of a split enzyme for targeted prodrug activation based on the sensing of cancer-specific miRNAs.

Dynamic protein assembly by programmable DNA strand displacement

NASA Astrophysics Data System (ADS)

Chen, Rebecca P.; Blackstock, Daniel; Sun, Qing; Chen, Wilfred

2018-03-01

Inspired by the remarkable ability of natural protein switches to sense and respond to a wide range of environmental queues, here we report a strategy to engineer synthetic protein switches by using DNA strand displacement to dynamically organize proteins with highly diverse and complex logic gate architectures. We show that DNA strand displacement can be used to dynamically control the spatial proximity and the corresponding fluorescence resonance energy transfer between two fluorescent proteins. Performing Boolean logic operations enabled the explicit control of protein proximity using multi-input, reversible and amplification architectures. We further demonstrate the power of this technology beyond sensing by achieving dynamic control of an enzyme cascade. Finally, we establish the utility of the approach as a synthetic computing platform that drives the dynamic reconstitution of a split enzyme for targeted prodrug activation based on the sensing of cancer-specific miRNAs.

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

Cement-based piezoelectric ceramic composites for sensor applications in civil engineering

NASA Astrophysics Data System (ADS)

Dong, Biqin

The objectives of this thesis are to develop and apply a new smart composite for the sensing and actuation application of civil engineering. Piezoelectric ceramic powder is incorporated into cement-based composite to achieve the sensing and actuation capability. The research investigates microstructure, polarization and aging, material properties and performance of cement-based piezoelectric ceramic composites both theoretically and experimentally. A hydrogen bonding is found at the interface of piezoelectric ceramic powder and cement phase by IR (Infrared Ray), XPS (X-ray Photoelectron Spectroscopy) and SIMS (Secondary Ion Mass Spectroscopy). It largely affects the material properties of composites. A simple first order model is introduced to explain the poling mechanism of composites and the dependency of polarization is discussed using electromechanical coupling coefficient kt. The mechanisms acting on the aging effect is explored in detail. Dielectrical, piezoelectric and mechanical properties of the cement-based piezoelectric ceramic composites are studied by experiment and theoretical calculation based on modified cube model (n=1) with chemical bonding . A complex circuit model is proposed to explain the unique feature of impedance spectra and the instinct of high-loss of cement-based piezoelectric ceramic composite. The sensing ability of cement-based piezoelectric ceramic composite has been evaluated by using step wave, sine wave, and random wave. It shows that the output of the composite can reflects the nature and characteristics of mechanical input. The work in this thesis opens a new direction for the current actuation/sensing technology in civil engineering. The materials and techniques, developed in this work, have a great potential in application of health monitoring of buildings and infrastructures.

Reinforcement-Learning-Based Robust Controller Design for Continuous-Time Uncertain Nonlinear Systems Subject to Input Constraints.

PubMed

Liu, Derong; Yang, Xiong; Wang, Ding; Wei, Qinglai

2015-07-01

The design of stabilizing controller for uncertain nonlinear systems with control constraints is a challenging problem. The constrained-input coupled with the inability to identify accurately the uncertainties motivates the design of stabilizing controller based on reinforcement-learning (RL) methods. In this paper, a novel RL-based robust adaptive control algorithm is developed for a class of continuous-time uncertain nonlinear systems subject to input constraints. The robust control problem is converted to the constrained optimal control problem with appropriately selecting value functions for the nominal system. Distinct from typical action-critic dual networks employed in RL, only one critic neural network (NN) is constructed to derive the approximate optimal control. Meanwhile, unlike initial stabilizing control often indispensable in RL, there is no special requirement imposed on the initial control. By utilizing Lyapunov's direct method, the closed-loop optimal control system and the estimated weights of the critic NN are proved to be uniformly ultimately bounded. In addition, the derived approximate optimal control is verified to guarantee the uncertain nonlinear system to be stable in the sense of uniform ultimate boundedness. Two simulation examples are provided to illustrate the effectiveness and applicability of the present approach.

An Approximation to the Adaptive Exponential Integrate-and-Fire Neuron Model Allows Fast and Predictive Fitting to Physiological Data.

PubMed

Hertäg, Loreen; Hass, Joachim; Golovko, Tatiana; Durstewitz, Daniel

2012-01-01

For large-scale network simulations, it is often desirable to have computationally tractable, yet in a defined sense still physiologically valid neuron models. In particular, these models should be able to reproduce physiological measurements, ideally in a predictive sense, and under different input regimes in which neurons may operate in vivo. Here we present an approach to parameter estimation for a simple spiking neuron model mainly based on standard f-I curves obtained from in vitro recordings. Such recordings are routinely obtained in standard protocols and assess a neuron's response under a wide range of mean-input currents. Our fitting procedure makes use of closed-form expressions for the firing rate derived from an approximation to the adaptive exponential integrate-and-fire (AdEx) model. The resulting fitting process is simple and about two orders of magnitude faster compared to methods based on numerical integration of the differential equations. We probe this method on different cell types recorded from rodent prefrontal cortex. After fitting to the f-I current-clamp data, the model cells are tested on completely different sets of recordings obtained by fluctuating ("in vivo-like") input currents. For a wide range of different input regimes, cell types, and cortical layers, the model could predict spike times on these test traces quite accurately within the bounds of physiological reliability, although no information from these distinct test sets was used for model fitting. Further analyses delineated some of the empirical factors constraining model fitting and the model's generalization performance. An even simpler adaptive LIF neuron was also examined in this context. Hence, we have developed a "high-throughput" model fitting procedure which is simple and fast, with good prediction performance, and which relies only on firing rate information and standard physiological data widely and easily available.

Light adaptation alters the source of inhibition to the mouse retinal OFF pathway

PubMed Central

Mazade, Reece E.

2013-01-01

Sensory systems must avoid saturation to encode a wide range of stimulus intensities. One way the retina accomplishes this is by using both dim-light-sensing rod and bright-light-sensing cone photoreceptor circuits. OFF cone bipolar cells are a key point in this process, as they receive both excitatory input from cones and inhibitory input from AII amacrine cells via the rod pathway. However, in addition to AII amacrine cell input, other inhibitory inputs from cone pathways also modulate OFF cone bipolar cell light signals. It is unknown how these inhibitory inputs to OFF cone bipolar cells change when switching between rod and cone pathways or whether all OFF cone bipolar cells receive rod pathway input. We found that one group of OFF cone bipolar cells (types 1, 2, and 4) receive rod-mediated inhibitory inputs that likely come from the rod-AII amacrine cell pathway, while another group of OFF cone bipolar cells (type 3) do not. In both cases, dark-adapted rod-dominant light responses showed a significant contribution of glycinergic inhibition, which decreased with light adaptation and was, surprisingly, compensated by an increase in GABAergic inhibition. As GABAergic input has distinct timing and spatial spread from glycinergic input, a shift from glycinergic to GABAergic inhibition could significantly alter OFF cone bipolar cell signaling to downstream OFF ganglion cells. Larger GABAergic input could reflect an adjustment of OFF bipolar cell spatial inhibition, which may be one mechanism that contributes to retinal spatial sensitivity in the light. PMID:23926034

A gold nanocluster-based fluorescent probe for simultaneous pH and temperature sensing and its application to cellular imaging and logic gates

NASA Astrophysics Data System (ADS)

Wu, Yun-Tse; Shanmugam, Chandirasekar; Tseng, Wei-Bin; Hiseh, Ming-Mu; Tseng, Wei-Lung

2016-05-01

Metal nanocluster-based nanomaterials for the simultaneous determination of temperature and pH variations in micro-environments are still a challenge. In this study, we develop a dual-emission fluorescent probe consisting of bovine serum albumin-stabilized gold nanoclusters (BSA-AuNCs) and fluorescein-5-isothiocyanate (FITC) as temperature- and pH-responsive fluorescence signals. Under single wavelength excitation the FITC/BSA-AuNCs exhibited well-separated dual emission bands at 525 and 670 nm. When FITC was used as a reference fluorophore, FITC/BSA-AuNCs showed a good linear response over the temperature range 1-71 °C and offered temperature-independent spectral shifts, temperature accuracy, activation energy, and reusability. The possible mechanism for high temperature-induced fluorescence quenching of FITC/BSA-AuNCs could be attributed to a weakening of the Au-S bond, thereby lowering the charge transfer from BSA to AuNCs. Additionally, the pH- and temperature-responsive properties of FITC/BSA-AuNCs allow simultaneous temperature sensing from 21 to 41 °C (at intervals of 5 °C) and pH from 6.0 to 8.0 (at intervals of 0.5 pH unit), facilitating the construction of two-input AND logic gates. Three-input AND logic gates were also designed using temperature, pH, and trypsin as inputs. The practicality of using FITC/BSA-AuNCs to determine the temperature and pH changes in HeLa cells is also validated.Metal nanocluster-based nanomaterials for the simultaneous determination of temperature and pH variations in micro-environments are still a challenge. In this study, we develop a dual-emission fluorescent probe consisting of bovine serum albumin-stabilized gold nanoclusters (BSA-AuNCs) and fluorescein-5-isothiocyanate (FITC) as temperature- and pH-responsive fluorescence signals. Under single wavelength excitation the FITC/BSA-AuNCs exhibited well-separated dual emission bands at 525 and 670 nm. When FITC was used as a reference fluorophore, FITC/BSA-AuNCs showed a good linear response over the temperature range 1-71 °C and offered temperature-independent spectral shifts, temperature accuracy, activation energy, and reusability. The possible mechanism for high temperature-induced fluorescence quenching of FITC/BSA-AuNCs could be attributed to a weakening of the Au-S bond, thereby lowering the charge transfer from BSA to AuNCs. Additionally, the pH- and temperature-responsive properties of FITC/BSA-AuNCs allow simultaneous temperature sensing from 21 to 41 °C (at intervals of 5 °C) and pH from 6.0 to 8.0 (at intervals of 0.5 pH unit), facilitating the construction of two-input AND logic gates. Three-input AND logic gates were also designed using temperature, pH, and trypsin as inputs. The practicality of using FITC/BSA-AuNCs to determine the temperature and pH changes in HeLa cells is also validated. Electronic supplementary information (ESI) available. See DOI: 10.1039/c6nr02341j

A New Approach to Image Fusion Based on Cokriging

NASA Technical Reports Server (NTRS)

Memarsadeghi, Nargess; LeMoigne, Jacqueline; Mount, David M.; Morisette, Jeffrey T.

2005-01-01

We consider the image fusion problem involving remotely sensed data. We introduce cokriging as a method to perform fusion. We investigate the advantages of fusing Hyperion with ALI. The evaluation is performed by comparing the classification of the fused data with that of input images and by calculating well-chosen quantitative fusion quality metrics. We consider the Invasive Species Forecasting System (ISFS) project as our fusion application. The fusion of ALI with Hyperion data is studies using PCA and wavelet-based fusion. We then propose utilizing a geostatistical based interpolation method called cokriging as a new approach for image fusion.

Diet and Energy-Sensing Inputs Affect TorC1-Mediated Axon Misrouting but Not TorC2-Directed Synapse Growth in a Drosophila Model of Tuberous Sclerosis

PubMed Central

Dimitroff, Brian; Lee, Hyun-Gwan; Zhao, Na; O'Connor, Michael B.; Neufeld, Thomas P.; Selleck, Scott B.

2012-01-01

The Target of Rapamycin (TOR) growth regulatory system is influenced by a number of different inputs, including growth factor signaling, nutrient availability, and cellular energy levels. While the effects of TOR on cell and organismal growth have been well characterized, this pathway also has profound effects on neural development and behavior. Hyperactivation of the TOR pathway by mutations in the upstream TOR inhibitors TSC1 (tuberous sclerosis complex 1) or TSC2 promotes benign tumors and neurological and behavioral deficits, a syndrome known as tuberous sclerosis (TS). In Drosophila, neuron-specific overexpression of Rheb, the direct downstream target inhibited by Tsc1/Tsc2, produced significant synapse overgrowth, axon misrouting, and phototaxis deficits. To understand how misregulation of Tor signaling affects neural and behavioral development, we examined the influence of growth factor, nutrient, and energy sensing inputs on these neurodevelopmental phenotypes. Neural expression of Pi3K, a principal mediator of growth factor inputs to Tor, caused synapse overgrowth similar to Rheb, but did not disrupt axon guidance or phototaxis. Dietary restriction rescued Rheb-mediated behavioral and axon guidance deficits, as did overexpression of AMPK, a component of the cellular energy sensing pathway, but neither was able to rescue synapse overgrowth. While axon guidance and behavioral phenotypes were affected by altering the function of a Tor complex 1 (TorC1) component, Raptor, or a TORC1 downstream element (S6k), synapse overgrowth was only suppressed by reducing the function of Tor complex 2 (TorC2) components (Rictor, Sin1). These findings demonstrate that different inputs to Tor signaling have distinct activities in nervous system development, and that Tor provides an important connection between nutrient-energy sensing systems and patterning of the nervous system. PMID:22319582

Mineralogy and Astrobiology Detection Using Laser Remote Sensing Instrument

NASA Technical Reports Server (NTRS)

Abedin, M. Nurul; Bradley, Arthur T.; Sharma, Shiv K.; Misra, Anupam K.; Lucey, Paul G.; Mckay, Chistopher P.; Ismail, Syed; Sandford, Stephen P.

2015-01-01

A multispectral instrument based on Raman, laser-induced fluorescence (LIF), laser-induced breakdown spectroscopy (LIBS), and a lidar system provides high-fidelity scientific investigations, scientific input, and science operation constraints in the context of planetary field campaigns with the Jupiter Europa Robotic Lander and Mars Sample Return mission opportunities. This instrument conducts scientific investigations analogous to investigations anticipated for missions to Mars and Jupiter's icy moons. This combined multispectral instrument is capable of performing Raman and fluorescence spectroscopy out to a >100 m target distance from the rover system and provides single-wavelength atmospheric profiling over long ranges (>20 km). In this article, we will reveal integrated remote Raman, LIF, and lidar technologies for use in robotic and lander-based planetary remote sensing applications. Discussions are focused on recently developed Raman, LIF, and lidar systems in addition to emphasizing surface water ice, surface and subsurface minerals, organics, biogenic, biomarker identification, atmospheric aerosols and clouds distributions, i.e., near-field atmospheric thin layers detection for next robotic-lander based instruments to measure all the above-mentioned parameters. OCIS codes: (120.0280) Remote sensing and sensors; (130.0250) Optoelectronics; (280.3640) Lidar; (300.2530) Fluorescence, laser-induced; (300.6450) Spectroscopy, Raman; (300.6365) Spectroscopy, laser induced breakdown

The review of dynamic monitoring technology for crop growth

NASA Astrophysics Data System (ADS)

Zhang, Hong-wei; Chen, Huai-liang; Zou, Chun-hui; Yu, Wei-dong

2010-10-01

In this paper, crop growth monitoring methods are described elaborately. The crop growth models, Netherlands-Wageningen model system, the United States-GOSSYM model and CERES models, Australia APSIM model and CCSODS model system in China, are introduced here more focus on the theories of mechanism, applications, etc. The methods and application of remote sensing monitoring methods, which based on leaf area index (LAI) and biomass were proposed by different scholars at home and abroad, are highly stressed in the paper. The monitoring methods of remote sensing coupling with crop growth models are talked out at large, including the method of "forced law" which using remote sensing retrieval state parameters as the crop growth model parameters input, and then to enhance the dynamic simulation accuracy of crop growth model and the method of "assimilation of Law" which by reducing the gap difference between the value of remote sensing retrieval and the simulated values of crop growth model and thus to estimate the initial value or parameter values to increasing the simulation accuracy. At last, the developing trend of monitoring methods are proposed based on the advantages and shortcomings in previous studies, it is assured that the combination of remote sensing with moderate resolution data of FY-3A, MODIS, etc., crop growth model, "3S" system and observation in situ are the main methods in refinement of dynamic monitoring and quantitative assessment techniques for crop growth in future.

Dialect Distance Assessment Based on 2-Dimensional Pitch Slope Features and Kullback Leibler Divergence

DTIC Science & Technology

2009-04-08

to changes on input data is quantified. It is also shown in a perceptive evaluation that the presented objective approach of dialect distance...of Arabic dialects are discussed. We also show the repeatability of presented mea- sure, and its correlation with human perception . Conclusions are...in the strict sense of metric spaces. PREPRINT 1 2. Proposed Method Human perception tests indicate that prosodic cues, including pitch movements

[The progress in retrieving land surface temperature based on thermal infrared and microwave remote sensing technologies].

PubMed

Zhang, Jia-Hua; Li, Xin; Yao, Feng-Mei; Li, Xian-Hua

2009-08-01

Land surface temperature (LST) is an important parameter in the study on the exchange of substance and energy between land surface and air for the land surface physics process at regional and global scales. Many applications of satellites remotely sensed data must provide exact and quantificational LST, such as drought, high temperature, forest fire, earthquake, hydrology and the vegetation monitor, and the models of global circulation and regional climate also need LST as input parameter. Therefore, the retrieval of LST using remote sensing technology becomes one of the key tasks in quantificational remote sensing study. Normally, in the spectrum bands, the thermal infrared (TIR, 3-15 microm) and microwave bands (1 mm-1 m) are important for retrieval of the LST. In the present paper, firstly, several methods for estimating the LST on the basis of thermal infrared (TIR) remote sensing were synthetically reviewed, i. e., the LST measured with an ground-base infrared thermometer, the LST retrieval from mono-window algorithm (MWA), single-channel algorithm (SCA), split-window techniques (SWT) and multi-channels algorithm(MCA), single-channel & multi-angle algorithm and multi-channels algorithm & multi-angle algorithm, and retrieval method of land surface component temperature using thermal infrared remotely sensed satellite observation. Secondly, the study status of land surface emissivity (epsilon) was presented. Thirdly, in order to retrieve LST for all weather conditions, microwave remotely sensed data, instead of thermal infrared data, have been developed recently, and the LST retrieval method from passive microwave remotely sensed data was also introduced. Finally, the main merits and shortcomings of different kinds of LST retrieval methods were discussed, respectively.

Estimates of Storage Capacity of Multilayer Perceptron with Threshold Logic Hidden Units.

PubMed

Kowalczyk, Adam

1997-11-01

We estimate the storage capacity of multilayer perceptron with n inputs, h(1) threshold logic units in the first hidden layer and 1 output. We show that if the network can memorize 50% of all dichotomies of a randomly selected N-tuple of points of R(n) with probability 1, then N

Operational Remote Sensing Services in North Eastern Region of India for Natural Resources Management, Early Warning for Disaster Risk Reduction and Dissemination of Information and Services

NASA Astrophysics Data System (ADS)

Raju, P. L. N.; Sarma, K. K.; Barman, D.; Handique, B. K.; Chutia, D.; Kundu, S. S.; Das, R. Kr.; Chakraborty, K.; Das, R.; Goswami, J.; Das, P.; Devi, H. S.; Nongkynrih, J. M.; Bhusan, K.; Singh, M. S.; Singh, P. S.; Saikhom, V.; Goswami, C.; Pebam, R.; Borgohain, A.; Gogoi, R. B.; Singh, N. R.; Bharali, A.; Sarma, D.; Lyngdoh, R. B.; Mandal, P. P.; Chabukdhara, M.

2016-06-01

North Eastern Region (NER) of India comprising of eight states considered to be most unique and one of the most challenging regions to govern due to its unique physiographic condition, rich biodiversity, disaster prone and diverse socio-economic characteristics. Operational Remote Sensing services increased manifolds in the region with the establishment of North Eastern Space Applications Centre (NESAC) in the year 2000. Since inception, NESAC has been providing remote sensing services in generating inventory, planning and developmental activities, and management of natural resources, disasters and dissemination of information and services through geo-web services for NER. The operational remote sensing services provided by NESAC can be broadly divided into three categories viz. natural resource planning and developmental services, disaster risk reduction and early warning services and information dissemination through geo-portal services. As a apart of natural resources planning and developmental services NESAC supports the state forest departments in preparing the forest working plans by providing geospatial inputs covering entire NER, identifying the suitable culturable wastelands for cultivation of silkworm food plants, mapping of natural resources such as land use/land cover, wastelands, land degradation etc. on temporal basis. In the area of disaster risk reduction, NESAC has initiated operational services for early warning and post disaster assessment inputs for flood early warning system (FLEWS) using satellite remote sensing, numerical weather prediction, hydrological modeling etc.; forest fire alert system with actionable attribute information; Japanese Encephalitis Early Warning System (JEWS) based on mosquito vector abundance, pig population and historical disease intensity and agriculture drought monitoring for the region. The large volumes of geo-spatial databases generated as part of operational services are made available to the administrators and local government bodies for better management, preparing prospective planning, and sustainable use of available resources. The knowledge dissemination is being done through online web portals wherever the internet access is available and as well as offline space based information kiosks, where the internet access is not available or having limited bandwidth availability. This paper presents a systematic and comprehensive study on the remote sensing services operational in NER of India for natural resources management, disaster risk reduction and dissemination of information and services, in addition to outlining future areas and direction of space applications for the region.

Mechanisms of selective attention and space motion sickness

NASA Technical Reports Server (NTRS)

Kohl, R. L.

1987-01-01

The neural mismatch theory of space motion sickness asserts that the central and peripheral autonomic sequelae of discordant sensory input arise from central integrative processes falling to reconcile patterns of incoming sensory information with existing memory. Stated differently, perceived novelty reaches a stress level as integrative mechanisms fail to return a sense of control to the individual in the new environment. Based on evidence summarized here, the severity of the neural mismatch may be dependent upon the relative amount of attention selectively afforded to each sensory input competing for control of behavior. Components of the limbic system may play important roles in match-mismatch operations, be therapeutically modulated by antimotion sickness drugs, and be optimally positioned to control autonomic output.

Optimal Guaranteed Cost Sliding Mode Control for Constrained-Input Nonlinear Systems With Matched and Unmatched Disturbances.

PubMed

Zhang, Huaguang; Qu, Qiuxia; Xiao, Geyang; Cui, Yang

2018-06-01

Based on integral sliding mode and approximate dynamic programming (ADP) theory, a novel optimal guaranteed cost sliding mode control is designed for constrained-input nonlinear systems with matched and unmatched disturbances. When the system moves on the sliding surface, the optimal guaranteed cost control problem of sliding mode dynamics is transformed into the optimal control problem of a reformulated auxiliary system with a modified cost function. The ADP algorithm based on single critic neural network (NN) is applied to obtain the approximate optimal control law for the auxiliary system. Lyapunov techniques are used to demonstrate the convergence of the NN weight errors. In addition, the derived approximate optimal control is verified to guarantee the sliding mode dynamics system to be stable in the sense of uniform ultimate boundedness. Some simulation results are presented to verify the feasibility of the proposed control scheme.

Smart Sensing Based on DNA-Metal Interaction Enables a Label-Free and Resettable Security Model of Electrochemical Molecular Keypad Lock.

PubMed

Du, Yan; Han, Xu; Wang, Chenxu; Li, Yunhui; Li, Bingling; Duan, Hongwei

2018-01-26

Recently, molecular keypad locks have received increasing attention. As a new subgroup of smart biosensors, they show great potential for protecting information as a molecular security data processor, rather than merely molecular recognition and quantitation. Herein, label-free electrochemically transduced Ag + and cysteine (Cys) sensors were developed. A molecular keypad lock model with reset function was successfully realized based on the balanced interaction of metal ion with its nucleic acid and chemical ligands. The correct input of "1-2-3" (i.e., "Ag + -Cys-cDNA") is the only password of such molecular keypad lock. Moreover, the resetting process of either correct or wrong input order could be easily made by Cys, buffer, and DI water treatment. Therefore, our system provides an even smarter system of molecular keypad lock, which could inhibit illegal access of unauthorized users, holding great promise in information protection at the molecular level.

Distributed Adaptive Neural Network Output Tracking of Leader-Following High-Order Stochastic Nonlinear Multiagent Systems With Unknown Dead-Zone Input.

PubMed

Hua, Changchun; Zhang, Liuliu; Guan, Xinping

2017-01-01

This paper studies the problem of distributed output tracking consensus control for a class of high-order stochastic nonlinear multiagent systems with unknown nonlinear dead-zone under a directed graph topology. The adaptive neural networks are used to approximate the unknown nonlinear functions and a new inequality is used to deal with the completely unknown dead-zone input. Then, we design the controllers based on backstepping method and the dynamic surface control technique. It is strictly proved that the resulting closed-loop system is stable in probability in the sense of semiglobally uniform ultimate boundedness and the tracking errors between the leader and the followers approach to a small residual set based on Lyapunov stability theory. Finally, two simulation examples are presented to show the effectiveness and the advantages of the proposed techniques.

Reading as Active Sensing: A Computational Model of Gaze Planning in Word Recognition

PubMed Central

Ferro, Marcello; Ognibene, Dimitri; Pezzulo, Giovanni; Pirrelli, Vito

2010-01-01

We offer a computational model of gaze planning during reading that consists of two main components: a lexical representation network, acquiring lexical representations from input texts (a subset of the Italian CHILDES database), and a gaze planner, designed to recognize written words by mapping strings of characters onto lexical representations. The model implements an active sensing strategy that selects which characters of the input string are to be fixated, depending on the predictions dynamically made by the lexical representation network. We analyze the developmental trajectory of the system in performing the word recognition task as a function of both increasing lexical competence, and correspondingly increasing lexical prediction ability. We conclude by discussing how our approach can be scaled up in the context of an active sensing strategy applied to a robotic setting. PMID:20577589

Reading as active sensing: a computational model of gaze planning in word recognition.

PubMed

Ferro, Marcello; Ognibene, Dimitri; Pezzulo, Giovanni; Pirrelli, Vito

2010-01-01

WE OFFER A COMPUTATIONAL MODEL OF GAZE PLANNING DURING READING THAT CONSISTS OF TWO MAIN COMPONENTS: a lexical representation network, acquiring lexical representations from input texts (a subset of the Italian CHILDES database), and a gaze planner, designed to recognize written words by mapping strings of characters onto lexical representations. The model implements an active sensing strategy that selects which characters of the input string are to be fixated, depending on the predictions dynamically made by the lexical representation network. We analyze the developmental trajectory of the system in performing the word recognition task as a function of both increasing lexical competence, and correspondingly increasing lexical prediction ability. We conclude by discussing how our approach can be scaled up in the context of an active sensing strategy applied to a robotic setting.

A three-step reconstruction method for fluorescence molecular tomography based on compressive sensing

NASA Astrophysics Data System (ADS)

Zhu, Yansong; Jha, Abhinav K.; Dreyer, Jakob K.; Le, Hanh N. D.; Kang, Jin U.; Roland, Per E.; Wong, Dean F.; Rahmim, Arman

2017-02-01

Fluorescence molecular tomography (FMT) is a promising tool for real time in vivo quantification of neurotransmission (NT) as we pursue in our BRAIN initiative effort. However, the acquired image data are noisy and the reconstruction problem is ill-posed. Further, while spatial sparsity of the NT effects could be exploited, traditional compressive-sensing methods cannot be directly applied as the system matrix in FMT is highly coherent. To overcome these issues, we propose and assess a three-step reconstruction method. First, truncated singular value decomposition is applied on the data to reduce matrix coherence. The resultant image data are input to a homotopy-based reconstruction strategy that exploits sparsity via l1 regularization. The reconstructed image is then input to a maximum-likelihood expectation maximization (MLEM) algorithm that retains the sparseness of the input estimate and improves upon the quantitation by accurate Poisson noise modeling. The proposed reconstruction method was evaluated in a three-dimensional simulated setup with fluorescent sources in a cuboidal scattering medium with optical properties simulating human brain cortex (reduced scattering coefficient: 9.2 cm-1, absorption coefficient: 0.1 cm-1 and tomographic measurements made using pixelated detectors. In different experiments, fluorescent sources of varying size and intensity were simulated. The proposed reconstruction method provided accurate estimates of the fluorescent source intensity, with a 20% lower root mean square error on average compared to the pure-homotopy method for all considered source intensities and sizes. Further, compared with conventional l2 regularized algorithm, overall, the proposed method reconstructed substantially more accurate fluorescence distribution. The proposed method shows considerable promise and will be tested using more realistic simulations and experimental setups.

Constant Switching Frequency DTC for Matrix Converter Fed Speed Sensorless Induction Motor Drive

NASA Astrophysics Data System (ADS)

Mir, Tabish Nazir; Singh, Bhim; Bhat, Abdul Hamid

2018-05-01

The paper presents a constant switching frequency scheme for speed sensorless Direct Torque Control (DTC) of Matrix Converter fed Induction Motor Drive. The use of matrix converter facilitates improved power quality on input as well as motor side, along with Input Power Factor control, besides eliminating the need for heavy passive elements. Moreover, DTC through Space Vector Modulation helps in achieving a fast control over the torque and flux of the motor, with added benefit of constant switching frequency. A constant switching frequency aids in maintaining desired power quality of AC mains current even at low motor speeds, and simplifies input filter design of the matrix converter, as compared to conventional hysteresis based DTC. Further, stator voltage estimation from sensed input voltage, and subsequent stator (and rotor) flux estimation is done. For speed sensorless operation, a Model Reference Adaptive System is used, which emulates the speed dependent rotor flux equations of the induction motor. The error between conventionally estimated rotor flux (reference model) and the rotor flux estimated through the adaptive observer is processed through PI controller to generate the rotor speed estimate.

The intercrater plains of Mercury and the Moon: Their nature, origin and role in terrestrial planet evolution. Remote sensing and physical data and the Moon. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Leake, M. A.

1982-01-01

Imagery data from Mariner 10 and Lunar Orbiter IV form the major base of observations analyzed. But a variety of other information aids in constraining the composition and structure of the Moon and Mercury, and in particular, provides input to the problem of the nature and origin of their intercrater plains. This information for Mercury is remotely sensed from Earth or from the Mariner 10 spacecraft. Lunar data includes, of course, ground truth information from the Apollo landing sites. Since neither intercrater region was sampled, lunar and Mercurian data are similar in type and limitations. Constraints on surface and interior composition and structure are reviewed.

Remote sensing inputs to National Model Implementation Program for water resources quality improvement

NASA Technical Reports Server (NTRS)

Eidenshink, J. C.; Schmer, F. A.

1979-01-01

The Lake Herman watershed in southeastern South Dakota has been selected as one of seven water resources systems in the United States for involvement in the National Model Implementation Program (MIP). MIP is a pilot program initiated to illustrate the effectiveness of existing water resources quality improvement programs. The Remote Sensing Institute (RSI) at South Dakota State University has produced a computerized geographic information system for the Lake Herman watershed. All components necessary for the monitoring and evaluation process were included in the data base. The computerized data were used to produce thematic maps and tabular data for the land cover and soil classes within the watershed. These data are being utilized operationally by SCS resource personnel for planning and management purposes.

Multichannel optical sensing device

DOEpatents

Selkowitz, S.E.

1985-08-16

A multichannel optical sensing device is disclosed, for measuring the outdoor sky luminance or illuminance or the luminance or illuminance distribution in a room, comprising a plurality of light receptors, an optical shutter matrix including a plurality of liquid crystal optical shutter elements operable by electrical control signals between light transmitting and light stopping conditions, fiber optical elements connected between the receptors and the shutter elements, a microprocessor based programmable control unit for selectively supplying control signals to the optical shutter elements in a programmable sequence, a photodetector including an optical integrating spherical chamber having an input port for receiving the light from the shutter matrix and at least one detector element in the spherical chamber for producing output signals corresponding to the light, and output units for utilizing the output signals including a storage unit having a control connection to the microprocessor based programmable control unit for storing the output signals under the sequence control of the programmable control unit.

Multichannel optical sensing device

DOEpatents

Selkowitz, Stephen E.

1990-01-01

A multichannel optical sensing device is disclosed, for measuring the outr sky luminance or illuminance or the luminance or illuminance distribution in a room, comprising a plurality of light receptors, an optical shutter matrix including a plurality of liquid crystal optical shutter elements operable by electrical control signals between light transmitting and light stopping conditions, fiber optic elements connected between the receptors and the shutter elements, a microprocessor based programmable control unit for selectively supplying control signals to the optical shutter elements in a programmable sequence, a photodetector including an optical integrating spherical chamber having an input port for receiving the light from the shutter matrix and at least one detector element in the spherical chamber for producing output signals corresponding to the light, and output units for utilizing the output signals including a storage unit having a control connection to the microprocessor based programmable control unit for storing the output signals under the sequence control of the programmable control unit.

A modular cell-based biosensor using engineered genetic logic circuits to detect and integrate multiple environmental signals

PubMed Central

Wang, Baojun; Barahona, Mauricio; Buck, Martin

2013-01-01

Cells perceive a wide variety of cellular and environmental signals, which are often processed combinatorially to generate particular phenotypic responses. Here, we employ both single and mixed cell type populations, pre-programmed with engineered modular cell signalling and sensing circuits, as processing units to detect and integrate multiple environmental signals. Based on an engineered modular genetic AND logic gate, we report the construction of a set of scalable synthetic microbe-based biosensors comprising exchangeable sensory, signal processing and actuation modules. These cellular biosensors were engineered using distinct signalling sensory modules to precisely identify various chemical signals, and combinations thereof, with a quantitative fluorescent output. The genetic logic gate used can function as a biological filter and an amplifier to enhance the sensing selectivity and sensitivity of cell-based biosensors. In particular, an Escherichia coli consortium-based biosensor has been constructed that can detect and integrate three environmental signals (arsenic, mercury and copper ion levels) via either its native two-component signal transduction pathways or synthetic signalling sensors derived from other bacteria in combination with a cell-cell communication module. We demonstrate how a modular cell-based biosensor can be engineered predictably using exchangeable synthetic gene circuit modules to sense and integrate multiple-input signals. This study illustrates some of the key practical design principles required for the future application of these biosensors in broad environmental and healthcare areas. PMID:22981411

Compressive Sensing with Cross-Validation and Stop-Sampling for Sparse Polynomial Chaos Expansions

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

Huan, Xun; Safta, Cosmin; Sargsyan, Khachik

Compressive sensing is a powerful technique for recovering sparse solutions of underdetermined linear systems, which is often encountered in uncertainty quanti cation analysis of expensive and high-dimensional physical models. We perform numerical investigations employing several com- pressive sensing solvers that target the unconstrained LASSO formulation, with a focus on linear systems that arise in the construction of polynomial chaos expansions. With core solvers of l1 ls, SpaRSA, CGIST, FPC AS, and ADMM, we develop techniques to mitigate over tting through an automated selection of regularization constant based on cross-validation, and a heuristic strategy to guide the stop-sampling decision. Practical recommendationsmore » on parameter settings for these tech- niques are provided and discussed. The overall method is applied to a series of numerical examples of increasing complexity, including large eddy simulations of supersonic turbulent jet-in-cross flow involving a 24-dimensional input. Through empirical phase-transition diagrams and convergence plots, we illustrate sparse recovery performance under structures induced by polynomial chaos, accuracy and computational tradeoffs between polynomial bases of different degrees, and practi- cability of conducting compressive sensing for a realistic, high-dimensional physical application. Across test cases studied in this paper, we find ADMM to have demonstrated empirical advantages through consistent lower errors and faster computational times.« less

Measurand transient signal suppressor

NASA Technical Reports Server (NTRS)

Bozeman, Richard J., Jr. (Inventor)

1994-01-01

A transient signal suppressor for use in a controls system which is adapted to respond to a change in a physical parameter whenever it crosses a predetermined threshold value in a selected direction of increasing or decreasing values with respect to the threshold value and is sustained for a selected discrete time interval is presented. The suppressor includes a sensor transducer for sensing the physical parameter and generating an electrical input signal whenever the sensed physical parameter crosses the threshold level in the selected direction. A manually operated switch is provided for adapting the suppressor to produce an output drive signal whenever the physical parameter crosses the threshold value in the selected direction of increasing or decreasing values. A time delay circuit is selectively adjustable for suppressing the transducer input signal for a preselected one of a plurality of available discrete suppression time and producing an output signal only if the input signal is sustained for a time greater than the selected suppression time. An electronic gate is coupled to receive the transducer input signal and the timer output signal and produce an output drive signal for energizing a control relay whenever the transducer input is a non-transient signal which is sustained beyond the selected time interval.

Sensing the gas metal arc welding process

NASA Technical Reports Server (NTRS)

Carlson, N. M.; Johnson, J. A.; Smartt, H. B.; Watkins, A. D.; Larsen, E. D.; Taylor, P. L.; Waddoups, M. A.

1994-01-01

Control of gas metal arc welding (GMAW) requires real-time sensing of the process. Three sensing techniques for GMAW are being developed at the Idaho National Engineering Laboratory (INEL). These are (1) noncontacting ultrasonic sensing using a laser/EMAT (electromagnetic acoustic transducer) to detect defects in the solidified weld on a pass-by-pass basis, (2) integrated optical sensing using a CCD camera and a laser stripe to obtain cooling rate and weld bead geometry information, and (3) monitoring fluctuations in digitized welding voltage data to detect the mode of metal droplet transfer and assure that the desired mass input is achieved.

Sensing the gas metal arc welding process

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

Carlson, N.M.; Johnson, J.A.; Smartt, H.B.

1992-01-01

Control of gas metal arc welding (GMAW) requires real-time sensing of the process. Three sensing techniques for GMAW are being developed at the Idaho National Engineering Laboratory (INEL). These are (1) noncontacting ultrasonic sensing using a laser/EMAT (electromagnetic acoustic transducer) to detect defects in the solidified weld on a pass-bypass basis, (2) integrated optical sensing using a CCD camera and a laser stripe to obtain cooling rate and weld bead geometry information, and (3) monitoring fluctuations in digitized welding voltage data to detect the mode of metal droplet transfer and assure that the desired mass input is achieved.

Sensing the gas metal arc welding process

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

Carlson, N.M.; Johnson, J.A.; Smartt, H.B.

1992-10-01

Control of gas metal arc welding (GMAW) requires real-time sensing of the process. Three sensing techniques for GMAW are being developed at the Idaho National Engineering Laboratory (INEL). These are (1) noncontacting ultrasonic sensing using a laser/EMAT (electromagnetic acoustic transducer) to detect defects in the solidified weld on a pass-bypass basis, (2) integrated optical sensing using a CCD camera and a laser stripe to obtain cooling rate and weld bead geometry information, and (3) monitoring fluctuations in digitized welding voltage data to detect the mode of metal droplet transfer and assure that the desired mass input is achieved.

A Neural Network-Based Gait Phase Classification Method Using Sensors Equipped on Lower Limb Exoskeleton Robots

PubMed Central

Jung, Jun-Young; Heo, Wonho; Yang, Hyundae; Park, Hyunsub

2015-01-01

An exact classification of different gait phases is essential to enable the control of exoskeleton robots and detect the intentions of users. We propose a gait phase classification method based on neural networks using sensor signals from lower limb exoskeleton robots. In such robots, foot sensors with force sensing registers are commonly used to classify gait phases. We describe classifiers that use the orientation of each lower limb segment and the angular velocities of the joints to output the current gait phase. Experiments to obtain the input signals and desired outputs for the learning and validation process are conducted, and two neural network methods (a multilayer perceptron and nonlinear autoregressive with external inputs (NARX)) are used to develop an optimal classifier. Offline and online evaluations using four criteria are used to compare the performance of the classifiers. The proposed NARX-based method exhibits sufficiently good performance to replace foot sensors as a means of classifying gait phases. PMID:26528986

A Neural Network-Based Gait Phase Classification Method Using Sensors Equipped on Lower Limb Exoskeleton Robots.

PubMed

Jung, Jun-Young; Heo, Wonho; Yang, Hyundae; Park, Hyunsub

2015-10-30

An exact classification of different gait phases is essential to enable the control of exoskeleton robots and detect the intentions of users. We propose a gait phase classification method based on neural networks using sensor signals from lower limb exoskeleton robots. In such robots, foot sensors with force sensing registers are commonly used to classify gait phases. We describe classifiers that use the orientation of each lower limb segment and the angular velocities of the joints to output the current gait phase. Experiments to obtain the input signals and desired outputs for the learning and validation process are conducted, and two neural network methods (a multilayer perceptron and nonlinear autoregressive with external inputs (NARX)) are used to develop an optimal classifier. Offline and online evaluations using four criteria are used to compare the performance of the classifiers. The proposed NARX-based method exhibits sufficiently good performance to replace foot sensors as a means of classifying gait phases.

Development of a portable electrical impedance tomography data acquisition system for near-real-time spatial sensing

NASA Astrophysics Data System (ADS)

Huang, Shieh-Kung; Loh, Kenneth J.

2015-04-01

The main goal of this study was to develop and validate the performance of a miniature and portable data acquisition (DAQ) system designed for interrogating carbon nanotube (CNT)-based thin films for real-time spatial structural sensing and damage detection. Previous research demonstrated that the electrical properties of CNT-based thin film strain sensors were linearly correlated with applied strains. When coupled with an electrical impedance tomography (EIT) algorithm, the detection and localization of damage was possible. In short, EIT required that the film or "sensing skin" be interrogated along its boundaries. Electrical current was injected across a pair of boundary electrodes, and voltage was simultaneously recorded along the remaining electrode pairs. This was performed multiple times to obtain a large dataset needed for solving the EIT spatial conductivity mapping inverse problem. However, one of the main limitations of this technique was the large amount of time required for data acquisition. In order to facilitate the adoption of this technology and for field implementation purposes, a miniature DAQ that could interrogate these CNT-based sensing skins at high sampling rates was designed and tested. The prototype DAQ featured a Howland current source that could generate stable and controlled direct current. Measurement of boundary electrode voltages and the switching of the input, output, and measurement channels were achieved using multiplexer units. The DAQ prototype was fabricated on a two-layer printed circuit board, and it was designed for integration with a prototype wireless sensing system, which is the next phase of this research.

A tool for NDVI time series extraction from wide-swath remotely sensed images

NASA Astrophysics Data System (ADS)

Li, Zhishan; Shi, Runhe; Zhou, Cong

2015-09-01

Normalized Difference Vegetation Index (NDVI) is one of the most widely used indicators for monitoring the vegetation coverage in land surface. The time series features of NDVI are capable of reflecting dynamic changes of various ecosystems. Calculating NDVI via Moderate Resolution Imaging Spectrometer (MODIS) and other wide-swath remotely sensed images provides an important way to monitor the spatial and temporal characteristics of large-scale NDVI. However, difficulties are still existed for ecologists to extract such information correctly and efficiently because of the problems in several professional processes on the original remote sensing images including radiometric calibration, geometric correction, multiple data composition and curve smoothing. In this study, we developed an efficient and convenient online toolbox for non-remote sensing professionals who want to extract NDVI time series with a friendly graphic user interface. It is based on Java Web and Web GIS technically. Moreover, Struts, Spring and Hibernate frameworks (SSH) are integrated in the system for the purpose of easy maintenance and expansion. Latitude, longitude and time period are the key inputs that users need to provide, and the NDVI time series are calculated automatically.

Frequency Agile Lidar Receiver for Chem-Bio Sensing

DTIC Science & Technology

2010-06-01

receiver module design is based on the following key attributes: 1) The use of an inexpensive COTS PV MCT , 2) A custom detector amplifier with ultra low...input-referenced noise density of 0.8 nV/ Hz0.5 that is carefully matched to the electrical properties of the detector and temporal characteristics of...LIDAR transmitter. The low- noise amplifier matched to the receiver detector was developed in order to realize the BLIP noise reduction resulting from

Engineering dynamical control of cell fate switching using synthetic phospho-regulons

PubMed Central

Gordley, Russell M.; Williams, Reid E.; Bashor, Caleb J.; Toettcher, Jared E.; Yan, Shude; Lim, Wendell A.

2016-01-01

Many cells can sense and respond to time-varying stimuli, selectively triggering changes in cell fate only in response to inputs of a particular duration or frequency. A common motif in dynamically controlled cells is a dual-timescale regulatory network: although long-term fate decisions are ultimately controlled by a slow-timescale switch (e.g., gene expression), input signals are first processed by a fast-timescale signaling layer, which is hypothesized to filter what dynamic information is efficiently relayed downstream. Directly testing the design principles of how dual-timescale circuits control dynamic sensing, however, has been challenging, because most synthetic biology methods have focused solely on rewiring transcriptional circuits, which operate at a single slow timescale. Here, we report the development of a modular approach for flexibly engineering phosphorylation circuits using designed phospho-regulon motifs. By then linking rapid phospho-feedback with slower downstream transcription-based bistable switches, we can construct synthetic dual-timescale circuits in yeast in which the triggering dynamics and the end-state properties of the ON state can be selectively tuned. These phospho-regulon tools thus open up the possibility to engineer cells with customized dynamical control. PMID:27821768

Implementation of a Wavefront-Sensing Algorithm

NASA Technical Reports Server (NTRS)

Smith, Jeffrey S.; Dean, Bruce; Aronstein, David

2013-01-01

A computer program has been written as a unique implementation of an image-based wavefront-sensing algorithm reported in "Iterative-Transform Phase Retrieval Using Adaptive Diversity" (GSC-14879-1), NASA Tech Briefs, Vol. 31, No. 4 (April 2007), page 32. This software was originally intended for application to the James Webb Space Telescope, but is also applicable to other segmented-mirror telescopes. The software is capable of determining optical-wavefront information using, as input, a variable number of irradiance measurements collected in defocus planes about the best focal position. The software also uses input of the geometrical definition of the telescope exit pupil (otherwise denoted the pupil mask) to identify the locations of the segments of the primary telescope mirror. From the irradiance data and mask information, the software calculates an estimate of the optical wavefront (a measure of performance) of the telescope generally and across each primary mirror segment specifically. The software is capable of generating irradiance data, wavefront estimates, and basis functions for the full telescope and for each primary-mirror segment. Optionally, each of these pieces of information can be measured or computed outside of the software and incorporated during execution of the software.

Modeling Common-Sense Decisions in Artificial Intelligence

NASA Technical Reports Server (NTRS)

Zak, Michail

2010-01-01

A methodology has been conceived for efficient synthesis of dynamical models that simulate common-sense decision- making processes. This methodology is intended to contribute to the design of artificial-intelligence systems that could imitate human common-sense decision making or assist humans in making correct decisions in unanticipated circumstances. This methodology is a product of continuing research on mathematical models of the behaviors of single- and multi-agent systems known in biology, economics, and sociology, ranging from a single-cell organism at one extreme to the whole of human society at the other extreme. Earlier results of this research were reported in several prior NASA Tech Briefs articles, the three most recent and relevant being Characteristics of Dynamics of Intelligent Systems (NPO -21037), NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 48; Self-Supervised Dynamical Systems (NPO-30634), NASA Tech Briefs, Vol. 27, No. 3 (March 2003), page 72; and Complexity for Survival of Living Systems (NPO- 43302), NASA Tech Briefs, Vol. 33, No. 7 (July 2009), page 62. The methodology involves the concepts reported previously, albeit viewed from a different perspective. One of the main underlying ideas is to extend the application of physical first principles to the behaviors of living systems. Models of motor dynamics are used to simulate the observable behaviors of systems or objects of interest, and models of mental dynamics are used to represent the evolution of the corresponding knowledge bases. For a given system, the knowledge base is modeled in the form of probability distributions and the mental dynamics is represented by models of the evolution of the probability densities or, equivalently, models of flows of information. Autonomy is imparted to the decisionmaking process by feedback from mental to motor dynamics. This feedback replaces unavailable external information by information stored in the internal knowledge base. Representation of the dynamical models in a parameterized form reduces the task of common-sense-based decision making to a solution of the following hetero-associated-memory problem: store a set of m predetermined stochastic processes given by their probability distributions in such a way that when presented with an unexpected change in the form of an input out of the set of M inputs, the coupled motormental dynamics converges to the corresponding one of the m pre-assigned stochastic process, and a sample of this process represents the decision.

Development of a Global Evaporative Stress Index Based on Thermal and Microwave LST towards Improved Monitoring of Agricultural Drought

NASA Astrophysics Data System (ADS)

Hain, C.; Anderson, M. C.; Otkin, J.; Holmes, T. R.; Gao, F.

2017-12-01

This presentation will describe the development of a global agricultural monitoring tool, with a focus on providing early warning of developing vegetation stress for agricultural decision-makers and stakeholders at relatively high spatial resolution (5-km). The tool is based on remotely sensed estimates of evapotranspiration, retrieved via energy balance principals using observations of land surface temperature. The Evaporative Stress Index (ESI) represents anomalies in the ratio of actual-to-potential ET generated with the ALEXI surface energy balance model. The LST inputs to ESI have been shown to provide early warning information about the development of vegetation stress with stress-elevated canopy temperatures observed well before a decrease in greenness is detected in remotely sensed vegetation indices. As a diagnostic indicator of actual ET, the ESI requires no information regarding antecedent precipitation or soil moisture storage capacity - the current available moisture to vegetation is deduced directly from the remotely sensed LST signal. This signal also inherently accounts for both precipitation and non-precipitation related inputs/sinks to the plant-available soil moisture pool (e.g., irrigation) which can modify crop response to rainfall anomalies. Independence from precipitation data is a benefit for global agricultural monitoring applications due to sparseness in existing ground-based precipitation networks, and time delays in public reporting. Several enhancements to the current ESI framework will be addressed as requested from project stakeholders: (a) integration of "all-sky" MW Ka-band LST retrievals to augment "clear-sky" thermal-only ESI in persistently cloudy regions; (b) operational production of ESI Rapid Change Indices which provide important early warning information related to onset of actual vegetation stress; and (c) assessment of ESI as a predictor of global yield anomalies; initial studies have shown the ability of intra-seasonal ESI to provide an early indication of at-harvest agricultural yield anomalies.

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.

A novel cyanide-selective colorimetric and fluorescent chemosensor: first molecular security keypad lock based on phosphotungstic acid and CN- inputs.

PubMed

Tavallali, Hossein; Deilamy-Rad, Gohar; Parhami, Abolfath; Hasanli, Nahid

2014-02-15

Rhodamine B (RhB) an available dye has been developed as novel and efficient colorimetric and fluorometric chemosensor for cyanide ions in an absolutely aqueous media. The UV-vis absorption and fluorescent emission titrations experiments have been employed to study the sensing process. RhB could act as an efficient "ON-OFF" fluorescent response for phosphotungstic acid (H3PW12O40 or PTA) based on an ion associate process. Also (RhB(+))3 · PTA(3-) could operate as an "OFF-ON" fluorescent sensor for cyanide anions based on a ligand substitution process. It has been identified as highly sensitive probe for CN(-) which responds at 0.3 and 0.04 μmol L(-1) concentration levels by absorption and fluorescent method respectively. Depending upon the sequence of addition of PTA and CN(-) ions into the solution, RhB could be as a molecular security keypad lock with PTA and CN(-) inputs. The ionic inputs to new fluorophore have been mimicked as a superimposed electronic molecular keypad lock. The results were compared successfully (>96%) with the data of a spectrophotometry approved method (EPA 9014-1) for cyanide ions. Copyright © 2013 Elsevier B.V. All rights reserved.

Estimation of Spatiotemporal Sensitivity Using Band-limited Signals with No Additional Acquisitions for k-t Parallel Imaging.

PubMed

Takeshima, Hidenori; Saitoh, Kanako; Nitta, Shuhei; Shiodera, Taichiro; Takeguchi, Tomoyuki; Bannae, Shuhei; Kuhara, Shigehide

2018-03-13

Dynamic MR techniques, such as cardiac cine imaging, benefit from shorter acquisition times. The goal of the present study was to develop a method that achieves short acquisition times, while maintaining a cost-effective reconstruction, for dynamic MRI. k - t sensitivity encoding (SENSE) was identified as the base method to be enhanced meeting these two requirements. The proposed method achieves a reduction in acquisition time by estimating the spatiotemporal (x - f) sensitivity without requiring the acquisition of the alias-free signals, typical of the k - t SENSE technique. The cost-effective reconstruction, in turn, is achieved by a computationally efficient estimation of the x - f sensitivity from the band-limited signals of the aliased inputs. Such band-limited signals are suitable for sensitivity estimation because the strongly aliased signals have been removed. For the same reduction factor 4, the net reduction factor 4 for the proposed method was significantly higher than the factor 2.29 achieved by k - t SENSE. The processing time is reduced from 4.1 s for k - t SENSE to 1.7 s for the proposed method. The image quality obtained using the proposed method proved to be superior (mean squared error [MSE] ± standard deviation [SD] = 6.85 ± 2.73) compared to the k - t SENSE case (MSE ± SD = 12.73 ± 3.60) for the vertical long-axis (VLA) view, as well as other views. In the present study, k - t SENSE was identified as a suitable base method to be improved achieving both short acquisition times and a cost-effective reconstruction. To enhance these characteristics of base method, a novel implementation is proposed, estimating the x - f sensitivity without the need for an explicit scan of the reference signals. Experimental results showed that the acquisition, computational times and image quality for the proposed method were improved compared to the standard k - t SENSE method.

A Multi-Stage Method for Connecting Participatory Sensing and Noise Simulations

PubMed Central

Hu, Mingyuan; Che, Weitao; Zhang, Qiuju; Luo, Qingli; Lin, Hui

2015-01-01

Most simulation-based noise maps are important for official noise assessment but lack local noise characteristics. The main reasons for this lack of information are that official noise simulations only provide information about expected noise levels, which is limited by the use of large-scale monitoring of noise sources, and are updated infrequently. With the emergence of smart cities and ubiquitous sensing, the possible improvements enabled by sensing technologies provide the possibility to resolve this problem. This study proposed an integrated methodology to propel participatory sensing from its current random and distributed sampling origins to professional noise simulation. The aims of this study were to effectively organize the participatory noise data, to dynamically refine the granularity of the noise features on road segments (e.g., different portions of a road segment), and then to provide a reasonable spatio-temporal data foundation to support noise simulations, which can be of help to researchers in understanding how participatory sensing can play a role in smart cities. This study first discusses the potential limitations of the current participatory sensing and simulation-based official noise maps. Next, we explain how participatory noise data can contribute to a simulation-based noise map by providing (1) spatial matching of the participatory noise data to the virtual partitions at a more microscopic level of road networks; (2) multi-temporal scale noise estimations at the spatial level of virtual partitions; and (3) dynamic aggregation of virtual partitions by comparing the noise values at the relevant temporal scale to form a dynamic segmentation of each road segment to support multiple spatio-temporal noise simulations. In this case study, we demonstrate how this method could play a significant role in a simulation-based noise map. Together, these results demonstrate the potential benefits of participatory noise data as dynamic input sources for noise simulations on multiple spatio-temporal scales. PMID:25621604

A multi-stage method for connecting participatory sensing and noise simulations.

PubMed

Hu, Mingyuan; Che, Weitao; Zhang, Qiuju; Luo, Qingli; Lin, Hui

2015-01-22

Most simulation-based noise maps are important for official noise assessment but lack local noise characteristics. The main reasons for this lack of information are that official noise simulations only provide information about expected noise levels, which is limited by the use of large-scale monitoring of noise sources, and are updated infrequently. With the emergence of smart cities and ubiquitous sensing, the possible improvements enabled by sensing technologies provide the possibility to resolve this problem. This study proposed an integrated methodology to propel participatory sensing from its current random and distributed sampling origins to professional noise simulation. The aims of this study were to effectively organize the participatory noise data, to dynamically refine the granularity of the noise features on road segments (e.g., different portions of a road segment), and then to provide a reasonable spatio-temporal data foundation to support noise simulations, which can be of help to researchers in understanding how participatory sensing can play a role in smart cities. This study first discusses the potential limitations of the current participatory sensing and simulation-based official noise maps. Next, we explain how participatory noise data can contribute to a simulation-based noise map by providing (1) spatial matching of the participatory noise data to the virtual partitions at a more microscopic level of road networks; (2) multi-temporal scale noise estimations at the spatial level of virtual partitions; and (3) dynamic aggregation of virtual partitions by comparing the noise values at the relevant temporal scale to form a dynamic segmentation of each road segment to support multiple spatio-temporal noise simulations. In this case study, we demonstrate how this method could play a significant role in a simulation-based noise map. Together, these results demonstrate the potential benefits of participatory noise data as dynamic input sources for noise simulations on multiple spatio-temporal scales.

Assimilating Leaf Area Index Estimates from Remote Sensing into the Simulations of a Cropping Systems Model

USDA-ARS?s Scientific Manuscript database

Spatial extrapolation of cropping systems models for regional crop growth and water use assessment and farm-level precision management has been limited by the vast model input requirements and the model sensitivity to parameter uncertainty. Remote sensing has been proposed as a viable source of spat...

Carving up Word Meaning: Portioning and Grinding

ERIC Educational Resources Information Center

Frisson, S.; Frazier, L.

2005-01-01

Two eye-tracking experiments investigated the processing of mass nouns used as count nouns and count nouns used as mass nouns. Following Copestake and Briscoe (1995), the basic or underived sense of a word was treated as the input to a derivational rule (''grinding'' or ''portioning'') which produced the derived sense as output. It was…

A High Performance LIA-Based Interface for Battery Powered Sensing Devices

PubMed Central

García-Romeo, Daniel; Valero, María R.; Medrano, Nicolás; Calvo, Belén; Celma, Santiago

2015-01-01

This paper proposes a battery-compatible electronic interface based on a general purpose lock-in amplifier (LIA) capable of recovering input signals up to the MHz range. The core is a novel ASIC fabricated in 1.8 V 0.18 µm CMOS technology, which contains a dual-phase analog lock-in amplifier consisting of carefully designed building blocks to allow configurability over a wide frequency range while maintaining low power consumption. It operates using square input signals. Hence, for battery-operated microcontrolled systems, where square reference and exciting signals can be generated by the embedded microcontroller, the system benefits from intrinsic advantages such as simplicity, versatility and reduction in power and size. Experimental results confirm the signal recovery capability with signal-to-noise power ratios down to −39 dB with relative errors below 0.07% up to 1 MHz. Furthermore, the system has been successfully tested measuring the response of a microcantilever-based resonant sensor, achieving similar results with better power-bandwidth trade-off compared to other LIAs based on commercial off-the-shelf (COTS) components and commercial LIA equipment. PMID:26437408

A High Performance LIA-Based Interface for Battery Powered Sensing Devices.

PubMed

García-Romeo, Daniel; Valero, María R; Medrano, Nicolás; Calvo, Belén; Celma, Santiago

2015-09-30

This paper proposes a battery-compatible electronic interface based on a general purpose lock-in amplifier (LIA) capable of recovering input signals up to the MHz range. The core is a novel ASIC fabricated in 1.8 V 0.18 µm CMOS technology, which contains a dual-phase analog lock-in amplifier consisting of carefully designed building blocks to allow configurability over a wide frequency range while maintaining low power consumption. It operates using square input signals. Hence, for battery-operated microcontrolled systems, where square reference and exciting signals can be generated by the embedded microcontroller, the system benefits from intrinsic advantages such as simplicity, versatility and reduction in power and size. Experimental results confirm the signal recovery capability with signal-to-noise power ratios down to -39 dB with relative errors below 0.07% up to 1 MHz. Furthermore, the system has been successfully tested measuring the response of a microcantilever-based resonant sensor, achieving similar results with better power-bandwidth trade-off compared to other LIAs based on commercial off-the-shelf (COTS) components and commercial LIA equipment.

Crop status evaluations and yield predictions

NASA Technical Reports Server (NTRS)

Haun, J. R.

1976-01-01

One phase of the large area crop inventory project is presented. Wheat yield models based on the input of environmental variables potentially obtainable through the use of space remote sensing were developed and demonstrated. By the use of a unique method for visually qualifying daily plant development and subsequent multifactor computer analyses, it was possible to develop practical models for predicting crop development and yield. Development of wheat yield prediction models was based on the discovery that morphological changes in plants are detected and quantified on a daily basis, and that this change during a portion of the season was proportional to yield.

Hybrid Speaker Recognition Using Universal Acoustic Model

NASA Astrophysics Data System (ADS)

Nishimura, Jun; Kuroda, Tadahiro

We propose a novel speaker recognition approach using a speaker-independent universal acoustic model (UAM) for sensornet applications. In sensornet applications such as “Business Microscope”, interactions among knowledge workers in an organization can be visualized by sensing face-to-face communication using wearable sensor nodes. In conventional studies, speakers are detected by comparing energy of input speech signals among the nodes. However, there are often synchronization errors among the nodes which degrade the speaker recognition performance. By focusing on property of the speaker's acoustic channel, UAM can provide robustness against the synchronization error. The overall speaker recognition accuracy is improved by combining UAM with the energy-based approach. For 0.1s speech inputs and 4 subjects, speaker recognition accuracy of 94% is achieved at the synchronization error less than 100ms.

Evaluating the two-source energy balance model using local thermal and surface flux observations in a strongly advective irrigated agricultural area

NASA Astrophysics Data System (ADS)

Kustas, William P.; Alfieri, Joseph G.; Anderson, Martha C.; Colaizzi, Paul D.; Prueger, John H.; Evett, Steven R.; Neale, Christopher M. U.; French, Andrew N.; Hipps, Lawrence E.; Chávez, José L.; Copeland, Karen S.; Howell, Terry A.

2012-12-01

Application and validation of many thermal remote sensing-based energy balance models involve the use of local meteorological inputs of incoming solar radiation, wind speed and air temperature as well as accurate land surface temperature (LST), vegetation cover and surface flux measurements. For operational applications at large scales, such local information is not routinely available. In addition, the uncertainty in LST estimates can be several degrees due to sensor calibration issues, atmospheric effects and spatial variations in surface emissivity. Time differencing techniques using multi-temporal thermal remote sensing observations have been developed to reduce errors associated with deriving the surface-air temperature gradient, particularly in complex landscapes. The Dual-Temperature-Difference (DTD) method addresses these issues by utilizing the Two-Source Energy Balance (TSEB) model of Norman et al. (1995) [1], and is a relatively simple scheme requiring meteorological input from standard synoptic weather station networks or mesoscale modeling. A comparison of the TSEB and DTD schemes is performed using LST and flux observations from eddy covariance (EC) flux towers and large weighing lysimeters (LYs) in irrigated cotton fields collected during BEAREX08, a large-scale field experiment conducted in the semi-arid climate of the Texas High Plains as described by Evett et al. (2012) [2]. Model output of the energy fluxes (i.e., net radiation, soil heat flux, sensible and latent heat flux) generated with DTD and TSEB using local and remote meteorological observations are compared with EC and LY observations. The DTD method is found to be significantly more robust in flux estimation compared to the TSEB using the remote meteorological observations. However, discrepancies between model and measured fluxes are also found to be significantly affected by the local inputs of LST and vegetation cover and the representativeness of the remote sensing observations with the local flux measurement footprint.

Modeling the role of quorum sensing in interspecies competition in biofilms

NASA Astrophysics Data System (ADS)

Narla, Avaneesh V.; Wingreen, Ned S.; Borenstein, David B.

Bacteria grow on surfaces in complex immobile communities known as biofilms, composed of cells embedded in an extracellular matrix. Within biofilms, bacteria often communicate, cooperate, and compete within their own species and with other species using Quorum Sensing (QS). QS refers to the process by which bacteria produce, secrete, and subsequently detect small molecules called autoinducers as a way to assess the local population density of their species, or of other species. QS is known to regulate the production of extracellular matrix. We investigated the possible benefit of QS in regulating matrix production to best gain access to a nutrient that diffuses from a source positioned away from the surface on which the biofilm grows. We employed Agent-Based Modeling (ABM), a form of simulation that allows cells to modify their behavior based on local inputs, e.g. nutrient and QS concentrations. We first determined the optimal fixed strategies (that do not use QS) for pairwise competitions, and then demonstrated that simple QS-based strategies can be superior to any fixed strategy. In nature, species can compete by sensing and/or interfering with each other's QS signals, and we explore approaches for targeting specific species via QS-interference. A.V.N. and N.S.W. contributed equally to this project.

An Updating System for the Gridded Population Database of China Based on Remote Sensing, GIS and Spatial Database Technologies.

PubMed

Yang, Xiaohuan; Huang, Yaohuan; Dong, Pinliang; Jiang, Dong; Liu, Honghui

2009-01-01

The spatial distribution of population is closely related to land use and land cover (LULC) patterns on both regional and global scales. Population can be redistributed onto geo-referenced square grids according to this relation. In the past decades, various approaches to monitoring LULC using remote sensing and Geographic Information Systems (GIS) have been developed, which makes it possible for efficient updating of geo-referenced population data. A Spatial Population Updating System (SPUS) is developed for updating the gridded population database of China based on remote sensing, GIS and spatial database technologies, with a spatial resolution of 1 km by 1 km. The SPUS can process standard Moderate Resolution Imaging Spectroradiometer (MODIS L1B) data integrated with a Pattern Decomposition Method (PDM) and an LULC-Conversion Model to obtain patterns of land use and land cover, and provide input parameters for a Population Spatialization Model (PSM). The PSM embedded in SPUS is used for generating 1 km by 1 km gridded population data in each population distribution region based on natural and socio-economic variables. Validation results from finer township-level census data of Yishui County suggest that the gridded population database produced by the SPUS is reliable.

Numerical analysis of a 3D optical sensor based on single mode fiber to multimode interference graphene design

NASA Astrophysics Data System (ADS)

Mutter, Kussay N.; Jafri, Zubir M.; Tan, Kok Chooi

2016-04-01

In this paper, the simulation and design of a waveguide for water turbidity sensing are presented. The structure of the proposed sensor uses a 2x2 array of multimode interference (MMI) coupler based on micro graphene waveguide for high sensitivity. The beam propagation method (BPM) are used to efficiently design the sensor structure. The structure is consist of an array of two by two elements of sensors. Each element has three sections of single mode for field input tapered to MMI as the main core sensor without cladding which is graphene based material, and then a single mode fiber as an output. In this configuration MMI responses to any change in the environment. We validate and present the results by implementing the design on a set of sucrose solution and showing how these samples lead to a sensitivity change in the sensor based on the MMI structures. Overall results, the 3D design has a feasible and effective sensing by drawing topographical distribution of suspended particles in the water.

Overview and Assessment of Antarctic Ice-Sheet Mass Balance Estimates: 1992-2009

NASA Technical Reports Server (NTRS)

Zwally, H. Jay; Giovinetto, Mario B.

2011-01-01

Mass balance estimates for the Antarctic Ice Sheet (AIS) in the 2007 report by the Intergovernmental Panel on Climate Change and in more recent reports lie between approximately ?50 to -250 Gt/year for 1992 to 2009. The 300 Gt/year range is approximately 15% of the annual mass input and 0.8 mm/year Sea Level Equivalent (SLE). Two estimates from radar altimeter measurements of elevation change by European Remote-sensing Satellites (ERS) (?28 and -31 Gt/year) lie in the upper part, whereas estimates from the Input-minus-Output Method (IOM) and the Gravity Recovery and Climate Experiment (GRACE) lie in the lower part (-40 to -246 Gt/year). We compare the various estimates, discuss the methodology used, and critically assess the results. We also modify the IOM estimate using (1) an alternate extrapolation to estimate the discharge from the non-observed 15% of the periphery, and (2) substitution of input from a field data compilation for input from an atmospheric model in 6% of area. The modified IOM estimate reduces the loss from 136 Gt/year to 13 Gt/year. Two ERS-based estimates, the modified IOM, and a GRACE-based estimate for observations within 1992 2005 lie in a narrowed range of ?27 to -40 Gt/year, which is about 3% of the annual mass input and only 0.2 mm/year SLE. Our preferred estimate for 1992 2001 is -47 Gt/year for West Antarctica, ?16 Gt/year for East Antarctica, and -31 Gt/year overall (?0.1 mm/year SLE), not including part of the Antarctic Peninsula (1.07% of the AIS area). Although recent reports of large and increasing rates of mass loss with time from GRACE-based studies cite agreement with IOM results, our evaluation does not support that conclusion

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

NASA Astrophysics Data System (ADS)

Fard, Miad

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

Modified sensing element of a fibre-optic current sensor based on a low-eigenellipticity spun fibre

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

Przhiyalkovsky, Ya V; Morshnev, S K; Starostin, N I

2014-10-31

We have proposed and investigated a modified sensing element of a spun fibre current sensor for the case when the beat length of the built-in linear birefringence of the fibre is equal to or less than the spin pitch of its helical structure. The proposed configuration makes it possible to restore the interferometer contrast reduced because of the decrease in the ellipticity of the wavelength-averaged polarisation state of radiation propagating in such spun fibre. The modified sensing element contains two polarisation state converters: one, located at the spun fibre input, produces polarisation with ellipticity equal to the eigenellipticity of themore » fibre, and the other ensures conversion of the elliptical polarisation to an orthogonal one through mirror reflection at the fibre output. We have also demonstrated that the magneto-optical sensitivity decreases slightly for the analysed spectrum-averaged parameters of the polarisation state of radiation in the spun fibre. Experimental data lend support to the theoretical predictions. (fibre-optic sensors)« less

Non-contact capacitance based image sensing method and system

DOEpatents

Novak, James L.; Wiczer, James J.

1995-01-01

A system and a method is provided for imaging desired surfaces of a workpiece. A sensor having first and second sensing electrodes which are electrically isolated from the workpiece is positioned above and in proximity to the desired surfaces of the workpiece. An electric field is developed between the first and second sensing electrodes of the sensor in response to input signals being applied thereto and capacitance signals are developed which are indicative of any disturbances in the electric field as a result of the workpiece. An image signal of the workpiece may be developed by processing the capacitance signals. The image signals may provide necessary control information to a machining device for machining the desired surfaces of the workpiece in processes such as deburring or chamfering. Also, the method and system may be used to image dimensions of weld pools on a workpiece and surfaces of glass vials. The sensor may include first and second preview sensors used to determine the feed rate of a workpiece with respect to the machining device.

Non-contact capacitance based image sensing method and system

DOEpatents

Novak, James L.; Wiczer, James J.

1994-01-01

A system and a method for imaging desired surfaces of a workpiece. A sensor having first and second sensing electrodes which are electrically isolated from the workpiece is positioned above and in proximity to the desired surfaces of the workpiece. An electric field is developed between the first and second sensing electrodes of the sensor in response to input signals being applied thereto and capacitance signals are developed which are indicative of any disturbances in the electric field as a result of the workpiece. An image signal of the workpiece may be developed by processing the capacitance signals. The image signals may provide necessary control information to a machining device for machining the desired surfaces of the workpiece in processes such as deburring or chamfering. Also, the method and system may be used to image dimensions of weld pools on a workpiece and surfaces of glass vials. The sensor may include first and second preview sensors used to determine the feed rate of a workpiece with respect to the machining device.

Crack identification for reinforced concrete using PZT based smart rebar active sensing diagnostic network

NASA Astrophysics Data System (ADS)

Song, N. N.; Wu, F.

2016-04-01

An active sensing diagnostic system using PZT based smart rebar for SHM of RC structure has been currently under investigation. Previous test results showed that the system could detect the de-bond of concrete from reinforcement, and the diagnostic signals were increased exponentially with the de-bonding size. Previous study also showed that the smart rebar could function well like regular reinforcement to undertake tension stresses. In this study, a smart rebar network has been used to detect the crack damage of concrete based on guided waves. Experimental test has been carried out for the study. In the test, concrete beams with 2 reinforcements have been built. 8 sets of PZT elements were mounted onto the reinforcement bars in an optimized way to form an active sensing diagnostic system. A 90 kHz 5-cycle Hanning-windowed tone burst was used as input. Multiple cracks have been generated on the concrete structures. Through the guided bulk waves propagating in the structures from actuators and sensors mounted from different bars, crack damage could be detected clearly. Cases for both single and multiple cracks were tested. Different crack depths from the surface and different crack numbers have been studied. Test result shows that the amplitude of sensor output signals is deceased linearly with a propagating crack, and is decreased exponentially with increased crack numbers. From the study, the active sensing diagnostic system using PZT based smart rebar network shows a promising way to provide concrete crack damage information through the "talk" among sensors.

Enhanced Response Time of Electrowetting Lenses with Shaped Input Voltage Functions.

PubMed

Supekar, Omkar D; Zohrabi, Mo; Gopinath, Juliet T; Bright, Victor M

2017-05-16

Adaptive optical lenses based on the electrowetting principle are being rapidly implemented in many applications, such as microscopy, remote sensing, displays, and optical communication. To characterize the response of these electrowetting lenses, the dependence upon direct current (DC) driving voltage functions was investigated in a low-viscosity liquid system. Cylindrical lenses with inner diameters of 2.45 and 3.95 mm were used to characterize the dynamic behavior of the liquids under DC voltage electrowetting actuation. With the increase of the rise time of the input exponential driving voltage, the originally underdamped system response can be damped, enabling a smooth response from the lens. We experimentally determined the optimal rise times for the fastest response from the lenses. We have also performed numerical simulations of the lens actuation with input exponential driving voltage to understand the variation in the dynamics of the liquid-liquid interface with various input rise times. We further enhanced the response time of the devices by shaping the input voltage function with multiple exponential rise times. For the 3.95 mm inner diameter lens, we achieved a response time improvement of 29% when compared to the fastest response obtained using single-exponential driving voltage. The technique shows great promise for applications that require fast response times.

Regional surface soil heat flux estimate from multiple remote sensing data in a temperate and semiarid basin

NASA Astrophysics Data System (ADS)

Li, Nana; Jia, Li; Lu, Jing; Menenti, Massimo; Zhou, Jie

2017-01-01

The regional surface soil heat flux (G0) estimation is very important for the large-scale land surface process modeling. However, most of the regional G0 estimation methods are based on the empirical relationship between G0 and the net radiation flux. A physical model based on harmonic analysis was improved (referred to as "HM model") and applied over the Heihe River Basin northwest China with multiple remote sensing data, e.g., FY-2C, AMSR-E, and MODIS, and soil map data. The sensitivity analysis of the model was studied as well. The results show that the improved model describes the variation of G0 well. Land surface temperature (LST) and thermal inertia (Γ) are the two key input variables to the HM model. Compared with in situ G0, there are some differences, mainly due to the differences between remote-sensed LST and the in situ LST. The sensitivity analysis shows that the errors from -7 to -0.5 K in LST amplitude and from -300 to 300 J m-2 K-1 s-0.5 in Γ will cause about 20% errors, which are acceptable for G0 estimation.

Surveillance system for air pollutants by combination of the decision support system COMPAS and optical remote sensing systems

NASA Astrophysics Data System (ADS)

Flassak, Thomas; de Witt, Helmut; Hahnfeld, Peter; Knaup, Andreas; Kramer, Lothar

1995-09-01

COMPAS is a decision support system designed to assist in the assessment of the consequences of accidental releases of toxic and flammable substances. One of the key elements of COMPAS is a feedback algorithm which allows us to calculate the source term with the aid of concentration measurements. Up to now the feedback technique is applied to concentration measurements done with test tubes or conventional point sensors. In this paper the extension of the actual method is presented which is the combination of COMPAS and an optical remote sensing system like the KAYSER-THREDE K300 FTIR system. Active remote sensing methods based on FTIR are, among other applications, ideal for the so-called fence line monitoring of the diffuse emissions and accidental releases from industrial facilities, since from the FTIR spectra averaged concentration levels along the measurement path can be achieved. The line-averaged concentrations are ideally suited as on-line input for COMPAS' feedback technique. Uncertainties in the assessment of the source term related with both shortcomings of the dispersion model itself and also problems of a feedback strategy based on point measurements are reduced.

Remote sensing study of Maumee River effects of Lake Erie

NASA Technical Reports Server (NTRS)

Svehla, R.; Raquet, C.; Shook, D.; Salzman, J.; Coney, T.; Wachter, D.; Gedney, R.

1975-01-01

The effects of river inputs on boundary waters were studied in partial support of the task to assess the significance of river inputs into receiving waters, dispersion of pollutants, and water quality. The effects of the spring runoff of the Maumee River on Lake Erie were assessed by a combination of ship survey and remote sensing techniques. The imagery obtained from a multispectral scanner of the west basin of Lake Erie is discussed: this clearly showed the distribution of particulates throughout the covered area. This synoptic view, in addition to its qualitative value, is very useful in selecting sampling stations for shipboard in situ measurements, and for extrapolating these quantitative results throughout the area of interest.

Specification for procurement of water-level sensing instrumentation, specification number HIF-I-1

USGS Publications Warehouse

Rapp, D.H.

1982-01-01

This specification is to communicate to instrument manufacturers the U.S. Geological Survey 's requirements. It covers systems for sensing the elevation of the water surface on open channels, rivers, lakes, reservoirs, storm-sewer pipes, and observation wells at Survey data-collection sites. The signal output (mechanical or electrical) must meet the signal input requirements of analog to digital and digital input recorders in use by the Survey. A classification of stage-sensing systems by common characteristics is used to aid Survey people making system selections. These characteristics are (1) system type (contact or noncontact), (2) sensor type and sensing distance, (3) accuracy, (4) range, (5) power requirements, (6) system size and weight, and (7) data output signal. Acceptable system requirements cover system configurations, signal outputs, materials, operation manuals, detailed environmental conditions, calibration procedures, system accuracy, power requirements, installation limitations, maintainability, safety, and workmanship. An outline of the qualification test procedures and failure criteria are also given. The Hydrologic Instrumentation Facility at NSTL Station, Mississippi will test available systems to determine if they meet the specification in this report for inclusion in the Survey 's 'Qualified Products List'. This list will be used for future procurement of water-level sensing systems by the Survey. (USGS)

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.

A General Uncertainty Quantification Methodology for Cloud Microphysical Property Retrievals

NASA Astrophysics Data System (ADS)

Tang, Q.; Xie, S.; Chen, X.; Zhao, C.

2014-12-01

The US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program provides long-term (~20 years) ground-based cloud remote sensing observations. However, there are large uncertainties in the retrieval products of cloud microphysical properties based on the active and/or passive remote-sensing measurements. To address this uncertainty issue, a DOE Atmospheric System Research scientific focus study, Quantification of Uncertainties in Cloud Retrievals (QUICR), has been formed. In addition to an overview of recent progress of QUICR, we will demonstrate the capacity of an observation-based general uncertainty quantification (UQ) methodology via the ARM Climate Research Facility baseline cloud microphysical properties (MICROBASE) product. This UQ method utilizes the Karhunen-Loéve expansion (KLE) and Central Limit Theorems (CLT) to quantify the retrieval uncertainties from observations and algorithm parameters. The input perturbations are imposed on major modes to take into account the cross correlations between input data, which greatly reduces the dimension of random variables (up to a factor of 50) and quantifies vertically resolved full probability distribution functions of retrieved quantities. Moreover, this KLE/CLT approach has the capability of attributing the uncertainties in the retrieval output to individual uncertainty source and thus sheds light on improving the retrieval algorithm and observations. We will present the results of a case study for the ice water content at the Southern Great Plains during an intensive observing period on March 9, 2000. This work is performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Satellite detection of land-use change and effects on regional forest aboveground biomass estimates

Treesearch

Daolan Zheng; Linda S. Heath; Mark J. Ducey

2008-01-01

We used remote-sensing-driven models to detect land-cover change effects on forest aboveground biomass (AGB) density (Mg·ha−1, dry weight) and total AGB (Tg) in Minnesota, Wisconsin, and Michigan USA, between the years 1992-2001, and conducted an evaluation of the approach. Inputs included remotely-sensed 1992 reflectance data...

Information Extraction of High Resolution Remote Sensing Images Based on the Calculation of Optimal Segmentation Parameters

PubMed Central

Zhu, Hongchun; Cai, Lijie; Liu, Haiying; Huang, Wei

2016-01-01

Multi-scale image segmentation and the selection of optimal segmentation parameters are the key processes in the object-oriented information extraction of high-resolution remote sensing images. The accuracy of remote sensing special subject information depends on this extraction. On the basis of WorldView-2 high-resolution data, the optimal segmentation parameters methodof object-oriented image segmentation and high-resolution image information extraction, the following processes were conducted in this study. Firstly, the best combination of the bands and weights was determined for the information extraction of high-resolution remote sensing image. An improved weighted mean-variance method was proposed andused to calculatethe optimal segmentation scale. Thereafter, the best shape factor parameter and compact factor parameters were computed with the use of the control variables and the combination of the heterogeneity and homogeneity indexes. Different types of image segmentation parameters were obtained according to the surface features. The high-resolution remote sensing images were multi-scale segmented with the optimal segmentation parameters. Ahierarchical network structure was established by setting the information extraction rules to achieve object-oriented information extraction. This study presents an effective and practical method that can explain expert input judgment by reproducible quantitative measurements. Furthermore the results of this procedure may be incorporated into a classification scheme. PMID:27362762

Information Extraction of High Resolution Remote Sensing Images Based on the Calculation of Optimal Segmentation Parameters.

PubMed

Zhu, Hongchun; Cai, Lijie; Liu, Haiying; Huang, Wei

2016-01-01

Multi-scale image segmentation and the selection of optimal segmentation parameters are the key processes in the object-oriented information extraction of high-resolution remote sensing images. The accuracy of remote sensing special subject information depends on this extraction. On the basis of WorldView-2 high-resolution data, the optimal segmentation parameters methodof object-oriented image segmentation and high-resolution image information extraction, the following processes were conducted in this study. Firstly, the best combination of the bands and weights was determined for the information extraction of high-resolution remote sensing image. An improved weighted mean-variance method was proposed andused to calculatethe optimal segmentation scale. Thereafter, the best shape factor parameter and compact factor parameters were computed with the use of the control variables and the combination of the heterogeneity and homogeneity indexes. Different types of image segmentation parameters were obtained according to the surface features. The high-resolution remote sensing images were multi-scale segmented with the optimal segmentation parameters. Ahierarchical network structure was established by setting the information extraction rules to achieve object-oriented information extraction. This study presents an effective and practical method that can explain expert input judgment by reproducible quantitative measurements. Furthermore the results of this procedure may be incorporated into a classification scheme.

Quantifying the Terrestrial Surface Energy Fluxes Using Remotely-Sensed Satellite Data

NASA Astrophysics Data System (ADS)

Siemann, Amanda Lynn

The dynamics of the energy fluxes between the land surface and the atmosphere drive local and regional climate and are paramount to understand the past, present, and future changes in climate. Although global reanalysis datasets, land surface models (LSMs), and climate models estimate these fluxes by simulating the physical processes involved, they merely simulate our current understanding of these processes. Global estimates of the terrestrial, surface energy fluxes based on observations allow us to capture the dynamics of the full climate system. Remotely-sensed satellite data is the source of observations of the land surface which provide the widest spatial coverage. Although net radiation and latent heat flux global, terrestrial, surface estimates based on remotely-sensed satellite data have progressed, comparable sensible heat data products and ground heat flux products have not progressed at this scale. Our primary objective is quantifying and understanding the terrestrial energy fluxes at the Earth's surface using remotely-sensed satellite data with consistent development among all energy budget components [through the land surface temperature (LST) and input meteorology], including validation of these products against in-situ data, uncertainty assessments, and long-term trend analysis. The turbulent fluxes are constrained by the available energy using the Bowen ratio of the un-constrained products to ensure energy budget closure. All final products are within uncertainty ranges of literature values, globally. When validated against the in-situ estimates, the sensible heat flux estimates using the CFSR air temperature and constrained with the products using the MODIS albedo produce estimates closest to the FLUXNET in-situ observations. Poor performance over South America is consistent with the largest uncertainties in the energy budget. From 1984-2007, the longwave upward flux increase due to the LST increase drives the net radiation decrease, and the decrease in the available energy balances the decrease in the sensible heat flux. These datasets are useful for benchmarking climate models and LSM output at the global annual scale and the regional scale subject to the regional uncertainties and performance. Future work should improve the input data, particularly the temperature gradient and Zilitinkevich empirical constant, to reduce uncertainties.

Advanced wireless mobile collaborative sensing network for tactical and strategic missions

NASA Astrophysics Data System (ADS)

Xu, Hao

2017-05-01

In this paper, an advanced wireless mobile collaborative sensing network will be developed. Through properly combining wireless sensor network, emerging mobile robots and multi-antenna sensing/communication techniques, we could demonstrate superiority of developed sensing network. To be concrete, heterogeneous mobile robots including unmanned aerial vehicle (UAV) and unmanned ground vehicle (UGV) are equipped with multi-model sensors and wireless transceiver antennas. Through real-time collaborative formation control, multiple mobile robots can team the best formation that can provide most accurate sensing results. Also, formatting multiple mobile robots can also construct a multiple-input multiple-output (MIMO) communication system that can provide a reliable and high performance communication network.

Event-triggered decentralized adaptive fault-tolerant control of uncertain interconnected nonlinear systems with actuator failures.

PubMed

Choi, Yun Ho; Yoo, Sung Jin

2018-06-01

This paper investigates the event-triggered decentralized adaptive tracking problem of a class of uncertain interconnected nonlinear systems with unexpected actuator failures. It is assumed that local control signals are transmitted to local actuators with time-varying faults whenever predefined conditions for triggering events are satisfied. Compared with the existing control-input-based event-triggering strategy for adaptive control of uncertain nonlinear systems, the aim of this paper is to propose a tracking-error-based event-triggering strategy in the decentralized adaptive fault-tolerant tracking framework. The proposed approach can relax drastic changes in control inputs caused by actuator faults in the existing triggering strategy. The stability of the proposed event-triggering control system is analyzed in the Lyapunov sense. Finally, simulation comparisons of the proposed and existing approaches are provided to show the effectiveness of the proposed theoretical result in the presence of actuator faults. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Development and Implementation of Software for Visualizing and Editing Multidimensional Flight Simulation Input Data

NASA Technical Reports Server (NTRS)

Whelan, Todd Michael

1996-01-01

In a real-time or batch mode simulation that is designed to model aircraft dynamics over a wide range of flight conditions, a table look- up scheme is implemented to determine the forces and moments on the vehicle based upon the values of parameters such as angle of attack, altitude, Mach number, and control surface deflections. Simulation Aerodynamic Variable Interface (SAVI) is a graphical user interface to the flight simulation input data, designed to operate on workstations that support X Windows. The purpose of the application is to provide two and three dimensional visualization of the data, to allow an intuitive sense of the data set. SAVI also allows the user to manipulate the data, either to conduct an interactive study of the influence of changes on the vehicle dynamics, or to make revisions to data set based on new information such as flight test. This paper discusses the reasons for developing the application, provides an overview of its capabilities, and outlines the software architecture and operating environment.

Purification of Training Samples Based on Spectral Feature and Superpixel Segmentation

NASA Astrophysics Data System (ADS)

Guan, X.; Qi, W.; He, J.; Wen, Q.; Chen, T.; Wang, Z.

2018-04-01

Remote sensing image classification is an effective way to extract information from large volumes of high-spatial resolution remote sensing images. Generally, supervised image classification relies on abundant and high-precision training data, which is often manually interpreted by human experts to provide ground truth for training and evaluating the performance of the classifier. Remote sensing enterprises accumulated lots of manually interpreted products from early lower-spatial resolution remote sensing images by executing their routine research and business programs. However, these manually interpreted products may not match the very high resolution (VHR) image properly because of different dates or spatial resolution of both data, thus, hindering suitability of manually interpreted products in training classification models, or small coverage area of these manually interpreted products. We also face similar problems in our laboratory in 21st Century Aerospace Technology Co. Ltd (short for 21AT). In this work, we propose a method to purify the interpreted product to match newly available VHRI data and provide the best training data for supervised image classifiers in VHR image classification. And results indicate that our proposed method can efficiently purify the input data for future machine learning use.

Expansion of Smartwatch Touch Interface from Touchscreen to Around Device Interface Using Infrared Line Image Sensors.

PubMed

Lim, Soo-Chul; Shin, Jungsoon; Kim, Seung-Chan; Park, Joonah

2015-07-09

Touchscreen interaction has become a fundamental means of controlling mobile phones and smartwatches. However, the small form factor of a smartwatch limits the available interactive surface area. To overcome this limitation, we propose the expansion of the touch region of the screen to the back of the user's hand. We developed a touch module for sensing the touched finger position on the back of the hand using infrared (IR) line image sensors, based on the calibrated IR intensity and the maximum intensity region of an IR array. For complete touch-sensing solution, a gyroscope installed in the smartwatch is used to read the wrist gestures. The gyroscope incorporates a dynamic time warping gesture recognition algorithm for eliminating unintended touch inputs during the free motion of the wrist while wearing the smartwatch. The prototype of the developed sensing module was implemented in a commercial smartwatch, and it was confirmed that the sensed positional information of the finger when it was used to touch the back of the hand could be used to control the smartwatch graphical user interface. Our system not only affords a novel experience for smartwatch users, but also provides a basis for developing other useful interfaces.

Development of remote sensing based site specific weed management for Midwest mint production

NASA Astrophysics Data System (ADS)

Gumz, Mary Saumur Paulson

Peppermint and spearmint are high value essential oil crops in Indiana, Michigan, and Wisconsin. Although the mints are profitable alternatives to corn and soybeans, mint production efficiency must improve in order to allow industry survival against foreign produced oils and synthetic flavorings. Weed control is the major input cost in mint production and tools to increase efficiency are necessary. Remote sensing-based site-specific weed management offers potential for decreasing weed control costs through simplified weed detection and control from accurate site specific weed and herbicide application maps. This research showed the practicability of remote sensing for weed detection in the mints. Research was designed to compare spectral response curves of field grown mint and weeds, and to use these data to develop spectral vegetation indices for automated weed detection. Viability of remote sensing in mint production was established using unsupervised classification, supervised classification, handheld spectroradiometer readings and spectral vegetation indices (SVIs). Unsupervised classification of multispectral images of peppermint production fields generated crop health maps with 92 and 67% accuracy in meadow and row peppermint, respectively. Supervised classification of multispectral images identified weed infestations with 97% and 85% accuracy for meadow and row peppermint, respectively. Supervised classification showed that peppermint was spectrally distinct from weeds, but the accuracy of these measures was dependent on extensive ground referencing which is impractical and too costly for on-farm use. Handheld spectroradiometer measurements of peppermint, spearmint, and several weeds and crop and weed mixtures were taken over three years from greenhouse grown plants, replicated field plots, and production peppermint and spearmint fields. Results showed that mints have greater near infrared (NIR) and lower green reflectance and a steeper red edge slope than all weed species. These distinguishing characteristics were combined to develop narrow band and broadband spectral vegetation indices (SVIs, ratios of NIR/green reflectance), that were effective in differentiating mint from key weed species. Hyperspectral images of production peppermint and spearmint fields were then classified using SVI-based classification. Narrowband and broadband SVIs classified early season peppermint and spearmint with 64 to 100% accuracy compared to 79 to 100% accuracy for supervised classification of multispectral images of the same fields. Broadband SVIs have potential for use as an automated spectral indicator for weeds in the mints since they require minimal ground referencing and can be calculated from multispectral imagery which is cheaper and more readily available than hyperspectral imagery. This research will allow growers to implement remote sensing based site specific weed management in mint resulting in reduced grower input costs and reduced herbicide entry into the environment and will have applications in other specialty and meadow crops.

Effects of cold temperatures on the excitability of rat trigeminal ganglion neurons that are not for cold-sensing

PubMed Central

Kanda, Hirosato; Gu, Jianguo G.

2016-01-01

Except a small population of primary afferent neurons for sensing cold to generate the sensations of innocuous and noxious cold, it is generally believed that cold temperatures suppress the excitability of other primary afferent neurons that are not for cold-sensing. These not-for-cold-sensing neurons include the majority of non-nociceptive and nociceptive afferent neurons. In the present study we have found that not-for-cold-sensing neurons of rat trigeminal ganglia (TG) change their excitability in several ways at cooling temperatures. In nearly 70% of not-for-cold-sensing TG neurons, the cooling temperature of 15°C increases their membrane excitability. We regard these neurons as cold-active neurons. For the remaining 30% of not-for-cold-sensing TG neurons, the cooling temperature of 15°C either has no effect (regarded as cold-ineffective neurons) or suppress (regarded as cold-suppressive neurons) their membrane excitability. For cold-active neurons, the cold temperature of 15°C increases their excitability as is evidenced by the increases in action potential (AP) firing numbers and/or reduction of AP rheobase when these neurons are depolarized electrically. The cold temperature of 15°C significantly inhibits M-currents and increases membrane input resistance of cold-active neurons. Retigabine, an M-current activator, abolishes the effect of cold temperatures on AP firing but not the effect of cold temperature on AP rheobase levels. The inhibition of M-currents and the increases of membrane input resistance are likely two mechanisms by which cooling temperatures increase the excitability of not-for-cold-sensing TG neurons. PMID:26709732

Effects of cold temperatures on the excitability of rat trigeminal ganglion neurons that are not for cold sensing.

PubMed

Kanda, Hirosato; Gu, Jianguo G

2017-05-01

Aside from a small population of primary afferent neurons for sensing cold, which generate sensations of innocuous and noxious cold, it is generally believed that cold temperatures suppress the excitability of primary afferent neurons not responsible for cold sensing. These not-for-cold-sensing neurons include the majority of non-nociceptive and nociceptive afferent neurons. In this study we have found that the not-for-cold-sensing neurons of rat trigeminal ganglia (TG) change their excitability in several ways at cooling temperatures. In nearly 70% of not-for-cold-sensing TG neurons, a cooling temperature of 15°C increases their membrane excitability. We regard these neurons as cold-active neurons. For the remaining 30% of not-for-cold-sensing TG neurons, the cooling temperature of 15°C either has no effect (cold-ineffective neurons) or suppress their membrane excitability (cold-suppressive neurons). For cold-active neurons, the cold temperature of 15°C increases their excitability as is evidenced by increases in action potential (AP) firing numbers and/or the reduction in AP rheobase when these neurons are depolarized electrically. The cold temperature of 15°C significantly inhibits M-currents and increases membrane input resistance of cold-active neurons. Retigabine, an M-current activator, abolishes the effect of cold temperatures on AP firing, but not the effect of cold temperature on AP rheobase levels. The inhibition of M-currents and the increases of membrane input resistance are likely two mechanisms by which cooling temperatures increase the excitability of not-for-cold-sensing TG neurons. This article is part of the special article series "Pain". © 2015 International Society for Neurochemistry.

Inputs requested from earth resources remote sensing data users regarding LANDSAT-C mission requirements and data needs

NASA Technical Reports Server (NTRS)

1976-01-01

Inputs from prospective LANDSAT-C data users are requested to aid NASA in defining LANDSAT-C mission and data requirements and in making decisions regarding the scheduling of satellite operations and ground data processing operations. Design specifications, multispectral band scanner performance characteristics, satellite schedule operations, and types of available data products are briefly described.

Team Science Approach to Developing Consensus on Research Good Practices for Practice-Based Research Networks: A Case Study.

PubMed

Campbell-Voytal, Kimberly; Daly, Jeanette M; Nagykaldi, Zsolt J; Aspy, Cheryl B; Dolor, Rowena J; Fagnan, Lyle J; Levy, Barcey T; Palac, Hannah L; Michaels, LeAnn; Patterson, V Beth; Kano, Miria; Smith, Paul D; Sussman, Andrew L; Williams, Robert; Sterling, Pamela; O'Beirne, Maeve; Neale, Anne Victoria

2015-12-01

Using peer learning strategies, seven experienced PBRNs working in collaborative teams articulated procedures for PBRN Research Good Practices (PRGPs). The PRGPs is a PBRN-specific resource to facilitate PBRN management and staff training, to promote adherence to study protocols, and to increase validity and generalizability of study findings. This paper describes the team science processes which culminated in the PRGPs. Skilled facilitators used team science strategies and methods from the Technology of Participation (ToP®), and the Consensus Workshop Method to support teams to codify diverse research expertise in practice-based research. The participatory nature of "sense-making" moved through identifiable stages. Lessons learned include (1) team input into the scope of the final outcome proved vital to project relevance; (2) PBRNs with diverse domains of research expertise contributed broad knowledge on each topic; and (3) ToP® structured facilitation techniques were critical for establishing trust and clarifying the "sense-making" process. © 2015 Wiley Periodicals, Inc.

Dispersal forcing of a southern California river plumes, based on field and remote sensing observations

USGS Publications Warehouse

Warrick, Jonathan A.; Mertes, Leal A.K.; Washburn, Libe; Siegel, David A.

2004-01-01

River plumes are important pathways of terrestrial materials entering the sea. In southern California, rivers are known to be the dominant source of littoral, shelf and basin sediment and coastal pollution, although a basic understanding of the dynamics of these river inputs does not exist. Here we evaluate forcing parameters of a southern California river plume using ship-based hydrographic surveys and satellite remote sensing measurements to provide the first insights of river dispersal dynamics in southern California. Our results suggest that plumes of the Santa Clara River are strongly influenced by river inertia, producing jet-like structures ~10 km offshore during annual recurrence (~two-year) flood events and ~30 km during exceptional (~10-year recurrence) floods. Upwelling-favorable winds may be strong following stormwater events and can alter dispersal pathways of thse plumes. Due to similar runoff relationships and other reported satellite observations, we hypothesize that interia-dominated dispersal may be an important characteristic of the small, mountainous rivers throughout southern California.

Remote sensing inputs to water demand modeling

NASA Technical Reports Server (NTRS)

Estes, J. E.; Jensen, J. R.; Tinney, L. R.; Rector, M.

1975-01-01

In an attempt to determine the ability of remote sensing techniques to economically generate data required by water demand models, the Geography Remote Sensing Unit, in conjunction with the Kern County Water Agency of California, developed an analysis model. As a result it was determined that agricultural cropland inventories utilizing both high altitude photography and LANDSAT imagery can be conducted cost effectively. In addition, by using average irrigation application rates in conjunction with cropland data, estimates of agricultural water demand can be generated. However, more accurate estimates are possible if crop type, acreage, and crop specific application rates are employed. An analysis of the effect of saline-alkali soils on water demand in the study area is also examined. Finally, reference is made to the detection and delineation of water tables that are perched near the surface by semi-permeable clay layers. Soil salinity prediction, automated crop identification on a by-field basis, and a potential input to the determination of zones of equal benefit taxation are briefly touched upon.

Light coupling and distribution for Si3N4/SiO2 integrated multichannel single-mode sensing system

NASA Astrophysics Data System (ADS)

Kaźmierczak, Andrzej; Dortu, Fabian; Schrevens, Olivier; Giannone, Domenico; Bouville, David; Cassan, Eric; Gylfason, Kristinn B.; Sohlström, Hans; Sanchez, Benito; Griol, Amadeu; Hill, Daniel

2009-01-01

We present an efficient and highly alignment-tolerant light coupling and distribution system for a multichannel Si3N4/SiO2 single-mode photonics sensing chip. The design of the input and output couplers and the distribution splitters is discussed. Examples of multichannel data obtained with the system are given.

The application of remote sensing to the development and formulation of hydrologic planning models: Executive summary

NASA Technical Reports Server (NTRS)

Castruccio, P. A.; Loats, H. L., Jr.; Fowler, T. R.

1977-01-01

Methods for the reduction of remotely sensed data and its application in hydrologic land use assessment, surface water inventory, and soil property studies are presented. LANDSAT data is used to provide quantitative parameters and coefficients to construct watershed transfer functions for a hydrologic planning model aimed at estimating peak outflow from rainfall inputs.

Review of FEWS NET Biophysical Monitoring Requirements

NASA Technical Reports Server (NTRS)

Ross, K. W.; Brown, Molly E.; Verdin, J.; Underwood, L. W.

2009-01-01

The Famine Early Warning System Network (FEWS NET) provides monitoring and early warning support to decision makers responsible for responding to famine and food insecurity. FEWS NET transforms satellite remote sensing data into rainfall and vegetation information that can be used by these decision makers. The National Aeronautics and Space Administration has recently funded activities to enhance remote sensing inputs to FEWS NET. To elicit Earth observation requirements, a professional review questionnaire was disseminated to FEWS NET expert end-users: it focused upon operational requirements to determine additional useful remote sensing data and; subsequently, beneficial FEWS NET biophysical supplementary inputs. The review was completed by over 40 experts from around the world, enabling a robust set of professional perspectives to be gathered and analyzed rapidly. Reviewers were asked to evaluate the relative importance of environmental variables and spatio-temporal requirements for Earth science data products, in particular for rainfall and vegetation products. The results showed that spatio-temporal resolution requirements are complex and need to vary according to place, time, and hazard: that high resolution remote sensing products continue to be in demand, and that rainfall and vegetation products were valued as data that provide actionable food security information.

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

PubMed

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

2009-01-01

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

The integration of geophysical and enhanced Moderate Resolution Imaging Spectroradiometer Normalized Difference Vegetation Index data into a rule-based, piecewise regression-tree model to estimate cheatgrass beginning of spring growth

USGS Publications Warehouse

Boyte, Stephen P.; Wylie, Bruce K.; Major, Donald J.; Brown, Jesslyn F.

2015-01-01

Cheatgrass exhibits spatial and temporal phenological variability across the Great Basin as described by ecological models formed using remote sensing and other spatial data-sets. We developed a rule-based, piecewise regression-tree model trained on 99 points that used three data-sets – latitude, elevation, and start of season time based on remote sensing input data – to estimate cheatgrass beginning of spring growth (BOSG) in the northern Great Basin. The model was then applied to map the location and timing of cheatgrass spring growth for the entire area. The model was strong (R2 = 0.85) and predicted an average cheatgrass BOSG across the study area of 29 March–4 April. Of early cheatgrass BOSG areas, 65% occurred at elevations below 1452 m. The highest proportion of cheatgrass BOSG occurred between mid-April and late May. Predicted cheatgrass BOSG in this study matched well with previous Great Basin cheatgrass green-up studies.

Mineralogy and astrobiology detection using laser remote sensing instrument.

PubMed

Abedin, M Nurul; Bradley, Arthur T; Sharma, Shiv K; Misra, Anupam K; Lucey, Paul G; McKay, Christopher P; Ismail, Syed; Sandford, Stephen P

2015-09-01

A multispectral instrument based on Raman, laser-induced fluorescence (LIF), laser-induced breakdown spectroscopy (LIBS), and a lidar system provides high-fidelity scientific investigations, scientific input, and science operation constraints in the context of planetary field campaigns with the Jupiter Europa Robotic Lander and Mars Sample Return mission opportunities. This instrument conducts scientific investigations analogous to investigations anticipated for missions to Mars and Jupiter's icy moons. This combined multispectral instrument is capable of performing Raman and fluorescence spectroscopy out to a >100  m target distance from the rover system and provides single-wavelength atmospheric profiling over long ranges (>20  km). In this article, we will reveal integrated remote Raman, LIF, and lidar technologies for use in robotic and lander-based planetary remote sensing applications. Discussions are focused on recently developed Raman, LIF, and lidar systems in addition to emphasizing surface water ice, surface and subsurface minerals, organics, biogenic, biomarker identification, atmospheric aerosols and clouds distributions, i.e., near-field atmospheric thin layers detection for next robotic-lander based instruments to measure all the above-mentioned parameters.

Pre-Flight Radiometric Model of Linear Imager on LAPAN-IPB Satellite

NASA Astrophysics Data System (ADS)

Hadi Syafrudin, A.; Salaswati, Sartika; Hasbi, Wahyudi

2018-05-01

LAPAN-IPB Satellite is Microsatellite class with mission of remote sensing experiment. This satellite carrying Multispectral Line Imager for captured of radiometric reflectance value from earth to space. Radiometric quality of image is important factor to classification object on remote sensing process. Before satellite launch in orbit or pre-flight, Line Imager have been tested by Monochromator and integrating sphere to get spectral and every pixel radiometric response characteristic. Pre-flight test data with variety setting of line imager instrument used to see correlation radiance input and digital number of images output. Output input correlation is described by the radiance conversion model with imager setting and radiometric characteristics. Modelling process from hardware level until normalize radiance formula are presented and discussed in this paper.

Real-Time Identification of Smoldering and Flaming Combustion Phases in Forest Using a Wireless Sensor Network-Based Multi-Sensor System and Artificial Neural Network

PubMed Central

Yan, Xiaofei; Cheng, Hong; Zhao, Yandong; Yu, Wenhua; Huang, Huan; Zheng, Xiaoliang

2016-01-01

Diverse sensing techniques have been developed and combined with machine learning method for forest fire detection, but none of them referred to identifying smoldering and flaming combustion phases. This study attempts to real-time identify different combustion phases using a developed wireless sensor network (WSN)-based multi-sensor system and artificial neural network (ANN). Sensors (CO, CO2, smoke, air temperature and relative humidity) were integrated into one node of WSN. An experiment was conducted using burning materials from residual of forest to test responses of each node under no, smoldering-dominated and flaming-dominated combustion conditions. The results showed that the five sensors have reasonable responses to artificial forest fire. To reduce cost of the nodes, smoke, CO2 and temperature sensors were chiefly selected through correlation analysis. For achieving higher identification rate, an ANN model was built and trained with inputs of four sensor groups: smoke; smoke and CO2; smoke and temperature; smoke, CO2 and temperature. The model test results showed that multi-sensor input yielded higher predicting accuracy (≥82.5%) than single-sensor input (50.9%–92.5%). Based on these, it is possible to reduce the cost with a relatively high fire identification rate and potential application of the system can be tested in future under real forest condition. PMID:27527175

Estimating floodwater depths from flood inundation maps and topography

USGS Publications Warehouse

Cohen, Sagy; Brakenridge, G. Robert; Kettner, Albert; Bates, Bradford; Nelson, Jonathan M.; McDonald, Richard R.; Huang, Yu-Fen; Munasinghe, Dinuke; Zhang, Jiaqi

2018-01-01

Information on flood inundation extent is important for understanding societal exposure, water storage volumes, flood wave attenuation, future flood hazard, and other variables. A number of organizations now provide flood inundation maps based on satellite remote sensing. These data products can efficiently and accurately provide the areal extent of a flood event, but do not provide floodwater depth, an important attribute for first responders and damage assessment. Here we present a new methodology and a GIS-based tool, the Floodwater Depth Estimation Tool (FwDET), for estimating floodwater depth based solely on an inundation map and a digital elevation model (DEM). We compare the FwDET results against water depth maps derived from hydraulic simulation of two flood events, a large-scale event for which we use medium resolution input layer (10 m) and a small-scale event for which we use a high-resolution (LiDAR; 1 m) input. Further testing is performed for two inundation maps with a number of challenging features that include a narrow valley, a large reservoir, and an urban setting. The results show FwDET can accurately calculate floodwater depth for diverse flooding scenarios but also leads to considerable bias in locations where the inundation extent does not align well with the DEM. In these locations, manual adjustment or higher spatial resolution input is required.

Real-Time Identification of Smoldering and Flaming Combustion Phases in Forest Using a Wireless Sensor Network-Based Multi-Sensor System and Artificial Neural Network.

PubMed

Yan, Xiaofei; Cheng, Hong; Zhao, Yandong; Yu, Wenhua; Huang, Huan; Zheng, Xiaoliang

2016-08-04

Diverse sensing techniques have been developed and combined with machine learning method for forest fire detection, but none of them referred to identifying smoldering and flaming combustion phases. This study attempts to real-time identify different combustion phases using a developed wireless sensor network (WSN)-based multi-sensor system and artificial neural network (ANN). Sensors (CO, CO₂, smoke, air temperature and relative humidity) were integrated into one node of WSN. An experiment was conducted using burning materials from residual of forest to test responses of each node under no, smoldering-dominated and flaming-dominated combustion conditions. The results showed that the five sensors have reasonable responses to artificial forest fire. To reduce cost of the nodes, smoke, CO₂ and temperature sensors were chiefly selected through correlation analysis. For achieving higher identification rate, an ANN model was built and trained with inputs of four sensor groups: smoke; smoke and CO₂; smoke and temperature; smoke, CO₂ and temperature. The model test results showed that multi-sensor input yielded higher predicting accuracy (≥82.5%) than single-sensor input (50.9%-92.5%). Based on these, it is possible to reduce the cost with a relatively high fire identification rate and potential application of the system can be tested in future under real forest condition.

Modeling the Ionosphere-Thermosphere Response to a Geomagnetic Storm Using Physics-based Magnetospheric Energy Input: OpenGGCM-CTIM Results

NASA Technical Reports Server (NTRS)

Connor, Hyunju K.; Zesta, Eftyhia; Fedrizzi, Mariangel; Shi, Yong; Raeder, Joachim; Codrescu, Mihail V.; Fuller-Rowell, Tim J.

2016-01-01

The magnetosphere is a major source of energy for the Earth's ionosphere and thermosphere (IT) system. Current IT models drive the upper atmosphere using empirically calculated magnetospheric energy input. Thus, they do not sufficiently capture the storm-time dynamics, particularly at high latitudes. To improve the prediction capability of IT models, a physics-based magnetospheric input is necessary. Here, we use the Open Global General Circulation Model (OpenGGCM) coupled with the Coupled Thermosphere Ionosphere Model (CTIM). OpenGGCM calculates a three-dimensional global magnetosphere and a two-dimensional high-latitude ionosphere by solving resistive magnetohydrodynamic (MHD) equations with solar wind input. CTIM calculates a global thermosphere and a high-latitude ionosphere in three dimensions using realistic magnetospheric inputs from the OpenGGCM. We investigate whether the coupled model improves the storm-time IT responses by simulating a geomagnetic storm that is preceded by a strong solar wind pressure front on August 24, 2005. We compare the OpenGGCM-CTIM results with low-earth-orbit satellite observations and with the model results of Coupled Thermosphere-Ionosphere-Plasmasphere electrodynamics (CTIPe). CTIPe is an up-to-date version of CTIM that incorporates more IT dynamics such as a low-latitude ionosphere and a plasmasphere, but uses empirical magnetospheric input. OpenGGCMCTIM reproduces localized neutral density peaks at approx. 400 km altitude in the high-latitude dayside regions in agreement with in situ observations during the pressure shock and the early phase of the storm. Although CTIPe is in some sense a much superior model than CTIM, it misses these localized enhancements. Unlike the CTIPe empirical input models, OpenGGCM-CTIM more faithfully produces localized increases of both auroral precipitation and ionospheric electric fields near the high-latitude dayside region after the pressure shock and after the storm onset, which in turn effectively heats the thermosphere and causes the neutral density increase at 400 km altitude.

Universal power transistor base drive control unit

DOEpatents

Gale, Allan R.; Gritter, David J.

1988-01-01

A saturation condition regulator system for a power transistor which achieves the regulation objectives of a Baker clamp but without dumping excess base drive current into the transistor output circuit. The base drive current of the transistor is sensed and used through an active feedback circuit to produce an error signal which modulates the base drive current through a linearly operating FET. The collector base voltage of the power transistor is independently monitored to develop a second error signal which is also used to regulate base drive current. The current-sensitive circuit operates as a limiter. In addition, a fail-safe timing circuit is disclosed which automatically resets to a turn OFF condition in the event the transistor does not turn ON within a predetermined time after the input signal transition.

Universal power transistor base drive control unit

DOEpatents

Gale, A.R.; Gritter, D.J.

1988-06-07

A saturation condition regulator system for a power transistor is disclosed which achieves the regulation objectives of a Baker clamp but without dumping excess base drive current into the transistor output circuit. The base drive current of the transistor is sensed and used through an active feedback circuit to produce an error signal which modulates the base drive current through a linearly operating FET. The collector base voltage of the power transistor is independently monitored to develop a second error signal which is also used to regulate base drive current. The current-sensitive circuit operates as a limiter. In addition, a fail-safe timing circuit is disclosed which automatically resets to a turn OFF condition in the event the transistor does not turn ON within a predetermined time after the input signal transition. 2 figs.

Experiments in sensing transient rotational acceleration cues on a flight simulator

NASA Technical Reports Server (NTRS)

Parrish, R. V.

1979-01-01

Results are presented for two transient motion sensing experiments which were motivated by the identification of an anomalous roll cue (a 'jerk' attributed to an acceleration spike) in a prior investigation of realistic fighter motion simulation. The experimental results suggest the consideration of several issues for motion washout and challenge current sensory system modeling efforts. Although no sensory modeling effort is made it is argued that such models must incorporate the ability to handle transient inputs of short duration (some of which are less than the accepted latency times for sensing), and must represent separate channels for rotational acceleration and velocity sensing.

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

NASA Technical Reports Server (NTRS)

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

1990-01-01

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

A GIS/Remote Sensing-based methodology for groundwater potentiality assessment in Tirnavos area, Greece

NASA Astrophysics Data System (ADS)

Oikonomidis, D.; Dimogianni, S.; Kazakis, N.; Voudouris, K.

2015-06-01

The aim of this paper is to assess the groundwater potentiality combining Geographic Information Systems and Remote Sensing with data obtained from the field, as an additional tool to the hydrogeological research. The present study was elaborated in the broader area of Tirnavos, covering 419.4 km2. The study area is located in Thessaly (central Greece) and is crossed by two rivers, Pinios and Titarisios. Agriculture is one of the main elements of Thessaly's economy resulting in intense agricultural activity and consequently increased exploitation of groundwater resources. Geographic Information Systems (GIS) and Remote Sensing (RS) were used in order to create a map that depicts the likelihood of existence of groundwater, consisting of five classes, showing the groundwater potentiality and ranging from very high to very low. The extraction of this map is based on the study of input data such as: rainfall, potential recharge, lithology, lineament density, slope, drainage density and depth to groundwater. Weights were assigned to all these factors according to their relevance to groundwater potential and eventually a map based on weighted spatial modeling system was created. Furthermore, a groundwater quality suitability map was illustrated by overlaying the groundwater potentiality map with the map showing the potential zones for drinking groundwater in the study area. The results provide significant information and the maps could be used from local authorities for groundwater exploitation and management.

The Effects of Mechanical Transparency on Adjustment to a Complex Visuomotor Transformation at Early and Late Working Age

ERIC Educational Resources Information Center

Heuer, Herbert; Hegele, Mathias

2010-01-01

Mechanical tools are transparent in the sense that their input-output relations can be derived from their perceptible characteristics. Modern technology creates more and more tools that lack mechanical transparency, such as in the control of the position of a cursor by means of a computer mouse or some other input device. We inquired whether an…

Optimization of an integrated wavelength monitor device

NASA Astrophysics Data System (ADS)

Wang, Pengfei; Brambilla, Gilberto; Semenova, Yuliya; Wu, Qiang; Farrell, Gerald

2011-05-01

In this paper an edge filter based on multimode interference in an integrated waveguide is optimized for a wavelength monitoring application. This can also be used as a demodulation element in a fibre Bragg grating sensing system. A global optimization algorithm is presented for the optimum design of the multimode interference device, including a range of parameters of the multimode waveguide, such as length, width and position of the input and output waveguides. The designed structure demonstrates the desired spectral response for wavelength measurements. Fabrication tolerance is also analysed numerically for this structure.

A prospective approach to coastal geography from satellite. [technological forecasting

NASA Technical Reports Server (NTRS)

Munday, J. C., Jr.

1981-01-01

A forecasting protocol termed the "prospective approach' was used to examine probable futures relative to coastal applications of satellite data. Significant variables include the energy situation, the national economy, national Earth satellite programs, and coastal zone research, commercial activity, and regulatory activity. Alternative scenarios for the period until 1986 are presented. Possible response by state/local remote sensing centers include operational applications for users, input to geo-base information systems (GIS), development of decision-making algorithms using GIS data, and long term research programs for coastal management using merged satellite and traditional data.

Analog system for computing sparse codes

DOEpatents

Rozell, Christopher John; Johnson, Don Herrick; Baraniuk, Richard Gordon; Olshausen, Bruno A.; Ortman, Robert Lowell

2010-08-24

A parallel dynamical system for computing sparse representations of data, i.e., where the data can be fully represented in terms of a small number of non-zero code elements, and for reconstructing compressively sensed images. The system is based on the principles of thresholding and local competition that solves a family of sparse approximation problems corresponding to various sparsity metrics. The system utilizes Locally Competitive Algorithms (LCAs), nodes in a population continually compete with neighboring units using (usually one-way) lateral inhibition to calculate coefficients representing an input in an over complete dictionary.

Logarithmic circuit with wide dynamic range

NASA Technical Reports Server (NTRS)

Wiley, P. H.; Manus, E. A. (Inventor)

1978-01-01

A circuit deriving an output voltage that is proportional to the logarithm of a dc input voltage susceptible to wide variations in amplitude includes a constant current source which forward biases a diode so that the diode operates in the exponential portion of its voltage versus current characteristic, above its saturation current. The constant current source includes first and second, cascaded feedback, dc operational amplifiers connected in negative feedback circuit. An input terminal of the first amplifier is responsive to the input voltage. A circuit shunting the first amplifier output terminal includes a resistor in series with the diode. The voltage across the resistor is sensed at the input of the second dc operational feedback amplifier. The current flowing through the resistor is proportional to the input voltage over the wide range of variations in amplitude of the input voltage.

Building a team through a strategic planning process.

PubMed

Albert, Debra; Priganc, Dave

2014-01-01

Strategic planning is a process often left to senior hospital leadership, with limited input from unit-level, bedside patient care providers. This frequent approach to strategic planning misses the opportunity to engage a wide range of employees, build a shared sense of commitment, produce a collaborative team environment, and to generate greater acceptance of the plan. The Patient Care Services division at the University of Chicago Medicine used a strategic planning process that incorporated 360-degree input from both within the Patient Care Services division and outside of the division. The result is a strategic vision and plan that, shaped by broad-based input from both internal and external constituencies, is strengthened by the team that emerged from the process. Through the process of identifying a common understanding of the group's future direction, a shared purpose was created that transcended traditional professional boundaries and shaped a cohesive team focused on effective and efficient patient care. Now, with a focused strategic plan and a team centered on a shared purpose, the team is beginning to effectively deliver on the plan.

Digital Imprinting of RNA Recognition and Processing on a Self-Assembled Nucleic Acid Matrix

NASA Astrophysics Data System (ADS)

Redhu, Shiv K.; Castronovo, Matteo; Nicholson, Allen W.

2013-08-01

The accelerating progress of research in nanomedicine and nanobiotechnology has included initiatives to develop highly-sensitive, high-throughput methods to detect biomarkers at the single-cell level. Current sensing approaches, however, typically involve integrative instrumentation that necessarily must balance sensitivity with rapidity in optimizing biomarker detection quality. We show here that laterally-confined, self-assembled monolayers of a short, double-stranded(ds)[RNA-DNA] chimera enable permanent digital detection of dsRNA-specific inputs. The action of ribonuclease III and the binding of an inactive, dsRNA-binding mutant can be permanently recorded by the input-responsive action of a restriction endonuclease that cleaves an ancillary reporter site within the dsDNA segment. The resulting irreversible height change of the arrayed ds[RNA-DNA], as measured by atomic force microscopy, provides a distinct digital output for each dsRNA-specific input. These findings provide the basis for developing imprinting-based bio-nanosensors, and reveal the versatility of AFM as a tool for characterizing the behaviour of highly-crowded biomolecules at the nanoscale.

Development of a Land Use Mapping and Monitoring Protocol for the High Plains Region: A Multitemporal Remote Sensing Application

NASA Technical Reports Server (NTRS)

Price, Kevin P.; Nellis, M. Duane

1996-01-01

The purpose of this project was to develop a practical protocol that employs multitemporal remotely sensed imagery, integrated with environmental parameters to model and monitor agricultural and natural resources in the High Plains Region of the United States. The value of this project would be extended throughout the region via workshops targeted at carefully selected audiences and designed to transfer remote sensing technology and the methods and applications developed. Implementation of such a protocol using remotely sensed satellite imagery is critical for addressing many issues of regional importance, including: (1) Prediction of rural land use/land cover (LULC) categories within a region; (2) Use of rural LULC maps for successive years to monitor change; (3) Crop types derived from LULC maps as important inputs to water consumption models; (4) Early prediction of crop yields; (5) Multi-date maps of crop types to monitor patterns related to crop change; (6) Knowledge of crop types to monitor condition and improve prediction of crop yield; (7) More precise models of crop types and conditions to improve agricultural economic forecasts; (8;) Prediction of biomass for estimating vegetation production, soil protection from erosion forces, nonpoint source pollution, wildlife habitat quality and other related factors; (9) Crop type and condition information to more accurately predict production of biogeochemicals such as CO2, CH4, and other greenhouse gases that are inputs to global climate models; (10) Provide information regarding limiting factors (i.e., economic constraints of pumping, fertilizing, etc.) used in conjunction with other factors, such as changes in climate for predicting changes in rural LULC; (11) Accurate prediction of rural LULC used to assess the effectiveness of government programs such as the U.S. Soil Conservation Service (SCS) Conservation Reserve Program; and (12) Prediction of water demand based on rural LULC that can be related to rates of draw-down of underground water supplies.

Gifted Education in the Commonwealth of Virginia: A Qualitative Exploratory Study of How Gifted Education Coordinators Make Sense of and Implement Gifted Education Policy

ERIC Educational Resources Information Center

Beckerdite, Kimberly B.

2017-01-01

This study examined both the influence of leadership and policy development on gifted education in the Commonwealth of Virginia and how leaders of gifted education programs make sense of gifted education policy to promote effective change. Considerations of local politics, funding, networking, and input from stakeholders shaped the sensemaking…

Remote sensing of the seasonal variation of coniferous forest structure and function

NASA Technical Reports Server (NTRS)

Spanner, Michael; Waring, Richard

1991-01-01

One of the objectives of the Oregon Transect Ecosystem Research (OTTER) project is the remotely sensed determination of the seasonal variation of leaf area index (LAI) and absorbed photosynthetically active radiation (APAR). These measurements are required for input into a forest ecosystem model which predicts net primary production evapotranspiration, and photosynthesis of coniferous forests. Details of the study are given.

A classification model of Hyperion image base on SAM combined decision tree

NASA Astrophysics Data System (ADS)

Wang, Zhenghai; Hu, Guangdao; Zhou, YongZhang; Liu, Xin

2009-10-01

Monitoring the Earth using imaging spectrometers has necessitated more accurate analyses and new applications to remote sensing. A very high dimensional input space requires an exponentially large amount of data to adequately and reliably represent the classes in that space. On the other hand, with increase in the input dimensionality the hypothesis space grows exponentially, which makes the classification performance highly unreliable. Traditional classification algorithms Classification of hyperspectral images is challenging. New algorithms have to be developed for hyperspectral data classification. The Spectral Angle Mapper (SAM) is a physically-based spectral classification that uses an ndimensional angle to match pixels to reference spectra. The algorithm determines the spectral similarity between two spectra by calculating the angle between the spectra, treating them as vectors in a space with dimensionality equal to the number of bands. The key and difficulty is that we should artificial defining the threshold of SAM. The classification precision depends on the rationality of the threshold of SAM. In order to resolve this problem, this paper proposes a new automatic classification model of remote sensing image using SAM combined with decision tree. It can automatic choose the appropriate threshold of SAM and improve the classify precision of SAM base on the analyze of field spectrum. The test area located in Heqing Yunnan was imaged by EO_1 Hyperion imaging spectrometer using 224 bands in visual and near infrared. The area included limestone areas, rock fields, soil and forests. The area was classified into four different vegetation and soil types. The results show that this method choose the appropriate threshold of SAM and eliminates the disturbance and influence of unwanted objects effectively, so as to improve the classification precision. Compared with the likelihood classification by field survey data, the classification precision of this model heightens 9.9%.

Assimilation of remote sensing data into a process-based ecosystem model for monitoring changes of soil water content in croplands

NASA Astrophysics Data System (ADS)

Ju, Weimin; Gao, Ping; Wang, Jun; Li, Xianfeng; Chen, Shu

2008-10-01

Soil water content (SWC) is an important factor affecting photosynthesis, growth, and final yields of crops. The information on SWC is of importance for mitigating the reduction of crop yields caused by drought through proper agricultural water management. A variety of methodologies have been developed to estimate SWC at local and regional scales, including field sampling, remote sensing monitoring and model simulations. The reliability of regional SWC simulation depends largely on the accuracy of spatial input datasets, including vegetation parameters, soil and meteorological data. Remote sensing has been proved to be an effective technique for controlling uncertainties in vegetation parameters. In this study, the vegetation parameters (leaf area index and land cover type) derived from the Moderate Resolution Imaging Spectrometer (MODIS) were assimilated into a process-based ecosystem model BEPS for simulating the variations of SWC in croplands of Jiangsu province, China. Validation shows that the BEPS model is able to capture 81% and 83% of across-site variations of SWC at 10 and 20 cm depths during the period from September to December, 2006 when a serous autumn drought occurred. The simulated SWC responded the events of rainfall well at regional scale, demonstrating the usefulness of our methodology for SWC and practical agricultural water management at large scales.

A wireless batteryless in vivo EKG and core body temperature sensing microsystem with 60 Hz suppression technique for untethered genetically engineered mice real-time monitoring.

PubMed

Chaimanonart, Nattapon; Young, Darrin J

2009-01-01

A wireless, batteryless, and implantable EKG and core body temperature sensing microsystem with adaptive RF powering for untethered genetically engineered mice real-time monitoring is designed, implemented, and in vivo characterized. A packaged microsystem, exhibiting a total size of 9 mm x 7 mm x 3 mm with a weight of 400 mg including a pair of stainless-steel EKG electrodes, is implanted in a mouse abdomen for real-time monitoring. A low power 2 mm x 2 mm ASIC, consisting of an EKG amplifier, a proportional-to-absolute-temperature (PTAT)-based temperature sensor, an RF power sensing circuit, an RF-DC power converter, an 8-bit ADC, digital control circuitry, and a 433 MHz FSK transmitter, is powered by an adaptively controlled external RF energy source at 4 MHz to ensure a stable 2V supply with 156microA current driving capability for the overall microsystem. An electrical model for analyzing 60 Hz interference based on 2-electrode and 3-electrode configurations is proposed and compared with in vivo evaluation results. Due to the small laboratory animal chest area, a 60 Hz suppression technique by employing input termination resistors is chosen for two-EKG-electrode implant configuration.

Towards a Near Real-Time Satellite-Based Flux Monitoring System for the MENA Region

NASA Astrophysics Data System (ADS)

Ershadi, A.; Houborg, R.; McCabe, M. F.; Anderson, M. C.; Hain, C.

2013-12-01

Satellite remote sensing has the potential to offer spatially and temporally distributed information on land surface characteristics, which may be used as inputs and constraints for estimating land surface fluxes of carbon, water and energy. Enhanced satellite-based monitoring systems for aiding local water resource assessments and agricultural management activities are particularly needed for the Middle East and North Africa (MENA) region. The MENA region is an area characterized by limited fresh water resources, an often inefficient use of these, and relatively poor in-situ monitoring as a result of sparse meteorological observations. To address these issues, an integrated modeling approach for near real-time monitoring of land surface states and fluxes at fine spatio-temporal scales over the MENA region is presented. This approach is based on synergistic application of multiple sensors and wavebands in the visible to shortwave infrared and thermal infrared (TIR) domain. The multi-scale flux mapping and monitoring system uses the Atmosphere-Land Exchange Inverse (ALEXI) model and associated flux disaggregation scheme (DisALEXI), and the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) in conjunction with model reanalysis data and multi-sensor remotely sensed data from polar orbiting (e.g. Landsat and MODerate resolution Imaging Spectroradiometer (MODIS)) and geostationary (MSG; Meteosat Second Generation) satellite platforms to facilitate time-continuous (i.e. daily) estimates of field-scale water, energy and carbon fluxes. Within this modeling system, TIR satellite data provide information about the sub-surface moisture status and plant stress, obviating the need for precipitation input and a detailed soil surface characterization (i.e. for prognostic modeling of soil transport processes). The STARFM fusion methodology blends aspects of high frequency (spatially coarse) and spatially fine resolution sensors and is applied directly to flux output fields to facilitate daily mapping of fluxes at sub-field scales. A complete processing infrastructure to automatically ingest and pre-process all required input data and to execute the integrated modeling system for near real-time agricultural monitoring purposes over targeted MENA sites is being developed, and initial results from this concerted effort will be discussed.

Feature selection for elderly faller classification based on wearable sensors.

PubMed

Howcroft, Jennifer; Kofman, Jonathan; Lemaire, Edward D

2017-05-30

Wearable sensors can be used to derive numerous gait pattern features for elderly fall risk and faller classification; however, an appropriate feature set is required to avoid high computational costs and the inclusion of irrelevant features. The objectives of this study were to identify and evaluate smaller feature sets for faller classification from large feature sets derived from wearable accelerometer and pressure-sensing insole gait data. A convenience sample of 100 older adults (75.5 ± 6.7 years; 76 non-fallers, 24 fallers based on 6 month retrospective fall occurrence) walked 7.62 m while wearing pressure-sensing insoles and tri-axial accelerometers at the head, pelvis, left and right shanks. Feature selection was performed using correlation-based feature selection (CFS), fast correlation based filter (FCBF), and Relief-F algorithms. Faller classification was performed using multi-layer perceptron neural network, naïve Bayesian, and support vector machine classifiers, with 75:25 single stratified holdout and repeated random sampling. The best performing model was a support vector machine with 78% accuracy, 26% sensitivity, 95% specificity, 0.36 F1 score, and 0.31 MCC and one posterior pelvis accelerometer input feature (left acceleration standard deviation). The second best model achieved better sensitivity (44%) and used a support vector machine with 74% accuracy, 83% specificity, 0.44 F1 score, and 0.29 MCC. This model had ten input features: maximum, mean and standard deviation posterior acceleration; maximum, mean and standard deviation anterior acceleration; mean superior acceleration; and three impulse features. The best multi-sensor model sensitivity (56%) was achieved using posterior pelvis and both shank accelerometers and a naïve Bayesian classifier. The best single-sensor model sensitivity (41%) was achieved using the posterior pelvis accelerometer and a naïve Bayesian classifier. Feature selection provided models with smaller feature sets and improved faller classification compared to faller classification without feature selection. CFS and FCBF provided the best feature subset (one posterior pelvis accelerometer feature) for faller classification. However, better sensitivity was achieved by the second best model based on a Relief-F feature subset with three pressure-sensing insole features and seven head accelerometer features. Feature selection should be considered as an important step in faller classification using wearable sensors.

Super-resolution algorithm based on sparse representation and wavelet preprocessing for remote sensing imagery

NASA Astrophysics Data System (ADS)

Ren, Ruizhi; Gu, Lingjia; Fu, Haoyang; Sun, Chenglin

2017-04-01

An effective super-resolution (SR) algorithm is proposed for actual spectral remote sensing images based on sparse representation and wavelet preprocessing. The proposed SR algorithm mainly consists of dictionary training and image reconstruction. Wavelet preprocessing is used to establish four subbands, i.e., low frequency, horizontal, vertical, and diagonal high frequency, for an input image. As compared to the traditional approaches involving the direct training of image patches, the proposed approach focuses on the training of features derived from these four subbands. The proposed algorithm is verified using different spectral remote sensing images, e.g., moderate-resolution imaging spectroradiometer (MODIS) images with different bands, and the latest Chinese Jilin-1 satellite images with high spatial resolution. According to the visual experimental results obtained from the MODIS remote sensing data, the SR images using the proposed SR algorithm are superior to those using a conventional bicubic interpolation algorithm or traditional SR algorithms without preprocessing. Fusion algorithms, e.g., standard intensity-hue-saturation, principal component analysis, wavelet transform, and the proposed SR algorithms are utilized to merge the multispectral and panchromatic images acquired by the Jilin-1 satellite. The effectiveness of the proposed SR algorithm is assessed by parameters such as peak signal-to-noise ratio, structural similarity index, correlation coefficient, root-mean-square error, relative dimensionless global error in synthesis, relative average spectral error, spectral angle mapper, and the quality index Q4, and its performance is better than that of the standard image fusion algorithms.

Non-contact capacitance based image sensing method and system

DOEpatents

Novak, J.L.; Wiczer, J.J.

1994-01-25

A system and a method for imaging desired surfaces of a workpiece is described. A sensor having first and second sensing electrodes which are electrically isolated from the workpiece is positioned above and in proximity to the desired surfaces of the workpiece. An electric field is developed between the first and second sensing electrodes of the sensor in response to input signals being applied thereto and capacitance signals are developed which are indicative of any disturbances in the electric field as a result of the workpiece. An image signal of the workpiece may be developed by processing the capacitance signals. The image signals may provide necessary control information to a machining device for machining the desired surfaces of the workpiece in processes such as deburring or chamfering. Also, the method and system may be used to image dimensions of weld pools on a workpiece and surfaces of glass vials. The sensor may include first and second preview sensors used to determine the feed rate of a workpiece with respect to the machining device. 18 figures.

Non-contact capacitance based image sensing method and system

DOEpatents

Novak, J.L.; Wiczer, J.J.

1995-01-03

A system and a method is provided for imaging desired surfaces of a workpiece. A sensor having first and second sensing electrodes which are electrically isolated from the workpiece is positioned above and in proximity to the desired surfaces of the workpiece. An electric field is developed between the first and second sensing electrodes of the sensor in response to input signals being applied thereto and capacitance signals are developed which are indicative of any disturbances in the electric field as a result of the workpiece. An image signal of the workpiece may be developed by processing the capacitance signals. The image signals may provide necessary control information to a machining device for machining the desired surfaces of the workpiece in processes such as deburring or chamfering. Also, the method and system may be used to image dimensions of weld pools on a workpiece and surfaces of glass vials. The sensor may include first and second preview sensors used to determine the feed rate of a workpiece with respect to the machining device. 18 figures.

The role of remotely sensed and other spatial data for predictive modeling: the Umatilla, Oregon example

USGS Publications Warehouse

Loveland, Thomas R.; Johnson, Gary E.

1981-01-01

The U. S. Geological Survey's Earth Resources Observations Systems Data Center, in cooperation with the U.S. Army Corps of Engineers, Portland District, developed and tested techniques that used remotely sensed and other spatial data in predictive models to evaluate irrigation agriculture in the Umatilla River Basin of north-central Oregon. Landsat data and 1:24,000-scale aerial photographs were initially used to map he expansion of irrigate from 1973 to 1979 and to identify crops under irrigation in 1979. The crop data were then used with historical water requirement figures and digital topographic and hydrographic data to estimate water and power use for the 1979 irrigation season. The final project task involved production of a composite map of land suitability for irrigation development based on land cover (from Landsat), land-ownership, soil irrigability, slope gradient, and potential energy costs. The methods and data used in the study demonstrated the flexibility of remotely sensed and other spatial data as input for predictive models. When combined, they provided useful answers to complex questions facing resource managers.

Controllers for Battery Chargers and Battery Chargers Therefrom

NASA Technical Reports Server (NTRS)

Elmes, John (Inventor); Kersten, Rene (Inventor); Pepper, Michael (Inventor)

2014-01-01

A controller for a battery charger that includes a power converter has parametric sensors for providing a sensed Vin signal, a sensed Vout signal and a sensed Iout signal. A battery current regulator (BCR) is coupled to receive the sensed Iout signal and an Iout reference, and outputs a first duty cycle control signal. An input voltage regulator (IVR) receives the sensed Vin signal and a Vin reference. The IVR provides a second duty cycle control signal. A processor receives the sensed Iout signal and utilizes a Maximum Power Point Tracking (MPPT) algorithm, and provides the Vin reference to the IVR. A selection block forwards one of the first and second duty cycle control signals as a duty cycle control signal to the power converter. Dynamic switching between the first and second duty cycle control signals maximizes the power delivered to the battery.

Room-temperature quantum noise limited spectrometry and methods of the same

DOEpatents

Stevens, Charles G.; Tringe, Joseph W.; Cunningham, Christopher Thomas

2014-08-26

In one embodiment, a heterodyne detection system for detecting light includes a first input aperture adapted for receiving first light from a scene input, a second input aperture adapted for receiving second light from a local oscillator input, a broadband local oscillator adapted for providing the second light to the second input aperture, a dispersive element adapted for dispersing the first light and the second light, and a final condensing lens coupled to an infrared detector. The final condensing lens is adapted for concentrating incident light from a primary condensing lens onto the infrared detector, and the infrared detector is a square-law detector capable of sensing the frequency difference between the first light and the second light. More systems and methods for detecting light are described according to other embodiments.

Room-temperature quantum noise limited spectrometry and methods of the same

DOEpatents

Stevens, Charles G; Tringe, Joseph W

2014-12-02

In one embodiment, a heterodyne detection system for detecting light includes a first input aperture adapted for receiving a first light from a scene input, a second input aperture adapted for receiving a second light from a local oscillator input, a broadband local oscillator adapted for providing the second light to the second input aperture, a dispersive element adapted for dispersing the first light and the second light, and a final condensing lens coupled to an infrared detector. The final condensing lens is adapted for concentrating incident light from a primary condensing lens onto the detector, and the detector is a square-law detector capable of sensing the frequency difference between the first light and the second light. More systems and methods for detecting light are disclosed according to more embodiments.

Room-temperature quantum noise limited spectrometry and methods of the same

DOEpatents

Stevens, Charles G.; Tringe, Joseph W.; Cunningham, Christopher T.

2016-08-02

In one embodiment, a heterodyne detection system for detecting light includes a first input aperture configured to receive first light from a scene input, a second input aperture configured to receive second light from a local oscillator input, a broadband local oscillator configured to provide the second light to the second input aperture, a dispersive element configured to disperse the first light and the second light, and a final condensing lens coupled to an infrared detector. The final condensing lens is configured to concentrate incident light from a primary condensing lens onto the infrared detector, and the infrared detector is a square-law detector capable of sensing the frequency difference between the first light and the second light. More systems and methods for detecting light are described according to other embodiments.

Application of Terrestrial Microwave Remote Sensing to Agricultural Drought Monitoring

NASA Astrophysics Data System (ADS)

Crow, W. T.; Bolten, J. D.

2014-12-01

Root-zone soil moisture information is a valuable diagnostic for detecting the onset and severity of agricultural drought. Current attempts to globally monitor root-zone soil moisture are generally based on the application of soil water balance models driven by observed meteorological variables. Such systems, however, are prone to random error associated with: incorrect process model physics, poor parameter choices and noisy meteorological inputs. The presentation will describe attempts to remediate these sources of error via the assimilation of remotely-sensed surface soil moisture retrievals from satellite-based passive microwave sensors into a global soil water balance model. Results demonstrate the ability of satellite-based soil moisture retrieval products to significantly improve the global characterization of root-zone soil moisture - particularly in data-poor regions lacking adequate ground-based rain gage instrumentation. This success has lead to an on-going effort to implement an operational land data assimilation system at the United States Department of Agriculture's Foreign Agricultural Service (USDA FAS) to globally monitor variations in root-zone soil moisture availability via the integration of satellite-based precipitation and soil moisture information. Prospects for improving the performance of the USDA FAS system via the simultaneous assimilation of both passive and active-based soil moisture retrievals derived from the upcoming NASA Soil Moisture Active/Passive mission will also be discussed.

Random Predictor Models for Rigorous Uncertainty Quantification: Part 2

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Kenny, Sean P.; Giesy, Daniel P.

2015-01-01

This and a companion paper propose techniques for constructing parametric mathematical models describing key features of the distribution of an output variable given input-output data. By contrast to standard models, which yield a single output value at each value of the input, Random Predictors Models (RPMs) yield a random variable at each value of the input. Optimization-based strategies for calculating RPMs having a polynomial dependency on the input and a linear dependency on the parameters are proposed. These formulations yield RPMs having various levels of fidelity in which the mean, the variance, and the range of the model's parameter, thus of the output, are prescribed. As such they encompass all RPMs conforming to these prescriptions. The RPMs are optimal in the sense that they yield the tightest predictions for which all (or, depending on the formulation, most) of the observations are less than a fixed number of standard deviations from the mean prediction. When the data satisfies mild stochastic assumptions, and the optimization problem(s) used to calculate the RPM is convex (or, when its solution coincides with the solution to an auxiliary convex problem), the model's reliability, which is the probability that a future observation would be within the predicted ranges, is bounded rigorously.

Random Predictor Models for Rigorous Uncertainty Quantification: Part 1

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Kenny, Sean P.; Giesy, Daniel P.

2015-01-01

This and a companion paper propose techniques for constructing parametric mathematical models describing key features of the distribution of an output variable given input-output data. By contrast to standard models, which yield a single output value at each value of the input, Random Predictors Models (RPMs) yield a random variable at each value of the input. Optimization-based strategies for calculating RPMs having a polynomial dependency on the input and a linear dependency on the parameters are proposed. These formulations yield RPMs having various levels of fidelity in which the mean and the variance of the model's parameters, thus of the predicted output, are prescribed. As such they encompass all RPMs conforming to these prescriptions. The RPMs are optimal in the sense that they yield the tightest predictions for which all (or, depending on the formulation, most) of the observations are less than a fixed number of standard deviations from the mean prediction. When the data satisfies mild stochastic assumptions, and the optimization problem(s) used to calculate the RPM is convex (or, when its solution coincides with the solution to an auxiliary convex problem), the model's reliability, which is the probability that a future observation would be within the predicted ranges, can be bounded tightly and rigorously.

Interval Predictor Models for Data with Measurement Uncertainty

NASA Technical Reports Server (NTRS)

Lacerda, Marcio J.; Crespo, Luis G.

2017-01-01

An interval predictor model (IPM) is a computational model that predicts the range of an output variable given input-output data. This paper proposes strategies for constructing IPMs based on semidefinite programming and sum of squares (SOS). The models are optimal in the sense that they yield an interval valued function of minimal spread containing all the observations. Two different scenarios are considered. The first one is applicable to situations where the data is measured precisely whereas the second one is applicable to data subject to known biases and measurement error. In the latter case, the IPMs are designed to fully contain regions in the input-output space where the data is expected to fall. Moreover, we propose a strategy for reducing the computational cost associated with generating IPMs as well as means to simulate them. Numerical examples illustrate the usage and performance of the proposed formulations.

Attofarad resolution potentiostat for electrochemical measurements on nanoscale biomolecular interfacial systems.

PubMed

Carminati, Marco; Ferrari, Giorgio; Sampietro, Marco

2009-12-01

We present an instrument that enables electrochemical measurements (cyclic voltammetry, impedance tracking, and impedance spectroscopy) on submicrometric samples. The system features a frequency range from dc to 1 MHz and a current resolution of 10 fA for a measurement time of 1 s, giving a sensitivity of few attofarads in terms of measurable capacitance with an applied voltage of only 100 mV. These performances are obtained using a low-noise wide-bandwidth integrator/differentiator stage to sense the input current and a modular approach to minimize the effect of input stray capacitances. A digitally implemented lock-in filter optimally extracts the impedance of the sample, providing time tracking and spectroscopy operating modes. This computer-based and flexible instrument is well suited for characterizing and tracking the electrical properties of biomolecules kept in the physiological solution down to the nanoscale.

The global view: issues affecting US production agriculture.

PubMed

Goldsmith, Peter

2010-07-01

This paper discusses small events occurring among developing countries, particularly but not exclusively in Asia, and their subsequent large impacts on net food exporting countries in the world, particularly, but not exclusively, located in the Western hemisphere. A Green Revolution II is underway as a result where the world's agricultural system will produce more (output) with less (inputs). Agriculture will meet the rapidly growing demand for bio-based foods, fuels, feeds, and fiber while reducing input usage, preserving the natural environment, and maintaining native ecosystems. In turn agricultural workers will receive a health dividend as chemical usage falls, automation, metering, and sensing technologies rise, and exposure to harsh environmental, both natural and man-made, conditions is reduced. This paper was prepared for the Agricultural Safety and Health Council of America/National Institute for Occupational Safety and Health Conference, "Be Safe, Be Profitable: Protecting Workers in Agriculture," January 27-28, 2010, Dallas/Fort Worth, Texas.

Pseudo-Hall Effect in Graphite on Paper Based Four Terminal Devices for Stress Sensing Applications

NASA Astrophysics Data System (ADS)

Qamar, Afzaal; Sarwar, Tuba; Dinh, Toan; Foisal, A. R. M.; Phan, Hoang-Phuong; Viet Dao, Dzung

2017-04-01

A cost effective and easy to fabricate stress sensor based on pseudo-Hall effect in Graphite on Paper (GOP) has been presented in this article. The four terminal devices were developed by pencil drawing with hand on to the paper substrate. The stress was applied to the paper containing four terminal devices with the input current applied at two terminals and the offset voltage observed at other two terminals called pseudo-Hall effect. The GOP stress sensor showed significant response to the applied stress which was smooth and linear. These results showed that the pseudo-Hall effect in GOP based four terminal devices can be used for cost effective, flexible and easy to make stress, strain or force sensors.

Soil Erosion map of Europe based on high resolution input datasets

NASA Astrophysics Data System (ADS)

Panagos, Panos; Borrelli, Pasquale; Meusburger, Katrin; Ballabio, Cristiano; Alewell, Christine

2015-04-01

Modelling soil erosion in European Union is of major importance for agro-environmental policies. Soil erosion estimates are important inputs for the Common Agricultural Policy (CAP) and the implementation of the Soil Thematic Strategy. Using the findings of a recent pan-European data collection through the EIONET network, it was concluded that most Member States are applying the empirical Revised Universal Soil Loss Equation (RUSLE) for the modelling soil erosion at National level. This model was chosen for the pan-European soil erosion risk assessment and it is based on 6 input factors. Compared to past approaches, each of the factors is modelled using the latest pan-European datasets, expertise and data from Member states and high resolution remote sensing data. The soil erodibility (K-factor) is modelled using the recently published LUCAS topsoil database with 20,000 point measurements and incorporating the surface stone cover which can reduce K-factor by 15%. The rainfall erosivity dataset (R-factor) has been implemented using high temporal resolution rainfall data from more than 1,500 precipitation stations well distributed in Europe. The cover-management (C-factor) incorporates crop statistics and management practices such as cover crops, tillage practices and plant residuals. The slope length and steepness (combined LS-factor) is based on the first ever 25m Digital Elevation Model (DEM) of Europe. Finally, the support practices (P-factor) is modelled for first time at this scale taking into account the 270,000 LUCAS earth observations and the Good Agricultural and Environmental Condition (GAEC) that farmers have to follow in Europe. The high resolution input layers produce the final soil erosion risk map at 100m resolution and allow policy makers to run future land use, management and climate change scenarios.

Using aerial images for establishing a workflow for the quantification of water management measures

NASA Astrophysics Data System (ADS)

Leuschner, Annette; Merz, Christoph; van Gasselt, Stephan; Steidl, Jörg

2017-04-01

Quantified landscape characteristics, such as morphology, land use or hydrological conditions, play an important role for hydrological investigations as landscape parameters directly control the overall water balance. A powerful assimilation and geospatial analysis of remote sensing datasets in combination with hydrological modeling allows to quantify landscape parameters and water balances efficiently. This study focuses on the development of a workflow to extract hydrologically relevant data from aerial image datasets and derived products in order to allow an effective parametrization of a hydrological model. Consistent and self-contained data source are indispensable for achieving reasonable modeling results. In order to minimize uncertainties and inconsistencies, input parameters for modeling should be extracted from one remote-sensing dataset mainly if possbile. Here, aerial images have been chosen because of their high spatial and spectral resolution that permits the extraction of various model relevant parameters, like morphology, land-use or artificial drainage-systems. The methodological repertoire to extract environmental parameters range from analyses of digital terrain models, multispectral classification and segmentation of land use distribution maps and mapping of artificial drainage-systems based on spectral and visual inspection. The workflow has been tested for a mesoscale catchment area which forms a characteristic hydrological system of a young moraine landscape located in the state of Brandenburg, Germany. These dataset were used as input-dataset for multi-temporal hydrological modelling of water balances to detect and quantify anthropogenic and meteorological impacts. ArcSWAT, as a GIS-implemented extension and graphical user input interface for the Soil Water Assessment Tool (SWAT) was chosen. The results of this modeling approach provide the basis for anticipating future development of the hydrological system, and regarding system changes for the adaption of water resource management decisions.

The Global Integrated Drought Monitoring and Prediction System (GIDMaPS): Overview and Capabilities

NASA Astrophysics Data System (ADS)

AghaKouchak, A.; Hao, Z.; Farahmand, A.; Nakhjiri, N.

2013-12-01

Development of reliable monitoring and prediction indices and tools are fundamental to drought preparedness and management. Motivated by the Global Drought Information Systems (GDIS) activities, this paper presents the Global Integrated Drought Monitoring and Prediction System (GIDMaPS) which provides near real-time drought information using both remote sensing observations and model simulations. The monthly data from the NASA Modern-Era Retrospective analysis for Research and Applications (MERRA-Land), North American Land Data Assimilation System (NLDAS), and remotely sensed precipitation data are used as input to GIDMaPS. Numerous indices have been developed for drought monitoring based on various indicator variables (e.g., precipitation, soil moisture, water storage). Defining droughts based on a single variable (e.g., precipitation, soil moisture or runoff) may not be sufficient for reliable risk assessment and decision making. GIDMaPS provides drought information based on multiple indices including Standardized Precipitation Index (SPI), Standardized Soil Moisture Index (SSI) and the Multivariate Standardized Drought Index (MSDI) which combines SPI and SSI probabilistically. In other words, MSDI incorporates the meteorological and agricultural drought conditions for overall characterization of droughts. The seasonal prediction component of GIDMaPS is based on a persistence model which requires historical data and near-past observations. The seasonal drought prediction component is based on two input data sets (MERRA and NLDAS) and three drought indicators (SPI, SSI and MSDI). The drought prediction model provides the empirical probability of drought for different severity levels. In this presentation, both monitoring and prediction components of GIDMaPS will be discussed, and the results from several major droughts including the 2013 Namibia, 2012-2013 United States, 2011-2012 Horn of Africa, and 2010 Amazon Droughts will be presented. The results indicate that GIDMaPS advances our drought monitoring and prediction capabilities through integration of multiple data and indicators.

Spatial Irrigation Management Using Remote Sensing Water Balance Modeling and Soil Water Content Monitoring

NASA Astrophysics Data System (ADS)

Barker, J. Burdette

Spatially informed irrigation management may improve the optimal use of water resources. Sub-field scale water balance modeling and measurement were studied in the context of irrigation management. A spatial remote-sensing-based evapotranspiration and soil water balance model was modified and validated for use in real-time irrigation management. The modeled ET compared well with eddy covariance data from eastern Nebraska. Placement and quantity of sub-field scale soil water content measurement locations was also studied. Variance reduction factor and temporal stability were used to analyze soil water content data from an eastern Nebraska field. No consistent predictor of soil water temporal stability patterns was identified. At least three monitoring locations were needed per irrigation management zone to adequately quantify the mean soil water content. The remote-sensing-based water balance model was used to manage irrigation in a field experiment. The research included an eastern Nebraska field in 2015 and 2016 and a western Nebraska field in 2016 for a total of 210 plot-years. The response of maize and soybean to irrigation using variations of the model were compared with responses from treatments using soil water content measurement and a rainfed treatment. The remote-sensing-based treatment prescribed more irrigation than the other treatments in all cases. Excessive modeled soil evaporation and insufficient drainage times were suspected causes of the model drift. Modifying evaporation and drainage reduced modeled soil water depletion error. None of the included response variables were significantly different between treatments in western Nebraska. In eastern Nebraska, treatment differences for maize and soybean included evapotranspiration and a combined variable including evapotranspiration and deep percolation. Both variables were greatest for the remote-sensing model when differences were found to be statistically significant. Differences in maize yield in 2015 were attributed to random error. Soybean yield was lowest for the remote-sensing-based treatment and greatest for rainfed, possibly because of overwatering and lodging. The model performed well considering that it did not include soil water content measurements during the season. Future work should improve the soil evaporation and drainage formulations, because of excessive precipitation and include aerial remote sensing imagery and soil water content measurement as model inputs.

Ultrasonic sensing of GMAW: Laser/EMAT defect detection system

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

Carlson, N.M.; Johnson, J.A.; Larsen, E.D.

1992-08-01

In-process ultrasonic sensing of welding allows detection of weld defects in real time. A noncontacting ultrasonic system is being developed to operate in a production environment. The principal components are a pulsed laser for ultrasound generation and an electromagnetic acoustic transducer (EMAT) for ultrasound reception. A PC-based data acquisition system determines the quality of the weld on a pass-by-pass basis. The laser/EMAT system interrogates the area in the weld volume where defects are most likely to occur. This area of interest is identified by computer calculations on a pass-by-pass basis using weld planning information provided by the off-line programmer. Themore » absence of a signal above the threshold level in the computer-calculated time interval indicates a disruption of the sound path by a defect. The ultrasonic sensor system then provides an input signal to the weld controller about the defect condition. 8 refs.« less

Quantitative Inspection of Remanence of Broken Wire Rope Based on Compressed Sensing.

PubMed

Zhang, Juwei; Tan, Xiaojiang

2016-08-25

Most traditional strong magnetic inspection equipment has disadvantages such as big excitation devices, high weight, low detection precision, and inconvenient operation. This paper presents the design of a giant magneto-resistance (GMR) sensor array collection system. The remanence signal is collected to acquire two-dimensional magnetic flux leakage (MFL) data on the surface of wire ropes. Through the use of compressed sensing wavelet filtering (CSWF), the image expression of wire ropes MFL on the surface was obtained. Then this was taken as the input of the designed back propagation (BP) neural network to extract three kinds of MFL image geometry features and seven invariant moments of defect images. Good results were obtained. The experimental results show that nondestructive inspection through the use of remanence has higher accuracy and reliability compared with traditional inspection devices, along with smaller volume, lighter weight and higher precision.

A Monolithic Electrochemical Micro Seismic Sensor Capable of Monitoring Three-Dimensional Vibrations

PubMed Central

Chen, Lianhong; Sun, Zhenyuan; Li, Guanglei; Chen, Deyong; Wang, Junbo

2018-01-01

A monolithic electrochemical micro seismic sensor capable of monitoring three-axial vibrations was proposed in this paper. The proposed micro sensor mainly consisted of four sensing units interconnected within flow channels and by interpreting the voltage outputs of the sensing units, vibrations with arbitrary directions can be quantified. The proposed seismic sensors are fabricated based on MEMS technologies and characterized, which produced sensitivities along x, y, and z axes as 2473.2 ± 184.5 V/(m/s), 2261.7 ± 119.6 V/(m/s), and 3480.7 ± 417.2 V/(m/s) at 30 Hz. In addition, the vibrations in x-y, x-z, and y-z planes were applied to the developed seismic sensors, leading to comparable monitoring results after decoupling calculations with the input velocities. Furthermore, the results have shown its feasibilities for seismic data recording. PMID:29614720

Quantitative Inspection of Remanence of Broken Wire Rope Based on Compressed Sensing

PubMed Central

Zhang, Juwei; Tan, Xiaojiang

2016-01-01

Most traditional strong magnetic inspection equipment has disadvantages such as big excitation devices, high weight, low detection precision, and inconvenient operation. This paper presents the design of a giant magneto-resistance (GMR) sensor array collection system. The remanence signal is collected to acquire two-dimensional magnetic flux leakage (MFL) data on the surface of wire ropes. Through the use of compressed sensing wavelet filtering (CSWF), the image expression of wire ropes MFL on the surface was obtained. Then this was taken as the input of the designed back propagation (BP) neural network to extract three kinds of MFL image geometry features and seven invariant moments of defect images. Good results were obtained. The experimental results show that nondestructive inspection through the use of remanence has higher accuracy and reliability compared with traditional inspection devices, along with smaller volume, lighter weight and higher precision. PMID:27571077

Focused sunlight factor of forest fire danger assessment using Web-GIS and RS technologies

NASA Astrophysics Data System (ADS)

Baranovskiy, Nikolay V.; Sherstnyov, Vladislav S.; Yankovich, Elena P.; Engel, Marina V.; Belov, Vladimir V.

2016-08-01

Timiryazevskiy forestry of Tomsk region (Siberia, Russia) is a study area elaborated in current research. Forest fire danger assessment is based on unique technology using probabilistic criterion, statistical data on forest fires, meteorological conditions, forest sites classification and remote sensing data. MODIS products are used for estimating some meteorological conditions and current forest fire situation. Geonformation technologies are used for geospatial analysis of forest fire danger situation on controlled forested territories. GIS-engine provides opportunities to construct electronic maps with different levels of forest fire probability and support raster layer for satellite remote sensing data on current forest fires. Web-interface is used for data loading on specific web-site and for forest fire danger data representation via World Wide Web. Special web-forms provide interface for choosing of relevant input data in order to process the forest fire danger data and assess the forest fire probability.

University/industry collaboration in remote sensing education

NASA Technical Reports Server (NTRS)

Ragan, R. M.; Royal, J. A.

1981-01-01

A graduate level course covering the development and structure of geographical information systems and the acquisition and processing of LANDSAT data for input to these systems is described. A portion of the course was devoted to hands-on classification of LANDSAT digital tapes utilizing both university and private industry processing systems. This industry/university collaboration was extremely successful and resulted in a high quality course. It gave the students an excellent experience in working in a real-world client/consultant relationship undertaken to accomplish a specific task. There were two key factors in the success of the collaboration. First, there was a very careful product definition and advance meetings between the University faculty and the company personnel to be involved. Second, the students were not taken into the industrial facility until late in the course, after they had a reasonable knowledge of the physical bases of remote sensing, the concept of spectral signatures, and the fundamentals of pattern analysis.

Displacement sensing system and method

DOEpatents

VunKannon, Jr., Robert S

2006-08-08

A displacement sensing system and method addresses demanding requirements for high precision sensing of displacement of a shaft, for use typically in a linear electro-dynamic machine, having low failure rates over multi-year unattended operation in hostile environments. Applications include outer space travel by spacecraft having high-temperature, sealed environments without opportunity for servicing over many years of operation. The displacement sensing system uses a three coil sensor configuration, including a reference and sense coils, to provide a pair of ratio-metric signals, which are inputted into a synchronous comparison circuit, which is synchronously processed for a resultant displacement determination. The pair of ratio-metric signals are similarly affected by environmental conditions so that the comparison circuit is able to subtract or nullify environmental conditions that would otherwise cause changes in accuracy to occur.

Advances in soil erosion modelling through remote sensing data availability at European scale

NASA Astrophysics Data System (ADS)

Panagos, Panos; Karydas, Christos; Borrelli, Pasqualle; Ballabio, Cristiano; Meusburger, Katrin

2014-08-01

Under the European Union's Thematic Strategy for Soil Protection, the European Commission's Directorate-General for the Environment (DG Environment) has identified the mitigation of soil losses by erosion as a priority area. Policy makers call for an overall assessment of soil erosion in their geographical area of interest. They have asked that risk areas for soil erosion be mapped under present land use and climate conditions, and that appropriate measures be taken to control erosion within the legal and social context of natural resource management. Remote sensing data help to better assessment of factors that control erosion, such as vegetation coverage, slope length and slope angle. In this context, the data availability of remote sensing data during the past decade facilitates the more precise estimation of soil erosion risk. Following the principles of the Universal Soil Loss Equation (USLE), various options to calculate vegetative cover management (C-factor) have been investigated. The use of the CORINE Land Cover dataset in combination with lookup table values taken from the literature is presented as an option that has the advantage of a coherent input dataset but with the drawback of static input. Recent developments in the Copernicus programme have made detailed datasets available on land cover, leaf area index and base soil characteristics. These dynamic datasets allow for seasonal estimates of vegetation coverage, and their application in the G2 soil erosion model which represents a recent approach to the seasonal monitoring of soil erosion. The use of phenological datasets and the LUCAS land use/cover survey are proposed as auxiliary information in the selection of the best methodology.

Development of an extended Kalman filter for the self-sensing application of a spring-biased shape memory alloy wire actuator

NASA Astrophysics Data System (ADS)

Gurung, H.; Banerjee, A.

2016-02-01

This report presents the development of an extended Kalman filter (EKF) to harness the self-sensing capability of a shape memory alloy (SMA) wire, actuating a linear spring. The stress and temperature of the SMA wire, constituting the state of the system, are estimated using the EKF, from the measured change in electrical resistance (ER) of the SMA. The estimated stress is used to compute the change in length of the spring, eliminating the need for a displacement sensor. The system model used in the EKF comprises the heat balance equation and the constitutive relation of the SMA wire coupled with the force-displacement behavior of a spring. Both explicit and implicit approaches are adopted to evaluate the system model at each time-update step of the EKF. Next, in the measurement-update step, estimated states are updated based on the measured electrical resistance. It has been observed that for the same time step, the implicit approach consumes less computational time than the explicit method. To verify the implementation, EKF estimated states of the system are compared with those of an established model for different inputs to the SMA wire. An experimental setup is developed to measure the actual spring displacement and ER of the SMA, for any time-varying voltage applied to it. The process noise covariance is decided using a heuristic approach, whereas the measurement noise covariance is obtained experimentally. Finally, the EKF is used to estimate the spring displacement for a given input and the corresponding experimentally obtained ER of the SMA. The qualitative agreement between the EKF estimated displacement with that obtained experimentally reveals the true potential of this approach to harness the self-sensing capability of the SMA.

Modelling Hydrologic Processes in the Mekong River Basin Using a Distributed Model Driven by Satellite Precipitation and Rain Gauge Observations

PubMed Central

Wang, Wei; Lu, Hui; Yang, Dawen; Sothea, Khem; Jiao, Yang; Gao, Bin; Peng, Xueting; Pang, Zhiguo

2016-01-01

The Mekong River is the most important river in Southeast Asia. It has increasingly suffered from water-related problems due to economic development, population growth and climate change in the surrounding areas. In this study, we built a distributed Geomorphology-Based Hydrological Model (GBHM) of the Mekong River using remote sensing data and other publicly available data. Two numerical experiments were conducted using different rainfall data sets as model inputs. The data sets included rain gauge data from the Mekong River Commission (MRC) and remote sensing rainfall data from the Tropic Rainfall Measurement Mission (TRMM 3B42V7). Model calibration and validation were conducted for the two rainfall data sets. Compared to the observed discharge, both the gauge simulation and TRMM simulation performed well during the calibration period (1998–2001). However, the performance of the gauge simulation was worse than that of the TRMM simulation during the validation period (2002–2012). The TRMM simulation is more stable and reliable at different scales. Moreover, the calibration period was changed to 2, 4, and 8 years to test the impact of the calibration period length on the two simulations. The results suggest that longer calibration periods improved the GBHM performance during validation periods. In addition, the TRMM simulation is more stable and less sensitive to the calibration period length than is the gauge simulation. Further analysis reveals that the uneven distribution of rain gauges makes the input rainfall data less representative and more heterogeneous, worsening the simulation performance. Our results indicate that remotely sensed rainfall data may be more suitable for driving distributed hydrologic models, especially in basins with poor data quality or limited gauge availability. PMID:27010692

Modelling Hydrologic Processes in the Mekong River Basin Using a Distributed Model Driven by Satellite Precipitation and Rain Gauge Observations.

PubMed

Wang, Wei; Lu, Hui; Yang, Dawen; Sothea, Khem; Jiao, Yang; Gao, Bin; Peng, Xueting; Pang, Zhiguo

2016-01-01

The Mekong River is the most important river in Southeast Asia. It has increasingly suffered from water-related problems due to economic development, population growth and climate change in the surrounding areas. In this study, we built a distributed Geomorphology-Based Hydrological Model (GBHM) of the Mekong River using remote sensing data and other publicly available data. Two numerical experiments were conducted using different rainfall data sets as model inputs. The data sets included rain gauge data from the Mekong River Commission (MRC) and remote sensing rainfall data from the Tropic Rainfall Measurement Mission (TRMM 3B42V7). Model calibration and validation were conducted for the two rainfall data sets. Compared to the observed discharge, both the gauge simulation and TRMM simulation performed well during the calibration period (1998-2001). However, the performance of the gauge simulation was worse than that of the TRMM simulation during the validation period (2002-2012). The TRMM simulation is more stable and reliable at different scales. Moreover, the calibration period was changed to 2, 4, and 8 years to test the impact of the calibration period length on the two simulations. The results suggest that longer calibration periods improved the GBHM performance during validation periods. In addition, the TRMM simulation is more stable and less sensitive to the calibration period length than is the gauge simulation. Further analysis reveals that the uneven distribution of rain gauges makes the input rainfall data less representative and more heterogeneous, worsening the simulation performance. Our results indicate that remotely sensed rainfall data may be more suitable for driving distributed hydrologic models, especially in basins with poor data quality or limited gauge availability.

Expansion of Smartwatch Touch Interface from Touchscreen to Around Device Interface Using Infrared Line Image Sensors

PubMed Central

Lim, Soo-Chul; Shin, Jungsoon; Kim, Seung-Chan; Park, Joonah

2015-01-01

Touchscreen interaction has become a fundamental means of controlling mobile phones and smartwatches. However, the small form factor of a smartwatch limits the available interactive surface area. To overcome this limitation, we propose the expansion of the touch region of the screen to the back of the user’s hand. We developed a touch module for sensing the touched finger position on the back of the hand using infrared (IR) line image sensors, based on the calibrated IR intensity and the maximum intensity region of an IR array. For complete touch-sensing solution, a gyroscope installed in the smartwatch is used to read the wrist gestures. The gyroscope incorporates a dynamic time warping gesture recognition algorithm for eliminating unintended touch inputs during the free motion of the wrist while wearing the smartwatch. The prototype of the developed sensing module was implemented in a commercial smartwatch, and it was confirmed that the sensed positional information of the finger when it was used to touch the back of the hand could be used to control the smartwatch graphical user interface. Our system not only affords a novel experience for smartwatch users, but also provides a basis for developing other useful interfaces. PMID:26184202

Estimation of Transmittance of Solar Radiation in the Visible Domain Based on Remote Sensing: Evaluation of Models Using In Situ Data

NASA Astrophysics Data System (ADS)

Zoffoli, M. Laura; Lee, Zhongping; Ondrusek, Michael; Lin, Junfang; Kovach, Charles; Wei, Jianwei; Lewis, Marlon

2017-11-01

The transmittance of solar radiation in the oceanic water column plays an important role in heat transfer and photosynthesis, with implications for the global carbon cycle, global circulation, and climate. Globally, the transmittance of solar radiation in the visible domain (˜400-700 nm) (TRVIS) through the water column, which determines the vertical distribution of visible light, has to be based on remote sensing products. There are models centered on chlorophyll-a (Chl) concentration or Inherent Optical Properties (IOPs) as both can be derived from ocean color measurements. We present evaluations of both schemes with field data from clear oceanic and from coastal waters. Here five models were evaluated: (1) Morel and Antoine (1994) (MA94), (2) Ohlmann and Siegel (2000) (OS00), (3) Murtugudde et al. (2002) (MU02), (4) Manizza et al. (2005) (MA05), and (5) Lee et al. ([Lee, Z., 2005]) (IOPs05), where the first four are Chl-based and the last one is IOPs-based, with all inputs derived from remote sensing reflectance. It is found that the best performing model is the IOPs05, with Unbiased Absolute Percent Difference (UAPD) ˜23%, while Chl-based models show higher uncertainties (UAPD for MA94: ˜54%, OS00: ˜133%, MU02: ˜56%, and MA05: ˜39%). The IOPs-based model was insensitive to the type of water, allowing it to be applied in most marine environments; whereas some of the Chl-based models (MU02 and MA05) show much higher sensitivities in coastal turbid waters (higher Chl waters). These results highlight the applicablity of using IOPs products for such applications.

Remote sensing requirements as suggested by watershed model sensitivity analyses

NASA Technical Reports Server (NTRS)

Salomonson, V. V.; Rango, A.; Ormsby, J. P.; Ambaruch, R.

1975-01-01

A continuous simulation watershed model has been used to perform sensitivity analyses that provide guidance in defining remote sensing requirements for the monitoring of watershed features and processes. The results show that out of 26 input parameters having meaningful effects on simulated runoff, 6 appear to be obtainable with existing remote sensing techniques. Of these six parameters, 3 require the measurement of the areal extent of surface features (impervious areas, water bodies, and the extent of forested area), two require the descrimination of land use that can be related to overland flow roughness coefficient or the density of vegetation so as to estimate the magnitude of precipitation interception, and one parameter requires the measurement of distance to get the length over which overland flow typically occurs. Observational goals are also suggested for monitoring such fundamental watershed processes as precipitation, soil moisture, and evapotranspiration. A case study on the Patuxent River in Maryland shows that runoff simulation is improved if recent satellite land use observations are used as model inputs as opposed to less timely topographic map information.

Some Insights of Spectral Optimization in Ocean Color Inversion

NASA Technical Reports Server (NTRS)

Lee, Zhongping; Franz, Bryan; Shang, Shaoling; Dong, Qiang; Arnone, Robert

2011-01-01

In the past decades various algorithms have been developed for the retrieval of water constituents from the measurement of ocean color radiometry, and one of the approaches is spectral optimization. This approach defines an error target (or error function) between the input remote sensing reflectance and the output remote sensing reflectance, with the latter modeled with a few variables that represent the optically active properties (such as the absorption coefficient of phytoplankton and the backscattering coefficient of particles). The values of the variables when the error reach a minimum (optimization is achieved) are considered the properties that form the input remote sensing reflectance; or in other words, the equations are solved numerically. The applications of this approach implicitly assume that the error is a monotonic function of the various variables. Here, with data from numerical simulation and field measurements, we show the shape of the error surface, in a way to justify the possibility of finding a solution of the various variables. In addition, because the spectral properties could be modeled differently, impacts of such differences on the error surface as well as on the retrievals are also presented.

A Novel Switching-Based Control Framework for Improved Task Performance in Teleoperation System With Asymmetric Time-Varying Delays.

PubMed

Zhai, Di-Hua; Xia, Yuanqing

2018-02-01

This paper addresses the adaptive control for task-space teleoperation systems with constrained predefined synchronization error, where a novel switched control framework is investigated. Based on multiple Lyapunov-Krasovskii functionals method, the stability of the resulting closed-loop system is established in the sense of state-independent input-to-output stability. Compared with previous work, the developed method can simultaneously handle the unknown kinematics/dynamics, asymmetric varying time delays, and prescribed performance control in a unified framework. It is shown that the developed controller can guarantee the prescribed transient-state and steady-state synchronization performances between the master and slave robots, which is demonstrated by the simulation study.

An evaluation of open set recognition for FLIR images

NASA Astrophysics Data System (ADS)

Scherreik, Matthew; Rigling, Brian

2015-05-01

Typical supervised classification algorithms label inputs according to what was learned in a training phase. Thus, test inputs that were not seen in training are always given incorrect labels. Open set recognition algorithms address this issue by accounting for inputs that are not present in training and providing the classifier with an option to reject" unknown samples. A number of such techniques have been developed in the literature, many of which are based on support vector machines (SVMs). One approach, the 1-vs-set machine, constructs a slab" in feature space using the SVM hyperplane. Inputs falling on one side of the slab or within the slab belong to a training class, while inputs falling on the far side of the slab are rejected. We note that rejection of unknown inputs can be achieved by thresholding class posterior probabilities. Another recently developed approach, the Probabilistic Open Set SVM (POS-SVM), empirically determines good probability thresholds. We apply the 1-vs-set machine, POS-SVM, and closed set SVMs to FLIR images taken from the Comanche SIG dataset. Vehicles in the dataset are divided into three general classes: wheeled, armored personnel carrier (APC), and tank. For each class, a coarse pose estimate (front, rear, left, right) is taken. In a closed set sense, we analyze these algorithms for prediction of vehicle class and pose. To test open set performance, one or more vehicle classes are held out from training. By considering closed and open set performance separately, we may closely analyze both inter-class discrimination and threshold effectiveness.

Sensing circuits for multiwire proportional chambers

NASA Technical Reports Server (NTRS)

Peterson, H. T.; Worley, E. R.

1977-01-01

Integrated sensing circuits were designed, fabricated, and packaged for use in determining the direction and fluence of ionizing radiation passing through a multiwire proportional chamber. CMOS on sapphire was selected because of its high speed and low power capabilities. The design of the proposed circuits is described and the results of computer simulations are presented. The fabrication processes for the CMOS on sapphire sensing circuits and hybrid substrates are outlined. Several design options are described and the cost implications of each discussed. To be most effective, each chip should handle not more than 32 inputs, and should be mounted on its own hybrid substrate.

Input filter compensation for switching regulators

NASA Technical Reports Server (NTRS)

Kelkar, S. S.; Lee, F. C.

1983-01-01

A novel input filter compensation scheme for a buck regulator that eliminates the interaction between the input filter output impedance and the regulator control loop is presented. The scheme is implemented using a feedforward loop that senses the input filter state variables and uses this information to modulate the duty cycle signal. The feedforward design process presented is seen to be straightforward and the feedforward easy to implement. Extensive experimental data supported by analytical results show that significant performance improvement is achieved with the use of feedforward in the following performance categories: loop stability, audiosusceptibility, output impedance and transient response. The use of feedforward results in isolating the switching regulator from its power source thus eliminating all interaction between the regulator and equipment upstream. In addition the use of feedforward removes some of the input filter design constraints and makes the input filter design process simpler thus making it possible to optimize the input filter. The concept of feedforward compensation can also be extended to other types of switching regulators.

Kinesthetic coupling between operator and remote manipulator

NASA Technical Reports Server (NTRS)

Bejczy, A. K.; Salisbury, J. K., Jr.

1980-01-01

A universal force-reflecting hand controller has been developed which allows the establishment of a kinesthetic coupling between the operator and a remote manipulator. The six-degree-of-freedom controller was designed to generate forces and torques on its three positional and three rotational axes in order to permit the operator to accurately feel the forces encountered by the manipulator and be as transparent to operate as possible. The universal controller has been used in an application involving a six-degree-of-freedom mechanical arm equipped with a six-dimensional force-torque sensor at its base. In this application, the hand controller acts as a position control input device to the arm, while forces and torques sensed at the base of the mechanical hand back drive the hand controller. The positional control relation and the back driving of the controller according to inputs experienced by the force-torque sensor are established through complex mathematical transformations performed by a minicomputer. The hand controller is intended as a development tool for investigating force-reflecting master-slave manipulator control technology.

Infant perceptual development for faces and spoken words: An integrated approach

PubMed Central

Watson, Tamara L; Robbins, Rachel A; Best, Catherine T

2014-01-01

There are obvious differences between recognizing faces and recognizing spoken words or phonemes that might suggest development of each capability requires different skills. Recognizing faces and perceiving spoken language, however, are in key senses extremely similar endeavors. Both perceptual processes are based on richly variable, yet highly structured input from which the perceiver needs to extract categorically meaningful information. This similarity could be reflected in the perceptual narrowing that occurs within the first year of life in both domains. We take the position that the perceptual and neurocognitive processes by which face and speech recognition develop are based on a set of common principles. One common principle is the importance of systematic variability in the input as a source of information rather than noise. Experience of this variability leads to perceptual tuning to the critical properties that define individual faces or spoken words versus their membership in larger groupings of people and their language communities. We argue that parallels can be drawn directly between the principles responsible for the development of face and spoken language perception. PMID:25132626

A simplified model of all-sky artificial sky glow derived from VIIRS Day/Night band data

NASA Astrophysics Data System (ADS)

Duriscoe, Dan M.; Anderson, Sharolyn J.; Luginbuhl, Christian B.; Baugh, Kimberly E.

2018-07-01

We present a simplified method using geographic analysis tools to predict the average artificial luminance over the hemisphere of the night sky, expressed as a ratio to the natural condition. The VIIRS Day/Night Band upward radiance data from the Suomi NPP orbiting satellite was used for input to the model. The method is based upon a relation between sky glow brightness and the distance from the observer to the source of upward radiance. This relationship was developed using a Garstang radiative transfer model with Day/Night Band data as input, then refined and calibrated with ground-based all-sky V-band photometric data taken under cloudless and low atmospheric aerosol conditions. An excellent correlation was found between observed sky quality and the predicted values from the remotely sensed data. Thematic maps of large regions of the earth showing predicted artificial V-band sky brightness may be quickly generated with modest computing resources. We have found a fast and accurate method based on previous work to model all-sky quality. We provide limitations to this method. The proposed model meets requirements needed by decision makers and land managers of an easy to interpret and understand metric of sky quality.

Design and development of an IoT-based web application for an intelligent remote SCADA system

NASA Astrophysics Data System (ADS)

Kao, Kuang-Chi; Chieng, Wei-Hua; Jeng, Shyr-Long

2018-03-01

This paper presents a design of an intelligent remote electrical power supervisory control and data acquisition (SCADA) system based on the Internet of Things (IoT), with Internet Information Services (IIS) for setting up web servers, an ASP.NET model-view- controller (MVC) for establishing a remote electrical power monitoring and control system by using responsive web design (RWD), and a Microsoft SQL Server as the database. With the web browser connected to the Internet, the sensing data is sent to the client by using the TCP/IP protocol, which supports mobile devices with different screen sizes. The users can provide instructions immediately without being present to check the conditions, which considerably reduces labor and time costs. The developed system incorporates a remote measuring function by using a wireless sensor network and utilizes a visual interface to make the human-machine interface (HMI) more instinctive. Moreover, it contains an analog input/output and a basic digital input/output that can be applied to a motor driver and an inverter for integration with a remote SCADA system based on IoT, and thus achieve efficient power management.

Building Extraction from Remote Sensing Data Using Fully Convolutional Networks

NASA Astrophysics Data System (ADS)

Bittner, K.; Cui, S.; Reinartz, P.

2017-05-01

Building detection and footprint extraction are highly demanded for many remote sensing applications. Though most previous works have shown promising results, the automatic extraction of building footprints still remains a nontrivial topic, especially in complex urban areas. Recently developed extensions of the CNN framework made it possible to perform dense pixel-wise classification of input images. Based on these abilities we propose a methodology, which automatically generates a full resolution binary building mask out of a Digital Surface Model (DSM) using a Fully Convolution Network (FCN) architecture. The advantage of using the depth information is that it provides geometrical silhouettes and allows a better separation of buildings from background as well as through its invariance to illumination and color variations. The proposed framework has mainly two steps. Firstly, the FCN is trained on a large set of patches consisting of normalized DSM (nDSM) as inputs and available ground truth building mask as target outputs. Secondly, the generated predictions from FCN are viewed as unary terms for a Fully connected Conditional Random Fields (FCRF), which enables us to create a final binary building mask. A series of experiments demonstrate that our methodology is able to extract accurate building footprints which are close to the buildings original shapes to a high degree. The quantitative and qualitative analysis show the significant improvements of the results in contrast to the multy-layer fully connected network from our previous work.

Frequency-Agile LIDAR Receiver for Chemical and Biological Agent Sensing

DTIC Science & Technology

2010-06-01

transimpedance preamplifier architecture was optimized around the selected IR detector diode – Input-referenced noise density of 0.8 nV/ Hz0.5  A portion of...objectives: • Reduce baseline (background) photon flux on detector : Tunable Fabry-Perot etalon in optical train • Reduce input-referenced amplifier noise ...custom amplifier • Reduce detector dark current: High impedance detector  Performance Metrics: – Noise equivalent power of receiver system (NEP

Borehole geological assessment

NASA Technical Reports Server (NTRS)

Spuck, W. H., III (Inventor)

1979-01-01

A method and apparatus are discussed for performing geological assessments of a formation located along a borehole, and a boring tool that bores a pair of holes into the walls of the borehole and into the surrounding strata along with a pair of probes which are installed in the holes. One of the probes applies an input such as a current or pressured fluid, and the other probe senses a corresponding input which it receives from the strata.

The relative degree enhancement problem for MIMO nonlinear systems

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

Schoenwald, D.A.; Oezguener, Ue.

1995-07-01

The authors present a result for linearizing a nonlinear MIMO system by employing partial feedback - feedback at all but one input-output channel such that the SISO feedback linearization problem is solvable at the remaining input-output channel. The partial feedback effectively enhances the relative degree at the open input-output channel provided the feedback functions are chosen to satisfy relative degree requirements. The method is useful for nonlinear systems that are not feedback linearizable in a MIMO sense. Several examples are presented to show how these feedback functions can be computed. This strategy can be combined with decentralized observers for amore » completely decentralized feedback linearization result for at least one input-output channel.« less

Linking Arctic plant biodiversity measurements with landscape heterogeneity

NASA Astrophysics Data System (ADS)

Gerber, F.; Schaepman-Strub, G.; Furrer, R.

2016-12-01

Climate warming in the Arctic region triggers changes in the vegetation productivity and species composition of the tundra. To investigate these changes and their feedback to climate, we consider species richness and abundance data of the International Tundra EXperiment (ITEX). As this information is very sparse in time and space, we aim to upscale available records to climatically relevant scales with a remote sensing based characterization of the study sites. More precisely, we relate species richness and evenness derived from the ITEX data to summary statistics describing the landscape heterogeneity, which are derived from an elevation model (ASTER GDEM) and spectral satellite observations (LANDSAT 5 and 7). Preliminary results from the statistical analysis using generalized linear mixed models show that no remote sensing based landscape characterization does significantly explain species richness. Reasons could be a mismatch of the spatial scales, an inappropriate characterization of the test sites through the satellite measurements, incomparable plot measurements from the different test sites and/or too few plot measurements. We are looking forward to presenting our results and getting your inputs.

Non-Destructive Detection of Wire Rope Discontinuities from Residual Magnetic Field Images Using the Hilbert-Huang Transform and Compressed Sensing

PubMed Central

Zhang, Juwei; Tan, Xiaojiang; Zheng, Pengbo

2017-01-01

Electromagnetic methods are commonly employed to detect wire rope discontinuities. However, determining the residual strength of wire rope based on the quantitative recognition of discontinuities remains problematic. We have designed a prototype device based on the residual magnetic field (RMF) of ferromagnetic materials, which overcomes the disadvantages associated with in-service inspections, such as large volume, inconvenient operation, low precision, and poor portability by providing a relatively small and lightweight device with improved detection precision. A novel filtering system consisting of the Hilbert-Huang transform and compressed sensing wavelet filtering is presented. Digital image processing was applied to achieve the localization and segmentation of defect RMF images. The statistical texture and invariant moment characteristics of the defect images were extracted as the input of a radial basis function neural network. Experimental results show that the RMF device can detect defects in various types of wire rope and prolong the service life of test equipment by reducing the friction between the detection device and the wire rope by accommodating a high lift-off distance. PMID:28300790

Langasite surface acoustic wave gas sensors: modeling and verification

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

Peng Zheng,; Greve, D. W.; Oppenheim, I. J.

2013-03-01

We report finite element simulations of the effect of conductive sensing layers on the surface wave velocity of langasite substrates. The simulations include both the mechanical and electrical influences of the conducting sensing layer. We show that three-dimensional simulations are necessary because of the out-of-plane displacements of the commonly used (0, 138.5, 26.7) Euler angle. Measurements of the transducer input admittance in reflective delay-line devices yield a value for the electromechanical coupling coefficient that is in good agreement with the three-dimensional simulations on bare langasite substrate. The input admittance measurements also show evidence of excitation of an additional wave modemore » and excess loss due to the finger resistance. The results of these simulations and measurements will be useful in the design of surface acoustic wave gas sensors.« less

Snowmelt-runoff Model Utilizing Remotely-sensed Data

NASA Technical Reports Server (NTRS)

Rango, A.

1985-01-01

Remotely sensed snow cover information is the critical data input for the Snowmelt-Runoff Model (SRM), which was developed to simulatke discharge from mountain basins where snowmelt is an important component of runoff. Of simple structure, the model requires only input of temperature, precipitation, and snow covered area. SRM was run successfully on two widely separated basins. The simulations on the Kings River basin are significant because of the large basin area (4000 sq km) and the adequate performance in the most extreme drought year of record (1976). The performance of SRM on the Okutadami River basin was important because it was accomplished with minimum snow cover data available. Tables show: optimum and minimum conditions for model application; basin sizes and elevations where SRM was applied; and SRM strengths and weaknesses. Graphs show results of discharge simulation.

Information fusion via isocortex-based Area 37 modeling

NASA Astrophysics Data System (ADS)

Peterson, James K.

2004-08-01

A simplified model of information processing in the brain can be constructed using primary sensory input from two modalities (auditory and visual) and recurrent connections to the limbic subsystem. Information fusion would then occur in Area 37 of the temporal cortex. The creation of meta concepts from the low order primary inputs is managed by models of isocortex processing. Isocortex algorithms are used to model parietal (auditory), occipital (visual), temporal (polymodal fusion) cortex and the limbic system. Each of these four modules is constructed out of five cortical stacks in which each stack consists of three vertically oriented six layer isocortex models. The input to output training of each cortical model uses the OCOS (on center - off surround) and FFP (folded feedback pathway) circuitry of (Grossberg, 1) which is inherently a recurrent network type of learning characterized by the identification of perceptual groups. Models of this sort are thus closely related to cognitive models as it is difficult to divorce the sensory processing subsystems from the higher level processing in the associative cortex. The overall software architecture presented is biologically based and is presented as a potential architectural prototype for the development of novel sensory fusion strategies. The algorithms are motivated to some degree by specific data from projects on musical composition and autonomous fine art painting programs, but only in the sense that these projects use two specific types of auditory and visual cortex data. Hence, the architectures are presented for an artificial information processing system which utilizes two disparate sensory sources. The exact nature of the two primary sensory input streams is irrelevant.

Fluidic self-actuating control assembly

DOEpatents

Grantz, Alan L.

1979-01-01

A fluidic self-actuating control assembly for use in a reactor wherein no external control inputs are required to actuate (scram) the system. The assembly is constructed to scram upon sensing either a sudden depressurization of reactor inlet flow or a sudden increase in core neutron flux. A fluidic control system senses abnormal flow or neutron flux transients and actuates the system, whereupon assembly coolant flow reverses, forcing absorber balls into the reactor core region.

Parallel algorithm of real-time infrared image restoration based on total variation theory

NASA Astrophysics Data System (ADS)

Zhu, Ran; Li, Miao; Long, Yunli; Zeng, Yaoyuan; An, Wei

2015-10-01

Image restoration is a necessary preprocessing step for infrared remote sensing applications. Traditional methods allow us to remove the noise but penalize too much the gradients corresponding to edges. Image restoration techniques based on variational approaches can solve this over-smoothing problem for the merits of their well-defined mathematical modeling of the restore procedure. The total variation (TV) of infrared image is introduced as a L1 regularization term added to the objective energy functional. It converts the restoration process to an optimization problem of functional involving a fidelity term to the image data plus a regularization term. Infrared image restoration technology with TV-L1 model exploits the remote sensing data obtained sufficiently and preserves information at edges caused by clouds. Numerical implementation algorithm is presented in detail. Analysis indicates that the structure of this algorithm can be easily implemented in parallelization. Therefore a parallel implementation of the TV-L1 filter based on multicore architecture with shared memory is proposed for infrared real-time remote sensing systems. Massive computation of image data is performed in parallel by cooperating threads running simultaneously on multiple cores. Several groups of synthetic infrared image data are used to validate the feasibility and effectiveness of the proposed parallel algorithm. Quantitative analysis of measuring the restored image quality compared to input image is presented. Experiment results show that the TV-L1 filter can restore the varying background image reasonably, and that its performance can achieve the requirement of real-time image processing.

Modeling Habitat Suitability of Migratory Birds from Remote Sensing Images Using Convolutional Neural Networks

PubMed Central

Su, Jin-He; Piao, Ying-Chao; Luo, Ze; Yan, Bao-Ping

2018-01-01

Simple Summary The understanding of the spatio-temporal distribution of the species habitats would facilitate wildlife resource management and conservation efforts. Existing methods have poor performance due to the limited availability of training samples. More recently, location-aware sensors have been widely used to track animal movements. The aim of the study was to generate suitability maps of bar-head geese using movement data coupled with environmental parameters, such as remote sensing images and temperature data. Therefore, we modified a deep convolutional neural network for the multi-scale inputs. The results indicate that the proposed method can identify the areas with the dense goose species around Qinghai Lake. In addition, this approach might also be interesting for implementation in other species with different niche factors or in areas where biological survey data are scarce. Abstract With the application of various data acquisition devices, a large number of animal movement data can be used to label presence data in remote sensing images and predict species distribution. In this paper, a two-stage classification approach for combining movement data and moderate-resolution remote sensing images was proposed. First, we introduced a new density-based clustering method to identify stopovers from migratory birds’ movement data and generated classification samples based on the clustering result. We split the remote sensing images into 16 × 16 patches and labeled them as positive samples if they have overlap with stopovers. Second, a multi-convolution neural network model is proposed for extracting the features from temperature data and remote sensing images, respectively. Then a Support Vector Machines (SVM) model was used to combine the features together and predict classification results eventually. The experimental analysis was carried out on public Landsat 5 TM images and a GPS dataset was collected on 29 birds over three years. The results indicated that our proposed method outperforms the existing baseline methods and was able to achieve good performance in habitat suitability prediction. PMID:29701686

Natural resources information system.

NASA Technical Reports Server (NTRS)

Leachtenauer, J. C.; Woll, A. M.

1972-01-01

A computer-based Natural Resources Information System was developed for the Bureaus of Indian Affairs and Land Management. The system stores, processes and displays data useful to the land manager in the decision making process. Emphasis is placed on the use of remote sensing as a data source. Data input consists of maps, imagery overlays, and on-site data. Maps and overlays are entered using a digitizer and stored as irregular polygons, lines and points. Processing functions include set intersection, union and difference and area, length and value computations. Data output consists of computer tabulations and overlays prepared on a drum plotter.

A knowledge-based system for prototypical reasoning

NASA Astrophysics Data System (ADS)

Lieto, Antonio; Minieri, Andrea; Piana, Alberto; Radicioni, Daniele P.

2015-04-01

In this work we present a knowledge-based system equipped with a hybrid, cognitively inspired architecture for the representation of conceptual information. The proposed system aims at extending the classical representational and reasoning capabilities of the ontology-based frameworks towards the realm of the prototype theory. It is based on a hybrid knowledge base, composed of a classical symbolic component (grounded on a formal ontology) with a typicality based one (grounded on the conceptual spaces framework). The resulting system attempts to reconcile the heterogeneous approach to the concepts in Cognitive Science with the dual process theories of reasoning and rationality. The system has been experimentally assessed in a conceptual categorisation task where common sense linguistic descriptions were given in input, and the corresponding target concepts had to be identified. The results show that the proposed solution substantially extends the representational and reasoning 'conceptual' capabilities of standard ontology-based systems.

MEMS sensing and control: an aerospace perspective

NASA Astrophysics Data System (ADS)

Schoess, Jeffrey N.; Arch, David K.; Yang, Wei; Cabuz, Cleopatra; Hocker, Ben; Johnson, Burgess R.; Wilson, Mark L.

2000-06-01

Future advanced fixed- and rotary-wing aircraft, launch vehicles, and spacecraft will incorporate smart microsensors to monitor flight integrity and provide flight control inputs. This paper provides an overview of Honeywell's MEMS technologies for aerospace applications of sensing and control. A unique second-generation polysilicon resonant microbeam sensor design is described. It incorporates a micron-level vacuum-encapsulated microbeam to optically sense aerodynamic parameters and to optically excite the sensor pick off: optically excited self-resonant microbeams form the basis for a new class of versatile, high- performance, low-cost MEMS sensors that uniquely combine silicon microfabrication technology with optoelectronic technology that can sense dynamic pressure, acceleration forces, acoustic emission, and many other aerospace parameters of interest. Honeywell's recent work in MEMS tuning fork gyros for inertial sensing and a MEMS free- piston engine are also described.

Optimization of Systems with Uncertainty: Initial Developments for Performance, Robustness and Reliability Based Designs

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Bushnell, Dennis M. (Technical Monitor)

2002-01-01

This paper presents a study on the optimization of systems with structured uncertainties, whose inputs and outputs can be exhaustively described in the probabilistic sense. By propagating the uncertainty from the input to the output in the space of the probability density functions and the moments, optimization problems that pursue performance, robustness and reliability based designs are studied. Be specifying the desired outputs in terms of desired probability density functions and then in terms of meaningful probabilistic indices, we settle a computationally viable framework for solving practical optimization problems. Applications to static optimization and stability control are used to illustrate the relevance of incorporating uncertainty in the early stages of the design. Several examples that admit a full probabilistic description of the output in terms of the design variables and the uncertain inputs are used to elucidate the main features of the generic problem and its solution. Extensions to problems that do not admit closed form solutions are also evaluated. Concrete evidence of the importance of using a consistent probabilistic formulation of the optimization problem and a meaningful probabilistic description of its solution is provided in the examples. In the stability control problem the analysis shows that standard deterministic approaches lead to designs with high probability of running into instability. The implementation of such designs can indeed have catastrophic consequences.

Early Examples from the Integrated Multi-Satellite Retrievals for GPM (IMERG)

NASA Astrophysics Data System (ADS)

Huffman, George; Bolvin, David; Braithwaite, Daniel; Hsu, Kuolin; Joyce, Robert; Kidd, Christopher; Sorooshian, Soroosh; Xie, Pingping

2014-05-01

The U.S. GPM Science Team's Day-1 algorithm for computing combined precipitation estimates as part of GPM is the Integrated Multi-satellitE Retrievals for GPM (IMERG). The goal is to compute the best time series of (nearly) global precipitation from "all" precipitation-relevant satellites and global surface precipitation gauge analyses. IMERG is being developed as a unified U.S. algorithm drawing on strengths in the three contributing groups, whose previous work includes: 1) the TRMM Multi-satellite Precipitation Analysis (TMPA); 2) the CPC Morphing algorithm with Kalman Filtering (K-CMORPH); and 3) the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks using a Cloud Classification System (PERSIANN-CCS). We review the IMERG design and development, plans for testing, and current status. Some of the lessons learned in running and reprocessing the previous data sets include the importance of quality-controlling input data sets, strategies for coping with transitions in the various input data sets, and practical approaches to retrospective analysis of multiple output products (namely the real- and post-real-time data streams). IMERG output will be illustrated using early test data, including the variety of supporting fields, such as the merged-microwave and infrared estimates, and the precipitation type. We end by considering recent changes in input data specifications, the transition from TRMM-based calibration to GPM-based, and further "Day 2" development.

Two-electrode non-differential biopotential amplifier.

PubMed

Dobrev, D

2002-09-01

A circuit is proposed for a non-differential two-electrode biopotential amplifier, with a current source and a transimpedance amplifier as a potential equaliser for its inputs, fully emulating a differential amplifier. The principle of operation is that the current in the input of the transimpedance amplifier is sensed and made to flow with the same value in the other input. The circuit has a simple structure and uses a small number of components. The current source maintains balanced common-mode interference currents, thus ensuring high signal input impedance. In addition, these currents can be tolerated up to more than 10 microA per input, at a supply voltage of +/- 5 V. A two-electrode differential amplifier with 2 x 10 Mohm input resistances to the reference point allows less than 0.5 microA per input. The circuit can be useful in cases of biosignal acquisition by portable instruments, using low supply voltages, from subjects in areas of high electromagnetic fields. Examples include biosignal recordings in electric power stations and electrically powered locomotives, where traditionally designed input amplifier stages can be saturated.

Clinical efficacy and safety of an implantable cardioverter-defibrillator lead with a floating atrial sensing dipole.

PubMed

Safak, Erdal; Schmitz, Dietmar; Konorza, Thomas; Wende, Christian; De Ros, Jose Olague; Schirdewan, Alexander

2013-08-01

The concept of a single-lead implantable cardioverter-defibrillator (ICD), with a floating dipole, has been proven safe and functional. The studied active-fixation, steroid-eluting lead (Linox(smart) S DX, BIOTRONIK SE & Co KG, Berlin, Germany) is one French thinner than its predecessor and coated with lubricious SilGlide to improve lead handling. A dedicated ICD device has a self-adaptive atrial input stage including a fourfold amplifier. The amplification, filtering, and adapted atrial input stage are located in the Lumax 540 VR-T DX (BIOTRONIK). The Linox(smart) S DX ICD lead delivers only the signal. The lead was evaluated during implantation; at predischarge; and 1-, 3-, and 6-month follow-up examinations. The primary endpoint (efficacy) was the rate of appropriate atrial sensing tests. The secondary endpoint (safety) was freedom from lead-related invasive reinterventions. Both safety and efficacy were expected to be significantly higher than 90%. The study enrolled 116 patients at 25 clinical sites. Skin-to-skin operation time was 52.4 ± 26.2 minutes. The investigators graded lead insertion as "easy" in 87% of patients. Mean P-wave amplitudes (preamplified) varied from 5.0 to 6.1 mV in different body positions. Both primary and secondary endpoints were met, as 93.8% (364/388; P = 0.005) of specific sensing tests indicated appropriate atrial sensing, and 94.8% (110/116; P = 0.048) of patients were free from reinterventions (lead dislodgement). Analysis of arrhythmia episodes stored in ICDs and elective 24-hour Holter electrocardiogram tests raised no concerns about lead functionality. The studied ICD lead with a floating atrial sensing dipole met the predefined safety expectation and demonstrated appropriate atrial sensing performance. ©2013, The Authors. Journal compilation ©2013 Wiley Periodicals, Inc.

A resettable and reprogrammable keypad lock based on electrochromic Prussian blue films and biocatalysis of immobilized glucose oxidase in a bipolar electrode system.

PubMed

Yu, Xue; Liang, Jiying; Yang, Tiangang; Gong, Mengjie; Xi, Dongman; Liu, Hongyun

2018-01-15

Herein, a resettable and reprogrammable biomolecular keypad lock on the basis of a closed bipolar electrode (BPE) system was established. In this system, one ITO electrode with immobilized chitosan (CS) and glucose oxidase (GOD), designated as CS-GOD, acted as one pole of BPE in the sensing cell; another ITO with electrodeposited Prussian blue (PB) films as the other pole in the reporting cell. The addition of ascorbic acid (AA) in the sensing cell with driving voltage (V tot ) at +2.5V would make the PB films become Prussian white (PW) in the reporting cell, accompanied by the color change from blue to nearly transparent. On the other hand, with the help of oxygen, the addition of glucose in the sensing cell with V tot at -1.5V would induce PW back to PB. The change of color and the corresponding UV-vis absorbance at 700nm for the PB/PW films in the reporting cell could be reversibly switched by changing the solute in the sensing cell between AA and glucose and then switching V tot between +2.5 and -1.5V. Based on these, a keypad lock was developed with AA, glucose and V tot as 3 inputs, and the color change of the PB/PW films as the output. This keypad lock system combined enzymatic catalysis with bipolar electrochemistry, demonstrating some unique advantages such as good reprogrammability, easy resettability and visual readout by naked eye. Copyright © 2017 Elsevier B.V. All rights reserved.

Mapping CDOM Concentration in Waters Influenced by the Mississippi River Plume

NASA Technical Reports Server (NTRS)

Miller, Richard L.; DelCastillo, Carlos E.; Powell, Rodney T.; DSa, Eurico; Spiering, Bruce

2002-01-01

Colored dissolved organic matter (CDOM) is often an important component of the organic carbon pool in river-dominated coastal margins. CDOM directly influences remote sensing applications through its strong absorption in the UV and blue regions of the spectrum. This effect can complicate the use of chlorophyll a retrieval algorithms and phytoplankton production models that are based on remotely sensed ocean color. As freshwater input is the principle source of CDOM in coastal margins, CDOM distribution can often be described by conservative mixing with open ocean waters and may serve as an optical tracer of riverine water. Hence, there is considerable interest in the ability to accurately measure and map CDOM concentrations as well as understand the processes that govern the optical properties and distribution of CDOM in coastal environments. We are examining CDOM dynamics in the waters influenced by the Mississippi River plume. Our program incorporates discrete samples, flow-through measurements, and remote sensing. CDOM absorption spectra of discrete samples are measured at sea using a portable, multiple pathlength waveguide system. A SAFire multi-spectral fluorescence meter provides spectral characterization of CDOM (fluorescence and absorption) using a ship flow-through system for continuous surface mapping. In situ reflectance spectra are obtained by a hand held spectroradiometer. Remotely sensed images are obtained from the SeaWiFS and CRIS (Coastal Research Imaging Spectrometer) instruments. We describe here the instruments used, sampling protocols employed, and the relationships derived between in situ measurements and remotely sensed data for this optically complex environment.

Knowledge-based processing for aircraft flight control

NASA Technical Reports Server (NTRS)

Painter, John H.

1991-01-01

The purpose is to develop algorithms and architectures for embedding artificial intelligence in aircraft guidance and control systems. With the approach adopted, AI-computing is used to create an outer guidance loop for driving the usual aircraft autopilot. That is, a symbolic processor monitors the operation and performance of the aircraft. Then, based on rules and other stored knowledge, commands are automatically formulated for driving the autopilot so as to accomplish desired flight operations. The focus is on developing a software system which can respond to linguistic instructions, input in a standard format, so as to formulate a sequence of simple commands to the autopilot. The instructions might be a fairly complex flight clearance, input either manually or by data-link. Emphasis is on a software system which responds much like a pilot would, employing not only precise computations, but, also, knowledge which is less precise, but more like common-sense. The approach is based on prior work to develop a generic 'shell' architecture for an AI-processor, which may be tailored to many applications by describing the application in appropriate processor data bases (libraries). Such descriptions include numerical models of the aircraft and flight control system, as well as symbolic (linguistic) descriptions of flight operations, rules, and tactics.

Real time network traffic monitoring for wireless local area networks based on compressed sensing

NASA Astrophysics Data System (ADS)

Balouchestani, Mohammadreza

2017-05-01

A wireless local area network (WLAN) is an important type of wireless networks which connotes different wireless nodes in a local area network. WLANs suffer from important problems such as network load balancing, large amount of energy, and load of sampling. This paper presents a new networking traffic approach based on Compressed Sensing (CS) for improving the quality of WLANs. The proposed architecture allows reducing Data Delay Probability (DDP) to 15%, which is a good record for WLANs. The proposed architecture is increased Data Throughput (DT) to 22 % and Signal to Noise (S/N) ratio to 17 %, which provide a good background for establishing high qualified local area networks. This architecture enables continuous data acquisition and compression of WLAN's signals that are suitable for a variety of other wireless networking applications. At the transmitter side of each wireless node, an analog-CS framework is applied at the sensing step before analog to digital converter in order to generate the compressed version of the input signal. At the receiver side of wireless node, a reconstruction algorithm is applied in order to reconstruct the original signals from the compressed signals with high probability and enough accuracy. The proposed algorithm out-performs existing algorithms by achieving a good level of Quality of Service (QoS). This ability allows reducing 15 % of Bit Error Rate (BER) at each wireless node.

Classification of permafrost active layer depth from remotely sensed and topographic evidence

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

Peddle, D.R.; Franklin, S.E.

1993-04-01

The remote detection of permafrost (perennially frozen ground) has important implications to environmental resource development, engineering studies, natural hazard prediction, and climate change research. In this study, the authors present results from two experiments into the classification of permafrost active layer depth within the zone of discontinuous permafrost in northern Canada. A new software system based on evidential reasoning was implemented to permit the integrated classification of multisource data consisting of landcover, terrain aspect, and equivalent latitude, each of which possessed different formats, data types, or statistical properties that could not be handled by conventional classification algorithms available to thismore » study. In the first experiment, four active layer depth classes were classified using ground based measurements of the three variables with an accuracy of 83% compared to in situ soil probe determination of permafrost active layer depth at over 500 field sites. This confirmed the environmental significance of the variables selected, and provided a baseline result to which a remote sensing classification could be compared. In the second experiment, evidence for each input variable was obtained from image processing of digital SPOT imagery and a photogrammetric digital elevation model, and used to classify active layer depth with an accuracy of 79%. These results suggest the classification of evidence from remotely sensed measures of spectral response and topography may provide suitable indicators of permafrost active layer depth.« less

A Wireless Fiber Photometry System Based on a High-Precision CMOS Biosensor With Embedded Continuous-Time Modulation.

PubMed

Khiarak, Mehdi Noormohammadi; Martianova, Ekaterina; Bories, Cyril; Martel, Sylvain; Proulx, Christophe D; De Koninck, Yves; Gosselin, Benoit

2018-06-01

Fluorescence biophotometry measurements require wide dynamic range (DR) and high-sensitivity laboratory apparatus. Indeed, it is often very challenging to accurately resolve the small fluorescence variations in presence of noise and high-background tissue autofluorescence. There is a great need for smaller detectors combining high linearity, high sensitivity, and high-energy efficiency. This paper presents a new biophotometry sensor merging two individual building blocks, namely a low-noise sensing front-end and a order continuous-time modulator (CTSDM), into a single module for enabling high-sensitivity and high energy-efficiency photo-sensing. In particular, a differential CMOS photodetector associated with a differential capacitive transimpedance amplifier-based sensing front-end is merged with an incremental order 1-bit CTSDM to achieve a large DR, low hardware complexity, and high-energy efficiency. The sensor leverages a hardware sharing strategy to simplify the implementation and reduce power consumption. The proposed CMOS biosensor is integrated within a miniature wireless head mountable prototype for enabling biophotometry with a single implantable fiber in the brain of live mice. The proposed biophotometry sensor is implemented in a 0.18- CMOS technology, consuming from a 1.8- supply voltage, while achieving a peak dynamic range of over a 50- input bandwidth, a sensitivity of 24 mV/nW, and a minimum detectable current of 2.46- at a 20- sampling rate.

Dynamic curvature sensing employing ionic-polymer-metal composite sensors

NASA Astrophysics Data System (ADS)

Bahramzadeh, Yousef; Shahinpoor, Mohsen

2011-09-01

A dynamic curvature sensor is presented based on ionic-polymer-metal composite (IPMC) for curvature monitoring of deployable/inflatable dynamic space structures. Monitoring the curvature variation is of high importance in various engineering structures including shape monitoring of deployable/inflatable space structures in which the structural boundaries undergo a dynamic deployment process. The high sensitivity of IPMCs to the applied deformations as well as its flexibility make IPMCs a promising candidate for sensing of dynamic curvature changes. Herein, we explore the dynamic response of an IPMC sensor strip with respect to controlled curvature deformations subjected to different forms of input functions. Using a specially designed experimental setup, the voltage recovery effect, phase delay, and rate dependency of the output voltage signal of an IPMC curvature sensor are analyzed. Experimental results show that the IPMC sensor maintains the linearity, sensitivity, and repeatability required for curvature sensing. Besides, in order to describe the dynamic phenomena such as the rate dependency of the IPMC sensor, a chemo-electro-mechanical model based on the Poisson-Nernst-Planck (PNP) equation for the kinetics of ion diffusion is presented. By solving the governing partial differential equations the frequency response of the IPMC sensor is derived. The physical model is able to describe the dynamic properties of the IPMC sensor and the dependency of the signal on rate of excitations.

MIMO system identification using frequency response data

NASA Technical Reports Server (NTRS)

Medina, Enrique A.; Irwin, R. D.; Mitchell, Jerrel R.; Bukley, Angelia P.

1992-01-01

A solution to the problem of obtaining a multi-input, multi-output statespace model of a system from its individual input/output frequency responses is presented. The Residue Identification Algorithm (RID) identifies the system poles from a transfer function model of the determinant of the frequency response data matrix. Next, the residue matrices of the modes are computed guaranteeing that each input/output frequency response is fitted in the least squares sense. Finally, a realization of the system is computed. Results of the application of RID to experimental frequency responses of a large space structure ground test facility are presented and compared to those obtained via the Eigensystem Realization Algorithm.

Footprint Reduction for the Acoustic Electric Feedthrough Technique

DTIC Science & Technology

2010-03-01

input current measured using a 1 Ω sense resistor . Modulation depth of the peak- to-peak input current was 2Δ ~ 20...behaviour of an AEF arrangement formed using piezo -ceramic disks with diameter 38 mm and thickness 2 mm, across an aluminium plate with thickness 1.6 to 5...the 38 mm diameter piezo -ceramic disks. In an attempt to resolve this matter, the DSTO has examined an AEF system formed using disks with 10 mm

Generic functional requirements for a NASA general-purpose data base management system

NASA Technical Reports Server (NTRS)

Lohman, G. M.

1981-01-01

Generic functional requirements for a general-purpose, multi-mission data base management system (DBMS) for application to remotely sensed scientific data bases are detailed. The motivation for utilizing DBMS technology in this environment is explained. The major requirements include: (1) a DBMS for scientific observational data; (2) a multi-mission capability; (3) user-friendly; (4) extensive and integrated information about data; (5) robust languages for defining data structures and formats; (6) scientific data types and structures; (7) flexible physical access mechanisms; (8) ways of representing spatial relationships; (9) a high level nonprocedural interactive query and data manipulation language; (10) data base maintenance utilities; (11) high rate input/output and large data volume storage; and adaptability to a distributed data base and/or data base machine configuration. Detailed functions are specified in a top-down hierarchic fashion. Implementation, performance, and support requirements are also given.

Emissions-critical charge cooling using an organic rankine cycle

DOEpatents

Ernst, Timothy C.; Nelson, Christopher R.

2014-07-15

The disclosure provides a system including a Rankine power cycle cooling subsystem providing emissions-critical charge cooling of an input charge flow. The system includes a boiler fluidly coupled to the input charge flow, an energy conversion device fluidly coupled to the boiler, a condenser fluidly coupled to the energy conversion device, a pump fluidly coupled to the condenser and the boiler, an adjuster that adjusts at least one parameter of the Rankine power cycle subsystem to change a temperature of the input charge exiting the boiler, and a sensor adapted to sense a temperature characteristic of the vaporized input charge. The system includes a controller that can determine a target temperature of the input charge sufficient to meet or exceed predetermined target emissions and cause the adjuster to adjust at least one parameter of the Rankine power cycle to achieve the predetermined target emissions.

FLUXCOM - Overview and First Synthesis

NASA Astrophysics Data System (ADS)

Jung, M.; Ichii, K.; Tramontana, G.; Camps-Valls, G.; Schwalm, C. R.; Papale, D.; Reichstein, M.; Gans, F.; Weber, U.

2015-12-01

We present a community effort aiming at generating an ensemble of global gridded flux products by upscaling FLUXNET data using an array of different machine learning methods including regression/model tree ensembles, neural networks, and kernel machines. We produced products for gross primary production, terrestrial ecosystem respiration, net ecosystem exchange, latent heat, sensible heat, and net radiation for two experimental protocols: 1) at a high spatial and 8-daily temporal resolution (5 arc-minute) using only remote sensing based inputs for the MODIS era; 2) 30 year records of daily, 0.5 degree spatial resolution by incorporating meteorological driver data. Within each set-up, all machine learning methods were trained with the same input data for carbon and energy fluxes respectively. Sets of input driver variables were derived using an extensive formal variable selection exercise. The performance of the extrapolation capacities of the approaches is assessed with a fully internally consistent cross-validation. We perform cross-consistency checks of the gridded flux products with independent data streams from atmospheric inversions (NEE), sun-induced fluorescence (GPP), catchment water balances (LE, H), satellite products (Rn), and process-models. We analyze the uncertainties of the gridded flux products and for example provide a breakdown of the uncertainty of mean annual GPP originating from different machine learning methods, different climate input data sets, and different flux partitioning methods. The FLUXCOM archive will provide an unprecedented source of information for water, energy, and carbon cycle studies.

Low noise charge sensitive preamplifier DC stabilized without a physical resistor

DOEpatents

Bertuccio, Giuseppe; Rehak, Pavel; Xi, Deming

1994-09-13

The invention is a novel charge sensitive preamplifier (CSP) which has no resistor in parallel with the feedback capacitor. No resetting circuit is required to discharge the feedback capacitor. The DC stabilization of the preamplifier is obtained by means of a second feedback loop between the preamplifier output and the common base transistor of the input cascode. The input transistor of the preamplifier is a Junction Field Transistor (JFET) with the gate-source junction forward biased. The detector leakage current flows into this junction. This invention is concerned with a new circuit configuration for a charge sensitive preamplifier and a novel use of the input Field Effect Transistor of the CSP itself. In particular this invention, in addition to eliminating the feedback resistor, eliminates the need for external devices between the detector and the preamplifier, and it eliminates the need for external circuitry to sense the output voltage and reset the CSP. Furthermore, the noise level of the novel CSP is very low, comparable with the performance achieved with other solutions. Experimental tests prove that this configuration for the charge sensitive preamplifier permits an excellent noise performance at temperatures including room temperature. An equivalent noise charge of less than 20 electrons r.m.s. has been measured at room temperature by using a commercial JFET as input device of the preamplifier.

Low noise charge sensitive preamplifier DC stabilized without a physical resistor

DOEpatents

Bertuccio, G.; Rehak, P.; Xi, D.

1994-09-13

The invention is a novel charge sensitive preamplifier (CSP) which has no resistor in parallel with the feedback capacitor. No resetting circuit is required to discharge the feedback capacitor. The DC stabilization of the preamplifier is obtained by means of a second feedback loop between the preamplifier output and the common base transistor of the input cascode. The input transistor of the preamplifier is a Junction Field Transistor (JFET) with the gate-source junction forward biased. The detector leakage current flows into this junction. This invention is concerned with a new circuit configuration for a charge sensitive preamplifier and a novel use of the input Field Effect Transistor of the CSP itself. In particular this invention, in addition to eliminating the feedback resistor, eliminates the need for external devices between the detector and the preamplifier, and it eliminates the need for external circuitry to sense the output voltage and reset the CSP. Furthermore, the noise level of the novel CSP is very low, comparable with the performance achieved with other solutions. Experimental tests prove that this configuration for the charge sensitive preamplifier permits an excellent noise performance at temperatures including room temperature. An equivalent noise charge of less than 20 electrons r.m.s. has been measured at room temperature by using a commercial JFET as input device of the preamplifier. 6 figs.

Methods for In-Flight Wing Shape Predictions of Highly Flexible Unmanned Aerial Vehicles: Formulation of Ko Displacement Theory

NASA Technical Reports Server (NTRS)

Ko, William L.; Fleischer, Van Tran

2010-01-01

The Ko displacement theory is formulated for a cantilever tubular wing spar under bending, torsion, and combined bending and torsion loading. The Ko displacement equations are expressed in terms of strains measured at multiple sensing stations equally spaced on the surface of the wing spar. The bending and distortion strain data can then be input to the displacement equations to calculate slopes, deflections, and cross-sectional twist angles of the wing spar at the strain-sensing stations for generating the deformed shapes of flexible aircraft wing spars. The displacement equations have been successfully validated for accuracy by finite-element analysis. The Ko displacement theory that has been formulated could also be applied to calculate the deformed shape of simple and tapered beams, plates, and tapered cantilever wing boxes. The Ko displacement theory and associated strain-sensing system (such as fiber optic sensors) form a powerful tool for in-flight deformation monitoring of flexible wings and tails, such as those often employed on unmanned aerial vehicles. Ultimately, the calculated displacement data can be visually displayed in real time to the ground-based pilot for monitoring the deformed shape of unmanned aerial vehicles during flight.

Offset-free rail-to-rail derandomizing peak detect-and-hold circuit

DOEpatents

DeGeronimo, Gianluigi; O'Connor, Paul; Kandasamy, Anand

2003-01-01

A peak detect-and-hold circuit eliminates errors introduced by conventional amplifiers, such as common-mode rejection and input voltage offset. The circuit includes an amplifier, three switches, a transistor, and a capacitor. During a detect-and-hold phase, a hold voltage at a non-inverting in put terminal of the amplifier tracks an input voltage signal and when a peak is reached, the transistor is switched off, thereby storing a peak voltage in the capacitor. During a readout phase, the circuit functions as a unity gain buffer, in which the voltage stored in the capacitor is provided as an output voltage. The circuit is able to sense signals rail-to-rail and can readily be modified to sense positive, negative, or peak-to-peak voltages. Derandomization may be achieved by using a plurality of peak detect-and-hold circuits electrically connected in parallel.

Remote sensing-aided systems for snow qualification, evapotranspiration estimation, and their application in hydrologic models

NASA Technical Reports Server (NTRS)

Korram, S.

1977-01-01

The design of general remote sensing-aided methodologies was studied to provide the estimates of several important inputs to water yield forecast models. These input parameters are snow area extent, snow water content, and evapotranspiration. The study area is Feather River Watershed (780,000 hectares), Northern California. The general approach involved a stepwise sequence of identification of the required information, sample design, measurement/estimation, and evaluation of results. All the relevent and available information types needed in the estimation process are being defined. These include Landsat, meteorological satellite, and aircraft imagery, topographic and geologic data, ground truth data, and climatic data from ground stations. A cost-effective multistage sampling approach was employed in quantification of all the required parameters. The physical and statistical models for both snow quantification and evapotranspiration estimation was developed. These models use the information obtained by aerial and ground data through appropriate statistical sampling design.

Estimation of Global Subsurface Thermal Structure from Satellite Remote Sensing Observations Based on Machine Learning

NASA Astrophysics Data System (ADS)

Su, H.; Yan, X. H.

2017-12-01

Subsurface thermal structure of the global ocean is a key factor that reflects the impact of the global climate variability and change. Accurately determining and describing the global subsurface and deeper ocean thermal structure from satellite measurements is becoming even more important for understanding the ocean interior anomaly and dynamic processes during recent global warming and hiatus. It is essential but challenging to determine the extent to which such surface remote sensing observations can be used to develop information about the global ocean interior. This study proposed a Support Vector Regression (SVR) method to estimate Subsurface Temperature Anomaly (STA) in the global ocean. The SVR model can well estimate the global STA upper 1000 m through a suite of satellite remote sensing observations of sea surface parameters (including Sea Surface Height Anomaly (SSHA), Sea Surface Temperature Anomaly (SSTA), Sea Surface Salinity Anomaly (SSSA) and Sea Surface Wind Anomaly (SSWA)) with in situ Argo data for training and testing at different depth levels. Here, we employed the MSE and R2 to assess SVR performance on the STA estimation. The results from the SVR model were validated for the accuracy and reliability using the worldwide Argo STA data. The average MSE and R2 of the 15 levels are 0.0090 / 0.0086 / 0.0087 and 0.443 / 0.457 / 0.485 for 2-attributes (SSHA, SSTA) / 3-attributes (SSHA, SSTA, SSSA) / 4-attributes (SSHA, SSTA, SSSA, SSWA) SVR, respectively. The estimation accuracy was improved by including SSSA and SSWA for SVR input (MSE decreased by 0.4% / 0.3% and R2 increased by 1.4% / 4.2% on average). While, the estimation accuracy gradually decreased with the increase of the depth from 500 m. The results showed that SSSA and SSWA, in addition to SSTA and SSHA, are useful parameters that can help estimate the subsurface thermal structure, as well as improve the STA estimation accuracy. In future, we can figure out more potential and useful sea surface parameters from satellite remote sensing as input attributes so as to further improve the STA sensing accuracy from machine learning. This study can provide a helpful technique for studying thermal variability in the ocean interior which has played an important role in recent global warming and hiatus from satellite observations over global scale.

Weighted Iterative Bayesian Compressive Sensing (WIBCS) for High Dimensional Polynomial Surrogate Construction

NASA Astrophysics Data System (ADS)

Sargsyan, K.; Ricciuto, D. M.; Safta, C.; Debusschere, B.; Najm, H. N.; Thornton, P. E.

2016-12-01

Surrogate construction has become a routine procedure when facing computationally intensive studies requiring multiple evaluations of complex models. In particular, surrogate models, otherwise called emulators or response surfaces, replace complex models in uncertainty quantification (UQ) studies, including uncertainty propagation (forward UQ) and parameter estimation (inverse UQ). Further, surrogates based on Polynomial Chaos (PC) expansions are especially convenient for forward UQ and global sensitivity analysis, also known as variance-based decomposition. However, the PC surrogate construction strongly suffers from the curse of dimensionality. With a large number of input parameters, the number of model simulations required for accurate surrogate construction is prohibitively large. Relatedly, non-adaptive PC expansions typically include infeasibly large number of basis terms far exceeding the number of available model evaluations. We develop Weighted Iterative Bayesian Compressive Sensing (WIBCS) algorithm for adaptive basis growth and PC surrogate construction leading to a sparse, high-dimensional PC surrogate with a very few model evaluations. The surrogate is then readily employed for global sensitivity analysis leading to further dimensionality reduction. Besides numerical tests, we demonstrate the construction on the example of Accelerated Climate Model for Energy (ACME) Land Model for several output QoIs at nearly 100 FLUXNET sites covering multiple plant functional types and climates, varying 65 input parameters over broad ranges of possible values. This work is supported by the U.S. Department of Energy, Office of Science, Biological and Environmental Research, Accelerated Climate Modeling for Energy (ACME) project. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Sensing device and method for measuring emission time delay during irradiation of targeted samples

NASA Technical Reports Server (NTRS)

Danielson, J. D. Sheldon (Inventor)

2000-01-01

An apparatus for measuring emission time delay during irradiation of targeted samples by utilizing digital signal processing to determine the emission phase shift caused by the sample is disclosed. The apparatus includes a source of electromagnetic radiation adapted to irradiate a target sample. A mechanism generates first and second digital input signals of known frequencies with a known phase relationship, and a device then converts the first and second digital input signals to analog sinusoidal signals. An element is provided to direct the first input signal to the electromagnetic radiation source to modulate the source by the frequency thereof to irradiate the target sample and generate a target sample emission. A device detects the target sample emission and produces a corresponding first output signal having a phase shift relative to the phase of the first input signal, the phase shift being caused by the irradiation time delay in the sample. A member produces a known phase shift in the second input signal to create a second output signal. A mechanism is then provided for converting each of the first and second analog output signals to digital signals. A mixer receives the first and second digital output signals and compares the signal phase relationship therebetween to produce a signal indicative of the change in phase relationship between the first and second output signals caused by the target sample emission. Finally, a feedback arrangement alters the phase of the second input signal based on the mixer signal to ultimately place the first and second output signals in quadrature. Mechanisms for enhancing this phase comparison and adjustment technique are also disclosed.

Sensing device and method for measuring emission time delay during irradiation of targeted samples utilizing variable phase tracking

NASA Technical Reports Server (NTRS)

Danielson, J. D. Sheldon (Inventor)

2006-01-01

An apparatus for measuring emission time delay during irradiation of targeted samples by utilizing digital signal processing to determine the emission phase shift caused by the sample is disclosed. The apparatus includes a source of electromagnetic radiation adapted to irradiate a target sample. A mechanism generates first and second digital input signals of known frequencies with a known phase relationship, and a device then converts the first and second digital input signals to analog sinusoidal signals. An element is provided to direct the first input signal to the electromagnetic radiation source to modulate the source by the frequency thereof to irradiate the target sample and generate a target sample emission. A device detects the target sample emission and produces a corresponding first output signal having a phase shift relative to the phase of the first input signal, the phase shift being caused by the irradiation time delay in the sample. A member produces a known phase shift in the second input signal to create a second output signal. A mechanism is then provided for converting each of the first and second analog output signals to digital signals. A mixer receives the first and second digital output signals and compares the signal phase relationship therebetween to produce a signal indicative of the change in phase relationship between the first and second output signals caused by the target sample emission. Finally, a feedback arrangement alters the phase of the second input signal based on the mixer signal to ultimately place the first and second output signals in quadrature. Mechanisms for enhancing this phase comparison and adjustment technique are also disclosed.

Automated Liquid-Level Control of a Nutrient Reservoir for a Hydroponic System

NASA Technical Reports Server (NTRS)

Smith, Boris; Asumadu, Johnson A.; Dogan, Numan S.

1997-01-01

A microprocessor-based system for control of the liquid level of a nutrient reservoir for a plant hydroponic growing system has been developed. The system uses an ultrasonic transducer to sense the liquid level or height. A National Instruments' Multifunction Analog and Digital Input/Output PC Kit includes NI-DAQ DOS/Windows driver software for an IBM 486 personal computer. A Labview Full Development system for Windows is the graphical programming system being used. The system allows liquid level control to within 0.1 cm for all levels tried between 8 and 36 cm in the hydroponic system application. The detailed algorithms have been developed and a fully automated microprocessor based nutrient replenishment system has been described for this hydroponic system.

High-resolution LCOS microdisplay with sub-kHz frame rate for high performance, high precision 3D sensor

NASA Astrophysics Data System (ADS)

Lazarev, Grigory; Bonifer, Stefanie; Engel, Philip; Höhne, Daniel; Notni, Gunther

2017-06-01

We report about the implementation of the liquid crystal on silicon (LCOS) microdisplay with 1920 by 1080 resolution and 720 Hz frame rate. The driving solution is FPGA-based. The input signal is converted from the ultrahigh-resolution HDMI 2.0 signal into HD frames, which follow with the specified 720 Hz frame rate. Alternatively the signal is generated directly on the FPGA with built-in pattern generator. The display is showing switching times below 1.5 ms for the selected working temperature. The bit depth of the addressed image achieves 8 bit within each frame. The microdisplay is used in the fringe projection-based 3D sensing system, implemented by Fraunhofer IOF.

Robust Algorithms for on Minor-Free Graphs Based on the Sherali-Adams Hierarchy

NASA Astrophysics Data System (ADS)

Magen, Avner; Moharrami, Mohammad

This work provides a Linear Programming-based Polynomial Time Approximation Scheme (PTAS) for two classical NP-hard problems on graphs when the input graph is guaranteed to be planar, or more generally Minor Free. The algorithm applies a sufficiently large number (some function of when approximation is required) of rounds of the so-called Sherali-Adams Lift-and-Project system. needed to obtain a -approximation, where f is some function that depends only on the graph that should be avoided as a minor. The problem we discuss are the well-studied problems, the and problems. An curious fact we expose is that in the world of minor-free graph, the is harder in some sense than the.

Elicitation of State and Local User Needs for Future Moderate Resolution Earth Observations: The AmericaView Contribution

NASA Astrophysics Data System (ADS)

French, N. H. F.; Lawrence, R. L.

2017-12-01

AmericaView is a nationwide partnership of remote sensing scientists who support the use of Landsat and other public domain remotely sensed data through applied remote sensing research, K-12 and higher STEM education, workforce development, and technology transfer. The national AmericaView program currently has active university-lead members in 39 states, each of which has a "stateview" consortium consisting of some combination of university, agency, non-profit, and other members. This "consortium of consortia" has resulted in a strong and unique nationwide network of remote sensing practitioners. AmericaView has used this network to contribute to the USGS Requirements Capabilities & Analysis for Earth Observations. Participating states have conducted interviews of key remote sensing end users across the country to provide key input at the state and local level for the design and implementation of future U.S. moderate resolution Earth observations.

A Z-Axis Quartz Cross-Fork Micromachined Gyroscope Based on Shear Stress Detection

PubMed Central

Xie, Liqiang; Wu, Xuezhong; Li, Shengyi; Wang, Haoxu; Su, Jianbin; Dong, Peitao

2010-01-01

Here we propose a novel quartz micromachined gyroscope. The sensor has a simple cross-fork structure in the x-y plane of quartz crystal. Shear stress rather than normal stress is utilized to sense Coriolis’ force generated by the input angular rate signal. Compared to traditional quartz gyroscopes, which have two separate sense electrodes on each sidewall, there is only one electrode on each sidewall of the sense beam. As a result, the fabrication of the electrodes is simplified and the structure can be easily miniaturized. In order to increase sensitivity, a pair of proof masses is attached to the ends of the drive beam, and the sense beam has a tapered design. The structure is etched from a z-cut quartz wafer and the electrodes are realized by direct evaporation using the aperture mask method. The drive mode frequency of the prototype is 13.38 kHz, and the quality factor is approximately 1,000 in air. Therefore, the gyroscope can work properly without a vacuum package. The measurement ability of the shear stress detection design scheme is validated by the Coriolis’ force test. The performance of the sensor is characterized on a precision rate table using a specially designed readout circuit. The experimentally obtained scale factor is 1.45 mV/°/s and the nonlinearity is 3.6% in range of ±200 °/s. PMID:22294887

Paper-based piezoelectric touch pads with hydrothermally grown zinc oxide nanowires.

PubMed

Li, Xiao; Wang, Yu-Hsuan; Zhao, Chen; Liu, Xinyu

2014-12-24

This paper describes a new type of paper-based piezoelectric touch pad integrating zinc oxide nanowires (ZnO NWs), which can serve as user interfaces in paper-based electronics. The sensing functionality of these touch pads is enabled by the piezoelectric property of ZnO NWs grown on paper using a simple, cost-efficient hydrothermal method. A piece of ZnO-NW paper with two screen-printed silver electrodes forms a touch button, and touch-induced electric charges from the button are converted into a voltage output using a charge amplifier circuit. A touch pad consisting of an array of buttons can be readily integrated into paper-based electronic devices, allowing user input of information for various purposes such as programming, identification checking, and gaming. This novel design features ease of fabrication, low cost, ultrathin structure, and good compatibility with techniques in printed electronics, and further enriches the available technologies of paper-based electronics.

Model and Data Reduction for Control, Identification and Compressed Sensing

NASA Astrophysics Data System (ADS)

Kramer, Boris

This dissertation focuses on problems in design, optimization and control of complex, large-scale dynamical systems from different viewpoints. The goal is to develop new algorithms and methods, that solve real problems more efficiently, together with providing mathematical insight into the success of those methods. There are three main contributions in this dissertation. In Chapter 3, we provide a new method to solve large-scale algebraic Riccati equations, which arise in optimal control, filtering and model reduction. We present a projection based algorithm utilizing proper orthogonal decomposition, which is demonstrated to produce highly accurate solutions at low rank. The method is parallelizable, easy to implement for practitioners, and is a first step towards a matrix free approach to solve AREs. Numerical examples for n ≥ 106 unknowns are presented. In Chapter 4, we develop a system identification method which is motivated by tangential interpolation. This addresses the challenge of fitting linear time invariant systems to input-output responses of complex dynamics, where the number of inputs and outputs is relatively large. The method reduces the computational burden imposed by a full singular value decomposition, by carefully choosing directions on which to project the impulse response prior to assembly of the Hankel matrix. The identification and model reduction step follows from the eigensystem realization algorithm. We present three numerical examples, a mass spring damper system, a heat transfer problem, and a fluid dynamics system. We obtain error bounds and stability results for this method. Chapter 5 deals with control and observation design for parameter dependent dynamical systems. We address this by using local parametric reduced order models, which can be used online. Data available from simulations of the system at various configurations (parameters, boundary conditions) is used to extract a sparse basis to represent the dynamics (via dynamic mode decomposition). Subsequently, a new, compressed sensing based classification algorithm is developed which incorporates the extracted dynamic information into the sensing basis. We show that this augmented classification basis makes the method more robust to noise, and results in superior identification of the correct parameter. Numerical examples consist of a Navier-Stokes, as well as a Boussinesq flow application.

Code Description for Generation of Meteorological Height and Pressure Level and Layer Profiles

DTIC Science & Technology

2016-06-01

defined by user input height or pressure levels. It can process input profiles from sensing systems such as radiosonde, lidar, or wind profiling radar...nearly the same way, but the split between wind and temperature/humidity (TH) special levels leads to some changes to one other routine. If changes are...top of the sounding, sometimes the moisture, the thermal, both thermal and moisture, and/or the wind data are missing. Missing data items in the

Multicriteria analysis for sources of renewable energy using data from remote sensing

NASA Astrophysics Data System (ADS)

Matejicek, L.

2015-04-01

Renewable energy sources are major components of the strategy to reduce harmful emissions and to replace depleting fossil energy resources. Data from remote sensing can provide information for multicriteria analysis for sources of renewable energy. Advanced land cover quantification makes it possible to search for suitable sites. Multicriteria analysis, together with other data, is used to determine the energy potential and socially acceptability of suggested locations. The described case study is focused on an area of surface coal mines in the northwestern region of the Czech Republic, where the impacts of surface mining and reclamation constitute a dominant force in land cover changes. High resolution satellite images represent the main input datasets for identification of suitable sites. Solar mapping, wind predictions, the location of weirs in watersheds, road maps and demographic information complement the data from remote sensing for multicriteria analysis, which is implemented in a geographic information system (GIS). The input spatial datasets for multicriteria analysis in GIS are reclassified to a common scale and processed with raster algebra tools to identify suitable sites for sources of renewable energy. The selection of suitable sites is limited by the CORINE land cover database to mining and agricultural areas. The case study is focused on long term land cover changes in the 1985-2015 period. Multicriteria analysis based on CORINE data shows moderate changes in mapping of suitable sites for utilization of selected sources of renewable energy in 1990, 2000, 2006 and 2012. The results represent map layers showing the energy potential on a scale of a few preference classes (1-7), where the first class is linked to minimum preference and the last class to maximum preference. The attached histograms show the moderate variability of preference classes due to land cover changes caused by mining activities. The results also show a slight increase in the more preferred classes for utilization of sources of renewable energy due to an increase area of reclaimed sites. Using data from remote sensing, such as the multispectral images and the CORINE land cover datasets, can reduce the financial resources currently required for finding and assessing suitable areas.

Position sensor for a fuel injection element in an internal combustion engine

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

Fulkerson, D.E.; Geske, M.L.

1987-08-18

This patent describes an electronic circuit for dynamically sensing and processing signals representative of changes in a magnet field, the circuit comprising: means for sensing a change in a magnetic field external to the circuit and providing an output representative of the change; circuit means electronically coupled with the output of the sensing means for providing an output indicating the presence of the magnetic field change; and a nulling circuit coupled with the output of the sensing means and across the indicating circuit means for nulling the electronic circuit responsive to the sensing means output, to thereby avoid ambient magneticmore » fields temperature and process variations, and wherein the nulling circuit comprises a capacitor coupled to the output of the nulling circuit, means for charging and discharging the capacitor responsive to any imbalance in the input to the nulling circuit, and circuit means coupling the capacitor with the output of the sensing means for nulling any imbalance during the charging or discharging of the capacitor.« less

Towards automatic lithological classification from remote sensing data using support vector machines

NASA Astrophysics Data System (ADS)

Yu, Le; Porwal, Alok; Holden, Eun-Jung; Dentith, Michael

2010-05-01

Remote sensing data can be effectively used as a mean to build geological knowledge for poorly mapped terrains. Spectral remote sensing data from space- and air-borne sensors have been widely used to geological mapping, especially in areas of high outcrop density in arid regions. However, spectral remote sensing information by itself cannot be efficiently used for a comprehensive lithological classification of an area due to (1) diagnostic spectral response of a rock within an image pixel is conditioned by several factors including the atmospheric effects, spectral and spatial resolution of the image, sub-pixel level heterogeneity in chemical and mineralogical composition of the rock, presence of soil and vegetation cover; (2) only surface information and is therefore highly sensitive to the noise due to weathering, soil cover, and vegetation. Consequently, for efficient lithological classification, spectral remote sensing data needs to be supplemented with other remote sensing datasets that provide geomorphological and subsurface geological information, such as digital topographic model (DEM) and aeromagnetic data. Each of the datasets contain significant information about geology that, in conjunction, can potentially be used for automated lithological classification using supervised machine learning algorithms. In this study, support vector machine (SVM), which is a kernel-based supervised learning method, was applied to automated lithological classification of a study area in northwestern India using remote sensing data, namely, ASTER, DEM and aeromagnetic data. Several digital image processing techniques were used to produce derivative datasets that contained enhanced information relevant to lithological discrimination. A series of SVMs (trained using k-folder cross-validation with grid search) were tested using various combinations of input datasets selected from among 50 datasets including the original 14 ASTER bands and 36 derivative datasets (including 14 principal component bands, 14 independent component bands, 3 band ratios, 3 DEM derivatives: slope/curvatureroughness and 2 aeromagnetic derivatives: mean and variance of susceptibility) extracted from the ASTER, DEM and aeromagnetic data, in order to determine the optimal inputs that provide the highest classification accuracy. It was found that a combination of ASTER-derived independent components, principal components and band ratios, DEM-derived slope, curvature and roughness, and aeromagnetic-derived mean and variance of magnetic susceptibility provide the highest classification accuracy of 93.4% on independent test samples. A comparison of the classification results of the SVM with those of maximum likelihood (84.9%) and minimum distance (38.4%) classifiers clearly show that the SVM algorithm returns much higher classification accuracy. Therefore, the SVM method can be used to produce quick and reliable geological maps from scarce geological information, which is still the case with many under-developed frontier regions of the world.

Image processing methods used to simulate flight over remotely sensed data

NASA Technical Reports Server (NTRS)

Mortensen, H. B.; Hussey, K. J.; Mortensen, R. A.

1988-01-01

It has been demonstrated that image processing techniques can provide an effective means of simulating flight over remotely sensed data (Hussey et al. 1986). This paper explains the methods used to simulate and animate three-dimensional surfaces from two-dimensional imagery. The preprocessing techniques used on the input data, the selection of the animation sequence, the generation of the animation frames, and the recording of the animation is covered. The software used for all steps is discussed.

Long-term records of global radiation, carbon and water fluxes derived from multi-satellite data and a process-based model

NASA Astrophysics Data System (ADS)

Ryu, Youngryel; Jiang, Chongya

2016-04-01

To gain insights about the underlying impacts of global climate change on terrestrial ecosystem fluxes, we present a long-term (1982-2015) global radiation, carbon and water fluxes products by integrating multi-satellite data with a process-based model, the Breathing Earth System Simulator (BESS). BESS is a coupled processed model that integrates radiative transfer in the atmosphere and canopy, photosynthesis (GPP), and evapotranspiration (ET). BESS was designed most sensitive to the variables that can be quantified reliably, fully taking advantages of remote sensing atmospheric and land products. Originally, BESS entirely relied on MODIS as input variables to produce global GPP and ET during the MODIS era. This study extends the work to provide a series of long-term products from 1982 to 2015 by incorporating AVHRR data. In addition to GPP and ET, more land surface processes related datasets are mapped to facilitate the discovery of the ecological variations and changes. The CLARA-A1 cloud property datasets, the TOMS aerosol datasets, along with the GLASS land surface albedo datasets, were input to a look-up table derived from an atmospheric radiative transfer model to produce direct and diffuse components of visible and near infrared radiation datasets. Theses radiation components together with the LAI3g datasets and the GLASS land surface albedo datasets, were used to calculate absorbed radiation through a clumping corrected two-stream canopy radiative transfer model. ECMWF ERA interim air temperature data were downscaled by using ALP-II land surface temperature dataset and a region-dependent regression model. The spatial and seasonal variations of CO2 concentration were accounted by OCO-2 datasets, whereas NOAA's global CO2 growth rates data were used to describe interannual variations. All these remote sensing based datasets are used to run the BESS. Daily fluxes in 1/12 degree were computed and then aggregated to half-month interval to match with the spatial-temporal resolution of LAI3g dataset. The BESS GPP and ET products were compared to other independent datasets including MPI-BGC and CLM. Overall, the BESS products show good agreement with the other two datasets, indicating a compelling potential for bridging remote sensing and land surface models.

Methods and decision making on a Mars rover for identification of fossils

NASA Technical Reports Server (NTRS)

Eberlein, Susan; Yates, Gigi

1989-01-01

A system for automated fusion and interpretation of image data from multiple sensors, including multispectral data from an imaging spectrometer is being developed. Classical artificial intelligence techniques and artificial neural networks are employed to make real time decision based on current input and known scientific goals. Emphasis is placed on identifying minerals which could indicate past life activity or an environment supportive of life. Multispectral data can be used for geological analysis because different minerals have characteristic spectral reflectance in the visible and near infrared range. Classification of each spectrum into a broad class, based on overall spectral shape and locations of absorption bands is possible in real time using artificial neural networks. The goal of the system is twofold: multisensor and multispectral data must be interpreted in real time so that potentially interesting sites can be flagged and investigated in more detail while the rover is near those sites; and the sensed data must be reduced to the most compact form possible without loss of crucial information. Autonomous decision making will allow a rover to achieve maximum scientific benefit from a mission. Both a classical rule based approach and a decision neural network for making real time choices are being considered. Neural nets may work well for adaptive decision making. A neural net can be trained to work in two steps. First, the actual input state is mapped to the closest of a number of memorized states. After weighing the importance of various input parameters, the net produces an output decision based on the matched memory state. Real time, autonomous image data analysis and decision making capabilities are required for achieving maximum scientific benefit from a rover mission. The system under development will enhance the chances of identifying fossils or environments capable of supporting life on Mars

Spike-Interval Triggered Averaging Reveals a Quasi-Periodic Spiking Alternative for Stochastic Resonance in Catfish Electroreceptors

PubMed Central

Lankheet, Martin J. M.; Klink, P. Christiaan; Borghuis, Bart G.; Noest, André J.

2012-01-01

Catfish detect and identify invisible prey by sensing their ultra-weak electric fields with electroreceptors. Any neuron that deals with small-amplitude input has to overcome sensitivity limitations arising from inherent threshold non-linearities in spike-generation mechanisms. Many sensory cells solve this issue with stochastic resonance, in which a moderate amount of intrinsic noise causes irregular spontaneous spiking activity with a probability that is modulated by the input signal. Here we show that catfish electroreceptors have adopted a fundamentally different strategy. Using a reverse correlation technique in which we take spike interval durations into account, we show that the electroreceptors generate a supra-threshold bias current that results in quasi-periodically produced spikes. In this regime stimuli modulate the interval between successive spikes rather than the instantaneous probability for a spike. This alternative for stochastic resonance combines threshold-free sensitivity for weak stimuli with similar sensitivity for excitations and inhibitions based on single interspike intervals. PMID:22403709

Complex cellular logic computation using ribocomputing devices.

PubMed

Green, Alexander A; Kim, Jongmin; Ma, Duo; Silver, Pamela A; Collins, James J; Yin, Peng

2017-08-03

Synthetic biology aims to develop engineering-driven approaches to the programming of cellular functions that could yield transformative technologies. Synthetic gene circuits that combine DNA, protein, and RNA components have demonstrated a range of functions such as bistability, oscillation, feedback, and logic capabilities. However, it remains challenging to scale up these circuits owing to the limited number of designable, orthogonal, high-performance parts, the empirical and often tedious composition rules, and the requirements for substantial resources for encoding and operation. Here, we report a strategy for constructing RNA-only nanodevices to evaluate complex logic in living cells. Our 'ribocomputing' systems are composed of de-novo-designed parts and operate through predictable and designable base-pairing rules, allowing the effective in silico design of computing devices with prescribed configurations and functions in complex cellular environments. These devices operate at the post-transcriptional level and use an extended RNA transcript to co-localize all circuit sensing, computation, signal transduction, and output elements in the same self-assembled molecular complex, which reduces diffusion-mediated signal losses, lowers metabolic cost, and improves circuit reliability. We demonstrate that ribocomputing devices in Escherichia coli can evaluate two-input logic with a dynamic range up to 900-fold and scale them to four-input AND, six-input OR, and a complex 12-input expression (A1 AND A2 AND NOT A1*) OR (B1 AND B2 AND NOT B2*) OR (C1 AND C2) OR (D1 AND D2) OR (E1 AND E2). Successful operation of ribocomputing devices based on programmable RNA interactions suggests that systems employing the same design principles could be implemented in other host organisms or in extracellular settings.

A Bidirectional Subsurface Remote Sensing Reflectance Model Explicitly Accounting for Particle Backscattering Shapes

NASA Astrophysics Data System (ADS)

He, Shuangyan; Zhang, Xiaodong; Xiong, Yuanheng; Gray, Deric

2017-11-01

The subsurface remote sensing reflectance (rrs, sr-1), particularly its bidirectional reflectance distribution function (BRDF), depends fundamentally on the angular shape of the volume scattering functions (VSFs, m-1 sr-1). Recent technological advancement has greatly expanded the collection, and the knowledge of natural variability, of the VSFs of oceanic particles. This allows us to test the Zaneveld's theoretical rrs model that explicitly accounts for particle VSF shapes. We parameterized the rrs model based on HydroLight simulations using 114 VSFs measured in three coastal waters around the United States and in oceanic waters of North Atlantic Ocean. With the absorption coefficient (a), backscattering coefficient (bb), and VSF shape as inputs, the parameterized model is able to predict rrs with a root mean square relative error of ˜4% for solar zenith angles from 0 to 75°, viewing zenith angles from 0 to 60°, and viewing azimuth angles from 0 to 180°. A test with the field data indicates the performance of our model, when using only a and bb as inputs and selecting the VSF shape using bb, is comparable to or slightly better than the currently used models by Morel et al. and Lee et al. Explicitly expressing VSF shapes in rrs modeling has great potential to further constrain the uncertainty in the ocean color studies as our knowledge on the VSFs of natural particles continues to improve. Our study represents a first effort in this direction.

Remote sensing and GIS for land use/cover mapping and integrated land management: case from the middle Ganga plain

NASA Astrophysics Data System (ADS)

Singh, R. B.; Kumar, Dilip

2012-06-01

In India, land resources have reached a critical stage due to the rapidly growing population. This challenge requires an integrated approach toward harnessing land resources, while taking into account the vulnerable environmental conditions. Remote sensing and Geographical Information System (GIS) based technologies may be applied to an area in order to generate a sustainable development plan that is optimally suited to the terrain and to the productive potential of the local resources. The present study area is a part of the middle Ganga plain, known as Son-Karamnasa interfluve, in India. Alternative land use systems and the integration of livestock enterprises with the agricultural system have been suggested for land resources management. The objective of this paper is to prepare a land resource development plan in order to increase the productivity of land for sustainable development. The present study will contribute necessary input for policy makers to improve the socio-economic and environmental conditions of the region.

Improving evaluation of climate change impacts on the water cycle by remote sensing ET-retrieval

NASA Astrophysics Data System (ADS)

García Galiano, S. G.; Olmos Giménez, P.; Ángel Martínez Pérez, J.; Diego Giraldo Osorio, J.

2015-05-01

Population growth and intense consumptive water uses are generating pressures on water resources in the southeast of Spain. Improving the knowledge of the climate change impacts on water cycle processes at the basin scale is a step to building adaptive capacity. In this work, regional climate model (RCM) ensembles are considered as an input to the hydrological model, for improving the reliability of hydroclimatic projections. To build the RCMs ensembles, the work focuses on probability density function (PDF)-based evaluation of the ability of RCMs to simulate of rainfall and temperature at the basin scale. To improve the spatial calibration of the continuous hydrological model used, an algorithm for remote sensing actual evapotranspiration (AET) retrieval was applied. From the results, a clear decrease in runoff is expected for 2050 in the headwater basin studied. The plausible future scenario of water shortage will produce negative impacts on the regional economy, where the main activity is irrigated agriculture.

Ultrasonic sensing of GMAW: Laser/EMAT defect detection system. [Gas Metal Arc Welding (GMAW), Electromagnetic acoustic transducer (EMAT)

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

Carlson, N.M.; Johnson, J.A.; Larsen, E.D.

1992-01-01

In-process ultrasonic sensing of welding allows detection of weld defects in real time. A noncontacting ultrasonic system is being developed to operate in a production environment. The principal components are a pulsed laser for ultrasound generation and an electromagnetic acoustic transducer (EMAT) for ultrasound reception. A PC-based data acquisition system determines the quality of the weld on a pass-by-pass basis. The laser/EMAT system interrogates the area in the weld volume where defects are most likely to occur. This area of interest is identified by computer calculations on a pass-by-pass basis using weld planning information provided by the off-line programmer. Themore » absence of a signal above the threshold level in the computer-calculated time interval indicates a disruption of the sound path by a defect. The ultrasonic sensor system then provides an input signal to the weld controller about the defect condition. 8 refs.« less

Haptic feedback in OP:Sense - augmented reality in telemanipulated robotic surgery.

PubMed

Beyl, T; Nicolai, P; Mönnich, H; Raczkowksy, J; Wörn, H

2012-01-01

In current research, haptic feedback in robot assisted interventions plays an important role. However most approaches to haptic feedback only regard the mapping of the current forces at the surgical instrument to the haptic input devices, whereas surgeons demand a combination of medical imaging and telemanipulated robotic setups. In this paper we describe how this feature is integrated in our robotic research platform OP:Sense. The proposed method allows the automatic transfer of segmented imaging data to the haptic renderer and therefore allows enriching the haptic feedback with virtual fixtures based on imaging data. Anatomical structures are extracted from pre-operative generated medical images or virtual walls are defined by the surgeon inside the imaging data. Combining real forces with virtual fixtures can guide the surgeon to the regions of interest as well as helps to prevent the risk of damage to critical structures inside the patient. We believe that the combination of medical imaging and telemanipulation is a crucial step for the next generation of MIRS-systems.

Process Algebra Approach for Action Recognition in the Maritime Domain

NASA Technical Reports Server (NTRS)

Huntsberger, Terry

2011-01-01

The maritime environment poses a number of challenges for autonomous operation of surface boats. Among these challenges are the highly dynamic nature of the environment, the onboard sensing and reasoning requirements for obeying the navigational rules of the road, and the need for robust day/night hazard detection and avoidance. Development of full mission level autonomy entails addressing these challenges, coupled with inference of the tactical and strategic intent of possibly adversarial vehicles in the surrounding environment. This paper introduces PACIFIC (Process Algebra Capture of Intent From Information Content), an onboard system based on formal process algebras that is capable of extracting actions/activities from sensory inputs and reasoning within a mission context to ensure proper responses. PACIFIC is part of the Behavior Engine in CARACaS (Cognitive Architecture for Robotic Agent Command and Sensing), a system that is currently running on a number of U.S. Navy unmanned surface and underwater vehicles. Results from a series of experimental studies that demonstrate the effectiveness of the system are also presented.

Fusion of shallow and deep features for classification of high-resolution remote sensing images

NASA Astrophysics Data System (ADS)

Gao, Lang; Tian, Tian; Sun, Xiao; Li, Hang

2018-02-01

Effective spectral and spatial pixel description plays a significant role for the classification of high resolution remote sensing images. Current approaches of pixel-based feature extraction are of two main kinds: one includes the widelyused principal component analysis (PCA) and gray level co-occurrence matrix (GLCM) as the representative of the shallow spectral and shape features, and the other refers to the deep learning-based methods which employ deep neural networks and have made great promotion on classification accuracy. However, the former traditional features are insufficient to depict complex distribution of high resolution images, while the deep features demand plenty of samples to train the network otherwise over fitting easily occurs if only limited samples are involved in the training. In view of the above, we propose a GLCM-based convolution neural network (CNN) approach to extract features and implement classification for high resolution remote sensing images. The employment of GLCM is able to represent the original images and eliminate redundant information and undesired noises. Meanwhile, taking shallow features as the input of deep network will contribute to a better guidance and interpretability. In consideration of the amount of samples, some strategies such as L2 regularization and dropout methods are used to prevent over-fitting. The fine-tuning strategy is also used in our study to reduce training time and further enhance the generalization performance of the network. Experiments with popular data sets such as PaviaU data validate that our proposed method leads to a performance improvement compared to individual involved approaches.

Runoff simulation sensitivity to remotely sensed initial soil water content

NASA Astrophysics Data System (ADS)

Goodrich, D. C.; Schmugge, T. J.; Jackson, T. J.; Unkrich, C. L.; Keefer, T. O.; Parry, R.; Bach, L. B.; Amer, S. A.

1994-05-01

A variety of aircraft remotely sensed and conventional ground-based measurements of volumetric soil water content (SW) were made over two subwatersheds (4.4 and 631 ha) of the U.S. Department of Agriculture's Agricultural Research Service Walnut Gulch experimental watershed during the 1990 monsoon season. Spatially distributed soil water contents estimated remotely from the NASA push broom microwave radiometer (PBMR), an Institute of Radioengineering and Electronics (IRE) multifrequency radiometer, and three ground-based point methods were used to define prestorm initial SW for a distributed rainfall-runoff model (KINEROS; Woolhiser et al., 1990) at a small catchment scale (4.4 ha). At a medium catchment scale (631 ha or 6.31 km2) spatially distributed PBMR SW data were aggregated via stream order reduction. The impacts of the various spatial averages of SW on runoff simulations are discussed and are compared to runoff simulations using SW estimates derived from a simple daily water balance model. It was found that at the small catchment scale the SW data obtained from any of the measurement methods could be used to obtain reasonable runoff predictions. At the medium catchment scale, a basin-wide remotely sensed average of initial water content was sufficient for runoff simulations. This has important implications for the possible use of satellite-based microwave soil moisture data to define prestorm SW because the low spatial resolutions of such sensors may not seriously impact runoff simulations under the conditions examined. However, at both the small and medium basin scale, adequate resources must be devoted to proper definition of the input rainfall to achieve reasonable runoff simulations.

Being First Matters: Topographical Representational Similarity Analysis of ERP Signals Reveals Separate Networks for Audiovisual Temporal Binding Depending on the Leading Sense.

PubMed

Cecere, Roberto; Gross, Joachim; Willis, Ashleigh; Thut, Gregor

2017-05-24

In multisensory integration, processing in one sensory modality is enhanced by complementary information from other modalities. Intersensory timing is crucial in this process because only inputs reaching the brain within a restricted temporal window are perceptually bound. Previous research in the audiovisual field has investigated various features of the temporal binding window, revealing asymmetries in its size and plasticity depending on the leading input: auditory-visual (AV) or visual-auditory (VA). Here, we tested whether separate neuronal mechanisms underlie this AV-VA dichotomy in humans. We recorded high-density EEG while participants performed an audiovisual simultaneity judgment task including various AV-VA asynchronies and unisensory control conditions (visual-only, auditory-only) and tested whether AV and VA processing generate different patterns of brain activity. After isolating the multisensory components of AV-VA event-related potentials (ERPs) from the sum of their unisensory constituents, we ran a time-resolved topographical representational similarity analysis (tRSA) comparing the AV and VA ERP maps. Spatial cross-correlation matrices were built from real data to index the similarity between the AV and VA maps at each time point (500 ms window after stimulus) and then correlated with two alternative similarity model matrices: AV maps = VA maps versus AV maps ≠ VA maps The tRSA results favored the AV maps ≠ VA maps model across all time points, suggesting that audiovisual temporal binding (indexed by synchrony perception) engages different neural pathways depending on the leading sense. The existence of such dual route supports recent theoretical accounts proposing that multiple binding mechanisms are implemented in the brain to accommodate different information parsing strategies in auditory and visual sensory systems. SIGNIFICANCE STATEMENT Intersensory timing is a crucial aspect of multisensory integration, determining whether and how inputs in one modality enhance stimulus processing in another modality. Our research demonstrates that evaluating synchrony of auditory-leading (AV) versus visual-leading (VA) audiovisual stimulus pairs is characterized by two distinct patterns of brain activity. This suggests that audiovisual integration is not a unitary process and that different binding mechanisms are recruited in the brain based on the leading sense. These mechanisms may be relevant for supporting different classes of multisensory operations, for example, auditory enhancement of visual attention (AV) and visual enhancement of auditory speech (VA). Copyright © 2017 Cecere et al.

Optimization of the resolution of remotely sensed digital elevation model to facilitate the simulation and spatial propagation of flood events in flat areas

NASA Astrophysics Data System (ADS)

Karapetsas, Nikolaos; Skoulikaris, Charalampos; Katsogiannos, Fotis; Zalidis, George; Alexandridis, Thomas

2013-04-01

The use of satellite remote sensing products, such as Digital Elevation Models (DEMs), under specific computational interfaces of Geographic Information Systems (GIS) has fostered and facilitated the acquisition of data on specific hydrologic features, such as slope, flow direction and flow accumulation, which are crucial inputs to hydrology or hydraulic models at the river basin scale. However, even though DEMs of different resolution varying from a few km up to 20m are freely available for the European continent, these remotely sensed elevation data are rather coarse in cases where large flat areas are dominant inside a watershed, resulting in an unsatisfactory representation of the terrain characteristics. This scientific work aims at implementing a combing interpolation technique for the amelioration of the analysis of a DEM in order to be used as the input ground model to a hydraulic model for the assessment of potential flood events propagation in plains. More specifically, the second version of the ASTER Global Digital Elevation Model (GDEM2), which has an overall accuracy of around 20 meters, was interpolated with a vast number of aerial control points available from the Hellenic Mapping and Cadastral Organization (HMCO). The uncertainty that was inherent in both the available datasets (ASTER & HMCO) and the appearance of uncorrelated errors and artifacts was minimized by incorporating geostatistical filtering. The resolution of the produced DEM was approximately 10 meters and its validation was conducted with the use of an external dataset of 220 geodetic survey points. The derived DEM was then used as an input to the hydraulic model InfoWorks RS, whose operation is based on the relief characteristics contained in the ground model, for defining, in an automated way, the cross section parameters and simulating the flood spatial distribution. The plain of Serres, which is located in the downstream part of the Struma/Strymon transboundary river basin shared by Bulgaria and Greece, was selected as the case study area, because of its importance to the regional and national economy of Greece and because of the numerous flood events recorded in the past. The results of the simulation processing demonstrated the importance of high resolution relief models for estimating the potential flood hazard zones in order to mitigate the catastrophe caused, both in economic and environmental terms, by this type of extreme event.

Being First Matters: Topographical Representational Similarity Analysis of ERP Signals Reveals Separate Networks for Audiovisual Temporal Binding Depending on the Leading Sense

PubMed Central

2017-01-01

In multisensory integration, processing in one sensory modality is enhanced by complementary information from other modalities. Intersensory timing is crucial in this process because only inputs reaching the brain within a restricted temporal window are perceptually bound. Previous research in the audiovisual field has investigated various features of the temporal binding window, revealing asymmetries in its size and plasticity depending on the leading input: auditory–visual (AV) or visual–auditory (VA). Here, we tested whether separate neuronal mechanisms underlie this AV–VA dichotomy in humans. We recorded high-density EEG while participants performed an audiovisual simultaneity judgment task including various AV–VA asynchronies and unisensory control conditions (visual-only, auditory-only) and tested whether AV and VA processing generate different patterns of brain activity. After isolating the multisensory components of AV–VA event-related potentials (ERPs) from the sum of their unisensory constituents, we ran a time-resolved topographical representational similarity analysis (tRSA) comparing the AV and VA ERP maps. Spatial cross-correlation matrices were built from real data to index the similarity between the AV and VA maps at each time point (500 ms window after stimulus) and then correlated with two alternative similarity model matrices: AVmaps = VAmaps versus AVmaps ≠ VAmaps. The tRSA results favored the AVmaps ≠ VAmaps model across all time points, suggesting that audiovisual temporal binding (indexed by synchrony perception) engages different neural pathways depending on the leading sense. The existence of such dual route supports recent theoretical accounts proposing that multiple binding mechanisms are implemented in the brain to accommodate different information parsing strategies in auditory and visual sensory systems. SIGNIFICANCE STATEMENT Intersensory timing is a crucial aspect of multisensory integration, determining whether and how inputs in one modality enhance stimulus processing in another modality. Our research demonstrates that evaluating synchrony of auditory-leading (AV) versus visual-leading (VA) audiovisual stimulus pairs is characterized by two distinct patterns of brain activity. This suggests that audiovisual integration is not a unitary process and that different binding mechanisms are recruited in the brain based on the leading sense. These mechanisms may be relevant for supporting different classes of multisensory operations, for example, auditory enhancement of visual attention (AV) and visual enhancement of auditory speech (VA). PMID:28450537

Systematic Biological Filter Design with a Desired I/O Filtering Response Based on Promoter-RBS Libraries.

PubMed

Hsu, Chih-Yuan; Pan, Zhen-Ming; Hu, Rei-Hsing; Chang, Chih-Chun; Cheng, Hsiao-Chun; Lin, Che; Chen, Bor-Sen

2015-01-01

In this study, robust biological filters with an external control to match a desired input/output (I/O) filtering response are engineered based on the well-characterized promoter-RBS libraries and a cascade gene circuit topology. In the field of synthetic biology, the biological filter system serves as a powerful detector or sensor to sense different molecular signals and produces a specific output response only if the concentration of the input molecular signal is higher or lower than a specified threshold. The proposed systematic design method of robust biological filters is summarized into three steps. Firstly, several well-characterized promoter-RBS libraries are established for biological filter design by identifying and collecting the quantitative and qualitative characteristics of their promoter-RBS components via nonlinear parameter estimation method. Then, the topology of synthetic biological filter is decomposed into three cascade gene regulatory modules, and an appropriate promoter-RBS library is selected for each module to achieve the desired I/O specification of a biological filter. Finally, based on the proposed systematic method, a robust externally tunable biological filter is engineered by searching the promoter-RBS component libraries and a control inducer concentration library to achieve the optimal reference match for the specified I/O filtering response.

Generalized Hofmann quantum process fidelity bounds for quantum filters

NASA Astrophysics Data System (ADS)

Sedlák, Michal; Fiurášek, Jaromír

2016-04-01

We propose and investigate bounds on the quantum process fidelity of quantum filters, i.e., probabilistic quantum operations represented by a single Kraus operator K . These bounds generalize the Hofmann bounds on the quantum process fidelity of unitary operations [H. F. Hofmann, Phys. Rev. Lett. 94, 160504 (2005), 10.1103/PhysRevLett.94.160504] and are based on probing the quantum filter with pure states forming two mutually unbiased bases. Determination of these bounds therefore requires far fewer measurements than full quantum process tomography. We find that it is particularly suitable to construct one of the probe bases from the right eigenstates of K , because in this case the bounds are tight in the sense that if the actual filter coincides with the ideal one, then both the lower and the upper bounds are equal to 1. We theoretically investigate the application of these bounds to a two-qubit optical quantum filter formed by the interference of two photons on a partially polarizing beam splitter. For an experimentally convenient choice of factorized input states and measurements we study the tightness of the bounds. We show that more stringent bounds can be obtained by more sophisticated processing of the data using convex optimization and we compare our methods for different choices of the input probe states.

Incomplete data based parameter identification of nonlinear and time-variant oscillators with fractional derivative elements

NASA Astrophysics Data System (ADS)

Kougioumtzoglou, Ioannis A.; dos Santos, Ketson R. M.; Comerford, Liam

2017-09-01

Various system identification techniques exist in the literature that can handle non-stationary measured time-histories, or cases of incomplete data, or address systems following a fractional calculus modeling. However, there are not many (if any) techniques that can address all three aforementioned challenges simultaneously in a consistent manner. In this paper, a novel multiple-input/single-output (MISO) system identification technique is developed for parameter identification of nonlinear and time-variant oscillators with fractional derivative terms subject to incomplete non-stationary data. The technique utilizes a representation of the nonlinear restoring forces as a set of parallel linear sub-systems. In this regard, the oscillator is transformed into an equivalent MISO system in the wavelet domain. Next, a recently developed L1-norm minimization procedure based on compressive sensing theory is applied for determining the wavelet coefficients of the available incomplete non-stationary input-output (excitation-response) data. Finally, these wavelet coefficients are utilized to determine appropriately defined time- and frequency-dependent wavelet based frequency response functions and related oscillator parameters. Several linear and nonlinear time-variant systems with fractional derivative elements are used as numerical examples to demonstrate the reliability of the technique even in cases of noise corrupted and incomplete data.

An Internet of Things System for Underground Mine Air Quality Pollutant Prediction Based on Azure Machine Learning

PubMed Central

Jo, ByungWan

2018-01-01

The implementation of wireless sensor networks (WSNs) for monitoring the complex, dynamic, and harsh environment of underground coal mines (UCMs) is sought around the world to enhance safety. However, previously developed smart systems are limited to monitoring or, in a few cases, can report events. Therefore, this study introduces a reliable, efficient, and cost-effective internet of things (IoT) system for air quality monitoring with newly added features of assessment and pollutant prediction. This system is comprised of sensor modules, communication protocols, and a base station, running Azure Machine Learning (AML) Studio over it. Arduino-based sensor modules with eight different parameters were installed at separate locations of an operational UCM. Based on the sensed data, the proposed system assesses mine air quality in terms of the mine environment index (MEI). Principal component analysis (PCA) identified CH4, CO, SO2, and H2S as the most influencing gases significantly affecting mine air quality. The results of PCA were fed into the ANN model in AML studio, which enabled the prediction of MEI. An optimum number of neurons were determined for both actual input and PCA-based input parameters. The results showed a better performance of the PCA-based ANN for MEI prediction, with R2 and RMSE values of 0.6654 and 0.2104, respectively. Therefore, the proposed Arduino and AML-based system enhances mine environmental safety by quickly assessing and predicting mine air quality. PMID:29561777

An Internet of Things System for Underground Mine Air Quality Pollutant Prediction Based on Azure Machine Learning.

PubMed

Jo, ByungWan; Khan, Rana Muhammad Asad

2018-03-21

The implementation of wireless sensor networks (WSNs) for monitoring the complex, dynamic, and harsh environment of underground coal mines (UCMs) is sought around the world to enhance safety. However, previously developed smart systems are limited to monitoring or, in a few cases, can report events. Therefore, this study introduces a reliable, efficient, and cost-effective internet of things (IoT) system for air quality monitoring with newly added features of assessment and pollutant prediction. This system is comprised of sensor modules, communication protocols, and a base station, running Azure Machine Learning (AML) Studio over it. Arduino-based sensor modules with eight different parameters were installed at separate locations of an operational UCM. Based on the sensed data, the proposed system assesses mine air quality in terms of the mine environment index (MEI). Principal component analysis (PCA) identified CH₄, CO, SO₂, and H₂S as the most influencing gases significantly affecting mine air quality. The results of PCA were fed into the ANN model in AML studio, which enabled the prediction of MEI. An optimum number of neurons were determined for both actual input and PCA-based input parameters. The results showed a better performance of the PCA-based ANN for MEI prediction, with R ² and RMSE values of 0.6654 and 0.2104, respectively. Therefore, the proposed Arduino and AML-based system enhances mine environmental safety by quickly assessing and predicting mine air quality.

Remote sensing techniques for monitoring drought hazards: an intercomparison (Invited)

NASA Astrophysics Data System (ADS)

Brown, J. F.; Anderson, M. C.; Wardlow, B. D.; Svoboda, M. D.

2009-12-01

Drought events are frequently described using many different terms; for example, recurring climate phenomena, creeping natural hazards, agricultural disasters, and moisture deficiencies. In addition, droughts operate at many different spatial and temporal scales and affect different societal sectors, making them quite challenging to monitor, map, and assess impacts. Because of these factors, determining drought severity often requires using a convergence of evidence assisted by an analysis of multiple drought indicators. Frequent optical and thermal observations collected by daily polar-orbiting and geostationary satellites allow for regular monitoring of the land surface. In recent decades, with the launching of more advanced sensors and the maturation of remote sensing techniques, a variety of tools have been designed for improved understanding and tracking of drought events as they are occurring. These applications are intended to provide key decision makers with timely geospatial drought information to support various drought planning and mitigation activities. Two such tools highlighted in this study, are the Vegetation Drought Response Index (VegDRI) and the Evaporative Stress Index (ESI). While both indices incorporate satellite-based inputs, they are involved in different modeling approaches and observations from different parts of the electromagnetic spectrum. The VegDRI is a hybrid remote sensing and climate based indicator of drought-induced vegetation stress that combines satellite-based vegetation index observations from Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Very High Resolution Radiometer (AVHRR) sensors with climate-based drought index data and other biophysical parameters (such as land use/land cover type and soil characteristics). VegDRI provides near real-time vegetation drought severity information at relatively higher spatial resolution (1-km2) than traditional climatic drought indices such as the Standardized Precipitation Index (SPI) or the U.S. Drought Monitor (USDM), which tend to depicted broad-scale spatial drought patterns. . The ESI is an indicator of anomalous land-surface evaporation and soil moisture deficiency. The ESI is related to the ratio of actual-to-potential evapotranspiration (ET), where actual ET is estimated with a thermal-infrared (TIR) based surface energy balance algorithm. The ESI product is generated in near-real time at 10-km2 resolution over the continental U.S. using TIR imagery from the Geostationary Operational Environmental Satellites (GOES). Because it does not use precipitation data as an input, it is a valuable complement to existing precipitation-based indices and is readily portable to data-poor regions with sparse ground-based rainfall monitoring networks. In this study, we present an intercomparison of the VegDRI and the ESI for the 2009 growing season, highlighting weekly, monthly, and seasonal patterns of moisture flux from soils and vegetation.

Landsat Thematic Mapper studies of land cover spatial variability related to hydrology

NASA Technical Reports Server (NTRS)

Wharton, S.; Ormsby, J.; Salomonson, V.; Mulligan, P.

1984-01-01

Past accomplishments involving remote sensing based land-cover analysis for hydrologic applications are reviewed. Ongoing research in exploiting the increased spatial, radiometric, and spectral capabilities afforded by the TM on Landsats 4 and 5 is considered. Specific studies to compare MSS and TM for urbanizing watersheds, wetlands, and floodplain mapping situations show that only a modest improvement in classification accuracy is achieved via statistical per pixel multispectral classifiers. The limitations of current approaches to multispectral classification are illustrated. The objectives, background, and progress in the development of an alternative analysis approach for defining inputs to urban hydrologic models using TM are discussed.

Remote Sensing of Vegetation Nitrogen Content for Spatially Explicit Carbon and Water Cycle Estimation

NASA Astrophysics Data System (ADS)

Zhang, Y. L.; Miller, J. R.; Chen, J. M.

2009-05-01

Foliage nitrogen concentration is a determinant of photosynthetic capacity of leaves, thereby an important input to ecological models for estimating terrestrial carbon and water budgets. Recently, spectrally continuous airborne hyperspectral remote sensing imagery has proven to be useful for retrieving an important related parameter, total chlorophyll content at both leaf and canopy scales. Thus remote sensing of vegetation biochemical parameters has promising potential for improving the prediction of global carbon and water balance patterns. In this research, we explored the feasibility of estimating leaf nitrogen content using hyperspectral remote sensing data for spatially explicit estimation of carbon and water budgets. Multi-year measurements of leaf biochemical contents of seven major boreal forest species were carried out in northeastern Ontario, Canada. The variation of leaf chlorophyll and nitrogen content in response to various growth conditions, and the relationship between them,were investigated. Despite differences in plant type (deciduous and evergreen), leaf age, stand growth conditions and developmental stages, leaf nitrogen content was strongly correlated with leaf chlorophyll content on a mass basis during the active growing season (r2=0.78). With this general correlation, leaf nitrogen content was estimated from leaf chlorophyll content at an accuracy of RMSE=2.2 mg/g, equivalent to 20.5% of the average measured leaf nitrogen content. Based on this correlation and a hyperspectral remote sensing algorithm for leaf chlorophyll content retrieval, the spatial variation of leaf nitrogen content was inferred from the airborne hyperspectral remote sensing imagery acquired by Compact Airborne Spectrographic Imager (CASI). A process-based ecological model Boreal Ecosystem Productivity Simulator (BEPS) was used for estimating terrestrial carbon and water budgets. In contrast to the scenario with leaf nitrogen content assigned as a constant value without differentiation between and within vegetation types for calculating the photosynthesis rate, we incorporated the spatial distribution of leaf nitrogen content in the model to estimate net primary productivity and evaportranspiration of boreal ecosystem. These regional estimates of carbon and water budgets with and without N mapping are compared, and the importance of this leaf biochemistry information derived from hyperspectral remote sensing in regional mapping of carbon and water fluxes is quantitatively assessed. Keywords: Remote Sensing, Leaf Nitrogen Content, Spatial Distribution, Carbon and Water Budgets, Estimation

Real-time skeleton tracking for embedded systems

NASA Astrophysics Data System (ADS)

Coleca, Foti; Klement, Sascha; Martinetz, Thomas; Barth, Erhardt

2013-03-01

Touch-free gesture technology is beginning to become more popular with consumers and may have a significant future impact on interfaces for digital photography. However, almost every commercial software framework for gesture and pose detection is aimed at either desktop PCs or high-powered GPUs, making mobile implementations for gesture recognition an attractive area for research and development. In this paper we present an algorithm for hand skeleton tracking and gesture recognition that runs on an ARM-based platform (Pandaboard ES, OMAP 4460 architecture). The algorithm uses self-organizing maps to fit a given topology (skeleton) into a 3D point cloud. This is a novel way of approaching the problem of pose recognition as it does not employ complex optimization techniques or data-based learning. After an initial background segmentation step, the algorithm is ran in parallel with heuristics, which detect and correct artifacts arising from insufficient or erroneous input data. We then optimize the algorithm for the ARM platform using fixed-point computation and the NEON SIMD architecture the OMAP4460 provides. We tested the algorithm with two different depth-sensing devices (Microsoft Kinect, PMD Camboard). For both input devices we were able to accurately track the skeleton at the native framerate of the cameras.

The economic value of remote sensing of earth resources from space: An ERTS overview and the value of continuity of service. Volume 9: Oceans

NASA Technical Reports Server (NTRS)

Lietzke, K. R.

1974-01-01

The impact of remote sensing upon marine activities and oceanography is presented. The present capabilities of the current Earth Resources Technology Satellite (ERTS-1), as demonstrated by the principal investigators are discussed. Cost savings benefits are quantified in the area of nautical and hygrographic mapping and charting. Benefits are found in aiding coastal zone management and in the fields of weather (marine) prediction, fishery harvesting and management, and potential uses for ocean vegetation. Difficulties in quantification are explained, the primary factor being that remotely sensed information will be of greater benefit as input to forecasting models which have not yet been constructed.

Experimental and theoretical study of the in- fiber twist sensor based on quasi-fan Solc structure filter.

PubMed

Sun, Chunran; Wang, Muguang; Jian, Shuisheng

2017-08-21

In this paper, a novel quasi-fan Solc structure filter based on elliptical-core spun fiber for twist sensing has been experimentally investigated and theoretically analyzed. The discrete model of spun fiber has been built to analyze the transmission characteristics of proposed sensor. Both experimental and simulated results indicate that the extinction ratio of the comb spectrum based on quasi-fan Solc birefringent fiber filter varies with twist angle and agrees well with each other. Based on the intensity modulation, the proposed twist sensor exhibits a high sensitivity of 0.02219 dB/(°/m). Moreover, thanks to the invariability of the fiber birefringence and the state of polarization of the input light, the proposed twist sensor has a very low temperature and strain sensitivity, which can avoid the cross-sensitivity problem existing in most twist sensors.

Assessment of Antarctic Ice-Sheet Mass Balance Estimates: 1992 - 2009

NASA Technical Reports Server (NTRS)

Zwally, H. Jay; Giovinetto, Mario B.

2011-01-01

Published mass balance estimates for the Antarctic Ice Sheet (AIS) lie between approximately +50 to -250 Gt/year for 1992 to 2009, which span a range equivalent to 15% of the annual mass input and 0.8 mm/year Sea Level Equivalent (SLE). Two estimates from radar-altimeter measurements of elevation change by European Remote-sensing Satellites (ERS) (+28 and -31 Gt/year) lie in the upper part, whereas estimates from the Input-minus-Output Method (IOM) and the Gravity Recovery and Climate Experiment (GRACE) lie in the lower part (-40 to -246 Gt/year). We compare the various estimates, discuss the methodology used, and critically assess the results. Although recent reports of large and accelerating rates of mass loss from GRACE=based studies cite agreement with IOM results, our evaluation does not support that conclusion. We find that the extrapolation used in the published IOM estimates for the 15 % of the periphery for which discharge velocities are not observed gives twice the rate of discharge per unit of associated ice-sheet area than the 85% faster-moving parts. Our calculations show that the published extrapolation overestimates the ice discharge by 282 Gt/yr compared to our assumption that the slower moving areas have 70% as much discharge per area as the faster moving parts. Also, published data on the time-series of discharge velocities and accumulation/precipitation do not support mass output increases or input decreases with time, respectively. Our modified IOM estimate, using the 70% discharge assumption and substituting input from a field-data compilation for input from an atmospheric model over 6% of area, gives a loss of only 13 Gt/year (versus 136 Gt/year) for the period around 2000. Two ERS-based estimates, our modified IOM, and a GRACE-based estimate for observations within 1992 to 2005 lie in a narrowed range of +27 to - 40 Gt/year, which is about 3% of the annual mass input and only 0.2 mm/year SLE. Our preferred estimate for 1992-2001 is - 47 Gt/year for West Antarctica, + 16 Gt/year for East Antarctica, and -31 Gt/year overall (+0.1 mm/year SLE), not including part of the Antarctic Peninsula (1.07 % of the AIS area)

Human sense utilization method on real-time computer graphics

NASA Astrophysics Data System (ADS)

Maehara, Hideaki; Ohgashi, Hitoshi; Hirata, Takao

1997-06-01

We are developing an adjustment method of real-time computer graphics, to obtain effective ones which give audience various senses intended by producer, utilizing human sensibility technologically. Generally, production of real-time computer graphics needs much adjustment of various parameters, such as 3D object models/their motions/attributes/view angle/parallax etc., in order that the graphics gives audience superior effects as reality of materials, sense of experience and so on. And it is also known it costs much to adjust such various parameters by trial and error. A graphics producer often evaluates his graphics to improve it. For example, it may lack 'sense of speed' or be necessary to be given more 'sense of settle down,' to improve it. On the other hand, we can know how the parameters in computer graphics affect such senses by means of statistically analyzing several samples of computer graphics which provide different senses. We paid attention to these two facts, so that we designed an adjustment method of the parameters by inputting phases of sense into a computer. By the way of using this method, it becomes possible to adjust real-time computer graphics more effectively than by conventional way of trial and error.

A flexible and robust approach for segmenting cell nuclei from 2D microscopy images using supervised learning and template matching

PubMed Central

Chen, Cheng; Wang, Wei; Ozolek, John A.; Rohde, Gustavo K.

2013-01-01

We describe a new supervised learning-based template matching approach for segmenting cell nuclei from microscopy images. The method uses examples selected by a user for building a statistical model which captures the texture and shape variations of the nuclear structures from a given dataset to be segmented. Segmentation of subsequent, unlabeled, images is then performed by finding the model instance that best matches (in the normalized cross correlation sense) local neighborhood in the input image. We demonstrate the application of our method to segmenting nuclei from a variety of imaging modalities, and quantitatively compare our results to several other methods. Quantitative results using both simulated and real image data show that, while certain methods may work well for certain imaging modalities, our software is able to obtain high accuracy across several imaging modalities studied. Results also demonstrate that, relative to several existing methods, the template-based method we propose presents increased robustness in the sense of better handling variations in illumination, variations in texture from different imaging modalities, providing more smooth and accurate segmentation borders, as well as handling better cluttered nuclei. PMID:23568787

A new approach to estimating evaporation from lakes and reservoirs based on energy balance and remote sensing data

NASA Astrophysics Data System (ADS)

Majidi, Maysam; Sadeghi, Morteza; Shafiei, Mojtaba; Alizadeh, Amin; Farid, Alireza; Azad, Mohammadreza; Vazifedoust, Majid

2016-04-01

Estimating evaporation from water bodies such as lakes and reservoirs is commonly a difficult task, especially due to the lack of reliable and available ground data. Remote sensing (RS) data has shown a great potential for filling the gap. Nonetheless, interpretation of the RS data (e.g. optical reflectance, thermal emission, etc.) for estimating water evaporation has remained as a challenge. In this paper, we present a novel approach for estimating water evaporation based on satellite RS data and some readily measurable ground data. In the proposed approach, named as "Reference and Water surface Energy Balance (RWEB)", we define a reference surface and then solve the energy balance equation simultaneously for the reference surfaces and water surface. This approach was tested over the Doosti dam reservoir (north east of Iran) using whether station and RS data as well as water temperature measured biweekly along the study. Accuracy of the RWEB algorithm was examined by comparison to the standard "Bowen Ratio Energy Balance (BREB)" RS algorithm. The RMSD value of 0.047 mm/year indicated a good agreement between RWEB and BREB algorithms, while RWEB provides an easier-to-use approach regarding its required input variables.

Grid-cell-based crop water accounting for the famine early warning system

USGS Publications Warehouse

Verdin, J.; Klaver, R.

2002-01-01

Rainfall monitoring is a regular activity of food security analysts for sub-Saharan Africa due to the potentially disastrous impact of drought. Crop water accounting schemes are used to track rainfall timing and amounts relative to phenological requirements, to infer water limitation impacts on yield. Unfortunately, many rain gauge reports are available only after significant delays, and the gauge locations leave large gaps in coverage. As an alternative, a grid-cell-based formulation for the water requirement satisfaction index (WRSI) was tested for maize in Southern Africa. Grids of input variables were obtained from remote sensing estimates of rainfall, meteorological models, and digital soil maps. The spatial WRSI was computed for the 1996–97 and 1997–98 growing seasons. Maize yields were estimated by regression and compared with a limited number of reports from the field for the 1996–97 season in Zimbabwe. Agreement at a useful level (r = 0·80) was observed. This is comparable to results from traditional analysis with station data. The findings demonstrate the complementary role that remote sensing, modelling, and geospatial analysis can play in an era when field data collection in sub-Saharan Africa is suffering an unfortunate decline.

Sensing of metal-transfer mode for process control of GMAW (gas metal arc welding)

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

Carlson, N.M.; Johnson, J.A.; Smartt, H.B.

1989-01-01

One of the requirements of a sensing system for feedback control of gas metal arc welding (GMAW) is the capability to determine the metal-transfer mode. Because the operating boundary for the desired transfer mode, expressed as a function of mass input and heat input, may vary due to conditions beyond the control of the system, a means of detecting the transfer mode during welding is necessary. A series of sensing experiments was performed during which the ultrasonic emissions, audio emissions, welding current fluctuations and welding voltage fluctuations were recorded as a function of the transfer mode. In addition, high speedmore » movies (5000 frames/s) of the droplet formation and detachment were taken synchronously with the sensing data. An LED mounted in the camera was used to mark the film at the beginning and end of the data acquisition period. A second LED was pulsed at a 1 kHz rate and the pulses recorded on film and with the sensor data. Thus events recorded on the film can be correlated with the sensor data. Data acquired during globular transfer, spray transfer, and stiff spray or streaming transfer were observed to correlate with droplet detachment and arc shorting. The audio, current, and voltage data can be used to discriminate among these different transfer modes. However, the current and voltage data are also dependent on the characteristic of the welding power supply. 5 refs., 3 figs., 1 tab.« less

Monitoring Drought at Continental Scales Using Thermal Remote Sensing of Evapotranspiration (Invited)

NASA Astrophysics Data System (ADS)

Anderson, M. C.; Hain, C.; Mecikalski, J. R.; Kustas, W. P.

2009-12-01

Thermal infrared (TIR) remote sensing of land-surface temperature (LST) provides valuable information about the sub-surface moisture status: soil surface temperature increases with decreasing water content, while moisture depletion in the plant root zone leads to stomatal closure, reduced transpiration, and elevated canopy temperatures that can be effectively detected from space. Empirical indices measuring anomalies in LST and vegetation amount (e.g., as quantified by the Normalized Difference Vegetation Index; NDVI) have demonstrated utility in monitoring drought conditions over large areas, but may provide ambiguous results when vegetation growth is limited by energy (radiation, air temperature) rather than moisture. A more physically based interpretation of LST and NDVI and their relationship to sub-surface moisture conditions can be obtained with a surface energy balance model driven by TIR remote sensing. In this approach, moisture stress can be quantified in terms of the reduction of evapotranspiration (ET) from the potential rate (PET) expected under non-moisture limiting conditions. The Atmosphere-Land Exchange Inverse (ALEXI) model couples a two-source (soil+canopy) land-surface model with an atmospheric boundary layer model in time-differencing mode to routinely and robustly map fluxes across the U.S. continent at 5-10km resolution using thermal band imagery from the Geostationary Operational Environmental Satellites (GOES). Finer resolution flux maps can be generated through spatial disaggregation using TIR data from polar orbiting instruments such as Landsat (60-120m) and MODIS (1km). A derived Evaporative Stress Index (ESI), given by 1-ET/PET, shows good correspondence with standard drought metrics and with patterns of antecedent precipitation, but can be produced at significantly higher spatial resolution due to limited reliance on ground observations. Because the ESI does not use precipitation data as input, it provides an independent means for assessing standard meteorologically-based drought indicators, and may be more robust in regions with limited monitoring networks. In this study, monthly maps of ESI anomalies for 2000-2008 are compared to standard drought indices and to drought classifications in the U.S. Drought Monitor. The ESI shows better skill in ranking drought severity than do precipitation-based indices composited over comparable time intervals. The thermal remote sensing inputs to ALEXI detect drought conditions even under the dense forest cover along the East Coast of the United States, where microwave soil moisture retrievals typically lose sensitivity. On the other hand, microwave observations are not constrained by cloud cover and provide better temporal continuity, but typically at significantly lower spatial resolution. A merged TIR-microwave moisture anomaly product may have potential for optimizing both spatial and temporal coverage in continental-scale drought monitoring.

Modeling of extreme freshwater outflow from the north-eastern Japanese river basins to western Pacific Ocean

NASA Astrophysics Data System (ADS)

Troselj, Josko; Sayama, Takahiro; Varlamov, Sergey M.; Sasaki, Toshiharu; Racault, Marie-Fanny; Takara, Kaoru; Miyazawa, Yasumasa; Kuroki, Ryusuke; Yamagata, Toshio; Yamashiki, Yosuke

2017-12-01

This study demonstrates the importance of accurate extreme discharge input in hydrological and oceanographic combined modeling by introducing two extreme typhoon events. We investigated the effects of extreme freshwater outflow events from river mouths on sea surface salinity distribution (SSS) in the coastal zone of the north-eastern Japan. Previous studies have used observed discharge at the river mouth, as well as seasonally averaged inter-annual, annual, monthly or daily simulated data. Here, we reproduced the hourly peak discharge during two typhoon events for a targeted set of nine rivers and compared their impact on SSS in the coastal zone based on observed, climatological and simulated freshwater outflows in conjunction with verification of the results using satellite remote-sensing data. We created a set of hourly simulated freshwater outflow data from nine first-class Japanese river basins flowing to the western Pacific Ocean for the two targeted typhoon events (Chataan and Roke) and used it with the integrated hydrological (CDRMV3.1.1) and oceanographic (JCOPE-T) model, to compare the case using climatological mean monthly discharges as freshwater input from rivers with the case using our hydrological model simulated discharges. By using the CDRMV model optimized with the SCE-UA method, we successfully reproduced hindcasts for peak discharges of extreme typhoon events at the river mouths and could consider multiple river basin locations. Modeled SSS results were verified by comparison with Chlorophyll-a distribution, observed by satellite remote sensing. The projection of SSS in the coastal zone became more realistic than without including extreme freshwater outflow. These results suggest that our hydrological models with optimized model parameters calibrated to the Typhoon Roke and Chataan cases can be successfully used to predict runoff values from other extreme precipitation events with similar physical characteristics. Proper simulation of extreme typhoon events provides more realistic coastal SSS and may allow a different scenario analysis with various precipitation inputs for developing a nowcasting analysis in the future.

VLSI Design of Trusted Virtual Sensors.

PubMed

Martínez-Rodríguez, Macarena C; Prada-Delgado, Miguel A; Brox, Piedad; Baturone, Iluminada

2018-01-25

This work presents a Very Large Scale Integration (VLSI) design of trusted virtual sensors providing a minimum unitary cost and very good figures of size, speed and power consumption. The sensed variable is estimated by a virtual sensor based on a configurable and programmable PieceWise-Affine hyper-Rectangular (PWAR) model. An algorithm is presented to find the best values of the programmable parameters given a set of (empirical or simulated) input-output data. The VLSI design of the trusted virtual sensor uses the fast authenticated encryption algorithm, AEGIS, to ensure the integrity of the provided virtual measurement and to encrypt it, and a Physical Unclonable Function (PUF) based on a Static Random Access Memory (SRAM) to ensure the integrity of the sensor itself. Implementation results of a prototype designed in a 90-nm Complementary Metal Oxide Semiconductor (CMOS) technology show that the active silicon area of the trusted virtual sensor is 0.86 mm 2 and its power consumption when trusted sensing at 50 MHz is 7.12 mW. The maximum operation frequency is 85 MHz, which allows response times lower than 0.25 μ s. As application example, the designed prototype was programmed to estimate the yaw rate in a vehicle, obtaining root mean square errors lower than 1.1%. Experimental results of the employed PUF show the robustness of the trusted sensing against aging and variations of the operation conditions, namely, temperature and power supply voltage (final value as well as ramp-up time).

VLSI Design of Trusted Virtual Sensors

PubMed Central

2018-01-01

This work presents a Very Large Scale Integration (VLSI) design of trusted virtual sensors providing a minimum unitary cost and very good figures of size, speed and power consumption. The sensed variable is estimated by a virtual sensor based on a configurable and programmable PieceWise-Affine hyper-Rectangular (PWAR) model. An algorithm is presented to find the best values of the programmable parameters given a set of (empirical or simulated) input-output data. The VLSI design of the trusted virtual sensor uses the fast authenticated encryption algorithm, AEGIS, to ensure the integrity of the provided virtual measurement and to encrypt it, and a Physical Unclonable Function (PUF) based on a Static Random Access Memory (SRAM) to ensure the integrity of the sensor itself. Implementation results of a prototype designed in a 90-nm Complementary Metal Oxide Semiconductor (CMOS) technology show that the active silicon area of the trusted virtual sensor is 0.86 mm2 and its power consumption when trusted sensing at 50 MHz is 7.12 mW. The maximum operation frequency is 85 MHz, which allows response times lower than 0.25 μs. As application example, the designed prototype was programmed to estimate the yaw rate in a vehicle, obtaining root mean square errors lower than 1.1%. Experimental results of the employed PUF show the robustness of the trusted sensing against aging and variations of the operation conditions, namely, temperature and power supply voltage (final value as well as ramp-up time). PMID:29370141

The use of Space Technology for the Benefit of Society in Context of Planning and Sustainable Development

NASA Astrophysics Data System (ADS)

Kuldeep, Kuldeep; Banu, Vijaya

2016-07-01

The introduction of the novel technology mostly leads to a number of advantages to the society. The space technology has shown such benefits in many fields including the areas of health and education, communication sectors, land and water resources management, weather forecasting and disaster management. It has vast potential for addressing a variety of societal problems of the developing countries especially in India in a effective manner. Large population which is spread over vast and remote areas of the nation, reaching out to them is a difficult task. This manuscript aims to explain the benefits originated from the application of space technology. The satellite imagery and its derived products can better be utilized for local level planning and sustainable development of a region. A case-study using Bhuvan Panchayat Portal developed by National Remote Sensing Centre, ISRO under the project "Space Based Information Support for De-Centralised Planning" towards Digital Empowerment of Society for Panchayat level Planning and Governance has been carried out, which list out the benefits that have accrued from the use of space technology for planning and development at grass root level in India. It covers, in particular, the benefits expected to be derived from the Indian Remote Sensing Satellite (IRS) Images and derived products. Certain conclusions about the benefits from space based inputs have been drawn that may be generally applicable to all developing countries. This paper also investigates the various possibilities and potentials of Remote Sensing technologies for societal applications.

Developing a Data Driven Process-Based Model for Remote Sensing of Ecosystem Production

NASA Astrophysics Data System (ADS)

Elmasri, B.; Rahman, A. F.

2010-12-01

Estimating ecosystem carbon fluxes at various spatial and temporal scales is essential for quantifying the global carbon cycle. Numerous models have been developed for this purpose using several environmental variables as well as vegetation indices derived from remotely sensed data. Here we present a data driven modeling approach for gross primary production (GPP) that is based on a process based model BIOME-BGC. The proposed model was run using available remote sensing data and it does not depend on look-up tables. Furthermore, this approach combines the merits of both empirical and process models, and empirical models were used to estimate certain input variables such as light use efficiency (LUE). This was achieved by using remotely sensed data to the mathematical equations that represent biophysical photosynthesis processes in the BIOME-BGC model. Moreover, a new spectral index for estimating maximum photosynthetic activity, maximum photosynthetic rate index (MPRI), is also developed and presented here. This new index is based on the ratio between the near infrared and the green bands (ρ858.5/ρ555). The model was tested and validated against MODIS GPP product and flux measurements from two eddy covariance flux towers located at Morgan Monroe State Forest (MMSF) in Indiana and Harvard Forest in Massachusetts. Satellite data acquired by the Advanced Microwave Scanning Radiometer (AMSR-E) and MODIS were used. The data driven model showed a strong correlation between the predicted and measured GPP at the two eddy covariance flux towers sites. This methodology produced better predictions of GPP than did the MODIS GPP product. Moreover, the proportion of error in the predicted GPP for MMSF and Harvard forest was dominated by unsystematic errors suggesting that the results are unbiased. The analysis indicated that maintenance respiration is one of the main factors that dominate the overall model outcome errors and improvement in maintenance respiration estimation will result in improved GPP predictions. Although there might be a room for improvements in our model outcomes through improved parameterization, our results suggest that such a methodology for running BIOME-BGC model based entirely on routinely available data can produce good predictions of GPP.

Tephra dispersal and fallout reconstructed integrating field, ground-based and satellite-based data: Application to the 23rd November 2013 Etna paroxysm

NASA Astrophysics Data System (ADS)

Poret, M.; Corradini, S.; Merucci, L.; Costa, A.; Andronico, D.; Montopoli, M.; Vulpiani, G.; Scollo, S.; Freret-Lorgeril, V.

2017-12-01

On the 23rd November 2013, Etna erupted giving one of the most intense lava fountain recorded. The eruption produced a buoyant plume that rose higher than 10 km a.s.l. from which two volcanic clouds were observed from satellite at two different atmospheric levels. A Previous study described one of the two clouds as mainly composed by ash making use of remote sensing instruments. Besides, the second cloud is made of ice/SO2 droplets and is not measurable in terms of ash mass. Both clouds spread out under north-easterly winds transporting the tephra from Etna towards the Puglia region. The untypical meteorological conditions permit to collect tephra samples in proximal areas to the Etna emission source as well as far away in the Calabria region. The eruption was observed by satellite (MSG-SEVIRI, MODIS) and ground-based (X-band weather radar, VIS/IR cameras and L-band Doppler radar) remote sensing systems. This study uses the FALL3D code to model the evolution of the plume and the tephra deposition by constraining the simulation results with remote sensing products for volcanic cloud (cloud height, fine ash Mass - Ma, Aerosol Optical Depth at 0.55 mm - AOD). Among the input parameters, the Total Grain-Size Distribution (TGSD) is reconstructed by integrating field deposits with estimations from the X-band radar data. The optimal TGSD was selected through an inverse problem method that best-fits both the field deposits and airborne measurements. The results of the simulations capture the main behavior of the two volcanic clouds at their altitudes. The best agreement between the simulated Ma and AOD and the SEVIRI retrievals indicates a PM20 fraction of 3.4 %. The total erupted mass is estimated at 1.6 × 109 kg in consistency with the estimations made from remote sensing data (3.0 × 109 kg) and ground deposit (1.3 × 109 kg).

Method and system to perform energy-extraction based active noise control

NASA Technical Reports Server (NTRS)

Kelkar, Atul (Inventor); Joshi, Suresh M. (Inventor)

2009-01-01

A method to provide active noise control to reduce noise and vibration in reverberant acoustic enclosures such as aircraft, vehicles, appliances, instruments, industrial equipment and the like is presented. A continuous-time multi-input multi-output (MIMO) state space mathematical model of the plant is obtained via analytical modeling and system identification. Compensation is designed to render the mathematical model passive in the sense of mathematical system theory. The compensated system is checked to ensure robustness of the passive property of the plant. The check ensures that the passivity is preserved if the mathematical model parameters are perturbed from nominal values. A passivity-based controller is designed and verified using numerical simulations and then tested. The controller is designed so that the resulting closed-loop response shows the desired noise reduction.

High speed sampler and demultiplexer

DOEpatents

McEwan, Thomas E.

1995-01-01

A high speed sampling demultiplexer based on a plurality of sampler banks, each bank comprising a sample transmission line for transmitting an input signal, a strobe transmission line for transmitting a strobe signal, and a plurality of sampling gates at respective positions along the sample transmission line for sampling the input signal in response to the strobe signal. Strobe control circuitry is coupled to the plurality of banks, and supplies a sequence of bank strobe signals to the strobe transmission lines in each of the plurality of banks, and includes circuits for controlling the timing of the bank strobe signals among the banks of samplers. Input circuitry is included for supplying the input signal to be sampled to the plurality of sample transmission lines in the respective banks. The strobe control circuitry can repetitively strobe the plurality of banks of samplers such that the banks of samplers are cycled to create a long sample length. Second tier demultiplexing circuitry is coupled to each of the samplers in the plurality of banks. The second tier demultiplexing circuitry senses the sample taken by the corresponding sampler each time the bank in which the sampler is found is strobed. A plurality of such samples can be stored by the second tier demultiplexing circuitry for later processing. Repetitive sampling with the high speed transient sampler induces an effect known as "strobe kickout". The sample transmission lines include structures which reduce strobe kickout to acceptable levels, generally 60 dB below the signal, by absorbing the kickout pulses before the next sampling repetition.

Coastal erosion vs riverline sediment discharge in the Arctic shelfx seas

USGS Publications Warehouse

Rachold, V.; Grigoriev, M.N.; Are, F.E.; Solomon, Sean C.; Reimnitz, E.; Kassens, H.; Antonow, M.

2000-01-01

This article presents a comparison of sediment input by rivers and by coastal erosion into both the Laptev Sea and the Canadian Beaufort Sea (CBS). New data on coastal erosion in the Laptev Sea, which are based on field measurements and remote sensing information and existing data on coastal erosion in the CBS as well as riverine sediment discharge into both the Laptev Sea and the CBS are included. Strong regional differences in the percentages of coastal ero- sion and riverine sediment supply are observed. The CBS is dominated by the riverine sediment discharge (64.45x106 t a-1) mainly of the Mackenzie River. which is the largest single source of sediments in the Arctic. Riverine sediment discharge into the Laptev Sea amounts to 24.10x106 t a-1, more than 70% of which are related to the Lena River. In comparison with the CBS. the Laptev Sea coast on average delivers approximately twice as much sediment mass per kilometer, a result of higher erosion rates due to higher cliffs and seasonal ice melting. In the Laptev Sea sediment input by coastal erosion (58.4x106 t a-1) is therefore more important than in the CBS and the ratio between riverine and coastal sediment input amounts to 0.4. Coastal erosion supplying 5.6x106 t a-1 is less significant for the sediment budget of the CBS where riverine sediment discharge exceeds coastal sediment input by a factor of ca. 10.

Excitatory synaptic inputs to mouse on-off direction-selective retinal ganglion cells lack direction tuning.

PubMed

Park, Silvia J H; Kim, In-Jung; Looger, Loren L; Demb, Jonathan B; Borghuis, Bart G

2014-03-12

Direction selectivity represents a fundamental visual computation. In mammalian retina, On-Off direction-selective ganglion cells (DSGCs) respond strongly to motion in a preferred direction and weakly to motion in the opposite, null direction. Electrical recordings suggested three direction-selective (DS) synaptic mechanisms: DS GABA release during null-direction motion from starburst amacrine cells (SACs) and DS acetylcholine and glutamate release during preferred direction motion from SACs and bipolar cells. However, evidence for DS acetylcholine and glutamate release has been inconsistent and at least one bipolar cell type that contacts another DSGC (On-type) lacks DS release. Here, whole-cell recordings in mouse retina showed that cholinergic input to On-Off DSGCs lacked DS, whereas the remaining (glutamatergic) input showed apparent DS. Fluorescence measurements with the glutamate biosensor intensity-based glutamate-sensing fluorescent reporter (iGluSnFR) conditionally expressed in On-Off DSGCs showed that glutamate release in both On- and Off-layer dendrites lacked DS, whereas simultaneously recorded excitatory currents showed apparent DS. With GABA-A receptors blocked, both iGluSnFR signals and excitatory currents lacked DS. Our measurements rule out DS release from bipolar cells onto On-Off DSGCs and support a theoretical model suggesting that apparent DS excitation in voltage-clamp recordings results from inadequate voltage control of DSGC dendrites during null-direction inhibition. SAC GABA release is the apparent sole source of DS input onto On-Off DSGCs.

Cyanobacteriochrome-based photoswitchable adenylyl cyclases (cPACs) for broad spectrum light regulation of cAMP levels in cells.

PubMed

Blain-Hartung, Matthew; Rockwell, Nathan C; Moreno, Marcus V; Martin, Shelley S; Gan, Fei; Bryant, Donald A; Lagarias, J Clark

2018-06-01

Class III adenylyl cyclases generate the ubiquitous second messenger cAMP from ATP often in response to environmental or cellular cues. During evolution, soluble adenylyl cyclase catalytic domains have been repeatedly juxtaposed with signal-input domains to place cAMP synthesis under the control of a wide variety of these environmental and endogenous signals. Adenylyl cyclases with light-sensing domains have proliferated in photosynthetic species depending on light as an energy source, yet are also widespread in nonphotosynthetic species. Among such naturally occurring light sensors, several flavin-based photoactivated adenylyl cyclases (PACs) have been adopted as optogenetic tools to manipulate cellular processes with blue light. In this report, we report the discovery of a cyanobacteriochrome-based photoswitchable adenylyl cyclase (cPAC) from the cyanobacterium Microcoleus sp. PCC 7113. Unlike flavin-dependent PACs, which must thermally decay to be deactivated, cPAC exhibits a bistable photocycle whose adenylyl cyclase could be reversibly activated and inactivated by blue and green light, respectively. Through domain exchange experiments, we also document the ability to extend the wavelength-sensing specificity of cPAC into the near IR. In summary, our work has uncovered a cyanobacteriochrome-based adenylyl cyclase that holds great potential for the design of bistable photoswitchable adenylyl cyclases to fine-tune cAMP-regulated processes in cells, tissues, and whole organisms with light across the visible spectrum and into the near IR.

Yield estimation of corn based on multitemporal LANDSAT-TM data as input for an agrometeorological model

NASA Astrophysics Data System (ADS)

Bach, Heike

1998-07-01

In order to test remote sensing data with advanced yield formation models for accuracy and timeliness of yield estimation of corn, a project was conducted for the State Ministry for Rural Environment, Food, and Forestry of Baden-Württemberg (Germany). This project was carried out during the course of the `Special Yield Estimation', a regular procedure conducted for the European Union, to more accurately estimate agricultural yield. The methodology employed uses field-based plant parameter estimation from atmospherically corrected multitemporal/multispectral LANDSAT-TM data. An agrometeorological plant-production-model is used for yield prediction. Based solely on four LANDSAT-derived estimates (between May and August) and daily meteorological data, the grain yield of corn fields was determined for 1995. The modelled yields were compared with results gathered independently within the Special Yield Estimation for 23 test fields in the upper Rhine valley. The agreement between LANDSAT-based estimates (six weeks before harvest) and Special Yield Estimation (at harvest) shows a relative error of 2.3%. The comparison of the results for single fields shows that six weeks before harvest, the grain yield of corn was estimated with a mean relative accuracy of 13% using satellite information. The presented methodology can be transferred to other crops and geographical regions. For future applications hyperspectral sensors show great potential to further enhance the results for yield prediction with remote sensing.

Design of container velocity profile for the suppression of liquid sloshing

NASA Astrophysics Data System (ADS)

Kim, Dongjoo

2016-11-01

In many industrial applications, high-speed position control of a liquid container causes undesirable liquid vibrations called 'sloshing' which poses a control challenge in fast maneuvering and accurate positioning of containers. Recently, it has been shown that a control theory called 'input shaping' is successfully applied to reduce the sloshing, but its success comes at a cost of longer process time. Therefore, we aim to minimize liquid sloshing without increasing the process time when a container moves horizontally by a target distance within a limited time. In this study, sensing and feedback actuation are not permitted but the container velocity is allowed to be modified from a given triangular profile. A new design is proposed by applying input shaping to the container velocity with carefully selected acceleration time. That is, the acceleration time is chosen to be the 1st mode natural period, and the input shaper is determined based on the 3rd mode natural frequency. The proposed approach is validated by performing numerical simulations, which show that the simple modification of container velocity reduces the sloshing significantly without additional process time in a feedforward manner. Supported by the NRF programs (NRF-2015R1D1A1A01059675) of Korean government.

System level latchup mitigation for single event and transient radiation effects on electronics

DOEpatents

Kimbrough, J.R.; Colella, N.J.

1997-09-30

A ``blink`` technique, analogous to a person blinking at a flash of bright light, is provided for mitigating the effects of single event current latchup and prompt pulse destructive radiation on a micro-electronic circuit. The system includes event detection circuitry, power dump logic circuitry, and energy limiting measures with autonomous recovery. The event detection circuitry includes ionizing radiation pulse detection means for detecting a pulse of ionizing radiation and for providing at an output terminal thereof a detection signal indicative of the detection of a pulse of ionizing radiation. The current sensing circuitry is coupled to the power bus for determining an occurrence of excess current through the power bus caused by ionizing radiation or by ion-induced destructive latchup of a semiconductor device. The power dump circuitry includes power dump logic circuitry having a first input terminal connected to the output terminal of the ionizing radiation pulse detection circuitry and having a second input terminal connected to the output terminal of the current sensing circuitry. The power dump logic circuitry provides an output signal to the input terminal of the circuitry for opening the power bus and the circuitry for shorting the power bus to a ground potential to remove power from the power bus. The energy limiting circuitry with autonomous recovery includes circuitry for opening the power bus and circuitry for shorting the power bus to a ground potential. The circuitry for opening the power bus and circuitry for shorting the power bus to a ground potential includes a series FET and a shunt FET. The invention provides for self-contained sensing for latchup, first removal of power to protect latched components, and autonomous recovery to enable transparent operation of other system elements. 18 figs.

System level latchup mitigation for single event and transient radiation effects on electronics

DOEpatents

Kimbrough, Joseph Robert; Colella, Nicholas John

1997-01-01

A "blink" technique, analogous to a person blinking at a flash of bright light, is provided for mitigating the effects of single event current latchup and prompt pulse destructive radiation on a micro-electronic circuit. The system includes event detection circuitry, power dump logic circuitry, and energy limiting measures with autonomous recovery. The event detection circuitry includes ionizing radiation pulse detection means for detecting a pulse of ionizing radiation and for providing at an output terminal thereof a detection signal indicative of the detection of a pulse of ionizing radiation. The current sensing circuitry is coupled to the power bus for determining an occurrence of excess current through the power bus caused by ionizing radiation or by ion-induced destructive latchup of a semiconductor device. The power dump circuitry includes power dump logic circuitry having a first input terminal connected to the output terminal of the ionizing radiation pulse detection circuitry and having a second input terminal connected to the output terminal of the current sensing circuitry. The power dump logic circuitry provides an output signal to the input terminal of the circuitry for opening the power bus and the circuitry for shorting the power bus to a ground potential to remove power from the power bus. The energy limiting circuitry with autonomous recovery includes circuitry for opening the power bus and circuitry for shorting the power bus to a ground potential. The circuitry for opening the power bus and circuitry for shorting the power bus to a ground potential includes a series FET and a shunt FET. The invention provides for self-contained sensing for latchup, first removal of power to protect latched components, and autonomous recovery to enable transparent operation of other system elements.

Ultra-Compact Motor Controller

NASA Technical Reports Server (NTRS)

Townsend, William T.; Cromwell, Adam; Hauptman, Traveler; Pratt, Gill Andrews

2012-01-01

This invention is an electronically commutated brushless motor contro ller that incorporates Hall-array sensing in a small, 42-gram packag e that provides 4096 absolute counts per motor revolution position s ensing. The unit is the size of a miniature hockey puck, and is a 44 -pin male connector that provides many I/O channels, including CANbus , RS-232 communications, general-purpose analog and digital I/O (GPI O), analog and digital Hall inputs, DC power input (18-90 VDC, 0-l0 A), three-phase motor outputs, and a strain gauge amplifier.

Subwavelength Sensing Using Nonlinear Feedback in a Wave-Chaotic Cavity

DTIC Science & Technology

2013-01-01

r̃in and r̃in are the Fourier transforms of the input pulse and output pulse response, respectively. The magnitude and phase of Hcavity( f ) are plotted...function between its input and output voltages. But, as f increases (beyond ∼ 500 MHz), the amplitudes of the output signals decrease and the phase delay...coupled to free space where it is directed along two paths via a beam splitter (BS), where it is reflected of of mirrors (M1 and M2) that are attached to

Coordinated aircraft and ship surveys for determining impact of river inputs on great lakes waters. Remote sensing results

NASA Technical Reports Server (NTRS)

Raquet, C. A.; Salzman, J. A.; Coney, T. A.; Svehla, R. A.; Shook, D. F.; Gedney, R. T.

1980-01-01

The remote sensing results of aircraft and ship surveys for determining the impact of river effluents on Great Lakes waters are presented. Aircraft multi-spectral scanner data were acquired throughout the spring and early summer of 1976 at five locations: the West Basin of Lake Erie, Genesee River - Lake Ontario, Menomonee River - Lake Michigan, Grand River - Lake Michigan, and Nemadji River - Lake Superior. Multispectral scanner data and ship surface sample data are correlated resulting in 40 contour plots showing large-scale distributions of parameters such as total suspended solids, turbidity, Secchi depth, nutrients, salts, and dissolved oxygen. The imagery and data analysis are used to determine the transport and dispersion of materials from the river discharges, especially during spring runoff events, and to evaluate the relative effects of river input, resuspension, and shore erosion. Twenty-five LANDSAT satellite images of the study sites are also included in the analysis. Examples of the use of remote sensing data in quantitatively estimating total particulate loading in determining water types, in assessing transport across international boundaries, and in supporting numerical current modeling are included. The importance of coordination of aircraft and ship lake surveys is discussed, including the use of telefacsimile for the transmission of imagery.

Variable-Domain Displacement Transfer Functions for Converting Surface Strains into Deflections for Structural Deformed Shape Predictions

NASA Technical Reports Server (NTRS)

Ko, William L.; Fleischer, Van Tran

2015-01-01

Variable-Domain Displacement Transfer Functions were formulated for shape predictions of complex wing structures, for which surface strain-sensing stations must be properly distributed to avoid jointed junctures, and must be increased in the high strain gradient region. Each embedded beam (depth-wise cross section of structure along a surface strain-sensing line) was discretized into small variable domains. Thus, the surface strain distribution can be described with a piecewise linear or a piecewise nonlinear function. Through discretization, the embedded beam curvature equation can be piece-wisely integrated to obtain the Variable-Domain Displacement Transfer Functions (for each embedded beam), which are expressed in terms of geometrical parameters of the embedded beam and the surface strains along the strain-sensing line. By inputting the surface strain data into the Displacement Transfer Functions, slopes and deflections along each embedded beam can be calculated for mapping out overall structural deformed shapes. A long tapered cantilever tubular beam was chosen for shape prediction analysis. The input surface strains were analytically generated from finite-element analysis. The shape prediction accuracies of the Variable- Domain Displacement Transfer Functions were then determined in light of the finite-element generated slopes and deflections, and were fofound to be comparable to the accuracies of the constant-domain Displacement Transfer Functions

A review and analysis of neural networks for classification of remotely sensed multispectral imagery

NASA Technical Reports Server (NTRS)

Paola, Justin D.; Schowengerdt, Robert A.

1993-01-01

A literature survey and analysis of the use of neural networks for the classification of remotely sensed multispectral imagery is presented. As part of a brief mathematical review, the backpropagation algorithm, which is the most common method of training multi-layer networks, is discussed with an emphasis on its application to pattern recognition. The analysis is divided into five aspects of neural network classification: (1) input data preprocessing, structure, and encoding; (2) output encoding and extraction of classes; (3) network architecture, (4) training algorithms; and (5) comparisons to conventional classifiers. The advantages of the neural network method over traditional classifiers are its non-parametric nature, arbitrary decision boundary capabilities, easy adaptation to different types of data and input structures, fuzzy output values that can enhance classification, and good generalization for use with multiple images. The disadvantages of the method are slow training time, inconsistent results due to random initial weights, and the requirement of obscure initialization values (e.g., learning rate and hidden layer size). Possible techniques for ameliorating these problems are discussed. It is concluded that, although the neural network method has several unique capabilities, it will become a useful tool in remote sensing only if it is made faster, more predictable, and easier to use.

THERMOCOUPLE VACUUM GAUGE

DOEpatents

Price, G.W.

1954-08-01

A protector device is described for use in controlling the pressure within a cyclotron. In particular, an electrical circuit functions to actuate a vacuum pump when a predetermined low pressure is reached and disconnect the pump when the pressure increases abcve a certain value. The principal feature of the control circuit lies in the use of a voltage divider network at the input to a relay control tube comprising two parallel, adjustable resistances wherein one resistor is switched into the circuit when the relay connects the pump to a power source. With this arrangement the relay is energized at one input level received from a sensing element within the cyclotron chamber and is de-energized when a second input level, representing the higher pressure limit, is reached.

Optical source and apparatus for remote sensing

NASA Technical Reports Server (NTRS)

Coyle, Donald Barry (Inventor)

2011-01-01

An optical amplifier is configured to amplify an injected seed optical pulse. The optical amplifier may include two or more gain sections coupled to form a continuous solid waveguide along a primary optical path. Each gain section may include: (i) an optical isolator forming an input to that gain section; (ii) a doped optical fiber having a first end coupled to the optical isolator and having a second end; (iii) a plurality of pump laser diodes; (iv) a controller providing drive signals to each of the plurality, the controller being configured to provide at least pulsed drive signals; and (v) an optical coupler having a first input port coupled to the second end, and a second input port coupled to the plurality and an output port.

Functional expansion representations of artificial neural networks

NASA Technical Reports Server (NTRS)

Gray, W. Steven

1992-01-01

In the past few years, significant interest has developed in using artificial neural networks to model and control nonlinear dynamical systems. While there exists many proposed schemes for accomplishing this and a wealth of supporting empirical results, most approaches to date tend to be ad hoc in nature and rely mainly on heuristic justifications. The purpose of this project was to further develop some analytical tools for representing nonlinear discrete-time input-output systems, which when applied to neural networks would give insight on architecture selection, pruning strategies, and learning algorithms. A long term goal is to determine in what sense, if any, a neural network can be used as a universal approximator for nonliner input-output maps with memory (i.e., realized by a dynamical system). This property is well known for the case of static or memoryless input-output maps. The general architecture under consideration in this project was a single-input, single-output recurrent feedforward network.

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 closed-loop neurobotic system for fine touch sensing

NASA Astrophysics Data System (ADS)

Bologna, L. L.; Pinoteau, J.; Passot, J.-B.; Garrido, J. A.; Vogel, J.; Ros Vidal, E.; Arleo, A.

2013-08-01

Objective. Fine touch sensing relies on peripheral-to-central neurotransmission of somesthetic percepts, as well as on active motion policies shaping tactile exploration. This paper presents a novel neuroengineering framework for robotic applications based on the multistage processing of fine tactile information in the closed action-perception loop. Approach. The integrated system modules focus on (i) neural coding principles of spatiotemporal spiking patterns at the periphery of the somatosensory pathway, (ii) probabilistic decoding mechanisms mediating cortical-like tactile recognition and (iii) decision-making and low-level motor adaptation underlying active touch sensing. We probed the resulting neural architecture through a Braille reading task. Main results. Our results on the peripheral encoding of primary contact features are consistent with experimental data on human slow-adapting type I mechanoreceptors. They also suggest second-order processing by cuneate neurons may resolve perceptual ambiguities, contributing to a fast and highly performing online discrimination of Braille inputs by a downstream probabilistic decoder. The implemented multilevel adaptive control provides robustness to motion inaccuracy, while making the number of finger accelerations covariate with Braille character complexity. The resulting modulation of fingertip kinematics is coherent with that observed in human Braille readers. Significance. This work provides a basis for the design and implementation of modular neuromimetic systems for fine touch discrimination in robotics.

Active control of sound transmission through a rectangular panel using point-force actuators and piezoelectric film sensors.

PubMed

Sanada, Akira; Higashiyama, Kouji; Tanaka, Nobuo

2015-01-01

This study deals with the active control of sound transmission through a rectangular panel, based on single input, single output feedforward vibration control using point-force actuators and piezoelectric film sensors. It focuses on the phenomenon in which the sound power transmitted through a finite-sized panel drops significantly at some frequencies just below the resonance frequencies of the panel in the low-frequency range as a result of modal coupling cancellation. In a previous study, it was shown that when point-force actuators are located on nodal lines for the frequency at which this phenomenon occurs, a force equivalent to the incident sound wave can act on the panel. In this study, a practical method for sensing volume velocity using a small number of piezoelectric film strips is investigated. It is found that two quadratically shaped piezoelectric film strips, attached at the same nodal lines as those where the actuators were placed, can sense the volume velocity approximately in the low-frequency range. Results of simulations show that combining the proposed actuation method and the sensing method can achieve a practical control effect at low frequencies over a wide frequency range. Finally, experiments are carried out to demonstrate the validity and feasibility of the proposed method.

A low-power integrated humidity CMOS sensor by printing-on-chip technology.

PubMed

Lee, Chang-Hung; Chuang, Wen-Yu; Cowan, Melissa A; Wu, Wen-Jung; Lin, Chih-Ting

2014-05-23

A low-power, wide-dynamic-range integrated humidity sensing chip is implemented using a printable polymer sensing material with an on-chip pulse-width-modulation interface circuit. By using the inkjet printing technique, poly(3,4-ethylene-dioxythiophene)/polystyrene sulfonate that has humidity sensing features can be printed onto the top metal layer of a 0.35 μm CMOS IC. The developed printing-on-chip humidity sensor achieves a heterogeneous three dimensional sensor system-on-chip architecture. The humidity sensing of the implemented printing-on-chip sensor system is experimentally tested. The sensor shows a sensitivity of 0.98% to humidity in the atmosphere. The maximum dynamic range of the readout circuit is 9.8 MΩ, which can be further tuned by the frequency of input signal to fit the requirement of the resistance of printed sensor. The power consumption keeps only 154 μW. This printing-on-chip sensor provides a practical solution to fulfill an ultra-small integrated sensor for the applications in miniaturized sensing systems.

A Low-Power Integrated Humidity CMOS Sensor by Printing-on-Chip Technology

PubMed Central

Lee, Chang-Hung; Chuang, Wen-Yu; Cowan, Melissa A.; Wu, Wen-Jung; Lin, Chih-Ting

2014-01-01

A low-power, wide-dynamic-range integrated humidity sensing chip is implemented using a printable polymer sensing material with an on-chip pulse-width-modulation interface circuit. By using the inkjet printing technique, poly(3,4-ethylene-dioxythiophene)/polystyrene sulfonate that has humidity sensing features can be printed onto the top metal layer of a 0.35 μm CMOS IC. The developed printing-on-chip humidity sensor achieves a heterogeneous three dimensional sensor system-on-chip architecture. The humidity sensing of the implemented printing-on-chip sensor system is experimentally tested. The sensor shows a sensitivity of 0.98% to humidity in the atmosphere. The maximum dynamic range of the readout circuit is 9.8 MΩ, which can be further tuned by the frequency of input signal to fit the requirement of the resistance of printed sensor. The power consumption keeps only 154 μW. This printing-on-chip sensor provides a practical solution to fulfill an ultra-small integrated sensor for the applications in miniaturized sensing systems. PMID:24859027

MOSFET analog memory circuit achieves long duration signal storage

NASA Technical Reports Server (NTRS)

1966-01-01

Memory circuit maintains the signal voltage at the output of an analog signal amplifier when the input signal is interrupted or removed. The circuit uses MOSFET /Metal Oxide Semiconductor Field Effect Transistor/ devices as voltage-controlled switches, triggered by an external voltage-sensing device.

A Sensitivity Study of the Aircraft Vortex Spacing System (AVOSS) Wake Predictor Algorithm to the Resolution of Input Meteorological Profiles

NASA Technical Reports Server (NTRS)

Rutishauser, David K.; Butler, Patrick; Riggins, Jamie

2004-01-01

The AVOSS project demonstrated the feasibility of applying aircraft wake vortex sensing and prediction technologies to safe aircraft spacing for single runway arrivals. On average, AVOSS provided spacing recommendations that were less than the current FAA prescribed spacing rules, resulting in a potential airport efficiency gain. Subsequent efforts have included quantifying the operational specifications for future Wake Vortex Advisory Systems (WakeVAS). In support of these efforts, each of the candidate subsystems for a WakeVAS must be specified. The specifications represent a consensus between the high-level requirements and the capabilities of the candidate technologies. This report documents the beginnings of an effort to quantify the capabilities of the AVOSS Prediction Algorithm (APA). Specifically, the APA horizontal position and circulation strength output sensitivity to the resolution of its wind and turbulence inputs is examined. The results of this analysis have implications for the requirements of the meteorological sensing and prediction systems comprising a WakeVAS implementation.

High Latitude Dust Sources, Transport Pathways and Impacts

NASA Astrophysics Data System (ADS)

Bullard, J. E.; Baddock, M. C.; Darlington, E.; Mockford, T.; Van-Soest, M.

2017-12-01

Estimates from field studies, remote sensing and modelling all suggest around 5% of global dust emissions originate in the high latitudes (≥50°N and ≥40°S), a similar proportion to that from the USA (excluding Alaska) or Australia. This paper identifies contemporary sources of dust within the high latitudes and their role within local, regional and hemispherical environmental systems. Field data and remote sensing analyses are used to identify the environmental and climatic conditions that characterize high latitude dust sources in both hemispheres. Examples from Arctic and sub-Arctic dust sources are used to demonstrate and explain the different regional relationships among dust emissions, glacio-fluvial dynamics and snow cover. The relative timing of dust input to high latitude terrestrial, cryospheric and marine systems determines its short to medium term environmental impact. This is highlighted through quantifying the importance of locally-redistributed dust as a nutrient input to high latitude soils and lakes in West Greenland.

Voltage sensing systems and methods for passive compensation of temperature related intrinsic phase shift

DOEpatents

Davidson, James R.; Lassahn, Gordon D.

2001-01-01

A small sized electro-optic voltage sensor capable of accurate measurement of high levels of voltages without contact with a conductor or voltage source is provided. When placed in the presence of an electric field, the sensor receives an input beam of electromagnetic radiation into the sensor. A polarization beam displacer serves as a filter to separate the input beam into two beams with orthogonal linear polarizations. The beam displacer is oriented in such a way as to rotate the linearly polarized beams such that they enter a Pockels crystal at a preferred angle of 45 degrees. The beam displacer is therefore capable of causing a linearly polarized beam to impinge a crystal at a desired angle independent of temperature. The Pockels electro-optic effect induces a differential phase shift on the major and minor axes of the input beam as it travels through the Pockels crystal, which causes the input beam to be elliptically polarized. A reflecting prism redirects the beam back through the crystal and the beam displacer. On the return path, the polarization beam displacer separates the elliptically polarized beam into two output beams of orthogonal linear polarization representing the major and minor axes. In crystals that introduce a phase differential attributable to temperature, a compensating crystal is provided to cancel the effect of temperature on the phase differential of the input beam. The system may include a detector for converting the output beams into electrical signals, and a signal processor for determining the voltage based on an analysis of the output beams. The output beams are amplitude modulated by the frequency of the electric field and the amplitude of the output beams is proportional to the magnitude of the electric field, which is related to the voltage being measured.

Impact of remote sensing upon the planning, management, and development of water resources

NASA Technical Reports Server (NTRS)

Castruccio, P. A.; Loats, H. L.; Fowler, T. R.; Frech, S. L.

1975-01-01

Principal water resources users were surveyed to determine the impact of remote data streams on hydrologic computer models. Analysis of responses demonstrated that: most water resources effort suitable to remote sensing inputs is conducted through federal agencies or through federally stimulated research; and, most hydrologic models suitable to remote sensing data are federally developed. Computer usage by major water resources users was analyzed to determine the trends of usage and costs for the principal hydrologic users/models. The laws and empirical relationships governing the growth of the data processing loads were described and applied to project the future data loads. Data loads for ERTS CCT image processing were computed and projected through the 1985 era.

Sensing new chemicals with bacterial transcription factors.

PubMed

Libis, Vincent; Delépine, Baudoin; Faulon, Jean-Loup

2016-10-01

Bacteria rely on allosteric transcription factors (aTFs) to sense a wide range of chemicals. The variety of effectors has contributed in making aTFs the most used input system in synthetic biological circuits. Considering their enabling role in biotechnology, an important question concerns the size of the chemical space that can potentially be detected by these biosensors. From digging into the ever changing repertoire of natural regulatory circuits, to advances in aTF engineering, we review here different strategies that are pushing the boundaries of this chemical space. We also review natural and synthetic cases of indirect sensing, where aTFs work in combination with metabolism to enable detection of new molecules. Copyright © 2016 Elsevier Ltd. All rights reserved.

Relationship between upper extremity kinesthetic sense and writing performance by students with low vision.

PubMed

Aki, Esra; Atasavun, Songül; Kayihan, Holya

2008-06-01

Kinesthetic sense plays an important role in writing. Children with low vision lack sensory input from the environment given their loss of vision. This study assessed the effect of upper extremity kinesthetic sense on writing function in two groups, one of students with low vision (9 girls and 11 boys, 9.4 +/- 1.9 yr. of age) and one of sighted students (10 girls and 10 boys, 10.1 +/- 1.3 yr. of age). All participants were given the Kinesthesia Test and Jebsen Hand Function Test-Writing subtest. Students with low vision scored lower on kinesthetic perception and writing performance than sighted peers. The correlation between scores for writing performance and upper extremity kinesthetic sense in the two groups was significant (r = -.34). The probability of deficiencies in kinesthetic information in students with low vision must be remembered.

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

PubMed

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

2018-01-22

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

Incorporating maps of leaf chlorophyll in a thermal-based two-source energy balance scheme for mapping coupled fluxes of carbon and water exchange at a range of scales

NASA Astrophysics Data System (ADS)

Houborg, R.; Anderson, M. C.; Kustas, W. P.

2008-12-01

A light-use efficiency (LUE) based model of canopy resistance was recently implemented within a thermal- based Two-Source Energy Balance (TSEB) scheme facilitating coupled simulations of land-surface fluxes of water, energy and CO2 exchange from field to regional scales (Anderson et al., 2008). The LUE model component computes canopy-scale carbon assimilation and transpiration fluxes and incorporates LUE modifications from biome specific nominal values (Bn) in response to variations in humidity, CO2 concentration, temperature (soil and air), wind speed, and direct beam vs. diffuse light composition. Here we incorporate leaf chlorophyll content (Cab) as a determinant of spatial and temporal variations in Bn as Cab is related to key LUE modulating factors such as crop phenology, vegetation stress and photosynthetic capacity. A linear relationship between Bn and Cab, established from stand-level measurement of LUE for unstressed environmental conditions and a representative set of Cab values for a range of agricultural and natural vegetation groups, is used to distribute Bn over the modeling domain. The technique is tested for an agricultural area near Bushland, Texas by fusing reflective and thermal based remote sensing inputs from SPOT, Landsat, ASTER and aircraft sensor systems. Maps of LAI and Cab are generated by using at-sensor radiances in green, red and near-infrared wavelengths as input to a REGularized canopy reFLECtance (REGFLEC) modeling tool that couples leaf optics (PROSPECT), canopy reflectance (ACRM), and atmospheric radiative transfer (6SV1) model components. Modeled carbon and water fluxes are compared with eddy covariance measurements made in stands of cotton and with fluxes measured by an aircraft flying transects over irrigated and non-irrigated agricultural land and natural vegetation. The technique is flexible and scalable and is portable to continental scales using GOES and MODIS data products. The results demonstrate utility in combining remotely sensed observations in the reflective solar and thermal domains for estimating carbon and water fluxes within a coupled framework.

Stochastic associative memory

NASA Astrophysics Data System (ADS)

Baumann, Erwin W.; Williams, David L.

1993-08-01

Artificial neural networks capable of learning and recalling stochastic associations between non-deterministic quantities have received relatively little attention to date. One potential application of such stochastic associative networks is the generation of sensory 'expectations' based on arbitrary subsets of sensor inputs to support anticipatory and investigate behavior in sensor-based robots. Another application of this type of associative memory is the prediction of how a scene will look in one spectral band, including noise, based upon its appearance in several other wavebands. This paper describes a semi-supervised neural network architecture composed of self-organizing maps associated through stochastic inter-layer connections. This 'Stochastic Associative Memory' (SAM) can learn and recall non-deterministic associations between multi-dimensional probability density functions. The stochastic nature of the network also enables it to represent noise distributions that are inherent in any true sensing process. The SAM architecture, training process, and initial application to sensor image prediction are described. Relationships to Fuzzy Associative Memory (FAM) are discussed.

SQUID-based current sensing noise thermometry for quantum resistors at dilution refrigerator temperatures

NASA Astrophysics Data System (ADS)

Kleinbaum, Ethan; Shingla, Vidhi; Csáthy, G. A.

2017-03-01

We present a dc Superconducting QUantum Interference Device (SQUID)-based current amplifier with an estimated input referred noise of only 2.3 fA/√{Hz}. Because of such a low amplifier noise, the circuit is useful for Johnson noise thermometry of quantum resistors in the kΩ range down to mK temperatures. In particular, we demonstrate that our circuit does not contribute appreciable noise to the Johnson noise of a 3.25 kΩ resistor down to 16 mK. Our circuit is a useful alternative to the commonly used High Electron Mobility Transistor-based amplifiers, but in contrast to the latter, it offers a much reduced 1/f noise. In comparison to SQUIDs interfaced with cryogenic current comparators, our circuit has similar low noise levels, but it is easier to build and to shield from magnetic pickup.

In-vivo detection of binary PKA network interactions upon activation of endogenous GPCRs

PubMed Central

Röck, Ruth; Bachmann, Verena; Bhang, Hyo-eun C; Malleshaiah, Mohan; Raffeiner, Philipp; Mayrhofer, Johanna E; Tschaikner, Philipp M; Bister, Klaus; Aanstad, Pia; Pomper, Martin G; Michnick, Stephen W; Stefan, Eduard

2015-01-01

Membrane receptor-sensed input signals affect and modulate intracellular protein-protein interactions (PPIs). Consequent changes occur to the compositions of protein complexes, protein localization and intermolecular binding affinities. Alterations of compartmentalized PPIs emanating from certain deregulated kinases are implicated in the manifestation of diseases such as cancer. Here we describe the application of a genetically encoded Protein-fragment Complementation Assay (PCA) based on the Renilla Luciferase (Rluc) enzyme to compare binary PPIs of the spatially and temporally controlled protein kinase A (PKA) network in diverse eukaryotic model systems. The simplicity and sensitivity of this cell-based reporter allows for real-time recordings of mutually exclusive PPIs of PKA upon activation of selected endogenous G protein-coupled receptors (GPCRs) in cancer cells, xenografts of mice, budding yeast, and zebrafish embryos. This extends the application spectrum of Rluc PCA for the quantification of PPI-based receptor-effector relationships in physiological and pathological model systems. PMID:26099953

BGen: A UML Behavior Network Generator Tool

NASA Technical Reports Server (NTRS)

Huntsberger, Terry; Reder, Leonard J.; Balian, Harry

2010-01-01

BGen software was designed for autogeneration of code based on a graphical representation of a behavior network used for controlling automatic vehicles. A common format used for describing a behavior network, such as that used in the JPL-developed behavior-based control system, CARACaS ["Control Architecture for Robotic Agent Command and Sensing" (NPO-43635), NASA Tech Briefs, Vol. 32, No. 10 (October 2008), page 40] includes a graph with sensory inputs flowing through the behaviors in order to generate the signals for the actuators that drive and steer the vehicle. A computer program to translate Unified Modeling Language (UML) Freeform Implementation Diagrams into a legacy C implementation of Behavior Network has been developed in order to simplify the development of C-code for behavior-based control systems. UML is a popular standard developed by the Object Management Group (OMG) to model software architectures graphically. The C implementation of a Behavior Network is functioning as a decision tree.

Design of energy harvesting systems for harnessing vibrational motion from human and vehicular motion

NASA Astrophysics Data System (ADS)

Wickenheiser, Adam; Garcia, Ephrahim

2010-04-01

In much of the vibration-based energy harvesting literature, devices are modeled, designed, and tested for dissipating energy across a resistive load at a single base excitation frequency. This paper presents several practical scenarios germane to tracking, sensing, and wireless communication on humans and land vehicles. Measured vibrational data from these platforms are used to provide a time-varying, broadband input to the energy harvesting system. Optimal power considerations are given for several circuit topologies, including a passive rectifier circuit and active, switching methods. Under various size and mass constraints, the optimal design is presented for two scenarios: walking and idling a car. The frequency response functions are given alongside time histories of the power harvested using the experimental base accelerations recorded. The issues involved in designing an energy harvester for practical (i.e. timevarying, non-sinusoidal) applications are discussed.

Wireless implantable passive strain sensor: design, fabrication and characterization

NASA Astrophysics Data System (ADS)

Umbrecht, F.; Wägli, P.; Dechand, S.; Gattiker, F.; Neuenschwander, J.; Sennhauser, U.; Hierold, Ch

2010-08-01

This work presents a new passive sensor concept for monitoring the deformation of orthopedic implants. The novel sensing principle of the WIPSS (wireless implantable passive strain sensor) is based on a hydro-mechanical amplification effect. The WIPSS is entirely made from biocompatible PMMA and consists of a microchannel attached to a reservoir, which is filled with an incompressible fluid. As the reservoir is exposed to strain, its volume changes and consequently the fill level inside the microchannel varies. The wireless detection of the microchannel's strain-dependent fill level is based on ultrasound. The WIPSS' sensing principle is proved by finite-element simulations and the reservoir's design is optimized toward maximum volume change, in order to achieve high sensitivity. A fabrication process for WIPSS sensor devices entirely made from PMMA is presented. The obtained measurement results confirmed the sensor's functionality and showed very good agreement with the obtained results of the conducted FE simulations regarding the sensor's sensitivity. A strain resolution of 1.7 ± 0.2 × 10-5 was achieved. Further, the determination of the cross-sensitivity to temperature and strains applied out of the sensing direction is presented. The response to dynamic inputs (0.1-5 Hz) has been measured and showed decreasing sensor output with increasing frequency. Test structures of the sensor device allow the application of a signal bandwidth up to 1 Hz. Therefore, the proposed sensor concept of the WIPSS presents a promising new sensor system for static in vivo strain monitoring of orthopedic implants. In combination with the developed ultrasound-based read-out method, this new sensor system offers the potential of wireless sensor read-out with medical ultrasound scanners, which are commercially available.

Annual regression-based estimates of evapotranspiration for the contiguous United States based on climate, remote sensing, and stream gage data

NASA Astrophysics Data System (ADS)

Reitz, M. D.; Sanford, W. E.; Senay, G. B.; Cazenas, J.

2015-12-01

Evapotranspiration (ET) is a key quantity in the hydrologic cycle, accounting for ~70% of precipitation across the contiguous United States (CONUS). However, it is a challenge to estimate, due to difficulty in making direct measurements and gaps in our theoretical understanding. Here we present a new data-driven, ~1km2 resolution map of long-term average actual evapotranspiration rates across the CONUS. The new ET map is a function of the USGS Landsat-derived National Land Cover Database (NLCD), precipitation, temperature, and daily average temperature range (from the PRISM climate dataset), and is calibrated to long-term water balance data from 679 watersheds. It is unique from previously presented ET maps in that (1) it was co-developed with estimates of runoff and recharge; (2) the regression equation was chosen from among many tested, previously published and newly proposed functional forms for its optimal description of long-term water balance ET data; (3) it has values over open-water areas that are derived from separate mass-transfer and humidity equations; and (4) the data include additional precipitation representing amounts converted from 2005 USGS water-use census irrigation data. The regression equation is calibrated using data from 2000-2013, but can also be applied to individual years with their corresponding input datasets. Comparisons among this new map, the more detailed remote-sensing-based estimates of MOD16 and SSEBop, and AmeriFlux ET tower measurements shows encouraging consistency, and indicates that the empirical ET estimate approach presented here produces closer agreement with independent flux tower data for annual average actual ET than other more complex remote sensing approaches.

Developing the remote sensing-based early warning system for monitoring TSS concentrations in Lake Mead.

PubMed

Imen, Sanaz; Chang, Ni-Bin; Yang, Y Jeffrey

2015-09-01

Adjustment of the water treatment process to changes in water quality is a focus area for engineers and managers of water treatment plants. The desired and preferred capability depends on timely and quantitative knowledge of water quality monitoring in terms of total suspended solids (TSS) concentrations. This paper presents the development of a suite of nowcasting and forecasting methods by using high-resolution remote-sensing-based monitoring techniques on a daily basis. First, the integrated data fusion and mining (IDFM) technique was applied to develop a near real-time monitoring system for daily nowcasting of the TSS concentrations. Then a nonlinear autoregressive neural network with external input (NARXNET) model was selected and applied for forecasting analysis of the changes in TSS concentrations over time on a rolling basis onward using the IDFM technique. The implementation of such an integrated forecasting and nowcasting approach was assessed by a case study at Lake Mead hosting the water intake for Las Vegas, Nevada, in the water-stressed western U.S. Long-term monthly averaged results showed no simultaneous impact from forest fire events on accelerating the rise of TSS concentration. However, the results showed a probable impact of a decade of drought on increasing TSS concentration in the Colorado River Arm and Overton Arm. Results of the forecasting model highlight the reservoir water level as a significant parameter in predicting TSS in Lake Mead. In addition, the R-squared value of 0.98 and the root mean square error of 0.5 between the observed and predicted TSS values demonstrates the reliability and application potential of this remote sensing-based early warning system in terms of TSS projections at a drinking water intake. Copyright © 2015 Elsevier Ltd. All rights reserved.

Estimating Evaporative Fraction From Readily Obtainable Variables in Mangrove Forests of the Everglades, U.S.A.

NASA Technical Reports Server (NTRS)

Yagci, Ali Levent; Santanello, Joseph A.; Jones, John; Barr, Jordan

2017-01-01

A remote-sensing-based model to estimate evaporative fraction (EF) the ratio of latent heat (LE; energy equivalent of evapotranspiration -ET-) to total available energy from easily obtainable remotely-sensed and meteorological parameters is presented. This research specifically addresses the shortcomings of existing ET retrieval methods such as calibration requirements of extensive accurate in situ micro-meteorological and flux tower observations, or of a large set of coarse-resolution or model-derived input datasets. The trapezoid model is capable of generating spatially varying EF maps from standard products such as land surface temperature [T(sub s)] normalized difference vegetation index (NDVI)and daily maximum air temperature [T(sub a)]. The 2009 model results were validated at an eddy-covariance tower (Fluxnet ID: US-Skr) in the Everglades using T(sub s) and NDVI products from Landsat as well as the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. Results indicate that the model accuracy is within the range of instrument uncertainty, and is dependent on the spatial resolution and selection of end-members (i.e. wet/dry edge). The most accurate results were achieved with the T(sub s) from Landsat relative to the T(sub s) from the MODIS flown on the Terra and Aqua platforms due to the fine spatial resolution of Landsat (30 m). The bias, mean absolute percentage error and root mean square percentage error were as low as 2.9% (3.0%), 9.8% (13.3%), and 12.1% (16.1%) for Landsat-based (MODIS-based) EF estimates, respectively. Overall, this methodology shows promise for bridging the gap between temporally limited ET estimates at Landsat scales and more complex and difficult to constrain global ET remote-sensing models.

Estimating evaporative fraction from readily obtainable variables in mangrove forests of the Everglades, U.S.A.

USGS Publications Warehouse

Yagci, Ali Levent; Santanello, Joseph A.; Jones, John W.; Barr, Jordan G.

2017-01-01

A remote-sensing-based model to estimate evaporative fraction (EF) – the ratio of latent heat (LE; energy equivalent of evapotranspiration –ET–) to total available energy – from easily obtainable remotely-sensed and meteorological parameters is presented. This research specifically addresses the shortcomings of existing ET retrieval methods such as calibration requirements of extensive accurate in situ micrometeorological and flux tower observations or of a large set of coarse-resolution or model-derived input datasets. The trapezoid model is capable of generating spatially varying EF maps from standard products such as land surface temperature (Ts) normalized difference vegetation index (NDVI) and daily maximum air temperature (Ta). The 2009 model results were validated at an eddy-covariance tower (Fluxnet ID: US-Skr) in the Everglades using Ts and NDVI products from Landsat as well as the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. Results indicate that the model accuracy is within the range of instrument uncertainty, and is dependent on the spatial resolution and selection of end-members (i.e. wet/dry edge). The most accurate results were achieved with the Ts from Landsat relative to the Ts from the MODIS flown on the Terra and Aqua platforms due to the fine spatial resolution of Landsat (30 m). The bias, mean absolute percentage error and root mean square percentage error were as low as 2.9% (3.0%), 9.8% (13.3%), and 12.1% (16.1%) for Landsat-based (MODIS-based) EF estimates, respectively. Overall, this methodology shows promise for bridging the gap between temporally limited ET estimates at Landsat scales and more complex and difficult to constrain global ET remote-sensing models.

Magnetic tunnel junction based spintronic logic devices

NASA Astrophysics Data System (ADS)

Lyle, Andrew Paul

The International Technology Roadmap for Semiconductors (ITRS) predicts that complimentary metal oxide semiconductor (CMOS) based technologies will hit their last generation on or near the 16 nm node, which we expect to reach by the year 2025. Thus future advances in computational power will not be realized from ever-shrinking device sizes, but rather by 'outside the box' designs and new physics, including molecular or DNA based computation, organics, magnonics, or spintronic. This dissertation investigates magnetic logic devices for post-CMOS computation. Three different architectures were studied, each relying on a different magnetic mechanism to compute logic functions. Each design has it benefits and challenges that must be overcome. This dissertation focuses on pushing each design from the drawing board to a realistic logic technology. The first logic architecture is based on electrically connected magnetic tunnel junctions (MTJs) that allow direct communication between elements without intermediate sensing amplifiers. Two and three input logic gates, which consist of two and three MTJs connected in parallel, respectively were fabricated and are compared. The direct communication is realized by electrically connecting the output in series with the input and applying voltage across the series connections. The logic gates rely on the fact that a change in resistance at the input modulates the voltage that is needed to supply the critical current for spin transfer torque switching the output. The change in resistance at the input resulted in a voltage margin of 50--200 mV and 250--300 mV for the closest input states for the three and two input designs, respectively. The two input logic gate realizes the AND, NAND, NOR, and OR logic functions. The three input logic function realizes the Majority, AND, NAND, NOR, and OR logic operations. The second logic architecture utilizes magnetostatically coupled nanomagnets to compute logic functions, which is the basis of Magnetic Quantum Cellular Automata (MQCA). MQCA has the potential to be thousands of times more energy efficient than CMOS technology. While interesting, these systems are academic unless they can be interfaced into current technologies. This dissertation pushed past a major hurdle by experimentally demonstrating a spintronic input/output (I/O) interface for the magnetostatically coupled nanomagnets by incorporating MTJs. This spintronic interface allows individual nanomagnets to be programmed using spin transfer torque and read using magneto resistance structure. Additionally the spintronic interface allows statistical data on the reliability of the magnetic coupling utilized for data propagation to be easily measured. The integration of spintronics and MQCA for an electrical interface to achieve a magnetic logic device with low power creates a competitive post-CMOS logic device. The final logic architecture that was studied used MTJs to compute logic functions and magnetic domain walls to communicate between gates. Simulations were used to optimize the design of this architecture. Spin transfer torque was used to compute logic function at each MTJ gate and was used to drive the domain walls. The design demonstrated that multiple nanochannels could be connected to each MTJ to realize fan-out from the logic gates. As a result this logic scheme eliminates the need for intermediate reads and conversions to pass information from one logic gate to another.

Distributed Fiber Optic Sensor for On-Line Monitoring of Coal Gasifier Refractory Health

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

Wang, Anbo; Yu, Zhihao

This report summarizes technical progress on the program “Distributed Fiber Optic Sensor for On-Line Monitoring of Coal Gasifier Refractory Health,” 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. The scope of work entails analyses of traveling grating generation technologies in an optical fiber, as well as the interrogation of the gratings to infer a distributed temperature along the fiber, for the purpose of developing a real-time refractory health condition monitoring technology for coal gasifiers. Duringmore » the project period, which is from 2011-2015, three different sensing principles were studied, including four-wave mixing (FWM), coherent optical time-domain reflectometer (C-OTDR) and Brillouin optical time-domain analysis (BOTDA). By comparing the three methods, the BOTDA was selected for further development into a complete bench-top sensing system for the proposed high-temperature sensing application. Based on the input from Eastman Chemical, the industrial collaborator on this project, a cylindrical furnace was designed and constructed to simulate typical gasifier refractory temperature conditions in the laboratory, and verify the sensor’s capability to fully monitor refractory conditions on the back-side at temperatures up to 1000°C. In the later stages of the project, the sensing system was tested in the simulated environment for its sensing performance and high-temperature survivability. Through theoretical analyses and experimental research on the different factors affecting the sensor performance, a sensor field deployment strategy was proposed for possible future sensor field implementations.« less

Wavevector multiplexed atomic quantum memory via spatially-resolved single-photon detection.

PubMed

Parniak, Michał; Dąbrowski, Michał; Mazelanik, Mateusz; Leszczyński, Adam; Lipka, Michał; Wasilewski, Wojciech

2017-12-15

Parallelized quantum information processing requires tailored quantum memories to simultaneously handle multiple photons. The spatial degree of freedom is a promising candidate to facilitate such photonic multiplexing. Using a single-photon resolving camera, we demonstrate a wavevector multiplexed quantum memory based on a cold atomic ensemble. Observation of nonclassical correlations between Raman scattered photons is confirmed by an average value of the second-order correlation function [Formula: see text] in 665 separated modes simultaneously. The proposed protocol utilizing the multimode memory along with the camera will facilitate generation of multi-photon states, which are a necessity in quantum-enhanced sensing technologies and as an input to photonic quantum circuits.

Automated synthetic scene generation

NASA Astrophysics Data System (ADS)

Givens, Ryan N.

Physics-based simulations generate synthetic imagery to help organizations anticipate system performance of proposed remote sensing systems. However, manually constructing synthetic scenes which are sophisticated enough to capture the complexity of real-world sites can take days to months depending on the size of the site and desired fidelity of the scene. This research, sponsored by the Air Force Research Laboratory's Sensors Directorate, successfully developed an automated approach to fuse high-resolution RGB imagery, lidar data, and hyperspectral imagery and then extract the necessary scene components. The method greatly reduces the time and money required to generate realistic synthetic scenes and developed new approaches to improve material identification using information from all three of the input datasets.

Graphene-Based Three-Dimensional Capacitive Touch Sensor for Wearable Electronics.

PubMed

Kang, Minpyo; Kim, Jejung; Jang, Bongkyun; Chae, Youngcheol; Kim, Jae-Hyun; Ahn, Jong-Hyun

2017-08-22

The development of input device technology in a conformal and stretchable format is important for the advancement of various wearable electronics. Herein, we report a capacitive touch sensor with good sensing capabilities in both contact and noncontact modes, enabled by the use of graphene and a thin device geometry. This device can be integrated with highly deformable areas of the human body, such as the forearms and palms. This touch sensor detects multiple touch signals in acute recordings and recognizes the distance and shape of the approaching objects before direct contact is made. This technology offers a convenient and immersive human-machine interface and additional potential utility as a multifunctional sensor for emerging wearable electronics and robotics.

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

Chen Lin; Chen Yixin

We show that no universal quantum cloning machine exists that can broadcast an arbitrary mixed qubit with a constant fidelity. Based on this result, we investigate the dependent quantum cloner in the sense that some parameter of the input qubit {rho}{sub s}({theta},{omega},{lambda}) is regarded as constant in the fidelity. For the case of constant {omega}, we establish the 1{yields}2 optimal symmetric dependent cloner with a fidelity 1/2. It is also shown that the 1{yields}M optimal quantum cloning machine for pure qubits is also optimal for mixed qubits, when {lambda} is the unique parameter in the fidelity. For general N{yields}M broadcastingmore » of mixed qubits, the situation is very different.« less

Modeling fuel succession

USGS Publications Warehouse

Davis, Brett; Van Wagtendonk, Jan W.; Beck, Jen; van Wagtendonk, Kent A.

2009-01-01

Surface fuels data are of critical importance for supporting fire incident management, risk assessment, and fuel management planning, but the development of surface fuels data can be expensive and time consuming. The data development process is extensive, generally beginning with acquisition of remotely sensed spatial data such as aerial photography or satellite imagery (Keane and others 2001). The spatial vegetation data are then crosswalked to a set of fire behavior fuel models that describe the available fuels (the burnable portions of the vegetation) (Anderson 1982, Scott and Burgan 2005). Finally, spatial fuels data are used as input to tools such as FARSITE and FlamMap to model current and potential fire spread and behavior (Finney 1998, Finney 2006). The capture date of the remotely sensed data defines the period for which the vegetation, and, therefore, fuels, data are most accurate. The more time that passes after the capture date, the less accurate the data become due to vegetation growth and processes such as fire. Subsequently, the results of any fire simulation based on these data become less accurate as the data age. Because of the amount of labor and expense required to develop these data, keeping them updated may prove to be a challenge. In this article, we describe the Sierra Nevada Fuel Succession Model, a modeling tool that can quickly and easily update surface fuel models with a minimum of additional input data. Although it was developed for use by Yosemite, Sequoia, and Kings Canyon National Parks, it is applicable to much of the central and southern Sierra Nevada. Furthermore, the methods used to develop the model have national applicability.

Evaluating Satellite-based Rainfall Estimates for Basin-scale Hydrologic Modeling

NASA Astrophysics Data System (ADS)

Yilmaz, K. K.; Hogue, T. S.; Hsu, K.; Gupta, H. V.; Mahani, S. E.; Sorooshian, S.

2003-12-01

The reliability of any hydrologic simulation and basin outflow prediction effort depends primarily on the rainfall estimates. The problem of estimating rainfall becomes more obvious in basins with scarce or no rain gauges. We present an evaluation of satellite-based rainfall estimates for basin-scale hydrologic modeling with particular interest in ungauged basins. The initial phase of this study focuses on comparison of mean areal rainfall estimates from ground-based rain gauge network, NEXRAD radar Stage-III, and satellite-based PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks) and their influence on hydrologic model simulations over several basins in the U.S. Six-hourly accumulations of the above competing mean areal rainfall estimates are used as input to the Sacramento Soil Moisture Accounting Model. Preliminary experiments for the Leaf River Basin in Mississippi, for the period of March 2000 - June 2002, reveals that seasonality plays an important role in the comparison. There is an overestimation during the summer and underestimation during the winter in satellite-based rainfall with respect to the competing rainfall estimates. The consequence of this result on the hydrologic model is that simulated discharge underestimates the major observed peak discharges during early spring for the basin under study. Future research will entail developing correction procedures, which depend on different factors such as seasonality, geographic location and basin size, for satellite-based rainfall estimates over basins with dense rain gauge network and/or radar coverage. Extension of these correction procedures to satellite-based rainfall estimates over ungauged basins with similar characteristics has the potential for reducing the input uncertainty in ungauged basin modeling efforts.

Vestibular-somatosensory convergence in head movement control during locomotion after long-duration space flight.

PubMed

Mulavara, A P; Ruttley, T; Cohen, H S; Peters, B T; Miller, C; Brady, R; Merkle, L; Bloomberg, J J

2012-01-01

Space flight causes astronauts to be exposed to adaptation in both the vestibular and body load-sensing somatosensory systems. The goal of these studies was to examine the contributions of vestibular and body load-sensing somatosensory influences on vestibular mediated head movement control during locomotion after long-duration space flight. Subjects walked on a motor driven treadmill while performing a gaze stabilization task. Data were collected from three independent subject groups that included bilateral labyrinthine deficient (LD) patients, normal subjects before and after 30 minutes of 40% bodyweight unloaded treadmill walking, and astronauts before and after long-duration space flight. Motion data from the head and trunk segments were used to calculate the amplitude of angular head pitch and trunk vertical translation movement while subjects performed a gaze stabilization task, to estimate the contributions of vestibular reflexive mechanisms in head pitch movements. Exposure to unloaded locomotion caused a significant increase in head pitch movements in normal subjects, whereas the head pitch movements of LD patients were significantly decreased. This is the first evidence of adaptation of vestibular mediated head movement responses to unloaded treadmill walking. Astronaut subjects showed a heterogeneous response of both increases and decreases in the amplitude of head pitch movement. We infer that body load-sensing somatosensory input centrally modulates vestibular input and can adaptively modify vestibularly mediated head-movement control during locomotion. Thus, space flight may cause central adaptation of the converging vestibular and body load-sensing somatosensory systems leading to alterations in head movement control.

MetaSensing's FastGBSAR: ground based radar for deformation monitoring

NASA Astrophysics Data System (ADS)

Rödelsperger, Sabine; Meta, Adriano

2014-10-01

The continuous monitoring of ground deformation and structural movement has become an important task in engineering. MetaSensing introduces a novel sensor system, the Fast Ground Based Synthetic Aperture Radar (FastGBSAR), based on innovative technologies that have already been successfully applied to airborne SAR applications. The FastGBSAR allows the remote sensing of deformations of a slope or infrastructure from up to a distance of 4 km. The FastGBSAR can be setup in two different configurations: in Real Aperture Radar (RAR) mode it is capable of accurately measuring displacements along a linear range profile, ideal for monitoring vibrations of structures like bridges and towers (displacement accuracy up to 0.01 mm). Modal parameters can be determined within half an hour. Alternatively, in Synthetic Aperture Radar (SAR) configuration it produces two-dimensional displacement images with an acquisition time of less than 5 seconds, ideal for monitoring areal structures like dams, landslides and open pit mines (displacement accuracy up to 0.1 mm). The MetaSensing FastGBSAR is the first ground based SAR instrument on the market able to produce two-dimensional deformation maps with this high acquisition rate. By that, deformation time series with a high temporal and spatial resolution can be generated, giving detailed information useful to determine the deformation mechanisms involved and eventually to predict an incoming failure. The system is fully portable and can be quickly installed on bedrock or a basement. The data acquisition and processing can be fully automated leading to a low effort in instrument operation and maintenance. Due to the short acquisition time of FastGBSAR, the coherence between two acquisitions is very high and the phase unwrapping is simplified enormously. This yields a high density of resolution cells with good quality and high reliability of the acquired deformations. The deformation maps can directly be used as input into an Early Warning system, to determine the state and danger of a slope or structure. In this paper, the technical principles of the instrument are described and case studies of different monitoring tasks are presented.

Reactor protection system with automatic self-testing and diagnostic

DOEpatents

Gaubatz, Donald C.

1996-01-01

A reactor protection system having four divisions, with quad redundant sensors for each scram parameter providing input to four independent microprocessor-based electronic chassis. Each electronic chassis acquires the scram parameter data from its own sensor, digitizes the information, and then transmits the sensor reading to the other three electronic chassis via optical fibers. To increase system availability and reduce false scrams, the reactor protection system employs two levels of voting on a need for reactor scram. The electronic chassis perform software divisional data processing, vote 2/3 with spare based upon information from all four sensors, and send the divisional scram signals to the hardware logic panel, which performs a 2/4 division vote on whether or not to initiate a reactor scram. Each chassis makes a divisional scram decision based on data from all sensors. Automatic detection and discrimination against failed sensors allows the reactor protection system to automatically enter a known state when sensor failures occur. Cross communication of sensor readings allows comparison of four theoretically "identical" values. This permits identification of sensor errors such as drift or malfunction. A diagnostic request for service is issued for errant sensor data. Automated self test and diagnostic monitoring, sensor input through output relay logic, virtually eliminate the need for manual surveillance testing. This provides an ability for each division to cross-check all divisions and to sense failures of the hardware logic.

Reactor protection system with automatic self-testing and diagnostic

DOEpatents

Gaubatz, D.C.

1996-12-17

A reactor protection system is disclosed having four divisions, with quad redundant sensors for each scram parameter providing input to four independent microprocessor-based electronic chassis. Each electronic chassis acquires the scram parameter data from its own sensor, digitizes the information, and then transmits the sensor reading to the other three electronic chassis via optical fibers. To increase system availability and reduce false scrams, the reactor protection system employs two levels of voting on a need for reactor scram. The electronic chassis perform software divisional data processing, vote 2/3 with spare based upon information from all four sensors, and send the divisional scram signals to the hardware logic panel, which performs a 2/4 division vote on whether or not to initiate a reactor scram. Each chassis makes a divisional scram decision based on data from all sensors. Automatic detection and discrimination against failed sensors allows the reactor protection system to automatically enter a known state when sensor failures occur. Cross communication of sensor readings allows comparison of four theoretically ``identical`` values. This permits identification of sensor errors such as drift or malfunction. A diagnostic request for service is issued for errant sensor data. Automated self test and diagnostic monitoring, sensor input through output relay logic, virtually eliminate the need for manual surveillance testing. This provides an ability for each division to cross-check all divisions and to sense failures of the hardware logic. 16 figs.

A sensitivity analysis of regional and small watershed hydrologic models

NASA Technical Reports Server (NTRS)

Ambaruch, R.; Salomonson, V. V.; Simmons, J. W.

1975-01-01

Continuous simulation models of the hydrologic behavior of watersheds are important tools in several practical applications such as hydroelectric power planning, navigation, and flood control. Several recent studies have addressed the feasibility of using remote earth observations as sources of input data for hydrologic models. The objective of the study reported here was to determine how accurately remotely sensed measurements must be to provide inputs to hydrologic models of watersheds, within the tolerances needed for acceptably accurate synthesis of streamflow by the models. The study objective was achieved by performing a series of sensitivity analyses using continuous simulation models of three watersheds. The sensitivity analysis showed quantitatively how variations in each of 46 model inputs and parameters affect simulation accuracy with respect to five different performance indices.

All Source Solution Decision Support Products Created for Stennis Space Center in Response to Hurricane Katrina

NASA Technical Reports Server (NTRS)

Ross, Kenton W.; Graham, William D.

2007-01-01

In the aftermath of Hurricane Katrina and in response to the needs of SSC (Stennis Space Center), NASA required the generation of decision support products with a broad range of geospatial inputs. Applying a systems engineering approach, the NASA ARTPO (Applied Research and Technology Project Office) at SSC evaluated the Center's requirements and source data quality. ARTPO identified data and information products that had the potential to meet decision-making requirements; included were remotely sensed data ranging from high-spatial-resolution aerial images through high-temporal-resolution MODIS (Moderate Resolution Imaging Spectroradiometer) products. Geospatial products, such as FEMA's (Federal Emergency Management Agency's) Advisory Base Flood Elevations, were also relevant. Where possible, ARTPO applied SSC calibration/validation expertise to both clarify the quality of various data source options and to validate that the inputs that were finally chosen met SSC requirements. ARTPO integrated various information sources into multiple decision support products, including two maps: Hurricane Katrina Inundation Effects at Stennis Space Center (highlighting surge risk posture) and Vegetation Change In and Around Stennis Space Center: Katrina and Beyond (highlighting fire risk posture).

Sequential Modular Position and Momentum Measurements of a Trapped Ion Mechanical Oscillator

NASA Astrophysics Data System (ADS)

Flühmann, C.; Negnevitsky, V.; Marinelli, M.; Home, J. P.

2018-04-01

The noncommutativity of position and momentum observables is a hallmark feature of quantum physics. However, this incompatibility does not extend to observables that are periodic in these base variables. Such modular-variable observables have been suggested as tools for fault-tolerant quantum computing and enhanced quantum sensing. Here, we implement sequential measurements of modular variables in the oscillatory motion of a single trapped ion, using state-dependent displacements and a heralded nondestructive readout. We investigate the commutative nature of modular variable observables by demonstrating no-signaling in time between successive measurements, using a variety of input states. Employing a different periodicity, we observe signaling in time. This also requires wave-packet overlap, resulting in quantum interference that we enhance using squeezed input states. The sequential measurements allow us to extract two-time correlators for modular variables, which we use to violate a Leggett-Garg inequality. Signaling in time and Leggett-Garg inequalities serve as efficient quantum witnesses, which we probe here with a mechanical oscillator, a system that has a natural crossover from the quantum to the classical regime.

HVS-based quantization steps for validation of digital cinema extended bitrates

NASA Astrophysics Data System (ADS)

Larabi, M.-C.; Pellegrin, P.; Anciaux, G.; Devaux, F.-O.; Tulet, O.; Macq, B.; Fernandez, C.

2009-02-01

In Digital Cinema, the video compression must be as transparent as possible to provide the best image quality to the audience. The goal of compression is to simplify transport, storing, distribution and projection of films. For all those tasks, equipments need to be developed. It is thus mandatory to reduce the complexity of the equipments by imposing limitations in the specifications. In this sense, the DCI has fixed the maximum bitrate for a compressed stream to 250 Mbps independently from the input format (4K/24fps, 2K/48fps or 2K/24fps). The work described in this paper This parameter is discussed in this paper because it is not consistent to double/quadruple the input rate without increasing the output rate. The work presented in this paper is intended to define quantization steps ensuring the visually lossless compression. Two steps are followed first to evaluate the effect of each subband separately and then to fin the scaling ratio. The obtained results show that it is necessary to increase the bitrate limit for cinema material in order to achieve the visually lossless.

Stability and Performance Metrics for Adaptive Flight Control

NASA Technical Reports Server (NTRS)

Stepanyan, Vahram; Krishnakumar, Kalmanje; Nguyen, Nhan; VanEykeren, Luarens

2009-01-01

This paper addresses the problem of verifying adaptive control techniques for enabling safe flight in the presence of adverse conditions. Since the adaptive systems are non-linear by design, the existing control verification metrics are not applicable to adaptive controllers. Moreover, these systems are in general highly uncertain. Hence, the system's characteristics cannot be evaluated by relying on the available dynamical models. This necessitates the development of control verification metrics based on the system's input-output information. For this point of view, a set of metrics is introduced that compares the uncertain aircraft's input-output behavior under the action of an adaptive controller to that of a closed-loop linear reference model to be followed by the aircraft. This reference model is constructed for each specific maneuver using the exact aerodynamic and mass properties of the aircraft to meet the stability and performance requirements commonly accepted in flight control. The proposed metrics are unified in the sense that they are model independent and not restricted to any specific adaptive control methods. As an example, we present simulation results for a wing damaged generic transport aircraft with several existing adaptive controllers.

Faraday rotation data analysis with least-squares elliptical fitting

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

White, Adam D.; McHale, G. Brent; Goerz, David A.

2010-10-15

A method of analyzing Faraday rotation data from pulsed magnetic field measurements is described. The method uses direct least-squares elliptical fitting to measured data. The least-squares fit conic parameters are used to rotate, translate, and rescale the measured data. Interpretation of the transformed data provides improved accuracy and time-resolution characteristics compared with many existing methods of analyzing Faraday rotation data. The method is especially useful when linear birefringence is present at the input or output of the sensing medium, or when the relative angle of the polarizers used in analysis is not aligned with precision; under these circumstances the methodmore » is shown to return the analytically correct input signal. The method may be pertinent to other applications where analysis of Lissajous figures is required, such as the velocity interferometer system for any reflector (VISAR) diagnostics. The entire algorithm is fully automated and requires no user interaction. An example of algorithm execution is shown, using data from a fiber-based Faraday rotation sensor on a capacitive discharge experiment.« less

Collaborative Estimation in Distributed Sensor Networks

ERIC Educational Resources Information Center

Kar, Swarnendu

2013-01-01

Networks of smart ultra-portable devices are already indispensable in our lives, augmenting our senses and connecting our lives through real time processing and communication of sensory (e.g., audio, video, location) inputs. Though usually hidden from the user's sight, the engineering of these devices involves fierce tradeoffs between energy…

40 CFR 60.703 - Monitoring of emissions and operations.

Code of Federal Regulations, 2011 CFR

2011-07-01

... position before any substantial heat exchange is encountered. (ii) Where a catalytic incinerator is used... equipment: (1) A heat sensing device, such as an ultraviolet beam sensor or thermocouple, at the pilot light... 44 MW (150 million Btu/hr) design heat input capacity. Any vent stream introduced with primary fuel...

40 CFR 60.703 - Monitoring of emissions and operations.

Code of Federal Regulations, 2012 CFR

2012-07-01

... position before any substantial heat exchange is encountered. (ii) Where a catalytic incinerator is used... equipment: (1) A heat sensing device, such as an ultraviolet beam sensor or thermocouple, at the pilot light... 44 MW (150 million Btu/hr) design heat input capacity. Any vent stream introduced with primary fuel...

40 CFR 60.703 - Monitoring of emissions and operations.

Code of Federal Regulations, 2010 CFR

2010-07-01

... position before any substantial heat exchange is encountered. (ii) Where a catalytic incinerator is used... equipment: (1) A heat sensing device, such as an ultraviolet beam sensor or thermocouple, at the pilot light... 44 MW (150 million Btu/hr) design heat input capacity. Any vent stream introduced with primary fuel...

A Skylab program for the International Hydrological Decade (IHD). [Lake Ontario Basin

NASA Technical Reports Server (NTRS)

Polcyn, F. C. (Principal Investigator); Rebel, D. L.

1974-01-01

The author has identified the following significant results. The development of the algorithm (using real data) relating red and IR reflectance to surface soil moisture over regions of variable vegetation cover will enable remote sensing to make direct inputs into determination of this important hydrologic parameter.

A vegetation mapping strategy for conifer forests by combining airborne LiDAR data and aerial imagery

Treesearch

Yanjun Su; Qinghua Guo; Danny L. Fry; Brandon M. Collins; Maggi Kelly; Jacob P. Flanagan; John J. Battles

2016-01-01

Abstract. Accurate vegetation mapping is critical for natural resources management, ecological analysis, and hydrological modeling, among other tasks. Remotely sensed multispectral and hyperspectral imageries have proved to be valuable inputs to the vegetation mapping process, but they can provide only limited vegetation structure...

78 FR 29387 - Government-Owned Inventions, Available for Licensing

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-20

... System for Physiologically Modulating Action Role-playing Open World Video Games and Simulations Which... Deposition Measurement for the Electron Beam Free Form Fabrication (EBF3) Process; NASA Case No.: LAR-17887-1... Modulating Videogames and Simulations Which Use Gesture and Body Image Sensing Control Input Devices; NASA...

Human mobility prediction from region functions with taxi trajectories.

PubMed

Wang, Minjie; Yang, Su; Sun, Yi; Gao, Jun

2017-01-01

People in cities nowadays suffer from increasingly severe traffic jams due to less awareness of how collective human mobility is affected by urban planning. Besides, understanding how region functions shape human mobility is critical for business planning but remains unsolved so far. This study aims to discover the association between region functions and resulting human mobility. We establish a linear regression model to predict the traffic flows of Beijing based on the input referred to as bag of POIs. By solving the predictor in the sense of sparse representation, we find that the average prediction precision is over 74% and each type of POI contributes differently in the predictor, which accounts for what factors and how such region functions attract people visiting. Based on these findings, predictive human mobility could be taken into account when planning new regions and region functions.

Auroral photometry from the atmosphere Explorer satellite

NASA Technical Reports Server (NTRS)

Rees, M. H.; Abreu, V. J.

1984-01-01

Attention is given to the ability of remote sensing from space to yield quantitative auroral and ionospheric parametrers, in view of the auroral measurements made during two passes of the Explorer C satellite over the Poker Flat Optical Observatory and the Chatanika Radar Facility. The emission rate of the N2(+) 4278 A band computed from intensity measurements of energetic auroral electrons has tracked the same spetral feature that was measured remotely from the satellite over two decades of intensity, providing a stringent test for the measurement of atmospheric scattering effects. It also verifies the absolute intensity with respect to ground-based photometric measurements. In situ satellite measurments of ion densities and ground based electron density profile radar measurements provide a consistent picture of the ionospheric response to auroral input, while also predicting the observed optical emission rate.

Modifying Bagnold's Sediment Transport Equation for Use in Watershed-Scale Channel Incision Models

NASA Astrophysics Data System (ADS)

Lammers, R. W.; Bledsoe, B. P.

2016-12-01

Destabilized stream channels may evolve through a sequence of stages, initiated by bed incision and followed by bank erosion and widening. Channel incision can be modeled using Exner-type mass balance equations, but model accuracy is limited by the accuracy and applicability of the selected sediment transport equation. Additionally, many sediment transport relationships require significant data inputs, limiting their usefulness in data-poor environments. Bagnold's empirical relationship for bedload transport is attractive because it is based on stream power, a relatively straightforward parameter to estimate using remote sensing data. However, the equation is also dependent on flow depth, which is more difficult to measure or estimate for entire drainage networks. We recast Bagnold's original sediment transport equation using specific discharge in place of flow depth. Using a large dataset of sediment transport rates from the literature, we show that this approach yields similar predictive accuracy as other stream power based relationships. We also explore the applicability of various critical stream power equations, including Bagnold's original, and support previous conclusions that these critical values can be predicted well based solely on sediment grain size. In addition, we propagate error in these sediment transport equations through channel incision modeling to compare the errors associated with our equation to alternative formulations. This new version of Bagnold's bedload transport equation has utility for channel incision modeling at larger spatial scales using widely available and remote sensing data.

Compressive sensing reconstruction of 3D wet refractivity based on GNSS and InSAR observations

NASA Astrophysics Data System (ADS)

Heublein, Marion; Alshawaf, Fadwa; Erdnüß, Bastian; Zhu, Xiao Xiang; Hinz, Stefan

2018-06-01

In this work, the reconstruction quality of an approach for neutrospheric water vapor tomography based on Slant Wet Delays (SWDs) obtained from Global Navigation Satellite Systems (GNSS) and Interferometric Synthetic Aperture Radar (InSAR) is investigated. The novelties of this approach are (1) the use of both absolute GNSS and absolute InSAR SWDs for tomography and (2) the solution of the tomographic system by means of compressive sensing (CS). The tomographic reconstruction is performed based on (i) a synthetic SWD dataset generated using wet refractivity information from the Weather Research and Forecasting (WRF) model and (ii) a real dataset using GNSS and InSAR SWDs. Thus, the validation of the achieved results focuses (i) on a comparison of the refractivity estimates with the input WRF refractivities and (ii) on radiosonde profiles. In case of the synthetic dataset, the results show that the CS approach yields a more accurate and more precise solution than least squares (LSQ). In addition, the benefit of adding synthetic InSAR SWDs into the tomographic system is analyzed. When applying CS, adding synthetic InSAR SWDs into the tomographic system improves the solution both in magnitude and in scattering. When solving the tomographic system by means of LSQ, no clear behavior is observed. In case of the real dataset, the estimated refractivities of both methodologies show a consistent behavior although the LSQ and CS solution strategies differ.

Low-Cost Ultra-High Spatial and Temporal Resolution Mapping of Intertidal Rock Platforms

NASA Astrophysics Data System (ADS)

Bryson, M.; Johnson-Roberson, M.; Murphy, R.

2012-07-01

Intertidal ecosystems have primarily been studied using field-based sampling; remote sensing offers the ability to collect data over large areas in a snapshot of time which could compliment field-based sampling methods by extrapolating them into the wider spatial and temporal context. Conventional remote sensing tools (such as satellite and aircraft imaging) provide data at relatively course, sub-meter resolutions or with limited temporal resolutions and relatively high costs for small-scale environmental science and ecology studies. In this paper, we describe a low-cost, kite-based imaging system and photogrammetric pipeline that was developed for constructing highresolution, 3D, photo-realistic terrain models of intertidal rocky shores. The processing pipeline uses automatic image feature detection and matching, structure-from-motion and photo-textured terrain surface reconstruction algorithms that require minimal human input and only a small number of ground control points and allow the use of cheap, consumer-grade digital cameras. The resulting maps combine colour and topographic information at sub-centimeter resolutions over an area of approximately 100m, thus enabling spatial properties of the intertidal environment to be determined across a hierarchy of spatial scales. Results of the system are presented for an intertidal rock platform at Cape Banks, Sydney, Australia. Potential uses of this technique include mapping of plant (micro- and macro-algae) and animal (e.g. gastropods) assemblages at multiple spatial and temporal scales.

The storage and recall of auditory memory.

PubMed

Nebenzahl, I; Albeck, Y

1990-01-01

The architecture of the auditory memory is investigated. The auditory information is assumed to be represented by f-t patterns. With the help of a psycho-physical experiment it is demonstrated that the storage of these patterns is highly folded in the sense that a long signal is broken into many short stretches before being stored in the memory. Recognition takes place by correlating newly heard input in the short term memory to information previously stored in the long term memory. We show that this correlation is performed after the input is accumulated and held statically in the short term memory.

All-DNA finite-state automata with finite memory

PubMed Central

Wang, Zhen-Gang; Elbaz, Johann; Remacle, F.; Levine, R. D.; Willner, Itamar

2010-01-01

Biomolecular logic devices can be applied for sensing and nano-medicine. We built three DNA tweezers that are activated by the inputs H+/OH-; ; nucleic acid linker/complementary antilinker to yield a 16-states finite-state automaton. The outputs of the automata are the configuration of the respective tweezers (opened or closed) determined by observing fluorescence from a fluorophore/quencher pair at the end of the arms of the tweezers. The system exhibits a memory because each current state and output depend not only on the source configuration but also on past states and inputs. PMID:21135212

Fractional Modeling of the AC Large-Signal Frequency Response in Magnetoresistive Current Sensors

PubMed Central

Arias, Sergio Iván Ravello; Muñoz, Diego Ramírez; Moreno, Jaime Sánchez; Cardoso, Susana; Ferreira, Ricardo; de Freitas, Paulo Jorge Peixeiro

2013-01-01

Fractional calculus is considered when derivatives and integrals of non-integer order are applied over a specific function. In the electrical and electronic domain, the transfer function dependence of a fractional filter not only by the filter order n, but additionally, of the fractional order α is an example of a great number of systems where its input-output behavior could be more exactly modeled by a fractional behavior. Following this aim, the present work shows the experimental ac large-signal frequency response of a family of electrical current sensors based in different spintronic conduction mechanisms. Using an ac characterization set-up the sensor transimpedance function Zt(if) is obtained considering it as the relationship between sensor output voltage and input sensing current, Zt(jf)=Vo,sensor(jf)/Isensor(jf). The study has been extended to various magnetoresistance sensors based in different technologies like anisotropic magnetoresistance (AMR), giant magnetoresistance (GMR), spin-valve (GMR-SV) and tunnel magnetoresistance (TMR). The resulting modeling shows two predominant behaviors, the low-pass and the inverse low-pass with fractional index different from the classical integer response. The TMR technology with internal magnetization offers the best dynamic and sensitivity properties opening the way to develop actual industrial applications. PMID:24351648

Use of Space Technology in Flood Mitigation (Western Province, Zambia)

NASA Astrophysics Data System (ADS)

Mulando, A.

2001-05-01

Disasters, by definition are events that appear suddenly and with little warning. They are usually short lived, with extreme events bringing death, injury and destruction of buildings and communications. Their aftermath can be as damaging as their physical effects through destruction of sanitation and water supplies, destruction of housing and breakdown of transport for food, temporary shelter and emergency services. Since floods are one of the natural disasters which endanger both life and property, it becomes vital to know its extents and where the hazards exists. Flood disasters manifest natural processes on a larger scale and information provided by Remote Sensing is a most appropriate input to analysis of actual events and investigations of potential risks. An analytical and qualitative image processing and interpretation of Remotely Sensed data as well as other data such as rainfall, population, settlements not to mention but a few should be used to derive good mitigation strategies. Since mitigation is the cornerstone of emergency management, it therefore becomes a sustained action that will reduce or eliminate long term risks to people and property from natural hazards such as floods and their effects. This will definitely involve keeping of homes and other sensitive structures away from flood plains. Promotion of sound land use planning based on this known hazard, "FLOODS" is one such form of mitigation that can be applied in flood affected areas within flood plain. Therefore future mitigation technologies and procedures should increasingly be based on the use of flood extent information provided by Remote Sensing Satellites like the NOAA AVHRR as well as information on the designated flood hazard and risk areas.

Differential solute gas response in ionic-liquid-based QCM arrays: elucidating design factors responsible for discriminative explosive gas sensing.

PubMed

Rehman, Abdul; Hamilton, Andrew; Chung, Alfred; Baker, Gary A; Wang, Zhe; Zeng, Xiangqun

2011-10-15

An eight-sensor array coupling a chemoselective room-temperature ionic liquid (RTIL) with quartz crystal microbalance (QCM) transduction is presented in this work in order to demonstrate the power of this approach in differentiating closely related analytes in sensory devices. The underlying mechanism behind the specific sensory response was explored by (i) studying mass loading and viscoelasticity effects of the sensing layers, predominantly through variation in damping impedance, the combination of which determines the sensitivity; (ii) creation of a solvation model based on Abraham's solvation descriptors which reveals the fact that polarizability and lipophilicity are the main factors influencing the dissolution of gas analytes into the RTILs; and (iii) determination of enthalpy and entropy values for the studied interactions and comparison via a simulation model, which is also effective for pattern discrimination, in order to establish a foundation for the analytical scientist as well as inspiration for synthetic pathways and innovative research into next-generation sensory approaches. The reported sensors displayed an excellent sensitivity with detection limit of <0.2%, fast response and recovery, and a workable temperature range of 27-55 °C and even higher. Linear discriminant analysis (LDA) showed a discrimination accuracy of 86-92% for nitromethane and 1-ethyl-2-nitrobenzene, 71% for different mixtures of nitromethane, and 100% for these analytes when thermodynamic parameters were used as input data. We envisage applications to detecting other nitroaromatics and security-related gas targets, and high-temperature or real-time situations where manual access is restricted, opening up new horizons in chemical sensing. © 2011 American Chemical Society

Assimilating Merged Remote Sensing and Ground based Snowpack Information for Runoff Simulation and Forecasting using Hydrological Models

NASA Astrophysics Data System (ADS)

Infante Corona, J. A.; Lakhankar, T.; Khanbilvardi, R.; Pradhanang, S. M.

2013-12-01

Stream flow estimation and flood prediction influenced by snow melting processes have been studied for the past couple of decades because of their destruction potential, money losses and demises. It has been observed that snow, that was very stationary during its seasons, now is variable in shorter time-scales (daily and hourly) and rapid snowmelt can contribute or been the cause of floods. Therefore, good estimates of snowpack properties on ground are necessary in order to have an accurate prediction of these destructive events. The snow thermal model (SNTHERM) is a 1-dimensional model that analyzes the snowpack properties given the climatological conditions of a particular area. Gridded data from both, in-situ meteorological observations and remote sensing data will be produced using interpolation methods; thus, snow water equivalent (SWE) and snowmelt estimations can be obtained. The soil and water assessment tool (SWAT) is a hydrological model capable of predicting runoff quantity and quality of a watershed given its main physical and hydrological properties. The results from SNTHERM will be used as an input for SWAT in order to have simulated runoff under snowmelt conditions. This project attempts to improve the river discharge estimation considering both, excess rainfall runoff and the snow melting process. Obtaining a better estimation of the snowpack properties and evolution is expected. A coupled use of SNTHERM and SWAT based on meteorological in situ and remote sensed data will improve the temporal and spatial resolution of the snowpack characterization and river discharge estimations, and thus flood prediction.

Graphene-based aptamer logic gates and their application to multiplex detection.

PubMed

Wang, Li; Zhu, Jinbo; Han, Lei; Jin, Lihua; Zhu, Chengzhou; Wang, Erkang; Dong, Shaojun

2012-08-28

In this work, a GO/aptamer system was constructed to create multiplex logic operations and enable sensing of multiplex targets. 6-Carboxyfluorescein (FAM)-labeled adenosine triphosphate binding aptamer (ABA) and FAM-labeled thrombin binding aptamer (TBA) were first adsorbed onto graphene oxide (GO) to form a GO/aptamer complex, leading to the quenching of the fluorescence of FAM. We demonstrated that the unique GO/aptamer interaction and the specific aptamer-target recognition in the target/GO/aptamer system were programmable and could be utilized to regulate the fluorescence of FAM via OR and INHIBIT logic gates. The fluorescence changed according to different input combinations, and the integration of OR and INHIBIT logic gates provided an interesting approach for logic sensing applications where multiple target molecules were present. High-throughput fluorescence imagings that enabled the simultaneous processing of many samples by using the combinatorial logic gates were realized. The developed logic gates may find applications in further development of DNA circuits and advanced sensors for the identification of multiple targets in complex chemical environments.

Monitoring and validating spatio-temporal continuously daily evapotranspiration and its components at river basin scale

NASA Astrophysics Data System (ADS)

Song, L.; Liu, S.; Kustas, W. P.; Nieto, H.

2017-12-01

Operational estimation of spatio-temporal continuously daily evapotranspiration (ET), and the components evaporation (E) and transpiration (T), at watershed scale is very useful for developing a sustainable water resource strategy in semi-arid and arid areas. In this study, multi-year all-weather daily ET, E and T were estimated using MODIS-based (Dual Temperature Difference) DTD model under different land covers in Heihe watershed, China. The remotely sensed ET was validated using ground measurements from large aperture scintillometer systems, with a source area of several kilometers, under grassland, cropland and riparian shrub-forest. The results showed that the remotely sensed ET produced mean absolute percent deviation (MAPD) errors of about 30% during the growing season for all-weather conditions, but the model performed better under clear sky conditions. However, uncertainty in interpolated MODIS land surface temperature input data under cloudy conditions to the DTD model, and the representativeness of LAS measurements for the heterogeneous land surfaces contribute to the discrepancies between the modeled and ground measured surface heat fluxes, especially for the more humid grassland and heterogeneous shrub-forest sites.

Fully integrated low-noise readout circuit with automatic offset cancellation loop for capacitive microsensors.

PubMed

Song, Haryong; Park, Yunjong; Kim, Hyungseup; Cho, Dong-Il Dan; Ko, Hyoungho

2015-10-14

Capacitive sensing schemes are widely used for various microsensors; however, such microsensors suffer from severe parasitic capacitance problems. This paper presents a fully integrated low-noise readout circuit with automatic offset cancellation loop (AOCL) for capacitive microsensors. The output offsets of the capacitive sensing chain due to the parasitic capacitances and process variations are automatically removed using AOCL. The AOCL generates electrically equivalent offset capacitance and enables charge-domain fine calibration using a 10-bit R-2R digital-to-analog converter, charge-transfer switches, and a charge-storing capacitor. The AOCL cancels the unwanted offset by binary-search algorithm based on 10-bit successive approximation register (SAR) logic. The chip is implemented using 0.18 μm complementary metal-oxide-semiconductor (CMOS) process with an active area of 1.76 mm². The power consumption is 220 μW with 3.3 V supply. The input parasitic capacitances within the range of -250 fF to 250 fF can be cancelled out automatically, and the required calibration time is lower than 10 ms.

A humidity sensing organic-inorganic composite for environmental monitoring.

PubMed

Ahmad, Zubair; Zafar, Qayyum; Sulaiman, Khaulah; Akram, Rizwan; Karimov, Khasan S

2013-03-14

In this paper, we present the effect of varying humidity levels on the electrical parameters and the multi frequency response of the electrical parameters of an organic-inorganic composite (PEPC+NiPc+Cu2O)-based humidity sensor. Silver thin films (thickness ~200 nm) were primarily deposited on plasma cleaned glass substrates by the physical vapor deposition (PVD) technique. A pair of rectangular silver electrodes was formed by patterning silver film through standard optical lithography technique. An active layer of organic-inorganic composite for humidity sensing was later spun coated to cover the separation between the silver electrodes. The electrical characterization of the sensor was performed as a function of relative humidity levels and frequency of the AC input signal. The sensor showed reversible changes in its capacitance with variations in humidity level. The maximum sensitivity ~31.6 pF/%RH at 100 Hz in capacitive mode of operation has been attained. The aim of this study was to increase the sensitivity of the previously reported humidity sensors using PEPC and NiPc, which has been successfully achieved.

A Humidity Sensing Organic-Inorganic Composite for Environmental Monitoring

PubMed Central

Ahmad, Zubair; Zafar, Qayyum; Sulaiman, Khaulah; Akram, Rizwan; Karimov, Khasan S.

2013-01-01

In this paper, we present the effect of varying humidity levels on the electrical parameters and the multi frequency response of the electrical parameters of an organic-inorganic composite (PEPC+NiPc+Cu2O)-based humidity sensor. Silver thin films (thickness ∼200 nm) were primarily deposited on plasma cleaned glass substrates by the physical vapor deposition (PVD) technique. A pair of rectangular silver electrodes was formed by patterning silver film through standard optical lithography technique. An active layer of organic-inorganic composite for humidity sensing was later spun coated to cover the separation between the silver electrodes. The electrical characterization of the sensor was performed as a function of relative humidity levels and frequency of the AC input signal. The sensor showed reversible changes in its capacitance with variations in humidity level. The maximum sensitivity ∼31.6 pF/%RH at 100 Hz in capacitive mode of operation has been attained. The aim of this study was to increase the sensitivity of the previously reported humidity sensors using PEPC and NiPc, which has been successfully achieved. PMID:23493124

Fully Integrated Low-Noise Readout Circuit with Automatic Offset Cancellation Loop for Capacitive Microsensors

PubMed Central

Song, Haryong; Park, Yunjong; Kim, Hyungseup; Cho, Dong-il Dan; Ko, Hyoungho

2015-01-01

Capacitive sensing schemes are widely used for various microsensors; however, such microsensors suffer from severe parasitic capacitance problems. This paper presents a fully integrated low-noise readout circuit with automatic offset cancellation loop (AOCL) for capacitive microsensors. The output offsets of the capacitive sensing chain due to the parasitic capacitances and process variations are automatically removed using AOCL. The AOCL generates electrically equivalent offset capacitance and enables charge-domain fine calibration using a 10-bit R-2R digital-to-analog converter, charge-transfer switches, and a charge-storing capacitor. The AOCL cancels the unwanted offset by binary-search algorithm based on 10-bit successive approximation register (SAR) logic. The chip is implemented using 0.18 μm complementary metal-oxide-semiconductor (CMOS) process with an active area of 1.76 mm2. The power consumption is 220 μW with 3.3 V supply. The input parasitic capacitances within the range of −250 fF to 250 fF can be cancelled out automatically, and the required calibration time is lower than 10 ms. PMID:26473877

An Interoperable, Agricultural Information System Based on Satellite Remote Sensing Data

NASA Technical Reports Server (NTRS)

Teng, William; Chiu, Long; Doraiswamy, Paul; Kempler, Steven; Liu, Zhong; Pham, Long; Rui, Hualan

2005-01-01

Monitoring global agricultural crop conditions during the growing season and estimating potential seasonal production are critically important for market development of US. agricultural products and for global food security. The Goddard Space Flight Center Earth Sciences Data and Information Services Center Distributed Active Archive Center (GES DISC DAAC) is developing an Agricultural Information System (AIS), evolved from an existing TRMM Online Visualization and Analysis System (TOVAS), which will operationally provide satellite remote sensing data products (e.g., rainfall) and services. The data products will include crop condition and yield prediction maps, generated from a crop growth model with satellite data inputs, in collaboration with the USDA Agricultural Research Service. The AIS will enable the remote, interoperable access to distributed data, by using the GrADS-DODS Server (GDS) and by being compliant with Open GIS Consortium standards. Users will be able to download individual files, perform interactive online analysis, as well as receive operational data flows. AIS outputs will be integrated into existing operational decision support systems for global crop monitoring, such as those of the USDA Foreign Agricultural Service and the U.N. World Food Program.

Self-Powered Viscosity and Pressure Sensing in Microfluidic Systems Based on the Piezoelectric Energy Harvesting of Flowing Droplets.

PubMed

Wang, Zhao; Tan, Lun; Pan, Xumin; Liu, Gao; He, Yahua; Jin, Wenchao; Li, Meng; Hu, Yongming; Gu, Haoshuang

2017-08-30

The rapid development of microscaled piezoelectric energy harvesters has provided a simple and highly efficient way for building self-powered sensor systems through harvesting the mechanical energy from the ambient environment. In this work, a self-powered microfluidic sensor that can harvest the mechanical energy of the fluid and simultaneously monitor their characteristics was fabricated by integrating the flexible piezoelectric poly(vinylidene fluoride) (PVDF) nanofibers with the well-designed microfluidic chips. Those devices could generate open-circuit high output voltage up to 1.8 V when a droplet of water is flowing past the suspended PVDF nanofibers and result in their periodical deformations. The impulsive output voltage signal allowed them to be utilized for droplets or bubbles counting in the microfluidic systems. Furthermore, the devices also exhibited self-powered sensing behavior due to the decreased voltage amplitude with increasing input pressure and liquid viscosity. The drop of output voltage could be attributed to the variation of flow condition and velocity of the droplets, leading to the reduced deformation of the piezoelectric PVDF layer and the decrease of the generated piezoelectric potential.

Advances in remote sensing of forest background reflectance with MODIS BRDF data across Europe

NASA Astrophysics Data System (ADS)

Pisek, Jan; Alikas, Krista; Lukeš, Petr; Lundin, Lars; Kobler, Johannes; Santos-Reis, Margarida; Chen, Jing

2017-04-01

Spatial and temporal patterns of forest background (understory) reflectance are crucial for retrieving biophysical parameters of forest canopies (overstory) and subsequently for ecosystem modeling. However, systematic reflectance data covering different site types are almost missing. This presentation will focus on the validation of background reflectance retrievals using MODIS bidirectional reflectance distribution function (BRDF) data against in-situ understory reflectance measurements covering a diverse set of long-term ecological research (LTER) sites distributed along a wide latitudinal and elevational gradient across Europe: protected coniferous blueberry forest in Sweden, karst forest system in Austria, floodplain broadleaf forest and coniferous forest in the Czech Republic, and Mediterranean agro-sylvo-pastoral woodlands in Portugal. The multi-angle remote sensing data-based methodology was originally developed for the forest background signal retrieval in a boreal region. Here its performance will be tested across diverse forest conditions and moments during the growing season, which is a necessary step before conducting extensive mapping over forested areas. The results can be also used as an input for improved modeling of local carbon and energy fluxes.

The Amygdala is a Chemosensor that Detects Carbon Dioxide and Acidosis to Elicit Fear Behavior

PubMed Central

Ziemann, Adam E.; Allen, Jason E.; Dahdaleh, Nader S.; Drebot, Iuliia I.; Coryell, Matt; Wunsch, Amanda M.; Lynch, Cynthia M.; Faraci, Frank M.; Howard, Matthew A.; Welsh, Michael J.; Wemmie, John A.

2009-01-01

SUMMARY The amygdala processes and directs inputs and outputs that are key to fear behavior. However, whether it directly senses fear-evoking stimuli is unknown. Because the amygdala expresses acid sensing ion channel-1a (ASIC1a), and ASIC1a is required for normal fear responses, we hypothesized that the amygdala might detect a reduced pH. We found that inhaled CO2 reduced brain pH and evoked fear behavior in mice. Eliminating or inhibiting ASIC1a markedly impaired this activity, and localized ASIC1a expression in the amygdala rescued the CO2- induced fear deficit of ASIC1a-null animals. Buffering pH attenuated fear behavior, whereas directly reducing pH with amygdala microinjections reproduced the effect of CO2. These data identify the amygdala as an important chemosensor that detects hypercarbia and acidosis and initiates behavioral responses. They also give a molecular explanation for how rising CO2 concentrations elicit intense fear and provide a foundation for dissecting the bases of anxiety and panic disorders. PMID:19945383

High speed sampler and demultiplexer

DOEpatents

McEwan, T.E.

1995-12-26

A high speed sampling demultiplexer based on a plurality of sampler banks, each bank comprising a sample transmission line for transmitting an input signal, a strobe transmission line for transmitting a strobe signal, and a plurality of sampling gates at respective positions along the sample transmission line for sampling the input signal in response to the strobe signal. Strobe control circuitry is coupled to the plurality of banks, and supplies a sequence of bank strobe signals to the strobe transmission lines in each of the plurality of banks, and includes circuits for controlling the timing of the bank strobe signals among the banks of samplers. Input circuitry is included for supplying the input signal to be sampled to the plurality of sample transmission lines in the respective banks. The strobe control circuitry can repetitively strobe the plurality of banks of samplers such that the banks of samplers are cycled to create a long sample length. Second tier demultiplexing circuitry is coupled to each of the samplers in the plurality of banks. The second tier demultiplexing circuitry senses the sample taken by the corresponding sampler each time the bank in which the sampler is found is strobed. A plurality of such samples can be stored by the second tier demultiplexing circuitry for later processing. Repetitive sampling with the high speed transient sampler induces an effect known as ``strobe kickout``. The sample transmission lines include structures which reduce strobe kickout to acceptable levels, generally 60 dB below the signal, by absorbing the kickout pulses before the next sampling repetition. 16 figs.

Efficient Multiplexer FPGA Block Structures Based on G4FETs

NASA Technical Reports Server (NTRS)

Vatan, Farrokh; Fijany, Amir

2009-01-01

Generic structures have been conceived for multiplexer blocks to be implemented in field-programmable gate arrays (FPGAs) based on four-gate field-effect transistors (G(sup 4)FETs). This concept is a contribution to the continuing development of digital logic circuits based on G4FETs and serves as a further demonstration that logic circuits based on G(sup 4)FETs could be more efficient (in the sense that they could contain fewer transistors), relative to functionally equivalent logic circuits based on conventional transistors. Results in this line of development at earlier stages were summarized in two previous NASA Tech Briefs articles: "G(sup 4)FETs as Universal and Programmable Logic Gates" (NPO-41698), Vol. 31, No. 7 (July 2007), page 44, and "Efficient G4FET-Based Logic Circuits" (NPO-44407), Vol. 32, No. 1 ( January 2008), page 38 . As described in the first-mentioned previous article, a G4FET can be made to function as a three-input NOT-majority gate, which has been shown to be a universal and programmable logic gate. The universality and programmability could be exploited to design logic circuits containing fewer components than are required for conventional transistor-based circuits performing the same logic functions. The second-mentioned previous article reported results of a comparative study of NOT-majority-gate (G(sup 4)FET)-based logic-circuit designs and equivalent NOR- and NAND-gate-based designs utilizing conventional transistors. [NOT gates (inverters) were also included, as needed, in both the G(sup 4)FET- and the NOR- and NAND-based designs.] In most of the cases studied, fewer logic gates (and, hence, fewer transistors), were required in the G(sup 4)FET-based designs. There are two popular categories of FPGA block structures or architectures: one based on multiplexers, the other based on lookup tables. In standard multiplexer- based architectures, the basic building block is a tree-like configuration of multiplexers, with possibly a few additional logic gates such as ANDs or ORs. Interconnections are realized by means of programmable switches that may connect the input terminals of a block to output terminals of other blocks, may bridge together some of the inputs, or may connect some of the input terminals to signal sources representing constant logical levels 0 or 1. The left part of the figure depicts a four-to-one G(sup 4)FET-based multiplexer tree; the right part of the figure depicts a functionally equivalent four-to-one multiplexer based on conventional transistors. The G(sup 4)FET version would contains 54 transistors; the conventional version contains 70 transistors.

Human-centric sensing.

PubMed

Srivastava, Mani; Abdelzaher, Tarek; Szymanski, Boleslaw

2012-01-13

The first decade of the century witnessed a proliferation of devices with sensing and communication capabilities in the possession of the average individual. Examples range from camera phones and wireless global positioning system units to sensor-equipped, networked fitness devices and entertainment platforms (such as Wii). Social networking platforms emerged, such as Twitter, that allow sharing information in real time. The unprecedented deployment scale of such sensors and connectivity options ushers in an era of novel data-driven applications that rely on inputs collected by networks of humans or measured by sensors acting on their behalf. These applications will impact domains as diverse as health, transportation, energy, disaster recovery, intelligence and warfare. This paper surveys the important opportunities in human-centric sensing, identifies challenges brought about by such opportunities and describes emerging solutions to these challenges.

Remote shock sensing and notification system

DOEpatents

Muralidharan, Govindarajan [Knoxville, TN; Britton, Charles L [Alcoa, TN; Pearce, James [Lenoir City, TN; Jagadish, Usha [Knoxville, TN; Sikka, Vinod K [Oak Ridge, TN

2010-11-02

A low-power shock sensing system includes at least one shock sensor physically coupled to a chemical storage tank to be monitored for impacts, and an RF transmitter which is in a low-power idle state in the absence of a triggering signal. The system includes interface circuitry including or activated by the shock sensor, wherein an output of the interface circuitry is coupled to an input of the RF transmitter. The interface circuitry triggers the RF transmitter with the triggering signal to transmit an alarm message to at least one remote location when the sensor senses a shock greater than a predetermined threshold. In one embodiment the shock sensor is a shock switch which provides an open and a closed state, the open state being a low power idle state.

Remote shock sensing and notification system

DOEpatents

Muralidharan, Govindarajan; Britton, Charles L.; Pearce, James; Jagadish, Usha; Sikka, Vinod K.

2008-11-11

A low-power shock sensing system includes at least one shock sensor physically coupled to a chemical storage tank to be monitored for impacts, and an RF transmitter which is in a low-power idle state in the absence of a triggering signal. The system includes interference circuitry including or activated by the shock sensor, wherein an output of the interface circuitry is coupled to an input of the RF transmitter. The interface circuitry triggers the RF transmitting with the triggering signal to transmit an alarm message to at least one remote location when the sensor senses a shock greater than a predetermined threshold. In one embodiment the shock sensor is a shock switch which provides an open and a closed state, the open state being a low power idle state.

Impact of remote sensing upon the planning, management, and development of water resources

NASA Technical Reports Server (NTRS)

Loats, H. L.; Fowler, T. R.; Frech, S. L.

1974-01-01

A survey of the principal water resource users was conducted to determine the impact of new remote data streams on hydrologic computer models. The analysis of the responses and direct contact demonstrated that: (1) the majority of water resource effort of the type suitable to remote sensing inputs is conducted by major federal water resources agencies or through federally stimulated research, (2) the federal government develops most of the hydrologic models used in this effort; and (3) federal computer power is extensive. The computers, computer power, and hydrologic models in current use were determined.

The energy balance of wind waves and the remote sensing problem

NASA Technical Reports Server (NTRS)

Hasselmann, K.

1972-01-01

Measurements of wave growth indicate an energy balance of the wave spectrum governed primarily by input from the atmosphere, nonlinear transfer to shorter and longer waves, and advection. The pronounced spectral peak and sharp low frequency cut-off characteristic of fetch-limited spectra are explained as a self-stabilizing feature of the nonlinear wave-wave interactions. The momentum transferred from the atmosphere to the wind waves accounts for a large part of the wind drag. These findings are relevant for remote microwave sensing of the sea surface by backscatter and passive radiometry methods.

Development of a computer model to predict platform station keeping requirements in the Gulf of Mexico using remote sensing data

NASA Technical Reports Server (NTRS)

Barber, Bryan; Kahn, Laura; Wong, David

1990-01-01

Offshore operations such as oil drilling and radar monitoring require semisubmersible platforms to remain stationary at specific locations in the Gulf of Mexico. Ocean currents, wind, and waves in the Gulf of Mexico tend to move platforms away from their desired locations. A computer model was created to predict the station keeping requirements of a platform. The computer simulation uses remote sensing data from satellites and buoys as input. A background of the project, alternate approaches to the project, and the details of the simulation are presented.

Cropland measurement using Thematic Mapper data and radiometric model

NASA Technical Reports Server (NTRS)

Lyon, John G.; Khuwaiter, I. H. S.

1989-01-01

To halt erosion and desertification, it is necessary to quantify resources that are affected. Necessary information includes inventory of croplands and desert areas as they change over time. Several studies indicate the value of remote sensor data as input to inventories. In this study, the radiometric modeling of spectral characteristics of soil and vegetation provides the theoretical basis for the remote sensing approach. Use of Landsat Thematic Mapper images allows measurement of croplands in Saudi Arabia, demonstrating the capability of the approach. The inventory techniques and remote sensing approach presented are potentially useful in developing countries.

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.

Space View of the 1991 Gulf War Kuwaiti Oil Fires

NASA Astrophysics Data System (ADS)

Torres, O.; Bhartia, P. K.; Larko, D.

2014-12-01

During the 1991 Persian Gulf War, over 700 oil wells in Kuwait were set ablaze by the withdrawing Iraqi army with the apparent intent of hindering satellite reconnaissance and intelligence gathering activities by the coalition of forces repelling Iraq from occupied Kuwait. The oil fires that burned for an estimated 10 months, created a huge smoke plume whose spatial extent went at times beyond the Persian Gulf region, mobilized across the Saharan Desert reaching as far west as the North Atlantic Ocean. The Nimbus-7 TOMS Total Ozone Mapping Spectrometer, in operation from October 1978 to May 1993, measured the near UV radiances that in the mid-1990's became the input in the calculation of the well know Absorbing Aerosol Index that represented a major breakthrough in satellite-based aerosol remote sensing. Thus, unknowingly to the world, the N7-TOMS sensor was collecting in 1991 an unprecedented daily record of what can be considered the worst environmental catastrophe affecting the atmosphere since the beginning of the era of space-based remote sensing in the 1970's. An overview of the temporal and spatial extent of the synoptic scale 1991 Gulf War smoke plume as seen by the Nimbus-7 TOMS Absorbing Aerosol Index will be presented.

Biologically inspired collision avoidance system for unmanned vehicles

NASA Astrophysics Data System (ADS)

Ortiz, Fernando E.; Graham, Brett; Spagnoli, Kyle; Kelmelis, Eric J.

2009-05-01

In this project, we collaborate with researchers in the neuroscience department at the University of Delaware to develop an Field Programmable Gate Array (FPGA)-based embedded computer, inspired by the brains of small vertebrates (fish). The mechanisms of object detection and avoidance in fish have been extensively studied by our Delaware collaborators. The midbrain optic tectum is a biological multimodal navigation controller capable of processing input from all senses that convey spatial information, including vision, audition, touch, and lateral-line (water current sensing in fish). Unfortunately, computational complexity makes these models too slow for use in real-time applications. These simulations are run offline on state-of-the-art desktop computers, presenting a gap between the application and the target platform: a low-power embedded device. EM Photonics has expertise in developing of high-performance computers based on commodity platforms such as graphic cards (GPUs) and FPGAs. FPGAs offer (1) high computational power, low power consumption and small footprint (in line with typical autonomous vehicle constraints), and (2) the ability to implement massively-parallel computational architectures, which can be leveraged to closely emulate biological systems. Combining UD's brain modeling algorithms and the power of FPGAs, this computer enables autonomous navigation in complex environments, and further types of onboard neural processing in future applications.

Risk evaluation of available phosphorus loss in agricultural land based on remote sensing and GIS

NASA Astrophysics Data System (ADS)

Ding, Xiaodong; Zhou, Bin; Xu, Junfeng; Liu, Ting; Xie, Bin

2010-09-01

The surplus of phosphorus leads to water eutrophication. Huge input of fertilizers in agricultural activities enriches nutrition in soil. The superfluous nutrient moves easily to riparian water by rainfall and surface runoff; leads to water eutrophication of riparian wetlands and downstream water; and consequently affects ecological balance. Thus it is significant to investigate the risk of phosphorus loss in agricultural land, to identify high concentration areas and guide the management of nutrition loss. This study was implemented mainly in the area of agricultural use in southern Western Australia, where a three-year period preliminary monitoring of water quality showed that the concentration of different forms of phosphorus in water had far exceeded the standard. Due to the large scale surface runoff caused by occasional storms in Western Australia, soil erosion was selected as the main driving factor for the loss of phosphorus. Remote sensing and ground truth data were used to reflect the seasonal changes of plants. The spatial distribution of available phosphorus was then predicted and combined with the evaluation matrix to evaluate the loss risk of phosphorus. This evaluation was based on quantitative rather than qualitative data to make better precision. It could help making decision support for monitoring water quality of rivers and riparian wetlands.

Grid-cell-based crop water accounting for the famine early warning system

NASA Astrophysics Data System (ADS)

Verdin, James; Klaver, Robert

2002-06-01

Rainfall monitoring is a regular activity of food security analysts for sub-Saharan Africa due to the potentially disastrous impact of drought. Crop water accounting schemes are used to track rainfall timing and amounts relative to phenological requirements, to infer water limitation impacts on yield. Unfortunately, many rain gauge reports are available only after significant delays, and the gauge locations leave large gaps in coverage. As an alternative, a grid-cell-based formulation for the water requirement satisfaction index (WRSI) was tested for maize in Southern Africa. Grids of input variables were obtained from remote sensing estimates of rainfall, meteorological models, and digital soil maps. The spatial WRSI was computed for the 1996-97 and 1997-98 growing seasons. Maize yields were estimated by regression and compared with a limited number of reports from the field for the 1996-97 season in Zimbabwe. Agreement at a useful level (r = 0·80) was observed. This is comparable to results from traditional analysis with station data. The findings demonstrate the complementary role that remote sensing, modelling, and geospatial analysis can play in an era when field data collection in sub-Saharan Africa is suffering an unfortunate decline. Published in 2002 by John Wiley & Sons, Ltd.