Compressive sensing method for recognizing cat-eye effect targets.

PubMed

Li, Li; Li, Hui; Dang, Ersheng; Liu, Bo

2013-10-01

This paper proposes a cat-eye effect target recognition method with compressive sensing (CS) and presents a recognition method (sample processing before reconstruction based on compressed sensing, or SPCS) for image processing. In this method, the linear projections of original image sequences are applied to remove dynamic background distractions and extract cat-eye effect targets. Furthermore, the corresponding imaging mechanism for acquiring active and passive image sequences is put forward. This method uses fewer images to recognize cat-eye effect targets, reduces data storage, and translates the traditional target identification, based on original image processing, into measurement vectors processing. The experimental results show that the SPCS method is feasible and superior to the shape-frequency dual criteria method.

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.

Fast Dynamic 3D MRSI with Compressed Sensing and Multiband Excitation Pulses for Hyperpolarized 13C Studies

PubMed Central

Larson, Peder E. Z.; Hu, Simon; Lustig, Michael; Kerr, Adam B.; Nelson, Sarah J.; Kurhanewicz, John; Pauly, John M.; Vigneron, Daniel B.

2010-01-01

Hyperpolarized 13C MRSI can detect not only the uptake of the pre-polarized molecule but also its metabolic products in vivo, thus providing a powerful new method to study cellular metabolism. Imaging the dynamic perfusion and conversion of these metabolites provides additional tissue information but requires methods for efficient hyperpolarization usage and rapid acquisitions. In this work, we have developed a time-resolved 3D MRSI method for acquiring hyperpolarized 13C data by combining compressed sensing methods for acceleration and multiband excitation pulses to efficiently use the magnetization. This method achieved a 2 sec temporal resolution with full volumetric coverage of a mouse, and metabolites were observed for up to 60 sec following injection of hyperpolarized [1-13C]-pyruvate. The compressed sensing acquisition used random phase encode gradient blips to create a novel random undersampling pattern tailored to dynamic MRSI with sampling incoherency in four (time, frequency and two spatial) dimensions. The reconstruction was also tailored to dynamic MRSI by applying a temporal wavelet sparsifying transform in order to exploit the inherent temporal sparsity. Customized multiband excitation pulses were designed with a lower flip angle for the [1-13C]-pyruvate substrate given its higher concentration than its metabolic products ([1-13C]-lactate and [1-13C]-alanine), thus using less hyperpolarization per excitation. This approach has enabled the monitoring of perfusion and uptake of the pyruvate, and the conversion dynamics to lactate and alanine throughout a volume with high spatial and temporal resolution. PMID:20939089

Ferroelectric Zinc Oxide Nanowire Embedded Flexible Sensor for Motion and Temperature Sensing.

PubMed

Shin, Sung-Ho; Park, Dae Hoon; Jung, Joo-Yun; Lee, Min Hyung; Nah, Junghyo

2017-03-22

We report a simple method to realize multifunctional flexible motion sensor using ferroelectric lithium-doped ZnO-PDMS. The ferroelectric layer enables piezoelectric dynamic sensing and provides additional motion information to more precisely discriminate different motions. The PEDOT:PSS-functionalized AgNWs, working as electrode layers for the piezoelectric sensing layer, resistively detect a change of both movement or temperature. Thus, through the optimal integration of both elements, the sensing limit, accuracy, and functionality can be further expanded. The method introduced here is a simple and effective route to realize a high-performance flexible motion sensor with integrated multifunctionalities.

Inertial mass sensing with low Q-factor vibrating microcantilevers

NASA Astrophysics Data System (ADS)

Adhikari, S.

2017-10-01

Mass sensing using micromechanical cantilever oscillators has been established as a promising approach. The scientific principle underpinning this technique is the shift in the resonance frequency caused by the additional mass in the dynamic system. This approach relies on the fact that the Q-factor of the underlying oscillator is high enough so that it does not significantly affect the resonance frequencies. We consider the case when the Q-factor is low to the extent that the effect of damping is prominent. It is shown that the mass sensing can be achieved using a shift in the damping factor. We prove that the shift in the damping factor is of the same order as that of the resonance frequency. Based on this crucial observation, three new approaches have been proposed, namely, (a) mass sensing using frequency shifts in the complex plane, (b) mass sensing from damped free vibration response in the time domain, and (c) mass sensing from the steady-state response in the frequency domain. Explicit closed-form expressions relating absorbed mass with changes in the measured dynamic properties have been derived. The rationale behind each new method has been explained using non-dimensional graphical illustrations. The new mass sensing approaches using damped dynamic characteristics can expand the current horizon of micromechanical sensing by incorporating a wide range of additional measurements.

Self-Evaluation of PANDA-FBG Based Sensing System for Dynamic Distributed Strain and Temperature Measurement.

PubMed

Zhu, Mengshi; Murayama, Hideaki; Wada, Daichi

2017-10-12

A novel method is introduced in this work for effectively evaluating the performance of the PANDA type polarization-maintaining fiber Bragg grating (PANDA-FBG) distributed dynamic strain and temperature sensing system. Conventionally, the errors during the measurement are unknown or evaluated by using other sensors such as strain gauge and thermocouples. This will make the sensing system complicated and decrease the efficiency since more than one kind of sensor is applied for the same measurand. In this study, we used the approximately constant ratio of primary errors in strain and temperature measurement and realized the self-evaluation of the sensing system, which can significantly enhance the applicability, as well as the reliability in strategy making.

Proposal and Implementation of a Robust Sensing Method for DVB-T Signal

NASA Astrophysics Data System (ADS)

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

This paper proposes a sensing method for TV signals of DVB-T standard to realize effective TV White Space (TVWS) Communication. In the TVWS technology trial organized by the Infocomm Development Authority (iDA) of Singapore, with regard to the sensing level and sensing time, detecting DVB-T signal at the level of -120dBm over an 8MHz channel with a sensing time below 1 second is required. To fulfill such a strict sensing requirement, we propose a smart sensing method which combines feature detection and energy detection (CFED), and is also characterized by using dynamic threshold selection (DTS) based on a threshold table to improve sensing robustness to noise uncertainty. The DTS based CFED (DTS-CFED) is evaluated by computer simulations and is also implemented into a hardware sensing prototype. The results show that the DTS-CFED achieves a detection probability above 0.9 for a target false alarm probability of 0.1 for DVB-T signals at the level of -120dBm over an 8MHz channel with the sensing time equals to 0.1 second.

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.

Condition assessment of reinforced concrete beams using dynamic data measured with distributed long-gage macro-strain sensors

NASA Astrophysics Data System (ADS)

Hong, W.; Wu, Z. S.; Yang, C. Q.; Wan, C. F.; Wu, G.; Zhang, Y. F.

2012-06-01

A new condition assessment strategy of reinforced concrete (RC) beams is proposed in this paper. This strategy is based on frequency analysis of the dynamic data measured with distributed long-gage macro-stain sensors. After extracting modal macro-strain, the reference-based damage index is theoretically deducted in which the variations of modal flexural rigidity and modal neutral axis height are considered. The reference-free damage index is also presented for comparison. Both finite element simulation and experiment investigations were carried out to verify the proposed method. The manufacturing procedure of long-gage fiber Bragg grating (FBG) sensor chosen in the experiment is firstly presented, followed by an experimental study on the essential sensing properties of the long-gage macro-strain sensors and the results verify the excellent sensing properties, in particular the measurement accuracy and dynamic measuring capacity. Modal analysis results of a concrete beam show that the damage appearing in the beam can be well identified by the damage index while the vibration testing results of a RC beam show that the proposed method can not only capture small crack initiation but its propagation. It can be concluded that distributed long-gage dynamic macro-strain sensing technique has great potential for the condition assessment of RC structures subjected to dynamic loading.

In vivo THz sensing of the cornea of the eye

NASA Astrophysics Data System (ADS)

Ozheredov, Ilya; Prokopchuk, Mikhail; Mischenko, Mikhail; Safonova, Tatiana; Solyankin, Petr; Larichev, Andrey; Angeluts, Andrey; Balakin, Alexei; Shkurinov, Alexander

2018-05-01

Measurement of the absolute value of the humidity of the cornea of the human eye and its dynamics is of paramount importance for the preservation of eyesight. In the present paper we have demonstrated that terahertz technologies can be practically applied for quantitative measurement of the physiological dynamics of tear film and sensing of corneal tissue hydration. We suggest uses of the equipment for application in clinics and a method for absolute calibration of the values for measurement. The proposed method is fundamentally different from existing and currently available methods of ophthalmological diagnosis. This suggests that the developed technique may have high diagnostic significance and can be used in the study and treatment of several diseases of the ocular surface.

Multidimensional Compressed Sensing MRI Using Tensor Decomposition-Based Sparsifying Transform

PubMed Central

Yu, Yeyang; Jin, Jin; Liu, Feng; Crozier, Stuart

2014-01-01

Compressed Sensing (CS) has been applied in dynamic Magnetic Resonance Imaging (MRI) to accelerate the data acquisition without noticeably degrading the spatial-temporal resolution. A suitable sparsity basis is one of the key components to successful CS applications. Conventionally, a multidimensional dataset in dynamic MRI is treated as a series of two-dimensional matrices, and then various matrix/vector transforms are used to explore the image sparsity. Traditional methods typically sparsify the spatial and temporal information independently. In this work, we propose a novel concept of tensor sparsity for the application of CS in dynamic MRI, and present the Higher-order Singular Value Decomposition (HOSVD) as a practical example. Applications presented in the three- and four-dimensional MRI data demonstrate that HOSVD simultaneously exploited the correlations within spatial and temporal dimensions. Validations based on cardiac datasets indicate that the proposed method achieved comparable reconstruction accuracy with the low-rank matrix recovery methods and, outperformed the conventional sparse recovery methods. PMID:24901331

3D undersampled golden-radial phase encoding for DCE-MRA using inherently regularized iterative SENSE.

PubMed

Prieto, Claudia; Uribe, Sergio; Razavi, Reza; Atkinson, David; Schaeffter, Tobias

2010-08-01

One of the current limitations of dynamic contrast-enhanced MR angiography is the requirement of both high spatial and high temporal resolution. Several undersampling techniques have been proposed to overcome this problem. However, in most of these methods the tradeoff between spatial and temporal resolution is constant for all the time frames and needs to be specified prior to data collection. This is not optimal for dynamic contrast-enhanced MR angiography where the dynamics of the process are difficult to predict and the image quality requirements are changing during the bolus passage. Here, we propose a new highly undersampled approach that allows the retrospective adaptation of the spatial and temporal resolution. The method combines a three-dimensional radial phase encoding trajectory with the golden angle profile order and non-Cartesian Sensitivity Encoding (SENSE) reconstruction. Different regularization images, obtained from the same acquired data, are used to stabilize the non-Cartesian SENSE reconstruction for the different phases of the bolus passage. The feasibility of the proposed method was demonstrated on a numerical phantom and in three-dimensional intracranial dynamic contrast-enhanced MR angiography of healthy volunteers. The acquired data were reconstructed retrospectively with temporal resolutions from 1.2 sec to 8.1 sec, providing a good depiction of small vessels, as well as distinction of different temporal phases.

[Application of hyperspectral remote sensing in research on ecological boundary in north farming-pasturing transition in China].

PubMed

Wang, Hong-Mei; Wang, Kun; Xie, Ying-Zhong

2009-06-01

Studies of ecological boundaries are important and have become a rapidly evolving part of contemporary ecology. The ecotones are dynamic and play several functional roles in ecosystem dynamics, and the changes in their locations can be used as an indicator of environment changes, and for these reasons, ecotones have recently become a focus of investigation of landscape ecology and global climate change. As the interest in ecotone increases, there is an increased need for formal techniques to detect it. Hence, to better study and understand the functional roles and dynamics of ecotones in ecosystem, we need quantitative methods to characterize them. In the semi-arid region of northern China, there exists a farming-pasturing transition resulting from grassland reclamation and deforestation. With the fragmentation of grassland landscape, the structure and function of the grassland ecosystem are changing. Given this perspective; new-image processing approaches are needed to focus on transition themselves. Hyperspectral remote sensing data, compared with wide-band remote sensing data, has the advantage of high spectral resolution. Hyperspectral remote sensing can be used to visualize transitional zones and to detect ecotone based on surface properties (e. g. vegetation, soil type, and soil moisture etc). In this paper, the methods of hyperspectral remote sensing information processing, spectral analysis and its application in detecting the vegetation classifications, vegetation growth state, estimating the canopy biochemical characteristics, soil moisture, soil organic matter etc are reviewed in detail. Finally the paper involves further application of hyperspectral remote sensing information in research on local climate in ecological boundary in north farming-pasturing transition in China.

Remote sensing of forest insect disturbances: Current state and future directions

NASA Astrophysics Data System (ADS)

Senf, Cornelius; Seidl, Rupert; Hostert, Patrick

2017-08-01

Insect disturbance are important agents of change in forest ecosystems around the globe, yet their spatial and temporal distribution and dynamics are not well understood. Remote sensing has gained much attention in mapping and understanding insect outbreak dynamics. Consequently, we here review the current literature on the remote sensing of insect disturbances. We suggest to group studies into three insect types: bark beetles, broadleaved defoliators, and coniferous defoliators. By so doing, we systematically compare the sensors and methods used for mapping insect disturbances within and across insect types. Results suggest that there are substantial differences between methods used for mapping bark beetles and defoliators, and between methods used for mapping broadleaved and coniferous defoliators. Following from this, we highlight approaches that are particularly suited for each insect type. Finally, we conclude by highlighting future research directions for remote sensing of insect disturbances. In particular, we suggest to: 1) Separate insect disturbances from other agents; 2) Extend the spatial and temporal domain of analysis; 3) Make use of dense time series; 4) Operationalize near-real time monitoring of insect disturbances; 5) Identify insect disturbances in the context of coupled human-natural systems; and 6) Improve reference data for assessing insect disturbances. Since the remote sensing of insect disturbances has gained much interest beyond the remote sensing community recently, the future developments identified here will help integrating remote sensing products into operational forest management. Furthermore, an improved spatiotemporal quantification of insect disturbances will support an inclusion of these processes into regional to global ecosystem models.

Remote sensing of forest insect disturbances: Current state and future directions.

PubMed

Senf, Cornelius; Seidl, Rupert; Hostert, Patrick

2017-08-01

Insect disturbance are important agents of change in forest ecosystems around the globe, yet their spatial and temporal distribution and dynamics are not well understood. Remote sensing has gained much attention in mapping and understanding insect outbreak dynamics. Consequently, we here review the current literature on the remote sensing of insect disturbances. We suggest to group studies into three insect types: bark beetles, broadleaved defoliators, and coniferous defoliators. By so doing, we systematically compare the sensors and methods used for mapping insect disturbances within and across insect types. Results suggest that there are substantial differences between methods used for mapping bark beetles and defoliators, and between methods used for mapping broadleaved and coniferous defoliators. Following from this, we highlight approaches that are particularly suited for each insect type. Finally, we conclude by highlighting future research directions for remote sensing of insect disturbances. In particular, we suggest to: 1) Separate insect disturbances from other agents; 2) Extend the spatial and temporal domain of analysis; 3) Make use of dense time series; 4) Operationalize near-real time monitoring of insect disturbances; 5) Identify insect disturbances in the context of coupled human-natural systems; and 6) Improve reference data for assessing insect disturbances. Since the remote sensing of insect disturbances has gained much interest beyond the remote sensing community recently, the future developments identified here will help integrating remote sensing products into operational forest management. Furthermore, an improved spatiotemporal quantification of insect disturbances will support an inclusion of these processes into regional to global ecosystem models.

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.

Effects of ankle strengthening exercise program on an unstable supporting surface on proprioception and balance in adults with functional ankle instability.

PubMed

Ha, Sun-Young; Han, Jun-Ho; Sung, Yun-Hee

2018-04-01

The present study was conducted to investigate the effect of ankle strengthening exercise applied on unstable supporting surfaces on the proprioceptive sense and balance in adults with functional ankle instability. As for the study method, 30 adults with functional ankle instability were randomly assigned to an ankle strengthening exercise group and a stretching group on unstable supporting surfaces, and the interventions were implemented for 40 min. Before and after the interventions, a digital dual inclinometer was used to measure the proprioceptive sense of the ankle, the Balancia program was used to measure static balance ability, and the functional reach test was used to measure dynamic balance ability. In the results, both proprioceptive sense and static dynamic balance ability were significantly different between before and after the intervention in the experimental group ( P <0.05). When such results are put together, it can be seen that ankle strengthening exercise applied on unstable supporting surfaces may be presented as an effective treatment method for enhancing the proprioceptive sense and balance ability in adults with functional ankle instability.

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.

Study on environment detection and appraisement of mining area with RS

NASA Astrophysics Data System (ADS)

Yang, Fengjie; Hou, Peng; Zhou, Guangzhu; Li, Qingting; Wang, Jie; Cheng, Jianguang

2006-12-01

In this paper, the big coal mining area Yanzhou is selected as the typical research area. According to the special dynamic change characteristic of the environment in the mining area, the environmental dynamic changes are timely monitored with the remote sensing detection technology. Environmental special factors, such as vegetation, water, air, land-over, are extracted by the professional remote sensing image processing software, then the spatial information is managed and analyzed in the geographical information system (GIS) software. As the result, the dynamic monitor and query for change information is achieved, and the special environmental factor dynamic change maps are protracted. On the base of the data coming from the remote sensing image, GIS and the traditional environment monitoring, the environmental quality is appraised with the method of indistinct matrix analysis, the multi-index and the analytical hierarchy process. At last, those provide the credible science foundation for the local environment appraised and the sustained development. In addition, this paper apply the hyper spectrum graphs by the FieldSpec Pro spectroradiometer, together with the analytical data from environmental chemical, to study the growth of vegetation which were seed in the land-over consisting of gangue, which is a new method to study the impact to vegetation that are growing in the soil.

Utilizing multisource remotely sensed data to dynamically monitor drought in China

NASA Astrophysics Data System (ADS)

Liu, Sanchao; Li, Wenbo

2011-12-01

Drought is one of major nature disaster in the world and China. China has a vast territory and very different spatio-temporal distribution weather condition. Therefore, drought disasters occur frequently throughout China, which may affect large areas and cause great economic loss every year. In this paper, geostationary meteorological remote sensing data, FY-2C/D/E VISSR and three quantitative remotely sensed models including Cloud Parameters Method (CPM), Vegetation Supply Water Index (VSWI), and Temperature Vegetation Dryness Index (TVDI) have been used to dynamically monitor severe drought in southwest China from 2009 to 2010. The results have effectively revealed the occurrence, development and disappearance of this drought event. The monitoring results can be used for the relevant disaster management departments' decision-making works.

Remote sensing monitoring and driving force analysis to forest and greenbelt in Zhuhai

NASA Astrophysics Data System (ADS)

Yuliang Qiao, Pro.

As an important city in the southern part of Chu Chiang Delta, Zhuhai is one of the four special economic zones which are opening up to the outside at the earliest in China. With pure and fresh air and trees shading the street, Zhuhai is a famous beach port city which is near the mountain and by the sea. On the basis of Garden City, the government of Zhuhai decides to build National Forest City in 2011, which firstly should understand the situation of greenbelt in Zhuhai in short term. Traditional methods of greenbelt investigation adopt the combination of field surveying and statistics, whose efficiency is low and results are not much objective because of artificial influence. With the adventure of the information technology such as remote sensing to earth observation, especially the launch of many remote sensing satellites with high resolution for the past few years, kinds of urban greenbelt information extraction can be carried out by using remote sensing technology; and dynamic monitoring to spatial pattern evolvement of forest and greenbelt in Zhuhai can be achieved by the combination of remote sensing and GIS technology. Taking Landsat5 TM data in 1995, Landsat7 ETM+ data in 2002, CCD and HR data of CBERS-02B in 2009 as main information source, this research firstly makes remote sensing monitoring to dynamic change of forest and greenbelt in Zhuhai by using the combination of vegetation coverage index and three different information extraction methods, then does a driving force analysis to the dynamic change results in 3 months. The results show: the forest area in Zhuhai shows decreasing tendency from 1995 to 2002, increasing tendency from 2002 to 2009; overall, the forest area show a small diminution tendency from 1995 to 2009. Through the comparison to natural and artificial driving force, the artificial driving force is the leading factor to the change of forest and greenbelt in Zhuhai. The research results provide a timely and reliable scientific basis for the Zhuhai Government in building National Forest City. Keywords: forest and greenbelt; remote sensing; dynamic monitoring; driving force; vegetation coverage

The research of differential reference electrode arrayed flexible IGZO glucose biosensor based on microfluidic framework

NASA Astrophysics Data System (ADS)

Chen, Jian-Syun; Chou, Jung-Chuan; Liao, Yi-Hung; Chen, Ruei-Ting; Huang, Min-Siang; Wu, Tong-Yu

2017-03-01

This study used a fast, simple, and low-cost method to fabricate arrayed flexible glucose biosensor, and the glucose biosensor was integrated with microfluidic framework for investigating sensing characteristics of glucose biosensor at the dynamic conditions. The indium gallium zinc oxide (IGZO) was adopted as sensing membrane and it was deposited on aluminum electrodes / polyethylene terephthalate (PET) substrate by the radio frequency sputtering system. Then, we utilized screen-printed technology to accomplish miniaturization of glucose biosensor. Finally, the glucose sensing membrane was composed of glucose oxidase (GOx) and nafion, which was dropped on IGZO sensing membrane to complete glucose biosensor. According to the experimental results, we found that optimal sensing characteristics of arrayed flexible IGZO glucose biosensor at the dynamic conditions were better than at the static conditions. The optimal average sensitivity and linearity of the arrayed flexible IGZO glucose biosensor were 7.255 mV/mM and 0.994 at 20 µL/min flow rate, respectively.

Observing and modeling dynamics in terrestrial gross primary productivity and phenology from remote sensing: An assessment using in-situ measurements

NASA Astrophysics Data System (ADS)

Verma, Manish K.

Terrestrial gross primary productivity (GPP) is the largest and most variable component of the carbon cycle and is strongly influenced by phenology. Realistic characterization of spatio-temporal variation in GPP and phenology is therefore crucial for understanding dynamics in the global carbon cycle. In the last two decades, remote sensing has become a widely-used tool for this purpose. However, no study has comprehensively examined how well remote sensing models capture spatiotemporal patterns in GPP, and validation of remote sensing-based phenology models is limited. Using in-situ data from 144 eddy covariance towers located in all major biomes, I assessed the ability of 10 remote sensing-based methods to capture spatio-temporal variation in GPP at annual and seasonal scales. The models are based on different hypotheses regarding ecophysiological controls on GPP and span a range of structural and computational complexity. The results lead to four main conclusions: (i) at annual time scale, models were more successful capturing spatial variability than temporal variability; (ii) at seasonal scale, models were more successful in capturing average seasonal variability than interannual variability; (iii) simpler models performed as well or better than complex models; and (iv) models that were best at explaining seasonal variability in GPP were different from those that were best able to explain variability in annual scale GPP. Seasonal phenology of vegetation follows bounded growth and decay, and is widely modeled using growth functions. However, the specific form of the growth function affects how phenological dynamics are represented in ecosystem and remote sensing-base models. To examine this, four different growth functions (the logistic, Gompertz, Mirror-Gompertz and Richards function) were assessed using remotely sensed and in-situ data collected at several deciduous forest sites. All of the growth functions provided good statistical representation of in-situ and remote sensing time series. However, the Richards function captured observed asymmetric dynamics that were not captured by the other functions. The timing of key phenophase transitions derived using the Richards function therefore agreed best with observations. This suggests that ecosystem models and remote-sensing algorithms would benefit from using the Richards function to represent phenological dynamics.

Carbon nanotube film interlayer for strain and damage sensing in composites during dynamic compressive loading

NASA Astrophysics Data System (ADS)

Wu, A. S.; Na, W.-J.; Yu, W.-R.; Byun, J.-H.; Chou, T.-W.

2012-11-01

A major challenge in the damage assessment of materials under dynamic, high strain rate loading lies in the inability to apply most health monitoring methodologies to the analysis and evaluation of damage incurred on short timescales. Here, we present a resistance-based sensing method utilizing an electrically conductive carbon nanotube film in a fiberglass/vinyl ester composite. This method reveals that applied strain and damage in the form of matrix cracking and delamination give rise to electrical resistance increases across the composite specimen; these can be measured in real-time during high strain rate loading. Damage within the composite specimens is confirmed through pre- and post-mortem x-ray micro computed tomography imaging.

Sensing dynamic cytoplasm refractive index changes of adherent cells with quantitative phase microscopy using incorporated microspheres as optical probes.

PubMed

Przibilla, Sabine; Dartmann, Sebastian; Vollmer, Angelika; Ketelhut, Steffi; Greve, Burkhard; von Bally, Gert; Kemper, Björn

2012-09-01

The intracellular refractive index is an important parameter that describes the optical density of the cytoplasm and the concentration of the intracellular solutes. The refractive index of adherently grown cells is difficult to access. We present a method in which silica microspheres in living cells are used to determine the cytoplasm refractive index with quantitative phase microscopy. The reliability of our approach for refractive index retrieval is shown by data from a comparative study on osmotically stimulated adherent and suspended human pancreatic tumor cells. Results from adherent human fibro sarcoma cells demonstrate the capability of the method for sensing of dynamic refractive index changes and its usage with microfluidics.

Method and apparatus for monitoring dynamic cardiovascular function using n-dimensional representatives of critical functions

NASA Technical Reports Server (NTRS)

Syroid, Noah (Inventor); Westinskow, Dwayne (Inventor); Agutter, James (Inventor); Albert, Robert (Inventor); Strayer, David (Inventor); Wachter, S. Blake (Inventor); Drews, Frank (Inventor)

2010-01-01

A method, system, apparatus and device for the monitoring, diagnosis and evaluation of the state of a dynamic pulmonary system is disclosed. This method and system provides the processing means for receiving sensed and/or simulated data, converting such data into a displayable object format and displaying such objects in a manner such that the interrelationships between the respective variables can be correlated and identified by a user. This invention provides for the rapid cognitive grasp of the overall state of a pulmonary critical function with respect to a dynamic system.

Effect of ankle proprioceptive exercise on static and dynamic balance in normal adults.

PubMed

Yong, Min-Sik; Lee, Yun-Seob

2017-02-01

[Purpose] The present study was conducted to investigate whether ankle proprioceptive exercise affects static and dynamic balance in normal adults. [Subjects and Methods] Twenty-eight normal adults were recruited to measure their static and dynamic balancing before and after the proprioceptive exercise. A subject stood with bare feet on the round supporting platform of the device for measuring balance, and the investigator entered the age and the height of the subjects and set his/her feet on the central point of the monitor screen. Training of ankle proprioceptive sense for the movements of plantar-flexion and dorsiflexion was performed. In the training of joint position sense in plantar-flexion and dorsiflexion, the plantar-flexion and the dorsiflexion were set as 15°, respectively. [Results] The static balancing did not show significant differences in average, while the dynamic balancing showed significant differences. [Conclusion] Ankle proprioceptive exercise can affect dynamic balance.

Interfacing geographic information systems and remote sensing for rural land-use analysis

NASA Technical Reports Server (NTRS)

Nellis, M. Duane; Lulla, Kamlesh; Jensen, John

1990-01-01

Recent advances in computer-based geographic information systems (GISs) are briefly reviewed, with an emphasis on the incorporation of remote-sensing data in GISs for rural applications. Topics addressed include sampling procedures for rural land-use analyses; GIS-based mapping of agricultural land use and productivity; remote sensing of land use and agricultural, forest, rangeland, and water resources; monitoring the dynamics of irrigation agriculture; GIS methods for detecting changes in land use over time; and the development of land-use modeling strategies.

A distributed optical fiber sensing system for dynamic strain measurement based on artificial reflector

NASA Astrophysics Data System (ADS)

Sun, Zhenhong; Shan, Yuanyuan; Li, Yanting; Zhang, Yixin; Zhang, Xuping

2016-10-01

Phase sensitive optical time domain reflectometry (Φ-OTDR) has been widely used in many applications for its distributed sensing ability on weak disturbance all along the sensing fiber. However, traditional Φ-OTDR cannot make quantitative measurement on the external disturbance due to the randomly distributed position and reflectivity of scatters within the optical fiber. Recently, some methods have been proposed to realize quantitative measurement of dynamic strain. In these literatures, the fiber with or without FBGs in practice was easily damaged and with difficulty of maintenance. PZT is employed to generate strain event in the fiber. There is a large gap compared with the real detecting environment, which will not reveal the full performance of the sensing system. In this paper, a distributed optical fiber sensing (DOFS) system for dynamic strain measurement based on artificial reflector is proposed and demonstrated experimentally. The fiber under test (FUT) is composed by four 20-meter long single mode optical fiber patch cords (OFPCs), which are cascaded with ferrule contactor/physical contact (FC/PC) connectors via fiber flanges. The fiber facet of FC/PC connector forms an artificial reflector. When the interval between the two reflectors is changed, the phase of the interference signal will also be changed. A symmetric 3×3 coupler with table-look-up scheme is introduced to discriminate the phase change through interference intensity. In our experiment, the center 10m section of the second OFPC is attached to the bottom of an aluminum alloy plate. An ordinary loudspeaker box was located on the top of the aluminum alloy plate. The dynamic strain generated by the loudspeaker box is transmitted from the aluminum alloy plate to the OFPC. Experimental results show that the proposed method has a good frequency response characteristic up to 3.2 kHz and a linear intensity response of R2=0.9986 while the optical probe pulse width and repetition rate were 100ns and 10 kHz respectively. Meanwhile, triangle and cosine amplitude-modulated (AM) dynamic strain applied on the fiber are successfully discriminated. The artificial reflectors based on FC/PCs were easily assembled and maintained, and the method of vibration transmission closely resembled the real circumstance than PZT. Therefore, these advantages will extend the potential of this Φ-OTDR technology in structure health monitoring.

Lattice Anharmonicity and Thermal Conductivity from Compressive Sensing of First-Principles Calculations

DOE PAGES

Zhou, Fei; Nielson, Weston; Xia, Yi; ...

2014-10-27

First-principles prediction of lattice thermal conductivity K L of strongly anharmonic crystals is a long-standing challenge in solid state physics. Using recent advances in information science, we propose a systematic and rigorous approach to this problem, compressive sensing lattice dynamics (CSLD). Compressive sensing is used to select the physically important terms in the lattice dynamics model and determine their values in one shot. Non-intuitively, high accuracy is achieved when the model is trained on first-principles forces in quasi-random atomic configurations. The method is demonstrated for Si, NaCl, and Cu 12Sb 4S 13, an earth-abundant thermoelectric with strong phononphonon interactions thatmore » limit the room-temperature K L to values near the amorphous limit.« less

Sensing mode coupling analysis for dual-mass MEMS gyroscope and bandwidth expansion within wide-temperature range

NASA Astrophysics Data System (ADS)

Cao, Huiliang; Li, Hongsheng; Shao, Xingling; Liu, Zhiyu; Kou, Zhiwei; Shan, Yanhu; Shi, Yunbo; Shen, Chong; Liu, Jun

2018-01-01

This paper presents the bandwidth expanding method with wide-temperature range for sense mode coupling dual-mass MEMS gyro. The real sensing mode of the gyroscope is analyzed to be the superposition of in-phase and anti-phase sensing modes. The mechanical sensitivity and bandwidth of the gyroscope structure are conflicted with each other and both governed by the frequency difference between sensing and drive modes (min {Δω1, Δω2}). The sensing mode force rebalancing combs stimulation method (FRCSM) is presented to simulate the Coriolis force, and based on this method, the gyro's dynamic characteristics are tested. The sensing closed- loop controller is achieved by operational amplifier based on phase lead method, which enable the magnitude margin and phase margin of the system to reach 7.21 dB and 34.6° respectively, and the closed-loop system also expands gyro bandwidth from 13 Hz (sensing open-loop) to 102 Hz (sensing closed-loop). What's more, the turntable test results show that the sensing closed-loop works stably in wide-temperature range (from -40 °C to 60 °C) and the bandwidth values are 107 Hz @-40 °C and 97 Hz @60 °C. The results indicate that the higher temperature causes lower bandwidth, and verify the simulation results are 103 Hz @-40 °C and 98.2 Hz @60 °C. The new bottleneck of the closed loop bandwidth is the valley generated by conjugate zeros, which is formed by superposition of sensing modes.

Optofluidic laser for dual-mode sensitive biomolecular detection with a large dynamic range

NASA Astrophysics Data System (ADS)

Wu, Xiang; Oo, Maung Kyaw Khaing; Reddy, Karthik; Chen, Qiushu; Sun, Yuze; Fan, Xudong

2014-04-01

Enzyme-linked immunosorbent assay (ELISA) is a powerful method for biomolecular analysis. The traditional ELISA employing light intensity as the sensing signal often encounters large background arising from non-specific bindings, material autofluorescence and leakage of excitation light, which deteriorates its detection limit and dynamic range. Here we develop the optofluidic laser-based ELISA, where ELISA occurs inside a laser cavity. The laser onset time is used as the sensing signal, which is inversely proportional to the enzyme concentration and hence the analyte concentration inside the cavity. We first elucidate the principle of the optofluidic laser-based ELISA, and then characterize the optofluidic laser performance. Finally, we present the dual-mode detection of interleukin-6 using commercial ELISA kits, where the sensing signals are simultaneously obtained by the traditional and the optofluidic laser-based ELISA, showing a detection limit of 1 fg ml-1 (38 aM) and a dynamic range of 6 orders of magnitude.

Comprehensive studies of the dynamics of geosystems with the use of remote sensing techniques

NASA Astrophysics Data System (ADS)

Vasilev, L. N.; Kaczyński, R.; Ney, B. I.

The described research programme for comprehensive studies of changes occuring within geosystems is a part of scientific activity of INTERKOSMOS, which will be executed mainly with the use of remote sensing methods and techniques. The main aim of the programme is to get an insight into the seasonal rithm of environmental changes on both regional and global level. The work will consist of gathering systematized information concerning quantitative and qualitative relations between various components of the environment. The application of remote sensing methods enables the acquisition of such environmental data in dynamic setting. Research will be conducted for areas comprising distinct geosystems and will lead to the detection of diurnal, seasonal and yearly dynamics of geosystems as well as long-term trends. Except cognitive, the programme will also serve the methodological purpose. The first aim will be realized with respect to individual geosystems; the resulting sets of data will consist of matrixes of statistical data characterizing relations between various components of geosystems. The methodological aim will be achieved through the process of practical verification of the preliminary assumptions. Information will be collected from different data acquisition levels namely from satellite and aerial platforms and through ground measurements. Different types of data, such as multispectral photography (SALYUT, KOSMOS), multispectral scanner images (LANDSAT THEMATIC MAPPER, SPOT), infrared photography, radar imagery and spectrometric measurements will be gathered during simultaneous data acquisition projects. All types of observations will be timed in accordance with the natural rithm of the observed phenomena. The paper contains the description of geosystems under anthropogenic stress based on the previous research of the authors. The presented multifactor characteristics of soil and crops is a part of completed studies on agricultural geosystems. The results of comprehensive remote sensing experiments already completed within the framework of INTERKOSMOS programme on test sites in member countries fully support the approved programme for studying the dynamics of geosystems with the use of remote sensing.

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

PubMed

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

2018-01-01

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

Highly Sensitive and Wide-Dynamic-Range Multichannel Optical-Fiber pH Sensor Based on PWM Technique.

PubMed

Khan, Md Rajibur Rahaman; Kang, Shin-Won

2016-11-09

In this study, we propose a highly sensitive multichannel pH sensor that is based on an optical-fiber pulse width modulation (PWM) technique. According to the optical-fiber PWM method, the received sensing signal's pulse width changes when the optical-fiber pH sensing-element of the array comes into contact with pH buffer solutions. The proposed optical-fiber PWM pH-sensing system offers a linear sensing response over a wide range of pH values from 2 to 12, with a high pH-sensing ability. The sensitivity of the proposed pH sensor is 0.46 µs/pH, and the correlation coefficient R² is approximately 0.997. Additional advantages of the proposed optical-fiber PWM pH sensor include a short/fast response-time of about 8 s, good reproducibility properties with a relative standard deviation (RSD) of about 0.019, easy fabrication, low cost, small size, reusability of the optical-fiber sensing-element, and the capability of remote sensing. Finally, the performance of the proposed PWM pH sensor was compared with that of potentiometric, optical-fiber modal interferometer, and optical-fiber Fabry-Perot interferometer pH sensors with respect to dynamic range width, linearity as well as response and recovery times. We observed that the proposed sensing systems have better sensing abilities than the above-mentioned pH sensors.

Highly Sensitive and Wide-Dynamic-Range Multichannel Optical-Fiber pH Sensor Based on PWM Technique

PubMed Central

Khan, Md. Rajibur Rahaman; Kang, Shin-Won

2016-01-01

In this study, we propose a highly sensitive multichannel pH sensor that is based on an optical-fiber pulse width modulation (PWM) technique. According to the optical-fiber PWM method, the received sensing signal’s pulse width changes when the optical-fiber pH sensing-element of the array comes into contact with pH buffer solutions. The proposed optical-fiber PWM pH-sensing system offers a linear sensing response over a wide range of pH values from 2 to 12, with a high pH-sensing ability. The sensitivity of the proposed pH sensor is 0.46 µs/pH, and the correlation coefficient R2 is approximately 0.997. Additional advantages of the proposed optical-fiber PWM pH sensor include a short/fast response-time of about 8 s, good reproducibility properties with a relative standard deviation (RSD) of about 0.019, easy fabrication, low cost, small size, reusability of the optical-fiber sensing-element, and the capability of remote sensing. Finally, the performance of the proposed PWM pH sensor was compared with that of potentiometric, optical-fiber modal interferometer, and optical-fiber Fabry–Perot interferometer pH sensors with respect to dynamic range width, linearity as well as response and recovery times. We observed that the proposed sensing systems have better sensing abilities than the above-mentioned pH sensors. PMID:27834865

A Flexible Spatiotemporal Method for Fusing Satellite Images with Different Resolutions

USDA-ARS?s Scientific Manuscript database

Studies of land surface dynamics in heterogeneous landscapes often require remote sensing data with high acquisition frequency and high spatial resolution. However, no single sensor meets this requirement. This study presents a new spatiotemporal data fusion method, the Flexible Spatiotemporal DAta ...

Blind compressive sensing dynamic MRI

PubMed Central

Lingala, Sajan Goud; Jacob, Mathews

2013-01-01

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

A flexible spatiotemporal method for fusing satellite images with different resolutions

Treesearch

Xiaolin Zhu; Eileen H. Helmer; Feng Gao; Desheng Liu; Jin Chen; Michael A. Lefsky

2016-01-01

Studies of land surface dynamics in heterogeneous landscapes often require remote sensing datawith high acquisition frequency and high spatial resolution. However, no single sensor meets this requirement. This study presents a new spatiotemporal data fusion method, the Flexible Spatiotemporal DAta Fusion (FSDAF) method, to generate synthesized frequent high spatial...

Active and Passive 3D Vector Radiative Transfer with Preferentially-Aligned Ice Particles

NASA Technical Reports Server (NTRS)

Adams, Ian S.; Munchak, Stephen J.; Pelissier, Craig S.; Kuo, Kwo-Sen; Heymsfield, Gerald M.

2017-01-01

For the purposes of interpreting active (radar) and passive (radiometer) microwave and millimeter wave remote sensing data, we have constructed a consistent radiative transfer modeling framework to simulate the responses for arbitrary sensors with differing sensing geometries and hardware configurations. As part of this work, we have implemented a recent method for calculating the electromagnetic properties of individual ice crystals and snow flakes. These calculations will allow us to exploit polarized remote sensing observations to discriminate different particles types and elucidate dynamics of cloud and precipitating systems.

Establishment and analysis of coupled dynamic model for dual-mass silicon micro-gyroscope

NASA Astrophysics Data System (ADS)

Wang, Zhanghui; Qiu, Anping; Shi, Qin; Zhang, Taoyuan

2017-12-01

This paper presents a coupled dynamic model for a dual-mass silicon micro-gyroscope (DMSG). It can quantitatively analyze the influence of left-right stiffness difference on the natural frequencies, modal matrix and modal coupling coefficient of the DMSG. The analytic results are verified by using the finite element method (FEM) simulation. The model shows that with the left-right stiffness difference of 1%, the modal coupling coefficient is 12% in the driving direction and 31% in the sensing direction. It also shows that in order to achieve good separation, the stiffness of base beam should be small enough in both the driving and sensing direction.

Spin dynamics in storage rings and linear accelerators

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

Irwin, J.

1994-12-01

The purpose of these lectures is to survey the subject of spin dynamics in accelerators: to give a sense of the underlying physics, the typical analytic and numeric methods used, and an overview of results achieved. Consideration will be limited to electrons and protons. Examples of experimental and theoretical results in both linear and circular machines are included.

Compressive sensing sectional imaging for single-shot in-line self-interference incoherent holography

NASA Astrophysics Data System (ADS)

Weng, Jiawen; Clark, David C.; Kim, Myung K.

2016-05-01

A numerical reconstruction method based on compressive sensing (CS) for self-interference incoherent digital holography (SIDH) is proposed to achieve sectional imaging by single-shot in-line self-interference incoherent hologram. The sensing operator is built up based on the physical mechanism of SIDH according to CS theory, and a recovery algorithm is employed for image restoration. Numerical simulation and experimental studies employing LEDs as discrete point-sources and resolution targets as extended sources are performed to demonstrate the feasibility and validity of the method. The intensity distribution and the axial resolution along the propagation direction of SIDH by angular spectrum method (ASM) and by CS are discussed. The analysis result shows that compared to ASM the reconstruction by CS can improve the axial resolution of SIDH, and achieve sectional imaging. The proposed method may be useful to 3D analysis of dynamic systems.

The Measurement of Unsteady Surface Pressure Using a Remote Microphone Probe.

PubMed

Guan, Yaoyi; Berntsen, Carl R; Bilka, Michael J; Morris, Scott C

2016-12-03

Microphones are widely applied to measure pressure fluctuations at the walls of solid bodies immersed in turbulent flows. Turbulent motions with various characteristic length scales can result in pressure fluctuations over a wide frequency range. This property of turbulence requires sensing devices to have sufficient sensitivity over a wide range of frequencies. Furthermore, the small characteristic length scales of turbulent structures require small sensing areas and the ability to place the sensors in very close proximity to each other. The complex geometries of the solid bodies, often including large surface curvatures or discontinuities, require the probe to have the ability to be set up in very limited spaces. The development of a remote microphone probe, which is inexpensive, consistent, and repeatable, is described in the present communication. It allows for the measurement of pressure fluctuations with high spatial resolution and dynamic response over a wide range of frequencies. The probe is small enough to be placed within the interior of typical wind tunnel models. The remote microphone probe includes a small, rigid, and hollow tube that penetrates the model surface to form the sensing area. This tube is connected to a standard microphone, at some distance away from the surface, using a "T" junction. An experimental method is introduced to determine the dynamic response of the remote microphone probe. In addition, an analytical method for determining the dynamic response is described. The analytical method can be applied in the design stage to determine the dimensions and properties of the RMP components.

Virtual Passive Controller for Robot Systems Using Joint Torque Sensors

NASA Technical Reports Server (NTRS)

Aldridge, Hal A.; Juang, Jer-Nan

1997-01-01

This paper presents a control method based on virtual passive dynamic control that will stabilize a robot manipulator using joint torque sensors and a simple joint model. The method does not require joint position or velocity feedback for stabilization. The proposed control method is stable in the sense of Lyaponov. The control method was implemented on several joints of a laboratory robot. The controller showed good stability robustness to system parameter error and to the exclusion of nonlinear dynamic effects on the joints. The controller enhanced position tracking performance and, in the absence of position control, dissipated joint energy.

Ultra-Low Power Dynamic Knob in Adaptive Compressed Sensing Towards Biosignal Dynamics.

PubMed

Wang, Aosen; Lin, Feng; Jin, Zhanpeng; Xu, Wenyao

2016-06-01

Compressed sensing (CS) is an emerging sampling paradigm in data acquisition. Its integrated analog-to-information structure can perform simultaneous data sensing and compression with low-complexity hardware. To date, most of the existing CS implementations have a fixed architectural setup, which lacks flexibility and adaptivity for efficient dynamic data sensing. In this paper, we propose a dynamic knob (DK) design to effectively reconfigure the CS architecture by recognizing the biosignals. Specifically, the dynamic knob design is a template-based structure that comprises a supervised learning module and a look-up table module. We model the DK performance in a closed analytic form and optimize the design via a dynamic programming formulation. We present the design on a 130 nm process, with a 0.058 mm (2) fingerprint and a 187.88 nJ/event energy-consumption. Furthermore, we benchmark the design performance using a publicly available dataset. Given the energy constraint in wireless sensing, the adaptive CS architecture can consistently improve the signal reconstruction quality by more than 70%, compared with the traditional CS. The experimental results indicate that the ultra-low power dynamic knob can provide an effective adaptivity and improve the signal quality in compressed sensing towards biosignal dynamics.

Computational modeling of three-dimensional ECM-rigidity sensing to guide directed cell migration.

PubMed

Kim, Min-Cheol; Silberberg, Yaron R; Abeyaratne, Rohan; Kamm, Roger D; Asada, H Harry

2018-01-16

Filopodia have a key role in sensing both chemical and mechanical cues in surrounding extracellular matrix (ECM). However, quantitative understanding is still missing in the filopodial mechanosensing of local ECM stiffness, resulting from dynamic interactions between filopodia and the surrounding 3D ECM fibers. Here we present a method for characterizing the stiffness of ECM that is sensed by filopodia based on the theory of elasticity and discrete ECM fiber. We have applied this method to a filopodial mechanosensing model for predicting directed cell migration toward stiffer ECM. This model provides us with a distribution of force and displacement as well as their time rate of changes near the tip of a filopodium when it is bound to the surrounding ECM fibers. Aggregating these effects in each local region of 3D ECM, we express the local ECM stiffness sensed by the cell and explain polarity in the cellular durotaxis mechanism.

Angular Rate Sensing with GyroWheel Using Genetic Algorithm Optimized Neural Networks.

PubMed

Zhao, Yuyu; Zhao, Hui; Huo, Xin; Yao, Yu

2017-07-22

GyroWheel is an integrated device that can provide three-axis control torques and two-axis angular rate sensing for small spacecrafts. Large tilt angle of its rotor and de-tuned spin rate lead to a complex and non-linear dynamics as well as difficulties in measuring angular rates. In this paper, the problem of angular rate sensing with the GyroWheel is investigated. Firstly, a simplified rate sensing equation is introduced, and the error characteristics of the method are analyzed. According to the analysis results, a rate sensing principle based on torque balance theory is developed, and a practical way to estimate the angular rates within the whole operating range of GyroWheel is provided by using explicit genetic algorithm optimized neural networks. The angular rates can be determined by the measurable values of the GyroWheel (including tilt angles, spin rate and torque coil currents), the weights and the biases of the neural networks. Finally, the simulation results are presented to illustrate the effectiveness of the proposed angular rate sensing method with GyroWheel.

Research on calibration method of downhole optical fiber temperature measurement and its application in SAGD well

NASA Astrophysics Data System (ADS)

Lu, Zhiwei; Han, Li; Hu, Chengjun; Pan, Yong; Duan, Shengnan; Wang, Ningbo; Li, Shijian; Nuer, Maimaiti

2017-10-01

With the development of oil and gas fields, the accuracy and quantity requirements of real-time dynamic monitoring data needed for well dynamic analysis and regulation are increasing. Permanent, distributed downhole optical fiber temperature and pressure monitoring and other online real-time continuous data monitoring has become an important data acquisition and transmission technology in digital oil field and intelligent oil field construction. Considering the requirement of dynamic analysis of steam chamber developing state in SAGD horizontal wells in F oil reservoir in Xinjiang oilfield, it is necessary to carry out real-time and continuous temperature monitoring in horizontal section. Based on the study of the principle of optical fiber temperature measurement, the factors that cause the deviation of optical fiber temperature sensing are analyzed, and the method of fiber temperature calibration is proposed to solve the problem of temperature deviation. Field application in three wells showed that it could attain accurate measurement of downhole temperature by temperature correction. The real-time and continuous downhole distributed fiber temperature sensing technology has higher application value in the reservoir management of SAGD horizontal wells. It also has a reference for similar dynamic monitoring in reservoir production.

A PRESTO-SENSE sequence with alternating partial-Fourier encoding for rapid susceptibility-weighted 3D MRI time series.

PubMed

Klarhöfer, Markus; Dilharreguy, Bixente; van Gelderen, Peter; Moonen, Chrit T W

2003-10-01

A 3D sequence for dynamic susceptibility imaging is proposed which combines echo-shifting principles (such as PRESTO), sensitivity encoding (SENSE), and partial-Fourier acquisition. The method uses a moderate SENSE factor of 2 and takes advantage of an alternating partial k-space acquisition in the "slow" phase encode direction allowing an iterative reconstruction using high-resolution phase estimates. Offering an isotropic spatial resolution of 4 x 4 x 4 mm(3), the novel sequence covers the whole brain including parts of the cerebellum in 0.5 sec. Its temporal signal stability is comparable to that of a full-Fourier, full-FOV EPI sequence having the same dynamic scan time but much less brain coverage. Initial functional MRI experiments showed consistent activation in the motor cortex with an average signal change slightly less than that of EPI. Copyright 2003 Wiley-Liss, Inc.

A Sense of Place: Integrating Environmental Psychology into Marine Socio-Ecological Models

NASA Astrophysics Data System (ADS)

van Putten, I. E.; Fleming, A.; Fulton, E.; Plaganyi-Lloyd, E.

2016-02-01

Sense of place is a concept that is increasingly applied in different social research contexts where it can act as a bridge between disciplines that might otherwise work in parallel. A sense of place is a well established and flexible concept that has been empirically measured using different survey methods. The psychological principals and theories that underpin sense of place have been inextricably linked to the quality of ecological systems and the impact on development of the system, and vice versa. Ecological models and scenario analyses play an important role in characterising, assessing and predicting the potential impacts of alternative developments and other changes affecting ecological systems. To improve the predictive accuracy of ecological models, human drivers, interactions, and uses have been dynamically incorporated, for instance, through management strategy evaluation applied to marine ecosystem models. However, to date no socio-ecological models (whether terrestrial or marine) have been developed that incorporate a dynamic feedback between ecosystem characteristics and peoples' sense of place. These models thus essentially ignore the influence of environmental psychology on the way people use and interact with ecosystems. We develop a proof of concept and provide a mathematical basis for a Sense of Place Index (SoPI) that allows the quantitative integration of environmental psychology into socio-ecological models. Incorporating dynamic feedback between the SoPI for different resource user groups and the ecological system improves the accuracy and precision of predictions regarding future resource use as well as, ultimately, the potential state of the resource to be developed.

Phase retrieval based wavefront sensing experimental implementation and wavefront sensing accuracy calibration

NASA Astrophysics Data System (ADS)

Mao, Heng; Wang, Xiao; Zhao, Dazun

2009-05-01

As a wavefront sensing (WFS) tool, Baseline algorithm, which is classified as the iterative-transform algorithm of phase retrieval, estimates the phase distribution at pupil from some known PSFs at defocus planes. By using multiple phase diversities and appropriate phase unwrapping methods, this algorithm can accomplish reliable unique solution and high dynamic phase measurement. In the paper, a Baseline algorithm based wavefront sensing experiment with modification of phase unwrapping has been implemented, and corresponding Graphical User Interfaces (GUI) software has also been given. The adaptability and repeatability of Baseline algorithm have been validated in experiments. Moreover, referring to the ZYGO interferometric results, the WFS accuracy of this algorithm has been exactly calibrated.

Sensing of the atmospheric variation using Low Cost GNSS Receiver

NASA Astrophysics Data System (ADS)

Bramanto, Brian; Gumilar, Irwan; Sidiq, Teguh P.; Kuntjoro, Wedyanto; Tampubolon, Daniel A.

2018-05-01

As the GNSS signals transmitted through the atmosphere, they are delayed by interference of TEC (Total Electron Content) in the ionosphere and water vapor in the troposphere. By using inverse-problem, name GNSS Meteorology, those parameters can be obtained precisely and several researches has approved and supported that method. However, the geodetic GNSS receivers are relatively high cost (30,000 to 70,000 each) to be established on a regular and uniform network. This research aims to investigate the potential use of low cost GNSS receiver (less than 2,000) to observe the atmospheric dynamic both in ionosphere and troposphere. Results indicated that low cost GNSS receiver is a promising tools to sensing the atmospheric dynamic, however, further processing is needed to enhance the data quality. It is found that both of ionosphere and troposphere dynamic has diurnal periodic component.

Environmental application of remote sensing methods to coastal zone land use and marine resources management

NASA Technical Reports Server (NTRS)

Goodell, H. G.

1970-01-01

The interrelationships of biophysical environmental systems are investigated. Social decision-making affecting the environments of a coastal megapolis are examined. Remote sensing from high altitude aircraft and satellites afforded a powerful and indepensible tool for inventory and planning for urban development. Repetitive low to medium altitude photography is also used for studying environmental dynamics, and to document the cultural impact of man on his environment.

Combined electromechanical impedance and fiber optic diagnosis of aerospace structures

NASA Astrophysics Data System (ADS)

Schlavin, Jon; Zagrai, Andrei; Clemens, Rebecca; Black, Richard J.; Costa, Joey; Moslehi, Behzad; Patel, Ronak; Sotoudeh, Vahid; Faridian, Fereydoun

2014-03-01

Electromechanical impedance is a popular diagnostic method for assessing structural conditions at high frequencies. It has been utilized, and shown utility, in aeronautic, space, naval, civil, mechanical, and other types of structures. By contrast, fiber optic sensing initially found its niche in static strain measurement and low frequency structural dynamic testing. Any low frequency limitations of the fiber optic sensing, however, are mainly governed by its hardware elements. As hardware improves, so does the bandwidth (frequency range * number of sensors) provided by the appropriate enabling fiber optic sensor interrogation system. In this contribution we demonstrate simultaneous high frequency measurements using fiber optic and electromechanical impedance structural health monitoring technologies. A laboratory specimen imitating an aircraft wing structure, incorporating surfaces with adjustable boundary conditions, was instrumented with piezoelectric and fiber optic sensors. Experiments were conducted at different structural boundary conditions associated with deterioration of structural health. High frequency dynamic responses were collected at multiple locations on a laboratory wing specimen and conclusions were drawn about correspondence between structural damage and dynamic signatures as well as correlation between electromechanical impedance and fiber optic sensors spectra. Theoretical investigation of the effect of boundary conditions on electromechanical impedance spectra is presented and connection to low frequency structural dynamics is suggested. It is envisioned that acquisition of high frequency structural dynamic responses with multiple fiber optic sensors may open new diagnostic capabilities for fiber optic sensing technologies.

Visual Sensing for Urban Flood Monitoring

PubMed Central

Lo, Shi-Wei; Wu, Jyh-Horng; Lin, Fang-Pang; Hsu, Ching-Han

2015-01-01

With the increasing climatic extremes, the frequency and severity of urban flood events have intensified worldwide. In this study, image-based automated monitoring of flood formation and analyses of water level fluctuation were proposed as value-added intelligent sensing applications to turn a passive monitoring camera into a visual sensor. Combined with the proposed visual sensing method, traditional hydrological monitoring cameras have the ability to sense and analyze the local situation of flood events. This can solve the current problem that image-based flood monitoring heavily relies on continuous manned monitoring. Conventional sensing networks can only offer one-dimensional physical parameters measured by gauge sensors, whereas visual sensors can acquire dynamic image information of monitored sites and provide disaster prevention agencies with actual field information for decision-making to relieve flood hazards. The visual sensing method established in this study provides spatiotemporal information that can be used for automated remote analysis for monitoring urban floods. This paper focuses on the determination of flood formation based on image-processing techniques. The experimental results suggest that the visual sensing approach may be a reliable way for determining the water fluctuation and measuring its elevation and flood intrusion with respect to real-world coordinates. The performance of the proposed method has been confirmed; it has the capability to monitor and analyze the flood status, and therefore, it can serve as an active flood warning system. PMID:26287201

New modeling method for the dielectric relaxation of a DRAM cell capacitor

NASA Astrophysics Data System (ADS)

Choi, Sujin; Sun, Wookyung; Shin, Hyungsoon

2018-02-01

This study proposes a new method for automatically synthesizing the equivalent circuit of the dielectric relaxation (DR) characteristic in dynamic random access memory (DRAM) without frequency dependent capacitance measurement. Charge loss due to DR can be observed by a voltage drop at the storage node and this phenomenon can be analyzed by an equivalent circuit. The Havariliak-Negami model is used to accurately determine the electrical characteristic parameters of an equivalent circuit. The DRAM sensing operation is performed in HSPICE simulations to verify this new method. The simulation demonstrates that the storage node voltage drop resulting from DR and the reduction in the sensing voltage margin, which has a critical impact on DRAM read operation, can be accurately estimated using this new method.

A novel scattering switch-on detection technique for target-induced plasmon-coupling based sensing by single-particle optical anisotropy imaging.

PubMed

Peng, Lan; Cao, Xuan; Xiong, Bin; He, Yan; Yeung, Edward S

2016-06-18

We reported a novel scattering switch-on detection technique using flash-lamp polarization darkfield microscopy (FLPDM) for target-induced plasmon-coupling based sensing in homogeneous solution. With this method, we demonstrated sub-nM sensitivity for hydrogen sulfide (H2S) detection over a dynamic range of five orders of magnitude. This robust technique holds great promise for applications in toxic environmental pollutants and biological molecules.

Research on the Construction of Remote Sensing Automatic Interpretation Symbol Big Data

NASA Astrophysics Data System (ADS)

Gao, Y.; Liu, R.; Liu, J.; Cheng, T.

2018-04-01

Remote sensing automatic interpretation symbol (RSAIS) is an inexpensive and fast method in providing precise in-situ information for image interpretation and accuracy. This study designed a scientific and precise RSAIS data characterization method, as well as a distributed and cloud architecture massive data storage method. Additionally, it introduced an offline and online data update mode and a dynamic data evaluation mechanism, with the aim to create an efficient approach for RSAIS big data construction. Finally, a national RSAIS database with more than 3 million samples covering 86 land types was constructed during 2013-2015 based on the National Geographic Conditions Monitoring Project of China and then annually updated since the 2016 period. The RSAIS big data has proven to be a good method for large scale image interpretation and field validation. It is also notable that it has the potential to solve image automatic interpretation with the assistance of deep learning technology in the remote sensing big data era.

Zonal wavefront sensing using a grating array printed on a polyester film

NASA Astrophysics Data System (ADS)

Pathak, Biswajit; Kumar, Suraj; Boruah, Bosanta R.

2015-12-01

In this paper, we describe the development of a zonal wavefront sensor that comprises an array of binary diffraction gratings realized on a transparent sheet (i.e., polyester film) followed by a focusing lens and a camera. The sensor works in a manner similar to that of a Shack-Hartmann wavefront sensor. The fabrication of the array of gratings is immune to certain issues associated with the fabrication of the lenslet array which is commonly used in zonal wavefront sensing. Besides the sensing method offers several important advantages such as flexible dynamic range, easy configurability, and option to enhance the sensing frame rate. Here, we have demonstrated the working of the proposed sensor using a proof-of-principle experimental arrangement.

Ultrasonic guided wave sensing characteristics of large area thin piezo coating

NASA Astrophysics Data System (ADS)

Rathod, V. T.; Jeyaseelan, A. Antony; Dutta, Soma; Mahapatra, D. Roy

2017-10-01

This paper reports on the characterization method and performance enhancement of thin piezo coating for ultrasonic guided wave sensing applications. We deposited the coatings by an in situ slurry coating method and studied their guided wave sensing properties on a one-dimensional metallic beam as a substrate waveguide. The developed piezo coatings show good sensitivity to the longitudinal and flexural modes of guided waves. Sensing voltage due to the guided waves at various different ultrasonic frequencies shows a linear dependence on the thickness of the coating. The coatings also exhibit linear sensor output voltage with respect to the induced dynamic strain magnitude. Diameter/size of the piezo coatings strongly influences the voltage response in relation to the wavelength. The proposed method used a characterization set-up involving coated sensors, reference transducers and an analytical model to estimate the piezoelectric coefficient of the piezo coating. The method eliminates the size dependent effect on the piezo property accurately and gives further insight to design better sensors/filters with respect to frequency/wavelength of interest. The developed coatings will have interesting applications in structural health monitoring (SHM) and internet of things (IOT).

Use of self-actuating and self-sensing cantilevers for imaging biological samples in fluid

PubMed Central

Barbero, R J; Deutschinger, A; Todorov, V; Gray, D S; Belcher, A M; Rangelow, I W; Youcef-Toumi, K

2014-01-01

In this paper, we present a detailed investigation into the suitability of atomic force microscopy (AFM) cantilevers with integrated deflection sensor and micro-actuator for imaging of soft biological samples in fluid. The Si cantilevers are actuated using a micro-heater at the bottom end of the cantilever. Sensing is achieved through p-doped resistors connected in a Wheatstone bridge. We investigated the influence of the water on the cantilever dynamics, the actuation and the sensing mechanisms, as well as the crosstalk between sensing and actuation. Successful imaging of yeast cells in water using the integrated sensor and actuator shows the potential of the combination of this actuation and sensing method. This constitutes a major step towards the automation and miniaturization required to establish AFM in routine biomedical diagnostics and in vivo applications. PMID:19801750

SU-G-IeP1-13: Sub-Nyquist Dynamic MRI Via Prior Rank, Intensity and Sparsity Model (PRISM)

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

Jiang, B; Gao, H

Purpose: Accelerated dynamic MRI is important for MRI guided radiotherapy. Inspired by compressive sensing (CS), sub-Nyquist dynamic MRI has been an active research area, i.e., sparse sampling in k-t space for accelerated dynamic MRI. This work is to investigate sub-Nyquist dynamic MRI via a previously developed CS model, namely Prior Rank, Intensity and Sparsity Model (PRISM). Methods: The proposed method utilizes PRISM with rank minimization and incoherent sampling patterns for sub-Nyquist reconstruction. In PRISM, the low-rank background image, which is automatically calculated by rank minimization, is excluded from the L1 minimization step of the CS reconstruction to further sparsify themore » residual image, thus allowing for higher acceleration rates. Furthermore, the sampling pattern in k-t space is made more incoherent by sampling a different set of k-space points at different temporal frames. Results: Reconstruction results from L1-sparsity method and PRISM method with 30% undersampled data and 15% undersampled data are compared to demonstrate the power of PRISM for dynamic MRI. Conclusion: A sub- Nyquist MRI reconstruction method based on PRISM is developed with improved image quality from the L1-sparsity method.« less

Dynamic drought risk assessment using crop model and remote sensing techniques

NASA Astrophysics Data System (ADS)

Sun, H.; Su, Z.; Lv, J.; Li, L.; Wang, Y.

2017-02-01

Drought risk assessment is of great significance to reduce the loss of agricultural drought and ensure food security. The normally drought risk assessment method is to evaluate its exposure to the hazard and the vulnerability to extended periods of water shortage for a specific region, which is a static evaluation method. The Dynamic Drought Risk Assessment (DDRA) is to estimate the drought risk according to the crop growth and water stress conditions in real time. In this study, a DDRA method using crop model and remote sensing techniques was proposed. The crop model we employed is DeNitrification and DeComposition (DNDC) model. The drought risk was quantified by the yield losses predicted by the crop model in a scenario-based method. The crop model was re-calibrated to improve the performance by the Leaf Area Index (LAI) retrieved from MODerate Resolution Imaging Spectroradiometer (MODIS) data. And the in-situ station-based crop model was extended to assess the regional drought risk by integrating crop planted mapping. The crop planted area was extracted with extended CPPI method from MODIS data. This study was implemented and validated on maize crop in Liaoning province, China.

Ten year change in forest succession and composition measured by remote sensing

NASA Technical Reports Server (NTRS)

Hall, Forrest G.; Botkin, Daniel B.; Strebel, Donald E.; Woods, Kerry K.; Goetz, Scott J.

1987-01-01

Vegetation dynamics and changes in ecological patterns were measured by remote sensing over a 10 year period (1973 to 1983) for 148,406 landscape elements, covering more than 500 sq km in a protected forested wilderness. Quantitative measurements were made possible by methods to detect ecologically meaningful landscape units; these allowed measurement of ecological transition frequencies and calculation of expected recurrence times. Measured ecological transition frequencies reveal boreal forest wilderness as spatially heterogeneous and highly dynamic, with one-sixth of the area in clearings and early successional stages, consistent with recent postulates about the spatial and temporal patterns of natural ecosystems. Differences between managed forest areas and a protected wilderness allow assessment of different management regimes.

Modal Correction Method For Dynamically Induced Errors In Wind-Tunnel Model Attitude Measurements

NASA Technical Reports Server (NTRS)

Buehrle, R. D.; Young, C. P., Jr.

1995-01-01

This paper describes a method for correcting the dynamically induced bias errors in wind tunnel model attitude measurements using measured modal properties of the model system. At NASA Langley Research Center, the predominant instrumentation used to measure model attitude is a servo-accelerometer device that senses the model attitude with respect to the local vertical. Under smooth wind tunnel operating conditions, this inertial device can measure the model attitude with an accuracy of 0.01 degree. During wind tunnel tests when the model is responding at high dynamic amplitudes, the inertial device also senses the centrifugal acceleration associated with model vibration. This centrifugal acceleration results in a bias error in the model attitude measurement. A study of the response of a cantilevered model system to a simulated dynamic environment shows significant bias error in the model attitude measurement can occur and is vibration mode and amplitude dependent. For each vibration mode contributing to the bias error, the error is estimated from the measured modal properties and tangential accelerations at the model attitude device. Linear superposition is used to combine the bias estimates for individual modes to determine the overall bias error as a function of time. The modal correction model predicts the bias error to a high degree of accuracy for the vibration modes characterized in the simulated dynamic environment.

Hybrid wavefront sensor for the fast detection of wavefront disturbances.

PubMed

Dong, Shihao; Haist, Tobias; Osten, Wolfgang

2012-09-01

Strongly aberrated wavefronts lead to inaccuracies and nonlinearities in holography-based modal wavefront sensing (HMWS). In this contribution, a low-resolution Shack-Hartmann sensor (LRSHS) is incorporated into HMWS via a compact holographic design to extend the dynamic range of HMWS. A static binary-phase computer-generated hologram is employed to generate the desired patterns for Shack-Hartmann sensing and HMWS. The low-order aberration modes dominating the wavefront error are first sensed with the LRSHS and corrected by the wavefront modulator. The system then switches to HMWS to obtain better sensor sensitivity and accuracy. Simulated as well as experimental results are shown for validating the proposed method.

Monitoring of the Abrasion Processes (by the Example of Alakol Lake, Republic of Kazakhstan)

ERIC Educational Resources Information Center

Abitbayeva, Ainagul; Valeyev, Adilet; Yegemberdiyeva, Kamshat; Assylbekova, Aizhan; Ryskeldieva, Aizhan

2016-01-01

The purpose of the study is to analyze the abrasion processes in the regions of dynamically changing Alakol lake shores. Using the field method, methods of positioning by the GPS receiver and interpretation of remote sensing data, the authors determined that abrasion processes actively contributed to the formation the modern landscape, causing the…

Volumetric MRI of the lungs during forced expiration.

PubMed

Berman, Benjamin P; Pandey, Abhishek; Li, Zhitao; Jeffries, Lindsie; Trouard, Theodore P; Oliva, Isabel; Cortopassi, Felipe; Martin, Diego R; Altbach, Maria I; Bilgin, Ali

2016-06-01

Lung function is typically characterized by spirometer measurements, which do not offer spatially specific information. Imaging during exhalation provides spatial information but is challenging due to large movement over a short time. The purpose of this work is to provide a solution to lung imaging during forced expiration using accelerated magnetic resonance imaging. The method uses radial golden angle stack-of-stars gradient echo acquisition and compressed sensing reconstruction. A technique for dynamic three-dimensional imaging of the lungs from highly undersampled data is developed and tested on six subjects. This method takes advantage of image sparsity, both spatially and temporally, including the use of reference frames called bookends. Sparsity, with respect to total variation, and residual from the bookends, enables reconstruction from an extremely limited amount of data. Dynamic three-dimensional images can be captured at sub-150 ms temporal resolution, using only three (or less) acquired radial lines per slice per timepoint. The images have a spatial resolution of 4.6×4.6×10 mm. Lung volume calculations based on image segmentation are compared to those from simultaneously acquired spirometer measurements. Dynamic lung imaging during forced expiration is made possible by compressed sensing accelerated dynamic three-dimensional radial magnetic resonance imaging. Magn Reson Med 75:2295-2302, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Optical chaos and hybrid WDM/TDM based large capacity quasi-distributed sensing network with real-time fiber fault monitoring.

PubMed

Luo, Yiyang; Xia, Li; Xu, Zhilin; Yu, Can; Sun, Qizhen; Li, Wei; Huang, Di; Liu, Deming

2015-02-09

An optical chaos and hybrid wavelength division multiplexing/time division multiplexing (WDM/TDM) based large capacity quasi-distributed sensing network with real-time fiber fault monitoring is proposed. Chirped fiber Bragg grating (CFBG) intensity demodulation is adopted to improve the dynamic range of the measurements. Compared with the traditional sensing interrogation methods in time, radio frequency and optical wavelength domains, the measurand sensing and the precise locating of the proposed sensing network can be simultaneously interrogated by the relative amplitude change (RAC) and the time delay of the correlation peak in the cross-correlation spectrum. Assisted with the WDM/TDM technology, hundreds of sensing units could be potentially multiplexed in the multiple sensing fiber lines. Based on the proof-of-concept experiment for axial strain measurement with three sensing fiber lines, the strain sensitivity up to 0.14% RAC/με and the precise locating of the sensors are achieved. Significantly, real-time fiber fault monitoring in the three sensing fiber lines is also implemented with a spatial resolution of 2.8 cm.

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

Remote Sensing and Characterization of Oil on Water Using Coherent Fringe Projection and Holographic in-Line Interferometry

DTIC Science & Technology

2013-03-01

holo- graphic recording on photo-thermo-plastic structure ,” J. Modern Opt. 57(10), 854–858 (2010). 6. N. Kukhtarev and T. Kukhtareva, “ Dynamic ...RESPONSIBLE PERSON 19b. TELEPHONE NUMBER (Include area code) 21-10-2013 Journal Article Remote Sensing and Characterization of Oil on Water Using...green-blue region can also degrade oil. This finding indicates that properly structured laser clean-up can be an alternative method of decontamination

Distributed video data fusion and mining

NASA Astrophysics Data System (ADS)

Chang, Edward Y.; Wang, Yuan-Fang; Rodoplu, Volkan

2004-09-01

This paper presents an event sensing paradigm for intelligent event-analysis in a wireless, ad hoc, multi-camera, video surveillance system. In particilar, we present statistical methods that we have developed to support three aspects of event sensing: 1) energy-efficient, resource-conserving, and robust sensor data fusion and analysis, 2) intelligent event modeling and recognition, and 3) rapid deployment, dynamic configuration, and continuous operation of the camera networks. We outline our preliminary results, and discuss future directions that research might take.

Hyperspectral remote sensing of plant pigments.

PubMed

Blackburn, George Alan

2007-01-01

The dynamics of pigment concentrations are diagnostic of a range of plant physiological properties and processes. This paper appraises the developing technologies and analytical methods for quantifying pigments non-destructively and repeatedly across a range of spatial scales using hyperspectral remote sensing. Progress in deriving predictive relationships between various characteristics and transforms of hyperspectral reflectance data are evaluated and the roles of leaf and canopy radiative transfer models are reviewed. Requirements are identified for more extensive intercomparisons of different approaches and for further work on the strategies for interpreting canopy scale data. The paper examines the prospects for extending research to the wider range of pigments in addition to chlorophyll, testing emerging methods of hyperspectral analysis and exploring the fusion of hyperspectral and LIDAR remote sensing. In spite of these opportunities for further development and the refinement of techniques, current evidence of an expanding range of applications in the ecophysiological, environmental, agricultural, and forestry sciences highlights the growing value of hyperspectral remote sensing of plant pigments.

Highly sensitive distributed birefringence measurements based on a two-pulse interrogation of a dynamic Brillouin grating

NASA Astrophysics Data System (ADS)

Soto, Marcelo A.; Denisov, Andrey; Angulo-Vinuesa, Xabier; Martin-Lopez, Sonia; Thévenaz, Luc; Gonzalez-Herraez, Miguel

2017-04-01

A method for distributed birefringence measurements is proposed based on the interference pattern generated by the interrogation of a dynamic Brillouin grating (DBG) using two short consecutive optical pulses. Compared to existing DBG interrogation techniques, the method here offers an improved sensitivity to birefringence changes thanks to the interferometric effect generated by the reflections of the two pulses. Experimental results demonstrate the possibility to obtain the longitudinal birefringence profile of a 20 m-long Panda fibre with an accuracy of 10-8 using 16 averages and 30 cm spatial resolution. The method enables sub-metric and highly-accurate distributed temperature and strain sensing.

An HDR imaging method with DTDI technology for push-broom cameras

NASA Astrophysics Data System (ADS)

Sun, Wu; Han, Chengshan; Xue, Xucheng; Lv, Hengyi; Shi, Junxia; Hu, Changhong; Li, Xiangzhi; Fu, Yao; Jiang, Xiaonan; Huang, Liang; Han, Hongyin

2018-03-01

Conventionally, high dynamic-range (HDR) imaging is based on taking two or more pictures of the same scene with different exposure. However, due to a high-speed relative motion between the camera and the scene, it is hard for this technique to be applied to push-broom remote sensing cameras. For the sake of HDR imaging in push-broom remote sensing applications, the present paper proposes an innovative method which can generate HDR images without redundant image sensors or optical components. Specifically, this paper adopts an area array CMOS (complementary metal oxide semiconductor) with the digital domain time-delay-integration (DTDI) technology for imaging, instead of adopting more than one row of image sensors, thereby taking more than one picture with different exposure. And then a new HDR image by fusing two original images with a simple algorithm can be achieved. By conducting the experiment, the dynamic range (DR) of the image increases by 26.02 dB. The proposed method is proved to be effective and has potential in other imaging applications where there is a relative motion between the cameras and scenes.

Surge of Bering Glacier and Bagley Ice Field: Parameterization of surge characteristics based on automated analysis of crevasse image data and laser altimeter data

NASA Astrophysics Data System (ADS)

Stachura, M.; Herzfeld, U. C.; McDonald, B.; Weltman, A.; Hale, G.; Trantow, T.

2012-12-01

The dynamical processes that occur during the surge of a large, complex glacier system are far from being understood. The aim of this paper is to derive a parameterization of surge characteristics that captures the principle processes and can serve as the basis for a dynamic surge model. Innovative mathematical methods are introduced that facilitate derivation of such a parameterization from remote-sensing observations. Methods include automated geostatistical characterization and connectionist-geostatistical classification of dynamic provinces and deformation states, using the vehicle of crevasse patterns. These methods are applied to analyze satellite and airborne image and laser altimeter data collected during the current surge of Bering Glacier and Bagley Ice Field, Alaska.

Enhanced damping for bridge cables using a self-sensing MR damper

NASA Astrophysics Data System (ADS)

Chen, Z. H.; Lam, K. H.; Ni, Y. Q.

2016-08-01

This paper investigates enhanced damping for protecting bridge stay cables from excessive vibration using a newly developed self-sensing magnetorheological (MR) damper. The semi-active control strategy for effectively operating the self-sensing MR damper is formulated based on the linear-quadratic-Gaussian (LQG) control by further considering a collocated control configuration, limited measurements and nonlinear damper dynamics. Due to its attractive feature of sensing-while-damping, the self-sensing MR damper facilitates the collocated control. On the other hand, only the sensor measurements from the self-sensing device are employed in the feedback control. The nonlinear dynamics of the self-sensing MR damper, represented by a validated Bayesian NARX network technique, are further accommodated in the control formulation to compensate for its nonlinearities. Numerical and experimental investigations are conducted on stay cables equipped with the self-sensing MR damper operated in passive and semi-active control modes. The results verify that the collocated self-sensing MR damper facilitates smart damping for inclined cables employing energy-dissipative LQG control with only force and displacement measurements at the damper. It is also demonstrated that the synthesis of nonlinear damper dynamics in the LQG control enhances damping force tracking efficiently, explores the features of the self-sensing MR damper, and achieves better control performance over the passive MR damping control and the Heaviside step function-based LQG control that ignores the damper dynamics.

Use of Landsat thermal imagery for dynamically monitoring spontaneous combustion of Datong Jurassic coalfields in China

NASA Astrophysics Data System (ADS)

Xue, Yongan; Liu, Jin; Li, Jun; Shang, Changsheng; Zhao, Jinling; Zhang, Mingmei

2018-06-01

It is highly helpful and necessary to investigate and monitor the status of coal seam. Fortunately, remote sensing has facilitated the identification and dynamical monitoring of spontaneous combustion for a large area coal mining area, especially using the time series remotely-sensed datasets. In this paper, Datong Jurassic coal mining area is used as the study area, China, and an exclusion method and a multiple-factor analysis method are jointly used to identify the spontaneous combustion, including land surface temperature (LST), burnt rocks, and land use and land cover change (LUCC). The LST is firstly retrieved using a single-window algorithm due to a thermal infrared band of Landsat-5 TM (Thematic Mapper). Burnt rocks is then extracted using a decision-tree classification method based on a high-resolution SPOT-5 image. The thermal anomaly areas are identified and refined by the spatial overlay analysis of the above affecting factors. Three-period maps of coal fire areas are obtained and dynamically analyzed in 2007, 2009 and 2010. The results show that a total of 12 coal fire areas have been identified, which account for more than 1% of the total area of the study area. In general, there is an increasing trend yearly and a total of 771,970 m2 is increased. The average annual increase is 257,320 m2, the average annual growth rate is 3.78%, and the dynamic degree is 11.29%.

Zonal wavefront sensing using a grating array printed on a polyester film

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

Pathak, Biswajit; Boruah, Bosanta R., E-mail: brboruah@iitg.ernet.in; Kumar, Suraj

2015-12-15

In this paper, we describe the development of a zonal wavefront sensor that comprises an array of binary diffraction gratings realized on a transparent sheet (i.e., polyester film) followed by a focusing lens and a camera. The sensor works in a manner similar to that of a Shack-Hartmann wavefront sensor. The fabrication of the array of gratings is immune to certain issues associated with the fabrication of the lenslet array which is commonly used in zonal wavefront sensing. Besides the sensing method offers several important advantages such as flexible dynamic range, easy configurability, and option to enhance the sensing framemore » rate. Here, we have demonstrated the working of the proposed sensor using a proof-of-principle experimental arrangement.« less

A Portable Dynamic Laser Speckle System for Sensing Long-Term Changes Caused by Treatments in Painting Conservation.

PubMed

Pérez, Alberto J; González-Peña, Rolando J; Braga, Roberto; Perles, Ángel; Pérez-Marín, Eva; García-Diego, Fernando J

2018-01-11

Dynamic laser speckle (DLS) is used as a reliable sensor of activity for all types of materials. Traditional applications are based on high-rate captures (usually greater than 10 frames-per-second, fps). Even for drying processes in conservation treatments, where there is a high level of activity in the first moments after the application and slower activity after some minutes or hours, the process is based on the acquisition of images at a time rate that is the same in moments of high and low activity. In this work, we present an alternative approach to track the drying process of protective layers and other painting conservation processes that take a long time to reduce their levels of activity. We illuminate, using three different wavelength lasers, a temporary protector (cyclododecane) and a varnish, and monitor them using a low fps rate during long-term drying. The results are compared to the traditional method. This work also presents a monitoring method that uses portable equipment. The results present the feasibility of using the portable device and show the improved sensitivity of the dynamic laser speckle when sensing the long-term process for drying cyclododecane and varnish in conservation.

Yellow River Icicle Hazard Dynamic Monitoring Using UAV Aerial Remote Sensing Technology

NASA Astrophysics Data System (ADS)

Wang, H. B.; Wang, G. H.; Tang, X. M.; Li, C. H.

2014-02-01

Monitoring the response of Yellow River icicle hazard change requires accurate and repeatable topographic surveys. A new method based on unmanned aerial vehicle (UAV) aerial remote sensing technology is proposed for real-time data processing in Yellow River icicle hazard dynamic monitoring. The monitoring area is located in the Yellow River ice intensive care area in southern BaoTou of Inner Mongolia autonomous region. Monitoring time is from the 20th February to 30th March in 2013. Using the proposed video data processing method, automatic extraction covering area of 7.8 km2 of video key frame image 1832 frames took 34.786 seconds. The stitching and correcting time was 122.34 seconds and the accuracy was better than 0.5 m. Through the comparison of precise processing of sequence video stitching image, the method determines the change of the Yellow River ice and locates accurate positioning of ice bar, improving the traditional visual method by more than 100 times. The results provide accurate aid decision information for the Yellow River ice prevention headquarters. Finally, the effect of dam break is repeatedly monitored and ice break five meter accuracy is calculated through accurate monitoring and evaluation analysis.

Readers and Authors: Fictionalized Constructs or Dynamic Collaborations?

ERIC Educational Resources Information Center

Blakeslee, Ann M.

1993-01-01

Uses ethnographic field methods to investigate the ways that scientific authors develop an understanding of their audiences. Finds that, rather than writing a text for an abstract audience, these scientists engaged their readers in direct interactions to obtain a clearer sense of their concerns. (RS)

Long-term analysis of Zostera noltei: A retrospective approach for understanding seagrasses' dynamics.

PubMed

Calleja, Felipe; Galván, Cristina; Silió-Calzada, Ana; Juanes, José A; Ondiviela, Bárbara

2017-09-01

Long-term studies are necessary to establish trends and to understand seagrasses' spatial and temporal dynamic. Nevertheless, this type of research is scarce, as the required databases are often unavailable. The objectives of this study are to create a method for mapping the seagrass Zostera noltei using remote sensing techniques, and to apply it to the characterization of the meadows' extension trend and the potential drivers of change. A time series was created using a novel method based on remote sensing techniques that proved to be adequate for mapping the seagrass in the emerged intertidal. The meadows seem to have a decreasing trend between 1984 and the early 2000s, followed by an increasing tendency that represents a recovery in the extension area of the species. This 30-year analysis demonstrated the Z. noltei's recovery in the study site, similar to that in other estuaries nearby and contrary to the worldwide decreasing behavior of seagrasses. Copyright © 2017 Elsevier Ltd. All rights reserved.

Sensing Urban Land-Use Patterns by Integrating Google Tensorflow and Scene-Classification Models

NASA Astrophysics Data System (ADS)

Yao, Y.; Liang, H.; Li, X.; Zhang, J.; He, J.

2017-09-01

With the rapid progress of China's urbanization, research on the automatic detection of land-use patterns in Chinese cities is of substantial importance. Deep learning is an effective method to extract image features. To take advantage of the deep-learning method in detecting urban land-use patterns, we applied a transfer-learning-based remote-sensing image approach to extract and classify features. Using the Google Tensorflow framework, a powerful convolution neural network (CNN) library was created. First, the transferred model was previously trained on ImageNet, one of the largest object-image data sets, to fully develop the model's ability to generate feature vectors of standard remote-sensing land-cover data sets (UC Merced and WHU-SIRI). Then, a random-forest-based classifier was constructed and trained on these generated vectors to classify the actual urban land-use pattern on the scale of traffic analysis zones (TAZs). To avoid the multi-scale effect of remote-sensing imagery, a large random patch (LRP) method was used. The proposed method could efficiently obtain acceptable accuracy (OA = 0.794, Kappa = 0.737) for the study area. In addition, the results show that the proposed method can effectively overcome the multi-scale effect that occurs in urban land-use classification at the irregular land-parcel level. The proposed method can help planners monitor dynamic urban land use and evaluate the impact of urban-planning schemes.

The free and forced vibrations of structures using the finite dynamic element method. Ph.D. Thesis, Aug. 1991 Final Report

NASA Technical Reports Server (NTRS)

Fergusson, Neil J.

1992-01-01

In addition to an extensive review of the literature on exact and corrective displacement based methods of vibration analysis, a few theorems are proven concerning the various structural matrices involved in such analyses. In particular, the consistent mass matrix and the quasi-static mass matrix are shown to be equivalent, in the sense that the terms in their respective Taylor expansions are proportional to one another, and that they both lead to the same dynamic stiffness matrix when used with the appropriate stiffness matrix.

Evaluation of a multiple spin- and gradient-echo (SAGE) EPI acquisition with SENSE acceleration: applications for perfusion imaging in and outside the brain.

PubMed

Skinner, Jack T; Robison, Ryan K; Elder, Christopher P; Newton, Allen T; Damon, Bruce M; Quarles, C Chad

2014-12-01

Perfusion-based changes in MR signal intensity can occur in response to the introduction of exogenous contrast agents and endogenous tissue properties (e.g. blood oxygenation). MR measurements aimed at capturing these changes often implement single-shot echo planar imaging (ssEPI). In recent years ssEPI readouts have been combined with parallel imaging (PI) to allow fast dynamic multi-slice imaging as well as the incorporation of multiple echoes. A multiple spin- and gradient-echo (SAGE) EPI acquisition has recently been developed to allow measurement of transverse relaxation rate (R2 and R2(*)) changes in dynamic susceptibility contrast (DSC)-MRI experiments in the brain. With SAGE EPI, the use of PI can influence image quality, temporal resolution, and achievable echo times. The effect of PI on dynamic SAGE measurements, however, has not been evaluated. In this work, a SAGE EPI acquisition utilizing SENSE PI and partial Fourier (PF) acceleration was developed and evaluated. Voxel-wise measures of R2 and R2(*) in healthy brain were compared using SAGE EPI and conventional non-EPI multiple echo acquisitions with varying SENSE and PF acceleration. A conservative SENSE factor of 2 with PF factor of 0.73 was found to provide accurate measures of R2 and R2(*) in white (WM) (rR2=[0.55-0.79], rR2*=[0.47-0.71]) and gray (GM) matter (rR2=[0.26-0.59], rR2*=[0.39-0.74]) across subjects. The combined use of SENSE and PF allowed the first dynamic SAGE EPI measurements in muscle, with a SENSE factor of 3 and PF factor of 0.6 providing reliable relaxation rate estimates when compared to multi-echo methods. Application of the optimized SAGE protocol in DSC-MRI of high-grade glioma patients provided T1 leakage-corrected estimates of CBV and CBF as well as mean vessel diameter (mVD) and simultaneous measures of DCE-MRI parameters K(trans) and ve. Likewise, application of SAGE in a muscle reperfusion model allowed dynamic measures of R2', a parameter that has been shown to correlate with muscle oxy-hemoglobin saturation. Copyright © 2014 Elsevier Inc. All rights reserved.

An Online Dictionary Learning-Based Compressive Data Gathering Algorithm in Wireless Sensor Networks

PubMed Central

Wang, Donghao; Wan, Jiangwen; Chen, Junying; Zhang, Qiang

2016-01-01

To adapt to sense signals of enormous diversities and dynamics, and to decrease the reconstruction errors caused by ambient noise, a novel online dictionary learning method-based compressive data gathering (ODL-CDG) algorithm is proposed. The proposed dictionary is learned from a two-stage iterative procedure, alternately changing between a sparse coding step and a dictionary update step. The self-coherence of the learned dictionary is introduced as a penalty term during the dictionary update procedure. The dictionary is also constrained with sparse structure. It’s theoretically demonstrated that the sensing matrix satisfies the restricted isometry property (RIP) with high probability. In addition, the lower bound of necessary number of measurements for compressive sensing (CS) reconstruction is given. Simulation results show that the proposed ODL-CDG algorithm can enhance the recovery accuracy in the presence of noise, and reduce the energy consumption in comparison with other dictionary based data gathering methods. PMID:27669250

An Online Dictionary Learning-Based Compressive Data Gathering Algorithm in Wireless Sensor Networks.

PubMed

Wang, Donghao; Wan, Jiangwen; Chen, Junying; Zhang, Qiang

2016-09-22

To adapt to sense signals of enormous diversities and dynamics, and to decrease the reconstruction errors caused by ambient noise, a novel online dictionary learning method-based compressive data gathering (ODL-CDG) algorithm is proposed. The proposed dictionary is learned from a two-stage iterative procedure, alternately changing between a sparse coding step and a dictionary update step. The self-coherence of the learned dictionary is introduced as a penalty term during the dictionary update procedure. The dictionary is also constrained with sparse structure. It's theoretically demonstrated that the sensing matrix satisfies the restricted isometry property (RIP) with high probability. In addition, the lower bound of necessary number of measurements for compressive sensing (CS) reconstruction is given. Simulation results show that the proposed ODL-CDG algorithm can enhance the recovery accuracy in the presence of noise, and reduce the energy consumption in comparison with other dictionary based data gathering methods.

The method of parallel-hierarchical transformation for rapid recognition of dynamic images using GPGPU technology

NASA Astrophysics Data System (ADS)

Timchenko, Leonid; Yarovyi, Andrii; Kokriatskaya, Nataliya; Nakonechna, Svitlana; Abramenko, Ludmila; Ławicki, Tomasz; Popiel, Piotr; Yesmakhanova, Laura

2016-09-01

The paper presents a method of parallel-hierarchical transformations for rapid recognition of dynamic images using GPU technology. Direct parallel-hierarchical transformations based on cluster CPU-and GPU-oriented hardware platform. Mathematic models of training of the parallel hierarchical (PH) network for the transformation are developed, as well as a training method of the PH network for recognition of dynamic images. This research is most topical for problems on organizing high-performance computations of super large arrays of information designed to implement multi-stage sensing and processing as well as compaction and recognition of data in the informational structures and computer devices. This method has such advantages as high performance through the use of recent advances in parallelization, possibility to work with images of ultra dimension, ease of scaling in case of changing the number of nodes in the cluster, auto scan of local network to detect compute nodes.

The dynamic micro computed tomography at SSRF

NASA Astrophysics Data System (ADS)

Chen, R.; Xu, L.; Du, G.; Deng, B.; Xie, H.; Xiao, T.

2018-05-01

Synchrotron radiation micro-computed tomography (SR-μCT) is a critical technique for quantitative characterizing the 3D internal structure of samples, recently the dynamic SR-μCT has been attracting vast attention since it can evaluate the three-dimensional structure evolution of a sample. A dynamic μCT method, which is based on monochromatic beam, was developed at the X-ray Imaging and Biomedical Application Beamline at Shanghai Synchrotron Radiation Facility, by combining the compressed sensing based CT reconstruction algorithm and hardware upgrade. The monochromatic beam based method can achieve quantitative information, and lower dose than the white beam base method in which the lower energy beam is absorbed by the sample rather than contribute to the final imaging signal. The developed method is successfully used to investigate the compression of the air sac during respiration in a bell cricket, providing new knowledge for further research on the insect respiratory system.

A Comparative Study of Chemically and Biologically Synthesized MgO Nanomaterial for Liquefied Petroleum Gas Detection

NASA Astrophysics Data System (ADS)

Thirupathi, Rampelly; Solleti, Goutham; Sreekanth, Tirumala; Sadasivuni, Kishor Kumar; Venkateswara Rao, Kalagadda

2018-03-01

The exceptional chemical and physical properties of nanostructured materials are extremely suitable for designing new and enhanced sensing devices, particularly gas sensors and biosensors. The present work describes the synthesis of magnesium oxide (MgO) nanoparticles through two methods: a green synthesis using aloe vera plant extract and a chemical method using a glycine-based solution combustion route. In a single step, the extracted organic molecules from aloe vera plants were used to reduce metal ions by the green method. MgO nanoparticles were coated onto the interdigital electrode using the drop-drying method. The dynamic gas-sensing characteristics were measured for liquefied petroleum gas (LPG) at different concentrations and various temperatures. The MgO nanoparticles were characterized by using x-ray diffraction, field emission scanning electron microscopy, and high-resolution transmission electron microscopy to determine the size and structure of the particles. The product's functional properties were analyzed by Fourier transform-infrared spectroscopy and UV-visible spectroscopy. We found that the LPG sensing behavior of biologically synthesized MgO registers excellent sensitivity at various operating temperatures.

A Comparative Study of Chemically and Biologically Synthesized MgO Nanomaterial for Liquefied Petroleum Gas Detection

NASA Astrophysics Data System (ADS)

Thirupathi, Rampelly; Solleti, Goutham; Sreekanth, Tirumala; Sadasivuni, Kishor Kumar; Venkateswara Rao, Kalagadda

2018-07-01

The exceptional chemical and physical properties of nanostructured materials are extremely suitable for designing new and enhanced sensing devices, particularly gas sensors and biosensors. The present work describes the synthesis of magnesium oxide (MgO) nanoparticles through two methods: a green synthesis using aloe vera plant extract and a chemical method using a glycine-based solution combustion route. In a single step, the extracted organic molecules from aloe vera plants were used to reduce metal ions by the green method. MgO nanoparticles were coated onto the interdigital electrode using the drop-drying method. The dynamic gas-sensing characteristics were measured for liquefied petroleum gas (LPG) at different concentrations and various temperatures. The MgO nanoparticles were characterized by using x-ray diffraction, field emission scanning electron microscopy, and high-resolution transmission electron microscopy to determine the size and structure of the particles. The product's functional properties were analyzed by Fourier transform-infrared spectroscopy and UV-visible spectroscopy. We found that the LPG sensing behavior of biologically synthesized MgO registers excellent sensitivity at various operating temperatures.

Scott Dana | NREL

Science.gov Websites

Dana Scott Dana Mechanical and Vibrations Engineer Scott.Dana@nrel.gov | 303-384-7036 Scott focuses on field testing of wind turbines and components for mechanical loads and power performance structural health monitoring using dynamic-based sensing methods. Education B.S. and M.S. in Mechanical

Bridge Displacement Monitoring Method Based on Laser Projection-Sensing Technology

PubMed Central

Zhao, Xuefeng; Liu, Hao; Yu, Yan; Xu, Xiaodong; Hu, Weitong; Li, Mingchu; Ou, Jingping

2015-01-01

Bridge displacement is the most basic evaluation index of the health status of a bridge structure. The existing measurement methods for bridge displacement basically fail to realize long-term and real-time dynamic monitoring of bridge structures, because of the low degree of automation and the insufficient precision, causing bottlenecks and restriction. To solve this problem, we proposed a bridge displacement monitoring system based on laser projection-sensing technology. First, the laser spot recognition method was studied. Second, the software for the displacement monitoring system was developed. Finally, a series of experiments using this system were conducted, and the results show that such a system has high measurement accuracy and speed. We aim to develop a low-cost, high-accuracy and long-term monitoring method for bridge displacement based on these preliminary efforts. PMID:25871716

Upper Limb Asymmetries in the Perception of Proprioceptively Determined Dynamic Position Sense

ERIC Educational Resources Information Center

Goble, Daniel J.; Brown, Susan H.

2010-01-01

Recent studies of position-related proprioceptive sense have provided evidence of a nonpreferred left arm advantage in right-handed individuals. The present study sought to determine whether similar asymmetries might exist in "dynamic position" sense. Thirteen healthy, right-handed adults were blindfolded and seated with arms placed on…

High-Frequency Observation of Water Spectrum and Its Application in Monitoring of Dynamic Variation of Suspended Materials in the Hangzhou Bay.

PubMed

Dai, Qian; Pan, De-lu; He, Xian-qiang; Zhu, Qian-kun; Gong, Fang; Huang, Hai-qing

2015-11-01

In situ measurement of water spectrum is the basis of the validation of the ocean color remote sensing. The traditional method to obtain the water spectrum is based on the shipboard measurement at limited stations, which is difficult to meet the requirement of validation of ocean color remote sensing in the highly dynamic coastal waters. To overcome this shortage, continuously observing systems of water spectrum have been developed in the world. However, so far, there are still few high-frequency observation systems of the water spectrum in coastal waters, especially in the highly turbid and high-dynamic waters. Here, we established a high-frequency water-spectrum observing system based on tower in the Hangzhou Bay. The system measures the water spectrum at a step of 3 minutes, which can fully match the satellite observation. In this paper, we primarily developed a data processing method for the tower-based high-frequency water spectrum data, to realize automatic judgment of clear sky, sun glint, platform shadow, and weak illumination, etc. , and verified the processing results. The results show that the normalized water-leaving radiance spectra obtained through tower observation have relatively high consistency with the shipboard measurement results, with correlation coefficient of more than 0. 99, and average relative error of 9.96%. In addition, the long-term observation capability of the tower-based high-frequency water-spectrum observing system was evaluated, and the results show that although the system has run for one year, the normalized water-leaving radiance obtained by this system have good consistency with the synchronously measurement by Portable spectrometer ASD in respect of spectral shape and value, with correlation coefficient of more than 0.90 and average relative error of 6.48%. Moreover, the water spectra from high-frequency observation by the system can be used to effectively monitor the rapid dynamic variation in concentration of suspended materials with tide. The tower-based high-frequency water-spectrum observing system provided rich in situ spectral data for the validation of ocean color remote sensing in turbid waters, especially for validation of the high temporal-resolution geostationary satellite ocean color remote sensing.

Integrating dynamic and distributed compressive sensing techniques to enhance image quality of the compressive line sensing system for unmanned aerial vehicles application

NASA Astrophysics Data System (ADS)

Ouyang, Bing; Hou, Weilin; Caimi, Frank M.; Dalgleish, Fraser R.; Vuorenkoski, Anni K.; Gong, Cuiling

2017-07-01

The compressive line sensing imaging system adopts distributed compressive sensing (CS) to acquire data and reconstruct images. Dynamic CS uses Bayesian inference to capture the correlated nature of the adjacent lines. An image reconstruction technique that incorporates dynamic CS in the distributed CS framework was developed to improve the quality of reconstructed images. The effectiveness of the technique was validated using experimental data acquired in an underwater imaging test facility. Results that demonstrate contrast and resolution improvements will be presented. The improved efficiency is desirable for unmanned aerial vehicles conducting long-duration missions.

Methods of satellite oceanography

NASA Technical Reports Server (NTRS)

Stewart, R. H.

1985-01-01

The theoretical basis for remote sensing measurements of climate and ocean dynamics is examined. Consideration is given to: the absorption of electromagnetic radiation in the atmosphere; scattering in the atmosphere; and satellite observations using visible light. Consideration is also given to: the theory of radio scatter from the sea; scatter of centimeter waves from the sea; and the theory of operation of synthetic aperture radars. Additional topics include: the coordinate systems of satellite orbits for oceanographic remote sensing applications; the operating features of the major U.S. satellite systems for viewing the ocean; and satellite altimetry.

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.

Gait development on Minitaur, a direct drive quadrupedal robot

NASA Astrophysics Data System (ADS)

Blackman, Daniel J.; Nicholson, John V.; Ordonez, Camilo; Miller, Bruce D.; Clark, Jonathan E.

2016-05-01

This paper describes the development of a dynamic, quadrupedal robot designed for rapid traversal and interaction in human environments. We explore improvements to both physical and control methods to a legged robot (Minitaur) in order to improve the speed and stability of its gaits and increase the range of obstacles that it can overcome, with an eye toward negotiating man-made terrains such as stairs. These modifications include an analysis of physical compliance, an investigation of foot and leg design, and the implementation of ground and obstacle contact sensing for inclusion in the control schemes. Structural and mechanical improvements were made to reduce undesired compliance for more consistent agreement with dynamic models, which necessitated refinement of foot design for greater durability. Contact sensing was implemented into the control scheme for identifying obstacles and deviations in surface level for negotiation of varying terrain. Overall the incorporation of these features greatly enhances the mobility of the dynamic quadrupedal robot and helps to establish a basis for overcoming obstacles.

Dual-loop model of the human controller

NASA Technical Reports Server (NTRS)

Hess, R. A.

1978-01-01

A dual-loop model of the human controller in single-axis compensatory tracking tasks is introduced. This model possesses an inner-loop closure that involves feeding back that portion of controlled element output rate that is due to control activity. A novel feature of the model is the explicit appearance of the human's internal representation of the manipulator-controlled element dynamics in the inner loop. The sensor inputs to the human controller are assumed to be system error and control force. The former can be sensed via visual, aural, or tactile displays, whereas the latter is assumed to be sensed in kinesthetic fashion. A set of general adaptive characteristics for the model is hypothesized, including a method for selecting simplified internal models of the manipulator-controlled element dynamics. It is demonstrated that the model can produce controller describing functions that closely approximate those measured in four laboratory tracking tasks in which the controlled element dynamics vary considerably in terms of ease of control. An empirically derived expression for the normalized injected error remnant spectrum is introduced.

Modeling and control of a self-sensing polymer metal composite actuator

NASA Astrophysics Data System (ADS)

Nam, Doan Ngoc Chi; Ahn, Kyoung Kwan

2014-02-01

An ion polymer metal composite (IPMC) is an electro-active polymer (EAP) that bends in response to a small applied electrical field as a result of mobility of cations in the polymer network and vice versa. One drawback in the use of an IPMC is the sensing problem for such a small size actuator. The aim of this paper is to develop a physical model for a self-sensing IPMC actuator and to verify its applicability for practical position control. Firstly, ion dynamics inside a polymer membrane is investigated with an asymmetric solution in the presence of distributed surface resistance. Based on this analysis, a modified equivalent circuit and a simple configuration to realize the self-sensing IPMC actuator are proposed. Mathematical modelling and experimental evaluation indicate that the bending curvature can be obtained accurately using several feedback voltage signals along with the IPMC length. Finally, the controllability of the developed self-sensing IPMC actuator is investigated using a robust position control. Experimental results prove that the self-sensing characteristics can be applied in engineering control problems to provide a more convenient sensing method for IPMC actuating systems.

Research on the Sensing Performance of the Tuning Fork-Probe as a Micro Interaction Sensor

PubMed Central

Gao, Fengli; Li, Xide

2015-01-01

The shear force position system has been widely used in scanning near-field optical microscopy (SNOM) and recently extended into the force sensing area. The dynamic properties of a tuning fork (TF), the core component of this system, directly determine the sensing performance of the shear positioning system. Here, we combine experimental results and finite element method (FEM) analysis to investigate the dynamic behavior of the TF probe assembled structure (TF-probe). Results from experiments under varying atmospheric pressures illustrate that the oscillation amplitude of the TF-probe is linearly related to the quality factor, suggesting that decreasing the pressure will dramatically increase the quality factor. The results from FEM analysis reveal the influences of various parameters on the resonant performance of the TF-probe. We compared numerical results of the frequency spectrum with the experimental data collected by our recently developed laser Doppler vibrometer system. Then, we investigated the parameters affecting spatial resolution of the SNOM and the dynamic response of the TF-probe under longitudinal and transverse interactions. It is found that the interactions in transverse direction is much more sensitive than that in the longitudinal direction. Finally, the TF-probe was used to measure the friction coefficient of a silica–silica interface. PMID:26404310

Motion-compensated compressed sensing for dynamic contrast-enhanced MRI using regional spatiotemporal sparsity and region tracking: Block LOw-rank Sparsity with Motion-guidance (BLOSM)

PubMed Central

Chen, Xiao; Salerno, Michael; Yang, Yang; Epstein, Frederick H.

2014-01-01

Purpose Dynamic contrast-enhanced MRI of the heart is well-suited for acceleration with compressed sensing (CS) due to its spatiotemporal sparsity; however, respiratory motion can degrade sparsity and lead to image artifacts. We sought to develop a motion-compensated CS method for this application. Methods A new method, Block LOw-rank Sparsity with Motion-guidance (BLOSM), was developed to accelerate first-pass cardiac MRI, even in the presence of respiratory motion. This method divides the images into regions, tracks the regions through time, and applies matrix low-rank sparsity to the tracked regions. BLOSM was evaluated using computer simulations and first-pass cardiac datasets from human subjects. Using rate-4 acceleration, BLOSM was compared to other CS methods such as k-t SLR that employs matrix low-rank sparsity applied to the whole image dataset, with and without motion tracking, and to k-t FOCUSS with motion estimation and compensation that employs spatial and temporal-frequency sparsity. Results BLOSM was qualitatively shown to reduce respiratory artifact compared to other methods. Quantitatively, using root mean squared error and the structural similarity index, BLOSM was superior to other methods. Conclusion BLOSM, which exploits regional low rank structure and uses region tracking for motion compensation, provides improved image quality for CS-accelerated first-pass cardiac MRI. PMID:24243528

Self-Organized Air Tasking: Examining a Non-Hierarchical Model for Joint Air Operations

DTIC Science & Technology

2004-06-01

refers to systems with this dynamic incoherence as “strong sense of agency ” systems, and uses “weak sense of agency ” to refer to more predictable...agent-based systems, such as robotics or state-determined automata. Increasing the level of dynamic incoherency indicates a stronger sense of agency . This

Wavelength selection for portable noninvasive blood component measurement system based on spectral difference coefficient and dynamic spectrum

NASA Astrophysics Data System (ADS)

Feng, Ximeng; Li, Gang; Yu, Haixia; Wang, Shaohui; Yi, Xiaoqing; Lin, Ling

2018-03-01

Noninvasive blood component analysis by spectroscopy has been a hotspot in biomedical engineering in recent years. Dynamic spectrum provides an excellent idea for noninvasive blood component measurement, but studies have been limited to the application of broadband light sources and high-resolution spectroscopy instruments. In order to remove redundant information, a more effective wavelength selection method has been presented in this paper. In contrast to many common wavelength selection methods, this method is based on sensing mechanism which has a clear mechanism and can effectively avoid the noise from acquisition system. The spectral difference coefficient was theoretically proved to have a guiding significance for wavelength selection. After theoretical analysis, the multi-band spectral difference coefficient-wavelength selection method combining with the dynamic spectrum was proposed. An experimental analysis based on clinical trial data from 200 volunteers has been conducted to illustrate the effectiveness of this method. The extreme learning machine was used to develop the calibration models between the dynamic spectrum data and hemoglobin concentration. The experiment result shows that the prediction precision of hemoglobin concentration using multi-band spectral difference coefficient-wavelength selection method is higher compared with other methods.

Power electromagnetic strike machine for engineering-geological surveys

NASA Astrophysics Data System (ADS)

Usanov, K. M.; Volgin, A. V.; Chetverikov, E. A.; Kargin, V. A.; Moiseev, A. P.; Ivanova, Z. I.

2017-10-01

When implementing the processes of dynamic sensing of soils and pulsed nonexplosive seismic exploration, the most common and effective method is the strike one, which is provided by a variety of structure and parameters of pneumatic, hydraulic, electrical machines of strike action. The creation of compact portable strike machines which do not require transportation and use of mechanized means is important. A promising direction in the development of strike machines is the use of pulsed electromagnetic actuator characterized by relatively low energy consumption, relatively high specific performance and efficiency, and providing direct conversion of electrical energy into mechanical work of strike mass with linear movement trajectory. The results of these studies allowed establishing on the basis of linear electromagnetic motors the electromagnetic pulse machines with portable performance for dynamic sensing of soils and land seismic pulse of small depths.

Some insights on grassland health assessment based on remote sensing.

PubMed

Xu, Dandan; Guo, Xulin

2015-01-29

Grassland ecosystem is one of the largest ecosystems, which naturally occurs on all continents excluding Antarctica and provides both ecological and economic functions. The deterioration of natural grassland has been attracting many grassland researchers to monitor the grassland condition and dynamics for decades. Remote sensing techniques, which are advanced in dealing with the scale constraints of ecological research and provide temporal information, become a powerful approach of grassland ecosystem monitoring. So far, grassland health monitoring studies have mostly focused on different areas, for example, productivity evaluation, classification, vegetation dynamics, livestock carrying capacity, grazing intensity, natural disaster detecting, fire, climate change, coverage assessment and soil erosion. However, the grassland ecosystem is a complex system which is formed by soil, vegetation, wildlife and atmosphere. Thus, it is time to consider the grassland ecosystem as an entity synthetically and establish an integrated grassland health monitoring system to combine different aspects of the complex grassland ecosystem. In this review, current grassland health monitoring methods, including rangeland health assessment, ecosystem health assessment and grassland monitoring by remote sensing from different aspects, are discussed along with the future directions of grassland health assessment.

Some Insights on Grassland Health Assessment Based on Remote Sensing

PubMed Central

Xu, Dandan; Guo, Xulin

2015-01-01

Grassland ecosystem is one of the largest ecosystems, which naturally occurs on all continents excluding Antarctica and provides both ecological and economic functions. The deterioration of natural grassland has been attracting many grassland researchers to monitor the grassland condition and dynamics for decades. Remote sensing techniques, which are advanced in dealing with the scale constraints of ecological research and provide temporal information, become a powerful approach of grassland ecosystem monitoring. So far, grassland health monitoring studies have mostly focused on different areas, for example, productivity evaluation, classification, vegetation dynamics, livestock carrying capacity, grazing intensity, natural disaster detecting, fire, climate change, coverage assessment and soil erosion. However, the grassland ecosystem is a complex system which is formed by soil, vegetation, wildlife and atmosphere. Thus, it is time to consider the grassland ecosystem as an entity synthetically and establish an integrated grassland health monitoring system to combine different aspects of the complex grassland ecosystem. In this review, current grassland health monitoring methods, including rangeland health assessment, ecosystem health assessment and grassland monitoring by remote sensing from different aspects, are discussed along with the future directions of grassland health assessment. PMID:25643060

Local sharpening and subspace wavefront correction with predictive dynamic digital holography

NASA Astrophysics Data System (ADS)

Sulaiman, Sennan; Gibson, Steve

2017-09-01

Digital holography holds several advantages over conventional imaging and wavefront sensing, chief among these being significantly fewer and simpler optical components and the retrieval of complex field. Consequently, many imaging and sensing applications including microscopy and optical tweezing have turned to using digital holography. A significant obstacle for digital holography in real-time applications, such as wavefront sensing for high energy laser systems and high speed imaging for target racking, is the fact that digital holography is computationally intensive; it requires iterative virtual wavefront propagation and hill-climbing to optimize some sharpness criteria. It has been shown recently that minimum-variance wavefront prediction can be integrated with digital holography and image sharpening to reduce significantly large number of costly sharpening iterations required to achieve near-optimal wavefront correction. This paper demonstrates further gains in computational efficiency with localized sharpening in conjunction with predictive dynamic digital holography for real-time applications. The method optimizes sharpness of local regions in a detector plane by parallel independent wavefront correction on reduced-dimension subspaces of the complex field in a spectral plane.

Study of Influencing Factors of Dynamic Measurements Based on SnO2 Gas Sensor

PubMed Central

Sun, Yufeng; Huang, Xingjiu; Meng, Fanli; Liu, Jinhuai

2004-01-01

The gas-sensing behaviour based on a dynamic measurement method of a single SnO2 gas sensor was investigated by comparison with the static measurement. The influencing factors of nonlinear response such as modulation temperature, duty ratio, heating waveform (rectangular, sinusoidal, saw-tooth, pulse, etc.) were also studied. Experimental data showed that temperature was the most essential factor because the changes of frequency and heating waveform could result in the changes of temperature essentially.

A new method of inshore ship detection in high-resolution optical remote sensing images

NASA Astrophysics Data System (ADS)

Hu, Qifeng; Du, Yaling; Jiang, Yunqiu; Ming, Delie

2015-10-01

Ship as an important military target and water transportation, of which the detection has great significance. In the military field, the automatic detection of ships can be used to monitor ship dynamic in the harbor and maritime of enemy, and then analyze the enemy naval power. In civilian field, the automatic detection of ships can be used in monitoring transportation of harbor and illegal behaviors such as illegal fishing, smuggling and pirates, etc. In recent years, research of ship detection is mainly concentrated in three categories: forward-looking infrared images, downward-looking SAR image, and optical remote sensing images with sea background. Little research has been done into ship detection of optical remote sensing images with harbor background, as the gray-scale and texture features of ships are similar to the coast in high-resolution optical remote sensing images. In this paper, we put forward an effective harbor ship target detection method. First of all, in order to overcome the shortage of the traditional difference method in obtaining histogram valley as the segmentation threshold, we propose an iterative histogram valley segmentation method which separates the harbor and ships from the water quite well. Secondly, as landing ships in optical remote sensing images usually lead to discontinuous harbor edges, we use Hough Transform method to extract harbor edges. First, lines are detected by Hough Transform. Then, lines that have similar slope are connected into a new line, thus we access continuous harbor edges. Secondary segmentation on the result of the land-and-sea separation, we eventually get the ships. At last, we calculate the aspect ratio of the ROIs, thereby remove those targets which are not ship. The experiment results show that our method has good robustness and can tolerate a certain degree of noise and occlusion.

Emergence of the Green’s Functions from Noise and Passive Acoustic Remote Sensing of Ocean Dynamics

DTIC Science & Technology

2009-09-30

Acoustic Remote Sensing of Ocean Dynamics Oleg A. Godin CIRES/Univ. of Colorado and NOAA/OAR/Earth System Research Lab., R/PSD99, 325 Broadway...characterization of a time-varying ocean where ambient acoustic noise is utilized as a probing signal. • To develop a passive remote sensing technique for...inapplicable. 3. To quantify degradation of performance of passive remote sensing techniques due to ocean surface motion and other variations of underwater

Fluorogenic Ag+–Tetrazolate Aggregation Enables Efficient Fluorescent Biological Silver Staining

PubMed Central

Xie, Sheng; Wong, Alex Y. H.; Kwok, Ryan T. K.; Li, Ying; Su, Huifang; Lam, Jacky W. Y.

2018-01-01

Abstract Silver staining, which exploits the special bioaffinity and the chromogenic reduction of silver ions, is an indispensable visualization method in biology. It is a most popular method for in‐gel protein detection. However, it is limited by run‐to‐run variability, background staining, inability for protein quantification, and limited compatibility with mass spectroscopic (MS) analysis; limitations that are largely attributed to the tricky chromogenic visualization. Herein, we reported a novel water‐soluble fluorogenic Ag+ probe, the sensing mechanism of which is based on an aggregation‐induced emission (AIE) process driven by tetrazolate‐Ag+ interactions. The fluorogenic sensing can substitute the chromogenic reaction, leading to a new fluorescence silver staining method. This new staining method offers sensitive detection of total proteins in polyacrylamide gels with a broad linear dynamic range and robust operations that rival the silver nitrate stain and the best fluorescent stains. PMID:29575702

LCAMP: Location Constrained Approximate Message Passing for Compressed Sensing MRI

PubMed Central

Sung, Kyunghyun; Daniel, Bruce L; Hargreaves, Brian A

2016-01-01

Iterative thresholding methods have been extensively studied as faster alternatives to convex optimization methods for solving large-sized problems in compressed sensing. A novel iterative thresholding method called LCAMP (Location Constrained Approximate Message Passing) is presented for reducing computational complexity and improving reconstruction accuracy when a nonzero location (or sparse support) constraint can be obtained from view shared images. LCAMP modifies the existing approximate message passing algorithm by replacing the thresholding stage with a location constraint, which avoids adjusting regularization parameters or thresholding levels. This work is first compared with other conventional reconstruction methods using random 1D signals and then applied to dynamic contrast-enhanced breast MRI to demonstrate the excellent reconstruction accuracy (less than 2% absolute difference) and low computation time (5 - 10 seconds using Matlab) with highly undersampled 3D data (244 × 128 × 48; overall reduction factor = 10). PMID:23042658

A Portable Dynamic Laser Speckle System for Sensing Long-Term Changes Caused by Treatments in Painting Conservation

PubMed Central

Pérez, Alberto J.; Braga, Roberto; Perles, Ángel; Pérez–Marín, Eva; García-Diego, Fernando J.

2018-01-01

Dynamic laser speckle (DLS) is used as a reliable sensor of activity for all types of materials. Traditional applications are based on high-rate captures (usually greater than 10 frames-per-second, fps). Even for drying processes in conservation treatments, where there is a high level of activity in the first moments after the application and slower activity after some minutes or hours, the process is based on the acquisition of images at a time rate that is the same in moments of high and low activity. In this work, we present an alternative approach to track the drying process of protective layers and other painting conservation processes that take a long time to reduce their levels of activity. We illuminate, using three different wavelength lasers, a temporary protector (cyclododecane) and a varnish, and monitor them using a low fps rate during long-term drying. The results are compared to the traditional method. This work also presents a monitoring method that uses portable equipment. The results present the feasibility of using the portable device and show the improved sensitivity of the dynamic laser speckle when sensing the long-term process for drying cyclododecane and varnish in conservation. PMID:29324692

A new real-time method for investigation of affinity properties and binding kinetics of magnetic nanoparticles

NASA Astrophysics Data System (ADS)

Orlov, Alexey V.; Nikitin, Maxim P.; Bragina, Vera A.; Znoyko, Sergey L.; Zaikina, Marina N.; Ksenevich, Tatiana I.; Gorshkov, Boris G.; Nikitin, Petr I.

2015-04-01

A method for quantitative investigation of affinity constants of receptors immobilized on magnetic nanoparticles (MP) is developed based on spectral correlation interferometry (SCI). The SCI records with a picometer resolution the thickness changes of a layer of molecules or nanoparticles due to a biochemical reaction on a cover slip, averaged over the sensing area. The method is compatible with other types of sensing surfaces employed in biosensing. The measured values of kinetic association constants of magnetic nanoparticles are 4 orders of magnitude higher than those of molecular antibody association with antigen. The developed method also suggests highly sensitive detection of antigens in a wide dynamic range. The limit of detection of 92 pg/ml has been demonstrated for prostate-specific antigen (PSA) with 50-nm MP employed as labels, which produce 3-order amplification of the SCI signals. The calibration curve features high sensitivity (slope) of 3-fold signal raise per 10-fold increase of PSA concentration within 4-order dynamic range, which is an attractive compromise for precise quantitative and highly sensitive immunoassay. The proposed biosensing technique offers inexpensive disposable sensor chips of cover slips and represents an economically sound alternative to traditional immunoassays for disease diagnostics, detection of pathogens in food and environmental monitoring.

Maximum-likelihood methods in wavefront sensing: stochastic models and likelihood functions

PubMed Central

Barrett, Harrison H.; Dainty, Christopher; Lara, David

2008-01-01

Maximum-likelihood (ML) estimation in wavefront sensing requires careful attention to all noise sources and all factors that influence the sensor data. We present detailed probability density functions for the output of the image detector in a wavefront sensor, conditional not only on wavefront parameters but also on various nuisance parameters. Practical ways of dealing with nuisance parameters are described, and final expressions for likelihoods and Fisher information matrices are derived. The theory is illustrated by discussing Shack–Hartmann sensors, and computational requirements are discussed. Simulation results show that ML estimation can significantly increase the dynamic range of a Shack–Hartmann sensor with four detectors and that it can reduce the residual wavefront error when compared with traditional methods. PMID:17206255

A theoretical framework for the study of compression sensing in ionic polymer metal composites

NASA Astrophysics Data System (ADS)

Volpini, Valentina; Bardella, Lorenzo; Rodella, Andrea; Cha, Youngsu; Porfiri, Maurizio

2017-04-01

Ionic Polymer Metal Composites (IPMCs) are electro-responsive materials for sensing and actuation, consisting of an ion-exchange polymeric membrane with ionized units, plated within noble metal electrodes. In this work, we investigate the sensing response of IPMCs that are subject to a through-the-thickness compression, by specializing the continuum model introduced by Cha and Porfiri,1 to this one-dimensional problem. This model modifies the classical Poisson-Nernst-Plank system governing the electrochemistry in the absence of mechanical effects, by accounting for finite deformations underlying the actuation and sensing processes. With the aim of accurately describing the IPMC dynamic compressive behavior, we introduce a spatial asymmetry in the properties of the membrane, which must be accounted for to trigger a sensing response. Then, we determine an analytical solution by applying the singular perturbation theory, and in particular the method of matched asymptotic expansions. This solution shows a good agreement with experimental findings reported in literature.

The role of satellite remote sensing in structured ecosystem risk assessments.

PubMed

Murray, Nicholas J; Keith, David A; Bland, Lucie M; Ferrari, Renata; Lyons, Mitchell B; Lucas, Richard; Pettorelli, Nathalie; Nicholson, Emily

2018-04-01

The current set of global conservation targets requires methods for monitoring the changing status of ecosystems. Protocols for ecosystem risk assessment are uniquely suited to this task, providing objective syntheses of a wide range of data to estimate the likelihood of ecosystem collapse. Satellite remote sensing can deliver ecologically relevant, long-term datasets suitable for analysing changes in ecosystem area, structure and function at temporal and spatial scales relevant to risk assessment protocols. However, there is considerable uncertainty about how to select and effectively utilise remotely sensed variables for risk assessment. Here, we review the use of satellite remote sensing for assessing spatial and functional changes of ecosystems, with the aim of providing guidance on the use of these data in ecosystem risk assessment. We suggest that decisions on the use of satellite remote sensing should be made a priori and deductively with the assistance of conceptual ecosystem models that identify the primary indicators representing the dynamics of a focal ecosystem. Copyright © 2017 Elsevier B.V. All rights reserved.

Dynamic force signal processing system of a robot manipulator

NASA Technical Reports Server (NTRS)

Uchiyama, M.; Kitagaki, K.; Hakomori, K.

1987-01-01

If dynamic noises such as those caused by the inertia forces of the hand can be eliminated from the signal of the force sensor installed on the wrist of the robot manipulator and if the necessary information of the external force can be detected with high sensitivity and high accuracy, a fine force feedback control for robots used in high speed and various fields will be possible. As the dynamic force sensing system, an external force estimate method with the extended Kalman filter is suggested and simulations and tests for a one axis force were performed. Later a dynamic signal processing system of six axes was composed and tested. The results are presented.

Sparse dynamical Boltzmann machine for reconstructing complex networks with binary dynamics

NASA Astrophysics Data System (ADS)

Chen, Yu-Zhong; Lai, Ying-Cheng

2018-03-01

Revealing the structure and dynamics of complex networked systems from observed data is a problem of current interest. Is it possible to develop a completely data-driven framework to decipher the network structure and different types of dynamical processes on complex networks? We develop a model named sparse dynamical Boltzmann machine (SDBM) as a structural estimator for complex networks that host binary dynamical processes. The SDBM attains its topology according to that of the original system and is capable of simulating the original binary dynamical process. We develop a fully automated method based on compressive sensing and a clustering algorithm to construct the SDBM. We demonstrate, for a variety of representative dynamical processes on model and real world complex networks, that the equivalent SDBM can recover the network structure of the original system and simulates its dynamical behavior with high precision.

Sparse dynamical Boltzmann machine for reconstructing complex networks with binary dynamics.

PubMed

Chen, Yu-Zhong; Lai, Ying-Cheng

2018-03-01

Revealing the structure and dynamics of complex networked systems from observed data is a problem of current interest. Is it possible to develop a completely data-driven framework to decipher the network structure and different types of dynamical processes on complex networks? We develop a model named sparse dynamical Boltzmann machine (SDBM) as a structural estimator for complex networks that host binary dynamical processes. The SDBM attains its topology according to that of the original system and is capable of simulating the original binary dynamical process. We develop a fully automated method based on compressive sensing and a clustering algorithm to construct the SDBM. We demonstrate, for a variety of representative dynamical processes on model and real world complex networks, that the equivalent SDBM can recover the network structure of the original system and simulates its dynamical behavior with high precision.

Reconstruction of network topology using status-time-series data

NASA Astrophysics Data System (ADS)

Pandey, Pradumn Kumar; Badarla, Venkataramana

2018-01-01

Uncovering the heterogeneous connection pattern of a networked system from the available status-time-series (STS) data of a dynamical process on the network is of great interest in network science and known as a reverse engineering problem. Dynamical processes on a network are affected by the structure of the network. The dependency between the diffusion dynamics and structure of the network can be utilized to retrieve the connection pattern from the diffusion data. Information of the network structure can help to devise the control of dynamics on the network. In this paper, we consider the problem of network reconstruction from the available status-time-series (STS) data using matrix analysis. The proposed method of network reconstruction from the STS data is tested successfully under susceptible-infected-susceptible (SIS) diffusion dynamics on real-world and computer-generated benchmark networks. High accuracy and efficiency of the proposed reconstruction procedure from the status-time-series data define the novelty of the method. Our proposed method outperforms compressed sensing theory (CST) based method of network reconstruction using STS data. Further, the same procedure of network reconstruction is applied to the weighted networks. The ordering of the edges in the weighted networks is identified with high accuracy.

Closing the water balance with cosmic-ray soil moisture measurements and assessing their relation to evapotranspiration in two semiarid watersheds

USDA-ARS?s Scientific Manuscript database

Soil moisture dynamics reflect the complex interactions of meteorological conditions with soil, vegetation and terrain properties. In this study, intermediate-scale soil moisture estimates from the cosmic-ray neutron sensing (CRNS) method are evaluated for two semiarid ecosystems in the southwestern...

Sampling the isothermal-isobaric ensemble by Langevin dynamics

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

Gao, Xingyu; Institute of Applied Physics and Computational Mathematics, Fenghao East Road 2, Beijing 100094; CAEP Software Center for High Performance Numerical Simulation, Huayuan Road 6, Beijing 100088

2016-03-28

We present a new method of conducting fully flexible-cell molecular dynamics simulation in isothermal-isobaric ensemble based on Langevin equations of motion. The stochastic coupling to all particle and cell degrees of freedoms is introduced in a correct way, in the sense that the stationary configurational distribution is proved to be consistent with that of the isothermal-isobaric ensemble. In order to apply the proposed method in computer simulations, a second order symmetric numerical integration scheme is developed by Trotter’s splitting of the single-step propagator. Moreover, a practical guide of choosing working parameters is suggested for user specified thermo- and baro-coupling timemore » scales. The method and software implementation are carefully validated by a numerical example.« less

Differential Equations Models to Study Quorum Sensing.

PubMed

Pérez-Velázquez, Judith; Hense, Burkhard A

2018-01-01

Mathematical models to study quorum sensing (QS) have become an important tool to explore all aspects of this type of bacterial communication. A wide spectrum of mathematical tools and methods such as dynamical systems, stochastics, and spatial models can be employed. In this chapter, we focus on giving an overview of models consisting of differential equations (DE), which can be used to describe changing quantities, for example, the dynamics of one or more signaling molecule in time and space, often in conjunction with bacterial growth dynamics. The chapter is divided into two sections: ordinary differential equations (ODE) and partial differential equations (PDE) models of QS. Rates of change are represented mathematically by derivatives, i.e., in terms of DE. ODE models allow describing changes in one independent variable, for example, time. PDE models can be used to follow changes in more than one independent variable, for example, time and space. Both types of models often consist of systems (i.e., more than one equation) of equations, such as equations for bacterial growth and autoinducer concentration dynamics. Almost from the onset, mathematical modeling of QS using differential equations has been an interdisciplinary endeavor and many of the works we revised here will be placed into their biological context.

Hyperspectral remote sensing of coral reefs: Deriving bathymetry, aquatic optical properties and a benthic spectral unmixing classification using AVIRIS data in the Hawaiian Islands

NASA Astrophysics Data System (ADS)

Goodman, James Ansell

My research focuses on the development and application of hyperspectral remote sensing as a valuable component in the assessment and management of coral ecosystems. Remote sensing provides an important quantitative ability to investigate the spatial dynamics of coral health and evaluate the impacts of local, regional and global change on this important natural resource. Furthermore, advances in detector capabilities and analysis methods, particularly with respect to hyperspectral remote sensing, are also increasing the accuracy and level of effectiveness of the resulting data products. Using imagery of Kaneohe Bay and French Frigate Shoals in the Hawaiian Islands, acquired in 2000 by NASA's Airborne Visible InfraRed Imaging Spectrometer (AVIRIS), I developed, applied and evaluated algorithms for analyzing coral reefs using hyperspectral remote sensing data. Research included developing methods for acquiring in situ underwater reflectance, collecting spectral measurements of the dominant bottom components in Kaneohe Bay, applying atmospheric correction and sunglint removal algorithms, employing a semianalytical optimization model to derive bathymetry and aquatic optical properties, and developing a linear unmixing approach for deriving bottom composition. Additionally, algorithm development focused on using fundamental scientific principles to facilitate the portability of methods to diverse geographic locations and across variable environmental conditions. Assessments of this methodology compared favorably with available field measurements and habitat information, and the overall analysis demonstrated the capacity to derive information on water properties, bathymetry and habitat composition. Thus, results illustrated a successful approach for extracting environmental information and habitat composition from a coral reef environment using hyperspectral remote sensing.

Monitoring Ecosystem Dynamics Ecosystem Using Hyperspectral Reflectance and a Robotic Tram System in Barrow Alaska

NASA Astrophysics Data System (ADS)

Goswami, S.; Gamon, J. A.; Tweedie, C. E.

2012-12-01

Understanding the future state of the earth system requires improved knowledge of ecosystem dynamics and long term observations of how ecosystem structures and functions are being impacted by global change. Improving remote sensing methods is essential for such advancement because satellite remote sensing is the only means by which landscape to continental-scale change can be observed. The Arctic appears to be impacted by climate change more than any other region on Earth. Arctic terrestrial ecosystems comprise only 6% of the land surface area on Earth yet contain an estimated 25% of global soil organic carbon, most of which is stored in permafrost. If projected increases in plant productivity do not offset forecast losses of soil carbon to the atmosphere as greenhouse gases, regional to global greenhouse warming could be enhanced. Soil moisture is an important control of land-atmosphere carbon exchange in arctic terrestrial ecosystems. However, few studies to date have examined using remote sensing, or developed remote sensing methods for observing the complex interplay between soil moisture and plant phenology and productivity in arctic landscapes. This study was motivated by this knowledge gap and addressed the following questions as a contribution to a large scale, multi investigator flooding and draining experiment funded by the National Science Foundation near Barrow, Alaska from 2005 - 2009. 1. How can optical remote sensing be used to monitor the surface hydrology of arctic landscapes? 2. What are the spatio-temporal dynamics of land-surface phenology (NDVI) in the study area and do hydrological treatment has any effect on inter-annual patterns? A new spectral index, the normalized difference surface water index (NDSWI) was developed and tested at multiple spatial and temporal scales. NDSWI uses the 460nm (blue) and 1000nm (IR) bands and was developed to capture surface hydrological dynamics in the study area using the robotic tram system. When applied to high spatial resolution satellite imagery, NDSWI was also able to capture changes in surface hydrology at the landscape scale. Interannual patterns of landsurface phenology (measured with the normalized difference vegetation index - NDVI) unexpectedly lacked marked differences under experimental conditions. Measurement of NDVI was, however, compromised when WTD was above ground level. NDVI and NDSWI were negatively correlated when WTD was above ground level, which held when scaled to MODIS imagery collected from satellite, suggesting that published findings showing a 'greening of the Arctic' may be related to a 'drying of the Arctic' in landscapes dominated by vegetated landscapes where WTD is close to ground level.

Using Remote Sensing, Weather, and Demographic Data to Create Risk Maps for Zika, Dengue, and Chikungunya in Brazil

NASA Astrophysics Data System (ADS)

Manore, C.; Conrad, J.; Del Valle, S.; Ziemann, A.; Fairchild, G.; Generous, E. N.

2017-12-01

Mosquito-borne diseases such as Zika, dengue, and chikungunya viruses have dynamics coupled to weather, ecology, human infrastructure, socio-economic demographics, and behavior. We use time-varying remote sensing and weather data, along with demographics and ecozones to predict risk through time for Zika, dengue, and chikungunya outbreaks in Brazil. We use distributed lag methods to quantify the lag between outbreaks and weather. Our statistical model indicates that the relationships between the variables are complex, but that quantifying risk is possible with the right data at appropriate spatio-temporal scales.

A Novel Physical Sensing Principle for Liquid Characterization Using Paper-Based Hygro-Mechanical Systems (PB-HMS).

PubMed

Perez-Cruz, Angel; Stiharu, Ion; Dominguez-Gonzalez, Aurelio

2017-07-20

In recent years paper-based microfluidic systems have emerged as versatile tools for developing sensors in different areas. In this work; we report a novel physical sensing principle for the characterization of liquids using a paper-based hygro-mechanical system (PB-HMS). The PB-HMS is formed by the interaction of liquid droplets and paper-based mini-structures such as cantilever beams. The proposed principle takes advantage of the hygroscopic properties of paper to produce hygro-mechanical motion. The dynamic response of the PB-HMS reveals information about the tested liquid that can be applied to characterize certain properties of liquids. A suggested method to characterize liquids by means of the proposed principle is introduced. The experimental results show the feasibility of such a method. It is expected that the proposed principle may be applied to sense properties of liquids in different applications where both disposability and portability are of extreme importance.

Organic light emitting board for dynamic interactive display

PubMed Central

Kim, Eui Hyuk; Cho, Sung Hwan; Lee, Ju Han; Jeong, Beomjin; Kim, Richard Hahnkee; Yu, Seunggun; Lee, Tae-Woo; Shim, Wooyoung; Park, Cheolmin

2017-01-01

Interactive displays involve the interfacing of a stimuli-responsive sensor with a visual human-readable response. Here, we describe a polymeric electroluminescence-based stimuli-responsive display method that simultaneously detects external stimuli and visualizes the stimulant object. This organic light-emitting board is capable of both sensing and direct visualization of a variety of conductive information. Simultaneous sensing and visualization of the conductive substance is achieved when the conductive object is coupled with the light emissive material layer on application of alternating current. A variety of conductive materials can be detected regardless of their work functions, and thus information written by a conductive pen is clearly visualized, as is a human fingerprint with natural conductivity. Furthermore, we demonstrate that integration of the organic light-emitting board with a fluidic channel readily allows for dynamic monitoring of metallic liquid flow through the channel, which may be suitable for biological detection and imaging applications. PMID:28406151

Organic light emitting board for dynamic interactive display

NASA Astrophysics Data System (ADS)

Kim, Eui Hyuk; Cho, Sung Hwan; Lee, Ju Han; Jeong, Beomjin; Kim, Richard Hahnkee; Yu, Seunggun; Lee, Tae-Woo; Shim, Wooyoung; Park, Cheolmin

2017-04-01

Interactive displays involve the interfacing of a stimuli-responsive sensor with a visual human-readable response. Here, we describe a polymeric electroluminescence-based stimuli-responsive display method that simultaneously detects external stimuli and visualizes the stimulant object. This organic light-emitting board is capable of both sensing and direct visualization of a variety of conductive information. Simultaneous sensing and visualization of the conductive substance is achieved when the conductive object is coupled with the light emissive material layer on application of alternating current. A variety of conductive materials can be detected regardless of their work functions, and thus information written by a conductive pen is clearly visualized, as is a human fingerprint with natural conductivity. Furthermore, we demonstrate that integration of the organic light-emitting board with a fluidic channel readily allows for dynamic monitoring of metallic liquid flow through the channel, which may be suitable for biological detection and imaging applications.

XD-GRASP: Golden-Angle Radial MRI with Reconstruction of Extra Motion-State Dimensions Using Compressed Sensing

PubMed Central

Feng, Li; Axel, Leon; Chandarana, Hersh; Block, Kai Tobias; Sodickson, Daniel K.; Otazo, Ricardo

2015-01-01

Purpose To develop a novel framework for free-breathing MRI called XD-GRASP, which sorts dynamic data into extra motion-state dimensions using the self-navigation properties of radial imaging and reconstructs the multidimensional dataset using compressed sensing. Methods Radial k-space data are continuously acquired using the golden-angle sampling scheme and sorted into multiple motion-states based on respiratory and/or cardiac motion signals derived directly from the data. The resulting under-sampled multidimensional dataset is reconstructed using a compressed sensing approach that exploits sparsity along the new dynamic dimensions. The performance of XD-GRASP is demonstrated for free-breathing three-dimensional (3D) abdominal imaging, two-dimensional (2D) cardiac cine imaging and 3D dynamic contrast-enhanced (DCE) MRI of the liver, comparing against reconstructions without motion sorting in both healthy volunteers and patients. Results XD-GRASP separates respiratory motion from cardiac motion in cardiac imaging, and respiratory motion from contrast enhancement in liver DCE-MRI, which improves image quality and reduces motion-blurring artifacts. Conclusion XD-GRASP represents a new use of sparsity for motion compensation and a novel way to handle motions in the context of a continuous acquisition paradigm. Instead of removing or correcting motion, extra motion-state dimensions are reconstructed, which improves image quality and also offers new physiological information of potential clinical value. PMID:25809847

Integrated optical sensors for 2D spatial chemical mapping (Conference Presentation)

NASA Astrophysics Data System (ADS)

Flores, Raquel; Janeiro, Ricardo; Viegas, Jaime

2017-02-01

Sensors based on optical waveguides for chemical sensing have attracted increasing interest over the last two decades, fueled by potential applications in commercial lab-on-a-chip devices for medical and food safety industries. Even though the early studies were oriented for single-point detection, progress in device size reduction and device yield afforded by photonics foundries have opened the opportunity for distributed dynamic chemical sensing at the microscale. This will allow researchers to follow the dynamics of chemical species in field of microbiology, and microchemistry, with a complementary method to current technologies based on microfluorescence and hyperspectral imaging. The study of the chemical dynamics at the surface of photoelectrodes in water splitting cells are a good candidate to benefit from such optochemical sensing devices that includes a photonic integrated circuit (PIC) with multiple sensors for real-time detection and spatial mapping of chemical species. In this project, we present experimental results on a prototype integrated optical system for chemical mapping based on the interaction of cascaded resonant optical devices, spatially covered with chemically sensitive polymers and plasmon-enhanced nanostructured metal/metal-oxide claddings offering chemical selectivity in a pixelated surface. In order to achieve a compact footprint, the prototype is based in a silicon photonics platform. A discussion on the relative merits of a photonic platform based on large bandgap metal oxides and nitrides which have higher chemical resistance than silicon is also presented.

Chemical Remote Sensing ’Proof of Concept’,

DTIC Science & Technology

1981-03-31

A122 579 CHEMICAL REMOTE SENSING ;PROOF OF CONCEPT’(U) UTAH 1/I \\ STATE UNIV LOGAN ELECTRO-DYNAMICS LAB BARTSCHI ET AL. 31 MAR 81 SCIENTIFC-8...STANDARDS -I963-A AFGL-TR-81-021 2 CHEMICAL REMOTE SENSING "Proof of Concept" B.Y. Bartschi F. P. DelGreco M. Ahmadjian Electro-Dynamics Laboratories...Applications of remote sensing 2 2.2 Program Development 4 -O 3.1 Optical Layout 6 3.2 Block Diagram of Sensor System 7 3.3 Sensor Facility 10 3.4

Self-expressive Dictionary Learning for Dynamic 3D Reconstruction.

PubMed

Zheng, Enliang; Ji, Dinghuang; Dunn, Enrique; Frahm, Jan-Michael

2017-08-22

We target the problem of sparse 3D reconstruction of dynamic objects observed by multiple unsynchronized video cameras with unknown temporal overlap. To this end, we develop a framework to recover the unknown structure without sequencing information across video sequences. Our proposed compressed sensing framework poses the estimation of 3D structure as the problem of dictionary learning, where the dictionary is defined as an aggregation of the temporally varying 3D structures. Given the smooth motion of dynamic objects, we observe any element in the dictionary can be well approximated by a sparse linear combination of other elements in the same dictionary (i.e. self-expression). Our formulation optimizes a biconvex cost function that leverages a compressed sensing formulation and enforces both structural dependency coherence across video streams, as well as motion smoothness across estimates from common video sources. We further analyze the reconstructability of our approach under different capture scenarios, and its comparison and relation to existing methods. Experimental results on large amounts of synthetic data as well as real imagery demonstrate the effectiveness of our approach.

The Contact Dynamics method: A nonsmooth story

NASA Astrophysics Data System (ADS)

Dubois, Frédéric; Acary, Vincent; Jean, Michel

2018-03-01

When velocity jumps are occurring, the dynamics is said to be nonsmooth. For instance, in collections of contacting rigid bodies, jumps are caused by shocks and dry friction. Without compliance at the interface, contact laws are not only non-differentiable in the usual sense but also multi-valued. Modeling contacting bodies is of interest in order to understand the behavior of numerous mechanical systems such as flexible multi-body systems, granular materials or masonry. These granular materials behave puzzlingly either like a solid or a fluid and a description in the frame of classical continuous mechanics would be welcome though far to be satisfactory nowadays. Jean-Jacques Moreau greatly contributed to convex analysis, functions of bounded variations, differential measure theory, sweeping process theory, definitive mathematical tools to deal with nonsmooth dynamics. He converted all these underlying theoretical ideas into an original nonsmooth implicit numerical method called Contact Dynamics (CD); a robust and efficient method to simulate large collections of bodies with frictional contacts and impacts. The CD method offers a very interesting complementary alternative to the family of smoothed explicit numerical methods, often called Distinct Elements Method (DEM). In this paper developments and improvements of the CD method are presented together with a critical comparative review of advantages and drawbacks of both approaches. xml:lang="fr"

Modeling the dynamics of shape generation and sensing by proteins on lipid membranes

NASA Astrophysics Data System (ADS)

Walani, Nikhil; Arroyo, Marino

Lipid membranes are fluid surfaces with flexural resistance that interact with proteins to perform their function in a biological context. A set of these proteins are responsible for shaping the lipid membranes, or of sensing curvature. A large body of work has examined the curvature sensing and generation properties of these proteins. Even though such processes are fundamentally dynamical in cells and in in vitro reconstituted systems, theoretical and computational studies have largely focussed on equilibrium thermodynamics. In this work, we propose a theoretical framework based on Onsager's variational principle of irreversible thermodynamics that captures the dynamics of adsorption, diffusion, and shape generation or sensing of proteins on lipid surfaces. We acknowledge the funds from European Research Council CoG- 681434 to support this research.

3D Compressed Sensing for Highly Accelerated Hyperpolarized 13C MRSI With In Vivo Applications to Transgenic Mouse Models of Cancer

PubMed Central

Hu, Simon; Lustig, Michael; Balakrishnan, Asha; Larson, Peder E. Z.; Bok, Robert; Kurhanewicz, John; Nelson, Sarah J.; Goga, Andrei; Pauly, John M.; Vigneron, Daniel B.

2010-01-01

High polarization of nuclear spins in liquid state through hyperpolarized technology utilizing dynamic nuclear polarization has enabled the direct monitoring of 13C metabolites in vivo at a high signal-to-noise ratio. Acquisition time limitations due to T1 decay of the hyperpolarized signal require accelerated imaging methods, such as compressed sensing, for optimal speed and spatial coverage. In this paper, the design and testing of a new echo-planar 13C three-dimensional magnetic resonance spectroscopic imaging (MRSI) compressed sensing sequence is presented. The sequence provides up to a factor of 7.53 in acceleration with minimal reconstruction artifacts. The key to the design is employing x and y gradient blips during a fly-back readout to pseudorandomly undersample kf-kx-ky space. The design was validated in simulations and phantom experiments where the limits of undersampling and the effects of noise on the compressed sensing nonlinear reconstruction were tested. Finally, this new pulse sequence was applied in vivo in preclinical studies involving transgenic prostate cancer and transgenic liver cancer murine models to obtain much higher spatial and temporal resolution than possible with conventional echo-planar spectroscopic imaging methods. PMID:20017160

Global vegetation phenology from Moderate Resolution Imaging Spectroradiometer (MODIS): Evaluation of global patterns and comparison with in situ measurements

NASA Astrophysics Data System (ADS)

Zhang, Xiaoyang; Friedl, Mark A.; Schaaf, Crystal B.

2006-12-01

In the last two decades the availability of global remote sensing data sets has provided a new means of studying global patterns and dynamics in vegetation. The vast majority of previous work in this domain has used data from the Advanced Very High Resolution Radiometer, which until recently was the primary source of global land remote sensing data. In recent years, however, a number of new remote sensing data sources have become available that have significantly improved the capability of remote sensing to monitor global ecosystem dynamics. In this paper, we describe recent results using data from NASA's Moderate Resolution Imaging Spectroradiometer to study global vegetation phenology. Using a novel new method based on fitting piecewise logistic models to time series data from MODIS, key transition dates in the annual cycle(s) of vegetation growth can be estimated in an ecologically realistic fashion. Using this method we have produced global maps of seven phenological metrics at 1-km spatial resolution for all ecosystems exhibiting identifiable annual phenologies. These metrics include the date of year for (1) the onset of greenness increase (greenup), (2) the onset of greenness maximum (maturity), (3) the onset of greenness decrease (senescence), and (4) the onset of greenness minimum (dormancy). The three remaining metrics are the growing season minimum, maximum, and summation of the enhanced vegetation index derived from MODIS. Comparison of vegetation phenology retrieved from MODIS with in situ measurements shows that these metrics provide realistic estimates of the four transition dates identified above. More generally, the spatial distribution of phenological metrics estimated from MODIS data is qualitatively realistic, and exhibits strong correspondence with temperature patterns in mid- and high-latitude climates, with rainfall seasonality in seasonally dry climates, and with cropping patterns in agricultural areas.

Integrated Approach to Inform the New York City Water Supply System Coupling SAR Remote Sensing Observations and the SWAT Watershed Model

NASA Astrophysics Data System (ADS)

Tesser, D.; Hoang, L.; McDonald, K. C.

2017-12-01

Efforts to improve municipal water supply systems increasingly rely on an ability to elucidate variables that drive hydrologic dynamics within large watersheds. However, fundamental model variables such as precipitation, soil moisture, evapotranspiration, and soil freeze/thaw state remain difficult to measure empirically across large, heterogeneous watersheds. Satellite remote sensing presents a method to validate these spatially and temporally dynamic variables as well as better inform the watershed models that monitor the water supply for many of the planet's most populous urban centers. PALSAR 2 L-band, Sentinel 1 C-band, and SMAP L-band scenes covering the Cannonsville branch of the New York City (NYC) water supply watershed were obtained for the period of March 2015 - October 2017. The SAR data provides information on soil moisture, free/thaw state, seasonal surface inundation, and variable source areas within the study site. Integrating the remote sensing products with watershed model outputs and ground survey data improves the representation of related processes in the Soil and Water Assessment Tool (SWAT) utilized to monitor the NYC water supply. PALSAR 2 supports accurate mapping of the extent of variable source areas while Sentinel 1 presents a method to model the timing and magnitude of snowmelt runoff events. SMAP Active Radar soil moisture product directly validates SWAT outputs at the subbasin level. This blended approach verifies the distribution of soil wetness classes within the watershed that delineate Hydrologic Response Units (HRUs) in the modified SWAT-Hillslope. The research expands the ability to model the NYC water supply source beyond a subset of the watershed while also providing high resolution information across a larger spatial scale. The global availability of these remote sensing products provides a method to capture fundamental hydrology variables in regions where current modeling efforts and in situ data remain limited.

Near ground level sensing for spatial analysis of vegetation

NASA Technical Reports Server (NTRS)

Sauer, Tom; Rasure, John; Gage, Charlie

1991-01-01

Measured changes in vegetation indicate the dynamics of ecological processes and can identify the impacts from disturbances. Traditional methods of vegetation analysis tend to be slow because they are labor intensive; as a result, these methods are often confined to small local area measurements. Scientists need new algorithms and instruments that will allow them to efficiently study environmental dynamics across a range of different spatial scales. A new methodology that addresses this problem is presented. This methodology includes the acquisition, processing, and presentation of near ground level image data and its corresponding spatial characteristics. The systematic approach taken encompasses a feature extraction process, a supervised and unsupervised classification process, and a region labeling process yielding spatial information.

Tensor-based Dictionary Learning for Dynamic Tomographic Reconstruction

PubMed Central

Tan, Shengqi; Zhang, Yanbo; Wang, Ge; Mou, Xuanqin; Cao, Guohua; Wu, Zhifang; Yu, Hengyong

2015-01-01

In dynamic computed tomography (CT) reconstruction, the data acquisition speed limits the spatio-temporal resolution. Recently, compressed sensing theory has been instrumental in improving CT reconstruction from far few-view projections. In this paper, we present an adaptive method to train a tensor-based spatio-temporal dictionary for sparse representation of an image sequence during the reconstruction process. The correlations among atoms and across phases are considered to capture the characteristics of an object. The reconstruction problem is solved by the alternating direction method of multipliers. To recover fine or sharp structures such as edges, the nonlocal total variation is incorporated into the algorithmic framework. Preclinical examples including a sheep lung perfusion study and a dynamic mouse cardiac imaging demonstrate that the proposed approach outperforms the vectorized dictionary-based CT reconstruction in the case of few-view reconstruction. PMID:25779991

Extended FDD-WT method based on correcting the errors due to non-synchronous sensing of sensors

NASA Astrophysics Data System (ADS)

Tarinejad, Reza; Damadipour, Majid

2016-05-01

In this research, a combinational non-parametric method called frequency domain decomposition-wavelet transform (FDD-WT) that was recently presented by the authors, is extended for correction of the errors resulting from asynchronous sensing of sensors, in order to extend the application of the algorithm for different kinds of structures, especially for huge structures. Therefore, the analysis process is based on time-frequency domain decomposition and is performed with emphasis on correcting time delays between sensors. Time delay estimation (TDE) methods are investigated for their efficiency and accuracy for noisy environmental records and the Phase Transform - β (PHAT-β) technique was selected as an appropriate method to modify the operation of traditional FDD-WT in order to achieve the exact results. In this paper, a theoretical example (3DOF system) has been provided in order to indicate the non-synchronous sensing effects of the sensors on the modal parameters; moreover, the Pacoima dam subjected to 13 Jan 2001 earthquake excitation was selected as a case study. The modal parameters of the dam obtained from the extended FDD-WT method were compared with the output of the classical signal processing method, which is referred to as 4-Spectral method, as well as other literatures relating to the dynamic characteristics of Pacoima dam. The results comparison indicates that values are correct and reliable.

Method and apparatus for the control of fluid dynamic mixing in pulse combustors

DOEpatents

Bramlette, T.T.; Keller, J.O.

1992-06-02

In a method and apparatus for controlling total ignition delay time in a pulse combustor, and thus controlling the mixing characteristics of the combustion reactants and the combustion products in the combustor, the total ignition delay time is controlled by adjusting the inlet geometry of the inlet to the combustion chamber. The inlet geometry may be fixed or variable for controlling the mixing characteristics. A feedback loop may be employed to sense actual combustion characteristics, and, in response to the sensed combustion characteristics, the inlet geometry may be varied to obtain the total ignition delay time necessary to achieve the desired combustion characteristics. Various embodiments relate to the varying of the mass flow rate of reactants while holding the radius/velocity ratio constant. 10 figs.

Method and apparatus for the control of fluid dynamic mixing in pulse combustors

DOEpatents

Bramlette, T. Tazwell; Keller, Jay O.

1992-06-02

In a method and apparatus for controlling total ignition delay time in a pulse combustor, and thus controlling the mixing characteristics of the combustion reactants and the combustion products in the combustor, the total ignition delay time is controlled by adjusting the inlet geometry of the inlet to the combustion chamber. The inlet geometry may be fixed or variable for controlling the mixing characteristics. A feedback loop may be employed to sense actual combustion characteristics, and, in response to the sensed combustion characteristics, the inlet geometry may be varied to obtain the total ignition delay time necessary to achieve the desired combustion characteristics. Various embodiments relate to the varying of the mass flow rate of reactants while holding the radius/velocity ratio constant.

Remotely-sensed and in-situ observations of Greenland firn aquifers

NASA Astrophysics Data System (ADS)

Forster, R. R.; Miège, C.; Koenig, L.; Solomon, D. K.; Schmerr, N. C.; Miller, O. L.; Ligtenberg, S.; Montgomery, L. N.; Brucker, L.; Miller, J.; Legchenko, A.

2017-12-01

In 2011, prior to seasonal melt, our research team drilled into an unknown firn aquifer system in Southeast Greenland. Since 2013, we have conducted four field seasons, complemented with modeling and remote sensing to gain knowledge regarding firn aquifers and surrounding snow/firn/ice. We aim to provide a more complete picture of the system including formation conditions, controlling mechanisms, spatial and temporal changes, and connections with the larger ice sheet hydrologic system. This work summarizes remote sensing data since 1993 showing the spatial and temporal evolution of the aquifer extent. To complement the remote sensing and better characterize the firn aquifer in the field, we use a combination of three different geophysics methods. Ground penetrating radar provides us knowledge of the water table elevation and its variations, magnetic-resonance soundings give us the water volume held in the aquifer and the active seismic data allow us to locate the bottom of the aquifer. In addition, firn/ice-core stratigraphy suggests that the timing and evolution of the aquifer bottom is controlled by thermodynamics. Our compilation of remote sensing measurements point to a dynamic and expanding aquifer system. We found that firn aquifers have existed at least since 1993 (dataset start) in the high melt and high accumulation region of the South Eastern Greenland ice sheet. Firn aquifers are now growing toward the interior related to the warming air temperatures in the Arctic and more intense melt during summers. These remotely sensed observations and in-situ measurements are required to validate improved ice sheet mass balance models that incorporate firn aquifers. They are also needed to further investigate the potential of firn aquifer discharge to the glacier bed via crevasse hydrofracturing influencing ice dynamics.

Virtual sensors for active noise control in acoustic-structural coupled enclosures using structural sensing: robust virtual sensor design.

PubMed

Halim, Dunant; Cheng, Li; Su, Zhongqing

2011-03-01

The work was aimed to develop a robust virtual sensing design methodology for sensing and active control applications of vibro-acoustic systems. The proposed virtual sensor was designed to estimate a broadband acoustic interior sound pressure using structural sensors, with robustness against certain dynamic uncertainties occurring in an acoustic-structural coupled enclosure. A convex combination of Kalman sub-filters was used during the design, accommodating different sets of perturbed dynamic model of the vibro-acoustic enclosure. A minimax optimization problem was set up to determine an optimal convex combination of Kalman sub-filters, ensuring an optimal worst-case virtual sensing performance. The virtual sensing and active noise control performance was numerically investigated on a rectangular panel-cavity system. It was demonstrated that the proposed virtual sensor could accurately estimate the interior sound pressure, particularly the one dominated by cavity-controlled modes, by using a structural sensor. With such a virtual sensing technique, effective active noise control performance was also obtained even for the worst-case dynamics. © 2011 Acoustical Society of America

Prototype of Self-Sensing Magnetic Bearing for Liquid Nitrogen Pump

NASA Astrophysics Data System (ADS)

Eguchi, Seiji; Komori, Mochimitsu; Okuhata, Taro

Recently, pumps used in extremely low temperature such as 77K are found to be necessary. They are expected to use for rocket engines and hydrogen stations for fueled vehicles. Generally, conventional magnetic bearings do not work in the extremely low temperature. Therefore, we have studied magnitic bearings for these pumps. Self-sensing technique is tried to apply to magnetic bearings. If self-sensing magnetic bearings were made, we could apply the self-sensing magnetic bearing to liquid nitrogen pumps. In this paper, we propose a prototype self-sensing magnetic bearing and study the static and dynamic characteristics. The dynamic characteristics in the air and in liquid nitrogen are also discussed.

Dynamic Sensing Performance of a Point-Wise Fiber Bragg Grating Displacement Measurement System Integrated in an Active Structural Control System

PubMed Central

Chuang, Kuo-Chih; Liao, Heng-Tseng; Ma, Chien-Ching

2011-01-01

In this work, a fiber Bragg grating (FBG) sensing system which can measure the transient response of out-of-plane point-wise displacement responses is set up on a smart cantilever beam and the feasibility of its use as a feedback sensor in an active structural control system is studied experimentally. An FBG filter is employed in the proposed fiber sensing system to dynamically demodulate the responses obtained by the FBG displacement sensor with high sensitivity. For comparison, a laser Doppler vibrometer (LDV) is utilized simultaneously to verify displacement detection ability of the FBG sensing system. An optical full-field measurement technique called amplitude-fluctuation electronic speckle pattern interferometry (AF-ESPI) is used to provide full-field vibration mode shapes and resonant frequencies. To verify the dynamic demodulation performance of the FBG filter, a traditional FBG strain sensor calibrated with a strain gauge is first employed to measure the dynamic strain of impact-induced vibrations. Then, system identification of the smart cantilever beam is performed by FBG strain and displacement sensors. Finally, by employing a velocity feedback control algorithm, the feasibility of integrating the proposed FBG displacement sensing system in a collocated feedback system is investigated and excellent dynamic feedback performance is demonstrated. In conclusion, our experiments show that the FBG sensor is capable of performing dynamic displacement feedback and/or strain measurements with high sensitivity and resolution. PMID:22247683

Dynamical discrete/continuum linear response shells theory of solvation: convergence test for NH4+ and OH- ions in water solution using DFT and DFTB methods.

PubMed

de Lima, Guilherme Ferreira; Duarte, Hélio Anderson; Pliego, Josefredo R

2010-12-09

A new dynamical discrete/continuum solvation model was tested for NH(4)(+) and OH(-) ions in water solvent. The method is similar to continuum solvation models in a sense that the linear response approximation is used. However, different from pure continuum models, explicit solvent molecules are included in the inner shell, which allows adequate treatment of specific solute-solvent interactions present in the first solvation shell, the main drawback of continuum models. Molecular dynamics calculations coupled with SCC-DFTB method are used to generate the configurations of the solute in a box with 64 water molecules, while the interaction energies are calculated at the DFT level. We have tested the convergence of the method using a variable number of explicit water molecules and it was found that even a small number of waters (as low as 14) are able to produce converged values. Our results also point out that the Born model, often used for long-range correction, is not reliable and our method should be applied for more accurate calculations.

Studies and Application of Remote Sensing Retrieval Method of Soil Moisture Content in Land Parcel Units in Irrigation Area

NASA Astrophysics Data System (ADS)

Zhu, H.; Zhao, H. L.; Jiang, Y. Z.; Zang, W. B.

2018-05-01

Soil moisture is one of the important hydrological elements. Obtaining soil moisture accurately and effectively is of great significance for water resource management in irrigation area. During the process of soil moisture content retrieval with multiremote sensing data, multi- remote sensing data always brings multi-spatial scale problems which results in inconformity of soil moisture content retrieved by remote sensing in different spatial scale. In addition, agricultural water use management has suitable spatial scale of soil moisture information so as to satisfy the demands of dynamic management of water use and water demand in certain unit. We have proposed to use land parcel unit as the minimum unit to do soil moisture content research in agricultural water using area, according to soil characteristics, vegetation coverage characteristics in underlying layer, and hydrological characteristic into the basis of study unit division. We have proposed division method of land parcel units. Based on multi thermal infrared and near infrared remote sensing data, we calculate the ndvi and tvdi index and make a statistical model between the tvdi index and soil moisture of ground monitoring station. Then we move forward to study soil moisture remote sensing retrieval method on land parcel unit scale. And the method has been applied in Hetao irrigation area. Results show that compared with pixel scale the soil moisture content in land parcel unit scale has displayed stronger correlation with true value. Hence, remote sensing retrieval method of soil moisture content in land parcel unit scale has shown good applicability in Hetao irrigation area. We converted the research unit into the scale of land parcel unit. Using the land parcel units with unified crops and soil attributes as the research units more complies with the characteristics of agricultural water areas, avoids the problems such as decomposition of mixed pixels and excessive dependence on high-resolution data caused by the research units of pixels, and doesn't involve compromises in the spatial scale and simulating precision like the grid simulation. When the application needs are met, the production efficiency of products can also be improved at a certain degree.

Bayesian Tracking within a Feedback Sensing Environment: Estimating Interacting, Spatially Constrained Complex Dynamical Systems from Multiple Sources of Controllable Devices

DTIC Science & Technology

2014-07-25

composition of simple temporal structures to a speaker diarization task with the goal of segmenting conference audio in the presence of an unknown number of...application domains including neuroimaging, diverse document selection, speaker diarization , stock modeling, and target tracking. We detail each of...recall performance than competing methods in a task of discovering articles preferred by the user • a gold-standard speaker diarization method, as

Potential for using remote sensing to estimate carbon fluxes across northern peatlands - A review.

PubMed

Lees, K J; Quaife, T; Artz, R R E; Khomik, M; Clark, J M

2018-02-15

Peatlands store large amounts of terrestrial carbon and any changes to their carbon balance could cause large changes in the greenhouse gas (GHG) balance of the Earth's atmosphere. There is still much uncertainty about how the GHG dynamics of peatlands are affected by climate and land use change. Current field-based methods of estimating annual carbon exchange between peatlands and the atmosphere include flux chambers and eddy covariance towers. However, remote sensing has several advantages over these traditional approaches in terms of cost, spatial coverage and accessibility to remote locations. In this paper, we outline the basic principles of using remote sensing to estimate ecosystem carbon fluxes and explain the range of satellite data available for such estimations, considering the indices and models developed to make use of the data. Past studies, which have used remote sensing data in comparison with ground-based calculations of carbon fluxes over Northern peatland landscapes, are discussed, as well as the challenges of working with remote sensing on peatlands. Finally, we suggest areas in need of future work on this topic. We conclude that the application of remote sensing to models of carbon fluxes is a viable research method over Northern peatlands but further work is needed to develop more comprehensive carbon cycle models and to improve the long-term reliability of models, particularly on peatland sites undergoing restoration. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Multiple-Octave-Spanning Vibration Sensing Based on Simultaneous Vector Demodulation of 499 Fizeau Interference Signals from Identical Ultra-Weak Fiber Bragg Gratings Over 2.5 km.

PubMed

Li, Yi; Qian, Li; Zhou, Ciming; Fan, Dian; Xu, Qiannan; Pang, Yandong; Chen, Xi; Tang, Jianguan

2018-01-12

Multi-point vibration sensing at the low frequency range of 0.5-100 Hz is of vital importance for applications such as seismic monitoring and underwater acoustic imaging. Location-resolved multi-point sensing using a single fiber and a single demodulation system can greatly reduce system deployment and maintenance costs. We propose and demonstrate the demodulation of a fiber-optic system consisting of 500 identical ultra-weak Fiber Bragg gratings (uwFBGs), capable of measuring the amplitude, frequency and phase of acoustic signals from 499 sensing fibers covering a total range of 2.5 km. For demonstration purposes, we arbitrarily chose six consecutive sensors and studied their performance in detail. Using a passive demodulation method, we interrogated the six sensors simultaneously, and achieved a high signal-to-noise ratio of 22.1 dB, excellent linearity, phase sensitivity of around 0.024 rad/Pa, and a dynamic range of about 38 dB. We demonstrated a frequency response flatness of <1.2 dB in the range of 0.5-100 Hz. Compared to the prior state-of-the-art demonstration using a similar method, we have increased the sensing range from 1 km to 2.5 km, and increased the frequency range from 0.4 octaves to 7.6 octaves, in addition to achieving sensing in the very challenging low-frequency range of 0.5-100 Hz.

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.

Determination of dynamic variations in the optical properties of graphene oxide in response to gas exposure based on thin-film interference.

PubMed

Tabassum, Shawana; Dong, Liang; Kumar, Ratnesh

2018-03-05

We present an effective yet simple approach to study the dynamic variations in optical properties (such as the refractive index (RI)) of graphene oxide (GO) when exposed to gases in the visible spectral region, using the thin-film interference method. The dynamic variations in the complex refractive index of GO in response to exposure to a gas is an important factor affecting the performance of GO-based gas sensors. In contrast to the conventional ellipsometry, this method alleviates the need of selecting a dispersion model from among a list of model choices, which is limiting if an applicable model is not known a priori. In addition, the method used is computationally simpler, and does not need to employ any functional approximations. Further advantage over ellipsometry is that no bulky optics is required, and as a result it can be easily integrated into the sensing system, thereby allowing the reliable, simple, and dynamic evaluation of the optical performance of any GO-based gas sensor. In addition, the derived values of the dynamically changing RI values of the GO layer obtained from the method we have employed are corroborated by comparing with the values obtained from ellipsometry.

A Photoactivated Gas Detector for Toluene Sensing at Room Temperature Based on New Coral-Like ZnO Nanostructure Arrays

PubMed Central

Yeh, Li-Ko; Luo, Jie-Chun; Chen, Min-Chun; Wu, Chih-Hung; Chen, Jian-Zhang; Cheng, I-Chun; Hsu, Cheng-Che; Tian, Wei-Cheng

2016-01-01

A photoactivated gas detector operated at room temperature was microfabricated using a simple hydrothermal method. We report that the photoactivated gas detector can detect toluene using a UV illumination of 2 μW/cm2. By ultraviolet (UV) illumination, gas detectors sense toluene at room temperature without heating. A significant enhancement of detector sensitivity is achieved because of the high surface-area-to-volume ratio of the morphology of the coral-like ZnO nanorods arrays (NRAs) and the increased number of photo-induced oxygen ions under UV illumination. The corresponding sensitivity (ΔR/R0) of the detector based on coral-like ZnO NRAs is enhanced by approximately 1022% compared to that of thin-film detectors. The proposed detector greatly extends the dynamic range of detection of metal-oxide-based detectors for gas sensing applications. We report the first-ever detection of toluene with a novel coral-like NRAs gas detector at room temperature. A sensing mechanism model is also proposed to explain the sensing responses of gas detectors based on coral-like ZnO NRAs. PMID:27809222

A Photoactivated Gas Detector for Toluene Sensing at Room Temperature Based on New Coral-Like ZnO Nanostructure Arrays.

PubMed

Yeh, Li-Ko; Luo, Jie-Chun; Chen, Min-Chun; Wu, Chih-Hung; Chen, Jian-Zhang; Cheng, I-Chun; Hsu, Cheng-Che; Tian, Wei-Cheng

2016-10-31

A photoactivated gas detector operated at room temperature was microfabricated using a simple hydrothermal method. We report that the photoactivated gas detector can detect toluene using a UV illumination of 2 μW/cm². By ultraviolet (UV) illumination, gas detectors sense toluene at room temperature without heating. A significant enhancement of detector sensitivity is achieved because of the high surface-area-to-volume ratio of the morphology of the coral-like ZnO nanorods arrays (NRAs) and the increased number of photo-induced oxygen ions under UV illumination. The corresponding sensitivity (ΔR/R₀) of the detector based on coral-like ZnO NRAs is enhanced by approximately 1022% compared to that of thin-film detectors. The proposed detector greatly extends the dynamic range of detection of metal-oxide-based detectors for gas sensing applications. We report the first-ever detection of toluene with a novel coral-like NRAs gas detector at room temperature. A sensing mechanism model is also proposed to explain the sensing responses of gas detectors based on coral-like ZnO NRAs.

Click chemistry-mediated cyclic cleavage of metal ion-dependent DNAzymes for amplified and colorimetric detection of human serum copper (II).

PubMed

Li, Daxiu; Xie, Jiaqing; Zhou, Wenjiao; Jiang, Bingying; Yuan, Ruo; Xiang, Yun

2017-11-01

The determination of the level of Cu 2+ plays important roles in disease diagnosis and environmental monitoring. By coupling Cu + -catalyzed click chemistry and metal ion-dependent DNAzyme cyclic amplification, we have developed a convenient and sensitive colorimetric sensing method for the detection of Cu 2+ in human serums. The target Cu 2+ can be reduced by ascorbate to form Cu + , which catalyzes the azide-alkyne cycloaddition between the azide- and alkyne-modified DNAs to form Mg 2+ -dependent DNAzymes. Subsequently, the Mg 2+ ions catalyze the cleavage of the hairpin DNA substrate sequences of the DNAzymes and trigger cyclic generation of a large number of free G-quadruplex sequences, which bind hemin to form the G-quadruplex/hemin artificial peroxidase to cause significant color transition of the sensing solution for sensitive colorimetric detection of Cu 2+ . This method shows a dynamic range of 5 to 500 nM and a detection limit of 2 nM for Cu 2+ detection. Besides, the level of Cu 2+ in human serums can also be determined by using this sensing approach. With the advantages of simplicity and high sensitivity, such sensing method thus holds great potential for on-site determination of Cu 2+ in different samples. Graphical abstract Sensitive colorimetric detection of copper (II) by coupling click chemistry with metal ion-dependentDNAzymes.

Effects of 4D-Var data assimilation using remote sensing precipitation products in a WRF over the complex Heihe River Basin

NASA Astrophysics Data System (ADS)

Pan, Xiaoduo; Li, Xin; Cheng, Guodong

2017-04-01

Traditionally, ground-based, in situ observations, remote sensing, and regional climate modeling, individually, cannot provide the high-quality precipitation data required for hydrological prediction, especially over complex terrain. Data assimilation techniques are often used to assimilate ground observations and remote sensing products into models for dynamic downscaling. In this study, the Weather Research and Forecasting (WRF) model was used to assimilate two satellite precipitation products (TRMM 3B42 and FY-2D) using the 4D-Var data assimilation method. The results show that the assimilation of remote sensing precipitation products can improve the initial WRF fields of humidity and temperature, thereby improving precipitation forecasting and decreasing the spin-up time. Hence, assimilating TRMM and FY-2D remote sensing precipitation products using WRF 4D-Var can be viewed as a positive step toward improving the accuracy and lead time of numerical weather prediction models, particularly for short-term weather forecasting. Future work is proposed to assimilate a suite of remote sensing data, e.g., the combination of precipitation and soil moisture data, into a WRF model to improve 7-8 day forecasts of precipitation and other atmospheric variables.

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

PubMed Central

Gao, Fengli; Li, Xide

2018-01-01

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

Assessment of soil moisture dynamics on an irrigated maize field using cosmic ray neutron sensing

NASA Astrophysics Data System (ADS)

Scheiffele, Lena Maria; Baroni, Gabriele; Oswald, Sascha E.

2015-04-01

In recent years cosmic ray neutron sensing (CRS) developed as a valuable, indirect and non-invasive method to estimate soil moisture at a scale of tens of hectares, covering the gap between point scale measurements and large scale remote sensing techniques. The method is particularly promising in cropped and irrigated fields where invasive installation of belowground measurement devices could conflict with the agricultural management. However, CRS is affected by all hydrogen pools in the measurement footprint and a fast growing biomass provides some challenges for the interpretation of the signal and application of the method for detecting soil moisture. For this aim, in this study a cosmic ray probe was installed on a field near Braunschweig (Germany) during one maize growing season (2014). The field was irrigated in stripes of 50 m width using sprinkler devices for a total of seven events. Three soil sampling campaigns were conducted throughout the growing season to assess the effect of different hydrogen pools on calibration results. Additionally, leaf area index and biomass measurements were collected to provide the relative contribution of the biomass on the CRS signal. Calibration results obtained with the different soil sampling campaigns showed some discrepancy well correlated with the biomass growth. However, after the calibration function was adjusted to account also for lattice water and soil organic carbon, thus representing an equivalent water content of the soil, the differences decreased. Soil moisture estimated with CRS responded well to precipitation and irrigation events, confirming also the effective footprint of the method (i.e., radius 300 m) and showing occurring water stress for the crop. Thus, the dynamics are in agreement with the soil moisture determined with point scale measurements but they are less affected by the heterogeneous moisture conditions within the field. For this reason, by applying a detailed calibration, CRS proves to be a valuable method for the application on agricultural sites to assess and improve irrigation management.

Topics in Modeling of Cochlear Dynamics: Computation, Response and Stability Analysis

NASA Astrophysics Data System (ADS)

Filo, Maurice G.

This thesis touches upon several topics in cochlear modeling. Throughout the literature, mathematical models of the cochlea vary according to the degree of biological realism to be incorporated. This thesis casts the cochlear model as a continuous space-time dynamical system using operator language. This framework encompasses a wider class of cochlear models and makes the dynamics more transparent and easier to analyze before applying any numerical method to discretize space. In fact, several numerical methods are investigated to study the computational efficiency of the finite dimensional realizations in space. Furthermore, we study the effects of the active gain perturbations on the stability of the linearized dynamics. The stability analysis is used to explain possible mechanisms underlying spontaneous otoacoustic emissions and tinnitus. Dynamic Mode Decomposition (DMD) is introduced as a useful tool to analyze the response of nonlinear cochlear models. Cochlear response features are illustrated using DMD which has the advantage of explicitly revealing the spatial modes of vibrations occurring in the Basilar Membrane (BM). Finally, we address the dynamic estimation problem of BM vibrations using Extended Kalman Filters (EKF). Due to the limitations of noninvasive sensing schemes, such algorithms are inevitable to estimate the dynamic behavior of a living cochlea.

Androgynous, Reconfigurable Closed Loop Feedback Controlled Low Impact Docking System With Load Sensing Electromagnetic Capture Ring

NASA Technical Reports Server (NTRS)

Lewis, James L. (Inventor); Carroll, Monty B. (Inventor); Morales, Ray H. (Inventor); Le, Thang D. (Inventor)

2002-01-01

The present invention relates to a fully androgynous, reconfigurable closed loop feedback controlled low impact docking system with load sensing electromagnetic capture ring. The docking system of the present invention preferably comprises two Docking- assemblies, each docking assembly comprising a load sensing ring having an outer face, one of more electromagnets, one or more load cells coupled to said load sensing ring. The docking assembly further comprises a plurality of actuator arms coupled to said load sensing ring and capable of dynamically adjusting the orientation of said load sensing ring and a reconfigurable closed loop control system capable of analyzing signals originating from said plurality of load cells and of outputting real time control for each of the actuators. The docking assembly of the present invention incorporates an active load sensing system to automatically dynamically adjust the load sensing ring during capture instead of requiring significant force to push and realign the ring.

Achieving Efficient Spectrum Usage in Passive and Active Sensing

NASA Astrophysics Data System (ADS)

Wang, Huaiyi

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

Revealing physical interaction networks from statistics of collective dynamics

PubMed Central

Nitzan, Mor; Casadiego, Jose; Timme, Marc

2017-01-01

Revealing physical interactions in complex systems from observed collective dynamics constitutes a fundamental inverse problem in science. Current reconstruction methods require access to a system’s model or dynamical data at a level of detail often not available. We exploit changes in invariant measures, in particular distributions of sampled states of the system in response to driving signals, and use compressed sensing to reveal physical interaction networks. Dynamical observations following driving suffice to infer physical connectivity even if they are temporally disordered, are acquired at large sampling intervals, and stem from different experiments. Testing various nonlinear dynamic processes emerging on artificial and real network topologies indicates high reconstruction quality for existence as well as type of interactions. These results advance our ability to reveal physical interaction networks in complex synthetic and natural systems. PMID:28246630

Monitoring vegetation phenology using MODIS

USGS Publications Warehouse

Zhang, Xiayong; Friedl, Mark A.; Schaaf, Crystal B.; Strahler, Alan H.; Hodges, John C.F.; Gao, Feng; Reed, Bradley C.; Huete, Alfredo

2003-01-01

Accurate measurements of regional to global scale vegetation dynamics (phenology) are required to improve models and understanding of inter-annual variability in terrestrial ecosystem carbon exchange and climate–biosphere interactions. Since the mid-1980s, satellite data have been used to study these processes. In this paper, a new methodology to monitor global vegetation phenology from time series of satellite data is presented. The method uses series of piecewise logistic functions, which are fit to remotely sensed vegetation index (VI) data, to represent intra-annual vegetation dynamics. Using this approach, transition dates for vegetation activity within annual time series of VI data can be determined from satellite data. The method allows vegetation dynamics to be monitored at large scales in a fashion that it is ecologically meaningful and does not require pre-smoothing of data or the use of user-defined thresholds. Preliminary results based on an annual time series of Moderate Resolution Imaging Spectroradiometer (MODIS) data for the northeastern United States demonstrate that the method is able to monitor vegetation phenology with good success.

Inverse dynamics of a 3 degree of freedom spatial flexible manipulator

NASA Technical Reports Server (NTRS)

Bayo, Eduardo; Serna, M.

1989-01-01

A technique is presented for solving the inverse dynamics and kinematics of 3 degree of freedom spatial flexible manipulator. The proposed method finds the joint torques necessary to produce a specified end effector motion. Since the inverse dynamic problem in elastic manipulators is closely coupled to the inverse kinematic problem, the solution of the first also renders the displacements and rotations at any point of the manipulator, including the joints. Furthermore the formulation is complete in the sense that it includes all the nonlinear terms due to the large rotation of the links. The Timoshenko beam theory is used to model the elastic characteristics, and the resulting equations of motion are discretized using the finite element method. An iterative solution scheme is proposed that relies on local linearization of the problem. The solution of each linearization is carried out in the frequency domain. The performance and capabilities of this technique are tested through simulation analysis. Results show the potential use of this method for the smooth motion control of space telerobots.

Family Dynamics and Personal Strengths among Dementia Caregivers in Argentina

PubMed Central

Elnasseh, Aaliah G.; Trujillo, Michael A.; Peralta, Silvina Victoria; Stolfi, Miriam E.; Morelli, Eliana; Perrin, Paul B.

2016-01-01

This study examined whether healthier family dynamics were associated with higher personal strengths of resilience, sense of coherence, and optimism among dementia caregivers in Argentina. Caregivers are usually required to assist individuals with dementia, and family members have typically fulfilled that role. Personal strengths such as resilience, sense of coherence, and optimism have been shown to protect caregivers from some of the negative experiences of providing care, though the family-related variables associated with these personal strengths are largely unknown. Hierarchical multiple regressions investigated the extent to which family dynamics variables are associated with each of the caregiver personal strengths after controlling for demographic and caregiver characteristics. A sample of 105 caregivers from Argentina completed a set of questionnaires during a neurologist visit. Family dynamics explained 32% of the variance in resilience and 39% of the variance in sense of coherence. Greater family empathy and decreased family problems were uniquely associated with higher resilience. Greater communication and decreased family problems were uniquely associated with higher sense of coherence. Optimism was not found to be significantly associated with family dynamics. These results suggest that caregiver intervention research focused on the family may help improve caregiver personal strengths in Argentina and other Latin American countries. PMID:27413574

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Integrating Eddy Covariance, Penman-Monteith and METRIC based Evapotranspiration estimates to generate high resolution space-time ET over the Brazos River Basin

NASA Astrophysics Data System (ADS)

Mbabazi, D.; Mohanty, B.; Gaur, N.

2017-12-01

Evapotranspiration (ET) is an important component of the water and energy balance and accounts for 60 -70% of precipitation losses. However, accurate estimates of ET are difficult to quantify at varying spatial and temporal scales. Eddy covariance methods estimate ET at high temporal resolutions but without capturing the spatial variation in ET within its footprint. On the other hand, remote sensing methods using Landsat imagery provide ET with high spatial resolution but low temporal resolution (16 days). In this study, we used both eddy covariance and remote sensing methods to generate high space-time resolution ET. Daily, monthly and seasonal ET estimates were obtained using the eddy covariance (EC) method, Penman-Monteith (PM) and Mapping Evapotranspiration with Internalized Calibration (METRIC) models to determine cotton and native prairie ET dynamics in the Brazos river basin characterized by varying hydro-climatic and geological gradients. Daily estimates of spatially distributed ET (30 m resolution) were generated using spatial autocorrelation and temporal interpolations between the EC flux variable footprints and METRIC ET for the 2016 and 2017 growing seasons. A comparison of the 2016 and 2017 preliminary daily ET estimates showed similar ET dynamics/trends among the EC, PM and METRIC methods, and 5-20% differences in seasonal ET estimates. This study will improve the spatial estimates of EC ET and temporal resolution of satellite derived ET thus providing better ET data for water use management.

Definition of spatial patterns of bark beetle Ips typographus (L.) outbreak spreading in Tatra Mountains (Central Europe), using GIS

Treesearch

Rastislav Jakus; Wojciech Grodzki; Marek Jezik; Marcin Jachym

2003-01-01

The spread of bark beetle outbreaks in the Tatra Mountains was explored by using both terrestrial and remote sensing techniques. Both approaches have proven to be useful for studying spatial patterns of bark beetle population dynamics. The terrestrial methods were applied on existing forestry databases. Vegetation change analysis (image differentiation), digital...

A wideband magnetoresistive sensor for monitoring dynamic fault slip in laboratory fault friction experiments

USGS Publications Warehouse

Kilgore, Brian D.

2017-01-01

A non-contact, wideband method of sensing dynamic fault slip in laboratory geophysical experiments employs an inexpensive magnetoresistive sensor, a small neodymium rare earth magnet, and user built application-specific wideband signal conditioning. The magnetoresistive sensor generates a voltage proportional to the changing angles of magnetic flux lines, generated by differential motion or rotation of the near-by magnet, through the sensor. The performance of an array of these sensors compares favorably to other conventional position sensing methods employed at multiple locations along a 2 m long × 0.4 m deep laboratory strike-slip fault. For these magnetoresistive sensors, the lack of resonance signals commonly encountered with cantilever-type position sensor mounting, the wide band response (DC to ≈ 100 kHz) that exceeds the capabilities of many traditional position sensors, and the small space required on the sample, make them attractive options for capturing high speed fault slip measurements in these laboratory experiments. An unanticipated observation of this study is the apparent sensitivity of this sensor to high frequency electomagnetic signals associated with fault rupture and (or) rupture propagation, which may offer new insights into the physics of earthquake faulting.

Relationship of various factors affecting the sustainable private forest management at Pajangan District, Special Regions Yogyakarta, Indonesia

NASA Astrophysics Data System (ADS)

Widayanto, B.; Karsidi, R.; Kusnandar; Sutrisno, J.

2018-03-01

Forests have a role and function in providing good atmosphere with stable oxygen content and affecting global climate stability. Good forest management will provide stable climatic conditions in global climate change. A good forest is managed to provide a sustainable environment condition. This study aims to analyze the relationship of various factors affecting the sustainability of private forests management. This research is a quantitative research with survey method and determination of sampling are was by purposive sampling. Sampling method using multiple stage cluster sampling with 60 samples. From the results it was found that the successful sustainable private forest management influenced by various factors, such as group dynamics, stakeholder support, community institutions, and farmer participation. The continuity of private forest management is determined by the fulfillment of economic, social and environmental dimensions. The most interesting finding is that the group dynamics conditions are very good, whereas the sense of togetherness among community is very strong under limited resources managing private forests. The sense of togetherness resulted creativity to diversify business and thus reduced the pressure in exploiting the forest. Some people think that managing the people's forest as a culture so that its existence can be more sustainable.

Analysis of terrestrial conditions and dynamics

NASA Technical Reports Server (NTRS)

Goward, S. N. (Principal Investigator)

1984-01-01

Land spectral reflectance properties for selected locations, including the Goddard Space Flight Center, the Wallops Flight Facility, a MLA test site in Cambridge, Maryland, and an acid test site in Burlington, Vermont, were measured. Methods to simulate the bidirectional reflectance properties of vegetated landscapes and a data base for spatial resolution were developed. North American vegetation patterns observed with the Advanced Very High Resolution Radiometer were assessed. Data and methods needed to model large-scale vegetation activity with remotely sensed observations and climate data were compiled.

A spectral-spatial-dynamic hierarchical Bayesian (SSD-HB) model for estimating soybean yield

NASA Astrophysics Data System (ADS)

Kazama, Yoriko; Kujirai, Toshihiro

2014-10-01

A method called a "spectral-spatial-dynamic hierarchical-Bayesian (SSD-HB) model," which can deal with many parameters (such as spectral and weather information all together) by reducing the occurrence of multicollinearity, is proposed. Experiments conducted on soybean yields in Brazil fields with a RapidEye satellite image indicate that the proposed SSD-HB model can predict soybean yield with a higher degree of accuracy than other estimation methods commonly used in remote-sensing applications. In the case of the SSD-HB model, the mean absolute error between estimated yield of the target area and actual yield is 0.28 t/ha, compared to 0.34 t/ha when conventional PLS regression was applied, showing the potential effectiveness of the proposed model.

Compressive sensing for single-shot two-dimensional coherent spectroscopy

NASA Astrophysics Data System (ADS)

Harel, E.; Spencer, A.; Spokoyny, B.

2017-02-01

In this work, we explore the use of compressive sensing for the rapid acquisition of two-dimensional optical spectra that encodes the electronic structure and ultrafast dynamics of condensed-phase molecular species. Specifically, we have developed a means to combine multiplexed single-element detection and single-shot and phase-resolved two-dimensional coherent spectroscopy. The method described, which we call Single Point Array Reconstruction by Spatial Encoding (SPARSE) eliminates the need for costly array detectors while speeding up acquisition by several orders of magnitude compared to scanning methods. Physical implementation of SPARSE is facilitated by combining spatiotemporal encoding of the nonlinear optical response and signal modulation by a high-speed digital micromirror device. We demonstrate the approach by investigating a well-characterized cyanine molecule and a photosynthetic pigment-protein complex. Hadamard and compressive sensing algorithms are demonstrated, with the latter achieving compression factors as high as ten. Both show good agreement with directly detected spectra. We envision a myriad of applications in nonlinear spectroscopy using SPARSE with broadband femtosecond light sources in so-far unexplored regions of the electromagnetic spectrum.

Optical dynamic range maximization for humidity sensing by controlling growth of zinc oxide nanorods

NASA Astrophysics Data System (ADS)

Yusof, Haziezol Helmi Mohd; Harun, Sulaiman Wadi; Dimyati, Kaharudin; Bora, Tanujjal; Mohammed, Waleed S.; Dutta, Joydeep

2018-07-01

An experimental study of the dynamic range maximization with Zinc Oxide (ZnO) nanorods coated glass substrates for humidity and vapor sensing is reported. Growth time of the nanorods and the length of the coated segments were controlled to study the differences between a reference environmental condition (normal humidity or dry condition) and water vapor concentrations. In order to achieve long dynamic range of detection with respect to nanorods coverage, several substrates with triangular patterns of ZnO nanostructures were fabricated by selective hydrothermal growth over different durations of time (5 h, 10 h and 15 h). It was found that maximum dynamic range for the humidity sensing occurs for the combination parameters of normalized length (Z) of 0.23 and normalized scattering coefficient (ζ) of 0.3. A reduction in transmittance by 38% at humidity levels of 80% with reference point as 50% humidity was observed. The results could be correlated to a first order approximation model that assumes uniform growth and the optimum operating conditions for humidity sensing device. This study provides an option to correlate ZnO growth conditions for different vapor sensing applications which can set a platform for compact sensors where modulation of light intensity is followed.

High spatial resolution three-dimensional mapping of vegetation spectral dynamics using computer vision

Treesearch

Jonathan P. Dandois; Erle C. Ellis

2013-01-01

High spatial resolution three-dimensional (3D) measurements of vegetation by remote sensing are advancing ecological research and environmental management. However, substantial economic and logistical costs limit this application, especially for observing phenological dynamics in ecosystem structure and spectral traits. Here we demonstrate a new aerial remote sensing...

Teachers' Preferences for Educational Planning: Dynamic Testing, Teaching Experience and Teachers' Sense of Efficacy

ERIC Educational Resources Information Center

Bosma, Tirza; Hessels, Marco G. P.; Resing, Wilma C. M.

2012-01-01

This study surveyed a sample of 188 elementary teachers with respect to their preference for information regarding educational planning, in particular information captured with dynamic testing procedures. The influence of teachers' experience and sense of efficacy on teachers' preferences was also investigated. Results indicated teachers'…

[Study on extraction method of Panax notoginseng plots in Wenshan of Yunnan province based on decision tree model].

PubMed

Shi, Ting-Ting; Zhang, Xiao-Bo; Guo, Lan-Ping; Huang, Lu-Qi

2017-11-01

The herbs used as the material for traditional Chinese medicine are always planted in the mountainous area where the natural environment is suitable. As the mountain terrain is complex and the distribution of planting plots is scattered, the traditional survey method is difficult to obtain accurate planting area. It is of great significance to provide decision support for the conservation and utilization of traditional Chinese medicine resources by studying the method of extraction of Chinese herbal medicine planting area based on remote sensing and realizing the dynamic monitoring and reserve estimation of Chinese herbal medicines. In this paper, taking the Panax notoginseng plots in Wenshan prefecture of Yunnan province as an example, the China-made GF-1multispectral remote sensing images with a 16 m×16 m resolution were obtained. Then, the time series that can reflect the difference of spectrum of P. notoginseng shed and the background objects were selected to the maximum extent, and the decision tree model of extraction the of P. notoginseng plots was constructed according to the spectral characteristics of the surface features. The results showed that the remote sensing classification method based on the decision tree model could extract P. notoginseng plots in the study area effectively. The method can provide technical support for extraction of P. notoginseng plots at county level. Copyright© by the Chinese Pharmaceutical Association.

Generation of high-dynamic range image from digital photo

NASA Astrophysics Data System (ADS)

Wang, Ying; Potemin, Igor S.; Zhdanov, Dmitry D.; Wang, Xu-yang; Cheng, Han

2016-10-01

A number of the modern applications such as medical imaging, remote sensing satellites imaging, virtual prototyping etc use the High Dynamic Range Image (HDRI). Generally to obtain HDRI from ordinary digital image the camera is calibrated. The article proposes the camera calibration method based on the clear sky as the standard light source and takes sky luminance from CIE sky model for the corresponding geographical coordinates and time. The article considers base algorithms for getting real luminance values from ordinary digital image and corresponding programmed implementation of the algorithms. Moreover, examples of HDRI reconstructed from ordinary images illustrate the article.

Measurement of unsteady airflow velocity at nozzle outlet

NASA Astrophysics Data System (ADS)

Pyszko, René; Machů, Mário

2017-09-01

The paper deals with a method of measuring and evaluating the cooling air flow velocity at the outlet of the flat nozzle for cooling a rolled steel product. The selected properties of the Prandtl and Pitot sensing tubes were measured and compared. A Pitot tube was used for operational measurements of unsteady dynamic pressure of the air flowing from nozzles to abtain the flow velocity. The article also discusses the effects of air temperature, pressure and relative air humidity on air density, as well as the influence of dynamic pressure filtering on the error of averaged velocity.

Sliding window prior data assisted compressed sensing for MRI tracking of lung tumors.

PubMed

Yip, Eugene; Yun, Jihyun; Wachowicz, Keith; Gabos, Zsolt; Rathee, Satyapal; Fallone, B G

2017-01-01

Hybrid magnetic resonance imaging and radiation therapy devices are capable of imaging in real-time to track intrafractional lung tumor motion during radiotherapy. Highly accelerated magnetic resonance (MR) imaging methods can potentially reduce system delay time and/or improves imaging spatial resolution, and provide flexibility in imaging parameters. Prior Data Assisted Compressed Sensing (PDACS) has previously been proposed as an acceleration method that combines the advantages of 2D compressed sensing and the KEYHOLE view-sharing technique. However, as PDACS relies on prior data acquired at the beginning of a dynamic imaging sequence, decline in image quality occurs for longer duration scans due to drifts in MR signal. Novel sliding window-based techniques for refreshing prior data are proposed as a solution to this problem. MR acceleration is performed by retrospective removal of data from the fully sampled sets. Six patients with lung tumors are scanned with a clinical 3 T MRI using a balanced steady-state free precession (bSSFP) sequence for 3 min at approximately 4 frames per second, for a total of 650 dynamics. A series of distinct pseudo-random patterns of partial k-space acquisition is generated such that, when combined with other dynamics within a sliding window of 100 dynamics, covers the entire k-space. The prior data in the sliding window are continuously refreshed to reduce the impact of MR signal drifts. We intended to demonstrate two different ways to utilize the sliding window data: a simple averaging method and a navigator-based method. These two sliding window methods are quantitatively compared against the original PDACS method using three metrics: artifact power, centroid displacement error, and Dice's coefficient. The study is repeated with pseudo 0.5 T images by adding complex, normally distributed noise with a standard deviation that reduces image SNR, relative to original 3 T images, by a factor of 6. Without sliding window implemented, PDACS-reconstructed dynamic datasets showed progressive increases in image artifact power as the 3 min scan progresses. With sliding windows implemented, this increase in artifact power is eliminated. Near the end of a 3 min scan at 3 T SNR and 5× acceleration, implementation of an averaging (navigator) sliding window method improves our metrics by the following ways: artifact power decreases from 0.065 without sliding window to 0.030 (0.031), centroid error decreases from 2.64 to 1.41 mm (1.28 mm), and Dice coefficient agreement increases from 0.860 to 0.912 (0.915). At pseudo 0.5 T SNR, the improvements in metrics are as follows: artifact power decreases from 0.110 without sliding window to 0.0897 (0.0985), centroid error decreases from 2.92 mm to 1.36 mm (1.32 mm), and Dice coefficient agreements increases from 0.851 to 0.894 (0.896). In this work we demonstrated the negative impact of slow changes in MR signal for longer duration PDACS dynamic scans, namely increases in image artifact power and reductions of tumor tracking accuracy. We have also demonstrated sliding window implementations (i.e., refreshing of prior data) of PDACS are effective solutions to this problem at both 3 T and simulated 0.5 T bSSFP images. © 2016 American Association of Physicists in Medicine.

Mitochondrial Dynamics Mediated by Mitofusin 1 Is Required for POMC Neuron Glucose-Sensing and Insulin Release Control.

PubMed

Ramírez, Sara; Gómez-Valadés, Alicia G; Schneeberger, Marc; Varela, Luis; Haddad-Tóvolli, Roberta; Altirriba, Jordi; Noguera, Eduard; Drougard, Anne; Flores-Martínez, Álvaro; Imbernón, Mónica; Chivite, Iñigo; Pozo, Macarena; Vidal-Itriago, Andrés; Garcia, Ainhoa; Cervantes, Sara; Gasa, Rosa; Nogueiras, Ruben; Gama-Pérez, Pau; Garcia-Roves, Pablo M; Cano, David A; Knauf, Claude; Servitja, Joan-Marc; Horvath, Tamas L; Gomis, Ramon; Zorzano, Antonio; Claret, Marc

2017-06-06

Proopiomelanocortin (POMC) neurons are critical sensors of nutrient availability implicated in energy balance and glucose metabolism control. However, the precise mechanisms underlying nutrient sensing in POMC neurons remain incompletely understood. We show that mitochondrial dynamics mediated by Mitofusin 1 (MFN1) in POMC neurons couple nutrient sensing with systemic glucose metabolism. Mice lacking MFN1 in POMC neurons exhibited defective mitochondrial architecture remodeling and attenuated hypothalamic gene expression programs during the fast-to-fed transition. This loss of mitochondrial flexibility in POMC neurons bidirectionally altered glucose sensing, causing abnormal glucose homeostasis due to defective insulin secretion by pancreatic β cells. Fed mice lacking MFN1 in POMC neurons displayed enhanced hypothalamic mitochondrial oxygen flux and reactive oxygen species generation. Central delivery of antioxidants was able to normalize the phenotype. Collectively, our data posit MFN1-mediated mitochondrial dynamics in POMC neurons as an intrinsic nutrient-sensing mechanism and unveil an unrecognized link between this subset of neurons and insulin release. Copyright © 2017 Elsevier Inc. All rights reserved.

Modeling Common-Sense Decisions

NASA Astrophysics Data System (ADS)

Zak, Michail

This paper presents a methodology for efficient synthesis of dynamical model simulating a common-sense decision making process. The approach is based upon the extension of the physics' First Principles that includes behavior of living systems. The new architecture consists of motor dynamics simulating actual behavior of the object, and mental dynamics representing evolution of the corresponding knowledge-base and incorporating it in the form of information flows into the motor dynamics. The autonomy of the decision making process is achieved by a feedback from mental to motor dynamics. This feedback replaces unavailable external information by an internal knowledgebase stored in the mental model in the form of probability distributions.

Distribution of chlorophyll and harmful algal blooms (HABs): A review on space based studies in the coastal environments of Chinese marginal seas

NASA Astrophysics Data System (ADS)

Wei, Guifeng; Tang, Danling; Wang, Sufen

Monitoring of spatial and temporal distribution of chlorophyll (Chl-a) concentrations in the aquatic milieu is always challenging and often interesting. However, the recent advancements in satellite digital data play a significant role in providing outstanding results for the marine environmental investigations. The present paper is aimed to review ‘remote sensing research in Chinese seas’ within the period of 24 years from 1978 to 2002. Owing to generalized distributional pattern, the Chl-a concentrations are recognized high towards northern Chinese seas than the southern. Moreover, the coastal waters, estuaries, and upwelling zones always exhibit relatively high Chl-a concentrations compared with offshore waters. On the basis of marine Chl-a estimates obtained from satellite and other field measured environmental parameters, we have further discussed on the applications of satellite remote sensing in the fields of harmful algal blooms (HABs), primary production and physical oceanographic currents of the regional seas. Concerned with studies of HABs, satellite remote sensing proved more advantageous than any other conventional methods for large-scale applications. Probably, it may be the only source of authentic information responsible for the evaluation of new research methodologies to detect HABs. At present, studies using remote sensing methods are mostly confined to observe algal bloom occurrences, hence, it is essential to coordinate the mechanism of marine ecological and oceanographic dynamic processes of HABs using satellite remote sensing data with in situ measurements of marine environmental parameters. The satellite remote sensing on marine environment and HABs is believed to have a great improvement with popular application of technology.

A Decision Mixture Model-Based Method for Inshore Ship Detection Using High-Resolution Remote Sensing Images

PubMed Central

Bi, Fukun; Chen, Jing; Zhuang, Yin; Bian, Mingming; Zhang, Qingjun

2017-01-01

With the rapid development of optical remote sensing satellites, ship detection and identification based on large-scale remote sensing images has become a significant maritime research topic. Compared with traditional ocean-going vessel detection, inshore ship detection has received increasing attention in harbor dynamic surveillance and maritime management. However, because the harbor environment is complex, gray information and texture features between docked ships and their connected dock regions are indistinguishable, most of the popular detection methods are limited by their calculation efficiency and detection accuracy. In this paper, a novel hierarchical method that combines an efficient candidate scanning strategy and an accurate candidate identification mixture model is presented for inshore ship detection in complex harbor areas. First, in the candidate region extraction phase, an omnidirectional intersected two-dimension scanning (OITDS) strategy is designed to rapidly extract candidate regions from the land-water segmented images. In the candidate region identification phase, a decision mixture model (DMM) is proposed to identify real ships from candidate objects. Specifically, to improve the robustness regarding the diversity of ships, a deformable part model (DPM) was employed to train a key part sub-model and a whole ship sub-model. Furthermore, to improve the identification accuracy, a surrounding correlation context sub-model is built. Finally, to increase the accuracy of candidate region identification, these three sub-models are integrated into the proposed DMM. Experiments were performed on numerous large-scale harbor remote sensing images, and the results showed that the proposed method has high detection accuracy and rapid computational efficiency. PMID:28640236

A Decision Mixture Model-Based Method for Inshore Ship Detection Using High-Resolution Remote Sensing Images.

PubMed

Bi, Fukun; Chen, Jing; Zhuang, Yin; Bian, Mingming; Zhang, Qingjun

2017-06-22

With the rapid development of optical remote sensing satellites, ship detection and identification based on large-scale remote sensing images has become a significant maritime research topic. Compared with traditional ocean-going vessel detection, inshore ship detection has received increasing attention in harbor dynamic surveillance and maritime management. However, because the harbor environment is complex, gray information and texture features between docked ships and their connected dock regions are indistinguishable, most of the popular detection methods are limited by their calculation efficiency and detection accuracy. In this paper, a novel hierarchical method that combines an efficient candidate scanning strategy and an accurate candidate identification mixture model is presented for inshore ship detection in complex harbor areas. First, in the candidate region extraction phase, an omnidirectional intersected two-dimension scanning (OITDS) strategy is designed to rapidly extract candidate regions from the land-water segmented images. In the candidate region identification phase, a decision mixture model (DMM) is proposed to identify real ships from candidate objects. Specifically, to improve the robustness regarding the diversity of ships, a deformable part model (DPM) was employed to train a key part sub-model and a whole ship sub-model. Furthermore, to improve the identification accuracy, a surrounding correlation context sub-model is built. Finally, to increase the accuracy of candidate region identification, these three sub-models are integrated into the proposed DMM. Experiments were performed on numerous large-scale harbor remote sensing images, and the results showed that the proposed method has high detection accuracy and rapid computational efficiency.

Into the environment of mosquito-borne disease: A spatial analysis of vector distribution using traditional and remotely sensed methods

NASA Astrophysics Data System (ADS)

Brown, Heidi E.

Spatially explicit information is increasingly available for infectious disease modeling. However, such information is reluctantly or inappropriately incorporated. My dissertation research uses spatially explicit data to assess relationships between landscape and mosquito species distribution and discusses challenges regarding accurate predictive risk modeling. The goal of my research is to use remotely sensed environmental information and spatial statistical methods to better understand mosquito-borne disease epidemiology for improvement of public health responses. In addition to reviewing the progress of spatial infectious disease modeling, I present four research projects. I begin by evaluating the biases in surveillance data and build up to predictive modeling of mosquito species presence. In the first study I explore how mosquito surveillance trap types influence estimations of mosquito populations. Then. I use county-based human surveillance data and landscape variables to identify risk factors for West Nile virus disease. The third study uses satellite-based vegetation indices to identify spatial variation among West Nile virus vectors in an urban area and relates the variability to virus transmission dynamics. Finally, I explore how information from three satellite sensors of differing spatial and spectral resolution can be used to identify and distinguish mosquito habitat across central Connecticut wetlands. Analyses presented here constitute improvements to the prediction of mosquito distribution and therefore identification of disease risk factors. Current methods for mosquito surveillance data collection are labor intensive and provide an extremely limited, incomplete picture of the species composition and abundance. Human surveillance data offers additional challenges with respect to reporting bias and resolution, but is nonetheless informative in identifying environmental risk factors and disease transmission dynamics. Remotely sensed imagery supports mosquito and human disease surveillance data by providing spatially explicit, line resolution information about environmental factors relevant to vector-borne disease processes. Together, surveillance and remotely sensed environmental data facilitate improved description and modeling of disease transmission. Remote sensing can be used to develop predictive maps of mosquito distribution in relation to disease risk. This has implications for increased accuracy of mosquito control efforts. The projects presented in this dissertation enhance current public health capacities by examining the applications of spatial modeling with respect to mosquito-borne disease.

PREDICT: Privacy and Security Enhancing Dynamic Information Monitoring

DTIC Science & Technology

2015-08-03

consisting of global server-side probabilistic assignment by an untrusted server using cloaked locations, followed by feedback-loop guided local...12], consisting of global server-side probabilistic assignment by an untrusted server using cloaked locations, followed by feedback-loop guided...these methods achieve high sensing coverage with low cost using cloaked locations [3]. In follow-on work, the issue of mobility is addressed. Task

Biology-Inspired Autonomous Control

DTIC Science & Technology

2011-08-31

from load sensing in a turbulent flow field with high levels of plant uncertainty and optical feedback latency. The results of this paper suggest... Mimicry of biological systems, in the form of precise mathematical or physical dynamical modeling, is yielding impressive insight into the underlying...processing and plants , the aerospace industry has been slow to accept adaptive control. In the past decade however, newer methods for design of adaptive

Monitoring post-wildfire vegetation response with remotely sensed time-series data in Spain, USA and Israel

Treesearch

Willem J.D. van Leeuwen; Grant M. Casady; Daniel G. Neary; Susana Bautista; Jose Antonio Alloza; Yohay Carmel; Lea Wittenberg; Dan Malkinson; Barron J. Orr

2010-01-01

Due to the challenges faced by resource managers in maintaining post-fire ecosystem health, there is a need for methods to assess the ecological consequences of disturbances. This research examines an approach for assessing changes in post-fire vegetation dynamics for sites in Spain, Israel and the USA that burned in 1998, 1999 and 2002 respectively. Moderate...

Dynamical class of a two-dimensional plasmonic Dirac system.

PubMed

Silva, Érica de Mello

2015-10-01

A current goal in plasmonic science and technology is to figure out how to manage the relaxational dynamics of surface plasmons in graphene since its damping constitutes a hinder for the realization of graphene-based plasmonic devices. In this sense we believe it might be of interest to enlarge the knowledge on the dynamical class of two-dimensional plasmonic Dirac systems. According to the recurrence relations method, different systems are said to be dynamically equivalent if they have identical relaxation functions at all times, and such commonality may lead to deep connections between seemingly unrelated physical systems. We employ the recurrence relations approach to obtain relaxation and memory functions of density fluctuations and show that a two-dimensional plasmonic Dirac system at long wavelength and zero temperature belongs to the same dynamical class of standard two-dimensional electron gas and classical harmonic oscillator chain with an impurity mass.

The Real-Time Monitoring Service Platform for Land Supervision Based on Cloud Integration

NASA Astrophysics Data System (ADS)

Sun, J.; Mao, M.; Xiang, H.; Wang, G.; Liang, Y.

2018-04-01

Remote sensing monitoring has become the important means for land and resources departments to strengthen supervision. Aiming at the problems of low monitoring frequency and poor data currency in current remote sensing monitoring, this paper researched and developed the cloud-integrated real-time monitoring service platform for land supervision which enhanced the monitoring frequency by acquiring the domestic satellite image data overall and accelerated the remote sensing image data processing efficiency by exploiting the intelligent dynamic processing technology of multi-source images. Through the pilot application in Jinan Bureau of State Land Supervision, it has been proved that the real-time monitoring technical method for land supervision is feasible. In addition, the functions of real-time monitoring and early warning are carried out on illegal land use, permanent basic farmland protection and boundary breakthrough in urban development. The application has achieved remarkable results.

The dynamic monitoring of warm-water discharge based on the airborne high-resolution thermal infrared remote sensing data

NASA Astrophysics Data System (ADS)

Shao, Honglan; Xie, Feng; Liu, Chengyu; Liu, Zhihui; Zhang, Changxing; Yang, Gui; Wang, Jianyu

2016-04-01

The cooling water discharged from the coastal plants flow into the sea continuously, whose temperature is higher than original sea surface temperature (SST). The fact will have non-negligible influence on the marine environment in and around where the plants site. Hence, it's significant to monitor the temporal and spatial variation of the warm-water discharge for the assessment of the effect of the plant on its surrounding marine environment. The paper describes an approach for the dynamic monitoring of the warm-water discharge of coastal plants based on the airborne high-resolution thermal infrared remote sensing technology. Firstly, the geometric correction was carried out for the thermal infrared remote sensing images acquired on the aircraft. Secondly, the atmospheric correction method was used to retrieve the sea surface temperature of the images. Thirdly, the temperature-rising districts caused by the warm-water discharge were extracted. Lastly, the temporal and spatial variations of the warm-water discharge were analyzed through the geographic information system (GIS) technology. The approach was applied to Qinshan nuclear power plant (NPP), in Zhejiang Province, China. In considering with the tide states, the diffusion, distribution and temperature-rising values of the warm-water discharged from the plant were calculated and analyzed, which are useful to the marine environment assessment.

Intercomparison of phenological transition dates derived from the PhenoCam Dataset V1.0 and MODIS satellite remote sensing.

PubMed

Richardson, Andrew D; Hufkens, Koen; Milliman, Tom; Frolking, Steve

2018-04-09

Phenology is a valuable diagnostic of ecosystem health, and has applications to environmental monitoring and management. Here, we conduct an intercomparison analysis using phenological transition dates derived from near-surface PhenoCam imagery and MODIS satellite remote sensing. We used approximately 600 site-years of data, from 128 camera sites covering a wide range of vegetation types and climate zones. During both "greenness rising" and "greenness falling" transition phases, we found generally good agreement between PhenoCam and MODIS transition dates for agricultural, deciduous forest, and grassland sites, provided that the vegetation in the camera field of view was representative of the broader landscape. The correlation between PhenoCam and MODIS transition dates was poor for evergreen forest sites. We discuss potential reasons (including sub-pixel spatial heterogeneity, flexibility of the transition date extraction method, vegetation index sensitivity in evergreen systems, and PhenoCam geolocation uncertainty) for varying agreement between time series of vegetation indices derived from PhenoCam and MODIS imagery. This analysis increases our confidence in the ability of satellite remote sensing to accurately characterize seasonal dynamics in a range of ecosystems, and provides a basis for interpreting those dynamics in the context of tangible phenological changes occurring on the ground.

Vibratory regime classification of infant phonation.

PubMed

Buder, Eugene H; Chorna, Lesya B; Oller, D Kimbrough; Robinson, Rebecca B

2008-09-01

Infant phonation is highly variable in many respects, including the basic vibratory patterns by which the vocal tissues create acoustic signals. Previous studies have identified the regular occurrence of nonmodal phonation types in normal infant phonation. The glottis is like many oscillating systems that, because of nonlinear relationships among the elements, may vibrate in ways representing the deterministic patterns classified theoretically within the mathematical framework of nonlinear dynamics. The infant's preverbal vocal explorations present such a variety of phonations that it may be possible to find effectively all the classes of vibration predicted by nonlinear dynamic theory. The current report defines acoustic criteria for an important subset of such vibratory regimes, and demonstrates that analysts can be trained to reliably use these criteria for a classification that includes all instances of infant phonation in the recorded corpora. The method is thus internally comprehensive in the sense that all phonations are classified, but it is not exhaustive in the sense that all vocal qualities are thereby represented. Using the methods thus developed, this study also demonstrates that the distributions of these phonation types vary significantly across sessions of recording in the first year of life, suggesting developmental changes. The method of regime classification is thus capable of tracking changes that may be indicative of maturation of the mechanism, the learning of categories of phonatory control, and the possibly varying use of vocalizations across social contexts.

An optical sensor for detecting the contact location of a gas-liquid interface on a body.

PubMed

Belden, Jesse; Jandron, Michael

2014-08-01

An optical sensor for detecting the dynamic contact location of a gas-liquid interface along the length of a body is described. The sensor is developed in the context of applications to supercavitating bodies requiring measurement of the dynamic cavity contact location; however, the sensing method is extendable to other applications as well. The optical principle of total internal reflection is exploited to detect changes in refractive index of the medium contacting the body at discrete locations along its length. The derived theoretical operation of the sensor predicts a signal attenuation of 18 dB when a sensed location changes from air-contacting to water-contacting. Theory also shows that spatial resolution (d) scales linearly with sensor length (L(s)) and a resolution of 0.01L(s) can be achieved. A prototype sensor is constructed from simple components and response characteristics are quantified for different ambient light conditions as well as partial wetting states. Three methods of sensor calibration are described and a signal processing framework is developed that allows for robust detection of the gas-liquid contact location. In a tank draining experiment, the prototype sensor resolves the water level with accuracy limited only by the spatial resolution, which is constrained by the experimental setup. A more representative experiment is performed in which the prototype sensor accurately measures the dynamic contact location of a gas cavity on a water tunnel wall.

Decomposed direct matrix inversion for fast non-cartesian SENSE reconstructions.

PubMed

Qian, Yongxian; Zhang, Zhenghui; Wang, Yi; Boada, Fernando E

2006-08-01

A new k-space direct matrix inversion (DMI) method is proposed here to accelerate non-Cartesian SENSE reconstructions. In this method a global k-space matrix equation is established on basic MRI principles, and the inverse of the global encoding matrix is found from a set of local matrix equations by taking advantage of the small extension of k-space coil maps. The DMI algorithm's efficiency is achieved by reloading the precalculated global inverse when the coil maps and trajectories remain unchanged, such as in dynamic studies. Phantom and human subject experiments were performed on a 1.5T scanner with a standard four-channel phased-array cardiac coil. Interleaved spiral trajectories were used to collect fully sampled and undersampled 3D raw data. The equivalence of the global k-space matrix equation to its image-space version, was verified via conjugate gradient (CG) iterative algorithms on a 2x undersampled phantom and numerical-model data sets. When applied to the 2x undersampled phantom and human-subject raw data, the decomposed DMI method produced images with small errors (< or = 3.9%) relative to the reference images obtained from the fully-sampled data, at a rate of 2 s per slice (excluding 4 min for precalculating the global inverse at an image size of 256 x 256). The DMI method may be useful for noise evaluations in parallel coil designs, dynamic MRI, and 3D sodium MRI with fixed coils and trajectories. Copyright 2006 Wiley-Liss, Inc.

A qualitative approach for recovering relative depths in dynamic scenes

NASA Technical Reports Server (NTRS)

Haynes, S. M.; Jain, R.

1987-01-01

This approach to dynamic scene analysis is a qualitative one. It computes relative depths using very general rules. The depths calculated are qualitative in the sense that the only information obtained is which object is in front of which others. The motion is qualitative in the sense that the only required motion data is whether objects are moving toward or away from the camera. Reasoning, which takes into account the temporal character of the data and the scene, is qualitative. This approach to dynamic scene analysis can tolerate imprecise data because in dynamic scenes the data are redundant.

Modelling and simulation of a dynamical system with the Atangana-Baleanu fractional derivative

NASA Astrophysics Data System (ADS)

Owolabi, Kolade M.

2018-01-01

In this paper, we model an ecological system consisting of a predator and two preys with the newly derived two-step fractional Adams-Bashforth method via the Atangana-Baleanu derivative in the Caputo sense. We analyze the dynamical system for correct choice of parameter values that are biologically meaningful. The local analysis of the main model is based on the application of qualitative theory for ordinary differential equations. By using the fixed point theorem idea, we establish the existence and uniqueness of the solutions. Convergence results of the new scheme are verified in both space and time. Dynamical wave phenomena of solutions are verified via some numerical results obtained for different values of the fractional index, which have some interesting ecological implications.

Development of an Algorithm for Satellite Remote Sensing of Sea and Lake Ice

NASA Astrophysics Data System (ADS)

Dorofy, Peter T.

Satellite remote sensing of snow and ice has a long history. The traditional method for many snow and ice detection algorithms has been the use of the Normalized Difference Snow Index (NDSI). This manuscript is composed of two parts. Chapter 1, Development of a Mid-Infrared Sea and Lake Ice Index (MISI) using the GOES Imager, discusses the desirability, development, and implementation of alternative index for an ice detection algorithm, application of the algorithm to the detection of lake ice, and qualitative validation against other ice mapping products; such as, the Ice Mapping System (IMS). Chapter 2, Application of Dynamic Threshold in a Lake Ice Detection Algorithm, continues with a discussion of the development of a method that considers the variable viewing and illumination geometry of observations throughout the day. The method is an alternative to Bidirectional Reflectance Distribution Function (BRDF) models. Evaluation of the performance of the algorithm is introduced by aggregating classified pixels within geometrical boundaries designated by IMS and obtaining sensitivity and specificity statistical measures.

Electric field feedback for Magneto(elasto)Electric magnetometer development

NASA Astrophysics Data System (ADS)

Yang, M.-T.; Zhuang, X.; Sing, M. Lam Chok; Dolabdjian, C.; Finkel, P.; Li, J.; Viehland, D.

2017-12-01

Magneto(elasto)Electric (ME) sensors based on magnetostrictive-piezoelectric composites have been investigated to evaluate their performances to sense a magnetic signal. Previous results have shown that the dielectric loss noise in the piezoelectric layer exhibits as the dominant intrinsic noise at low frequencies, which limits the sensor performances. Also, it has intrinsically no DC capability. To avoid a part of this limitation, modulation detection methods are evaluated through a frequency up-conversion technique [1-4]. Moreover, classical magnetic field feedback techniques can be used to increase the dynamic range, the sensing stability and the system linearity, too. In this paper, we propose a new method to feedback the system by using both the magneto-capacitance modulation and an electric field feedback technique. Our development shows the feasibility of the method and the results match with the theoretical description and material properties. Even if the present results are not totally satisfactory, they give the proof of concept and yield a way for the development of very low power magnetometers.

Remote sensing, hydrological modeling and in situ observations in snow cover research: A review

NASA Astrophysics Data System (ADS)

Dong, Chunyu

2018-06-01

Snow is an important component of the hydrological cycle. As a major part of the cryosphere, snow cover also represents a valuable terrestrial water resource. In the context of climate change, the dynamics of snow cover play a crucial role in rebalancing the global energy and water budgets. Remote sensing, hydrological modeling and in situ observations are three techniques frequently utilized for snow cover investigations. However, the uncertainties caused by systematic errors, scale gaps, and complicated snow physics, among other factors, limit the usability of these three approaches in snow studies. In this paper, an overview of the advantages, limitations and recent progress of the three methods is presented, and more effective ways to estimate snow cover properties are evaluated. The possibility of improving remotely sensed snow information using ground-based observations is discussed. As a rapidly growing source of volunteered geographic information (VGI), web-based geotagged photos have great potential to provide ground truth data for remotely sensed products and hydrological models and thus contribute to procedures for cloud removal, correction, validation, forcing and assimilation. Finally, this review proposes a synergistic framework for the future of snow cover research. This framework highlights the cross-scale integration of in situ and remotely sensed snow measurements and the assimilation of improved remote sensing data into hydrological models.

Assessment of Knee Proprioception in the Anterior Cruciate Ligament Injury Risk Position in Healthy Subjects: A Cross-sectional Study.

PubMed

Mir, Seyed Mohsen; Talebian, Saeed; Naseri, Nasrin; Hadian, Mohammad-Reza

2014-10-01

[Purpose] Knee joint proprioception combines sensory input from a variety of afferent receptors that encompasses the sensations of joint position and motion. Poor proprioception is one of the risk factors of anterior cruciate ligament injury. Most studies have favored testing knee joint position sense in the sagittal plane and non-weight-bearing position. One of the most common mechanisms of noncontact anterior cruciate ligament injury is dynamic knee valgus. No study has measured joint position sense in a manner relevant to the mechanism of injury. Therefore, the aim of this study was to measure knee joint position sense in the noncontact anterior cruciate ligament injury risk position and normal condition. [Subjects and Methods] Thirty healthy male athletes participated in the study. Joint position sense was evaluated by active reproduction of the anterior cruciate ligament injury risk position and normal condition. The dominant knees of subjects were tested. [Results] The results showed less accurate knee joint position sense in the noncontact anterior cruciate ligament injury risk position rather than the normal condition. [Conclusion] The poorer joint position sense in non-contact anterior cruciate ligament injury risk position compared with the normal condition may contribute to the increased incidence of anterior cruciate ligament injury.

Testing the limits of gradient sensing

PubMed Central

Lakhani, Vinal

2017-01-01

The ability to detect a chemical gradient is fundamental to many cellular processes. In multicellular organisms gradient sensing plays an important role in many physiological processes such as wound healing and development. Unicellular organisms use gradient sensing to move (chemotaxis) or grow (chemotropism) towards a favorable environment. Some cells are capable of detecting extremely shallow gradients, even in the presence of significant molecular-level noise. For example, yeast have been reported to detect pheromone gradients as shallow as 0.1 nM/μm. Noise reduction mechanisms, such as time-averaging and the internalization of pheromone molecules, have been proposed to explain how yeast cells filter fluctuations and detect shallow gradients. Here, we use a Particle-Based Reaction-Diffusion model of ligand-receptor dynamics to test the effectiveness of these mechanisms and to determine the limits of gradient sensing. In particular, we develop novel simulation methods for establishing chemical gradients that not only allow us to study gradient sensing under steady-state conditions, but also take into account transient effects as the gradient forms. Based on reported measurements of reaction rates, our results indicate neither time-averaging nor receptor endocytosis significantly improves the cell’s accuracy in detecting gradients over time scales associated with the initiation of polarized growth. Additionally, our results demonstrate the physical barrier of the cell membrane sharpens chemical gradients across the cell. While our studies are motivated by the mating response of yeast, we believe our results and simulation methods will find applications in many different contexts. PMID:28207738

Relative Orientation and Position Detections Based on an RGB-D Sensor and Dynamic Cooperation Strategies for Jumping Sensor Nodes Recycling

PubMed Central

Zhang, Jun; Yang, Xi; Song, Guang-Ming; Chen, Tian-Yuan; Zhang, Yong

2015-01-01

This paper presents relative orientation and position detection methods for jumping sensor nodes (JSNs) recycling. The methods are based on motion captures of the JSNs by an RGB-D sensor mounted on a carrier robot and the dynamic cooperation between the carrier and the JSNs. A disc-like label with two different colored sides is mounted on the top of the JSNs. The RGB-D sensor can detect the motion of the label to calculate the orientations and positions of the JSNs and the carrier relative to each other. After the orientations and positions have been detected, the JSNs jump into a cabin mounted on the carrier in dynamic cooperation with the carrier for recycling. The performances of the proposed methods are tested with a prototype system. The results show that the carrier can detect a JSN from up to 2 m away and sense its relative orientation and position successfully. The errors of the JSN’s orientation and position detections relative to the carrier could be reduced to the values smaller than 1° and 1 cm, respectively, by using the dynamic cooperation strategies. The proposed methods in this paper could also be used for other kinds of mobile sensor nodes and multi-robot systems. PMID:26393589

A Symbolic Dynamics Perspective of Conway’s Game of Life

NASA Astrophysics Data System (ADS)

Chen, Fangyue; Chen, Bo; Guan, Junbiao; Jin, Weifeng

An interesting question is whether the intrinsic complexity of the gliders in D-dimensional cellular automata could be quantitatively analyzed in rigorously mathematical sense. In this paper, by introducing the D-dimensional symbolic space, some fundamental dynamical properties of D-dimensional shift map are explored in a subtle way. The purpose of this article is to present an accurate characterization of complex symbolic dynamics of gliders in Conway’s game of life. A series of dynamical properties of gliders on their concrete subsystems are investigated by means of the directed graph representation and transition matrix. More specifically, the gliders here are topologically mixing and possess the positive topological entropy on their subsystems. Finally, it is worth mentioning that the method presented in this paper is also applicable to other gliders in different D dimensions.

Multiview 3D sensing and analysis for high quality point cloud reconstruction

NASA Astrophysics Data System (ADS)

Satnik, Andrej; Izquierdo, Ebroul; Orjesek, Richard

2018-04-01

Multiview 3D reconstruction techniques enable digital reconstruction of 3D objects from the real world by fusing different viewpoints of the same object into a single 3D representation. This process is by no means trivial and the acquisition of high quality point cloud representations of dynamic 3D objects is still an open problem. In this paper, an approach for high fidelity 3D point cloud generation using low cost 3D sensing hardware is presented. The proposed approach runs in an efficient low-cost hardware setting based on several Kinect v2 scanners connected to a single PC. It performs autocalibration and runs in real-time exploiting an efficient composition of several filtering methods including Radius Outlier Removal (ROR), Weighted Median filter (WM) and Weighted Inter-Frame Average filtering (WIFA). The performance of the proposed method has been demonstrated through efficient acquisition of dense 3D point clouds of moving objects.

High dynamic range charge measurements

DOEpatents

De Geronimo, Gianluigi

2012-09-04

A charge amplifier for use in radiation sensing includes an amplifier, at least one switch, and at least one capacitor. The switch selectively couples the input of the switch to one of at least two voltages. The capacitor is electrically coupled in series between the input of the amplifier and the input of the switch. The capacitor is electrically coupled to the input of the amplifier without a switch coupled therebetween. A method of measuring charge in radiation sensing includes selectively diverting charge from an input of an amplifier to an input of at least one capacitor by selectively coupling an output of the at least one capacitor to one of at least two voltages. The input of the at least one capacitor is operatively coupled to the input of the amplifier without a switch coupled therebetween. The method also includes calculating a total charge based on a sum of the amplified charge and the diverted charge.

Quasi-periodic concave microlens array for liquid refractive index sensing fabricated by femtosecond laser assisted with chemical etching.

PubMed

Zhang, F; Wang, C; Yin, K; Dong, X R; Song, Y X; Tian, Y X; Duan, J A

2018-02-05

In this study, a high-efficiency single-pulsed femtosecond laser assisted with chemical wet etching method has been proposed to obtain large-area concave microlens array (MLA). The quasi-periodic MLA consisting of about two million microlenses with tunable diameter and sag height by adjusting laser scanning speed and etching time is uniformly manufactured on fused silica and sapphire within 30 minutes. Moreover, the fabricated MLA behaves excellent optical focusing and imaging performance, which could be used to sense the change of the liquid refractive index (RI). In addition, it is demonstrated that small period and high RI of MLA could acquire high sensitivity and broad dynamic measurement range, respectively. Furthermore, the theoretical diffraction efficiency is calculated by the finite domain time difference (FDTD) method, which is in good agreement with the experimental results.

Spacecraft angular velocity estimation algorithm for star tracker based on optical flow techniques

NASA Astrophysics Data System (ADS)

Tang, Yujie; Li, Jian; Wang, Gangyi

2018-02-01

An integrated navigation system often uses the traditional gyro and star tracker for high precision navigation with the shortcomings of large volume, heavy weight and high-cost. With the development of autonomous navigation for deep space and small spacecraft, star tracker has been gradually used for attitude calculation and angular velocity measurement directly. At the same time, with the dynamic imaging requirements of remote sensing satellites and other imaging satellites, how to measure the angular velocity in the dynamic situation to improve the accuracy of the star tracker is the hotspot of future research. We propose the approach to measure angular rate with a nongyro and improve the dynamic performance of the star tracker. First, the star extraction algorithm based on morphology is used to extract the star region, and the stars in the two images are matched according to the method of angular distance voting. The calculation of the displacement of the star image is measured by the improved optical flow method. Finally, the triaxial angular velocity of the star tracker is calculated by the star vector using the least squares method. The method has the advantages of fast matching speed, strong antinoise ability, and good dynamic performance. The triaxial angular velocity of star tracker can be obtained accurately with these methods. So, the star tracker can achieve better tracking performance and dynamic attitude positioning accuracy to lay a good foundation for the wide application of various satellites and complex space missions.

Electron wavepacket dynamics in highly quasi-degenerate coupled electronic states: a theory for chemistry where the notion of adiabatic potential energy surface loses the sense.

PubMed

Yonehara, Takehiro; Takatsuka, Kazuo

2012-12-14

We develop a theory and the method of its application for chemical dynamics in systems, in which the adiabatic potential energy hyper-surfaces (PES) are densely quasi-degenerate to each other in a wide range of molecular geometry. Such adiabatic electronic states tend to couple each other through strong nonadiabatic interactions. Technically, therefore, it is often extremely hard to accurately single out the individual PES in those systems. Moreover, due to the mutual nonadiabatic couplings that may spread wide in space and due to the energy-time uncertainty relation, the notion of the isolated and well-defined potential energy surface should lose the sense. On the other hand, such dense electronic states should offer a very interesting molecular field in which chemical reactions to proceed in characteristic manners. However, to treat these systems, the standard theoretical framework of chemical reaction dynamics, which starts from the Born-Oppenheimer approximation and ends up with quantum nuclear wavepacket dynamics, is not very useful. We here explore this problem with our developed nonadiabatic electron wavepacket theory, which we call the phase-space averaging and natural branching (PSANB) method [T. Yonehara and K. Takatsuka, J. Chem. Phys. 129, 134109 (2008)], or branching-path representation, in which the packets are propagated in time along the non-Born-Oppenheimer branching paths. In this paper, after outlining the basic theory, we examine using a one-dimensional model how well the PSANB method works with such densely quasi-degenerate nonadiabatic systems. To do so, we compare the performance of PSANB with the full quantum mechanical results and those given by the fewest switches surface hopping (FSSH) method, which is known to be one of the most reliable and flexible methods to date. It turns out that the PSANB electron wavepacket approach actually yields very good results with far fewer initial sampling paths. Then we apply the electron wavepacket dynamics in path-branching representation and the so-called semiclassical Ehrenfest theory to a hydrogen molecule embedded in twelve membered boron cluster (B(12)) in excited states, which are densely quasi-degenerate due to the vacancy in 2p orbitals of boron atom [1s(2)2s(2)2p(1)]. Bond dissociation of the hydrogen molecule quickly takes place in the cluster and the resultant hydrogen atoms are squeezed out to the surface of the cluster. We further study collision dynamics between H(2) and B(12), which also gives interesting phenomena. The present study suggests an interesting functionality of the boron clusters.

A coatable, light-weight, fast-response nanocomposite sensor for the in situ acquisition of dynamic elastic disturbance: from structural vibration to ultrasonic waves

NASA Astrophysics Data System (ADS)

Zeng, Zhihui; Liu, Menglong; Xu, Hao; Liu, Weijian; Liao, Yaozhong; Jin, Hao; Zhou, Limin; Zhang, Zhong; Su, Zhongqing

2016-06-01

Inspired by an innovative sensing philosophy, a light-weight nanocomposite sensor made of a hybrid of carbon black (CB)/polyvinylidene fluoride (PVDF) has been developed. The nanoscalar architecture and percolation characteristics of the hybrid were optimized in order to fulfil the in situ acquisition of dynamic elastic disturbance from low-frequency vibration to high-frequency ultrasonic waves. Dynamic particulate motion induced by elastic disturbance modulates the infrastructure of the CB conductive network in the sensor, with the introduction of the tunneling effect, leading to dynamic alteration in the piezoresistivity measured by the sensor. Electrical analysis, morphological characterization, and static/dynamic electromechanical response interrogation were implemented to advance our insight into the sensing mechanism of the sensor, and meanwhile facilitate understanding of the optimal percolation threshold. At the optimal threshold (˜6.5 wt%), the sensor exhibits high fidelity, a fast response, and high sensitivity to ultrafast elastic disturbance (in an ultrasonic regime up to 400 kHz), yet with an ultralow magnitude (on the order of micrometers). The performance of the sensor was evaluated against a conventional strain gauge and piezoelectric transducer, showing excellent coincidence, yet a much greater gauge factor and frequency-independent piezoresistive behavior. Coatable on a structure and deployable in a large quantity to form a dense sensor network, this nanocomposite sensor has blazed a trail for implementing in situ sensing for vibration- or ultrasonic-wave-based structural health monitoring, by striking a compromise between ‘sensing cost’ and ‘sensing effectiveness’.

On event-based optical flow detection

PubMed Central

Brosch, Tobias; Tschechne, Stephan; Neumann, Heiko

2015-01-01

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

Research and Application of Remote Sensing Monitoring Method for Desertification Land Under Time and Space Constraints

NASA Astrophysics Data System (ADS)

Zhang, Nannnan; Wang, Rongbao; Zhang, Feng

2018-04-01

Serious land desertification and sandified threaten the urban ecological security and the sustainable economic and social development. In recent years, a large number of mobile sand dunes in Horqin sandy land flow into the northwest of Liaoning Province under the monsoon, make local agriculture suffer serious harm. According to the characteristics of desertification land in northwestern Liaoning, based on the First National Geographical Survey data, the Second National Land Survey data and the 1984-2014 Landsat satellite long time sequence data and other multi-source data, we constructed a remote sensing monitoring index system of desertification land in Northwest Liaoning. Through the analysis of space-time-spectral characteristics of desertification land, a method for multi-spectral remote sensing image recognition of desertification land under time-space constraints is proposed. This method was used to identify and extract the distribution and classification of desertification land of Chaoyang City (a typical citie of desertification in northwestern Liaoning) in 2008 and 2014, and monitored the changes and transfers of desertification land from 2008 to 2014. Sandification information was added to the analysis of traditional landscape changes, improved the analysis model of desertification land landscape index, and the characteristics and laws of landscape dynamics and landscape pattern change of desertification land from 2008 to 2014 were analyzed and revealed.

A novel polarization demodulation method using polarization beam splitter (PBS) for dynamic pressure sensor

NASA Astrophysics Data System (ADS)

Su, Yang; Zhou, Hua; Wang, Yiming; Shen, Huiping

2018-03-01

In this paper we propose a new design to demodulate polarization properties induced by pressure using a PBS (polarization beam splitter), which is different with traditional polarimeter based on the 4-detector polarization measurement approach. The theoretical model is established by Muller matrix method. Experimental results confirm the validity of our analysis. Proportional relationships and linear fit are found between output signal and applied pressure. A maximum sensitivity of 0.092182 mv/mv is experimentally achieved and the frequency response exhibits a <0.14 dB variation across the measurement bandwidth. The sensitivity dependence on incident SOP (state of polarization) is investigated. The simple and all-fiber configuration, low-cost and high speed potential make it promising for fiber-based dynamic pressure sensing.

Environmental mapping and monitoring of Iceland by remote sensing (EMMIRS)

NASA Astrophysics Data System (ADS)

Pedersen, Gro B. M.; Vilmundardóttir, Olga K.; Falco, Nicola; Sigurmundsson, Friðþór S.; Rustowicz, Rose; Belart, Joaquin M.-C.; Gísladóttir, Gudrun; Benediktsson, Jón A.

2016-04-01

Iceland is exposed to rapid and dynamic landscape changes caused by natural processes and man-made activities, which impact and challenge the country. Fast and reliable mapping and monitoring techniques are needed on a big spatial scale. However, currently there is lack of operational advanced information processing techniques, which are needed for end-users to incorporate remote sensing (RS) data from multiple data sources. Hence, the full potential of the recent RS data explosion is not being fully exploited. The project Environmental Mapping and Monitoring of Iceland by Remote Sensing (EMMIRS) bridges the gap between advanced information processing capabilities and end-user mapping of the Icelandic environment. This is done by a multidisciplinary assessment of two selected remote sensing super sites, Hekla and Öræfajökull, which encompass many of the rapid natural and man-made landscape changes that Iceland is exposed to. An open-access benchmark repository of the two remote sensing supersites is under construction, providing high-resolution LIDAR topography and hyperspectral data for land-cover and landform classification. Furthermore, a multi-temporal and multi-source archive stretching back to 1945 allows a decadal evaluation of landscape and ecological changes for the two remote sensing super sites by the development of automated change detection techniques. The development of innovative pattern recognition and machine learning-based approaches to image classification and change detection is one of the main tasks of the EMMIRS project, aiming to extract and compute earth observation variables as automatically as possible. Ground reference data collected through a field campaign will be used to validate the implemented methods, which outputs are then inferred with geological and vegetation models. Here, preliminary results of an automatic land-cover classification based on hyperspectral image analysis are reported. Furthermore, the EMMIRS project investigates the complex landscape dynamics between geological and ecological processes. This is done through cross-correlation of mapping results and implementation of modelling techniques that simulate geological and ecological processes in order to extrapolate the landscape evolution

Monitoring of rock glacier dynamics by multi-temporal UAV images

NASA Astrophysics Data System (ADS)

Morra di Cella, Umberto; Pogliotti, Paolo; Diotri, Fabrizio; Cremonese, Edoardo; Filippa, Gianluca; Galvagno, Marta

2015-04-01

During the last years several steps forward have been made in the comprehension of rock glaciers dynamics mainly for their potential evolution into rapid mass movements phenomena. Monitoring the surface movement of creeping mountain permafrost is important for understanding the potential effect of ongoing climate change on such a landforms. This study presents the reconstruction of two years of surface movements and DEM changes obtained by multi-temporal analysis of UAV images (provided by SenseFly Swinglet CAM drone). The movement rate obtained by photogrammetry are compared to those obtained by differential GNSS repeated campaigns on almost fifty points distributed on the rock glacier. Results reveals a very good agreements between both rates velocities obtained by the two methods and vertical displacements on fixed points. Strengths, weaknesses and shrewdness of this methods will be discussed. Such a method is very promising mainly for remote regions with difficult access.

Solution and reasoning reuse in space planning and scheduling applications

NASA Technical Reports Server (NTRS)

Verfaillie, Gerard; Schiex, Thomas

1994-01-01

In the space domain, as in other domains, the CSP (Constraint Satisfaction Problems) techniques are increasingly used to represent and solve planning and scheduling problems. But these techniques have been developed to solve CSP's which are composed of fixed sets of variables and constraints, whereas many planning and scheduling problems are dynamic. It is therefore important to develop methods which allow a new solution to be rapidly found, as close as possible to the previous one, when some variables or constraints are added or removed. After presenting some existing approaches, this paper proposes a simple and efficient method, which has been developed on the basis of the dynamic backtracking algorithm. This method allows previous solution and reasoning to be reused in the framework of a CSP which is close to the previous one. Some experimental results on general random CSPs and on operation scheduling problems for remote sensing satellites are given.

Method for making a dynamic pressure sensor and a pressure sensor made according to the method

NASA Technical Reports Server (NTRS)

Zuckerwar, Allan J. (Inventor); Robbins, William E. (Inventor); Robins, Glenn M. (Inventor)

1994-01-01

A method for providing a perfectly flat top with a sharp edge on a dynamic pressure sensor using a cup-shaped stretched membrane as a sensing element is described. First, metal is deposited on the membrane and surrounding areas. Next, the side wall of the pressure sensor with the deposited metal is machined to a predetermined size. Finally, deposited metal is removed from the top of the membrane in small steps, by machining or lapping while the pressure sensor is mounted in a jig or the wall of a test object, until the true top surface of the membrane appears. A thin indicator layer having a color contrasting with the color of the membrane may be applied to the top of the membrane before metal is deposited to facilitate the determination of when to stop metal removal from the top surface of the membrane.

Indirect rotor position sensing in real time for brushless permanent magnet motor drives

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

Ertugrul, N.; Acarnley, P.P.

1998-07-01

This paper describes a modern solution to real-time rotor position estimation of brushless permanent magnet (PM) motor drives. The position estimation scheme, based on flux linkage and line-current estimation, is implemented in real time by using the abc reference frame, and it is tested dynamically. The position estimation model of the test motor, development of hardware, and basic operation of the digital signal processor (DSP) are discussed. The overall position estimation strategy is accomplished with a fast DSP (TMS320C30). The method is a shaft position sensorless method that is applicable to a wide range of excitation types in brushless PMmore » motors without any restriction on the motor model and the current excitation. Both rectangular and sinewave-excited brushless PM motor drives are examined, and the results are given to demonstrate the effectiveness of the method with dynamic loads in closed estimated position loop.« less

Design of distributed FBG vibration measuring system based on Fabry-Perot tunable filter

NASA Astrophysics Data System (ADS)

Zhang, Cheng; Miao, Changyun; Li, Hongqiang; Gao, Hua; Gan, Jingmeng

2011-11-01

A distributed optical fiber grating wavelength interrogator based on fiber Fabry Perot tunable filter(FFP-TF) was proposed, which could measure dynamic strain or vibration of multi-sensing fiber gratings in one optical fiber by time division way. The wavelength demodulated mathematical model was built, the formulas of system output voltage and sensitivity were deduced and the method of finding static operating point was determined. The wavelength drifting characteristic of FFP-TF was discussed when the center wavelength of FFP-TF was set on the static operating point. A wavelength locking method was proposed by introducing a high-frequency driving voltage signal. A demodulated system was established based on Labview and its demodulated wavelength dynamic range is 290pm in theory. In experiment, by digital filtering applied to the system output data, 100Hz and 250Hz vibration signals were measured. The experiment results proved the feasibility of the demodulated method.

Chemical detection system and related methods

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

Caffrey, Augustine J.; Chichester, David L.; Egger, Ann E.

2017-06-27

A chemical detection system includes a frame, an emitter coupled to the frame, and a detector coupled to the frame proximate the emitter. The system also includes a shielding system coupled to the frame and positioned at least partially between the emitter and the detector, wherein the frame positions a sensing surface of the detector in a direction substantially parallel to a plane extending along a front portion of the frame. A method of analyzing composition of a suspect object includes directing neutrons at the object, detecting gamma rays emitted from the object, and communicating spectrometer information regarding the gammamore » rays. The method also includes presenting a GUI to a user with a dynamic status of an ongoing neutron spectroscopy process. The dynamic status includes a present confidence for a plurality of compounds being present in the suspect object responsive to changes in the spectrometer information during the ongoing process.« less

Application of Terahertz Field Enhancement Effect in Metal Microstructures

NASA Astrophysics Data System (ADS)

Nakajima, M.; Kurihara, T.; Tadokoro, Y.; Kang, B.; Takano, K.; Yamaguchi, K.; Watanabe, H.; Oto, K.; Suemoto, T.; Hangyo, M.

2016-12-01

Applications of high-field terahertz pulses are attractive in physics and terahertz technology. In this study, two applications related to high-intensity terahertz pulses are demonstrated. The field enhancement effect by subwavelength metallic microstructures is utilized for terahertz excitation measurement. The spin precession dynamics in magnetic materials was induced by a terahertz magnetic field. Spin precession was amplified by one order of magnitude in amplitude by the enhanced magnetic terahertz field in orthoferrite ErFeO3 with metal microstructures. The induced spin dynamics was analyzed and explained by LLG-LCR model. Moreover, a detection method for terahertz pulses was developed using a cholesteric liquid crystal at room temperature without any electronic devices. The beam profile of terahertz pulses was visualized and compared to other methods such as the knife edge method using pyroelectric detector and micro-bolometer array. The liquid crystal terahertz imager is very simple and has good applicability as a portable terahertz-sensing card.

Distributed Aerodynamic Sensing and Processing Toolbox

NASA Technical Reports Server (NTRS)

Brenner, Martin; Jutte, Christine; Mangalam, Arun

2011-01-01

A Distributed Aerodynamic Sensing and Processing (DASP) toolbox was designed and fabricated for flight test applications with an Aerostructures Test Wing (ATW) mounted under the fuselage of an F-15B on the Flight Test Fixture (FTF). DASP monitors and processes the aerodynamics with the structural dynamics using nonintrusive, surface-mounted, hot-film sensing. This aerodynamic measurement tool benefits programs devoted to static/dynamic load alleviation, body freedom flutter suppression, buffet control, improvement of aerodynamic efficiency through cruise control, supersonic wave drag reduction through shock control, etc. This DASP toolbox measures local and global unsteady aerodynamic load distribution with distributed sensing. It determines correlation between aerodynamic observables (aero forces) and structural dynamics, and allows control authority increase through aeroelastic shaping and active flow control. It offers improvements in flutter suppression and, in particular, body freedom flutter suppression, as well as aerodynamic performance of wings for increased range/endurance of manned/ unmanned flight vehicles. Other improvements include inlet performance with closed-loop active flow control, and development and validation of advanced analytical and computational tools for unsteady aerodynamics.

A Non-Intrusive Cyber Physical Social Sensing Solution to People Behavior Tracking: Mechanism, Prototype, and Field Experiments.

PubMed

Jia, Yunjian; Zhou, Zhenyu; Chen, Fei; Duan, Peng; Guo, Zhen; Mumtaz, Shahid

2017-01-13

Tracking people's behaviors is a main category of cyber physical social sensing (CPSS)-related people-centric applications. Most tracking methods utilize camera networks or sensors built into mobile devices such as global positioning system (GPS) and Bluetooth. In this article, we propose a non-intrusive wireless fidelity (Wi-Fi)-based tracking method. To show the feasibility, we target tracking people's access behaviors in Wi-Fi networks, which has drawn a lot of interest from the academy and industry recently. Existing methods used for acquiring access traces either provide very limited visibility into media access control (MAC)-level transmission dynamics or sometimes are inflexible and costly. In this article, we present a passive CPSS system operating in a non-intrusive, flexible, and simplified manner to overcome above limitations. We have implemented the prototype on the off-the-shelf personal computer, and performed real-world deployment experiments. The experimental results show that the method is feasible, and people's access behaviors can be correctly tracked within a one-second delay.

A Non-Intrusive Cyber Physical Social Sensing Solution to People Behavior Tracking: Mechanism, Prototype, and Field Experiments

PubMed Central

Jia, Yunjian; Zhou, Zhenyu; Chen, Fei; Duan, Peng; Guo, Zhen; Mumtaz, Shahid

2017-01-01

Tracking people’s behaviors is a main category of cyber physical social sensing (CPSS)-related people-centric applications. Most tracking methods utilize camera networks or sensors built into mobile devices such as global positioning system (GPS) and Bluetooth. In this article, we propose a non-intrusive wireless fidelity (Wi-Fi)-based tracking method. To show the feasibility, we target tracking people’s access behaviors in Wi-Fi networks, which has drawn a lot of interest from the academy and industry recently. Existing methods used for acquiring access traces either provide very limited visibility into media access control (MAC)-level transmission dynamics or sometimes are inflexible and costly. In this article, we present a passive CPSS system operating in a non-intrusive, flexible, and simplified manner to overcome above limitations. We have implemented the prototype on the off-the-shelf personal computer, and performed real-world deployment experiments. The experimental results show that the method is feasible, and people’s access behaviors can be correctly tracked within a one-second delay. PMID:28098772

Method of transmission of dynamic multibit digital images from micro-unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Petrov, E. P.; Kharina, N. L.

2018-01-01

In connection with successful usage of nanotechnologies in remote sensing great attention is paid to the systems in micro-unmanned aerial vehicles (MUAVs) capable to provide high spatial resolution of dynamic multibit digital images (MDI). Limited energy resources on board the MUAV do not allow transferring a large amount of video information in the shortest possible time. It keeps back the broad development of MUAV. The search for methods to shorten the transmission time of dynamic MDIs from MUAV over the radio channel leads to the methods of MDI compression without computational operations onboard the MUAV. The known compression codecs of video information can not be applied because of the limited energy resources. In this paper we propose a method for reducing the transmission time of dynamic MDIs without computational operations and distortions onboard the MUAV. To develop the method a mathematical apparatus of the theory of conditional Markov processes with discrete arguments was used. On its basis a mathematical model for the transformation of the MDI represented by binary images (BI) in the MDI, consisting of groups of neighboring BIs (GBI) transmitted by multiphase (MP) signals, is constructed. The algorithm for multidimensional nonlinear filtering of MP signals is synthesized, realizing the statistical redundancy of the MDI to compensate for the noise stability losses caused by the use of MP signals.

Dynamic Response of CoSb2O6 Trirutile-Type Oxides in a CO2 Atmosphere at Low-Temperatures

PubMed Central

Guillén-Bonilla, Alex; Rodríguez-Betancourtt, Verónica-María; Flores-Martínez, Martín; Blanco-Alonso, Oscar; Reyes-Gómez, Juan; Gildo-Ortiz, Lorenzo; Guillén-Bonilla, Héctor

2014-01-01

Experimental work on the synthesis of the CoSb2O6 oxide and its CO2 sensing properties is presented here. The oxide was synthesized by a microwave-assisted colloidal method in presence of ethylenediamine after calcination at 600 °C. This CoSb2O6 oxide crystallized in a tetragonal structure with cell parameters a = 4.6495 and c = 9.2763 Å, and space group P42/mnm. To prove its physical, chemical and sensing properties, the oxide was subjected to a series of tests: Raman spectroscopy, Scanning Electron Microscopy (SEM) and impedance (Z) measurements. Microstructures, like columns, bars and hollow hemispheres, were observed. For the CO2 sensing test, a thick film of CoSb2O6 was used, measuring the impedance variations on the presence of air/CO2 flows (0.100 sccm/0.100 sccm) using AC (alternating current) signals in the frequency-range 0.1–100 kHz and low relative temperatures (250 and 300 °C). The CO2 sensing results were quite good. PMID:25162232

Acousto-Optical Method of Encoding and Visualization of Underwater Space

DTIC Science & Technology

2014-01-27

neurons which are mathematically described as coupled nonlinear oscillators that are slightly unstable. They have a property called ’ Self - Referential ... self - regulating process which is represented by Equation (5) in the ensuing description. [0083] The input/output circuitry 64 outputs signals that...other words, self -correcting dynamics of the Na and Ca ions in the membranes are closely related to the sensing and the flopping of motion actuators

Determination of Orbiter and Carrier Aerodynamic Coefficients from Load Cell Measurements

NASA Technical Reports Server (NTRS)

Glenn, G. M.

1976-01-01

A method of determining orbiter and carrier total aerodynamic coefficients from load cell measurements is required to support the inert and the captive active flights of the ALT program. A set of equations expressing the orbiter and carrier total aerodynamic coefficients in terms of the load cell measurements, the sensed dynamics of the Boeing 747 (carrier) aircraft, and the relative geometry of the orbiter/carrier is derived.

Surveying the Dynamic Radio Sky with the Long Wavelength Demonstrator Array

DTIC Science & Technology

2010-10-01

and potentially the Lunar Radio Array. Subject headings: instrumentation: interferometers — methods : observational — radio continuum: gen- eral 1Remote...Sensing Division, Naval Research Laboratory, 4555 Overlook Ave. SW, Washington, DC 20375 USA 2NASA Lunar Science Institute, NASA Ames Research Center...Moffett Field, CA 94035 USA 3Space Science Division, Naval Research Laboratory, 4555 Overlook Ave. SW, Washington, DC 20375-5382 USA 4Praxis, Inc

Freedom, Order, and the Child: Self-Control and Mastery of the World Mark the Dynamic Montessori Method

ERIC Educational Resources Information Center

Rambusch, Nancy McCormick

2010-01-01

Today, on almost every continent, there are schools adopting in spirit and practice the ideas of Maria Montessori who ranks with Pestalozzi, Froebel, and Dewey in the field of education. Her approach to early childhood education can be linked to the Thomistic dictum that there is nothing in the intellect which is not first in the senses. In this…

What does remote sensing do for ecology?

NASA Technical Reports Server (NTRS)

Roughgarden, J.; Running, S. W.; Matson, P. A.

1991-01-01

The application of remote sensing to ecological investigations is briefly discussed. Emphasis is given to the recruitment problem in marine population dynamics, the regional analysis of terrestrial ecosystems, and the monitoring of ecological changes. Impediments to the use of remote sensing data in ecology are addressed.

Integration of remote sensing technique and hydrologic model for monitoring tidal flat dynamics of Juiduansha in Shanghai

NASA Astrophysics Data System (ADS)

Zheng, Zongsheng; Zhou, Yunxuan; Jiang, Xuezhong

2007-06-01

Ground survey is restricted by the difficulty of access to wide-range and dynamic salt marsh. Waterline method and hydrodynamic model were investigated to construct Digital Elevation Model (DEM) at Jiudunasha Shoals. A series of waterlines were extracted from multi-temporal remotely sensing images collected over the period of 2000-2004. The assignment of an elevation to each waterline at the satellite overpass was performed according to hydrodynamic model. The corrected waterlines labeled elevations were used to construct Triangulated Irregular Networks (TINs). Then an interpolation for each grid elevation was performed in accordance with the associated triangle. This initial DEM, produced using the corrected waterline set, was then used to refine the topography in the intertidal zone, and the model was re-run to produce improved water levels and a new DEM. This procedure was iterated by comparing modeled and actual waterlines until no further improvement occurred. Three DEMs of different intervals were built by this approach and were compared to evaluate the effect of Deep Water Channel Project (DWCP) at the north of Jiuduansha Island. Waterline method combined with numerical model, is an effective tool for constructing digital elevation model of mudflats. The result can provide invaluable information for coastal land use and engineer construction.

Stochastic global identification of a bio-inspired self-sensing composite UAV wing via wind tunnel experiments

NASA Astrophysics Data System (ADS)

Kopsaftopoulos, Fotios; Nardari, Raphael; Li, Yu-Hung; Wang, Pengchuan; Chang, Fu-Kuo

2016-04-01

In this work, the system design, integration, and wind tunnel experimental evaluation are presented for a bioinspired self-sensing intelligent composite unmanned aerial vehicle (UAV) wing. A total of 148 micro-sensors, including piezoelectric, strain, and temperature sensors, in the form of stretchable sensor networks are embedded in the layup of a composite wing in order to enable its self-sensing capabilities. Novel stochastic system identification techniques based on time series models and statistical parameter estimation are employed in order to accurately interpret the sensing data and extract real-time information on the coupled air flow-structural dynamics. Special emphasis is given to the wind tunnel experimental assessment under various flight conditions defined by multiple airspeeds and angles of attack. A novel modeling approach based on the recently introduced Vector-dependent Functionally Pooled (VFP) model structure is employed for the stochastic identification of the "global" coupled airflow-structural dynamics of the wing and their correlation with dynamic utter and stall. The obtained results demonstrate the successful system-level integration and effectiveness of the stochastic identification approach, thus opening new perspectives for the state sensing and awareness capabilities of the next generation of "fly-by-fee" UAVs.

Data based identification and prediction of nonlinear and complex dynamical systems

NASA Astrophysics Data System (ADS)

Wang, Wen-Xu; Lai, Ying-Cheng; Grebogi, Celso

2016-07-01

The problem of reconstructing nonlinear and complex dynamical systems from measured data or time series is central to many scientific disciplines including physical, biological, computer, and social sciences, as well as engineering and economics. The classic approach to phase-space reconstruction through the methodology of delay-coordinate embedding has been practiced for more than three decades, but the paradigm is effective mostly for low-dimensional dynamical systems. Often, the methodology yields only a topological correspondence of the original system. There are situations in various fields of science and engineering where the systems of interest are complex and high dimensional with many interacting components. A complex system typically exhibits a rich variety of collective dynamics, and it is of great interest to be able to detect, classify, understand, predict, and control the dynamics using data that are becoming increasingly accessible due to the advances of modern information technology. To accomplish these goals, especially prediction and control, an accurate reconstruction of the original system is required. Nonlinear and complex systems identification aims at inferring, from data, the mathematical equations that govern the dynamical evolution and the complex interaction patterns, or topology, among the various components of the system. With successful reconstruction of the system equations and the connecting topology, it may be possible to address challenging and significant problems such as identification of causal relations among the interacting components and detection of hidden nodes. The "inverse" problem thus presents a grand challenge, requiring new paradigms beyond the traditional delay-coordinate embedding methodology. The past fifteen years have witnessed rapid development of contemporary complex graph theory with broad applications in interdisciplinary science and engineering. The combination of graph, information, and nonlinear dynamical systems theories with tools from statistical physics, optimization, engineering control, applied mathematics, and scientific computing enables the development of a number of paradigms to address the problem of nonlinear and complex systems reconstruction. In this Review, we describe the recent advances in this forefront and rapidly evolving field, with a focus on compressive sensing based methods. In particular, compressive sensing is a paradigm developed in recent years in applied mathematics, electrical engineering, and nonlinear physics to reconstruct sparse signals using only limited data. It has broad applications ranging from image compression/reconstruction to the analysis of large-scale sensor networks, and it has become a powerful technique to obtain high-fidelity signals for applications where sufficient observations are not available. We will describe in detail how compressive sensing can be exploited to address a diverse array of problems in data based reconstruction of nonlinear and complex networked systems. The problems include identification of chaotic systems and prediction of catastrophic bifurcations, forecasting future attractors of time-varying nonlinear systems, reconstruction of complex networks with oscillatory and evolutionary game dynamics, detection of hidden nodes, identification of chaotic elements in neuronal networks, reconstruction of complex geospatial networks and nodal positioning, and reconstruction of complex spreading networks with binary data.. A number of alternative methods, such as those based on system response to external driving, synchronization, and noise-induced dynamical correlation, will also be discussed. Due to the high relevance of network reconstruction to biological sciences, a special section is devoted to a brief survey of the current methods to infer biological networks. Finally, a number of open problems including control and controllability of complex nonlinear dynamical networks are discussed. The methods outlined in this Review are principled on various concepts in complexity science and engineering such as phase transitions, bifurcations, stabilities, and robustness. The methodologies have the potential to significantly improve our ability to understand a variety of complex dynamical systems ranging from gene regulatory systems to social networks toward the ultimate goal of controlling such systems.

[Research progress on remote sensing of ecological and environmental changes in the Three Gorges Reservoir area, China].

PubMed

Teng, Ming-jun; Zeng, Li-xiong; Xiao, Wen-fa; Zhou, Zhi-xiang; Huang, Zhi-lin; Wang, Peng-cheng; Dian, Yuan-yong

2014-12-01

The Three Gorges Reservoir area (TGR area) , one of the most sensitive ecological zones in China, has dramatically changes in ecosystem configurations and services driven by the Three Gorges Engineering Project and its related human activities. Thus, understanding the dynamics of ecosystem configurations, ecological processes and ecosystem services is an attractive and critical issue to promote regional ecological security of the TGR area. The remote sensing of environment is a promising approach to the target and is thus increasingly applied to and ecosystem dynamics of the TGR area on mid- and macro-scales. However, current researches often showed controversial results in ecological and environmental changes in the TGR area due to the differences in remote sensing data, scale, and land-use/cover classification. Due to the complexity of ecological configurations and human activities, challenges still exist in the remote-sensing based research of ecological and environmental changes in the TGR area. The purpose of this review was to summarize the research advances in remote sensing of ecological and environmental changes in the TGR area. The status, challenges and trends of ecological and environmental remote-sensing in the TGR area were further discussed and concluded in the aspect of land-use/land-cover, vegetation dynamics, soil and water security, ecosystem services, ecosystem health and its management. The further researches on the remote sensing of ecological and environmental changes were proposed to improve the ecosystem management of the TGR area.

Shock sensing dual mode warhead

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

Shamblen, M.; Walchak, M.T.; Richmond, L.

1980-12-31

A shock sensing dual mode warhead is provided for use against both soft and hard targets and is capable of sensing which type of target has been struck. The warhead comprises a casing made of a ductile material containing an explosive charge and a fuze assembly. The ductile warhead casing will mushroom upon striking a hard target while still confining the explosive. Proper ductility and confinement are necessary for fuze shock sensing. The fuze assembly contains a pair of parallel firing trains, one initiated only by dynamic pressure caused high impact deceleration and one initiated by low impact deceleration. Themore » firing train actuated by high impact deceleration senses dynamic pressure transmitted, during deformation of the warhead, through the explosive filler which is employed as a fuzing signature. The firing train actuated by low impact deceleration contains a pyrotechnic delay to allow penetration of soft targets.« less

Integrated dynamic and static tactile sensor: focus on static force sensing

NASA Astrophysics Data System (ADS)

Wettels, Nicholas; Pletner, Baruch

2012-04-01

Object grasping by robotic hands in unstructured environments demands a sensor that is durable, compliant, and responsive to static and dynamic force conditions. In order for a tactile sensor to be useful for grasp control in these, it should have the following properties: tri-axial force sensing (two shear plus normal component), dynamic event sensing across slip frequencies, compliant surface for grip, wide dynamic range (depending on application), insensitivity to environmental conditions, ability to withstand abuse and good sensing behavior (e.g. low hysteresis, high repeatability). These features can be combined in a novel multimodal tactile sensor. This sensor combines commercial-off-the-shelf MEMS technology with two proprietary force sensors: a high bandwidth device based on PZT technology and low bandwidth device based on elastomers and optics. In this study, we focus on the latter transduction mechanism and the proposed architecture of the completed device. In this study, an embedded LED was utilized to produce a constant light source throughout a layer of silicon rubber which covered a plastic mandrel containing a set of sensitive phototransistors. Features about the contacted object such as center of pressure and force vectors can be extracted from the information in the changing patterns of light. The voltage versus force relationship obtained with this molded humanlike finger had a wide dynamic range that coincided with forces relevant for most human grip tasks.

Bond graph modelling of multibody dynamics and its symbolic scheme

NASA Astrophysics Data System (ADS)

Kawase, Takehiko; Yoshimura, Hiroaki

A bond graph method of modeling multibody dynamics is demonstrated. Specifically, a symbolic generation scheme which fully utilizes the bond graph information is presented. It is also demonstrated that structural understanding and representation in bond graph theory is quite powerful for the modeling of such large scale systems, and that the nonenergic multiport of junction structure, which is a multiport expression of the system structure, plays an important role, as first suggested by Paynter. The principal part of the proposed symbolic scheme, that is, the elimination of excess variables, is done through tearing and interconnection in the sense of Kron using newly defined causal and causal coefficient arrays.

High spatial resolution distributed optical fiber dynamic strain sensor with enhanced frequency and strain resolution.

PubMed

Masoudi, Ali; Newson, Trevor P

2017-01-15

A distributed optical fiber dynamic strain sensor with high spatial and frequency resolution is demonstrated. The sensor, which uses the ϕ-OTDR interrogation technique, exhibited a higher sensitivity thanks to an improved optical arrangement and a new signal processing procedure. The proposed sensing system is capable of fully quantifying multiple dynamic perturbations along a 5 km long sensing fiber with a frequency and spatial resolution of 5 Hz and 50 cm, respectively. The strain resolution of the sensor was measured to be 40 nε.

Constitutional dynamic self-sensing in a zinc(II)/polyiminofluorenes system.

PubMed

Giuseppone, Nicolas; Lehn, Jean-Marie

2004-09-22

The interaction of an external effector, ZnII ions, with a constitutional dynamic library of fluorescent polyiminofluorenes leads to component exchange, which generates an entity responding by a change in emission to the effector that has induced its formation. The overall coupled system displays a tuning of optical signal, resulting from two synergistic processes: adaptative constitutional reorganization and self-sensing. In broader terms, this work highlights the perspectives opened by constitutional dynamic chemistry toward the design of smart materials, capable of expressing different latent properties in response to environmental conditions.

Multilattice sampling strategies for region of interest dynamic MRI.

PubMed

Rilling, Gabriel; Tao, Yuehui; Marshall, Ian; Davies, Mike E

2013-08-01

A multilattice sampling approach is proposed for dynamic MRI with Cartesian trajectories. It relies on the use of sampling patterns composed of several different lattices and exploits an image model where only some parts of the image are dynamic, whereas the rest is assumed static. Given the parameters of such an image model, the methodology followed for the design of a multilattice sampling pattern adapted to the model is described. The multi-lattice approach is compared to single-lattice sampling, as used by traditional acceleration methods such as UNFOLD (UNaliasing by Fourier-Encoding the Overlaps using the temporal Dimension) or k-t BLAST, and random sampling used by modern compressed sensing-based methods. On the considered image model, it allows more flexibility and higher accelerations than lattice sampling and better performance than random sampling. The method is illustrated on a phase-contrast carotid blood velocity mapping MR experiment. Combining the multilattice approach with the KEYHOLE technique allows up to 12× acceleration factors. Simulation and in vivo undersampling results validate the method. Compared to lattice and random sampling, multilattice sampling provides significant gains at high acceleration factors. © 2012 Wiley Periodicals, Inc.

Water Quality Sensing and Spatio-Temporal Monitoring Structure with Autocorrelation Kernel Methods.

PubMed

Vizcaíno, Iván P; Carrera, Enrique V; Muñoz-Romero, Sergio; Cumbal, Luis H; Rojo-Álvarez, José Luis

2017-10-16

Pollution on water resources is usually analyzed with monitoring campaigns, which consist of programmed sampling, measurement, and recording of the most representative water quality parameters. These campaign measurements yields a non-uniform spatio-temporal sampled data structure to characterize complex dynamics phenomena. In this work, we propose an enhanced statistical interpolation method to provide water quality managers with statistically interpolated representations of spatial-temporal dynamics. Specifically, our proposal makes efficient use of the a priori available information of the quality parameter measurements through Support Vector Regression (SVR) based on Mercer's kernels. The methods are benchmarked against previously proposed methods in three segments of the Machángara River and one segment of the San Pedro River in Ecuador, and their different dynamics are shown by statistically interpolated spatial-temporal maps. The best interpolation performance in terms of mean absolute error was the SVR with Mercer's kernel given by either the Mahalanobis spatial-temporal covariance matrix or by the bivariate estimated autocorrelation function. In particular, the autocorrelation kernel provides with significant improvement of the estimation quality, consistently for all the six water quality variables, which points out the relevance of including a priori knowledge of the problem.

Water Quality Sensing and Spatio-Temporal Monitoring Structure with Autocorrelation Kernel Methods

PubMed Central

Vizcaíno, Iván P.; Muñoz-Romero, Sergio; Cumbal, Luis H.

2017-01-01

Pollution on water resources is usually analyzed with monitoring campaigns, which consist of programmed sampling, measurement, and recording of the most representative water quality parameters. These campaign measurements yields a non-uniform spatio-temporal sampled data structure to characterize complex dynamics phenomena. In this work, we propose an enhanced statistical interpolation method to provide water quality managers with statistically interpolated representations of spatial-temporal dynamics. Specifically, our proposal makes efficient use of the a priori available information of the quality parameter measurements through Support Vector Regression (SVR) based on Mercer’s kernels. The methods are benchmarked against previously proposed methods in three segments of the Machángara River and one segment of the San Pedro River in Ecuador, and their different dynamics are shown by statistically interpolated spatial-temporal maps. The best interpolation performance in terms of mean absolute error was the SVR with Mercer’s kernel given by either the Mahalanobis spatial-temporal covariance matrix or by the bivariate estimated autocorrelation function. In particular, the autocorrelation kernel provides with significant improvement of the estimation quality, consistently for all the six water quality variables, which points out the relevance of including a priori knowledge of the problem. PMID:29035333

Gating Charge Calculations by Computational Electrophysiology Simulations.

PubMed

Machtens, Jan-Philipp; Briones, Rodolfo; Alleva, Claudia; de Groot, Bert L; Fahlke, Christoph

2017-04-11

Electrical cell signaling requires adjustment of ion channel, receptor, or transporter function in response to changes in membrane potential. For the majority of such membrane proteins, the molecular details of voltage sensing remain insufficiently understood. Here, we present a molecular dynamics simulation-based method to determine the underlying charge movement across the membrane-the gating charge-by measuring electrical capacitor properties of membrane-embedded proteins. We illustrate the approach by calculating the charge transfer upon membrane insertion of the HIV gp41 fusion peptide, and validate the method on two prototypical voltage-dependent proteins, the Kv1.2 K + channel and the voltage sensor of the Ciona intestinalis voltage-sensitive phosphatase, against experimental data. We then use the gating charge analysis to study how the T1 domain modifies voltage sensing in Kv1.2 channels and to investigate the voltage dependence of the initial binding of two Na + ions in Na + -coupled glutamate transporters. Our simulation approach quantifies various mechanisms of voltage sensing, enables direct comparison with experiments, and supports mechanistic interpretation of voltage sensitivity by fractional amino acid contributions. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Whole left ventricular functional assessment from two minutes free breathing multi-slice CINE acquisition

NASA Astrophysics Data System (ADS)

Usman, M.; Atkinson, D.; Heathfield, E.; Greil, G.; Schaeffter, T.; Prieto, C.

2015-04-01

Two major challenges in cardiovascular MRI are long scan times due to slow MR acquisition and motion artefacts due to respiratory motion. Recently, a Motion Corrected-Compressed Sensing (MC-CS) technique has been proposed for free breathing 2D dynamic cardiac MRI that addresses these challenges by simultaneously accelerating MR acquisition and correcting for any arbitrary motion in a compressed sensing reconstruction. In this work, the MC-CS framework is combined with parallel imaging for further acceleration, and is termed Motion Corrected Sparse SENSE (MC-SS). Validation of the MC-SS framework is demonstrated in eight volunteers and three patients for left ventricular functional assessment and results are compared with the breath-hold acquisitions as reference. A non-significant difference (P > 0.05) was observed in the volumetric functional measurements (end diastolic volume, end systolic volume, ejection fraction) and myocardial border sharpness values obtained with the proposed and gold standard methods. The proposed method achieves whole heart multi-slice coverage in 2 min under free breathing acquisition eliminating the time needed between breath-holds for instructions and recovery. This results in two-fold speed up of the total acquisition time in comparison to the breath-hold acquisition.

Application of phase-diverse phase retrieval to wavefront sensing in non-connected complicated pupil optics

NASA Astrophysics Data System (ADS)

Mao, Heng; Wang, Xiao; Zhao, Dazun

2007-07-01

Baseline algorithm, as a tool in wavefront sensing (WFS), incorporates the phase-diverse phase retrieval (PDPR) method with hybrid-unwrapping approach to ensure a unique pupil phase estimate with high WFS accuracy even in the case of high dynamic range aberration, as long as the pupil shape is of a convex set. However, for a complicated pupil, such as that in obstructed pupil optics, the said unwrapping approach would fail owing to the fake values at points located in obstructed areas of the pupil. Thus a modified unwrapping approach that can minimize the negative effects of the obstructed areas is proposed. Simulations have shown the validity of this unwrapping approach when it is embedded in Baseline algorithm.

Fast, Highly-Sensitive, and Wide-Dynamic-Range Interdigitated Capacitor Glucose Biosensor Using Solvatochromic Dye-Containing Sensing Membrane

PubMed Central

Khan, Md. Rajibur Rahaman; Khalilian, Alireza; Kang, Shin-Won

2016-01-01

In this paper, we proposed an interdigitated capacitor (IDC)-based glucose biosensor to measure different concentrations of glucose from 1 μM to 1 M. We studied four different types of solvatochromic dyes: Auramine O, Nile red, Rhodamine B, and Reichardt’s dye (R-dye). These dyes were individually incorporated into a polymer [polyvinyl chloride (PVC)] and N,N-Dimethylacetamide (DMAC) solution to make the respective dielectric/sensing materials. To the best of our knowledge, we report for the first time an IDC glucose biosensing system utilizing a solvatochromic-dye-containing sensing membrane. These four dielectric or sensing materials were individually placed into the interdigitated electrode (IDE) by spin coating to make four IDC glucose biosensing elements. The proposed IDC glucose biosensor has a high sensing ability over a wide dynamic range and its sensitivity was about 23.32 mV/decade. It also has fast response and recovery times of approximately 7 s and 5 s, respectively, excellent reproducibility with a standard deviation of approximately 0.023, highly stable sensing performance, and real-time monitoring capabilities. The proposed IDC glucose biosensor was compared with an IDC, potentiometric, FET, and fiber-optic glucose sensor with respect to response time, dynamic range width, sensitivity, and linearity. We observed that the designed IDC glucose biosensor offered excellent performance. PMID:26907291

Fast, Highly-Sensitive, and Wide-Dynamic-Range Interdigitated Capacitor Glucose Biosensor Using Solvatochromic Dye-Containing Sensing Membrane.

PubMed

Khan, Md Rajibur Rahaman; Khalilian, Alireza; Kang, Shin-Won

2016-02-20

In this paper, we proposed an interdigitated capacitor (IDC)-based glucose biosensor to measure different concentrations of glucose from 1 μM to 1 M. We studied four different types of solvatochromic dyes: Auramine O, Nile red, Rhodamine B, and Reichardt's dye (R-dye). These dyes were individually incorporated into a polymer [polyvinyl chloride (PVC)] and N,N-Dimethylacetamide (DMAC) solution to make the respective dielectric/sensing materials. To the best of our knowledge, we report for the first time an IDC glucose biosensing system utilizing a solvatochromic-dye-containing sensing membrane. These four dielectric or sensing materials were individually placed into the interdigitated electrode (IDE) by spin coating to make four IDC glucose biosensing elements. The proposed IDC glucose biosensor has a high sensing ability over a wide dynamic range and its sensitivity was about 23.32 mV/decade. It also has fast response and recovery times of approximately 7 s and 5 s, respectively, excellent reproducibility with a standard deviation of approximately 0.023, highly stable sensing performance, and real-time monitoring capabilities. The proposed IDC glucose biosensor was compared with an IDC, potentiometric, FET, and fiber-optic glucose sensor with respect to response time, dynamic range width, sensitivity, and linearity. We observed that the designed IDC glucose biosensor offered excellent performance.

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.

Prediction-based Dynamic Energy Management in Wireless Sensor Networks

PubMed Central

Wang, Xue; Ma, Jun-Jie; Wang, Sheng; Bi, Dao-Wei

2007-01-01

Energy consumption is a critical constraint in wireless sensor networks. Focusing on the energy efficiency problem of wireless sensor networks, this paper proposes a method of prediction-based dynamic energy management. A particle filter was introduced to predict a target state, which was adopted to awaken wireless sensor nodes so that their sleep time was prolonged. With the distributed computing capability of nodes, an optimization approach of distributed genetic algorithm and simulated annealing was proposed to minimize the energy consumption of measurement. Considering the application of target tracking, we implemented target position prediction, node sleep scheduling and optimal sensing node selection. Moreover, a routing scheme of forwarding nodes was presented to achieve extra energy conservation. Experimental results of target tracking verified that energy-efficiency is enhanced by prediction-based dynamic energy management.

Dealing with Daily Challenges in Dementia (Deal-id Study): An Experience Sampling Study to Assess Caregivers' Sense of Competence and Experienced Positive Affect in Daily Life.

PubMed

van Knippenberg, Rosalia J M; de Vugt, Marjolein E; Ponds, Rudolf W; Myin-Germeys, Inez; Verhey, Frans R J

2017-08-01

Positive emotions and feelings of competence seem to play an important role in the well-being of caregivers of people with dementia. Both are likely to fluctuate constantly throughout the caretaking process. Unlike standard retrospective methods, momentary assessments in daily life can provide insight into these moment-to-moment fluctuations. Therefore, in this study both retrospective and momentary assessments were used to examine the relationship between caregivers' sense of competence and their experienced positive affect (PA) in daily life. Thirty Dutch caregivers provided momentary data on PA and daily sense of competence ratings for 6 consecutive days using the experience sampling methodology. Additionally, they reported retrospectively on their sense of competence with a traditional questionnaire. A positive association was found between retrospective and daily measured sense of competence. Caregivers reported corresponding levels of sense of competence on both measures. Both daily and retrospective sense of competence were positively associated with the experienced levels of PA. However, daily sense of competence appeared to be the strongest predictor. Regarding the variability in PA, only daily sense of competence showed a significant association, with a higher daily sense of competence predicting a more stable PA pattern. This study provides support for redirecting caregiver support interventions toward enhancement of positive rather than negative experiences and focusing more on caregivers' momentary emotional experiences. Momentary assessments are a valuable addition to standard retrospective measures and provide a more comprehensive and dynamic view of caregiver functioning. Copyright © 2016 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.

Landscape dynamics analysis of the Yongding River watershed (Mentougou section) by multi-temporal Landsat imagery

NASA Astrophysics Data System (ADS)

Zhang, Yuhu; Yu, Changqing; Qi, Jiaguo; Zhang, Zili; Shi, Qinshan

2007-11-01

The problem of efficient use of multi-temporal remotely sensed data for land-cover and landscape pattern dynamics has already considerable attention in landscape ecology and some other disciplines. This research develops and tests a methodological approach to monitor and analysis landscape dynamics change of Yongding river watershed (Mentougou section) as study area from 1988 to 2005, The result shows that the OIF is the best method of optimal bands selection in Landsat TM remote sensing data, TM3, 4, 5 bands is optimal band combination ;the Mentougou Reach of Yongding river watershed landscape changed significantly in terms of its composition over the period 1988-2005, The total landscape patches of study area in 2005 are more those in 1988,2001, Mean patch size(MPS)decreased sharply, Number of patches(NP) increased sharply, The landscape pattern takes on the fragmentation trends under the effect on the human activity. The forest (woodland and shrubland)are the main landscape matrix. with a significant decrease in croplands and a increase in built-up (residential, urban land) and industrial minerals mining land(coal, open-pit)over the 17 years, And the underlying socio-economic and other drivers of landscape change in study area are discussed.

Optoelectrofluidic enhanced immunoreaction based on optically-induced dynamic AC electroosmosis.

PubMed

Han, Dongsik; Park, Je-Kyun

2016-04-07

We report a novel optoelectrofluidic immunoreaction system based on electroosmotic flow for enhancing antibody-analyte binding efficiency on a surface-based sensing system. Two conventional indium tin oxide glass slides are assembled to provide a reaction chamber for a tiny volume of sample droplet (∼5 μL), in which the top layer is employed as an antibody-immobilized substrate and the bottom layer acts as a photoconductive layer of an optoelectrofluidic device. Under the application of an AC voltage, an illuminated light pattern on the photoconductive layer causes strong counter-rotating vortices to transport analytes from the bulk solution to the vicinity of the assay spot on the glass substrate. This configuration overcomes the slow immunoreaction problem of a diffusion-based sensing system, resulting in the enhancement of binding efficiency via an optoelectrofluidic method. Furthermore, we investigate the effect of optically-induced dynamic AC electroosmotic flow on optoelectrofluidic enhancement for surface-based immunoreaction with a mathematical simulation study and real experiments using immunoglobulin G (IgG) and anti-IgG. As a result, dynamic light patterns provided better immunoreaction efficiency than static light patterns due to effective mass transport of the target analyte, resulting in an achievement of 2.18-fold enhancement under a growing circular light pattern compared to the passive mode.

A New Strategy for Humidity Independent Oxide Chemiresistors: Dynamic Self-Refreshing of In2 O3 Sensing Surface Assisted by Layer-by-Layer Coated CeO2 Nanoclusters.

PubMed

Yoon, Ji-Wook; Kim, Jun-Sik; Kim, Tae-Hyung; Hong, Young Jun; Kang, Yun Chan; Lee, Jong-Heun

2016-08-01

The humidity dependence of the gas sensing characteristics of metal oxide semiconductors has been one of the greatest obstacles for gas sensor applications during the last five decades because ambient humidity dynamically changes with the environmental conditions. Herein, a new and novel strategy is reported to eliminate the humidity dependence of the gas sensing characteristics of oxide chemiresistors via dynamic self-refreshing of the sensing surface affected by water vapor chemisorption. The sensor resistance and gas response of pure In2 O3 hollow spheres significantly change and deteriorate in humid atmospheres. In contrast, the humidity dependence becomes negligible when an optimal concentration of CeO2 nanoclusters is uniformly loaded onto In2 O3 hollow spheres via layer-by-layer (LBL) assembly. Moreover, In2 O3 sensors LBL-coated with CeO2 nanoclusters show fast response/recovery, low detection limit (500 ppb), and high selectivity to acetone even in highly humid conditions (relative humidity 80%). The mechanism underlying the dynamic refreshing of the In2 O3 sensing surfaces regardless of humidity variation is investigated in relation to the role of CeO2 and the chemical interaction among CeO2 , In2 O3 , and water vapor. This strategy can be widely used to design high performance gas sensors including disease diagnosis via breath analysis and pollutant monitoring. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

Tribological Effects on DNA Translocation in a Nanochannel Coated with a Self-Assembled Monolayer

PubMed Central

Luan, Binquan; Afzali, Ali; Harrer, Stefan; Peng, Hongbo; Waggoner, Philip; Polonsky, Stas; Stolovitzky, Gustavo; Martyna, Glenn

2010-01-01

A biomimetic nanochannel coated with a self-assembled monolayer (SAM) can be used for sensing and analyzing biomolecules. The interaction between a transported biomolecule and a SAM governs the mechanically or electrically driven motion of the molecule. To investigate the translocation dynamics of a biomolecule, we performed all-atom molecular dynamics simulations on a single-stranded DNA in a solid-state nanochannel coated with a SAM that consists of octane or octanol polymers. Simulation results demonstrate that the interaction between DNA and a hydrophobic or a hydrophilic SAM is effectively repulsive or adhesive, respectively, resulting in different translocation dynamics of DNA. Therefore, with proper designs of SAMs coated on a channel surface, it is possible to control the translocation dynamics of a biomolecule. This work also demonstrates that traditional tribology methods can be deployed to study a biological or bio-mimetic transport process. PMID:21128651

Asteroid family dynamics in the inner main belt

NASA Astrophysics Data System (ADS)

Dykhuis, Melissa Joy

The inner main asteroid belt is an important source of near-Earth objects and terrestrial planet impactors; however, the dynamics and history of this region are challenging to understand, due to its high population density and the presence of multiple orbital resonances. This dissertation explores the properties of two of the most populous inner main belt family groups --- the Flora family and the Nysa-Polana complex --- investigating their memberships, ages, spin properties, collision dynamics, and range in orbital and reflectance parameters. Though diffuse, the family associated with asteroid (8) Flora dominates the inner main belt in terms of the extent of its members in orbital parameter space, resulting in its significant overlap with multiple neighboring families. This dissertation introduces a new method for membership determination (the core sample method) which enables the distinction of the Flora family from the background, permitting its further analysis. The Flora family is shown to have a signature in plots of semimajor axis vs. size consistent with that expected for a collisional family dispersed as a result of the Yarkovsky radiation effect. The family's age is determined from the Yarkovsky dispersion to be 950 My. Furthermore, a survey of the spin sense of 21 Flora-region asteroids, accomplished via a time-efficient modification of the epoch method for spin sense determination, confirms the single-collision Yarkovsky-dispersed model for the family's origin. The neighboring Nysa-Polana complex is the likely source region for many of the carbonaceous near-Earth asteroids, several of which are important targets for spacecraft reconnaissance and sample return missions. Family identification in the Nysa-Polana complex via the core sample method reveals two families associated with asteroid (135) Hertha, both with distinct age and reflectance properties. The larger of these two families demonstrates a correlation in semimajor axis and eccentricity indicating that its family-forming collision occurred near the parent body's aphelion. In addition, the Eulalia family is connected with a possible second component, suggesting an anisotropic distribution of ejecta from its collision event.

Ultrafast Dynamic Pressure Sensors Based on Graphene Hybrid Structure.

PubMed

Liu, Shanbiao; Wu, Xing; Zhang, Dongdong; Guo, Congwei; Wang, Peng; Hu, Weida; Li, Xinming; Zhou, Xiaofeng; Xu, Hejun; Luo, Chen; Zhang, Jian; Chu, Junhao

2017-07-19

Mechanical flexible electronic skin has been focused on sensing various physical parameters, such as pressure and temperature. The studies of material design and array-accessible devices are the building blocks of strain sensors for subtle pressure sensing. Here, we report a new and facile preparation of a graphene hybrid structure with an ultrafast dynamic pressure response. Graphene oxide nanosheets are used as a surfactant to prevent graphene restacking in aqueous solution. This graphene hybrid structure exhibits a frequency-independent pressure resistive sensing property. Exceeding natural skin, such pressure sensors, can provide transient responses from static up to 10 000 Hz dynamic frequencies. Integrated by the controlling system, the array-accessible sensors can manipulate a robot arm and self-rectify the temperature of a heating blanket. This may pave a path toward the future application of graphene-based wearable electronics.

Electrochemical Sensing and Imaging Based on Ion Transfer at Liquid/Liquid Interfaces

PubMed Central

Amemiya, Shigeru; Kim, Jiyeon; Izadyar, Anahita; Kabagambe, Benjamin; Shen, Mei; Ishimatsu, Ryoichi

2013-01-01

Here we review the recent applications of ion transfer (IT) at the interface between two immiscible electrolyte solutions (ITIES) for electrochemical sensing and imaging. In particular, we focus on the development and recent applications of the nanopipet-supported ITIES and double-polymer-modified electrode, which enable the dynamic electrochemical measurements of IT at nanoscopic and macroscopic ITIES, respectively. High-quality IT voltammograms are obtainable using either technique to quantitatively assess the kinetics and dynamic mechanism of IT at the ITIES. Nanopipet-supported ITIES serves as an amperometric tip for scanning electrochemical microscopy to allow for unprecedentedly high-resolution electrochemical imaging. Voltammetric ion sensing at double-polymer-modified electrodes offers high sensitivity and unique multiple-ion selectivity. The promising future applications of these dynamic approaches for bioanalysis and electrochemical imaging are also discussed. PMID:24363454

Mapping land water and energy balance relations through conditional sampling of remote sensing estimates of atmospheric forcing and surface states

NASA Astrophysics Data System (ADS)

Farhadi, Leila; Entekhabi, Dara; Salvucci, Guido

2016-04-01

In this study, we develop and apply a mapping estimation capability for key unknown parameters that link the surface water and energy balance equations. The method is applied to the Gourma region in West Africa. The accuracy of the estimation method at point scale was previously examined using flux tower data. In this study, the capability is scaled to be applicable with remotely sensed data products and hence allow mapping. Parameters of the system are estimated through a process that links atmospheric forcing (precipitation and incident radiation), surface states, and unknown parameters. Based on conditional averaging of land surface temperature and moisture states, respectively, a single objective function is posed that measures moisture and temperature-dependent errors solely in terms of observed forcings and surface states. This objective function is minimized with respect to parameters to identify evapotranspiration and drainage models and estimate water and energy balance flux components. The uncertainty of the estimated parameters (and associated statistical confidence limits) is obtained through the inverse of Hessian of the objective function, which is an approximation of the covariance matrix. This calibration-free method is applied to the mesoscale region of Gourma in West Africa using multiplatform remote sensing data. The retrievals are verified against tower-flux field site data and physiographic characteristics of the region. The focus is to find the functional form of the evaporative fraction dependence on soil moisture, a key closure function for surface and subsurface heat and moisture dynamics, using remote sensing data.

Development of a database for the verification of trans-ionospheric remote sensing systems

NASA Astrophysics Data System (ADS)

Leitinger, R.

2005-08-01

Remote sensing systems need verification by means of in-situ data or by means of model data. In the case of ionospheric occultation inversion, ionosphere tomography and other imaging methods on the basis of satellite-to-ground or satellite-to-satellite electron content, the availability of in-situ data with adequate spatial and temporal co-location is a very rare case, indeed. Therefore the method of choice for verification is to produce artificial electron content data with realistic properties, subject these data to the inversion/retrieval method, compare the results with model data and apply a suitable type of “goodness of fit” classification. Inter-comparison of inversion/retrieval methods should be done with sets of artificial electron contents in a “blind” (or even “double blind”) way. The set up of a relevant database for the COST 271 Action is described. One part of the database will be made available to everyone interested in testing of inversion/retrieval methods. The artificial electron content data are calculated by means of large-scale models that are “modulated” in a realistic way to include smaller scale and dynamic structures, like troughs and traveling ionospheric disturbances.

Dynamics of psychological crisis experience with psychological consulting by gestalt therapy methods.

PubMed

Fahrutdinova, Liliya Raifovna; Nugmanova, Dzhamilia Renatovna

2015-01-01

Dynamics of experience as such and its corporeal, emotional and cognitive elements in the situation of psychological consulting provisioning is covered. The aim of research was to study psychological crisis experience dynamics in the situation when psychological consulting by gestalt therapy methods is provided. Theoretical analysis of the problem of crisis situations, phenomenon and structural, and dynamic organization of experience of the subject of consulting have been carried out. To fulfill research project test subjects experience crisis situation have been selected, studied in the situation when they provided psychological consulting by methods of gestalt therapy, and methodology of study of crisis situations experience has been prepared. Specifics of psychological crisis experience have been revealed and its elements in different stages of psychological consulting by gestalt therapy methods. Dynamics of experience of psychological crisis and its structural elements have been revealed and reliable changes in it have been revealed. Dynamics of psychological crisis experience and its structural elements have been revealed and reliable changes in it have been revealed. "Desiccation" of experience is being observed, releasing its substantiality of negative impression to the end of consulting and development of the new experience of control over crisis situation. Interrelations of structural elements of experience in the process of psychological consulting have been shown. Effecting one structure causes reliable changes in all others structural elements of experience. Giving actual psychological help to clients in crisis situation by methods of gestalt therapy is possible as it was shown in psychological consulting sessions. Structure of client's request has been revealed - problems of personal sense are fixed as the most frequent cause of clients' applications, as well as absence of choices, obtrusiveness of negative thoughts, tend to getting stuck on events took place in the past, drawing into oneself, etc.

Heterogeneity and dynamics of the ligand recognition mode in purine-sensing riboswitches.

PubMed

Jain, Niyati; Zhao, Liang; Liu, John D; Xia, Tianbing

2010-05-04

High-resolution crystal structures and biophysical analyses of purine-sensing riboswitches have revealed that a network of hydrogen bonding interactions appear to be largey responsible for discrimination of cognate ligands against structurally related compounds. Here we report that by using femtosecond time-resolved fluorescence spectroscopy to capture the ultrafast decay dynamics of the 2-aminopurine base as the ligand, we have detected the presence of multiple conformations of the ligand within the binding pockets of one guanine-sensing and two adenine-sensing riboswitches. All three riboswitches have similar conformational distributions of the ligand-bound state. The known crystal structures represent the global minimum that accounts for 50-60% of the population, where there is no significant stacking interaction between the ligand and bases of the binding pocket, but the hydrogen-bonding cage collectively provides an electronic environment that promotes an ultrafast ( approximately 1 ps) charge transfer pathway. The ligand also samples multiple conformations in which it significantly stacks with either the adenine or the uracil bases of the A21-U75 and A52-U22 base pairs that form the ceiling and floor of the binding pocket, respectively, but favors the larger adenine bases. These alternative conformations with well-defined base stacking interactions are approximately 1-1.5 kcal/mol higher in DeltaG degrees than the global minimum and have distinct charge transfer dynamics within the picosecond to nanosecond time regime. Inside the pocket, the purine ligand undergoes dynamic motion on the low nanosecond time scale, sampling the multiple conformations based on time-resolved anisotropy decay dynamics. These results allowed a description of the energy landscape of the bound ligand with intricate details and demonstrated the elastic nature of the ligand recognition mode by the purine-sensing riboswitches, where there is a dynamic balance between hydrogen bonding and base stacking interactions, yielding the high affinity and specificity by the aptamer domain.

Spherical Harmonic Inductive Detection Coils and their use In Dynamic Pre-emphasis for Magnetic Resonance Imaging

NASA Astrophysics Data System (ADS)

Edler, Karl T.

The issue of eddy currents induced by the rapid switching of magnetic field gradients is a long-standing problem in magnetic resonance imaging. A new method for dealing with this problem is presented whereby spatial harmonic components of the magnetic field are continuously sensed, through their temporal rates of change, and corrected. In this way, the effects of the eddy currents on multiple spatial harmonic components of the magnetic field can be detected and corrections applied during the rise time of the gradients. Sensing the temporal changes in each spatial harmonic is made possible with specially designed detection coils. However to make the design of these coils possible, general relationships between the spatial harmonics of the field, scalar potential, and vector potential are found within the quasi-static approximation. These relationships allow the vector potential to be found from the field -- an inverse curl operation -- and may be of use beyond the specific problem of detection coil design. Using the detection coils as sensors, methods are developed for designing a negative feedback system to control the eddy current effects and optimizing that system with respect to image noise and distortion. The design methods are successfully tested in a series of proof-of-principle experiments which lead to a discussion of how to incorporate similar designs into an operational MRI. Keywords: magnetic resonance imaging, eddy currents, dynamic shimming, negative feedback, quasi-static fields, vector potential, inverse curl

Vibratory Regime Classification of Infant Phonation

PubMed Central

Buder, Eugene H.; Chorna, Lesya B.; Oller, D. Kimbrough; Robinson, Rebecca B.

2008-01-01

Infant phonation is highly variable in many respects, including the basic vibratory patterns by which the vocal tissues create acoustic signals. Previous studies have identified the regular occurrence of non-modal phonation types in normal infant phonation. The glottis is like many oscillating systems that, because of non-linear relationships among the elements, may vibrate in ways representing the deterministic patterns classified theoretically within the mathematical framework of non-linear dynamics. The infant’s pre-verbal vocal explorations present such a variety of phonations that it may be possible to find effectively all the classes of vibration predicted by non-linear dynamic theory. The current report defines acoustic criteria for an important subset of such vibratory regimes, and demonstrates that analysts can be trained to reliably use these criteria for a classification that includes all instances of infant phonation in the recorded corpora. The method is thus internally comprehensive in the sense that all phonations are classified, but it is not exhaustive in the sense that all vocal qualities are thereby represented. Using the methods thus developed, this study also demonstrates that the distributions of these phonation types vary significantly across sessions of recording in the first year of life, suggesting developmental changes. The method of regime classification is thus capable of tracking changes that may be indicative of maturation of the mechanism, the learning of categories of phonatory control, and the possibly varying use of vocalizations across social contexts. PMID:17509829

High temporal resolution dynamic contrast-enhanced MRI using compressed sensing-combined sequence in quantitative renal perfusion measurement.

PubMed

Chen, Bin; Zhao, Kai; Li, Bo; Cai, Wenchao; Wang, Xiaoying; Zhang, Jue; Fang, Jing

2015-10-01

To demonstrate the feasibility of the improved temporal resolution by using compressed sensing (CS) combined imaging sequence in dynamic contrast-enhanced MRI (DCE-MRI) of kidney, and investigate its quantitative effects on renal perfusion measurements. Ten rabbits were included in the accelerated scans with a CS-combined 3D pulse sequence. To evaluate the image quality, the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were compared between the proposed CS strategy and the conventional full sampling method. Moreover, renal perfusion was estimated by using the separable compartmental model in both CS simulation and realistic CS acquisitions. The CS method showed DCE-MRI images with improved temporal resolution and acceptable image contrast, while presenting significantly higher SNR than the fully sampled images (p<.01) at 2-, 3- and 4-X acceleration. In quantitative measurements, renal perfusion results were in good agreement with the fully sampled one (concordance correlation coefficient=0.95, 0.91, 0.88) at 2-, 3- and 4-X acceleration in CS simulation. Moreover, in realistic acquisitions, the estimated perfusion by the separable compartmental model exhibited no significant differences (p>.05) between each CS-accelerated acquisition and the full sampling method. The CS-combined 3D sequence could improve the temporal resolution for DCE-MRI in kidney while yielding diagnostically acceptable image quality, and it could provide effective measurements of renal perfusion. Copyright © 2015 Elsevier Inc. All rights reserved.

An application of aerial remote sensing to monitor salinization at Xinding Basin

NASA Astrophysics Data System (ADS)

Qiao, Yu-Liang

In this paper, a method to interpret the high, mid, low salinized ploughland and the salinized wasteland using comprehensive aerophoto interpretation principles will be described for Xinding Basin, Shanxi Province. The dynamic change of salinized soil during 7 years from 1980 to 1987 will be compared with the typical Dingxiang County. The map and data obtained, with an accuracy of more than 90%, are provided to the local government as the scientific grounds to instruct agricultural productivity. Soil salinization is a worldwide problem. With the sharp increase in world population and modern industrialisation development, the natural resource consumption is increasing day and day, and bringing about a lack of land resource worldwide. As a kind of back-up land resource, salinized land has not only attracted the concern and study of the agricultural scientists in all countries, but also by the whole society. Shanxi is such a province in China where more than 1/3 of its total area of irrigation land is salinized. The statistics used to monitor this salinized area lack objectivity and accuracy. In 1987, the government of Shanxi Province began to investigate the salinized area of the whole province, using remote sensing technology. We selected the Xinding Basin in central Shanxi as the test district to perform the aerial remote sensing investigation, and, at the same time, studied the salinization dynamic change on the Dingxiang County used as the typical district.

The influence of underwater turbulence on optical phase measurements

NASA Astrophysics Data System (ADS)

Redding, Brandon; Davis, Allen; Kirkendall, Clay; Dandridge, Anthony

2016-05-01

Emerging underwater optical imaging and sensing applications rely on phase-sensitive detection to provide added functionality and improved sensitivity. However, underwater turbulence introduces spatio-temporal variations in the refractive index of water which can degrade the performance of these systems. Although the influence of turbulence on traditional, non-interferometric imaging has been investigated, its influence on the optical phase remains poorly understood. Nonetheless, a thorough understanding of the spatio-temporal dynamics of the optical phase of light passing through underwater turbulence are crucial to the design of phase-sensitive imaging and sensing systems. To address this concern, we combined underwater imaging with high speed holography to provide a calibrated characterization of the effects of turbulence on the optical phase. By measuring the modulation transfer function of an underwater imaging system, we were able to calibrate varying levels of optical turbulence intensity using the Simple Underwater Imaging Model (SUIM). We then used high speed holography to measure the temporal dynamics of the optical phase of light passing through varying levels of turbulence. Using this method, we measured the variance in the amplitude and phase of the beam, the temporal correlation of the optical phase, and recorded the turbulence induced phase noise as a function of frequency. By bench marking the effects of varying levels of turbulence on the optical phase, this work provides a basis to evaluate the real-world potential of emerging underwater interferometric sensing modalities.

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

PubMed

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

2015-12-01

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

Statistical processing of large image sequences.

PubMed

Khellah, F; Fieguth, P; Murray, M J; Allen, M

2005-01-01

The dynamic estimation of large-scale stochastic image sequences, as frequently encountered in remote sensing, is important in a variety of scientific applications. However, the size of such images makes conventional dynamic estimation methods, for example, the Kalman and related filters, impractical. In this paper, we present an approach that emulates the Kalman filter, but with considerably reduced computational and storage requirements. Our approach is illustrated in the context of a 512 x 512 image sequence of ocean surface temperature. The static estimation step, the primary contribution here, uses a mixture of stationary models to accurately mimic the effect of a nonstationary prior, simplifying both computational complexity and modeling. Our approach provides an efficient, stable, positive-definite model which is consistent with the given correlation structure. Thus, the methods of this paper may find application in modeling and single-frame estimation.

Interfacial bioconjugation on emulsion droplet for biosensors.

PubMed

Zhang, Qifan; Scigliano, Anita; Biver, Tarita; Pucci, Andrea; Swager, Timothy M

2018-04-13

Interfacial bioconjugation methods are developed for intact liquid emulsion droplets. Complex emulsion droplets having internal hydrocarbon and fluorocarbon immiscible structured phases maintain a dynamic interface for controlled interfacial reactivity. The internal morphological change after binding to biomolecules is readily visualized and detected by light transmission, which provides a platform for the formation of inexpensive and portable bio-sensing assays for enzymes, antibodies, nucleic acids and carbohydrates. Copyright © 2018. Published by Elsevier Ltd.

Semi-Autonomous Control with Cyber-Pain for Artificial Muscles and Smart Structures

DTIC Science & Technology

2010-09-15

avoid some key failure modes. Our approach has built on our developments in dynamic self-sensing and realistic simulation of DEA electromechanics...local controller) to avoid some key failure modes. Our approach has built on our developments in dynamic self-sensing and realistic simulation of DEA...strains [4]. In its natural state long polymer backbones are entangled with intermittent cross-links tying neighbouring backbones together. The soft

Analysis of amyloplast dynamics involved in gravity sensing using a novel centrifuge microscope

NASA Astrophysics Data System (ADS)

Toyota, Masatsugu; Tasaka, Masao; Morita, Miyo T.

Plants sense gravity and change their growth orientation, a phenomenon known as gravitropism. According to the starch-statolith hypothesis, sedimentation of high-density starch-filled plastids (amyloplasts) within endodermal cells appears to be involved in gravity sensing of Arabidop-sis shoots. Recent studies suggest, however, that amyloplasts are never static but continu-ously show dynamic and complicated movements due to interaction with vacuole/cytoskeleton. Therefore, it remains unclear what movement/state of amyloplasts is required for gravity sens-ing. To address this critical issue, we analyzed gravitropism and amyloplast dynamics under hypergravity condition where sedimentation by gravity is more dominant than other movements. Segments of Arabidopsis inflorescence stem showed a gravitropism in response to hypergrav-ity (10g) that had been applied perpendicularly to the growth axis for 30 s in a conventional centrifuge, suggesting that amyloplast dynamics during this short time period is involved in gravity sensing. Real-time imaging of amyloplasts during the 10g stimulation was performed using a novel centrifuge microscope (NSK Ltd, Japan): all optical devices including objective lens, light source (LED) and CCD camera are mounted on an AC motor, enabling bright-field imaging with a temporal resolution of 30 frames/sec during rotation. Almost all amyloplasts started to move toward 10g and some reached the one side of endodermal cell within 30 s. These results clearly support the starch-statolith hypothesis that redistribution of amyloplasts to gravity is important for gravity sensing. Furthermore, we analyzed the shoot gravitropic mutant, sgr2, that has non-sedimentable amyloplasts and shows little gravitropism at 1g. An obvious gravitropism was induced by 30g for 5 min where amyloplasts were moved to the hyper-gravity but not by 10g where amyloplasts were not moved. These results not only suggest that gravity sensing of Arabidopsis inflorescence stems is triggered by the amyloplast redistribution resulting from the directional movement to gravity, but also provide a new interpretation of sgr2 that sgr2 has a gravity-sensing mechanism, which is inactivated at 1g probably due to non-sedimentable amyloplasts.

Gender differences in autobiographical memory for everyday events: retrieval elicited by SenseCam images versus verbal cues.

PubMed

St Jacques, Peggy L; Conway, Martin A; Cabeza, Roberto

2011-10-01

Gender differences are frequently observed in autobiographical memory (AM). However, few studies have investigated the neural basis of potential gender differences in AM. In the present functional MRI (fMRI) study we investigated gender differences in AMs elicited using dynamic visual images vs verbal cues. We used a novel technology called a SenseCam, a wearable device that automatically takes thousands of photographs. SenseCam differs considerably from other prospective methods of generating retrieval cues because it does not disrupt the ongoing experience. This allowed us to control for potential gender differences in emotional processing and elaborative rehearsal, while manipulating how the AMs were elicited. We predicted that males would retrieve more richly experienced AMs elicited by the SenseCam images vs the verbal cues, whereas females would show equal sensitivity to both cues. The behavioural results indicated that there were no gender differences in subjective ratings of reliving, importance, vividness, emotion, and uniqueness, suggesting that gender differences in brain activity were not due to differences in these measures of phenomenological experience. Consistent with our predictions, the fMRI results revealed that males showed a greater difference in functional activity associated with the rich experience of SenseCam vs verbal cues, than did females.

Reliable fusion of control and sensing in intelligent machines. Thesis

NASA Technical Reports Server (NTRS)

Mcinroy, John E.

1991-01-01

Although robotics research has produced a wealth of sophisticated control and sensing algorithms, very little research has been aimed at reliably combining these control and sensing strategies so that a specific task can be executed. To improve the reliability of robotic systems, analytic techniques are developed for calculating the probability that a particular combination of control and sensing algorithms will satisfy the required specifications. The probability can then be used to assess the reliability of the design. An entropy formulation is first used to quickly eliminate designs not capable of meeting the specifications. Next, a framework for analyzing reliability based on the first order second moment methods of structural engineering is proposed. To ensure performance over an interval of time, lower bounds on the reliability of meeting a set of quadratic specifications with a Gaussian discrete time invariant control system are derived. A case study analyzing visual positioning in robotic system is considered. The reliability of meeting timing and positioning specifications in the presence of camera pixel truncation, forward and inverse kinematic errors, and Gaussian joint measurement noise is determined. This information is used to select a visual sensing strategy, a kinematic algorithm, and a discrete compensator capable of accomplishing the desired task. Simulation results using PUMA 560 kinematic and dynamic characteristics are presented.

Single-Shot MR Spectroscopic Imaging with Partial Parallel Imaging

PubMed Central

Posse, Stefan; Otazo, Ricardo; Tsai, Shang-Yueh; Yoshimoto, Akio Ernesto; Lin, Fa-Hsuan

2010-01-01

An MR spectroscopic imaging (MRSI) pulse sequence based on Proton-Echo-Planar-Spectroscopic-Imaging (PEPSI) is introduced that measures 2-dimensional metabolite maps in a single excitation. Echo-planar spatial-spectral encoding was combined with interleaved phase encoding and parallel imaging using SENSE to reconstruct absorption mode spectra. The symmetrical k-space trajectory compensates phase errors due to convolution of spatial and spectral encoding. Single-shot MRSI at short TE was evaluated in phantoms and in vivo on a 3 T whole body scanner equipped with 12-channel array coil. Four-step interleaved phase encoding and 4-fold SENSE acceleration were used to encode a 16×16 spatial matrix with 390 Hz spectral width. Comparison with conventional PEPSI and PEPSI with 4-fold SENSE acceleration demonstrated comparable sensitivity per unit time when taking into account g-factor related noise increases and differences in sampling efficiency. LCModel fitting enabled quantification of Inositol, Choline, Creatine and NAA in vivo with concentration values in the ranges measured with conventional PEPSI and SENSE-accelerated PEPSI. Cramer-Rao lower bounds were comparable to those obtained with conventional SENSE-accelerated PEPSI at the same voxel size and measurement time. This single-shot MRSI method is therefore suitable for applications that require high temporal resolution to monitor temporal dynamics or to reduce sensitivity to tissue movement. PMID:19097245

[Review of estimation on oceanic primary productivity by using remote sensing methods.

PubMed

Xu, Hong Yun; Zhou, Wei Feng; Ji, Shi Jian

2016-09-01

Accuracy estimation of oceanic primary productivity is of great significance in the assessment and management of fisheries resources, marine ecology systems, global change and other fields. The traditional measurement and estimation of oceanic primary productivity has to rely on in situ sample data by vessels. Satellite remote sensing has advantages of providing dynamic and eco-environmental parameters of ocean surface at large scale in real time. Thus, satellite remote sensing has increasingly become an important means for oceanic primary productivity estimation on large spatio-temporal scale. Combining with the development of ocean color sensors, the models to estimate the oceanic primary productivity by satellite remote sensing have been developed that could be mainly summarized as chlorophyll-based, carbon-based and phytoplankton absorption-based approach. The flexibility and complexity of the three kinds of models were presented in the paper. On this basis, the current research status for global estimation of oceanic primary productivity was analyzed and evaluated. In view of these, four research fields needed to be strengthened in further stu-dy: 1) Global oceanic primary productivity estimation should be segmented and studied, 2) to dee-pen the research on absorption coefficient of phytoplankton, 3) to enhance the technology of ocea-nic remote sensing, 4) to improve the in situ measurement of primary productivity.

Predicting non-linear dynamics by stable local learning in a recurrent spiking neural network.

PubMed

Gilra, Aditya; Gerstner, Wulfram

2017-11-27

The brain needs to predict how the body reacts to motor commands, but how a network of spiking neurons can learn non-linear body dynamics using local, online and stable learning rules is unclear. Here, we present a supervised learning scheme for the feedforward and recurrent connections in a network of heterogeneous spiking neurons. The error in the output is fed back through fixed random connections with a negative gain, causing the network to follow the desired dynamics. The rule for Feedback-based Online Local Learning Of Weights (FOLLOW) is local in the sense that weight changes depend on the presynaptic activity and the error signal projected onto the postsynaptic neuron. We provide examples of learning linear, non-linear and chaotic dynamics, as well as the dynamics of a two-link arm. Under reasonable approximations, we show, using the Lyapunov method, that FOLLOW learning is uniformly stable, with the error going to zero asymptotically.

Predicting non-linear dynamics by stable local learning in a recurrent spiking neural network

PubMed Central

Gerstner, Wulfram

2017-01-01

The brain needs to predict how the body reacts to motor commands, but how a network of spiking neurons can learn non-linear body dynamics using local, online and stable learning rules is unclear. Here, we present a supervised learning scheme for the feedforward and recurrent connections in a network of heterogeneous spiking neurons. The error in the output is fed back through fixed random connections with a negative gain, causing the network to follow the desired dynamics. The rule for Feedback-based Online Local Learning Of Weights (FOLLOW) is local in the sense that weight changes depend on the presynaptic activity and the error signal projected onto the postsynaptic neuron. We provide examples of learning linear, non-linear and chaotic dynamics, as well as the dynamics of a two-link arm. Under reasonable approximations, we show, using the Lyapunov method, that FOLLOW learning is uniformly stable, with the error going to zero asymptotically. PMID:29173280

Monitoring terrestrial dissolved organic carbon export at land-water interfaces using remote sensing

NASA Astrophysics Data System (ADS)

Yu, Q.; Li, J.; Tian, Y. Q.

2017-12-01

Carbon flux from land to oceans and lakes is a crucial component of carbon cycling. However, this lateral carbon flow at land-water interface is often neglected in the terrestrial carbon cycle budget, mainly because observations of the carbon dynamics are very limited. Monitoring CDOM/DOC dynamics using remote sensing and assessing DOC export from land to water remains a challenge. Current CDOM retrieval algorithms in the field of ocean color are not simply applicable to inland aquatic ecosystems since they were developed for coarse resolution ocean-viewing imagery and less complex water types in open-sea. We developed a new semi-analytical algorithm, called SBOP (Shallow water Bio-Optical Properties algorithm) to adapt to shallow inland waters. SBOP was first developed and calibrated based on in situ hyperspectral radiometer data. Then we applied it to the Landsat-8 OLI images and evaluated the effectiveness of the multispectral images on inversion of CDOM absorption based on our field sampling at the Saginaw Bay in the Lake Huron. The algorithm performances (RMSE = 0.17 and R2 = 0.87 in the Saginaw Bay; R2 = 0.80 in the northeastern US lakes) is promising and we conclude the CDOM absorption can be derived from Landsat-8 OLI image in both optically deep and optically shallow waters with high accuracy. Our method addressed challenges on employing appropriate atmospheric correction, determining bottom reflectance influence for shallow waters, and improving for bio-optical properties retrieval, as well as adapting to both hyperspectral and the multispectral remote sensing imagery. Over 100 Landsat-8 images in Lake Huron, northeastern US lakes, and the Arctic major rivers were processed to understand the CDOM spatio-temporal dynamics and its associated driving factors.

Failure detection and fault management techniques for flush airdata sensing systems

NASA Technical Reports Server (NTRS)

Whitmore, Stephen A.; Moes, Timothy R.; Leondes, Cornelius T.

1992-01-01

Methods based on chi-squared analysis are presented for detecting system and individual-port failures in the high-angle-of-attack flush airdata sensing system on the NASA F-18 High Alpha Research Vehicle. The HI-FADS hardware is introduced, and the aerodynamic model describes measured pressure in terms of dynamic pressure, angle of attack, angle of sideslip, and static pressure. Chi-squared analysis is described in the presentation of the concept for failure detection and fault management which includes nominal, iteration, and fault-management modes. A matrix of pressure orifices arranged in concentric circles on the nose of the aircraft indicate the parameters which are applied to the regression algorithms. The sensing techniques are applied to the F-18 flight data, and two examples are given of the computed angle-of-attack time histories. The failure-detection and fault-management techniques permit the matrix to be multiply redundant, and the chi-squared analysis is shown to be useful in the detection of failures.

Modulation of nitrogen vacancy charge state and fluorescence in nanodiamonds using electrochemical potential

PubMed Central

Karaveli, Sinan; Gaathon, Ophir; Wolcott, Abraham; Sakakibara, Reyu; Shemesh, Or A.; Peterka, Darcy S.; Boyden, Edward S.; Owen, Jonathan S.; Yuste, Rafael; Englund, Dirk

2016-01-01

The negatively charged nitrogen vacancy (NV−) center in diamond has attracted strong interest for a wide range of sensing and quantum information processing applications. To this end, recent work has focused on controlling the NV charge state, whose stability strongly depends on its electrostatic environment. Here, we demonstrate that the charge state and fluorescence dynamics of single NV centers in nanodiamonds with different surface terminations can be controlled by an externally applied potential difference in an electrochemical cell. The voltage dependence of the NV charge state can be used to stabilize the NV− state for spin-based sensing protocols and provides a method of charge state-dependent fluorescence sensing of electrochemical potentials. We detect clear NV fluorescence modulation for voltage changes down to 100 mV, with a single NV and down to 20 mV with multiple NV centers in a wide-field imaging mode. These results suggest that NV centers in nanodiamonds could enable parallel optical detection of biologically relevant electrochemical potentials. PMID:27035935

Modulation of nitrogen vacancy charge state and fluorescence in nanodiamonds using electrochemical potential.

PubMed

Karaveli, Sinan; Gaathon, Ophir; Wolcott, Abraham; Sakakibara, Reyu; Shemesh, Or A; Peterka, Darcy S; Boyden, Edward S; Owen, Jonathan S; Yuste, Rafael; Englund, Dirk

2016-04-12

The negatively charged nitrogen vacancy (NV(-)) center in diamond has attracted strong interest for a wide range of sensing and quantum information processing applications. To this end, recent work has focused on controlling the NV charge state, whose stability strongly depends on its electrostatic environment. Here, we demonstrate that the charge state and fluorescence dynamics of single NV centers in nanodiamonds with different surface terminations can be controlled by an externally applied potential difference in an electrochemical cell. The voltage dependence of the NV charge state can be used to stabilize the NV(-) state for spin-based sensing protocols and provides a method of charge state-dependent fluorescence sensing of electrochemical potentials. We detect clear NV fluorescence modulation for voltage changes down to 100 mV, with a single NV and down to 20 mV with multiple NV centers in a wide-field imaging mode. These results suggest that NV centers in nanodiamonds could enable parallel optical detection of biologically relevant electrochemical potentials.

Modulation of nitrogen vacancy charge state and fluorescence in nanodiamonds using electrochemical potential

NASA Astrophysics Data System (ADS)

Karaveli, Sinan; Gaathon, Ophir; Wolcott, Abraham; Sakakibara, Reyu; Shemesh, Or A.; Peterka, Darcy S.; Boyden, Edward S.; Owen, Jonathan S.; Yuste, Rafael; Englund, Dirk

2016-04-01

The negatively charged nitrogen vacancy (NV-) center in diamond has attracted strong interest for a wide range of sensing and quantum information processing applications. To this end, recent work has focused on controlling the NV charge state, whose stability strongly depends on its electrostatic environment. Here, we demonstrate that the charge state and fluorescence dynamics of single NV centers in nanodiamonds with different surface terminations can be controlled by an externally applied potential difference in an electrochemical cell. The voltage dependence of the NV charge state can be used to stabilize the NV- state for spin-based sensing protocols and provides a method of charge state-dependent fluorescence sensing of electrochemical potentials. We detect clear NV fluorescence modulation for voltage changes down to 100 mV, with a single NV and down to 20 mV with multiple NV centers in a wide-field imaging mode. These results suggest that NV centers in nanodiamonds could enable parallel optical detection of biologically relevant electrochemical potentials.

Optical Probes for Neurobiological Sensing and Imaging.

PubMed

Kim, Eric H; Chin, Gregory; Rong, Guoxin; Poskanzer, Kira E; Clark, Heather A

2018-05-15

Fluorescent nanosensors and molecular probes are next-generation tools for imaging chemical signaling inside and between cells. Electrophysiology has long been considered the gold standard in elucidating neural dynamics with high temporal resolution and precision, particularly on the single-cell level. However, electrode-based techniques face challenges in illuminating the specific chemicals involved in neural cell activation with adequate spatial information. Measuring chemical dynamics is of fundamental importance to better understand synergistic interactions between neurons as well as interactions between neurons and non-neuronal cells. Over the past decade, significant technological advances in optical probes and imaging methods have enabled entirely new possibilities for studying neural cells and circuits at the chemical level. These optical imaging modalities have shown promise for combining chemical, temporal, and spatial information. This potential makes them ideal candidates to unravel the complex neural interactions at multiple scales in the brain, which could be complemented by traditional electrophysiological methods to obtain a full spatiotemporal picture of neurochemical dynamics. Despite the potential, only a handful of probe candidates have been utilized to provide detailed chemical information in the brain. To date, most live imaging and chemical mapping studies rely on fluorescent molecular indicators to report intracellular calcium (Ca 2+ ) dynamics, which correlates with neuronal activity. Methodological advances for monitoring a full array of chemicals in the brain with improved spatial, temporal, and chemical resolution will thus enable mapping of neurochemical circuits with finer precision. On the basis of numerous studies in this exciting field, we review the current efforts to develop and apply a palette of optical probes and nanosensors for chemical sensing in the brain. There is a strong impetus to further develop technologies capable of probing entire neurobiological units with high spatiotemporal resolution. Thus, we introduce selected applications for ion and neurotransmitter detection to investigate both neurons and non-neuronal brain cells. We focus on families of optical probes because of their ability to sense a wide array of molecules and convey spatial information with minimal damage to tissue. We start with a discussion of currently available molecular probes, highlight recent advances in genetically modified fluorescent probes for ions and small molecules, and end with the latest research in nanosensors for biological imaging. Customizable, nanoscale optical sensors that accurately and dynamically monitor the local environment with high spatiotemporal resolution could lead to not only new insights into the function of all cell types but also a broader understanding of how diverse neural signaling systems act in conjunction with neighboring cells in a spatially relevant manner.

Sea Surface Salinity: The Next Remote Sensing Challenge

NASA Technical Reports Server (NTRS)

Lagerloef, Gary S. E.; Swift, Calvin T.; LeVine, David M.

1995-01-01

A brief history of salinity remote sensing is presented. The role of sea surface salinity (SSS) in the far north Atlantic and the influence of salinity variations on upper ocean dynamics in the tropics are described. An assessment of the present state of the technology of the SSS satellite remote sensing is given.

Quality as Sense-Making

ERIC Educational Resources Information Center

Marshall, Stephen

2016-01-01

Sense-making is a process of engaging with complex and dynamic environments that provides organisations and their leaders with a flexible and agile model of the world. The seven key properties of sense-making describe a process that is social and that respects the range of different stakeholders in an organisation. It also addresses the need to…

Thermal Infrared Remote Sensing for Analysis of Landscape Ecological Processes: Methods and Applications

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Luvall, Jeffrey C.

1998-01-01

Thermal Infrared (TIR) remote sensing data can provide important measurements of surface energy fluxes and temperatures, which are integral to understanding landscape processes and responses. One example of this is the successful application of TIR remote sensing data to estimate evapotranspiration and soil moisture, where results from a number of studies suggest that satellite-based measurements from TIR remote sensing data can lead to more accurate regional-scale estimates of daily evapotranspiration. With further refinement in analytical techniques and models, the use of TIR data from airborne and satellite sensors could be very useful for parameterizing surface moisture conditions and developing better simulations of landscape energy exchange over a variety of conditions and space and time scales. Thus, TIR remote sensing data can significantly contribute to the observation, measurement, and analysis of energy balance characteristics (i.e., the fluxes and redistribution of thermal energy within and across the land surface) as an implicit and important aspect of landscape dynamics and landscape functioning. The application of TIR remote sensing data in landscape ecological studies has been limited, however, for several fundamental reasons that relate primarily to the perceived difficulty in use and availability of these data by the landscape ecology community, and from the fragmentation of references on TIR remote sensing throughout the scientific literature. It is our purpose here to provide evidence from work that has employed TIR remote sensing for analysis of landscape characteristics to illustrate how these data can provide important data for the improved measurement of landscape energy response and energy flux relationships. We examine the direct or indirect use of TIR remote sensing data to analyze landscape biophysical characteristics, thereby offering some insight on how these data can be used more robustly to further the understanding and modeling of landscape ecological processes.

System identification of a small low-cost unmanned aerial vehicle using flight data from low-cost sensors

NASA Astrophysics Data System (ADS)

Hoffer, Nathan Von

Remote sensing has traditionally been done with satellites and manned aircraft. While. these methods can yield useful scientificc data, satellites and manned aircraft have limitations in data frequency, process time, and real time re-tasking. Small low-cost unmanned aerial vehicles (UAVs) provide greater possibilities for personal scientic research than traditional remote sensing platforms. Precision aerial data requires an accurate vehicle dynamics model for controller development, robust flight characteristics, and fault tolerance. One method of developing a model is system identification (system ID). In this thesis system ID of a small low-cost fixed-wing T-tail UAV is conducted. The linerized longitudinal equations of motion are derived from first principles. Foundations of Recursive Least Squares (RLS) are presented along with RLS with an Error Filtering Online Learning scheme (EFOL). Sensors, data collection, data consistency checking, and data processing are described. Batch least squares (BLS) and BLS with EFOL are used to identify aerodynamic coecoefficients of the UAV. Results of these two methods with flight data are discussed.

Quasi-D-shaped optical fiber plasmonic refractive index sensor

NASA Astrophysics Data System (ADS)

An, Guowen; Li, Shuguang; Wang, Haiyang; Zhang, Xuenan; Yan, Xin

2018-03-01

A quasi-D-shaped photonic crystal fiber plasmonic sensor with a rectangular lattice is proposed by using Au as a plasmonic layer and graphene to enhance the sensing performance. By moving the core to the edge of the fiber, a shorter polishing depth is achieved, which makes the fiber proposed have a greater mechanical strength than other common D-shaped fibers. Benefiting from the natural advantage of the rectangular lattice, the dual sensing channels make the proposed sensor show a maximum wavelength interrogation sensitivity of 3877 nm/RIU with the dynamic refractive index range from 1.33 to 1.42 and a maximum amplitude sensitivity of 1236 RIU-1 with the analyte RI = 1.41 in the visible region. The corresponding resolutions are 2.58 × 10-5 and 8.1 × 10-6 with the methods of the wavelength interrogation method and amplitude- or phase-based method. These advantages make the proposed sensor a competitive candidate for biosensing in the field of refractive index detection, such as water quality analysis, clinical medicine detection, and pharmaceutical testing.

Effects of stick dynamics on helicopter flying qualities

NASA Technical Reports Server (NTRS)

Watson, Douglas C.; Schroeder, Jeffery A.

1990-01-01

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

Seasonality of a boreal forest: a remote sensing perspective

NASA Astrophysics Data System (ADS)

Rautiainen, Miina; Heiskanen, Janne; Lukes, Petr; Majasalmi, Titta; Mottus, Matti; Pisek, Jan

2016-04-01

Understanding the seasonal dynamics of boreal ecosystems through interpretation of satellite reflectance data is needed for efficient large-scale monitoring of northern vegetation dynamics and productivity trends. Satellite remote sensing enables continuous global monitoring of vegetation status and is not limited to single-date phenological metrics. Using remote sensing also enables gaining a wider perspective to the seasonality of vegetation dynamics. The seasonal reflectance cycles of boreal forests observed in optical satellite images are explained by changes in biochemical properties and geometrical structure of vegetation as well as seasonal variation in solar illumination. This poster provides a synthesis of a research project (2010-2015) dedicated to monitoring the seasonal cycle of boreal forests. It is based on satellite and field data collected from the Hyytiälä Forestry Field Station in Finland. The results highlight the role understory vegetation has in forming the forest reflectance measured by satellite instruments.

Dynamic Covalent Chemistry within Biphenyl Scaffolds: Reversible Covalent Bonding, Control of Selectivity, and Chirality Sensing with a Single System.

PubMed

Ni, Cailing; Zha, Daijun; Ye, Hebo; Hai, Yu; Zhou, Yuntao; Anslyn, Eric V; You, Lei

2018-01-26

Axial chirality is a prevalent and important phenomenon in chemistry. Herein we report a combination of dynamic covalent chemistry and axial chirality for the development of a versatile platform for the binding and chirality sensing of multiple classes of mononucleophiles. An equilibrium between an open aldehyde and its cyclic hemiaminal within biphenyl derivatives enabled the dynamic incorporation of a broad range of alcohols, thiols, primary amines, and secondary amines with high efficiency. Selectivity toward different classes of nucleophiles was also achieved by regulating the distinct reactivity of the system with external stimuli. Through induced helicity as a result of central-to-axial chirality transfer, the handedness and ee values of chiral monoalcohol and monoamine analytes were reported by circular dichroism. The strategies introduced herein should find application in many contexts, including assembly, sensing, and labeling. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

A novel design of the high-precision magnetic locator with three-dimension measurement capability applying dynamically sensing mechanism

NASA Astrophysics Data System (ADS)

Huang, Wen-Nan; Chen, Po-Shen; Chen, Mu-Ping; Teng, Ching-Cheng

2006-09-01

A novel design of the magnetic locator, for obtaining the high-precision measurement information of variety of the buried metal pipes, is presented in this paper. The concept of dynamically sensing mechanism, including the vibrating and moving devices, proposed herein is a simple and effective way to improve the precision of three-dimension location sensing for the underground utilities. Based on the primary magnetism of Lenz's law and Faraday's law, the functions of the amplifying effect for the sensing magnetic signals, as well as the distinguishing effect by the simple filtering algorithms embedded in processing programs, are achieved while the relatively strong noise exists. The verification results of these integration designs demonstrate the effectiveness both by precise locating for the buried utility, and accurate measurement for the depth.

Optimal critic learning for robot control in time-varying environments.

PubMed

Wang, Chen; Li, Yanan; Ge, Shuzhi Sam; Lee, Tong Heng

2015-10-01

In this paper, optimal critic learning is developed for robot control in a time-varying environment. The unknown environment is described as a linear system with time-varying parameters, and impedance control is employed for the interaction control. Desired impedance parameters are obtained in the sense of an optimal realization of the composite of trajectory tracking and force regulation. Q -function-based critic learning is developed to determine the optimal impedance parameters without the knowledge of the system dynamics. The simulation results are presented and compared with existing methods, and the efficacy of the proposed method is verified.

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

Inertial measurement unit using rotatable MEMS sensors

DOEpatents

Kohler, Stewart M [Albuquerque, NM; Allen, James J [Albuquerque, NM

2007-05-01

A MEM inertial sensor (e.g. accelerometer, gyroscope) having integral rotational means for providing static and dynamic bias compensation is disclosed. A bias compensated MEM inertial sensor is described comprising a MEM inertial sense element disposed on a rotatable MEM stage. A MEM actuator drives the rotation of the stage between at least two predetermined rotational positions. Measuring and comparing the output of the MEM inertial sensor in the at least two rotational positions allows for both static and dynamic bias compensation in inertial calculations based on the sensor's output. An inertial measurement unit (IMU) comprising a plurality of independently rotatable MEM inertial sensors and methods for making bias compensated inertial measurements are disclosed.

Inertial measurement unit using rotatable MEMS sensors

DOEpatents

Kohler, Stewart M.; Allen, James J.

2006-06-27

A MEM inertial sensor (e.g. accelerometer, gyroscope) having integral rotational means for providing static and dynamic bias compensation is disclosed. A bias compensated MEM inertial sensor is described comprising a MEM inertial sense element disposed on a rotatable MEM stage. A MEM actuator for drives the rotation of the stage between at least two predetermined rotational positions. Measuring and comparing the output of the MEM inertial sensor in the at least two rotational positions allows, for both static and dynamic bias compensation in inertial calculations based on the sensor's output. An inertial measurement unit (IMU) comprising a plurality of independently rotatable MEM inertial sensors and methods for making bias compensated inertial measurements are disclosed.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Monitoring soil water dynamics at 0.1-1000 m scales using active DTS: the MOISST experience

NASA Astrophysics Data System (ADS)

Sayde, C.; Moreno, D.; Legrand, C.; Dong, J.; Steele-Dunne, S. C.; Ochsner, T. E.; Selker, J. S.

2014-12-01

The Actively Heated Fiber Optics (AHFO) method can measure soil water content at high temporal (<1hr) and spatial (every 0.25 m) resolutions along buried fiber optics (FO) cables multiple kilometers in length. As observed by Sayde et al. 2014, this unprecedented density of measurements captures soil water dynamics over four orders of magnitude in spatial scale (0.1-1000 m), bridging the gap between point scale measurements and large scale remote sensing. 4900 m of FO sensing cables were installed at the MOISST experimental site in Stillwater, Ok. The FO cables were deployed at 3 depths: 5, 10, and 15 cm. In this system the FO sensing system provides measurements of soil moisture at >39,000 locations simultaneously for each heat pulse. Six soil monitoring stations along the fiber optic path were installed to provide additional validation and calibration of the AHFO data. Gravimetric soil moisture and soil thermal samplings were performed periodically to provide additional distributed validation and calibration of the DTS data. In this work we present the preliminary results of this experiment. We will also address the experience learned from this large scale deployment of the AHFO method. In particular, we will present the in-situ soil moisture calibration method developed to tackle the calibration challenges associated with the high spatial heterogeneity of the soil physical and thermal properties. The material is based upon work supported by NASA under award NNX12AP58G, with equipment and assistance also provided by CTEMPs.org with support from the National Science Foundation under Grant Number 1129003. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of NASA or the National Science Foundation. Sayde, C., J. Benitez Buelga, L. Rodriguez-Sinobas, L. El Khoury, M. English, N. van de Giesen, and J.S. Selker (2014). Mapping Variability of Soil Water Content and Flux across 1-1,000 m scales using the Actively Heated Fiber Optic Method, Accepted for publication in Water Resour. Res.

Simultaneous Ionic Current and Potential Detection of Nanoparticles by a Multifunctional Nanopipette.

PubMed

Panday, Namuna; Qian, Gongming; Wang, Xuewen; Chang, Shuai; Pandey, Popular; He, Jin

2016-12-27

Nanopore sensing-based technologies have made significant progress for single molecule and single nanoparticle detection and analysis. In recent years, multimode sensing by multifunctional nanopores shows the potential to greatly improve the sensitivity and selectivity of traditional resistive-pulse sensing methods. In this paper, we showed that two label-free electric sensing modes could work cooperatively to detect the motion of 40 nm diameter spherical gold nanoparticles (GNPs) in solution by a multifunctional nanopipette. The multifunctional nanopipettes containing both nanopore and nanoelectrode (pyrolytic carbon) at the tip were fabricated quickly and cheaply. We demonstrated that the ionic current and local electrical potential changes could be detected simultaneously during the translocation of individual GNPs. We also showed that the nanopore/CNE tip geometry enabled the CNE not only to detect the translocation of single GNP but also to collectively detect several GNPs outside the nanopore entrance. The dynamic accumulation of GNPs near the nanopore entrance resulted in no detectable current changes, but was detected by the potential changes at the CNE. We revealed the motions of GNPs both outside and inside the nanopore, individually and collectively, with the combination of ionic current and potential measurements.

Construction of Green Tide Monitoring System and Research on its Key Techniques

NASA Astrophysics Data System (ADS)

Xing, B.; Li, J.; Zhu, H.; Wei, P.; Zhao, Y.

2018-04-01

As a kind of marine natural disaster, Green Tide has been appearing every year along the Qingdao Coast, bringing great loss to this region, since the large-scale bloom in 2008. Therefore, it is of great value to obtain the real time dynamic information about green tide distribution. In this study, methods of optical remote sensing and microwave remote sensing are employed in Green Tide Monitoring Research. A specific remote sensing data processing flow and a green tide information extraction algorithm are designed, according to the optical and microwave data of different characteristics. In the aspect of green tide spatial distribution information extraction, an automatic extraction algorithm of green tide distribution boundaries is designed based on the principle of mathematical morphology dilation/erosion. And key issues in information extraction, including the division of green tide regions, the obtaining of basic distributions, the limitation of distribution boundary, and the elimination of islands, have been solved. The automatic generation of green tide distribution boundaries from the results of remote sensing information extraction is realized. Finally, a green tide monitoring system is built based on IDL/GIS secondary development in the integrated environment of RS and GIS, achieving the integration of RS monitoring and information extraction.

Mechanical design optimization of a single-axis MOEMS accelerometer based on a grating interferometry cavity for ultrahigh sensitivity

NASA Astrophysics Data System (ADS)

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

2016-08-01

The ultrahigh static displacement-acceleration sensitivity of a mechanical sensing chip is essential primarily for an ultrasensitive accelerometer. In this paper, an optimal design to implement to a single-axis MOEMS accelerometer consisting of a grating interferometry cavity and a micromachined sensing chip is presented. The micromachined sensing chip is composed of a proof mass along with its mechanical cantilever suspension and substrate. The dimensional parameters of the sensing chip, including the length, width, thickness and position of the cantilevers are evaluated and optimized both analytically and by finite-element-method (FEM) simulation to yield an unprecedented acceleration-displacement sensitivity. Compared with one of the most sensitive single-axis MOEMS accelerometers reported in the literature, the optimal mechanical design can yield a profound sensitivity improvement with an equal footprint area, specifically, 200% improvement in displacement-acceleration sensitivity with moderate resonant frequency and dynamic range. The modified design was microfabricated, packaged with the grating interferometry cavity and tested. The experimental results demonstrate that the MOEMS accelerometer with modified design can achieve the acceleration-displacement sensitivity of about 150μm/g and acceleration sensitivity of greater than 1500V/g, which validates the effectiveness of the optimal design.

Platelike WO3 sensitized with CdS quantum dots heterostructures for photoelectrochemical dynamic sensing of H2O2 based on enzymatic etching.

PubMed

Wang, Yanhu; Gao, Chaomin; Ge, Shenguang; Yu, Jinghua; Yan, Mei

2016-11-15

A platelike tungsten trioxide (WO3) sensitized with CdS quantum dots (QDs) heterojunction is developed for solar-driven, real-time, and selective photoelectrochemical (PEC) sensing of H2O2 in the living cells. The structure is synthesized by hydrothermally growing platelike WO3 on fluorine doped tin oxide (FTO) and subsequently sensitized with CdS QDs. The as-prepared WO3-CdS QDs heterojunction achieve significant photocurrent enhancement, which is remarkably beneficial for light absorption and charge carrier separation. Based on the enzymatic etching of CdS QDs enables the activation of quenching the charge transfer efficiency, thus leading to sensitive PEC recording of H2O2 level in buffer and cellular environments. The results indicated that the proposed method will pave the way for the development of excellent PEC sensing platform with the quantum dot sensitization. This study could also provide a new train of thought on designing of self-operating photoanode in PEC sensing, promoting the application of semiconductor nanomaterials in photoelectrochemistry. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

Shape Sensing Techniques for Continuum Robots in Minimally Invasive Surgery: A Survey.

PubMed

Shi, Chaoyang; Luo, Xiongbiao; Qi, Peng; Li, Tianliang; Song, Shuang; Najdovski, Zoran; Fukuda, Toshio; Ren, Hongliang

2017-08-01

Continuum robots provide inherent structural compliance with high dexterity to access the surgical target sites along tortuous anatomical paths under constrained environments and enable to perform complex and delicate operations through small incisions in minimally invasive surgery. These advantages enable their broad applications with minimal trauma and make challenging clinical procedures possible with miniaturized instrumentation and high curvilinear access capabilities. However, their inherent deformable designs make it difficult to realize 3-D intraoperative real-time shape sensing to accurately model their shape. Solutions to this limitation can lead themselves to further develop closely associated techniques of closed-loop control, path planning, human-robot interaction, and surgical manipulation safety concerns in minimally invasive surgery. Although extensive model-based research that relies on kinematics and mechanics has been performed, accurate shape sensing of continuum robots remains challenging, particularly in cases of unknown and dynamic payloads. This survey investigates the recent advances in alternative emerging techniques for 3-D shape sensing in this field and focuses on the following categories: fiber-optic-sensor-based, electromagnetic-tracking-based, and intraoperative imaging modality-based shape-reconstruction methods. The limitations of existing technologies and prospects of new technologies are also discussed.

A Comparative evaluation of Graphene oxide based materials for Electrochemical non-enzymatic sensing of Curcumin

NASA Astrophysics Data System (ADS)

Dey, Nibedita; Devasena, T.; Sivalingam, Tamilarasu

2018-02-01

This work reports a comparative study on the development of a sensitive voltammetric method for the assay of diferuloylmethane which is fabricated using cost-effective sensing material graphene oxide (GO modified electrode) and reduced graphene oxide (rGO modified electrode) modified on glassy carbon electrode respectively. The prepared materials were characterized using SEM, XRD, FTIR, and Raman techniques to understand the formation. Between the both modified electrodes, rGO modified electrode demonstrated a lower limit detection of 0.9 pM and good signal quality. But, the better linear dynamic range for detection was found to be 1 nm to 100 nM for GO and 0.1 nM to 10 nM for rGO modified electrodes respectively. The repeatability is checked for seven cycles and interference studies were also performed for checking the sensors’ selectivity to curcumin. rGO modified electrode and GO modified electrode both shows specific signals for Diferuloylmethane under conditions similar to physiology. But, with better properties over GO modified electrode, rGO modified electrode is suggested a better candidate for real-time usability in sensing. The detection limit reported is the lowest till date for the given plant drug using any sensing assay.

A Nonlinearity Mitigation Method for a Broadband RF Front-End in a Sensor Based on Best Delay Searching

PubMed Central

Zhao, Wen; Ma, Hong; Zhang, Hua; Jin, Jiang; Dai, Gang; Hu, Lin

2017-01-01

The cognitive radio wireless sensor network (CR-WSN) is experiencing more and more attention for its capacity to automatically extract broadband instantaneous radio environment information. Obtaining sufficient linearity and spurious-free dynamic range (SFDR) is a significant premise of guaranteeing sensing performance which, however, usually suffers from the nonlinear distortion coming from the broadband radio frequency (RF) front-end in the sensor node. Moreover, unlike other existing methods, the joint effect of non-constant group delay distortion and nonlinear distortion is discussed, and its corresponding solution is provided in this paper. After that, the nonlinearity mitigation architecture based on best delay searching is proposed. Finally, verification experiments, both on simulation signals and signals from real-world measurement, are conducted and discussed. The achieved results demonstrate that with best delay searching, nonlinear distortion can be alleviated significantly and, in this way, spectrum sensing performance is more reliable and accurate. PMID:28956860

Emerging methods for the study of coastal ecosystem landscape structure and change

USGS Publications Warehouse

Brock, John C.; Danielson, Jeffrey J.; Purkis, Sam

2013-01-01

Coastal landscapes are heterogeneous, dynamic, and evolve over a range of time scales due to intertwined climatic, geologic, hydrologic, biologic, and meteorological processes, and are also heavily impacted by human development, commercial activities, and resource extraction. A diversity of complex coastal systems around the globe, spanning glaciated shorelines to tropical atolls, wetlands, and barrier islands are responding to multiple human and natural drivers. Interdisciplinary research based on remote-sensing observations linked to process studies and models is required to understand coastal ecosystem landscape structure and change. Moreover, new techniques for coastal mapping and monitoring are increasingly serving the needs of policy-makers and resource managers across local, regional, and national scales. Emerging remote-sensing methods associated with a diversity of instruments and platforms are a key enabling element of integrated coastal ecosystem studies. These investigations require both targeted and synoptic mapping, and involve the monitoring of formative processes such as hydrodynamics, sediment transport, erosion, accretion, flooding, habitat modification, land-cover change, and biogeochemical fluxes.

Self-doped polyaniline multifunctional optical probes in confined nanostructure for pH sensing

NASA Astrophysics Data System (ADS)

Hong, Yoochan; Hwang, Seungyeon; Yang, Jaemoon

2017-07-01

We have successfully fabricated nanocomposite, which is composed of polyaniline (PAni) and pyrene butyric acid (Pyba) via solvent shift method, and the outer layer was enclosed by Tween 80 as a surfactant. First of all, the various ratios between PAni and Pyba were applied for synthesis of polyaniline nanocomposite, and an identical condition for exhibition of proper absorbance and fluorescence properties was found out. The morphology of polyaniline nanocomposite was confirmed via scanning electron microscopic imaging and hydrodynamic size was also confirmed by dynamic light scattering method. We demonstrated that confined self-doped polyaniline nanocomposite as a pH sensing agent are preserved in the doped state even at a neutral pH value. Especially, PAni exhibited strong convertible property at absorbance spectra, on the other hand, Pyba showed changing property at fluorescence spectra at various pH values. In conclude, this polyaniline nanocomposite can accomplish as a fine nanoagent expressing absorbance and fluorescence properties according to surrounding pH values.

Wavelet-based multiscale analysis of bioimpedance data measured by electric cell-substrate impedance sensing for classification of cancerous and normal cells.

PubMed

Das, Debanjan; Shiladitya, Kumar; Biswas, Karabi; Dutta, Pranab Kumar; Parekh, Aditya; Mandal, Mahitosh; Das, Soumen

2015-12-01

The paper presents a study to differentiate normal and cancerous cells using label-free bioimpedance signal measured by electric cell-substrate impedance sensing. The real-time-measured bioimpedance data of human breast cancer cells and human epithelial normal cells employs fluctuations of impedance value due to cellular micromotions resulting from dynamic structural rearrangement of membrane protrusions under nonagitated condition. Here, a wavelet-based multiscale quantitative analysis technique has been applied to analyze the fluctuations in bioimpedance. The study demonstrates a method to classify cancerous and normal cells from the signature of their impedance fluctuations. The fluctuations associated with cellular micromotion are quantified in terms of cellular energy, cellular power dissipation, and cellular moments. The cellular energy and power dissipation are found higher for cancerous cells associated with higher micromotions in cancer cells. The initial study suggests that proposed wavelet-based quantitative technique promises to be an effective method to analyze real-time bioimpedance signal for distinguishing cancer and normal cells.

Fiber optic pressure sensors in skin-friction measurements

NASA Technical Reports Server (NTRS)

Cuomo, F. W.

1986-01-01

A fiber optic lever sensing technique that can be used to measure normal pressure as well as shear stresses is discussed. This method uses three unequal fibers combining small size and good sensitivity. Static measurements appear to confirm the theoretical models predicted by geometrical optics and dynamic tests performed at frequencies up to 10 kHz indicate a flat response within this frequency range. These sensors are intended for use in a low speed wind tunnel environment.

The Evolution of Israeli Civil-Military Relations: Domestic Enablers and the Quest for Peace

DTIC Science & Technology

2009-12-01

Israeli society, its sense of security, and its view of military institutions. It is safe to assume, however, the changing social attitudes will...It is safe to assume, however, the changing social attitudes will continue to shape the state’s often obscure civil-military dynamic, which will...2 (2005): 231. “For Israelis, armed conflict became the ultimate method of resolving the issue of their state’s disputed existence.” 5 Charles D

Adsorption dynamics of CVD graphene investigated by a contactless microwave method

NASA Astrophysics Data System (ADS)

Black, N. C. G.; Rungger, I.; Li, B.; Maier, S. A.; Cohen, L. F.; Gallop, J. C.; Hao, L.

2018-07-01

We use a contactless microwave dielectric resonator gas sensing platform to study the adsorption dynamics of NO2 gas present in air onto a graphene surface. The use of microwaves removes the need for metal contacts that would otherwise be necessary for traditional conductivity measurements, and therefore allows non-invasive determination of NO2 concentrations to sub parts per million. As a result, gas‑metal interactions and localised graphene doping in the vicinity of metal contacts are eliminated, with the advantage that only graphene‑gas adsorbate interactions are responsible for the measured signal. We show that the sensor response for all considered concentrations can be described using a surface coverage dependent Langmuir model. We demonstrate that the possible variation of the NO2 binding energy, which is frequently considered as the main parameter, plays only a secondary role compared to the rising adsorption energy barrier with increasing NO2 coverage. The continuous distribution of the properties of the graphene adsorption sites used in the theoretical model is supported by our Kelvin probe and Raman surface analysis. Our results demonstrate that the non-invasive microwave method is a promising alternative platform for gas sensing. Moreover it provides valuable insights towards the understanding of the microscopic processes occurring in graphene based gas sensors, which is a key factor in the realization of reproducible and optimized device properties.

Remotely Sensed Based Lake/Reservoir Routing in Congo River Basin

NASA Astrophysics Data System (ADS)

Raoufi, R.; Beighley, E.; Lee, H.

2017-12-01

Lake and reservoir dynamics can influence local to regional water cycles but are often not well represented in hydrologic models. One challenge that limits their inclusion in models is the need for detailed storage-discharge behavior that can be further complicated in reservoirs where specific operation rules are employed. Here, the Hillslope River Routing (HRR) model is combined with a remotely sensed based Reservoir Routing (RR) method and applied to the Congo River Basin. Given that topographic data are often continuous over the entire terrestrial surface (i.e., does not differentiate between land and open water), the HRR-RR model integrates topographic derived river networks and catchment boundaries (e.g., HydroSHEDs) with water boundary extents (e.g., Global Lakes and Wetlands Database) to develop the computational framework. The catchments bordering lakes and reservoirs are partitioned into water and land portions, where representative flowpath characteristics are determined and vertical water balance and lateral routings is performed separately on each partition based on applicable process models (e.g., open water evaporation vs. evapotranspiration). To enable reservoir routing, remotely sensed water surface elevations and extents are combined to determine the storage change time series. Based on the available time series, representative storage change patterns are determined. Lake/reservoir routing is performed by combining inflows from the HRR-RR model and the representative storage change patterns to determine outflows. In this study, a suite of storage change patterns derived from remotely sensed measurements are determined representative patterns for wet, dry and average conditions. The HRR-RR model dynamically selects and uses the optimal storage change pattern for the routing process based on these hydrologic conditions. The HRR-RR model results are presented to highlight the importance of lake attenuation/routing in the Congo Basin.

Distributed Compressive Sensing vs. Dynamic Compressive Sensing: Improving the Compressive Line Sensing Imaging System through Their Integration

DTIC Science & Technology

2015-01-01

streak tube imaging Lidar [15]. Nevertheless, instead of one- dimensional (1D) fan beam, a laser source modulates the digital micromirror device DMD and...Trans. Inform. Theory, vol. 52, pp. 1289-1306, 2006. [10] D. Dudley, W. Duncan and J. Slaughter, "Emerging Digital Micromirror Device (DMD) Applications

Forest canopy growth dynamic modeling based on remote sensing prodcuts and meteorological data in Daxing'anling of Northeast China

NASA Astrophysics Data System (ADS)

Wu, Qiaoli; Song, Jinling; Wang, Jindi; Xiao, Zhiqiang

2014-11-01

Leaf Area Index (LAI) is an important biophysical variable for vegetation. Compared with vegetation indexes like NDVI and EVI, LAI is more capable of monitoring forest canopy growth quantitatively. GLASS LAI is a spatially complete and temporally continuous product derived from AVHRR and MODIS reflectance data. In this paper, we present the approach to build dynamic LAI growth models for young and mature Larix gmelinii forest in north Daxing'anling in Inner Mongolia of China using the Dynamic Harmonic Regression (DHR) model and Double Logistic (D-L) model respectively, based on the time series extracted from multi-temporal GLASS LAI data. Meanwhile we used the dynamic threshold method to attract the key phenological phases of Larix gmelinii forest from the simulated time series. Then, through the relationship analysis between phenological phases and the meteorological factors, we found that the annual peak LAI and the annual maximum temperature have a good correlation coefficient. The results indicate this forest canopy growth dynamic model to be very effective in predicting forest canopy LAI growth and extracting forest canopy LAI growth dynamic.

New Interest in Wild Forest Products in Europe as an Expression of Biocultural Dynamics.

PubMed

Wiersum, K F

2017-01-01

In Europe, interest in wild forest products is increasing. Such products may be interpreted in a biological sense as deriving from autonomously growing forest species or in a biocultural sense as reflecting dynamics in human living with biodiversity through re-wilding of earlier domesticated species. In this article I elaborate the idea that the new interests reflect biocultural dynamics. First, I identify these dynamics as involving both domestication and re-wilding and characterize these processes as involving biological, environmental, and cultural dimensions. Next, I present a comparative review of two approaches to re-wilding forest production in the Netherlands: meat production from new types of natural grazing systems, and food production from plants re-introduced to the wild. The first approach is based on the stimulation of naturally occurring ecological processes and the second on the stimulation of new forms of experiencing bio-cultural heritage. The examples demonstrate that the new interests in wild forest products involve both a return to earlier stages of domestication in an ecological sense and a new phase of acculturation to evolving socio-cultural conditions.

Awareness-based game-theoretic space resource management

NASA Astrophysics Data System (ADS)

Chen, Genshe; Chen, Huimin; Pham, Khanh; Blasch, Erik; Cruz, Jose B., Jr.

2009-05-01

Over recent decades, the space environment becomes more complex with a significant increase in space debris and a greater density of spacecraft, which poses great difficulties to efficient and reliable space operations. In this paper we present a Hierarchical Sensor Management (HSM) method to space operations by (a) accommodating awareness modeling and updating and (b) collaborative search and tracking space objects. The basic approach is described as follows. Firstly, partition the relevant region of interest into district cells. Second, initialize and model the dynamics of each cell with awareness and object covariance according to prior information. Secondly, explicitly assign sensing resources to objects with user specified requirements. Note that when an object has intelligent response to the sensing event, the sensor assigned to observe an intelligent object may switch from time-to-time between a strong, active signal mode and a passive mode to maximize the total amount of information to be obtained over a multi-step time horizon and avoid risks. Thirdly, if all explicitly specified requirements are satisfied and there are still more sensing resources available, we assign the additional sensing resources to objects without explicitly specified requirements via an information based approach. Finally, sensor scheduling is applied to each sensor-object or sensor-cell pair according to the object type. We demonstrate our method with realistic space resources management scenario using NASA's General Mission Analysis Tool (GMAT) for space object search and track with multiple space borne observers.

Spatio-Temporal Field Estimation Using Kriged Kalman Filter (KKF) with Sparsity-Enforcing Sensor Placement.

PubMed

Roy, Venkat; Simonetto, Andrea; Leus, Geert

2018-06-01

We propose a sensor placement method for spatio-temporal field estimation based on a kriged Kalman filter (KKF) using a network of static or mobile sensors. The developed framework dynamically designs the optimal constellation to place the sensors. We combine the estimation error (for the stationary as well as non-stationary component of the field) minimization problem with a sparsity-enforcing penalty to design the optimal sensor constellation in an economic manner. The developed sensor placement method can be directly used for a general class of covariance matrices (ill-conditioned or well-conditioned) modelling the spatial variability of the stationary component of the field, which acts as a correlated observation noise, while estimating the non-stationary component of the field. Finally, a KKF estimator is used to estimate the field using the measurements from the selected sensing locations. Numerical results are provided to exhibit the feasibility of the proposed dynamic sensor placement followed by the KKF estimation method.

Stepwise inference of likely dynamic flux distributions from metabolic time series data.

PubMed

Faraji, Mojdeh; Voit, Eberhard O

2017-07-15

Most metabolic pathways contain more reactions than metabolites and therefore have a wide stoichiometric matrix that corresponds to infinitely many possible flux distributions that are perfectly compatible with the dynamics of the metabolites in a given dataset. This under-determinedness poses a challenge for the quantitative characterization of flux distributions from time series data and thus for the design of adequate, predictive models. Here we propose a method that reduces the degrees of freedom in a stepwise manner and leads to a dynamic flux distribution that is, in a statistical sense, likely to be close to the true distribution. We applied the proposed method to the lignin biosynthesis pathway in switchgrass. The system consists of 16 metabolites and 23 enzymatic reactions. It has seven degrees of freedom and therefore admits a large space of dynamic flux distributions that all fit a set of metabolic time series data equally well. The proposed method reduces this space in a systematic and biologically reasonable manner and converges to a likely dynamic flux distribution in just a few iterations. The estimated solution and the true flux distribution, which is known in this case, show excellent agreement and thereby lend support to the method. The computational model was implemented in MATLAB (version R2014a, The MathWorks, Natick, MA). The source code is available at https://github.gatech.edu/VoitLab/Stepwise-Inference-of-Likely-Dynamic-Flux-Distributions and www.bst.bme.gatech.edu/research.php . mojdeh@gatech.edu or eberhard.voit@bme.gatech.edu. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Effects of land use/cover change and harvests on forest carbon dynamics in northern states of the United States from remote sensing and inventory data: 1992-2001

Treesearch

Daolan Zheng; Linda S. Heath; Mark J. Ducey; James E. Smith

2011-01-01

We examined spatial patterns of changes in forest area and nonsoil carbon (C) dynamics affected by land use/cover change (LUC) and harvests in 24 northern states of the United States using an integrated methodology combining remote sensing and ground inventory data between 1992 and 2001. We used the Retrofit Change Product from the Multi-Resolution Land Characteristics...

Evolution of the cerebellum as a neuronal machine for Bayesian state estimation

NASA Astrophysics Data System (ADS)

Paulin, M. G.

2005-09-01

The cerebellum evolved in association with the electric sense and vestibular sense of the earliest vertebrates. Accurate information provided by these sensory systems would have been essential for precise control of orienting behavior in predation. A simple model shows that individual spikes in electrosensory primary afferent neurons can be interpreted as measurements of prey location. Using this result, I construct a computational neural model in which the spatial distribution of spikes in a secondary electrosensory map forms a Monte Carlo approximation to the Bayesian posterior distribution of prey locations given the sense data. The neural circuit that emerges naturally to perform this task resembles the cerebellar-like hindbrain electrosensory filtering circuitry of sharks and other electrosensory vertebrates. The optimal filtering mechanism can be extended to handle dynamical targets observed from a dynamical platform; that is, to construct an optimal dynamical state estimator using spiking neurons. This may provide a generic model of cerebellar computation. Vertebrate motion-sensing neurons have specific fractional-order dynamical characteristics that allow Bayesian state estimators to be implemented elegantly and efficiently, using simple operations with asynchronous pulses, i.e. spikes. The computational neural models described in this paper represent a novel kind of particle filter, using spikes as particles. The models are specific and make testable predictions about computational mechanisms in cerebellar circuitry, while providing a plausible explanation of cerebellar contributions to aspects of motor control, perception and cognition.

Two worlds collide: Image analysis methods for quantifying structural variation in cluster molecular dynamics

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

Steenbergen, K. G., E-mail: kgsteen@gmail.com; Gaston, N.

2014-02-14

Inspired by methods of remote sensing image analysis, we analyze structural variation in cluster molecular dynamics (MD) simulations through a unique application of the principal component analysis (PCA) and Pearson Correlation Coefficient (PCC). The PCA analysis characterizes the geometric shape of the cluster structure at each time step, yielding a detailed and quantitative measure of structural stability and variation at finite temperature. Our PCC analysis captures bond structure variation in MD, which can be used to both supplement the PCA analysis as well as compare bond patterns between different cluster sizes. Relying only on atomic position data, without requirement formore » a priori structural input, PCA and PCC can be used to analyze both classical and ab initio MD simulations for any cluster composition or electronic configuration. Taken together, these statistical tools represent powerful new techniques for quantitative structural characterization and isomer identification in cluster MD.« less

Two worlds collide: image analysis methods for quantifying structural variation in cluster molecular dynamics.

PubMed

Steenbergen, K G; Gaston, N

2014-02-14

Inspired by methods of remote sensing image analysis, we analyze structural variation in cluster molecular dynamics (MD) simulations through a unique application of the principal component analysis (PCA) and Pearson Correlation Coefficient (PCC). The PCA analysis characterizes the geometric shape of the cluster structure at each time step, yielding a detailed and quantitative measure of structural stability and variation at finite temperature. Our PCC analysis captures bond structure variation in MD, which can be used to both supplement the PCA analysis as well as compare bond patterns between different cluster sizes. Relying only on atomic position data, without requirement for a priori structural input, PCA and PCC can be used to analyze both classical and ab initio MD simulations for any cluster composition or electronic configuration. Taken together, these statistical tools represent powerful new techniques for quantitative structural characterization and isomer identification in cluster MD.

Mapping and modeling the urban landscape in Bangkok, Thailand: Physical-spectral-spatial relations of population-environmental interactions

NASA Astrophysics Data System (ADS)

Shao, Yang

This research focuses on the application of remote sensing, geographic information systems, statistical modeling, and spatial analysis to examine the dynamics of urban land cover, urban structure, and population-environment interactions in Bangkok, Thailand, with an emphasis on rural-to-urban migration from rural Nang Rong District, Northeast Thailand to the primate city of Bangkok. The dissertation consists of four main sections: (1) development of remote sensing image classification and change-detection methods for characterizing imperviousness for Bangkok, Thailand from 1993-2002; (2) development of 3-D urban mapping methods, using high spatial resolution IKONOS satellite images, to assess high-rises and other urban structures; (3) assessment of urban spatial structure from 2-D and 3-D perspectives; and (4) an analysis of the spatial clustering of migrants from Nang Rong District in Bangkok and the neighborhood environments of migrants' locations. Techniques are developed to improve the accuracy of the neural network classification approach for the analysis of remote sensing data, with an emphasis on the spectral unmixing problem. The 3-D building heights are derived using the shadow information on the high-resolution IKONOS image. The results from the 2-D and 3-D mapping are further examined to assess urban structure and urban feature identification. This research contributes to image processing of remotely-sensed images and urban studies. The rural-urban migration process and migrants' settlement patterns are examined using spatial statistics, GIS, and remote sensing perspectives. The results show that migrants' spatial clustering in urban space is associated with the source village and a number of socio-demographic variables. In addition, the migrants' neighborhood environments in urban setting are modeled using a set of geographic and socio-demographic variables, and the results are scale-dependent.

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Kullback-Leibler Divergence-Based Differential Evolution Markov Chain Filter for Global Localization of Mobile Robots.

PubMed

Martín, Fernando; Moreno, Luis; Garrido, Santiago; Blanco, Dolores

2015-09-16

One of the most important skills desired for a mobile robot is the ability to obtain its own location even in challenging environments. The information provided by the sensing system is used here to solve the global localization problem. In our previous work, we designed different algorithms founded on evolutionary strategies in order to solve the aforementioned task. The latest developments are presented in this paper. The engine of the localization module is a combination of the Markov chain Monte Carlo sampling technique and the Differential Evolution method, which results in a particle filter based on the minimization of a fitness function. The robot's pose is estimated from a set of possible locations weighted by a cost value. The measurements of the perceptive sensors are used together with the predicted ones in a known map to define a cost function to optimize. Although most localization methods rely on quadratic fitness functions, the sensed information is processed asymmetrically in this filter. The Kullback-Leibler divergence is the basis of a cost function that makes it possible to deal with different types of occlusions. The algorithm performance has been checked in a real map. The results are excellent in environments with dynamic and unmodeled obstacles, a fact that causes occlusions in the sensing area.

Kullback-Leibler Divergence-Based Differential Evolution Markov Chain Filter for Global Localization of Mobile Robots

PubMed Central

Martín, Fernando; Moreno, Luis; Garrido, Santiago; Blanco, Dolores

2015-01-01

One of the most important skills desired for a mobile robot is the ability to obtain its own location even in challenging environments. The information provided by the sensing system is used here to solve the global localization problem. In our previous work, we designed different algorithms founded on evolutionary strategies in order to solve the aforementioned task. The latest developments are presented in this paper. The engine of the localization module is a combination of the Markov chain Monte Carlo sampling technique and the Differential Evolution method, which results in a particle filter based on the minimization of a fitness function. The robot’s pose is estimated from a set of possible locations weighted by a cost value. The measurements of the perceptive sensors are used together with the predicted ones in a known map to define a cost function to optimize. Although most localization methods rely on quadratic fitness functions, the sensed information is processed asymmetrically in this filter. The Kullback-Leibler divergence is the basis of a cost function that makes it possible to deal with different types of occlusions. The algorithm performance has been checked in a real map. The results are excellent in environments with dynamic and unmodeled obstacles, a fact that causes occlusions in the sensing area. PMID:26389914

Research on Land Use Changes in Panjin City Basing on Remote Sensing Data

NASA Astrophysics Data System (ADS)

Ding, Hua; Li, Ru Ren; Shuang Sun, Li; Wang, Xin; Liu, Yu Mei

2018-05-01

Taking Landsat remote sensing image as the main data source, the research on land use changes in Panjin City in 2005 to 2015 is made with the support of remote sensing platform and GIS platform in this paper; the range of land use changes and change rate are analyzed through the classification of remote sensing image; the dynamic analysis on land changes is made with the help of transfer matrix of land use type; the quantitative calculation on all kinds of dynamic change features of land changes is made by utilizing mathematical model; and the analysis on driving factors of land changes of image is made at last. The research results show that, in recent ten years, the area of cultivated land in Panjin City decreased, the area of vegetation increased, and meanwhile the area of road increased drastically, the settlement place decreased than ever, and water area changed slightly.

Full load estimation of an offshore wind turbine based on SCADA and accelerometer data

NASA Astrophysics Data System (ADS)

Noppe, N.; Iliopoulos, A.; Weijtjens, W.; Devriendt, C.

2016-09-01

As offshore wind farms (OWFs) grow older, the optimal use of the actual fatigue lifetime of an offshore wind turbine (OWT) and predominantly its foundation will get more important. In case of OWTs, both quasi-static wind/thrust loads and dynamic loads, as induced by turbulence, waves and the turbine's dynamics, contribute to its fatigue life progression. To estimate the remaining useful life of an OWT, the stresses acting on the fatigue critical locations within the structure should be monitored continuously. Unfortunately, in case of the most common monopile foundations these locations are often situated below sea-level and near the mud line and thus difficult or even impossible to access for existing OWTs. Actual strain measurements taken at accessible locations above the sea level show a correlation between thrust load and several SCADA parameters. Therefore a model is created to estimate the thrust load using SCADA data and strain measurements. Afterwards the thrust load acting on the OWT is estimated using the created model and SCADA data only. From this model the quasi static loads on the foundation can be estimated over the lifetime of the OWT. To estimate the contribution of the dynamic loads a modal decomposition and expansion based virtual sensing technique is applied. This method only uses acceleration measurements recorded at accessible locations on the tower. Superimposing both contributions leads to a so-called multi-band virtual sensing. The result is a method that allows to estimate the strain history at any location on the foundation and thus the full load, being a combination of both quasi-static and dynamic loads, acting on the entire structure. This approach is validated using data from an operating Belgian OWF. An initial good match between measured and predicted strains for a short period of time proofs the concept.

Cat-eye effect target recognition with single-pixel detectors

NASA Astrophysics Data System (ADS)

Jian, Weijian; Li, Li; Zhang, Xiaoyue

2015-12-01

A prototype of cat-eye effect target recognition with single-pixel detectors is proposed. Based on the framework of compressive sensing, it is possible to recognize cat-eye effect targets by projecting a series of known random patterns and measuring the backscattered light with three single-pixel detectors in different locations. The prototype only requires simpler, less expensive detectors and extends well beyond the visible spectrum. The simulations are accomplished to evaluate the feasibility of the proposed prototype. We compared our results to that obtained from conventional cat-eye effect target recognition methods using area array sensor. The experimental results show that this method is feasible and superior to the conventional method in dynamic and complicated backgrounds.

Analysis of economic values of land use and land cover changes in crisis territories by satellite data: models of socio-economy and population dynamics in war

NASA Astrophysics Data System (ADS)

Kostyuchenko, Yuriy V.; Yuschenko, Maxim; Movchan, Dmytro; Kopachevsky, Ivan

2017-10-01

Problem of remote sensing data harnessing for decision making in conflict territories is considered. Approach for analysis of socio-economic and demographic parameters with a limited set of data and deep uncertainty is described. Number of interlinked techniques to estimate a population and economy in crisis territories are proposed. Stochastic method to assessment of population dynamics using multi-source data using remote sensing data is proposed. Adaptive Markov's chain based method to study of land-use changes using satellite data is proposed. Proposed approach is applied to analysis of socio-economic situation in Donbas (East Ukraine) territory of conflict in 2014-2015. Land-use and landcover patterns for different periods were analyzed using the Landsat and MODIS data . The land-use classification scheme includes the following categories: (1) urban or built-up land, (2) barren land, (3) cropland, (4) horticulture farms, (5) livestock farms, (6) forest, and (7) water. It was demonstrated, that during the period 2014-2015 was not detected drastic changes in land-use structure of study area. Heterogeneously distributed decreasing of horticulture farms (4-6%), livestock farms (5-6%), croplands (3-4%), and increasing of barren land (6-7%) have been observed. Way to analyze land-cover productivity variations using satellite data is proposed. Algorithm is based on analysis of time-series of NDVI and NDWI distributions. Drastic changes of crop area and its productivity were detected. Set of indirect indicators, such as night light intensity, is also considered. Using the approach proposed, using the data utilized, the local and regional GDP, local population, and its dynamics are estimated.

Spectrum sensing and resource allocation for multicarrier cognitive radio systems under interference and power constraints

NASA Astrophysics Data System (ADS)

Dikmese, Sener; Srinivasan, Sudharsan; Shaat, Musbah; Bader, Faouzi; Renfors, Markku

2014-12-01

Multicarrier waveforms have been commonly recognized as strong candidates for cognitive radio. In this paper, we study the dynamics of spectrum sensing and spectrum allocation functions in cognitive radio context using very practical signal models for the primary users (PUs), including the effects of power amplifier nonlinearities. We start by sensing the spectrum with energy detection-based wideband multichannel spectrum sensing algorithm and continue by investigating optimal resource allocation methods. Along the way, we examine the effects of spectral regrowth due to the inevitable power amplifier nonlinearities of the PU transmitters. The signal model includes frequency selective block-fading channel models for both secondary and primary transmissions. Filter bank-based wideband spectrum sensing techniques are applied for detecting spectral holes and filter bank-based multicarrier (FBMC) modulation is selected for transmission as an alternative multicarrier waveform to avoid the disadvantage of limited spectral containment of orthogonal frequency-division multiplexing (OFDM)-based multicarrier systems. The optimization technique used for the resource allocation approach considered in this study utilizes the information obtained through spectrum sensing and knowledge of spectrum leakage effects of the underlying waveforms, including a practical power amplifier model for the PU transmitter. This study utilizes a computationally efficient algorithm to maximize the SU link capacity with power and interference constraints. It is seen that the SU transmission capacity depends critically on the spectral containment of the PU waveform, and these effects are quantified in a case study using an 802.11-g WLAN scenario.

Cochlea-inspired sensing node for compressive sensing

NASA Astrophysics Data System (ADS)

Peckens, Courtney A.; Lynch, Jerome P.

2013-04-01

While sensing technologies for structural monitoring applications have made significant advances over the last several decades, there is still room for improvement in terms of computational efficiency, as well as overall energy consumption. The biological nervous system can offer a potential solution to address these current deficiencies. The nervous system is capable of sensing and aggregating information about the external environment through very crude processing units known as neurons. Neurons effectively communicate in an extremely condensed format by encoding information into binary electrical spike trains, thereby reducing the amount of raw information sent throughout a neural network. Due to its unique signal processing capabilities, the mammalian cochlea and its interaction with the biological nervous system is of particular interest for devising compressive sensing strategies for dynamic engineered systems. The cochlea uses a novel method of place theory and frequency decomposition, thereby allowing for rapid signal processing within the nervous system. In this study, a low-power sensing node is proposed that draws inspiration from the mechanisms employed by the cochlea and the biological nervous system. As such, the sensor is able to perceive and transmit a compressed representation of the external stimulus with minimal distortion. Each sensor represents a basic building block, with function similar to the neuron, and can form a network with other sensors, thus enabling a system that can convey input stimulus in an extremely condensed format. The proposed sensor is validated through a structural monitoring application of a single degree of freedom structure excited by seismic ground motion.

Combining remote sensing and watershed modeling for regional-scale carbon cycling studies in disturbance-prone systems

NASA Astrophysics Data System (ADS)

Hanan, E. J.; Tague, C.; Choate, J.; Liu, M.; Adam, J. C.

2016-12-01

Disturbance is a major force regulating C dynamics in terrestrial ecosystems. Evaluating future C balance in disturbance-prone systems requires understanding the underlying mechanisms that drive ecosystem processes over multiple scales of space and time. Simulation modeling is a powerful tool for bridging these scales, however, model projections are limited by large uncertainties in the initial state of vegetation C and N stores. Watershed models typically use one of two methods to initialize these stores. Spin up involves running a model until vegetation reaches steady state based on climate. This "potential" state however assumes the vegetation across the entire watershed has reached maturity and has a homogeneous age distribution. Yet to reliably represent C and N dynamics in disturbance-prone systems, models should be initialized to reflect their non-equilibrium conditions. Alternatively, remote sensing of a single vegetation parameter (typically leaf area index; LAI) can be combined with allometric relationships to allocate C and N to model stores and can reflect non-steady-state conditions. However, allometric relationships are species and region specific and do not account for environmental variation, thus resulting in C and N stores that may be unstable. To address this problem, we developed a new approach for initializing C and N pools using the watershed-scale ecohydrologic model RHESSys. The new approach merges the mechanistic stability of spinup with the spatial fidelity of remote sensing. Unlike traditional spin up, this approach supports non-homogeneous stand ages. We tested our approach in a pine-dominated watershed in central Idaho, which partially burned in July of 2000. We used LANDSAT and MODIS data to calculate LAI across the watershed following the 2000 fire. We then ran three sets of simulations using spin up, direct measurements, and the combined approach to initialize vegetation C and N stores, and compared our results to remotely sensed LAI following the simulation period. Model estimates of C, N, and water fluxes varied depending on which approach was used. The combined approach provided the best LAI estimates after 10 years of simulation. This method shows promise for improving projections of C, N, and water fluxes in disturbance-prone watersheds.

Dynamic traversal of large gaps by insects and legged robots reveals a template.

PubMed

Gart, Sean W; Yan, Changxin; Othayoth, Ratan; Ren, Zhiyi; Li, Chen

2018-02-02

It is well known that animals can use neural and sensory feedback via vision, tactile sensing, and echolocation to negotiate obstacles. Similarly, most robots use deliberate or reactive planning to avoid obstacles, which relies on prior knowledge or high-fidelity sensing of the environment. However, during dynamic locomotion in complex, novel, 3D terrains, such as a forest floor and building rubble, sensing and planning suffer bandwidth limitation and large noise and are sometimes even impossible. Here, we study rapid locomotion over a large gap-a simple, ubiquitous obstacle-to begin to discover the general principles of the dynamic traversal of large 3D obstacles. We challenged the discoid cockroach and an open-loop six-legged robot to traverse a large gap of varying length. Both the animal and the robot could dynamically traverse a gap as large as one body length by bridging the gap with its head, but traversal probability decreased with gap length. Based on these observations, we developed a template that accurately captured body dynamics and quantitatively predicted traversal performance. Our template revealed that a high approach speed, initial body pitch, and initial body pitch angular velocity facilitated dynamic traversal, and successfully predicted a new strategy for using body pitch control that increased the robot's maximal traversal gap length by 50%. Our study established the first template of dynamic locomotion beyond planar surfaces, and is an important step in expanding terradynamics into complex 3D terrains.

A Model of Rapid Radicalization Behavior Using Agent-Based Modeling and Quorum Sensing

NASA Technical Reports Server (NTRS)

Schwartz, Noah; Drucker, Nick; Campbell, Kenyth

2012-01-01

Understanding the dynamics of radicalization, especially rapid radicalization, has become increasingly important to US policy in the past several years. Traditionally, radicalization is considered a slow process, but recent social and political events demonstrate that the process can occur quickly. Examining this rapid process, in real time, is impossible. However, recreating an event using modeling and simulation (M&S) allows researchers to study some of the complex dynamics associated with rapid radicalization. We propose to adapt the biological mechanism of quorum sensing as a tool to explore, or possibly explain, rapid radicalization. Due to the complex nature of quorum sensing, M&S allows us to examine events that we could not otherwise examine in real time. For this study, we employ Agent Based Modeling (ABM), an M&S paradigm suited to modeling group behavior. The result of this study was the successful creation of rapid radicalization using quorum sensing. The Battle of Mogadishu was the inspiration for this model and provided the testing conditions used to explore quorum sensing and the ideas behind rapid radicalization. The final product has wider applicability however, using quorum sensing as a possible tool for examining other catalytic rapid radicalization events.

A High Sensitivity IDC-Electronic Tongue Using Dielectric/Sensing Membranes with Solvatochromic Dyes

PubMed Central

Khan, Md. Rajibur Rahaman; Khalilian, Alireza; Kang, Shin-Won

2016-01-01

In this paper, an electronic tongue/taste sensor array containing different interdigitated capacitor (IDC) sensing elements to detect different types of tastes, such as sweetness (glucose), saltiness (NaCl), sourness (HCl), bitterness (quinine-HCl), and umami (monosodium glutamate) is proposed. We present for the first time an IDC electronic tongue using sensing membranes containing solvatochromic dyes. The proposed highly sensitive (30.64 mV/decade sensitivity) IDC electronic tongue has fast response and recovery times of about 6 s and 5 s, respectively, with extremely stable responses, and is capable of linear sensing performance (R2 ≈ 0.985 correlation coefficient) over the wide dynamic range of 1 µM to 1 M. The designed IDC electronic tongue offers excellent reproducibility, with a relative standard deviation (RSD) of about 0.029. The proposed device was found to have better sensing performance than potentiometric-, cascoded compatible lateral bipolar transistor (C-CLBT)-, Electronic Tongue (SA402)-, and fiber-optic-based taste sensing systems in what concerns dynamic range width, response time, sensitivity, and linearity. Finally, we applied principal component analysis (PCA) to distinguish between various kinds of taste in mixed taste compounds. PMID:27171095

A High Sensitivity IDC-Electronic Tongue Using Dielectric/Sensing Membranes with Solvatochromic Dyes.

PubMed

Khan, Md Rajibur Rahaman; Khalilian, Alireza; Kang, Shin-Won

2016-05-10

In this paper, an electronic tongue/taste sensor array containing different interdigitated capacitor (IDC) sensing elements to detect different types of tastes, such as sweetness (glucose), saltiness (NaCl), sourness (HCl), bitterness (quinine-HCl), and umami (monosodium glutamate) is proposed. We present for the first time an IDC electronic tongue using sensing membranes containing solvatochromic dyes. The proposed highly sensitive (30.64 mV/decade sensitivity) IDC electronic tongue has fast response and recovery times of about 6 s and 5 s, respectively, with extremely stable responses, and is capable of linear sensing performance (R² ≈ 0.985 correlation coefficient) over the wide dynamic range of 1 µM to 1 M. The designed IDC electronic tongue offers excellent reproducibility, with a relative standard deviation (RSD) of about 0.029. The proposed device was found to have better sensing performance than potentiometric-, cascoded compatible lateral bipolar transistor (C-CLBT)-, Electronic Tongue (SA402)-, and fiber-optic-based taste sensing systems in what concerns dynamic range width, response time, sensitivity, and linearity. Finally, we applied principal component analysis (PCA) to distinguish between various kinds of taste in mixed taste compounds.

Comparison of RF spectrum prediction methods for dynamic spectrum access

NASA Astrophysics Data System (ADS)

Kovarskiy, Jacob A.; Martone, Anthony F.; Gallagher, Kyle A.; Sherbondy, Kelly D.; Narayanan, Ram M.

2017-05-01

Dynamic spectrum access (DSA) refers to the adaptive utilization of today's busy electromagnetic spectrum. Cognitive radio/radar technologies require DSA to intelligently transmit and receive information in changing environments. Predicting radio frequency (RF) activity reduces sensing time and energy consumption for identifying usable spectrum. Typical spectrum prediction methods involve modeling spectral statistics with Hidden Markov Models (HMM) or various neural network structures. HMMs describe the time-varying state probabilities of Markov processes as a dynamic Bayesian network. Neural Networks model biological brain neuron connections to perform a wide range of complex and often non-linear computations. This work compares HMM, Multilayer Perceptron (MLP), and Recurrent Neural Network (RNN) algorithms and their ability to perform RF channel state prediction. Monte Carlo simulations on both measured and simulated spectrum data evaluate the performance of these algorithms. Generalizing spectrum occupancy as an alternating renewal process allows Poisson random variables to generate simulated data while energy detection determines the occupancy state of measured RF spectrum data for testing. The results suggest that neural networks achieve better prediction accuracy and prove more adaptable to changing spectral statistics than HMMs given sufficient training data.

Developing a Dynamic SPARROW Water Quality Decision Support System Using NASA Remotely-Sensed Products

NASA Astrophysics Data System (ADS)

Al-Hamdan, M. Z.; Smith, R. A.; Hoos, A.; Schwarz, G. E.; Alexander, R. B.; Crosson, W. L.; Srikishen, J.; Estes, M., Jr.; Cruise, J.; Al-Hamdan, A.; Ellenburg, W. L., II; Flores, A.; Sanford, W. E.; Zell, W.; Reitz, M.; Miller, M. P.; Journey, C. A.; Befus, K. M.; Swann, R.; Herder, T.; Sherwood, E.; Leverone, J.; Shelton, M.; Smith, E. T.; Anastasiou, C. J.; Seachrist, J.; Hughes, A.; Graves, D.

2017-12-01

The USGS Spatially Referenced Regression on Watershed Attributes (SPARROW) surface water quality modeling system has been widely used for long term, steady state water quality analysis. However, users have increasingly requested a dynamic version of SPARROW that can provide seasonal estimates of nutrients and suspended sediment to receiving waters. The goal of this NASA-funded project is to develop a dynamic decision support system to enhance the southeast SPARROW water quality model and finer-scale dynamic models for selected coastal watersheds through the use of remotely-sensed data and other NASA Land Information System (LIS) products. The spatial and temporal scale of satellite remote sensing products and LIS modeling data make these sources ideal for the purposes of development and operation of the dynamic SPARROW model. Remote sensing products including MODIS vegetation indices, SMAP surface soil moisture, and OMI atmospheric chemistry along with LIS-derived evapotranspiration (ET) and soil temperature and moisture products will be included in model development and operation. MODIS data will also be used to map annual land cover/land use in the study areas and in conjunction with Landsat and Sentinel to identify disturbed areas that might be sources of sediment and increased phosphorus loading through exposure of the bare soil. These data and others constitute the independent variables in a regression analysis whose dependent variables are the water quality constituents total nitrogen, total phosphorus, and suspended sediment. Remotely-sensed variables such as vegetation indices and ET can be proxies for nutrient uptake by vegetation; MODIS Leaf Area Index can indicate sources of phosphorus from vegetation; soil moisture and temperature are known to control rates of denitrification; and bare soil areas serve as sources of enhanced nutrient and sediment production. The enhanced SPARROW dynamic models will provide improved tools for end users to manage water quality in near real time and for the formulation of future scenarios to inform strategic planning. Time-varying SPARROW outputs will aid water managers in decision making regarding allocation of resources in protecting aquatic habitats, planning for harmful algal blooms, and restoration of degraded habitats, stream segments, or lakes.

Learning gait of quadruped robot without prior knowledge of the environment

NASA Astrophysics Data System (ADS)

Xu, Tao; Chen, Qijun

2012-09-01

Walking is the basic skill of a legged robot, and one of the promising ways to improve the walking performance and its adaptation to environment changes is to let the robot learn its walking by itself. Currently, most of the walking learning methods are based on robot vision system or some external sensing equipment to estimate the walking performance of certain walking parameters, and therefore are usually only applicable under laboratory condition, where environment can be pre-defined. Inspired by the rhythmic swing movement during walking of legged animals and the behavior of their adjusting their walking gait on different walking surfaces, a concept of walking rhythmic pattern(WRP) is proposed to evaluate the walking specialty of legged robot, which is just based on the walking dynamics of the robot. Based on the onboard acceleration sensor data, a method to calculate WRP using power spectrum in frequency domain and diverse smooth filters is also presented. Since the evaluation of WRP is only based on the walking dynamics data of the robot's body, the proposed method doesn't require prior knowledge of environment and thus can be applied in unknown environment. A gait learning approach of legged robots based on WRP and evolution algorithm(EA) is introduced. By using the proposed approach, a quadruped robot can learn its locomotion by its onboard sensing in an unknown environment, where the robot has no prior knowledge about this place. The experimental result proves proportional relationship exits between WRP match score and walking performance of legged robot, which can be used to evaluate the walking performance in walking optimization under unknown environment.

An economic value of remote-sensing information—Application to agricultural production and maintaining groundwater quality

USGS Publications Warehouse

Forney, William M.; Raunikar, Ronald P.; Bernknopf, Richard L.; Mishra, Shruti K.

2012-01-01

Does remote-sensing information provide economic benefits to society, and can a value be assigned to those benefits? Can resource management and policy decisions be better informed by coupling past and present Earth observations with groundwater nitrate measurements? Using an integrated assessment approach, the U.S. Geological Survey (USGS) applied an established conceptual framework to answer these questions, as well as to estimate the value of information (VOI) for remote-sensing imagery. The approach uses moderate-resolution land-imagery (MRLI) data from the Landsat and Advanced Wide Field Sensor satellites that has been classified by the National Agricultural Statistics Service into the Cropland Data Layer (CDL). Within the constraint of the U.S. Environmental Protection Agency's public health threshold for potable groundwater resources, the USGS modeled the relation between a population of the CDL's land uses and dynamic nitrate (NO3-) contamination of aquifers in a case study region in northeastern Iowa. Employing various multiscaled, multitemporal geospatial datasets with MRLI to maximize the value of agricultural production, the approach develops and uses multiple environmental science models to address dynamic nitrogen loading and transport at specified distances from specific sites (wells) and at landscape scales (for example, across 35 counties and two aquifers). In addition to the ecosystem service of potable groundwater, this effort focuses on the use of MRLI for the management of the major land uses in the study region-the production of corn and soybeans, which can impact groundwater quality. Derived methods and results include (1) economic and dynamic nitrate-pollution models, (2) probabilities of the survival of groundwater, and (3) a VOI for remote sensing. For the northeastern Iowa study region, the marginal benefit of the MRLI VOI (in 2010 dollars) is $858 million ±$197 million annualized, which corresponds to a net present value of $38.1 billion ±$8.8 billion for that flow of benefits in perpetuity. Given that these economic estimates are derived from one case study in a part of only one State, the estimates provide a lower estimate related to the potential value of the Landsat Data Continuity Mission.

Changes in E-cadherin rigidity sensing regulate cell adhesion.

PubMed

Collins, Caitlin; Denisin, Aleksandra K; Pruitt, Beth L; Nelson, W James

2017-07-18

Mechanical cues are sensed and transduced by cell adhesion complexes to regulate diverse cell behaviors. Extracellular matrix (ECM) rigidity sensing by integrin adhesions has been well studied, but rigidity sensing by cadherins during cell adhesion is largely unexplored. Using mechanically tunable polyacrylamide (PA) gels functionalized with the extracellular domain of E-cadherin (Ecad-Fc), we showed that E-cadherin-dependent epithelial cell adhesion was sensitive to changes in PA gel elastic modulus that produced striking differences in cell morphology, actin organization, and membrane dynamics. Traction force microscopy (TFM) revealed that cells produced the greatest tractions at the cell periphery, where distinct types of actin-based membrane protrusions formed. Cells responded to substrate rigidity by reorganizing the distribution and size of high-traction-stress regions at the cell periphery. Differences in adhesion and protrusion dynamics were mediated by balancing the activities of specific signaling molecules. Cell adhesion to a 30-kPa Ecad-Fc PA gel required Cdc42- and formin-dependent filopodia formation, whereas adhesion to a 60-kPa Ecad-Fc PA gel induced Arp2/3-dependent lamellipodial protrusions. A quantitative 3D cell-cell adhesion assay and live cell imaging of cell-cell contact formation revealed that inhibition of Cdc42, formin, and Arp2/3 activities blocked the initiation, but not the maintenance of established cell-cell adhesions. These results indicate that the same signaling molecules activated by E-cadherin rigidity sensing on PA gels contribute to actin organization and membrane dynamics during cell-cell adhesion. We hypothesize that a transition in the stiffness of E-cadherin homotypic interactions regulates actin and membrane dynamics during initial stages of cell-cell adhesion.

Changes in E-cadherin rigidity sensing regulate cell adhesion

PubMed Central

Collins, Caitlin; Pruitt, Beth L.; Nelson, W. James

2017-01-01

Mechanical cues are sensed and transduced by cell adhesion complexes to regulate diverse cell behaviors. Extracellular matrix (ECM) rigidity sensing by integrin adhesions has been well studied, but rigidity sensing by cadherins during cell adhesion is largely unexplored. Using mechanically tunable polyacrylamide (PA) gels functionalized with the extracellular domain of E-cadherin (Ecad-Fc), we showed that E-cadherin–dependent epithelial cell adhesion was sensitive to changes in PA gel elastic modulus that produced striking differences in cell morphology, actin organization, and membrane dynamics. Traction force microscopy (TFM) revealed that cells produced the greatest tractions at the cell periphery, where distinct types of actin-based membrane protrusions formed. Cells responded to substrate rigidity by reorganizing the distribution and size of high-traction-stress regions at the cell periphery. Differences in adhesion and protrusion dynamics were mediated by balancing the activities of specific signaling molecules. Cell adhesion to a 30-kPa Ecad-Fc PA gel required Cdc42- and formin-dependent filopodia formation, whereas adhesion to a 60-kPa Ecad-Fc PA gel induced Arp2/3-dependent lamellipodial protrusions. A quantitative 3D cell–cell adhesion assay and live cell imaging of cell–cell contact formation revealed that inhibition of Cdc42, formin, and Arp2/3 activities blocked the initiation, but not the maintenance of established cell–cell adhesions. These results indicate that the same signaling molecules activated by E-cadherin rigidity sensing on PA gels contribute to actin organization and membrane dynamics during cell–cell adhesion. We hypothesize that a transition in the stiffness of E-cadherin homotypic interactions regulates actin and membrane dynamics during initial stages of cell–cell adhesion. PMID:28674019

Equality of the Spectral and Dynamical Definitions of Reflection

NASA Astrophysics Data System (ADS)

Breuer, Jonathan; Ryckman, Eric; Simon, Barry

2010-04-01

For full-line Jacobi matrices, Schrödinger operators, and CMV matrices, we show that being reflectionless, in the sense of the well-known property of m-functions, is equivalent to a lack of reflection in the dynamics in the sense that any state that goes entirely to x = -∞ as t → -∞ goes entirely to x = ∞ as t → ∞. This allows us to settle a conjecture of Deift and Simon from 1983 regarding ergodic Jacobi matrices.

Coherent Two-Mode Dynamics of a Nanowire Force Sensor

NASA Astrophysics Data System (ADS)

Braakman, Floris R.; Rossi, Nicola; Tütüncüoglu, Gözde; Morral, Anna Fontcuberta i.; Poggio, Martino

2018-05-01

Classically coherent dynamics analogous to those of quantum two-level systems are studied in the setting of force sensing. We demonstrate quantitative control over the coupling between two orthogonal mechanical modes of a nanowire cantilever through measurement of avoided crossings as we deterministically position the nanowire inside an electric field. Furthermore, we demonstrate Rabi oscillations between the two mechanical modes in the strong-coupling regime. These results give prospects of implementing coherent two-mode control techniques for force-sensing signal enhancement.

Investigation of the dynamics of ephemeral gully erosion on arable land of the forest-steppe and steppe zone of the East of the Russian Plain from remote sensing data

NASA Astrophysics Data System (ADS)

Platoncheva, E. V.

2018-01-01

Spatio-temporal estimation of the erosion of arable soils is still an urgent task, in spite of the numerous methods of such assessments. Development of information technologies, the emergence of high and ultra-high resolution images allows reliable identification of linear forms of erosion to determine its dynamics on arable land. The study drew attention to the dynamics of the most active erosion unit - an ephemeral gully. The estimation of the dynamics was carried out on the basis of different space images for the maximum possible period (from 1986 to 2016). The cartographic method was used as the main research method. Identification of a belt of ephemeral gully erosion based on materials of multi-zone space surveys and GIS-technology of their processing was carried out. In the course of work with satellite imagery and subsequent verification of the received data on the ground, the main signs of deciphering the ephemeral gully network were determined. A methodology for geoinformation mapping of the dynamics of ephemeral gully erosion belt was developed and a system of indicators quantitatively characterizing its development on arable slopes was proposed. The evaluation of the current ephemeral gully network based on the interpretation of space images includes the definition of such indicators of ephemeral gully erosion as the density of the ephemeral gully net, the density of the ephemeral gullies, the area and linear dynamics of the ephemeral gully network. Preliminary results of the assessment of the dynamics of the belt erosion showed an increase in all quantitative indicators of ephemeral gully erosion for the observed period.

Redundancy relations and robust failure detection

NASA Technical Reports Server (NTRS)

Chow, E. Y.; Lou, X. C.; Verghese, G. C.; Willsky, A. S.

1984-01-01

All failure detection methods are based on the use of redundancy, that is on (possible dynamic) relations among the measured variables. Consequently the robustness of the failure detection process depends to a great degree on the reliability of the redundancy relations given the inevitable presence of model uncertainties. The problem of determining redundancy relations which are optimally robust in a sense which includes the major issues of importance in practical failure detection is addressed. A significant amount of intuition concerning the geometry of robust failure detection is provided.

Hierarchical layered double hydroxides with Ag nanoparticle modification for ethanol sensing

NASA Astrophysics Data System (ADS)

Qin, Yuxiang; Wang, Liping; Wang, Xiaofei

2018-07-01

Layered double hydroxides (LDHs) have recently been revealed to be promising in gas sensor applications due to their compositional flexibility and unique 2D-interlayer channel for gas diffusion and adsorption. This work demonstrates highly porous hierarchical LDHs containing Mg2+ and Al3+ (MgAl-LDHs) for ethanol sensing at room temperature. These MgAl-LDHs, with unique flower-like hierarchical structure and mesoporous interlayer, were synthesized hydrothermally using sodium dodecyl sulfate as soft template as well as intercalating agent. Further modification by discrete Ag nanoparticles (NPs) was achieved via an environmentally friendly glucose-reduction method to improve the gas-sensing response of the LDH-based sensor. It is found that the hierarchical MgAl-LDHs show potential in sensing ethanol gas with rapid dynamic characteristics at room temperature; their response magnitude towards ethanol can be enhanced significantly by Ag NP modification. The gas-response value of the Ag-modified MgAl-LDH sensor is about twice that of pristine MgAl-LDH sensors, towards 5–200 ppm ethanol at room temperature. Meanwhile, rapid response-recovery characteristics are achieved, with response and recovery times shorter than 10 and 50 s, respectively. The satisfactory sensing performance and remarkable response enhancement by Ag NP modification are demonstrated in terms of the unique microstructure of the hierarchical MgAl-LDHs and a constructed conductive effect model of Ag functionalized LDHs.

Single-shot magnetic resonance spectroscopic imaging with partial parallel imaging.

PubMed

Posse, Stefan; Otazo, Ricardo; Tsai, Shang-Yueh; Yoshimoto, Akio Ernesto; Lin, Fa-Hsuan

2009-03-01

A magnetic resonance spectroscopic imaging (MRSI) pulse sequence based on proton-echo-planar-spectroscopic-imaging (PEPSI) is introduced that measures two-dimensional metabolite maps in a single excitation. Echo-planar spatial-spectral encoding was combined with interleaved phase encoding and parallel imaging using SENSE to reconstruct absorption mode spectra. The symmetrical k-space trajectory compensates phase errors due to convolution of spatial and spectral encoding. Single-shot MRSI at short TE was evaluated in phantoms and in vivo on a 3-T whole-body scanner equipped with a 12-channel array coil. Four-step interleaved phase encoding and fourfold SENSE acceleration were used to encode a 16 x 16 spatial matrix with a 390-Hz spectral width. Comparison with conventional PEPSI and PEPSI with fourfold SENSE acceleration demonstrated comparable sensitivity per unit time when taking into account g-factor-related noise increases and differences in sampling efficiency. LCModel fitting enabled quantification of inositol, choline, creatine, and N-acetyl-aspartate (NAA) in vivo with concentration values in the ranges measured with conventional PEPSI and SENSE-accelerated PEPSI. Cramer-Rao lower bounds were comparable to those obtained with conventional SENSE-accelerated PEPSI at the same voxel size and measurement time. This single-shot MRSI method is therefore suitable for applications that require high temporal resolution to monitor temporal dynamics or to reduce sensitivity to tissue movement.

Hierarchical layered double hydroxides with Ag nanoparticle modification for ethanol sensing.

PubMed

Qin, Yuxiang; Wang, Liping; Wang, Xiaofei

2018-07-06

Layered double hydroxides (LDHs) have recently been revealed to be promising in gas sensor applications due to their compositional flexibility and unique 2D-interlayer channel for gas diffusion and adsorption. This work demonstrates highly porous hierarchical LDHs containing Mg 2+ and Al 3+ (MgAl-LDHs) for ethanol sensing at room temperature. These MgAl-LDHs, with unique flower-like hierarchical structure and mesoporous interlayer, were synthesized hydrothermally using sodium dodecyl sulfate as soft template as well as intercalating agent. Further modification by discrete Ag nanoparticles (NPs) was achieved via an environmentally friendly glucose-reduction method to improve the gas-sensing response of the LDH-based sensor. It is found that the hierarchical MgAl-LDHs show potential in sensing ethanol gas with rapid dynamic characteristics at room temperature; their response magnitude towards ethanol can be enhanced significantly by Ag NP modification. The gas-response value of the Ag-modified MgAl-LDH sensor is about twice that of pristine MgAl-LDH sensors, towards 5-200 ppm ethanol at room temperature. Meanwhile, rapid response-recovery characteristics are achieved, with response and recovery times shorter than 10 and 50 s, respectively. The satisfactory sensing performance and remarkable response enhancement by Ag NP modification are demonstrated in terms of the unique microstructure of the hierarchical MgAl-LDHs and a constructed conductive effect model of Ag functionalized LDHs.

Capturing dynamic processes of change in GROW mutual help groups for mental health.

PubMed

Finn, Lizzie D; Bishop, Brian J; Sparrow, Neville

2009-12-01

The need for a model that can portray dynamic processes of change in mutual help groups for mental health (MHGMHs) is emphasized. A dynamic process model has the potential to capture a more comprehensive understanding of how MHGMHs may assist their members. An investigation into GROW, a mutual help organization for mental health, employed ethnographic, phenomenological and collaborative research methods. The study examined how GROW impacts on psychological well being. Study outcomes aligned with the social ecological paradigm (Maton in Understanding the self-help organization: frameworks and findings. Sage, Thousand Oaks 1994) indicating multifactorial processes of change at and across three levels of analysis: group level, GROW program/community level and individual level. Outcome themes related to life skills acquisition and a change in self-perception in terms of belonging within community and an increased sense of personal value. The GROW findings are used to assist development of a dynamic multi-dimensional process model to explain how MHGMHs may promote positive change.

Real-time combustion control and diagnostics sensor-pressure oscillation monitor

DOEpatents

Chorpening, Benjamin T [Morgantown, WV; Thornton, Jimmy [Morgantown, WV; Huckaby, E David [Morgantown, WV; Richards, George A [Morgantown, WV

2009-07-14

An apparatus and method for monitoring and controlling the combustion process in a combustion system to determine the amplitude and/or frequencies of dynamic pressure oscillations during combustion. An electrode in communication with the combustion system senses hydrocarbon ions and/or electrons produced by the combustion process and calibration apparatus calibrates the relationship between the standard deviation of the current in the electrode and the amplitudes of the dynamic pressure oscillations by applying a substantially constant voltage between the electrode and ground resulting in a current in the electrode and by varying one or more of (1) the flow rate of the fuel, (2) the flow rate of the oxidant, (3) the equivalence ratio, (4) the acoustic tuning of the combustion system, and (5) the fuel distribution in the combustion chamber such that the amplitudes of the dynamic pressure oscillations in the combustion chamber are calculated as a function of the standard deviation of the electrode current. Thereafter, the supply of fuel and/or oxidant is varied to modify the dynamic pressure oscillations.

Dynamic piezoresistive response of hybrid nanocomposites

NASA Astrophysics Data System (ADS)

Gbaguidi, Audrey; Anees, Muhammad; Namilae, Sirish; Kim, Daewon

2017-04-01

Hybrid nanocomposites with carbon nanotubes and graphitic platelets as fillers are known to exhibit remarkable electrical and mechanical properties with many potential strain and damage sensing applications. In this work, we fabricate hybrid nanocomposites with carbon nanotube sheet and coarse graphite platelets as fillers with epoxy matrix. We then examine the electromechanical behavior of these nanocomposites under dynamic loading. The electrical resistivity responses of the nanocomposites are measured in frequency range of 1 Hz to 50 Hz with different levels of induced strains. Axial cycling loading is applied using a uniaxial electrodynamic shaker, and transverse loading is applied on end-clamped specimen using modified speakers. In addition, a dynamic mechanical analysis of nanocomposite specimen is performed to characterize the thermal and dynamic behavior of the nanocomposite. Our results indicate that these hybrid nanocomposites exhibit a distinct piezoresistive response under a wide range of dynamic loading conditions, which can be beneficial for potential sensing applications.

High Spatial and Temporal Resolution Dynamic Contrast-Enhanced Magnetic Resonance Angiography (CE-MRA) using Compressed Sensing with Magnitude Image Subtraction

PubMed Central

Rapacchi, Stanislas; Han, Fei; Natsuaki, Yutaka; Kroeker, Randall; Plotnik, Adam; Lehman, Evan; Sayre, James; Laub, Gerhard; Finn, J Paul; Hu, Peng

2014-01-01

Purpose We propose a compressed-sensing (CS) technique based on magnitude image subtraction for high spatial and temporal resolution dynamic contrast-enhanced MR angiography (CE-MRA). Methods Our technique integrates the magnitude difference image into the CS reconstruction to promote subtraction sparsity. Fully sampled Cartesian 3D CE-MRA datasets from 6 volunteers were retrospectively under-sampled and three reconstruction strategies were evaluated: k-space subtraction CS, independent CS, and magnitude subtraction CS. The techniques were compared in image quality (vessel delineation, image artifacts, and noise) and image reconstruction error. Our CS technique was further tested on 7 volunteers using a prospectively under-sampled CE-MRA sequence. Results Compared with k-space subtraction and independent CS, our magnitude subtraction CS provides significantly better vessel delineation and less noise at 4X acceleration, and significantly less reconstruction error at 4X and 8X (p<0.05 for all). On a 1–4 point image quality scale in vessel delineation, our technique scored 3.8±0.4 at 4X, 2.8±0.4 at 8X and 2.3±0.6 at 12X acceleration. Using our CS sequence at 12X acceleration, we were able to acquire dynamic CE-MRA with higher spatial and temporal resolution than current clinical TWIST protocol while maintaining comparable image quality (2.8±0.5 vs. 3.0±0.4, p=NS). Conclusion Our technique is promising for dynamic CE-MRA. PMID:23801456

Satellite remote sensing of landscape freeze/thaw state dynamics for complex Topography and Fire Disturbance Areas Using multi-sensor radar and SRTM digital elevation models

NASA Technical Reports Server (NTRS)

Podest, Erika; McDonald, Kyle; Kimball, John; Randerson, James

2003-01-01

We characterize differences in radar-derived freeze/thaw state, examining transitions over complex terrain and landscape disturbance regimes. In areas of complex terrain, we explore freezekhaw dynamics related to elevation, slope aspect and varying landcover. In the burned regions, we explore the timing of seasonal freeze/thaw transition as related to the recovering landscape, relative to that of a nearby control site. We apply in situ biophysical measurements, including flux tower measurements to validate and interpret the remotely sensed parameters. A multi-scale analysis is performed relating high-resolution SAR backscatter and moderate resolution scatterometer measurements to assess trade-offs in spatial and temporal resolution in the remotely sensed fields.

Live cell imaging of cytoskeletal and organelle dynamics in gravity-sensing cells in plant gravitropism.

PubMed

Nakamura, Moritaka; Toyota, Masatsugu; Tasaka, Masao; Morita, Miyo Terao

2015-01-01

Plants sense gravity and change their morphology/growth direction accordingly (gravitropism). The early process of gravitropism, gravity sensing, is supposed to be triggered by sedimentation of starch-filled plastids (amyloplasts) in statocytes such as root columella cells and shoot endodermal cells. For several decades, many scientists have focused on characterizing the role of the amyloplasts and observed their intracellular sedimentation in various plants. Recently, it has been discovered that the complex sedimentary movements of the amyloplasts are created not only by gravity but also by cytoskeletal/organelle dynamics, such as those of actin filaments and the vacuolar membrane. Thus, to understand how plants sense gravity, we need to analyze both amyloplast movements and their regulatory systems in statocytes. We have developed a vertical-stage confocal microscope that allows multicolor fluorescence imaging of amyloplasts, actin filaments and vacuolar membranes in vertically oriented plant tissues. We also developed a centrifuge microscope that allows bright-field imaging of amyloplasts during centrifugation. These microscope systems provide new insights into gravity-sensing mechanisms in Arabidopsis.

On Searching Available Channels with Asynchronous MAC-Layer Spectrum Sensing

NASA Astrophysics Data System (ADS)

Jiang, Chunxiao; Ma, Xin; Chen, Canfeng; Ma, Jian; Ren, Yong

Dynamic spectrum access has become a focal issue recently, in which identifying the available spectrum plays a rather important role. Lots of work has been done concerning secondary user (SU) synchronously accessing primary user's (PU's) network. However, on one hand, SU may have no idea about PU's communication protocols; on the other, it is possible that communications among PU are not based on synchronous scheme at all. In order to address such problems, this paper advances a strategy for SU to search available spectrums with asynchronous MAC-layer sensing. With this method, SUs need not know the communication mechanisms in PU's network when dynamically accessing. We will focus on four aspects: 1) strategy for searching available channels; 2) vacating strategy when PUs come back; 3) estimation of channel parameters; 4) impact of SUs' interference on PU's data rate. The simulations show that our search strategy not only can achieve nearly 50% less interference probability than equal allocation of total search time, but also well adapts to time-varying channels. Moreover, access by our strategies can attain 150% more access time than random access. The moment matching estimator shows good performance in estimating and tracing time-varying channels.

Understanding of coupled terrestrial carbon, nitrogen and water dynamics-an overview.

PubMed

Chen, Baozhang; Coops, Nicholas C

2009-01-01

Coupled terrestrial carbon (C), nitrogen (N) and hydrological processes play a crucial role in the climate system, providing both positive and negative feedbacks to climate change. In this review we summarize published research results to gain an increased understanding of the dynamics between vegetation and atmosphere processes. A variety of methods, including monitoring (e.g., eddy covariance flux tower, remote sensing, etc.) and modeling (i.e., ecosystem, hydrology and atmospheric inversion modeling) the terrestrial carbon and water budgeting, are evaluated and compared. We highlight two major research areas where additional research could be focused: (i) Conceptually, the hydrological and biogeochemical processes are closely linked, however, the coupling processes between terrestrial C, N and hydrological processes are far from well understood; and (ii) there are significant uncertainties in estimates of the components of the C balance, especially at landscape and regional scales. To address these two questions, a synthetic research framework is needed which includes both bottom-up and top-down approaches integrating scalable (footprint and ecosystem) models and a spatially nested hierarchy of observations which include multispectral remote sensing, inventories, existing regional clusters of eddy-covariance flux towers and CO(2) mixing ratio towers and chambers.

Relation of phytoplankton species to ecosystem definition in the northwest Atlantic using remote sensing data

NASA Astrophysics Data System (ADS)

Devred, Emmanuel; Sathyendranath, Shubha; Fuentes-yaco, Cesar; Maass, Heidi; Platt, Trevor

2005-08-01

In this work, we present a new method for dynamic assignment of the boundaries of the ecological provinces of the North West Atlantic. The results are compared with the distribution of diatoms in the study area. Both analyses rely on ocean-colour data for the region. Diatoms were identified using remoteely-sensed data on the basis of their species-dependent absorption characteristics, which were embedded in a simple reflectance model(Sathyendranath et al., 2004). Maps of diatom distributions were produced for the area. Satellite-derived chlorophyll biomass and sea surface temperature (MODIS data) for the same period were used to redefine, in a dynamic way, the static borders of the ecological provinces (Sathyendranath et al., 1995; Longhurst 1998). The analyses were carried on two-week composite images, at different times of the year (April-May, July and October), to examine seasonal variability in the boundaries. The boundaries of provinces and the occurrence of diatoms were spatially coherent. Diatoms were favoured in rich waters on the continental shelf and in cold waters at high latitudes. In provinces labelled as oligotrophic (subtropical gyre and Gulf Stream), very negligible fractions of diatoms were found at any time of the year.

Uncovering hidden nodes in complex networks in the presence of noise

PubMed Central

Su, Ri-Qi; Lai, Ying-Cheng; Wang, Xiao; Do, Younghae

2014-01-01

Ascertaining the existence of hidden objects in a complex system, objects that cannot be observed from the external world, not only is curiosity-driven but also has significant practical applications. Generally, uncovering a hidden node in a complex network requires successful identification of its neighboring nodes, but a challenge is to differentiate its effects from those of noise. We develop a completely data-driven, compressive-sensing based method to address this issue by utilizing complex weighted networks with continuous-time oscillatory or discrete-time evolutionary-game dynamics. For any node, compressive sensing enables accurate reconstruction of the dynamical equations and coupling functions, provided that time series from this node and all its neighbors are available. For a neighboring node of the hidden node, this condition cannot be met, resulting in abnormally large prediction errors that, counterintuitively, can be used to infer the existence of the hidden node. Based on the principle of differential signal, we demonstrate that, when strong noise is present, insofar as at least two neighboring nodes of the hidden node are subject to weak background noise only, unequivocal identification of the hidden node can be achieved. PMID:24487720

Mental states as macrostates emerging from brain electrical dynamics

NASA Astrophysics Data System (ADS)

Allefeld, Carsten; Atmanspacher, Harald; Wackermann, Jiří

2009-03-01

Psychophysiological correlations form the basis for different medical and scientific disciplines, but the nature of this relation has not yet been fully understood. One conceptual option is to understand the mental as "emerging" from neural processes in the specific sense that psychology and physiology provide two different descriptions of the same system. Stating these descriptions in terms of coarser- and finer-grained system states (macro- and microstates), the two descriptions may be equally adequate if the coarse-graining preserves the possibility to obtain a dynamical rule for the system. To test the empirical viability of our approach, we describe an algorithm to obtain a specific form of such a coarse-graining from data, and illustrate its operation using a simulated dynamical system. We then apply the method to an electroencephalographic recording, where we are able to identify macrostates from the physiological data that correspond to mental states of the subject.

Toward a systems-level view of dynamic phosphorylation networks

PubMed Central

Newman, Robert H.; Zhang, Jin; Zhu, Heng

2014-01-01

To better understand how cells sense and respond to their environment, it is important to understand the organization and regulation of the phosphorylation networks that underlie most cellular signal transduction pathways. These networks, which are composed of protein kinases, protein phosphatases and their respective cellular targets, are highly dynamic. Importantly, to achieve signaling specificity, phosphorylation networks must be regulated at several levels, including at the level of protein expression, substrate recognition, and spatiotemporal modulation of enzymatic activity. Here, we briefly summarize some of the traditional methods used to study the phosphorylation status of cellular proteins before focusing our attention on several recent technological advances, such as protein microarrays, quantitative mass spectrometry, and genetically-targetable fluorescent biosensors, that are offering new insights into the organization and regulation of cellular phosphorylation networks. Together, these approaches promise to lead to a systems-level view of dynamic phosphorylation networks. PMID:25177341

Fingerprint Stimulated Raman Scattering Imaging Reveals Retinoid Coupling Lipid Metabolism and Survival.

PubMed

Chen, Andy Jing; Li, Junjie; Jannasch, Amber; Ozseker, Sena; Wang, Meng C; Cheng, Ji-Xin

2018-06-17

Retinoids play critical roles in development, immunity and lipid metabolism, and their deficiency leads to various human disorders. Yet, tools for sensing retinoids in vivo are lacking, which limits the understanding of retinoid distribution, dynamics and functions in living organisms. Here, using hyperspectral stimulated Raman scattering microscopy, we discover a previously unknown cytoplasmic store of retinoids in Caenorahbditis elegans. Following the temporal dynamics of retinoids, we reveal that their levels are positively correlated with fat storage, and their supplementation slows down fat loss during dauer starvation. We also discover that retinoids promote fat unsaturation in response to high-glucose stress, and improve organism survival. Together, our studies report a new method for tracking the spatiotemporal dynamics of retinoids in living organisms, and suggest the crucial roles of retinoids in maintaining metabolic homeostasis and enhancing organism fitness upon developmental and dietary stresses. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Remote sensing of Gulf Stream using GEOS-3 radar altimeter

NASA Technical Reports Server (NTRS)

Leitao, C. D.; Huang, N. E.; Parra, C. G.

1978-01-01

Radar altimeter measurements from the GEOS-3 satellite to the ocean surface indicated the presence of expected geostrophic height differences across the the Gulf Stream. Dynamic sea surface heights were found by both editing and filtering the raw sea surface heights and then referencing these processed data to a 5 minute x 5 minute geoid. Any trend between the processed data and the geoid was removed by subtracting out a linear fit to the residuals in the open ocean. The mean current velocity of 107 + or - 29 cm/sec calculated from the dynamic heights for all orbits corresponded with velocities obtained from hydrographic methods. Also, dynamic topographic maps were produced for August, September, and October 1975. Results pointed out limitations in the accuracy of the geoid, height anomaly deteriorations due to filtering, and lack of dense time and space distribution of measurements.

Finite-size effect on the dynamic and sensing performances of graphene resonators: the role of edge stress.

PubMed

Kim, Chang-Wan; Dai, Mai Duc; Eom, Kilho

2016-01-01

We have studied the finite-size effect on the dynamic behavior of graphene resonators and their applications in atomic mass detection using a continuum elastic model such as modified plate theory. In particular, we developed a model based on von Karman plate theory with including the edge stress, which arises from the imbalance between the coordination numbers of bulk atoms and edge atoms of graphene. It is shown that as the size of a graphene resonator decreases, the edge stress depending on the edge structure of a graphene resonator plays a critical role on both its dynamic and sensing performances. We found that the resonance behavior of graphene can be tuned not only through edge stress but also through nonlinear vibration, and that the detection sensitivity of a graphene resonator can be controlled by using the edge stress. Our study sheds light on the important role of the finite-size effect in the effective design of graphene resonators for their mass sensing applications.

Knowledge-based zonal grid generation for computational fluid dynamics

NASA Technical Reports Server (NTRS)

Andrews, Alison E.

1988-01-01

Automation of flow field zoning in two dimensions is an important step towards reducing the difficulty of three-dimensional grid generation in computational fluid dynamics. Using a knowledge-based approach makes sense, but problems arise which are caused by aspects of zoning involving perception, lack of expert consensus, and design processes. These obstacles are overcome by means of a simple shape and configuration language, a tunable zoning archetype, and a method of assembling plans from selected, predefined subplans. A demonstration system for knowledge-based two-dimensional flow field zoning has been successfully implemented and tested on representative aerodynamic configurations. The results show that this approach can produce flow field zonings that are acceptable to experts with differing evaluation criteria.

Fluid and particle transport of a hairy structure

NASA Astrophysics Data System (ADS)

Lee, Hongki; Lahooti, Mohsen; Kim, Daegyoum; Jung, Seyeong

2017-11-01

Hairy appendages of animals are used to capture particles, sense surrounding flow, and generate propulsive force. Due to the small size of the hairy structures, their hydrodynamics have been studied mostly in very low Reynolds number. In this work, in a broad range of Reynolds number, O(1) - O(100), flow structure and inertial particle dynamics around an array of two-dimensional cylinders are investigated numerically by using an immersed boundary method. Given flow fields, Maxey-Riley equation is adopted to examine particle dynamics. Here, we discuss the effects of Reynolds number, density ratio of inertial particles and fluid, and distance between cylinders on particle behaviors around a moving structure. In addition, drift volume of inertial particles is correlated with the model parameters.

Using chaos to generate variations on movement sequences

NASA Astrophysics Data System (ADS)

Bradley, Elizabeth; Stuart, Joshua

1998-12-01

We describe a method for introducing variations into predefined motion sequences using a chaotic symbol-sequence reordering technique. A progression of symbols representing the body positions in a dance piece, martial arts form, or other motion sequence is mapped onto a chaotic trajectory, establishing a symbolic dynamics that links the movement sequence and the attractor structure. A variation on the original piece is created by generating a trajectory with slightly different initial conditions, inverting the mapping, and using special corpus-based graph-theoretic interpolation schemes to smooth any abrupt transitions. Sensitive dependence guarantees that the variation is different from the original; the attractor structure and the symbolic dynamics guarantee that the two resemble one another in both aesthetic and mathematical senses.

Model of lidar range-Doppler signatures of solid rocket fuel plumes

NASA Astrophysics Data System (ADS)

Bankman, Isaac N.; Giles, John W.; Chan, Stephen C.; Reed, Robert A.

2004-09-01

The analysis of particles produced by solid rocket motor fuels relates to two types of studies: the effect of these particles on the Earth's ozone layer, and the dynamic flight behavior of solid fuel boosters used by the NASA Space Shuttle. Since laser backscatter depends on the particle size and concentration, a lidar system can be used to analyze the particle distributions inside a solid rocket plume in flight. We present an analytical model that simulates the lidar returns from solid rocket plumes including effects of beam profile, spot size, polarization and sensing geometry. The backscatter and extinction coefficients of alumina particles are computed with the T-matrix method that can address non-spherical particles. The outputs of the model include time-resolved return pulses and range-Doppler signatures. Presented examples illustrate the effects of sensing geometry.

Demodulation algorithm for optical fiber F-P sensor.

PubMed

Yang, Huadong; Tong, Xinglin; Cui, Zhang; Deng, Chengwei; Guo, Qian; Hu, Pan

2017-09-10

The demodulation algorithm is very important to improving the measurement accuracy of a sensing system. In this paper, the variable step size hill climbing search method will be initially used for the optical fiber Fabry-Perot (F-P) sensing demodulation algorithm. Compared with the traditional discrete gap transformation demodulation algorithm, the computation is greatly reduced by changing step size of each climb, which could achieve nano-scale resolution, high measurement accuracy, high demodulation rates, and large dynamic demodulation range. An optical fiber F-P pressure sensor based on micro-electro-mechanical system (MEMS) has been fabricated to carry out the experiment, and the results show that the resolution of the algorithm can reach nano-scale level, the sensor's sensitivity is about 2.5  nm/KPa, which is similar to the theoretical value, and this sensor has great reproducibility.

Label-free sensing of the binding state of MUC1 peptide and anti-MUC1 aptamer solution in fluidic chip by terahertz spectroscopy.

PubMed

Zhao, Xiang; Zhang, Mingkun; Wei, Dongshan; Wang, Yunxia; Yan, Shihan; Liu, Mengwan; Yang, Xiang; Yang, Ke; Cui, Hong-Liang; Fu, Weiling

2017-10-01

The aptamer and target molecule binding reaction has been widely applied for construction of aptasensors, most of which are labeled methods. In contrast, terahertz technology proves to be a label-free sensing tool for biomedical applications. We utilize terahertz absorption spectroscopy and molecular dynamics simulation to investigate the variation of binding-induced collective vibration of hydrogen bond network in a mixed solution of MUC1 peptide and anti-MUC1 aptamer. The results show that binding-induced alterations of hydrogen bond numbers could be sensitively reflected by the variation of terahertz absorption coefficients of the mixed solution in a customized fluidic chip. The minimal detectable concentration is determined as 1 pmol/μL, which is approximately equal to the optimal immobilized concentration of aptasensors.

Modeling of estuarne chlorophyll a from an airborne scanner

USGS Publications Warehouse

Khorram, Siamak; Catts, Glenn P.; Cloern, James E.; Knight, Allen W.

1987-01-01

Near simultaneous collection of 34 surface water samples and airborne multispectral scanner data provided input for regression models developed to predict surface concentrations of estuarine chlorophyll a. Two wavelength ratios were employed in model development. The ratios werechosen to capitalize on the spectral characteristics of chlorophyll a, while minimizing atmospheric influences. Models were then applied to data previously acquired over the study area thre years earlier. Results are in the form of color-coded displays of predicted chlorophyll a concentrations and comparisons of the agreement among measured surface samples and predictions basedon coincident remotely sensed data. The influence of large variations in fresh-water inflow to the estuary are clearly apparent in the results. The synoptic view provided by remote sensing is another method of examining important estuarine dynamics difficult to observe from in situ sampling alone.

Elastomeric optical fiber sensors and method for detecting and measuring events occurring in elastic materials

DOEpatents

Muhs, Jeffrey D.; Capps, Gary J.; Smith, David B.; White, Clifford P.

1994-01-01

Fiber optic sensing means for the detection and measurement of events such as dynamic loadings imposed upon elastic materials including cementitious materials, elastomers, and animal body components and/or the attrition of such elastic materials are provided. One or more optical fibers each having a deformable core and cladding formed of an elastomeric material such as silicone rubber are embedded in the elastic material. Changes in light transmission through any of the optical fibers due the deformation of the optical fiber by the application of dynamic loads such as compression, tension, or bending loadings imposed on the elastic material or by the attrition of the elastic material such as by cracking, deterioration, aggregate break-up, and muscle, tendon, or organ atrophy provide a measurement of the dynamic loadings and attrition. The fiber optic sensors can be embedded in elastomers subject to dynamic loadings and attrition such as commonly used automobiles and in shoes for determining the amount and frequency of the dynamic loadings and the extent of attrition. The fiber optic sensors are also useable in cementitious material for determining the maturation thereof.

Driving terrestrial ecosystem models from space

NASA Technical Reports Server (NTRS)

Waring, R. H.

1993-01-01

Regional air pollution, land-use conversion, and projected climate change all affect ecosystem processes at large scales. Changes in vegetation cover and growth dynamics can impact the functioning of ecosystems, carbon fluxes, and climate. As a result, there is a need to assess and monitor vegetation structure and function comprehensively at regional to global scales. To provide a test of our present understanding of how ecosystems operate at large scales we can compare model predictions of CO2, O2, and methane exchange with the atmosphere against regional measurements of interannual variation in the atmospheric concentration of these gases. Recent advances in remote sensing of the Earth's surface are beginning to provide methods for estimating important ecosystem variables at large scales. Ecologists attempting to generalize across landscapes have made extensive use of models and remote sensing technology. The success of such ventures is dependent on merging insights and expertise from two distinct fields. Ecologists must provide the understanding of how well models emulate important biological variables and their interactions; experts in remote sensing must provide the biophysical interpretation of complex optical reflectance and radar backscatter data.

a model based on crowsourcing for detecting natural hazards

NASA Astrophysics Data System (ADS)

Duan, J.; Ma, C.; Zhang, J.; Liu, S.; Liu, J.

2015-12-01

Remote Sensing Technology provides a new method for the detecting,early warning,mitigation and relief of natural hazards. Given the suddenness and the unpredictability of the location of natural hazards as well as the actual demands for hazards work, this article proposes an evaluation model for remote sensing detecting of natural hazards based on crowdsourcing. Firstly, using crowdsourcing model and with the help of the Internet and the power of hundreds of millions of Internet users, this evaluation model provides visual interpretation of high-resolution remote sensing images of hazards area and collects massive valuable disaster data; secondly, this evaluation model adopts the strategy of dynamic voting consistency to evaluate the disaster data provided by the crowdsourcing workers; thirdly, this evaluation model pre-estimates the disaster severity with the disaster pre-evaluation model based on regional buffers; lastly, the evaluation model actuates the corresponding expert system work according to the forecast results. The idea of this model breaks the boundaries between geographic information professionals and the public, makes the public participation and the citizen science eventually be realized, and improves the accuracy and timeliness of hazards assessment results.

Temperature-strain discrimination in distributed optical fiber sensing using phase-sensitive optical time-domain reflectometry.

PubMed

Lu, Xin; Soto, Marcelo A; Thévenaz, Luc

2017-07-10

A method based on coherent Rayleigh scattering distinctly evaluating temperature and strain is proposed and experimentally demonstrated for distributed optical fiber sensing. Combining conventional phase-sensitive optical time-domain domain reflectometry (ϕOTDR) and ϕOTDR-based birefringence measurements, independent distributed temperature and strain profiles are obtained along a polarization-maintaining fiber. A theoretical analysis, supported by experimental data, indicates that the proposed system for temperature-strain discrimination is intrinsically better conditioned than an equivalent existing approach that combines classical Brillouin sensing with Brillouin dynamic gratings. This is due to the higher sensitivity of coherent Rayleigh scatting compared to Brillouin scattering, thus offering better performance and lower temperature-strain uncertainties in the discrimination. Compared to the Brillouin-based approach, the ϕOTDR-based system here proposed requires access to only one fiber-end, and a much simpler experimental layout. Experimental results validate the full discrimination of temperature and strain along a 100 m-long elliptical-core polarization-maintaining fiber with measurement uncertainties of ~40 mK and ~0.5 με, respectively. These values agree very well with the theoretically expected measurand resolutions.

Time-Resolved Fluorescent Immunochromatography of Aflatoxin B1 in Soybean Sauce: A Rapid and Sensitive Quantitative Analysis.

PubMed

Wang, Du; Zhang, Zhaowei; Li, Peiwu; Zhang, Qi; Zhang, Wen

2016-07-14

Rapid and quantitative sensing of aflatoxin B1 with high sensitivity and specificity has drawn increased attention of studies investigating soybean sauce. A sensitive and rapid quantitative immunochromatographic sensing method was developed for the detection of aflatoxin B1 based on time-resolved fluorescence. It combines the advantages of time-resolved fluorescent sensing and immunochromatography. The dynamic range of a competitive and portable immunoassay was 0.3-10.0 µg·kg(-1), with a limit of detection (LOD) of 0.1 µg·kg(-1) and recoveries of 87.2%-114.3%, within 10 min. The results showed good correlation (R² > 0.99) between time-resolved fluorescent immunochromatographic strip test and high performance liquid chromatography (HPLC). Soybean sauce samples analyzed using time-resolved fluorescent immunochromatographic strip test revealed that 64.2% of samples contained aflatoxin B1 at levels ranging from 0.31 to 12.5 µg·kg(-1). The strip test is a rapid, sensitive, quantitative, and cost-effective on-site screening technique in food safety analysis.

Evolutions Of Diff-Tomo For Sensing Subcanopy Deformations And Height-Varying Temporal Coherence

NASA Astrophysics Data System (ADS)

Lombardini, Fabrizio; Cai, Francesco

2012-01-01

Interest is continuing to grow in advanced interferometric SAR methods for sensing complex scenarios with multiple (layover or volumetric) scatterers mapped in the SAR cell. Multibaseline SAR tomographic (3D) elevation beam forming is a promising technique in this field. Recently, the Tomo concept has been integrated with the differential interferometry concept, producing the advanced “differential tomography” (Diff-Tomo, “4D”) processing mode which furnishes “space-time” signatures of multiple scatterer dynamics in the SAR cell. Advances in the application of this new framework are investigated for complex volume scattering scenarios including temporal signal variations, both from scatterer temporal decorrelation and deformation motions. In particular, new results are reported concerning the potentials of Diff-Tomo for the analysis of forest scenarios, based on the original concept of the space-time signatures of temporal decorrelation. E-SAR P-band data results are expanded of tomography robust to temporal decorrelation, and first trials are reported of separation of different temporal decorrelation mechanisms of canopy and ground, and of sensing possible sub-canopy subsidences.

How do People Make Sense of Unfamiliar Visualizations?: A Grounded Model of Novice's Information Visualization Sensemaking.

PubMed

Lee, Sukwon; Kim, Sung-Hee; Hung, Ya-Hsin; Lam, Heidi; Kang, Youn-ah; Yi, Ji Soo

2016-01-01

In this paper, we would like to investigate how people make sense of unfamiliar information visualizations. In order to achieve the research goal, we conducted a qualitative study by observing 13 participants when they endeavored to make sense of three unfamiliar visualizations (i.e., a parallel-coordinates plot, a chord diagram, and a treemap) that they encountered for the first time. We collected data including audio/video record of think-aloud sessions and semi-structured interview; and analyzed the data using the grounded theory method. The primary result of this study is a grounded model of NOvice's information Vlsualization Sensemaking (NOVIS model), which consists of the five major cognitive activities: 1 encountering visualization, 2 constructing a frame, 3 exploring visualization, 4 questioning the frame, and 5 floundering on visualization. We introduce the NOVIS model by explaining the five activities with representative quotes from our participants. We also explore the dynamics in the model. Lastly, we compare with other existing models and share further research directions that arose from our observations.

A telescopic cinema sound camera for observing high altitude aerospace vehicles

NASA Astrophysics Data System (ADS)

Slater, Dan

2014-09-01

Rockets and other high altitude aerospace vehicles produce interesting visual and aural phenomena that can be remotely observed from long distances. This paper describes a compact, passive and covert remote sensing system that can produce high resolution sound movies at >100 km viewing distances. The telescopic high resolution camera is capable of resolving and quantifying space launch vehicle dynamics including plume formation, staging events and payload fairing jettison. Flight vehicles produce sounds and vibrations that modulate the local electromagnetic environment. These audio frequency modulations can be remotely sensed by passive optical and radio wave detectors. Acousto-optic sensing methods were primarily used but an experimental radioacoustic sensor using passive micro-Doppler radar techniques was also tested. The synchronized combination of high resolution flight vehicle imagery with the associated vehicle sounds produces a cinema like experience that that is useful in both an aerospace engineering and a Hollywood film production context. Examples of visual, aural and radar observations of the first SpaceX Falcon 9 v1.1 rocket launch are shown and discussed.

The Complicate Observations and Multi-Parameter Land Information Constructions on Allied Telemetry Experiment (COMPLICATE)

PubMed Central

Tian, Xin; Li, Zengyuan; Chen, Erxue; Liu, Qinhuo; Yan, Guangjian; Wang, Jindi; Niu, Zheng; Zhao, Shaojie; Li, Xin; Pang, Yong; Su, Zhongbo; van der Tol, Christiaan; Liu, Qingwang; Wu, Chaoyang; Xiao, Qing; Yang, Le; Mu, Xihan; Bo, Yanchen; Qu, Yonghua; Zhou, Hongmin; Gao, Shuai; Chai, Linna; Huang, Huaguo; Fan, Wenjie; Li, Shihua; Bai, Junhua; Jiang, Lingmei; Zhou, Ji

2015-01-01

The Complicate Observations and Multi-Parameter Land Information Constructions on Allied Telemetry Experiment (COMPLICATE) comprises a network of remote sensing experiments designed to enhance the dynamic analysis and modeling of remotely sensed information for complex land surfaces. Two types of experimental campaigns were established under the framework of COMPLICATE. The first was designed for continuous and elaborate experiments. The experimental strategy helps enhance our understanding of the radiative and scattering mechanisms of soil and vegetation and modeling of remotely sensed information for complex land surfaces. To validate the methodologies and models for dynamic analyses of remote sensing for complex land surfaces, the second campaign consisted of simultaneous satellite-borne, airborne, and ground-based experiments. During field campaigns, several continuous and intensive observations were obtained. Measurements were undertaken to answer key scientific issues, as follows: 1) Determine the characteristics of spatial heterogeneity and the radiative and scattering mechanisms of remote sensing on complex land surfaces. 2) Determine the mechanisms of spatial and temporal scale extensions for remote sensing on complex land surfaces. 3) Determine synergist inversion mechanisms for soil and vegetation parameters using multi-mode remote sensing on complex land surfaces. Here, we introduce the background, the objectives, the experimental designs, the observations and measurements, and the overall advances of COMPLICATE. As a result of the implementation of COMLICATE and for the next several years, we expect to contribute to quantitative remote sensing science and Earth observation techniques. PMID:26332035

Get Close to Glaciers with Satellite Imagery.

ERIC Educational Resources Information Center

Hall, Dorothy K.

1986-01-01

Discusses the use of remote sensing from satellites to monitor glaciers. Discusses efforts to use remote sensing satellites of the Landsat series for examining the global distribution, mass, balance, movements, and dynamics of the world's glaciers. Includes several Landsat images of various glaciers. (TW)

Ground based remote sensing and physiological measurements provide novel insights into canopy photosynthetic optimization in arctic shrubs

NASA Astrophysics Data System (ADS)

Magney, T. S.; Griffin, K. L.; Boelman, N.; Eitel, J.; Greaves, H.; Prager, C.; Logan, B.; Oliver, R.; Fortin, L.; Vierling, L. A.

2014-12-01

Because changes in vegetation structure and function in the Arctic are rapid and highly dynamic phenomena, efforts to understand the C balance of the tundra require repeatable, objective, and accurate remote sensing methods for estimating aboveground C pools and fluxes over large areas. A key challenge addressing the modelling of aboveground C is to utilize process-level information from fine-scale studies. Utilizing information obtained from high resolution remote sensing systems could help to better understand the C source/sink strength of the tundra, which will in part depend on changes in photosynthesis resulting from the partitioning of photosynthetic machinery within and among deciduous shrub canopies. Terrestrial LiDAR and passive hyperspectral remote sensing measurements offer an effective, repeatable, and scalable method to understand photosynthetic performance and partitioning at the canopy scale previously unexplored in arctic systems. Using a 3-D shrub canopy model derived from LiDAR, we quantified the light regime of leaves within shrub canopies to gain a better understanding of how light interception varies in response to the Arctic's complex radiation regime. This information was then coupled with pigment sampling (i.e., xanthophylls, and Chl a/b) to evaluate the optimization of foliage photosynthetic capacity within shrub canopies due to light availability. In addition, a lab experiment was performed to validate evidence of canopy level optimization via gradients of light intensity and leaf light environment. For this, hyperspectral reflectance (photochemical reflectance index (PRI)), and solar induced fluorescence (SIF)) was collected in conjunction with destructive pigment samples (xanthophylls) and chlorophyll fluorescence measurements in both sunlit and shaded canopy positions.

Application of Thermal Infrared Remote Sensing for Quantitative Evaluation of Crop Characteristics

NASA Technical Reports Server (NTRS)

Shaw, J.; Luvall, J.; Rickman, D.; Mask, P.; Wersinger, J.; Sullivan, D.; Arnold, James E. (Technical Monitor)

2002-01-01

Evidence suggests that thermal infrared emittance (TIR) at the field-scale is largely a function of the integrated crop/soil moisture continuum. Because soil moisture dynamics largely determine crop yields in non-irrigated farming (85 % of Alabama farms are non-irrigated), TIR may be an effective method of mapping within field crop yield variability, and possibly, absolute yields. The ability to map yield variability at juvenile growth stages can lead to improved soil fertility and pest management, as well as facilitating the development of economic forecasting. Researchers at GHCC/MSFC/NASA and Auburn University are currently investigating the role of TIR in site-specific agriculture. Site-specific agriculture (SSA), or precision farming, is a method of crop production in which zones and soils within a field are delineated and managed according to their unique properties. The goal of SSA is to improve farm profits and reduce environmental impacts through targeted agrochemical applications. The foundation of SSA depends upon the spatial and temporal characterization of soil and crop properties through the creation of management zones. Management zones can be delineated using: 1) remote sensing (RS) data, 2) conventional soil testing and soil mapping, and 3) yield mapping. Portions of this research have concentrated on using remote sensing data to map yield variability in corn (Zea mays L.) and soybean (Glycine max L.) crops. Remote sensing data have been collected for several fields in the Tennessee Valley region at various crop growth stages during the last four growing seasons. Preliminary results of this study will be presented.

Dynamic Histogram Analysis To Determine Free Energies and Rates from Biased Simulations.

PubMed

Stelzl, Lukas S; Kells, Adam; Rosta, Edina; Hummer, Gerhard

2017-12-12

We present an algorithm to calculate free energies and rates from molecular simulations on biased potential energy surfaces. As input, it uses the accumulated times spent in each state or bin of a histogram and counts of transitions between them. Optimal unbiased equilibrium free energies for each of the states/bins are then obtained by maximizing the likelihood of a master equation (i.e., first-order kinetic rate model). The resulting free energies also determine the optimal rate coefficients for transitions between the states or bins on the biased potentials. Unbiased rates can be estimated, e.g., by imposing a linear free energy condition in the likelihood maximization. The resulting "dynamic histogram analysis method extended to detailed balance" (DHAMed) builds on the DHAM method. It is also closely related to the transition-based reweighting analysis method (TRAM) and the discrete TRAM (dTRAM). However, in the continuous-time formulation of DHAMed, the detailed balance constraints are more easily accounted for, resulting in compact expressions amenable to efficient numerical treatment. DHAMed produces accurate free energies in cases where the common weighted-histogram analysis method (WHAM) for umbrella sampling fails because of slow dynamics within the windows. Even in the limit of completely uncorrelated data, where WHAM is optimal in the maximum-likelihood sense, DHAMed results are nearly indistinguishable. We illustrate DHAMed with applications to ion channel conduction, RNA duplex formation, α-helix folding, and rate calculations from accelerated molecular dynamics. DHAMed can also be used to construct Markov state models from biased or replica-exchange molecular dynamics simulations. By using binless WHAM formulated as a numerical minimization problem, the bias factors for the individual states can be determined efficiently in a preprocessing step and, if needed, optimized globally afterward.

Dynamics modeling for parallel haptic interfaces with force sensing and control.

PubMed

Bernstein, Nicholas; Lawrence, Dale; Pao, Lucy

2013-01-01

Closed-loop force control can be used on haptic interfaces (HIs) to mitigate the effects of mechanism dynamics. A single multidimensional force-torque sensor is often employed to measure the interaction force between the haptic device and the user's hand. The parallel haptic interface at the University of Colorado (CU) instead employs smaller 1D force sensors oriented along each of the five actuating rods to build up a 5D force vector. This paper shows that a particular manipulandum/hand partition in the system dynamics is induced by the placement and type of force sensing, and discusses the implications on force and impedance control for parallel haptic interfaces. The details of a "squaring down" process are also discussed, showing how to obtain reduced degree-of-freedom models from the general six degree-of-freedom dynamics formulation.

Ultrafast water sensing and thermal imaging by a metal-organic framework with switchable luminescence

NASA Astrophysics Data System (ADS)

Chen, Ling; Ye, Jia-Wen; Wang, Hai-Ping; Pan, Mei; Yin, Shao-Yun; Wei, Zhang-Wen; Zhang, Lu-Yin; Wu, Kai; Fan, Ya-Nan; Su, Cheng-Yong

2017-06-01

A convenient, fast and selective water analysis method is highly desirable in industrial and detection processes. Here a robust microporous Zn-MOF (metal-organic framework, Zn(hpi2cf)(DMF)(H2O)) is assembled from a dual-emissive H2hpi2cf (5-(2-(5-fluoro-2-hydroxyphenyl)-4,5-bis(4-fluorophenyl)-1H-imidazol-1-yl)isophthalic acid) ligand that exhibits characteristic excited state intramolecular proton transfer (ESIPT). This Zn-MOF contains amphipathic micropores (<3 Å) and undergoes extremely facile single-crystal-to-single-crystal transformation driven by reversible removal/uptake of coordinating water molecules simply stimulated by dry gas blowing or gentle heating at 70 °C, manifesting an excellent example of dynamic reversible coordination behaviour. The interconversion between the hydrated and dehydrated phases can turn the ligand ESIPT process on or off, resulting in sensitive two-colour photoluminescence switching over cycles. Therefore, this Zn-MOF represents an excellent PL water-sensing material, showing a fast (on the order of seconds) and highly selective response to water on a molecular level. Furthermore, paper or in situ grown ZnO-based sensing films have been fabricated and applied in humidity sensing (RH<1%), detection of traces of water (<0.05% v/v) in various organic solvents, thermal imaging and as a thermometer.

Remote sensing science for the Nineties; Proceedings of IGARSS '90 - 10th Annual International Geoscience and Remote Sensing Symposium, University of Maryland, College Park, May 20-24, 1990. Vols. 1, 2, & 3

NASA Technical Reports Server (NTRS)

1990-01-01

Various papers on remote sensing (RS) for the nineties are presented. The general topics addressed include: subsurface methods, radar scattering, oceanography, microwave models, atmospheric correction, passive microwave systems, RS in tropical forests, moderate resolution land analysis, SAR geometry and SNR improvement, image analysis, inversion and signal processing for geoscience, surface scattering, rain measurements, sensor calibration, wind measurements, terrestrial ecology, agriculture, geometric registration, subsurface sediment geology, radar modulation mechanisms, radar ocean scattering, SAR calibration, airborne radar systems, water vapor retrieval, forest ecosystem dynamics, land analysis, multisensor data fusion. Also considered are: geologic RS, RS sensor optical measurements, RS of snow, temperature retrieval, vegetation structure, global change, artificial intelligence, SAR processing techniques, geologic RS field experiment, stochastic modeling, topography and Digital Elevation model, SAR ocean waves, spaceborne lidar and optical, sea ice field measurements, millimeter waves, advanced spectroscopy, spatial analysis and data compression, SAR polarimetry techniques. Also discussed are: plant canopy modeling, optical RS techniques, optical and IR oceanography, soil moisture, sea ice back scattering, lightning cloud measurements, spatial textural analysis, SAR systems and techniques, active microwave sensing, lidar and optical, radar scatterometry, RS of estuaries, vegetation modeling, RS systems, EOS/SAR Alaska, applications for developing countries, SAR speckle and texture.

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

A design of an on-orbit radiometric calibration device for high dynamic range infrared remote sensors

NASA Astrophysics Data System (ADS)

Sheng, Yicheng; Jin, Weiqi; Dun, Xiong; Zhou, Feng; Xiao, Si

2017-10-01

With the demand of quantitative remote sensing technology growing, high reliability as well as high accuracy radiometric calibration technology, especially the on-orbit radiometric calibration device has become an essential orientation in term of quantitative remote sensing technology. In recent years, global launches of remote sensing satellites are equipped with innovative on-orbit radiometric calibration devices. In order to meet the requirements of covering a very wide dynamic range and no-shielding radiometric calibration system, we designed a projection-type radiometric calibration device for high dynamic range sensors based on the Schmidt telescope system. In this internal radiometric calibration device, we select the EF-8530 light source as the calibration blackbody. EF-8530 is a high emittance Nichrome (Ni-Cr) reference source. It can operate in steady or pulsed state mode at a peak temperature of 973K. The irradiance from the source was projected to the IRFPA. The irradiance needs to ensure that the IRFPA can obtain different amplitude of the uniform irradiance through the narrow IR passbands and cover the very wide dynamic range. Combining the internal on-orbit radiometric calibration device with the specially designed adaptive radiometric calibration algorithms, an on-orbit dynamic non-uniformity correction can be accomplished without blocking the optical beam from outside the telescope. The design optimizes optics, source design, and power supply electronics for irradiance accuracy and uniformity. The internal on-orbit radiometric calibration device not only satisfies a series of indexes such as stability, accuracy, large dynamic range and uniformity of irradiance, but also has the advantages of short heating and cooling time, small volume, lightweight, low power consumption and many other features. It can realize the fast and efficient relative radiometric calibration without shielding the field of view. The device can applied to the design and manufacture of the scanning infrared imaging system, the infrared remote sensing system, the infrared early-warning satellite, and so on.

Determinants of Curvature-Sensing Behavior for MARCKS-Fragment Peptides.

PubMed

de Jesus, Armando J; White, Ormacinda R; Flynn, Aaron D; Yin, Hang

2016-05-10

It is increasingly recognized that membrane curvature plays an important role in various cellular activities such as signaling and trafficking, as well as key issues involving health and disease development. Thus, curvature-sensing peptides are essential to the study and detection of highly curved bilayer structures. The effector domain of myristoylated alanine-rich C-kinase substrate (MARCKS-ED) has been demonstrated to have curvature-sensing ability. Research of the MARCKS-ED has further revealed that its Lys and Phe residues play an essential role in how MARCKS-ED detects and binds to curved bilayers. MARCKS-ED has the added property of being a lower-molecular-weight curvature sensor, which offers advantages in production. With that in mind, this work investigates peptide-sequence-related factors that influence curvature sensing and explores whether peptide fragments of even shorter length can function as curvature sensors. Using both experimental and computational methods, we studied the curvature-sensing capabilities of seven fragments of MARCKS-ED. Two of the longer fragments were designed from approximately the two halves of the full-length peptide whereas the five shorter fragments were taken from the central stretch of MARCKS-ED. Fully atomistic molecular dynamics simulations show that the fragments that remain bound to the bilayer exhibit interactions with the bilayer similar to that of the full-length MARCKS-ED peptide. Fluorescence enhancement and anisotropy assays, meanwhile, reveal that five of the MARCKS fragments possess the ability to sense membrane curvature. Based on the sequences of the curvature-sensing fragments, it appears that the ability to sense curvature involves a balance between the numbers of positively charged residues and hydrophobic anchoring residues. Together, these findings help crystallize our understanding of the molecular mechanisms underpinning the curvature-sensing behaviors of peptides, which will prove useful in the design of future curvature sensors. Copyright © 2016 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Indirectly sensing accelerator beam currents for limiting maximum beam current magnitude

DOEpatents

Bogaty, J.M.; Clifft, B.E.; Bollinger, L.M.

1995-08-08

A beam current limiter is disclosed for sensing and limiting the beam current in a particle accelerator, such as a cyclotron or linear accelerator, used in scientific research and medical treatment. A pair of independently operable capacitive electrodes sense the passage of charged particle bunches to develop an RF signal indicative of the beam current magnitude produced at the output of a bunched beam accelerator. The RF signal produced by each sensing electrode is converted to a variable DC voltage indicative of the beam current magnitude. The variable DC voltages thus developed are compared to each other to verify proper system function and are further compared to known references to detect beam currents in excess of pre-established limits. In the event of a system malfunction, or if the detected beam current exceeds pre-established limits, the beam current limiter automatically inhibits further accelerator operation. A high Q tank circuit associated with each sensing electrode provides a narrow system bandwidth to reduce noise and enhance dynamic range. System linearity is provided by injecting, into each sensing electrode, an RF signal that is offset from the bunching frequency by a pre-determined beat frequency to ensure that subsequent rectifying diodes operate in a linear response region. The system thus provides a large dynamic range in combination with good linearity. 6 figs.

Indirectly sensing accelerator beam currents for limiting maximum beam current magnitude

DOEpatents

Bogaty, John M.; Clifft, Benny E.; Bollinger, Lowell M.

1995-01-01

A beam current limiter for sensing and limiting the beam current in a particle accelerator, such as a cyclotron or linear accelerator, used in scientific research and medical treatment. A pair of independently operable capacitive electrodes sense the passage of charged particle bunches to develop an RF signal indicative of the beam current magnitude produced at the output of a bunched beam accelerator. The RF signal produced by each sensing electrode is converted to a variable DC voltage indicative of the beam current magnitude. The variable DC voltages thus developed are compared to each other to verify proper system function and are further compared to known references to detect beam currents in excess of pre-established limits. In the event of a system malfunction, or if the detected beam current exceeds pre-established limits, the beam current limiter automatically inhibits further accelerator operation. A high Q tank circuit associated with each sensing electrode provides a narrow system bandwidth to reduce noise and enhance dynamic range. System linearity is provided by injecting, into each sensing electrode, an RF signal that is offset from the bunching frequency by a pre-determined beat frequency to ensure that subsequent rectifying diodes operate in a linear response region. The system thus provides a large dynamic range in combination with good linearity.

Remote sensing and GIS studies on the spatial distribution and management of Japanese beetle adults and grubs

NASA Astrophysics Data System (ADS)

Hamilton, Randy M.

Remote sensing and geographic information systems (GIS) are rapidly developing technologies that offer new opportunities and potentially more effective methods for detecting and monitoring insect pests, as well as understanding their spatial dynamics. These technologies (coupled with traditional trapping) were investigated for their use in managing Japanese beetle (Popillia japonica Newman) adults and grubs and studying their spatial distribution and dynamics. Japanese beetle grubs are important root-feeding pests of turfgrass in the Midwest and eastern United States. No non-invasive methods exist to detect grub infestations before unsightly damage has occurred. Studies were conducted to determine whether remote sensing could be used to detect the pre-visible symptoms of simulated and natural grub damage in turfgrass. Simulated grub damage was detected with surface temperature measurements (but not with spectrometer data) before significant visual differences were found. Plots infested with grubs were distinguished from uninfested plots using spectrometer data 10--16 days before significant differences in visual ratings were found. Results using multispectral imagery were mixed. Currently, Japanese beetles are not established in the western United States. There is great concern over their inadvertent transportation into Pacific costal states via cargo transport planes. Beetles may fly onboard cargo planes while they are loaded or unloaded and be accidentally transported to the western states. A study was initiated to evaluate trapping as a method to reliably detect Japanese beetle hotspots near cargo terminals at the Indianapolis International Airport and to assess the spatial variability of the population around the airport. The potential influence of land use on beetle abundance was also assessed, using a GIS. Baited Japanese beetle traps were placed around the perimeter of the airport and emptied daily. Location-dependent variation in trap catch was found. Seasonal average trap catches were highly correlated from year to year, by location. A mark-release-recapture study showed that Japanese beetles frequently flew up to 500m during a day, but could travel up to 700m. Using a GIS, a spatially explicit map of land use and trap location was created. Agricultural land within 500m of the traps was generally positively correlated with trap catch.

Biologically inspired rate control of chaos.

PubMed

Olde Scheper, Tjeerd V

2017-10-01

The overall intention of chaotic control is to eliminate chaos and to force the system to become stable in the classical sense. In this paper, I demonstrate a more subtle method that does not eliminate all traces of chaotic behaviour; yet it consistently, and reliably, can provide control as intended. The Rate Control of Chaos (RCC) method is derived from metabolic control processes and has several remarkable properties. RCC can control complex systems continuously, and unsupervised, it can also maintain control across bifurcations, and in the presence of significant systemic noise. Specifically, I show that RCC can control a typical set of chaotic models, including the 3 and 4 dimensional chaotic Lorenz systems, in all modes. Furthermore, it is capable of controlling spatiotemporal chaos without supervision and maintains control of the system across bifurcations. This property of RCC allows a dynamic system to operate in parameter spaces that are difficult to control otherwise. This may be particularly interesting for the control of forced systems or dynamic systems that are chaotically perturbed. These control properties of RCC are applicable to a range of dynamic systems, thereby appearing to have far-reaching effects beyond just controlling chaos. RCC may also point to the existence of a biochemical control function of an enzyme, to stabilise the dynamics of the reaction cascade.

Monitoring spacecraft atmosphere contaminants by laser absorption spectroscopy

NASA Technical Reports Server (NTRS)

Steinfeld, J. I.

1976-01-01

Laser-based spectrophotometric methods which have been proposed for the detection of trace concentrations of gaseous contaminants include Raman backscattering (LIDAR) and passive radiometry (LOPAIR). Remote sensing techniques using laser spectrometry are presented and in particular a simple long-path laser absorption method (LOLA), which is capable of resolving complex mixtures of closely related trace contaminants at ppm levels is discussed. A number of species were selected for study which are representative of those most likely to accumulate in closed environments, such as submarines or long-duration manned space flights. Computer programs were developed which will permit a real-time analysis of the monitored atmosphere. Estimates of the dynamic range of this monitoring technique for various system configurations, and comparison with other methods of analysis, are given.

Biologically inspired dynamic material systems.

PubMed

Studart, André R

2015-03-09

Numerous examples of material systems that dynamically interact with and adapt to the surrounding environment are found in nature, from hair-based mechanoreceptors in animals to self-shaping seed dispersal units in plants to remodeling bone in vertebrates. Inspired by such fascinating biological structures, a wide range of synthetic material systems have been created to replicate the design concepts of dynamic natural architectures. Examples of biological structures and their man-made counterparts are herein revisited to illustrate how dynamic and adaptive responses emerge from the intimate microscale combination of building blocks with intrinsic nanoscale properties. By using top-down photolithographic methods and bottom-up assembly approaches, biologically inspired dynamic material systems have been created 1) to sense liquid flow with hair-inspired microelectromechanical systems, 2) to autonomously change shape by utilizing plantlike heterogeneous architectures, 3) to homeostatically influence the surrounding environment through self-regulating adaptive surfaces, and 4) to spatially concentrate chemical species by using synthetic microcompartments. The ever-increasing complexity and remarkable functionalities of such synthetic systems offer an encouraging perspective to the rich set of dynamic and adaptive properties that can potentially be implemented in future man-made material systems. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Towards understanding temporal and spatial dynamics of seagrass landscapes using time-series remote sensing

NASA Astrophysics Data System (ADS)

Lyons, Mitchell B.; Roelfsema, Chris M.; Phinn, Stuart R.

2013-03-01

The spatial and temporal dynamics of seagrasses have been well studied at the leaf to patch scales, however, the link to large spatial extent landscape and population dynamics is still unresolved in seagrass ecology. Traditional remote sensing approaches have lacked the temporal resolution and consistency to appropriately address this issue. This study uses two high temporal resolution time-series of thematic seagrass cover maps to examine the spatial and temporal dynamics of seagrass at both an inter- and intra-annual time scales, one of the first globally to do so at this scale. Previous work by the authors developed an object-based approach to map seagrass cover level distribution from a long term archive of Landsat TM and ETM+ images on the Eastern Banks (≈200 km2), Moreton Bay, Australia. In this work a range of trend and time-series analysis methods are demonstrated for a time-series of 23 annual maps from 1988 to 2010 and a time-series of 16 monthly maps during 2008-2010. Significant new insight was presented regarding the inter- and intra-annual dynamics of seagrass persistence over time, seagrass cover level variability, seagrass cover level trajectory, and change in area of seagrass and cover levels over time. Overall we found that there was no significant decline in total seagrass area on the Eastern Banks, but there was a significant decline in seagrass cover level condition. A case study of two smaller communities within the Eastern Banks that experienced a decline in both overall seagrass area and condition are examined in detail, highlighting possible differences in environmental and process drivers. We demonstrate how trend and time-series analysis enabled seagrass distribution to be appropriately assessed in context of its spatial and temporal history and provides the ability to not only quantify change, but also describe the type of change. We also demonstrate the potential use of time-series analysis products to investigate seagrass growth and decline as well as the processes that drive it. This study demonstrates clear benefits over traditional seagrass mapping and monitoring approaches, and provides a proof of concept for the use of trend and time-series analysis of remotely sensed seagrass products to benefit current endeavours in seagrass ecology.

Dynamic profiling of different ready-to-drink fermented dairy products: A comparative study using Temporal Check-All-That-Apply (TCATA), Temporal Dominance of Sensations (TDS) and Progressive Profile (PP).

PubMed

Esmerino, Erick A; Castura, John C; Ferraz, Juliana P; Tavares Filho, Elson R; Silva, Ramon; Cruz, Adriano G; Freitas, Mônica Q; Bolini, Helena M A

2017-11-01

Despite the several differences in ingredients, processes and nutritional values, dairy foods as yogurts, fermented milks and milk beverages are widely accepted worldwide, and although they have their sensory profiling normally covered by descriptive analyses, the temporal perception involved during the consumption are rarely considered. In this sense, the present work aimed to assess the dynamic sensory profile of three categories of fermented dairy products using different temporal methodologies: Temporal Dominance of Sensations (TDS), Progressive Profiling (PP), Temporal CATA (TCATA), and compare the results obtained. The findings showed that the different sensory characteristics among the products are basically related to their commercial identity. Regarding the methods, all of them collected the variations between samples with great correlation between data. In addition, to detect differences in intensities, TCATA showed to be the most sensitive method in detecting textural changes. When using PP, a balanced experimental design considering the number of attributes, time intervals, and food matrix must be weighed. The findings are of interest to guide sensory and consumer practitioners involved in the dairy production to formulate/reformulate their products and help them choosing the most suitable dynamic method to temporally evaluate them. Copyright © 2017 Elsevier Ltd. All rights reserved.

Identifying the arterial input function from dynamic contrast-enhanced magnetic resonance images using an apex-seeking technique

NASA Astrophysics Data System (ADS)

Martel, Anne L.

2004-04-01

In order to extract quantitative information from dynamic contrast-enhanced MR images (DCE-MRI) it is usually necessary to identify an arterial input function. This is not a trivial problem if there are no major vessels present in the field of view. Most existing techniques rely on operator intervention or use various curve parameters to identify suitable pixels but these are often specific to the anatomical region or the acquisition method used. They also require the signal from several pixels to be averaged in order to improve the signal to noise ratio, however this introduces errors due to partial volume effects. We have described previously how factor analysis can be used to automatically separate arterial and venous components from DCE-MRI studies of the brain but although that method works well for single slice images through the brain when the blood brain barrier technique is intact, it runs into problems for multi-slice images with more complex dynamics. This paper will describe a factor analysis method that is more robust in such situations and is relatively insensitive to the number of physiological components present in the data set. The technique is very similar to that used to identify spectral end-members from multispectral remote sensing images.

Dynamic assessments of population exposure to urban greenspace using multi-source big data.

PubMed

Song, Yimeng; Huang, Bo; Cai, Jixuan; Chen, Bin

2018-09-01

A growing body of evidence has proven that urban greenspace is beneficial to improve people's physical and mental health. However, knowledge of population exposure to urban greenspace across different spatiotemporal scales remains unclear. Moreover, the majority of existing environmental assessments are unable to quantify how residents enjoy their ambient greenspace during their daily life. To deal with this challenge, we proposed a dynamic method to assess urban greenspace exposure with the integration of mobile-phone locating-request (MPL) data and high-spatial-resolution remote sensing images. This method was further applied to 30 major cities in China by assessing cities' dynamic greenspace exposure levels based on residents' surrounding areas with different buffer scales (0.5km, 1km, and 1.5km). Results showed that regarding residents' 0.5-km surrounding environment, Wenzhou and Hangzhou were found to be with the greenest exposure experience, whereas Zhengzhou and Tangshan were the least ones. The obvious diurnal and daily variations of population exposure to their surrounding greenspace were also identified to be highly correlated with the distribution pattern of urban greenspace and the dynamics of human mobility. Compared with two common measurements of urban greenspace (green coverage rate and green area per capita), the developed method integrated the dynamics of population distribution and geographic locations of urban greenspace into the exposure assessment, thereby presenting a more reasonable way to assess population exposure to urban greenspace. Additionally, this dynamic framework could hold potential utilities in supporting urban planning studies and environmental health studies and advancing our understanding of the magnitude of population exposure to greenspace at different spatiotemporal scales. Copyright © 2018 Elsevier B.V. All rights reserved.

Advancing High Spatial and Spectral Resolution Remote Sensing for Observing Plant Community Response to Environmental Variability and Change in the Alaskan Arctic

NASA Astrophysics Data System (ADS)

Vargas Zesati, Sergio A.

The Arctic is being impacted by climate change more than any other region on Earth. Impacts to terrestrial ecosystems have the potential to manifest through feedbacks with other components of the Earth System. Of particular concern is the potential for the massive store of soil organic carbon to be released from arctic permafrost to the atmosphere where it could exacerbate greenhouse warming and impact global climate and biogeochemical cycles. Even though substantial gains to our understanding of the changing Arctic have been made, especially over the past decade, linking research results from plot to regional scales remains a challenge due to the lack of adequate low/mid-altitude sampling platforms, logistic constraints, and the lack of cross-scale validation of research methodologies. The prime motivation of this study is to advance observational capacities suitable for documenting multi-scale environmental change in arctic terrestrial landscapes through the development and testing of novel ground-based and low altitude remote sensing methods. Specifically this study addressed the following questions: • How well can low-cost kite aerial photography and advanced computer vision techniques model the microtopographic heterogeneity of changing tundra surfaces? • How does imagery from kite aerial photography and fixed time-lapse digital cameras (pheno-cams) compare in their capacity to monitor plot-level phenological dynamics of arctic vegetation communities? • Can the use of multi-scale digital imaging systems be scaled to improve measurements of ecosystem properties and processes at the landscape level? • How do results from ground-based and low altitude digital remote sensing of the spatiotemporal variability in ecosystem processes compare with those from satellite remote sensing platforms? Key findings from this study suggest that cost-effective alternative digital imaging and remote sensing methods are suitable for monitoring and quantifying plot to landscape level ecosystem structure and phenological dynamics at multiple temporal scales. Overall, this study has furthered our knowledge of how tundra ecosystems in the Arctic change seasonally and how such change could impact remote sensing studies conducted from multiple platforms and across multiple spatial scales. Additionally, this study also highlights the urgent need for research into the validation of satellite products in order to better understand the causes and consequences of the changing Arctic and its potential effects on global processes. This study focused on sites located in northern Alaska and was formed in collaboration with Florida International University (FIU) and Grand Valley State University (GVSU) as a contribution to the US Arctic Observing Network (AON). All efforts were supported through the National Science Foundation (NSF), the Cyber-ShARE Center of Excellence, and the International Tundra Experiment (ITEX).

3D sensitivity encoded ellipsoidal MR spectroscopic imaging of gliomas at 3T☆

PubMed Central

Ozturk-Isik, Esin; Chen, Albert P.; Crane, Jason C.; Bian, Wei; Xu, Duan; Han, Eric T.; Chang, Susan M.; Vigneron, Daniel B.; Nelson, Sarah J.

2010-01-01

Purpose The goal of this study was to implement time efficient data acquisition and reconstruction methods for 3D magnetic resonance spectroscopic imaging (MRSI) of gliomas at a field strength of 3T using parallel imaging techniques. Methods The point spread functions, signal to noise ratio (SNR), spatial resolution, metabolite intensity distributions and Cho:NAA ratio of 3D ellipsoidal, 3D sensitivity encoding (SENSE) and 3D combined ellipsoidal and SENSE (e-SENSE) k-space sampling schemes were compared with conventional k-space data acquisition methods. Results The 3D SENSE and e-SENSE methods resulted in similar spectral patterns as the conventional MRSI methods. The Cho:NAA ratios were highly correlated (P<.05 for SENSE and P<.001 for e-SENSE) with the ellipsoidal method and all methods exhibited significantly different spectral patterns in tumor regions compared to normal appearing white matter. The geometry factors ranged between 1.2 and 1.3 for both the SENSE and e-SENSE spectra. When corrected for these factors and for differences in data acquisition times, the empirical SNRs were similar to values expected based upon theoretical grounds. The effective spatial resolution of the SENSE spectra was estimated to be same as the corresponding fully sampled k-space data, while the spectra acquired with ellipsoidal and e-SENSE k-space samplings were estimated to have a 2.36–2.47-fold loss in spatial resolution due to the differences in their point spread functions. Conclusion The 3D SENSE method retained the same spatial resolution as full k-space sampling but with a 4-fold reduction in scan time and an acquisition time of 9.28 min. The 3D e-SENSE method had a similar spatial resolution as the corresponding ellipsoidal sampling with a scan time of 4:36 min. Both parallel imaging methods provided clinically interpretable spectra with volumetric coverage and adequate SNR for evaluating Cho, Cr and NAA. PMID:19766422

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.

Superconducting Bearings Assisted by Self-sensing AMBs in Liquid Nitrogen

NASA Astrophysics Data System (ADS)

Komori, Mochimitsu; Shiraishi, Chiaki

This paper describes newly developed superconducting magnetic bearings (SMBs) assisted by self-sensing active magnetic bearings (AMBs). The self-sensing AMBs detect the gaps between rotor and electromagnets. The principle of the self-sensing sensors is based on a differential transformer. The sensitivity in liquid nitrogen is almost equal to that in the air. The sensor is found to be useful in liquid nitrogen at 77K(-196°C). Moreover, the sensors are applied to the SMBs. In this paper, dynamics of the SMBs with self-sensing AMBs are discussed. From the results, it is found that the system is useful and promising.

Sensing of molecules using quantum dynamics

PubMed Central

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

2015-01-01

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

Non-whole beat correlation method for the identification of an unbalance response of a dual-rotor system with a slight rotating speed difference

NASA Astrophysics Data System (ADS)

Zhang, Z. X.; Wang, L. Z.; Jin, Z. J.; Zhang, Q.; Li, X. L.

2013-08-01

The efficient identification of the unbalanced responses in the inner and outer rotors from the beat vibration is the key step in the dynamic balancing of a dual-rotor system with a slight rotating speed difference. This paper proposes a non-whole beat correlation method to identify the unbalance responses whose integral time is shorter than the whole beat correlation method. The principle, algorithm and parameter selection of the proposed method is emphatically demonstrated in this paper. From the numerical simulation and balancing experiment conducted on horizontal decanter centrifuge, conclusions can be drawn that the proposed approach is feasible and practicable. This method makes important sense in developing the field balancing equipment based on portable Single Chip Microcomputer (SCMC) with low expense.

Learning Methods of Remote Sensing In the 2013 Curriculum of Secondary School

NASA Astrophysics Data System (ADS)

Lili Somantri, Nandi

2016-11-01

The new remote sensing material included in the subjects of geography in the curriculum of 1994. For geography teachers generation of 90s and over who in college do not get the material remote sensing, for teaching is a tough matter. Most teachers only give a theoretical matter, and do not carry out practical reasons in the lack of facilities and infrastructure of computer laboratories. Therefore, in this paper studies the importance about the method or manner of teaching remote sensing material in schools. The purpose of this paper is 1) to explain the position of remote sensing material in the study of geography, 2) analyze the Geography Curriculum 2013 Subjects related to remote sensing material, 3) describes a method of teaching remote sensing material in schools. The method used in this paper is a descriptive analytical study supported by the literature. The conclusion of this paper that the position of remote sensing in the study of geography is a method or a way to obtain spatial data earth's surface. In the 2013 curriculum remote sensing material has been applied to the study of land use and transportation. Remote sensing methods of teaching must go through a practicum, which starts from the introduction of the theory of remote sensing, data extraction phase of remote sensing imagery to produce maps, both visually and digitally, field surveys, interpretation of test accuracy, and improved maps.

Fabrication of optical chemical ammonia sensors using anodized alumina supports and sol-gel method.

PubMed

Markovics, Akos; Kovács, Barna

2013-05-15

In this comparative study, the fabrication and the sensing properties of various reflectometric optical ammonia gas sensors are described. In the first set of experiments the role of the support material was investigated on four different sensor membranes. Two of them were prepared by the adsorption of bromocresol green indicator on anodized aluminum plates. The applied anodizing voltages were 12 V and 24 V, which resulted in different dynamic ranges and response times for gaseous ammonia. The sol-gel method was used for the preparation of the other batch of sensors. These layers were coated on anodized aluminum plates (24 V) and on standard microscope cover glasses. In spite of the identical sensing chemistry, slightly different response times were measured merely because of the aluminum surface porosity. Gas molecules can remain entrapped in the pores, which results in delayed recovery time. On the other hand, the porous oxide film provides excellent adhesion, making the anodized aluminum an attractive support for the sol-gel layer. Copyright © 2013 Elsevier B.V. All rights reserved.

Applying compressive sensing to TEM video: A substantial frame rate increase on any camera

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

Stevens, Andrew; Kovarik, Libor; Abellan, Patricia

One of the main limitations of imaging at high spatial and temporal resolution during in-situ transmission electron microscopy (TEM) experiments is the frame rate of the camera being used to image the dynamic process. While the recent development of direct detectors has provided the hardware to achieve frame rates approaching 0.1 ms, the cameras are expensive and must replace existing detectors. In this paper, we examine the use of coded aperture compressive sensing (CS) methods to increase the frame rate of any camera with simple, low-cost hardware modifications. The coded aperture approach allows multiple sub-frames to be coded and integratedmore » into a single camera frame during the acquisition process, and then extracted upon readout using statistical CS inversion. Here we describe the background of CS and statistical methods in depth and simulate the frame rates and efficiencies for in-situ TEM experiments. Depending on the resolution and signal/noise of the image, it should be possible to increase the speed of any camera by more than an order of magnitude using this approach.« less

Applying compressive sensing to TEM video: A substantial frame rate increase on any camera

DOE PAGES

Stevens, Andrew; Kovarik, Libor; Abellan, Patricia; ...

2015-08-13

One of the main limitations of imaging at high spatial and temporal resolution during in-situ transmission electron microscopy (TEM) experiments is the frame rate of the camera being used to image the dynamic process. While the recent development of direct detectors has provided the hardware to achieve frame rates approaching 0.1 ms, the cameras are expensive and must replace existing detectors. In this paper, we examine the use of coded aperture compressive sensing (CS) methods to increase the frame rate of any camera with simple, low-cost hardware modifications. The coded aperture approach allows multiple sub-frames to be coded and integratedmore » into a single camera frame during the acquisition process, and then extracted upon readout using statistical CS inversion. Here we describe the background of CS and statistical methods in depth and simulate the frame rates and efficiencies for in-situ TEM experiments. Depending on the resolution and signal/noise of the image, it should be possible to increase the speed of any camera by more than an order of magnitude using this approach.« less

Nanomaterials-based biosensors for detection of microorganisms and microbial toxins.

PubMed

Sutarlie, Laura; Ow, Sian Yang; Su, Xiaodi

2017-04-01

Detection of microorganisms and microbial toxins is important for health and safety. Due to their unique physical and chemical properties, nanomaterials have been extensively used to develop biosensors for rapid detection of microorganisms with microbial cells and toxins as target analytes. In this paper, the design principles of nanomaterials-based biosensors for four selected analyte categories (bacteria cells, toxins, mycotoxins, and protozoa cells), closely associated with the target analytes' properties is reviewed. Five signal transducing methods that are less equipment intensive (colorimetric, fluorimetric, surface enhanced Raman scattering, electrochemical, and magnetic relaxometry methods) is described and compared for their sensory performance (in term oflimit of detection, dynamic range, and response time) for all analyte categories. In the end, the suitability of these five sensing principles for on-site or field applications is discussed. With a comprehensive coverage of nanomaterials, design principles, sensing principles, and assessment on the sensory performance and suitability for on-site application, this review offers valuable insight and perspective for designing suitable nanomaterials-based microorganism biosensors for a given application. Copyright © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A compressed sensing method with analytical results for lidar feature classification

NASA Astrophysics Data System (ADS)

Allen, Josef D.; Yuan, Jiangbo; Liu, Xiuwen; Rahmes, Mark

2011-04-01

We present an innovative way to autonomously classify LiDAR points into bare earth, building, vegetation, and other categories. One desirable product of LiDAR data is the automatic classification of the points in the scene. Our algorithm automatically classifies scene points using Compressed Sensing Methods via Orthogonal Matching Pursuit algorithms utilizing a generalized K-Means clustering algorithm to extract buildings and foliage from a Digital Surface Models (DSM). This technology reduces manual editing while being cost effective for large scale automated global scene modeling. Quantitative analyses are provided using Receiver Operating Characteristics (ROC) curves to show Probability of Detection and False Alarm of buildings vs. vegetation classification. Histograms are shown with sample size metrics. Our inpainting algorithms then fill the voids where buildings and vegetation were removed, utilizing Computational Fluid Dynamics (CFD) techniques and Partial Differential Equations (PDE) to create an accurate Digital Terrain Model (DTM) [6]. Inpainting preserves building height contour consistency and edge sharpness of identified inpainted regions. Qualitative results illustrate other benefits such as Terrain Inpainting's unique ability to minimize or eliminate undesirable terrain data artifacts.

An Embedded Sensory System for Worker Safety: Prototype Development and Evaluation

PubMed Central

Cho, Chunhee; Park, JeeWoong

2018-01-01

At a construction site, workers mainly rely on two senses, which are sight and sound, in order to perceive their physical surroundings. However, they are often hindered by the nature of most construction sites, which are usually dynamic, loud, and complicated. To overcome these challenges, this research explored a method using an embedded sensory system that might offer construction workers an artificial sensing ability to better perceive their surroundings. This study identified three parameters (i.e., intensity, signal length, and delay between consecutive pulses) needed for tactile-based signals for the construction workers to communicate quickly. We developed a prototype system based on these parameters, conducted experimental studies to quantify and validate the sensitivity of the parameters for quick communication, and analyzed test data to reveal what was added by this method in order to perceive information from the tactile signals. The findings disclosed that the parameters of tactile-based signals and their distinguishable ranges could be perceived in a short amount of time (i.e., a fraction of a second). Further experimentation demonstrated the capability of the identified unit signals combined with a signal mapping technique to effectively deliver simple information to individuals and offer an additional sense of awareness to the surroundings. The findings of this study could serve as a basis for future research in exploring advanced tactile-based messages to overcome challenges in environments for which communication is a struggle. PMID:29662008

An Embedded Sensory System for Worker Safety: Prototype Development and Evaluation.

PubMed

Cho, Chunhee; Park, JeeWoong

2018-04-14

At a construction site, workers mainly rely on two senses, which are sight and sound, in order to perceive their physical surroundings. However, they are often hindered by the nature of most construction sites, which are usually dynamic, loud, and complicated. To overcome these challenges, this research explored a method using an embedded sensory system that might offer construction workers an artificial sensing ability to better perceive their surroundings. This study identified three parameters (i.e., intensity, signal length, and delay between consecutive pulses) needed for tactile-based signals for the construction workers to communicate quickly. We developed a prototype system based on these parameters, conducted experimental studies to quantify and validate the sensitivity of the parameters for quick communication, and analyzed test data to reveal what was added by this method in order to perceive information from the tactile signals. The findings disclosed that the parameters of tactile-based signals and their distinguishable ranges could be perceived in a short amount of time (i.e., a fraction of a second). Further experimentation demonstrated the capability of the identified unit signals combined with a signal mapping technique to effectively deliver simple information to individuals and offer an additional sense of awareness to the surroundings. The findings of this study could serve as a basis for future research in exploring advanced tactile-based messages to overcome challenges in environments for which communication is a struggle.

Tracking the Creation of Tropical Forest Canopy Gaps with UAV Computer Vision Remote Sensing

NASA Astrophysics Data System (ADS)

Dandois, J. P.

2015-12-01

The formation of canopy gaps is fundamental for shaping forest structure and is an important component of ecosystem function. Recent time-series of airborne LIDAR have shown great promise for improving understanding of the spatial distribution and size of forest gaps. However, such work typically looks at gap formation across multiple years and important intra-annual variation in gap dynamics remains unknown. Here we present findings on the intra-annual dynamics of canopy gap formation within the 50 ha forest dynamics plot of Barro Colorado Island (BCI), Panama based on unmanned aerial vehicle (UAV) remote sensing. High-resolution imagery (7 cm GSD) over the 50 ha plot was obtained regularly (≈ every 10 days) beginning October 2014 using a UAV equipped with a point and shoot camera. Imagery was processed into three-dimensional (3D) digital surface models (DSMs) using automated computer vision structure from motion / photogrammetric methods. New gaps that formed between each UAV flight were identified by subtracting DSMs between each interval and identifying areas of large deviation. A total of 48 new gaps were detected from 2014-10-02 to 2015-07-23, with sizes ranging from less than 20 m2 to greater than 350 m2. The creation of new gaps was also evaluated across wet and dry seasons with 4.5 new gaps detected per month in the dry season (Jan. - May) and 5.2 per month outside the dry season (Oct. - Jan. & May - July). The incidence of gap formation was positively correlated with ground-surveyed liana stem density (R2 = 0.77, p < 0.001) at the 1 hectare scale. Further research will consider the role of climate in predicting gap formation frequency as well as site history and other edaphic factors. Future satellite missions capable of observing vegetation structure at greater extents and frequencies than airborne observations will be greatly enhanced by the high spatial and temporal resolution bridging scale made possible by UAV remote sensing.

Aircraft path planning for optimal imaging using dynamic cost functions

NASA Astrophysics Data System (ADS)

Christie, Gordon; Chaudhry, Haseeb; Kochersberger, Kevin

2015-05-01

Unmanned aircraft development has accelerated with recent technological improvements in sensing and communications, which has resulted in an "applications lag" for how these aircraft can best be utilized. The aircraft are becoming smaller, more maneuverable and have longer endurance to perform sensing and sampling missions, but operating them aggressively to exploit these capabilities has not been a primary focus in unmanned systems development. This paper addresses a means of aerial vehicle path planning to provide a realistic optimal path in acquiring imagery for structure from motion (SfM) reconstructions and performing radiation surveys. This method will allow SfM reconstructions to occur accurately and with minimal flight time so that the reconstructions can be executed efficiently. An assumption is made that we have 3D point cloud data available prior to the flight. A discrete set of scan lines are proposed for the given area that are scored based on visibility of the scene. Our approach finds a time-efficient path and calculates trajectories between scan lines and over obstacles encountered along those scan lines. Aircraft dynamics are incorporated into the path planning algorithm as dynamic cost functions to create optimal imaging paths in minimum time. Simulations of the path planning algorithm are shown for an urban environment. We also present our approach for image-based terrain mapping, which is able to efficiently perform a 3D reconstruction of a large area without the use of GPS data.

Deriving urban dynamic evolution rules from self-adaptive cellular automata with multi-temporal remote sensing images

NASA Astrophysics Data System (ADS)

He, Yingqing; Ai, Bin; Yao, Yao; Zhong, Fajun

2015-06-01

Cellular automata (CA) have proven to be very effective for simulating and predicting the spatio-temporal evolution of complex geographical phenomena. Traditional methods generally pose problems in determining the structure and parameters of CA for a large, complex region or a long-term simulation. This study presents a self-adaptive CA model integrated with an artificial immune system to discover dynamic transition rules automatically. The model's parameters are allowed to be self-modified with the application of multi-temporal remote sensing images: that is, the CA can adapt itself to the changed and complex environment. Therefore, urban dynamic evolution rules over time can be efficiently retrieved by using this integrated model. The proposed AIS-based CA model was then used to simulate the rural-urban land conversion of Guangzhou city, located in the core of China's Pearl River Delta. The initial urban land was directly classified from TM satellite image in the year 1990. Urban land in the years 1995, 2000, 2005, 2009 and 2012 was correspondingly used as the observed data to calibrate the model's parameters. With the quantitative index figure of merit (FoM) and pattern similarity, the comparison was further performed between the AIS-based model and a Logistic CA model. The results indicate that the AIS-based CA model can perform better and with higher precision in simulating urban evolution, and the simulated spatial pattern is closer to the actual development situation.

Ubiquitous Geo-Sensing for Context-Aware Analysis: Exploring Relationships between Environmental and Human Dynamics

PubMed Central

Sagl, Günther; Blaschke, Thomas; Beinat, Euro; Resch, Bernd

2012-01-01

Ubiquitous geo-sensing enables context-aware analyses of physical and social phenomena, i.e., analyzing one phenomenon in the context of another. Although such context-aware analysis can potentially enable a more holistic understanding of spatio-temporal processes, it is rarely documented in the scientific literature yet. In this paper we analyzed the collective human behavior in the context of the weather. We therefore explored the complex relationships between these two spatio-temporal phenomena to provide novel insights into the dynamics of urban systems. Aggregated mobile phone data, which served as a proxy for collective human behavior, was linked with the weather data from climate stations in the case study area, the city of Udine, Northern Italy. To identify and characterize potential patterns within the weather-human relationships, we developed a hybrid approach which integrates several spatio-temporal statistical analysis methods. Thereby we show that explanatory factor analysis, when applied to a number of meteorological variables, can be used to differentiate between normal and adverse weather conditions. Further, we measured the strength of the relationship between the ‘global’ adverse weather conditions and the spatially explicit effective variations in user-generated mobile network traffic for three distinct periods using the Maximal Information Coefficient (MIC). The analyses result in three spatially referenced maps of MICs which reveal interesting insights into collective human dynamics in the context of weather, but also initiate several new scientific challenges. PMID:23012571

Dynamic Calibration of Our Sense of Time

ERIC Educational Resources Information Center

Grivel, Jeremy; Bernasconi, Fosco; Manuel, Aurelie L.; Murray, Micah M.; Spierer, Lucas

2011-01-01

An accurate sense of time contributes to functions ranging from the perception and anticipation of sensory events to the production of coordinated movements. However, accumulating evidence demonstrates that time perception is subject to strong illusory distortion. In two experiments, we investigated whether the subjective speed of temporal…

Real-time QCM-D monitoring of cancer cell death early events in a dynamic context.

PubMed

Nowacki, Laetitia; Follet, Julie; Vayssade, Muriel; Vigneron, Pascale; Rotellini, Laura; Cambay, Florian; Egles, Christophe; Rossi, Claire

2015-02-15

Since a few years, the acoustic sensing of whole cell is the focus of increasing interest for monitoring the cytoskeletal cellular response to morphological modulators. We aimed at illustrating the potentialities of the quartz crystal microbalance with dissipation (QCM-D) technique for the real-time detection of the earliest morphological changes that occur at the cell-substrate interface during programmed cell death. Human breast cancer cells (MCF-7) grown on serum protein-coated gold sensors were placed in dynamic conditions under a continuous medium flow. The mass and viscoelasticity changes of the cells were tracked by monitoring the frequency and dissipation shifts during the first 4h of cell exposure to staurosporine, a well-known apoptosis inducer. We have identified a QCM-D signature characteristic of morphological modifications and cell detachment from the sensing surface that are related to the pro-apoptotic treatment. In particular, for low staurosporine doses below 1 µM, we showed that recording the dissipation shift allows to detect an early cell response which is undetectable after the same duration by the classical analytical techniques in cell biology. Furthermore, this sensing method allows quantifying the efficiency of the drug effect in less than 4h without requiring labeling and without interfering in the system, thus preventing any loss of information. In the actual context of targeted cancer therapy development, we believe that these results bring new insights in favor of the use of the non invasive QCM-D technique for quickly probing the cancer cell sensitivity to death inducer drugs. Copyright © 2014 Elsevier B.V. All rights reserved.

Social Sensor Analytics: Making Sense of Network Models in Social Media

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

Dowling, Chase P.; Harrison, Joshua J.; Sathanur, Arun V.

Social networks can be thought of as noisy sensor networks mapping real world information to the web. Owing to the extensive body of literature in sensor network analysis, this work sought to apply several novel and traditional methods in sensor network analysis for the purposes of efficiently interrogating social media data streams from raw data. We carefully revisit our definition of a social media signal from previous work both in terms of time-varying features within the data and the networked nature of the medium. Further, we detail our analysis of global patterns in Twitter over the months of November 2013more » and June 2014, detect and categorize events, and illustrate how these analyses can be used to inform graph-based models of Twitter, namely using a recent network influence model called PhySense: similar to PageRank but tuned to behavioral analysis by leveraging a sociologically inspired probabilistic model. We ultimately identify forms of information dissemination via analysis of time series and dynamic graph spectra and corroborate these findings through manual investigation of the data as a requisite step in modeling the diffusion process with PhySense. We hope to sufficiently characterize global behavior in a medium such as Twitter as a means of learning global model parameters one may use to predict or simulate behavior on a large scale. We have made our time series and dynamic graph analytical code available via a GitHub repository https://github.com/cpatdowling/salsa and our data are available upon request.« less

A qrr noncoding RNA deploys four different regulatory mechanisms to optimize quorum-sensing dynamics.

PubMed

Feng, Lihui; Rutherford, Steven T; Papenfort, Kai; Bagert, John D; van Kessel, Julia C; Tirrell, David A; Wingreen, Ned S; Bassler, Bonnie L

2015-01-15

Quorum sensing is a cell-cell communication process that bacteria use to transition between individual and social lifestyles. In vibrios, homologous small RNAs called the Qrr sRNAs function at the center of quorum-sensing pathways. The Qrr sRNAs regulate multiple mRNA targets including those encoding the quorum-sensing regulatory components luxR, luxO, luxM, and aphA. We show that a representative Qrr, Qrr3, uses four distinct mechanisms to control its particular targets: the Qrr3 sRNA represses luxR through catalytic degradation, represses luxM through coupled degradation, represses luxO through sequestration, and activates aphA by revealing the ribosome binding site while the sRNA itself is degraded. Qrr3 forms different base-pairing interactions with each mRNA target, and the particular pairing strategy determines which regulatory mechanism occurs. Combined mathematical modeling and experiments show that the specific Qrr regulatory mechanism employed governs the potency, dynamics, and competition of target mRNA regulation, which in turn, defines the overall quorum-sensing response. Copyright © 2015 Elsevier Inc. All rights reserved.

Enhanced Quality Factor Label-free Biosensing with Micro-Cantilevers Integrated into Microfluidic Systems.

PubMed

Kartanas, Tadas; Ostanin, Victor; Challa, Pavan Kumar; Daly, Ronan; Charmet, Jerome; Knowles, Tuomas P J

2017-11-21

Microelectromechanical systems (MEMS) have enabled the development of a new generation of sensor platforms. Acoustic sensor operation in liquid, the native environment of biomolecules, causes, however, significant degradation of sensing performance due to viscous drag and relies on the availability of capture molecules to bind analytes of interest to the sensor surface. Here, we describe a strategy to interface MEMS sensors with microfluidic platforms through an aerosol spray. Our sensing platform comprises a microfluidic spray nozzle and a microcantilever array operated in dynamic mode within a closed loop oscillator. A solution containing the analyte is sprayed uniformly through picoliter droplets onto the microcantilever surface; the micrometer-scale drops evaporate rapidly and leave the solutes behind, adding to the mass of the cantilever. This sensing scheme results in a 50-fold increase in the quality factor compared to operation in liquid, yet allows the analytes to be introduced into the sensing system from a solution phase. It achieves a 370 femtogram limit of detection, and we demonstrate quantitative label-free analysis of inorganic salts and model proteins. These results demonstrate that the standard resolution limits of cantilever sensing in dynamic mode can be overcome with the integration of spray microfluidics with MEMS.

Quo vadis, remote sensing. [use of satellite data for resource management

NASA Technical Reports Server (NTRS)

Billingsley, F. C.

1977-01-01

The use of satellite remote sensing data for resource management is discussed. The evaluation of the need for management data is reviewed, and some legislative programs which require the monitoring of environmental resources are summarized. Several characteristics of data used in the monitoring of dynamic processes are analyzed, and the implications of routine processing of extensive remote sensing data for the development of a new world view are considered.

3-D Numerical Simulations of Biofilm Dynamics with Quorum Sensing in a Flow Cell

DTIC Science & Technology

2014-01-01

resistant mutants [?]. Inspired by experimental findings, researchers have come up with some mathematical models to study biofilm formation and function...develop a full 3D mathematical model to study how quorum sensing regulates biofilm formation and development as well as the pros and cons of quorum...have given an overview of current advances in mathematical modeling of biofilms. Concerning coupling biofilm growth with quorum sensing features

Coherent pulse interrogation system for fiber Bragg grating sensing of strain and pressure in dynamic extremes of materials.

PubMed

Rodriguez, George; Jaime, Marcelo; Balakirev, Fedor; Mielke, Chuck H; Azad, Abul; Marshall, Bruce; La Lone, Brandon M; Henson, Bryan; Smilowitz, Laura

2015-06-01

A 100 MHz fiber Bragg grating (FBG) interrogation system is described and applied to strain and pressure sensing. The approach relies on coherent pulse illumination of the FBG sensor with a broadband short pulse from a femtosecond modelocked erbium fiber laser. After interrogation of the FBG sensor, a long multi-kilometer run of single mode fiber is used for chromatic dispersion to temporally stretch the spectral components of the reflected pulse from the FBG sensor. Dynamic strain or pressure induced spectral shifts in the FBG sensor are detected as a pulsed time domain waveform shift after encoding by the chromatic dispersive line. Signals are recorded using a single 35 GHz photodetector and a 50 G Samples per second, 25 GHz bandwidth, digitizing oscilloscope. Application of this approach to high-speed strain sensing in magnetic materials in pulsed magnetic fields to ~150 T is demonstrated. The FBG wavelength shifts are used to study magnetic field driven magnetostriction effects in LaCoO₃. A sub-microsecond temporal shift in the FBG sensor wavelength attached to the sample under first order phase change appears as a fractional length change (strain: ΔL/L<10^-4) in the material. A second application used FBG sensing of pressure dynamics to nearly 2 GPa in the thermal ignition of the high explosive PBX-9501 is also demonstrated. Both applications demonstrate the use of this FBG interrogation system in dynamical extreme conditions that would otherwise not be possible using traditional FBG interrogation approaches that are deemed too slow to resolve such events.

Proton-Fueled, Reversible DNA Hybridization Chain Assembly for pH Sensing and Imaging.

PubMed

Liu, Lan; Liu, Jin-Wen; Huang, Zhi-Mei; Wu, Han; Li, Na; Tang, Li-Juan; Jiang, Jian-Hui

2017-07-05

Design of DNA self-assembly with reversible responsiveness to external stimuli is of great interest for diverse applications. We for the first time develop a pH-responsive, fully reversible hybridization chain reaction (HCR) assembly that allows sensitive sensing and imaging of pH in living cells. Our design relies on the triplex forming sequences that form DNA triplex with toehold regions under acidic conditions and then induce a cascade of strand displacement and DNA assembly. The HCR assembly has shown dynamic responses in physiological pH ranges with excellent reversibility and demonstrated the potential for in vitro detection and live-cell imaging of pH. Moreover, this method affords HCR assemblies with highly localized fluorescence responses, offering advantages of improving sensitivity and better selectivity. The proton-fueled, reversible HCR assembly may provide a useful approach for pH-related cell biology study and disease diagnostics.

Cosmic Ray Neutron Sensing in Complex Systems

NASA Astrophysics Data System (ADS)

Piussi, L. M.; Tomelleri, E.; Tonon, G.; Bertoldi, G.; Mejia Aguilar, A.; Monsorno, R.; Zebisch, M.

2017-12-01

Soil moisture is a key variable in environmental monitoring and modelling: being located at the soil-atmosphere boundary, it is a driving force for water, energy and carbon fluxes. Nevertheless its importance, soil moisture observations lack of long time-series at high acquisition frequency in spatial meso-scale resolutions: traditional measurements deliver either long time series with high measurement frequency at spatial point scale or large scale and low frequency acquisitions. The Cosmic Ray Neutron Sensing (CRNS) technique fills this gap because it supplies information from a footprint of 240m of diameter and 15 to 83 cm of depth at a temporal resolution varying between 15 minutes and 24 hours. In addition, being a passive sensing technique, it is non-invasive. For these reasons, CRNS is gaining more and more attention from the scientific community. Nevertheless, the application of this technique in complex systems is still an open issue: where different Hydrogen pools are present and where their distributions vary appreciably with space and time, the traditional calibration method shows some limits. In order to obtain a better understanding of the data and to compare them with remote sensing products and spatially distributed traditional measurements (i.e. Wireless Sensors Network), the complexity of the surrounding environment has to be taken into account. In the current work we assessed the effects of spatial-temporal variability of soil moisture within the footprint, in a steep, heterogeneous mountain grassland area. Measurement were performed with a Cosmic Ray Neutron Probe (CRNP) and a mobile Wireless Sensors Network. We performed an in-deep sensitivity analysis of the effects of varying distributions of soil moisture on the calibration of the CRNP and our preliminary results show how the footprint shape varies depending on these dynamics. The results are then compared with remote sensing data (Sentinel 1 and 2). The current work is an assessment of different calibration procedures and their effect on the measurement outcome. We found that the response of the CRNP follows quite well the punctual measurement performed by a TDR installed on the site, but discrepancies could be explained by using the Wireless Sensors Network to perform a spatially weighted calibration and to introduce temporal dynamics.

Experimental Nonlinear Dynamics and Snap-Through of Post-Buckled Thin Laminated Composite Plates

NASA Astrophysics Data System (ADS)

Kim, Han-Gyu

Modern aerospace systems are increasingly being designed with composite panels and plates to achieve light weight and high specific strength and stiffness. For constrained panels, thermally-induced axial loading may cause buckling of the structure, which can lead to nonlinear and potentially chaotic behavior. When post-buckled composite plates experience snap-through, they are subjected to large-amplitude deformations and in-plane compressive loading. These phenomena pose a potential threat to the structural integrity of composite structures. In this work, the nonlinear dynamic behavior of post-buckled composite plates was investigated experimentally and computationally. For the experimental work, an electrodynamic shaker was used to apply harmonic loads and the dynamic response of plate specimens was measured using a single-point displacement-sensing laser, a double-point laser vibrometer (velocity-sensing), and a set of digital image correlation cameras. Both chaotic and periodic steady-state snap-through behaviors were investigated. The experimental data were used to characterize snap-through behaviors of the post-buckled specimens and their boundaries in the harmonic forcing parameter space. The nonlinear behavior of post-buckled plates was modeled using the classical laminated plate theory (CLPT) and the von Karman strain-displacement relations. The static equilibrium paths of the post-buckled plates were analyzed using an arc-length method with a branch-switching technique. For the dynamic analysis, the nonlinear equations of motion were derived based on CLPT and the nonlinear finite element model of the equations was constructed using the Hermite cubic interpolation functions for both conforming and nonconforming elements. The numerical analyses were conducted using the model and were compared with the experimental data.

Novel fine-scale aerial mapping approach quantifies grassland weed cover dynamics and response to management.

PubMed

Malmstrom, Carolyn M; Butterfield, H Scott; Planck, Laura; Long, Christopher W; Eviner, Valerie T

2017-01-01

Invasive weeds threaten the biodiversity and forage productivity of grasslands worldwide. However, management of these weeds is constrained by the practical difficulty of detecting small-scale infestations across large landscapes and by limits in understanding of landscape-scale invasion dynamics, including mechanisms that enable patches to expand, contract, or remain stable. While high-end hyperspectral remote sensing systems can effectively map vegetation cover, these systems are currently too costly and limited in availability for most land managers. We demonstrate application of a more accessible and cost-effective remote sensing approach, based on simple aerial imagery, for quantifying weed cover dynamics over time. In California annual grasslands, the target communities of interest include invasive weedy grasses (Aegilops triuncialis and Elymus caput-medusae) and desirable forage grass species (primarily Avena spp. and Bromus spp.). Detecting invasion of annual grasses into an annual-dominated community is particularly challenging, but we were able to consistently characterize these two communities based on their phenological differences in peak growth and senescence using maximum likelihood supervised classification of imagery acquired twice per year (in mid- and end-of season). This approach permitted us to map weed-dominated cover at a 1-m scale (correctly detecting 93% of weed patches across the landscape) and to evaluate weed cover change over time. We found that weed cover was more pervasive and persistent in management units that had no significant grazing for several years than in those that were grazed, whereas forage cover was more abundant and stable in the grazed units. This application demonstrates the power of this method for assessing fine-scale vegetation transitions across heterogeneous landscapes. It thus provides means for small-scale early detection of invasive species and for testing fundamental questions about landscape dynamics.

Novel fine-scale aerial mapping approach quantifies grassland weed cover dynamics and response to management

PubMed Central

Butterfield, H. Scott; Planck, Laura; Long, Christopher W.; Eviner, Valerie T.

2017-01-01

Invasive weeds threaten the biodiversity and forage productivity of grasslands worldwide. However, management of these weeds is constrained by the practical difficulty of detecting small-scale infestations across large landscapes and by limits in understanding of landscape-scale invasion dynamics, including mechanisms that enable patches to expand, contract, or remain stable. While high-end hyperspectral remote sensing systems can effectively map vegetation cover, these systems are currently too costly and limited in availability for most land managers. We demonstrate application of a more accessible and cost-effective remote sensing approach, based on simple aerial imagery, for quantifying weed cover dynamics over time. In California annual grasslands, the target communities of interest include invasive weedy grasses (Aegilops triuncialis and Elymus caput-medusae) and desirable forage grass species (primarily Avena spp. and Bromus spp.). Detecting invasion of annual grasses into an annual-dominated community is particularly challenging, but we were able to consistently characterize these two communities based on their phenological differences in peak growth and senescence using maximum likelihood supervised classification of imagery acquired twice per year (in mid- and end-of season). This approach permitted us to map weed-dominated cover at a 1-m scale (correctly detecting 93% of weed patches across the landscape) and to evaluate weed cover change over time. We found that weed cover was more pervasive and persistent in management units that had no significant grazing for several years than in those that were grazed, whereas forage cover was more abundant and stable in the grazed units. This application demonstrates the power of this method for assessing fine-scale vegetation transitions across heterogeneous landscapes. It thus provides means for small-scale early detection of invasive species and for testing fundamental questions about landscape dynamics. PMID:29016604

Live imaging using adaptive optics with fluorescent protein guide-stars

PubMed Central

Tao, Xiaodong; Crest, Justin; Kotadia, Shaila; Azucena, Oscar; Chen, Diana C.; Sullivan, William; Kubby, Joel

2012-01-01

Spatially and temporally dependent optical aberrations induced by the inhomogeneous refractive index of live samples limit the resolution of live dynamic imaging. We introduce an adaptive optical microscope with a direct wavefront sensing method using a Shack-Hartmann wavefront sensor and fluorescent protein guide-stars for live imaging. The results of imaging Drosophila embryos demonstrate its ability to correct aberrations and achieve near diffraction limited images of medial sections of large Drosophila embryos. GFP-polo labeled centrosomes can be observed clearly after correction but cannot be observed before correction. Four dimensional time lapse images are achieved with the correction of dynamic aberrations. These studies also demonstrate that the GFP-tagged centrosome proteins, Polo and Cnn, serve as excellent biological guide-stars for adaptive optics based microscopy. PMID:22772285

Impacts of Myanmar's Democratic Transition on its Land Cover Dynamics.

NASA Astrophysics Data System (ADS)

Biswas, S.

2016-12-01

Recently Myanmar transitioned from a closed economy, military government to market based economy and democracy. The impacts of the political and economic transition on its land cover can be described by characterizing the land cover dynamics during the transition period. Preliminary stratified sampling of forest conversions revealed that most changes from forest to non-forest are due to establishment of rubber plantations. Agricultural concessions are granted by the government to develop the agriculture sector and rubber is the most common plantation crop in Southern Myanmar. This study establishes a method to map and quantify the extent and age of rubber plantations in Thaton district of Myanmar using satellite remote sensing, GIS and ground data. The resultant rubber maps can be used to inform policy on land use planning, agriculture, forest and sustainable development.

Precise tracking of remote sensing satellites with the Global Positioning System

NASA Technical Reports Server (NTRS)

Yunck, Thomas P.; Wu, Sien-Chong; Wu, Jiun-Tsong; Thornton, Catherine L.

1990-01-01

The Global Positioning System (GPS) can be applied in a number of ways to track remote sensing satellites at altitudes below 3000 km with accuracies of better than 10 cm. All techniques use a precise global network of GPS ground receivers operating in concert with a receiver aboard the user satellite, and all estimate the user orbit, GPS orbits, and selected ground locations simultaneously. The GPS orbit solutions are always dynamic, relying on the laws of motion, while the user orbit solution can range from purely dynamic to purely kinematic (geometric). Two variations show considerable promise. The first one features an optimal synthesis of dynamics and kinematics in the user solution, while the second introduces a novel gravity model adjustment technique to exploit data from repeat ground tracks. These techniques, to be demonstrated on the Topex/Poseidon mission in 1992, will offer subdecimeter tracking accuracy for dynamically unpredictable satellites down to the lowest orbital altitudes.

Dynamic tire pressure sensor for measuring ground vibration.

PubMed

Wang, Qi; McDaniel, James Gregory; Wang, Ming L

2012-11-07

This work presents a convenient and non-contact acoustic sensing approach for measuring ground vibration. This approach, which uses an instantaneous dynamic tire pressure sensor (DTPS), possesses the capability to replace the accelerometer or directional microphone currently being used for inspecting pavement conditions. By measuring dynamic pressure changes inside the tire, ground vibration can be amplified and isolated from environmental noise. In this work, verifications of the DTPS concept of sensing inside the tire have been carried out. In addition, comparisons between a DTPS, ground-mounted accelerometer, and directional microphone are made. A data analysis algorithm has been developed and optimized to reconstruct ground acceleration from DTPS data. Numerical and experimental studies of this DTPS reveal a strong potential for measuring ground vibration caused by a moving vehicle. A calibration of transfer function between dynamic tire pressure change and ground acceleration may be needed for different tire system or for more accurate application.

Non-contact FBG sensing based steam turbine rotor dynamic balance vibration detection system

NASA Astrophysics Data System (ADS)

Li, Tianliang; Tan, Yuegang; Cai, Lin

2015-10-01

This paper has proposed a non-contact vibration sensor based on fiber Bragg grating sensing, and applied to detect vibration of steam turbine rotor dynamic balance experimental platform. The principle of the sensor has been introduced, as well as the experimental analysis; performance of non-contact FBG vibration sensor has been analyzed in the experiment; in addition, turbine rotor dynamic vibration detection system based on eddy current displacement sensor and non-contact FBG vibration sensor have built; finally, compared with results of signals under analysis of the time domain and frequency domain. The analysis of experimental data contrast shows that: the vibration signal analysis of non-contact FBG vibration sensor is basically the same as the result of eddy current displacement sensor; it verified that the sensor can be used for non-contact measurement of steam turbine rotor dynamic balance vibration.

Dynamical predictive power of the generalized Gibbs ensemble revealed in a second quench.

PubMed

Zhang, J M; Cui, F C; Hu, Jiangping

2012-04-01

We show that a quenched and relaxed completely integrable system is hardly distinguishable from the corresponding generalized Gibbs ensemble in a dynamical sense. To be specific, the response of the quenched and relaxed system to a second quench can be accurately reproduced by using the generalized Gibbs ensemble as a substitute. Remarkably, as demonstrated with the transverse Ising model and the hard-core bosons in one dimension, not only the steady values but even the transient, relaxation dynamics of the physical variables can be accurately reproduced by using the generalized Gibbs ensemble as a pseudoinitial state. This result is an important complement to the previously established result that a quenched and relaxed system is hardly distinguishable from the generalized Gibbs ensemble in a static sense. The relevance of the generalized Gibbs ensemble in the nonequilibrium dynamics of completely integrable systems is then greatly strengthened.

Dynamic Tire Pressure Sensor for Measuring Ground Vibration

PubMed Central

Wang, Qi; McDaniel, James Gregory; Wang, Ming L.

2012-01-01

This work presents a convenient and non-contact acoustic sensing approach for measuring ground vibration. This approach, which uses an instantaneous dynamic tire pressure sensor (DTPS), possesses the capability to replace the accelerometer or directional microphone currently being used for inspecting pavement conditions. By measuring dynamic pressure changes inside the tire, ground vibration can be amplified and isolated from environmental noise. In this work, verifications of the DTPS concept of sensing inside the tire have been carried out. In addition, comparisons between a DTPS, ground-mounted accelerometer, and directional microphone are made. A data analysis algorithm has been developed and optimized to reconstruct ground acceleration from DTPS data. Numerical and experimental studies of this DTPS reveal a strong potential for measuring ground vibration caused by a moving vehicle. A calibration of transfer function between dynamic tire pressure change and ground acceleration may be needed for different tire system or for more accurate application. PMID:23202206

Mapping and spatial-temporal modeling of Bromus tectorum invasion in central Utah

NASA Astrophysics Data System (ADS)

Jin, Zhenyu

Cheatgrass, or Downy Brome, is an exotic winter annual weed native to the Mediterranean region. Since its introduction to the U.S., it has become a significant weed and aggressive invader of sagebrush, pinion-juniper, and other shrub communities, where it can completely out-compete native grasses and shrubs. In this research, remotely sensed data combined with field collected data are used to investigate the distribution of the cheatgrass in Central Utah, to characterize the trend of the NDVI time-series of cheatgrass, and to construct a spatially explicit population-based model to simulate the spatial-temporal dynamics of the cheatgrass. This research proposes a method for mapping the canopy closure of invasive species using remotely sensed data acquired at different dates. Different invasive species have their own distinguished phenologies and the satellite images in different dates could be used to capture the phenology. The results of cheatgrass abundance prediction have a good fit with the field data for both linear regression and regression tree models, although the regression tree model has better performance than the linear regression model. To characterize the trend of NDVI time-series of cheatgrass, a novel smoothing algorithm named RMMEH is presented in this research to overcome some drawbacks of many other algorithms. By comparing the performance of RMMEH in smoothing a 16-day composite of the MODIS NDVI time-series with that of two other methods, which are the 4253EH, twice and the MVI, we have found that RMMEH not only keeps the original valid NDVI points, but also effectively removes the spurious spikes. The reconstructed NDVI time-series of different land covers are of higher quality and have smoother temporal trend. To simulate the spatial-temporal dynamics of cheatgrass, a spatially explicit population-based model is built applying remotely sensed data. The comparison between the model output and the ground truth of cheatgrass closure demonstrates that the model could successfully simulate the spatial-temporal dynamics of cheatgrass in a simple cheatgrass-dominant environment. The simulation of the functional response of different prescribed fire rates also shows that this model is helpful to answer management questions like, "What are the effects of prescribed fire to invasive species?" It demonstrates that a medium fire rate of 10% can successfully prevent cheatgrass invasion.

Non-invasive studies of multiphase flow in process equipment. Positron emission particle tracking technique

NASA Astrophysics Data System (ADS)

Balakin, B. V.; Adamsen, T. C. H.; Chang, Y.-F.; Kosinski, P.; Hoffmann, A. C.

2017-01-01

Positron emission particle tracking (PEPT) is a novel experimental technique for non-invasive inspection of industrial fluid/particle flows. The method is based on the dynamic positioning of a positron-emitting, flowing object (particle) performed through the sensing of annihilation events and subsequent numerical treatment to determine the particle position. The present paper shows an integrated overview of PEPT studies which were carried out using a new PET scanner in the Bergen University Hospital to study multiphase flows in different geometric configurations.

Moving Beyond 2% Uncertainty: A New Framework for Quantifying Lidar Uncertainty

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

Newman, Jennifer F.; Clifton, Andrew

2017-03-08

Remote sensing of wind using lidar is revolutionizing wind energy. However, current generations of wind lidar are ascribed a climatic value of uncertainty, which is based on a poor description of lidar sensitivity to external conditions. In this presentation, we show how it is important to consider the complete lidar measurement process to define the measurement uncertainty, which in turn offers the ability to define a much more granular and dynamic measurement uncertainty. This approach is a progression from the 'white box' lidar uncertainty method.

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

PubMed

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

2015-07-01

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

Radar-based dynamic testing of the cable-suspended bridge crossing the Ebro River at Amposta, Spain

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

Gentile, Carmelo; Luzi, Guido

2014-05-27

Microwave remote sensing is the most recent experimental methodology suitable to the non-contact measurement of deflections on large structures, in static or dynamic conditions. After a brief description of the radar measurement system, the paper addresses the application of microwave remote sensing to ambient vibration testing of a cable-suspended bridge. The investigated bridge crosses the Ebro River at Amposta, Spain and consists of two steel stiffening trusses and a series of equally spaced steel floor beams; the main span is supported by inclined stay cables and two series of 8 suspension cables. The dynamic tests were performed in operational conditions,more » with the sensor being placed in two different positions so that the response of both the steel deck and the arrays of suspension elements was measured. The experimental investigation confirms the simplicity of use of the radar and the accuracy of the results provided by the microwave remote sensing as well as the issues often met in the clear localization of measurement points.« less

Whole-Body Human Inverse Dynamics with Distributed Micro-Accelerometers, Gyros and Force Sensing †

PubMed Central

Latella, Claudia; Kuppuswamy, Naveen; Romano, Francesco; Traversaro, Silvio; Nori, Francesco

2016-01-01

Human motion tracking is a powerful tool used in a large range of applications that require human movement analysis. Although it is a well-established technique, its main limitation is the lack of estimation of real-time kinetics information such as forces and torques during the motion capture. In this paper, we present a novel approach for a human soft wearable force tracking for the simultaneous estimation of whole-body forces along with the motion. The early stage of our framework encompasses traditional passive marker based methods, inertial and contact force sensor modalities and harnesses a probabilistic computational technique for estimating dynamic quantities, originally proposed in the domain of humanoid robot control. We present experimental analysis on subjects performing a two degrees-of-freedom bowing task, and we estimate the motion and kinetics quantities. The results demonstrate the validity of the proposed method. We discuss the possible use of this technique in the design of a novel soft wearable force tracking device and its potential applications. PMID:27213394

Integration of Libration Point Orbit Dynamics into a Universal 3-D Autonomous Formation Flying Algorithm

NASA Technical Reports Server (NTRS)

Folta, David; Bauer, Frank H. (Technical Monitor)

2001-01-01

The autonomous formation flying control algorithm developed by the Goddard Space Flight Center (GSFC) for the New Millennium Program (NMP) Earth Observing-1 (EO-1) mission is investigated for applicability to libration point orbit formations. In the EO-1 formation-flying algorithm, control is accomplished via linearization about a reference transfer orbit with a state transition matrix (STM) computed from state inputs. The effect of libration point orbit dynamics on this algorithm architecture is explored via computation of STMs using the flight proven code, a monodromy matrix developed from a N-body model of a libration orbit, and a standard STM developed from the gravitational and coriolis effects as measured at the libration point. A comparison of formation flying Delta-Vs calculated from these methods is made to a standard linear quadratic regulator (LQR) method. The universal 3-D approach is optimal in the sense that it can be accommodated as an open-loop or closed-loop control using only state information.

Parallel implementation of geometrical shock dynamics for two dimensional converging shock waves

NASA Astrophysics Data System (ADS)

Qiu, Shi; Liu, Kuang; Eliasson, Veronica

2016-10-01

Geometrical shock dynamics (GSD) theory is an appealing method to predict the shock motion in the sense that it is more computationally efficient than solving the traditional Euler equations, especially for converging shock waves. However, to solve and optimize large scale configurations, the main bottleneck is the computational cost. Among the existing numerical GSD schemes, there is only one that has been implemented on parallel computers, with the purpose to analyze detonation waves. To extend the computational advantage of the GSD theory to more general applications such as converging shock waves, a numerical implementation using a spatial decomposition method has been coupled with a front tracking approach on parallel computers. In addition, an efficient tridiagonal system solver for massively parallel computers has been applied to resolve the most expensive function in this implementation, resulting in an efficiency of 0.93 while using 32 HPCC cores. Moreover, symmetric boundary conditions have been developed to further reduce the computational cost, achieving a speedup of 19.26 for a 12-sided polygonal converging shock.

Beyond Epistemological Deficits: Dynamic Explanations of Engineering Students' Difficulties with Mathematical Sense-Making

ERIC Educational Resources Information Center

Gupta, Ayush; Elby, Andrew

2011-01-01

Researchers have argued against deficit-based explanations of students' difficulties with mathematical sense-making, pointing instead to factors such as epistemology. Students' beliefs about knowledge and learning can hinder the activation and integration of productive knowledge they have. Such explanations, however, risk falling into a…

Identifying drought adaptive traits in upland cotton using a proximal sensing cart for high-throughput phenotyping

USDA-ARS?s Scientific Manuscript database

Field-based high-throughput phenotyping is an emerging approach to characterize difficult, time-sensitive plant traits in relevant growing conditions. Proximal sensing carts have been developed as an alternative platform to more costly high-clearance tractors for phenotyping dynamic traits in the fi...

Chlorophyll fluorescence better captures seasonal and interannual gross primary productivity dynamics across dryland ecosystems of southwestern North America

USDA-ARS?s Scientific Manuscript database

Satellite remote sensing provides unmatched spatiotemporal information on vegetation gross primary productivity (GPP). Yet, understanding of the relationship between GPP and remote sensing observations and how it changes as a function of factors such as scale, biophysical constraint, and vegetation ...

Hair-based sensors for micro-autonomous systems

NASA Astrophysics Data System (ADS)

Sadeghi, Mahdi M.; Peterson, Rebecca L.; Najafi, Khalil

2012-06-01

We seek to harness microelectromechanical systems (MEMS) technologies to build biomimetic devices for low-power, high-performance, robust sensors and actuators on micro-autonomous robot platforms. Hair is used abundantly in nature for a variety of functions including balance and inertial sensing, flow sensing and aerodynamic (air foil) control, tactile and touch sensing, insulation and temperature control, particle filtering, and gas/chemical sensing. Biological hairs, which are typically characterized by large surface/volume ratios and mechanical amplification of movement, can be distributed in large numbers over large areas providing unprecedented sensitivity, redundancy, and stability (robustness). Local neural transduction allows for space- and power-efficient signal processing. Moreover by varying the hair structure and transduction mechanism, the basic hair form can be used for a wide diversity of functions. In this paper, by exploiting a novel wafer-level, bubble-free liquid encapsulation technology, we make arrays of micro-hydraulic cells capable of electrostatic actuation and hydraulic amplification, which enables high force/high deflection actuation and extremely sensitive detection (sensing) at low power. By attachment of cilia (hair) to the micro-hydraulic cell, air flow sensors with excellent sensitivity (< few cm/s) and dynamic range (> 10 m/s) have been built. A second-generation design has significantly reduced the sensor response time while maintaining sensitivity of about 2 cm/s and dynamic range of more than 15 m/s. These sensors can be used for dynamic flight control of flying robots or for situational awareness in surveillance applications. The core biomimetic technologies developed are applicable to a broad range of sensors and actuators.

Mixed-phase altocumulus clouds over Leipzig: Remote sensing measurements and spectral cloud microphysics simulations

NASA Astrophysics Data System (ADS)

Simmel, Martin; Bühl, Johannes; Ansmann, Albert; Tegen, Ina

2015-04-01

The present work combines remote sensing observations and detailed microphysics cloud modeling to investigate two altocumulus cloud cases observed over Leipzig, Germany. A suite of remote sensing instruments was able to detect primary ice at rather warm temperatures of -6°C. For comparison, a second mixed phase case at about -25°C is introduced. To further look into the details of cloud microphysical processes a simple dynamics model of the Asai-Kasahara type is combined with detailed spectral microphysics forming the model system AK-SPECS. Temperature and humidity profiles are taken either from observation (radiosonde) or GDAS reanalysis. Vertical velocities are prescribed to force the dynamics as well as main cloud features to be close to the observations. Subsequently, sensitivity studies with respect to dynamical as well as ice microphysical parameters are carried out with the aim to quantify the most important sensitivities for the cases investigated. For the cases selected, the liquid phase is mainly determined by the model dynamics (location and strength of vertical velocity) whereas the ice phase is much more sensitive to the microphysical parameters (ice nuclei (IN) number, ice particle shape). The choice of ice particle shape may induce large uncertainties which are in the same order as those for the temperature-dependent IN number distribution.

Combining Remote Temperature Sensing with in-Situ Sensing to Track Marine/Freshwater Mixing Dynamics

PubMed Central

McCaul, Margaret; Barland, Jack; Cleary, John; Cahalane, Conor; McCarthy, Tim; Diamond, Dermot

2016-01-01

The ability to track the dynamics of processes in natural water bodies on a global scale, and at a resolution that enables highly localised behaviour to be visualized, is an ideal scenario for understanding how local events can influence the global environment. While advances in in-situ chem/bio-sensing continue to be reported, costs and reliability issues still inhibit the implementation of large-scale deployments. In contrast, physical parameters like surface temperature can be tracked on a global scale using satellite remote sensing, and locally at high resolution via flyovers and drones using multi-spectral imaging. In this study, we show how a much more complete picture of submarine and intertidal groundwater discharge patterns in Kinvara Bay, Galway can be achieved using a fusion of data collected from the Earth Observation satellite (Landsat 8), small aircraft and in-situ sensors. Over the course of the four-day field campaign, over 65,000 in-situ temperatures, salinity and nutrient measurements were collected in parallel with high-resolution thermal imaging from aircraft flyovers. The processed in-situ data show highly correlated patterns between temperature and salinity at the southern end of the bay where freshwater springs can be identified at low tide. Salinity values range from 1 to 2 ppt at the southern end of the bay to 30 ppt at the mouth of the bay, indicating the presence of a freshwater wedge. The data clearly show that temperature differences can be used to track the dynamics of freshwater and seawater mixing in the inner bay region. This outcome suggests that combining the tremendous spatial density and wide geographical reach of remote temperature sensing (using drones, flyovers and satellites) with ground-truthing via appropriately located in-situ sensors (temperature, salinity, chemical, and biological) can produce a much more complete and accurate picture of the water dynamics than each modality used in isolation. PMID:27589770

Combining Remote Temperature Sensing with in-Situ Sensing to Track Marine/Freshwater Mixing Dynamics.

PubMed

McCaul, Margaret; Barland, Jack; Cleary, John; Cahalane, Conor; McCarthy, Tim; Diamond, Dermot

2016-08-31

The ability to track the dynamics of processes in natural water bodies on a global scale, and at a resolution that enables highly localised behaviour to be visualized, is an ideal scenario for understanding how local events can influence the global environment. While advances in in-situ chem/bio-sensing continue to be reported, costs and reliability issues still inhibit the implementation of large-scale deployments. In contrast, physical parameters like surface temperature can be tracked on a global scale using satellite remote sensing, and locally at high resolution via flyovers and drones using multi-spectral imaging. In this study, we show how a much more complete picture of submarine and intertidal groundwater discharge patterns in Kinvara Bay, Galway can be achieved using a fusion of data collected from the Earth Observation satellite (Landsat 8), small aircraft and in-situ sensors. Over the course of the four-day field campaign, over 65,000 in-situ temperatures, salinity and nutrient measurements were collected in parallel with high-resolution thermal imaging from aircraft flyovers. The processed in-situ data show highly correlated patterns between temperature and salinity at the southern end of the bay where freshwater springs can be identified at low tide. Salinity values range from 1 to 2 ppt at the southern end of the bay to 30 ppt at the mouth of the bay, indicating the presence of a freshwater wedge. The data clearly show that temperature differences can be used to track the dynamics of freshwater and seawater mixing in the inner bay region. This outcome suggests that combining the tremendous spatial density and wide geographical reach of remote temperature sensing (using drones, flyovers and satellites) with ground-truthing via appropriately located in-situ sensors (temperature, salinity, chemical, and biological) can produce a much more complete and accurate picture of the water dynamics than each modality used in isolation.

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.

Creating fast flow channels in paper fluidic devices to control timing of sequential reactions.

PubMed

Jahanshahi-Anbuhi, Sana; Chavan, Puneet; Sicard, Clémence; Leung, Vincent; Hossain, S M Zakir; Pelton, Robert; Brennan, John D; Filipe, Carlos D M

2012-12-07

This paper reports the development of a method to control the flow rate of fluids within paper-based microfluidic analytical devices. We demonstrate that by simply sandwiching paper channels between two flexible films, it is possible to accelerate the flow of water through paper by over 10-fold. The dynamics of this process are such that the height of the liquid is dependent on time to the power of 1/3. This dependence was validated using three different flexible films (with markedly different contact angles) and three different fluids (water and two silicon oils with different viscosities). These covered channels provide a low-cost method for controlling the flow rate of fluid in paper channels, and can be added following printing of reagents to control fluid flow in selected fluidic channels. Using this method, we redesigned a previously published bidirectional lateral flow pesticide sensor to allow more rapid detection of pesticides while eliminating the need to run the assay in two stages. The sensor is fabricated with sol-gel entrapped reagents (indoxyl acetate in a substrate zone and acetylcholinesterase, AChE, in a sensing zone) present in an uncovered "slow" flow channel, with a second, covered "fast" channel used to transport pesticide samples to the sensing region through a simple paper-flap valve. In this manner, pesticides reach the sensing region first to allow preincubation, followed by delivery of the substrate to generate a colorimetric signal. This format results in a uni-directional device that detects the presence of pesticides two times faster than the original bidirectional sensors.

Cognitive software defined radar: waveform design for clutter and interference suppression

NASA Astrophysics Data System (ADS)

Kirk, Benjamin H.; Owen, Jonathan W.; Narayanan, Ram M.; Blunt, Shannon D.; Martone, Anthony F.; Sherbondy, Kelly D.

2017-05-01

Clutter and radio frequency interference (RFI) are prevalent issues in the field of radar and are specifically of interest to of cognitive radar. Here, methods for applying and testing the utility of cognitive radar for clutter and RFI mitigation are explored. Using the adaptable transmit capability, environmental database, and general "awareness" of a cognitive radar system (i.e. spectrum sensing, geographical location, etc.), a matched waveform is synthesized that improves the signal-to-clutter ratio (SCR), assuming at least an estimate of the target response and the environmental clutter response are known a prior i. RFI may also be mitigated by sensing the RF spectrum and adapting the transmit center frequency and bandwidth using methods that optimize bandwidth and signal-to-interference plus noise ratio (SINR) (i.e. the spectrum sensing, multi-objective (SS-MO) algorithm). The improvement is shown by a decrease in the noise floor. The above methods' effectiveness are examined via a test-bed developed around a software defined radio (SDR). Testing and the general use of commercial off the shelf (COTS) devices are desirable for their cost effectiveness, general ease of use, as well as technical and community support, but these devices provide design challenges in order to be effective. The universal software radio peripheral (USRP) X310 SDR is a relatively cheap and portable device that has all the system components of a basic cognitive radar. Design challenges of the SDR include phase coherency between channels, bandwidth limitations, dynamic range, and speed of computation and data communication / recording.

Dynamic Data-Driven Reduced-Order Models of Macroscale Quantities for the Prediction of Equilibrium System State for Multiphase Porous Medium Systems

NASA Astrophysics Data System (ADS)

Talbot, C.; McClure, J. E.; Armstrong, R. T.; Mostaghimi, P.; Hu, Y.; Miller, C. T.

2017-12-01

Microscale simulation of multiphase flow in realistic, highly-resolved porous medium systems of a sufficient size to support macroscale evaluation is computationally demanding. Such approaches can, however, reveal the dynamic, steady, and equilibrium states of a system. We evaluate methods to utilize dynamic data to reduce the cost associated with modeling a steady or equilibrium state. We construct data-driven models using extensions to dynamic mode decomposition (DMD) and its connections to Koopman Operator Theory. DMD and its variants comprise a class of equation-free methods for dimensionality reduction of time-dependent nonlinear dynamical systems. DMD furnishes an explicit reduced representation of system states in terms of spatiotemporally varying modes with time-dependent oscillation frequencies and amplitudes. We use DMD to predict the steady and equilibrium macroscale state of a realistic two-fluid porous medium system imaged using micro-computed tomography (µCT) and simulated using the lattice Boltzmann method (LBM). We apply Koopman DMD to direct numerical simulation data resulting from simulations of multiphase fluid flow through a 1440x1440x4320 section of a full 1600x1600x5280 realization of imaged sandstone. We determine a representative set of system observables via dimensionality reduction techniques including linear and kernel principal component analysis. We demonstrate how this subset of macroscale quantities furnishes a representation of the time-evolution of the system in terms of dynamic modes, and discuss the selection of a subset of DMD modes yielding the optimal reduced model, as well as the time-dependence of the error in the predicted equilibrium value of each macroscale quantity. Finally, we describe how the above procedure, modified to incorporate methods from compressed sensing and random projection techniques, may be used in an online fashion to facilitate adaptive time-stepping and parsimonious storage of system states over time.

Advances in Remote Sensing for Vegetation Dynamics and Agricultural Management

NASA Technical Reports Server (NTRS)

Tucker, Compton; Puma, Michael

2015-01-01

Spaceborne remote sensing has led to great advances in the global monitoring of vegetation. For example, the NASA Global Inventory Modeling and Mapping Studies (GIMMS) group has developed widely used datasets from the Advanced Very High Resolution Radiometer (AVHRR) sensors as well as the Moderate Resolution Imaging Spectroradiometer (MODIS) map imagery and normalized difference vegetation index datasets. These data are valuable for analyzing vegetation trends and variability at the regional and global levels. Numerous studies have investigated such trends and variability for both natural vegetation (e.g., re-greening of the Sahel, shifts in the Eurasian boreal forest, Amazonian drought sensitivity) and crops (e.g., impacts of extremes on agricultural production). Here, a critical overview is presented on recent developments and opportunities in the use of remote sensing for monitoring vegetation and crop dynamics.

Force Sensing Applications of DNA Origami Nanodevices

NASA Astrophysics Data System (ADS)

Hudoba, Michael William

Mechanical forces in biological systems vary in both length and magnitude by orders of magnitude making them difficult to probe and characterize with existing experimental methodologies. From molecules to cells, forces can act across length scales of nanometers to microns at magnitudes ranging from picoNewtons to nanoNewtons. Although single-molecule techniques such as optical traps, magnetic tweezers, and atomic force microscopy have improved the resolution and sensitivity of such measurements, inherent drawbacks exist in their capabilities due to the nature of the tools themselves. Specifically, these techniques have limitations in their ability to measure forces in realistic cellular environments and are not amenable to in vivo applications or measurements in mimicked physiological environments. In this thesis, we present a method to develop DNA force-sensing nanodevices with sub-picoNewton resolution capable of measuring forces in realistic cellular environments, with future applications in vivo. We use a design technique known as DNA origami to assemble devices with nanoscale geometric precision through molecular self-assembly via Watson-Crick base pairing. The devices have multiple conformational states, monitored by observing a Forster Resonance Energy Transfer signal that can change under the application of force. We expanded this study by demonstrating the design of responsive structural dynamics in DNA-based nanodevices. While prior studies have relied on external inputs to drive relatively slow dynamics in DNA nanostructures, here we developed DNA nanodevices with thermally driven dynamic function. The device was designed with an ensemble of conformations, and we establish methods to tune the equilibrium distribution of conformations and the rate of switching between states. We also show this nanodynamic behavior is responsive to physical interactions with the environment by measuring molecular crowding forces in the sub-picoNewton range, which are known to play a critical role in regulating molecular interactions and processes. Broadly, this work establishes a foundation for nanodevices with thermally driven dynamics that enable new measurement and control functions. We also examine the effect that forces have on the mechanical properties of DNA origami devices by developing a method to automate mesh generation for Finite Element Analysis. With this approach we are able to determine how defects that arise during assembly affect mechanical strain within structures during force application that can ultimately lead to device failure.

Sensing of molecules using quantum dynamics

DOE PAGES

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

2015-04-24

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

Integrated remote sensing imagery and two-dimensional hydraulic modeling approach for impact evaluation of flood on crop yields

NASA Astrophysics Data System (ADS)

Chen, Huili; Liang, Zhongyao; Liu, Yong; Liang, Qiuhua; Xie, Shuguang

2017-10-01

The projected frequent occurrences of extreme flood events will cause significant losses to crops and will threaten food security. To reduce the potential risk and provide support for agricultural flood management, prevention, and mitigation, it is important to account for flood damage to crop production and to understand the relationship between flood characteristics and crop losses. A quantitative and effective evaluation tool is therefore essential to explore what and how flood characteristics will affect the associated crop loss, based on accurately understanding the spatiotemporal dynamics of flood evolution and crop growth. Current evaluation methods are generally integrally or qualitatively based on statistic data or ex-post survey with less diagnosis into the process and dynamics of historical flood events. Therefore, a quantitative and spatial evaluation framework is presented in this study that integrates remote sensing imagery and hydraulic model simulation to facilitate the identification of historical flood characteristics that influence crop losses. Remote sensing imagery can capture the spatial variation of crop yields and yield losses from floods on a grid scale over large areas; however, it is incapable of providing spatial information regarding flood progress. Two-dimensional hydraulic model can simulate the dynamics of surface runoff and accomplish spatial and temporal quantification of flood characteristics on a grid scale over watersheds, i.e., flow velocity and flood duration. The methodological framework developed herein includes the following: (a) Vegetation indices for the critical period of crop growth from mid-high temporal and spatial remote sensing imagery in association with agricultural statistics data were used to develop empirical models to monitor the crop yield and evaluate yield losses from flood; (b) The two-dimensional hydraulic model coupled with the SCS-CN hydrologic model was employed to simulate the flood evolution process, with the SCS-CN model as a rainfall-runoff generator and the two-dimensional hydraulic model implementing the routing scheme for surface runoff; and (c) The spatial combination between crop yield losses and flood dynamics on a grid scale can be used to investigate the relationship between the intensity of flood characteristics and associated loss extent. The modeling framework was applied for a 50-year return period flood that occurred in Jilin province, Northeast China, which caused large agricultural losses in August 2013. The modeling results indicated that (a) the flow velocity was the most influential factor that caused spring corn, rice and soybean yield losses from extreme storm event in the mountainous regions; (b) the power function archived the best results that fit the velocity-loss relationship for mountainous areas; and (c) integrated remote sensing imagery and two-dimensional hydraulic modeling approach are helpful for evaluating the influence of historical flood event on crop production and investigating the relationship between flood characteristics and crop yield losses.

Wetland fire remote sensing research--The Greater Everglades example

USGS Publications Warehouse

Jones, John W.

2012-01-01

Fire is a major factor in the Everglades ecosystem. For thousands of years, lightning-strike fires from summer thunderstorms have helped create and maintain a dynamic landscape suited both to withstand fire and recover quickly in the wake of frequent fires. Today, managers in the Everglades National Park are implementing controlled burns to promote healthy, sustainable vegetation patterns and ecosystem functions. The U.S. Geological Survey (USGS) is using remote sensing to improve fire-management databases in the Everglades, gain insights into post-fire land-cover dynamics, and develop spatially and temporally explicit fire-scar data for habitat and hydrologic modeling.

Vestibular ontogeny: Measuring the influence of the dynamic environment

NASA Technical Reports Server (NTRS)

Jones, Timothy A.; Devries, Sherri M.; Dubois, Linda M.; Nelson, Rick C.

1993-01-01

In comparison to other special senses, we are only meagerly informed about the development of vestibular function and the mechanisms that may operate to control or influence the course of vestibular ontogeny. Perhaps one contributing factor to this disparity is the difficulty of evaluating vestibular sense organs directly and noninvasively. The present report describes a recently developed direct noninvasive vestibular function test that can be used to address many basic questions about the developing vestibular system. More particularly, the test can be used to examine the effects of the dynamic environment (e.g. gravitational field and vibration) on vestibular ontogeny.

Interferometric fibre-optic curvature sensing for structural, directional vibration measurements

NASA Astrophysics Data System (ADS)

Kissinger, Thomas; Chehura, Edmon; James, Stephen W.; Tatam, Ralph P.

2017-06-01

Dynamic fibre-optic curvature sensing using fibre segment interferometry is demonstrated using a cost-effective rangeresolved interferometry interrogation system. Differential strain measurements from four fibre strings, each containing four fibre segments of gauge length 20 cm, allow the inference of lateral vibrations as well as the direction of the vibration of a cantilever test object. Dynamic tip displacement resolutions in the micrometre range over a 21 kHz interferometric bandwidth demonstrate the suitability of this approach for highly sensitive fibre-optic directional vibration measurements, complementing existing laser vibrometry techniques by removing the need for side access to the structure under test.

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.