Tracking and Classification of In-Air Hand Gesture Based on Thermal Guided Joint Filter

PubMed Central

Kim, Seongwan; Ban, Yuseok; Lee, Sangyoun

2017-01-01

The research on hand gestures has attracted many image processing-related studies, as it intuitively conveys the intention of a human as it pertains to motional meaning. Various sensors have been used to exploit the advantages of different modalities for the extraction of important information conveyed by the hand gesture of a user. Although many works have focused on learning the benefits of thermal information from thermal cameras, most have focused on face recognition or human body detection, rather than hand gesture recognition. Additionally, the majority of the works that take advantage of multiple modalities (e.g., the combination of a thermal sensor and a visual sensor), usually adopting simple fusion approaches between the two modalities. As both thermal sensors and visual sensors have their own shortcomings and strengths, we propose a novel joint filter-based hand gesture recognition method to simultaneously exploit the strengths and compensate the shortcomings of each. Our study is motivated by the investigation of the mutual supplementation between thermal and visual information in low feature level for the consistent representation of a hand in the presence of varying lighting conditions. Accordingly, our proposed method leverages the thermal sensor’s stability against luminance and the visual sensors textural detail, while complementing the low resolution and halo effect of thermal sensors and the weakness against illumination of visual sensors. A conventional region tracking method and a deep convolutional neural network have been leveraged to track the trajectory of a hand gesture and to recognize the hand gesture, respectively. Our experimental results show stability in recognizing a hand gesture against varying lighting conditions based on the contribution of the joint kernels of spatial adjacency and thermal range similarity. PMID:28106716

Markov logic network based complex event detection under uncertainty

NASA Astrophysics Data System (ADS)

Lu, Jingyang; Jia, Bin; Chen, Genshe; Chen, Hua-mei; Sullivan, Nichole; Pham, Khanh; Blasch, Erik

2018-05-01

In a cognitive reasoning system, the four-stage Observe-Orient-Decision-Act (OODA) reasoning loop is of interest. The OODA loop is essential for the situational awareness especially in heterogeneous data fusion. Cognitive reasoning for making decisions can take advantage of different formats of information such as symbolic observations, various real-world sensor readings, or the relationship between intelligent modalities. Markov Logic Network (MLN) provides mathematically sound technique in presenting and fusing data at multiple levels of abstraction, and across multiple intelligent sensors to conduct complex decision-making tasks. In this paper, a scenario about vehicle interaction is investigated, in which uncertainty is taken into consideration as no systematic approaches can perfectly characterize the complex event scenario. MLNs are applied to the terrestrial domain where the dynamic features and relationships among vehicles are captured through multiple sensors and information sources regarding the data uncertainty.

Scalable sensor management for automated fusion and tactical reconnaissance

NASA Astrophysics Data System (ADS)

Walls, Thomas J.; Wilson, Michael L.; Partridge, Darin C.; Haws, Jonathan R.; Jensen, Mark D.; Johnson, Troy R.; Petersen, Brad D.; Sullivan, Stephanie W.

2013-05-01

The capabilities of tactical intelligence, surveillance, and reconnaissance (ISR) payloads are expanding from single sensor imagers to integrated systems-of-systems architectures. Increasingly, these systems-of-systems include multiple sensing modalities that can act as force multipliers for the intelligence analyst. Currently, the separate sensing modalities operate largely independent of one another, providing a selection of operating modes but not an integrated intelligence product. We describe here a Sensor Management System (SMS) designed to provide a small, compact processing unit capable of managing multiple collaborative sensor systems on-board an aircraft. Its purpose is to increase sensor cooperation and collaboration to achieve intelligent data collection and exploitation. The SMS architecture is designed to be largely sensor and data agnostic and provide flexible networked access for both data providers and data consumers. It supports pre-planned and ad-hoc missions, with provisions for on-demand tasking and updates from users connected via data links. Management of sensors and user agents takes place over standard network protocols such that any number and combination of sensors and user agents, either on the local network or connected via data link, can register with the SMS at any time during the mission. The SMS provides control over sensor data collection to handle logging and routing of data products to subscribing user agents. It also supports the addition of algorithmic data processing agents for feature/target extraction and provides for subsequent cueing from one sensor to another. The SMS architecture was designed to scale from a small UAV carrying a limited number of payloads to an aircraft carrying a large number of payloads. The SMS system is STANAG 4575 compliant as a removable memory module (RMM) and can act as a vehicle specific module (VSM) to provide STANAG 4586 compliance (level-3 interoperability) to a non-compliant sensor system. The SMS architecture will be described and results from several flight tests and simulations will be shown.

The guided-mode resonance biosensor: principles, technology, and implementation

NASA Astrophysics Data System (ADS)

Magnusson, Robert; Lee, Kyu J.; Hemmati, Hafez; Ko, Yeong Hwan; Wenner, Brett R.; Allen, Jeffery W.; Allen, Monica S.; Gimlin, Susanne; Weidanz, Debra Wawro

2018-02-01

The guided-mode resonance (GMR) sensor operates with quasi-guided modes induced in periodic films. The resonance is enabled by 1D or 2D nanopatterns that are expeditiously fabricated. Optical sensors are needed in many fields including medical diagnostics, chemical analyses, and environmental monitoring. Inducing resonance in multiple modes enables extraction of complete bioreaction information including the biolayer thickness, biolayer refractive index, and any change in the refractive index in the background buffer solution. Thus, we refer to this version of the GMR sensor as the complete biosensor. We address the fundamentals, state of technological development, and implementation of this basic sensor modality.

Strain Modal Analysis of Small and Light Pipes Using Distributed Fibre Bragg Grating Sensors

PubMed Central

Huang, Jun; Zhou, Zude; Zhang, Lin; Chen, Juntao; Ji, Chunqian; Pham, Duc Truong

2016-01-01

Vibration fatigue failure is a critical problem of hydraulic pipes under severe working conditions. Strain modal testing of small and light pipes is a good option for dynamic characteristic evaluation, structural health monitoring and damage identification. Unique features such as small size, light weight, and high multiplexing capability enable Fibre Bragg Grating (FBG) sensors to measure structural dynamic responses where sensor size and placement are critical. In this paper, experimental strain modal analysis of pipes using distributed FBG sensors ispresented. Strain modal analysis and parameter identification methods are introduced. Experimental strain modal testing and finite element analysis for a cantilever pipe have been carried out. The analysis results indicate that the natural frequencies and strain mode shapes of the tested pipe acquired by FBG sensors are in good agreement with the results obtained by a reference accelerometer and simulation outputs. The strain modal parameters of a hydraulic pipe were obtained by the proposed strain modal testing method. FBG sensors have been shown to be useful in the experimental strain modal analysis of small and light pipes in mechanical, aeronautic and aerospace applications. PMID:27681728

Control systems using modal domain optical fiber sensors for smart structure applications

NASA Technical Reports Server (NTRS)

Lindner, Douglas K.; Reichard, Karl M.

1991-01-01

Recently, a new class of sensors has emerged for structural control which respond to environmental changes over a significant gauge length; these sensors are called distributed-effect sensors. These sensors can be fabricated with spatially varying sensitivity to the distributed measurand, and can be configured to measure a variety of structural parameters which can not be measured directly using point sensors. Examples of distributed-effect sensors include piezoelectric film, holographic sensors, and modal domain optical fiber sensors. Optical fiber sensors are particularly attractive for smart structure applications because they are flexible, have low mass, and can easily be embedded directly into materials. In this paper we describe the implementation of weighted modal domain optical fiber sensors. The mathematical model of the modal domain optical fiber sensor model is described and used to derive an expression for the sensor sensitivity. The effects of parameter variations on the sensor sensitivity are demonstrated to illustrate methods of spatially varying the sensor sensitivity.

Modal domain fiber optic sensor for closed loop vibration control of a flexible beam

NASA Technical Reports Server (NTRS)

Cox, D.; Thomas, D.; Reichard, K.; Lindner, D.; Claus, R. O.

1990-01-01

The use of a modal domain sensor in a vibration control experiment is described. An optical fiber is bonded along the length of a flexible beam. A control signal derived from the output of the modal domain sensor is used to suppress vibrations induced in the beam. A distributed effect model for the modal domain sensor is developed and combined with models of the beam and actuator dynamics to produce a system suitable for control design.

Human grasping database for activities of daily living with depth, color and kinematic data streams.

PubMed

Saudabayev, Artur; Rysbek, Zhanibek; Khassenova, Raykhan; Varol, Huseyin Atakan

2018-05-29

This paper presents a grasping database collected from multiple human subjects for activities of daily living in unstructured environments. The main strength of this database is the use of three different sensing modalities: color images from a head-mounted action camera, distance data from a depth sensor on the dominant arm and upper body kinematic data acquired from an inertial motion capture suit. 3826 grasps were identified in the data collected during 9-hours of experiments. The grasps were grouped according to a hierarchical taxonomy into 35 different grasp types. The database contains information related to each grasp and associated sensor data acquired from the three sensor modalities. We also provide our data annotation software written in Matlab as an open-source tool. The size of the database is 172 GB. We believe this database can be used as a stepping stone to develop big data and machine learning techniques for grasping and manipulation with potential applications in rehabilitation robotics and intelligent automation.

Data-driven sensor placement from coherent fluid structures

NASA Astrophysics Data System (ADS)

Manohar, Krithika; Kaiser, Eurika; Brunton, Bingni W.; Kutz, J. Nathan; Brunton, Steven L.

2017-11-01

Optimal sensor placement is a central challenge in the prediction, estimation and control of fluid flows. We reinterpret sensor placement as optimizing discrete samples of coherent fluid structures for full state reconstruction. This permits a drastic reduction in the number of sensors required for faithful reconstruction, since complex fluid interactions can often be described by a small number of coherent structures. Our work optimizes point sensors using the pivoted matrix QR factorization to sample coherent structures directly computed from flow data. We apply this sampling technique in conjunction with various data-driven modal identification methods, including the proper orthogonal decomposition (POD) and dynamic mode decomposition (DMD). In contrast to POD-based sensors, DMD demonstrably enables the optimization of sensors for prediction in systems exhibiting multiple scales of dynamics. Finally, reconstruction accuracy from pivot sensors is shown to be competitive with sensors obtained using traditional computationally prohibitive optimization methods.

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

PubMed

Halim, Dunant; Cheng, Li; Su, Zhongqing

2011-04-01

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

Cargo identification algorithms facilitating unmanned/unattended inspection at high throughput portals

NASA Astrophysics Data System (ADS)

Chalmers, Alex

2007-10-01

A simple model is presented of a possible inspection regimen applied to each leg of a cargo containers' journey between its point of origin and destination. Several candidate modalities are proposed to be used at multiple remote locations to act as a pre-screen inspection as the target approaches a perimeter and as the primary inspection modality at the portal. Information from multiple data sets are fused to optimize the costs and performance of a network of such inspection systems. A series of image processing algorithms are presented that automatically process X-ray images of containerized cargo. The goal of this processing is to locate the container in a real time stream of traffic traversing a portal without impeding the flow of commerce. Such processing may facilitate the inclusion of unmanned/unattended inspection systems in such a network. Several samples of the processing applied to data collected from deployed systems are included. Simulated data from a notional cargo inspection system with multiple sensor modalities and advanced data fusion algorithms are also included to show the potential increased detection and throughput performance of such a configuration.

Multimodal Interaction in Ambient Intelligence Environments Using Speech, Localization and Robotics

ERIC Educational Resources Information Center

Galatas, Georgios

2013-01-01

An Ambient Intelligence Environment is meant to sense and respond to the presence of people, using its embedded technology. In order to effectively sense the activities and intentions of its inhabitants, such an environment needs to utilize information captured from multiple sensors and modalities. By doing so, the interaction becomes more natural…

A Comparison of Video-Based and Interaction-Based Affect Detectors in Physics Playground

ERIC Educational Resources Information Center

Kai, Shiming; Paquette, Luc; Baker, Ryan S.; Bosch, Nigel; D'Mello, Sidney; Ocumpaugh, Jaclyn; Shute, Valerie; Ventura, Matthew

2015-01-01

Increased attention to the relationships between affect and learning has led to the development of machine-learned models that are able to identify students' affective states in computerized learning environments. Data for these affect detectors have been collected from multiple modalities including physical sensors, dialogue logs, and logs of…

Classification and data acquisition with incomplete data

NASA Astrophysics Data System (ADS)

Williams, David P.

In remote-sensing applications, incomplete data can result when only a subset of sensors (e.g., radar, infrared, acoustic) are deployed at certain regions. The limitations of single sensor systems have spurred interest in employing multiple sensor modalities simultaneously. For example, in land mine detection tasks, different sensor modalities are better-suited to capture different aspects of the underlying physics of the mines. Synthetic aperture radar sensors may be better at detecting surface mines, while infrared sensors may be better at detecting buried mines. By employing multiple sensor modalities to address the detection task, the strengths of the disparate sensors can be exploited in a synergistic manner to improve performance beyond that which would be achievable with either single sensor alone. When multi-sensor approaches are employed, however, incomplete data can be manifested. If each sensor is located on a separate platform ( e.g., aircraft), each sensor may interrogate---and hence collect data over---only partially overlapping areas of land. As a result, some data points may be characterized by data (i.e., features) from only a subset of the possible sensors employed in the task. Equivalently, this scenario implies that some data points will be missing features. Increasing focus in the future on using---and fusing data from---multiple sensors will make such incomplete-data problems commonplace. In many applications involving incomplete data, it is possible to acquire the missing data at a cost. In multi-sensor remote-sensing applications, data is acquired by deploying sensors to data points. Acquiring data is usually an expensive, time-consuming task, a fact that necessitates an intelligent data acquisition process. Incomplete data is not limited to remote-sensing applications, but rather, can arise in virtually any data set. In this dissertation, we address the general problem of classification when faced with incomplete data. We also address the closely related problem of active data acquisition, which develops a strategy to acquire missing features and labels that will most benefit the classification task. We first address the general problem of classification with incomplete data, maintaining the view that all data (i.e., information) is valuable. We employ a logistic regression framework within which we formulate a supervised classification algorithm for incomplete data. This principled, yet flexible, framework permits several interesting extensions that allow all available data to be utilized. One extension incorporates labeling error, which permits the usage of potentially imperfectly labeled data in learning a classifier. A second major extension converts the proposed algorithm to a semi-supervised approach by utilizing unlabeled data via graph-based regularization. Finally, the classification algorithm is extended to the case in which (image) data---from which features are extracted---are available from multiple resolutions. Taken together, this family of incomplete-data classification algorithms exploits all available data in a principled manner by avoiding explicit imputation. Instead, missing data is integrated out analytically with the aid of an estimated conditional density function (conditioned on the observed features). This feat is accomplished by invoking only mild assumptions. We also address the problem of active data acquisition by determining which missing data should be acquired to most improve performance. Specifically, we examine this data acquisition task when the data to be acquired can be either labels or features. The proposed approach is based on a criterion that accounts for the expected benefit of the acquisition. This approach, which is applicable for any general missing data problem, exploits the incomplete-data classification framework introduced in the first part of this dissertation. This data acquisition approach allows for the acquisition of both labels and features. Moreover, several types of feature acquisition are permitted, including the acquisition of individual or multiple features for individual or multiple data points, which may be either labeled or unlabeled. Furthermore, if different types of data acquisition are feasible for a given application, the algorithm will automatically determine the most beneficial type of data to acquire. Experimental results on both benchmark machine learning data sets and real (i.e., measured) remote-sensing data demonstrate the advantages of the proposed incomplete-data classification and active data acquisition algorithms.

Flexible Skins Containing Integrated Sensors and Circuitry

NASA Technical Reports Server (NTRS)

Liu, Chang

2007-01-01

Artificial sensor skins modeled partly in imitation of biological sensor skins are undergoing development. These sensor skins comprise flexible polymer substrates that contain and/or support dense one- and two-dimensional arrays of microscopic sensors and associated microelectronic circuits. They afford multiple tactile sensing modalities for measuring physical phenomena that can include contact forces; hardnesses, temperatures, and thermal conductivities of objects with which they are in contact; and pressures, shear stresses, and flow velocities in fluids. The sensor skins are mechanically robust, and, because of their flexibility, they can be readily attached to curved and possibly moving and flexing surfaces of robots, wind-tunnel models, and other objects that one might seek to equip for tactile sensing. Because of the diversity of actual and potential sensor-skin design criteria and designs and the complexity of the fabrication processes needed to realize the designs, it is not possible to describe the sensor-skin concept in detail within this article.

Performance Evaluation Modeling of Network Sensors

NASA Technical Reports Server (NTRS)

Clare, Loren P.; Jennings, Esther H.; Gao, Jay L.

2003-01-01

Substantial benefits are promised by operating many spatially separated sensors collectively. Such systems are envisioned to consist of sensor nodes that are connected by a communications network. A simulation tool is being developed to evaluate the performance of networked sensor systems, incorporating such metrics as target detection probabilities, false alarms rates, and classification confusion probabilities. The tool will be used to determine configuration impacts associated with such aspects as spatial laydown, and mixture of different types of sensors (acoustic, seismic, imaging, magnetic, RF, etc.), and fusion architecture. The QualNet discrete-event simulation environment serves as the underlying basis for model development and execution. This platform is recognized for its capabilities in efficiently simulating networking among mobile entities that communicate via wireless media. We are extending QualNet's communications modeling constructs to capture the sensing aspects of multi-target sensing (analogous to multiple access communications), unimodal multi-sensing (broadcast), and multi-modal sensing (multiple channels and correlated transmissions). Methods are also being developed for modeling the sensor signal sources (transmitters), signal propagation through the media, and sensors (receivers) that are consistent with the discrete event paradigm needed for performance determination of sensor network systems. This work is supported under the Microsensors Technical Area of the Army Research Laboratory (ARL) Advanced Sensors Collaborative Technology Alliance.

(DCT-FY08) Target Detection Using Multiple Modality Airborne and Ground Based Sensors

DTIC Science & Technology

2013-03-01

Plenoptic modeling: an image-based rendering system,” in SIGGRAPH ’95: Proceedings of the 22nd annual conference on Computer graphics and interactive...techniques. New York, NY, USA: ACM, 1995, pp. 39–46. [21] D. G. Aliaga and I. Carlbom, “ Plenoptic stitching: a scalable method for reconstructing 3D

Optically defined modal sensors incorporating spiropyran-doped liquid crystals with piezoelectric sensors.

PubMed

Chen, Kuan-Ting; Chang, Chin-Kai; Kuo, Hui-Lung; Lee, Chih-Kung

2011-01-01

We integrated a piezoelectric sensing layer lamina containing liquid crystals (LC) and spiropyran (SP) in a LC/SP mixture to create an optically reconfigurable modal sensor for a cantilever beam. The impedance of this LC/SP lamina was decreased by UV irradiation which constituted the underlying mechanism to modulate the voltage externally applied to the piezoelectric actuating layer. Illuminating a specific pattern onto the LC/SP lamina provided us with a way to spatially modulate the piezoelectric vibration signal. We showed that if an UV illuminated pattern matches the strain distribution of a specific mode, a piezoelectric modal sensor can be created. Since UV illumination can be changed in situ in real-time, our results confirm for the first time since the inception of smart sensors, that an optically tailored modal sensor can be created. Some potential applications of this type of sensor include energy harvesting devices, bio-chips, vibration sensing and actuating devices.

Vibration sensing in flexible structures using a distributed-effect modal domain optical fiber sensor

NASA Technical Reports Server (NTRS)

Reichard, Karl M.; Lindner, Douglas K.; Claus, Richard O.

1991-01-01

Modal domain optical fiber sensors have recently been employed in the implementation of system identification algorithms and the closed-loop control of vibrations in flexible structures. The mathematical model of the modal domain optical fiber sensor used in these applications, however, only accounted for the effects of strain in the direction of the fiber's longitudinal axis. In this paper, we extend this model to include the effects of arbitrary stress. Using this sensor model, we characterize the sensor's sensitivity and dynamic range.

Wave analysis of a plenoptic system and its applications

NASA Astrophysics Data System (ADS)

Shroff, Sapna A.; Berkner, Kathrin

2013-03-01

Traditional imaging systems directly image a 2D object plane on to the sensor. Plenoptic imaging systems contain a lenslet array at the conventional image plane and a sensor at the back focal plane of the lenslet array. In this configuration the data captured at the sensor is not a direct image of the object. Each lenslet effectively images the aperture of the main imaging lens at the sensor. Therefore the sensor data retains angular light-field information which can be used for a posteriori digital computation of multi-angle images and axially refocused images. If a filter array, containing spectral filters or neutral density or polarization filters, is placed at the pupil aperture of the main imaging lens, then each lenslet images the filters on to the sensor. This enables the digital separation of multiple filter modalities giving single snapshot, multi-modal images. Due to the diversity of potential applications of plenoptic systems, their investigation is increasing. As the application space moves towards microscopes and other complex systems, and as pixel sizes become smaller, the consideration of diffraction effects in these systems becomes increasingly important. We discuss a plenoptic system and its wave propagation analysis for both coherent and incoherent imaging. We simulate a system response using our analysis and discuss various applications of the system response pertaining to plenoptic system design, implementation and calibration.

Wide-area littoral discreet observation: success at the tactical edge

NASA Astrophysics Data System (ADS)

Toth, Susan; Hughes, William; Ladas, Andrew

2012-06-01

In June 2011, the United States Army Research Laboratory (ARL) participated in Empire Challenge 2011 (EC-11). EC-11 was United States Joint Forces Command's (USJFCOM) annual live, joint and coalition intelligence, surveillance and reconnaissance (ISR) interoperability demonstration under the sponsorship of the Under Secretary of Defense for Intelligence (USD/I). EC-11 consisted of a series of ISR interoperability events, using a combination of modeling & simulation, laboratory and live-fly events. Wide-area Littoral Discreet Observation (WALDO) was ARL's maritime/littoral capability. WALDO met a USD(I) directive that EC-11 have a maritime component and WALDO was the primary player in the maritime scenario conducted at Camp Lejeune, North Carolina. The WALDO effort demonstrated the utility of a networked layered sensor array deployed in a maritime littoral environment, focusing on maritime surveillance targeting counter-drug, counter-piracy and suspect activity in a littoral or riverine environment. In addition to an embedded analytical capability, the sensor array and control infrastructure consisted of the Oriole acoustic sensor, iScout unattended ground sensor (UGS), OmniSense UGS, the Compact Radar and the Universal Distributed Management System (UDMS), which included the Proxy Skyraider, an optionally manned aircraft mounting both wide and narrow FOV EO/IR imaging sensors. The capability seeded a littoral area with riverine and unattended sensors in order to demonstrate the utility of a Wide Area Sensor (WAS) capability in a littoral environment focused on maritime surveillance activities. The sensors provided a cue for WAS placement/orbit. A narrow field of view sensor would be used to focus on more discreet activities within the WAS footprint. Additionally, the capability experimented with novel WAS orbits to determine if there are more optimal orbits for WAS collection in a littoral environment. The demonstration objectives for WALDO at EC-11 were: * Demonstrate a networked, layered, multi-modal sensor array deployed in a maritime littoral environment, focusing on maritime surveillance targeting counter-drug, counter-piracy and suspect activity * Assess the utility of a Wide Area Surveillance (WAS) sensor in a littoral environment focused on maritime surveillance activities * Demonstrate the effectiveness of using UGS sensors to cue WAS sensor tasking * Employ a narrow field of view full motion video (FMV) sensor package that is collocated with the WAS to conduct more discrete observation of potential items of interest when queued by near-real-time data from UGS or observers * Couple the ARL Oriole sensor with other modality UGS networks in a ground layer ISR capability, and incorporate data collected from aerial sensors with a GEOINT base layer to form a fused product * Swarm multiple aerial or naval platforms to prosecute single or multiple targets * Track fast moving surface vessels in littoral areas * Disseminate time sensitive, high value data to the users at the tactical edge In short we sought to answer the following question: how do you layer, control and display disparate sensors and sensor modalities in such a way as to facilitate appropriate sensor cross-cue, data integration, and analyst control to effectively monitor activity in a littoral (or novel) environment?

Prediction of Cognitive States During Flight Simulation Using Multimodal Psychophysiological Sensing

NASA Technical Reports Server (NTRS)

Harrivel, Angela R.; Stephens, Chad L.; Milletich, Robert J.; Heinich, Christina M.; Last, Mary Carolyn; Napoli, Nicholas J.; Abraham, Nijo A.; Prinzel, Lawrence J.; Motter, Mark A.; Pope, Alan T.

2017-01-01

The Commercial Aviation Safety Team found the majority of recent international commercial aviation accidents attributable to loss of control inflight involved flight crew loss of airplane state awareness (ASA), and distraction was involved in all of them. Research on attention-related human performance limiting states (AHPLS) such as channelized attention, diverted attention, startle/surprise, and confirmation bias, has been recommended in a Safety Enhancement (SE) entitled "Training for Attention Management." To accomplish the detection of such cognitive and psychophysiological states, a broad suite of sensors was implemented to simultaneously measure their physiological markers during a high fidelity flight simulation human subject study. Twenty-four pilot participants were asked to wear the sensors while they performed benchmark tasks and motion-based flight scenarios designed to induce AHPLS. Pattern classification was employed to predict the occurrence of AHPLS during flight simulation also designed to induce those states. Classifier training data were collected during performance of the benchmark tasks. Multimodal classification was performed, using pre-processed electroencephalography, galvanic skin response, electrocardiogram, and respiration signals as input features. A combination of one, some or all modalities were used. Extreme gradient boosting, random forest and two support vector machine classifiers were implemented. The best accuracy for each modality-classifier combination is reported. Results using a select set of features and using the full set of available features are presented. Further, results are presented for training one classifier with the combined features and for training multiple classifiers with features from each modality separately. Using the select set of features and combined training, multistate prediction accuracy averaged 0.64 +/- 0.14 across thirteen participants and was significantly higher than that for the separate training case. These results support the goal of demonstrating simultaneous real-time classification of multiple states using multiple sensing modalities in high fidelity flight simulators. This detection is intended to support and inform training methods under development to mitigate the loss of ASA and thus reduce accidents and incidents.

Towards an autonomous sensor architecture for persistent area protection

NASA Astrophysics Data System (ADS)

Thomas, Paul A.; Marshall, Gillian F.; Stubbins, Daniel J.; Faulkner, David A.

2016-10-01

The majority of sensor installations for area protection (e.g. critical national infrastructure, military forward operating bases, etc.) make use of banks of screens each containing one or more sensor feeds, such that the burden of combining data from the various sources, understanding the situation, and controlling the sensors all lies with the human operator. Any automation in the system is generally heavily bespoke for the particular installation, leading to an inflexible system which is difficult to change or upgrade. We have developed a modular system architecture consisting of intelligent autonomous sensor modules, a high level decision making module, a middleware integration layer and an end-user GUI. The modules are all effectively "plug and play", and we have demonstrated that it is relatively simple to incorporate legacy sensors into the architecture. We have extended our previously-reported SAPIENT demonstration system to operate with a larger number and variety of sensor modules, over an extended area, detecting and classifying a wider variety of "threat activities", both vehicular and pedestrian. We report the results of a demonstration of the SAPIENT system containing multiple autonomous sensor modules with a range of modalities including laser scanners, radar, TI, EO, acoustic and seismic sensors. They operate from a combination of mains, generator and battery power, and communicate with the central "hub" over Ethernet, point-to-point wireless links and Wi-Fi. The system has been configured to protect an extended area in a complex semi-urban environment. We discuss the operation of the SAPIENT system in a realistic demonstration environment (which included significant activity not under trial control), showing sensor cueing, multi-modal sensor fusion, threat prioritisation and target hand-off.

An ECT/ERT dual-modality sensor for oil-water two-phase flow measurement

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

Wang, Pitao; Wang, Huaxiang; Sun, Benyuan

2014-04-11

This paper presents a new sensor for ECT/ERT dual-modality system which can simultaneously obtain the permittivity and conductivity of the materials in the pipeline. Quasi-static electromagnetic fields are produced by the inner electrodes array sensor of electrical capacitance tomography (ECT) system. The results of simulation show that the data of permittivity and conductivity can be simultaneously obtained from the same measurement electrode and the fusion of two kinds of data may improve the quality of the reconstructed images. For uniform oil-water mixtures, the performance of designed dual-modality sensor for measuring the various oil fractions has been tested on representative datamore » and the results of experiments show that the designed sensor broadens the measurement range compared to single modality.« less

Integration of Fiber-Optic Sensor Arrays into a Multi-Modal Tactile Sensor Processing System for Robotic End-Effectors

PubMed Central

Kampmann, Peter; Kirchner, Frank

2014-01-01

With the increasing complexity of robotic missions and the development towards long-term autonomous systems, the need for multi-modal sensing of the environment increases. Until now, the use of tactile sensor systems has been mostly based on sensing one modality of forces in the robotic end-effector. The use of a multi-modal tactile sensory system is motivated, which combines static and dynamic force sensor arrays together with an absolute force measurement system. This publication is focused on the development of a compact sensor interface for a fiber-optic sensor array, as optic measurement principles tend to have a bulky interface. Mechanical, electrical and software approaches are combined to realize an integrated structure that provides decentralized data pre-processing of the tactile measurements. Local behaviors are implemented using this setup to show the effectiveness of this approach. PMID:24743158

An EGO-like optimization framework for sensor placement optimization in modal analysis

NASA Astrophysics Data System (ADS)

Morlier, Joseph; Basile, Aniello; Chiplunkar, Ankit; Charlotte, Miguel

2018-07-01

In aircraft design, ground/flight vibration tests are conducted to extract aircraft’s modal parameters (natural frequencies, damping ratios and mode shapes) also known as the modal basis. The main problem in aircraft modal identification is the large number of sensors needed, which increases operational time and costs. The goal of this paper is to minimize the number of sensors by optimizing their locations in order to reconstruct a truncated modal basis of N mode shapes with a high level of accuracy in the reconstruction. There are several methods to solve sensors placement optimization (SPO) problems, but for this case an original approach has been established based on an iterative process for mode shapes reconstruction through an adaptive Kriging metamodeling approach so called efficient global optimization (EGO)-SPO. The main idea in this publication is to solve an optimization problem where the sensors locations are variables and the objective function is defined by maximizing the trace of criteria so called AutoMAC. The results on a 2D wing demonstrate a reduction of sensors by 30% using our EGO-SPO strategy.

A custom multi-modal sensor suite and data analysis pipeline for aerial field phenotyping

NASA Astrophysics Data System (ADS)

Bartlett, Paul W.; Coblenz, Lauren; Sherwin, Gary; Stambler, Adam; van der Meer, Andries

2017-05-01

Our group has developed a custom, multi-modal sensor suite and data analysis pipeline to phenotype crops in the field using unpiloted aircraft systems (UAS). This approach to high-throughput field phenotyping is part of a research initiative intending to markedly accelerate the breeding process for refined energy sorghum varieties. To date, single rotor and multirotor helicopters, roughly 14 kg in total weight, are being employed to provide sensor coverage over multiple hectaresized fields in tens of minutes. The quick, autonomous operations allow for complete field coverage at consistent plant and lighting conditions, with low operating costs. The sensor suite collects data simultaneously from six sensors and registers it for fusion and analysis. High resolution color imagery targets color and geometric phenotypes, along with lidar measurements. Long-wave infrared imagery targets temperature phenomena and plant stress. Hyperspectral visible and near-infrared imagery targets phenotypes such as biomass and chlorophyll content, as well as novel, predictive spectral signatures. Onboard spectrometers and careful laboratory and in-field calibration techniques aim to increase the physical validity of the sensor data throughout and across growing seasons. Off-line processing of data creates basic products such as image maps and digital elevation models. Derived data products include phenotype charts, statistics, and trends. The outcome of this work is a set of commercially available phenotyping technologies, including sensor suites, a fully integrated phenotyping UAS, and data analysis software. Effort is also underway to transition these technologies to farm management users by way of streamlined, lower cost sensor packages and intuitive software interfaces.

Characterization of identification errors and uses in localization of poor modal correlation

NASA Astrophysics Data System (ADS)

Martin, Guillaume; Balmes, Etienne; Chancelier, Thierry

2017-05-01

While modal identification is a mature subject, very few studies address the characterization of errors associated with components of a mode shape. This is particularly important in test/analysis correlation procedures, where the Modal Assurance Criterion is used to pair modes and to localize at which sensors discrepancies occur. Poor correlation is usually attributed to modeling errors, but clearly identification errors also occur. In particular with 3D Scanning Laser Doppler Vibrometer measurement, many transfer functions are measured. As a result individual validation of each measurement cannot be performed manually in a reasonable time frame and a notable fraction of measurements is expected to be fairly noisy leading to poor identification of the associated mode shape components. The paper first addresses measurements and introduces multiple criteria. The error measures the difference between test and synthesized transfer functions around each resonance and can be used to localize poorly identified modal components. For intermediate error values, diagnostic of the origin of the error is needed. The level evaluates the transfer function amplitude in the vicinity of a given mode and can be used to eliminate sensors with low responses. A Noise Over Signal indicator, product of error and level, is then shown to be relevant to detect poorly excited modes and errors due to modal property shifts between test batches. Finally, a contribution is introduced to evaluate the visibility of a mode in each transfer. Using tests on a drum brake component, these indicators are shown to provide relevant insight into the quality of measurements. In a second part, test/analysis correlation is addressed with a focus on the localization of sources of poor mode shape correlation. The MACCo algorithm, which sorts sensors by the impact of their removal on a MAC computation, is shown to be particularly relevant. Combined with the error it avoids keeping erroneous modal components. Applied after removal of poor modal components, it provides spatial maps of poor correlation, which help localizing mode shape correlation errors and thus prepare the selection of model changes in updating procedures.

Multiple Objects Fusion Tracker Using a Matching Network for Adaptively Represented Instance Pairs

PubMed Central

Oh, Sang-Il; Kang, Hang-Bong

2017-01-01

Multiple-object tracking is affected by various sources of distortion, such as occlusion, illumination variations and motion changes. Overcoming these distortions by tracking on RGB frames, such as shifting, has limitations because of material distortions caused by RGB frames. To overcome these distortions, we propose a multiple-object fusion tracker (MOFT), which uses a combination of 3D point clouds and corresponding RGB frames. The MOFT uses a matching function initialized on large-scale external sequences to determine which candidates in the current frame match with the target object in the previous frame. After conducting tracking on a few frames, the initialized matching function is fine-tuned according to the appearance models of target objects. The fine-tuning process of the matching function is constructed as a structured form with diverse matching function branches. In general multiple object tracking situations, scale variations for a scene occur depending on the distance between the target objects and the sensors. If the target objects in various scales are equally represented with the same strategy, information losses will occur for any representation of the target objects. In this paper, the output map of the convolutional layer obtained from a pre-trained convolutional neural network is used to adaptively represent instances without information loss. In addition, MOFT fuses the tracking results obtained from each modality at the decision level to compensate the tracking failures of each modality using basic belief assignment, rather than fusing modalities by selectively using the features of each modality. Experimental results indicate that the proposed tracker provides state-of-the-art performance considering multiple objects tracking (MOT) and KITTIbenchmarks. PMID:28420194

A multimodal image sensor system for identifying water stress in grapevines

NASA Astrophysics Data System (ADS)

Zhao, Yong; Zhang, Qin; Li, Minzan; Shao, Yongni; Zhou, Jianfeng; Sun, Hong

2012-11-01

Water stress is one of the most common limitations of fruit growth. Water is the most limiting resource for crop growth. In grapevines, as well as in other fruit crops, fruit quality benefits from a certain level of water deficit which facilitates to balance vegetative and reproductive growth and the flow of carbohydrates to reproductive structures. A multi-modal sensor system was designed to measure the reflectance signature of grape plant surfaces and identify different water stress levels in this paper. The multi-modal sensor system was equipped with one 3CCD camera (three channels in R, G, and IR). The multi-modal sensor can capture and analyze grape canopy from its reflectance features, and identify the different water stress levels. This research aims at solving the aforementioned problems. The core technology of this multi-modal sensor system could further be used as a decision support system that combines multi-modal sensory data to improve plant stress detection and identify the causes of stress. The images were taken by multi-modal sensor which could output images in spectral bands of near-infrared, green and red channel. Based on the analysis of the acquired images, color features based on color space and reflectance features based on image process method were calculated. The results showed that these parameters had the potential as water stress indicators. More experiments and analysis are needed to validate the conclusion.

Real time health monitoring and control system methodology for flexible space structures

NASA Astrophysics Data System (ADS)

Jayaram, Sanjay

This dissertation is concerned with the Near Real-time Autonomous Health Monitoring of Flexible Space Structures. The dynamics of multi-body flexible systems is uncertain due to factors such as high non-linearity, consideration of higher modal frequencies, high dimensionality, multiple inputs and outputs, operational constraints, as well as unexpected failures of sensors and/or actuators. Hence a systematic framework of developing a high fidelity, dynamic model of a flexible structural system needs to be understood. The fault detection mechanism that will be an integrated part of an autonomous health monitoring system comprises the detection of abnormalities in the sensors and/or actuators and correcting these detected faults (if possible). Applying the robust control law and the robust measures that are capable of detecting and recovering/replacing the actuators rectifies the actuator faults. The fault tolerant concept applied to the sensors will be in the form of an Extended Kalman Filter (EKF). The EKF is going to weigh the information coming from multiple sensors (redundant sensors used to measure the same information) and automatically identify the faulty sensors and weigh the best estimate from the remaining sensors. The mechanization is comprised of instrumenting flexible deployable panels (solar array) with multiple angular position and rate sensors connected to the data acquisition system. The sensors will give position and rate information of the solar panel in all three axes (i.e. roll, pitch and yaw). The position data corresponds to the steady state response and the rate data will give better insight on the transient response of the system. This is a critical factor for real-time autonomous health monitoring. MATLAB (and/or C++) software will be used for high fidelity modeling and fault tolerant mechanism.

Fusing Multiple Sensor Modalities for Complex Physiological State Monitoring

DTIC Science & Technology

2012-12-01

sleep-alpha variants (drowsiness alpha activity and REM -alpha bursts) over frontal, central, parietal and occipital regions. Note the higher spectral...contribution of the slowest components (7.8–8.6 Hz) during REM alpha bursts as compared with drowsiness-alpha activity (13...occipital regions of the brain during the drowsiness state as compared to REM sleep and other states, as seen in figure 1 (13). Furthermore, using EEG

Smooth adaptive sliding mode vibration control of a flexible parallel manipulator with multiple smart linkages in modal space

NASA Astrophysics Data System (ADS)

Zhang, Quan; Li, Chaodong; Zhang, Jiantao; Zhang, Jianhui

2017-12-01

This paper addresses the dynamic model and active vibration control of a rigid-flexible parallel manipulator with three smart links actuated by three linear ultrasonic motors. To suppress the vibration of three flexible intermediate links under high speed and acceleration, multiple Lead Zirconium Titanate (PZT) sensors and actuators are collocated mounted on each link, forming a smart structure which can achieve self-sensing and self-actuating. The dynamic characteristics and equations of the flexible link incorporated with the PZT sensors and actuator are analyzed and formulated. The smooth adaptive sliding mode based active vibration control is proposed to suppress the vibration of the smart links, and the first and second modes of the three links are targeted to be suppressed in modal space to avoid the spillover phenomenon. Simulations and experiments are implemented to validate the effectiveness of the smart structures and the proposed control laws. Experimental results show that the vibration of the first mode around 92 Hz and the second mode around 240 Hz of the three smart links are reduced respectively by 64.98%, 59.47%, 62.28%, and 45.80%, 36.79%, 33.33%, which further verify the multi-mode vibration control ability of the smooth adaptive sliding mode control law.

Optical fiber sensors and signal processing for intelligent structure monitoring

NASA Technical Reports Server (NTRS)

Thomas, Daniel; Cox, Dave; Lindner, D. K.; Claus, R. O.

1989-01-01

Few mode optical fibers have been shown to produce predictable interference patterns when placed under strain. The use is described of a modal domain sensor in a vibration control experiment. An optical fiber is bonded along the length of a flexible beam. Output from the modal domain sensor is used to suppress vibrations induced in the beam. A distributed effect model for the modal domain sensor is developed. This model is combined with the beam and actuator dynamics to produce a system suitable for control design. Computer simulations predict open and closed loop dynamic responses. An experimental apparatus is described and experimental results are presented.

Neural network for intelligent query of an FBI forensic database

NASA Astrophysics Data System (ADS)

Uvanni, Lee A.; Rainey, Timothy G.; Balasubramanian, Uma; Brettle, Dean W.; Weingard, Fred; Sibert, Robert W.; Birnbaum, Eric

1997-02-01

Examiner is an automated fired cartridge case identification system utilizing a dual-use neural network pattern recognition technology, called the statistical-multiple object detection and location system (S-MODALS) developed by Booz(DOT)Allen & Hamilton, Inc. in conjunction with Rome Laboratory. S-MODALS was originally designed for automatic target recognition (ATR) of tactical and strategic military targets using multisensor fusion [electro-optical (EO), infrared (IR), and synthetic aperture radar (SAR)] sensors. Since S-MODALS is a learning system readily adaptable to problem domains other than automatic target recognition, the pattern matching problem of microscopic marks for firearms evidence was analyzed using S-MODALS. The physics; phenomenology; discrimination and search strategies; robustness requirements; error level and confidence level propagation that apply to the pattern matching problem of military targets were found to be applicable to the ballistic domain as well. The Examiner system uses S-MODALS to rank a set of queried cartridge case images from the most similar to the least similar image in reference to an investigative fired cartridge case image. The paper presents three independent tests and evaluation studies of the Examiner system utilizing the S-MODALS technology for the Federal Bureau of Investigation.

Wearable sensors for human health monitoring

NASA Astrophysics Data System (ADS)

Asada, H. Harry; Reisner, Andrew

2006-03-01

Wearable sensors for continuous monitoring of vital signs for extended periods of weeks or months are expected to revolutionize healthcare services in the home and workplace as well as in hospitals and nursing homes. This invited paper describes recent research progress in wearable health monitoring technology and its clinical applications, with emphasis on blood pressure and circulatory monitoring. First, a finger ring-type wearable blood pressure sensor based on photo plethysmogram is presented. Technical issues, including motion artifact reduction, power saving, and wearability enhancement, will be addressed. Second, sensor fusion and sensor networking for integrating multiple sensors with diverse modalities will be discussed for comprehensive monitoring and diagnosis of health status. Unlike traditional snap-shot measurements, continuous monitoring with wearable sensors opens up the possibility to treat the physiological system as a dynamical process. This allows us to apply powerful system dynamics and control methodologies, such as adaptive filtering, single- and multi-channel system identification, active noise cancellation, and adaptive control, to the monitoring and treatment of highly complex physiological systems. A few clinical trials illustrate the potentials of the wearable sensor technology for future heath care services.

Integrating Iris and Signature Traits for Personal Authentication Using User-Specific Weighting

PubMed Central

Viriri, Serestina; Tapamo, Jules R.

2012-01-01

Biometric systems based on uni-modal traits are characterized by noisy sensor data, restricted degrees of freedom, non-universality and are susceptible to spoof attacks. Multi-modal biometric systems seek to alleviate some of these drawbacks by providing multiple evidences of the same identity. In this paper, a user-score-based weighting technique for integrating the iris and signature traits is presented. This user-specific weighting technique has proved to be an efficient and effective fusion scheme which increases the authentication accuracy rate of multi-modal biometric systems. The weights are used to indicate the importance of matching scores output by each biometrics trait. The experimental results show that our biometric system based on the integration of iris and signature traits achieve a false rejection rate (FRR) of 0.08% and a false acceptance rate (FAR) of 0.01%. PMID:22666032

Sensor modeling and demonstration of a multi-object spectrometer for performance-driven sensing

NASA Astrophysics Data System (ADS)

Kerekes, John P.; Presnar, Michael D.; Fourspring, Kenneth D.; Ninkov, Zoran; Pogorzala, David R.; Raisanen, Alan D.; Rice, Andrew C.; Vasquez, Juan R.; Patel, Jeffrey P.; MacIntyre, Robert T.; Brown, Scott D.

2009-05-01

A novel multi-object spectrometer (MOS) is being explored for use as an adaptive performance-driven sensor that tracks moving targets. Developed originally for astronomical applications, the instrument utilizes an array of micromirrors to reflect light to a panchromatic imaging array. When an object of interest is detected the individual micromirrors imaging the object are tilted to reflect the light to a spectrometer to collect a full spectrum. This paper will present example sensor performance from empirical data collected in laboratory experiments, as well as our approach in designing optical and radiometric models of the MOS channels and the micromirror array. Simulation of moving vehicles in a highfidelity, hyperspectral scene is used to generate a dynamic video input for the adaptive sensor. Performance-driven algorithms for feature-aided target tracking and modality selection exploit multiple electromagnetic observables to track moving vehicle targets.

System and Method for Dynamic Aeroelastic Control

NASA Technical Reports Server (NTRS)

Suh, Peter M. (Inventor)

2015-01-01

The present invention proposes a hardware and software architecture for dynamic modal structural monitoring that uses a robust modal filter to monitor a potentially very large-scale array of sensors in real time, and tolerant of asymmetric sensor noise and sensor failures, to achieve aircraft performance optimization such as minimizing aircraft flutter, drag and maximizing fuel efficiency.

Integrated multimodal human-computer interface and augmented reality for interactive display applications

NASA Astrophysics Data System (ADS)

Vassiliou, Marius S.; Sundareswaran, Venkataraman; Chen, S.; Behringer, Reinhold; Tam, Clement K.; Chan, M.; Bangayan, Phil T.; McGee, Joshua H.

2000-08-01

We describe new systems for improved integrated multimodal human-computer interaction and augmented reality for a diverse array of applications, including future advanced cockpits, tactical operations centers, and others. We have developed an integrated display system featuring: speech recognition of multiple concurrent users equipped with both standard air- coupled microphones and novel throat-coupled sensors (developed at Army Research Labs for increased noise immunity); lip reading for improving speech recognition accuracy in noisy environments, three-dimensional spatialized audio for improved display of warnings, alerts, and other information; wireless, coordinated handheld-PC control of a large display; real-time display of data and inferences from wireless integrated networked sensors with on-board signal processing and discrimination; gesture control with disambiguated point-and-speak capability; head- and eye- tracking coupled with speech recognition for 'look-and-speak' interaction; and integrated tetherless augmented reality on a wearable computer. The various interaction modalities (speech recognition, 3D audio, eyetracking, etc.) are implemented a 'modality servers' in an Internet-based client-server architecture. Each modality server encapsulates and exposes commercial and research software packages, presenting a socket network interface that is abstracted to a high-level interface, minimizing both vendor dependencies and required changes on the client side as the server's technology improves.

Addressing practical challenges in utility optimization of mobile wireless sensor networks

NASA Astrophysics Data System (ADS)

Eswaran, Sharanya; Misra, Archan; La Porta, Thomas; Leung, Kin

2008-04-01

This paper examines the practical challenges in the application of the distributed network utility maximization (NUM) framework to the problem of resource allocation and sensor device adaptation in a mission-centric wireless sensor network (WSN) environment. By providing rich (multi-modal), real-time information about a variety of (often inaccessible or hostile) operating environments, sensors such as video, acoustic and short-aperture radar enhance the situational awareness of many battlefield missions. Prior work on the applicability of the NUM framework to mission-centric WSNs has focused on tackling the challenges introduced by i) the definition of an individual mission's utility as a collective function of multiple sensor flows and ii) the dissemination of an individual sensor's data via a multicast tree to multiple consuming missions. However, the practical application and performance of this framework is influenced by several parameters internal to the framework and also by implementation-specific decisions. This is made further complex due to mobile nodes. In this paper, we use discrete-event simulations to study the effects of these parameters on the performance of the protocol in terms of speed of convergence, packet loss, and signaling overhead thereby addressing the challenges posed by wireless interference and node mobility in ad-hoc battlefield scenarios. This study provides better understanding of the issues involved in the practical adaptation of the NUM framework. It also helps identify potential avenues of improvement within the framework and protocol.

Nano-displacement sensor based on photonic crystal fiber modal interferometer.

PubMed

Dash, Jitendra Narayan; Jha, Rajan; Villatoro, Joel; Dass, Sumit

2015-02-15

A stable nano-displacement sensor based on large mode area photonic crystal fiber (PCF) modal interferometer is presented. The compact setup requires simple splicing of a small piece of PCF with a single mode fiber (SMF). The excitation and recombination of modes is carried out in a single splice. The use of a reflecting target creates an extra cavity that discretizes the interference pattern of the mode interferometer, boosting the displacement resolution to nanometer level. The proposed modal interferometric based displacement sensor is highly stable and shows sensitivity of 32  pm/nm.

Sense, decide, act, communicate (SDAC): next generation of smart sensor systems

NASA Astrophysics Data System (ADS)

Berry, Nina; Davis, Jesse; Ko, Teresa H.; Kyker, Ron; Pate, Ron; Stark, Doug; Stinnett, Regan; Baker, James; Cushner, Adam; Van Dyke, Colin; Kyckelhahn, Brian

2004-09-01

The recent war on terrorism and increased urban warfare has been a major catalysis for increased interest in the development of disposable unattended wireless ground sensors. While the application of these sensors to hostile domains has been generally governed by specific tasks, this research explores a unique paradigm capitalizing on the fundamental functionality related to sensor systems. This functionality includes a sensors ability to Sense - multi-modal sensing of environmental events, Decide - smart analysis of sensor data, Act - response to environmental events, and Communication - internal to system and external to humans (SDAC). The main concept behind SDAC sensor systems is to integrate the hardware, software, and networking to generate 'knowledge and not just data'. This research explores the usage of wireless SDAC units to collectively make up a sensor system capable of persistent, adaptive, and autonomous behavior. These systems are base on the evaluation of scenarios and existing systems covering various domains. This paper presents a promising view of sensor network characteristics, which will eventually yield smart (intelligent collectives) network arrays of SDAC sensing units generally applicable to multiple related domains. This paper will also discuss and evaluate the demonstration system developed to test the concepts related to SDAC systems.

Implementation of a multi-modal mobile sensor system for surface and subsurface assessment of roadways

NASA Astrophysics Data System (ADS)

Wang, Ming; Birken, Ralf; Shahini Shamsabadi, Salar

2015-03-01

There are more than 4 million miles of roads and 600,000 bridges in the United States alone. On-going investments are required to maintain the physical and operational quality of these assets to ensure public's safety and prosperity of the economy. Planning efficient maintenance and repair (M&R) operations must be armed with a meticulous pavement inspection method that is non-disruptive, is affordable and requires minimum manual effort. The Versatile Onboard Traffic Embedded Roaming Sensors (VOTERS) project developed a technology able to cost- effectively monitor the condition of roadway systems to plan for the right repairs, in the right place, at the right time. VOTERS technology consists of an affordable, lightweight package of multi-modal sensor systems including acoustic, optical, electromagnetic, and GPS sensors. Vehicles outfitted with this technology would be capable of collecting information on a variety of pavement-related characteristics at both surface and subsurface levels as they are driven. By correlating the sensors' outputs with the positioning data collected in tight time synchronization, a GIS-based control center attaches a spatial component to all the sensors' measurements and delivers multiple ratings of the pavement every meter. These spatially indexed ratings are then leveraged by VOTERS decision making modules to plan the optimum M&R operations and predict the future budget needs. In 2014, VOTERS inspection results were validated by comparing them to the outputs of recent professionally done condition surveys of a local engineering firm for 300 miles of Massachusetts roads. Success of the VOTERS project portrays rapid, intelligent, and comprehensive evaluation of tomorrow's transportation infrastructure to increase public's safety, vitalize the economy, and deter catastrophic failures.

Fiber-Optic Surface Temperature Sensor Based on Modal Interference.

PubMed

Musin, Frédéric; Mégret, Patrice; Wuilpart, Marc

2016-07-28

Spatially-integrated surface temperature sensing is highly useful when it comes to controlling processes, detecting hazardous conditions or monitoring the health and safety of equipment and people. Fiber-optic sensing based on modal interference has shown great sensitivity to temperature variation, by means of cost-effective image-processing of few-mode interference patterns. New developments in the field of sensor configuration, as described in this paper, include an innovative cooling and heating phase discrimination functionality and more precise measurements, based entirely on the image processing of interference patterns. The proposed technique was applied to the measurement of the integrated surface temperature of a hollow cylinder and compared with a conventional measurement system, consisting of an infrared camera and precision temperature probe. As a result, the optical technique is in line with the reference system. Compared with conventional surface temperature probes, the optical technique has the following advantages: low heat capacity temperature measurement errors, easier spatial deployment, and replacement of multiple angle infrared camera shooting and the continuous monitoring of surfaces that are not visually accessible.

Stochastic response analysis, order reduction, and output feedback controllers for flexible spacecraft

NASA Technical Reports Server (NTRS)

Hablani, H. B.

1985-01-01

Real disturbances and real sensors have finite bandwidths. The first objective of this paper is to incorporate this finiteness in the 'open-loop modal cost analysis' as applied to a flexible spacecraft. Analysis based on residue calculus shows that among other factors, significance of a mode depends on the power spectral density of disturbances and the response spectral density of sensors at the modal frequency. The second objective of this article is to compare performances of an optimal and a suboptimal output feedback controller, the latter based on 'minimum error excitation' of Kosut. Both the performances are found to be nearly the same, leading us to favor the latter technique because it entails only linear computations. Our final objective is to detect an instability due to truncated modes by representing them as a multiplicative and an additive perturbation in a nominal transfer function. In an example problem it is found that this procedure leads to a narrow range of permissible controller gains, and that it labels a wrong mode as a cause of instability. A free beam is used to illustrate the analysis in this work.

Active vibration control using a modal-domain fiber optic sensor

NASA Technical Reports Server (NTRS)

Cox, David E.

1992-01-01

A closed-loop control experiment is described in which vibrations of a cantilevered beam are suppressed using measurements from a modal-domain fiber optic sensor. Modal-domain sensors are interference between the modes of a few-mode optical waveguide to detect strain. The fiber is bonded along the length of the beam and provides a measurement related to the strain distribution on the surface of the beam. A model for the fiber optic sensor is derived, and this model is integrated with the dynamic model of the beam. A piezoelectric actuator is also bonded to the beam and used to provide control forces. Control forces are obtained through dynamic compensation of the signal from the fiber optic sensor. The compensator is implemented with a real-time digital controller. Analytical models are verified by comparing simulations to experimental results for both open-loop and closed-loop configurations.

The role of tactile sensation in online and offline hierarchical control of multi-finger force synergy.

PubMed

Koh, Kyung; Kwon, Hyun Joon; Yoon, Bum Chul; Cho, Yongseok; Shin, Joon-Ho; Hahn, Jin-Oh; Miller, Ross H; Kim, Yoon Hyuk; Shim, Jae Kun

2015-09-01

The hand, one of the most versatile but mechanically redundant parts of the human body, must overcome imperfect motor commands and inherent noise in both the sensory and motor systems in order to produce desired motor actions. For example, it is nearly impossible to produce a perfectly consistent note during a single violin stroke or to produce the exact same note over multiple strokes, which we denote online and offline control, respectively. To overcome these challenges, the central nervous system synergistically integrates multiple sensory modalities and coordinates multiple motor effectors. Among these sensory modalities, tactile sensation plays an important role in manual motor tasks by providing hand-object contact information. The purpose of this study was to investigate the role of tactile feedback in individual finger actions and multi-finger interactions during constant force production tasks. We developed analytical techniques for the linear decomposition of the overall variance in the motor system in both online and offline control. We removed tactile feedback from the fingers and demonstrated that tactile sensors played a critical role in the online control of synergistic interactions between fingers. In contrast, the same sensors did not contribute to offline control. We also demonstrated that when tactile feedback was removed from the fingers, the combined motor output of individual fingers did not change while individual finger behaviors did. This finding supports the idea of hierarchical control where individual fingers at the lower level work together to stabilize the performance of combined motor output at the higher level.

Erbium-doped fiber ring laser with SMS modal interferometer for hydrogen sensing

NASA Astrophysics Data System (ADS)

Zhang, Ya-nan; Zhang, Lebin; Han, Bo; Peng, Huijie; Zhou, Tianmin; Lv, Ri-qing

2018-06-01

A hydrogen sensor based on erbium-doped fiber ring laser with modal interferometer is proposed. A single mode-multimode-single mode (SMS) modal interferometer structure coated with Pd/WO3 film is used as the sensing head, due to that it is easy to be fabricated and low cost. The sensing structure is inserted into an erbium-doped fiber ring laser in order to solve the problem of spectral confusion and improve the detection limit of the hydrogen sensor based on the SMS modal interferometer. The SMS sensing structure is acted as a fiber band-pass filter. When hydrogen concentration around the sensor is changed, it will induce the refractive index and strain variations of the Pd/WO3 film, and then shift the resonant spectrum of the SMS modal interferometer as well as the laser wavelength of the fiber ring laser. Therefore, the hydrogen concentration can be measured by monitoring the wavelength shift of the laser, which has high intensity and narrow full width half maximum. Experimental results demonstrate that the sensor has high sensitivity of 1.23 nm/%, low detection limit of 0.017%, good stability and excellent repeatability.

New properties of a fiber optic sensor in application of a composite fence for critical infrastructure protection

NASA Astrophysics Data System (ADS)

Zyczkowski, M.; Szustakowski, M.; Markowski, P.

2015-09-01

This paper presents a new solution of using the composite fence with a novel fiber optic modalmetric sensor integrated within its structure. The modalmetric sensor is based on changes in a transverse modal field which is generated at the output of a multimode fiber. By a spatial limitation of the transverse modal field observation to its fragment thereof, changes' transformation in the modal distribution into changes of the output signal amplitude is made. Due to a constant analysis of the structure output signal, detection of an external disorder is possible. Integration of optical fibers with the fence structure allows for an accurate reproduction of the fence movement onto the optical fiber by significantly improving sensitivity of the modalmetric fiber sensor structure.

A reflective hydrogen sensor based on fiber ring laser with PCF modal interferometer

NASA Astrophysics Data System (ADS)

Zhang, Ya-Nan; Zhang, Aozhuo; Han, Bo; E, Siyu

2018-06-01

A new hydrogen sensor based on a fiber ring laser with a photonic crystal fiber (PCF) modal interferometer is proposed. The reflective PCF modal interferometer, which is fabricated by forming two collapse regions on the two ends of PCF with a fusion discharge technique, is utilized as the sensing head and filter. Particularly, the Pd/WO3 hydrogen-sensitive thin film is coated on the PCF for hydrogen sensing. The combination of the fiber ring laser and PCF modal interferometer gives the sensor a high signal-to-noise ratio and an improved detection limit. Experimental results show that the sensing system can achieve a hydrogen sensitivity of 1.28 nm/%, a high signal-to-noise ratio (∼30 dB), a narrow full width at half maximum (∼0.05 nm), and low detection limit of 0.0133%.

Nonlinear effects of a modal domain optical fiber sensor in a vibration suppression control loop for a flexible structure

NASA Technical Reports Server (NTRS)

Lindner, D. K.; Zvonar, G. A.; Baumann, W. T.; Delos, P. L.

1993-01-01

Recently, a modal domain optical fiber sensor has been demonstrated as a sensor in a control system for vibration suppression of a flexible cantilevered beam. This sensor responds to strain through a mechanical attachment to the structure. Because this sensor is of the interferometric type, the output of the sensor has a sinusoidal nonlinearity. For small levels of strain, the sensor can be operated in its linear region. For large levels of strain, the detection electronics can be configured to count fringes. In both of these configurations, the sensor nonlinearity imposes some restrictions on the performance of the control system. In this paper we investigate the effects of these sensor nonlinearities on the control system, and identify the region of linear operation in terms of the optical fiber sensor parameters.

The electrophotonic silicon biosensor

NASA Astrophysics Data System (ADS)

Juan-Colás, José; Parkin, Alison; Dunn, Katherine E.; Scullion, Mark G.; Krauss, Thomas F.; Johnson, Steven D.

2016-09-01

The emergence of personalized and stratified medicine requires label-free, low-cost diagnostic technology capable of monitoring multiple disease biomarkers in parallel. Silicon photonic biosensors combine high-sensitivity analysis with scalable, low-cost manufacturing, but they tend to measure only a single biomarker and provide no information about their (bio)chemical activity. Here we introduce an electrochemical silicon photonic sensor capable of highly sensitive and multiparameter profiling of biomarkers. Our electrophotonic technology consists of microring resonators optimally n-doped to support high Q resonances alongside electrochemical processes in situ. The inclusion of electrochemical control enables site-selective immobilization of different biomolecules on individual microrings within a sensor array. The combination of photonic and electrochemical characterization also provides additional quantitative information and unique insight into chemical reactivity that is unavailable with photonic detection alone. By exploiting both the photonic and the electrical properties of silicon, the sensor opens new modalities for sensing on the microscale.

All-Fiber Laser Curvature Sensor Using an In-Fiber Modal Interferometer Based on a Double Clad Fiber and a Multimode Fiber Structure

PubMed Central

Durán-Sánchez, Manuel; Prieto-Cortés, Patricia; Salceda-Delgado, Guillermo; Castillo-Guzmán, Arturo A.; Selvas-Aguilar, Romeo; Ibarra-Escamilla, Baldemar; Kuzin, Evgeny A.

2017-01-01

An all-fiber curvature laser sensor by using a novel modal interference in-fiber structure is proposed and experimentally demonstrated. The in-fiber device, fabricated by fusion splicing of multimode fiber and double-clad fiber segments, is used as wavelength filter as well as the sensing element. By including a multimode fiber in an ordinary modal interference structure based on a double-clad fiber, the fringe visibility of the filter transmission spectrum is significantly increased. By using the modal interferometer as a curvature sensitive wavelength filter within a ring cavity erbium-doped fiber laser, the spectral quality factor Q is considerably increased. The results demonstrate the reliability of the proposed curvature laser sensor with advantages of robustness, ease of fabrication, low cost, repeatability on the fabrication process and simple operation. PMID:29182527

All-Fiber Laser Curvature Sensor Using an In-Fiber Modal Interferometer Based on a Double Clad Fiber and a Multimode Fiber Structure.

PubMed

Álvarez-Tamayo, Ricardo I; Durán-Sánchez, Manuel; Prieto-Cortés, Patricia; Salceda-Delgado, Guillermo; Castillo-Guzmán, Arturo A; Selvas-Aguilar, Romeo; Ibarra-Escamilla, Baldemar; Kuzin, Evgeny A

2017-11-28

An all-fiber curvature laser sensor by using a novel modal interference in-fiber structure is proposed and experimentally demonstrated. The in-fiber device, fabricated by fusion splicing of multimode fiber and double-clad fiber segments, is used as wavelength filter as well as the sensing element. By including a multimode fiber in an ordinary modal interference structure based on a double-clad fiber, the fringe visibility of the filter transmission spectrum is significantly increased. By using the modal interferometer as a curvature sensitive wavelength filter within a ring cavity erbium-doped fiber laser, the spectral quality factor Q is considerably increased. The results demonstrate the reliability of the proposed curvature laser sensor with advantages of robustness, ease of fabrication, low cost, repeatability on the fabrication process and simple operation.

Wearable sensors: modalities, challenges, and prospects.

PubMed

Heikenfeld, J; Jajack, A; Rogers, J; Gutruf, P; Tian, L; Pan, T; Li, R; Khine, M; Kim, J; Wang, J; Kim, J

2018-01-16

Wearable sensors have recently seen a large increase in both research and commercialization. However, success in wearable sensors has been a mix of both progress and setbacks. Most of commercial progress has been in smart adaptation of existing mechanical, electrical and optical methods of measuring the body. This adaptation has involved innovations in how to miniaturize sensing technologies, how to make them conformal and flexible, and in the development of companion software that increases the value of the measured data. However, chemical sensing modalities have experienced greater challenges in commercial adoption, especially for non-invasive chemical sensors. There have also been significant challenges in making significant fundamental improvements to existing mechanical, electrical, and optical sensing modalities, especially in improving their specificity of detection. Many of these challenges can be understood by appreciating the body's surface (skin) as more of an information barrier than as an information source. With a deeper understanding of the fundamental challenges faced for wearable sensors and of the state-of-the-art for wearable sensor technology, the roadmap becomes clearer for creating the next generation of innovations and breakthroughs.

Reconfigurable wireless monitoring systems for bridges: validation on the Yeondae Bridge

NASA Astrophysics Data System (ADS)

Kim, Junhee; Lynch, Jerome P.; Zonta, Daniele; Lee, Jong-Jae; Yun, Chung-Bang

2009-03-01

The installation of a structural monitoring system on a medium- to large-span bridge can be a challenging undertaking due to high system costs and time consuming installations. However, these historical challenges can be eliminated by using wireless sensors as the primary building block of a structural monitoring system. Wireless sensors are low-cost data acquisition nodes that utilize wireless communication to transfer data from the sensor to the data repository. Another advantageous characteristic of wireless sensors is their ability to be easily removed and reinstalled in another sensor location on the same structure; this installation modularity is highlighted in this study. Wireless sensor nodes designed for structural monitoring applications are installed on the 180 m long Yeondae Bridge (Korea) to measure the dynamic response of the bridge to controlled truck loading. To attain a high nodal density with a small number (20) of wireless sensors, the wireless sensor network is installed three times with each installation concentrating sensors in one portion of the bridge. Using forced and free vibration response data from the three installations, the modal properties of the bridge are accurately identified. Intentional nodal overlapping of the three different sensor installations allows mode shapes from each installation to be stitched together into global mode shapes. Specifically, modal properties of the Yeondae Bridge are derived off-line using frequency domain decomposition (FDD) modal analysis methods.

Autonomous collection of dynamically-cued multi-sensor imagery

NASA Astrophysics Data System (ADS)

Daniel, Brian; Wilson, Michael L.; Edelberg, Jason; Jensen, Mark; Johnson, Troy; Anderson, Scott

2011-05-01

The availability of imagery simultaneously collected from sensors of disparate modalities enhances an image analyst's situational awareness and expands the overall detection capability to a larger array of target classes. Dynamic cooperation between sensors is increasingly important for the collection of coincident data from multiple sensors either on the same or on different platforms suitable for UAV deployment. Of particular interest is autonomous collaboration between wide area survey detection, high-resolution inspection, and RF sensors that span large segments of the electromagnetic spectrum. The Naval Research Laboratory (NRL) in conjunction with the Space Dynamics Laboratory (SDL) is building sensors with such networked communications capability and is conducting field tests to demonstrate the feasibility of collaborative sensor data collection and exploitation. Example survey / detection sensors include: NuSAR (NRL Unmanned SAR), a UAV compatible synthetic aperture radar system; microHSI, an NRL developed lightweight hyper-spectral imager; RASAR (Real-time Autonomous SAR), a lightweight podded synthetic aperture radar; and N-WAPSS-16 (Nighttime Wide-Area Persistent Surveillance Sensor-16Mpix), a MWIR large array gimbaled system. From these sensors, detected target cues are automatically sent to the NRL/SDL developed EyePod, a high-resolution, narrow FOV EO/IR sensor, for target inspection. In addition to this cooperative data collection, EyePod's real-time, autonomous target tracking capabilities will be demonstrated. Preliminary results and target analysis will be presented.

NASA SMART Probe: Breast Cancer Application

NASA Technical Reports Server (NTRS)

Mah, Robert W.; Norvig, Peter (Technical Monitor)

2000-01-01

There is evidence in breast cancer and other malignancies that the physiologic environment within a tumor correlates with clinical outcome. We are developing a unique percutaneous Smart Probe to be used at the time of needle biopsy of the breast. The Smart Probe will simultaneously measure multiple physiologic parameters within a breast tumor. Direct and indirect measurements of tissue oxygen levels, blood flow, pH, and tissue fluid pressure will be analyzed in real-time. These parameters will be interpreted individually and collectively by innovative neural network techniques using advanced intelligent software. The goals are 1) develop a pecutaneous Smart Probe with multiple sensor modalities and applying advanced Information Technologies to provide real time diagnostic information of the tissue at tip of the probe, 2) test the percutaneous Smart Probe in women with benign and malignant breast masses who will be undergoing surgical biopsy, 3) correlate probe sensor data with benign and malignant status of breast masses, 4) determine whether the probe can detect physiologic differences within a breast tumor, and its margins, and in adjacent normal breast tissue, 5) correlate probe sensor data with known prognostic factors for breast caner, including tumor size, tumor grade, axillary lymph node metastases, estrogen receptor and progesterone receptor status.

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

NASA Astrophysics Data System (ADS)

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

2011-06-01

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

A distributed automatic target recognition system using multiple low resolution sensors

NASA Astrophysics Data System (ADS)

Yue, Zhanfeng; Lakshmi Narasimha, Pramod; Topiwala, Pankaj

2008-04-01

In this paper, we propose a multi-agent system which uses swarming techniques to perform high accuracy Automatic Target Recognition (ATR) in a distributed manner. The proposed system can co-operatively share the information from low-resolution images of different looks and use this information to perform high accuracy ATR. An advanced, multiple-agent Unmanned Aerial Vehicle (UAV) systems-based approach is proposed which integrates the processing capabilities, combines detection reporting with live video exchange, and swarm behavior modalities that dramatically surpass individual sensor system performance levels. We employ real-time block-based motion analysis and compensation scheme for efficient estimation and correction of camera jitter, global motion of the camera/scene and the effects of atmospheric turbulence. Our optimized Partition Weighted Sum (PWS) approach requires only bitshifts and additions, yet achieves a stunning 16X pixel resolution enhancement, which is moreover parallizable. We develop advanced, adaptive particle-filtering based algorithms to robustly track multiple mobile targets by adaptively changing the appearance model of the selected targets. The collaborative ATR system utilizes the homographies between the sensors induced by the ground plane to overlap the local observation with the received images from other UAVs. The motion of the UAVs distorts estimated homography frame to frame. A robust dynamic homography estimation algorithm is proposed to address this, by using the homography decomposition and the ground plane surface estimation.

Demonstration of UAV deployment and control of mobile wireless sensing networks for modal analysis of structures

NASA Astrophysics Data System (ADS)

Zhou, Hao; Hirose, Mitsuhito; Greenwood, William; Xiao, Yong; Lynch, Jerome; Zekkos, Dimitrios; Kamat, Vineet

2016-04-01

Unmanned aerial vehicles (UAVs) can serve as a powerful mobile sensing platform for assessing the health of civil infrastructure systems. To date, the majority of their uses have been dedicated to vision and laser-based spatial imaging using on-board cameras and LiDAR units, respectively. Comparatively less work has focused on integration of other sensing modalities relevant to structural monitoring applications. The overarching goal of this study is to explore the ability for UAVs to deploy a network of wireless sensors on structures for controlled vibration testing. The study develops a UAV platform with an integrated robotic gripper that can be used to install wireless sensors in structures, drop a heavy weight for the introduction of impact loads, and to uninstall wireless sensors for reinstallation elsewhere. A pose estimation algorithm is embedded in the UAV to estimate the location of the UAV during sensor placement and impact load introduction. The Martlet wireless sensor network architecture is integrated with the UAV to provide the UAV a mobile sensing capability. The UAV is programmed to command field deployed Martlets, aggregate and temporarily store data from the wireless sensor network, and to communicate data to a fixed base station on site. This study demonstrates the integrated UAV system using a simply supported beam in the lab with Martlet wireless sensors placed by the UAV and impact load testing performed. The study verifies the feasibility of the integrated UAV-wireless monitoring system architecture with accurate modal characteristics of the beam estimated by modal analysis.

Map as a Service: A Framework for Visualising and Maximising Information Return from Multi-Modal Wireless Sensor Networks

PubMed Central

Hammoudeh, Mohammad; Newman, Robert; Dennett, Christopher; Mount, Sarah; Aldabbas, Omar

2015-01-01

This paper presents a distributed information extraction and visualisation service, called the mapping service, for maximising information return from large-scale wireless sensor networks. Such a service would greatly simplify the production of higher-level, information-rich, representations suitable for informing other network services and the delivery of field information visualisations. The mapping service utilises a blend of inductive and deductive models to map sense data accurately using externally available knowledge. It utilises the special characteristics of the application domain to render visualisations in a map format that are a precise reflection of the concrete reality. This service is suitable for visualising an arbitrary number of sense modalities. It is capable of visualising from multiple independent types of the sense data to overcome the limitations of generating visualisations from a single type of sense modality. Furthermore, the mapping service responds dynamically to changes in the environmental conditions, which may affect the visualisation performance by continuously updating the application domain model in a distributed manner. Finally, a distributed self-adaptation function is proposed with the goal of saving more power and generating more accurate data visualisation. We conduct comprehensive experimentation to evaluate the performance of our mapping service and show that it achieves low communication overhead, produces maps of high fidelity, and further minimises the mapping predictive error dynamically through integrating the application domain model in the mapping service. PMID:26378539

Sensor chip and apparatus for tactile and/or flow sensing

NASA Technical Reports Server (NTRS)

Liu, Chang (Inventor); Chen, Jack (Inventor); Engel, Jonathan (Inventor)

2008-01-01

A sensor chip, comprising a flexible, polymer-based substrate, and at least one microfabricated sensor disposed on the substrate and including a conductive element. The at least one sensor comprises at least one of a tactile sensor and a flow sensor. Other embodiments of the present invention include sensors and/or multi-modal sensor nodes.

Sensor chip and apparatus for tactile and/or flow sensing

NASA Technical Reports Server (NTRS)

Liu, Chang (Inventor); Chen, Jack (Inventor); Engel, Jonathan (Inventor)

2009-01-01

A sensor chip, comprising a flexible, polymer-based substrate, and at least one microfabricated sensor disposed on the substrate and including a conductive element. The at least one sensor comprises at least one of a tactile sensor and a flow sensor. Other embodiments of the present invention include sensors and/or multi-modal sensor nodes.

Response analysis of holography-based modal wavefront sensor.

PubMed

Dong, Shihao; Haist, Tobias; Osten, Wolfgang; Ruppel, Thomas; Sawodny, Oliver

2012-03-20

The crosstalk problem of holography-based modal wavefront sensing (HMWS) becomes more severe with increasing aberration. In this paper, crosstalk effects on the sensor response are analyzed statistically for typical aberrations due to atmospheric turbulence. For specific turbulence strength, we optimized the sensor by adjusting the detector radius and the encoded phase bias for each Zernike mode. Calibrated response curves of low-order Zernike modes were further utilized to improve the sensor accuracy. The simulation results validated our strategy. The number of iterations for obtaining a residual RMS wavefront error of 0.1λ is reduced from 18 to 3. © 2012 Optical Society of America

Statistical analysis of modal properties of a cable-stayed bridge through long-term structural health monitoring with wireless smart sensor networks

NASA Astrophysics Data System (ADS)

Asadollahi, Parisa; Li, Jian

2016-04-01

Understanding the dynamic behavior of complex structures such as long-span bridges requires dense deployment of sensors. Traditional wired sensor systems are generally expensive and time-consuming to install due to cabling. With wireless communication and on-board computation capabilities, wireless smart sensor networks have the advantages of being low cost, easy to deploy and maintain and therefore facilitate dense instrumentation for structural health monitoring. A long-term monitoring project was recently carried out for a cable-stayed bridge in South Korea with a dense array of 113 smart sensors, which feature the world's largest wireless smart sensor network for civil structural monitoring. This paper presents a comprehensive statistical analysis of the modal properties including natural frequencies, damping ratios and mode shapes of the monitored cable-stayed bridge. Data analyzed in this paper is composed of structural vibration signals monitored during a 12-month period under ambient excitations. The correlation between environmental temperature and the modal frequencies is also investigated. The results showed the long-term statistical structural behavior of the bridge, which serves as the basis for Bayesian statistical updating for the numerical model.

The effect of time synchronization of wireless sensors on the modal analysis of structures

NASA Astrophysics Data System (ADS)

Krishnamurthy, V.; Fowler, K.; Sazonov, E.

2008-10-01

Driven by the need to reduce the installation cost and maintenance cost of structural health monitoring (SHM) systems, wireless sensor networks (WSNs) are becoming increasingly popular. Perfect time synchronization amongst the wireless sensors is a key factor enabling the use of low-cost, low-power WSNs for structural health monitoring applications based on output-only modal analysis of structures. In this paper we present a theoretical framework for analysis of the impact created by time delays in the measured system response on the reconstruction of mode shapes using the popular frequency domain decomposition (FDD) technique. This methodology directly estimates the change in mode shape values based on sensor synchronicity. We confirm the proposed theoretical model by experimental validation in modal identification experiments performed on an aluminum beam. The experimental validation was performed using a wireless intelligent sensor and actuator network (WISAN) which allows for close time synchronization between sensors (0.6-10 µs in the tested configuration) and guarantees lossless data delivery under normal conditions. The experimental results closely match theoretical predictions and show that even very small delays in output response impact the mode shapes.

Optimal sensor placement for modal testing on wind turbines

NASA Astrophysics Data System (ADS)

Schulze, Andreas; Zierath, János; Rosenow, Sven-Erik; Bockhahn, Reik; Rachholz, Roman; Woernle, Christoph

2016-09-01

The mechanical design of wind turbines requires a profound understanding of the dynamic behaviour. Even though highly detailed simulation models are already in use to support wind turbine design, modal testing on a real prototype is irreplaceable to identify site-specific conditions such as the stiffness of the tower foundation. Correct identification of the mode shapes of a complex mechanical structure much depends on the placement of the sensors. For operational modal analysis of a 3 MW wind turbine with a 120 m rotor on a 100 m tower developed by W2E Wind to Energy, algorithms for optimal placement of acceleration sensors are applied. The mode shapes used for the optimisation are calculated by means of a detailed flexible multibody model of the wind turbine. Among the three algorithms in this study, the genetic algorithm with weighted off-diagonal criterion yields the sensor configuration with the highest quality. The ongoing measurements on the prototype will be the basis for the development of optimised wind turbine designs.

Ground Vibration Test Planning and Pre-Test Analysis for the X-33 Vehicle

NASA Technical Reports Server (NTRS)

Bedrossian, Herand; Tinker, Michael L.; Hidalgo, Homero

2000-01-01

This paper describes the results of the modal test planning and the pre-test analysis for the X-33 vehicle. The pre-test analysis included the selection of the target modes, selection of the sensor and shaker locations and the development of an accurate Test Analysis Model (TAM). For target mode selection, four techniques were considered, one based on the Modal Cost technique, one based on Balanced Singular Value technique, a technique known as the Root Sum Squared (RSS) method, and a Modal Kinetic Energy (MKE) approach. For selecting sensor locations, four techniques were also considered; one based on the Weighted Average Kinetic Energy (WAKE), one based on Guyan Reduction (GR), one emphasizing engineering judgment, and one based on an optimum sensor selection technique using Genetic Algorithm (GA) search technique combined with a criteria based on Hankel Singular Values (HSV's). For selecting shaker locations, four techniques were also considered; one based on the Weighted Average Driving Point Residue (WADPR), one based on engineering judgment and accessibility considerations, a frequency response method, and an optimum shaker location selection based on a GA search technique combined with a criteria based on HSV's. To evaluate the effectiveness of the proposed sensor and shaker locations for exciting the target modes, extensive numerical simulations were performed. Multivariate Mode Indicator Function (MMIF) was used to evaluate the effectiveness of each sensor & shaker set with respect to modal parameter identification. Several TAM reduction techniques were considered including, Guyan, IRS, Modal, and Hybrid. Based on a pre-test cross-orthogonality checks using various reduction techniques, a Hybrid TAM reduction technique was selected and was used for all three vehicle fuel level configurations.

A low-power multi-modal body sensor network with application to epileptic seizure monitoring.

PubMed

Altini, Marco; Del Din, Silvia; Patel, Shyamal; Schachter, Steven; Penders, Julien; Bonato, Paolo

2011-01-01

Monitoring patients' physiological signals during their daily activities in the home environment is one of the challenge of the health care. New ultra-low-power wireless technologies could help to achieve this goal. In this paper we present a low-power, multi-modal, wearable sensor platform for the simultaneous recording of activity and physiological data. First we provide a description of the wearable sensor platform, and its characteristics with respect to power consumption. Second we present the preliminary results of the comparison between our sensors and a reference system, on healthy subjects, to test the reliability of the detected physiological (electrocardiogram and respiration) and electromyography signals.

Active control for vibration suppression in a flexible beam using a modal domain optical fiber sensor

NASA Technical Reports Server (NTRS)

Cox, D. E.; Lindner, D. K.

1991-01-01

An account is given of the use of a modal-domain (MD) fiber-optic sensor as an active control system component for vibration suppression, whose output is proportional to the integral of the axial strain along the optical fiber. When an MD sensor is attached to, or embedded in, a flexible structure, it senses the strain in the structure along its gage length. On the basis of the present integration of the sensor model into a flexible-structure model, it becomes possible to design a control system with a dynamic compensator which adds damping to the low-order modes of the flexible structure. This modeling procedure has been experimentally validated.

Visualization of Time-Series Sensor Data to Inform the Design of Just-In-Time Adaptive Stress Interventions.

PubMed

Sharmin, Moushumi; Raij, Andrew; Epstien, David; Nahum-Shani, Inbal; Beck, J Gayle; Vhaduri, Sudip; Preston, Kenzie; Kumar, Santosh

2015-09-01

We investigate needs, challenges, and opportunities in visualizing time-series sensor data on stress to inform the design of just-in-time adaptive interventions (JITAIs). We identify seven key challenges: massive volume and variety of data, complexity in identifying stressors, scalability of space, multifaceted relationship between stress and time, a need for representation at multiple granularities, interperson variability, and limited understanding of JITAI design requirements due to its novelty. We propose four new visualizations based on one million minutes of sensor data (n=70). We evaluate our visualizations with stress researchers (n=6) to gain first insights into its usability and usefulness in JITAI design. Our results indicate that spatio-temporal visualizations help identify and explain between- and within-person variability in stress patterns and contextual visualizations enable decisions regarding the timing, content, and modality of intervention. Interestingly, a granular representation is considered informative but noise-prone; an abstract representation is the preferred starting point for designing JITAIs.

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

Chandra, Anirban; Patra, Puneet Kumar; Bhattacharya, Baidurya, E-mail: baidurya@civil.iitkgp.ernet.in

A nanomechanical resonator based sensor works by detecting small changes in the natural frequency of the device in presence of external agents. In this study, we address the length and the temperature-dependent sensitivity of precompressed armchair Boron-Nitride nanotubes towards their use as sensors. The vibrational data, obtained using molecular dynamics simulations, are analyzed for frequency content through the fast Fourier transformation. As the temperature of the system rises, the vibrational spectrum becomes noisy, and the modal frequencies show a red-shift irrespective of the length of the nanotube, suggesting that the nanotube based sensors calibrated at a particular temperature may notmore » function desirably at other temperatures. Temperature-induced noise becomes increasingly pronounced with the decrease in the length of the nanotube. For the shorter nanotube at higher temperatures, we observe multiple closely spaced peaks near the natural frequency, that create a masking effect and reduce the sensitivity of detection. However, longer nanotubes do not show these spurious frequencies, and are considerably more sensitive than the shorter ones.« less

Visualization of Time-Series Sensor Data to Inform the Design of Just-In-Time Adaptive Stress Interventions

PubMed Central

Sharmin, Moushumi; Raij, Andrew; Epstien, David; Nahum-Shani, Inbal; Beck, J. Gayle; Vhaduri, Sudip; Preston, Kenzie; Kumar, Santosh

2015-01-01

We investigate needs, challenges, and opportunities in visualizing time-series sensor data on stress to inform the design of just-in-time adaptive interventions (JITAIs). We identify seven key challenges: massive volume and variety of data, complexity in identifying stressors, scalability of space, multifaceted relationship between stress and time, a need for representation at multiple granularities, interperson variability, and limited understanding of JITAI design requirements due to its novelty. We propose four new visualizations based on one million minutes of sensor data (n=70). We evaluate our visualizations with stress researchers (n=6) to gain first insights into its usability and usefulness in JITAI design. Our results indicate that spatio-temporal visualizations help identify and explain between- and within-person variability in stress patterns and contextual visualizations enable decisions regarding the timing, content, and modality of intervention. Interestingly, a granular representation is considered informative but noise-prone; an abstract representation is the preferred starting point for designing JITAIs. PMID:26539566

Spatially distributed fiber sensor with dual processed outputs

NASA Astrophysics Data System (ADS)

Xu, X.; Spillman, William B., Jr.; Claus, Richard O.; Meissner, K. E.; Chen, K.

2005-05-01

Given the rapid aging of the world"s population, improvements in technology for automation of patient care and documentation are badly needed. We have previously demonstrated a 'smart bed' that can non-intrusively monitor a patient in bed and determine a patient's respiration, heart rate and movement without intrusive or restrictive medical measurements. This is an application of spatially distributed integrating fiber optic sensors. The basic concept is that any patient movement that also moves an optical fiber within a specified area will produce a change in the optical signal. Two modal modulation approaches were considered, a statistical mode (STM) sensor and a high order mode excitation (HOME) sensor. The present design includes an STM sensor combined with a HOME sensor, using both modal modulation approaches. A special lens system allows only the high order modes of the optical fiber to be excited and coupled into the sensor. For handling output from the dual STM-HOME sensor, computer processing methods are discussed that offer comprehensive perturbation analysis for more reliable patient monitoring.

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.

Sensing and data classification for a robotic meteorite search

NASA Astrophysics Data System (ADS)

Pedersen, Liam; Apostolopoulos, Dimi; Whittaker, William L.; Benedix, Gretchen; Rousch, Ted

1999-01-01

Upcoming missions to Mars and the mon call for highly autonomous robots with capability to perform intra-site exploration, reason about their scientific finds, and perform comprehensive on-board analysis of data collected. An ideal case for testing such technologies and robot capabilities is the robotic search for Antarctic meteorites. The successful identification and classification of meteorites depends on sensing modalities and intelligent evaluation of acquired data. Data from color imagery and spectroscopic measurements are used to identify terrestrial rocks and distinguish them from meteorites. However, because of the large number of rocks and the high cost and delay of using some of the sensors, it is necessary to eliminate as many meteorite candidates as possible using cheap long range sensors, such as color cameras. More resource consuming sensor will be held in reserve for the more promising samples only. Bayes networks are used as the formalism for incrementally combing data from multiple sources in a statistically rigorous manner. Furthermore, they can be used to infer the utility of further sensor readings given currently known data. This information, along with cost estimates, in necessary for the sensing system to rationally schedule further sensor reading sand deployments. This paper address issues associated with sensor selection and implementation of an architecture for automatic identification of rocks and meteorites from a mobile robot.

Fusing Sensor Paradigms to Acquire Chemical Information: An Integrative Role for Smart Biopolymeric Hydrogels

PubMed Central

Kim, Eunkyoung; Liu, Yi; Ben-Yoav, Hadar; Winkler, Thomas E.; Yan, Kun; Shi, Xiaowen; Shen, Jana; Kelly, Deanna L.; Ghodssi, Reza; Bentley, William E.

2017-01-01

The Information Age transformed our lives but it has had surprisingly little impact on the way chemical information (e.g., from our biological world) is acquired, analyzed and communicated. Sensor systems are poised to change this situation by providing rapid access to chemical information. This access will be enabled by technological advances from various fields: biology enables the synthesis, design and discovery of molecular recognition elements as well as the generation of cell-based signal processors; physics and chemistry are providing nano-components that facilitate the transmission and transduction of signals rich with chemical information; microfabrication is yielding sensors capable of receiving these signals through various modalities; and signal processing analysis enhances the extraction of chemical information. The authors contend that integral to the development of functional sensor systems will be materials that (i) enable the integrative and hierarchical assembly of various sensing components (for chemical recognition and signal transduction) and (ii) facilitate meaningful communication across modalities. It is suggested that stimuli-responsive self-assembling biopolymers can perform such integrative functions, and redox provides modality-spanning communication capabilities. Recent progress toward the development of electrochemical sensors to manage schizophrenia is used to illustrate the opportunities and challenges for enlisting sensors for chemical information processing. PMID:27616350

Quasi-modal vibration control by means of active control bearings

NASA Technical Reports Server (NTRS)

Nonami, K.; Fleming, D. P.

1986-01-01

This paper investigates a design method of an active control bearing system with only velocity feedback. The study provides a new quasi-modal control method for a control system design of an active control bearing system in which feedback coefficients are determined on the basis of a modal analysis. Although the number of sensors and actuators is small, this quasi-modal control method produces a control effect close to an ideal modal control.

Identification of multi-modal plasma responses to applied magnetic perturbations using the plasma reluctance

DOE PAGES

Logan, Nikolas C.; Paz-Soldan, Carlos; Park, Jong-Kyu; ...

2016-05-03

Using the plasma reluctance, the Ideal Perturbed Equilibrium Code is able to efficiently identify the structure of multi-modal magnetic plasma response measurements and the corresponding impact on plasma performance in the DIII-D tokamak. Recent experiments demonstrated that multiple kink modes of comparable amplitudes can be driven by applied nonaxisymmetric fields with toroidal mode number n = 2. This multi-modal response is in good agreement with ideal magnetohydrodynamic models, but detailed decompositions presented here show that the mode structures are not fully described by either the least stable modes or the resonant plasma response. This paper identifies the measured response fieldsmore » as the first eigenmodes of the plasma reluctance, enabling clear diagnosis of the plasma modes and their impact on performance from external sensors. The reluctance shows, for example, how very stable modes compose a significant portion of the multi-modal plasma response field and that these stable modes drive significant resonant current. Finally, this work is an overview of the first experimental applications using the reluctance to interpret the measured response and relate it to multifaceted physics, aimed towards providing the foundation of understanding needed to optimize nonaxisymmetric fields for independent control of stability and transport.« less

Computational Intelligence Techniques for Tactile Sensing Systems

PubMed Central

Gastaldo, Paolo; Pinna, Luigi; Seminara, Lucia; Valle, Maurizio; Zunino, Rodolfo

2014-01-01

Tactile sensing helps robots interact with humans and objects effectively in real environments. Piezoelectric polymer sensors provide the functional building blocks of the robotic electronic skin, mainly thanks to their flexibility and suitability for detecting dynamic contact events and for recognizing the touch modality. The paper focuses on the ability of tactile sensing systems to support the challenging recognition of certain qualities/modalities of touch. The research applies novel computational intelligence techniques and a tensor-based approach for the classification of touch modalities; its main results consist in providing a procedure to enhance system generalization ability and architecture for multi-class recognition applications. An experimental campaign involving 70 participants using three different modalities in touching the upper surface of the sensor array was conducted, and confirmed the validity of the approach. PMID:24949646

Computational intelligence techniques for tactile sensing systems.

PubMed

Gastaldo, Paolo; Pinna, Luigi; Seminara, Lucia; Valle, Maurizio; Zunino, Rodolfo

2014-06-19

Tactile sensing helps robots interact with humans and objects effectively in real environments. Piezoelectric polymer sensors provide the functional building blocks of the robotic electronic skin, mainly thanks to their flexibility and suitability for detecting dynamic contact events and for recognizing the touch modality. The paper focuses on the ability of tactile sensing systems to support the challenging recognition of certain qualities/modalities of touch. The research applies novel computational intelligence techniques and a tensor-based approach for the classification of touch modalities; its main results consist in providing a procedure to enhance system generalization ability and architecture for multi-class recognition applications. An experimental campaign involving 70 participants using three different modalities in touching the upper surface of the sensor array was conducted, and confirmed the validity of the approach.

A FBG pulse wave demodulation method based on PCF modal interference filter

NASA Astrophysics Data System (ADS)

Zhang, Cheng; Xu, Shan; Shen, Ziqi; Zhao, Junfa; Miao, Changyun; Bai, Hua

2016-10-01

Fiber optic sensor embedded in textiles has been a new direction of researching smart wearable technology. Pulse signal which is generated by heart beat contains vast amounts of physio-pathological information about the cardiovascular system. Therefore, the research for textile-based fiber optic sensor which can detect pulse wave has far-reaching effects on early discovery and timely treatment of cardiovascular diseases. A novel wavelength demodulation method based on photonic crystal fiber (PCF) modal interference filter is proposed for the purpose of developing FBG pulse wave sensing system embedded in smart clothing. The mechanism of the PCF modal interference and the principle of wavelength demodulation based on In-line Mach-Zehnder interferometer (In-line MZI) are analyzed in theory. The fabricated PCF modal interferometer has the advantages of good repeatability and low temperature sensitivity of 3.5pm/°C from 25°C to 60°C. The designed demodulation system can achieve linear demodulation in the range of 2nm, with the wavelength resolution of 2.2pm and the wavelength sensitivity of 0.055nm-1. The actual experiments' result indicates that the pulse wave can be well detected by this demodulation method, which is in accordance with the commercial demodulation instrument (SM130) and more sensitive than the traditional piezoelectric pulse sensor. This demodulation method provides important references for the research of smart clothing based on fiber grating sensor embedded in textiles and accelerates the developments of wearable fiber optic sensors technology.

Distributed pheromone-based swarming control of unmanned air and ground vehicles for RSTA

NASA Astrophysics Data System (ADS)

Sauter, John A.; Mathews, Robert S.; Yinger, Andrew; Robinson, Joshua S.; Moody, John; Riddle, Stephanie

2008-04-01

The use of unmanned vehicles in Reconnaissance, Surveillance, and Target Acquisition (RSTA) applications has received considerable attention recently. Cooperating land and air vehicles can support multiple sensor modalities providing pervasive and ubiquitous broad area sensor coverage. However coordination of multiple air and land vehicles serving different mission objectives in a dynamic and complex environment is a challenging problem. Swarm intelligence algorithms, inspired by the mechanisms used in natural systems to coordinate the activities of many entities provide a promising alternative to traditional command and control approaches. This paper describes recent advances in a fully distributed digital pheromone algorithm that has demonstrated its effectiveness in managing the complexity of swarming unmanned systems. The results of a recent demonstration at NASA's Wallops Island of multiple Aerosonde Unmanned Air Vehicles (UAVs) and Pioneer Unmanned Ground Vehicles (UGVs) cooperating in a coordinated RSTA application are discussed. The vehicles were autonomously controlled by the onboard digital pheromone responding to the needs of the automatic target recognition algorithms. UAVs and UGVs controlled by the same pheromone algorithm self-organized to perform total area surveillance, automatic target detection, sensor cueing, and automatic target recognition with no central processing or control and minimal operator input. Complete autonomy adds several safety and fault tolerance requirements which were integrated into the basic pheromone framework. The adaptive algorithms demonstrated the ability to handle some unplanned hardware failures during the demonstration without any human intervention. The paper describes lessons learned and the next steps for this promising technology.

Ca2+-sensors and ROS-GC: interlocked sensory transduction elements: a review

PubMed Central

Sharma, Rameshwar K.; Duda, Teresa

2012-01-01

From its initial discovery that ROS-GC membrane guanylate cyclase is a mono-modal Ca2+-transduction system linked exclusively with the photo-transduction machinery to the successive finding that it embodies a remarkable bimodal Ca2+ signaling device, its widened transduction role in the general signaling mechanisms of the sensory neuron cells was envisioned. A theoretical concept was proposed where Ca2+-modulates ROS-GC through its generated cyclic GMP via a nearby cyclic nucleotide gated channel and creates a hyper- or depolarized sate in the neuron membrane (Ca2+ Binding Proteins 1:1, 7–11, 2006). The generated electric potential then becomes a mode of transmission of the parent [Ca2+]i signal. Ca2+ and ROS-GC are interlocked messengers in multiple sensory transduction mechanisms. This comprehensive review discusses the developmental stages to the present status of this concept and demonstrates how neuronal Ca2+-sensor (NCS) proteins are the interconnected elements of this elegant ROS-GC transduction system. The focus is on the dynamism of the structural composition of this system, and how it accommodates selectivity and elasticity for the Ca2+ signals to perform multiple tasks linked with the SENSES of vision, smell, and possibly of taste and the pineal gland. An intriguing illustration is provided for the Ca2+ sensor GCAP1 which displays its remarkable ability for its flexibility in function from being a photoreceptor sensor to an odorant receptor sensor. In doing so it reverses its function from an inhibitor of ROS-GC to the stimulator of ONE-GC membrane guanylate cyclase. PMID:22509149

NASA Tech Briefs, April 2009

NASA Technical Reports Server (NTRS)

2009-01-01

Topics covered include: Direct-Solve Image-Based Wavefront Sensing; Use of UV Sources for Detection and Identification of Explosives; Using Fluorescent Viruses for Detecting Bacteria in Water; Gradiometer Using Middle Loops as Sensing Elements in a Low-Field SQUID MRI System; Volcano Monitor: Autonomous Triggering of In-Situ Sensors; Wireless Fluid-Level Sensors for Harsh Environments; Interference-Detection Module in a Digital Radar Receiver; Modal Vibration Analysis of Large Castings; Structural/Radiation-Shielding Epoxies; Integrated Multilayer Insulation; Apparatus for Screening Multiple Oxygen-Reduction Catalysts; Determining Aliasing in Isolated Signal Conditioning Modules; Composite Bipolar Plate for Unitized Fuel Cell/Electrolyzer Systems; Spectrum Analyzers Incorporating Tunable WGM Resonators; Quantum-Well Thermophotovoltaic Cells; Bounded-Angle Iterative Decoding of LDPC Codes; Conversion from Tree to Graph Representation of Requirements; Parallel Hybrid Vehicle Optimal Storage System; and Anaerobic Digestion in a Flooded Densified Leachbed.

Characterising a holographic modal phase mask for the detection of ocular aberrations

NASA Astrophysics Data System (ADS)

Corbett, A. D.; Leyva, D. Gil; Diaz-Santana, L.; Wilkinson, T. D.; Zhong, J. J.

2005-12-01

The accurate measurement of the double-pass ocular wave front has been shown to have a broad range of applications from LASIK surgery to adaptively corrected retinal imaging. The ocular wave front can be accurately described by a small number of Zernike circle polynomials. The modal wave front sensor was first proposed by Neil et al. and allows the coefficients of the individual Zernike modes to be measured directly. Typically the aberrations measured with the modal sensor are smaller than those seen in the ocular wave front. In this work, we investigated a technique for adapting a modal phase mask for the sensing of the ocular wave front. This involved extending the dynamic range of the sensor by increasing the pinhole size to 2.4mm and optimising the mask bias to 0.75λ. This was found to decrease the RMS error by up to a factor of three for eye-like aberrations with amplitudes up to 0.2μm. For aberrations taken from a sample of real-eye measurements a 20% decrease in the RMS error was observed.

Synthesizing spatiotemporally sparse smartphone sensor data for bridge modal identification

NASA Astrophysics Data System (ADS)

Ozer, Ekin; Feng, Maria Q.

2016-08-01

Smartphones as vibration measurement instruments form a large-scale, citizen-induced, and mobile wireless sensor network (WSN) for system identification and structural health monitoring (SHM) applications. Crowdsourcing-based SHM is possible with a decentralized system granting citizens with operational responsibility and control. Yet, citizen initiatives introduce device mobility, drastically changing SHM results due to uncertainties in the time and the space domains. This paper proposes a modal identification strategy that fuses spatiotemporally sparse SHM data collected by smartphone-based WSNs. Multichannel data sampled with the time and the space independence is used to compose the modal identification parameters such as frequencies and mode shapes. Structural response time history can be gathered by smartphone accelerometers and converted into Fourier spectra by the processor units. Timestamp, data length, energy to power conversion address temporal variation, whereas spatial uncertainties are reduced by geolocation services or determining node identity via QR code labels. Then, parameters collected from each distributed network component can be extended to global behavior to deduce modal parameters without the need of a centralized and synchronous data acquisition system. The proposed method is tested on a pedestrian bridge and compared with a conventional reference monitoring system. The results show that the spatiotemporally sparse mobile WSN data can be used to infer modal parameters despite non-overlapping sensor operation schedule.

Highly sensitive force sensor based on balloon-like interferometer

NASA Astrophysics Data System (ADS)

Wu, Yue; Xiao, Shiying; Xu, Yao; Shen, Ya; Jiang, Youchao; Jin, Wenxing; Yang, Yuguang; Jian, Shuisheng

2018-07-01

An all-fiber highly sensitive force sensor based on modal interferometer has been presented and demonstrated. The single-mode fiber (SMF) with coating stripped is designed into a balloon-like shape to form a modal interferometer. Due to the bent SMF, the interference occurs between the core mode and cladding modes. With variation of the force applied to the balloon-like interferometer, the bending diameter changes, which caused the wavelength shift of the modal interference. Thus the measurement of the force variation can be achieved by monitoring the wavelength shift. The performances of the interferometer with different bending diameter are experimentally investigated, and the maximum force sensitivity of 24.9 pm/ μ N can be achieved with the bending diameter 14 mm ranging from 0 μ N to 1464.12 μ N. Furthermore, the proposed fiber sensor exhibits the advantages of easy fabrication and low cost, making it a suitable candidate in the optical fiber sensing field.

Multiparameter fiber optic sensing system for monitoring enhanced geothermal systems

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

Challener, William A

2014-12-04

The goal of this project was to design, fabricate and test an optical fiber cable which supports multiple sensing modalities for measurements in the harsh environment of enhanced geothermal systems. To accomplish this task, optical fiber was tested at both high temperatures and strains for mechanical integrity, and in the presence of hydrogen for resistance to darkening. Both single mode (SM) and multimode (MM) commercially available optical fiber were identified and selected for the cable based on the results of these tests. The cable was designed and fabricated using a tube-within-tube construction containing two MM fibers and one SM fiber,more » and without supporting gel that is not suitable for high temperature environments. Commercial fiber optic sensing instruments using Raman DTS (distributed temperature sensing), Brillouin DTSS (distributed temperature and strain sensing), and Raleigh COTDR (coherent optical time domain reflectometry) were selected for field testing. A microelectromechanical systems (MEMS) pressure sensor was designed, fabricated, packaged, and calibrated for high pressure measurements at high temperatures and spliced to the cable. A fiber Bragg grating (FBG) temperature sensor was also spliced to the cable. A geothermal well was selected and its temperature and pressure were logged. The cable was then deployed in the well in two separate field tests and measurements were made on these different sensing modalities. Raman DTS measurements were found to be accurate to ±5°C, even with some residual hydrogen darkening. Brillouin DTSS measurements were in good agreement with the Raman results. The Rayleigh COTDR instrument was able to detect some acoustic signatures, but was generally disappointing. The FBG sensor was used to determine the effects of hydrogen darkening, but drift over time made it unreliable as a temperature or pressure sensor. The MEMS sensor was found to be highly stable and accurate to better than its 0.1% calibration.« less

Computer Based Behavioral Biometric Authentication via Multi-Modal Fusion

DTIC Science & Technology

2013-03-01

the decisions made by each individual modality. Fusion of features is the simple concatenation of feature vectors from multiple modalities to be...of Features BayesNet MDL 330 LibSVM PCA 80 J48 Wrapper Evaluator 11 3.5.3 Ensemble Based Decision Level Fusion. In ensemble learning multiple ...The high fusion percentages validate our hypothesis that by combining features from multiple modalities, classification accuracy can be improved. As

Displacement sensing based on modal interference in polymer optical fibers with partially applied strain

NASA Astrophysics Data System (ADS)

Mizuno, Yosuke; Hagiwara, Sonoko; Kawa, Tomohito; Lee, Heeyoung; Nakamura, Kentaro

2018-05-01

Strain sensing based on modal interference in multimode fibers (MMFs) has been extensively studied, but no experimental or theoretical reports have been given as to how the system works when strain is applied not to the whole MMF but only to part of the MMF. Here, using a perfluorinated graded-index polymer optical fiber as the MMF, we investigate the strain sensing characteristics of this type of sensor when strain is partially applied to fiber sections with different lengths. The strain sensitivity dependence on the length of the strained section reveals that this strain sensor actually behaves as a displacement sensor.

Rapid impact testing for quantitative assessment of large populations of bridges

NASA Astrophysics Data System (ADS)

Zhou, Yun; Prader, John; DeVitis, John; Deal, Adrienne; Zhang, Jian; Moon, Franklin; Aktan, A. Emin

2011-04-01

Although the widely acknowledged shortcomings of visual inspection have fueled significant advances in the areas of non-destructive evaluation and structural health monitoring (SHM) over the last several decades, the actual practice of bridge assessment has remained largely unchanged. The authors believe the lack of adoption, especially of SHM technologies, is related to the 'single structure' scenarios that drive most research. To overcome this, the authors have developed a concept for a rapid single-input, multiple-output (SIMO) impact testing device that will be capable of capturing modal parameters and estimating flexibility/deflection basins of common highway bridges during routine inspections. The device is composed of a trailer-mounted impact source (capable of delivering a 50 kip impact) and retractable sensor arms, and will be controlled by an automated data acquisition, processing and modal parameter estimation software. The research presented in this paper covers (a) the theoretical basis for SISO, SIMO and MIMO impact testing to estimate flexibility, (b) proof of concept numerical studies using a finite element model, and (c) a pilot implementation on an operating highway bridge. Results indicate that the proposed approach can estimate modal flexibility within a few percent of static flexibility; however, the estimated modal flexibility matrix is only reliable for the substructures associated with the various SIMO tests. To overcome this shortcoming, a modal 'stitching' approach for substructure integration to estimate the full Eigen vector matrix is developed, and preliminary results of these methods are also presented.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Multiview echocardiography fusion using an electromagnetic tracking system.

PubMed

Punithakumar, Kumaradevan; Hareendranathan, Abhilash R; Paakkanen, Riitta; Khan, Nehan; Noga, Michelle; Boulanger, Pierre; Becher, Harald

2016-08-01

Three-dimensional ultrasound is an emerging modality for the assessment of complex cardiac anatomy and function. The advantages of this modality include lack of ionizing radiation, portability, low cost, and high temporal resolution. Major limitations include limited field-of-view, reliance on frequently limited acoustic windows, and poor signal to noise ratio. This study proposes a novel approach to combine multiple views into a single image using an electromagnetic tracking system in order to improve the field-of-view. The novel method has several advantages: 1) it does not rely on image information for alignment, and therefore, the method does not require image overlap; 2) the alignment accuracy of the proposed approach is not affected by any poor image quality as in the case of image registration based approaches; 3) in contrast to previous optical tracking based system, the proposed approach does not suffer from line-of-sight limitation; and 4) it does not require any initial calibration. In this pilot project, we were able to show that using a heart phantom, our method can fuse multiple echocardiographic images and improve the field-of view. Quantitative evaluations showed that the proposed method yielded a nearly optimal alignment of image data sets in three-dimensional space. The proposed method demonstrates the electromagnetic system can be used for the fusion of multiple echocardiography images with a seamless integration of sensors to the transducer.

Time-Of-Flight Camera, Optical Tracker and Computed Tomography in Pairwise Data Registration.

PubMed

Pycinski, Bartlomiej; Czajkowska, Joanna; Badura, Pawel; Juszczyk, Jan; Pietka, Ewa

2016-01-01

A growing number of medical applications, including minimal invasive surgery, depends on multi-modal or multi-sensors data processing. Fast and accurate 3D scene analysis, comprising data registration, seems to be crucial for the development of computer aided diagnosis and therapy. The advancement of surface tracking system based on optical trackers already plays an important role in surgical procedures planning. However, new modalities, like the time-of-flight (ToF) sensors, widely explored in non-medical fields are powerful and have the potential to become a part of computer aided surgery set-up. Connection of different acquisition systems promises to provide a valuable support for operating room procedures. Therefore, the detailed analysis of the accuracy of such multi-sensors positioning systems is needed. We present the system combining pre-operative CT series with intra-operative ToF-sensor and optical tracker point clouds. The methodology contains: optical sensor set-up and the ToF-camera calibration procedures, data pre-processing algorithms, and registration technique. The data pre-processing yields a surface, in case of CT, and point clouds for ToF-sensor and marker-driven optical tracker representation of an object of interest. An applied registration technique is based on Iterative Closest Point algorithm. The experiments validate the registration of each pair of modalities/sensors involving phantoms of four various human organs in terms of Hausdorff distance and mean absolute distance metrics. The best surface alignment was obtained for CT and optical tracker combination, whereas the worst for experiments involving ToF-camera. The obtained accuracies encourage to further develop the multi-sensors systems. The presented substantive discussion concerning the system limitations and possible improvements mainly related to the depth information produced by the ToF-sensor is useful for computer aided surgery developers.

Oversampling in virtual visual sensors as a means to recover higher modes of vibration

NASA Astrophysics Data System (ADS)

Shariati, Ali; Schumacher, Thomas

2015-03-01

Vibration-based structural health monitoring (SHM) techniques require modal information from the monitored structure in order to estimate the location and severity of damage. Natural frequencies also provide useful information to calibrate finite element models. There are several types of physical sensors that can measure the response over a range of frequencies. For most of those sensors however, accessibility, limitation of measurement points, wiring, and high system cost represent major challenges. Recent optical sensing approaches offer advantages such as easy access to visible areas, distributed sensing capabilities, and comparatively inexpensive data recording while having no wiring issues. In this research we propose a novel methodology to measure natural frequencies of structures using digital video cameras based on virtual visual sensors (VVS). In our initial study where we worked with commercially available inexpensive digital video cameras we found that for multiple degrees of freedom systems it is difficult to detect all of the natural frequencies simultaneously due to low quantization resolution. In this study we show how oversampling enabled by the use of high-end high-frame-rate video cameras enable recovering all of the three natural frequencies from a three story lab-scale structure.

System identification of a tied arch bridge using reference-based wireless sensor networks

NASA Astrophysics Data System (ADS)

Hietbrink, Colby; Whelan, Matthew J.

2012-04-01

Vibration-based methods of structural health monitoring are generally founded on the principle that localized damage to a structure would exhibit changes within the global dynamic response. Upon this basis, accelerometers provide a unique health monitoring strategy in that a distributed network of sensors provides the technical feasibility to isolate the onset of damage without requiring that any sensor be located exactly on or in close proximity to the damage. While in theory this may be sufficient, practical experience has shown significant improvement in the application of damage diagnostic routines when mode shapes characterized by strongly localized behavior of specific elements are captured by the instrumentation array. In traditional applications, this presents a challenge since the cost and complexity of cable-based systems often effectively limits the number of instrumented locations thereby constraining the modal parameter extraction to only global modal responses. The advent of the low-cost RF chip transceiver with wireless networking capabilities has afforded a means by which a substantial number of output locations can be measured through referencebased testing using large-scale wireless sensor networks. In the current study, this approach was applied to the Prairie du Chien Bridge over the Mississippi River to extract operational mode shapes with high spatial reconstruction, including strongly localized modes. The tied arch bridge was instrumented at over 230 locations with single-axis accelerometers conditioned and acquired over a high-rate lossless wireless sensor network with simultaneous sampling capabilities. Acquisition of the dynamic response of the web plates of the arch rib was specifically targeted within the instrumentation array for diagnostic purposes. Reference-based operational modal analysis of the full structure through data-driven stochastic subspace identification is presented alongside finite element analysis results for confirmation of modal parameter plausibility. Particular emphasis is placed on the identification and reconstruction of modal response with large contribution from the arch rib web plates.

Measurement Of Multiphase Flow Water Fraction And Water-cut

NASA Astrophysics Data System (ADS)

Xie, Cheng-gang

2007-06-01

This paper describes a microwave transmission multiphase flow water-cut meter that measures the amplitude attenuation and phase shift across a pipe diameter at multiple frequencies using cavity-backed antennas. The multiphase flow mixture permittivity and conductivity are derived from a unified microwave transmission model for both water- and oil-continuous flows over a wide water-conductivity range; this is far beyond the capability of microwave-resonance-based sensors currently on the market. The water fraction and water cut are derived from a three-component gas-oil-water mixing model using the mixture permittivity or the mixture conductivity and an independently measured mixture density. Water salinity variations caused, for example, by changing formation water or formation/injection water breakthrough can be detected and corrected using an online water-conductivity tracking technique based on the interpretation of the mixture permittivity and conductivity, simultaneously measured by a single-modality microwave sensor.

A Data-Driven Response Virtual Sensor Technique with Partial Vibration Measurements Using Convolutional Neural Network.

PubMed

Sun, Shan-Bin; He, Yuan-Yuan; Zhou, Si-Da; Yue, Zhen-Jiang

2017-12-12

Measurement of dynamic responses plays an important role in structural health monitoring, damage detection and other fields of research. However, in aerospace engineering, the physical sensors are limited in the operational conditions of spacecraft, due to the severe environment in outer space. This paper proposes a virtual sensor model with partial vibration measurements using a convolutional neural network. The transmissibility function is employed as prior knowledge. A four-layer neural network with two convolutional layers, one fully connected layer, and an output layer is proposed as the predicting model. Numerical examples of two different structural dynamic systems demonstrate the performance of the proposed approach. The excellence of the novel technique is further indicated using a simply supported beam experiment comparing to a modal-model-based virtual sensor, which uses modal parameters, such as mode shapes, for estimating the responses of the faulty sensors. The results show that the presented data-driven response virtual sensor technique can predict structural response with high accuracy.

A Data-Driven Response Virtual Sensor Technique with Partial Vibration Measurements Using Convolutional Neural Network

PubMed Central

Sun, Shan-Bin; He, Yuan-Yuan; Zhou, Si-Da; Yue, Zhen-Jiang

2017-01-01

Measurement of dynamic responses plays an important role in structural health monitoring, damage detection and other fields of research. However, in aerospace engineering, the physical sensors are limited in the operational conditions of spacecraft, due to the severe environment in outer space. This paper proposes a virtual sensor model with partial vibration measurements using a convolutional neural network. The transmissibility function is employed as prior knowledge. A four-layer neural network with two convolutional layers, one fully connected layer, and an output layer is proposed as the predicting model. Numerical examples of two different structural dynamic systems demonstrate the performance of the proposed approach. The excellence of the novel technique is further indicated using a simply supported beam experiment comparing to a modal-model-based virtual sensor, which uses modal parameters, such as mode shapes, for estimating the responses of the faulty sensors. The results show that the presented data-driven response virtual sensor technique can predict structural response with high accuracy. PMID:29231868

Direction-of-arrival estimation for a uniform circular acoustic vector-sensor array mounted around a cylindrical baffle

NASA Astrophysics Data System (ADS)

Yang, DeSen; Zhu, ZhongRui

2012-12-01

This work investigates the direction-of-arrival (DOA) estimation for a uniform circular acoustic Vector-Sensor Array (UCAVSA) mounted around a cylindrical baffle. The total pressure field and the total particle velocity field near the surface of the cylindrical baffle are analyzed theoretically by applying the method of spatial Fourier transform. Then the so-called modal vector-sensor array signal processing algorithm, which is based on the decomposed wavefield representations, for the UCAVSA mounted around the cylindrical baffle is proposed. Simulation and experimental results show that the UCAVSA mounted around the cylindrical baffle has distinct advantages over the same manifold of traditional uniform circular pressure-sensor array (UCPSA). It is pointed out that the acoustic Vector-Sensor (AVS) could be used under the condition of the cylindrical baffle and that the UCAVSA mounted around the cylindrical baffle could also combine the anti-noise performance of the AVS with spatial resolution performance of array system by means of modal vector-sensor array signal processing algorithms.

Context-Aware Fusion of RGB and Thermal Imagery for Traffic Monitoring

PubMed Central

Alldieck, Thiemo; Bahnsen, Chris H.; Moeslund, Thomas B.

2016-01-01

In order to enable a robust 24-h monitoring of traffic under changing environmental conditions, it is beneficial to observe the traffic scene using several sensors, preferably from different modalities. To fully benefit from multi-modal sensor output, however, one must fuse the data. This paper introduces a new approach for fusing color RGB and thermal video streams by using not only the information from the videos themselves, but also the available contextual information of a scene. The contextual information is used to judge the quality of a particular modality and guides the fusion of two parallel segmentation pipelines of the RGB and thermal video streams. The potential of the proposed context-aware fusion is demonstrated by extensive tests of quantitative and qualitative characteristics on existing and novel video datasets and benchmarked against competing approaches to multi-modal fusion. PMID:27869730

Distributed-effect optical fiber sensors for trusses and plates

NASA Technical Reports Server (NTRS)

Reichard, Karl; Lindner, Douglas K.

1991-01-01

Modal domain optical fiber sensors, or distributed effect sensors, for active vibration suppression in flexible structures are considered. Preliminary modeling results indicate that these sensors can be used to sense vibrations in a flexible beam and the signal can be used to damp vibrations in the beam. Weighted distributed-effect sensors can be used to implement high order compensators with low order functional observers.

The optimal hormonal replacement modality selection for multiple organ procurement from brain-dead organ donors

PubMed Central

Mi, Zhibao; Novitzky, Dimitri; Collins, Joseph F; Cooper, David KC

2015-01-01

The management of brain-dead organ donors is complex. The use of inotropic agents and replacement of depleted hormones (hormonal replacement therapy) is crucial for successful multiple organ procurement, yet the optimal hormonal replacement has not been identified, and the statistical adjustment to determine the best selection is not trivial. Traditional pair-wise comparisons between every pair of treatments, and multiple comparisons to all (MCA), are statistically conservative. Hsu’s multiple comparisons with the best (MCB) – adapted from the Dunnett’s multiple comparisons with control (MCC) – has been used for selecting the best treatment based on continuous variables. We selected the best hormonal replacement modality for successful multiple organ procurement using a two-step approach. First, we estimated the predicted margins by constructing generalized linear models (GLM) or generalized linear mixed models (GLMM), and then we applied the multiple comparison methods to identify the best hormonal replacement modality given that the testing of hormonal replacement modalities is independent. Based on 10-year data from the United Network for Organ Sharing (UNOS), among 16 hormonal replacement modalities, and using the 95% simultaneous confidence intervals, we found that the combination of thyroid hormone, a corticosteroid, antidiuretic hormone, and insulin was the best modality for multiple organ procurement for transplantation. PMID:25565890

Control-structure interaction in precision pointing servo loops

NASA Technical Reports Server (NTRS)

Spanos, John T.

1989-01-01

The control-structure interaction problem is addressed via stability analysis of a generic linear servo loop model. With the plant described by the rigid body mode and a single elastic mode, structural flexibility is categorized into one of three types: (1) appendage, (2) in-the-loop minimum phase, and (3) in-the-loop nonminimum phase. Closing the loop with proportional-derivative (PD) control action and introducing sensor roll-off dynamics in the feedback path, stability conditions are obtained. Trade studies are conducted with modal frequency, modal participation, modal damping, loop bandwidth, and sensor bandwidth treated as free parameters. Results indicate that appendage modes are most likely to produce instability if they are near the sensor rolloff, whereas in-the-loop modes are most dangerous near the loop bandwidth. The main goal of this paper is to provide a fundamental understanding of the control-structure interaction problem so that it may benefit the design of complex spacecraft and pointing system servo loops. In this framework, the JPL Pathfinder gimbal pointer is considered as an example.

Advancements in Transmitters and Sensors for Biological Tissue Imaging in Magnetic Induction Tomography

PubMed Central

Zakaria, Zulkarnay; Rahim, Ruzairi Abdul; Mansor, Muhammad Saiful Badri; Yaacob, Sazali; Ayub, Nor Muzakkir Nor; Muji, Siti Zarina Mohd.; Rahiman, Mohd Hafiz Fazalul; Aman, Syed Mustafa Kamal Syed

2012-01-01

Magnetic Induction Tomography (MIT), which is also known as Electromagnetic Tomography (EMT) or Mutual Inductance Tomography, is among the imaging modalities of interest to many researchers around the world. This noninvasive modality applies an electromagnetic field and is sensitive to all three passive electromagnetic properties of a material that are conductivity, permittivity and permeability. MIT is categorized under the passive imaging family with an electrodeless technique through the use of excitation coils to induce an electromagnetic field in the material, which is then measured at the receiving side by sensors. The aim of this review is to discuss the challenges of the MIT technique and summarize the recent advancements in the transmitters and sensors, with a focus on applications in biological tissue imaging. It is hoped that this review will provide some valuable information on the MIT for those who have interest in this modality. The need of this knowledge may speed up the process of adopted of MIT as a medical imaging technology. PMID:22969341

Performance bounds for modal analysis using sparse linear arrays

NASA Astrophysics Data System (ADS)

Li, Yuanxin; Pezeshki, Ali; Scharf, Louis L.; Chi, Yuejie

2017-05-01

We study the performance of modal analysis using sparse linear arrays (SLAs) such as nested and co-prime arrays, in both first-order and second-order measurement models. We treat SLAs as constructed from a subset of sensors in a dense uniform linear array (ULA), and characterize the performance loss of SLAs with respect to the ULA due to using much fewer sensors. In particular, we claim that, provided the same aperture, in order to achieve comparable performance in terms of Cramér-Rao bound (CRB) for modal analysis, SLAs require more snapshots, of which the number is about the number of snapshots used by ULA times the compression ratio in the number of sensors. This is shown analytically for the case with one undamped mode, as well as empirically via extensive numerical experiments for more complex scenarios. Moreover, the misspecified CRB proposed by Richmond and Horowitz is also studied, where SLAs suffer more performance loss than their ULA counterpart.

Differential modal Zernike wavefront sensor employing a computer-generated hologram: a proposal.

PubMed

Mishra, Sanjay K; Bhatt, Rahul; Mohan, Devendra; Gupta, Arun Kumar; Sharma, Anurag

2009-11-20

The process of Zernike mode detection with a Shack-Hartmann wavefront sensor is computationally extensive. A holographic modal wavefront sensor has therefore evolved to process the data optically by use of the concept of equal and opposite phase bias. Recently, a multiplexed computer-generated hologram (CGH) technique was developed in which the output is in the form of bright dots that specify the presence and strength of a specific Zernike mode. We propose a wavefront sensor using the concept of phase biasing in the latter technique such that the output is a pair of bright dots for each mode to be sensed. A normalized difference signal between the intensities of the two dots is proportional to the amplitude of the sensed Zernike mode. In our method the number of holograms to be multiplexed is decreased, thereby reducing the modal cross talk significantly. We validated the proposed method through simulation studies for several cases. The simulation results demonstrate simultaneous wavefront detection of lower-order Zernike modes with a resolution better than lambda/50 for the wide measurement range of +/-3.5lambda with much reduced cross talk at high speed.

A Guided Wave Sensor Enabling Simultaneous Wavenumber-Frequency Analysis for Both Lamb and Shear-Horizontal Waves.

PubMed

Ren, Baiyang; Cho, Hwanjeong; Lissenden, Cliff J

2017-03-01

Guided waves in plate-like structures have been widely investigated for structural health monitoring. Lamb waves and shear horizontal (SH) waves, two commonly used types of waves in plates, provide different benefits for the detection of various types of defects and material degradation. However, there are few sensors that can detect both Lamb and SH waves and also resolve their modal content, namely the wavenumber-frequency spectrum. A sensor that can detect both waves is desirable to take full advantage of both types of waves in order to improve sensitivity to different discontinuity geometries. We demonstrate that polyvinylidene difluoride (PVDF) film provides the basis for a multi-element array sensor that detects both Lamb and SH waves and also measures their modal content, i.e., the wavenumber-frequency spectrum.

Multi-Modalities Sensor Science

DTIC Science & Technology

2015-02-28

enhanced multi-mode sensor science. bio -sensing, cross-discipling, multi-physics, nano-technology sailing He +46-8790 8465 1 Final Report for SOARD Project...spectroscopy, nano-technology, biophotonics and multi-physics modeling to produce adaptable bio -nanostructure enhanced multi-mode sensor science. 1...adaptable bio -nanostructure enhanced multi-mode sensor science. The accomplishments includes 1) A General Method for Designing a Radome to Enhance

Multiple sensor integration for seizure onset detection in human patients comparing conventional disc versus novel tripolar concentric ring electrodes.

PubMed

Makeyev, Oleksandr; Ding, Quan; Martínez-Juárez, Iris E; Gaitanis, John; Kay, Steven M; Besio, Walter G

2013-01-01

As epilepsy affects approximately one percent of the world population, electrical stimulation of the brain has recently shown potential for additive seizure control therapy. Closed-loop systems that apply electrical stimulation when seizure onset is automatically detected require high accuracy of automatic seizure detection based on electrographic brain activity. To improve this accuracy we propose to use noninvasive tripolar concentric ring electrodes that have been shown to have significantly better signal-to-noise ratio, spatial selectivity, and mutual information compared to conventional disc electrodes. The proposed detection methodology is based on integration of multiple sensors using exponentially embedded family (EEF). In this preliminary study it is validated on over 26.3 hours of data collected using both tripolar concentric ring and conventional disc electrodes concurrently each from 7 human patients with epilepsy including five seizures. For a cross-validation based group model EEF correctly detected 100% and 80% of seizures respectively with <0.76 and <1.56 false positive detections per hour respectively for the two electrode modalities. These results clearly suggest the potential of seizure onset detection based on data from tripolar concentric ring electrodes.

Development of a wearable CMOS-based contact imaging system for real-time skin condition diagnosis

NASA Astrophysics Data System (ADS)

Petitdidier, Nils; Koenig, Anne; Gerbelot, Rémi; Gioux, Sylvain; Dinten, Jean-Marc

2017-07-01

Diffuse reflectance spectroscopy has been widely used in the field of biological tissue characterization with various modalities [1-5,6]. One of these modalities consists in measuring the spatially resolved diffuse reflectance (SRDR). In this technique, light is collected at multiple distances from the excitation point. The obtained reflectance decay curve is used to determine scattering and absorption properties of the tissue [7], which are directly related to tissue content and structure. Existing systems usually use fiber optics to collect light reflected from the tissue and transfer it to an optical sensor [1,6]. Such devices make it possible to perform SRDR measurements directly in contact with the tissue. However, they offer poor spatial sampling of the reflectance and low light collection efficiency. We propose to overcome these limitations by using a CMOS sensor placed in contact with the tissue to achieve light collection with high spatial sampling over several millimeters and with increased fill factor. Our objective in this paper is to demonstrate the potential of our instrument to determine the optical properties of tissues from SRDR measurements. We first describe the instrument and the employed methodology. Then, preliminary results obtained on optical phantoms are presented. Finally, the potential of our system for SRDR measurements is evaluated through comparison with a fiber-optic probe previously developed in our laboratory [6,8].

Clutter and target discrimination in forward-looking ground penetrating radar using sparse structured basis pursuits

NASA Astrophysics Data System (ADS)

Camilo, Joseph A.; Malof, Jordan M.; Torrione, Peter A.; Collins, Leslie M.; Morton, Kenneth D.

2015-05-01

Forward-looking ground penetrating radar (FLGPR) is a remote sensing modality that has recently been investigated for buried threat detection. FLGPR offers greater standoff than other downward-looking modalities such as electromagnetic induction and downward-looking GPR, but it suffers from high false alarm rates due to surface and ground clutter. A stepped frequency FLGPR system consists of multiple radars with varying polarizations and bands, each of which interacts differently with subsurface materials and therefore might potentially be able to discriminate clutter from true buried targets. However, it is unclear which combinations of bands and polarizations would be most useful for discrimination or how to fuse them. This work applies sparse structured basis pursuit, a supervised statistical model which searches for sets of bands that are collectively effective for discriminating clutter from targets. The algorithm works by trying to minimize the number of selected items in a dictionary of signals; in this case the separate bands and polarizations make up the dictionary elements. A structured basis pursuit algorithm is employed to gather groups of modes together in collections to eliminate whole polarizations or sensors. The approach is applied to a large collection of FLGPR data for data around emplaced target and non-target clutter. The results show that a sparse structure basis pursuits outperforms a conventional CFAR anomaly detector while also pruning out unnecessary bands of the FLGPR sensor.

High resolution hybrid optical and acoustic sea floor maps (Invited)

NASA Astrophysics Data System (ADS)

Roman, C.; Inglis, G.

2013-12-01

This abstract presents a method for creating hybrid optical and acoustic sea floor reconstructions at centimeter scale grid resolutions with robotic vehicles. Multibeam sonar and stereo vision are two common sensing modalities with complementary strengths that are well suited for data fusion. We have recently developed an automated two stage pipeline to create such maps. The steps can be broken down as navigation refinement and map construction. During navigation refinement a graph-based optimization algorithm is used to align 3D point clouds created with both the multibeam sonar and stereo cameras. The process combats the typical growth in navigation error that has a detrimental affect on map fidelity and typically introduces artifacts at small grid sizes. During this process we are able to automatically register local point clouds created by each sensor to themselves and to each other where they overlap in a survey pattern. The process also estimates the sensor offsets, such as heading, pitch and roll, that describe how each sensor is mounted to the vehicle. The end results of the navigation step is a refined vehicle trajectory that ensures the points clouds from each sensor are consistently aligned, and the individual sensor offsets. In the mapping step, grid cells in the map are selectively populated by choosing data points from each sensor in an automated manner. The selection process is designed to pick points that preserve the best characteristics of each sensor and honor some specific map quality criteria to reduce outliers and ghosting. In general, the algorithm selects dense 3D stereo points in areas of high texture and point density. In areas where the stereo vision is poor, such as in a scene with low contrast or texture, multibeam sonar points are inserted in the map. This process is automated and results in a hybrid map populated with data from both sensors. Additional cross modality checks are made to reject outliers in a robust manner. The final hybrid map retains the strengths of both sensors and shows improvement over the single modality maps and a naively assembled multi-modal map where all the data points are included and averaged. Results will be presented from marine geological and archaeological applications using a 1350 kHz BlueView multibeam sonar and 1.3 megapixel digital still cameras.

Comparative VOCs sensing performance for conducting polymer and porphyrin functionalized carbon nanotubes based sensors

NASA Astrophysics Data System (ADS)

Datta, Kunal; Rushi, Arti; Ghosh, Prasanta; Shirsat, Mahendra

2018-05-01

We report sensors for detection of ethyl alcohol, a prominent volatile organic compound (VOC). Single walled carbon nanotubes were selected as main sensing backbone. As efficiency of sensor is dependent upon the choice of sensing materials, the performances of conducting polymer and porphyrin based sensors were compared. Chemiresistive sensing modality was adopted to observe the performance of sensors. It has been found that porphyrin based sensor shows higher affinity towards ethyl alcohol.

Multi-modal gesture recognition using integrated model of motion, audio and video

NASA Astrophysics Data System (ADS)

Goutsu, Yusuke; Kobayashi, Takaki; Obara, Junya; Kusajima, Ikuo; Takeichi, Kazunari; Takano, Wataru; Nakamura, Yoshihiko

2015-07-01

Gesture recognition is used in many practical applications such as human-robot interaction, medical rehabilitation and sign language. With increasing motion sensor development, multiple data sources have become available, which leads to the rise of multi-modal gesture recognition. Since our previous approach to gesture recognition depends on a unimodal system, it is difficult to classify similar motion patterns. In order to solve this problem, a novel approach which integrates motion, audio and video models is proposed by using dataset captured by Kinect. The proposed system can recognize observed gestures by using three models. Recognition results of three models are integrated by using the proposed framework and the output becomes the final result. The motion and audio models are learned by using Hidden Markov Model. Random Forest which is the video classifier is used to learn the video model. In the experiments to test the performances of the proposed system, the motion and audio models most suitable for gesture recognition are chosen by varying feature vectors and learning methods. Additionally, the unimodal and multi-modal models are compared with respect to recognition accuracy. All the experiments are conducted on dataset provided by the competition organizer of MMGRC, which is a workshop for Multi-Modal Gesture Recognition Challenge. The comparison results show that the multi-modal model composed of three models scores the highest recognition rate. This improvement of recognition accuracy means that the complementary relationship among three models improves the accuracy of gesture recognition. The proposed system provides the application technology to understand human actions of daily life more precisely.

Multimode excitation-induced phase shifts in intrinsic Fabry-Perot interferometric fiber sensor spectra.

PubMed

Ma, Cheng; Wang, Anbo

2010-09-01

We report the modal analysis of optical fiber single-mode-multimode-single-mode intrinsic Fabry-Perot interferometer sensors. The multimode nature of the Fabry-Perot cavity gives rise to an additional phase term in the spectrogram due to intermodal dispersion-induced wavefront distortion, which could significantly affect the cavity length demodulation accuracy. By using an exact model to analyze the modal behavior, this phase term is explained by employing a rotating vector approach. Comparison of the theoretical analysis with experimental results is presented.

FieldSAFE: Dataset for Obstacle Detection in Agriculture.

PubMed

Kragh, Mikkel Fly; Christiansen, Peter; Laursen, Morten Stigaard; Larsen, Morten; Steen, Kim Arild; Green, Ole; Karstoft, Henrik; Jørgensen, Rasmus Nyholm

2017-11-09

In this paper, we present a multi-modal dataset for obstacle detection in agriculture. The dataset comprises approximately 2 h of raw sensor data from a tractor-mounted sensor system in a grass mowing scenario in Denmark, October 2016. Sensing modalities include stereo camera, thermal camera, web camera, 360 ∘ camera, LiDAR and radar, while precise localization is available from fused IMU and GNSS. Both static and moving obstacles are present, including humans, mannequin dolls, rocks, barrels, buildings, vehicles and vegetation. All obstacles have ground truth object labels and geographic coordinates.

FieldSAFE: Dataset for Obstacle Detection in Agriculture

PubMed Central

Christiansen, Peter; Larsen, Morten; Steen, Kim Arild; Green, Ole; Karstoft, Henrik

2017-01-01

In this paper, we present a multi-modal dataset for obstacle detection in agriculture. The dataset comprises approximately 2 h of raw sensor data from a tractor-mounted sensor system in a grass mowing scenario in Denmark, October 2016. Sensing modalities include stereo camera, thermal camera, web camera, 360∘ camera, LiDAR and radar, while precise localization is available from fused IMU and GNSS. Both static and moving obstacles are present, including humans, mannequin dolls, rocks, barrels, buildings, vehicles and vegetation. All obstacles have ground truth object labels and geographic coordinates. PMID:29120383

Autonomous smart sensor network for full-scale structural health monitoring

NASA Astrophysics Data System (ADS)

Rice, Jennifer A.; Mechitov, Kirill A.; Spencer, B. F., Jr.; Agha, Gul A.

2010-04-01

The demands of aging infrastructure require effective methods for structural monitoring and maintenance. Wireless smart sensor networks offer the ability to enhance structural health monitoring (SHM) practices through the utilization of onboard computation to achieve distributed data management. Such an approach is scalable to the large number of sensor nodes required for high-fidelity modal analysis and damage detection. While smart sensor technology is not new, the number of full-scale SHM applications has been limited. This slow progress is due, in part, to the complex network management issues that arise when moving from a laboratory setting to a full-scale monitoring implementation. This paper presents flexible network management software that enables continuous and autonomous operation of wireless smart sensor networks for full-scale SHM applications. The software components combine sleep/wake cycling for enhanced power management with threshold detection for triggering network wide tasks, such as synchronized sensing or decentralized modal analysis, during periods of critical structural response.

Engineering of Sensor Network Structure for Dependable Fusion

DTIC Science & Technology

2014-08-15

Lossy Wireless Sensor Networks , IEEE/ACM Transactions on Networking , (04 2013): 0. doi: 10.1109/TNET.2013.2256795 Soumik Sarkar, Kushal Mukherjee...Phoha, Bharat B. Madan, Asok Ray. Distributed Network Control for Mobile Multi-Modal Wireless Sensor Networks , Journal of Parallel and Distributed...Deadline Constraints, IEEE Transactions on Automatic Control special issue on Wireless Sensor and Actuator Networks , (01 2011): 1. doi: Eric Keller

A guided wave sensor enabling simultaneous wavenumber-frequency analysis for both lamb and shear-horizontal waves

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

Ren, Baiyang; Cho, Hwanjeong; Lissenden, Cliff J.

Guided waves in plate-like structures have been widely investigated for structural health monitoring. Lamb waves and shear horizontal (SH) waves, two commonly used types of waves in plates, provide different benefits for the detection of various types of defects and material degradation. However, there are few sensors that can detect both Lamb and SH waves and also resolve their modal content, namely the wavenumber-frequency spectrum. A sensor that can detect both waves is desirable to take full advantage of both types of waves in order to improve sensitivity to different discontinuity geometries. As a result, we demonstrate that polyvinylidene difluoridemore » (PVDF) film provides the basis for a multi-element array sensor that detects both Lamb and SH waves and also measures their modal content, i.e., the wavenumber-frequency spectrum.« less

A guided wave sensor enabling simultaneous wavenumber-frequency analysis for both lamb and shear-horizontal waves

DOE PAGES

Ren, Baiyang; Cho, Hwanjeong; Lissenden, Cliff J.

2017-03-01

Guided waves in plate-like structures have been widely investigated for structural health monitoring. Lamb waves and shear horizontal (SH) waves, two commonly used types of waves in plates, provide different benefits for the detection of various types of defects and material degradation. However, there are few sensors that can detect both Lamb and SH waves and also resolve their modal content, namely the wavenumber-frequency spectrum. A sensor that can detect both waves is desirable to take full advantage of both types of waves in order to improve sensitivity to different discontinuity geometries. As a result, we demonstrate that polyvinylidene difluoridemore » (PVDF) film provides the basis for a multi-element array sensor that detects both Lamb and SH waves and also measures their modal content, i.e., the wavenumber-frequency spectrum.« less

Gyrocopter-Based Remote Sensing Platform

NASA Astrophysics Data System (ADS)

Weber, I.; Jenal, A.; Kneer, C.; Bongartz, J.

2015-04-01

In this paper the development of a lightweight and highly modularized airborne sensor platform for remote sensing applications utilizing a gyrocopter as a carrier platform is described. The current sensor configuration consists of a high resolution DSLR camera for VIS-RGB recordings. As a second sensor modality, a snapshot hyperspectral camera was integrated in the aircraft. Moreover a custom-developed thermal imaging system composed of a VIS-PAN camera and a LWIR-camera is used for aerial recordings in the thermal infrared range. Furthermore another custom-developed highly flexible imaging system for high resolution multispectral image acquisition with up to six spectral bands in the VIS-NIR range is presented. The performance of the overall system was tested during several flights with all sensor modalities and the precalculated demands with respect to spatial resolution and reliability were validated. The collected data sets were georeferenced, georectified, orthorectified and then stitched to mosaics.

Matching Teaching and Learning Styles.

ERIC Educational Resources Information Center

Caudill, Gil

1998-01-01

Outlines three basic learning modalities--auditory, visual, and tactile--and notes that technology can help incorporate multiple modalities within each lesson, to meet the needs of most students. Discusses the importance in multiple modality teaching of effectively assessing students. Presents visual, auditory and tactile activity suggestions.…

An Investigation of New Snow Water Equivalence Sensing Modalities

NASA Astrophysics Data System (ADS)

Frolik, J.; Skalka, C.; Wemple, B.

2008-12-01

It is well known that snowpack is highly variable and influenced by a range of factors, including topography and vegetation cover. As such, single point measurements may be viewed as being inadequate to characterize snowpack in a given area. Thus motivated by the desire for distributed sensing, this work presents results of a proof-of-concept investigation for new, low-cost, snow water equivalence (SWE) sensors based on the attenuation of microwave and gamma radiation. First, our work considers the attenuation of microwave signals at 2.4 GHz and 5 GHz due to an accumulating snowpack. These frequencies coincide with those used for common wireless networks and thus our proposed sensor can leverage existing hardware designs which are low-cost and power efficient. Second, we present attenuation data for radiation energy occurring between 500 keV and 1 MeV. These results were obtained utilizing a radiation detector based on Cadmium Zinc Telluride (CZT) technology. The proposed sensor will leverage recent investments such CZT based designs for homeland security applications. We contend that sensors based on these modalities will be low-cost and low-energy and thus readily integrated with wireless sensor network hardware for distributed monitoring. In addition, these sensors will be compact and thus can be placed in locations not feasible for current SWE sensor designs (e.g., snow pillows) or in locations too dangerous for snow course measurements (e.g., areas prone to avalanche). Since neither sensing methods requires contact with the snowpack, these modalities are also immune to snow bridging effects which plague existing designs. We also present preliminary findings of work conducted in a mountainous forested setting in northern New England which examines the influence of forest vegetation on snowpack.

Optimal sensor placement for spatial lattice structure based on genetic algorithms

NASA Astrophysics Data System (ADS)

Liu, Wei; Gao, Wei-cheng; Sun, Yi; Xu, Min-jian

2008-10-01

Optimal sensor placement technique plays a key role in structural health monitoring of spatial lattice structures. This paper considers the problem of locating sensors on a spatial lattice structure with the aim of maximizing the data information so that structural dynamic behavior can be fully characterized. Based on the criterion of optimal sensor placement for modal test, an improved genetic algorithm is introduced to find the optimal placement of sensors. The modal strain energy (MSE) and the modal assurance criterion (MAC) have been taken as the fitness function, respectively, so that three placement designs were produced. The decimal two-dimension array coding method instead of binary coding method is proposed to code the solution. Forced mutation operator is introduced when the identical genes appear via the crossover procedure. A computational simulation of a 12-bay plain truss model has been implemented to demonstrate the feasibility of the three optimal algorithms above. The obtained optimal sensor placements using the improved genetic algorithm are compared with those gained by exiting genetic algorithm using the binary coding method. Further the comparison criterion based on the mean square error between the finite element method (FEM) mode shapes and the Guyan expansion mode shapes identified by data-driven stochastic subspace identification (SSI-DATA) method are employed to demonstrate the advantage of the different fitness function. The results showed that some innovations in genetic algorithm proposed in this paper can enlarge the genes storage and improve the convergence of the algorithm. More importantly, the three optimal sensor placement methods can all provide the reliable results and identify the vibration characteristics of the 12-bay plain truss model accurately.

Time-Of-Flight Camera, Optical Tracker and Computed Tomography in Pairwise Data Registration

PubMed Central

Badura, Pawel; Juszczyk, Jan; Pietka, Ewa

2016-01-01

Purpose A growing number of medical applications, including minimal invasive surgery, depends on multi-modal or multi-sensors data processing. Fast and accurate 3D scene analysis, comprising data registration, seems to be crucial for the development of computer aided diagnosis and therapy. The advancement of surface tracking system based on optical trackers already plays an important role in surgical procedures planning. However, new modalities, like the time-of-flight (ToF) sensors, widely explored in non-medical fields are powerful and have the potential to become a part of computer aided surgery set-up. Connection of different acquisition systems promises to provide a valuable support for operating room procedures. Therefore, the detailed analysis of the accuracy of such multi-sensors positioning systems is needed. Methods We present the system combining pre-operative CT series with intra-operative ToF-sensor and optical tracker point clouds. The methodology contains: optical sensor set-up and the ToF-camera calibration procedures, data pre-processing algorithms, and registration technique. The data pre-processing yields a surface, in case of CT, and point clouds for ToF-sensor and marker-driven optical tracker representation of an object of interest. An applied registration technique is based on Iterative Closest Point algorithm. Results The experiments validate the registration of each pair of modalities/sensors involving phantoms of four various human organs in terms of Hausdorff distance and mean absolute distance metrics. The best surface alignment was obtained for CT and optical tracker combination, whereas the worst for experiments involving ToF-camera. Conclusion The obtained accuracies encourage to further develop the multi-sensors systems. The presented substantive discussion concerning the system limitations and possible improvements mainly related to the depth information produced by the ToF-sensor is useful for computer aided surgery developers. PMID:27434396

Hybrid optical acoustic seafloor mapping

NASA Astrophysics Data System (ADS)

Inglis, Gabrielle

The oceanographic research and industrial communities have a persistent demand for detailed three dimensional sea floor maps which convey both shape and texture. Such data products are used for archeology, geology, ship inspection, biology, and habitat classification. There are a variety of sensing modalities and processing techniques available to produce these maps and each have their own potential benefits and related challenges. Multibeam sonar and stereo vision are such two sensors with complementary strengths making them ideally suited for data fusion. Data fusion approaches however, have seen only limited application to underwater mapping and there are no established methods for creating hybrid, 3D reconstructions from two underwater sensing modalities. This thesis develops a processing pipeline to synthesize hybrid maps from multi-modal survey data. It is helpful to think of this processing pipeline as having two distinct phases: Navigation Refinement and Map Construction. This thesis extends existing work in underwater navigation refinement by incorporating methods which increase measurement consistency between both multibeam and camera. The result is a self consistent 3D point cloud comprised of camera and multibeam measurements. In map construction phase, a subset of the multi-modal point cloud retaining the best characteristics of each sensor is selected to be part of the final map. To quantify the desired traits of a map several characteristics of a useful map are distilled into specific criteria. The different ways that hybrid maps can address these criteria provides justification for producing them as an alternative to current methodologies. The processing pipeline implements multi-modal data fusion and outlier rejection with emphasis on different aspects of map fidelity. The resulting point cloud is evaluated in terms of how well it addresses the map criteria. The final hybrid maps retain the strengths of both sensors and show significant improvement over the single modality maps and naively assembled multi-modal maps.

Proton-counting radiography for proton therapy: a proof of principle using CMOS APS technology

NASA Astrophysics Data System (ADS)

Poludniowski, G.; Allinson, N. M.; Anaxagoras, T.; Esposito, M.; Green, S.; Manolopoulos, S.; Nieto-Camero, J.; Parker, D. J.; Price, T.; Evans, P. M.

2014-06-01

Despite the early recognition of the potential of proton imaging to assist proton therapy (Cormack 1963 J. Appl. Phys. 34 2722), the modality is still removed from clinical practice, with various approaches in development. For proton-counting radiography applications such as computed tomography (CT), the water-equivalent-path-length that each proton has travelled through an imaged object must be inferred. Typically, scintillator-based technology has been used in various energy/range telescope designs. Here we propose a very different alternative of using radiation-hard CMOS active pixel sensor technology. The ability of such a sensor to resolve the passage of individual protons in a therapy beam has not been previously shown. Here, such capability is demonstrated using a 36 MeV cyclotron beam (University of Birmingham Cyclotron, Birmingham, UK) and a 200 MeV clinical radiotherapy beam (iThemba LABS, Cape Town, SA). The feasibility of tracking individual protons through multiple CMOS layers is also demonstrated using a two-layer stack of sensors. The chief advantages of this solution are the spatial discrimination of events intrinsic to pixelated sensors, combined with the potential provision of information on both the range and residual energy of a proton. The challenges in developing a practical system are discussed.

Proton-counting radiography for proton therapy: a proof of principle using CMOS APS technology

PubMed Central

Poludniowski, G; Allinson, N M; Anaxagoras, T; Esposito, M; Green, S; Manolopoulos, S; Nieto-Camero, J; Parker, D J; Price, T; Evans, P M

2014-01-01

Despite the early recognition of the potential of proton imaging to assist proton therapy the modality is still removed from clinical practice, with various approaches in development. For proton-counting radiography applications such as Computed Tomography (CT), the Water-Equivalent-Path-Length (WEPL) that each proton has travelled through an imaged object must be inferred. Typically, scintillator-based technology has been used in various energy/range telescope designs. Here we propose a very different alternative of using radiation-hard CMOS Active Pixel Sensor (APS) technology. The ability of such a sensor to resolve the passage of individual protons in a therapy beam has not been previously shown. Here, such capability is demonstrated using a 36 MeV cyclotron beam (University of Birmingham Cyclotron, Birmingham, UK) and a 200 MeV clinical radiotherapy beam (iThemba LABS, Cape Town, SA). The feasibility of tracking individual protons through multiple CMOS layers is also demonstrated using a two-layer stack of sensors. The chief advantages of this solution are the spatial discrimination of events intrinsic to pixelated sensors, combined with the potential provision of information on both the range and residual energy of a proton. The challenges in developing a practical system are discussed. PMID:24785680

Energy Logic (EL): a novel fusion engine of multi-modality multi-agent data/information fusion for intelligent surveillance systems

NASA Astrophysics Data System (ADS)

Rababaah, Haroun; Shirkhodaie, Amir

2009-04-01

The rapidly advancing hardware technology, smart sensors and sensor networks are advancing environment sensing. One major potential of this technology is Large-Scale Surveillance Systems (LS3) especially for, homeland security, battlefield intelligence, facility guarding and other civilian applications. The efficient and effective deployment of LS3 requires addressing number of aspects impacting the scalability of such systems. The scalability factors are related to: computation and memory utilization efficiency, communication bandwidth utilization, network topology (e.g., centralized, ad-hoc, hierarchical or hybrid), network communication protocol and data routing schemes; and local and global data/information fusion scheme for situational awareness. Although, many models have been proposed to address one aspect or another of these issues but, few have addressed the need for a multi-modality multi-agent data/information fusion that has characteristics satisfying the requirements of current and future intelligent sensors and sensor networks. In this paper, we have presented a novel scalable fusion engine for multi-modality multi-agent information fusion for LS3. The new fusion engine is based on a concept we call: Energy Logic. Experimental results of this work as compared to a Fuzzy logic model strongly supported the validity of the new model and inspired future directions for different levels of fusion and different applications.

Novel near infrared sensors for hybrid BCI applications

NASA Astrophysics Data System (ADS)

Almajidy, Rand K.; Le, Khang S.; Hofmann, Ulrich G.

2015-07-01

This study's goal is to develop a low cost, portable, accurate and comfortable NIRS module that can be used simultaneously with EEG in a dual modality system for brain computer interface (BCI). The sensing modules consist of electroencephalography (EEG) electrodes (at the positions Fp1, Fpz and Fp2 in the international 10-20 system) with eight custom made functional near infrared spectroscopy (fNIRS) channels, positioned on the prefrontal cortex area with two extra channels to measure and eliminate extra-cranial oxygenation. The NIRS sensors were designed to guarantee good sensor-skin contact, without causing subject discomfort, using springs to press them to the skin instead of pressing them by cap fixture. Two open source software packages were modified to carry out dual modality hybrid BCI experiments. The experimental paradigm consisted of a mental task (arithmetic task or text reading) and a resting period. Both oxygenated hemoglobin concentration changes (HbO), and EEG signals showed an increase during the mental task, but the onset, period and amount of that increase depends on each modality's characteristics. The subject's degree of attention played an important role especially during online sessions. The sensors can be easily used to acquire brain signals from different cerebral cortex parts. The system serves as a simple technological test bed and will be used for stroke patient rehabilitation purposes.

Sensor-Free or Sensor-Full: A Comparison of Data Modalities in Multi-Channel Affect Detection

ERIC Educational Resources Information Center

Paquette, Luc; Rowe, Jonathan; Baker, Ryan; Mott, Bradford; Lester, James; DeFalco, Jeanine; Brawner, Keith; Sottilare, Robert; Georgoulas, Vasiliki

2016-01-01

Computational models that automatically detect learners' affective states are powerful tools for investigating the interplay of affect and learning. Over the past decade, affect detectors--which recognize learners' affective states at run-time using behavior logs and sensor data--have advanced substantially across a range of K-12 and postsecondary…

RadMAP: The Radiological Multi-sensor Analysis Platform

NASA Astrophysics Data System (ADS)

Bandstra, Mark S.; Aucott, Timothy J.; Brubaker, Erik; Chivers, Daniel H.; Cooper, Reynold J.; Curtis, Joseph C.; Davis, John R.; Joshi, Tenzing H.; Kua, John; Meyer, Ross; Negut, Victor; Quinlan, Michael; Quiter, Brian J.; Srinivasan, Shreyas; Zakhor, Avideh; Zhang, Richard; Vetter, Kai

2016-12-01

The variability of gamma-ray and neutron background during the operation of a mobile detector system greatly limits the ability of the system to detect weak radiological and nuclear threats. The natural radiation background measured by a mobile detector system is the result of many factors, including the radioactivity of nearby materials, the geometric configuration of those materials and the system, the presence of absorbing materials, and atmospheric conditions. Background variations tend to be highly non-Poissonian, making it difficult to set robust detection thresholds using knowledge of the mean background rate alone. The Radiological Multi-sensor Analysis Platform (RadMAP) system is designed to allow the systematic study of natural radiological background variations and to serve as a development platform for emerging concepts in mobile radiation detection and imaging. To do this, RadMAP has been used to acquire extensive, systematic background measurements and correlated contextual data that can be used to test algorithms and detector modalities at low false alarm rates. By combining gamma-ray and neutron detector systems with data from contextual sensors, the system enables the fusion of data from multiple sensors into novel data products. The data are curated in a common format that allows for rapid querying across all sensors, creating detailed multi-sensor datasets that are used to study correlations between radiological and contextual data, and develop and test novel techniques in mobile detection and imaging. In this paper we will describe the instruments that comprise the RadMAP system, the effort to curate and provide access to multi-sensor data, and some initial results on the fusion of contextual and radiological data.

Modal sensing and control of paraboloidal shell structronic system

NASA Astrophysics Data System (ADS)

Yue, Honghao; Lu, Yifan; Deng, Zongquan; Tzou, Hornsen

2018-02-01

Paraboloidal shells of revolution are commonly used as important components in the field of advanced aerospace structures and aviation mechanical systems. This study is to investigate the modal sensing behavior and the modal vibration control effect of distributed PVDF patches laminated on the paraboloidal shell. A paraboloidal shell sensing and control testing platform is set up first. Frequencies of lower order modes of the shell are obtained with the PVDF sensor and compared with the previous testing results to prove its accuracy. Then sensor patches are laminated on different positions (or different sides) of the shell and tested to reveal the relation between the sensing behaviors and their locations. Finally, a mathematical model of the structronic system is built by parameter identifications and the transfer function is derived. Independent and coupled modal controllers are designed based on the pole placement method and modal vibration control experiments are performed. The amplitude suppression ratio of each mode controlled by the pole placement controller is calculated and compared with the results obtained by using a PPF controller. Advantages of both methods are concluded and suggestions are given on how to choose control algorithm for different purpose.

Heterogeneous regional signal control : final report.

DOT National Transportation Integrated Search

2017-03-12

The goal of this project is to develop a comprehensive framework with a set of models to improve multi-modal traffic signal control, by incorporating advanced floating sensor data (e.g. GPS data, etc.) and traditional fixed sensor data (e.g. loop det...

Improving the performance of a pyramid wavefront sensor with modal sensitivity compensation.

PubMed

Korkiakoski, Visa; Vérinaud, Christophe; Le Louarn, Miska

2008-01-01

We describe a solution to increase the performance of a pyramid wavefront sensor (P-WFS) under bad seeing conditions. We show that most of the issues involve a reduced sensitivity that depends on the magnitude of the high frequency atmospheric distortions. We demonstrate in end-to-end closed loop adaptive optics simulations that with a modal sensitivity compensation method a high-order system with a nonmodulated P-WFS is robust in conditions with the Fried parameter r 0 at 0.5 microm in the range of 0.05-0.10 m. We also show that the method makes it possible to use a modal predictive control system to reach a total performance improvement of 0.06-0.45 in Strehl ratio at 1.6 microm. Especially at r 0=0.05 m the gain is dramatic.

Modal Frequency Detection in Composite Beams Using Fiber Optic Sensors

DTIC Science & Technology

1997-04-18

Structures 4, 270-280 (1995). [35] Chen-Jung Li and Ray Asok , "Neural Network Representation of Fatigue Damage Dynamics," Smart Materials and Structures 3...37] Roland Ray Kilcher, "Modal Analysis and Impact Damage Assessment of Composite Laminates: an Experimental Study," M.S. thesis, University of

Wind turbine blade fatigue tests: lessons learned and application to SHM system development

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

Taylor, Stuart G.; Farinholt, Kevin M.; Jeong, Hyomi

2012-06-28

This paper presents experimental results of several structural health monitoring (SHM) methods applied to a 9-meter CX-100 wind turbine blade that underwent fatigue loading. The blade was instrumented with piezoelectric transducers, accelerometers, acoustic emission sensors, and foil strain gauges. It underwent harmonic excitation at its first natural frequency using a hydraulically actuated resonant excitation system. The blade was initially excited at 25% of its design load, and then with steadily increasing loads until it failed. Various data were collected between and during fatigue loading sessions. The data were measured over multiple frequency ranges using a variety of acquisition equipment, includingmore » off-the-shelf systems and specially designed hardware developed by the authors. Modal response, diffuse wave-field transfer functions, and ultrasonic guided wave methods were applied to assess the condition of the wind turbine blade. The piezoelectric sensors themselves were also monitored using a sensor diagnostics procedure. This paper summarizes experimental procedures and results, focusing particularly on fatigue crack detection, and concludes with considerations for implementing such damage identification systems, which will be used as a guideline for future SHM system development for operating wind turbine blades.« less

On the Multi-Modal Object Tracking and Image Fusion Using Unsupervised Deep Learning Methodologies

NASA Astrophysics Data System (ADS)

LaHaye, N.; Ott, J.; Garay, M. J.; El-Askary, H. M.; Linstead, E.

2017-12-01

The number of different modalities of remote-sensors has been on the rise, resulting in large datasets with different complexity levels. Such complex datasets can provide valuable information separately, yet there is a bigger value in having a comprehensive view of them combined. As such, hidden information can be deduced through applying data mining techniques on the fused data. The curse of dimensionality of such fused data, due to the potentially vast dimension space, hinders our ability to have deep understanding of them. This is because each dataset requires a user to have instrument-specific and dataset-specific knowledge for optimum and meaningful usage. Once a user decides to use multiple datasets together, deeper understanding of translating and combining these datasets in a correct and effective manner is needed. Although there exists data centric techniques, generic automated methodologies that can potentially solve this problem completely don't exist. Here we are developing a system that aims to gain a detailed understanding of different data modalities. Such system will provide an analysis environment that gives the user useful feedback and can aid in research tasks. In our current work, we show the initial outputs our system implementation that leverages unsupervised deep learning techniques so not to burden the user with the task of labeling input data, while still allowing for a detailed machine understanding of the data. Our goal is to be able to track objects, like cloud systems or aerosols, across different image-like data-modalities. The proposed system is flexible, scalable and robust to understand complex likenesses within multi-modal data in a similar spatio-temporal range, and also to be able to co-register and fuse these images when needed.

A comparison of reduced-order modelling techniques for application in hyperthermia control and estimation.

PubMed

Bailey, E A; Dutton, A W; Mattingly, M; Devasia, S; Roemer, R B

1998-01-01

Reduced-order modelling techniques can make important contributions in the control and state estimation of large systems. In hyperthermia, reduced-order modelling can provide a useful tool by which a large thermal model can be reduced to the most significant subset of its full-order modes, making real-time control and estimation possible. Two such reduction methods, one based on modal decomposition and the other on balanced realization, are compared in the context of simulated hyperthermia heat transfer problems. The results show that the modal decomposition reduction method has three significant advantages over that of balanced realization. First, modal decomposition reduced models result in less error, when compared to the full-order model, than balanced realization reduced models of similar order in problems with low or moderate advective heat transfer. Second, because the balanced realization based methods require a priori knowledge of the sensor and actuator placements, the reduced-order model is not robust to changes in sensor or actuator locations, a limitation not present in modal decomposition. Third, the modal decomposition transformation is less demanding computationally. On the other hand, in thermal problems dominated by advective heat transfer, numerical instabilities make modal decomposition based reduction problematic. Modal decomposition methods are therefore recommended for reduction of models in which advection is not dominant and research continues into methods to render balanced realization based reduction more suitable for real-time clinical hyperthermia control and estimation.

Virtual Deformation Control of the X-56A Model with Simulated Fiber Optic Sensors

NASA Technical Reports Server (NTRS)

Suh, Peter M.; Chin, Alexander W.; Mavris, Dimitri N.

2014-01-01

A robust control law design methodology is presented to stabilize the X-56A model and command its wing shape. The X-56A was purposely designed to experience flutter modes in its flight envelope. The methodology introduces three phases: the controller design phase, the modal filter design phase, and the reference signal design phase. A mu-optimal controller is designed and made robust to speed and parameter variations. A conversion technique is presented for generating sensor strain modes from sensor deformation mode shapes. The sensor modes are utilized for modal filtering and simulating fiber optic sensors for feedback to the controller. To generate appropriate virtual deformation reference signals, rigid-body corrections are introduced to the deformation mode shapes. After successful completion of the phases, virtual deformation control is demonstrated. The wing is deformed and it is shown that angle-ofattack changes occur which could potentially be used to an advantage. The X-56A program must demonstrate active flutter suppression. It is shown that the virtual deformation controller can achieve active flutter suppression on the X-56A simulation model.

Virtual Deformation Control of the X-56A Model with Simulated Fiber Optic Sensors

NASA Technical Reports Server (NTRS)

Suh, Peter M.; Chin, Alexander Wong

2013-01-01

A robust control law design methodology is presented to stabilize the X-56A model and command its wing shape. The X-56A was purposely designed to experience flutter modes in its flight envelope. The methodology introduces three phases: the controller design phase, the modal filter design phase, and the reference signal design phase. A mu-optimal controller is designed and made robust to speed and parameter variations. A conversion technique is presented for generating sensor strain modes from sensor deformation mode shapes. The sensor modes are utilized for modal filtering and simulating fiber optic sensors for feedback to the controller. To generate appropriate virtual deformation reference signals, rigid-body corrections are introduced to the deformation mode shapes. After successful completion of the phases, virtual deformation control is demonstrated. The wing is deformed and it is shown that angle-of-attack changes occur which could potentially be used to an advantage. The X-56A program must demonstrate active flutter suppression. It is shown that the virtual deformation controller can achieve active flutter suppression on the X-56A simulation model.

Toward Non-Invasive and Automatic Intravenous Infiltration Detection: Evaluation of Bioimpedance and Skin Strain in a Pig Model.

PubMed

Bicen, A Ozan; West, Leanne L; Cesar, Liliana; Inan, Omer T

2018-01-01

Intravenous (IV) therapy is prevalent in hospital settings, where fluids are typically delivered with an IV into a peripheral vein of the patient. IV infiltration is the inadvertent delivery of fluids into the extravascular space rather than into the vein (and requires urgent treatment to avoid scarring and severe tissue damage), for which medical staff currently needs to check patients periodically. In this paper, the performance of two non-invasive sensing modalities, electrical bioimpedance (EBI), and skin strain sensing, for the automatic detection of IV infiltration was investigated in an animal model. Infiltrations were physically simulated on the hind limb of anesthetized pigs, where the sensors for EBI and skin strain sensing were co-located. The obtained data were used to examine the ability to distinguish between infusion into the vein and an infiltration event using bioresistance and bioreactance (derived from EBI), as well as skin strain. Skin strain and bioresistance sensing could achieve detection rates greater than 0.9 for infiltration fluid volumes of 2 and 10 mL, respectively, for a given false positive, i.e., false alarm rate of 0.05. Furthermore, the fusion of multiple sensing modalities could achieve a detection rate of 0.97 with a false alarm rate of 0.096 for 5mL fluid volume of infiltration. EBI and skin strain sensing can enable non-invasive and real-time IV infiltration detection systems. Fusion of multiple sensing modalities can help to detect expanded range of leaking fluid volumes. The provided performance results and comparisons in this paper are an important step towards clinical translation of sensing technologies for detecting IV infiltration.

Toward Non-Invasive and Automatic Intravenous Infiltration Detection: Evaluation of Bioimpedance and Skin Strain in a Pig Model

PubMed Central

Bicen, A. Ozan; West, Leanne L.; Cesar, Liliana

2018-01-01

Intravenous (IV) therapy is prevalent in hospital settings, where fluids are typically delivered with an IV into a peripheral vein of the patient. IV infiltration is the inadvertent delivery of fluids into the extravascular space rather than into the vein (and requires urgent treatment to avoid scarring and severe tissue damage), for which medical staff currently needs to check patients periodically. In this paper, the performance of two non-invasive sensing modalities, electrical bioimpedance (EBI), and skin strain sensing, for the automatic detection of IV infiltration was investigated in an animal model. Infiltrations were physically simulated on the hind limb of anesthetized pigs, where the sensors for EBI and skin strain sensing were co-located. The obtained data were used to examine the ability to distinguish between infusion into the vein and an infiltration event using bioresistance and bioreactance (derived from EBI), as well as skin strain. Skin strain and bioresistance sensing could achieve detection rates greater than 0.9 for infiltration fluid volumes of 2 and 10 mL, respectively, for a given false positive, i.e., false alarm rate of 0.05. Furthermore, the fusion of multiple sensing modalities could achieve a detection rate of 0.97 with a false alarm rate of 0.096 for 5mL fluid volume of infiltration. EBI and skin strain sensing can enable non-invasive and real-time IV infiltration detection systems. Fusion of multiple sensing modalities can help to detect expanded range of leaking fluid volumes. The provided performance results and comparisons in this paper are an important step towards clinical translation of sensing technologies for detecting IV infiltration. PMID:29692956

New false color mapping for image fusion

NASA Astrophysics Data System (ADS)

Toet, Alexander; Walraven, Jan

1996-03-01

A pixel-based color-mapping algorithm is presented that produces a fused false color rendering of two gray-level images representing different sensor modalities. The resulting images have a higher information content than each of the original images and retain sensor-specific image information. The unique component of each image modality is enhanced in the resulting fused color image representation. First, the common component of the two original input images is determined. Second, the common component is subtracted from the original images to obtain the unique component of each image. Third, the unique component of each image modality is subtracted from the image of the other modality. This step serves to enhance the representation of sensor-specific details in the final fused result. Finally, a fused color image is produced by displaying the images resulting from the last step through, respectively, the red and green channels of a color display. The method is applied to fuse thermal and visual images. The results show that the color mapping enhances the visibility of certain details and preserves the specificity of the sensor information. The fused images also have a fairly natural appearance. The fusion scheme involves only operations on corresponding pixels. The resolution of a fused image is therefore directly related to the resolution of the input images. Before fusing, the contrast of the images can be enhanced and their noise can be reduced by standard image- processing techniques. The color mapping algorithm is computationally simple. This implies that the investigated approaches can eventually be applied in real time and that the hardware needed is not too complicated or too voluminous (an important consideration when it has to fit in an airplane, for instance).

Dynamic modal estimation using instrumental variables

NASA Technical Reports Server (NTRS)

Salzwedel, H.

1980-01-01

A method to determine the modes of dynamical systems is described. The inputs and outputs of a system are Fourier transformed and averaged to reduce the error level. An instrumental variable method that estimates modal parameters from multiple correlations between responses of single input, multiple output systems is applied to estimate aircraft, spacecraft, and off-shore platform modal parameters.

Robotic and artificial intelligence for keyhole neurosurgery: the ROBOCAST project, a multi-modal autonomous path planner.

PubMed

De Momi, E; Ferrigno, G

2010-01-01

The robot and sensors integration for computer-assisted surgery and therapy (ROBOCAST) project (FP7-ICT-2007-215190) is co-funded by the European Union within the Seventh Framework Programme in the field of information and communication technologies. The ROBOCAST project focuses on robot- and artificial-intelligence-assisted keyhole neurosurgery (tumour biopsy and local drug delivery along straight or turning paths). The goal of this project is to assist surgeons with a robotic system controlled by an intelligent high-level controller (HLC) able to gather and integrate information from the surgeon, from diagnostic images, and from an array of on-field sensors. The HLC integrates pre-operative and intra-operative diagnostics data and measurements, intelligence augmentation, multiple-robot dexterity, and multiple sensory inputs in a closed-loop cooperating scheme including a smart interface for improved haptic immersion and integration. This paper, after the overall architecture description, focuses on the intelligent trajectory planner based on risk estimation and human criticism. The current status of development is reported, and first tests on the planner are shown by using a real image stack and risk descriptor phantom. The advantages of using a fuzzy risk description are given by the possibility of upgrading the knowledge on-field without the intervention of a knowledge engineer.

Feasibility demonstration of a massively parallelizable optical near-field sensor for sub-wavelength defect detection and imaging

PubMed Central

Mostafavi, Mahkamehossadat; Diaz, Rodolfo E.

2016-01-01

To detect and resolve sub-wavelength features at optical frequencies, beyond the diffraction limit, requires sensors that interact with the electromagnetic near-field of those features. Most instruments operating in this modality scan a single detector element across the surface under inspection because the scattered signals from a multiplicity of such elements would end up interfering with each other. However, an alternative massively parallelized configuration, capable of interrogating multiple adjacent areas of the surface at the same time, was proposed in 2002. Full physics simulations of the photonic antenna detector element that enables this instrument, show that using conventional red laser light (in the 600 nm range) the detector magnifies the signal from an 8 nm particle by up to 1.5 orders of magnitude. The antenna is a shaped slot element in a 60 nm silver film. The ability of this detector element to resolve λ/78 objects is confirmed experimentally at radio frequencies by fabricating an artificial material structure that mimics the optical permittivity of silver scaled to 2 GHz, and “cutting” into it the slot antenna. The experimental set-up is also used to demonstrate the imaging of a patterned surface in which the critical dimensions of the pattern are λ/22 in size. PMID:27185385

Multi-Modal Nano-Probes for Radionuclide and 5-color Near Infrared Optical Lymphatic Imaging

PubMed Central

Kobayashi, Hisataka; Koyama, Yoshinori; Barrett, Tristan; Hama, Yukihiro; Regino, Celeste A. S.; Shin, In Soo; Jang, Beom-Su; Le, Nhat; Paik, Chang H.; Choyke, Peter L.; Urano, Yasuteru

2008-01-01

Current contrast agents generally have one function and can only be imaged in monochrome, therefore, the majority of imaging methods can only impart uniparametric information. A single nano-particle has the potential to be loaded with multiple payloads. Such multi-modality probes have the ability to be imaged by more than one imaging technique, which could compensate for the weakness or even combine the advantages of each individual modality. Furthermore, optical imaging using different optical probes enables us to achieve multi-color in vivo imaging, wherein multiple parameters can be read from a single image. To allow differentiation of multiple optical signals in vivo, each probe should have a close but different near infrared emission. To this end, we synthesized nano-probes with multi-modal and multi-color potential, which employed a polyamidoamine dendrimer platform linked to both radionuclides and optical probes, permitting dual-modality scintigraphic and 5-color near infrared optical lymphatic imaging using a multiple excitation spectrally-resolved fluorescence imaging technique. PMID:19079788

Spatially distributed modal signals of free shallow membrane shell structronic system

NASA Astrophysics Data System (ADS)

Yue, H. H.; Deng, Z. Q.; Tzou, H. S.

2008-11-01

Based on the smart material and structronics technology, distributed sensor and control of shell structures have been rapidly developed for the last 20 years. This emerging technology has been utilized in aerospace, telecommunication, micro-electromechanical systems and other engineering applications. However, distributed monitoring technique and its resulting global spatially distributed sensing signals of shallow paraboloidal membrane shells are not clearly understood. In this paper, modeling of free flexible paraboloidal shell with spatially distributed sensor, micro-sensing signal characteristics, and location of distributed piezoelectric sensor patches are investigated based on a new set of assumed mode shape functions. Parametric analysis indicates that the signal generation depends on modal membrane strains in the meridional and circumferential directions in which the latter is more significant than the former, when all bending strains vanish in membrane shells. This study provides a modeling and analysis technique for distributed sensors laminated on lightweight paraboloidal flexible structures and identifies critical components and regions that generate significant signals.

PageRank versatility analysis of multilayer modality-based network for exploring the evolution of oil-water slug flow.

PubMed

Gao, Zhong-Ke; Dang, Wei-Dong; Li, Shan; Yang, Yu-Xuan; Wang, Hong-Tao; Sheng, Jing-Ran; Wang, Xiao-Fan

2017-07-14

Numerous irregular flow structures exist in the complicated multiphase flow and result in lots of disparate spatial dynamical flow behaviors. The vertical oil-water slug flow continually attracts plenty of research interests on account of its significant importance. Based on the spatial transient flow information acquired through our designed double-layer distributed-sector conductance sensor, we construct multilayer modality-based network to encode the intricate spatial flow behavior. Particularly, we calculate the PageRank versatility and multilayer weighted clustering coefficient to quantitatively explore the inferred multilayer modality-based networks. Our analysis allows characterizing the complicated evolution of oil-water slug flow, from the opening formation of oil slugs, to the succedent inter-collision and coalescence among oil slugs, and then to the dispersed oil bubbles. These properties render our developed method particularly powerful for mining the essential flow features from the multilayer sensor measurements.

An Holistic Approach for Counsellors: Embracing Multiple Intelligences

ERIC Educational Resources Information Center

Booth, Rosslyn; O'Brien, Patrick John

2008-01-01

This paper explores a range of therapeutic modalities used by counsellors of children and positions those modalities within Gardner's theory of multiple intelligences. Research by O'Brien ("Gardner's theory of multiple intelligence and its implications for the counselling of children." Unpublished doctoral dissertation, Queensland University of…

Effects of auditory and visual modalities in recall of words.

PubMed

Gadzella, B M; Whitehead, D A

1975-02-01

Ten experimental conditions were used to study the effects of auditory and visual (printed words, uncolored and colored pictures) modalities and their various combinations with college students. A recall paradigm was employed in which subjects responded in a written test. Analysis of data showed the auditory modality was superior to visual (pictures) ones but was not significantly different from visual (printed words) modality. In visual modalities, printed words were superior to colored pictures. Generally, conditions with multiple modes of representation of stimuli were significantly higher than for conditions with single modes. Multiple modalities, consisting of two or three modes, did not differ significantly from each other. It was concluded that any two modalities of the stimuli presented simultaneously were just as effective as three in recall of stimulus words.

Bayesian operational modal analysis of Jiangyin Yangtze River Bridge

NASA Astrophysics Data System (ADS)

Brownjohn, James Mark William; Au, Siu-Kui; Zhu, Yichen; Sun, Zhen; Li, Binbin; Bassitt, James; Hudson, Emma; Sun, Hongbin

2018-09-01

Vibration testing of long span bridges is becoming a commissioning requirement, yet such exercises represent the extreme of experimental capability, with challenges for instrumentation (due to frequency range, resolution and km-order separation of sensor) and system identification (because of the extreme low frequencies). The challenge with instrumentation for modal analysis is managing synchronous data acquisition from sensors distributed widely apart inside and outside the structure. The ideal solution is precisely synchronised autonomous recorders that do not need cables, GPS or wireless communication. The challenge with system identification is to maximise the reliability of modal parameters through experimental design and subsequently to identify the parameters in terms of mean values and standard errors. The challenge is particularly severe for modes with low frequency and damping typical of long span bridges. One solution is to apply 'third generation' operational modal analysis procedures using Bayesian approaches in both the planning and analysis stages. The paper presents an exercise on the Jiangyin Yangtze River Bridge, a suspension bridge with a 1385 m main span. The exercise comprised planning of a test campaign to optimise the reliability of operational modal analysis, the deployment of a set of independent data acquisition units synchronised using precision oven controlled crystal oscillators and the subsequent identification of a set of modal parameters in terms of mean and variance errors. Although the bridge has had structural health monitoring technology installed since it was completed, this was the first full modal survey, aimed at identifying important features of the modal behaviour rather than providing fine resolution of mode shapes through the whole structure. Therefore, measurements were made in only the (south) tower, while torsional behaviour was identified by a single measurement using a pair of recorders across the carriageway. The modal survey revealed a first lateral symmetric mode with natural frequency 0.0536 Hz with standard error ±3.6% and damping ratio 4.4% with standard error ±88%. First vertical mode is antisymmetric with frequency 0.11 Hz ± 1.2% and damping ratio 4.9% ± 41%. A significant and novel element of the exercise was planning of the measurement setups and their necessary duration linked to prior estimation of the precision of the frequency and damping estimates. The second novelty is the use of the multi-sensor precision synchronised acquisition without external time reference on a structure of this scale. The challenges of ambient vibration testing and modal identification in a complex environment are addressed leveraging on advances in practical implementation and scientific understanding of the problem.

Ultra-sensitive fluorescent imaging-biosensing using biological photonic crystals

NASA Astrophysics Data System (ADS)

Squire, Kenny; Kong, Xianming; Wu, Bo; Rorrer, Gregory; Wang, Alan X.

2018-02-01

Optical biosensing is a growing area of research known for its low limits of detection. Among optical sensing techniques, fluorescence detection is among the most established and prevalent. Fluorescence imaging is an optical biosensing modality that exploits the sensitivity of fluorescence in an easy-to-use process. Fluorescence imaging allows a user to place a sample on a sensor and use an imager, such as a camera, to collect the results. The image can then be processed to determine the presence of the analyte. Fluorescence imaging is appealing because it can be performed with as little as a light source, a camera and a data processor thus being ideal for nontrained personnel without any expensive equipment. Fluorescence imaging sensors generally employ an immunoassay procedure to selectively trap analytes such as antigens or antibodies. When the analyte is present, the sensor fluoresces thus transducing the chemical reaction into an optical signal capable of imaging. Enhancement of this fluorescence leads to an enhancement in the detection capabilities of the sensor. Diatoms are unicellular algae with a biosilica shell called a frustule. The frustule is porous with periodic nanopores making them biological photonic crystals. Additionally, the porous nature of the frustule allows for large surface area capable of multiple analyte binding sites. In this paper, we fabricate a diatom based ultra-sensitive fluorescence imaging biosensor capable of detecting the antibody mouse immunoglobulin down to a concentration of 1 nM. The measured signal has an enhancement of 6× when compared to sensors fabricated without diatoms.

A dual modality optical fiber sensor

NASA Astrophysics Data System (ADS)

Herrera-Piad, Luis A.; Haus, Joseph W.; Jauregui-Vazquez, Daniel; Lopez-Dieguez, Yanelis; Estudillo-Ayala, Julian M.; Sierra-Hernandez, Juan M.; Hernandez-Garcia, Juan C.; Rojas-Laguna, Roberto

2018-02-01

We propose and demonstrate a fibre optic system based on bi-tapered silica fibre that can simultaneously measure strain and fibre curvature. Both modalities on the signal can be extracted with no measurable crosstalk between them. The experimental signal has a pure phase modulation when strain is applied to the tapered fibre optic section of the sensor and the signal shows only intensity modulation when an un-tapered fibre section is bent. High sensitivity is achieved from the experimental results for strain and bending losses and the estimation of measurement errors is 0.2 and 0.1%, respectively. This system offers low-cost, compactness and it can be adapted for structural health monitoring.

Fiber-Optic Strain Sensors With Linear Characteristics

NASA Technical Reports Server (NTRS)

Egalon, Claudio O.; Rogowski, Robert S.

1993-01-01

Fiber-optic modal domain strain sensors having linear characteristics over wide range of strains proposed. Conceived in effort to improve older fiber-optic strain sensors. Linearity obtained by appropriate choice of design parameters. Pattern of light and dark areas at output end of optical fiber produced by interference between electromagnetic modes in which laser beam propagates in fiber. Photodetector monitors intensity at one point in pattern.

X-ray digital intra-oral tomosynthesis for quasi-three-dimensional imaging: system, reconstruction algorithm, and experiments

NASA Astrophysics Data System (ADS)

Li, Liang; Chen, Zhiqiang; Zhao, Ziran; Wu, Dufan

2013-01-01

At present, there are mainly three x-ray imaging modalities for dental clinical diagnosis: radiography, panorama and computed tomography (CT). We develop a new x-ray digital intra-oral tomosynthesis (IDT) system for quasi-three-dimensional dental imaging which can be seen as an intermediate modality between traditional radiography and CT. In addition to normal x-ray tube and digital sensor used in intra-oral radiography, IDT has a specially designed mechanical device to complete the tomosynthesis data acquisition. During the scanning, the measurement geometry is such that the sensor is stationary inside the patient's mouth and the x-ray tube moves along an arc trajectory with respect to the intra-oral sensor. Therefore, the projection geometry can be obtained without any other reference objects, which makes it be easily accepted in clinical applications. We also present a compressed sensing-based iterative reconstruction algorithm for this kind of intra-oral tomosynthesis. Finally, simulation and experiment were both carried out to evaluate this intra-oral imaging modality and algorithm. The results show that IDT has its potentiality to become a new tool for dental clinical diagnosis.

The coronagraphic Modal Wavefront Sensor: a hybrid focal-plane sensor for the high-contrast imaging of circumstellar environments

NASA Astrophysics Data System (ADS)

Wilby, M. J.; Keller, C. U.; Snik, F.; Korkiakoski, V.; Pietrow, A. G. M.

2017-01-01

The raw coronagraphic performance of current high-contrast imaging instruments is limited by the presence of a quasi-static speckle (QSS) background, resulting from instrumental Non-Common Path Errors (NCPEs). Rapid development of efficient speckle subtraction techniques in data reduction has enabled final contrasts of up to 10-6 to be obtained, however it remains preferable to eliminate the underlying NCPEs at the source. In this work we introduce the coronagraphic Modal Wavefront Sensor (cMWS), a new wavefront sensor suitable for real-time NCPE correction. This combines the Apodizing Phase Plate (APP) coronagraph with a holographic modal wavefront sensor to provide simultaneous coronagraphic imaging and focal-plane wavefront sensing with the science point-spread function. We first characterise the baseline performance of the cMWS via idealised closed-loop simulations, showing that the sensor is able to successfully recover diffraction-limited coronagraph performance over an effective dynamic range of ±2.5 radians root-mean-square (rms) wavefront error within 2-10 iterations, with performance independent of the specific choice of mode basis. We then present the results of initial on-sky testing at the William Herschel Telescope, which demonstrate that the sensor is capable of NCPE sensing under realistic seeing conditions via the recovery of known static aberrations to an accuracy of 10 nm (0.1 radians) rms error in the presence of a dominant atmospheric speckle foreground. We also find that the sensor is capable of real-time measurement of broadband atmospheric wavefront variance (50% bandwidth, 158 nm rms wavefront error) at a cadence of 50 Hz over an uncorrected telescope sub-aperture. When combined with a suitable closed-loop adaptive optics system, the cMWS holds the potential to deliver an improvement of up to two orders of magnitude over the uncorrected QSS floor. Such a sensor would be eminently suitable for the direct imaging and spectroscopy of exoplanets with both existing and future instruments, including EPICS and METIS for the E-ELT.

Interactive wearable systems for upper body rehabilitation: a systematic review.

PubMed

Wang, Qi; Markopoulos, Panos; Yu, Bin; Chen, Wei; Timmermans, Annick

2017-03-11

The development of interactive rehabilitation technologies which rely on wearable-sensing for upper body rehabilitation is attracting increasing research interest. This paper reviews related research with the aim: 1) To inventory and classify interactive wearable systems for movement and posture monitoring during upper body rehabilitation, regarding the sensing technology, system measurements and feedback conditions; 2) To gauge the wearability of the wearable systems; 3) To inventory the availability of clinical evidence supporting the effectiveness of related technologies. A systematic literature search was conducted in the following search engines: PubMed, ACM, Scopus and IEEE (January 2010-April 2016). Forty-five papers were included and discussed in a new cuboid taxonomy which consists of 3 dimensions: sensing technology, feedback modalities and system measurements. Wearable sensor systems were developed for persons in: 1) Neuro-rehabilitation: stroke (n = 21), spinal cord injury (n = 1), cerebral palsy (n = 2), Alzheimer (n = 1); 2) Musculoskeletal impairment: ligament rehabilitation (n = 1), arthritis (n = 1), frozen shoulder (n = 1), bones trauma (n = 1); 3) Others: chronic pulmonary obstructive disease (n = 1), chronic pain rehabilitation (n = 1) and other general rehabilitation (n = 14). Accelerometers and inertial measurement units (IMU) are the most frequently used technologies (84% of the papers). They are mostly used in multiple sensor configurations to measure upper limb kinematics and/or trunk posture. Sensors are placed mostly on the trunk, upper arm, the forearm, the wrist, and the finger. Typically sensors are attachable rather than embedded in wearable devices and garments; although studies that embed and integrate sensors are increasing in the last 4 years. 16 studies applied knowledge of result (KR) feedback, 14 studies applied knowledge of performance (KP) feedback and 15 studies applied both in various modalities. 16 studies have conducted their evaluation with patients and reported usability tests, while only three of them conducted clinical trials including one randomized clinical trial. This review has shown that wearable systems are used mostly for the monitoring and provision of feedback on posture and upper extremity movements in stroke rehabilitation. The results indicated that accelerometers and IMUs are the most frequently used sensors, in most cases attached to the body through ad hoc contraptions for the purpose of improving range of motion and movement performance during upper body rehabilitation. Systems featuring sensors embedded in wearable appliances or garments are only beginning to emerge. Similarly, clinical evaluations are scarce and are further needed to provide evidence on effectiveness and pave the path towards implementation in clinical settings.

New biometric modalities using internal physical characteristics

NASA Astrophysics Data System (ADS)

Mortenson, Juliana (Brooks)

2010-04-01

Biometrics is described as the science of identifying people based on physical characteristics such as their fingerprints, facial features, hand geometry, iris patterns, palm prints, or speech recognition. Notably, all of these physical characteristics are visible or detectable from the exterior of the body. These external characteristics can be lifted, photographed, copied or recorded for unauthorized access to a biometric system. Individual humans are unique internally, however, just as they are unique externally. New biometric modalities have been developed which identify people based on their unique internal characteristics. For example, "BoneprintsTM" use acoustic fields to scan the unique bone density pattern of a thumb pressed on a small acoustic sensor. Thanks to advances in piezoelectric materials the acoustic sensor can be placed in virtually any device such as a steering wheel, door handle, or keyboard. Similarly, "Imp-PrintsTM" measure the electrical impedance patterns of a hand to identify or verify a person's identity. Small impedance sensors can be easily embedded in devices such as smart cards, handles, or wall mounts. These internal biometric modalities rely on physical characteristics which are not visible or photographable, providing an added level of security. In addition, both the acoustic and impedance methods can be combined with physiologic measurements such as acoustic Doppler or impedance plethysmography, respectively. Added verification that the biometric pattern came from a living person can be obtained. These new biometric modalities have the potential to allay user concerns over protection of privacy, while providing a higher level of security.*

An adaptive learning control system for large flexible structures

NASA Technical Reports Server (NTRS)

Thau, F. E.

1985-01-01

The objective of the research has been to study the design of adaptive/learning control systems for the control of large flexible structures. In the first activity an adaptive/learning control methodology for flexible space structures was investigated. The approach was based on using a modal model of the flexible structure dynamics and an output-error identification scheme to identify modal parameters. In the second activity, a least-squares identification scheme was proposed for estimating both modal parameters and modal-to-actuator and modal-to-sensor shape functions. The technique was applied to experimental data obtained from the NASA Langley beam experiment. In the third activity, a separable nonlinear least-squares approach was developed for estimating the number of excited modes, shape functions, modal parameters, and modal amplitude and velocity time functions for a flexible structure. In the final research activity, a dual-adaptive control strategy was developed for regulating the modal dynamics and identifying modal parameters of a flexible structure. A min-max approach was used for finding an input to provide modal parameter identification while not exceeding reasonable bounds on modal displacement.

Integration of Multi-Modal Biomedical Data to Predict Cancer Grade and Patient Survival.

PubMed

Phan, John H; Hoffman, Ryan; Kothari, Sonal; Wu, Po-Yen; Wang, May D

2016-02-01

The Big Data era in Biomedical research has resulted in large-cohort data repositories such as The Cancer Genome Atlas (TCGA). These repositories routinely contain hundreds of matched patient samples for genomic, proteomic, imaging, and clinical data modalities, enabling holistic and multi-modal integrative analysis of human disease. Using TCGA renal and ovarian cancer data, we conducted a novel investigation of multi-modal data integration by combining histopathological image and RNA-seq data. We compared the performances of two integrative prediction methods: majority vote and stacked generalization. Results indicate that integration of multiple data modalities improves prediction of cancer grade and outcome. Specifically, stacked generalization, a method that integrates multiple data modalities to produce a single prediction result, outperforms both single-data-modality prediction and majority vote. Moreover, stacked generalization reveals the contribution of each data modality (and specific features within each data modality) to the final prediction result and may provide biological insights to explain prediction performance.

Influence of model errors in optimal sensor placement

NASA Astrophysics Data System (ADS)

Vincenzi, Loris; Simonini, Laura

2017-02-01

The paper investigates the role of model errors and parametric uncertainties in optimal or near optimal sensor placements for structural health monitoring (SHM) and modal testing. The near optimal set of measurement locations is obtained by the Information Entropy theory; the results of placement process considerably depend on the so-called covariance matrix of prediction error as well as on the definition of the correlation function. A constant and an exponential correlation function depending on the distance between sensors are firstly assumed; then a proposal depending on both distance and modal vectors is presented. With reference to a simple case-study, the effect of model uncertainties on results is described and the reliability and the robustness of the proposed correlation function in the case of model errors are tested with reference to 2D and 3D benchmark case studies. A measure of the quality of the obtained sensor configuration is considered through the use of independent assessment criteria. In conclusion, the results obtained by applying the proposed procedure on a real 5-spans steel footbridge are described. The proposed method also allows to better estimate higher modes when the number of sensors is greater than the number of modes of interest. In addition, the results show a smaller variation in the sensor position when uncertainties occur.

Noncontact Sleep Study by Multi-Modal Sensor Fusion.

PubMed

Chung, Ku-Young; Song, Kwangsub; Shin, Kangsoo; Sohn, Jinho; Cho, Seok Hyun; Chang, Joon-Hyuk

2017-07-21

Polysomnography (PSG) is considered as the gold standard for determining sleep stages, but due to the obtrusiveness of its sensor attachments, sleep stage classification algorithms using noninvasive sensors have been developed throughout the years. However, the previous studies have not yet been proven reliable. In addition, most of the products are designed for healthy customers rather than for patients with sleep disorder. We present a novel approach to classify sleep stages via low cost and noncontact multi-modal sensor fusion, which extracts sleep-related vital signals from radar signals and a sound-based context-awareness technique. This work is uniquely designed based on the PSG data of sleep disorder patients, which were received and certified by professionals at Hanyang University Hospital. The proposed algorithm further incorporates medical/statistical knowledge to determine personal-adjusted thresholds and devise post-processing. The efficiency of the proposed algorithm is highlighted by contrasting sleep stage classification performance between single sensor and sensor-fusion algorithms. To validate the possibility of commercializing this work, the classification results of this algorithm were compared with the commercialized sleep monitoring device, ResMed S+. The proposed algorithm was investigated with random patients following PSG examination, and results show a promising novel approach for determining sleep stages in a low cost and unobtrusive manner.

Noncontact Sleep Study by Multi-Modal Sensor Fusion

PubMed Central

Chung, Ku-young; Song, Kwangsub; Shin, Kangsoo; Sohn, Jinho; Cho, Seok Hyun; Chang, Joon-Hyuk

2017-01-01

Polysomnography (PSG) is considered as the gold standard for determining sleep stages, but due to the obtrusiveness of its sensor attachments, sleep stage classification algorithms using noninvasive sensors have been developed throughout the years. However, the previous studies have not yet been proven reliable. In addition, most of the products are designed for healthy customers rather than for patients with sleep disorder. We present a novel approach to classify sleep stages via low cost and noncontact multi-modal sensor fusion, which extracts sleep-related vital signals from radar signals and a sound-based context-awareness technique. This work is uniquely designed based on the PSG data of sleep disorder patients, which were received and certified by professionals at Hanyang University Hospital. The proposed algorithm further incorporates medical/statistical knowledge to determine personal-adjusted thresholds and devise post-processing. The efficiency of the proposed algorithm is highlighted by contrasting sleep stage classification performance between single sensor and sensor-fusion algorithms. To validate the possibility of commercializing this work, the classification results of this algorithm were compared with the commercialized sleep monitoring device, ResMed S+. The proposed algorithm was investigated with random patients following PSG examination, and results show a promising novel approach for determining sleep stages in a low cost and unobtrusive manner. PMID:28753994

Electromagnetic Tracking Navigation to Guide Radiofrequency Ablation (RFA) of a Lung Tumor

PubMed Central

Amalou, Hayet; Wood, Bradford J.

2013-01-01

Radiofrequency ablation (RFA) may be an option for patients with lung tumors who have unresectable disease and are not suitable for available palliative modalities. RFA electrode positioning may take several attempts, necessitating multiple imaging acquisitions or continuous use of CT (Computed Tomography). Electromagnetic tracking utilizes miniature sensors integrated with RFA equipment to guide tools in real-time, while referencing to pre-procedure imaging. This technology was demonstrated successfully during a lung tumor ablation, and was more accurate at targeting the tumor, compared to traditional freehand needle insertion. It is possible, although speculative and anecdotal, that more accuracy could prevent unnecessary repositioning punctures and decrease radiation exposure. Electromagnetic tracking has theoretical potential to benefit minimally invasive interventions. PMID:23207535

Numerical performance analysis of quartz tuning fork-based force sensors

NASA Astrophysics Data System (ADS)

Dagdeviren, Omur E.; Schwarz, Udo D.

2017-01-01

Quartz tuning fork-based force sensors where one prong is immobilized onto a holder while the other one is allowed to oscillate freely (‘qPlus’ configuration) are in widespread use for high-resolution scanning probe microscopy applications. Due to the small size of the tuning forks (≈3 mm) and the complexity of the sensor assemblies, the reliable and repeatable manufacturing of the sensors has been challenging. In this paper, we investigate the contribution of the amount and location of the epoxy glue used to attach the tuning fork to its holder on the sensor’s performance. Towards this end, we use finite element analysis to model the entire sensor assembly and to perform static and dynamic numerical simulations. Our analysis reveals that increasing the thickness of the epoxy layer between prong and holder results in a decrease of the sensor’s spring constant, eigenfrequency, and quality factor while showing an increasing deviation from oscillation in its primary modal shape. Adding epoxy at the sides of the tuning fork also leads to a degradation of the quality factor even though in this case, spring constant and eigenfrequency rise in tandem with a lessening of the deviation from its ideal modal shape.

Sensor 17 Thermal Isolation Mounting Structure (TIMS) Design Improvements

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

Enstrom, K.

2015-09-04

The SENSOR 17 thermographic camera weighs approximately 0.5lbs, has a fundamental mode of 167 Hz, and experiences 0.75W of heat leakage in through the TIMS. The configuration, shown in Figure 1, is comprised of four 300 Series SST washers paired in tandem with P.E.I (Ultem 100) washers. The SENSOR 17 sensor is mounted to a 300 series stainless plate with A-shaped arms. The Plate can be assumed to be at ambient temperatures (≈293K) and the I.R. Mount needs to be cooled to 45K. It is attached to the tip of a cryocooler by a ‘cold strap’ and is assumed tomore » be at the temperature of the cold-strap (≈45K). During flights SENSOR 17 experiences excitations at frequencies centered around 10-30Hz, 60Hz, and 120Hz from the aircraft flight environment. The temporal progression described below depicts the 1st Modal shape at the systems resonant frequency. This simulation indicates Modal articulation will cause a pitch rate of the camera with respect to the body axis of the airplane. This articulation shows up as flutter in the camera.« less

Intranasal Insulin for Improving Cognitive Function in Multiple Sclerosis

DTIC Science & Technology

2017-10-01

Insulin, Symbol Digit Modalities Test , Minimal Assessment of Cognitive Function in Multiple Sclerosis 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF...going to evaluate if intranasal insulin improves cognition in people with MS, as assessed by standardized cognitive assessment tests . 2. KEYWORDS...Multiple Sclerosis, Cognitive Impairment, Neurodegenerative diseases, Intranasal Insulin, Symbol Digit Modalities Test , Minimal Assessment of Cognitive

A Multi-Modal Face Recognition Method Using Complete Local Derivative Patterns and Depth Maps

PubMed Central

Yin, Shouyi; Dai, Xu; Ouyang, Peng; Liu, Leibo; Wei, Shaojun

2014-01-01

In this paper, we propose a multi-modal 2D + 3D face recognition method for a smart city application based on a Wireless Sensor Network (WSN) and various kinds of sensors. Depth maps are exploited for the 3D face representation. As for feature extraction, we propose a new feature called Complete Local Derivative Pattern (CLDP). It adopts the idea of layering and has four layers. In the whole system, we apply CLDP separately on Gabor features extracted from a 2D image and depth map. Then, we obtain two features: CLDP-Gabor and CLDP-Depth. The two features weighted by the corresponding coefficients are combined together in the decision level to compute the total classification distance. At last, the probe face is assigned the identity with the smallest classification distance. Extensive experiments are conducted on three different databases. The results demonstrate the robustness and superiority of the new approach. The experimental results also prove that the proposed multi-modal 2D + 3D method is superior to other multi-modal ones and CLDP performs better than other Local Binary Pattern (LBP) based features. PMID:25333290

Active Noise Control of Low Speed Fan Rotor-Stator Modes

NASA Technical Reports Server (NTRS)

Sutliff, Daniel L.; Hu, Ziqiang; Pla, Frederic G.; Heidelberg, Laurence J.

1996-01-01

This report describes the Active Noise Cancellation System designed by General Electric and tested in the NASA Lewis Research Center's 48 inch Active Noise Control Fan. The goal of this study was to assess the feasibility of using wall mounted secondary acoustic sources and sensors within the duct of a high bypass turbofan aircraft engine for active noise cancellation of fan tones. The control system is based on a modal control approach. A known acoustic mode propagating in the fan duct is cancelled using an array of flush-mounted compact sound sources. Controller inputs are signals from a shaft encoder and a microphone array which senses the residual acoustic mode in the duct. The canceling modal signal is generated by a modal controller. The key results are that the (6,0) mode was completely eliminated at 920 Hz and substantially reduced elsewhere. The total tone power was reduced 9.4 dB. Farfield 2BPF SPL reductions of 13 dB were obtained. The (4,0) and (4,1) modes were reduced simultaneously yielding a 15 dB modal PWL decrease. Global attenuation of PWL was obtained using an actuator and sensor system totally contained within the duct.

Quantitative multi-modal NDT data analysis

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

Heideklang, René; Shokouhi, Parisa

2014-02-18

A single NDT technique is often not adequate to provide assessments about the integrity of test objects with the required coverage or accuracy. In such situations, it is often resorted to multi-modal testing, where complementary and overlapping information from different NDT techniques are combined for a more comprehensive evaluation. Multi-modal material and defect characterization is an interesting task which involves several diverse fields of research, including signal and image processing, statistics and data mining. The fusion of different modalities may improve quantitative nondestructive evaluation by effectively exploiting the augmented set of multi-sensor information about the material. It is the redundantmore » information in particular, whose quantification is expected to lead to increased reliability and robustness of the inspection results. There are different systematic approaches to data fusion, each with its specific advantages and drawbacks. In our contribution, these will be discussed in the context of nondestructive materials testing. A practical study adopting a high-level scheme for the fusion of Eddy Current, GMR and Thermography measurements on a reference metallic specimen with built-in grooves will be presented. Results show that fusion is able to outperform the best single sensor regarding detection specificity, while retaining the same level of sensitivity.« less

Experimental modal analysis on fresh-frozen human hemipelvic bones employing a 3D laser vibrometer for the purpose of modal parameter identification.

PubMed

Neugebauer, R; Werner, M; Voigt, C; Steinke, H; Scholz, R; Scherer, S; Quickert, M

2011-05-17

To provide a close-to-reality simulation model, such as for improved surgery planning, this model has to be experimentally verified. The present article describes the use of a 3D laser vibrometer for determining modal parameters of human pelvic bones that can be used for verifying a finite elements model. Compared to previously used sensors, such as acceleration sensors or strain gauges, the laser vibrometric procedure used here is a non-contact and non-interacting measuring method that allows a high density of measuring points and measurement in a global coordinate system. Relevant modal parameters were extracted from the measured data and provided for verifying the model. The use of the 3D laser vibrometer allowed the establishment of a process chain for experimental examination of the pelvic bones that was optimized with respect to time and effort involved. The transfer functions determined feature good signal quality. Furthermore, a comparison of the results obtained from pairs of pelvic bones showed that repeatable measurements can be obtained with the method used. Copyright © 2011 Elsevier Ltd. All rights reserved.

Fiber optic sensor technology - An opportunity for smart aerospace structures

NASA Technical Reports Server (NTRS)

Heyman, J. S.; Rogowski, R. S.; Claus, R. O.

1988-01-01

Fiber optic sensors provide the opportunity for fabricating materials with internal sensors which can serve as lifetime health monitors, analogous to a central nervous system. The embedded fiber optic sensors can be interrogated by various techniques to measure internal strain, temperature, pressure, acoustic waves and other parameters indicative of structural integrity. Experiments have been conducted with composite samples with embedded sensors to measure strain using optical time domain reflectometry, modal interference and an optical phase locked loop. Fiber optic sensors have been developed to detect acoustic emission and impact damage and have been demonstrated for cure monitoring. These sensors have the potential for lifetime monitoring of structural properties, providing real time nondestructive evaluation.

Development of an electromagnetic imaging system for well bore integrity inspection

NASA Astrophysics Data System (ADS)

Plotnikov, Yuri; Wheeler, Frederick W.; Mandal, Sudeep; Climent, Helene C.; Kasten, A. Matthias; Ross, William

2017-02-01

State-of-the-art imaging technologies for monitoring the integrity of oil and gas well bores are typically limited to the inspection of metal casings and cement bond interfaces close to the first casing region. The objective of this study is to develop and evaluate a novel well-integrity inspection system that is capable of providing enhanced information about the flaw structure and topology of hydrocarbon producing well bores. In order to achieve this, we propose the development of a multi-element electromagnetic (EM) inspection tool that can provide information about material loss in the first and second casing structure as well as information about eccentricity between multiple casing strings. Furthermore, the information gathered from the EM inspection tool will be combined with other imaging modalities (e.g. data from an x-ray backscatter imaging device). The independently acquired data are then fused to achieve a comprehensive assessment of integrity with greater accuracy. A test rig composed of several concentric metal casings with various defect structures was assembled and imaged. Initial test results were obtained with a scanning system design that includes a single transmitting coil and several receiving coils mounted on a single rod. A mechanical linear translation stage was used to move the EM sensors in the axial direction during data acquisition. For simplicity, a single receiving coil and repetitive scans were employed to simulate performance of the designed receiving sensor array system. The resulting electromagnetic images enable the detection of the metal defects in the steel pipes. Responses from several sensors were used to assess the location and amount of material loss in the first and second metal pipe as well as the relative eccentric position between these two pipes. The results from EM measurements and x-ray backscatter simulations demonstrate that data fusion from several sensing modalities can provide an enhanced assessment of flaw structures in producing well bores and potentially allow for early detection of anomalies that if undetected might lead to catastrophic failures.

Combinations of Multiple Neuroimaging Markers using Logistic Regression for Auxiliary Diagnosis of Alzheimer Disease and Mild Cognitive Impairment.

PubMed

Mao, Nini; Liu, Yunting; Chen, Kewei; Yao, Li; Wu, Xia

2018-06-05

Multiple neuroimaging modalities have been developed providing various aspects of information on the human brain. Used together and properly, these complementary multimodal neuroimaging data integrate multisource information which can facilitate a diagnosis and improve the diagnostic accuracy. In this study, 3 types of brain imaging data (sMRI, FDG-PET, and florbetapir-PET) were fused in the hope to improve diagnostic accuracy, and multivariate methods (logistic regression) were applied to these trimodal neuroimaging indices. Then, the receiver-operating characteristic (ROC) method was used to analyze the outcomes of the logistic classifier, with either each index, multiples from each modality, or all indices from all 3 modalities, to investigate their differential abilities to identify the disease. With increasing numbers of indices within each modality and across modalities, the accuracy of identifying Alzheimer disease (AD) increases to varying degrees. For example, the area under the ROC curve is above 0.98 when all the indices from the 3 imaging data types are combined. Using a combination of different indices, the results confirmed the initial hypothesis that different biomarkers were potentially complementary, and thus the conjoint analysis of multiple information from multiple sources would improve the capability to identify diseases such as AD and mild cognitive impairment. © 2018 S. Karger AG, Basel.

Framework and implementation of a continuous network-wide health monitoring system for roadways

NASA Astrophysics Data System (ADS)

Wang, Ming; Birken, Ralf; Shahini Shamsabadi, Salar

2014-03-01

According to the 2013 ASCE report card America's infrastructure scores only a D+. There are more than four million miles of roads (grade D) in the U.S. requiring a broad range of maintenance activities. The nation faces a monumental problem of infrastructure management in the scheduling and implementation of maintenance and repair operations, and in the prioritization of expenditures within budgetary constraints. The efficient and effective performance of these operations however is crucial to ensuring roadway safety, preventing catastrophic failures, and promoting economic growth. There is a critical need for technology that can cost-effectively monitor the condition of a network-wide road system and provide accurate, up-to-date information for maintenance activity prioritization. The Versatile Onboard Traffic Embedded Roaming Sensors (VOTERS) project provides a framework and the sensing capability to complement periodical localized inspections to continuous network-wide health monitoring. Research focused on the development of a cost-effective, lightweight package of multi-modal sensor systems compatible with this framework. An innovative software infrastructure is created that collects, processes, and evaluates these large time-lapse multi-modal data streams. A GIS-based control center manages multiple inspection vehicles and the data for further analysis, visualization, and decision making. VOTERS' technology can monitor road conditions at both the surface and sub-surface levels while the vehicle is navigating through daily traffic going about its normal business, thereby allowing for network-wide frequent assessment of roadways. This deterioration process monitoring at unprecedented time and spatial scales provides unique experimental data that can be used to improve life-cycle cost analysis models.

A 24-Week Multi-Modality Exercise Program Improves Executive Control in Older Adults with a Self-Reported Cognitive Complaint: Evidence from the Antisaccade Task.

PubMed

Heath, Matthew; Shellington, Erin; Titheridge, Sam; Gill, Dawn P; Petrella, Robert J

2017-01-01

Exercise programs involving aerobic and resistance training (i.e., multiple-modality) have shown promise in improving cognition and executive control in older adults at risk, or experiencing, cognitive decline. It is, however, unclear whether cognitive training within a multiple-modality program elicits an additive benefit to executive/cognitive processes. This is an important question to resolve in order to identify optimal training programs that delay, or ameliorate, executive deficits in persons at risk for further cognitive decline. In the present study, individuals with a self-reported cognitive complaint (SCC) participated in a 24-week multiple-modality (i.e., the M2 group) exercise intervention program. In addition, a separate group of individuals with a SCC completed the same aerobic and resistance training as the M2 group but also completed a cognitive-based stepping task (i.e., multiple-modality, mind-motor intervention: M4 group). Notably, pre- and post-intervention executive control was examined via the antisaccade task (i.e., eye movement mirror-symmetrical to a target). Antisaccades are an ideal tool for the study of individuals with subtle executive deficits because of its hands- and language-free nature and because the task's neural mechanisms are linked to neuropathology in cognitive decline (i.e., prefrontal cortex). Results showed that M2 and M4 group antisaccade reaction times reliably decreased from pre- to post-intervention and the magnitude of the decrease was consistent across groups. Thus, multi-modality exercise training improved executive performance in persons with a SCC independent of mind-motor training. Accordingly, we propose that multiple-modality training provides a sufficient intervention to improve executive control in persons with a SCC.

Efficient integration of spectral features for vehicle tracking utilizing an adaptive sensor

NASA Astrophysics Data System (ADS)

Uzkent, Burak; Hoffman, Matthew J.; Vodacek, Anthony

2015-03-01

Object tracking in urban environments is an important and challenging problem that is traditionally tackled using visible and near infrared wavelengths. By inserting extended data such as spectral features of the objects one can improve the reliability of the identification process. However, huge increase in data created by hyperspectral imaging is usually prohibitive. To overcome the complexity problem, we propose a persistent air-to-ground target tracking system inspired by a state-of-the-art, adaptive, multi-modal sensor. The adaptive sensor is capable of providing panchromatic images as well as the spectra of desired pixels. This addresses the data challenge of hyperspectral tracking by only recording spectral data as needed. Spectral likelihoods are integrated into a data association algorithm in a Bayesian fashion to minimize the likelihood of misidentification. A framework for controlling spectral data collection is developed by incorporating motion segmentation information and prior information from a Gaussian Sum filter (GSF) movement predictions from a multi-model forecasting set. An intersection mask of the surveillance area is extracted from OpenStreetMap source and incorporated into the tracking algorithm to perform online refinement of multiple model set. The proposed system is tested using challenging and realistic scenarios generated in an adverse environment.

Phase discriminating capacitive array sensor system

NASA Technical Reports Server (NTRS)

Vranish, John M. (Inventor); Rahim, Wadi (Inventor)

1993-01-01

A phase discriminating capacitive sensor array system which provides multiple sensor elements which are maintained at a phase and amplitude based on a frequency reference provided by a single frequency stabilized oscillator. Sensor signals provided by the multiple sensor elements are controlled by multiple phase control units, which correspond to the multiple sensor elements, to adjust the sensor signals from the multiple sensor elements based on the frequency reference. The adjustment made to the sensor signals is indicated by output signals which indicate the proximity of the object. The output signals may also indicate the closing speed of the object based on the rate of change of the adjustment made, and the edges of the object based on a sudden decrease in the adjustment made.

Flight-Ready TDLAS Combustion Sensor for the HIFiRE 2 Hypersonic Research Program

DTIC Science & Technology

2009-09-01

Noise Sources 20 5.7 Total System Performance 21 6.0 ZOLO ARCHITECTURE 22 7.0 DESIGN DETAILS 23 7.1 Laser and Drive Electronics 23 7.2 Fiber Couplers...targets 8 2 Tunable Diode Laser Absorption Spectroscopy experiment 9 3 Light absorption by water vapor near 1393 nm 10 4a light transmission vs time 10...20 13 multimode fiber modal noise 21 14 TDLAS sensor architecture 22 15 sensor exploded view 23 16 sensor outline and mounting 23 17 laser power and

Blind identification of full-field vibration modes from video measurements with phase-based video motion magnification

NASA Astrophysics Data System (ADS)

Yang, Yongchao; Dorn, Charles; Mancini, Tyler; Talken, Zachary; Kenyon, Garrett; Farrar, Charles; Mascareñas, David

2017-02-01

Experimental or operational modal analysis traditionally requires physically-attached wired or wireless sensors for vibration measurement of structures. This instrumentation can result in mass-loading on lightweight structures, and is costly and time-consuming to install and maintain on large civil structures, especially for long-term applications (e.g., structural health monitoring) that require significant maintenance for cabling (wired sensors) or periodic replacement of the energy supply (wireless sensors). Moreover, these sensors are typically placed at a limited number of discrete locations, providing low spatial sensing resolution that is hardly sufficient for modal-based damage localization, or model correlation and updating for larger-scale structures. Non-contact measurement methods such as scanning laser vibrometers provide high-resolution sensing capacity without the mass-loading effect; however, they make sequential measurements that require considerable acquisition time. As an alternative non-contact method, digital video cameras are relatively low-cost, agile, and provide high spatial resolution, simultaneous, measurements. Combined with vision based algorithms (e.g., image correlation, optical flow), video camera based measurements have been successfully used for vibration measurements and subsequent modal analysis, based on techniques such as the digital image correlation (DIC) and the point-tracking. However, they typically require speckle pattern or high-contrast markers to be placed on the surface of structures, which poses challenges when the measurement area is large or inaccessible. This work explores advanced computer vision and video processing algorithms to develop a novel video measurement and vision-based operational (output-only) modal analysis method that alleviate the need of structural surface preparation associated with existing vision-based methods and can be implemented in a relatively efficient and autonomous manner with little user supervision and calibration. First a multi-scale image processing method is applied on the frames of the video of a vibrating structure to extract the local pixel phases that encode local structural vibration, establishing a full-field spatiotemporal motion matrix. Then a high-spatial dimensional, yet low-modal-dimensional, over-complete model is used to represent the extracted full-field motion matrix using modal superposition, which is physically connected and manipulated by a family of unsupervised learning models and techniques, respectively. Thus, the proposed method is able to blindly extract modal frequencies, damping ratios, and full-field (as many points as the pixel number of the video frame) mode shapes from line of sight video measurements of the structure. The method is validated by laboratory experiments on a bench-scale building structure and a cantilever beam. Its ability for output (video measurements)-only identification and visualization of the weakly-excited mode is demonstrated and several issues with its implementation are discussed.

Fixed Base Modal Survey of the MPCV Orion European Service Module Structural Test Article

NASA Technical Reports Server (NTRS)

Winkel, James P.; Akers, J. C.; Suarez, Vicente J.; Staab, Lucas D.; Napolitano, Kevin L.

2017-01-01

Recently, the MPCV Orion European Service Module Structural Test Article (E-STA) underwent sine vibration testing using the multi-axis shaker system at NASA GRC Plum Brook Station Mechanical Vibration Facility (MVF). An innovative approach using measured constraint shapes at the interface of E-STA to the MVF allowed high-quality fixed base modal parameters of the E-STA to be extracted, which have been used to update the E-STA finite element model (FEM), without the need for a traditional fixed base modal survey. This innovative approach provided considerable program cost and test schedule savings. This paper documents this modal survey, which includes the modal pretest analysis sensor selection, the fixed base methodology using measured constraint shapes as virtual references and measured frequency response functions, and post-survey comparison between measured and analysis fixed base modal parameters.

40 CFR 1033.520 - Alternative ramped modal cycles.

Code of Federal Regulations, 2012 CFR

2012-07-01

...) Following the completion of the third test phase of the applicable ramped modal cycle, conduct the post... POLLUTION CONTROLS CONTROL OF EMISSIONS FROM LOCOMOTIVES Test Procedures § 1033.520 Alternative ramped modal... locomotive notch settings. Ramped modal cycles combine multiple test modes of a discrete-mode steady-state...

A novel automated method for doing registration and 3D reconstruction from multi-modal RGB/IR image sequences

NASA Astrophysics Data System (ADS)

Kirby, Richard; Whitaker, Ross

2016-09-01

In recent years, the use of multi-modal camera rigs consisting of an RGB sensor and an infrared (IR) sensor have become increasingly popular for use in surveillance and robotics applications. The advantages of using multi-modal camera rigs include improved foreground/background segmentation, wider range of lighting conditions under which the system works, and richer information (e.g. visible light and heat signature) for target identification. However, the traditional computer vision method of mapping pairs of images using pixel intensities or image features is often not possible with an RGB/IR image pair. We introduce a novel method to overcome the lack of common features in RGB/IR image pairs by using a variational methods optimization algorithm to map the optical flow fields computed from different wavelength images. This results in the alignment of the flow fields, which in turn produce correspondences similar to those found in a stereo RGB/RGB camera rig using pixel intensities or image features. In addition to aligning the different wavelength images, these correspondences are used to generate dense disparity and depth maps. We obtain accuracies similar to other multi-modal image alignment methodologies as long as the scene contains sufficient depth variations, although a direct comparison is not possible because of the lack of standard image sets from moving multi-modal camera rigs. We test our method on synthetic optical flow fields and on real image sequences that we created with a multi-modal binocular stereo RGB/IR camera rig. We determine our method's accuracy by comparing against a ground truth.

Sensor and information fusion for improved hostile fire situational awareness

NASA Astrophysics Data System (ADS)

Scanlon, Michael V.; Ludwig, William D.

2010-04-01

A research-oriented Army Technology Objective (ATO) named Sensor and Information Fusion for Improved Hostile Fire Situational Awareness uniquely focuses on the underpinning technologies to detect and defeat any hostile threat; before, during, and after its occurrence. This is a joint effort led by the Army Research Laboratory, with the Armaments and the Communications and Electronics Research, Development, and Engineering Centers (CERDEC and ARDEC) partners. It addresses distributed sensor fusion and collaborative situational awareness enhancements, focusing on the underpinning technologies to detect/identify potential hostile shooters prior to firing a shot and to detect/classify/locate the firing point of hostile small arms, mortars, rockets, RPGs, and missiles after the first shot. A field experiment conducted addressed not only diverse modality sensor performance and sensor fusion benefits, but gathered useful data to develop and demonstrate the ad hoc networking and dissemination of relevant data and actionable intelligence. Represented at this field experiment were various sensor platforms such as UGS, soldier-worn, manned ground vehicles, UGVs, UAVs, and helicopters. This ATO continues to evaluate applicable technologies to include retro-reflection, UV, IR, visible, glint, LADAR, radar, acoustic, seismic, E-field, narrow-band emission and image processing techniques to detect the threats with very high confidence. Networked fusion of multi-modal data will reduce false alarms and improve actionable intelligence by distributing grid coordinates, detection report features, and imagery of threats.

Multiple-modality exercise and mind-motor training to improve cardiovascular health and fitness in older adults at risk for cognitive impairment: A randomized controlled trial.

PubMed

Boa Sorte Silva, Narlon C; Gregory, Michael A; Gill, Dawn P; Petrella, Robert J

The effects of multiple-modality exercise on arterial stiffening and cardiovascular fitness has not been fully explored. To explore the influence of a 24-week multiple-modality exercise program associated with a mind-motor training in cardiovascular health and fitness in community-dwelling older adults, compared to multiple-modality exercise (M2) alone. Participants (n=127, aged 67.5 [7.3] years, 71% females) were randomized to either M4 or M2 groups. Both groups received multiple-modality exercise intervention (60min/day, 3days/week for 24-weeks); however, the M4 group underwent additional 15min of mind-motor training, whereas the M2 group received 15min of balance training. Participants were assessed at 24-weeks and after a 28-week non-contact follow-up (52-weeks). at 52-weeks, the M4 group demonstrated a greater VO2max (ml/kg/min) compared to the M2 group (mean difference: 2.39, 95% CI: 0. 61 to 4.16, p=0.009). Within-group analysis indicated that the M4 group demonstrated a positive change in VO2max at 24-weeks (mean change: 1.93, 95% CI: 0.82 to 3.05, p=0.001) and 52-weeks (4.02, 95% CI: 2.71 to 5.32, p=0.001). Similarly, the M2 group increased VO2max at 24-weeks (2.28, 95% CI: 1.23 to 3.32, p<0.001) and 52-weeks (1.63, 95% CI: 0.43 to 2.83, p=0.008). Additionally, the M2 group decreased 24h SBP (mmHg) at 24-weeks (-2.31, 95% CI: -4.61 to -0.01, p=0.049); whereas the M4 group improved 24h DBP (-1.6, 95% CI: -3.03 to -0.17, p=0.028) at 52-weeks. Mind-motor training associated with multiple-modality exercise can positively impact cardiovascular fitness to the same extent as multiple-modality exercise alone. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Collaboration of Miniature Multi-Modal Mobile Smart Robots over a Network

DTIC Science & Technology

2015-08-14

theoretical research on mathematics of failures in sensor-network-based miniature multimodal mobile robots and electromechanical systems. The views...theoretical research on mathematics of failures in sensor-network-based miniature multimodal mobile robots and electromechanical systems. The...independently evolving research directions based on physics-based models of mechanical, electromechanical and electronic devices, operational constraints

Design of a piezoelectric-based structural health monitoring system for damage detection in composite materials

NASA Astrophysics Data System (ADS)

Kessler, Seth S.; Spearing, S. Mark

2002-07-01

Cost-effective and reliable damage detection is critical for the utilization of composite materials. This paper presents the conclusions of an experimental and analytical survey of candidate methods for in-situ damage detection in composite structures. Experimental results are presented for the application of modal analysis and Lamb wave techniques to quasi-isotropic graphite/epoxy test specimens containing representative damage. Piezoelectric patches were used as actuators and sensors for both sets of experiments. Modal analysis methods were reliable for detecting small amounts of global damage in a simple composite structure. By comparison, Lamb wave methods were sensitive to all types of local damage present between the sensor and actuator, provided useful information about damage presence and severity, and present the possibility of estimating damage type and location. Analogous experiments were also performed for more complex built-up structures. These techniques are suitable for structural health monitoring applications since they can be applied with low power conformable sensors and can provide useful information about the state of a structure during operation. Piezoelectric patches could also be used as multipurpose sensors to detect damage by a variety of methods such as modal analysis, Lamb wave, acoustic emission and strain based methods simultaneously, by altering driving frequencies and sampling rates. This paper present guidelines and recommendations drawn from this research to assist in the design of a structural health monitoring system for a vehicle. These systems will be an important component in future designs of air and spacecraft to increase the feasibility of their missions.

Eigensystem realization algorithm user's guide forVAX/VMS computers: Version 931216

NASA Technical Reports Server (NTRS)

Pappa, Richard S.

1994-01-01

The eigensystem realization algorithm (ERA) is a multiple-input, multiple-output, time domain technique for structural modal identification and minimum-order system realization. Modal identification is the process of calculating structural eigenvalues and eigenvectors (natural vibration frequencies, damping, mode shapes, and modal masses) from experimental data. System realization is the process of constructing state-space dynamic models for modern control design. This user's guide documents VAX/VMS-based FORTRAN software developed by the author since 1984 in conjunction with many applications. It consists of a main ERA program and 66 pre- and post-processors. The software provides complete modal identification capabilities and most system realization capabilities.

Modal control of an oblique wing aircraft

NASA Technical Reports Server (NTRS)

Phillips, James D.

1989-01-01

A linear modal control algorithm is applied to the NASA Oblique Wing Research Aircraft (OWRA). The control law is evaluated using a detailed nonlinear flight simulation. It is shown that the modal control law attenuates the coupling and nonlinear aerodynamics of the oblique wing and remains stable during control saturation caused by large command inputs or large external disturbances. The technique controls each natural mode independently allowing single-input/single-output techniques to be applied to multiple-input/multiple-output systems.

Asian Perspectives on Diagnostic and Therapeutic Strategies in Inflammatory Bowel Disease: Report and Analysis of a Survey with Questionnaires.

PubMed

Yoshida, Atsushi; Ueno, Fumiaki; Morizane, Toshio; Joh, Takashi; Kamiya, Takeshi; Takahashi, Shin''ichi; Tokunaga, Kengo; Iwakiri, Ryuichi; Kinoshita, Yoshikazu; Suzuki, Hidekazu; Naito, Yuji; Uchiyama, Kazuhiko; Fukodo, Shin; Chan, Francis K L; Halm, Ki-Baik; Kachintorn, Udom; Fock, Kwong Ming; Rani, Abdul Aziz; Syam, Ari Fahrial; Sollano, Jose D; Zhu, Qi

2017-01-01

Diagnostic and therapeutic strategies in inflammatory bowel disease (IBD) vary among countries in terms of availability of modalities, affordability of health care resource, health care policy and cultural background. This may be the case in different countries in Eastern Asia. The aim of this study was to determine and understand the differences in diagnostic and therapeutic strategies of IBD between Japan and the rest of Asian countries (ROA). Questionnaires with regard to clinical practice in IBD were distributed to members of the International Gastroenterology Consensus Symposium Study Group. The responders were allowed to select multiple items for each question, as multiple modalities are frequently utilized in the diagnosis and the management of IBD. Dependency and independency of selected items for each question were evaluated by the Bayesian network analysis. The selected diagnostic modalities were not very different between Japan and ROA, except for those related to small bowel investigations. Balloon-assisted enteroscopy and small bowel follow through are frequently used in Japan, while CT/MR enterography is popular in ROA. Therapeutic modalities for IBD depend on availability of such modalities in clinical practice. As far as modalities commonly available in both regions are concerned, there seemed to be similarity in the selection of each therapeutic modality. However, evaluation of dependency of separate therapeutic modalities by Bayesian network analysis disclosed some difference in therapeutic strategies between Japan and ROA. Although selected modalities showed some similarity, Bayesian network analysis elicited certain differences in the clinical approaches combining multiple modalities in various aspects of IBD between Japan and ROA. © 2016 S. Karger AG, Basel.

Simultaneous monitoring the real and imaginary parts of the analyte refractive index using liquid-core photonic bandgap Bragg fibers.

PubMed

Li, Jingwen; Qu, Hang; Skorobogatiy, Maksim

2015-09-07

We demonstrate simultaneous monitoring of the real and imaginary parts of the liquid analyte refractive index by using a hollow-core Bragg fiber. We apply this two-channel fiber sensor to monitor concentrations of various commercial cooling oils. The sensor operates using spectral monitoring of the fiber bandgap center wavelength, as well as monitoring of the fiber transmission amplitude at mid-bandgap position. The sensitivity of the fiber sensor to changes in the real part of the core refractive index is found to be 1460nm/Refractive index unit (RIU). By using spectral modality and effective medium theory, we determine the concentrations of the two commercial fluids from the measured refractive indices with an accuracy of ~0.57% for both low- and high-loss oils. Moreover, using an amplitude-based detection modality allows determination of the oil concentration with accuracy of ~1.64% for low-loss oils and ~2.81% for the high-loss oils.

An Evaluation of Multimodal Interactions with Technology while Learning Science Concepts

ERIC Educational Resources Information Center

Anastopoulou, Stamatina; Sharples, Mike; Baber, Chris

2011-01-01

This paper explores the value of employing multiple modalities to facilitate science learning with technology. In particular, it is argued that when multiple modalities are employed, learners construct strong relations between physical movement and visual representations of motion. Body interactions with visual representations, enabled by…

A Fusion Architecture for Tracking a Group of People Using a Distributed Sensor Network

DTIC Science & Technology

2013-07-01

Determining the composition of the group is done using several classifiers. The fusion is done at the UGS level to fuse information from all the modalities to...to classification and counting of the targets. Section III also presents the algorithms for fusion of distributed sensor data at the UGS level and...ultrasonic sensors. Determining the composition of the group is done using several classifiers. The fusion is done at the UGS level to fuse

Fiber waveguide sensors for intelligent materials

NASA Technical Reports Server (NTRS)

Flax, A. R.; Claus, R. O.

1988-01-01

This report, an addendum to the six month report submitted to NASA Langley Research Center in December 1987, covers research performed by the Fiber and Electro-Optics Research Center (FEORC) at Virginia Tech for the NASA Langley Research Center, Grant NAG1-780, for the period from December 1987 to June 1988. This final report discusses the research performed in the following four areas as described in the proposal: Fabrication of Sensor Fibers Optimized for Embedding in Advanced Composites; Fabrication of Sensor Fiber with In-Line Splices and Evaluation via OTR methods; Modal Domain Optical Fiber Sensor Analysis; and Acoustic Fiber Waveguide Implementation.

Development and investigation of MOEMS type displacement-pressure sensor for biological information monitoring

NASA Astrophysics Data System (ADS)

Ostasevicius, Vytautas; Malinauskas, Karolis; Janusas, Giedrius; Palevicius, Arvydas; Cekas, Elingas

2016-04-01

The aim of this paper is to develop and investigate MOEMS displacement-pressure sensor for biological information monitoring. Developing computational periodical microstructure models using COMSOL Multiphysics modeling software for modal and shape analysis and implementation of these results for design MOEMS displacement-pressure sensor for biological information monitoring was performed. The micro manufacturing technology of periodical microstructure having good diffraction efficiency was proposed. Experimental setup for characterisation of optical properties of periodical microstructure used for design of displacement-pressure sensor was created. Pulsating human artery dynamic characteristics in this paper were analysed.

Dynamic reweighting of three modalities for sensor fusion.

PubMed

Hwang, Sungjae; Agada, Peter; Kiemel, Tim; Jeka, John J

2014-01-01

We simultaneously perturbed visual, vestibular and proprioceptive modalities to understand how sensory feedback is re-weighted so that overall feedback remains suited to stabilizing upright stance. Ten healthy young subjects received an 80 Hz vibratory stimulus to their bilateral Achilles tendons (stimulus turns on-off at 0.28 Hz), a ± 1 mA binaural monopolar galvanic vestibular stimulus at 0.36 Hz, and a visual stimulus at 0.2 Hz during standing. The visual stimulus was presented at different amplitudes (0.2, 0.8 deg rotation about ankle axis) to measure: the change in gain (weighting) to vision, an intramodal effect; and a change in gain to vibration and galvanic vestibular stimulation, both intermodal effects. The results showed a clear intramodal visual effect, indicating a de-emphasis on vision when the amplitude of visual stimulus increased. At the same time, an intermodal visual-proprioceptive reweighting effect was observed with the addition of vibration, which is thought to change proprioceptive inputs at the ankles, forcing the nervous system to rely more on vision and vestibular modalities. Similar intermodal effects for visual-vestibular reweighting were observed, suggesting that vestibular information is not a "fixed" reference, but is dynamically adjusted in the sensor fusion process. This is the first time, to our knowledge, that the interplay between the three primary modalities for postural control has been clearly delineated, illustrating a central process that fuses these modalities for accurate estimates of self-motion.

Voxelwise multivariate analysis of multimodality magnetic resonance imaging

PubMed Central

Naylor, Melissa G.; Cardenas, Valerie A.; Tosun, Duygu; Schuff, Norbert; Weiner, Michael; Schwartzman, Armin

2015-01-01

Most brain magnetic resonance imaging (MRI) studies concentrate on a single MRI contrast or modality, frequently structural MRI. By performing an integrated analysis of several modalities, such as structural, perfusion-weighted, and diffusion-weighted MRI, new insights may be attained to better understand the underlying processes of brain diseases. We compare two voxelwise approaches: (1) fitting multiple univariate models, one for each outcome and then adjusting for multiple comparisons among the outcomes and (2) fitting a multivariate model. In both cases, adjustment for multiple comparisons is performed over all voxels jointly to account for the search over the brain. The multivariate model is able to account for the multiple comparisons over outcomes without assuming independence because the covariance structure between modalities is estimated. Simulations show that the multivariate approach is more powerful when the outcomes are correlated and, even when the outcomes are independent, the multivariate approach is just as powerful or more powerful when at least two outcomes are dependent on predictors in the model. However, multiple univariate regressions with Bonferroni correction remains a desirable alternative in some circumstances. To illustrate the power of each approach, we analyze a case control study of Alzheimer's disease, in which data from three MRI modalities are available. PMID:23408378

A flexible data fusion architecture for persistent surveillance using ultra-low-power wireless sensor networks

NASA Astrophysics Data System (ADS)

Hanson, Jeffrey A.; McLaughlin, Keith L.; Sereno, Thomas J.

2011-06-01

We have developed a flexible, target-driven, multi-modal, physics-based fusion architecture that efficiently searches sensor detections for targets and rejects clutter while controlling the combinatoric problems that commonly arise in datadriven fusion systems. The informational constraints imposed by long lifetime requirements make systems vulnerable to false alarms. We demonstrate that our data fusion system significantly reduces false alarms while maintaining high sensitivity to threats. In addition, mission goals can vary substantially in terms of targets-of-interest, required characterization, acceptable latency, and false alarm rates. Our fusion architecture provides the flexibility to match these trade-offs with mission requirements unlike many conventional systems that require significant modifications for each new mission. We illustrate our data fusion performance with case studies that span many of the potential mission scenarios including border surveillance, base security, and infrastructure protection. In these studies, we deployed multi-modal sensor nodes - including geophones, magnetometers, accelerometers and PIR sensors - with low-power processing algorithms and low-bandwidth wireless mesh networking to create networks capable of multi-year operation. The results show our data fusion architecture maintains high sensitivities while suppressing most false alarms for a variety of environments and targets.

Mode-independent attenuation in evanescent-field sensors

NASA Astrophysics Data System (ADS)

Gnewuch, Harald; Renner, Hagen

1995-03-01

Generally, the total power attenuation in multimode evanescent-field sensor waveguides is nonproportional to the bulk absorbance because the modal attenuation constants differ. Hence a direct measurement is difficult and is additionally aggravated because the waveguide absorbance is highly sensitive to the specific launching conditions at the waveguide input. A general asymptotic formula for the modal power attenuation in strongly asymmetric inhomogeneous planar waveguides with arbitrarily distributed weak absorption in the low-index superstrate is derived. Explicit expressions for typical refractive-index profiles are given. Except when very close to the cutoff, the predicted asymptotic attenuation behavior agrees well with exact calculations. The ratio of TM versus TE absorption has been derived to be (2 - n0 2/nf2 ) for arbitrary profiles. Waveguides with a linear refractive-index profile show mode-independent attenuation coefficients within each polarization. Further, the asymptotic sensitivity is independent of the wavelength, so that it should be possible to directly measure the spectral variation of the bulk absorption. The mode independence of the attenuation has been verified experimentally for a second-order polynomial profile, which is close to a linear refractive-index distribution. In contrast, the attenuation in the step-profile waveguide has been found to depend strongly on the mode number, as predicted by theory. A strong spread of the modal attenuation coefficients is also predicted for the parabolic-profile waveguide sensor.

Towards Omni-Tomography—Grand Fusion of Multiple Modalities for Simultaneous Interior Tomography

PubMed Central

Wang, Ge; Zhang, Jie; Gao, Hao; Weir, Victor; Yu, Hengyong; Cong, Wenxiang; Xu, Xiaochen; Shen, Haiou; Bennett, James; Furth, Mark; Wang, Yue; Vannier, Michael

2012-01-01

We recently elevated interior tomography from its origin in computed tomography (CT) to a general tomographic principle, and proved its validity for other tomographic modalities including SPECT, MRI, and others. Here we propose “omni-tomography”, a novel concept for the grand fusion of multiple tomographic modalities for simultaneous data acquisition in a region of interest (ROI). Omni-tomography can be instrumental when physiological processes under investigation are multi-dimensional, multi-scale, multi-temporal and multi-parametric. Both preclinical and clinical studies now depend on in vivo tomography, often requiring separate evaluations by different imaging modalities. Over the past decade, two approaches have been used for multimodality fusion: Software based image registration and hybrid scanners such as PET-CT, PET-MRI, and SPECT-CT among others. While there are intrinsic limitations with both approaches, the main obstacle to the seamless fusion of multiple imaging modalities has been the bulkiness of each individual imager and the conflict of their physical (especially spatial) requirements. To address this challenge, omni-tomography is now unveiled as an emerging direction for biomedical imaging and systems biomedicine. PMID:22768108

Blind identification of full-field vibration modes of output-only structures from uniformly-sampled, possibly temporally-aliased (sub-Nyquist), video measurements

NASA Astrophysics Data System (ADS)

Yang, Yongchao; Dorn, Charles; Mancini, Tyler; Talken, Zachary; Nagarajaiah, Satish; Kenyon, Garrett; Farrar, Charles; Mascareñas, David

2017-03-01

Enhancing the spatial and temporal resolution of vibration measurements and modal analysis could significantly benefit dynamic modelling, analysis, and health monitoring of structures. For example, spatially high-density mode shapes are critical for accurate vibration-based damage localization. In experimental or operational modal analysis, higher (frequency) modes, which may be outside the frequency range of the measurement, contain local structural features that can improve damage localization as well as the construction and updating of the modal-based dynamic model of the structure. In general, the resolution of vibration measurements can be increased by enhanced hardware. Traditional vibration measurement sensors such as accelerometers have high-frequency sampling capacity; however, they are discrete point-wise sensors only providing sparse, low spatial sensing resolution measurements, while dense deployment to achieve high spatial resolution is expensive and results in the mass-loading effect and modification of structure's surface. Non-contact measurement methods such as scanning laser vibrometers provide high spatial and temporal resolution sensing capacity; however, they make measurements sequentially that requires considerable acquisition time. As an alternative non-contact method, digital video cameras are relatively low-cost, agile, and provide high spatial resolution, simultaneous, measurements. Combined with vision based algorithms (e.g., image correlation or template matching, optical flow, etc.), video camera based measurements have been successfully used for experimental and operational vibration measurement and subsequent modal analysis. However, the sampling frequency of most affordable digital cameras is limited to 30-60 Hz, while high-speed cameras for higher frequency vibration measurements are extremely costly. This work develops a computational algorithm capable of performing vibration measurement at a uniform sampling frequency lower than what is required by the Shannon-Nyquist sampling theorem for output-only modal analysis. In particular, the spatio-temporal uncoupling property of the modal expansion of structural vibration responses enables a direct modal decoupling of the temporally-aliased vibration measurements by existing output-only modal analysis methods, yielding (full-field) mode shapes estimation directly. Then the signal aliasing properties in modal analysis is exploited to estimate the modal frequencies and damping ratios. The proposed method is validated by laboratory experiments where output-only modal identification is conducted on temporally-aliased acceleration responses and particularly the temporally-aliased video measurements of bench-scale structures, including a three-story building structure and a cantilever beam.

Manifold Regularized Multitask Feature Learning for Multimodality Disease Classification

PubMed Central

Jie, Biao; Zhang, Daoqiang; Cheng, Bo; Shen, Dinggang

2015-01-01

Multimodality based methods have shown great advantages in classification of Alzheimer’s disease (AD) and its prodromal stage, that is, mild cognitive impairment (MCI). Recently, multitask feature selection methods are typically used for joint selection of common features across multiple modalities. However, one disadvantage of existing multimodality based methods is that they ignore the useful data distribution information in each modality, which is essential for subsequent classification. Accordingly, in this paper we propose a manifold regularized multitask feature learning method to preserve both the intrinsic relatedness among multiple modalities of data and the data distribution information in each modality. Specifically, we denote the feature learning on each modality as a single task, and use group-sparsity regularizer to capture the intrinsic relatedness among multiple tasks (i.e., modalities) and jointly select the common features from multiple tasks. Furthermore, we introduce a new manifold-based Laplacian regularizer to preserve the data distribution information from each task. Finally, we use the multikernel support vector machine method to fuse multimodality data for eventual classification. Conversely, we also extend our method to the semisupervised setting, where only partial data are labeled. We evaluate our method using the baseline magnetic resonance imaging (MRI), fluorodeoxyglucose positron emission tomography (FDG-PET), and cerebrospinal fluid (CSF) data of subjects from AD neuroimaging initiative database. The experimental results demonstrate that our proposed method can not only achieve improved classification performance, but also help to discover the disease-related brain regions useful for disease diagnosis. PMID:25277605

Nanoscale NMR spectroscopy and imaging of multiple nuclear species.

PubMed

DeVience, Stephen J; Pham, Linh M; Lovchinsky, Igor; Sushkov, Alexander O; Bar-Gill, Nir; Belthangady, Chinmay; Casola, Francesco; Corbett, Madeleine; Zhang, Huiliang; Lukin, Mikhail; Park, Hongkun; Yacoby, Amir; Walsworth, Ronald L

2015-02-01

Nuclear magnetic resonance (NMR) spectroscopy and magnetic resonance imaging (MRI) provide non-invasive information about multiple nuclear species in bulk matter, with wide-ranging applications from basic physics and chemistry to biomedical imaging. However, the spatial resolution of conventional NMR and MRI is limited to several micrometres even at large magnetic fields (>1 T), which is inadequate for many frontier scientific applications such as single-molecule NMR spectroscopy and in vivo MRI of individual biological cells. A promising approach for nanoscale NMR and MRI exploits optical measurements of nitrogen-vacancy (NV) colour centres in diamond, which provide a combination of magnetic field sensitivity and nanoscale spatial resolution unmatched by any existing technology, while operating under ambient conditions in a robust, solid-state system. Recently, single, shallow NV centres were used to demonstrate NMR of nanoscale ensembles of proton spins, consisting of a statistical polarization equivalent to ∼100-1,000 spins in uniform samples covering the surface of a bulk diamond chip. Here, we realize nanoscale NMR spectroscopy and MRI of multiple nuclear species ((1)H, (19)F, (31)P) in non-uniform (spatially structured) samples under ambient conditions and at moderate magnetic fields (∼20 mT) using two complementary sensor modalities.

Multimode-singlemode-multimode fiber sensor for alcohol sensing application

NASA Astrophysics Data System (ADS)

Rofi'ah, Iftihatur; Hatta, A. M.; Sekartedjo, Sekartedjo

2016-11-01

Alcohol is volatile and flammable liquid which is soluble substances both on polar and non polar substances that has been used in some industrial sectors. Alcohol detection method now widely used one of them is the optical fiber sensor. In this paper used fiber optic sensor based on Multimode-Single-mode-Multimode (MSM) to detect alcohol solution at a concentration range of 0-3%. The working principle of sensor utilizes the modal interference between the core modes and the cladding modes, thus make the sensor sensitive to environmental changes. The result showed that characteristic of the sensor not affect the length of the single-mode fiber (SMF). We obtain that the sensor with a length of 5 mm of single-mode can sensing the alcohol with a sensitivity of 0.107 dB/v%.

An algorithm for monitoring the traffic on a less-travelled road using multi-modal sensor suite

NASA Astrophysics Data System (ADS)

Damarla, Thyagaraju; Chatters, Gary; Liss, Brian; Vu, Hao; Sabatier, James M.

2014-06-01

We conducted an experiment to correlate the information gathered by a suite of hard sensors with the information on social networks such as Twitter, Facebook, etc. The experiment consisting of monitoring traffic on a well- traveled road and on a road inside a facility. The sensors suite selected mainly consists of sensors that require low power for operation and last a longtime. The output of each sensor is analyzed to classify the targets as ground vehicles, humans, and airborne targets. The algorithm is also used to count the number of targets belonging to each type so the sensor can store the information for anomaly detection. In this paper, we describe the classifier algorithms used for acoustic, seismic, and passive infrared (PIR) sensor data.

Modality-specific selective attention attenuates multisensory integration.

PubMed

Mozolic, Jennifer L; Hugenschmidt, Christina E; Peiffer, Ann M; Laurienti, Paul J

2008-01-01

Stimuli occurring in multiple sensory modalities that are temporally synchronous or spatially coincident can be integrated together to enhance perception. Additionally, the semantic content or meaning of a stimulus can influence cross-modal interactions, improving task performance when these stimuli convey semantically congruent or matching information, but impairing performance when they contain non-matching or distracting information. Attention is one mechanism that is known to alter processing of sensory stimuli by enhancing perception of task-relevant information and suppressing perception of task-irrelevant stimuli. It is not known, however, to what extent attention to a single sensory modality can minimize the impact of stimuli in the unattended sensory modality and reduce the integration of stimuli across multiple sensory modalities. Our hypothesis was that modality-specific selective attention would limit processing of stimuli in the unattended sensory modality, resulting in a reduction of performance enhancements produced by semantically matching multisensory stimuli, and a reduction in performance decrements produced by semantically non-matching multisensory stimuli. The results from two experiments utilizing a cued discrimination task demonstrate that selective attention to a single sensory modality prevents the integration of matching multisensory stimuli that is normally observed when attention is divided between sensory modalities. Attention did not reliably alter the amount of distraction caused by non-matching multisensory stimuli on this task; however, these findings highlight a critical role for modality-specific selective attention in modulating multisensory integration.

Overview of multi-input frequency domain modal testing methods with an emphasis on sine testing

NASA Technical Reports Server (NTRS)

Rost, Robert W.; Brown, David L.

1988-01-01

An overview of the current state of the art multiple-input, multiple-output modal testing technology is discussed. A very brief review of the current time domain methods is given. A detailed review of frequency and spatial domain methods is presented with an emphasis on sine testing.

Roles of Frequency, Attitudes, and Multiple Intelligence Modality Surrounding Electricity Content-Based Reader's Theatre

ERIC Educational Resources Information Center

Hosier, Julie Winchester

2009-01-01

Integration of subjects is something elementary teachers must do to insure required objectives are covered. Science-based Reader's Theatre is one way to weave reading into science. This study examined the roles of frequency, attitudes, and Multiple Intelligence modalities surrounding Electricity Content-Based Reader's Theatre. This study used…

Synchronizing data from irregularly sampled sensors

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

Uluyol, Onder

A system and method include receiving a set of sampled measurements for each of multiple sensors, wherein the sampled measurements are at irregular intervals or different rates, re-sampling the sampled measurements of each of the multiple sensors at a higher rate than one of the sensor's set of sampled measurements, and synchronizing the sampled measurements of each of the multiple sensors.

Control and trajectory design of a highly flexible air vehicle with a distributed sensing architecture

NASA Astrophysics Data System (ADS)

Pachikara, Abraham James

Next generational aircraft are becoming very flexible due to efforts to reduce weight and increase aerodynamic efficiency. As a result, flight control systems and trajectories that were designed with traditional rigid body assumptions may no longer become valid. When an aircraft becomes more flexible, the shape of the aircraft can deform significantly due to the aeroservoelastic dynamics. No longer are few sensors located at the CG and elsewhere will be enough to maximize performance. Instead, a full suite of sensors will be needed all throughout the aircraft to accurately measure the complete aerodynamic distribution and dynamics. First, a parametric study will be conducted to understand how flexibility impacts both the open-loop and closed-loop dynamics of a generic micro air vehicle (MAV). Once the impact of flexibility on the MAV's aeroservoelastic dynamics is well understood, an aeroservoelastic flight controller will be designed that leverages a "Fly-By-Feel" sensor architecture. A sensor architecture will be developed that uses several sensors to estimate the MAV's full aerodynamic and inertial distribution along with inertial sensors at the CG. A modal filtering approach will be used for the relevant sensor management and to extract useful modal characteristics from the sensor data. Once that is done, a controller will be designed for maneuver tracking. Once a flight controller has been designed, a set of representative motion primitives for the MAV can be developed that model how the aircraft moves for trajectory generation. Then trajectories can be developed for the flexible vehicle. Analysis will then be conducted to understand how flexibility impacts the creation of trajectories and MAV performance metrics.

Online Multi-Modal Robust Non-Negative Dictionary Learning for Visual Tracking

PubMed Central

Zhang, Xiang; Guan, Naiyang; Tao, Dacheng; Qiu, Xiaogang; Luo, Zhigang

2015-01-01

Dictionary learning is a method of acquiring a collection of atoms for subsequent signal representation. Due to its excellent representation ability, dictionary learning has been widely applied in multimedia and computer vision. However, conventional dictionary learning algorithms fail to deal with multi-modal datasets. In this paper, we propose an online multi-modal robust non-negative dictionary learning (OMRNDL) algorithm to overcome this deficiency. Notably, OMRNDL casts visual tracking as a dictionary learning problem under the particle filter framework and captures the intrinsic knowledge about the target from multiple visual modalities, e.g., pixel intensity and texture information. To this end, OMRNDL adaptively learns an individual dictionary, i.e., template, for each modality from available frames, and then represents new particles over all the learned dictionaries by minimizing the fitting loss of data based on M-estimation. The resultant representation coefficient can be viewed as the common semantic representation of particles across multiple modalities, and can be utilized to track the target. OMRNDL incrementally learns the dictionary and the coefficient of each particle by using multiplicative update rules to respectively guarantee their non-negativity constraints. Experimental results on a popular challenging video benchmark validate the effectiveness of OMRNDL for visual tracking in both quantity and quality. PMID:25961715

Online multi-modal robust non-negative dictionary learning for visual tracking.

PubMed

Zhang, Xiang; Guan, Naiyang; Tao, Dacheng; Qiu, Xiaogang; Luo, Zhigang

2015-01-01

Dictionary learning is a method of acquiring a collection of atoms for subsequent signal representation. Due to its excellent representation ability, dictionary learning has been widely applied in multimedia and computer vision. However, conventional dictionary learning algorithms fail to deal with multi-modal datasets. In this paper, we propose an online multi-modal robust non-negative dictionary learning (OMRNDL) algorithm to overcome this deficiency. Notably, OMRNDL casts visual tracking as a dictionary learning problem under the particle filter framework and captures the intrinsic knowledge about the target from multiple visual modalities, e.g., pixel intensity and texture information. To this end, OMRNDL adaptively learns an individual dictionary, i.e., template, for each modality from available frames, and then represents new particles over all the learned dictionaries by minimizing the fitting loss of data based on M-estimation. The resultant representation coefficient can be viewed as the common semantic representation of particles across multiple modalities, and can be utilized to track the target. OMRNDL incrementally learns the dictionary and the coefficient of each particle by using multiplicative update rules to respectively guarantee their non-negativity constraints. Experimental results on a popular challenging video benchmark validate the effectiveness of OMRNDL for visual tracking in both quantity and quality.

Modal Identification in an Automotive Multi-Component System Using HS 3D-DIC

PubMed Central

López-Alba, Elías; Felipe-Sesé, Luis; Díaz, Francisco A.

2018-01-01

The modal characterization of automotive lighting systems becomes difficult using sensors due to the light weight of the elements which compose the component as well as the intricate access to allocate them. In experimental modal analysis, high speed 3D digital image correlation (HS 3D-DIC) is attracting the attention since it provides full-field contactless measurements of 3D displacements as main advantage over other techniques. Different methodologies have been published that perform modal identification, i.e., natural frequencies, damping ratios, and mode shapes using the full-field information. In this work, experimental modal analysis has been performed in a multi-component automotive lighting system using HS 3D-DIC. Base motion excitation was applied to simulate operating conditions. A recently validated methodology has been employed for modal identification using transmissibility functions, i.e., the transfer functions from base motion tests. Results make it possible to identify local and global behavior of the different elements of injected polymeric and metallic materials. PMID:29401725

Information Fusion in Ad hoc Wireless Sensor Networks for Aircraft Health Monitoring

NASA Astrophysics Data System (ADS)

Fragoulis, Nikos; Tsagaris, Vassilis; Anastassopoulos, Vassilis

In this paper the use of an ad hoc wireless sensor network for implementing a structural health monitoring system is discussed. The network is consisted of sensors deployed throughout the aircraft. These sensors being in the form of a microelectronic chip and consisted of sensing, data processing and communicating components could be easily embedded in any mechanical aircraft component. The established sensor network, due to its ad hoc nature is easily scalable, allowing adding or removing any number of sensors. The position of the sensor nodes need not necessarily to be engineered or predetermined, giving this way the ability to be deployed in inaccessible points. Information collected from various sensors of different modalities throughout the aircraft is then fused in order to provide a more comprehensive image of the aircraft structural health. Sensor level fusion along with decision quality information is used, in order to enhance detection performance.

A new method for registration of heterogeneous sensors in a dimensional measurement system

NASA Astrophysics Data System (ADS)

Zhao, Yan; Wang, Zhong; Fu, Luhua; Qu, Xinghua; Zhang, Heng; Liu, Changjie

2017-10-01

Registration of multiple sensors is a basic step in multi-sensor dimensional or coordinate measuring systems before any measurement. In most cases, a common standard is used to be measured by all sensors, and this may work well for general registration of multiple homogeneous sensors. However, when inhomogeneous sensors detect a common standard, it is usually very difficult to obtain the same information, because of the different working principles of the sensors. In this paper, a new method called multiple steps registration is proposed to register two sensors: a video camera sensor (VCS) and a tactile probe sensor (TPS). In this method, the two sensors measure two separated standards: a chrome circle on a reticle and a reference sphere with a constant distance between them, fixed on a steel plate. The VCS captures only the circle and the TPS touches only the sphere. Both simulations and real experiments demonstrate that the proposed method is robust and accurate in the registration of multiple inhomogeneous sensors in a dimensional measurement system.

Emerging Cytokine Biosensors with Optical Detection Modalities and Nanomaterial-Enabled Signal Enhancement

PubMed Central

Singh, Manpreet; Truong, Johnson; Reeves, W. Brian; Hahm, Jong-in

2017-01-01

Protein biomarkers, especially cytokines, play a pivotal role in the diagnosis and treatment of a wide spectrum of diseases. Therefore, a critical need for advanced cytokine sensors has been rapidly growing and will continue to expand to promote clinical testing, new biomarker development, and disease studies. In particular, sensors employing transduction principles of various optical modalities have emerged as the most common means of detection. In typical cytokine assays which are based on the binding affinities between the analytes of cytokines and their specific antibodies, optical schemes represent the most widely used mechanisms, with some serving as the gold standard against which all existing and new sensors are benchmarked. With recent advancements in nanoscience and nanotechnology, many of the recently emerging technologies for cytokine detection exploit various forms of nanomaterials for improved sensing capabilities. Nanomaterials have been demonstrated to exhibit exceptional optical properties unique to their reduced dimensionality. Novel sensing approaches based on the newly identified properties of nanomaterials have shown drastically improved performances in both the qualitative and quantitative analyses of cytokines. This article brings together the fundamentals in the literature that are central to different optical modalities developed for cytokine detection. Recent advancements in the applications of novel technologies are also discussed in terms of those that enable highly sensitive and multiplexed cytokine quantification spanning a wide dynamic range. For each highlighted optical technique, its current detection capabilities as well as associated challenges are discussed. Lastly, an outlook for nanomaterial-based cytokine sensors is provided from the perspective of optimizing the technologies for sensitivity and multiplexity as well as promoting widespread adaptations of the emerging optical techniques by lowering high thresholds currently present in the new approaches. PMID:28241443

Using a Smart City IoT to Incentivise and Target Shifts in Mobility Behaviour—Is It a Piece of Pie?

PubMed Central

Poslad, Stefan; Ma, Athen; Wang, Zhenchen; Mei, Haibo

2015-01-01

Whilst there is an increasing capability to instrument smart cities using fixed and mobile sensors to produce the big data to better understand and manage transportation use, there still exists a wide gap between the sustainability goals of smart cities, e.g., to promote less private car use at peak times, with respect to their ability to more dynamically support individualised shifts in multi-modal transportation use to help achieve such goals. We describe the development of the tripzoom system developed as part of the SUNSET—SUstainable social Network SErvices for Transport—project to research and develop a mobile and fixed traffic sensor system to help facilitate individual mobility shifts. Its main novelty was its ability to use mobile sensors to classify common multiple urban transportation modes, to generate information-rich individual and group mobility profiles and to couple this with the use of a targeted incentivised marketplace to gamify travel. This helps to promote mobility shifts towards achieving sustainability goals. This system was trialled in three European country cities operated as Living Labs over six months. Our main findings were that we were able to accomplish a level of behavioural shifts in travel behaviour. Hence, we have provided a proof-of-concept system that uses positive incentives to change individual travel behaviour. PMID:26053752

Sampling considerations for modal analysis with damping

NASA Astrophysics Data System (ADS)

Park, Jae Young; Wakin, Michael B.; Gilbert, Anna C.

2015-03-01

Structural health monitoring (SHM) systems are critical for monitoring aging infrastructure (such as buildings or bridges) in a cost-effective manner. Wireless sensor networks that sample vibration data over time are particularly appealing for SHM applications due to their flexibility and low cost. However, in order to extend the battery life of wireless sensor nodes, it is essential to minimize the amount of vibration data these sensors must collect and transmit. In recent work, we have studied the performance of the Singular Value Decomposition (SVD) applied to the collection of data and provided new finite sample analysis characterizing conditions under which this simple technique{also known as the Proper Orthogonal Decomposition (POD){can correctly estimate the mode shapes of the structure. Specifically, we provided theoretical guarantees on the number and duration of samples required in order to estimate a structure's mode shapes to a desired level of accuracy. In that previous work, however, we considered simplified Multiple-Degree-Of-Freedom (MDOF) systems with no damping. In this paper we consider MDOF systems with proportional damping and show that, with sufficiently light damping, the POD can continue to provide accurate estimates of a structure's mode shapes. We support our discussion with new analytical insight and experimental demonstrations. In particular, we study the tradeoffs between the level of damping, the sampling rate and duration, and the accuracy to which the structure's mode shapes can be estimated.

Using a Smart City IoT to Incentivise and Target Shifts in Mobility Behaviour--Is It a Piece of Pie?

PubMed

Poslad, Stefan; Ma, Athen; Wang, Zhenchen; Mei, Haibo

2015-06-04

Whilst there is an increasing capability to instrument smart cities using fixed and mobile sensors to produce the big data to better understand and manage transportation use, there still exists a wide gap between the sustainability goals of smart cities, e.g., to promote less private car use at peak times, with respect to their ability to more dynamically support individualised shifts in multi-modal transportation use to help achieve such goals. We describe the development of the tripzoom system developed as part of the SUNSET-SUstainable social Network SErvices for Transport-project to research and develop a mobile and fixed traffic sensor system to help facilitate individual mobility shifts. Its main novelty was its ability to use mobile sensors to classify common multiple urban transportation modes, to generate information-rich individual and group mobility profiles and to couple this with the use of a targeted incentivised marketplace to gamify travel. This helps to promote mobility shifts towards achieving sustainability goals. This system was trialled in three European country cities operated as Living Labs over six months. Our main findings were that we were able to accomplish a level of behavioural shifts in travel behaviour. Hence, we have provided a proof-of-concept system that uses positive incentives to change individual travel behaviour.

Linked independent component analysis for multimodal data fusion.

PubMed

Groves, Adrian R; Beckmann, Christian F; Smith, Steve M; Woolrich, Mark W

2011-02-01

In recent years, neuroimaging studies have increasingly been acquiring multiple modalities of data and searching for task- or disease-related changes in each modality separately. A major challenge in analysis is to find systematic approaches for fusing these differing data types together to automatically find patterns of related changes across multiple modalities, when they exist. Independent Component Analysis (ICA) is a popular unsupervised learning method that can be used to find the modes of variation in neuroimaging data across a group of subjects. When multimodal data is acquired for the subjects, ICA is typically performed separately on each modality, leading to incompatible decompositions across modalities. Using a modular Bayesian framework, we develop a novel "Linked ICA" model for simultaneously modelling and discovering common features across multiple modalities, which can potentially have completely different units, signal- and contrast-to-noise ratios, voxel counts, spatial smoothnesses and intensity distributions. Furthermore, this general model can be configured to allow tensor ICA or spatially-concatenated ICA decompositions, or a combination of both at the same time. Linked ICA automatically determines the optimal weighting of each modality, and also can detect single-modality structured components when present. This is a fully probabilistic approach, implemented using Variational Bayes. We evaluate the method on simulated multimodal data sets, as well as on a real data set of Alzheimer's patients and age-matched controls that combines two very different types of structural MRI data: morphological data (grey matter density) and diffusion data (fractional anisotropy, mean diffusivity, and tensor mode). Copyright © 2010 Elsevier Inc. All rights reserved.

Meaning Making through Multiple Modalities in a Biology Classroom: A Multimodal Semiotics Discourse Analysis

ERIC Educational Resources Information Center

Jaipal, Kamini

2010-01-01

The teaching of science is a complex process, involving the use of multiple modalities. This paper illustrates the potential of a multimodal semiotics discourse analysis framework to illuminate meaning-making possibilities during the teaching of a science concept. A multimodal semiotics analytical framework is developed and used to (1) analyze the…

Psychophysical Isolation of the Modality Responsible for Detecting Multimodal Stimuli: A Chemosensory Example

ERIC Educational Resources Information Center

Nagata, Hisanori; Dalton, Pamela; Doolittle, Nadine; Breslin, Paul A. S.

2005-01-01

Multiple sense modalities can be stimulated conjointly by a physically complex item, such as a predator, and also by a physically solitary stimulus that acts on multiple receptor classes. As a prime example of this latter group, l-menthol from mint stimulates taste, smell, and several somatosensory submodalities. In 6 experiments that used a…

Linear high-boost fusion of Stokes vector imagery for effective discrimination and recognition of real targets in the presence of multiple identical decoys

NASA Astrophysics Data System (ADS)

El-Saba, Aed; Sakla, Wesam A.

2010-04-01

Recently, the use of imaging polarimetry has received considerable attention for use in automatic target recognition (ATR) applications. In military remote sensing applications, there is a great demand for sensors that are capable of discriminating between real targets and decoys. Accurate discrimination of decoys from real targets is a challenging task and often requires the fusion of various sensor modalities that operate simultaneously. In this paper, we use a simple linear fusion technique known as the high-boost fusion method for effective discrimination of real targets in the presence of multiple decoys. The HBF assigns more weight to the polarization-based imagery in forming the final fused image that is used for detection. We have captured both intensity and polarization-based imagery from an experimental laboratory arrangement containing a mixture of sand/dirt, rocks, vegetation, and other objects for the purpose of simulating scenery that would be acquired in a remote sensing military application. A target object and three decoys that are identical in physical appearance (shape, surface structure and color) and different in material composition have also been placed in the scene. We use the wavelet-filter joint transform correlation (WFJTC) technique to perform detection between input scenery and the target object. Our results show that use of the HBF method increases the correlation performance metrics associated with the WFJTC-based detection process when compared to using either the traditional intensity or polarization-based images.

Flood extent and water level estimation from SAR using data-model integration

NASA Astrophysics Data System (ADS)

Ajadi, O. A.; Meyer, F. J.

2017-12-01

Synthetic Aperture Radar (SAR) images have long been recognized as a valuable data source for flood mapping. Compared to other sources, SAR's weather and illumination independence and large area coverage at high spatial resolution supports reliable, frequent, and detailed observations of developing flood events. Accordingly, SAR has the potential to greatly aid in the near real-time monitoring of natural hazards, such as flood detection, if combined with automated image processing. This research works towards increasing the reliability and temporal sampling of SAR-derived flood hazard information by integrating information from multiple SAR sensors and SAR modalities (images and Interferometric SAR (InSAR) coherence) and by combining SAR-derived change detection information with hydrologic and hydraulic flood forecast models. First, the combination of multi-temporal SAR intensity images and coherence information for generating flood extent maps is introduced. The application of least-squares estimation integrates flood information from multiple SAR sensors, thus increasing the temporal sampling. SAR-based flood extent information will be combined with a Digital Elevation Model (DEM) to reduce false alarms and to estimate water depth and flood volume. The SAR-based flood extent map is assimilated into the Hydrologic Engineering Center River Analysis System (Hec-RAS) model to aid in hydraulic model calibration. The developed technology is improving the accuracy of flood information by exploiting information from data and models. It also provides enhanced flood information to decision-makers supporting the response to flood extent and improving emergency relief efforts.

Detection of Obstacles in Monocular Image Sequences

NASA Technical Reports Server (NTRS)

Kasturi, Rangachar; Camps, Octavia

1997-01-01

The ability to detect and locate runways/taxiways and obstacles in images captured using on-board sensors is an essential first step in the automation of low-altitude flight, landing, takeoff, and taxiing phase of aircraft navigation. Automation of these functions under different weather and lighting situations, can be facilitated by using sensors of different modalities. An aircraft-based Synthetic Vision System (SVS), with sensors of different modalities mounted on-board, complements the current ground-based systems in functions such as detection and prevention of potential runway collisions, airport surface navigation, and landing and takeoff in all weather conditions. In this report, we address the problem of detection of objects in monocular image sequences obtained from two types of sensors, a Passive Millimeter Wave (PMMW) sensor and a video camera mounted on-board a landing aircraft. Since the sensors differ in their spatial resolution, and the quality of the images obtained using these sensors is not the same, different approaches are used for detecting obstacles depending on the sensor type. These approaches are described separately in two parts of this report. The goal of the first part of the report is to develop a method for detecting runways/taxiways and objects on the runway in a sequence of images obtained from a moving PMMW sensor. Since the sensor resolution is low and the image quality is very poor, we propose a model-based approach for detecting runways/taxiways. We use the approximate runway model and the position information of the camera provided by the Global Positioning System (GPS) to define regions of interest in the image plane to search for the image features corresponding to the runway markers. Once the runway region is identified, we use histogram-based thresholding to detect obstacles on the runway and regions outside the runway. This algorithm is tested using image sequences simulated from a single real PMMW image.

Observation, Identification, and Impact of Multi-Modal Plasma Responses to Applied Magnetic Perturbations

NASA Astrophysics Data System (ADS)

Logan, Nikolas

2015-11-01

Experiments on DIII-D have demonstrated that multiple kink modes with comparable amplitudes can be driven by applied nonaxisymmetric fields with toroidal mode number n=2, in good agreement with ideal MHD models. In contrast to a single-mode model, the structure of the response measured using poloidally distributed magnetic sensors changes when varying the applied poloidal spectrum. This is most readily evident in that different spectra of applied fields can independently excite inboard and outboard magnetic responses, which are identified as distinct plasma modes by IPEC modeling. The outboard magnetic response is correlated with the plasma pressure and consistent with the long wavelength perturbations of the least stable, pressure driven kinks calculated by DCON and used in IPEC. The models show the structure of the pressure driven modes extends throughout the bad curvature region and into the plasma core. The inboard plasma response is correlated with the edge current profile and requires the inclusion of multiple kink modes with greater stability, including opposite helicity modes, to replicate the experimental observations in the models. IPEC reveals the resulting mode structure to be highly localized in the plasma edge. Scans of the applied spectrum show this response induces the transport that influences the density pump-out, as well as the toroidal rotation drag observed in experiment and modeled using PENT. The classification of these two mode types establishes a new multi-modal paradigm for n=2 plasma response and guides the understanding needed to optimize 3D fields for independent control of stability and transport. Supported by US DOE contract DE-AC02-09CH11466.

Discrete piezoelectric sensors and actuators for active control of two-dimensional spacecraft components

NASA Technical Reports Server (NTRS)

Bayer, Janice I.; Varadan, V. V.; Varadan, V. K.

1991-01-01

This paper describes research into the use of discrete piezoelectric sensors and actuators for active modal control of flexible two-dimensional structures such as might be used as components for spacecraft. A dynamic coupling term is defined between the sensor/actuator and the structure in terms of structural model shapes, location and piezoelectric behavior. The relative size of the coupling term determines sensor/actuator placement. Results are shown for a clamped square plate and for a large antenna. An experiment was performed on a thin foot-square plate clamped on all sides. Sizable vibration control was achieved for first, second/third (degenerate) and fourth modes.

Voxelwise multivariate analysis of multimodality magnetic resonance imaging.

PubMed

Naylor, Melissa G; Cardenas, Valerie A; Tosun, Duygu; Schuff, Norbert; Weiner, Michael; Schwartzman, Armin

2014-03-01

Most brain magnetic resonance imaging (MRI) studies concentrate on a single MRI contrast or modality, frequently structural MRI. By performing an integrated analysis of several modalities, such as structural, perfusion-weighted, and diffusion-weighted MRI, new insights may be attained to better understand the underlying processes of brain diseases. We compare two voxelwise approaches: (1) fitting multiple univariate models, one for each outcome and then adjusting for multiple comparisons among the outcomes and (2) fitting a multivariate model. In both cases, adjustment for multiple comparisons is performed over all voxels jointly to account for the search over the brain. The multivariate model is able to account for the multiple comparisons over outcomes without assuming independence because the covariance structure between modalities is estimated. Simulations show that the multivariate approach is more powerful when the outcomes are correlated and, even when the outcomes are independent, the multivariate approach is just as powerful or more powerful when at least two outcomes are dependent on predictors in the model. However, multiple univariate regressions with Bonferroni correction remain a desirable alternative in some circumstances. To illustrate the power of each approach, we analyze a case control study of Alzheimer's disease, in which data from three MRI modalities are available. Copyright © 2013 Wiley Periodicals, Inc.

Interferometric fiber-optic temperature sensor with spiral polarization couplers

NASA Astrophysics Data System (ADS)

Cortés, R.; Khomenko, A. V.; Starodumov, A. N.; Arzate, N.; Zenteno, L. A.

1998-09-01

A fiber optic temperature sensor, for which the changes in modal birefringence of a short section of a long birefringent fiber are monitored remotely, is described. It employs a white light interferometer, which is formed by two concatenated spiral polarization mode couplers. A new method for white light interferometer output signal processing is described which provides a high accuracy absolute temperature measurement even in discontinuous operation of the sensor. Experimental results are presented for temperature measurements over a 100°C range with resolution of 3×10 -3 °C.

Structural system identification based on variational mode decomposition

NASA Astrophysics Data System (ADS)

Bagheri, Abdollah; Ozbulut, Osman E.; Harris, Devin K.

2018-03-01

In this paper, a new structural identification method is proposed to identify the modal properties of engineering structures based on dynamic response decomposition using the variational mode decomposition (VMD). The VMD approach is a decomposition algorithm that has been developed as a means to overcome some of the drawbacks and limitations of the empirical mode decomposition method. The VMD-based modal identification algorithm decomposes the acceleration signal into a series of distinct modal responses and their respective center frequencies, such that when combined their cumulative modal responses reproduce the original acceleration response. The decaying amplitude of the extracted modal responses is then used to identify the modal damping ratios using a linear fitting function on modal response data. Finally, after extracting modal responses from available sensors, the mode shape vector for each of the decomposed modes in the system is identified from all obtained modal response data. To demonstrate the efficiency of the algorithm, a series of numerical, laboratory, and field case studies were evaluated. The laboratory case study utilized the vibration response of a three-story shear frame, whereas the field study leveraged the ambient vibration response of a pedestrian bridge to characterize the modal properties of the structure. The modal properties of the shear frame were computed using analytical approach for a comparison with the experimental modal frequencies. Results from these case studies demonstrated that the proposed method is efficient and accurate in identifying modal data of the structures.

Projection Mapping User Interface for Disabled People

PubMed Central

Simutis, Rimvydas; Maskeliūnas, Rytis

2018-01-01

Difficulty in communicating is one of the key challenges for people suffering from severe motor and speech disabilities. Often such person can communicate and interact with the environment only using assistive technologies. This paper presents a multifunctional user interface designed to improve communication efficiency and person independence. The main component of this interface is a projection mapping technique used to highlight objects in the environment. Projection mapping makes it possible to create a natural augmented reality information presentation method. The user interface combines a depth sensor and a projector to create camera-projector system. We provide a detailed description of camera-projector system calibration procedure. The described system performs tabletop object detection and automatic projection mapping. Multiple user input modalities have been integrated into the multifunctional user interface. Such system can be adapted to the needs of people with various disabilities. PMID:29686827

FLIM FRET Technology for Drug Discovery: Automated Multiwell-Plate High-Content Analysis, Multiplexed Readouts and Application in Situ**

PubMed Central

Kumar, Sunil; Alibhai, Dominic; Margineanu, Anca; Laine, Romain; Kennedy, Gordon; McGinty, James; Warren, Sean; Kelly, Douglas; Alexandrov, Yuriy; Munro, Ian; Talbot, Clifford; Stuckey, Daniel W; Kimberly, Christopher; Viellerobe, Bertrand; Lacombe, Francois; Lam, Eric W-F; Taylor, Harriet; Dallman, Margaret J; Stamp, Gordon; Murray, Edward J; Stuhmeier, Frank; Sardini, Alessandro; Katan, Matilda; Elson, Daniel S; Neil, Mark A A; Dunsby, Chris; French, Paul M W

2011-01-01

A fluorescence lifetime imaging (FLIM) technology platform intended to read out changes in Förster resonance energy transfer (FRET) efficiency is presented for the study of protein interactions across the drug-discovery pipeline. FLIM provides a robust, inherently ratiometric imaging modality for drug discovery that could allow the same sensor constructs to be translated from automated cell-based assays through small transparent organisms such as zebrafish to mammals. To this end, an automated FLIM multiwell-plate reader is described for high content analysis of fixed and live cells, tomographic FLIM in zebrafish and FLIM FRET of live cells via confocal endomicroscopy. For cell-based assays, an exemplar application reading out protein aggregation using FLIM FRET is presented, and the potential for multiple simultaneous FLIM (FRET) readouts in microscopy is illustrated. PMID:21337485

Audio-visual affective expression recognition

NASA Astrophysics Data System (ADS)

Huang, Thomas S.; Zeng, Zhihong

2007-11-01

Automatic affective expression recognition has attracted more and more attention of researchers from different disciplines, which will significantly contribute to a new paradigm for human computer interaction (affect-sensitive interfaces, socially intelligent environments) and advance the research in the affect-related fields including psychology, psychiatry, and education. Multimodal information integration is a process that enables human to assess affective states robustly and flexibly. In order to understand the richness and subtleness of human emotion behavior, the computer should be able to integrate information from multiple sensors. We introduce in this paper our efforts toward machine understanding of audio-visual affective behavior, based on both deliberate and spontaneous displays. Some promising methods are presented to integrate information from both audio and visual modalities. Our experiments show the advantage of audio-visual fusion in affective expression recognition over audio-only or visual-only approaches.

Projection Mapping User Interface for Disabled People.

PubMed

Gelšvartas, Julius; Simutis, Rimvydas; Maskeliūnas, Rytis

2018-01-01

Difficulty in communicating is one of the key challenges for people suffering from severe motor and speech disabilities. Often such person can communicate and interact with the environment only using assistive technologies. This paper presents a multifunctional user interface designed to improve communication efficiency and person independence. The main component of this interface is a projection mapping technique used to highlight objects in the environment. Projection mapping makes it possible to create a natural augmented reality information presentation method. The user interface combines a depth sensor and a projector to create camera-projector system. We provide a detailed description of camera-projector system calibration procedure. The described system performs tabletop object detection and automatic projection mapping. Multiple user input modalities have been integrated into the multifunctional user interface. Such system can be adapted to the needs of people with various disabilities.

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

NASA Astrophysics Data System (ADS)

Kim, Soogeun; Kim, ByungHyun; Sohn, Won Bum; Byun, Kyung Min; Lee, Soo Yeol

2017-02-01

To discriminate between normal and cancerous tissue, a dual modal approach using Raman spectroscopy and pH sensor was designed and applied. Raman spectroscopy has demonstrated the possibility of using as diagnostic method for the early detection of precancerous and cancerous lesions in vivo. It also can be used in identifying markers associated with malignant change. However, Raman spectroscopy lacks sufficient sensitivity due to very weak Raman scattering signal or less distinctive spectral pattern. A dual modal approach could be one of the solutions to solve this issue. The level of extracellular pH in cancer tissue is lower than that in normal tissue due to increased lactic acid production, decreased interstitial fluid buffering and decreased perfusion. High sensitivity and specificity required for accurate cancer diagnosis could be achieved by combining the chemical information from Raman spectrum with metabolic information from pH level. Raman spectra were acquired by using a fiber optic Raman probe, a cooled CCD camera connected to a spectrograph and 785 nm laser source. Different transmission spectra depending on tissue pH were measured by a lossy-mode resonance sensor based on fiber optic. The discriminative capability of pH-Raman dual modal method was evaluated using principal component analysis (PCA). The obtained results showed that the pH-Raman dual modal approach can improve discriminative capability between normal and cancerous tissue, which can lead to very high sensitivity and specificity. The proposed method for cancer detection is expected to be used in endoscopic diagnosis later.

Designing and testing the coronagraphic Modal Wavefront Sensor: a fast non-common path error sensor for high-contrast imaging

NASA Astrophysics Data System (ADS)

Wilby, M. J.; Keller, C. U.; Haffert, S.; Korkiakoski, V.; Snik, F.; Pietrow, A. G. M.

2016-07-01

Non-Common Path Errors (NCPEs) are the dominant factor limiting the performance of current astronomical high-contrast imaging instruments. If uncorrected, the resulting quasi-static speckle noise floor limits coronagraph performance to a raw contrast of typically 10-4, a value which does not improve with increasing integration time. The coronagraphic Modal Wavefront Sensor (cMWS) is a hybrid phase optic which uses holographic PSF copies to supply focal-plane wavefront sensing information directly from the science camera, whilst maintaining a bias-free coronagraphic PSF. This concept has already been successfully implemented on-sky at the William Herschel Telescope (WHT), La Palma, demonstrating both real-time wavefront sensing capability and successful extraction of slowly varying wavefront errors under a dominant and rapidly changing atmospheric speckle foreground. In this work we present an overview of the development of the cMWS and recent first light results obtained using the Leiden EXoplanet Instrument (LEXI), a high-contrast imager and high-dispersion spectrograph pathfinder instrument for the WHT.

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

PubMed

Kelly, Daniel; Caulfield, Brian

2012-01-01

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

Multi-modal myocontrol: Testing combined force- and electromyography.

PubMed

Nowak, Markus; Eiband, Thomas; Castellini, Claudio

2017-07-01

Myocontrol, that is control of prostheses using bodily signals, has proved in the decades to be a surprisingly hard problem for the scientific community of assistive and rehabilitation robotics. In particular, traditional surface electromyography (sEMG) seems to be no longer enough to guarantee dexterity (i.e., control over several degrees of freedom) and, most importantly, reliability. Multi-modal myocontrol is concerned with the idea of using novel signal gathering techniques as a replacement of, or alongside, sEMG, to provide high-density and diverse signals to improve dexterity and make the control more reliable. In this paper we present an offline and online assessment of multi-modal sEMG and force myography (FMG) targeted at hand and wrist myocontrol. A total number of twenty sEMG and FMG sensors were used simultaneously, in several combined configurations, to predict opening/closing of the hand and activation of two degrees of freedom of the wrist of ten intact subjects. The analysis was targeted at determining the optimal sensor combination and control parameters; the experimental results indicate that sEMG sensors alone perform worst, yielding a nRMSE of 9.1%, while mixing FMG and sEMG or using FMG only reduces the nRMSE to 5.2-6.6%. To validate these results, we engaged the subject with median performance in an online goal-reaching task. Analysis of this further experiment reveals that the online behaviour is similar to the offline one.

Assisted Perception, Planning and Control for Remote Mobility and Dexterous Manipulation

DTIC Science & Technology

2017-04-01

on unmanned aerial vehicles (UAVs). The underlying algorithm is based on an Extended Kalman Filter (EKF) that simultaneously estimates robot state...and sensor biases. The filter developed provided a probabilistic fusion of sensor data from many modalities to produce a single consistent position...estimation for a walking humanoid. Given a prior map using a Gaussian particle filter , the LIDAR based system is able to provide a drift-free

Multi-Sensor Information Integration and Automatic Understanding

DTIC Science & Technology

2008-05-27

distributions for target tracks and class which are utilized by an active learning cueing management framework to optimally task the appropriate sensor...modality to cued regions of interest. Moreover, this active learning approach also facilitates analyst cueing to help resolve track ambiguities in complex...scenes. We intend to leverage SIG’s active learning with analyst cueing under future efforts with ONR and other DoD agencies. Obtaining long- term

Multi-Sensor Information Integration and Automatic Understanding

DTIC Science & Technology

2008-08-27

distributions for target tracks and class which are utilized by an active learning cueing management framework to optimally task the appropriate sensor modality...to cued regions of interest. Moreover, this active learning approach also facilitates analyst cueing to help resolve track ambiguities in complex...scenes. We intend to leverage SIG’s active learning with analyst cueing under future efforts with ONR and other DoD agencies. Obtaining long- term

Robust Modal Filtering and Control of the X-56A Model with Simulated Fiber Optic Sensor Failures

NASA Technical Reports Server (NTRS)

Suh, Peter M.; Chin, Alexander W.; Marvis, Dimitri N.

2014-01-01

The X-56A aircraft is a remotely-piloted aircraft with flutter modes intentionally designed into the flight envelope. The X-56A program must demonstrate flight control while suppressing all unstable modes. A previous X-56A model study demonstrated a distributed-sensing-based active shape and active flutter suppression controller. The controller relies on an estimator which is sensitive to bias. This estimator is improved herein, and a real-time robust estimator is derived and demonstrated on 1530 fiber optic sensors. It is shown in simulation that the estimator can simultaneously reject 230 worst-case fiber optic sensor failures automatically. These sensor failures include locations with high leverage (or importance). To reduce the impact of leverage outliers, concentration based on a Mahalanobis trim criterion is introduced. A redescending M-estimator with Tukey bisquare weights is used to improve location and dispersion estimates within each concentration step in the presence of asymmetry (or leverage). A dynamic simulation is used to compare the concentrated robust estimator to a state-of-the-art real-time robust multivariate estimator. The estimators support a previously-derived mu-optimal shape controller. It is found that during the failure scenario, the concentrated modal estimator keeps the system stable.

Robust Modal Filtering and Control of the X-56A Model with Simulated Fiber Optic Sensor Failures

NASA Technical Reports Server (NTRS)

Suh, Peter M.; Chin, Alexander W.; Mavris, Dimitri N.

2016-01-01

The X-56A aircraft is a remotely-piloted aircraft with flutter modes intentionally designed into the flight envelope. The X-56A program must demonstrate flight control while suppressing all unstable modes. A previous X-56A model study demonstrated a distributed-sensing-based active shape and active flutter suppression controller. The controller relies on an estimator which is sensitive to bias. This estimator is improved herein, and a real-time robust estimator is derived and demonstrated on 1530 fiber optic sensors. It is shown in simulation that the estimator can simultaneously reject 230 worst-case fiber optic sensor failures automatically. These sensor failures include locations with high leverage (or importance). To reduce the impact of leverage outliers, concentration based on a Mahalanobis trim criterion is introduced. A redescending M-estimator with Tukey bisquare weights is used to improve location and dispersion estimates within each concentration step in the presence of asymmetry (or leverage). A dynamic simulation is used to compare the concentrated robust estimator to a state-of-the-art real-time robust multivariate estimator. The estimators support a previously-derived mu-optimal shape controller. It is found that during the failure scenario, the concentrated modal estimator keeps the system stable.

Fiber pressure sensors based on periodical mode coupling effects

NASA Astrophysics Data System (ADS)

Lotem, Haim; Wang, Wen C.; Wang, Michael; Schaafsma, David; Skolnick, Bob; Grebel, Haim

2005-05-01

Fiber optic sensor technology offers the possibility of implementing low weight, high performance and cost effective health and damage assessment for infrastructure elements. Common fiber sensors are based on the effect of external action on the spectral response of a Fabry-Perot or a Bragg grating section, or on the modal dynamics in multimode (MM) fiber. In the latter case, the fiber itself acts as the sensor, giving it the potential for large range coverage. We were interested in this type of sensor because of its cost advantage in monitoring structural health. In the course of the research, a new type of a rugged modal filter device, based on off-center splicing, was developed. This device, in combination with a MM fiber, was found to be a potential single point-pressure sensing device. Additionally, by translating the pressing point along a MM sensing fiber with a constant load and speed, a sinusoidal intensity modulation was observed. This harmonic behavior, during load translation, is explained by the theory of mode coupling and dispersion. The oscillation period, L~0.43. mm, obtained at 980 nm in a Corning SMF-28 fiber, corresponds to the wavevector difference, Db, between the two-coupled modes, by L = 2p/Db. An additional outcome of the present research is the observation that the response of the loaded MM fiber is strongly dependent on the polarization state of the light traveling along the MM fiber due to different response of the modes to polarization active elements. Our main conclusions are that in MM fiber optic sensor design, special cautions need to be taken in order to stabilize the system, and that the sensitivity along a MM fiber sensor is periodic with a period of ~ 0.4 - 0.5 mm, depending on various fiber parameters and excited modes.

Non-invasive monitoring of chewing and swallowing for objective quantification of ingestive behavior.

PubMed

Sazonov, Edward; Schuckers, Stephanie; Lopez-Meyer, Paulo; Makeyev, Oleksandr; Sazonova, Nadezhda; Melanson, Edward L; Neuman, Michael

2008-05-01

A methodology of studying of ingestive behavior by non-invasive monitoring of swallowing (deglutition) and chewing (mastication) has been developed. The target application for the developed methodology is to study the behavioral patterns of food consumption and producing volumetric and weight estimates of energy intake. Monitoring is non-invasive based on detecting swallowing by a sound sensor located over laryngopharynx or by a bone-conduction microphone and detecting chewing through a below-the-ear strain sensor. Proposed sensors may be implemented in a wearable monitoring device, thus enabling monitoring of ingestive behavior in free-living individuals. In this paper, the goals in the development of this methodology are two-fold. First, a system comprising sensors, related hardware and software for multi-modal data capture is designed for data collection in a controlled environment. Second, a protocol is developed for manual scoring of chewing and swallowing for use as a gold standard. The multi-modal data capture was tested by measuring chewing and swallowing in 21 volunteers during periods of food intake and quiet sitting (no food intake). Video footage and sensor signals were manually scored by trained raters. Inter-rater reliability study for three raters conducted on the sample set of five subjects resulted in high average intra-class correlation coefficients of 0.996 for bites, 0.988 for chews and 0.98 for swallows. The collected sensor signals and the resulting manual scores will be used in future research as a gold standard for further assessment of sensor design, development of automatic pattern recognition routines and study of the relationship between swallowing/chewing and ingestive behavior.

Modal Testing of Seven Shuttle Cargo Elements for Space Station

NASA Technical Reports Server (NTRS)

Kappus, Kathy O.; Driskill, Timothy C.; Parks, Russel A.; Patterson, Alan (Technical Monitor)

2001-01-01

From December 1996 to May 2001, the Modal and Control Dynamics Team at NASA's Marshall Space Flight Center (MSFC) conducted modal tests on seven large elements of the International Space Station. Each of these elements has been or will be launched as a Space Shuttle payload for transport to the International Space Station (ISS). Like other Shuttle payloads, modal testing of these elements was required for verification of the finite element models used in coupled loads analyses for launch and landing. The seven modal tests included three modules - Node, Laboratory, and Airlock, and four truss segments - P6, P3/P4, S1/P1, and P5. Each element was installed and tested in the Shuttle Payload Modal Test Bed at MSFC. This unique facility can accommodate any Shuttle cargo element for modal test qualification. Flexure assemblies were utilized at each Shuttle-to-payload interface to simulate a constrained boundary in the load carrying degrees of freedom. For each element, multiple-input, multiple-output burst random modal testing was the primary approach with controlled input sine sweeps for linearity assessments. The accelerometer channel counts ranged from 252 channels to 1251 channels. An overview of these tests, as well as some lessons learned, will be provided in this paper.

Blind identification of full-field vibration modes of output-only structures from uniformly-sampled, possibly temporally-aliased (sub-Nyquist), video measurements

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

Yang, Yongchao; Dorn, Charles; Mancini, Tyler

Enhancing the spatial and temporal resolution of vibration measurements and modal analysis could significantly benefit dynamic modelling, analysis, and health monitoring of structures. For example, spatially high-density mode shapes are critical for accurate vibration-based damage localization. In experimental or operational modal analysis, higher (frequency) modes, which may be outside the frequency range of the measurement, contain local structural features that can improve damage localization as well as the construction and updating of the modal-based dynamic model of the structure. In general, the resolution of vibration measurements can be increased by enhanced hardware. Traditional vibration measurement sensors such as accelerometers havemore » high-frequency sampling capacity; however, they are discrete point-wise sensors only providing sparse, low spatial sensing resolution measurements, while dense deployment to achieve high spatial resolution is expensive and results in the mass-loading effect and modification of structure's surface. Non-contact measurement methods such as scanning laser vibrometers provide high spatial and temporal resolution sensing capacity; however, they make measurements sequentially that requires considerable acquisition time. As an alternative non-contact method, digital video cameras are relatively low-cost, agile, and provide high spatial resolution, simultaneous, measurements. Combined with vision based algorithms (e.g., image correlation or template matching, optical flow, etc.), video camera based measurements have been successfully used for experimental and operational vibration measurement and subsequent modal analysis. However, the sampling frequency of most affordable digital cameras is limited to 30–60 Hz, while high-speed cameras for higher frequency vibration measurements are extremely costly. This work develops a computational algorithm capable of performing vibration measurement at a uniform sampling frequency lower than what is required by the Shannon-Nyquist sampling theorem for output-only modal analysis. In particular, the spatio-temporal uncoupling property of the modal expansion of structural vibration responses enables a direct modal decoupling of the temporally-aliased vibration measurements by existing output-only modal analysis methods, yielding (full-field) mode shapes estimation directly. Then the signal aliasing properties in modal analysis is exploited to estimate the modal frequencies and damping ratios. Furthermore, the proposed method is validated by laboratory experiments where output-only modal identification is conducted on temporally-aliased acceleration responses and particularly the temporally-aliased video measurements of bench-scale structures, including a three-story building structure and a cantilever beam.« less

Blind identification of full-field vibration modes of output-only structures from uniformly-sampled, possibly temporally-aliased (sub-Nyquist), video measurements

DOE PAGES

Yang, Yongchao; Dorn, Charles; Mancini, Tyler; ...

2016-12-05

Enhancing the spatial and temporal resolution of vibration measurements and modal analysis could significantly benefit dynamic modelling, analysis, and health monitoring of structures. For example, spatially high-density mode shapes are critical for accurate vibration-based damage localization. In experimental or operational modal analysis, higher (frequency) modes, which may be outside the frequency range of the measurement, contain local structural features that can improve damage localization as well as the construction and updating of the modal-based dynamic model of the structure. In general, the resolution of vibration measurements can be increased by enhanced hardware. Traditional vibration measurement sensors such as accelerometers havemore » high-frequency sampling capacity; however, they are discrete point-wise sensors only providing sparse, low spatial sensing resolution measurements, while dense deployment to achieve high spatial resolution is expensive and results in the mass-loading effect and modification of structure's surface. Non-contact measurement methods such as scanning laser vibrometers provide high spatial and temporal resolution sensing capacity; however, they make measurements sequentially that requires considerable acquisition time. As an alternative non-contact method, digital video cameras are relatively low-cost, agile, and provide high spatial resolution, simultaneous, measurements. Combined with vision based algorithms (e.g., image correlation or template matching, optical flow, etc.), video camera based measurements have been successfully used for experimental and operational vibration measurement and subsequent modal analysis. However, the sampling frequency of most affordable digital cameras is limited to 30–60 Hz, while high-speed cameras for higher frequency vibration measurements are extremely costly. This work develops a computational algorithm capable of performing vibration measurement at a uniform sampling frequency lower than what is required by the Shannon-Nyquist sampling theorem for output-only modal analysis. In particular, the spatio-temporal uncoupling property of the modal expansion of structural vibration responses enables a direct modal decoupling of the temporally-aliased vibration measurements by existing output-only modal analysis methods, yielding (full-field) mode shapes estimation directly. Then the signal aliasing properties in modal analysis is exploited to estimate the modal frequencies and damping ratios. Furthermore, the proposed method is validated by laboratory experiments where output-only modal identification is conducted on temporally-aliased acceleration responses and particularly the temporally-aliased video measurements of bench-scale structures, including a three-story building structure and a cantilever beam.« less

Dual-modality arterial pulse monitoring system for continuous blood pressure measurement.

PubMed

Wen-Xuan Dai; Yuan-Ting Zhang; Jing Liu; Xiao-Rong Ding; Ni Zhao

2016-08-01

Accurate and ambulatory measurement of blood pressure (BP) is essential for efficient diagnosis, management and prevention of cardiovascular diseases (CVDs). However, traditional cuff-based BP measurement methods provide only intermittent BP readings and can cause discomfort with the occlusive cuff. Although pulse transit time (PTT) method is promising for cuffless and continuous BP measurement, its pervasive use is restricted by its limited accuracy and requirement of placing sensors on multiple body sites. To tackle these issues, we propose a novel dual-modality arterial pulse monitoring system for continuous blood pressure measurement, which simultaneously records the pressure and photoplethysmography (PPG) signals of radial artery. The obtained signals can be used to generate a pressure-volume curve, from which the elasticity index (EI) and viscosity index (VI) can be extracted. Experiments were carried out among 7 healthy subjects with their PPG, ECG, arterial pressure wave and reference BP collected to examine the effectiveness of the proposed indexes. The results of this study demonstrate that a linear regression model combining EI and VI has significantly higher BP tracking correlation coefficient as compared to the PTT method. This suggests that the proposed system and method can potentially be used for convenient and continuous blood pressure estimation with higher accuracy.

Structural-change localization and monitoring through a perturbation-based inverse problem.

PubMed

Roux, Philippe; Guéguen, Philippe; Baillet, Laurent; Hamze, Alaa

2014-11-01

Structural-change detection and characterization, or structural-health monitoring, is generally based on modal analysis, for detection, localization, and quantification of changes in structure. Classical methods combine both variations in frequencies and mode shapes, which require accurate and spatially distributed measurements. In this study, the detection and localization of a local perturbation are assessed by analysis of frequency changes (in the fundamental mode and overtones) that are combined with a perturbation-based linear inverse method and a deconvolution process. This perturbation method is applied first to a bending beam with the change considered as a local perturbation of the Young's modulus, using a one-dimensional finite-element model for modal analysis. Localization is successful, even for extended and multiple changes. In a second step, the method is numerically tested under ambient-noise vibration from the beam support with local changes that are shifted step by step along the beam. The frequency values are revealed using the random decrement technique that is applied to the time-evolving vibrations recorded by one sensor at the free extremity of the beam. Finally, the inversion method is experimentally demonstrated at the laboratory scale with data recorded at the free end of a Plexiglas beam attached to a metallic support.

Optical fiber sensors and signal processing for intelligent structure monitoring

NASA Technical Reports Server (NTRS)

Rogowski, Robert; Claus, R. O.; Lindner, D. K.; Thomas, Daniel; Cox, Dave

1988-01-01

The analytic and experimental performance of optical fiber sensors for the control of vibration of large aerospace and other structures are investigated. In particular, model domain optical fiber sensor systems, are being studied due to their apparent potential as distributed, low mass sensors of vibration over appropriate ranges of both low frequency and low amplitude displacements. Progress during the past three months is outlined. Progress since September is divided into work in the areas of experimental hardware development, analytical analysis, control design and sensor development. During the next six months, tests of a prototype closed-loop control system for a beam are planned which will demonstrate the solution of several optical fiber instrumentation device problems, the performance of the control system theory which incorporates the model of the modal domain sensor, and the potential for distributed control which this sensor approach offers.

System level mechanical testing of the Clementine spacecraft

NASA Technical Reports Server (NTRS)

Haughton, James; Hauser, Joseph; Raynor, William; Lynn, Peter

1994-01-01

This paper discusses the system level structural testing that was performed to qualify the Clementine Spacecraft for flight. These tests included spin balance, combined acoustic and axial random vibration, lateral random vibration, quasi-static loads, pyrotechnic shock, modal survey and on-orbit jitter simulation. Some innovative aspects of this effort were: the simultaneously combined acoustic and random vibration test; the mass loaded interface modal survey test; and the techniques used to assess how operating on board mechanisms and thrusters affect sensor vision.

Multiple sensor fault diagnosis for dynamic processes.

PubMed

Li, Cheng-Chih; Jeng, Jyh-Cheng

2010-10-01

Modern industrial plants are usually large scaled and contain a great amount of sensors. Sensor fault diagnosis is crucial and necessary to process safety and optimal operation. This paper proposes a systematic approach to detect, isolate and identify multiple sensor faults for multivariate dynamic systems. The current work first defines deviation vectors for sensor observations, and further defines and derives the basic sensor fault matrix (BSFM), consisting of the normalized basic fault vectors, by several different methods. By projecting a process deviation vector to the space spanned by BSFM, this research uses a vector with the resulted weights on each direction for multiple sensor fault diagnosis. This study also proposes a novel monitoring index and derives corresponding sensor fault detectability. The study also utilizes that vector to isolate and identify multiple sensor faults, and discusses the isolatability and identifiability. Simulation examples and comparison with two conventional PCA-based contribution plots are presented to demonstrate the effectiveness of the proposed methodology. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.

On-chip photonic particle sensor

NASA Astrophysics Data System (ADS)

Singh, Robin; Ma, Danhao; Agarwal, Anu; Anthony, Brian

2018-02-01

We propose an on-chip photonic particle sensor design that can perform particle sizing and counting for various environmental applications. The sensor is based on micro photonic ring resonators that are able to detect the presence of the free space particles through the interaction with their evanescent electric field tail. The sensor can characterize a wide range of the particle size ranging from a few nano meters to micron ( 1 micron). The photonic platform offers high sensitivity, compactness, fast response of the device. Further, FDTD simulations are performed to analyze different particle-light interactions. Such a compact and portable platform, packaged with integrated photonic circuit provides a useful sensing modality in space shuttle and environmental applications.

Modal analysis using a Fourier analyzer, curve-fitting, and modal tuning

NASA Technical Reports Server (NTRS)

Craig, R. R., Jr.; Chung, Y. T.

1981-01-01

The proposed modal test program differs from single-input methods in that preliminary data may be acquired using multiple inputs, and modal tuning procedures may be employed to define closely spaced frquency modes more accurately or to make use of frequency response functions (FRF's) which are based on several input locations. In some respects the proposed modal test proram resembles earlier sine-sweep and sine-dwell testing in that broadband FRF's are acquired using several input locations, and tuning is employed to refine the modal parameter estimates. The major tasks performed in the proposed modal test program are outlined. Data acquisition and FFT processing, curve fitting, and modal tuning phases are described and examples are given to illustrate and evaluate them.

The contribution of cutaneous and kinesthetic sensory modalities in haptic perception of orientation.

PubMed

Frisoli, Antonio; Solazzi, Massimiliano; Reiner, Miriam; Bergamasco, Massimo

2011-06-30

The aim of this study was to understand the integration of cutaneous and kinesthetic sensory modalities in haptic perception of shape orientation. A specific robotic apparatus was employed to simulate the exploration of virtual surfaces by active touch with two fingers, with kinesthetic only, cutaneous only and combined sensory feedback. The cutaneous feedback was capable of displaying the local surface orientation at the contact point, through a small plate indenting the fingerpad at contact. A psychophysics test was conducted with SDT methodology on 6 subjects to assess the discrimination threshold of angle perception between two parallel surfaces, with three sensory modalities and two shape sizes. Results show that the cutaneous sensor modality is not affected by size of shape, but kinesthetic performance is decreasing with smaller size. Cutaneous and kinesthetic sensory cues are integrated according to a Bayesian model, so that the combined sensory stimulation always performs better than single modalities alone. Copyright © 2010 Elsevier Inc. All rights reserved.

Sensor Compromise Detection in Multiple-Target Tracking Systems

PubMed Central

Doucette, Emily A.; Curtis, Jess W.

2018-01-01

Tracking multiple targets using a single estimator is a problem that is commonly approached within a trusted framework. There are many weaknesses that an adversary can exploit if it gains control over the sensors. Because the number of targets that the estimator has to track is not known with anticipation, an adversary could cause a loss of information or a degradation in the tracking precision. Other concerns include the introduction of false targets, which would result in a waste of computational and material resources, depending on the application. In this work, we study the problem of detecting compromised or faulty sensors in a multiple-target tracker, starting with the single-sensor case and then considering the multiple-sensor scenario. We propose an algorithm to detect a variety of attacks in the multiple-sensor case, via the application of finite set statistics (FISST), one-class classifiers and hypothesis testing using nonparametric techniques. PMID:29466314

EDITORIAL: Sensors and sensing systems

NASA Astrophysics Data System (ADS)

Dewhurst, Richard; Tian, Gui Yun

2008-02-01

Sensors are very important for measurement science and technology. They serve as a vital component in new measurement techniques and instrumentation systems. Key qualities of a good sensor system are high resolution, high reliability, low cost, appropriate output for a given input (good sensitivity), rapid response time, small random error in results, and small systematic error. Linearity is also useful, but with the advent of lookup tables and software, it is not as important as it used to be. In the last several years, considerable effort around the world has been devoted to a wide range of sensors from nanoscale sensors to sensor networks. Collectively, these vast and multidisciplinary efforts are developing important technological roadmaps to futuristic sensors with new modalities, significantly enhanced effectiveness and integrated functionality (data processing, computation, decision making and communications). When properly organized, they will have important relevance to life science and security applications, e.g. the sensing and monitoring of chemical, biological, radiological and explosive threats. A special feature in this issue takes a snapshot of some recent developments that were first presented at an international conference, the 2007 IEEE International Conference on Networking, Sensing and Control (ICNSC). The conference discussed recent developments, from which a few papers have since been brought together in this special feature. Gas sensing for environmental monitoring remains a topical subject, and two papers deal with this issue. One is concerned with the exploitation of nanostructured Au-doped cobalt oxyhydroxide-based carbon monoxide sensors for fire detection at its earlier stages (Zhuiykov and Dowling), whilst another examines the role of oxygen in high temperature hydrogen sulfide detection using MISiC sensors (Weng et al). Again for environmental monitoring, another paper deals with accurate sound source localization in a reverberant environment using multiple acoustic sensors (Atmoko et al). Not only is gaseous monitoring important, there are particular difficulties when it comes to the continuous monitoring of solids by non-destructive evaluation techniques. Examples of potential solutions for specialist applications are sensors for the detection and measurement of thin dielectric layers using reflection of frequency-scanned millimetre electromagnetic waves (Bowring et al), and an electrostatic sensor for velocity measurements of pneumatically conveyed solid particles (Xu et al). For potential medical applications, position measurement of internal organs is an on-going challenge. Tracking of internal organ motion with a six degree-of-freedom MEMS sensor is discussed by Bandala and Joyce. We hope that these papers provide an insight into exciting developments that continue to take place in the field of sensors and control.

Utilizing Glove-Based Gestures and a Tactile Vest Display for Covert Communications and Robot Control

DTIC Science & Technology

2014-06-01

transmitted from a controller mechanism that contains inertial measurement unit ( IMU ) sensors to sense rotation and acceleration of movement. Earlier...assets, and standard hand signal commands can be presented to human team members via a variety of modalities. IMU sensor technologies placed on the body...obstacle event (e.g., climbing, crawling, combat roll , running) and between obstacles (i.e., walking). The following analyses are for each task

Development of a wavefront sensor for terahertz pulses.

PubMed

Abraham, Emmanuel; Cahyadi, Harsono; Brossard, Mathilde; Degert, Jérôme; Freysz, Eric; Yasui, Takeshi

2016-03-07

Wavefront characterization of terahertz pulses is essential to optimize far-field intensity distribution of time-domain (imaging) spectrometers or increase the peak power of intense terahertz sources. In this paper, we report on the wavefront measurement of terahertz pulses using a Hartmann sensor associated with a 2D electro-optic imaging system composed of a ZnTe crystal and a CMOS camera. We quantitatively determined the deformations of planar and converging spherical wavefronts using the modal Zernike reconstruction least-squares method. Associated with deformable mirrors, the sensor will also open the route to terahertz adaptive optics.

Two-mode elliptical-core weighted fiber sensors for vibration analysis

NASA Technical Reports Server (NTRS)

Vengsarkar, Ashish M.; Murphy, Kent A.; Fogg, Brian R.; Miller, William V.; Greene, Jonathan A.; Claus, Richard O.

1992-01-01

Two-mode, elliptical-core optical fibers are demonstrated in weighted, distributed and selective vibration-mode-filtering applications. We show how appropriate placement of optical fibers on a vibrating structure can lead to vibration mode filtering. Selective vibration-mode suppression on the order of 10 dB has been obtained using tapered two-mode, circular-core fibers with tapering functions that match the second derivatives of the modes of vibration to be enhanced. We also demonstrate the use of chirped, two-mode gratings in fibers as spatial modal sensors that are equivalents of shaped piezoelectric sensors.

Experimental Modal Analysis and Dynaic Strain Fiber Bragg Gratings for Structural Health Monitoring of Composite Aerospace Structures

NASA Astrophysics Data System (ADS)

Panopoulou, A.; Fransen, S.; Gomez Molinero, V.; Kostopoulos, V.

2012-07-01

The objective of this work is to develop a new structural health monitoring system for composite aerospace structures based on dynamic response strain measurements and experimental modal analysis techniques. Fibre Bragg Grating (FBG) optical sensors were used for monitoring the dynamic response of the composite structure. The structural dynamic behaviour has been numerically simulated and experimentally verified by means of vibration testing. The hypothesis of all vibration tests was that actual damage in composites reduces their stiffness and produces the same result as mass increase produces. Thus, damage was simulated by slightly varying locally the mass of the structure at different zones. Experimental modal analysis based on the strain responses was conducted and the extracted strain mode shapes were the input for the damage detection expert system. A feed-forward back propagation neural network was the core of the damage detection system. The features-input to the neural network consisted of the strain mode shapes, extracted from the experimental modal analysis. Dedicated training and validation activities were carried out based on the experimental results. The system showed high reliability, confirmed by the ability of the neural network to recognize the size and the position of damage on the structure. The experiments were performed on a real structure i.e. a lightweight antenna sub- reflector, manufactured and tested at EADS CASA ESPACIO. An integrated FBG sensor network, based on the advantage of multiplexing, was mounted on the structure with optimum topology. Numerical simulation of both structures was used as a support tool at all the steps of the work. Potential applications for the proposed system are during ground qualification extensive tests of space structures and during the mission as modal analysis tool on board, being able via the FBG responses to identify a potential failure.

A radar-enabled collaborative sensor network integrating COTS technology for surveillance and tracking.

PubMed

Kozma, Robert; Wang, Lan; Iftekharuddin, Khan; McCracken, Ernest; Khan, Muhammad; Islam, Khandakar; Bhurtel, Sushil R; Demirer, R Murat

2012-01-01

The feasibility of using Commercial Off-The-Shelf (COTS) sensor nodes is studied in a distributed network, aiming at dynamic surveillance and tracking of ground targets. Data acquisition by low-cost (<$50 US) miniature low-power radar through a wireless mote is described. We demonstrate the detection, ranging and velocity estimation, classification and tracking capabilities of the mini-radar, and compare results to simulations and manual measurements. Furthermore, we supplement the radar output with other sensor modalities, such as acoustic and vibration sensors. This method provides innovative solutions for detecting, identifying, and tracking vehicles and dismounts over a wide area in noisy conditions. This study presents a step towards distributed intelligent decision support and demonstrates effectiveness of small cheap sensors, which can complement advanced technologies in certain real-life scenarios.

Multimodal physiological sensor for motion artefact rejection.

PubMed

Goverdovsky, Valentin; Looney, David; Kidmose, Preben; Mandic, Danilo P

2014-01-01

This work introduces a novel physiological sensor, which combines electrical and mechanical modalities in a co-located arrangement, to reject motion-induced artefacts. The mechanically sensitive element consists of an electret condenser microphone containing a light diaphragm, allowing it to detect local mechanical displacements and disregard large-scale whole body movements. The electrically sensitive element comprises a highly flexible membrane, conductive on one side and insulating on the other. It covers the sound hole of the microphone, thereby forming an isolated pocket of air between the membrane and the diaphragm. The co-located arrangement of the modalities allows the microphone to sense mechanical disturbances directly through the electrode, thus providing an accurate proxy to artefacts caused by relative motion between the skin and the electrode. This proxy is used to reject such artefacts in the electrical physiological signals, enabling enhanced recording quality in wearable health applications.

Short-Term Effect of Prosthesis Transforming Sensory Modalities on Walking in Stroke Patients with Hemiparesis

PubMed Central

Sekiguchi, Yusuke; Honda, Keita; Ishiguro, Akio

2016-01-01

Sensory impairments caused by neurological or physical disorders hamper kinesthesia, making rehabilitation difficult. In order to overcome this problem, we proposed and developed a novel biofeedback prosthesis called Auditory Foot for transforming sensory modalities, in which the sensor prosthesis transforms plantar sensations to auditory feedback signals. This study investigated the short-term effect of the auditory feedback prosthesis on walking in stroke patients with hemiparesis. To evaluate the effect, we compared four conditions of auditory feedback from plantar sensors at the heel and fifth metatarsal. We found significant differences in the maximum hip extension angle and ankle plantar flexor moment on the affected side during the stance phase, between conditions with and without auditory feedback signals. These results indicate that our sensory prosthesis could enhance walking performance in stroke patients with hemiparesis, resulting in effective short-term rehabilitation. PMID:27547456

Scan Patterns Predict Sentence Production in the Cross-Modal Processing of Visual Scenes

ERIC Educational Resources Information Center

Coco, Moreno I.; Keller, Frank

2012-01-01

Most everyday tasks involve multiple modalities, which raises the question of how the processing of these modalities is coordinated by the cognitive system. In this paper, we focus on the coordination of visual attention and linguistic processing during speaking. Previous research has shown that objects in a visual scene are fixated before they…

Development of multichannel soft tactile sensors having fingerprint structure.

PubMed

Tsutsui, H; Murashima, Y; Honma, N; Kobayashi, K

2014-01-01

It is possible to accurately recognize the shape of an object or to grip it by setting soft tactile sensors on a robot's hands. We studied a multichannel soft tactile sensor as an artificial hand and evaluated the pressure's response performance from several directions and the slipping and sliding responses. The tactile sensor consisted of multiple pneumatic sensors and a soft cap with a fingerprint structure that was made of silicone gum and was separated from multiple spaces. Evaluation tests showed that the multiple soft tactile sensors estimate both an object's contact force and its contact location. Our tactile sensor also measured the object's roughness by the slide on surface texture.

The GuideView System for Interactive, Structured, Multi-modal Delivery of Clinical Guidelines

NASA Technical Reports Server (NTRS)

Iyengar, Sriram; Florez-Arango, Jose; Garcia, Carlos Andres

2009-01-01

GuideView is a computerized clinical guideline system which delivers clinical guidelines in an easy-to-understand and easy-to-use package. It may potentially enhance the quality of medical care or allow non-medical personnel to provide acceptable levels of care in situations where physicians or nurses may not be available. Such a system can be very valuable during space flight missions when a physician is not readily available, or perhaps the designated medical personnel is unable to provide care. Complex clinical guidelines are broken into simple steps. At each step clinical information is presented in multiple modes, including voice,audio, text, pictures, and video. Users can respond via mouse clicks or via voice navigation. GuideView can also interact with medical sensors using wireless or wired connections. The system's interface is illustrated and the results of a usability study are presented.

Roles of frequency, attitudes, and multiple intelligence modality surrounding Electricity Content-Based Reader's Theatre

NASA Astrophysics Data System (ADS)

Hosier, Julie Winchester

Integration of subjects is something elementary teachers must do to insure required objectives are covered. Science-based Reader's Theatre is one way to weave reading into science. This study examined the roles of frequency, attitudes, and Multiple Intelligence modalities surrounding Electricity Content-Based Reader's Theatre. This study used quasi-experimental, repeated measures ANOVA with time as a factor design. A convenience sample of two fifth-grade classrooms participated in the study for eighteen weeks. Five Electricity Achievement Tests were given throughout the study to assess students' growth. A Student Reader's Theatre Attitudinal Survey revealed students' attitudes before and after Electricity Content-Based Reader's Theatre treatment. The Multiple Intelligence Inventory for Kids (Faris, 2007) examined whether Multiple Intelligence modality played a role in achievement on Electricity Test 4, the post-treatment test. Analysis using repeated measures ANOVA and an independent t-test found that students in the experimental group, which practiced its student-created Electricity Content-Based Reader's Theatre skits ten times versus two times for the for control group, did significantly better on Electricity Achievement Test 4, t(76) = 3.018, p = 0.003. Dependent t-tests did not find statistically significant differences between students' attitudes about Electricity Content-Based Reader's Theatre before and after treatment. A Kruskal-Wallis test found no statistically significant difference between the various Multiple Intelligence modalities score mean ranks (x2 = 5.57, df = 2, alpha = .062). Qualitative data do, however, indicate students had strong positive feelings about Electricity Content-Based Reader's Theatre after treatment. Students indicated it to be motivating, confidence-building, and a fun way to learn about science; however, they disliked writing their own scripts. Examining the frequency, attitudes, and Multiple Intelligence modalities lead to the conclusion that the role of frequency had the greatest impact on the success of Electricity Content-Based Reader's Theatre. The participating teachers, students, and research found integrating science and reading through Electricity Content-Based Reader's Theatre beneficial.

Optical fiber sensors for the non-destructive evaluation of materials

NASA Technical Reports Server (NTRS)

1986-01-01

The operation of the modal domain vibration sensor was demonstrated in several simple vibrational systems. Two apparent advantages are the sensors bandwidth and sensitivity. An inherent drawback of standard vibration detection devices is their rapid cost increase with high frequency bandwidth. This sensor showed consistent response in the freqency range of 1.5 to 400 Hz. By imparting very small but measurable excitations in the structures, the sensors ability to respond to very low order vibration induced strain was established. Dynamic ranges on the order of 18 to 22 dB for the CF beam and string systems respectively were observed. The sensor itself represents a very simple system: a coherent source, a single fiber and a low bandwidth detector. The inherent advantages of ruggedness and immunity to external radiation can also be added. Finally, the sensor minimally impairs structural motion through loading, an advantage in monitoring small vibrations or lightweight structures. Some drawbacks of the sensor are also noted.

Detection of person borne IEDs using multiple cooperative sensors

NASA Astrophysics Data System (ADS)

MacIntosh, Scott; Deming, Ross; Hansen, Thorkild; Kishan, Neel; Tang, Ling; Shea, Jing; Lang, Stephen

2011-06-01

The use of multiple cooperative sensors for the detection of person borne IEDs is investigated. The purpose of the effort is to evaluate the performance benefits of adding multiple sensor data streams into an aided threat detection algorithm, and a quantitative analysis of which sensor data combinations improve overall detection performance. Testing includes both mannequins and human subjects with simulated suicide bomb devices of various configurations, materials, sizes and metal content. Aided threat recognition algorithms are being developed to test detection performance of individual sensors against combined fused sensors inputs. Sensors investigated include active and passive millimeter wave imaging systems, passive infrared, 3-D profiling sensors and acoustic imaging. The paper describes the experimental set-up and outlines the methodology behind a decision fusion algorithm-based on the concept of a "body model".

Psychophysiological Sensing and State Classification for Attention Management in Commercial Aviation

NASA Technical Reports Server (NTRS)

Harrivel, Angela R.; Liles, Charles; Stephens, Chad L.; Ellis, Kyle K.; Prinzel, Lawrence J.; Pope, Alan T.

2016-01-01

Attention-related human performance limiting states (AHPLS) can cause pilots to lose airplane state awareness (ASA), and their detection is important to improving commercial aviation safety. The Commercial Aviation Safety Team found that the majority of recent international commercial aviation accidents attributable to loss of control inflight involved flight crew loss of airplane state awareness, and that distraction of various forms was involved in all of them. Research on AHPLS, including channelized attention, diverted attention, startle / surprise, and confirmation bias, has been recommended in a Safety Enhancement (SE) entitled "Training for Attention Management." To accomplish the detection of such cognitive and psychophysiological states, a broad suite of sensors has been implemented to simultaneously measure their physiological markers during high fidelity flight simulation human subject studies. Pilot participants were asked to perform benchmark tasks and experimental flight scenarios designed to induce AHPLS. Pattern classification was employed to distinguish the AHPLS induced by the benchmark tasks. Unimodal classification using pre-processed electroencephalography (EEG) signals as input features to extreme gradient boosting, random forest and deep neural network multiclass classifiers was implemented. Multi-modal classification using galvanic skin response (GSR) in addition to the same EEG signals and using the same types of classifiers produced increased accuracy with respect to the unimodal case (90 percent vs. 86 percent), although only via the deep neural network classifier. These initial results are a first step toward the goal of demonstrating simultaneous real time classification of multiple states using multiple sensing modalities in high-fidelity flight simulators. This detection is intended to support and inform training methods under development to mitigate the loss of ASA and thus reduce accidents and incidents.

Modal control of a plate using a fuzzy logic controller

NASA Astrophysics Data System (ADS)

Sharma, Manu; Singh, S. P.; Sachdeva, B. L.

2007-08-01

This paper presents fuzzy logic based independent modal space control (IMSC) and fuzzy logic based modified independent modal space control (MIMSC) of vibration. The rule base of the controller consists of nine rules, which have been derived based upon simple human reasoning. Input to the controller consists of the first two modal displacements and velocities of the structure and the output of the controller is the modal force to be applied by the actuator. Fuzzy logic is used in such a way that the actuator is never called to apply effort which is beyond safe limits and also the operator is saved from calculating control gains. The proposed fuzzy controller is experimentally tested for active vibration control of a cantilevered plate. A piezoelectric patch is used as a sensor to sense vibrations of the plate and another piezoelectric patch is used as an actuator to control vibrations of the plate. For analytical formulation, a finite element method based upon Hamilton's principle is used to model the plate. For experimentation, the first two modes of the plate are observed using a Kalman observer. Real-time experiments are performed to control the first mode, the second mode and both modes simultaneously. Experiments are also performed to control the first mode by IMSC, the second mode by IMSC and both modes simultaneously by MIMSC. It is found that for the same decibel reduction in the first mode, the voltage applied by the fuzzy logic based controller is less than that applied by IMSC. While controlling the second mode by IMSC, a considerable amount of spillover is observed in the first mode and region just after the second mode, whereas while controlling the second mode by fuzzy logic, spillover effects are much smaller. While controlling two modes simultaneously, with a single sensor/actuator pair, appreciable resonance control is observed both with fuzzy logic based MIMSC as well as with direct MIMSC, but there is a considerable amount of spillover in the off-resonance region. This may be due to the sub-optimal location and/or an insufficient number of actuators. So, another smart plate with two piezoelectric actuators and one piezoelectric sensor is considered. Piezoelectric patches are fixed in an area where modal strains are high. With this configuration of the smart plate, experiments are conducted to control the first three modes of the plate and it is found that spillover effects are greatly reduced.

Image reconstruction by domain-transform manifold learning.

PubMed

Zhu, Bo; Liu, Jeremiah Z; Cauley, Stephen F; Rosen, Bruce R; Rosen, Matthew S

2018-03-21

Image reconstruction is essential for imaging applications across the physical and life sciences, including optical and radar systems, magnetic resonance imaging, X-ray computed tomography, positron emission tomography, ultrasound imaging and radio astronomy. During image acquisition, the sensor encodes an intermediate representation of an object in the sensor domain, which is subsequently reconstructed into an image by an inversion of the encoding function. Image reconstruction is challenging because analytic knowledge of the exact inverse transform may not exist a priori, especially in the presence of sensor non-idealities and noise. Thus, the standard reconstruction approach involves approximating the inverse function with multiple ad hoc stages in a signal processing chain, the composition of which depends on the details of each acquisition strategy, and often requires expert parameter tuning to optimize reconstruction performance. Here we present a unified framework for image reconstruction-automated transform by manifold approximation (AUTOMAP)-which recasts image reconstruction as a data-driven supervised learning task that allows a mapping between the sensor and the image domain to emerge from an appropriate corpus of training data. We implement AUTOMAP with a deep neural network and exhibit its flexibility in learning reconstruction transforms for various magnetic resonance imaging acquisition strategies, using the same network architecture and hyperparameters. We further demonstrate that manifold learning during training results in sparse representations of domain transforms along low-dimensional data manifolds, and observe superior immunity to noise and a reduction in reconstruction artefacts compared with conventional handcrafted reconstruction methods. In addition to improving the reconstruction performance of existing acquisition methodologies, we anticipate that AUTOMAP and other learned reconstruction approaches will accelerate the development of new acquisition strategies across imaging modalities.

Image reconstruction by domain-transform manifold learning

NASA Astrophysics Data System (ADS)

Zhu, Bo; Liu, Jeremiah Z.; Cauley, Stephen F.; Rosen, Bruce R.; Rosen, Matthew S.

2018-03-01

Image reconstruction is essential for imaging applications across the physical and life sciences, including optical and radar systems, magnetic resonance imaging, X-ray computed tomography, positron emission tomography, ultrasound imaging and radio astronomy. During image acquisition, the sensor encodes an intermediate representation of an object in the sensor domain, which is subsequently reconstructed into an image by an inversion of the encoding function. Image reconstruction is challenging because analytic knowledge of the exact inverse transform may not exist a priori, especially in the presence of sensor non-idealities and noise. Thus, the standard reconstruction approach involves approximating the inverse function with multiple ad hoc stages in a signal processing chain, the composition of which depends on the details of each acquisition strategy, and often requires expert parameter tuning to optimize reconstruction performance. Here we present a unified framework for image reconstruction—automated transform by manifold approximation (AUTOMAP)—which recasts image reconstruction as a data-driven supervised learning task that allows a mapping between the sensor and the image domain to emerge from an appropriate corpus of training data. We implement AUTOMAP with a deep neural network and exhibit its flexibility in learning reconstruction transforms for various magnetic resonance imaging acquisition strategies, using the same network architecture and hyperparameters. We further demonstrate that manifold learning during training results in sparse representations of domain transforms along low-dimensional data manifolds, and observe superior immunity to noise and a reduction in reconstruction artefacts compared with conventional handcrafted reconstruction methods. In addition to improving the reconstruction performance of existing acquisition methodologies, we anticipate that AUTOMAP and other learned reconstruction approaches will accelerate the development of new acquisition strategies across imaging modalities.

Standards-Based Wireless Sensor Networking Protocols for Spaceflight Applications

NASA Technical Reports Server (NTRS)

Wagner, Raymond S.

2010-01-01

Wireless sensor networks (WSNs) have the capacity to revolutionize data gathering in both spaceflight and terrestrial applications. WSNs provide a huge advantage over traditional, wired instrumentation since they do not require wiring trunks to connect sensors to a central hub. This allows for easy sensor installation in hard to reach locations, easy expansion of the number of sensors or sensing modalities, and reduction in both system cost and weight. While this technology offers unprecedented flexibility and adaptability, implementing it in practice is not without its difficulties. Recent advances in standards-based WSN protocols for industrial control applications have come a long way to solving many of the challenges facing practical WSN deployments. In this paper, we will overview two of the more promising candidates - WirelessHART from the HART Communication Foundation and ISA100.11a from the International Society of Automation - and present the architecture for a new standards-based sensor node for networking and applications research.

Graphene based chalcogenide fiber-optic evanescent wave sensor for detection of hemoglobin in human blood

NASA Astrophysics Data System (ADS)

Sharma, Anuj K.; Gupta, Jyoti

2018-03-01

Fiber optic evanescent wave sensor with graphene as an absorption-enhancing layer to measure hemoglobin concentration in human blood is proposed. Previous modal functions and experimental results describing the variation of optical constants of human blood with different hemoglobin concentrations in the near-infrared spectral region are considered for sensor design simulation. The sensor's performance is closely analyzed in terms of its absorption coefficient, sensitivity, and detection limit. It is found that the proposed sensor should be operated at longer light wavelength to get more enhanced sensitivity and smaller detection limit. At 1000 nm wavelength, a detection limit of 18 μg/dL and sensitivity of 6.71 × 10-4 per g/dL is achievable with the proposed sensor. The sensitivity is found to be better for larger hemoglobin concentrations. The results are correlated with the evanescent wave penetration depth.

Sensor-Only System Identification for Structural Health Monitoring of Advanced Aircraft

NASA Technical Reports Server (NTRS)

Kukreja, Sunil L.; Bernstein, Dennis S.

2012-01-01

Environmental conditions, cyclic loading, and aging contribute to structural wear and degradation, and thus potentially catastrophic events. The challenge of health monitoring technology is to determine incipient changes accurately and efficiently. This project addresses this challenge by developing health monitoring techniques that depend only on sensor measurements. Since actively controlled excitation is not needed, sensor-to-sensor identification (S2SID) provides an in-flight diagnostic tool that exploits ambient excitation to provide advance warning of significant changes. S2SID can subsequently be followed up by ground testing to localize and quantify structural changes. The conceptual foundation of S2SID is the notion of a pseudo-transfer function, where one sensor is viewed as the pseudo-input and another is viewed as the pseudo-output, is approach is less restrictive than transmissibility identification and operational modal analysis since no assumption is made about the locations of the sensors relative to the excitation.

Non-invasive photo acoustic approach for human bone diagnosis.

PubMed

Thella, Ashok Kumar; Rizkalla, James; Helmy, Ahdy; Suryadevara, Vinay Kumar; Salama, Paul; Rizkalla, Maher

2016-12-01

The existing modalities of bone diagnosis including X-ray and ultrasound may cite drawback in some cases related to health issues and penetration depth, while the ultrasound modality may lack image quality. Photo acoustic approach however, provides light energy to the acoustic wave, enabling it to activate and respond according to the propagating media (which is type of bones in this case). At the same time, a differential temperature change may result in the bio heat response, resulting from the heat absorbed across the multiple materials under study. In this work, we have demonstrated the features of using photo acoustic modality in order to non-invasively diagnose the type of human bones based on their electrical, thermal, and acoustic properties that differentiate the output response of each type. COMSOL software was utilized to combine both acoustic equations and bio heat equations, in order to study both the thermal and acoustic responses through which the differential diagnosis can be obtained. In this study, we solved both the acoustic equation and bio heat equations for four types of bones, bone (cancellous), bone (cortical), bone marrow (red), and bone marrow (yellow). 1 MHz acoustic source frequency was chosen and 10(5) W/m(2) power source was used in the simulation. The simulation tested the dynamic response of the wave over a distance of 5 cm from each side for the source. Near 2.4 cm was detected from simulation from each side of the source with a temperature change of within 0.5 K for various types of bones, citing a promising technique for a practical model to detect the type of bones via the differential temperature as well as the acoustic was response via the multiple materials associated with the human bones (skin and blood). The simulation results suggest that the PA technique may be applied to non-invasive diagnosis for the different types of bones, including cancerous bones. A practical model for detecting both the temperature change via IR sensors, and acoustic wave signals may be detected via sensitive pressure transducer, which is reserved for future realization.

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.

The direct effects of gravity on the control and output matrices of controlled structure models

NASA Technical Reports Server (NTRS)

Rey, Daniel A.; Alexander, Harold L.; Crawley, Edward F.

1992-01-01

The effects of gravity on the dynamic performance of structural control actuators and sensors are dual forms of an additive perturbation that can attenuate or amplify the device response (input or output). The modal modeling of these perturbations is derived for the general case of arbitrarily oriented devices and arbitrarily oriented planes of deformation. A nondimensional sensitivity analysis to identify the circumstances under which the effects of gravity are important is presented. Results show that gravity effects become important when the product of the ratio of the normalized modal slope and the modal displacement is comparable to the ratio of the gravitational acceleration and the product of the beam length and the squared eigenfrequency for a given mode.

Adaptable Optical Fiber Displacement-Curvature Sensor Based on a Modal Michelson Interferometer with a Tapered Single Mode Fiber

PubMed Central

Salceda-Delgado, G.; Martinez-Rios, A.; Selvas-Aguilar, R.; Álvarez-Tamayo, R. I.; Castillo-Guzman, A.; Ibarra-Escamilla, B.; Durán-Ramírez, V. M.; Enriquez-Gomez, L. F.

2017-01-01

A compact, highly sensitive optical fiber displacement and curvature radius sensor is presented. The device consists of an adiabatic bi-conical fused fiber taper spliced to a single-mode fiber (SMF) segment with a flat face end. The bi-conical taper structure acts as a modal coupling device between core and cladding modes for the SMF segment. When the bi-conical taper is bent by an axial displacement, the symmetrical bi-conical shape of the tapered structure is stressed, causing a change in the refractive index profile which becomes asymmetric. As a result, the taper adiabaticity is lost, and interference between modes appears. As the bending increases, a small change in the fringe visibility and a wavelength shift on the periodical reflection spectrum of the in-fiber interferometer is produced. The displacement sensitivity and the spectral periodicity of the device can be adjusted by the proper selection of the SMF length. Sensitivities from around 1.93 to 3.4 nm/mm were obtained for SMF length between 7.5 and 12.5 cm. Both sensor interrogations, wavelength shift and visibility contrast, can be used to measure displacement and curvature radius magnitudes. PMID:28574421

Adaptable Optical Fiber Displacement-Curvature Sensor Based on a Modal Michelson Interferometer with a Tapered Single Mode Fiber.

PubMed

Salceda-Delgado, G; Martinez-Rios, A; Selvas-Aguilar, R; Álvarez-Tamayo, R I; Castillo-Guzman, A; Ibarra-Escamilla, B; Durán-Ramírez, V M; Enriquez-Gomez, L F

2017-06-02

A compact, highly sensitive optical fiber displacement and curvature radius sensor is presented. The device consists of an adiabatic bi-conical fused fiber taper spliced to a single-mode fiber (SMF) segment with a flat face end. The bi-conical taper structure acts as a modal coupling device between core and cladding modes for the SMF segment. When the bi-conical taper is bent by an axial displacement, the symmetrical bi-conical shape of the tapered structure is stressed, causing a change in the refractive index profile which becomes asymmetric. As a result, the taper adiabaticity is lost, and interference between modes appears. As the bending increases, a small change in the fringe visibility and a wavelength shift on the periodical reflection spectrum of the in-fiber interferometer is produced. The displacement sensitivity and the spectral periodicity of the device can be adjusted by the proper selection of the SMF length. Sensitivities from around 1.93 to 3.4 nm/mm were obtained for SMF length between 7.5 and 12.5 cm. Both sensor interrogations, wavelength shift and visibility contrast, can be used to measure displacement and curvature radius magnitudes.

Combined Dynamic Time Warping with Multiple Sensors for 3D Gesture Recognition

PubMed Central

2017-01-01

Cyber-physical systems, which closely integrate physical systems and humans, can be applied to a wider range of applications through user movement analysis. In three-dimensional (3D) gesture recognition, multiple sensors are required to recognize various natural gestures. Several studies have been undertaken in the field of gesture recognition; however, gesture recognition was conducted based on data captured from various independent sensors, which rendered the capture and combination of real-time data complicated. In this study, a 3D gesture recognition method using combined information obtained from multiple sensors is proposed. The proposed method can robustly perform gesture recognition regardless of a user’s location and movement directions by providing viewpoint-weighted values and/or motion-weighted values. In the proposed method, the viewpoint-weighted dynamic time warping with multiple sensors has enhanced performance by preventing joint measurement errors and noise due to sensor measurement tolerance, which has resulted in the enhancement of recognition performance by comparing multiple joint sequences effectively. PMID:28817094

Combined Dynamic Time Warping with Multiple Sensors for 3D Gesture Recognition.

PubMed

Choi, Hyo-Rim; Kim, TaeYong

2017-08-17

Cyber-physical systems, which closely integrate physical systems and humans, can be applied to a wider range of applications through user movement analysis. In three-dimensional (3D) gesture recognition, multiple sensors are required to recognize various natural gestures. Several studies have been undertaken in the field of gesture recognition; however, gesture recognition was conducted based on data captured from various independent sensors, which rendered the capture and combination of real-time data complicated. In this study, a 3D gesture recognition method using combined information obtained from multiple sensors is proposed. The proposed method can robustly perform gesture recognition regardless of a user's location and movement directions by providing viewpoint-weighted values and/or motion-weighted values. In the proposed method, the viewpoint-weighted dynamic time warping with multiple sensors has enhanced performance by preventing joint measurement errors and noise due to sensor measurement tolerance, which has resulted in the enhancement of recognition performance by comparing multiple joint sequences effectively.

Cooperative angle-only orbit initialization via fusion of admissible areas

NASA Astrophysics Data System (ADS)

Jia, Bin; Pham, Khanh; Blasch, Erik; Chen, Genshe; Shen, Dan; Wang, Zhonghai

2017-05-01

For the short-arc angle only orbit initialization problem, the admissible area is often used. However, the accuracy using a single sensor is often limited. For high value space objects, it is desired to achieve more accurate results. Fortunately, multiple sensors, which are dedicated to space situational awareness, are available. The work in this paper uses multiple sensors' information to cooperatively initialize the orbit based on the fusion of multiple admissible areas. Both the centralized fusion and decentralized fusion are discussed. Simulation results verify the expectation that the orbit initialization accuracy is improved by using information from multiple sensors.

Determination of poles and zeros of transfer functions for flexible spacecraft attitude control

NASA Technical Reports Server (NTRS)

Ohkami, Y.; Likins, P. W.

1976-01-01

The transfer function matrix is obtained for a three-input and three-output model of minimum sensors and actuators for the attitude control system of flexible spacecraft, and a method is described for determining the poles and zeros of this transfer function. Three cases are considered: (1) the actuators and the sensors are all attached to the primary body, (2) the actuators are on the primary body and the sensors are on the sub-body, and (3) the actuators are on the sub-body and the sensors are on the primary body. The zero-determination problem is shown to reduce to eigenvalue calculations of a matrix which is constructed from the inertial and modal matrices in a simple fashion.

Magnetic Field Measurements Based on Terfenol Coated Photonic Crystal Fibers

PubMed Central

Quintero, Sully M. M.; Martelli, Cicero; Braga, Arthur M. B.; Valente, Luiz C. G.; Kato, Carla C.

2011-01-01

A magnetic field sensor based on the integration of a high birefringence photonic crystal fiber and a composite material made of Terfenol particles and an epoxy resin is proposed. An in-fiber modal interferometer is assembled by evenly exciting both eigenemodes of the HiBi fiber. Changes in the cavity length as well as the effective refractive index are induced by exposing the sensor head to magnetic fields. The magnetic field sensor has a sensitivity of 0.006 (nm/mT) over a range from 0 to 300 mT with a resolution about ±1 mT. A fiber Bragg grating magnetic field sensor is also fabricated and employed to characterize the response of Terfenol composite to the magnetic field. PMID:22247655

Kansei Biosensor and IT Society

NASA Astrophysics Data System (ADS)

Toko, Kiyoshi

A taste sensor with global selectivity is composed of several kinds of lipid/polymer membranes for transforming information of taste substances into electric signal. The sensor output shows different patterns for chemical substances which have different taste qualities such as saltiness and sourness. Taste interactions such as suppression effect, which occurs between bitterness and sweetness, can be detected and quantified using the taste sensor. The taste and also smell of foodstuffs such as beer, coffee, mineral water, soup and milk can be discussed quantitatively. The taste sensor provides the objective scale for the human sensory expression. Multi-modal communication becomes possible using a taste/smell recognition microchip, which produces virtual taste. We are now standing at the beginning of a new age of communication using digitized taste.

MITRE sensor layer prototype

NASA Astrophysics Data System (ADS)

Duff, Francis; McGarry, Donald; Zasada, David; Foote, Scott

2009-05-01

The MITRE Sensor Layer Prototype is an initial design effort to enable every sensor to help create new capabilities through collaborative data sharing. By making both upstream (raw) and downstream (processed) sensor data visible, users can access the specific level, type, and quantities of data needed to create new data products that were never anticipated by the original designers of the individual sensors. The major characteristic that sets sensor data services apart from typical enterprise services is the volume (on the order of multiple terabytes) of raw data that can be generated by most sensors. Traditional tightly coupled processing approaches extract pre-determined information from the incoming raw sensor data, format it, and send it to predetermined users. The community is rapidly reaching the conclusion that tightly coupled sensor processing loses too much potentially critical information.1 Hence upstream (raw and partially processed) data must be extracted, rapidly archived, and advertised to the enterprise for unanticipated uses. The authors believe layered sensing net-centric integration can be achieved through a standardize-encapsulate-syndicateaggregate- manipulate-process paradigm. The Sensor Layer Prototype's technical approach focuses on implementing this proof of concept framework to make sensor data visible, accessible and useful to the enterprise. To achieve this, a "raw" data tap between physical transducers associated with sensor arrays and the embedded sensor signal processing hardware and software has been exploited. Second, we encapsulate and expose both raw and partially processed data to the enterprise within the context of a service-oriented architecture. Third, we advertise the presence of multiple types, and multiple layers of data through geographic-enabled Really Simple Syndication (GeoRSS) services. These GeoRSS feeds are aggregated, manipulated, and filtered by a feed aggregator. After filtering these feeds to bring just the type and location of data sought by multiple processes to the attention of each processing station, just that specifically sought data is downloaded to each process application. The Sensor Layer Prototype participated in a proof-of-concept demonstration in April 2008. This event allowed multiple MITRE innovation programs to interact among themselves to demonstrate the ability to couple value-adding but previously unanticipated users to the enterprise. For this event, the Sensor Layer Prototype was used to show data entering the environment in real time. Multiple data types were encapsulated and added to the database via the Sensor Layer Prototype, specifically National Imagery Transmission Format 2.1 (NITF), NATO Standardization Format 4607 (STANAG 4607), Cursor-on-Target (CoT), Joint Photographic Experts Group (JPEG), Hierarchical Data Format (HDF5) and several additional sensor file formats describing multiple sensors addressing a common scenario.

Multiple frequency method for operating electrochemical sensors

DOEpatents

Martin, Louis P [San Ramon, CA

2012-05-15

A multiple frequency method for the operation of a sensor to measure a parameter of interest using calibration information including the steps of exciting the sensor at a first frequency providing a first sensor response, exciting the sensor at a second frequency providing a second sensor response, using the second sensor response at the second frequency and the calibration information to produce a calculated concentration of the interfering parameters, using the first sensor response at the first frequency, the calculated concentration of the interfering parameters, and the calibration information to measure the parameter of interest.

Dynamic Dependence Analysis : Modeling and Inference of Changing Dependence Among Multiple Time-Series

DTIC Science & Technology

2009-06-01

isolation. In addition to being inherently multi-modal, human perception takes advantages of multiple sources of information within a single modality...restric- tion was reasonable for the applications we looked at. However, consider using a TIM to model a teacher student relationship among moving objects...That is, imagine one teacher object demonstrating a behavior for a student object. The student can observe the teacher and then recreate the behavior

A wireless modular multi-modal multi-node patch platform for robust biosignal monitoring.

PubMed

Pantelopoulos, Alexandros; Saldivar, Enrique; Roham, Masoud

2011-01-01

In this paper a wireless modular, multi-modal, multi-node patch platform is described. The platform comprises low-cost semi-disposable patch design aiming at unobtrusive ambulatory monitoring of multiple physiological parameters. Owing to its modular design it can be interfaced with various low-power RF communication and data storage technologies, while the data fusion of multi-modal and multi-node features facilitates measurement of several biosignals from multiple on-body locations for robust feature extraction. Preliminary results of the patch platform are presented which illustrate the capability to extract respiration rate from three different independent metrics, which combined together can give a more robust estimate of the actual respiratory rate.

Learning Across Senses: Cross-Modal Effects in Multisensory Statistical Learning

PubMed Central

Mitchel, Aaron D.; Weiss, Daniel J.

2014-01-01

It is currently unknown whether statistical learning is supported by modality-general or modality-specific mechanisms. One issue within this debate concerns the independence of learning in one modality from learning in other modalities. In the present study, the authors examined the extent to which statistical learning across modalities is independent by simultaneously presenting learners with auditory and visual streams. After establishing baseline rates of learning for each stream independently, they systematically varied the amount of audiovisual correspondence across 3 experiments. They found that learners were able to segment both streams successfully only when the boundaries of the audio and visual triplets were in alignment. This pattern of results suggests that learners are able to extract multiple statistical regularities across modalities provided that there is some degree of cross-modal coherence. They discuss the implications of their results in light of recent claims that multisensory statistical learning is guided by modality-independent mechanisms. PMID:21574745

A Multiple Sensor Machine Vision System for Automatic Hardwood Feature Detection

Treesearch

D. Earl Kline; Richard W. Conners; Daniel L. Schmoldt; Philip A. Araman; Robert L. Brisbin

1993-01-01

A multiple sensor machine vision prototype is being developed to scan full size hardwood lumber at industrial speeds for automatically detecting features such as knots holes, wane, stain, splits, checks, and color. The prototype integrates a multiple sensor imaging system, a materials handling system, a computer system, and application software. The prototype provides...

A Radar-Enabled Collaborative Sensor Network Integrating COTS Technology for Surveillance and Tracking

PubMed Central

Kozma, Robert; Wang, Lan; Iftekharuddin, Khan; McCracken, Ernest; Khan, Muhammad; Islam, Khandakar; Bhurtel, Sushil R.; Demirer, R. Murat

2012-01-01

The feasibility of using Commercial Off-The-Shelf (COTS) sensor nodes is studied in a distributed network, aiming at dynamic surveillance and tracking of ground targets. Data acquisition by low-cost (<$50 US) miniature low-power radar through a wireless mote is described. We demonstrate the detection, ranging and velocity estimation, classification and tracking capabilities of the mini-radar, and compare results to simulations and manual measurements. Furthermore, we supplement the radar output with other sensor modalities, such as acoustic and vibration sensors. This method provides innovative solutions for detecting, identifying, and tracking vehicles and dismounts over a wide area in noisy conditions. This study presents a step towards distributed intelligent decision support and demonstrates effectiveness of small cheap sensors, which can complement advanced technologies in certain real-life scenarios. PMID:22438713

Dynamic Strain Measurements on Automotive and Aeronautic Composite Components by Means of Embedded Fiber Bragg Grating Sensors.

PubMed

Lamberti, Alfredo; Chiesura, Gabriele; Luyckx, Geert; Degrieck, Joris; Kaufmann, Markus; Vanlanduit, Steve

2015-10-26

The measurement of the internal deformations occurring in real-life composite components is a very challenging task, especially for those components that are rather difficult to access. Optical fiber sensors can overcome such a problem, since they can be embedded in the composite materials and serve as in situ sensors. In this article, embedded optical fiber Bragg grating (FBG) sensors are used to analyze the vibration characteristics of two real-life composite components. The first component is a carbon fiber-reinforced polymer automotive control arm; the second is a glass fiber-reinforced polymer aeronautic hinge arm. The modal parameters of both components were estimated by processing the FBG signals with two interrogation techniques: the maximum detection and fast phase correlation algorithms were employed for the demodulation of the FBG signals; the Peak-Picking and PolyMax techniques were instead used for the parameter estimation. To validate the FBG outcomes, reference measurements were performed by means of a laser Doppler vibrometer. Sensors 2015, 15 27175 The analysis of the results showed that the FBG sensing capabilities were enhanced when the recently-introduced fast phase correlation algorithm was combined with the state-of-the-art PolyMax estimator curve fitting method. In this case, the FBGs provided the most accurate results, i.e. it was possible to fully characterize the vibration behavior of both composite components. When using more traditional interrogation algorithms (maximum detection) and modal parameter estimation techniques (Peak-Picking), some of the modes were not successfully identified.

Experimental strain modal analysis for beam-like structure by using distributed fiber optics and its damage detection

NASA Astrophysics Data System (ADS)

Cheng, Liangliang; Busca, Giorgio; Cigada, Alfredo

2017-07-01

Modal analysis is commonly considered as an effective tool to obtain the intrinsic characteristics of structures including natural frequencies, modal damping ratios, and mode shapes, which are significant indicators for monitoring the health status of engineering structures. The complex mode indicator function (CMIF) can be regarded as an effective numerical tool to perform modal analysis. In this paper, experimental strain modal analysis based on the CMIF has been introduced. Moreover, a distributed fiber-optic sensor, as a dense measuring device, has been applied to acquire strain data along a beam surface. Thanks to the dense spatial resolution of the distributed fiber optics, more detailed mode shapes could be obtained. In order to test the effectiveness of the method, a mass lump—considered as a linear damage component—has been attached to the surface of the beam, and damage detection based on strain mode shape has been carried out. The results manifest that strain modal parameters can be estimated effectively by utilizing the CMIF based on the corresponding simulations and experiments. Furthermore, damage detection based on strain mode shapes benefits from the accuracy of strain mode shape recognition and the excellent performance of the distributed fiber optics.

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.

Modal characterization of the ASCIE segmented optics testbed: New algorithms and experimental results

NASA Technical Reports Server (NTRS)

Carrier, Alain C.; Aubrun, Jean-Noel

1993-01-01

New frequency response measurement procedures, on-line modal tuning techniques, and off-line modal identification algorithms are developed and applied to the modal identification of the Advanced Structures/Controls Integrated Experiment (ASCIE), a generic segmented optics telescope test-bed representative of future complex space structures. The frequency response measurement procedure uses all the actuators simultaneously to excite the structure and all the sensors to measure the structural response so that all the transfer functions are measured simultaneously. Structural responses to sinusoidal excitations are measured and analyzed to calculate spectral responses. The spectral responses in turn are analyzed as the spectral data become available and, which is new, the results are used to maintain high quality measurements. Data acquisition, processing, and checking procedures are fully automated. As the acquisition of the frequency response progresses, an on-line algorithm keeps track of the actuator force distribution that maximizes the structural response to automatically tune to a structural mode when approaching a resonant frequency. This tuning is insensitive to delays, ill-conditioning, and nonproportional damping. Experimental results show that is useful for modal surveys even in high modal density regions. For thorough modeling, a constructive procedure is proposed to identify the dynamics of a complex system from its frequency response with the minimization of a least-squares cost function as a desirable objective. This procedure relies on off-line modal separation algorithms to extract modal information and on least-squares parameter subset optimization to combine the modal results and globally fit the modal parameters to the measured data. The modal separation algorithms resolved modal density of 5 modes/Hz in the ASCIE experiment. They promise to be useful in many challenging applications.

A Simulation Environment for Benchmarking Sensor Fusion-Based Pose Estimators.

PubMed

Ligorio, Gabriele; Sabatini, Angelo Maria

2015-12-19

In-depth analysis and performance evaluation of sensor fusion-based estimators may be critical when performed using real-world sensor data. For this reason, simulation is widely recognized as one of the most powerful tools for algorithm benchmarking. In this paper, we present a simulation framework suitable for assessing the performance of sensor fusion-based pose estimators. The systems used for implementing the framework were magnetic/inertial measurement units (MIMUs) and a camera, although the addition of further sensing modalities is straightforward. Typical nuisance factors were also included for each sensor. The proposed simulation environment was validated using real-life sensor data employed for motion tracking. The higher mismatch between real and simulated sensors was about 5% of the measured quantity (for the camera simulation), whereas a lower correlation was found for an axis of the gyroscope (0.90). In addition, a real benchmarking example of an extended Kalman filter for pose estimation from MIMU and camera data is presented.

Multimodal Sparse Coding for Event Detection

DTIC Science & Technology

2015-10-13

classification tasks based on single modality. We present multimodal sparse coding for learning feature representations shared across multiple modalities...The shared representa- tions are applied to multimedia event detection (MED) and evaluated in compar- ison to unimodal counterparts, as well as other...and video tracks from the same multimedia clip, we can force the two modalities to share a similar sparse representation whose benefit includes robust

Statistical analysis of modal parameters of a suspension bridge based on Bayesian spectral density approach and SHM data

NASA Astrophysics Data System (ADS)

Li, Zhijun; Feng, Maria Q.; Luo, Longxi; Feng, Dongming; Xu, Xiuli

2018-01-01

Uncertainty of modal parameters estimation appear in structural health monitoring (SHM) practice of civil engineering to quite some significant extent due to environmental influences and modeling errors. Reasonable methodologies are needed for processing the uncertainty. Bayesian inference can provide a promising and feasible identification solution for the purpose of SHM. However, there are relatively few researches on the application of Bayesian spectral method in the modal identification using SHM data sets. To extract modal parameters from large data sets collected by SHM system, the Bayesian spectral density algorithm was applied to address the uncertainty of mode extraction from output-only response of a long-span suspension bridge. The posterior most possible values of modal parameters and their uncertainties were estimated through Bayesian inference. A long-term variation and statistical analysis was performed using the sensor data sets collected from the SHM system of the suspension bridge over a one-year period. The t location-scale distribution was shown to be a better candidate function for frequencies of lower modes. On the other hand, the burr distribution provided the best fitting to the higher modes which are sensitive to the temperature. In addition, wind-induced variation of modal parameters was also investigated. It was observed that both the damping ratios and modal forces increased during the period of typhoon excitations. Meanwhile, the modal damping ratios exhibit significant correlation with the spectral intensities of the corresponding modal forces.

Scientific and industrial challenges of developing nanoparticle-based theranostics and multiple-modality contrast agents for clinical application

NASA Astrophysics Data System (ADS)

Wáng, Yì Xiáng J.; Idée, Jean-Marc; Corot, Claire

2015-10-01

Designing of theranostics and dual or multi-modality contrast agents are currently two of the hottest topics in biotechnology and biomaterials science. However, for single entity theranostics, a right ratio of their diagnostic component and their therapeutic component may not always be realized in a composite suitable for clinical application. For dual/multiple modality molecular imaging agents, after in vivo administration, there is an optimal time window for imaging, when an agent is imaged by one modality, the pharmacokinetics of this agent may not allow imaging by another modality. Due to reticuloendothelial system clearance, efficient in vivo delivery of nanoparticles to the lesion site is sometimes difficult. The toxicity of these entities also remains poorly understood. While the medical need of theranostics is admitted, the business model remains to be established. There is an urgent need for a global and internationally harmonized re-evaluation of the approval and marketing processes of theranostics. However, a reasonable expectation exists that, in the near future, the current obstacles will be removed, thus allowing the wide use of these very promising agents.

Using queuing models to aid design and guide research effort for multimodality buried target detection systems

NASA Astrophysics Data System (ADS)

Malof, Jordan M.; Collins, Leslie M.

2016-05-01

Many remote sensing modalities have been developed for buried target detection (BTD), each one offering relative advantages over the others. There has been interest in combining several modalities into a single BTD system that benefits from the advantages of each constituent sensor. Recently an approach was developed, called multi-state management (MSM), that aims to achieve this goal by separating BTD system operation into discrete states, each with different sensor activity and system velocity. Additionally, a modeling approach, called Q-MSM, was developed to quickly analyze multi-modality BTD systems operating with MSM. This work extends previous work by demonstrating how Q-MSM modeling can be used to design BTD systems operating with MSM, and to guide research to yield the most performance benefits. In this work an MSM system is considered that combines a forward-looking infrared (FLIR) camera and a ground penetrating radar (GPR). Experiments are conducted using a dataset of real, field-collected, data which demonstrates how the Q-MSM model can be used to evaluate performance benefits of altering, or improving via research investment, various characteristics of the GPR and FLIR systems. Q-MSM permits fast analysis that can determine where system improvements will have the greatest impact, and can therefore help guide BTD research.

Experiments on vibration control of a piezoelectric laminated paraboloidal shell

NASA Astrophysics Data System (ADS)

Yue, Honghao; Lu, Yifan; Deng, Zongquan; Tzou, Hornsen

2017-01-01

A paraboloidal shell plays a key role in aerospace and optical structural systems applied to large optical reflector, communications antenna, rocket fairing, missile radome, etc. Due to the complexity of analytical procedures, an experimental study of active vibration control of a piezoelectric laminated paraboloidal shell by positive position feedback is carried out. Sixteen PVDF patches are laminated inside and outside of the shell, in which eight of them are used as sensors and eight as actuators to control the vibration of the first two natural modes. Lower natural frequencies and vibration modes of the paraboloidal shell are obtained via the frequency response function analysis by Modal VIEW software. A mathematical model of the control system is formulated by means of parameter identification. The first shell mode is controlled as well as coupled the first and second modes based on the positive position feedback (PPF) algorithm. To minimize the control energy consumption in orbit, an adaptive modal control method is developed in this study by using the PPF in laboratory experiments. The control system collects vibration signals from the piezoelectric sensors to identify location(s) of the largest vibration amplitudes and then select the best two from eight PVDF actuators to apply control forces so that the modal vibration suppression could be accomplished adaptively and effectively.

Modal vector estimation for closely spaced frequency modes

NASA Technical Reports Server (NTRS)

Craig, R. R., Jr.; Chung, Y. T.; Blair, M.

1982-01-01

Techniques for obtaining improved modal vector estimates for systems with closely spaced frequency modes are discussed. In describing the dynamical behavior of a complex structure modal parameters are often analyzed: undamped natural frequency, mode shape, modal mass, modal stiffness and modal damping. From both an analytical standpoint and an experimental standpoint, identification of modal parameters is more difficult if the system has repeated frequencies or even closely spaced frequencies. The more complex the structure, the more likely it is to have closely spaced frequencies. This makes it difficult to determine valid mode shapes using single shaker test methods. By employing band selectable analysis (zoom) techniques and by employing Kennedy-Pancu circle fitting or some multiple degree of freedom (MDOF) curve fit procedure, the usefulness of the single shaker approach can be extended.

Attitude control concepts for precision-pointing nonrigid spacecraft

NASA Technical Reports Server (NTRS)

Likins, P. W.

1974-01-01

Literal criteria are developed for the controllability and observability of general models of flexible spacecraft. Results are interpreted in special cases and in physical terms, permitting in some cases the identification of uncontrollable and unobservable states simply by examination of scalars composed of modal parameters and location matrices for sensors and actuators. A procedure is established for isolation of uncontrollable states, whereby sensor and actuator configurations assure that uncontrollable flexible mode states are also unobservable; in many applications such states can then be removed by coordinate truncation.

High frequency modal identification on noisy high-speed camera data

NASA Astrophysics Data System (ADS)

Javh, Jaka; Slavič, Janko; Boltežar, Miha

2018-01-01

Vibration measurements using optical full-field systems based on high-speed footage are typically heavily burdened by noise, as the displacement amplitudes of the vibrating structures are often very small (in the range of micrometers, depending on the structure). The modal information is troublesome to measure as the structure's response is close to, or below, the noise level of the camera-based measurement system. This paper demonstrates modal parameter identification for such noisy measurements. It is shown that by using the Least-Squares Complex-Frequency method combined with the Least-Squares Frequency-Domain method, identification at high-frequencies is still possible. By additionally incorporating a more precise sensor to identify the eigenvalues, a hybrid accelerometer/high-speed camera mode shape identification is possible even below the noise floor. An accelerometer measurement is used to identify the eigenvalues, while the camera measurement is used to produce the full-field mode shapes close to 10 kHz. The identified modal parameters improve the quality of the measured modal data and serve as a reduced model of the structure's dynamics.

The modular modality frame model: continuous body state estimation and plausibility-weighted information fusion.

PubMed

Ehrenfeld, Stephan; Butz, Martin V

2013-02-01

Humans show admirable capabilities in movement planning and execution. They can perform complex tasks in various contexts, using the available sensory information very effectively. Body models and continuous body state estimations appear necessary to realize such capabilities. We introduce the Modular Modality Frame (MMF) model, which maintains a highly distributed, modularized body model continuously updating, modularized probabilistic body state estimations over time. Modularization is realized with respect to modality frames, that is, sensory modalities in particular frames of reference and with respect to particular body parts. We evaluate MMF performance on a simulated, nine degree of freedom arm in 3D space. The results show that MMF is able to maintain accurate body state estimations despite high sensor and motor noise. Moreover, by comparing the sensory information available in different modality frames, MMF can identify faulty sensory measurements on the fly. In the near future, applications to lightweight robot control should be pursued. Moreover, MMF may be enhanced with neural encodings by introducing neural population codes and learning techniques. Finally, more dexterous goal-directed behavior should be realized by exploiting the available redundant state representations.

Multiple-Sensor Discrimination of Closely-Spaced Objects on a Ballistic Trajectory

DTIC Science & Technology

2015-05-18

Nominal System Architecture ..................................................................................... 8 2 Simulation Environment... architecture ........................................................................................... 8 Figure 2. Simulation environment developed...uncertainty band for one or multiple sensors within the observation architecture . Resolving targets from one sensor image to another can prove difficult

Wireless Prototype Based on Pressure and Bending Sensors for Measuring Gate Quality

PubMed Central

Grenez, Florent; Villarejo, María Viqueira; Zapirain, Begoña García; Zorrilla, Amaia Méndez

2013-01-01

This paper presents a technological solution based on sensors controlled remotely in order to monitor, track and evaluate the gait quality in people with or without associated pathology. Special hardware simulating a shoe was developed, which consists of three pressure sensors, two bending sensors, an Arduino mini and a Bluetooth module. The obtained signals are digitally processed, calculating the standard deviation and establishing thresholds obtained empirically. A group of users was chosen with the aim of executing two modalities: natural walking and dragging the left foot. The gait was parameterized with the following variables: as far as pressure sensors are concerned, one pressure sensor under the first metatarsal (right sensor), another one under the fifth metatarsal (left) and a third one under the heel were placed. With respect to bending sensors, one bending sensor was placed for the ankle movement and another one for the foot sole. The obtained results show a rate accuracy oscillating between 85% (right sensor) and 100% (heel and bending sensors). Therefore, the developed prototype is able to differentiate between healthy gait and pathological gait, and it will be used as the base of a more complex and integral technological solution, which is being developed currently. PMID:23899935

Wireless prototype based on pressure and bending sensors for measuring gait [corrected] quality.

PubMed

Grenez, Florent; Viqueira Villarejo, María; García Zapirain, Begoña; Méndez Zorrilla, Amaia

2013-07-29

This paper presents a technological solution based on sensors controlled remotely in order to monitor, track and evaluate the gait quality in people with or without associated pathology. Special hardware simulating a shoe was developed, which consists of three pressure sensors, two bending sensors, an Arduino mini and a Bluetooth module. The obtained signals are digitally processed, calculating the standard deviation and establishing thresholds obtained empirically. A group of users was chosen with the aim of executing two modalities: natural walking and dragging the left foot. The gait was parameterized with the following variables: as far as pressure sensors are concerned, one pressure sensor under the first metatarsal (right sensor), another one under the fifth metatarsal (left) and a third one under the heel were placed. With respect to bending sensors, one bending sensor was placed for the ankle movement and another one for the foot sole. The obtained results show a rate accuracy oscillating between 85% (right sensor) and 100% (heel and bending sensors). Therefore, the developed prototype is able to differentiate between healthy gait and pathological gait, and it will be used as the base of a more complex and integral technological solution, which is being developed currently.

Structural Finite Element Model Updating Using Vibration Tests and Modal Analysis for NPL footbridge - SHM demonstrator

NASA Astrophysics Data System (ADS)

Barton, E.; Middleton, C.; Koo, K.; Crocker, L.; Brownjohn, J.

2011-07-01

This paper presents the results from collaboration between the National Physical Laboratory (NPL) and the University of Sheffield on an ongoing research project at NPL. A 50 year old reinforced concrete footbridge has been converted to a full scale structural health monitoring (SHM) demonstrator. The structure is monitored using a variety of techniques; however, interrelating results and converting data to knowledge are not possible without a reliable numerical model. During the first stage of the project, the work concentrated on static loading and an FE model of the undamaged bridge was created, and updated, under specified static loading and temperature conditions. This model was found to accurately represent the response under static loading and it was used to identify locations for sensor installation. The next stage involves the evaluation of repair/strengthening patches under both static and dynamic loading. Therefore, before deliberately introducing significant damage, the first set of dynamic tests was conducted and modal properties were estimated. The measured modal properties did not match the modal analysis from the statically updated FE model; it was clear that the existing model required updating. This paper introduces the results of the dynamic testing and model updating. It is shown that the structure exhibits large non-linear, amplitude dependant characteristics. This creates a difficult updating process, but we attempt to produce the best linear representation of the structure. A sensitivity analysis is performed to determine the most sensitive locations for planned damage/repair scenarios and is used to decide whether additional sensors will be necessary.

Multi-Sensor Based State Prediction for Personal Mobility Vehicles

PubMed Central

Gupta, Pankaj; Umata, Ichiro; Watanabe, Atsushi; Even, Jani; Suyama, Takayuki; Ishii, Shin

2016-01-01

This paper presents a study on multi-modal human emotional state detection while riding a powered wheelchair (PMV; Personal Mobility Vehicle) in an indoor labyrinth-like environment. The study reports findings on the habituation of human stress response during self-driving. In addition, the effects of “loss of controllability”, change in the role of the driver to a passenger, are investigated via an autonomous driving modality. The multi-modal emotional state detector sensing framework consists of four sensing devices: electroencephalograph (EEG), heart inter-beat interval (IBI), galvanic skin response (GSR) and stressor level lever (in the case of autonomous riding). Physiological emotional state measurement characteristics are organized by time-scale, in terms of capturing slower changes (long-term) and quicker changes from moment-to-moment. Experimental results with fifteen participants regarding subjective emotional state reports and commercial software measurements validated the proposed emotional state detector. Short-term GSR and heart signal characterizations captured moment-to-moment emotional state during autonomous riding (Spearman correlation; ρ = 0.6, p < 0.001). Short-term GSR and EEG characterizations reliably captured moment-to-moment emotional state during self-driving (Classification accuracy; 69.7). Finally, long-term GSR and heart characterizations were confirmed to reliably capture slow changes during autonomous riding and also of emotional state during participant resting state. The purpose of this study and the exploration of various algorithms and sensors in a structured framework is to provide a comprehensive background for multi-modal emotional state prediction experiments and/or applications. Additional discussion regarding the feasibility and utility of the possibilities of these concepts are given. PMID:27732589

Multi-Sensor Based State Prediction for Personal Mobility Vehicles.

PubMed

Abdur-Rahim, Jamilah; Morales, Yoichi; Gupta, Pankaj; Umata, Ichiro; Watanabe, Atsushi; Even, Jani; Suyama, Takayuki; Ishii, Shin

2016-01-01

This paper presents a study on multi-modal human emotional state detection while riding a powered wheelchair (PMV; Personal Mobility Vehicle) in an indoor labyrinth-like environment. The study reports findings on the habituation of human stress response during self-driving. In addition, the effects of "loss of controllability", change in the role of the driver to a passenger, are investigated via an autonomous driving modality. The multi-modal emotional state detector sensing framework consists of four sensing devices: electroencephalograph (EEG), heart inter-beat interval (IBI), galvanic skin response (GSR) and stressor level lever (in the case of autonomous riding). Physiological emotional state measurement characteristics are organized by time-scale, in terms of capturing slower changes (long-term) and quicker changes from moment-to-moment. Experimental results with fifteen participants regarding subjective emotional state reports and commercial software measurements validated the proposed emotional state detector. Short-term GSR and heart signal characterizations captured moment-to-moment emotional state during autonomous riding (Spearman correlation; ρ = 0.6, p < 0.001). Short-term GSR and EEG characterizations reliably captured moment-to-moment emotional state during self-driving (Classification accuracy; 69.7). Finally, long-term GSR and heart characterizations were confirmed to reliably capture slow changes during autonomous riding and also of emotional state during participant resting state. The purpose of this study and the exploration of various algorithms and sensors in a structured framework is to provide a comprehensive background for multi-modal emotional state prediction experiments and/or applications. Additional discussion regarding the feasibility and utility of the possibilities of these concepts are given.

Modal analysis of a loaded tire with non-contact measurements and piezoelectric excitation

NASA Astrophysics Data System (ADS)

Ferhat, Ipar; Tarazaga, Pablo A.

2017-04-01

The complex nature of tires requires very precise test data to model the structure accurately. The highly damped characteristics, geometric features and operational conditions of tires cause various testing difficulties that affect the reliability of the modal testing. One of the biggest challenges of tire testing is exciting the whole tire at once. Conventionally, impact hammers, shakers, and cleats are used as an excitation input. The shortcomings of these excitation methods are the directional and force inconsistency of hammer impacts, coupled dynamics of shakers and speed limitations of cleat excitation. Other challenges of modal testing of tires are the effect of added mass due to sensor placements and difficulty of vibration measurement of a rotating tire with accelerometers. In order to remedy these problems, we conduct experimental modal analysis (EMA) using a non-contact measurement technique and piezoelectric excitation. For non-contact measurement, a 3-D scanning laser doppler vibrometer (SLDV) is used. For the piezoelectric excitation, Micro Fiber Composite (MFC) patches are used due to their flexible nature and power capacity. This excitation method can also be crucial to the excitation of rotating tires since the cleat excitation is not adequate for low-speed measurements. Furthermore, the piezoelectric actuation could be used as sensors as well as noise controllers in operating conditions. For this work, we run experiments for a loaded tire in non-rotating condition. Experiments are carried out for the frequency bandwidth up to 500Hz to capture the structural behavior under high-frequency excitations and its potential coupled behavior to airborne noise.

A zonal wavefront sensor with multiple detector planes

NASA Astrophysics Data System (ADS)

Pathak, Biswajit; Boruah, Bosanta R.

2018-03-01

A conventional zonal wavefront sensor estimates the wavefront from the data captured in a single detector plane using a single camera. In this paper, we introduce a zonal wavefront sensor which comprises multiple detector planes instead of a single detector plane. The proposed sensor is based on an array of custom designed plane diffraction gratings followed by a single focusing lens. The laser beam whose wavefront is to be estimated is incident on the grating array and one of the diffracted orders from each grating is focused on the detector plane. The setup, by employing a beam splitter arrangement, facilitates focusing of the diffracted beams on multiple detector planes where multiple cameras can be placed. The use of multiple cameras in the sensor can offer several advantages in the wavefront estimation. For instance, the proposed sensor can provide superior inherent centroid detection accuracy that can not be achieved by the conventional system. It can also provide enhanced dynamic range and reduced crosstalk performance. We present here the results from a proof of principle experimental arrangement that demonstrate the advantages of the proposed wavefront sensing scheme.

Unsteady flow sensing and optimal sensor placement using machine learning

NASA Astrophysics Data System (ADS)

Semaan, Richard

2016-11-01

Machine learning is used to estimate the flow state and to determine the optimal sensor placement over a two-dimensional (2D) airfoil equipped with a Coanda actuator. The analysis is based on flow field data obtained from 2D unsteady Reynolds averaged Navier-Stokes (uRANS) simulations with different jet blowing intensities and actuation frequencies, characterizing different flow separation states. This study shows how the "random forests" algorithm is utilized beyond its typical usage in fluid mechanics estimating the flow state to determine the optimal sensor placement. The results are compared against the current de-facto standard of maximum modal amplitude location and against a brute force approach that scans all possible sensor combinations. The results show that it is possible to simultaneously infer the state of flow and to determine the optimal sensor location without the need to perform proper orthogonal decomposition. Collaborative Research Center (CRC) 880, DFG.

All fiber magnetic field sensor with Ferrofluid-filled tapered microstructured optical fiber interferometer.

PubMed

Deng, Ming; Huang, Can; Liu, Danhui; Jin, Wei; Zhu, Tao

2015-08-10

An ultra-compact optical fiber magnetic field sensor based on a microstructured optical fiber (MOF) modal interference and ferrofluid (FF) has been proposed and experimentally demonstrated. The magnetic field sensor was fabricated by splicing a tapered germanium-doped index guided MOF with six big holes injected with FF to two conventional single-mode fibers. The transmission spectra of the proposed sensor under different magnetic field intensities have been measured and theoretically analyzed. Due to an efficient interaction between the magnetic nanoparticles in FF and the excited cladding mode, the magnetic field sensitivity reaches up to117.9pm/mT with a linear range from 0mT to 30mT. Moreover, the fabrication process of the proposed sensor is simple, easy and cost-effective. Therefore, it will be a promising candidate for military, aviation industry, and biomedical applications, especially, for the applications where the space is limited.

Multi-modal sensor system for plant water stress assessment

USDA-ARS?s Scientific Manuscript database

Plant stress critically affects plant growth and causes significant loss of productivity and quality. When the plant is under water stress, it impedes photosynthesis and transpiration, resulting in changes in leaf color and temperature. Leaf discoloration in photosynthesis can be assessed by measu...

Formation Flight of Multiple UAVs via Onboard Sensor Information Sharing.

PubMed

Park, Chulwoo; Cho, Namhoon; Lee, Kyunghyun; Kim, Youdan

2015-07-17

To monitor large areas or simultaneously measure multiple points, multiple unmanned aerial vehicles (UAVs) must be flown in formation. To perform such flights, sensor information generated by each UAV should be shared via communications. Although a variety of studies have focused on the algorithms for formation flight, these studies have mainly demonstrated the performance of formation flight using numerical simulations or ground robots, which do not reflect the dynamic characteristics of UAVs. In this study, an onboard sensor information sharing system and formation flight algorithms for multiple UAVs are proposed. The communication delays of radiofrequency (RF) telemetry are analyzed to enable the implementation of the onboard sensor information sharing system. Using the sensor information sharing, the formation guidance law for multiple UAVs, which includes both a circular and close formation, is designed. The hardware system, which includes avionics and an airframe, is constructed for the proposed multi-UAV platform. A numerical simulation is performed to demonstrate the performance of the formation flight guidance and control system for multiple UAVs. Finally, a flight test is conducted to verify the proposed algorithm for the multi-UAV system.

Formation Flight of Multiple UAVs via Onboard Sensor Information Sharing

PubMed Central

Park, Chulwoo; Cho, Namhoon; Lee, Kyunghyun; Kim, Youdan

2015-01-01

To monitor large areas or simultaneously measure multiple points, multiple unmanned aerial vehicles (UAVs) must be flown in formation. To perform such flights, sensor information generated by each UAV should be shared via communications. Although a variety of studies have focused on the algorithms for formation flight, these studies have mainly demonstrated the performance of formation flight using numerical simulations or ground robots, which do not reflect the dynamic characteristics of UAVs. In this study, an onboard sensor information sharing system and formation flight algorithms for multiple UAVs are proposed. The communication delays of radiofrequency (RF) telemetry are analyzed to enable the implementation of the onboard sensor information sharing system. Using the sensor information sharing, the formation guidance law for multiple UAVs, which includes both a circular and close formation, is designed. The hardware system, which includes avionics and an airframe, is constructed for the proposed multi-UAV platform. A numerical simulation is performed to demonstrate the performance of the formation flight guidance and control system for multiple UAVs. Finally, a flight test is conducted to verify the proposed algorithm for the multi-UAV system. PMID:26193281

Highly sensitive biochemical sensor utilizing Bragg grating in submicron Si/SiO2 waveguides

NASA Astrophysics Data System (ADS)

Tripathi, Saurabh Mani; Kumar, Arun; Meunier, Jean-Pierre; Marin, Emmanuel

2009-05-01

We present a novel highly sensitive biochemical sensor based on a Bragg grating written in the cladding region of a submicron planar Si/SiO2 waveguide. Owing to the high refractive index contrast at the Si/SiO2 boundary the TM modal power is relatively high in low refractive index sensing region, leading to higher sensitivity in this configuration [1]. Waveguide parameters have been optimized to obtain maximum modal power in the sensing region (PSe) and an optimum core width corresponding to maximum sensitivity is found to exist while operating in TM mode configuration, as has been shown in Fig. 1. It has been found that operating in TM mode configuration at optimum core width the structure exhibits extremely high sensitivity, ~ 5×10-6 RIU - 1.35×10-6 RIU for the ambient refractive indices between 1.33 - 1.63. Such high sensitivities are typically attainable for Surface Plasmon Polariton (SPP) based biosensors and is much higher than any non SPP based sensors. Being free from any metallic layer or bulky prism the structure is easy to realize. Owing to its simple structure and small dimensions the proposed sensor can be integrated with planar lightwave circuits and could be used in handy lab-on-a-chip devices. The device may find application in highly sensitive biological/chemical sensing areas in civil and defense sectors where analyzing the samples at the point of need is required rather than sending it to some centralized laboratory.

Dynamic Strain Measurements on Automotive and Aeronautic Composite Components by Means of Embedded Fiber Bragg Grating Sensors

PubMed Central

Lamberti, Alfredo; Chiesura, Gabriele; Luyckx, Geert; Degrieck, Joris; Kaufmann, Markus; Vanlanduit, Steve

2015-01-01

The measurement of the internal deformations occurring in real-life composite components is a very challenging task, especially for those components that are rather difficult to access. Optical fiber sensors can overcome such a problem, since they can be embedded in the composite materials and serve as in situ sensors. In this article, embedded optical fiber Bragg grating (FBG) sensors are used to analyze the vibration characteristics of two real-life composite components. The first component is a carbon fiber-reinforced polymer automotive control arm; the second is a glass fiber-reinforced polymer aeronautic hinge arm. The modal parameters of both components were estimated by processing the FBG signals with two interrogation techniques: the maximum detection and fast phase correlation algorithms were employed for the demodulation of the FBG signals; the Peak-Picking and PolyMax techniques were instead used for the parameter estimation. To validate the FBG outcomes, reference measurements were performed by means of a laser Doppler vibrometer. The analysis of the results showed that the FBG sensing capabilities were enhanced when the recently-introduced fast phase correlation algorithm was combined with the state-of-the-art PolyMax estimator curve fitting method. In this case, the FBGs provided the most accurate results, i.e., it was possible to fully characterize the vibration behavior of both composite components. When using more traditional interrogation algorithms (maximum detection) and modal parameter estimation techniques (Peak-Picking), some of the modes were not successfully identified. PMID:26516854

Study on Finite Element Model Updating in Highway Bridge Static Loading Test Using Spatially-Distributed Optical Fiber Sensors

PubMed Central

Wu, Bitao; Lu, Huaxi; Chen, Bo; Gao, Zhicheng

2017-01-01

A finite model updating method that combines dynamic-static long-gauge strain responses is proposed for highway bridge static loading tests. For this method, the objective function consisting of static long-gauge stains and the first order modal macro-strain parameter (frequency) is established, wherein the local bending stiffness, density and boundary conditions of the structures are selected as the design variables. The relationship between the macro-strain and local element stiffness was studied first. It is revealed that the macro-strain is inversely proportional to the local stiffness covered by the long-gauge strain sensor. This corresponding relation is important for the modification of the local stiffness based on the macro-strain. The local and global parameters can be simultaneously updated. Then, a series of numerical simulation and experiments were conducted to verify the effectiveness of the proposed method. The results show that the static deformation, macro-strain and macro-strain modal can be predicted well by using the proposed updating model. PMID:28753912

Study on Finite Element Model Updating in Highway Bridge Static Loading Test Using Spatially-Distributed Optical Fiber Sensors.

PubMed

Wu, Bitao; Lu, Huaxi; Chen, Bo; Gao, Zhicheng

2017-07-19

A finite model updating method that combines dynamic-static long-gauge strain responses is proposed for highway bridge static loading tests. For this method, the objective function consisting of static long-gauge stains and the first order modal macro-strain parameter (frequency) is established, wherein the local bending stiffness, density and boundary conditions of the structures are selected as the design variables. The relationship between the macro-strain and local element stiffness was studied first. It is revealed that the macro-strain is inversely proportional to the local stiffness covered by the long-gauge strain sensor. This corresponding relation is important for the modification of the local stiffness based on the macro-strain. The local and global parameters can be simultaneously updated. Then, a series of numerical simulation and experiments were conducted to verify the effectiveness of the proposed method. The results show that the static deformation, macro-strain and macro-strain modal can be predicted well by using the proposed updating model.

Hydra multiple head star sensor and its in-flight self-calibration of optical heads alignment

NASA Astrophysics Data System (ADS)

Majewski, L.; Blarre, L.; Perrimon, N.; Kocher, Y.; Martinez, P. E.; Dussy, S.

2017-11-01

HYDRA is EADS SODERN new product line of APS-based autonomous star trackers. The baseline is a multiple head sensor made of three separated optical heads and one electronic unit. Actually the concept which was chosen offers more than three single-head star trackers working independently. Since HYDRA merges all fields of view the result is a more accurate, more robust and completely autonomous multiple-head sensor, releasing the AOCS from the need to manage the outputs of independent single-head star trackers. Specific to the multiple head architecture and the underlying data fusion, is the calibration of the relative alignments between the sensor optical heads. The performance of the sensor is related to its estimation of such alignments. HYDRA design is first reminded in this paper along with simplification it can bring at system level (AOCS). Then self-calibration of optical heads alignment is highlighted through descriptions and simulation results, thus demonstrating the performances of a key part of HYDRA multiple-head concept.

Multimodal Spatial Calibration for Accurately Registering EEG Sensor Positions

PubMed Central

Chen, Shengyong; Xiao, Gang; Li, Xiaoli

2014-01-01

This paper proposes a fast and accurate calibration method to calibrate multiple multimodal sensors using a novel photogrammetry system for fast localization of EEG sensors. The EEG sensors are placed on human head and multimodal sensors are installed around the head to simultaneously obtain all EEG sensor positions. A multiple views' calibration process is implemented to obtain the transformations of multiple views. We first develop an efficient local repair algorithm to improve the depth map, and then a special calibration body is designed. Based on them, accurate and robust calibration results can be achieved. We evaluate the proposed method by corners of a chessboard calibration plate. Experimental results demonstrate that the proposed method can achieve good performance, which can be further applied to EEG source localization applications on human brain. PMID:24803954

Fast Bayesian approach for modal identification using free vibration data, Part I - Most probable value

NASA Astrophysics Data System (ADS)

Zhang, Feng-Liang; Ni, Yan-Chun; Au, Siu-Kui; Lam, Heung-Fai

2016-03-01

The identification of modal properties from field testing of civil engineering structures is becoming economically viable, thanks to the advent of modern sensor and data acquisition technology. Its demand is driven by innovative structural designs and increased performance requirements of dynamic-prone structures that call for a close cross-checking or monitoring of their dynamic properties and responses. Existing instrumentation capabilities and modal identification techniques allow structures to be tested under free vibration, forced vibration (known input) or ambient vibration (unknown broadband loading). These tests can be considered complementary rather than competing as they are based on different modeling assumptions in the identification model and have different implications on costs and benefits. Uncertainty arises naturally in the dynamic testing of structures due to measurement noise, sensor alignment error, modeling error, etc. This is especially relevant in field vibration tests because the test condition in the field environment can hardly be controlled. In this work, a Bayesian statistical approach is developed for modal identification using the free vibration response of structures. A frequency domain formulation is proposed that makes statistical inference based on the Fast Fourier Transform (FFT) of the data in a selected frequency band. This significantly simplifies the identification model because only the modes dominating the frequency band need to be included. It also legitimately ignores the information in the excluded frequency bands that are either irrelevant or difficult to model, thereby significantly reducing modeling error risk. The posterior probability density function (PDF) of the modal parameters is derived rigorously from modeling assumptions and Bayesian probability logic. Computational difficulties associated with calculating the posterior statistics, including the most probable value (MPV) and the posterior covariance matrix, are addressed. Fast computational algorithms for determining the MPV are proposed so that the method can be practically implemented. In the companion paper (Part II), analytical formulae are derived for the posterior covariance matrix so that it can be evaluated without resorting to finite difference method. The proposed method is verified using synthetic data. It is also applied to modal identification of full-scale field structures.

The Accuracy Benefit of Multiple Amperometric Glucose Sensors in People With Type 1 Diabetes

PubMed Central

Castle, Jessica R.; Pitts, Amy; Hanavan, Kathryn; Muhly, Rhonda; El Youssef, Joseph; Hughes-Karvetski, Colleen; Kovatchev, Boris; Ward, W. Kenneth

2012-01-01

OBJECTIVE To improve glucose sensor accuracy in subjects with type 1 diabetes by using multiple sensors and to assess whether the benefit of redundancy is affected by intersensor distance. RESEARCH DESIGN AND METHODS Nineteen adults with type 1 diabetes wore four Dexcom SEVEN PLUS subcutaneous glucose sensors during two 9-h studies. One pair of sensors was worn on each side of the abdomen, with each sensor pair placed at a predetermined distance apart and 20 cm away from the opposite pair. Arterialized venous blood glucose levels were measured every 15 min, and sensor glucose values were recorded every 5 min. Sensors were calibrated once at the beginning of the study. RESULTS The use of four sensors significantly reduced very large errors compared with one sensor (0.4 vs. 2.6% of errors ≥50% from reference glucose, P < 0.001) and also improved overall accuracy (mean absolute relative difference, 11.6 vs. 14.8%, P < 0.001). Using only two sensors also significantly improved very large errors and accuracy. Intersensor distance did not affect the function of sensor pairs. CONCLUSIONS Sensor accuracy is significantly improved with the use of multiple sensors compared with the use of a single sensor. The benefit of redundancy is present even when sensors are positioned very closely together (7 mm). These findings are relevant to the design of an artificial pancreas device. PMID:22357189

The accuracy benefit of multiple amperometric glucose sensors in people with type 1 diabetes.

PubMed

Castle, Jessica R; Pitts, Amy; Hanavan, Kathryn; Muhly, Rhonda; El Youssef, Joseph; Hughes-Karvetski, Colleen; Kovatchev, Boris; Ward, W Kenneth

2012-04-01

To improve glucose sensor accuracy in subjects with type 1 diabetes by using multiple sensors and to assess whether the benefit of redundancy is affected by intersensor distance. Nineteen adults with type 1 diabetes wore four Dexcom SEVEN PLUS subcutaneous glucose sensors during two 9-h studies. One pair of sensors was worn on each side of the abdomen, with each sensor pair placed at a predetermined distance apart and 20 cm away from the opposite pair. Arterialized venous blood glucose levels were measured every 15 min, and sensor glucose values were recorded every 5 min. Sensors were calibrated once at the beginning of the study. The use of four sensors significantly reduced very large errors compared with one sensor (0.4 vs. 2.6% of errors ≥50% from reference glucose, P < 0.001) and also improved overall accuracy (mean absolute relative difference, 11.6 vs. 14.8%, P < 0.001). Using only two sensors also significantly improved very large errors and accuracy. Intersensor distance did not affect the function of sensor pairs. Sensor accuracy is significantly improved with the use of multiple sensors compared with the use of a single sensor. The benefit of redundancy is present even when sensors are positioned very closely together (7 mm). These findings are relevant to the design of an artificial pancreas device.

Close-range sensors for small unmanned bottom vehicles: update

NASA Astrophysics Data System (ADS)

Bernstein, Charles L.

2000-07-01

The Surf Zone Reconnaissance Project is developing sensors for small, autonomous, Underwater Bottom-crawling Vehicles. The objective is to enable small, crawling robots to autonomously detect and classify mines and obstacles on the ocean bottom in depths between 0 and 10 feet. We have identified a promising set of techniques that will exploit the electromagnetic, shape, texture, image, and vibratory- modal features of this images. During FY99 and FY00 we have worked toward refining these techniques. Signature data sets have been collected for a standard target set to facilitate the development of sensor fusion and target detection and classification algorithms. Specific behaviors, termed microbehaviors, are developed to utilize the robot's mobility to position and operate the sensors. A first generation, close-range sensor suite, composed of 5 sensors, will be completed and tested on a crawling platform in FY00, and will be further refined and demonstrated in FY01 as part of the Mine Countermeasures 6.3 core program sponsored by the Office of Naval Research.

Buckling assisted and lithographically micropatterned fully flexible sensors for conformal integration applications

PubMed Central

Maji, Debashis; Das, Debanjan; Wala, Jyoti; Das, Soumen

2015-01-01

Development of flexible sensors/electronics over substrates thicker than 100 μm is of immense importance for its practical feasibility. However, unlike over ultrathin films, large bending stress hinders its flexibility. Here we have employed a novel technique of fabricating sensors over a non-planar ridge topology under pre-stretched condition which not only helps in spontaneous generation of large and uniform parallel buckles upon release, but also acts as stress reduction zones thereby preventing Poisson’s ratio induced lateral cracking. Further, we propose a complete lithography compatible process to realize flexible sensors over pre-stretched substrates thicker than 100 μm that are released through dissolution of a water soluble sacrificial layer of polyvinyl alcohol. These buckling assisted flexible sensors demonstrated superior performance along different flexible modalities. Based on the above concept, we also realized a micro thermal flow sensor, conformally wrapped around angiographic catheters to detect flow abnormalities for potential applications in interventional catheterization process. PMID:26640124

Identification of modal strains using sub-microstrain FBG data and a novel wavelength-shift detection algorithm

NASA Astrophysics Data System (ADS)

Anastasopoulos, Dimitrios; Moretti, Patrizia; Geernaert, Thomas; De Pauw, Ben; Nawrot, Urszula; De Roeck, Guido; Berghmans, Francis; Reynders, Edwin

2017-03-01

The presence of damage in a civil structure alters its stiffness and consequently its modal characteristics. The identification of these changes can provide engineers with useful information about the condition of a structure and constitutes the basic principle of the vibration-based structural health monitoring. While eigenfrequencies and mode shapes are the most commonly monitored modal characteristics, their sensitivity to structural damage may be low relative to their sensitivity to environmental influences. Modal strains or curvatures could offer an attractive alternative but current measurement techniques encounter difficulties in capturing the very small strain (sub-microstrain) levels occurring during ambient, or operational excitation, with sufficient accuracy. This paper investigates the ability to obtain sub-microstrain accuracy with standard fiber-optic Bragg gratings using a novel optical signal processing algorithm that identifies the wavelength shift with high accuracy and precision. The novel technique is validated in an extensive experimental modal analysis test on a steel I-beam which is instrumented with FBG sensors at its top and bottom flange. The raw wavelength FBG data are processed into strain values using both a novel correlation-based processing technique and a conventional peak tracking technique. Subsequently, the strain time series are used for identifying the beam's modal characteristics. Finally, the accuracy of both algorithms in identification of modal characteristics is extensively investigated.

Neuromorphic vision sensors and preprocessors in system applications

NASA Astrophysics Data System (ADS)

Kramer, Joerg; Indiveri, Giacomo

1998-09-01

A partial review of neuromorphic vision sensors that are suitable for use in autonomous systems is presented. Interfaces are being developed to multiplex the high- dimensional output signals of arrays of such sensors and to communicate them in standard formats to off-chip devices for higher-level processing, actuation, storage and display. Alternatively, on-chip processing stages may be implemented to extract sparse image parameters, thereby obviating the need for multiplexing. Autonomous robots are used to test neuromorphic vision chips in real-world environments and to explore the possibilities of data fusion from different sensing modalities. Examples of autonomous mobile systems that use neuromorphic vision chips for line tracking and optical flow matching are described.

Evaluating the performance of distributed approaches for modal identification

NASA Astrophysics Data System (ADS)

Krishnan, Sriram S.; Sun, Zhuoxiong; Irfanoglu, Ayhan; Dyke, Shirley J.; Yan, Guirong

2011-04-01

In this paper two modal identification approaches appropriate for use in a distributed computing environment are applied to a full-scale, complex structure. The natural excitation technique (NExT) is used in conjunction with a condensed eigensystem realization algorithm (ERA), and the frequency domain decomposition with peak-picking (FDD-PP) are both applied to sensor data acquired from a 57.5-ft, 10 bay highway sign truss structure. Monte-Carlo simulations are performed on a numerical example to investigate the statistical properties and sensitivity to noise of the two distributed algorithms. Experimental results are provided and discussed.

A Large-Scale Study of Fingerprint Matching Systems for Sensor Interoperability Problem

PubMed Central

Hussain, Muhammad; AboAlSamh, Hatim; AlZuair, Mansour

2018-01-01

The fingerprint is a commonly used biometric modality that is widely employed for authentication by law enforcement agencies and commercial applications. The designs of existing fingerprint matching methods are based on the hypothesis that the same sensor is used to capture fingerprints during enrollment and verification. Advances in fingerprint sensor technology have raised the question about the usability of current methods when different sensors are employed for enrollment and verification; this is a fingerprint sensor interoperability problem. To provide insight into this problem and assess the status of state-of-the-art matching methods to tackle this problem, we first analyze the characteristics of fingerprints captured with different sensors, which makes cross-sensor matching a challenging problem. We demonstrate the importance of fingerprint enhancement methods for cross-sensor matching. Finally, we conduct a comparative study of state-of-the-art fingerprint recognition methods and provide insight into their abilities to address this problem. We performed experiments using a public database (FingerPass) that contains nine datasets captured with different sensors. We analyzed the effects of different sensors and found that cross-sensor matching performance deteriorates when different sensors are used for enrollment and verification. In view of our analysis, we propose future research directions for this problem. PMID:29597286

A Large-Scale Study of Fingerprint Matching Systems for Sensor Interoperability Problem.

PubMed

AlShehri, Helala; Hussain, Muhammad; AboAlSamh, Hatim; AlZuair, Mansour

2018-03-28

The fingerprint is a commonly used biometric modality that is widely employed for authentication by law enforcement agencies and commercial applications. The designs of existing fingerprint matching methods are based on the hypothesis that the same sensor is used to capture fingerprints during enrollment and verification. Advances in fingerprint sensor technology have raised the question about the usability of current methods when different sensors are employed for enrollment and verification; this is a fingerprint sensor interoperability problem. To provide insight into this problem and assess the status of state-of-the-art matching methods to tackle this problem, we first analyze the characteristics of fingerprints captured with different sensors, which makes cross-sensor matching a challenging problem. We demonstrate the importance of fingerprint enhancement methods for cross-sensor matching. Finally, we conduct a comparative study of state-of-the-art fingerprint recognition methods and provide insight into their abilities to address this problem. We performed experiments using a public database (FingerPass) that contains nine datasets captured with different sensors. We analyzed the effects of different sensors and found that cross-sensor matching performance deteriorates when different sensors are used for enrollment and verification. In view of our analysis, we propose future research directions for this problem.

Li-ion battery thermal runaway suppression system using microchannel coolers and refrigerant injections

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

Bandhauer, Todd M.; Farmer, Joseph C.

A battery management system with thermally integrated fire suppression includes a multiplicity of individual battery cells in a housing; a multiplicity of cooling passages in the housing within or between the multiplicity of individual battery cells; a multiplicity of sensors operably connected to the individual battery cells, the sensors adapted to detect a thermal runaway event related to one or more of the multiplicity of individual battery cells; and a management system adapted to inject coolant into at least one of the multiplicity of cooling passages upon the detection of the thermal runaway event by the any one of themore » multiplicity of sensors, so that the thermal runaway event is rapidly quenched.« less

Energy storage management system with distributed wireless sensors

DOEpatents

Farmer, Joseph C.; Bandhauer, Todd M.

2015-12-08

An energy storage system having a multiple different types of energy storage and conversion devices. Each device is equipped with one or more sensors and RFID tags to communicate sensor information wirelessly to a central electronic management system, which is used to control the operation of each device. Each device can have multiple RFID tags and sensor types. Several energy storage and conversion devices can be combined.

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

PubMed

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

2013-10-02

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

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

PubMed Central

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

2013-01-01

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

Biological Parametric Mapping: A Statistical Toolbox for Multi-Modality Brain Image Analysis

PubMed Central

Casanova, Ramon; Ryali, Srikanth; Baer, Aaron; Laurienti, Paul J.; Burdette, Jonathan H.; Hayasaka, Satoru; Flowers, Lynn; Wood, Frank; Maldjian, Joseph A.

2006-01-01

In recent years multiple brain MR imaging modalities have emerged; however, analysis methodologies have mainly remained modality specific. In addition, when comparing across imaging modalities, most researchers have been forced to rely on simple region-of-interest type analyses, which do not allow the voxel-by-voxel comparisons necessary to answer more sophisticated neuroscience questions. To overcome these limitations, we developed a toolbox for multimodal image analysis called biological parametric mapping (BPM), based on a voxel-wise use of the general linear model. The BPM toolbox incorporates information obtained from other modalities as regressors in a voxel-wise analysis, thereby permitting investigation of more sophisticated hypotheses. The BPM toolbox has been developed in MATLAB with a user friendly interface for performing analyses, including voxel-wise multimodal correlation, ANCOVA, and multiple regression. It has a high degree of integration with the SPM (statistical parametric mapping) software relying on it for visualization and statistical inference. Furthermore, statistical inference for a correlation field, rather than a widely-used T-field, has been implemented in the correlation analysis for more accurate results. An example with in-vivo data is presented demonstrating the potential of the BPM methodology as a tool for multimodal image analysis. PMID:17070709

TREFEX: Trend Estimation and Change Detection in the Response of MOX Gas Sensors

PubMed Central

Pashami, Sepideh; Lilienthal, Achim J.; Schaffernicht, Erik; Trincavelli, Marco

2013-01-01

Many applications of metal oxide gas sensors can benefit from reliable algorithms to detect significant changes in the sensor response. Significant changes indicate a change in the emission modality of a distant gas source and occur due to a sudden change of concentration or exposure to a different compound. As a consequence of turbulent gas transport and the relatively slow response and recovery times of metal oxide sensors, their response in open sampling configuration exhibits strong fluctuations that interfere with the changes of interest. In this paper we introduce TREFEX, a novel change point detection algorithm, especially designed for metal oxide gas sensors in an open sampling system. TREFEX models the response of MOX sensors as a piecewise exponential signal and considers the junctions between consecutive exponentials as change points. We formulate non-linear trend filtering and change point detection as a parameter-free convex optimization problem for single sensors and sensor arrays. We evaluate the performance of the TREFEX algorithm experimentally for different metal oxide sensors and several gas emission profiles. A comparison with the previously proposed GLR method shows a clearly superior performance of the TREFEX algorithm both in detection performance and in estimating the change time. PMID:23736853

Force Sensing Resistor (FSR): a brief overview and the low-cost sensor for active compliance control

NASA Astrophysics Data System (ADS)

Sadun, A. S.; Jalani, J.; Sukor, J. A.

2016-07-01

Force Sensing Resistors (FSR) sensors are devices that allow measuring static and dynamic forces applied to a contact surface. Their range of responses is basically depending on the variation of its electric resistance. In general, Flexiforce and Interlink are two common types of FSR sensors that are available, cheap and easily found in the market. Studies have shown that the FSR sensors are usually applied for robotic grippers and for biomechanical fields. This paper provides a brief overview of the application of the FSR sensors. Subsequently, two different set of experiments are carried out to test the effectiveness of the Flexiforce and Interlink sensors. First, the hardness detector system (Case Study A) and second, the force-position control system (Case Study B). The hardware used for the experiment was developed from low-cost materials. The results revealed that both FSR sensors are sufficient and reliable to provide a good sensing modality particularly for measuring force. Apart from the low-cost sensors, essentially, the FSR sensors are very useful devices that able to provide a good active compliance control, particularly for the grasping robotic hand.

Sensor-augmented pump therapy lowers HbA(1c) in suboptimally controlled Type 1 diabetes; a randomized controlled trial.

PubMed

Hermanides, J; Nørgaard, K; Bruttomesso, D; Mathieu, C; Frid, A; Dayan, C M; Diem, P; Fermon, C; Wentholt, I M E; Hoekstra, J B L; DeVries, J H

2011-10-01

To investigate the efficacy of sensor-augmented pump therapy vs. multiple daily injection therapy in patients with suboptimally controlled Type 1 diabetes. In this investigator-initiated multi-centre trial (the Eurythmics Trial) in eight outpatient centres in Europe, we randomized 83 patients with Type 1 diabetes (40 women) currently treated with multiple daily injections, age 18-65 years and HbA(1c) ≥ 8.2% (≥ 66 mmol/mol) to 26 weeks of treatment with either a sensor-augmented insulin pump (n = 44) (Paradigm(®) REAL-Time) or continued with multiple daily injections (n = 39). Change in HbA(1c) between baseline and 26 weeks, sensor-derived endpoints and patient-reported outcomes were assessed. The trial was completed by 43/44 (98%) patients in the sensor-augmented insulin pump group and 35/39 (90%) patients in the multiple daily injections group. Mean HbA(1c) at baseline and at 26 weeks changed from 8.46% (SD 0.95) (69 mmol/mol) to 7.23% (SD 0.65) (56 mmol/mol) in the sensor-augmented insulin pump group and from 8.59% (SD 0.82) (70 mmol/mol) to 8.46% (SD 1.04) (69 mmol/mol) in the multiple daily injections group. Mean difference in change in HbA(1c) after 26 weeks was -1.21% (95% confidence interval -1.52 to -0.90, P < 0.001) in favour of the sensor-augmented insulin pump group. This was achieved without an increase in percentage of time spent in hypoglycaemia: between-group difference 0.0% (95% confidence interval -1.6 to 1.7, P = 0.96). There were four episodes of severe hypoglycaemia in the sensor-augmented insulin pump group and one episode in the multiple daily injections group (P = 0.21). Problem Areas in Diabetes and Diabetes Treatment Satisfaction Questionnaire scores improved in the sensor-augmented insulin pump group. Sensor augmented pump therapy effectively lowers HbA(1c) in patients with Type 1 diabetes suboptimally controlled with multiple daily injections. © 2011 The Authors. Diabetic Medicine © 2011 Diabetes UK.

Sensor fusion V; Proceedings of the Meeting, Boston, MA, Nov. 15-17, 1992

NASA Technical Reports Server (NTRS)

Schenker, Paul S. (Editor)

1992-01-01

Topics addressed include 3D object perception, human-machine interface in multisensor systems, sensor fusion architecture, fusion of multiple and distributed sensors, interface and decision models for sensor fusion, computational networks, simple sensing for complex action, multisensor-based control, and metrology and calibration of multisensor systems. Particular attention is given to controlling 3D objects by sketching 2D views, the graphical simulation and animation environment for flexible structure robots, designing robotic systems from sensorimotor modules, cylindrical object reconstruction from a sequence of images, an accurate estimation of surface properties by integrating information using Bayesian networks, an adaptive fusion model for a distributed detection system, multiple concurrent object descriptions in support of autonomous navigation, robot control with multiple sensors and heuristic knowledge, and optical array detectors for image sensors calibration. (No individual items are abstracted in this volume)

Intrinsic embedded sensors for polymeric mechatronics: flexure and force sensing.

PubMed

Jentoft, Leif P; Dollar, Aaron M; Wagner, Christopher R; Howe, Robert D

2014-02-25

While polymeric fabrication processes, including recent advances in additive manufacturing, have revolutionized manufacturing, little work has been done on effective sensing elements compatible with and embedded within polymeric structures. In this paper, we describe the development and evaluation of two important sensing modalities for embedding in polymeric mechatronic and robotic mechanisms: multi-axis flexure joint angle sensing utilizing IR phototransistors, and a small (12 mm), three-axis force sensing via embedded silicon strain gages with similar performance characteristics as an equally sized metal element based sensor.

Intrinsic Embedded Sensors for Polymeric Mechatronics: Flexure and Force Sensing

PubMed Central

Jentoft, Leif P.; Dollar, Aaron M.; Wagner, Christopher R.; Howe, Robert D.

2014-01-01

While polymeric fabrication processes, including recent advances in additive manufacturing, have revolutionized manufacturing, little work has been done on effective sensing elements compatible with and embedded within polymeric structures. In this paper, we describe the development and evaluation of two important sensing modalities for embedding in polymeric mechatronic and robotic mechanisms: multi-axis flexure joint angle sensing utilizing IR phototransistors, and a small (12 mm), three-axis force sensing via embedded silicon strain gages with similar performance characteristics as an equally sized metal element based sensor. PMID:24573310

Experimental investigation of an inversion technique for the determination of broadband duct mode amplitudes by the use of near-field sensor arrays.

PubMed

Castres, Fabrice O; Joseph, Phillip F

2007-08-01

This paper is an experimental investigation of an inverse technique for deducing the amplitudes of the modes radiated from a turbofan engine, including schemes for stablizing the solution. The detection of broadband modes generated by a laboratory-scaled fan inlet is performed using a near-field array of microphones arranged in a geodesic geometry. This array geometry is shown to allow a robust and accurate modal inversion. The sound power radiated from the fan inlet and the coherence function between different modal amplitudes are also presented. The knowledge of such modal content is useful in helping to characterize the source mechanisms of fan broadband noise generation, for determining the most appropriate mode distribution model for duct liner predictions, and for making sound power measurements of the radiated sound field.

Application of DIRI dynamic infrared imaging in reconstructive surgery

NASA Astrophysics Data System (ADS)

Pawlowski, Marek; Wang, Chengpu; Jin, Feng; Salvitti, Matthew; Tenorio, Xavier

2006-04-01

We have developed the BioScanIR System based on QWIP (Quantum Well Infrared Photodetector). Data collected by this sensor are processed using the DIRI (Dynamic Infrared Imaging) algorithms. The combination of DIRI data processing methods with the unique characteristics of the QWIP sensor permit the creation of a new imaging modality capable of detecting minute changes in temperature at the surface of the tissue and organs associated with blood perfusion due to certain diseases such as cancer, vascular disease and diabetes. The BioScanIR System has been successfully applied in reconstructive surgery to localize donor flap feeding vessels (perforators) during the pre-surgical planning stage. The device is also used in post-surgical monitoring of skin flap perfusion. Since the BioScanIR is mobile; it can be moved to the bedside for such monitoring. In comparison to other modalities, the BioScanIR can localize perforators in a single, 20 seconds scan with definitive results available in minutes. The algorithms used include (FFT) Fast Fourier Transformation, motion artifact correction, spectral analysis and thermal image scaling. The BioScanIR is completely non-invasive and non-toxic, requires no exogenous contrast agents and is free of ionizing radiation. In addition to reconstructive surgery applications, the BioScanIR has shown promise as a useful functional imaging modality in neurosurgery, drug discovery in pre-clinical animal models, wound healing and peripheral vascular disease management.

REKRIATE: A Knowledge Representation System for Object Recognition and Scene Interpretation

NASA Astrophysics Data System (ADS)

Meystel, Alexander M.; Bhasin, Sanjay; Chen, X.

1990-02-01

What humans actually observe and how they comprehend this information is complex due to Gestalt processes and interaction of context in predicting the course of thinking and enforcing one idea while repressing another. How we extract the knowledge from the scene, what we get from the scene indeed and what we bring from our mechanisms of perception are areas separated by a thin, ill-defined line. The purpose of this paper is to present a system for Representing Knowledge and Recognizing and Interpreting Attention Trailed Entities dubbed as REKRIATE. It will be used as a tool for discovering the underlying principles involved in knowledge representation required for conceptual learning. REKRIATE has some inherited knowledge and is given a vocabulary which is used to form rules for identification of the object. It has various modalities of sensing and has the ability to measure the distance between the objects in the image as well as the similarity between different images of presumably the same object. All sensations received from matrix of different sensors put into an adequate form. The methodology proposed is applicable to not only the pictorial or visual world representation, but to any sensing modality. It is based upon the two premises: a) inseparability of all domains of the world representation including linguistic, as well as those formed by various sensor modalities. and b) representativity of the object at several levels of resolution simultaneously.

A frequency domain global parameter estimation method for multiple reference frequency response measurements

NASA Astrophysics Data System (ADS)

Shih, C. Y.; Tsuei, Y. G.; Allemang, R. J.; Brown, D. L.

1988-10-01

A method of using the matrix Auto-Regressive Moving Average (ARMA) model in the Laplace domain for multiple-reference global parameter identification is presented. This method is particularly applicable to the area of modal analysis where high modal density exists. The method is also applicable when multiple reference frequency response functions are used to characterise linear systems. In order to facilitate the mathematical solution, the Forsythe orthogonal polynomial is used to reduce the ill-conditioning of the formulated equations and to decouple the normal matrix into two reduced matrix blocks. A Complex Mode Indicator Function (CMIF) is introduced, which can be used to determine the proper order of the rational polynomials.

Single Mode Air-Clad Single Crystal Sapphire Optical Fiber

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

Hill, Cary; Homa, Dan; Yu, Zhihao

The observation of single mode propagation in an air-clad single crystal sapphire optical fiber at wavelengths at and above 783 nm is presented for the first time. A high-temperature wet acid etching method was used to reduce the diameter of a 10 cm length of commercially-sourced sapphire fiber from 125 micrometers to 6.5 micrometers, and far-field imaging provided modal information at intervals as the fiber diameter decreased. Modal volume was shown to decrease with decreasing diameter, and single mode behavior was observed at the minimum diameter achieved. While weakly-guiding approximations are generally inaccurate for low modal volume optical fiber withmore » high core-cladding refractive index disparity, consistency between these approximations and experimental results was observed when the effective numerical aperture was measured and substituted for the theoretical numerical aperture in weakly-guiding approximation calculations. With the demonstration of very low modal volume in sapphire at fiber diameters much larger than anticipated by legacy calculations, the resolution of sapphire fiber distributed sensors may be increased and other sensing schemes requiring very low modal volume, such as fiber Bragg gratings, may be realized in extreme environment applications.« less

Single Mode Air-Clad Single Crystal Sapphire Optical Fiber

DOE PAGES

Hill, Cary; Homa, Dan; Yu, Zhihao; ...

2017-05-03

The observation of single mode propagation in an air-clad single crystal sapphire optical fiber at wavelengths at and above 783 nm is presented for the first time. A high-temperature wet acid etching method was used to reduce the diameter of a 10 cm length of commercially-sourced sapphire fiber from 125 micrometers to 6.5 micrometers, and far-field imaging provided modal information at intervals as the fiber diameter decreased. Modal volume was shown to decrease with decreasing diameter, and single mode behavior was observed at the minimum diameter achieved. While weakly-guiding approximations are generally inaccurate for low modal volume optical fiber withmore » high core-cladding refractive index disparity, consistency between these approximations and experimental results was observed when the effective numerical aperture was measured and substituted for the theoretical numerical aperture in weakly-guiding approximation calculations. With the demonstration of very low modal volume in sapphire at fiber diameters much larger than anticipated by legacy calculations, the resolution of sapphire fiber distributed sensors may be increased and other sensing schemes requiring very low modal volume, such as fiber Bragg gratings, may be realized in extreme environment applications.« less

The sensory substrate of multimodal communication in brown-headed cowbirds: are females sensory 'specialists' or 'generalists'?

PubMed

Ronald, Kelly L; Sesterhenn, Timothy M; Fernandez-Juricic, Esteban; Lucas, Jeffrey R

2017-11-01

Many animals communicate with multimodal signals. While we have an understanding of multimodal signal production, we know relatively less about receiver filtering of multimodal signals and whether filtering capacity in one modality influences filtering in a second modality. Most multimodal signals contain a temporal element, such as change in frequency over time or a dynamic visual display. We examined the relationship in temporal resolution across two modalities to test whether females are (1) sensory 'specialists', where a trade-off exists between the sensory modalities, (2) sensory 'generalists', where a positive relationship exists between the modalities, or (3) whether no relationship exists between modalities. We used female brown-headed cowbirds (Molothrus ater) to investigate this question as males court females with an audiovisual display. We found a significant positive relationship between female visual and auditory temporal resolution, suggesting that females are sensory 'generalists'. Females appear to resolve information well across multiple modalities, which may select for males that signal their quality similarly across modalities.

Deflation-activated receptors, not classical inflation-activated receptors, mediate the Hering-Breuer deflation reflex.

PubMed

Yu, Jerry

2016-11-01

Many airway sensory units respond to both lung inflation and deflation. Whether those responses to opposite stimuli come from one sensor (one-sensor theory) or more than one sensor (multiple-sensor theory) is debatable. One-sensor theory is commonly presumed in the literature. This article proposes a multiple-sensor theory in which a sensory unit contains different sensors for sensing different forces. Two major types of mechanical sensors operate in the lung: inflation- and deflation-activated receptors (DARs). Inflation-activated sensors can be further divided into slowly adapting receptors (SARs) and rapidly adapting receptors (RARs). Many SAR and RAR units also respond to lung deflation because they contain DARs. Pure DARs, which respond to lung deflation only, are rare in large animals but are easily identified in small animals. Lung deflation-induced reflex effects previously attributed to RARs should be assigned to DARs (including pure DARs and DARs associated with SARs and RARs) if the multiple-sensor theory is accepted. Thus, based on the information, it is proposed that activation of DARs can attenuate lung deflation, shorten expiratory time, increase respiratory rate, evoke inspiration, and cause airway secretion and dyspnea.

SafeSlinger: An Easy-to-use and Secure Approach for Human Trust Establishment

DTIC Science & Technology

2012-03-12

communication modalities (Bluetooth, WiFi , 4G), camera, and sensors. Unfortunately, smartphone platforms suffer from many risks. Vulnerabilities exist in...December 2010. [31] Dave Neal. Defcon hackers get hacked over 4G. http://www.theinquirer.net/inquirer/news/ 16 2100989/defcon-hackers- hacked -4g

Modal content based damage indicators and phased array transducers for structural health monitoring of aircraft structures using ultrasonic guided waves

NASA Astrophysics Data System (ADS)

Ren, Baiyang

Composite materials, especially carbon fiber reinforced polymers (CFRP), have been widely used in the aircraft industry because of their high specific strength and stiffness, resistance to corrosion and good fatigue life. Due to their highly anisotropic material properties and laminated structures, joining methods like bolting and riveting are no longer appropriate for joining CFRP since they initiate defects during the assembly and severely compromise the integrity of the structure; thus new techniques for joining CFRP are highly demanded. Adhesive bonding is a promising method because it relieves stress concentration, reduces weight and provides smooth surfaces. Additionally, it is a low-cost alternative to the co-cured method which is currently used to manufacture components of aircraft fuselage. Adhesive defects, disbonds at the interface between adherend and adhesive layer, are focused on in this thesis because they can be initialized by either poor surface preparation during the manufacturing or fatigue loads during service. Aircraft need structural health monitoring (SHM) systems to increase safety and reduce loss, and adhesive bonds usually represent the hotspots of the assembled structure. There are many nondestructive evaluation (NDE) methods for bond inspection. However, these methods cannot be readily integrated into an SHM system because of the bulk size and weight of the equipment and requirement of accessibility to one side of the bonded joint. The first objective of this work is to develop instruments, actuators, sensors and a data acquisition system for SHM of bond lines using ultrasonic guided waves which are well known to be able to cover large volume of the structure and inaccessible regions. Different from widely used guided wave sensors like PZT disks, the new actuators, piezoelectric fiber composite (PFC) phased array transducers0 (PAT), can control the modal content of the excited waves and the new sensors, polyvinylidene fluoride (PVDF) arrays, which can extract modal information from the received waves. Also, the PATs and array sensors have broad frequency bandwidth and can easily excite and receive high order guided wave modes which are not possible using PZT disks. Currently, many guided wave SHM techniques employ the fundamental guided wave modes below the first cut-off frequency because of their low dispersion in this frequency range. Such a practice ignores the possibility of using higher order modes which sometimes have much better sensitivity to defects. A frequency domain finite element model is created in this work to study the behavior of the interaction between guided waves and a disbond. The sensitivities of modes are classified into three levels, namely, good sensitivity, intermediate sensitivity and no sensitivity. The novel damage indicators, wave modal amplitude and wave modal composition, are proposed to increase the sensitivity to disbonds. The effects of environmental operational conditions (EOC) are presenting great challenges to reliable SHM practice because they may influence the wave amplitude and time of flight. The use of fundamental modes shows poor sensitivity to the disbond; but the use of higher order modes shows good sensitivity. The experiments demonstrate that the new damage indicators have excellent sensitivity to disbonds even with elevated temperatures and have the capability to characterize the size of a disbond. Additionally, the detection of other types of defects like notches on aluminum plates and disbonds in adhesively bonded aluminum plate are also demonstrated using the proposed damage indicators. The use of the new damage indicators for SHM applications relies on the capability of resolving the modal content of wave signals which is enabled only by using PFC PATs and polyvinylidene fluoride (PVDF) array sensors.

Design and test of three active flutter suppression controllers

NASA Technical Reports Server (NTRS)

Christhilf, David M.; Waszak, Martin R.; Adams, William M.; Srinathkumar, S.; Mukhopadhyay, Vivek

1991-01-01

Three flutter suppression control law design techniques are presented. Each uses multiple control surfaces and/or sensors. The first uses linear combinations of several accelerometer signals together with dynamic compensation to synthesize the modal rate of the critical mode for feedback to distributed control surfaces. The second uses traditional tools (pole/zero loci and Nyquist diagrams) to develop a good understanding of the flutter mechanism and produce a controller with minimal complexity and good robustness to plant uncertainty. The third starts with a minimum energy Linear Quadratic Gaussian controller, applies controller order reduction, and then modifies weight and noise covariance matrices to improve multi-variable robustness. The resulting designs were implemented digitally and tested subsonically on the Active Flexible Wing (AFW) wind tunnel model. Test results presented here include plant characteristics, maximum attained closed-loop dynamic pressure, and Root Mean Square control surface activity. A key result is that simultaneous symmetric and antisymmetric flutter suppression was achieved by the second control law, with a 24 percent increase in attainable dynamic pressure.

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

Samanta, C.; Yasasvi Gangavarapu, P. R.; Naik, A. K.

Atomically thin two dimensional (2D) layered materials have emerged as a new class of material for nanoelectromechanical systems (NEMS) due to their extraordinary mechanical properties and ultralow mass density. Among them, graphene has been the material of choice for nanomechanical resonator. However, recent interest in 2D chalcogenide compounds has also spurred research in using materials such as MoS{sub 2} for the NEMS applications. As the dimensions of devices fabricated using these materials shrink down to atomically thin membrane, strain and nonlinear effects have become important. A clear understanding of the nonlinear effects and the ability to manipulate them is essentialmore » for next generation sensors. Here, we report on all electrical actuation and detection of few-layer MoS{sub 2} resonator. The ability to electrically detect multiple modes and actuate the modes deep into the nonlinear regime enables us to probe the nonlinear coupling between various vibrational modes. The modal coupling in our device is strong enough to detect three distinct internal resonances.« less

A Survey of Recent Advances in Particle Filters and Remaining Challenges for Multitarget Tracking

PubMed Central

Wang, Xuedong; Sun, Shudong; Corchado, Juan M.

2017-01-01

We review some advances of the particle filtering (PF) algorithm that have been achieved in the last decade in the context of target tracking, with regard to either a single target or multiple targets in the presence of false or missing data. The first part of our review is on remarkable achievements that have been made for the single-target PF from several aspects including importance proposal, computing efficiency, particle degeneracy/impoverishment and constrained/multi-modal systems. The second part of our review is on analyzing the intractable challenges raised within the general multitarget (multi-sensor) tracking due to random target birth and termination, false alarm, misdetection, measurement-to-track (M2T) uncertainty and track uncertainty. The mainstream multitarget PF approaches consist of two main classes, one based on M2T association approaches and the other not such as the finite set statistics-based PF. In either case, significant challenges remain due to unknown tracking scenarios and integrated tracking management. PMID:29168772

Specific roles for DEG/ENaC and TRP channels in touch and thermosensation in C. elegans nociceptors

PubMed Central

Chatzigeorgiou, Marios; Yoo, Sungjae; Watson, Joseph D.; Lee, Wei-Hsiang; Spencer, W. Clay; Kindt, Katie S.; Hwang, Sun Wook; Miller, David M.; Treinin, Millet; Driscoll, Monica; Schafer, William R.

2010-01-01

Summary Polymodal nociceptors detect noxious stimuli including harsh touch, toxic chemicals, and extremes of heat and cold. The molecular mechanisms by which nociceptors are able to sense multiple qualitatively distinct stimuli are not well-understood. We show here that the C. elegans PVD neurons are mulitidendritic nociceptors that respond to harsh touch as well as cold temperatures. The harsh touch modality specifically requires the DEG/ENaC proteins MEC-10 and DEGT-1, which represent putative components of a harsh touch mechanotransduction complex. By contrast, responses to cold require the TRPA-1 channel and are MEC-10- and DEGT-1-independent. Heterologous expression of C. elegans TRPA-1 can confer cold responsiveness to other C. elegans neurons or to mammalian cells, indicating that TRPA-1 is itself a cold sensor. These results show that C. elegans nociceptors respond to thermal and mechanical stimuli using distinct sets of molecules, and identify DEG/ENaC channels as potential receptors for mechanical pain. PMID:20512132

Dynamics modeling and periodic control of horizontal-axis wind turbines

NASA Astrophysics Data System (ADS)

Stol, Karl Alexander

2001-07-01

The development of large multi-megawatt wind turbines has increased the need for active feedback control to meet multiple performance objectives. Power regulation is still of prime concern but there is an increasing interest in mitigating loads for these very large, dynamically soft and highly integrated power systems. This work explores the opportunities for utilizing state space modeling, modal analysis, and multi-objective controllers in advanced horizontal-axis wind turbines. A linear state-space representation of a generic, multiple degree-of-freedom wind turbine is developed to test various control methods and paradigms. The structural model, SymDyn, provides for limited flexibility in the tower, drive train and blades assuming a rigid component architecture with joint springs and dampers. Equations of motion are derived symbolically, verified by numerical simulation, and implemented in the Matlab with Simulink computational environment. AeroDyn, an industry-standard aerodynamics package for wind turbines, provides the aerodynamic load data through interfaced subroutines. Linearization of the structural model produces state equations with periodic coefficients due to the interaction of rotating and non-rotating components. Floquet theory is used to extract the necessary modal properties and several parametric studies identify the damping levels and dominant dynamic coupling influences. Two separate issues of control design are investigated: full-state feedback and state estimation. Periodic gains are developed using time-varying LQR techniques and many different time-invariant control designs are constructed, including a classical PID controller. Disturbance accommodating control (DAC) allows the estimation of wind speed for minimization of the disturbance effects on the system. Controllers are tested in simulation for multiple objectives using measurement of rotor position and rotor speed only and actuation of independent blade pitch. It is found that periodic control is capable of reducing cyclic blade bending moments while regulating speed but that optimal performance requires additional sensor information. Periodic control is also the only design found that could successfully control the yaw alignment although blade loads are increased as a consequence. When speed regulation is the only performance objective then a time-invariant state-space design or PID is appropriate.

Intelligent multi-sensor integrations

NASA Technical Reports Server (NTRS)

Volz, Richard A.; Jain, Ramesh; Weymouth, Terry

1989-01-01

Growth in the intelligence of space systems requires the use and integration of data from multiple sensors. Generic tools are being developed for extracting and integrating information obtained from multiple sources. The full spectrum is addressed for issues ranging from data acquisition, to characterization of sensor data, to adaptive systems for utilizing the data. In particular, there are three major aspects to the project, multisensor processing, an adaptive approach to object recognition, and distributed sensor system integration.

Miniaturized Planar Room Temperature Ionic Liquid Electrochemical Gas Sensor for Rapid Multiple Gas Pollutants Monitoring.

PubMed

Wan, Hao; Yin, Heyu; Lin, Lu; Zeng, Xiangqun; Mason, Andrew J

2018-02-01

The growing impact of airborne pollutants and explosive gases on human health and occupational safety has escalated the demand of sensors to monitor hazardous gases. This paper presents a new miniaturized planar electrochemical gas sensor for rapid measurement of multiple gaseous hazards. The gas sensor features a porous polytetrafluoroethylene substrate that enables fast gas diffusion and room temperature ionic liquid as the electrolyte. Metal sputtering was utilized for platinum electrodes fabrication to enhance adhesion between the electrodes and the substrate. Together with carefully selected electrochemical methods, the miniaturized gas sensor is capable of measuring multiple gases including oxygen, methane, ozone and sulfur dioxide that are important to human health and safety. Compared to its manually-assembled Clark-cell predecessor, this sensor provides better sensitivity, linearity and repeatability, as validated for oxygen monitoring. With solid performance, fast response and miniaturized size, this sensor is promising for deployment in wearable devices for real-time point-of-exposure gas pollutant monitoring.

Integrated multi-sensor package (IMSP) for unmanned vehicle operations

NASA Astrophysics Data System (ADS)

Crow, Eddie C.; Reichard, Karl; Rogan, Chris; Callen, Jeff; Seifert, Elwood

2007-10-01

This paper describes recent efforts to develop integrated multi-sensor payloads for small robotic platforms for improved operator situational awareness and ultimately for greater robot autonomy. The focus is on enhancements to perception through integration of electro-optic, acoustic, and other sensors for navigation and inspection. The goals are to provide easier control and operation of the robot through fusion of multiple sensor outputs, to improve interoperability of the sensor payload package across multiple platforms through the use of open standards and architectures, and to reduce integration costs by embedded sensor data processing and fusion within the sensor payload package. The solutions investigated in this project to be discussed include: improved capture, processing and display of sensor data from multiple, non-commensurate sensors; an extensible architecture to support plug and play of integrated sensor packages; built-in health, power and system status monitoring using embedded diagnostics/prognostics; sensor payload integration into standard product forms for optimized size, weight and power; and the use of the open Joint Architecture for Unmanned Systems (JAUS)/ Society of Automotive Engineers (SAE) AS-4 interoperability standard. This project is in its first of three years. This paper will discuss the applicability of each of the solutions in terms of its projected impact to reducing operational time for the robot and teleoperator.

The Compact Environmental Anomaly Sensor (CEASE) III

NASA Astrophysics Data System (ADS)

Roddy, P.; Hilmer, R. V.; Ballenthin, J.; Lindstrom, C. D.; Barton, D. A.; Ignazio, J. M.; Coombs, J. M.; Johnston, W. R.; Wheelock, A. T.; Quigley, S.

2016-12-01

The Air Force Research Laboratory's Energetic Charged Particle (ECP) sensor project is a comprehensive effort to measure the charged particle environment that causes satellite anomalies. The project includes the Compact Environmental Anomaly Sensor (CEASE) III, building on the flight heritage of prior CEASE designs. CEASE III consists of multiple sensor modules. High energy particles are observed using independent unique silicon detector stacks. In addition CEASE III includes an electrostatic analyzer (ESA) assembly which uses charge multiplication for particle detection. The sensors cover a wide range of proton and electron energies that contribute to satellite anomalies.

Detection of electromagnetic radiation using micromechanical multiple quantum wells structures

DOEpatents

Datskos, Panagiotis G [Knoxville, TN; Rajic, Slobodan [Knoxville, TN; Datskou, Irene [Knoxville, TN

2007-07-17

An apparatus and method for detecting electromagnetic radiation employs a deflectable micromechanical apparatus incorporating multiple quantum wells structures. When photons strike the quantum-well structure, physical stresses are created within the sensor, similar to a "bimetallic effect." The stresses cause the sensor to bend. The extent of deflection of the sensor can be measured through any of a variety of conventional means to provide a measurement of the photons striking the sensor. A large number of such sensors can be arranged in a two-dimensional array to provide imaging capability.

WO{sub 3} thin film based multiple sensor array for electronic nose application

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

Ramgir, Niranjan S., E-mail: niranjanpr@yahoo.com, E-mail: deepakcct1991@gmail.com; Goyal, C. P.; Datta, N.

2015-06-24

Multiple sensor array comprising 16 x 2 sensing elements were realized using RF sputtered WO{sub 3} thin films. The sensor films were modified with a thin layer of sensitizers namely Au, Ni, Cu, Al, Pd, Ti, Pt. The resulting sensor array were tested for their response towards different gases namely H{sub 2}S, NH{sub 3}, NO and C{sub 2}H{sub 5}OH. The sensor response values measured from the response curves indicates that the sensor array generates a unique signature pattern (bar chart) for the gases. The sensor response values can be used to get both qualitative and quantitative information about the gas.

Multiple incipient sensor faults diagnosis with application to high-speed railway traction devices.

PubMed

Wu, Yunkai; Jiang, Bin; Lu, Ningyun; Yang, Hao; Zhou, Yang

2017-03-01

This paper deals with the problem of incipient fault diagnosis for a class of Lipschitz nonlinear systems with sensor biases and explores further results of total measurable fault information residual (ToMFIR). Firstly, state and output transformations are introduced to transform the original system into two subsystems. The first subsystem is subject to system disturbances and free from sensor faults, while the second subsystem contains sensor faults but without any system disturbances. Sensor faults in the second subsystem are then formed as actuator faults by using a pseudo-actuator based approach. Since the effects of system disturbances on the residual are completely decoupled, multiple incipient sensor faults can be detected by constructing ToMFIR, and the fault detectability condition is then derived for discriminating the detectable incipient sensor faults. Further, a sliding-mode observers (SMOs) based fault isolation scheme is designed to guarantee accurate isolation of multiple sensor faults. Finally, simulation results conducted on a CRH2 high-speed railway traction device are given to demonstrate the effectiveness of the proposed approach. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Novel Tactile Sensor Technology and Smart Tactile Sensing Systems: A Review

PubMed Central

Ge, Chang; Wang, Z. Jane; Cretu, Edmond; Li, Xiaoou

2017-01-01

During the last decades, smart tactile sensing systems based on different sensing techniques have been developed due to their high potential in industry and biomedical engineering. However, smart tactile sensing technologies and systems are still in their infancy, as many technological and system issues remain unresolved and require strong interdisciplinary efforts to address them. This paper provides an overview of smart tactile sensing systems, with a focus on signal processing technologies used to interpret the measured information from tactile sensors and/or sensors for other sensory modalities. The tactile sensing transduction and principles, fabrication and structures are also discussed with their merits and demerits. Finally, the challenges that tactile sensing technology needs to overcome are highlighted. PMID:29149080

Mobile user identity sensing using the motion sensor

NASA Astrophysics Data System (ADS)

Zhao, Xi; Feng, Tao; Xu, Lei; Shi, Weidong

2014-05-01

Employing mobile sensor data to recognize user behavioral activities has been well studied in recent years. However, to adopt the data as a biometric modality has rarely been explored. Existing methods either used the data to recognize gait, which is considered as a distinguished identity feature; or segmented a specific kind of motion for user recognition, such as phone picking-up motion. Since the identity and the motion gesture jointly affect motion data, to fix the gesture (walking or phone picking-up) definitively simplifies the identity sensing problem. However, it meanwhile introduces the complexity from gesture detection or requirement on a higher sample rate from motion sensor readings, which may draw the battery fast and affect the usability of the phone. In general, it is still under investigation that motion based user authentication in a large scale satisfies the accuracy requirement as a stand-alone biometrics modality. In this paper, we propose a novel approach to use the motion sensor readings for user identity sensing. Instead of decoupling the user identity from a gesture, we reasonably assume users have their own distinguishing phone usage habits and extract the identity from fuzzy activity patterns, represented by a combination of body movements whose signals in chains span in relative low frequency spectrum and hand movements whose signals span in relative high frequency spectrum. Then Bayesian Rules are applied to analyze the dependency of different frequency components in the signals. During testing, a posterior probability of user identity given the observed chains can be computed for authentication. Tested on an accelerometer dataset with 347 users, our approach has demonstrated the promising results.

Citizen Sensors for SHM: Towards a Crowdsourcing Platform

PubMed Central

Ozer, Ekin; Feng, Maria Q.; Feng, Dongming

2015-01-01

This paper presents an innovative structural health monitoring (SHM) platform in terms of how it integrates smartphone sensors, the web, and crowdsourcing. The ubiquity of smartphones has provided an opportunity to create low-cost sensor networks for SHM. Crowdsourcing has given rise to citizen initiatives becoming a vast source of inexpensive, valuable but heterogeneous data. Previously, the authors have investigated the reliability of smartphone accelerometers for vibration-based SHM. This paper takes a step further to integrate mobile sensing and web-based computing for a prospective crowdsourcing-based SHM platform. An iOS application was developed to enable citizens to measure structural vibration and upload the data to a server with smartphones. A web-based platform was developed to collect and process the data automatically and store the processed data, such as modal properties of the structure, for long-term SHM purposes. Finally, the integrated mobile and web-based platforms were tested to collect the low-amplitude ambient vibration data of a bridge structure. Possible sources of uncertainties related to citizens were investigated, including the phone location, coupling conditions, and sampling duration. The field test results showed that the vibration data acquired by smartphones operated by citizens without expertise are useful for identifying structural modal properties with high accuracy. This platform can be further developed into an automated, smart, sustainable, cost-free system for long-term monitoring of structural integrity of spatially distributed urban infrastructure. Citizen Sensors for SHM will be a novel participatory sensing platform in the way that it offers hybrid solutions to transitional crowdsourcing parameters. PMID:26102490

Multi-modal automatic montaging of adaptive optics retinal images

PubMed Central

Chen, Min; Cooper, Robert F.; Han, Grace K.; Gee, James; Brainard, David H.; Morgan, Jessica I. W.

2016-01-01

We present a fully automated adaptive optics (AO) retinal image montaging algorithm using classic scale invariant feature transform with random sample consensus for outlier removal. Our approach is capable of using information from multiple AO modalities (confocal, split detection, and dark field) and can accurately detect discontinuities in the montage. The algorithm output is compared to manual montaging by evaluating the similarity of the overlapping regions after montaging, and calculating the detection rate of discontinuities in the montage. Our results show that the proposed algorithm has high alignment accuracy and a discontinuity detection rate that is comparable (and often superior) to manual montaging. In addition, we analyze and show the benefits of using multiple modalities in the montaging process. We provide the algorithm presented in this paper as open-source and freely available to download. PMID:28018714

Mode separation in frequency-wavenumber domain through compressed sensing of far-field Lamb waves

NASA Astrophysics Data System (ADS)

Gao, Fei; Zeng, Liang; Lin, Jing; Luo, Zhi

2017-07-01

This method based on Lamb waves shows great potential for long-range damage detection. Mode superposition resulting from multi-modal and dispersive characteristics makes signal interpretation and damage feature extraction difficult. Mode separation in the frequency-wavenumber (f-k) domain using a 1D sparse sensing array is a promising solution. However, due to the lack of prior knowledge about damage location, this method based on 1D linear measurement, for the mode extraction of arbitrary reflections caused by defects that are not in line with the sensor array, is restricted. In this paper, an improved compressed sensing method under the far-field assumption is established, which is beneficial to the reconstruction of reflections in the f-k domain. Hence, multiple components consisting of structure and damage features could be recovered via a limited number of measurements. Subsequently, a mode sweeping process based on theoretical dispersion curves has been designed for mode characterization and direction of arrival estimation. Moreover, 2D f-k filtering and inverse transforms are applied to the reconstructed f-k distribution in order to extract the purified mode of interest. As a result, overlapping waveforms can be separated and the direction of defects can be estimated. A uniform linear sensor array consisting of 16 laser excitations is finally employed for experimental investigations and the results demonstrate the efficiency of the proposed method.

Paradigms for restoration of somatosensory feedback via stimulation of the peripheral nervous system.

PubMed

Pasluosta, Cristian; Kiele, Patrick; Stieglitz, Thomas

2018-04-01

The somatosensory system contributes substantially to the integration of multiple sensor modalities into perception. Tactile sensations, proprioception and even temperature perception are integrated to perceive embodiment of our limbs. Damage of somatosensory networks can severely affect the execution of daily life activities. Peripheral injuries are optimally corrected via direct interfacing of the peripheral nerves. Recent advances in implantable devices, stimulation paradigms, and biomimetic sensors enabled the restoration of natural sensations after amputation of the limb. The refinement of stimulation patterns to deliver natural feedback that can be interpreted intuitively such to prescind from long-learning sessions is crucial to function restoration. For this review, we collected state-of-the-art knowledge on the evolution of stimulation paradigms from single fiber stimulation to the eliciting of multisensory sensations. Data from the literature are structured into six sections: (a) physiology of the somatosensory system; (b) stimulation of single fibers; (c) restoral of multisensory percepts; (d) closure of the control loop in hand prostheses; (e) sensory restoration and the sense of embodiment, and (f) methodologies to assess stimulation outcomes. Full functional recovery demands further research on multisensory integration and brain plasticity, which will bring new paradigms for intuitive sensory feedback in the next generation of limb prostheses. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Polyarteritis nodosa: MDCT as a 'One-Stop Shop' Modality for Whole-Body Arterial Evaluation

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

Tsai, W.-L.; Tsai, I-C.; Lee Tain, E-mail: s841082@ym.edu.t

Polyarteritis nodosa is a rare disease, which is characterized by aneurysm formation and occlusion in the arteries of multiple systems. Due to its extensive involvement, whole-body evaluation is necessary for diagnosis and treatment monitoring. We report a case of polyarteritis nodosa using multidetector-row computed tomography (MDCT) as a 'one-stop shop' modality for whole-body arterial evaluation. With precise protocol design, MDCT can be used as a reliable noninvasive modality providing comprehensive whole-body arterial evaluation.

A modal parameter extraction procedure applicable to linear time-invariant dynamic systems

NASA Technical Reports Server (NTRS)

Kurdila, A. J.; Craig, R. R., Jr.

1985-01-01

Modal analysis has emerged as a valuable tool in many phases of the engineering design process. Complex vibration and acoustic problems in new designs can often be remedied through use of the method. Moreover, the technique has been used to enhance the conceptual understanding of structures by serving to verify analytical models. A new modal parameter estimation procedure is presented. The technique is applicable to linear, time-invariant systems and accommodates multiple input excitations. In order to provide a background for the derivation of the method, some modal parameter extraction procedures currently in use are described. Key features implemented in the new technique are elaborated upon.

On Identifiability of Bias-Type Actuator-Sensor Faults in Multiple-Model-Based Fault Detection and Identification

NASA Technical Reports Server (NTRS)

Joshi, Suresh M.

2012-01-01

This paper explores a class of multiple-model-based fault detection and identification (FDI) methods for bias-type faults in actuators and sensors. These methods employ banks of Kalman-Bucy filters to detect the faults, determine the fault pattern, and estimate the fault values, wherein each Kalman-Bucy filter is tuned to a different failure pattern. Necessary and sufficient conditions are presented for identifiability of actuator faults, sensor faults, and simultaneous actuator and sensor faults. It is shown that FDI of simultaneous actuator and sensor faults is not possible using these methods when all sensors have biases.

Compact photonic crystal fiber refractometer based on modal interference

NASA Astrophysics Data System (ADS)

Wong, Wei Chang; Chan, Chi Chiu; Tou, Zhi Qiang; Chen, Li Han; Leong, Kam Chew

2011-05-01

A compact photonic crystal fiber (PCF) refractometer based on modal interference has been proposed by the use of commercial fusion splicer to collapse the holes of PCF to form a Mach Zehnder interferometer by splitting the fundamental core mode into cladding and core modes in the PCF. Collapsed of holes was done at the interface between the single mode fiber and PCF, and the PCF's end. The shift of the interference fringes was measured when the sensor was placed into different refractive index liquid. High linear sensitivity of 253.13nm/RIU with resolution of 3.950×10-5RIU was obtained.

Community Air Sensor Network (CAIRSENSE) project ...

EPA Pesticide Factsheets

Advances in air pollution sensor technology have enabled the development of small and low cost systems to measure outdoor air pollution. The deployment of a large number of sensors across a small geographic area would have potential benefits to supplement traditional monitoring networks with additional geographic and temporal measurement resolution, if the data quality were sufficient. To understand the capability of emerging air sensor technology, the Community Air Sensor Network (CAIRSENSE) project deployed low cost, continuous and commercially-available air pollution sensors at a regulatory air monitoring site and as a local sensor network over a surrounding ~2 km area in Southeastern U.S. Co-location of sensors measuring oxides of nitrogen, ozone, carbon monoxide, sulfur dioxide, and particles revealed highly variable performance, both in terms of comparison to a reference monitor as well as whether multiple identical sensors reproduced the same signal. Multiple ozone, nitrogen dioxide, and carbon monoxide sensors revealed low to very high correlation with a reference monitor, with Pearson sample correlation coefficient (r) ranging from 0.39 to 0.97, -0.25 to 0.76, -0.40 to 0.82, respectively. The only sulfur dioxide sensor tested revealed no correlation (r 0.5), step-wise multiple linear regression was performed to determine if ambient temperature, relative humidity (RH), or age of the sensor in sampling days could be used in a correction algorihm to im

Improvement of the Measurement Range and Temperature Characteristics of a Load Sensor Using a Quartz Crystal Resonator with All Crystal Layer Components.

PubMed

Murozaki, Yuichi; Sakuma, Shinya; Arai, Fumihito

2017-05-08

Monitoring multiple biosignals, such as heart rate, respiration cycle, and weight transitions, contributes to the health management of individuals. Specifically, it is possible to measure multiple biosignals using load information obtained through contact with the environment, such as a chair and bed, in daily use. A wide-range load sensor is essential since load information contains multiple biosignals with various load ranges. In this study, a load sensor is presented by using a quartz crystal resonator (QCR) with a wide measurement range of 1.5 × 10⁶ (0.4 mN to 600 N), and its temperature characteristic of load is improved to -7 Hz/°C (-18 mN/°C). In order to improve the measurement range of the load, a design method of this sensor is proposed by restraining the buckling of QCR and by using a thinner QCR. The proposed sensor allows a higher allowable load with high sensitivity. The load sensor mainly consists of three layers, namely a QCR layer and two holding layers. As opposed to the conventional holding layer composed of silicon, quartz crystal is utilized for the holding layers to improve the temperature characteristic of the load sensor. In the study, multiple biosignals, such as weight and pulse, are detected by using a fabricated sensor.

Data Fusion for a Vision-Radiological System for Source Tracking and Discovery

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

Enqvist, Andreas; Koppal, Sanjeev

2015-07-01

A multidisciplinary approach to allow the tracking of the movement of radioactive sources by fusing data from multiple radiological and visual sensors is under development. The goal is to improve the ability to detect, locate, track and identify nuclear/radiological threats. The key concept is that such widely available visual and depth sensors can impact radiological detection, since the intensity fall-off in the count rate can be correlated to movement in three dimensions. To enable this, we pose an important question; what is the right combination of sensing modalities and vision algorithms that can best compliment a radiological sensor, for themore » purpose of detection and tracking of radioactive material? Similarly what is the best radiation detection methods and unfolding algorithms suited for data fusion with tracking data? Data fusion of multi-sensor data for radiation detection have seen some interesting developments lately. Significant examples include intelligent radiation sensor systems (IRSS), which are based on larger numbers of distributed similar or identical radiation sensors coupled with position data for network capable to detect and locate radiation source. Other developments are gamma-ray imaging systems based on Compton scatter in segmented detector arrays. Similar developments using coded apertures or scatter cameras for neutrons have recently occurred. The main limitation of such systems is not so much in their capability but rather in their complexity and cost which is prohibitive for large scale deployment. Presented here is a fusion system based on simple, low-cost computer vision and radiological sensors for tracking of multiple objects and identifying potential radiological materials being transported or shipped. The main focus of this work is the development on two separate calibration algorithms for characterizing the fused sensor system. The deviation from a simple inverse square-root fall-off of radiation intensity is explored and accounted for. In particular, the computer vision system enables a map of distance-dependence of the sources being tracked. Infrared, laser or stereoscopic vision sensors are all options for computer-vision implementation depending on interior vs exterior deployment, resolution desired and other factors. Similarly the radiation sensors will be focused on gamma-ray or neutron detection due to the long travel length and ability to penetrate even moderate shielding. There is a significant difference between the vision sensors and radiation sensors in the way the 'source' or signals are generated. A vision sensor needs an external light-source to illuminate the object and then detects the re-emitted illumination (or lack thereof). However, for a radiation detector, the radioactive material is the source itself. The only exception to this is the field of active interrogations where radiation is beamed into a material to entice new/additional radiation emission beyond what the material would emit spontaneously. The aspect of the nuclear material being the source itself means that all other objects in the environment are 'illuminated' or irradiated by the source. Most radiation will readily penetrate regular material, scatter in new directions or be absorbed. Thus if a radiation source is located near a larger object that object will in turn scatter some radiation that was initially emitted in a direction other than the direction of the radiation detector, this can add to the count rate that is observed. The effect of these scatter is a deviation from the traditional distance dependence of the radiation signal and is a key challenge that needs a combined system calibration solution and algorithms. Thus both an algebraic approach as well as a statistical approach have been developed and independently evaluated to investigate the sensitivity to this deviation from the simplified radiation fall-off as a function of distance. The resulting calibrated system algorithms are used and demonstrated in various laboratory scenarios, and later in realistic tracking scenarios. The selection and testing of radiological and computer-vision sensors for the additional specific scenarios will be the subject of ongoing and future work. (authors)« less

OLAM: A wearable, non-contact sensor for continuous heart-rate and activity monitoring.

PubMed

Albright, Ryan K; Goska, Benjamin J; Hagen, Tory M; Chi, Mike Y; Cauwenberghs, G; Chiang, Patrick Y

2011-01-01

A wearable, multi-modal sensor is presented that can non-invasively monitor a patient's activity level and heart function concurrently for more than a week. The 4 in(2) sensor incorporates both a non-contact heartrate sensor and a 5-axis inertial measurement unit (IMU), allowing simultaneous heart, respiration, and movement monitoring without requiring physical contact with the skin [1]. Hence, this Oregon State University Life and Activity Monitor (OLAM) provides the unique opportunity to combine motion data with heart-rate information, enabling assessment of actual physical activity beyond conventional movement sensors. OLAM also provides a unique platform for non-contact sensing, enabling the filtering of movement artifacts generated by the non-contact capacitive interface, using the IMU data as a movement noise channel. Intended to be used in clinical trials for weeks at a time with no physician intervention, the OLAM allows continuous non-invasive monitoring of patients, providing the opportunity for long-term observation into a patient's physical activity and subtle longitudinal changes.

Unitary vs Multiple Semantics: PET Studies of Word and Picture Processing

ERIC Educational Resources Information Center

Bright, P.; Moss, H.; Tyler, L. K.

2004-01-01

In this paper we examine a central issue in cognitive neuroscience: are there separate conceptual representations associated with different input modalities (e.g., Paivio, 1971, 1986; Warrington & Shallice, 1984) or do inputs from different modalities converge on to the same set of representations (e.g., Caramazza, Hillis, Rapp, & Romani, 1990;…

Appraisal of unimodal cues during agonistic interactions in Maylandia zebra

PubMed Central

Ben Ammar, Imen; Fernandez, Marie S.A.; Boyer, Nicolas; Attia, Joël; Fonseca, Paulo J.; Amorim, M. Clara P.; Beauchaud, Marilyn

2017-01-01

Communication is essential during social interactions including animal conflicts and it is often a complex process involving multiple sensory channels or modalities. To better understand how different modalities interact during communication, it is fundamental to study the behavioural responses to both the composite multimodal signal and each unimodal component with adequate experimental protocols. Here we test how an African cichlid, which communicates with multiple senses, responds to different sensory stimuli in a social relevant scenario. We tested Maylandia zebra males with isolated chemical (urine or holding water coming both from dominant males), visual (real opponent or video playback) and acoustic (agonistic sounds) cues during agonistic interactions. We showed that (1) these fish relied mostly on the visual modality, showing increased aggressiveness in response to the sight of a real contestant but no responses to urine or agonistic sounds presented separately, (2) video playback in our study did not appear appropriate to test the visual modality and needs more technical prospecting, (3) holding water provoked territorial behaviours and seems to be promising for the investigation into the role of the chemical channel in this species. Our findings suggest that unimodal signals are non-redundant but how different sensory modalities interplay during communication remains largely unknown in fish. PMID:28785523

Physiological Modalities for Relaxation Skill Transfer in Biofeedback Games.

PubMed

Parnandi, Avinash; Gutierrez-Osuna, Ricardo

2017-03-01

We present an adaptive biofeedback game for teaching self-regulation of stress. Our approach consists of monitoring the user's physiology during gameplay and adapting the game using a positive feedback loop that rewards relaxing behaviors and penalizes states of high arousal. We evaluate the approach using a casual game under three biofeedback modalities: electrodermal activity, heart rate variability, and breathing rate. The three biosignals can be measured noninvasively with wearable sensors, and represent different degrees of voluntary control and selectivity toward arousal. We conducted an experiment trial with 25 participants to compare the three modalities against a standard treatment (deep breathing) and a control condition (the game without biofeedback). Our results indicate that breathing-based game biofeedback is more effective in inducing relaxation during treatment than the other four groups. Participants in this group also showed greater retention of the relaxation skills (without biofeedback) during a subsequent stressor.

Operational Modal Analysis of the Cablestayed Footbridge

NASA Astrophysics Data System (ADS)

Kortiš, Ján; Daniel, Ľuboš; Farbák, Matúš; Maliar, Lukáš; Škarupa, Milan

2017-12-01

Modern architecture leads to design subtle bridge structures that are more sensitive to increased dynamic loading than the massive ones. This phenomenon can be especially observed on lightweight steel structures such as suspended footbridges. As a result, it is necessary to know precisely its dynamic characteristics, such as natural frequencies, natural shapes and damping of construction. This information can be used for further analysis such as damage detection, system identification, health monitoring, etc. or also for the design of new types of construction. For this purpose, classical modal analysis using trigger load or harmonic vibration exciter in combination with acceleration sensors is used in practice. However, there are many situations where it is not possible to stop the traffic or operation of the bridge. The article presents an experimental measurement of the dynamic parameters of the structure at the operating load using the operational modal analysis.

A new method to extract modal parameters using output-only responses

NASA Astrophysics Data System (ADS)

Kim, Byeong Hwa; Stubbs, Norris; Park, Taehyo

2005-04-01

This work proposes a new output-only modal analysis method to extract mode shapes and natural frequencies of a structure. The proposed method is based on an approach with a single-degree-of-freedom in the time domain. For a set of given mode-isolated signals, the un-damped mode shapes are extracted utilizing the singular value decomposition of the output energy correlation matrix with respect to sensor locations. The natural frequencies are extracted from a noise-free signal that is projected on the estimated modal basis. The proposed method is particularly efficient when a high resolution of mode shape is essential. The accuracy of the method is numerically verified using a set of time histories that are simulated using a finite-element method. The feasibility and practicality of the method are verified using experimental data collected at the newly constructed King Storm Water Bridge in California, United States.

Smart wheelchair: integration of multiple sensors

NASA Astrophysics Data System (ADS)

Gassara, H. E.; Almuhamed, S.; Moukadem, A.; Schacher, L.; Dieterlen, A.; Adolphe, D.

2017-10-01

The aim of the present work is to develop a smart wheelchair by integrating multiple sensors for measuring user’s physiological signals and subsequently transmitting and monitoring the treated signals to the user, a designated person or institution. Among other sensors, force, accelerometer, and temperature sensors are successfully integrated within both the backrest and the seat cushions of the wheelchair; while a pulse sensor is integrated within the armrest. The pulse sensor is connected to an amplification circuit board that is, in turn, placed within the armrest. The force and temperature sensors are integrated into a textile cover of the cushions by means of embroidery and sewing techniques. The signal from accelerometer is transmitted through Wi-Fi connection. The electrical connections needed for power supplying of sensors are made by embroidered conductive threads.

An Imaging Sensor-Aided Vision Navigation Approach that Uses a Geo-Referenced Image Database.

PubMed

Li, Yan; Hu, Qingwu; Wu, Meng; Gao, Yang

2016-01-28

In determining position and attitude, vision navigation via real-time image processing of data collected from imaging sensors is advanced without a high-performance global positioning system (GPS) and an inertial measurement unit (IMU). Vision navigation is widely used in indoor navigation, far space navigation, and multiple sensor-integrated mobile mapping. This paper proposes a novel vision navigation approach aided by imaging sensors and that uses a high-accuracy geo-referenced image database (GRID) for high-precision navigation of multiple sensor platforms in environments with poor GPS. First, the framework of GRID-aided vision navigation is developed with sequence images from land-based mobile mapping systems that integrate multiple sensors. Second, a highly efficient GRID storage management model is established based on the linear index of a road segment for fast image searches and retrieval. Third, a robust image matching algorithm is presented to search and match a real-time image with the GRID. Subsequently, the image matched with the real-time scene is considered to calculate the 3D navigation parameter of multiple sensor platforms. Experimental results show that the proposed approach retrieves images efficiently and has navigation accuracies of 1.2 m in a plane and 1.8 m in height under GPS loss in 5 min and within 1500 m.

An Imaging Sensor-Aided Vision Navigation Approach that Uses a Geo-Referenced Image Database

PubMed Central

Li, Yan; Hu, Qingwu; Wu, Meng; Gao, Yang

2016-01-01

In determining position and attitude, vision navigation via real-time image processing of data collected from imaging sensors is advanced without a high-performance global positioning system (GPS) and an inertial measurement unit (IMU). Vision navigation is widely used in indoor navigation, far space navigation, and multiple sensor-integrated mobile mapping. This paper proposes a novel vision navigation approach aided by imaging sensors and that uses a high-accuracy geo-referenced image database (GRID) for high-precision navigation of multiple sensor platforms in environments with poor GPS. First, the framework of GRID-aided vision navigation is developed with sequence images from land-based mobile mapping systems that integrate multiple sensors. Second, a highly efficient GRID storage management model is established based on the linear index of a road segment for fast image searches and retrieval. Third, a robust image matching algorithm is presented to search and match a real-time image with the GRID. Subsequently, the image matched with the real-time scene is considered to calculate the 3D navigation parameter of multiple sensor platforms. Experimental results show that the proposed approach retrieves images efficiently and has navigation accuracies of 1.2 m in a plane and 1.8 m in height under GPS loss in 5 min and within 1500 m. PMID:26828496

Modeling the Development of Audiovisual Cue Integration in Speech Perception

PubMed Central

Getz, Laura M.; Nordeen, Elke R.; Vrabic, Sarah C.; Toscano, Joseph C.

2017-01-01

Adult speech perception is generally enhanced when information is provided from multiple modalities. In contrast, infants do not appear to benefit from combining auditory and visual speech information early in development. This is true despite the fact that both modalities are important to speech comprehension even at early stages of language acquisition. How then do listeners learn how to process auditory and visual information as part of a unified signal? In the auditory domain, statistical learning processes provide an excellent mechanism for acquiring phonological categories. Is this also true for the more complex problem of acquiring audiovisual correspondences, which require the learner to integrate information from multiple modalities? In this paper, we present simulations using Gaussian mixture models (GMMs) that learn cue weights and combine cues on the basis of their distributional statistics. First, we simulate the developmental process of acquiring phonological categories from auditory and visual cues, asking whether simple statistical learning approaches are sufficient for learning multi-modal representations. Second, we use this time course information to explain audiovisual speech perception in adult perceivers, including cases where auditory and visual input are mismatched. Overall, we find that domain-general statistical learning techniques allow us to model the developmental trajectory of audiovisual cue integration in speech, and in turn, allow us to better understand the mechanisms that give rise to unified percepts based on multiple cues. PMID:28335558

Modeling the Development of Audiovisual Cue Integration in Speech Perception.

PubMed

Getz, Laura M; Nordeen, Elke R; Vrabic, Sarah C; Toscano, Joseph C

2017-03-21

Adult speech perception is generally enhanced when information is provided from multiple modalities. In contrast, infants do not appear to benefit from combining auditory and visual speech information early in development. This is true despite the fact that both modalities are important to speech comprehension even at early stages of language acquisition. How then do listeners learn how to process auditory and visual information as part of a unified signal? In the auditory domain, statistical learning processes provide an excellent mechanism for acquiring phonological categories. Is this also true for the more complex problem of acquiring audiovisual correspondences, which require the learner to integrate information from multiple modalities? In this paper, we present simulations using Gaussian mixture models (GMMs) that learn cue weights and combine cues on the basis of their distributional statistics. First, we simulate the developmental process of acquiring phonological categories from auditory and visual cues, asking whether simple statistical learning approaches are sufficient for learning multi-modal representations. Second, we use this time course information to explain audiovisual speech perception in adult perceivers, including cases where auditory and visual input are mismatched. Overall, we find that domain-general statistical learning techniques allow us to model the developmental trajectory of audiovisual cue integration in speech, and in turn, allow us to better understand the mechanisms that give rise to unified percepts based on multiple cues.

Modal Parameter Identification and Numerical Simulation for Self-anchored Suspension Bridges Based on Ambient Vibration

NASA Astrophysics Data System (ADS)

Liu, Bing; Sun, Li Guo

2018-06-01

This paper chooses the Nanjing-Hangzhou high speed overbridge, a self-anchored suspension bridge, as the research target, trying to identify the dynamic characteristic parameters of the bridge by using the peak-picking method to analyze the velocity response data under ambient excitation collected by 7 vibration pickup sensors set on the bridge deck. The ABAQUS is used to set up a three-dimensional finite element model for the full bridge and amends the finite element model of the suspension bridge based on the identified modal parameter, and suspender force picked by the PDV100 laser vibrometer. The study shows that the modal parameter can well be identified by analyzing the bridge vibration velocity collected by 7 survey points. The identified modal parameter and measured suspender force can be used as the basis of the amendment of the finite element model of the suspension bridge. The amended model can truthfully reflect the structural physical features and it can also be the benchmark model for the long-term health monitoring and condition assessment of the bridge.

Multiset singular value decomposition for joint analysis of multi-modal data: application to fingerprint analysis

NASA Astrophysics Data System (ADS)

Emge, Darren K.; Adalı, Tülay

2014-06-01

As the availability and use of imaging methodologies continues to increase, there is a fundamental need to jointly analyze data that is collected from multiple modalities. This analysis is further complicated when, the size or resolution of the images differ, implying that the observation lengths of each of modality can be highly varying. To address this expanding landscape, we introduce the multiset singular value decomposition (MSVD), which can perform a joint analysis on any number of modalities regardless of their individual observation lengths. Through simulations, the inter modal relationships across the different modalities which are revealed by the MSVD are shown. We apply the MSVD to forensic fingerprint analysis, showing that MSVD joint analysis successfully identifies relevant similarities for further analysis, significantly reducing the processing time required. This reduction, takes this technique from a laboratory method to a useful forensic tool with applications across the law enforcement and security regimes.

Standards-Based Wireless Sensor Networking Protocols for Spaceflight Applications

NASA Technical Reports Server (NTRS)

Barton, Richard J.; Wagner, Raymond S.

2009-01-01

Wireless sensor networks (WSNs) have the capacity to revolutionize data gathering in both spaceflight and terrestrial applications. WSNs provide a huge advantage over traditional, wired instrumentation since they do not require wiring trunks to connect sensors to a central hub. This allows for easy sensor installation in hard to reach locations, easy expansion of the number of sensors or sensing modalities, and reduction in both system cost and weight. While this technology offers unprecedented flexibility and adaptability, implementing it in practice is not without its difficulties. Any practical WSN deployment must contend with a number of difficulties in its radio frequency (RF) environment. Multi-path reflections can distort signals, limit data rates, and cause signal fades that prevent nodes from having clear access to channels, especially in a closed environment such as a spacecraft. Other RF signal sources, such as wireless internet, voice, and data systems may contend with the sensor nodes for bandwidth. Finally, RF noise from electrical systems and periodic scattering from moving objects such as crew members will all combine to give an incredibly unpredictable, time-varying communication environment.

Noise-immune multisensor transduction of speech

NASA Astrophysics Data System (ADS)

Viswanathan, Vishu R.; Henry, Claudia M.; Derr, Alan G.; Roucos, Salim; Schwartz, Richard M.

1986-08-01

Two types of configurations of multiple sensors were developed, tested and evaluated in speech recognition application for robust performance in high levels of acoustic background noise: One type combines the individual sensor signals to provide a single speech signal input, and the other provides several parallel inputs. For single-input systems, several configurations of multiple sensors were developed and tested. Results from formal speech intelligibility and quality tests in simulated fighter aircraft cockpit noise show that each of the two-sensor configurations tested outperforms the constituent individual sensors in high noise. Also presented are results comparing the performance of two-sensor configurations and individual sensors in speaker-dependent, isolated-word speech recognition tests performed using a commercial recognizer (Verbex 4000) in simulated fighter aircraft cockpit noise.

Activity recognition using dynamic multiple sensor fusion in body sensor networks.

PubMed

Gao, Lei; Bourke, Alan K; Nelson, John

2012-01-01

Multiple sensor fusion is a main research direction for activity recognition. However, there are two challenges in those systems: the energy consumption due to the wireless transmission and the classifier design because of the dynamic feature vector. This paper proposes a multi-sensor fusion framework, which consists of the sensor selection module and the hierarchical classifier. The sensor selection module adopts the convex optimization to select the sensor subset in real time. The hierarchical classifier combines the Decision Tree classifier with the Naïve Bayes classifier. The dataset collected from 8 subjects, who performed 8 scenario activities, was used to evaluate the proposed system. The results show that the proposed system can obviously reduce the energy consumption while guaranteeing the recognition accuracy.

Response of a PCF-based modal interferometer to lateral stress: Resonant behavior and performance as sensor

NASA Astrophysics Data System (ADS)

Sanz-Felipe, Á.; Martín, J. C.

2017-11-01

The performance of a fiber-based modal interferometer as lateral stress sensor has been analyzed, both for static and periodic forces applied on it. The central fiber of the interferometer is a photonic crystal fiber. Forces are applied on it perpendicular to its axis, so that they squeeze it. In static situations, changes in the transmission spectrum of the interferometer are studied as a function of the charges applied. Measurements with several interferometers have been carried out in order to analyze the influence of its length and of its splices' transmission on the device operation, looking for optimization of its linearity and sensibility. The effect of periodic charges, as an emulation of vibrations, has also been studied. The analysis is centered on the frequency dependence of the response. In linear regime (small enough periodic charges), the results obtained are satisfactorily explained by treating the central fiber of the interferometer as a mechanical resonator whose vibration modes coincide with the ones of a cylinder with clamped ends. In nonlinear regime, period doubling and other anharmonic behaviors have been observed.

A high performance sensor for triaxial cutting force measurement in turning.

PubMed

Zhao, You; Zhao, Yulong; Liang, Songbo; Zhou, Guanwu

2015-04-03

This paper presents a high performance triaxial cutting force sensor with excellent accuracy, favorable natural frequency and acceptable cross-interference for high speed turning process. Octagonal ring is selected as sensitive element of the designed sensor, which is drawn inspiration from ring theory. A novel structure of two mutual-perpendicular octagonal rings is proposed and three Wheatstone full bridge circuits are specially organized in order to obtain triaxial cutting force components and restrain cross-interference. Firstly, the newly developed sensor is tested in static calibration; test results indicate that the sensor possesses outstanding accuracy in the range of 0.38%-0.83%. Secondly, impacting modal tests are conducted to identify the natural frequencies of the sensor in triaxial directions (i.e., 1147 Hz, 1122 Hz and 2035 Hz), which implies that the devised sensor can be used for cutting force measurement in a high speed lathe when the spindle speed does not exceed 17,205 rev/min in continuous cutting condition. Finally, an application of the sensor in turning process is operated to show its performance for real-time cutting force measurement; the measured cutting forces demonstrate a good accordance with the variation of cutting parameters. Thus, the developed sensor possesses perfect properties and it gains great potential for real-time cutting force measurement in turning.

A High Performance Sensor for Triaxial Cutting Force Measurement in Turning

PubMed Central

Zhao, You; Zhao, Yulong; Liang, Songbo; Zhou, Guanwu

2015-01-01

This paper presents a high performance triaxial cutting force sensor with excellent accuracy, favorable natural frequency and acceptable cross-interference for high speed turning process. Octagonal ring is selected as sensitive element of the designed sensor, which is drawn inspiration from ring theory. A novel structure of two mutual-perpendicular octagonal rings is proposed and three Wheatstone full bridge circuits are specially organized in order to obtain triaxial cutting force components and restrain cross-interference. Firstly, the newly developed sensor is tested in static calibration; test results indicate that the sensor possesses outstanding accuracy in the range of 0.38%–0.83%. Secondly, impacting modal tests are conducted to identify the natural frequencies of the sensor in triaxial directions (i.e., 1147 Hz, 1122 Hz and 2035 Hz), which implies that the devised sensor can be used for cutting force measurement in a high speed lathe when the spindle speed does not exceed 17,205 rev/min in continuous cutting condition. Finally, an application of the sensor in turning process is operated to show its performance for real-time cutting force measurement; the measured cutting forces demonstrate a good accordance with the variation of cutting parameters. Thus, the developed sensor possesses perfect properties and it gains great potential for real-time cutting force measurement in turning. PMID:25855035

Professional efficiencies for diagnostic imaging services rendered by different physicians: analysis of recent medicare multiple procedure payment reduction policy.

PubMed

Duszak, Richard; Silva, Ezequiel; Kim, Angela J; Barr, Robert M; Donovan, William D; Kassing, Pamela; McGinty, Geraldine; Allen, Bibb

2013-09-01

The aim of this study was to quantify potential physician work efficiencies and appropriate multiple procedure payment reductions for different same-session diagnostic imaging studies interpreted by different physicians in the same group practice. Medicare Resource-Based Relative Value Scale data were analyzed to determine the relative contributions of various preservice, intraservice, and postservice physician diagnostic imaging work activities. An expert panel quantified potential duplications in professional work activities when separate examinations were performed during the same session by different physicians within the same group practice. Maximum potential work duplications for various imaging modalities were calculated and compared with those used as the basis of CMS payment policy. No potential intraservice work duplication was identified when different examination interpretations were rendered by different physicians in the same group practice. When multiple interpretations within the same modality were rendered by different physicians, maximum potential duplicated preservice and postservice activities ranged from 5% (radiography, fluoroscopy, and nuclear medicine) to 13.6% (CT). Maximum mean potential duplicated work relative value units ranged from 0.0049 (radiography and fluoroscopy) to 0.0413 (CT). This equates to overall potential total work reductions ranging from 1.39% (nuclear medicine) to 2.73% (CT). Across all modalities, this corresponds to maximum Medicare professional component physician fee reductions of 1.23 ± 0.38% (range, 0.95%-1.87%) for services within the same modality, much less than an order of magnitude smaller than those implemented by CMS. For services from different modalities, potential duplications were too small to quantify. Although potential efficiencies exist in physician preservice and postservice work when same-session, same-modality imaging services are rendered by different physicians in the same group practice, these are relatively minuscule and have been grossly overestimated by current CMS payment policy. Greater transparency and methodologic rigor in government payment policy development are warranted. Copyright © 2013 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Method of forming a multiple layer dielectric and a hot film sensor therewith

NASA Technical Reports Server (NTRS)

Hopson, Purnell, Jr. (Inventor); Tran, Sang Q. (Inventor)

1990-01-01

The invention is a method of forming a multiple layer dielectric for use in a hot-film laminar separation sensor. The multiple layer dielectric substrate is formed by depositing a first layer of a thermoelastic polymer such as on an electrically conductive substrate such as the metal surface of a model to be tested under cryogenic conditions and high Reynolds numbers. Next, a second dielectric layer of fused silica is formed on the first dielectric layer of thermoplastic polymer. A resistive metal film is deposited on selected areas of the multiple layer dielectric substrate to form one or more hot-film sensor elements to which aluminum electrical circuits deposited upon the multiple layered dielectric substrate are connected.

Early detection of health and welfare compromises through automated detection of behavioural changes in pigs.

PubMed

Matthews, Stephen G; Miller, Amy L; Clapp, James; Plötz, Thomas; Kyriazakis, Ilias

2016-11-01

Early detection of health and welfare compromises in commercial piggeries is essential for timely intervention to enhance treatment success, reduce impact on welfare, and promote sustainable pig production. Behavioural changes that precede or accompany subclinical and clinical signs may have diagnostic value. Often referred to as sickness behaviour, this encompasses changes in feeding, drinking, and elimination behaviours, social behaviours, and locomotion and posture. Such subtle changes in behaviour are not easy to quantify and require lengthy observation input by staff, which is impractical on a commercial scale. Automated early-warning systems may provide an alternative by objectively measuring behaviour with sensors to automatically monitor and detect behavioural changes. This paper aims to: (1) review the quantifiable changes in behaviours with potential diagnostic value; (2) subsequently identify available sensors for measuring behaviours; and (3) describe the progress towards automating monitoring and detection, which may allow such behavioural changes to be captured, measured, and interpreted and thus lead to automation in commercial, housed piggeries. Multiple sensor modalities are available for automatic measurement and monitoring of behaviour, which require humans to actively identify behavioural changes. This has been demonstrated for the detection of small deviations in diurnal drinking, deviations in feeding behaviour, monitoring coughs and vocalisation, and monitoring thermal comfort, but not social behaviour. However, current progress is in the early stages of developing fully automated detection systems that do not require humans to identify behavioural changes; e.g., through automated alerts sent to mobile phones. Challenges for achieving automation are multifaceted and trade-offs are considered between health, welfare, and costs, between analysis of individuals and groups, and between generic and compromise-specific behaviours. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Driver drowsiness detection using multimodal sensor fusion

NASA Astrophysics Data System (ADS)

Andreeva, Elena O.; Aarabi, Parham; Philiastides, Marios G.; Mohajer, Keyvan; Emami, Majid

2004-04-01

This paper proposes a multi-modal sensor fusion algorithm for the estimation of driver drowsiness. Driver sleepiness is believed to be responsible for more than 30% of passenger car accidents and for 4% of all accident fatalities. In commercial vehicles, drowsiness is blamed for 58% of single truck accidents and 31% of commercial truck driver fatalities. This work proposes an innovative automatic sleep-onset detection system. Using multiple sensors, the driver"s body is studied as a mechanical structure of springs and dampeners. The sleep-detection system consists of highly sensitive triple-axial accelerometers to monitor the driver"s upper body in 3-D. The subject is modeled as a linear time-variant (LTV) system. An LMS adaptive filter estimation algorithm generates the transfer function (i.e. weight coefficients) for this LTV system. Separate coefficients are generated for the awake and asleep states of the subject. These coefficients are then used to train a neural network. Once trained, the neural network classifies the condition of the driver as either awake or asleep. The system has been tested on a total of 8 subjects. The tests were conducted on sleep-deprived individuals for the sleep state and on fully awake individuals for the awake state. When trained and tested on the same subject, the system detected sleep and awake states of the driver with a success rate of 95%. When the system was trained on three subjects and then retested on a fourth "unseen" subject, the classification rate dropped to 90%. Furthermore, it was attempted to correlate driver posture and sleepiness by observing how car vibrations propagate through a person"s body. Eight additional subjects were studied for this purpose. The results obtained in this experiment proved inconclusive which was attributed to significant differences in the individual habitual postures.

Adaptive sensor-fault tolerant control for a class of multivariable uncertain nonlinear systems.

PubMed

Khebbache, Hicham; Tadjine, Mohamed; Labiod, Salim; Boulkroune, Abdesselem

2015-03-01

This paper deals with the active fault tolerant control (AFTC) problem for a class of multiple-input multiple-output (MIMO) uncertain nonlinear systems subject to sensor faults and external disturbances. The proposed AFTC method can tolerate three additive (bias, drift and loss of accuracy) and one multiplicative (loss of effectiveness) sensor faults. By employing backstepping technique, a novel adaptive backstepping-based AFTC scheme is developed using the fact that sensor faults and system uncertainties (including external disturbances and unexpected nonlinear functions caused by sensor faults) can be on-line estimated and compensated via robust adaptive schemes. The stability analysis of the closed-loop system is rigorously proven using a Lyapunov approach. The effectiveness of the proposed controller is illustrated by two simulation examples. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Multi-Sensor Detection with Particle Swarm Optimization for Time-Frequency Coded Cooperative WSNs Based on MC-CDMA for Underground Coal Mines

PubMed Central

Xu, Jingjing; Yang, Wei; Zhang, Linyuan; Han, Ruisong; Shao, Xiaotao

2015-01-01

In this paper, a wireless sensor network (WSN) technology adapted to underground channel conditions is developed, which has important theoretical and practical value for safety monitoring in underground coal mines. According to the characteristics that the space, time and frequency resources of underground tunnel are open, it is proposed to constitute wireless sensor nodes based on multicarrier code division multiple access (MC-CDMA) to make full use of these resources. To improve the wireless transmission performance of source sensor nodes, it is also proposed to utilize cooperative sensors with good channel conditions from the sink node to assist source sensors with poor channel conditions. Moreover, the total power of the source sensor and its cooperative sensors is allocated on the basis of their channel conditions to increase the energy efficiency of the WSN. To solve the problem that multiple access interference (MAI) arises when multiple source sensors transmit monitoring information simultaneously, a kind of multi-sensor detection (MSD) algorithm with particle swarm optimization (PSO), namely D-PSO, is proposed for the time-frequency coded cooperative MC-CDMA WSN. Simulation results show that the average bit error rate (BER) performance of the proposed WSN in an underground coal mine is improved significantly by using wireless sensor nodes based on MC-CDMA, adopting time-frequency coded cooperative transmission and D-PSO algorithm with particle swarm optimization. PMID:26343660

Multi-Sensor Detection with Particle Swarm Optimization for Time-Frequency Coded Cooperative WSNs Based on MC-CDMA for Underground Coal Mines.

PubMed

Xu, Jingjing; Yang, Wei; Zhang, Linyuan; Han, Ruisong; Shao, Xiaotao

2015-08-27

In this paper, a wireless sensor network (WSN) technology adapted to underground channel conditions is developed, which has important theoretical and practical value for safety monitoring in underground coal mines. According to the characteristics that the space, time and frequency resources of underground tunnel are open, it is proposed to constitute wireless sensor nodes based on multicarrier code division multiple access (MC-CDMA) to make full use of these resources. To improve the wireless transmission performance of source sensor nodes, it is also proposed to utilize cooperative sensors with good channel conditions from the sink node to assist source sensors with poor channel conditions. Moreover, the total power of the source sensor and its cooperative sensors is allocated on the basis of their channel conditions to increase the energy efficiency of the WSN. To solve the problem that multiple access interference (MAI) arises when multiple source sensors transmit monitoring information simultaneously, a kind of multi-sensor detection (MSD) algorithm with particle swarm optimization (PSO), namely D-PSO, is proposed for the time-frequency coded cooperative MC-CDMA WSN. Simulation results show that the average bit error rate (BER) performance of the proposed WSN in an underground coal mine is improved significantly by using wireless sensor nodes based on MC-CDMA, adopting time-frequency coded cooperative transmission and D-PSO algorithm with particle swarm optimization.

Sensor fusion and augmented reality with the SAFIRE system

NASA Astrophysics Data System (ADS)

Saponaro, Philip; Treible, Wayne; Phelan, Brian; Sherbondy, Kelly; Kambhamettu, Chandra

2018-04-01

The Spectrally Agile Frequency-Incrementing Reconfigurable (SAFIRE) mobile radar system was developed and exercised at an arid U.S. test site. The system can detect hidden target using radar, a global positioning system (GPS), dual stereo color cameras, and dual stereo thermal cameras. An Augmented Reality (AR) software interface allows the user to see a single fused video stream containing the SAR, color, and thermal imagery. The stereo sensors allow the AR system to display both fused 2D imagery and 3D metric reconstructions, where the user can "fly" around the 3D model and switch between the modalities.

Considerations for multiple hypothesis correlation on tactical platforms

NASA Astrophysics Data System (ADS)

Thomas, Alan M.; Turpen, James E.

2013-05-01

Tactical platforms benefit greatly from the fusion of tracks from multiple sources in terms of increased situation awareness. As a necessary precursor to this track fusion, track-to-track association, or correlation, must first be performed. The related measurement-to-track fusion problem has been well studied with multiple hypothesis tracking and multiple frame assignment methods showing the most success. The track-to-track problem differs from this one in that measurements themselves are not available but rather track state update reports from the measuring sensors. Multiple hypothesis, multiple frame correlation systems have previously been considered; however, their practical implementation under the constraints imposed by tactical platforms is daunting. The situation is further exacerbated by the inconvenient nature of reports from legacy sensor systems on bandwidth- limited communications networks. In this paper, consideration is given to the special difficulties encountered when attempting the correlation of tracks from legacy sensors on tactical aircraft. Those difficulties include the following: covariance information from reporting sensors is frequently absent or incomplete; system latencies can create temporal uncertainty in data; and computational processing is severely limited by hardware and architecture. Moreover, consideration is given to practical solutions for dealing with these problems in a multiple hypothesis correlator.

An Authentication Protocol for Future Sensor Networks.

PubMed

Bilal, Muhammad; Kang, Shin-Gak

2017-04-28

Authentication is one of the essential security services in Wireless Sensor Networks (WSNs) for ensuring secure data sessions. Sensor node authentication ensures the confidentiality and validity of data collected by the sensor node, whereas user authentication guarantees that only legitimate users can access the sensor data. In a mobile WSN, sensor and user nodes move across the network and exchange data with multiple nodes, thus experiencing the authentication process multiple times. The integration of WSNs with Internet of Things (IoT) brings forth a new kind of WSN architecture along with stricter security requirements; for instance, a sensor node or a user node may need to establish multiple concurrent secure data sessions. With concurrent data sessions, the frequency of the re-authentication process increases in proportion to the number of concurrent connections. Moreover, to establish multiple data sessions, it is essential that a protocol participant have the capability of running multiple instances of the protocol run, which makes the security issue even more challenging. The currently available authentication protocols were designed for the autonomous WSN and do not account for the above requirements. Hence, ensuring a lightweight and efficient authentication protocol has become more crucial. In this paper, we present a novel, lightweight and efficient key exchange and authentication protocol suite called the Secure Mobile Sensor Network (SMSN) Authentication Protocol. In the SMSN a mobile node goes through an initial authentication procedure and receives a re-authentication ticket from the base station. Later a mobile node can use this re-authentication ticket when establishing multiple data exchange sessions and/or when moving across the network. This scheme reduces the communication and computational complexity of the authentication process. We proved the strength of our protocol with rigorous security analysis (including formal analysis using the BAN-logic) and simulated the SMSN and previously proposed schemes in an automated protocol verifier tool. Finally, we compared the computational complexity and communication cost against well-known authentication protocols.

An Authentication Protocol for Future Sensor Networks

PubMed Central

Bilal, Muhammad; Kang, Shin-Gak

2017-01-01

Authentication is one of the essential security services in Wireless Sensor Networks (WSNs) for ensuring secure data sessions. Sensor node authentication ensures the confidentiality and validity of data collected by the sensor node, whereas user authentication guarantees that only legitimate users can access the sensor data. In a mobile WSN, sensor and user nodes move across the network and exchange data with multiple nodes, thus experiencing the authentication process multiple times. The integration of WSNs with Internet of Things (IoT) brings forth a new kind of WSN architecture along with stricter security requirements; for instance, a sensor node or a user node may need to establish multiple concurrent secure data sessions. With concurrent data sessions, the frequency of the re-authentication process increases in proportion to the number of concurrent connections. Moreover, to establish multiple data sessions, it is essential that a protocol participant have the capability of running multiple instances of the protocol run, which makes the security issue even more challenging. The currently available authentication protocols were designed for the autonomous WSN and do not account for the above requirements. Hence, ensuring a lightweight and efficient authentication protocol has become more crucial. In this paper, we present a novel, lightweight and efficient key exchange and authentication protocol suite called the Secure Mobile Sensor Network (SMSN) Authentication Protocol. In the SMSN a mobile node goes through an initial authentication procedure and receives a re-authentication ticket from the base station. Later a mobile node can use this re-authentication ticket when establishing multiple data exchange sessions and/or when moving across the network. This scheme reduces the communication and computational complexity of the authentication process. We proved the strength of our protocol with rigorous security analysis (including formal analysis using the BAN-logic) and simulated the SMSN and previously proposed schemes in an automated protocol verifier tool. Finally, we compared the computational complexity and communication cost against well-known authentication protocols. PMID:28452937

Simulating Operation of a Complex Sensor Network

NASA Technical Reports Server (NTRS)

Jennings, Esther; Clare, Loren; Woo, Simon

2008-01-01

Simulation Tool for ASCTA Microsensor Network Architecture (STAMiNA) ["ASCTA" denotes the Advanced Sensors Collaborative Technology Alliance.] is a computer program for evaluating conceptual sensor networks deployed over terrain to provide military situational awareness. This or a similar program is needed because of the complexity of interactions among such diverse phenomena as sensing and communication portions of a network, deployment of sensor nodes, effects of terrain, data-fusion algorithms, and threat characteristics. STAMiNA is built upon a commercial network-simulator engine, with extensions to include both sensing and communication models in a discrete-event simulation environment. Users can define (1) a mission environment, including terrain features; (2) objects to be sensed; (3) placements and modalities of sensors, abilities of sensors to sense objects of various types, and sensor false alarm rates; (4) trajectories of threatening objects; (5) means of dissemination and fusion of data; and (6) various network configurations. By use of STAMiNA, one can simulate detection of targets through sensing, dissemination of information by various wireless communication subsystems under various scenarios, and fusion of information, incorporating such metrics as target-detection probabilities, false-alarm rates, and communication loads, and capturing effects of terrain and threat.

Fiber sensor network with multipoint sensing using double-pass hybrid LPFG-FBG sensor configuration

NASA Astrophysics Data System (ADS)

Yong, Yun-Thung; Lee, Sheng-Chyan; Rahman, Faidz Abd

2017-03-01

This is a study on double-pass intensity-based hybrid Long Period Fiber Grating (LPFG)and Fiber Bragg Grating (FBG) sensor configuration where a fiber sensor network was constructed with multiple sensing capability. The sensing principle is based on interrogation of intensity changes of the reflected signal from an FBG caused by the LPFG spectral response to the surrounding perturbations. The sensor network developed was tested in monitoring diesel adulteration of up to a distance of 8 km. Kerosene concentration from 0% to 50% was added as adulterant into diesel. The sensitivity of the double-pass hybrid LPFG-FBG sensor over multiple points was>0.21 dB/% (for adulteration range of 0-30%) and >0.45 dB/% from 30% to 50% adulteration. It is found that the sensitivity can drop up to 35% when the fiber length increased from 0 km to 8 km (for the case of adulteration of 0-30%). With the multiple sensing capabilities, normalized FBG's reflected power can be demodulated at the same time for comparison of sensitivity performance across various fiber sensors.

SU-E-P-10: Imaging in the Cardiac Catheterization Lab - Technologies and Clinical Applications

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

Fetterly, K

2014-06-01

Purpose: Diagnosis and treatment of cardiovascular disease in the cardiac catheterization laboratory is often aided by a multitude of imaging technologies. The purpose of this work is to highlight the contributions to patient care offered by the various imaging systems used during cardiovascular interventional procedures. Methods: Imaging technologies used in the cardiac catheterization lab were characterized by their fundamental technology and by the clinical applications for which they are used. Whether the modality is external to the patient, intravascular, or intracavity was specified. Specific clinical procedures for which multiple modalities are routinely used will be highlighted. Results: X-ray imaging modalitiesmore » include fluoroscopy/angiography and angiography CT. Ultrasound imaging is performed with external, trans-esophageal echocardiography (TEE), and intravascular (IVUS) transducers. Intravascular infrared optical coherence tomography (IVOCT) is used to assess vessel endothelium. Relatively large (>0.5 mm) anatomical structures are imaged with x-ray and ultrasound. IVUS and IVOCT provide high resolution images of vessel walls. Cardiac CT and MRI images are used to plan complex cardiovascular interventions. Advanced applications are used to spatially and temporally merge images from different technologies. Diagnosis and treatment of coronary artery disease frequently utilizes angiography and intra-vascular imaging, and treatment of complex structural heart conditions routinely includes use of multiple imaging modalities. Conclusion: There are several imaging modalities which are routinely used in the cardiac catheterization laboratory to diagnose and treat both coronary artery and structural heart disease. Multiple modalities are frequently used to enhance the quality and safety of procedures. The cardiac catheterization laboratory includes many opportunities for medical physicists to contribute substantially toward advancing patient care.« less

Sensor fusion III: 3-D perception and recognition; Proceedings of the Meeting, Boston, MA, Nov. 5-8, 1990

NASA Technical Reports Server (NTRS)

Schenker, Paul S. (Editor)

1991-01-01

The volume on data fusion from multiple sources discusses fusing multiple views, temporal analysis and 3D motion interpretation, sensor fusion and eye-to-hand coordination, and integration in human shape perception. Attention is given to surface reconstruction, statistical methods in sensor fusion, fusing sensor data with environmental knowledge, computational models for sensor fusion, and evaluation and selection of sensor fusion techniques. Topics addressed include the structure of a scene from two and three projections, optical flow techniques for moving target detection, tactical sensor-based exploration in a robotic environment, and the fusion of human and machine skills for remote robotic operations. Also discussed are K-nearest-neighbor concepts for sensor fusion, surface reconstruction with discontinuities, a sensor-knowledge-command fusion paradigm for man-machine systems, coordinating sensing and local navigation, and terrain map matching using multisensing techniques for applications to autonomous vehicle navigation.

A Novel Sensor System for Measuring Wheel Loads of Vehicles on Highways

PubMed Central

Zhang, Wenbin; Suo, Chunguang; Wang, Qi

2008-01-01

With the development of the highway transportation and business trade, vehicle Weigh-In-Motion (WIM) technology has become a key technology for measuring traffic loads. In this paper a novel WIM system based on monitoring of pavement strain responses in rigid pavement was investigated. In this WIM system multiple low cost, light weight, small volume and high accuracy embedded concrete strain sensors were used as WIM sensors to measure rigid pavement strain responses. In order to verify the feasibility of the method, a system prototype based on multiple sensors was designed and deployed on a relatively busy freeway. Field calibration and tests were performed with known two-axle truck wheel loads and the measurement errors were calculated based on the static weights measured with a static weighbridge. This enables the weights of other vehicles to be calculated from the calibration constant. Calibration and test results for individual sensors or three-sensor fusions are both provided. Repeatability, sources of error, and weight accuracy are discussed. Successful results showed that the proposed method was feasible and proven to have a high accuracy. Furthermore, a sample mean approach using multiple fused individual sensors could provide better performance compared to individual sensors. PMID:27873952

Cooperative UAV-Based Communications Backbone for Sensor Networks

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

Roberts, R S

2001-10-07

The objective of this project is to investigate the use of unmanned air vehicles (UAVs) as mobile, adaptive communications backbones for ground-based sensor networks. In this type of network, the UAVs provide communication connectivity to sensors that cannot communicate with each other because of terrain, distance, or other geographical constraints. In these situations, UAVs provide a vertical communication path for the sensors, thereby mitigating geographic obstacles often imposed on networks. With the proper use of UAVs, connectivity to a widely disbursed sensor network in rugged terrain is readily achieved. Our investigation has focused on networks where multiple cooperating UAVs aremore » used to form a network backbone. The advantage of using multiple UAVs to form the network backbone is parallelization of sensor connectivity. Many widely spaced or isolated sensors can be connected to the network at once using this approach. In these networks, the UAVs logically partition the sensor network into sub-networks (subnets), with one UAV assigned per subnet. Partitioning the network into subnets allows the UAVs to service sensors in parallel thereby decreasing the sensor-to-network connectivity. A UAV services sensors in its subnet by flying a route (path) through the subnet, uplinking data collected by the sensors, and forwarding the data to a ground station. An additional advantage of using multiple UAVs in the network is that they provide redundancy in the communications backbone, so that the failure of a single UAV does not necessarily imply the loss of the network.« less

Quantifying and managing uncertainty in operational modal analysis

NASA Astrophysics Data System (ADS)

Au, Siu-Kui; Brownjohn, James M. W.; Mottershead, John E.

2018-03-01

Operational modal analysis aims at identifying the modal properties (natural frequency, damping, etc.) of a structure using only the (output) vibration response measured under ambient conditions. Highly economical and feasible, it is becoming a common practice in full-scale vibration testing. In the absence of (input) loading information, however, the modal properties have significantly higher uncertainty than their counterparts identified from free or forced vibration (known input) tests. Mastering the relationship between identification uncertainty and test configuration is of great interest to both scientists and engineers, e.g., for achievable precision limits and test planning/budgeting. Addressing this challenge beyond the current state-of-the-art that are mostly concerned with identification algorithms, this work obtains closed form analytical expressions for the identification uncertainty (variance) of modal parameters that fundamentally explains the effect of test configuration. Collectively referred as 'uncertainty laws', these expressions are asymptotically correct for well-separated modes, small damping and long data; and are applicable under non-asymptotic situations. They provide a scientific basis for planning and standardization of ambient vibration tests, where factors such as channel noise, sensor number and location can be quantitatively accounted for. The work is reported comprehensively with verification through synthetic and experimental data (laboratory and field), scientific implications and practical guidelines for planning ambient vibration tests.

High-Temperature Modal Survey of a Hot-Structure Control Surface

NASA Technical Reports Server (NTRS)

Spivey, Natalie D.

2011-01-01

Ground vibration tests are routinely conducted for supporting flutter analysis for subsonic and supersonic vehicles; however, for hypersonic vehicles, thermoelastic vibration testing techniques are neither well established nor routinely performed. New high-temperature material systems, fabrication technologies and high-temperature sensors expand the opportunities to develop advanced techniques for performing ground vibration tests at elevated temperatures. When high-temperature materials, which increase in stiffness when heated, are incorporated into a hot-structure that contains metallic components that decrease in stiffness when heated, the interaction between those materials can affect the hypersonic flutter analysis. A high-temperature modal survey will expand the research database for hypersonics and improve the understanding of this dual-material interaction. This report discusses the vibration testing of the carbon-silicon carbide Ruddervator Subcomponent Test Article, which is a truncated version of a full-scale hot-structure control surface. Two series of room-temperature modal test configurations were performed in order to define the modal characteristics of the test article during the elevated-temperature modal survey: one with the test article suspended from a bungee cord (free-free) and the second with it mounted on the strongback (fixed boundary). Testing was performed in the NASA Dryden Flight Research Center Flight Loads Laboratory Large Nitrogen Test Chamber.

Music to My Eyes: Cross-Modal Interactions in the Perception of Emotions in Musical Performance

ERIC Educational Resources Information Center

Vines, Bradley W.; Krumhansl, Carol L.; Wanderley, Marcelo M.; Dalca, Ioana M.; Levitin, Daniel J.

2011-01-01

We investigate non-verbal communication through expressive body movement and musical sound, to reveal higher cognitive processes involved in the integration of emotion from multiple sensory modalities. Participants heard, saw, or both heard and saw recordings of a Stravinsky solo clarinet piece, performed with three distinct expressive styles:…

Two Modalities of the Contextualized Courseware in Three Modalities of Classroom Use

ERIC Educational Resources Information Center

Akpinar, Yavuz; Sengül, Özlem

2018-01-01

This study investigated the effect of various combinations of contextualization and teacher support on achievement and critical thinking. Two specially-designed sets of courseware were used to teach a unit on logic, one based on a single context and one based on multiple contexts. The participants were 151 9th graders in two vocational high…

Label-aligned Multi-task Feature Learning for Multimodal Classification of Alzheimer’s Disease and Mild Cognitive Impairment

PubMed Central

Zu, Chen; Jie, Biao; Liu, Mingxia; Chen, Songcan

2015-01-01

Multimodal classification methods using different modalities of imaging and non-imaging data have recently shown great advantages over traditional single-modality-based ones for diagnosis and prognosis of Alzheimer’s disease (AD), as well as its prodromal stage, i.e., mild cognitive impairment (MCI). However, to the best of our knowledge, most existing methods focus on mining the relationship across multiple modalities of the same subjects, while ignoring the potentially useful relationship across different subjects. Accordingly, in this paper, we propose a novel learning method for multimodal classification of AD/MCI, by fully exploring the relationships across both modalities and subjects. Specifically, our proposed method includes two subsequent components, i.e., label-aligned multi-task feature selection and multimodal classification. In the first step, the feature selection learning from multiple modalities are treated as different learning tasks and a group sparsity regularizer is imposed to jointly select a subset of relevant features. Furthermore, to utilize the discriminative information among labeled subjects, a new label-aligned regularization term is added into the objective function of standard multi-task feature selection, where label-alignment means that all multi-modality subjects with the same class labels should be closer in the new feature-reduced space. In the second step, a multi-kernel support vector machine (SVM) is adopted to fuse the selected features from multi-modality data for final classification. To validate our method, we perform experiments on the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database using baseline MRI and FDG-PET imaging data. The experimental results demonstrate that our proposed method achieves better classification performance compared with several state-of-the-art methods for multimodal classification of AD/MCI. PMID:26572145

Three-way parallel independent component analysis for imaging genetics using multi-objective optimization.

PubMed

Ulloa, Alvaro; Jingyu Liu; Vergara, Victor; Jiayu Chen; Calhoun, Vince; Pattichis, Marios

2014-01-01

In the biomedical field, current technology allows for the collection of multiple data modalities from the same subject. In consequence, there is an increasing interest for methods to analyze multi-modal data sets. Methods based on independent component analysis have proven to be effective in jointly analyzing multiple modalities, including brain imaging and genetic data. This paper describes a new algorithm, three-way parallel independent component analysis (3pICA), for jointly identifying genomic loci associated with brain function and structure. The proposed algorithm relies on the use of multi-objective optimization methods to identify correlations among the modalities and maximally independent sources within modality. We test the robustness of the proposed approach by varying the effect size, cross-modality correlation, noise level, and dimensionality of the data. Simulation results suggest that 3p-ICA is robust to data with SNR levels from 0 to 10 dB and effect-sizes from 0 to 3, while presenting its best performance with high cross-modality correlations, and more than one subject per 1,000 variables. In an experimental study with 112 human subjects, the method identified links between a genetic component (pointing to brain function and mental disorder associated genes, including PPP3CC, KCNQ5, and CYP7B1), a functional component related to signal decreases in the default mode network during the task, and a brain structure component indicating increases of gray matter in brain regions of the default mode region. Although such findings need further replication, the simulation and in-vivo results validate the three-way parallel ICA algorithm presented here as a useful tool in biomedical data decomposition applications.

Multimodal Imaging of the Normal Eye.

PubMed

Kawali, Ankush; Pichi, Francesco; Avadhani, Kavitha; Invernizzi, Alessandro; Hashimoto, Yuki; Mahendradas, Padmamalini

2017-10-01

Multimodal imaging is the concept of "bundling" images obtained from various imaging modalities, viz., fundus photograph, fundus autofluorescence imaging, infrared (IR) imaging, simultaneous fluorescein and indocyanine angiography, optical coherence tomography (OCT), and, more recently, OCT angiography. Each modality has its pros and cons as well as its limitations. Combination of multiple imaging techniques will overcome their individual weaknesses and give a comprehensive picture. Such approach helps in accurate localization of a lesion and understanding the pathology in posterior segment. It is important to know imaging of normal eye before one starts evaluating pathology. This article describes multimodal imaging modalities in detail and discusses healthy eye features as seen on various imaging modalities mentioned above.

Reward maximization justifies the transition from sensory selection at childhood to sensory integration at adulthood.

PubMed

Daee, Pedram; Mirian, Maryam S; Ahmadabadi, Majid Nili

2014-01-01

In a multisensory task, human adults integrate information from different sensory modalities--behaviorally in an optimal Bayesian fashion--while children mostly rely on a single sensor modality for decision making. The reason behind this change of behavior over age and the process behind learning the required statistics for optimal integration are still unclear and have not been justified by the conventional Bayesian modeling. We propose an interactive multisensory learning framework without making any prior assumptions about the sensory models. In this framework, learning in every modality and in their joint space is done in parallel using a single-step reinforcement learning method. A simple statistical test on confidence intervals on the mean of reward distributions is used to select the most informative source of information among the individual modalities and the joint space. Analyses of the method and the simulation results on a multimodal localization task show that the learning system autonomously starts with sensory selection and gradually switches to sensory integration. This is because, relying more on modalities--i.e. selection--at early learning steps (childhood) is more rewarding than favoring decisions learned in the joint space since, smaller state-space in modalities results in faster learning in every individual modality. In contrast, after gaining sufficient experiences (adulthood), the quality of learning in the joint space matures while learning in modalities suffers from insufficient accuracy due to perceptual aliasing. It results in tighter confidence interval for the joint space and consequently causes a smooth shift from selection to integration. It suggests that sensory selection and integration are emergent behavior and both are outputs of a single reward maximization process; i.e. the transition is not a preprogrammed phenomenon.

Estimating free-body modal parameters from tests of a constrained structure

NASA Technical Reports Server (NTRS)

Cooley, Victor M.

1993-01-01

Hardware advances in suspension technology for ground tests of large space structures provide near on-orbit boundary conditions for modal testing. Further advances in determining free-body modal properties of constrained large space structures have been made, on the analysis side, by using time domain parameter estimation and perturbing the stiffness of the constraints over multiple sub-tests. In this manner, passive suspension constraint forces, which are fully correlated and therefore not usable for spectral averaging techniques, are made effectively uncorrelated. The technique is demonstrated with simulated test data.

Use of external cavity quantum cascade laser compliance voltage in real-time trace gas sensing of multiple chemicals

NASA Astrophysics Data System (ADS)

Phillips, Mark C.; Taubman, Matthew S.; Kriesel, Jason

2015-01-01

We describe a prototype trace gas sensor designed for real-time detection of multiple chemicals. The sensor uses an external cavity quantum cascade laser (ECQCL) swept over its tuning range of 940-1075 cm-1 (9.30-10.7 μm) at a 10 Hz repetition rate. The sensor was designed for operation in multiple modes, including gas sensing within a multi-pass Heriott cell and intracavity absorption sensing using the ECQCL compliance voltage. In addition, the ECQCL compliance voltage was used to reduce effects of long-term drifts in the ECQCL output power. The sensor was characterized for noise, drift, and detection of chemicals including ammonia, methanol, ethanol, isopropanol, Freon- 134a, Freon-152a, and diisopropyl methylphosphonate (DIMP). We also present use of the sensor for mobile detection of ammonia downwind of cattle facilities, in which concentrations were recorded at 1-s intervals.

Multiple-modality exercise and mind-motor training to improve mobility in older adults: A randomized controlled trial.

PubMed

Boa Sorte Silva, Narlon C; Gill, Dawn P; Gregory, Michael A; Bocti, John; Petrella, Robert J

2018-03-01

To investigate the effects of multiple-modality exercise with or without additional mind-motor training on mobility outcomes in older adults with subjective cognitive complaints. This was a 24-week randomized controlled trial with a 28-week no-contact follow-up. Community-dwelling older adults underwent a thrice -weekly, Multiple-Modality exercise and Mind-Motor (M4) training or Multiple-Modality (M2) exercise with an active control intervention (balance, range of motion and breathing exercises). Study outcomes included differences between groups at 24weeks and after the no-contact follow-up (i.e., 52weeks) in usual and dual-task (DT, i.e., serial sevens [S7] and phonemic verbal fluency [VF] tasks) gait velocity, step length and cycle time variability, as well as DT cognitive accuracy. 127 participants (mean age 67.5 [7.3] years, 71% women) were randomized to either M2 (n=64) or M4 (n=63) groups. Participants were assessed at baseline, intervention endpoint (24weeks), and study endpoint (52weeks). At 24weeks, the M2 group demonstrated greater improvements in usual gait velocity, usual step length, and DT gait velocity (VF) compared to the M4 group, and no between- or within-group changes in DT accuracy were observed. At 52weeks, the M2 group retained the gains in gait velocity and step length, whereas the M4 group demonstrated trends for improvement (p=0.052) in DT cognitive accuracy (VF). Our results suggest that additional mind-motor training was not effective to improve mobility outcomes. In fact, participants in the active control group experienced greater benefits as a result of the intervention. Copyright © 2017 Elsevier Inc. All rights reserved.

Multi-modal data fusion using source separation: Two effective models based on ICA and IVA and their properties

PubMed Central

Adali, Tülay; Levin-Schwartz, Yuri; Calhoun, Vince D.

2015-01-01

Fusion of information from multiple sets of data in order to extract a set of features that are most useful and relevant for the given task is inherent to many problems we deal with today. Since, usually, very little is known about the actual interaction among the datasets, it is highly desirable to minimize the underlying assumptions. This has been the main reason for the growing importance of data-driven methods, and in particular of independent component analysis (ICA) as it provides useful decompositions with a simple generative model and using only the assumption of statistical independence. A recent extension of ICA, independent vector analysis (IVA) generalizes ICA to multiple datasets by exploiting the statistical dependence across the datasets, and hence, as we discuss in this paper, provides an attractive solution to fusion of data from multiple datasets along with ICA. In this paper, we focus on two multivariate solutions for multi-modal data fusion that let multiple modalities fully interact for the estimation of underlying features that jointly report on all modalities. One solution is the Joint ICA model that has found wide application in medical imaging, and the second one is the the Transposed IVA model introduced here as a generalization of an approach based on multi-set canonical correlation analysis. In the discussion, we emphasize the role of diversity in the decompositions achieved by these two models, present their properties and implementation details to enable the user make informed decisions on the selection of a model along with its associated parameters. Discussions are supported by simulation results to help highlight the main issues in the implementation of these methods. PMID:26525830

Method and apparatus for measuring surface changes, in porous materials, using multiple differently-configured acoustic sensors

DOEpatents

Hietala, Susan Leslie; Hietala, Vincent Mark; Tigges, Chris Phillip

2001-01-01

A method and apparatus for measuring surface changes, such as mass uptake at various pressures, in a thin-film material, in particular porous membranes, using multiple differently-configured acoustic sensors.

Steam distribution and energy delivery optimization using wireless sensors

NASA Astrophysics Data System (ADS)

Olama, Mohammed M.; Allgood, Glenn O.; Kuruganti, Teja P.; Sukumar, Sreenivas R.; Djouadi, Seddik M.; Lake, Joe E.

2011-05-01

The Extreme Measurement Communications Center at Oak Ridge National Laboratory (ORNL) explores the deployment of a wireless sensor system with a real-time measurement-based energy efficiency optimization framework in the ORNL campus. With particular focus on the 12-mile long steam distribution network in our campus, we propose an integrated system-level approach to optimize the energy delivery within the steam distribution system. We address the goal of achieving significant energy-saving in steam lines by monitoring and acting on leaking steam valves/traps. Our approach leverages an integrated wireless sensor and real-time monitoring capabilities. We make assessments on the real-time status of the distribution system by mounting acoustic sensors on the steam pipes/traps/valves and observe the state measurements of these sensors. Our assessments are based on analysis of the wireless sensor measurements. We describe Fourier-spectrum based algorithms that interpret acoustic vibration sensor data to characterize flows and classify the steam system status. We are able to present the sensor readings, steam flow, steam trap status and the assessed alerts as an interactive overlay within a web-based Google Earth geographic platform that enables decision makers to take remedial action. We believe our demonstration serves as an instantiation of a platform that extends implementation to include newer modalities to manage water flow, sewage and energy consumption.

An Extrinsic Fabry-Perot Interferometric Sensor using Intermodal Phase Shifting and Demultiplexing of the Propagating Modes in a Few-Mode Fiber

NASA Astrophysics Data System (ADS)

Chatterjee, Julius

This dissertation demonstrates a fiber-optic phase shifted Fabry-Perot interferometer (PS-FPI) as a sensor using modal demultiplexing. Single wavelength Fabry-Perot interferometers suffer from fringe ambiguity and loss of sensitivity at fringe extremes. These hindrances cause it to be a secondary choice when being selected for a measurement task at hand, and more often than not, white light based sensors are selected in favor of the single wavelength Fabry-Perot sensors. This work aims to introduce a technique involving the demultiplexing of the propagating linearly polarized (LP) modes in few mode fibers to obtain two fringe systems from the same sensing cavity. This results in a few-mode interferometer that effectively has two to three orders of magnitude higher perturbation sensitivity than a conventional few mode interferometer for the same sensing region. In this work, two different modal demultiplexing techniques (MD) are used to demodulate the propagating modes and to obtain two fringe sets. These output fringe sets are shifted in phase with respect to each other by a phase shift due to the propagation of the modes in the fiber-optic layout. A method of controlling this phase shift by straining a length of a two mode fiber located separate from the PS-FPI cavity is demonstrated and corresponding changes in phase shifts are shown. The results show a controllable phase shift for both the MD techniques, which is useful in sensing by permitting quadrature demodulation of interferometric fringes and also results in a novel few-mode sensing system having more than two orders of magnitude sensitivity than conventional few-mode devices.

Theory of the control of structures by low authority controllers

NASA Technical Reports Server (NTRS)

Aubrun, J. N.

1978-01-01

The novel idea presented is based on the observation that if a structure is controlled by distributed systems of sensors and actuators with limited authority, i.e., if the controller is allowed to modify only moderately the natural modes and frequencies of the structure, then it should be possible to apply root perturbation techniques to predict analytically the behavior of the total system. Attention is given to the root perturbation formula first derived by Jacobi for infinitesimal perturbations which neglect the induced eigenvector perturbation, a more general form of Jacobi's formula, first-order structural equations and modal state vectors, state-space equations for damper-augmented structures, and modal damping prediction formulas.

Air Force and Army Corps of Engineers Improperly Managed the Award of Contracts for the Blue Devil Block 2 Persistent Surveillance System

DTIC Science & Technology

2013-09-19

environments. This can include the development of new and/or improved analytical and numerical models, rapid data-processing techniques, and new subsurface ... imaging techniques that include active and passive sensor modalities in a variety of rural and urban terrains. Of particular interest is the broadband

Accurate Sample Time Reconstruction of Inertial FIFO Data.

PubMed

Stieber, Sebastian; Dorsch, Rainer; Haubelt, Christian

2017-12-13

In the context of modern cyber-physical systems, the accuracy of underlying sensor data plays an increasingly important role in sensor data fusion and feature extraction. The raw events of multiple sensors have to be aligned in time to enable high quality sensor fusion results. However, the growing number of simultaneously connected sensor devices make the energy saving data acquisition and processing more and more difficult. Hence, most of the modern sensors offer a first-in-first-out (FIFO) interface to store multiple data samples and to relax timing constraints, when handling multiple sensor devices. However, using the FIFO interface increases the negative influence of individual clock drifts-introduced by fabrication inaccuracies, temperature changes and wear-out effects-onto the sampling data reconstruction. Furthermore, additional timing offset errors due to communication and software latencies increases with a growing number of sensor devices. In this article, we present an approach for an accurate sample time reconstruction independent of the actual clock drift with the help of an internal sensor timer. Such timers are already available in modern sensors, manufactured in micro-electromechanical systems (MEMS) technology. The presented approach focuses on calculating accurate time stamps using the sensor FIFO interface in a forward-only processing manner as a robust and energy saving solution. The proposed algorithm is able to lower the overall standard deviation of reconstructed sampling periods below 40 μ s, while run-time savings of up to 42% are achieved, compared to single sample acquisition.

Multiple channel optical data acquisition system

DOEpatents

Fasching, G.E.; Goff, D.R.

1985-02-22

A multiple channel optical data acquisition system is provided in which a plurality of remote sensors monitoring specific process variable are interrogated by means of a single optical fiber connecting the remote station/sensors to a base station. The remote station/sensors derive all power from light transmitted through the fiber from the base station. Each station/sensor is individually accessed by means of a light modulated address code sent over the fiber. The remote station/sensors use a single light emitting diode to both send and receive light signals to communicate with the base station and provide power for the remote station. The system described can power at least 100 remote station/sensors over an optical fiber one mile in length.

Optimal Sensor Allocation for Fault Detection and Isolation

NASA Technical Reports Server (NTRS)

Azam, Mohammad; Pattipati, Krishna; Patterson-Hine, Ann

2004-01-01

Automatic fault diagnostic schemes rely on various types of sensors (e.g., temperature, pressure, vibration, etc) to measure the system parameters. Efficacy of a diagnostic scheme is largely dependent on the amount and quality of information available from these sensors. The reliability of sensors, as well as the weight, volume, power, and cost constraints, often makes it impractical to monitor a large number of system parameters. An optimized sensor allocation that maximizes the fault diagnosibility, subject to specified weight, volume, power, and cost constraints is required. Use of optimal sensor allocation strategies during the design phase can ensure better diagnostics at a reduced cost for a system incorporating a high degree of built-in testing. In this paper, we propose an approach that employs multiple fault diagnosis (MFD) and optimization techniques for optimal sensor placement for fault detection and isolation (FDI) in complex systems. Keywords: sensor allocation, multiple fault diagnosis, Lagrangian relaxation, approximate belief revision, multidimensional knapsack problem.

Convergent and invariant object representations for sight, sound, and touch.

PubMed

Man, Kingson; Damasio, Antonio; Meyer, Kaspar; Kaplan, Jonas T

2015-09-01

We continuously perceive objects in the world through multiple sensory channels. In this study, we investigated the convergence of information from different sensory streams within the cerebral cortex. We presented volunteers with three common objects via three different modalities-sight, sound, and touch-and used multivariate pattern analysis of functional magnetic resonance imaging data to map the cortical regions containing information about the identity of the objects. We could reliably predict which of the three stimuli a subject had seen, heard, or touched from the pattern of neural activity in the corresponding early sensory cortices. Intramodal classification was also successful in large portions of the cerebral cortex beyond the primary areas, with multiple regions showing convergence of information from two or all three modalities. Using crossmodal classification, we also searched for brain regions that would represent objects in a similar fashion across different modalities of presentation. We trained a classifier to distinguish objects presented in one modality and then tested it on the same objects presented in a different modality. We detected audiovisual invariance in the right temporo-occipital junction, audiotactile invariance in the left postcentral gyrus and parietal operculum, and visuotactile invariance in the right postcentral and supramarginal gyri. Our maps of multisensory convergence and crossmodal generalization reveal the underlying organization of the association cortices, and may be related to the neural basis for mental concepts. © 2015 Wiley Periodicals, Inc.

Multi-Modal Curriculum Learning for Semi-Supervised Image Classification.

PubMed

Gong, Chen; Tao, Dacheng; Maybank, Stephen J; Liu, Wei; Kang, Guoliang; Yang, Jie

2016-07-01

Semi-supervised image classification aims to classify a large quantity of unlabeled images by typically harnessing scarce labeled images. Existing semi-supervised methods often suffer from inadequate classification accuracy when encountering difficult yet critical images, such as outliers, because they treat all unlabeled images equally and conduct classifications in an imperfectly ordered sequence. In this paper, we employ the curriculum learning methodology by investigating the difficulty of classifying every unlabeled image. The reliability and the discriminability of these unlabeled images are particularly investigated for evaluating their difficulty. As a result, an optimized image sequence is generated during the iterative propagations, and the unlabeled images are logically classified from simple to difficult. Furthermore, since images are usually characterized by multiple visual feature descriptors, we associate each kind of features with a teacher, and design a multi-modal curriculum learning (MMCL) strategy to integrate the information from different feature modalities. In each propagation, each teacher analyzes the difficulties of the currently unlabeled images from its own modality viewpoint. A consensus is subsequently reached among all the teachers, determining the currently simplest images (i.e., a curriculum), which are to be reliably classified by the multi-modal learner. This well-organized propagation process leveraging multiple teachers and one learner enables our MMCL to outperform five state-of-the-art methods on eight popular image data sets.

High-Temperature Modal Survey of a Hot-Structure Control Surface

NASA Technical Reports Server (NTRS)

Spivey, Natalie Dawn

2010-01-01

Ground vibration tests or modal surveys are routinely conducted for supporting flutter analysis for subsonic and supersonic vehicles; however, for hypersonic vehicle applications, thermoelastic vibration testing techniques are not well established and are not routinely performed for supporting hypersonic flutter analysis. New high-temperature material systems, fabrication technologies and high-temperature sensors expand the opportunities to develop advanced techniques for performing ground vibration tests at elevated temperatures. High-temperature materials have the unique property of increasing in stiffness when heated. When these materials are incorporated into a hot-structure, which includes metallic components that decrease in stiffness with increasing temperature, the interaction between the two materials systems needs to be understood because that interaction could ultimately affect the hypersonic flutter analysis. Performing a high-temperature modal survey will expand the research database for hypersonics and will help build upon the understanding of the dual material interaction. This paper will discuss the vibration testing of the Carbon-Silicon Carbide Ruddervator Subcomponent Test Article which is a truncated version of the full-scale X-37 hot-structure control surface. In order to define the modal characteristics of the test article during the elevated-temperature modal survey, two series of room-temperature modal test configurations had to be performed. The room-temperature test series included one with the test article suspended from a bungee cord (free-free) and the second with it mounted on the strongback (fixed boundary condition) in NASA Dryden's Flight Loads Lab large nitrogen test chamber.

Algorithms exploiting ultrasonic sensors for subject classification

NASA Astrophysics Data System (ADS)

Desai, Sachi; Quoraishee, Shafik

2009-09-01

Proposed here is a series of techniques exploiting micro-Doppler ultrasonic sensors capable of characterizing various detected mammalian targets based on their physiological movements captured a series of robust features. Employed is a combination of unique and conventional digital signal processing techniques arranged in such a manner they become capable of classifying a series of walkers. These processes for feature extraction develops a robust feature space capable of providing discrimination of various movements generated from bipeds and quadrupeds and further subdivided into large or small. These movements can be exploited to provide specific information of a given signature dividing it in a series of subset signatures exploiting wavelets to generate start/stop times. After viewing a series spectrograms of the signature we are able to see distinct differences and utilizing kurtosis, we generate an envelope detector capable of isolating each of the corresponding step cycles generated during a walk. The walk cycle is defined as one complete sequence of walking/running from the foot pushing off the ground and concluding when returning to the ground. This time information segments the events that are readily seen in the spectrogram but obstructed in the temporal domain into individual walk sequences. This walking sequence is then subsequently translated into a three dimensional waterfall plot defining the expected energy value associated with the motion at particular instance of time and frequency. The value is capable of being repeatable for each particular class and employable to discriminate the events. Highly reliable classification is realized exploiting a classifier trained on a candidate sample space derived from the associated gyrations created by motion from actors of interest. The classifier developed herein provides a capability to classify events as an adult humans, children humans, horses, and dogs at potentially high rates based on the tested sample space. The algorithm developed and described will provide utility to an underused sensor modality for human intrusion detection because of the current high-rate of generated false alarms. The active ultrasonic sensor coupled in a multi-modal sensor suite with binary, less descriptive sensors like seismic devices realizing a greater accuracy rate for detection of persons of interest for homeland purposes.

Shapes, scents and sounds: quantifying the full multi-sensory basis of conceptual knowledge.

PubMed

Hoffman, Paul; Lambon Ralph, Matthew A

2013-01-01

Contemporary neuroscience theories assume that concepts are formed through experience in multiple sensory-motor modalities. Quantifying the contribution of each modality to different object categories is critical to understanding the structure of the conceptual system and to explaining category-specific knowledge deficits. Verbal feature listing is typically used to elicit this information but has a number of drawbacks: sensory knowledge often cannot easily be translated into verbal features and many features are experienced in multiple modalities. Here, we employed a more direct approach in which subjects rated their knowledge of objects in each sensory-motor modality separately. Compared with these ratings, feature listing over-estimated the importance of visual form and functional knowledge and under-estimated the contributions of other sensory channels. An item's sensory rating proved to be a better predictor of lexical-semantic processing speed than the number of features it possessed, suggesting that ratings better capture the overall quantity of sensory information associated with a concept. Finally, the richer, multi-modal rating data not only replicated the sensory-functional distinction between animals and non-living things but also revealed novel distinctions between different types of artefact. Hierarchical cluster analyses indicated that mechanical devices (e.g., vehicles) were distinct from other non-living objects because they had strong sound and motion characteristics, making them more similar to animals in this respect. Taken together, the ratings align with neuroscience evidence in suggesting that a number of distinct sensory processing channels make important contributions to object knowledge. Multi-modal ratings for 160 objects are provided as supplementary materials. Copyright © 2012 Elsevier Ltd. All rights reserved.

Multi-Modal Surrogates for Retrieving and Making Sense of Videos: Is Synchronization between the Multiple Modalities Optimal?

ERIC Educational Resources Information Center

Song, Yaxiao

2010-01-01

Video surrogates can help people quickly make sense of the content of a video before downloading or seeking more detailed information. Visual and audio features of a video are primary information carriers and might become important components of video retrieval and video sense-making. In the past decades, most research and development efforts on…

Feature-based fusion of medical imaging data.

PubMed

Calhoun, Vince D; Adali, Tülay

2009-09-01

The acquisition of multiple brain imaging types for a given study is a very common practice. There have been a number of approaches proposed for combining or fusing multitask or multimodal information. These can be roughly divided into those that attempt to study convergence of multimodal imaging, for example, how function and structure are related in the same region of the brain, and those that attempt to study the complementary nature of modalities, for example, utilizing temporal EEG information and spatial functional magnetic resonance imaging information. Within each of these categories, one can attempt data integration (the use of one imaging modality to improve the results of another) or true data fusion (in which multiple modalities are utilized to inform one another). We review both approaches and present a recent computational approach that first preprocesses the data to compute features of interest. The features are then analyzed in a multivariate manner using independent component analysis. We describe the approach in detail and provide examples of how it has been used for different fusion tasks. We also propose a method for selecting which combination of modalities provides the greatest value in discriminating groups. Finally, we summarize and describe future research topics.

Interferometric biosensing platform for multiplexed digital detection of viral pathogens and biomarkers

NASA Astrophysics Data System (ADS)

Daaboul, George

Label-free optical biosensors have been established as proven tools for monitoring specific biomolecular interactions. However, compact and robust embodiments of such instruments have yet to be introduced in order to provide sensitive, quantitative, and high-throughput biosensing for low-cost research and clinical applications. Here we present the interferometric reflectance-imaging sensor (IRIS). IRIS allows sensitive label free analysis using an inexpensive and durable multi-color LED illumination source on a silicon based surface. IRIS monitors biomolecular interaction through measurement of biomass addition to the sensor's surface. We demonstrate the capability of this system to dynamically monitor antigen---antibody interactions with a noise floor of 5.2 pg/mm 2 and DNA single mismatch detection under isothermal melting conditions in an array format. Ensemble detection of binding events using IRIS did not provide the sensitivity needed for detection of infectious disease and biomarkers at clinically relevant concentrations. Therefore, a new approach was adapted to the IRIS platform that allowed the detection and identification of individual nanoparticles on the sensor's surface. The new detection method was termed single-particle IRIS (SP-IRIS). We developed two detection modalities for SP-IRIS. The first modality is when the target is a nanoparticle such as a virus. We verified that SP-IRIS can accurately detect and size individual viral particles. Then we demonstrated that single nanoparticle counting and sizing methodology on SP-IRIS leads to a specific and sensitive virus sensor that can be multiplexed. Finally, we developed an assay for the detection of Ebola and Marburg. A detection limit of 3 x 103 PFU/ml was demonstrated for vesicular stomatitis virus (VSV) pseudotyped with Ebola or Marburg virus glycoprotein. We have demonstrated that virus detection can be done in human whole blood directly without the need for sample preparation. The second modality of SP-IRIS we developed was single molecule counting of biomarkers utilizing a sandwich assay with detection probes labeled with gold nanoparticles. We demonstrated the use of single molecule counting in a nucleic acid assay for melanoma biomarker detection. We showed that a single molecule counting assay can lead to detection limits in the attomolar range. The improved sensitivity of IRIS utilizing single nanoparticle detection holds promise for a simple and low-cost technology for rapid virus detection and multiplexed molecular screening for clinical applications.

Probabilistic Multi-Sensor Fusion Based Indoor Positioning System on a Mobile Device

PubMed Central

He, Xiang; Aloi, Daniel N.; Li, Jia

2015-01-01

Nowadays, smart mobile devices include more and more sensors on board, such as motion sensors (accelerometer, gyroscope, magnetometer), wireless signal strength indicators (WiFi, Bluetooth, Zigbee), and visual sensors (LiDAR, camera). People have developed various indoor positioning techniques based on these sensors. In this paper, the probabilistic fusion of multiple sensors is investigated in a hidden Markov model (HMM) framework for mobile-device user-positioning. We propose a graph structure to store the model constructed by multiple sensors during the offline training phase, and a multimodal particle filter to seamlessly fuse the information during the online tracking phase. Based on our algorithm, we develop an indoor positioning system on the iOS platform. The experiments carried out in a typical indoor environment have shown promising results for our proposed algorithm and system design. PMID:26694387

Probabilistic Multi-Sensor Fusion Based Indoor Positioning System on a Mobile Device.

PubMed

He, Xiang; Aloi, Daniel N; Li, Jia

2015-12-14

Nowadays, smart mobile devices include more and more sensors on board, such as motion sensors (accelerometer, gyroscope, magnetometer), wireless signal strength indicators (WiFi, Bluetooth, Zigbee), and visual sensors (LiDAR, camera). People have developed various indoor positioning techniques based on these sensors. In this paper, the probabilistic fusion of multiple sensors is investigated in a hidden Markov model (HMM) framework for mobile-device user-positioning. We propose a graph structure to store the model constructed by multiple sensors during the offline training phase, and a multimodal particle filter to seamlessly fuse the information during the online tracking phase. Based on our algorithm, we develop an indoor positioning system on the iOS platform. The experiments carried out in a typical indoor environment have shown promising results for our proposed algorithm and system design.

Noise Modeling From Conductive Shields Using Kirchhoff Equations.

PubMed

Sandin, Henrik J; Volegov, Petr L; Espy, Michelle A; Matlashov, Andrei N; Savukov, Igor M; Schultz, Larry J

2010-10-09

Progress in the development of high-sensitivity magnetic-field measurements has stimulated interest in understanding the magnetic noise of conductive materials, especially of magnetic shields based on high-permeability materials and/or high-conductivity materials. For example, SQUIDs and atomic magnetometers have been used in many experiments with mu-metal shields, and additionally SQUID systems frequently have radio frequency shielding based on thin conductive materials. Typical existing approaches to modeling noise only work with simple shield and sensor geometries while common experimental setups today consist of multiple sensor systems with complex shield geometries. With complex sensor arrays used in, for example, MEG and Ultra Low Field MRI studies, knowledge of the noise correlation between sensors is as important as knowledge of the noise itself. This is crucial for incorporating efficient noise cancelation schemes for the system. We developed an approach that allows us to calculate the Johnson noise for arbitrary shaped shields and multiple sensor systems. The approach is efficient enough to be able to run on a single PC system and return results on a minute scale. With a multiple sensor system our approach calculates not only the noise for each sensor but also the noise correlation matrix between sensors. Here we will show how the algorithm can be implemented.

Large Margin Multi-Modal Multi-Task Feature Extraction for Image Classification.

PubMed

Yong Luo; Yonggang Wen; Dacheng Tao; Jie Gui; Chao Xu

2016-01-01

The features used in many image analysis-based applications are frequently of very high dimension. Feature extraction offers several advantages in high-dimensional cases, and many recent studies have used multi-task feature extraction approaches, which often outperform single-task feature extraction approaches. However, most of these methods are limited in that they only consider data represented by a single type of feature, even though features usually represent images from multiple modalities. We, therefore, propose a novel large margin multi-modal multi-task feature extraction (LM3FE) framework for handling multi-modal features for image classification. In particular, LM3FE simultaneously learns the feature extraction matrix for each modality and the modality combination coefficients. In this way, LM3FE not only handles correlated and noisy features, but also utilizes the complementarity of different modalities to further help reduce feature redundancy in each modality. The large margin principle employed also helps to extract strongly predictive features, so that they are more suitable for prediction (e.g., classification). An alternating algorithm is developed for problem optimization, and each subproblem can be efficiently solved. Experiments on two challenging real-world image data sets demonstrate the effectiveness and superiority of the proposed method.

Community Air Sensor Network (CAIRSENSE) project: evaluation of low-cost sensor performance in a suburban environment in the southeastern United States

NASA Astrophysics Data System (ADS)

Jiao, Wan; Hagler, Gayle; Williams, Ronald; Sharpe, Robert; Brown, Ryan; Garver, Daniel; Judge, Robert; Caudill, Motria; Rickard, Joshua; Davis, Michael; Weinstock, Lewis; Zimmer-Dauphinee, Susan; Buckley, Ken

2016-11-01

Advances in air pollution sensor technology have enabled the development of small and low-cost systems to measure outdoor air pollution. The deployment of a large number of sensors across a small geographic area would have potential benefits to supplement traditional monitoring networks with additional geographic and temporal measurement resolution, if the data quality were sufficient. To understand the capability of emerging air sensor technology, the Community Air Sensor Network (CAIRSENSE) project deployed low-cost, continuous, and commercially available air pollution sensors at a regulatory air monitoring site and as a local sensor network over a surrounding ˜ 2 km area in the southeastern United States. Collocation of sensors measuring oxides of nitrogen, ozone, carbon monoxide, sulfur dioxide, and particles revealed highly variable performance, both in terms of comparison to a reference monitor as well as the degree to which multiple identical sensors produced the same signal. Multiple ozone, nitrogen dioxide, and carbon monoxide sensors revealed low to very high correlation with a reference monitor, with Pearson sample correlation coefficient (r) ranging from 0.39 to 0.97, -0.25 to 0.76, and -0.40 to 0.82, respectively. The only sulfur dioxide sensor tested revealed no correlation (r < 0.5) with a reference monitor and erroneously high concentration values. A wide variety of particulate matter (PM) sensors were tested with variable results - some sensors had very high agreement (e.g., r = 0.99) between identical sensors but moderate agreement with a reference PM2.5 monitor (e.g., r = 0.65). For select sensors that had moderate to strong correlation with reference monitors (r > 0.5), step-wise multiple linear regression was performed to determine if ambient temperature, relative humidity (RH), or age of the sensor in number of sampling days could be used in a correction algorithm to improve the agreement. Maximum improvement in agreement with a reference, incorporating all factors, was observed for an NO2 sensor (multiple correlation coefficient R2adj-orig = 0.57, R2adj-final = 0.81); however, other sensors showed no apparent improvement in agreement. A four-node sensor network was successfully able to capture ozone (two nodes) and PM (four nodes) data for an 8-month period of time and show expected diurnal concentration patterns, as well as potential ozone titration due to nearby traffic emissions. Overall, this study demonstrates the performance of emerging air quality sensor technologies in a real-world setting; the variable agreement between sensors and reference monitors indicates that in situ testing of sensors against benchmark monitors should be a critical aspect of all field studies.

Autonomous Modal Identification of the Space Shuttle Tail Rudder

NASA Technical Reports Server (NTRS)

Pappa, Richard S.; James, George H., III; Zimmerman, David C.

1997-01-01

Autonomous modal identification automates the calculation of natural vibration frequencies, damping, and mode shapes of a structure from experimental data. This technology complements damage detection techniques that use continuous or periodic monitoring of vibration characteristics. The approach shown in the paper incorporates the Eigensystem Realization Algorithm (ERA) as a data analysis engine and an autonomous supervisor to condense multiple estimates of modal parameters using ERA's Consistent-Mode Indicator and correlation of mode shapes. The procedure was applied to free-decay responses of a Space Shuttle tail rudder and successfully identified the seven modes of the structure below 250 Hz. The final modal parameters are a condensed set of results for 87 individual ERA cases requiring approximately five minutes of CPU time on a DEC Alpha computer.

Scaling laws for nanoFET sensors

NASA Astrophysics Data System (ADS)

Zhou, Fu-Shan; Wei, Qi-Huo

2008-01-01

The sensitive conductance change of semiconductor nanowires and carbon nanotubes in response to the binding of charged molecules provides a novel sensing modality which is generally denoted as nanoFET sensors. In this paper, we study the scaling laws of nanoplate FET sensors by simplifying nanoplates as random resistor networks with molecular receptors sitting on lattice sites. Nanowire/tube FETs are included as the limiting cases where the device width goes small. Computer simulations show that the field effect strength exerted by the binding molecules has significant impact on the scaling behaviors. When the field effect strength is small, nanoFETs have little size and shape dependence. In contrast, when the field effect strength becomes stronger, there exists a lower detection threshold for charge accumulation FETs and an upper detection threshold for charge depletion FET sensors. At these thresholds, the nanoFET devices undergo a transition between low and large sensitivities. These thresholds may set the detection limits of nanoFET sensors, while they could be eliminated by designing devices with very short source-drain distance and large width.

Performance evaluation of the Fiber Bragg Grating (FBG) sensing device and comparison with piezoelectric sensors for AE detection

NASA Astrophysics Data System (ADS)

Zhang, Chuang; Bond, Leonard J.

2017-02-01

Structural health monitoring (SHM) of engineering structures in service has assumed a significant role in assessing their safety and integrity. Several sensing modalities have been developed to monitor cracking, using acoustic emission (AE). Piezoelectric sensors are commonly used in AE systems, however, for some applications there are limitations and challenges. One alternative approach that is being investigated is using Fiber Bragg Grating (FBG) sensors which have emerged as a reliable, in situ and nondestructive tool in some applications for monitoring and diagnostics in large-scale structure. The main objective of this work is to evaluate and compare the AE sensing characteristics for FBG and piezoelectric sensors. A ball drop impact is used as the source for generating waves in an Aluminum plate. The source repeatability was verified and a 4-channel FBG AE detection device was used to compare with the response of PZT sensors, investigating amplitude and frequency response which can indicate sensitivity. The low sensitivity and slow sampling rate are identified, for the unit investigated, as the main factors limiting FBG engineering AE applications.

Imaging trends in suspected appendicitis-a Canadian perspective.

PubMed

Tan, Victoria F; Patlas, Michael N; Katz, Douglas S

2017-06-01

The purpose of our study was to assess trends in the imaging of suspected appendicitis in adult patients in emergency departments of academic centers in Canada. A questionnaire was sent to all 17 academic centers in Canada to be completed by a radiologist who works in emergency radiology. The questionnaires were sent and collected over a period of 4 months from October 2015 to February 2016. Sixteen centers (94%) responded to the questionnaire. Eleven respondents (73%) use IV contrast-enhanced computed tomography (CT) as the imaging modality of choice for all patients with suspected appendicitis. Thirteen respondents (81%) use ultrasound as the first modality of choice in imaging pregnant patients with suspected appendicitis. Eleven respondents (69%) use ultrasound (US) as the first modality of choice in patients younger than 40 years of age. Ten respondents (67%) use ultrasound as the first imaging modality in female patients younger than 40 years of age. When CT is used, 81% use non-focused CT of the abdomen and pelvis, and 44% of centers use oral contrast. Thirteen centers (81%) have ultrasound available 24 h a day/7 days a week. At 12 centers (75%), ultrasound is performed by ultrasound technologists. Four centers (40%) perform magnetic resonance imaging (MRI) in suspected appendicitis in adult patients at the discretion of the attending radiologist. Eleven centers (69%) have MRI available 24/7. All 16 centers (100%) use unenhanced MRI. Various imaging modalities are available for the work-up of suspected appendicitis. Although there are North American societal guidelines and recommendations regarding the appropriateness of the multiple imaging modalities, significant heterogeneity in the first-line modalities exist, which vary depending on the patient demographics and resource availability. Imaging trends in the use of the first-line modalities should be considered in order to plan for the availability of the imaging examinations and to consider plans for an imaging algorithm to permit standardization across multiple centers. While this study examined the imaging trends specifically in Canada, there are implications to other countries seeking to streamline imaging protocols and determining appropriateness of the first-line imaging modalities.

Multiple Two-Way Time Message Exchange (TTME) Time Synchronization for Bridge Monitoring Wireless Sensor Networks

PubMed Central

Shi, Fanrong; Tuo, Xianguo; Yang, Simon X.; Li, Huailiang; Shi, Rui

2017-01-01

Wireless sensor networks (WSNs) have been widely used to collect valuable information in Structural Health Monitoring (SHM) of bridges, using various sensors, such as temperature, vibration and strain sensors. Since multiple sensors are distributed on the bridge, accurate time synchronization is very important for multi-sensor data fusion and information processing. Based on shape of the bridge, a spanning tree is employed to build linear topology WSNs and achieve time synchronization in this paper. Two-way time message exchange (TTME) and maximum likelihood estimation (MLE) are employed for clock offset estimation. Multiple TTMEs are proposed to obtain a subset of TTME observations. The time out restriction and retry mechanism are employed to avoid the estimation errors that are caused by continuous clock offset and software latencies. The simulation results show that the proposed algorithm could avoid the estimation errors caused by clock drift and minimize the estimation error due to the large random variable delay jitter. The proposed algorithm is an accurate and low complexity time synchronization algorithm for bridge health monitoring. PMID:28471418

Multiple Two-Way Time Message Exchange (TTME) Time Synchronization for Bridge Monitoring Wireless Sensor Networks.

PubMed

Shi, Fanrong; Tuo, Xianguo; Yang, Simon X; Li, Huailiang; Shi, Rui

2017-05-04

Wireless sensor networks (WSNs) have been widely used to collect valuable information in Structural Health Monitoring (SHM) of bridges, using various sensors, such as temperature, vibration and strain sensors. Since multiple sensors are distributed on the bridge, accurate time synchronization is very important for multi-sensor data fusion and information processing. Based on shape of the bridge, a spanning tree is employed to build linear topology WSNs and achieve time synchronization in this paper. Two-way time message exchange (TTME) and maximum likelihood estimation (MLE) are employed for clock offset estimation. Multiple TTMEs are proposed to obtain a subset of TTME observations. The time out restriction and retry mechanism are employed to avoid the estimation errors that are caused by continuous clock offset and software latencies. The simulation results show that the proposed algorithm could avoid the estimation errors caused by clock drift and minimize the estimation error due to the large random variable delay jitter. The proposed algorithm is an accurate and low complexity time synchronization algorithm for bridge health monitoring.

A non-invasive blood glucose meter design using multi-type sensors

NASA Astrophysics Data System (ADS)

Nguyen, D.; Nguyen, Hienvu; Roveda, Janet

2012-10-01

In this paper, we present a design of a multi optical modalities blood glucose monitor. The Monte Carlo tissues optics simulation with typical human skin model suggests the SNR ratio for a detector sensor is 104 with high sensitivity that can detect low blood sugar limit at 1 mMole/dL ( <20 mg/dL). A Bayesian filtering algorithm is proposed for multisensor fusion to identify whether e user has the danger of having diabetes. The new design has real time response (on the average of 2 minutes) and provides great potential to perform real time monitoring for blood glucose.

All-fiber magnetic field sensor based on tapered thin-core fiber and magnetic fluid.

PubMed

Zhang, Junying; Qiao, Xueguang; Yang, Hangzhou; Wang, Ruohui; Rong, Qiangzhou; Lim, Kok-Sing; Ahmad, Harith

2017-01-10

A method for the measurement of a magnetic field by combining a tapered thin-core fiber (TTCF) and magnetic fluid is proposed and experimentally demonstrated. The modal interference effect is caused by the core mode and excited eigenmodes in the TTCF cladding. The transmission spectra of the proposed sensor are measured and theoretically analyzed at different magnetic field strengths. The results field show that the magnetic sensitivity reaches up to -0.1039  dB/Oe in the range of 40-1600 e. The proposed method possesses high sensitivity and low cost compared with other expensive methods.

Photonic crystal fiber modal interferometer with Pd/WO3 coating for real-time monitoring of dissolved hydrogen concentration in transformer oil

NASA Astrophysics Data System (ADS)

Zhang, Ya-nan; Wu, Qilu; Peng, Huijie; Zhao, Yong

2016-12-01

A highly-sensitive and temperature-robust photonic crystal fiber (PCF) modal interferometer coated with Pd/WO3 film was fabricated and studied, aiming for real-time monitoring of dissolved hydrogen concentration in transformer oil. The sensor probe was fabricated by splicing two segments of a single mode fiber (SMF) with both ends of the PCF. Since the collapse of air holes in the PCF in the interfaces between SMF and PCF, a SMF-PCF-SMF interferometer structure was formed. The Pd/WO3 film was fabricated by sol-gel method and coated on the surface of the PCF by dip-coating method. When the Pd/WO3 film is exposed to hydrogen, both the length and cladding refractive index of the PCF would be changed, resulting in the resonant wavelength shift of the interferometer. Experimental results showed that the hydrogen measurement sensitivity of the proposed sensor can reach 0.109 pm/(μl/l) in the transformer oil, with the measurement range of 0-10 000 μl/l and response time less than 33 min. Besides, the proposed sensor was temperature-insensitive without any compensation process, easy to fabricate without any tapering, polishing, or etching process, low cost and quickly response without any oil-gas separation device. All these performances satisfy the actual need of real-time monitoring of dissolved hydrogen concentration in the transformer oil.

Photonic crystal fiber modal interferometer with Pd/WO3 coating for real-time monitoring of dissolved hydrogen concentration in transformer oil.

PubMed

Zhang, Ya-Nan; Wu, Qilu; Peng, Huijie; Zhao, Yong

2016-12-01

A highly-sensitive and temperature-robust photonic crystal fiber (PCF) modal interferometer coated with Pd/WO 3 film was fabricated and studied, aiming for real-time monitoring of dissolved hydrogen concentration in transformer oil. The sensor probe was fabricated by splicing two segments of a single mode fiber (SMF) with both ends of the PCF. Since the collapse of air holes in the PCF in the interfaces between SMF and PCF, a SMF-PCF-SMF interferometer structure was formed. The Pd/WO 3 film was fabricated by sol-gel method and coated on the surface of the PCF by dip-coating method. When the Pd/WO 3 film is exposed to hydrogen, both the length and cladding refractive index of the PCF would be changed, resulting in the resonant wavelength shift of the interferometer. Experimental results showed that the hydrogen measurement sensitivity of the proposed sensor can reach 0.109 pm/(μl/l) in the transformer oil, with the measurement range of 0-10 000 μl/l and response time less than 33 min. Besides, the proposed sensor was temperature-insensitive without any compensation process, easy to fabricate without any tapering, polishing, or etching process, low cost and quickly response without any oil-gas separation device. All these performances satisfy the actual need of real-time monitoring of dissolved hydrogen concentration in the transformer oil.

On the physical significance of the Effective Independence method for sensor placement

NASA Astrophysics Data System (ADS)

Jiang, Yaoguang; Li, Dongsheng; Song, Gangbing

2017-05-01

Optimally deploy sparse sensors for better damage identification and structural health monitoring is always a challenging task. The Effective Independence(EI) is one of the most influential sensor placement method and to be discussed in the paper. Specifically, the effect of the different weighting coefficients on the maximization of the Fisher information matrix(FIM) and the physical significance of the re-orthogonalization of modal shapes through QR decomposition in the EI method are addressed. By analyzing the widely used EI method, we found that the absolute identification space put forward along with the EI method is preferable to ensuring the maximization of the FIM, instead of the original EI coefficient which was post-multiolied by a weighting matrix. That is, deleting the row with the minimum EI coefficient can’t achieve the objective of maximizing the trace of FIM as initially conceived. Furthermore, we observed that in the computation of EI method, the sum of each retained row in the absolute identification space is a constant in each iteration. This potential property can be revealed distinctively by the product of target mode and its transpose, and its form is similar to an alternative formula of the EI method through orthogonal-triangular(QR) decomposition previously proposed by the authors. With it, the physical significance of re-orthogonalization of modal shapes through QR decomposition in the computation of EI method can be obviously manifested from a new perspective. Finally, two simple examples are provided to demonstrate the above two observations.

Real-time multisensor data fusion for target detection, classification, tracking, counting, and range estimates

NASA Astrophysics Data System (ADS)

Tsui, Eddy K.; Thomas, Russell L.

2004-09-01

As part of the Commanding General of Army Material Command's Research, Development & Engineering Command (RDECOM), the U.S. Army Research Development and Engineering Center (ARDEC), Picatinny funded a joint development effort with McQ Associates, Inc. to develop an Advanced Minefield Sensor (AMS) as a technology evaluation prototype for the Anti-Personnel Landmine Alternatives (APLA) Track III program. This effort laid the fundamental groundwork of smart sensors for detection and classification of targets, identification of combatant or noncombatant, target location and tracking at and between sensors, fusion of information across targets and sensors, and automatic situation awareness to the 1st responder. The efforts have culminated in developing a performance oriented architecture meeting the requirements of size, weight, and power (SWAP). The integrated digital signal processor (DSP) paradigm is capable of computing signals from sensor modalities to extract needed information within either a 360° or fixed field of view with acceptable false alarm rate. This paper discusses the challenges in the developments of such a sensor, focusing on achieving reasonable operating ranges, achieving low power, small size and low cost, and applications for extensions of this technology.

Estimation in Linear Systems Featuring Correlated Uncertain Observations Coming from Multiple Sensors

NASA Astrophysics Data System (ADS)

Caballero-Águila, R.; Hermoso-Carazo, A.; Linares-Pérez, J.

2009-08-01

In this paper, the state least-squares linear estimation problem from correlated uncertain observations coming from multiple sensors is addressed. It is assumed that, at each sensor, the state is measured in the presence of additive white noise and that the uncertainty in the observations is characterized by a set of Bernoulli random variables which are only correlated at consecutive time instants. Assuming that the statistical properties of such variables are not necessarily the same for all the sensors, a recursive filtering algorithm is proposed, and the performance of the estimators is illustrated by a numerical simulation example wherein a signal is estimated from correlated uncertain observations coming from two sensors with different uncertainty characteristics.

Modal Parameters Evaluation in a Full-Scale Aircraft Demonstrator under Different Environmental Conditions Using HS 3D-DIC.

PubMed

Molina-Viedma, Ángel Jesús; López-Alba, Elías; Felipe-Sesé, Luis; Díaz, Francisco A; Rodríguez-Ahlquist, Javier; Iglesias-Vallejo, Manuel

2018-02-02

In real aircraft structures the comfort and the occupational performance of crewmembers and passengers are affected by the presence of noise. In this sense, special attention is focused on mechanical and material design for isolation and vibration control. Experimental characterization and, in particular, experimental modal analysis, provides information for adequate cabin noise control. Traditional sensors employed in the aircraft industry for this purpose are invasive and provide a low spatial resolution. This paper presents a methodology for experimental modal characterization of a front fuselage full-scale demonstrator using high-speed 3D digital image correlation, which is non-invasive, ensuring that the structural response is unperturbed by the instrumentation mass. Specifically, full-field measurements on the passenger window area were conducted when the structure was excited using an electrodynamic shaker. The spectral analysis of the measured time-domain displacements made it possible to identify natural frequencies and full-field operational deflection shapes. Changes in the modal parameters due to cabin pressurization and the behavior of different local structural modifications were assessed using this methodology. The proposed full-field methodology allowed the characterization of relevant dynamic response patterns, complementing the capabilities provided by accelerometers.

Modal Parameters Evaluation in a Full-Scale Aircraft Demonstrator under Different Environmental Conditions Using HS 3D-DIC

PubMed Central

López-Alba, Elías; Felipe-Sesé, Luis; Díaz, Francisco A.; Rodríguez-Ahlquist, Javier; Iglesias-Vallejo, Manuel

2018-01-01

In real aircraft structures the comfort and the occupational performance of crewmembers and passengers are affected by the presence of noise. In this sense, special attention is focused on mechanical and material design for isolation and vibration control. Experimental characterization and, in particular, experimental modal analysis, provides information for adequate cabin noise control. Traditional sensors employed in the aircraft industry for this purpose are invasive and provide a low spatial resolution. This paper presents a methodology for experimental modal characterization of a front fuselage full-scale demonstrator using high-speed 3D digital image correlation, which is non-invasive, ensuring that the structural response is unperturbed by the instrumentation mass. Specifically, full-field measurements on the passenger window area were conducted when the structure was excited using an electrodynamic shaker. The spectral analysis of the measured time-domain displacements made it possible to identify natural frequencies and full-field operational deflection shapes. Changes in the modal parameters due to cabin pressurization and the behavior of different local structural modifications were assessed using this methodology. The proposed full-field methodology allowed the characterization of relevant dynamic response patterns, complementing the capabilities provided by accelerometers. PMID:29393897

Modality dependency of familiarity ratings of Japanese words.

PubMed

Amano, S; Kondo, T; Kakehi, K

1995-07-01

Familiarity ratings for a large number of aurally and visually presented Japanese words wer measured for 11 subjects, in order to investigate the modality dependency of familiarity. The correlation coefficient between auditory and visual ratings was .808, which is lower than that observed for English words, suggesting that a substantial portion of the mental lexicon is modality dependent. It was shown that the modality dependency is greater for low-familiarity words than it is for medium- or high-familiarity words. This difference between the low- and the medium- or high-familiarity words has a relationship to orthography. That is, the dependency is larger in words consisting only of kanji, which may have multiple pronunciations and usually represent meaning, than it is in words consisting only of hiragana or katakana, which have a single pronunciation and usually do not represent meaning. These results indicate that the idiosyncratic characteristics of Japanese orthography contribute to the modality dependency.

Thin Film Physical Sensor Instrumentation Research and Development at NASA Glenn Research Center

NASA Technical Reports Server (NTRS)

Wrbanek, John D.; Fralick, Gustave C.

2006-01-01

A range of thin film sensor technology has been demonstrated enabling measurement of multiple parameters either individually or in sensor arrays including temperature, strain, heat flux, and flow. Multiple techniques exist for refractory thin film fabrication, fabrication and integration on complex surfaces and multilayered thin film insulation. Leveraging expertise in thin films and high temperature materials, investigations for the applications of thin film ceramic sensors has begun. The current challenges of instrumentation technology are to further develop systems packaging and component testing of specialized sensors, further develop instrumentation techniques on complex surfaces, improve sensor durability, and to address needs for extreme temperature applications. The technology research and development ongoing at NASA Glenn for applications to future launch vehicles, space vehicles, and ground systems is outlined.

Quasi-distributed fiber sensor using active mode locking laser cavity with multiple FBG reflections

NASA Astrophysics Data System (ADS)

Park, Chang Hyun; Kim, Gyeong Hun; Kim, Chang-Seok; Lee, Hwi Don; Chung, Youngjoo

2017-04-01

We have demonstrated a quasi-distributed sensor using an active mode-locking (AML) laser with multiple fiber Bragg grating (FBG) reflections of the same center wavelength. We found that variations in the multiple cavity segment lengths between FBGs can be measured by simply sweeping the modulation frequency, because the modulation frequency of the AML laser is proportionally affected by cavity length.

Direct system parameter identification of mechanical structures with application to modal analysis

NASA Technical Reports Server (NTRS)

Leuridan, J. M.; Brown, D. L.; Allemang, R. J.

1982-01-01

In this paper a method is described to estimate mechanical structure characteristics in terms of mass, stiffness and damping matrices using measured force input and response data. The estimated matrices can be used to calculate a consistent set of damped natural frequencies and damping values, mode shapes and modal scale factors for the structure. The proposed technique is attractive as an experimental modal analysis method since the estimation of the matrices does not require previous estimation of frequency responses and since the method can be used, without any additional complications, for multiple force input structure testing.