Ship Sensor Observations for Operation Deep Scope 2007 - Office of Ocean Exploration

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Hourly measurements made by selected ship sensors on the R/V Seward Johnson during the "Operation Deep Scope 2007" expedition sponsored by the National Oceanic and...

Design of Field Experiments for Adaptive Sampling of the Ocean with Autonomous Vehicles

Science.gov (United States)

Zheng, H.; Ooi, B. H.; Cho, W.; Dao, M. H.; Tkalich, P.; Patrikalakis, N. M.

2010-05-01

Due to the highly non-linear and dynamical nature of oceanic phenomena, the predictive capability of various ocean models depends on the availability of operational data. A practical method to improve the accuracy of the ocean forecast is to use a data assimilation methodology to combine in-situ measured and remotely acquired data with numerical forecast models of the physical environment. Autonomous surface and underwater vehicles with various sensors are economic and efficient tools for exploring and sampling the ocean for data assimilation; however there is an energy limitation to such vehicles, and thus effective resource allocation for adaptive sampling is required to optimize the efficiency of exploration. In this paper, we use physical oceanography forecasts of the coastal zone of Singapore for the design of a set of field experiments to acquire useful data for model calibration and data assimilation. The design process of our experiments relied on the oceanography forecast including the current speed, its gradient, and vorticity in a given region of interest for which permits for field experiments could be obtained and for time intervals that correspond to strong tidal currents. Based on these maps, resources available to our experimental team, including Autonomous Surface Craft (ASC) are allocated so as to capture the oceanic features that result from jets and vortices behind bluff bodies (e.g., islands) in the tidal current. Results are summarized from this resource allocation process and field experiments conducted in January 2009.

Testbeam Studies on Pick-Up in Sensors with Embedded Pitch Adapters

CERN Document Server

Rehnisch, Laura; The ATLAS collaboration

2017-01-01

For silicon strip sensors, the tracking information specifications can lead to challenging requirements for wire bonding. A common strategy is to use external pitch adapters to facilitate this step in the production of detector modules. A novel approach previously discussed in [1], is to implement the pitch adapters in the sensor, by embedding a second layer of metal tracks. The use of these embedded pitch adapters (EPAs) decouples the bond pad layout of the sensor from its implant layout by moving the adaption to the sensor production step. This solution, however, can yield the risk of performance losses due to the increase of inter-strip capacitance, or unwanted capacitive coupling between the metal layers (cross-talk) or the silicon bulk and the second metal layer (pick-up). In the prototyping stage of the ATLAS tracker end-cap upgrade, where different bond-pad layouts on sensor and readout chip lead to extremely challenging wire-bonding conditions, sensors with different geometries of EPA implementations ...

Image sensors for radiometric measurements in the ocean

Digital Repository Service at National Institute of Oceanography (India)

Desa, E.S.; Desa, B.A.E.

the sensors at a stabilised moderately cool temperature of 15 deg. C and to intelligently control the exposure time of the device, so as to reliably measure flux levels in the range 1 W/m super(2)/nm to 10/6 W/m super(2)/nm commonly encountered in the ocean...

Experimental study of temperature sensor for an ocean-going liquid hydrogen (LH2) carrier

Science.gov (United States)

Nakano, A.; Shimazaki, T.; Sekiya, M.; Shiozawa, H.; Aoyagi, A.; Ohtsuka, K.; Iwakiri, T.; Mikami, Z.; Sato, M.; Kinoshita, K.; Matsuoka, T.; Takayama, Y.; Yamamoto, K.

2018-04-01

The prototype temperature sensors for an ocean-going liquid hydrogen (LH2) carrier were manufactured by way of trial. All of the sensors adopted Platinum 1000 (PT-1000) resistance thermometer elements. Various configurations of preproduction temperature sensors were tested in AIST's LH2 test facility. In the experiments, a PT-1000 resistance thermometer, calibrated at the National Metrology Institute of Japan at AIST, was used as the standard thermometer. The temperatures measured by the preproduction sensors were compared with the temperatures measured by the standard thermometer, and the measurement accuracy of the temperature sensors in LH2 was investigated and discussed. It was confirmed that the measurement accuracies of the preproduction temperature sensors were within ±50 mK, which is the required measurement accuracy for a technical demonstration ocean-going LH2 carrier.

Adaptive Sensing Based on Profiles for Sensor Systems

Directory of Open Access Journals (Sweden)

Yoshiteru Ishida

2009-10-01

Full Text Available This paper proposes a profile-based sensing framework for adaptive sensor systems based on models that relate possibly heterogeneous sensor data and profiles generated by the models to detect events. With these concepts, three phases for building the sensor systems are extracted from two examples: a combustion control sensor system for an automobile engine, and a sensor system for home security. The three phases are: modeling, profiling, and managing trade-offs. Designing and building a sensor system involves mapping the signals to a model to achieve a given mission.

Ship Sensor Observations for Mountains in the Sea 2003 - Office of Ocean Exploration

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Hourly measurements made by selected ship sensors on the R/V Atlantis during the "Mountains in the Sea 2003" expedition sponsored by the National Oceanic and...

Ship Sensor Observations for Life on the Edge 2005 - Office of Ocean Exploration

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Hourly measurements made by selected ship sensors on the R/V Seward Johnson during the "Life on the Edge 2005" expedition sponsored by the National Oceanic and...

Ship Sensor Observations for Life on the Edge 2004 - Office of Ocean Exploration

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Hourly measurements made by selected ship sensors on the R/V Seward Johnson during the "Life on the Edge 2004" expedition sponsored by the National Oceanic and...

Validation of ocean color sensors using a profiling hyperspectral radiometer

Science.gov (United States)

Ondrusek, M. E.; Stengel, E.; Rella, M. A.; Goode, W.; Ladner, S.; Feinholz, M.

2014-05-01

Validation measurements of satellite ocean color sensors require in situ measurements that are accurate, repeatable and traceable enough to distinguish variability between in situ measurements and variability in the signal being observed on orbit. The utility of using a Satlantic Profiler II equipped with HyperOCR radiometers (Hyperpro) for validating ocean color sensors is tested by assessing the stability of the calibration coefficients and by comparing Hyperpro in situ measurements to other instruments and between different Hyperpros in a variety of water types. Calibration and characterization of the NOAA Satlantic Hyperpro instrument is described and concurrent measurements of water-leaving radiances conducted during cruises are presented between this profiling instrument and other profiling, above-water and moored instruments. The moored optical instruments are the US operated Marine Optical BuoY (MOBY) and the French operated Boussole Buoy. In addition, Satlantic processing versions are described in terms of accuracy and consistency. A new multi-cast approach is compared to the most commonly used single cast method. Analysis comparisons are conducted in turbid and blue water conditions. Examples of validation matchups with VIIRS ocean color data are presented. With careful data collection and analysis, the Satlantic Hyperpro profiling radiometer has proven to be a reliable and consistent tool for satellite ocean color validation.

Adaptive inferential sensors based on evolving fuzzy models.

Science.gov (United States)

Angelov, Plamen; Kordon, Arthur

2010-04-01

A new technique to the design and use of inferential sensors in the process industry is proposed in this paper, which is based on the recently introduced concept of evolving fuzzy models (EFMs). They address the challenge that the modern process industry faces today, namely, to develop such adaptive and self-calibrating online inferential sensors that reduce the maintenance costs while keeping the high precision and interpretability/transparency. The proposed new methodology makes possible inferential sensors to recalibrate automatically, which reduces significantly the life-cycle efforts for their maintenance. This is achieved by the adaptive and flexible open-structure EFM used. The novelty of this paper lies in the following: (1) the overall concept of inferential sensors with evolving and self-developing structure from the data streams; (2) the new methodology for online automatic selection of input variables that are most relevant for the prediction; (3) the technique to detect automatically a shift in the data pattern using the age of the clusters (and fuzzy rules); (4) the online standardization technique used by the learning procedure of the evolving model; and (5) the application of this innovative approach to several real-life industrial processes from the chemical industry (evolving inferential sensors, namely, eSensors, were used for predicting the chemical properties of different products in The Dow Chemical Company, Freeport, TX). It should be noted, however, that the methodology and conclusions of this paper are valid for the broader area of chemical and process industries in general. The results demonstrate that well-interpretable and with-simple-structure inferential sensors can automatically be designed from the data stream in real time, which predict various process variables of interest. The proposed approach can be used as a basis for the development of a new generation of adaptive and evolving inferential sensors that can address the

Lifetime Maximizing Adaptive Power Control in Wireless Sensor Networks

National Research Council Canada - National Science Library

Sun, Fangting; Shayman, Mark

2006-01-01

...: adaptive power control. They focus on the sensor networks that consist of a sink and a set of homogeneous wireless sensor nodes, which are randomly deployed according to a uniform distribution...

Calibration requirements and methodology for remote sensors viewing the ocean in the visible

Science.gov (United States)

Gordon, Howard R.

1987-01-01

The calibration requirements for ocean-viewing sensors are outlined, and the present methods of effecting such calibration are described in detail. For future instruments it is suggested that provision be made for the sensor to view solar irradiance in diffuse reflection and that the moon be used as a source of diffuse light for monitoring the sensor stability.

Ocean Acidification: Adaptive Challenge or Extinction Threat?

Science.gov (United States)

Caldeira, K.

2012-12-01

Most of the carbon dioxide that we emit to this atmosphere through fossil-fuel burning and deforestation is ultimately absorbed by the oceans. The effects of excess carbon dioxide on the inorganic chemistry of the ocean are largely well understood, but it is less clear what these chemical changes mean for the future of marine biota. Excess dissolved CO2 increases hydrogen-ion concentration (i.e., decreases pH) and decreases carbonate-ion concentrations, affecting the chemical speciation of nutrients and other chemicals dissolved in the ocean, and affecting the ability of organisms to form calcium carbonate shells or skeletons. Some organisms, such as corals, develop shells or skeletons made from aragonite, a particularly soluble form of calcium carbonate. The uptake of O2 and the release of CO2 from the blood of fish are affected by pH, with lower pH leading to a decrease in both O2 uptake and CO2 release. Of these concerns, the effects of excess CO2 on calcification may be the most worrisome. Doubling or quadrupling of atmospheric CO2 content within the space of a few centuries means doubling or quadrupling hydrogen-ion concentrations and halving or quartering the carbonate-ion concentration within a few centuries. Experiments and theory indicate that chemical changes of this magnitude could have important biotic consequences. Changes of this magnitude and rapidity have not occurred on this planet with the possible exception of various paroxysmal extreme events buried deep in Earth history. Most major changes to ocean chemistry occurred over millions of years allowing (i) seawater chemistry to be in approximate equilibrium with respect to riverine and sedimentary fluxes and (ii) marine biota to adapt in evolutionary time. Man's great geochemical experiment will go on at global scale for thousands of years. But experiments can be done in the laboratory in small tanks or in the sea in small enclosures only for limited periods of time. It is difficult to infer from

Thinking Outside of the Blue Marble: Novel Ocean Applications Using the VIIRS Sensor

Science.gov (United States)

Vandermeulen, Ryan A.; Arnone, Robert

2016-01-01

While planning for future space-borne sensors will increase the quality, quantity, and duration of ocean observations in the years to come, efforts to extend the limits of sensors currently in orbit can help shed light on future scientific gains as well as associated uncertainties. Here, we present several applications that are unique to the polar orbiting Visual Infrared Imaging Radiometer Suite (VIIRS), each of which challenge the threshold capabilities of the sensor and provide lessons for future missions. For instance, while moderate resolution polar orbiters typically have a one day revisit time, we are able to obtain multiple looks of the same area by focusing on the extreme zenith angles where orbital views overlap, and pair these observations with those from other sensors to create pseudo-geostationary data sets. Or, by exploiting high spatial resolution (imaging) channels and analyzing patterns of synoptic covariance across the visible spectrum, we can obtain higher spatial resolution bio-optical products. Alternatively, non-traditional products can illuminate important biological interactions in the ocean, such as the use of the Day-Night-Band to provide some quantification of phototactic behavior of marine life along light polluted beaches, as well as track the location of marine fishing vessel fleets along ocean fronts. In this talk, we explore ways to take full advantage of the capabilities of existing sensors in order to maximize insights for future missions.

arXiv Signal coupling to embedded pitch adapters in silicon sensors

CERN Document Server

Artuso, M.; Bezshyiko, I.; Blusk, S.; Bruendler, R.; Bugiel, S.; Dasgupta, R.; Dendek, A.; Dey, B.; Ely, S.; Lionetto, F.; Petruzzo, M.; Polyakov, I.; Rudolph, M.; Schindler, H.; Steinkamp, O.; Stone, S.

2018-01-01

We have examined the effects of embedded pitch adapters on signal formation in n-substrate silicon microstrip sensors with data from beam tests and simulation. According to simulation, the presence of the pitch adapter metal layer changes the electric field inside the sensor, resulting in slowed signal formation on the nearby strips and a pick-up effect on the pitch adapter. This can result in an inefficiency to detect particles passing through the pitch adapter region. All these effects have been observed in the beam test data.

Science requirements and the design of cabled ocean observatories

Directory of Open Access Journals (Sweden)

H. Mikada

2006-06-01

Full Text Available The ocean sciences are beginning a new phase in which scientists will enter the ocean environment and adaptively observe the Earth-Ocean system through remote control of sensors and sensor platforms. This new ocean science paradigm will be implemented using innovative facilities called ocean observatories which provide unprecedented levels of power and communication to access and manipulate real-time sensor networks deployed within many different environments in the ocean basins. Most of the principal design drivers for ocean observatories differ from those for commercial submarine telecommunications systems. First, ocean observatories require data to be input and output at one or more seafloor nodes rather than at a few land terminuses. Second, ocean observatories must distribute a lot of power to the seafloor at variable and fluctuating rates. Third, the seafloor infrastructure for an ocean observatory inherently requires that the wet plant be expandable and reconfigurable. Finally, because the wet communications and power infrastructure is comparatively complex, ocean observatory infrastructure must be designed for low life cycle cost rather than zero maintenance. The origin of these differences may be understood by taking a systems engineering approach to ocean observatory design through examining the requirements derived from science and then going through the process of iterative refinement to yield conceptual and physical designs. This is illustrated using the NEPTUNE regional cabled observatory power and data communications sub-systems.

Adaptation to Impacts of Greenhouse Gases on the Ocean (Invited)

Science.gov (United States)

Caldeira, K.

2010-12-01

Greenhouse gases are producing changes in ocean temperature and circulation, and these changes are already adversely affecting marine biota. Furthermore, carbon dioxide is absorbed by the oceans from the atmosphere, and this too is already adversely affecting some marine ecosystems. And, of course, sea-level rise affects both what is above and below the waterline. Clearly, the most effective approach to limit the negative impacts of climate change and acidification on the marine environment is to greatly diminish the rate of greenhouse gas emissions. However, there are other measures that can be taken to limit some of the negative effects of these stresses in the marine environment. Marine ecosystems are subject to multiple stresses, including overfishing, pollution, and loss of coastal wetlands that often serve as nurseries for the open ocean. The adaptive capacity of marine environments can be improved by limiting these other stresses. If current carbon dioxide emission trends continue, for some cases (e.g., coral reefs), it is possible that no amount of reduction in other stresses can offset the increase in stresses posed by warming and acidification. For other cases (e.g., blue-water top-predator fisheries), better fisheries management might yield improved population health despite continued warming and acidification. In addition to reducing stresses so as to improve the adaptive capacity of marine ecosystems, there is also the issue of adaptation in human communities that depend on this changing marine environment. For example, communities that depend on services provided by coral reefs may need to locate alternative foundations for their economies. The fishery industry will need to adapt to changes in fish abundance, timing and location. Most of the things we would like to do to increase the adaptive capacity of marine ecosystems (e.g., reduce fishing pressure, reduce coastal pollution, preserve coastal wetlands) are things that would make sense to do even in

Active Hearing Mechanisms Inspire Adaptive Amplification in an Acoustic Sensor System.

Science.gov (United States)

Guerreiro, Jose; Reid, Andrew; Jackson, Joseph C; Windmill, James F C

2018-06-01

Over many millions of years of evolution, nature has developed some of the most adaptable sensors and sensory systems possible, capable of sensing, conditioning and processing signals in a very power- and size-effective manner. By looking into biological sensors and systems as a source of inspiration, this paper presents the study of a bioinspired concept of signal processing at the sensor level. By exploiting a feedback control mechanism between a front-end acoustic receiver and back-end neuronal based computation, a nonlinear amplification with hysteretic behavior is created. Moreover, the transient response of the front-end acoustic receiver can also be controlled and enhanced. A theoretical model is proposed and the concept is prototyped experimentally through an embedded system setup that can provide dynamic adaptations of a sensory system comprising a MEMS microphone placed in a closed-loop feedback system. It faithfully mimics the mosquito's active hearing response as a function of the input sound intensity. This is an adaptive acoustic sensor system concept that can be exploited by sensor and system designers within acoustics and ultrasonic engineering fields.

Coupled sensor/platform control design for low-level chemical detection with position-adaptive micro-UAVs

Science.gov (United States)

Goodwin, Thomas; Carr, Ryan; Mitra, Atindra K.; Selmic, Rastko R.

2009-05-01

We discuss the development of Position-Adaptive Sensors [1] for purposes for detecting embedded chemical substances in challenging environments. This concept is a generalization of patented Position-Adaptive Radar Concepts developed at AFRL for challenging conditions such as urban environments. For purposes of investigating the detection of chemical substances using multiple MAV (Micro-UAV) platforms, we have designed and implemented an experimental testbed with sample structures such as wooden carts that contain controlled leakage points. Under this general concept, some of the members of a MAV swarm can serve as external position-adaptive "transmitters" by blowing air over the cart and some of the members of a MAV swarm can serve as external position-adaptive "receivers" that are equipped with chemical or biological (chem/bio) sensors that function as "electronic noses". The objective can be defined as improving the particle count of chem/bio concentrations that impinge on a MAV-based position-adaptive sensor that surrounds a chemical repository, such as a cart, via the development of intelligent position-adaptive control algorithms. The overall effect is to improve the detection and false-alarm statistics of the overall system. Within the major sections of this paper, we discuss a number of different aspects of developing our initial MAV-Based Sensor Testbed. This testbed includes blowers to simulate position-adaptive excitations and a MAV from Draganfly Innovations Inc. with stable design modifications to accommodate our chem/bio sensor boom design. We include details with respect to several critical phases of the development effort including development of the wireless sensor network and experimental apparatus, development of the stable sensor boom for the MAV, integration of chem/bio sensors and sensor node onto the MAV and boom, development of position-adaptive control algorithms and initial tests at IDCAST (Institute for the Development and

An Adaptive Sensor Mining Framework for Pervasive Computing Applications

Science.gov (United States)

Rashidi, Parisa; Cook, Diane J.

Analyzing sensor data in pervasive computing applications brings unique challenges to the KDD community. The challenge is heightened when the underlying data source is dynamic and the patterns change. We introduce a new adaptive mining framework that detects patterns in sensor data, and more importantly, adapts to the changes in the underlying model. In our framework, the frequent and periodic patterns of data are first discovered by the Frequent and Periodic Pattern Miner (FPPM) algorithm; and then any changes in the discovered patterns over the lifetime of the system are discovered by the Pattern Adaptation Miner (PAM) algorithm, in order to adapt to the changing environment. This framework also captures vital context information present in pervasive computing applications, such as the startup triggers and temporal information. In this paper, we present a description of our mining framework and validate the approach using data collected in the CASAS smart home testbed.

Calibration Uncertainty in Ocean Color Satellite Sensors and Trends in Long-term Environmental Records

Science.gov (United States)

Turpie, Kevin R.; Eplee, Robert E., Jr.; Franz, Bryan A.; Del Castillo, Carlos

2014-01-01

Launched in late 2011, the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (NPP) spacecraft is being evaluated by NASA to determine whether this sensor can continue the ocean color data record established through the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) and the MODerate resolution Imaging Spectroradiometer (MODIS). To this end, Goddard Space Flight Center generated evaluation ocean color data products using calibration techniques and algorithms established by NASA during the SeaWiFS and MODIS missions. The calibration trending was subjected to some initial sensitivity and uncertainty analyses. Here we present an introductory assessment of how the NASA-produced time series of ocean color is influenced by uncertainty in trending instrument response over time. The results help quantify the uncertainty in measuring regional and global biospheric trends in the ocean using satellite remote sensing, which better define the roles of such records in climate research.

Ocean Optics Protocols for Satellite Ocean Color Sensor Validation. Revised

Science.gov (United States)

Fargion, Giulietta S.; Mueller, James L.

2000-01-01

The document stipulates protocols for measuring bio-optical and radiometric data for the Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) Project activities and algorithm development. This document supersedes the earlier version (Mueller and Austin 1995) published as Volume 25 in the SeaWiFS Technical Report Series. This document marks a significant departure from, and improvement on, theformat and content of Mueller and Austin (1995). The authorship of the protocols has been greatly broadened to include experts specializing in some key areas. New chapters have been added to provide detailed and comprehensive protocols for stability monitoring of radiometers using portable sources, abovewater measurements of remote-sensing reflectance, spectral absorption measurements for discrete water samples, HPLC pigment analysis and fluorometric pigment analysis. Protocols were included in Mueller and Austin (1995) for each of these areas, but the new treatment makes significant advances in each topic area. There are also new chapters prescribing protocols for calibration of sun photometers and sky radiance sensors, sun photometer and sky radiance measurements and analysis, and data archival. These topic areas were barely mentioned in Mueller and Austin (1995).

A New, Adaptable, Optical High-Resolution 3-Axis Sensor

Directory of Open Access Journals (Sweden)

Niels Buchhold

2017-01-01

Full Text Available This article presents a new optical, multi-functional, high-resolution 3-axis sensor which serves to navigate and can, for example, replace standard joysticks in medical devices such as electric wheelchairs, surgical robots or medical diagnosis devices. A light source, e.g., a laser diode, is affixed to a movable axis and projects a random geometric shape on an image sensor (CMOS or CCD. The downstream microcontroller’s software identifies the geometric shape’s center, distortion and size, and then calculates x, y, and z coordinates, which can be processed in attached devices. Depending on the image sensor in use (e.g., 6.41 megapixels, the 3-axis sensor features a resolution of 1544 digits from right to left and 1038 digits up and down. Through interpolation, these values rise by a factor of 100. A unique feature is the exact reproducibility (deflection to coordinates and its precise ability to return to its neutral position. Moreover, optical signal processing provides a high level of protection against electromagnetic and radio frequency interference. The sensor is adaptive and adjustable to fit a user’s range of motion (stroke and force. This recommendation aims to optimize sensor systems such as joysticks in medical devices in terms of safety, ease of use, and adaptability.

Coastal Adaptation: The Case of Ocean Beach, San Francisco

Science.gov (United States)

Cheong, S.

2012-12-01

Coastal erosion, storms, sea-level rise, and tsunamis all lead to inundation that puts people and communities at risk. Adapting to these coastal hazards has gained increasing attention with climate change. Instead of promoting one particular strategy such as seawalls or defending against one type of hazard, scholars and practitioners encourage a combination of existing methods and strategies to promote synergistic effects. The recently published Intergovernmental Panel on Climate Change (IPCC) Special Report on climate extremes reflects this trend in the integration of disaster risk management and climate change adaptation. This paper focuses on the roles, compatibilities, and synergies of three coastal adaptation options - engineering, vegetation, and policy - in the case of Ocean Beach in San Francisco. Traditionally engineering approach and ecosystem conservation often have stood in opposition as hard shoreline structures destroy coastal habitats, worsen coastal erosion, divert ocean currents, and prevent the natural migration of shores. A natural migration of shores without structure translates into the abandonment of properties in the coastal zone, and is at odds with property rights and development. For example, policies of relocation, retreat, and insurance may not be popular given the concerns of infrastructure and coastal access. As such, engineering, natural defense, and policy can be more conflictual than complementary. Nonetheless, all these responses are used in combination in many locations. Complementarities and compatibilities, therefore, must be assessed when considering the necessity of engineering responses, natural defense capabilities, and policy options. In this light, the question is how to resolve the problem of mixed responses and short- and long-term interests and values, identify compatibilities, and generate synergies. In the case of Ocean Beach, recent erosions that endangered San Francisco's wastewater treatment system acted as major

Evolving RBF neural networks for adaptive soft-sensor design.

Science.gov (United States)

Alexandridis, Alex

2013-12-01

This work presents an adaptive framework for building soft-sensors based on radial basis function (RBF) neural network models. The adaptive fuzzy means algorithm is utilized in order to evolve an RBF network, which approximates the unknown system based on input-output data from it. The methodology gradually builds the RBF network model, based on two separate levels of adaptation: On the first level, the structure of the hidden layer is modified by adding or deleting RBF centers, while on the second level, the synaptic weights are adjusted with the recursive least squares with exponential forgetting algorithm. The proposed approach is tested on two different systems, namely a simulated nonlinear DC Motor and a real industrial reactor. The results show that the produced soft-sensors can be successfully applied to model the two nonlinear systems. A comparison with two different adaptive modeling techniques, namely a dynamic evolving neural-fuzzy inference system (DENFIS) and neural networks trained with online backpropagation, highlights the advantages of the proposed methodology.

Testbeam Studies on Pick-Up in Sensors with Embedded Pitch Adapters

CERN Document Server

Rehnisch, Laura; The ATLAS collaboration

2018-01-01

Embedded pitch adapters are an alternative solution to external pitch adapters widely used to facilitate the wire-bonding step when connecting silicon strip sensors and readout electronics of different pitch. The pad-pitch adaption can be moved into the sensor fabrication step by implementing a second layer of metal tracks, connected by vias to the primary metal layer of sensor strips. Such a solution, however, might bear the risk of performance losses introduced by various phenomena. One of these effects, the undesired capacitive coupling between the silicon bulk and this second metal layer (pick-up) has been investigated in photon testbeam measurements. For a worst-case embedded pitch adapter design, expected to be maximally susceptible to pick-up, a qualitative analysis has visualized the effect as a function of the location on the second metal layer structure. It was further found that the unwanted effect decreases towards expected values for operating thresholds of the binary readout used. Suggestions fo...

Interference mitigation through adaptive power control in wireless sensor networks

NARCIS (Netherlands)

Chincoli, M.; Bacchiani, C.; Syed, Aly; Exarchakos, G.; Liotta, A.

2016-01-01

Adaptive transmission power control schemes have been introduced in wireless sensor networks to adjust energy consumption under different network conditions. This is a crucial goal, given the constraints under which sensor communications operate. Power reduction may however have counter-productive

Ship Sensor Observations for Deep Sea Medicines 2003 - Office of Ocean Exploration

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Hourly measurements made by selected ship sensors on the NOAA ship Ronald H. Brown during the "Deep Sea Medicines 2003: Exploration of the Gulf of Mexico" expedition...

Multimode Adaptable Microwave Radar Sensor Based on Leaky-Wave Antennas

Czech Academy of Sciences Publication Activity Database

Hudec, P.; Pánek, Petr; Jeník, V.

2017-01-01

Roč. 65, č. 9 (2017), s. 3464-3473 ISSN 0018-9480 Institutional support: RVO:67985882 Keywords : adaptable sensor * low-range radar * multimode sensor Subject RIV: JA - Electronics ; Optoelectronics, Electrical Engineering OBOR OECD: Electrical and electronic engineering Impact factor: 2.897, year: 2016

Acclimatization and Adaptive Capacity of Marine Species in a Changing Ocean.

Science.gov (United States)

Foo, S A; Byrne, M

To persist in an ocean changing in temperature, pH and other stressors related to climate change, many marine species will likely need to acclimatize or adapt to avoid extinction. If marine populations possess adequate genetic variation in tolerance to climate change stressors, species might be able to adapt to environmental change. Marine climate change research is moving away from single life stage studies where individuals are directly placed into projected scenarios ('future shock' approach), to focus on the adaptive potential of populations in an ocean that will gradually change over coming decades. This review summarizes studies that consider the adaptive potential of marine invertebrates to climate change stressors and the methods that have been applied to this research, including quantitative genetics, laboratory selection studies and trans- and multigenerational experiments. Phenotypic plasticity is likely to contribute to population persistence providing time for genetic adaptation to occur. Transgenerational and epigenetic effects indicate that the environmental and physiological history of the parents can affect offspring performance. There is a need for long-term, multigenerational experiments to determine the influence of phenotypic plasticity, genetic variation and transgenerational effects on species' capacity to persist in a changing ocean. However, multigenerational studies are only practicable for short generation species. Consideration of multiple morphological and physiological traits, including changes in molecular processes (eg, DNA methylation) and long-term studies that facilitate acclimatization will be essential in making informed predictions of how the seascape and marine communities will be altered by climate change. © 2016 Elsevier Ltd. All rights reserved.

An Adaptive Fault-Tolerant Communication Scheme for Body Sensor Networks

Directory of Open Access Journals (Sweden)

Zichuan Xu

2010-10-01

Full Text Available A high degree of reliability for critical data transmission is required in body sensor networks (BSNs. However, BSNs are usually vulnerable to channel impairments due to body fading effect and RF interference, which may potentially cause data transmission to be unreliable. In this paper, an adaptive and flexible fault-tolerant communication scheme for BSNs, namely AFTCS, is proposed. AFTCS adopts a channel bandwidth reservation strategy to provide reliable data transmission when channel impairments occur. In order to fulfill the reliability requirements of critical sensors, fault-tolerant priority and queue are employed to adaptively adjust the channel bandwidth allocation. Simulation results show that AFTCS can alleviate the effect of channel impairments, while yielding lower packet loss rate and latency for critical sensors at runtime.

Vulnerability and adaptation of US shellfisheries to ocean acidification

NARCIS (Netherlands)

Ekstrom, Julia A.; Suatoni, Lisa; Cooley, Sarah R.; Pendleton, Linwood H.; Waldbusser, George G.; Cinner, Josh E.; Ritter, Jessica; Langdon, Chris; Van Hooidonk, Ruben; Gledhill, Dwight; Wellman, Katharine; Beck, Michael W.; Brander, Luke M.; Rittschof, Dan; Doherty, Carolyn; Edwards, Peter E.T.; Portela, Rosimeiry

2015-01-01

Ocean acidification is a global, long-term problem whose ultimate solution requires carbon dioxide reduction at a scope and scale that will take decades to accomplish successfully. Until that is achieved, feasible and locally relevant adaptation and mitigation measures are needed. To help to

Sensor Virtual Adaptable de Concentración de Etanol para Fermentadores Industriales

Directory of Open Access Journals (Sweden)

Boris Martínez

2009-07-01

Full Text Available Resumen: Los sistemas de control emplean sensores para observar el estado del proceso y tomar decisiones. En ocasiones, se necesita estimar las variables del proceso pues el sensor adecuado no existe, es prohibitivamente costoso o las mediciones son difíciles de realizar. Una solución consiste en inferir las variables no medidas a partir de otras variables mediante sensores virtuales o sensores por software (soft-sensors. En los procesos de fermentación alcohólica, la medición de la concentración del etanol es esencial. Sin embargo, no existen sensores baratos y confiables para medirla en línea ni existe una solución aceptada por todos del modelado de dicha variable. Además, las fermentaciones nunca son iguales pues los microorganismos son muy sensibles a pequeñas desviaciones en las variables involucradas. Por tanto, estos procesos requieren un sistema de estimación adaptable y altamente robusto. En este trabajo se presenta un sensor virtual adaptable para un proceso fermentativo de bioetanol empleando un modelo borroso evolutivo a partir de datos del proceso. Además, el modelo obtenido es compacto y presenta una estructura adecuada para su aplicación futura en estrategias de control, en aras de optimizar la productividad del proceso y disminuir los costos de producción. Palabras clave: bioetanol, procesos fermentativos, sensores virtuales o sensores software, sistemas adaptables, sistemas borrosos

Adaptive subdomain modeling: A multi-analysis technique for ocean circulation models

Science.gov (United States)

Altuntas, Alper; Baugh, John

2017-07-01

Many coastal and ocean processes of interest operate over large temporal and geographical scales and require a substantial amount of computational resources, particularly when engineering design and failure scenarios are also considered. This study presents an adaptive multi-analysis technique that improves the efficiency of these computations when multiple alternatives are being simulated. The technique, called adaptive subdomain modeling, concurrently analyzes any number of child domains, with each instance corresponding to a unique design or failure scenario, in addition to a full-scale parent domain providing the boundary conditions for its children. To contain the altered hydrodynamics originating from the modifications, the spatial extent of each child domain is adaptively adjusted during runtime depending on the response of the model. The technique is incorporated in ADCIRC++, a re-implementation of the popular ADCIRC ocean circulation model with an updated software architecture designed to facilitate this adaptive behavior and to utilize concurrent executions of multiple domains. The results of our case studies confirm that the method substantially reduces computational effort while maintaining accuracy.

Extending the Lifetime of Sensor Networks through Adaptive Reclustering

Directory of Open Access Journals (Sweden)

Gianluigi Ferrari

2007-06-01

Full Text Available We analyze the lifetime of clustered sensor networks with decentralized binary detection under a physical layer quality-of-service (QoS constraint, given by the maximum tolerable probability of decision error at the access point (AP. In order to properly model the network behavior, we consider four different distributions (exponential, uniform, Rayleigh, and lognormal for the lifetime of a single sensor. We show the benefits, in terms of longer network lifetime, of adaptive reclustering. We also derive an analytical framework for the computation of the network lifetime and the penalty, in terms of time delay and energy consumption, brought by adaptive reclustering. On the other hand, absence of reclustering leads to a shorter network lifetime, and we show the impact of various clustering configurations under different QoS conditions. Our results show that the organization of sensors in a few big clusters is the winning strategy to maximize the network lifetime. Moreover, the observation of the phenomenon should be frequent in order to limit the penalties associated with the reclustering procedure. We also apply the developed framework to analyze the energy consumption associated with the proposed reclustering protocol, obtaining results in good agreement with the performance of realistic wireless sensor networks. Finally, we present simulation results on the lifetime of IEEE 802.15.4 wireless sensor networks, which enrich the proposed analytical framework and show that typical networking performance metrics (such as throughput and delay are influenced by the sensor network lifetime.

Extending the Lifetime of Sensor Networks through Adaptive Reclustering

Directory of Open Access Journals (Sweden)

Ferrari Gianluigi

2007-01-01

Full Text Available We analyze the lifetime of clustered sensor networks with decentralized binary detection under a physical layer quality-of-service (QoS constraint, given by the maximum tolerable probability of decision error at the access point (AP. In order to properly model the network behavior, we consider four different distributions (exponential, uniform, Rayleigh, and lognormal for the lifetime of a single sensor. We show the benefits, in terms of longer network lifetime, of adaptive reclustering. We also derive an analytical framework for the computation of the network lifetime and the penalty, in terms of time delay and energy consumption, brought by adaptive reclustering. On the other hand, absence of reclustering leads to a shorter network lifetime, and we show the impact of various clustering configurations under different QoS conditions. Our results show that the organization of sensors in a few big clusters is the winning strategy to maximize the network lifetime. Moreover, the observation of the phenomenon should be frequent in order to limit the penalties associated with the reclustering procedure. We also apply the developed framework to analyze the energy consumption associated with the proposed reclustering protocol, obtaining results in good agreement with the performance of realistic wireless sensor networks. Finally, we present simulation results on the lifetime of IEEE 802.15.4 wireless sensor networks, which enrich the proposed analytical framework and show that typical networking performance metrics (such as throughput and delay are influenced by the sensor network lifetime.

Adapting Mobile Beacon-Assisted Localization in Wireless Sensor Networks

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Wei Dong

2009-04-01

Full Text Available The ability to automatically locate sensor nodes is essential in many Wireless Sensor Network (WSN applications. To reduce the number of beacons, many mobile-assisted approaches have been proposed. Current mobile-assisted approaches for localization require special hardware or belong to centralized localization algorithms involving some deterministic approaches due to the fact that they explicitly consider the impreciseness of location estimates. In this paper, we first propose a range-free, distributed and probabilistic Mobile Beacon-assisted Localization (MBL approach for static WSNs. Then, we propose another approach based on MBL, called Adapting MBL (A-MBL, to increase the efficiency and accuracy of MBL by adapting the size of sample sets and the parameter of the dynamic model during the estimation process. Evaluation results show that the accuracy of MBL and A-MBL outperform both Mobile and Static sensor network Localization (MSL and Arrival and Departure Overlap (ADO when both of them use only a single mobile beacon for localization in static WSNs.

Adapting mobile beacon-assisted localization in wireless sensor networks.

Science.gov (United States)

Teng, Guodong; Zheng, Kougen; Dong, Wei

2009-01-01

The ability to automatically locate sensor nodes is essential in many Wireless Sensor Network (WSN) applications. To reduce the number of beacons, many mobile-assisted approaches have been proposed. Current mobile-assisted approaches for localization require special hardware or belong to centralized localization algorithms involving some deterministic approaches due to the fact that they explicitly consider the impreciseness of location estimates. In this paper, we first propose a range-free, distributed and probabilistic Mobile Beacon-assisted Localization (MBL) approach for static WSNs. Then, we propose another approach based on MBL, called Adapting MBL (A-MBL), to increase the efficiency and accuracy of MBL by adapting the size of sample sets and the parameter of the dynamic model during the estimation process. Evaluation results show that the accuracy of MBL and A-MBL outperform both Mobile and Static sensor network Localization (MSL) and Arrival and Departure Overlap (ADO) when both of them use only a single mobile beacon for localization in static WSNs.

Embedded pitch adapters: A high-yield interconnection solution for strip sensors

Energy Technology Data Exchange (ETDEWEB)

Ullán, M., E-mail: miguel.ullan@imb-cnm.csic.es [Centro Nacional de Microelectronica (IMB-CNM, CSIC), Campus UAB-Bellaterra, 08193 Barcelona (Spain); Allport, P.P.; Baca, M.; Broughton, J.; Chisholm, A.; Nikolopoulos, K.; Pyatt, S.; Thomas, J.P.; Wilson, J.A. [School of Physics and Astronomy, University of Birmingham, Birmingham B15 2TT (United Kingdom); Kierstead, J.; Kuczewski, P.; Lynn, D. [Brookhaven National Laboratory, Physics Department and Instrumentation Division, Upton, NY 11973-5000 (United States); Hommels, L.B.A. [Cavendish Laboratory, University of Cambridge, JJ Thomson Avenue, Cambridge CB3 0HE (United Kingdom); Fleta, C.; Fernandez-Tejero, J.; Quirion, D. [Centro Nacional de Microelectronica (IMB-CNM, CSIC), Campus UAB-Bellaterra, 08193 Barcelona (Spain); Bloch, I.; Díez, S.; Gregor, I.M.; Lohwasser, K. [DESY, Notkestrasse 85, 22607 Hamburg (Germany); and others

2016-09-21

A proposal to fabricate large area strip sensors with integrated, or embedded, pitch adapters is presented for the End-cap part of the Inner Tracker in the ATLAS experiment. To implement the embedded pitch adapters, a second metal layer is used in the sensor fabrication, for signal routing to the ASICs. Sensors with different embedded pitch adapters have been fabricated in order to optimize the design and technology. Inter-strip capacitance, noise, pick-up, cross-talk, signal efficiency, and fabrication yield have been taken into account in their design and fabrication. Inter-strip capacitance tests taking into account all channel neighbors reveal the important differences between the various designs considered. These tests have been correlated with noise figures obtained in full assembled modules, showing that the tests performed on the bare sensors are a valid tool to estimate the final noise in the full module. The full modules have been subjected to test beam experiments in order to evaluate the incidence of cross-talk, pick-up, and signal loss. The detailed analysis shows no indication of cross-talk or pick-up as no additional hits can be observed in any channel not being hit by the beam above 170 mV threshold, and the signal in those channels is always below 1% of the signal recorded in the channel being hit, above 100 mV threshold. First results on irradiated mini-sensors with embedded pitch adapters do not show any change in the interstrip capacitance measurements with only the first neighbors connected.

Ship Sensor Observations for Investigating the Charleston Bump 2003 - Office of Ocean Exploration

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National Oceanic and Atmospheric Administration, Department of Commerce — Hourly measurements made by selected ship sensors on the R/V Seward Johnson during the "Investigating the Charleston Bump 2003" expedition sponsored by the National...

Ship Sensor Observations for North Atlantic Stepping Stones 2005 - Office of Ocean Exploration

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National Oceanic and Atmospheric Administration, Department of Commerce — Hourly measurements made by selected ship sensors on the NOAA ship Ronald H. Brown during the "North Atlantic Stepping Stones 2005" expedition sponsored by the...

Oxygen Optode Sensors: Principle, Characterization, Calibration, and Application in the Ocean

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Henry C. Bittig

2018-01-01

Full Text Available Recently, measurements of oxygen concentration in the ocean—one of the most classical parameters in chemical oceanography—are experiencing a revival. This is not surprising, given the key role of oxygen for assessing the status of the marine carbon cycle and feeling the pulse of the biological pump. The revival, however, has to a large extent been driven by the availability of robust optical oxygen sensors and their painstakingly thorough characterization. For autonomous observations, oxygen optodes are the sensors of choice: They are used abundantly on Biogeochemical-Argo floats, gliders and other autonomous oceanographic observation platforms. Still, data quality and accuracy are often suboptimal, in some part because sensor and data treatment are not always straightforward and/or sensor characteristics are not adequately taken into account. Here, we want to summarize the current knowledge about oxygen optodes, their working principle as well as their behavior with respect to oxygen, temperature, hydrostatic pressure, and response time. The focus will lie on the most widely used and accepted optodes made by Aanderaa and Sea-Bird. We revisit the essentials and caveats of in-situ in air calibration as well as of time response correction for profiling applications, and provide requirements for a successful field deployment. In addition, all required steps to post-correct oxygen optode data will be discussed. We hope this summary will serve as a comprehensive, yet concise reference to help people get started with oxygen observations, ensure successful sensor deployments and acquisition of highest quality data, and facilitate post-treatment of oxygen data. In the end, we hope that this will lead to more and higher-quality oxygen observations and help to advance our understanding of ocean biogeochemistry in a changing ocean.

An adaptive Kalman filter approach for cardiorespiratory signal extraction and fusion of non-contacting sensors.

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Foussier, Jerome; Teichmann, Daniel; Jia, Jing; Misgeld, Berno; Leonhardt, Steffen

2014-05-09

Extracting cardiorespiratory signals from non-invasive and non-contacting sensor arrangements, i.e. magnetic induction sensors, is a challenging task. The respiratory and cardiac signals are mixed on top of a large and time-varying offset and are likely to be disturbed by measurement noise. Basic filtering techniques fail to extract relevant information for monitoring purposes. We present a real-time filtering system based on an adaptive Kalman filter approach that separates signal offsets, respiratory and heart signals from three different sensor channels. It continuously estimates respiration and heart rates, which are fed back into the system model to enhance performance. Sensor and system noise covariance matrices are automatically adapted to the aimed application, thus improving the signal separation capabilities. We apply the filtering to two different subjects with different heart rates and sensor properties and compare the results to the non-adaptive version of the same Kalman filter. Also, the performance, depending on the initialization of the filters, is analyzed using three different configurations ranging from best to worst case. Extracted data are compared with reference heart rates derived from a standard pulse-photoplethysmographic sensor and respiration rates from a flowmeter. In the worst case for one of the subjects the adaptive filter obtains mean errors (standard deviations) of -0.2 min(-1) (0.3 min(-1)) and -0.7 bpm (1.7 bpm) (compared to -0.2 min(-1) (0.4 min(-1)) and 42.0 bpm (6.1 bpm) for the non-adaptive filter) for respiration and heart rate, respectively. In bad conditions the heart rate is only correctly measurable when the Kalman matrices are adapted to the target sensor signals. Also, the reduced mean error between the extracted offset and the raw sensor signal shows that adapting the Kalman filter continuously improves the ability to separate the desired signals from the raw sensor data. The average total computational time needed

Speech Adaptation to Kinematic Recording Sensors: Perceptual and Acoustic Findings

Science.gov (United States)

Dromey, Christopher; Hunter, Elise; Nissen, Shawn L.

2018-01-01

Purpose: This study used perceptual and acoustic measures to examine the time course of speech adaptation after the attachment of electromagnetic sensor coils to the tongue, lips, and jaw. Method: Twenty native English speakers read aloud stimulus sentences before the attachment of the sensors, immediately after attachment, and again 5, 10, 15,…

Multifunctional Web Enabled Ocean Sensor Systems for the Monitoring of a Changing Ocean

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Pearlman, Jay; Castro, Ayoze; Corrandino, Luigi; del Rio, Joaquin; Delory, Eric; Garello, Rene; Heuermann, Rudinger; Martinez, Enoc; Pearlman, Francoise; Rolin, Jean-Francois; Toma, Daniel; Waldmann, Christoph; Zielinski, Oliver

2016-04-01

As stated in the 2010 "Ostend Declaration", a major challenge in the coming years is the development of a truly integrated and sustainably funded European Ocean Observing System for supporting major policy initiatives such as the Integrated Maritime Policy and the Marine Strategy Framework Directive. This will be achieved with more long-term measurements of key parameters supported by a new generation of sensors whose costs and reliability will enable broad and consistent observations. Within the NeXOS project, a framework including new sensors capabilities and interface software has been put together that embraces the key technical aspects needed to improve the temporal and spatial coverage, resolution and quality of marine observations. The developments include new, low-cost, compact and integrated sensors with multiple functionalities that will allow for the measurements useful for a number of objectives, ranging from more precise monitoring and modeling of the marine environment to an improved assessment of fisheries. The project is entering its third year and will be demonstrating initial capabilities of optical and acoustic sensor prototypes that will become available for a number of platforms. For fisheries management, there is also a series of sensors that support an Ecosystem Approach to Fisheries (EAF). The greatest capabilities for comprehensive operations will occur when these sensors can be integrated into a multisensory capability on a single platform or multiply interconnected and coordinated platforms. Within NeXOS the full processing steps starting from the sensor signal all the way up to distributing collected environmental information will be encapsulated into standardized new state of the art Smart Sensor Interface and Web components to provide both improved integration and a flexible interface for scientists to control sensor operation. The use of the OGC SWE (Sensor Web Enablement) set of standards like OGC PUCK and SensorML at the instrument

Combination Adaptive Traffic Algorithm and Coordinated Sleeping in Wireless Sensor Network

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M. Udin Harun Al Rasyid

2014-12-01

Full Text Available Wireless sensor network (WSN uses a battery as its primary power source, so that WSN will be limited to battery power for long operations. The WSN should be able to save the energy consumption in order to operate in a long time.WSN has the potential to be the future of wireless communications solutions. WSN are small but has a variety of functions that can help human life. WSN has the wide variety of sensors and can communicate quickly making it easier for people to obtain information accurately and quickly. In this study, we combine adaptive traffic algorithms and coordinated sleeping as power‐efficient WSN solution. We compared the performance of our proposed ideas combination adaptive traffic and coordinated sleeping algorithm with non‐adaptive scheme. From the simulation results, our proposed idea has good‐quality data transmission and more efficient in energy consumption, but it has higher delay than that of non‐adaptive scheme. Keywords:WSN,adaptive traffic,coordinated sleeping,beacon order,superframe order.

Ocean Optics Protocols for Satellite Ocean Color Sensor Validation. Volume 2; Revised

Science.gov (United States)

Mueller, James L. (Editor); Fargion, Giulietta S. (Editor); Trees, C.; Austin, R. W.; Pietras, C. (Editor); Hooker, S.; Holben, B.; McClain, Charles R.; Clark, D. K.; Yuen, M.

2002-01-01

This document stipulates protocols for measuring bio-optical and radiometric data for the SIMBIOS Project. It supersedes the earlier version, and is organized into four parts: Introductory Background, Instrument Characteristics, Field Measurements and Data Analysis, Data Reporting and Archival. Changes in this revision include the addition of three new chapters: (1) Fundamental Definitions, Relationships and Conventions; (2) MOBY, A Radiometric Buoy for Performance Monitoring and Vicarious Calibration of Satellite Ocean Color Sensors: Measurement and Data Analysis Protocols; and (3) Normalized Water-Leaving Radiance and Remote Sensing Reflectance: Bidirectional Reflectance and Other Factors. Although the present document represents another significant, incremental improvement in the ocean optics protocols, there are several protocols that have either been overtaken by recent technological progress, or have been otherwise identified as inadequate. Revision 4 is scheduled for completion sometime in 2003. This technical report is not meant as a substitute for scientific literature. Instead, it will provide a ready and responsive vehicle for the multitude of technical reports issued by an operational Project. The contributions are published as submitted, after only minor editing to correct obvious grammatical or clerical errors.

Ocean Optics Protocols for Satellite Ocean Color Sensor Validation. Volume 1; Revised

Science.gov (United States)

Mueller, James L. (Editor); Fargion, Giulietta (Editor); Mueller, J. L.; Trees, C.; Austin, R. W.; Pietras, C.; Hooker, S.; Holben, B.; McClain, Charles R.; Clark, D. K.;

Sensor-centric calibration and characterization of the VIIRS Ocean Color bands using Suomi NPP operational data

Science.gov (United States)

Pratt, P.

2012-12-01

Ocean color bands on VIIRS span the visible spectrum and include two NIR bands. There are sixteen detectors per band and two HAM (Half-angle mirror) sides giving a total of thirty two independent systems. For each scan, thirty two hundred pixels are collected and each has a fixed specific optical path and a dynamic position relative to the earth geoid. For a given calibration target where scene variation is minimized, sensor characteristics can be observed. This gives insight into the performance and calibration of the instrument from a sensor-centric perspective. Calibration of the blue bands is especially challenging since there are few blue targets on land. An ocean region called the South Pacific Gyre (SPG) was chosen for its known stability and large area to serve as a calibration target for this investigation. Thousands of pixels from every granule that views the SPG are collected daily through an automated system and tabulated along with the detector, HAM and scan position. These are then collated and organized in a sensor-centric set of tables. The data are then analyzed by slicing by each variable and then plotted in a number of ways over time. Trends in the data show that the VIIRS sensor is largely behaving as expected according to heritage data and also reveals weaknesses where additional characterization of the sensor is possible. This work by Northrop Grumman NPP CalVal Team is supporting the VIIRS on-orbit calibration and validation teams for the sensor and ocean color as well as providing scientists interested in performing ground truth with results that show which detectors and scan angles are the most reliable over time. This novel approach offers a comprehensive sensor-centric on-orbit characterization of the VIIRS instrument on the NASA Suomi NPP mission.

Adaptive LINE-P: An Adaptive Linear Energy Prediction Model for Wireless Sensor Network Nodes.

Science.gov (United States)

Ahmed, Faisal; Tamberg, Gert; Le Moullec, Yannick; Annus, Paul

2018-04-05

In the context of wireless sensor networks, energy prediction models are increasingly useful tools that can facilitate the power management of the wireless sensor network (WSN) nodes. However, most of the existing models suffer from the so-called fixed weighting parameter, which limits their applicability when it comes to, e.g., solar energy harvesters with varying characteristics. Thus, in this article we propose the Adaptive LINE-P (all cases) model that calculates adaptive weighting parameters based on the stored energy profiles. Furthermore, we also present a profile compression method to reduce the memory requirements. To determine the performance of our proposed model, we have used real data for the solar and wind energy profiles. The simulation results show that our model achieves 90-94% accuracy and that the compressed method reduces memory overheads by 50% as compared to state-of-the-art models.

Environmentally adaptive processing for shallow ocean applications: A sequential Bayesian approach.

Science.gov (United States)

Candy, J V

2015-09-01

The shallow ocean is a changing environment primarily due to temperature variations in its upper layers directly affecting sound propagation throughout. The need to develop processors capable of tracking these changes implies a stochastic as well as an environmentally adaptive design. Bayesian techniques have evolved to enable a class of processors capable of performing in such an uncertain, nonstationary (varying statistics), non-Gaussian, variable shallow ocean environment. A solution to this problem is addressed by developing a sequential Bayesian processor capable of providing a joint solution to the modal function tracking and environmental adaptivity problem. Here, the focus is on the development of both a particle filter and an unscented Kalman filter capable of providing reasonable performance for this problem. These processors are applied to hydrophone measurements obtained from a vertical array. The adaptivity problem is attacked by allowing the modal coefficients and/or wavenumbers to be jointly estimated from the noisy measurement data along with tracking of the modal functions while simultaneously enhancing the noisy pressure-field measurements.

Dynamic reusable workflows for ocean science

Science.gov (United States)

Signell, Richard; Fernandez, Filipe; Wilcox, Kyle

2016-01-01

Digital catalogs of ocean data have been available for decades, but advances in standardized services and software for catalog search and data access make it now possible to create catalog-driven workflows that automate — end-to-end — data search, analysis and visualization of data from multiple distributed sources. Further, these workflows may be shared, reused and adapted with ease. Here we describe a workflow developed within the US Integrated Ocean Observing System (IOOS) which automates the skill-assessment of water temperature forecasts from multiple ocean forecast models, allowing improved forecast products to be delivered for an open water swim event. A series of Jupyter Notebooks are used to capture and document the end-to-end workflow using a collection of Python tools that facilitate working with standardized catalog and data services. The workflow first searches a catalog of metadata using the Open Geospatial Consortium (OGC) Catalog Service for the Web (CSW), then accesses data service endpoints found in the metadata records using the OGC Sensor Observation Service (SOS) for in situ sensor data and OPeNDAP services for remotely-sensed and model data. Skill metrics are computed and time series comparisons of forecast model and observed data are displayed interactively, leveraging the capabilities of modern web browsers. The resulting workflow not only solves a challenging specific problem, but highlights the benefits of dynamic, reusable workflows in general. These workflows adapt as new data enters the data system, facilitate reproducible science, provide templates from which new scientific workflows can be developed, and encourage data providers to use standardized services. As applied to the ocean swim event, the workflow exposed problems with two of the ocean forecast products which led to improved regional forecasts once errors were corrected. While the example is specific, the approach is general, and we hope to see increased use of dynamic

Dynamic Reusable Workflows for Ocean Science

Directory of Open Access Journals (Sweden)

Richard P. Signell

2016-10-01

Full Text Available Digital catalogs of ocean data have been available for decades, but advances in standardized services and software for catalog searches and data access now make it possible to create catalog-driven workflows that automate—end-to-end—data search, analysis, and visualization of data from multiple distributed sources. Further, these workflows may be shared, reused, and adapted with ease. Here we describe a workflow developed within the US Integrated Ocean Observing System (IOOS which automates the skill assessment of water temperature forecasts from multiple ocean forecast models, allowing improved forecast products to be delivered for an open water swim event. A series of Jupyter Notebooks are used to capture and document the end-to-end workflow using a collection of Python tools that facilitate working with standardized catalog and data services. The workflow first searches a catalog of metadata using the Open Geospatial Consortium (OGC Catalog Service for the Web (CSW, then accesses data service endpoints found in the metadata records using the OGC Sensor Observation Service (SOS for in situ sensor data and OPeNDAP services for remotely-sensed and model data. Skill metrics are computed and time series comparisons of forecast model and observed data are displayed interactively, leveraging the capabilities of modern web browsers. The resulting workflow not only solves a challenging specific problem, but highlights the benefits of dynamic, reusable workflows in general. These workflows adapt as new data enter the data system, facilitate reproducible science, provide templates from which new scientific workflows can be developed, and encourage data providers to use standardized services. As applied to the ocean swim event, the workflow exposed problems with two of the ocean forecast products which led to improved regional forecasts once errors were corrected. While the example is specific, the approach is general, and we hope to see increased

Noise-exploitation and adaptation in neuromorphic sensors

Science.gov (United States)

Hindo, Thamira; Chakrabartty, Shantanu

2012-04-01

Even though current micro-nano fabrication technology has reached integration levels where ultra-sensitive sensors can be fabricated, the sensing performance (resolution per joule) of synthetic systems are still orders of magnitude inferior to those observed in neurobiology. For example, the filiform hairs in crickets operate at fundamental limits of noise; auditory sensors in a parasitoid fly can overcome fundamental limitations to precisely localize ultra-faint acoustic signatures. Even though many of these biological marvels have served as inspiration for different types of neuromorphic sensors, the main focus these designs have been to faithfully replicate the biological functionalities, without considering the constructive role of "noise". In man-made sensors device and sensor noise are typically considered as a nuisance, where as in neurobiology "noise" has been shown to be a computational aid that enables biology to sense and operate at fundamental limits of energy efficiency and performance. In this paper, we describe some of the important noise-exploitation and adaptation principles observed in neurobiology and how they can be systematically used for designing neuromorphic sensors. Our focus will be on two types of noise-exploitation principles, namely, (a) stochastic resonance; and (b) noise-shaping, which are unified within our previously reported framework called Σ▵ learning. As a case-study, we describe the application of Σ▵ learning for the design of a miniature acoustic source localizer whose performance matches that of its biological counterpart(Ormia Ochracea).

Secure Adaptive Topology Control for Wireless Ad-Hoc Sensor Networks

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Yen-Chieh Ouyang

2010-02-01

Full Text Available This paper presents a secure decentralized clustering algorithm for wireless ad-hoc sensor networks. The algorithm operates without a centralized controller, operates asynchronously, and does not require that the location of the sensors be known a priori. Based on the cluster-based topology, secure hierarchical communication protocols and dynamic quarantine strategies are introduced to defend against spam attacks, since this type of attacks can exhaust the energy of sensor nodes and will shorten the lifetime of a sensor network drastically. By adjusting the threshold of infected percentage of the cluster coverage, our scheme can dynamically coordinate the proportion of the quarantine region and adaptively achieve the cluster control and the neighborhood control of attacks. Simulation results show that the proposed approach is feasible and cost effective for wireless sensor networks.

Taking Poseidon's Measure from Space: Advances in our Understanding of the Ocean

Science.gov (United States)

Avery, S. K.

2017-12-01

In many ways the ocean defines our planet and makes it livable. It provides marine resources and ecosystem services that are critical to a sustainable society. Today we understand that there is a growing need to predict, manage, and adapt to changes on our planet - changes that occur not only in the atmosphere but also in the ocean. Over the last 40 years remarkable advances in measuring key ocean quantities have been made - through the development of new satellite technologies and successful missions as well as through in-situ observing systems enabled by advances in robotics, communications, navigation, and sensors. Ocean science (and atmospheric science) is a science of numbers, imaging, and numerical models. Predictability of the ocean is tied to the scale of variability in space and time. Satellite observations have spectacularly showed us the incredible structure and variability of the ocean. It has been the combination of satellites and in-situ sensors that have allowed us to advance understanding and prediction. This presentation will highlight some of the key scientific advances that have been enabled by satellites.

Adaptive Energy-Efficient Target Detection Based on Mobile Wireless Sensor Networks

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Tengyue Zou

2017-05-01

Full Text Available Target detection is a widely used application for area surveillance, elder care, and fire alarms; its purpose is to find a particular object or event in a region of interest. Usually, fixed observing stations or static sensor nodes are arranged uniformly in the field. However, each part of the field has a different probability of being intruded upon; if an object suddenly enters an area with few guardian devices, a loss of detection will occur, and the stations in the safe areas will waste their energy for a long time without any discovery. Thus, mobile wireless sensor networks may benefit from adaptation and pertinence in detection. Sensor nodes equipped with wheels are able to move towards the risk area via an adaptive learning procedure based on Bayesian networks. Furthermore, a clustering algorithm based on k-means++ and an energy control mechanism is used to reduce the energy consumption of nodes. The extended Kalman filter and a voting data fusion method are employed to raise the localization accuracy of the target. The simulation and experimental results indicate that this new system with adaptive energy-efficient methods is able to achieve better performance than the traditional ones.

Adaptive Energy-Efficient Target Detection Based on Mobile Wireless Sensor Networks.

Science.gov (United States)

Zou, Tengyue; Li, Zhenjia; Li, Shuyuan; Lin, Shouying

2017-05-04

Target detection is a widely used application for area surveillance, elder care, and fire alarms; its purpose is to find a particular object or event in a region of interest. Usually, fixed observing stations or static sensor nodes are arranged uniformly in the field. However, each part of the field has a different probability of being intruded upon; if an object suddenly enters an area with few guardian devices, a loss of detection will occur, and the stations in the safe areas will waste their energy for a long time without any discovery. Thus, mobile wireless sensor networks may benefit from adaptation and pertinence in detection. Sensor nodes equipped with wheels are able to move towards the risk area via an adaptive learning procedure based on Bayesian networks. Furthermore, a clustering algorithm based on k -means++ and an energy control mechanism is used to reduce the energy consumption of nodes. The extended Kalman filter and a voting data fusion method are employed to raise the localization accuracy of the target. The simulation and experimental results indicate that this new system with adaptive energy-efficient methods is able to achieve better performance than the traditional ones.

Energy-efficient Organization of Wireless Sensor Networks with Adaptive Forecasting

Directory of Open Access Journals (Sweden)

Dao-Wei Bi

2008-04-01

Full Text Available Due to the wide potential applications of wireless sensor networks, this topic has attracted great attention. The strict energy constraints of sensor nodes result in great challenges for energy efficiency. This paper proposes an energy-efficient organization method. The organization of wireless sensor networks is formulated for target tracking. Target localization is achieved by collaborative sensing with multi-sensor fusion. The historical localization results are utilized for adaptive target trajectory forecasting. Combining autoregressive moving average (ARMA model and radial basis function networks (RBFNs, robust target position forecasting is performed. Moreover, an energyefficient organization method is presented to enhance the energy efficiency of wireless sensor networks. The sensor nodes implement sensing tasks are awakened in a distributed manner. When the sensor nodes transfer their observations to achieve data fusion, the routing scheme is obtained by ant colony optimization. Thus, both the operation and communication energy consumption can be minimized. Experimental results verify that the combination of ARMA model and RBFN can estimate the target position efficiently and energy saving is achieved by the proposed organization method in wireless sensor networks.

Multi-Sensor Optimal Data Fusion Based on the Adaptive Fading Unscented Kalman Filter.

Science.gov (United States)

Gao, Bingbing; Hu, Gaoge; Gao, Shesheng; Zhong, Yongmin; Gu, Chengfan

2018-02-06

This paper presents a new optimal data fusion methodology based on the adaptive fading unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has a two-level fusion structure: at the bottom level, an adaptive fading unscented Kalman filter based on the Mahalanobis distance is developed and serves as local filters to improve the adaptability and robustness of local state estimations against process-modeling error; at the top level, an unscented transformation-based multi-sensor optimal data fusion for the case of N local filters is established according to the principle of linear minimum variance to calculate globally optimal state estimation by fusion of local estimations. The proposed methodology effectively refrains from the influence of process-modeling error on the fusion solution, leading to improved adaptability and robustness of data fusion for multi-sensor nonlinear stochastic systems. It also achieves globally optimal fusion results based on the principle of linear minimum variance. Simulation and experimental results demonstrate the efficacy of the proposed methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite system/celestial navigation system) integrated navigation.

Ship Sensor Observations for Estuary to the Abyss 2004: Exploring Along the Latitude 31-30 Transect - Office of Ocean Exploration

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Hourly measurements made by selected ship sensors on the R/V Seward Johnson during the "Estuary to the Abyss 2004" expedition sponsored by the National Oceanic and...

Communal Sensor Network for Adaptive Noise Reduction in Aircraft Engine Nacelles

Science.gov (United States)

Jones, Kennie H.; Nark, Douglas M.; Jones, Michael G.

2011-01-01

Emergent behavior, a subject of much research in biology, sociology, and economics, is a foundational element of Complex Systems Science and is apropos in the design of sensor network systems. To demonstrate engineering for emergent behavior, a novel approach in the design of a sensor/actuator network is presented maintaining optimal noise attenuation as an adaptation to changing acoustic conditions. Rather than use the conventional approach where sensors are managed by a central controller, this new paradigm uses a biomimetic model where sensor/actuators cooperate as a community of autonomous organisms, sharing with neighbors to control impedance based on local information. From the combination of all individual actions, an optimal attenuation emerges for the global system.

Global Ocean Phytoplankton

Science.gov (United States)

Franz, B. A.; Behrenfeld, M. J.; Siegel, D. A.; Werdell, P. J.

2014-01-01

Marine phytoplankton are responsible for roughly half the net primary production (NPP) on Earth, fixing atmospheric CO2 into food that fuels global ocean ecosystems and drives the ocean's biogeochemical cycles. Phytoplankton growth is highly sensitive to variations in ocean physical properties, such as upper ocean stratification and light availability within this mixed layer. Satellite ocean color sensors, such as the Sea-viewing Wide Field-of-view Sensor (SeaWiFS; McClain 2009) and Moderate Resolution Imaging Spectroradiometer (MODIS; Esaias 1998), provide observations of sufficient frequency and geographic coverage to globally monitor physically-driven changes in phytoplankton distributions. In practice, ocean color sensors retrieve the spectral distribution of visible solar radiation reflected upward from beneath the ocean surface, which can then be related to changes in the photosynthetic phytoplankton pigment, chlorophyll- a (Chla; measured in mg m-3). Here, global Chla data for 2013 are evaluated within the context of the 16-year continuous record provided through the combined observations of SeaWiFS (1997-2010) and MODIS on Aqua (MODISA; 2002-present). Ocean color measurements from the recently launched Visible and Infrared Imaging Radiometer Suite (VIIRS; 2011-present) are also considered, but results suggest that the temporal calibration of the VIIRS sensor is not yet sufficiently stable for quantitative global change studies. All MODISA (version 2013.1), SeaWiFS (version 2010.0), and VIIRS (version 2013.1) data presented here were produced by NASA using consistent Chla algorithms.

Ship Sensor Observations for Islands in the Stream 2002 - Deep Reef Habitat - Office of Ocean Exploration

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Hourly measurements made by selected ship sensors on the R/V Seward Johnson during the 2002 "Islands in the Stream - Deep Reef Habitat" expedition sponsored by the...

Characterisation and deployment of an immobilised pH sensor spot towards surface ocean pH measurements.

Science.gov (United States)

Clarke, Jennifer S; Achterberg, Eric P; Rérolle, Victoire M C; Abi Kaed Bey, Samer; Floquet, Cedric F A; Mowlem, Matthew C

2015-10-15

The oceans are a major sink for anthropogenic atmospheric carbon dioxide, and the uptake causes changes to the marine carbonate system and has wide ranging effects on flora and fauna. It is crucial to develop analytical systems that allow us to follow the increase in oceanic pCO2 and corresponding reduction in pH. Miniaturised sensor systems using immobilised fluorescence indicator spots are attractive for this purpose because of their simple design and low power requirements. The technology is increasingly used for oceanic dissolved oxygen measurements. We present a detailed method on the use of immobilised fluorescence indicator spots to determine pH in ocean waters across the pH range 7.6-8.2. We characterised temperature (-0.046 pH/°C from 5 to 25 °C) and salinity dependences (-0.01 pH/psu over 5-35), and performed a preliminary investigation into the influence of chlorophyll on the pH measurement. The apparent pKa of the sensor spots was 6.93 at 20 °C. A drift of 0.00014 R (ca. 0.0004 pH, at 25 °C, salinity 35) was observed over a 3 day period in a laboratory based drift experiment. We achieved a precision of 0.0074 pH units, and observed a drift of 0.06 pH units during a test deployment of 5 week duration in the Southern Ocean as an underway surface ocean sensor, which was corrected for using certified reference materials. The temperature and salinity dependences were accounted for with the algorithm, R=0.00034-0.17·pH+0.15·S(2)+0.0067·T-0.0084·S·1.075. This study provides a first step towards a pH optode system suitable for autonomous deployment. The use of a short duration low power illumination (LED current 0.2 mA, 5 μs illumination time) improved the lifetime and precision of the spot. Further improvements to the pH indicator spot operations include regular application of certified reference materials for drift correction and cross-calibration against a spectrophotometric pH system. Desirable future developments should involve novel

Model wavefront sensor for adaptive confocal microscopy

Science.gov (United States)

Booth, Martin J.; Neil, Mark A. A.; Wilson, Tony

2000-05-01

A confocal microscope permits 3D imaging of volume objects by the inclusion of a pinhole in the detector path which eliminates out of focus light. This configuration is however very sensitive to aberrations induced by the specimen or the optical system and would therefore benefit from an adaptive optics approach. We present a wavefront sensor capable of measuring directly the Zernike components of an aberrated wavefront and show that it is particularly applicable to the confocal microscope since only those wavefronts originating in the focal region contribute to the measured aberration.

Adaptive Media Access Control for Energy Harvesting - Wireless Sensor Networks

DEFF Research Database (Denmark)

Fafoutis, Xenofon; Dragoni, Nicola

2012-01-01

ODMAC (On-Demand Media Access Control) is a recently proposed MAC protocol designed to support individual duty cycles for Energy Harvesting — Wireless Sensor Networks (EH-WSNs). Individual duty cycles are vital for EH-WSNs, because they allow nodes to adapt their energy consumption to the ever-ch...

Adaptive Home System Using Wireless Sensor Network And Multi Agent System

OpenAIRE

Jayarani Kamble; Prof.Nandini Dhole

2014-01-01

Smart Home is an emerging technology growing continuously which includes number of new technologies which helps to improve human’s quality of living. This paper proposes an adaptive home system for optimum utilization of power, through Artificial Intelligence and Wireless Sensor network. Artificial Intelligence is a technology for developing adaptive system that can perceive the enviornmrnt, learn from the environment and can make decision using Rule based system.Zigbee is a w...

An ADC-free adaptive interface circuit of resistive sensor for electronic nose system.

Science.gov (United States)

Chang, Chia-Lin; Chiu, Shih-Wen; Tang, Kea-Tiong

2013-01-01

The initial resistance of chemiresistive gas sensors could be affected by temperature, humidity, and background odors. In a sensing system, the traditional interface circuit always requires an ADC to convert analog signal to digital signal. In this paper, we propose an ADC-free adaptive interface circuit for a resistive gas sensor to read sensor signal and cancel the baseline drift. Furthermore, methanol was used to test the proposed interface circuit, which was connected with a FIGARO® gas sensor. This circuit was fabricated by TSMC 0.18 µm CMOS process, and consumed 86.41 µW under 1 V supply voltage.

Adaptation of sensor morphology: an integrative view of perception from biologically inspired robotics perspective

Science.gov (United States)

Nurzaman, Surya G.

2016-01-01

Sensor morphology, the morphology of a sensing mechanism which plays a role of shaping the desired response from physical stimuli from surroundings to generate signals usable as sensory information, is one of the key common aspects of sensing processes. This paper presents a structured review of researches on bioinspired sensor morphology implemented in robotic systems, and discusses the fundamental design principles. Based on literature review, we propose two key arguments: first, owing to its synthetic nature, biologically inspired robotics approach is a unique and powerful methodology to understand the role of sensor morphology and how it can evolve and adapt to its task and environment. Second, a consideration of an integrative view of perception by looking into multidisciplinary and overarching mechanisms of sensor morphology adaptation across biology and engineering enables us to extract relevant design principles that are important to extend our understanding of the unfinished concepts in sensing and perception. PMID:27499843

Oceans 2.0: Interactive tools for the Visualization of Multi-dimensional Ocean Sensor Data

Science.gov (United States)

Biffard, B.; Valenzuela, M.; Conley, P.; MacArthur, M.; Tredger, S.; Guillemot, E.; Pirenne, B.

2016-12-01

Ocean Networks Canada (ONC) operates ocean observatories on all three of Canada's coasts. The instruments produce 280 gigabytes of data per day with 1/2 petabyte archived so far. In 2015, 13 terabytes were downloaded by over 500 users from across the world. ONC's data management system is referred to as "Oceans 2.0" owing to its interactive, participative features. A key element of Oceans 2.0 is real time data acquisition and processing: custom device drivers implement the input-output protocol of each instrument. Automatic parsing and calibration takes place on the fly, followed by event detection and quality control. All raw data are stored in a file archive, while the processed data are copied to fast databases. Interactive access to processed data is provided through data download and visualization/quick look features that are adapted to diverse data types (scalar, acoustic, video, multi-dimensional, etc). Data may be post or re-processed to add features, analysis or correct errors, update calibrations, etc. A robust storage structure has been developed consisting of an extensive file system and a no-SQL database (Cassandra). Cassandra is a node-based open source distributed database management system. It is scalable and offers improved performance for big data. A key feature is data summarization. The system has also been integrated with web services and an ERDDAP OPeNDAP server, capable of serving scalar and multidimensional data from Cassandra for fixed or mobile devices.A complex data viewer has been developed making use of the big data capability to interactively display live or historic echo sounder and acoustic Doppler current profiler data, where users can scroll, apply processing filters and zoom through gigabytes of data with simple interactions. This new technology brings scientists one step closer to a comprehensive, web-based data analysis environment in which visual assessment, filtering, event detection and annotation can be integrated.

Distributed adaptive diagnosis of sensor faults using structural response data

Science.gov (United States)

Dragos, Kosmas; Smarsly, Kay

2016-10-01

The reliability and consistency of wireless structural health monitoring (SHM) systems can be compromised by sensor faults, leading to miscalibrations, corrupted data, or even data loss. Several research approaches towards fault diagnosis, referred to as ‘analytical redundancy’, have been proposed that analyze the correlations between different sensor outputs. In wireless SHM, most analytical redundancy approaches require centralized data storage on a server for data analysis, while other approaches exploit the on-board computing capabilities of wireless sensor nodes, analyzing the raw sensor data directly on board. However, using raw sensor data poses an operational constraint due to the limited power resources of wireless sensor nodes. In this paper, a new distributed autonomous approach towards sensor fault diagnosis based on processed structural response data is presented. The inherent correlations among Fourier amplitudes of acceleration response data, at peaks corresponding to the eigenfrequencies of the structure, are used for diagnosis of abnormal sensor outputs at a given structural condition. Representing an entirely data-driven analytical redundancy approach that does not require any a priori knowledge of the monitored structure or of the SHM system, artificial neural networks (ANN) are embedded into the sensor nodes enabling cooperative fault diagnosis in a fully decentralized manner. The distributed analytical redundancy approach is implemented into a wireless SHM system and validated in laboratory experiments, demonstrating the ability of wireless sensor nodes to self-diagnose sensor faults accurately and efficiently with minimal data traffic. Besides enabling distributed autonomous fault diagnosis, the embedded ANNs are able to adapt to the actual condition of the structure, thus ensuring accurate and efficient fault diagnosis even in case of structural changes.

Temperature and salinity data from moored seacat sensors of the Multi-disciplinary Ocean Sensors for Environmental Analyses and Networks (MOSEAN) project 2004-2007 (NODC Accession 0115703)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Temperature and salinity data were collected by seacat sensors from seven deployments within 2004-2007 on the HALE-ALOHA mooring, a location about 100 km north of...

Location-Based Self-Adaptive Routing Algorithm for Wireless Sensor Networks in Home Automation

Directory of Open Access Journals (Sweden)

Hong SeungHo

2011-01-01

Full Text Available The use of wireless sensor networks in home automation (WSNHA is attractive due to their characteristics of self-organization, high sensing fidelity, low cost, and potential for rapid deployment. Although the AODVjr routing algorithm in IEEE 802.15.4/ZigBee and other routing algorithms have been designed for wireless sensor networks, not all are suitable for WSNHA. In this paper, we propose a location-based self-adaptive routing algorithm for WSNHA called WSNHA-LBAR. It confines route discovery flooding to a cylindrical request zone, which reduces the routing overhead and decreases broadcast storm problems in the MAC layer. It also automatically adjusts the size of the request zone using a self-adaptive algorithm based on Bayes' theorem. This makes WSNHA-LBAR more adaptable to the changes of the network state and easier to implement. Simulation results show improved network reliability as well as reduced routing overhead.

Ship Sensor Observations for Islands in the Stream 2002 - Pharmaceutical Discovery, Vision, and Bioluminescence - Office of Ocean Exploration

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Hourly measurements made by selected ship sensors on the R/V Seward Johnson during the 2002 "Islands in the Stream - Pharmaceutical Discovery, Vision, and...

Kanaka Maoli and Kamáāina Seascapes - Knowing Our Ocean Through Times of Change

Science.gov (United States)

Puniwai, N.

2017-12-01

In Hawaíi our oceans define us, we come from the ocean. Our oceans change, and we change with them, as we always have. By learning from people who are dependent on their environment, we learn how to observe and how to adapt. Through the lens of climate change, we interviewed respected ocean observers and surfers to learn about changes they have witnessed over time and the spatial scales and ocean conditions important to them. We looked at our ancient and historical texts to see what processes they recorded and the language they used to ascribe their observations, interactions and relationships to these places. Yet, we also integrate what our mechanical data sensors have recorded over recent time. By expanding our time scales of reference, knowledge sources, and collaborators, these methods teach us how our ancestors adapted and how climate change may impact our subsistence, recreation, and interactions with the environment. Managing complex seascapes requires the integration of multiple ways of knowing; strengthening our understanding of seascapes and their resiliency in this changing environment.

An Energy Aware Adaptive Sampling Algorithm for Energy Harvesting WSN with Energy Hungry Sensors

Science.gov (United States)

Srbinovski, Bruno; Magno, Michele; Edwards-Murphy, Fiona; Pakrashi, Vikram; Popovici, Emanuel

2016-01-01

Wireless sensor nodes have a limited power budget, though they are often expected to be functional in the field once deployed for extended periods of time. Therefore, minimization of energy consumption and energy harvesting technology in Wireless Sensor Networks (WSN) are key tools for maximizing network lifetime, and achieving self-sustainability. This paper proposes an energy aware Adaptive Sampling Algorithm (ASA) for WSN with power hungry sensors and harvesting capabilities, an energy management technique that can be implemented on any WSN platform with enough processing power to execute the proposed algorithm. An existing state-of-the-art ASA developed for wireless sensor networks with power hungry sensors is optimized and enhanced to adapt the sampling frequency according to the available energy of the node. The proposed algorithm is evaluated using two in-field testbeds that are supplied by two different energy harvesting sources (solar and wind). Simulation and comparison between the state-of-the-art ASA and the proposed energy aware ASA (EASA) in terms of energy durability are carried out using in-field measured harvested energy (using both wind and solar sources) and power hungry sensors (ultrasonic wind sensor and gas sensors). The simulation results demonstrate that using ASA in combination with an energy aware function on the nodes can drastically increase the lifetime of a WSN node and enable self-sustainability. In fact, the proposed EASA in conjunction with energy harvesting capability can lead towards perpetual WSN operation and significantly outperform the state-of-the-art ASA. PMID:27043559

An Energy Aware Adaptive Sampling Algorithm for Energy Harvesting WSN with Energy Hungry Sensors

Directory of Open Access Journals (Sweden)

Bruno Srbinovski

2016-03-01

Full Text Available Wireless sensor nodes have a limited power budget, though they are often expected to be functional in the field once deployed for extended periods of time. Therefore, minimization of energy consumption and energy harvesting technology in Wireless Sensor Networks (WSN are key tools for maximizing network lifetime, and achieving self-sustainability. This paper proposes an energy aware Adaptive Sampling Algorithm (ASA for WSN with power hungry sensors and harvesting capabilities, an energy management technique that can be implemented on any WSN platform with enough processing power to execute the proposed algorithm. An existing state-of-the-art ASA developed for wireless sensor networks with power hungry sensors is optimized and enhanced to adapt the sampling frequency according to the available energy of the node. The proposed algorithm is evaluated using two in-field testbeds that are supplied by two different energy harvesting sources (solar and wind. Simulation and comparison between the state-of-the-art ASA and the proposed energy aware ASA (EASA in terms of energy durability are carried out using in-field measured harvested energy (using both wind and solar sources and power hungry sensors (ultrasonic wind sensor and gas sensors. The simulation results demonstrate that using ASA in combination with an energy aware function on the nodes can drastically increase the lifetime of a WSN node and enable self-sustainability. In fact, the proposed EASA in conjunction with energy harvesting capability can lead towards perpetual WSN operation and significantly outperform the state-of-the-art ASA.

An Autonomous Self-Aware and Adaptive Fault Tolerant Routing Technique for Wireless Sensor Networks.

Science.gov (United States)

Abba, Sani; Lee, Jeong-A

2015-08-18

We propose an autonomous self-aware and adaptive fault-tolerant routing technique (ASAART) for wireless sensor networks. We address the limitations of self-healing routing (SHR) and self-selective routing (SSR) techniques for routing sensor data. We also examine the integration of autonomic self-aware and adaptive fault detection and resiliency techniques for route formation and route repair to provide resilience to errors and failures. We achieved this by using a combined continuous and slotted prioritized transmission back-off delay to obtain local and global network state information, as well as multiple random functions for attaining faster routing convergence and reliable route repair despite transient and permanent node failure rates and efficient adaptation to instantaneous network topology changes. The results of simulations based on a comparison of the ASAART with the SHR and SSR protocols for five different simulated scenarios in the presence of transient and permanent node failure rates exhibit a greater resiliency to errors and failure and better routing performance in terms of the number of successfully delivered network packets, end-to-end delay, delivered MAC layer packets, packet error rate, as well as efficient energy conservation in a highly congested, faulty, and scalable sensor network.

Variability at Multiple Scales: Using an Array of Current- and Pressure-Sensor Equipped Inverted Echo Sounders to Measure the Ocean

Science.gov (United States)

2016-11-29

of Current- and Pressure - Sensor Equipped Inverted Echo Sounders to Measure the Ocean 5b. GRANT NUMBER NOOO 14-15-1-2857 5c. PROGRAM ELEMENT NUMBER...inverted echo sounders (lESs) equipped with pressure and current sensors (CPIESs). CPIESs are moored instruments that measure the round-trip acoustic...at a range of spatial and temporal scales. The goals of this project were to enhance the pool of pressure - sensor equipped lESs available at the

Variability at Multiple Scales: Using an Array of Current and Pressure Sensor Equipped Inverted Echo Sounders to Measure the Ocean

Science.gov (United States)

2016-11-29

of Current- and Pressure - Sensor Equipped Inverted Echo Sounders to Measure the Ocean 5b. GRANT NUMBER NOOO 14-15-1-2857 5c. PROGRAM ELEMENT NUMBER...inverted echo sounders (lESs) equipped with pressure and current sensors (CPIESs). CPIESs are moored instruments that measure the round-trip acoustic...at a range of spatial and temporal scales. The goals of this project were to enhance the pool of pressure - sensor equipped lESs available at the

An Emergency-Adaptive Routing Scheme for Wireless Sensor Networks for Building Fire Hazard Monitoring

Directory of Open Access Journals (Sweden)

Guilin Zheng

2011-03-01

Full Text Available Fire hazard monitoring and evacuation for building environments is a novel application area for the deployment of wireless sensor networks. In this context, adaptive routing is essential in order to ensure safe and timely data delivery in building evacuation and fire fighting resource applications. Existing routing mechanisms for wireless sensor networks are not well suited for building fires, especially as they do not consider critical and dynamic network scenarios. In this paper, an emergency-adaptive, real-time and robust routing protocol is presented for emergency situations such as building fire hazard applications. The protocol adapts to handle dynamic emergency scenarios and works well with the routing hole problem. Theoretical analysis and simulation results indicate that our protocol provides a real-time routing mechanism that is well suited for dynamic emergency scenarios in building fires when compared with other related work.

A Cluster-Based Dual-Adaptive Topology Control Approach in Wireless Sensor Networks.

Science.gov (United States)

Gui, Jinsong; Zhou, Kai; Xiong, Naixue

2016-09-25

Multi-Input Multi-Output (MIMO) can improve wireless network performance. Sensors are usually single-antenna devices due to the high hardware complexity and cost, so several sensors are used to form virtual MIMO array, which is a desirable approach to efficiently take advantage of MIMO gains. Also, in large Wireless Sensor Networks (WSNs), clustering can improve the network scalability, which is an effective topology control approach. The existing virtual MIMO-based clustering schemes do not either fully explore the benefits of MIMO or adaptively determine the clustering ranges. Also, clustering mechanism needs to be further improved to enhance the cluster structure life. In this paper, we propose an improved clustering scheme for virtual MIMO-based topology construction (ICV-MIMO), which can determine adaptively not only the inter-cluster transmission modes but also the clustering ranges. Through the rational division of cluster head function and the optimization of cluster head selection criteria and information exchange process, the ICV-MIMO scheme effectively reduces the network energy consumption and improves the lifetime of the cluster structure when compared with the existing typical virtual MIMO-based scheme. Moreover, the message overhead and time complexity are still in the same order of magnitude.

Sensor selection and chemo-sensory optimization: toward an adaptable chemo-sensory system

Directory of Open Access Journals (Sweden)

Alexander eVergara

2012-01-01

Full Text Available Over the past two decades, despite the tremendous research effort performed on chemical sensors and machine olfaction to develop micro-sensory systems that will accomplish the growing existent needs in personal health (implantable sensors, environment monitoring (widely distributed sensor networks, and security/threat detection (chemo/bio warfare agents, simple, low-cost molecular sensing platforms capable of long-term autonomous operation remain beyond the current state-of-the-art of chemical sensing. A fundamental issue within this context is that most of the chemical sensors depend on interactions between the targeted species and the surfaces functionalized with receptors that bind the target species selectively, and that these binding events are coupled with transduction processes that begin to change when they are exposed to the messy world of real samples. With the advent of fundamental breakthroughs at the intersection of materials science, micro/nano-technology, and signal processing, hybrid chemo-sensory systems have incorporated tunable, optimizable operating parameters, through which changes in the response characteristics can be modeled and compensated as the environmental conditions or application needs change.The objective of this article, in this context, is to bring together the key advances at the device, data processing, and system levels that enable chemo-sensory systems to adapt in response to their environments. Accordingly, in this review we will feature the research effort made by selected experts on chemical sensing and information theory, whose work has been devoted to develop strategies that provide tunability and adaptability to single sensor devices or sensory array systems. Particularly, we consider sensor-array selection, modulation of internal sensing parameters, and active sensing. The article ends with some conclusions drawn from the results presented and a visionary look toward the future in terms of how the

Tsunami simulation method initiated from waveforms observed by ocean bottom pressure sensors for real-time tsunami forecast; Applied for 2011 Tohoku Tsunami

Science.gov (United States)

Tanioka, Yuichiro

2017-04-01

After tsunami disaster due to the 2011 Tohoku-oki great earthquake, improvement of the tsunami forecast has been an urgent issue in Japan. National Institute of Disaster Prevention is installing a cable network system of earthquake and tsunami observation (S-NET) at the ocean bottom along the Japan and Kurile trench. This cable system includes 125 pressure sensors (tsunami meters) which are separated by 30 km. Along the Nankai trough, JAMSTEC already installed and operated the cable network system of seismometers and pressure sensors (DONET and DONET2). Those systems are the most dense observation network systems on top of source areas of great underthrust earthquakes in the world. Real-time tsunami forecast has depended on estimation of earthquake parameters, such as epicenter, depth, and magnitude of earthquakes. Recently, tsunami forecast method has been developed using the estimation of tsunami source from tsunami waveforms observed at the ocean bottom pressure sensors. However, when we have many pressure sensors separated by 30km on top of the source area, we do not need to estimate the tsunami source or earthquake source to compute tsunami. Instead, we can initiate a tsunami simulation from those dense tsunami observed data. Observed tsunami height differences with a time interval at the ocean bottom pressure sensors separated by 30 km were used to estimate tsunami height distribution at a particular time. In our new method, tsunami numerical simulation was initiated from those estimated tsunami height distribution. In this paper, the above method is improved and applied for the tsunami generated by the 2011 Tohoku-oki great earthquake. Tsunami source model of the 2011 Tohoku-oki great earthquake estimated using observed tsunami waveforms, coseimic deformation observed by GPS and ocean bottom sensors by Gusman et al. (2012) is used in this study. The ocean surface deformation is computed from the source model and used as an initial condition of tsunami

Self-adaptive calibration for staring infrared sensors

Science.gov (United States)

Kendall, William B.; Stocker, Alan D.

1993-10-01

This paper presents a new, self-adaptive technique for the correlation of non-uniformities (fixed-pattern noise) in high-density infrared focal-plane detector arrays. We have developed a new approach to non-uniformity correction in which we use multiple image frames of the scene itself, and take advantage of the aim-point wander caused by jitter, residual tracking errors, or deliberately induced motion. Such wander causes each detector in the array to view multiple scene elements, and each scene element to be viewed by multiple detectors. It is therefore possible to formulate (and solve) a set of simultaneous equations from which correction parameters can be computed for the detectors. We have tested our approach with actual images collected by the ARPA-sponsored MUSIC infrared sensor. For these tests we employed a 60-frame (0.75-second) sequence of terrain images for which an out-of-date calibration was deliberately used. The sensor was aimed at a point on the ground via an operator-assisted tracking system having a maximum aim point wander on the order of ten pixels. With these data, we were able to improve the calibration accuracy by a factor of approximately 100.

Environmental monitoring of coastal and oceanic areas with orbital sensors

Directory of Open Access Journals (Sweden)

Patrícia Genovez

2005-04-01

Full Text Available PETROBRAS is using spaceborne multi-sensor remote sensing for its sea surface monitoring program at the Campos, Santos and Espírito Santo basins, southeastern Brazilian coast. Ocean color (SeaWiFS and MODIS, thermal infrared (NOAA/AVHRR, scatterometer (QuikSCAT and Synthetic Aperture Radar (RADARSAT-1 and ASAR/ENVISAT data were integrated in order to detect and characterize different sorts of marine pollution and meteo-oceanographic phenomena. The near real time processing and delivery of the radar data allowed the timely in-situ verification and sampling of the remotely detected events. The integrated analysis of these dataset presents an important decision tool for emergencies, as well for the elaboration of contingency plans and evaluation of the oil industry activity impacts.

An Autonomous Self-Aware and Adaptive Fault Tolerant Routing Technique for Wireless Sensor Networks

Science.gov (United States)

Abba, Sani; Lee, Jeong-A

2015-01-01

We propose an autonomous self-aware and adaptive fault-tolerant routing technique (ASAART) for wireless sensor networks. We address the limitations of self-healing routing (SHR) and self-selective routing (SSR) techniques for routing sensor data. We also examine the integration of autonomic self-aware and adaptive fault detection and resiliency techniques for route formation and route repair to provide resilience to errors and failures. We achieved this by using a combined continuous and slotted prioritized transmission back-off delay to obtain local and global network state information, as well as multiple random functions for attaining faster routing convergence and reliable route repair despite transient and permanent node failure rates and efficient adaptation to instantaneous network topology changes. The results of simulations based on a comparison of the ASAART with the SHR and SSR protocols for five different simulated scenarios in the presence of transient and permanent node failure rates exhibit a greater resiliency to errors and failure and better routing performance in terms of the number of successfully delivered network packets, end-to-end delay, delivered MAC layer packets, packet error rate, as well as efficient energy conservation in a highly congested, faulty, and scalable sensor network. PMID:26295236

Accurate human limb angle measurement: sensor fusion through Kalman, least mean squares and recursive least-squares adaptive filtering

Science.gov (United States)

Olivares, A.; Górriz, J. M.; Ramírez, J.; Olivares, G.

2011-02-01

Inertial sensors are widely used in human body motion monitoring systems since they permit us to determine the position of the subject's limbs. Limb angle measurement is carried out through the integration of the angular velocity measured by a rate sensor and the decomposition of the components of static gravity acceleration measured by an accelerometer. Different factors derived from the sensors' nature, such as the angle random walk and dynamic bias, lead to erroneous measurements. Dynamic bias effects can be reduced through the use of adaptive filtering based on sensor fusion concepts. Most existing published works use a Kalman filtering sensor fusion approach. Our aim is to perform a comparative study among different adaptive filters. Several least mean squares (LMS), recursive least squares (RLS) and Kalman filtering variations are tested for the purpose of finding the best method leading to a more accurate and robust limb angle measurement. A new angle wander compensation sensor fusion approach based on LMS and RLS filters has been developed.

Accurate human limb angle measurement: sensor fusion through Kalman, least mean squares and recursive least-squares adaptive filtering

International Nuclear Information System (INIS)

Olivares, A; Olivares, G; Górriz, J M; Ramírez, J

2011-01-01

Inertial sensors are widely used in human body motion monitoring systems since they permit us to determine the position of the subject's limbs. Limb angle measurement is carried out through the integration of the angular velocity measured by a rate sensor and the decomposition of the components of static gravity acceleration measured by an accelerometer. Different factors derived from the sensors' nature, such as the angle random walk and dynamic bias, lead to erroneous measurements. Dynamic bias effects can be reduced through the use of adaptive filtering based on sensor fusion concepts. Most existing published works use a Kalman filtering sensor fusion approach. Our aim is to perform a comparative study among different adaptive filters. Several least mean squares (LMS), recursive least squares (RLS) and Kalman filtering variations are tested for the purpose of finding the best method leading to a more accurate and robust limb angle measurement. A new angle wander compensation sensor fusion approach based on LMS and RLS filters has been developed

A Cluster-Based Dual-Adaptive Topology Control Approach in Wireless Sensor Networks

Science.gov (United States)

Gui, Jinsong; Zhou, Kai; Xiong, Naixue

2016-01-01

Multi-Input Multi-Output (MIMO) can improve wireless network performance. Sensors are usually single-antenna devices due to the high hardware complexity and cost, so several sensors are used to form virtual MIMO array, which is a desirable approach to efficiently take advantage of MIMO gains. Also, in large Wireless Sensor Networks (WSNs), clustering can improve the network scalability, which is an effective topology control approach. The existing virtual MIMO-based clustering schemes do not either fully explore the benefits of MIMO or adaptively determine the clustering ranges. Also, clustering mechanism needs to be further improved to enhance the cluster structure life. In this paper, we propose an improved clustering scheme for virtual MIMO-based topology construction (ICV-MIMO), which can determine adaptively not only the inter-cluster transmission modes but also the clustering ranges. Through the rational division of cluster head function and the optimization of cluster head selection criteria and information exchange process, the ICV-MIMO scheme effectively reduces the network energy consumption and improves the lifetime of the cluster structure when compared with the existing typical virtual MIMO-based scheme. Moreover, the message overhead and time complexity are still in the same order of magnitude. PMID:27681731

A Cluster-Based Dual-Adaptive Topology Control Approach in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Jinsong Gui

2016-09-01

Full Text Available Multi-Input Multi-Output (MIMO can improve wireless network performance. Sensors are usually single-antenna devices due to the high hardware complexity and cost, so several sensors are used to form virtual MIMO array, which is a desirable approach to efficiently take advantage of MIMO gains. Also, in large Wireless Sensor Networks (WSNs, clustering can improve the network scalability, which is an effective topology control approach. The existing virtual MIMO-based clustering schemes do not either fully explore the benefits of MIMO or adaptively determine the clustering ranges. Also, clustering mechanism needs to be further improved to enhance the cluster structure life. In this paper, we propose an improved clustering scheme for virtual MIMO-based topology construction (ICV-MIMO, which can determine adaptively not only the inter-cluster transmission modes but also the clustering ranges. Through the rational division of cluster head function and the optimization of cluster head selection criteria and information exchange process, the ICV-MIMO scheme effectively reduces the network energy consumption and improves the lifetime of the cluster structure when compared with the existing typical virtual MIMO-based scheme. Moreover, the message overhead and time complexity are still in the same order of magnitude.

Blue Ocean strategic planning of acupuncture clinics’ business in Copenhagen-adapt “Jiankang Clinic” as a case study.

OpenAIRE

Kang, Shihan; Li, Duanyang

2013-01-01

The purpose of this paper is trying to adapt the Blue Ocean Strategy to help ”Jiankang Clinic ”to create competitive advantages to reach Blue Ocean position in Copenhagen acupuncture business. It is mainly using the Blue Ocean strategic tools and frameworks to analysis the company, industry and the market. Based on the in-depth interviews and questionnaires with the customers and owners of the clinics, concluding the product innovation and promotion improvement are important for the clinic st...

Effects of iron stress on chromatic adaptation by natural phytoplankton communities in the Southern Ocean

NARCIS (Netherlands)

van Leeuwe, M.A.; Timmermans, K.R.; Witte, H.J.; Kraay, G.W.; Veldhuis, M.J.W.; de Baar, H.J.W.

1998-01-01

Effects of iron stress on chromatic adaptation were studied in natural phytoplankton communities collected in the Pacific region of the Southern Ocean. Iron enrichment experiments (48 to 72 h) were performed, incubating plankton communities under white, green and blue light respectively, with and

Efficient and Adaptive Node Selection for Target Tracking in Wireless Sensor Network

Directory of Open Access Journals (Sweden)

Juan Feng

2016-01-01

Full Text Available In target tracking wireless sensor network, choosing the proper working nodes can not only minimize the number of active nodes, but also satisfy the tracking reliability requirement. However, most existing works focus on selecting sensor nodes which are the nearest to the target for tracking missions and they did not consider the correlation of the location of the sensor nodes so that these approaches can not meet all the goals of the network. This work proposes an efficient and adaptive node selection approach for tracking a target in a distributed wireless sensor network. The proposed approach combines the distance-based node selection strategy and particle filter prediction considering the spatial correlation of the different sensing nodes. Moreover, a joint distance weighted measurement is proposed to estimate the information utility of sensing nodes. Experimental results show that EANS outperformed the state-of-the-art approaches by reducing the energy cost and computational complexity as well as guaranteeing the tracking accuracy.

Adaptive Reliable Routing Based on Cluster Hierarchy for Wireless Multimedia Sensor Networks

Directory of Open Access Journals (Sweden)

Kai Lin

2010-01-01

Full Text Available As a multimedia information acquisition and processing method, wireless multimedia sensor network(WMSN has great application potential in military and civilian areas. Compared with traditional wireless sensor network, the routing design of WMSN should obtain more attention on the quality of transmission. This paper proposes an adaptive reliable routing based on clustering hierarchy named ARCH, which includes energy prediction and power allocation mechanism. To obtain a better performance, the cluster structure is formed based on cellular topology. The introduced prediction mechanism makes the sensor nodes predict the remaining energy of other nodes, which dramatically reduces the overall information needed for energy balancing. ARCH can dynamically balance the energy consumption of nodes based on the predicted results provided by power allocation. The simulation results prove the efficiency of the proposed ARCH routing.

Adaptive Multichannel Radiation Sensors for Plant Parameter Monitoring

Science.gov (United States)

Mollenhauer, Hannes; Remmler, Paul; Schuhmann, Gudrun; Lausch, Angela; Merbach, Ines; Assing, Martin; Mollenhauer, Olaf; Dietrich, Peter; Bumberger, Jan

2016-04-01

Nutrients such as nitrogen are playing a key role in the plant life cycle. They are much needed for chlorophyll production and other plant cell components. Therefore, the crop yield is strongly affected by plant nutrient status. Due to the spatial and temporal variability of soil characteristics or swaying agricultural inputs the plant development varies within a field. Thus, the determination of these fluctuations in the plant development is valuable for a detection of stress conditions and optimization of fertilisation due to its high environmental and economic impact. Plant parameters play crucial roles in plant growth estimation and prediction since they are used as indicators of plant performance. Especially indices derived out of remote sensing techniques provide quantitative information about agricultural crops instantaneously, and above all, non-destructively. Due to the specific absorption of certain plant pigments, a characteristic spectral signature can be seen in the visible and IR part of the electromagnetic spectrum, known as narrow-band peaks. In an analogous manner, the presence and concentration of different nutrients cause a characteristic spectral signature. To this end, an adequate remote sensing monitoring concept is needed, considering heterogeneity and dynamic of the plant population and economical aspects. This work will present the development and field investigations of an inexpensive multichannel radiation sensor to observe the incoming and reflected specific parts or rather distinct wavelengths of the solar light spectrum on the crop and facilitate the determination of different plant indices. Based on the selected sensor wavelengths, the sensing device allows the detection of specific parameters, e.g. plant vitality, chlorophyll content or nitrogen content. Besides the improvement of the sensor characteristic, the simple wavelength adaption, and the price-performance ratio, the achievement of appropriate energy efficiency as well as a

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

Science.gov (United States)

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.

Image sensor system with bio-inspired efficient coding and adaptation.

Science.gov (United States)

Okuno, Hirotsugu; Yagi, Tetsuya

2012-08-01

We designed and implemented an image sensor system equipped with three bio-inspired coding and adaptation strategies: logarithmic transform, local average subtraction, and feedback gain control. The system comprises a field-programmable gate array (FPGA), a resistive network, and active pixel sensors (APS), whose light intensity-voltage characteristics are controllable. The system employs multiple time-varying reset voltage signals for APS in order to realize multiple logarithmic intensity-voltage characteristics, which are controlled so that the entropy of the output image is maximized. The system also employs local average subtraction and gain control in order to obtain images with an appropriate contrast. The local average is calculated by the resistive network instantaneously. The designed system was successfully used to obtain appropriate images of objects that were subjected to large changes in illumination.

A Modified Adaptive Stochastic Resonance for Detecting Faint Signal in Sensors

Directory of Open Access Journals (Sweden)

Hengwei Li

2007-02-01

Full Text Available In this paper, an approach is presented to detect faint signals with strong noises in sensors by stochastic resonance (SR. We adopt the power spectrum as the evaluation tool of SR, which can be obtained by the fast Fourier transform (FFT. Furthermore, we introduce the adaptive filtering scheme to realize signal processing automatically. The key of the scheme is how to adjust the barrier height to satisfy the optimal condition of SR in the presence of any input. For the given input signal, we present an operable procedure to execute the adjustment scheme. An example utilizing one audio sensor to detect the fault information from the power supply is given. Simulation results show that th

Towards adaptive security for convergent wireless sensor networks in beyond 3G environments

DEFF Research Database (Denmark)

Mitseva, Anelia; Aivaloglou, Efthimia; Marchitti, Maria-Antonietta

2010-01-01

The integration of wireless sensor networks with different network systems gives rise to many research challenges to ensure security, privacy and trust in the overall architecture. The main contribution of this paper is a generic security, privacy and trust framework providing context-aware adapt...

Dynamic ocean provinces: a multi-sensor approach to global marine ecophysiology

Science.gov (United States)

Dowell, M.; Campbell, J.; Moore, T.

The concept of oceanic provinces or domains has existed for well over a century. Such systems, whether real or only conceptual, provide a useful framework for understanding the mechanisms controlling biological, physical and chemical processes and their interactions. Criteria have been established for defining provinces based on physical forcings, availability of light and nutrients, complexity of the marine food web, and other factors. In general, such classification systems reflect the heterogeneous nature of the ocean environment, and the effort of scientists to comprehend the whole system by understanding its various homogeneous components. If provinces are defined strictly on the basis of geospatial or temporal criteria (e.g., latitude zones, bathymetry, or season), the resulting maps exhibit discontinuities that are uncharacteristic of the ocean. While this may be useful for many purposes, it is unsatisfactory in that it does not capture the dynamic nature of fluid boundaries in the ocean. Boundaries fixed in time and space do not allow us to observe interannual or longer-term variability (e.g., regime shifts) that may result from climate change. The current study illustrates the potential of using fuzzy logic as a means of classifying the ocean into objectively defined provinces using properties measurable from satellite sensors (MODIS and SeaWiFS). This approach accommodates the dynamic variability of provinces which can be updated as each image is processed. We adopt this classification as the basis for parameterizing specific algorithms for each of the classes. Once the class specific algorithms have been applied, retrievals are then recomposed into a single blended product based on the "weighted" fuzzy memberships. This will be demonstrated through animations of multi-year time- series of monthly composites of the individual classes or provinces. The provinces themselves are identified on the basis of global fields of chlorophyll, sea surface temperature

Adaptation of an unstructured-mesh, finite-element ocean model to the simulation of ocean circulation beneath ice shelves

Science.gov (United States)

Kimura, Satoshi; Candy, Adam S.; Holland, Paul R.; Piggott, Matthew D.; Jenkins, Adrian

2013-07-01

Several different classes of ocean model are capable of representing floating glacial ice shelves. We describe the incorporation of ice shelves into Fluidity-ICOM, a nonhydrostatic finite-element ocean model with the capacity to utilize meshes that are unstructured and adaptive in three dimensions. This geometric flexibility offers several advantages over previous approaches. The model represents melting and freezing on all ice-shelf surfaces including vertical faces, treats the ice shelf topography as continuous rather than stepped, and does not require any smoothing of the ice topography or any of the additional parameterisations of the ocean mixed layer used in isopycnal or z-coordinate models. The model can also represent a water column that decreases to zero thickness at the 'grounding line', where the floating ice shelf is joined to its tributary ice streams. The model is applied to idealised ice-shelf geometries in order to demonstrate these capabilities. In these simple experiments, arbitrarily coarsening the mesh outside the ice-shelf cavity has little effect on the ice-shelf melt rate, while the mesh resolution within the cavity is found to be highly influential. Smoothing the vertical ice front results in faster flow along the smoothed ice front, allowing greater exchange with the ocean than in simulations with a realistic ice front. A vanishing water-column thickness at the grounding line has little effect in the simulations studied. We also investigate the response of ice shelf basal melting to variations in deep water temperature in the presence of salt stratification.

An adaptive wing for a small-aircraft application with a configuration of fibre Bragg grating sensors

International Nuclear Information System (INIS)

Mieloszyk, M; Krawczuk, M; Zak, A; Ostachowicz, W

2010-01-01

In this paper a concept of an adaptive wing for small-aircraft applications with an array of fibre Bragg grating (FBG) sensors has been presented and discussed. In this concept the shape of the wing can be controlled and altered thanks to the wing design and the use of integrated shape memory alloy actuators. The concept has been tested numerically by the use of the finite element method. For numerical calculations the commercial finite element package ABAQUS ® has been employed. A finite element model of the wing has been prepared in order to estimate the values of the wing twisting angles and distributions of the twist for various activation scenarios. Based on the results of numerical analysis the locations and numbers of the FBG sensors have also been determined. The results of numerical calculations obtained by the authors confirmed the usefulness of the assumed wing control strategy. Based on them and the concept developed of the adaptive wing, a wing demonstration stand has been designed and built. The stand has been used to verify experimentally the performance of the adaptive wing and the usefulness of the FBG sensors for evaluation of the wing condition

Adaptive Square-Shaped Trajectory-Based Service Location Protocol in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Hwa-Jung Lim

2010-04-01

Full Text Available In this paper we propose an adaptive square-shaped trajectory (ASST-based service location method to ensure load scalability in wireless sensor networks. This first establishes a square-shaped trajectory over the nodes that surround a target point computed by the hash function and any user can access it, using the hash. Both the width and the size of the trajectory are dynamically adjustable, depending on the number of queries made to the service information on the trajectory. The number of sensor nodes on the trajectory varies in proportion to the changing trajectory shape, allowing high loads to be distributed around the hot spot area.

ALES+: Adapting a homogenous ocean retracker for satellite altimetry to sea ice leads, coastal and inland waters

DEFF Research Database (Denmark)

Passaro, Marcello; Kildegaard Rose, Stine; Andersen, Ole B.

2018-01-01

ice retracker used for fitting specular echoes. Compared to an existing open ocean altimetry dataset, the presented strategy increases the number of sea level retrievals in the sea ice-covered area and the correlation with a local tide gauge. Further tests against in-situ data show that also......Water level from sea ice-covered oceans is particularly challenging to retrieve with satellite radar altimeters due to the different shapes assumed by the returned signal compared with the standard open ocean waveforms. Valid measurements are scarce in large areas of the Arctic and Antarctic Oceans...... the fitting of the signal depending on the sea state and on the slope of its trailing edge. The algorithm modifies the existing Adaptive Leading Edge Subwaveform retracker originally designed for coastal waters, and is applied to Envisat and ERS-2 missions. The validation in a test area of the Arctic Ocean...

Online Sensor Drift Compensation for E-Nose Systems Using Domain Adaptation and Extreme Learning Machine

Science.gov (United States)

Luo, Guangchun; Qin, Ke; Wang, Nan; Niu, Weina

2018-01-01

Sensor drift is a common issue in E-Nose systems and various drift compensation methods have received fruitful results in recent years. Although the accuracy for recognizing diverse gases under drift conditions has been largely enhanced, few of these methods considered online processing scenarios. In this paper, we focus on building online drift compensation model by transforming two domain adaptation based methods into their online learning versions, which allow the recognition models to adapt to the changes of sensor responses in a time-efficient manner without losing the high accuracy. Experimental results using three different settings confirm that the proposed methods save large processing time when compared with their offline versions, and outperform other drift compensation methods in recognition accuracy. PMID:29494543

Online Sensor Drift Compensation for E-Nose Systems Using Domain Adaptation and Extreme Learning Machine

Directory of Open Access Journals (Sweden)

Zhiyuan Ma

2018-03-01

Full Text Available Sensor drift is a common issue in E-Nose systems and various drift compensation methods have received fruitful results in recent years. Although the accuracy for recognizing diverse gases under drift conditions has been largely enhanced, few of these methods considered online processing scenarios. In this paper, we focus on building online drift compensation model by transforming two domain adaptation based methods into their online learning versions, which allow the recognition models to adapt to the changes of sensor responses in a time-efficient manner without losing the high accuracy. Experimental results using three different settings confirm that the proposed methods save large processing time when compared with their offline versions, and outperform other drift compensation methods in recognition accuracy.

Multipoint dynamically reconfigure adaptive distributed fiber optic acoustic emission sensor (FAESense) system for condition based maintenance

Science.gov (United States)

Mendoza, Edgar; Prohaska, John; Kempen, Connie; Esterkin, Yan; Sun, Sunjian; Krishnaswamy, Sridhar

2010-09-01

This paper describes preliminary results obtained under a Navy SBIR contract by Redondo Optics Inc. (ROI), in collaboration with Northwestern University towards the development and demonstration of a next generation, stand-alone and fully integrated, dynamically reconfigurable, adaptive fiber optic acoustic emission sensor (FAESense™) system for the in-situ unattended detection and localization of shock events, impact damage, cracks, voids, and delaminations in new and aging critical infrastructures found in ships, submarines, aircraft, and in next generation weapon systems. ROI's FAESense™ system is based on the integration of proven state-of-the-art technologies: 1) distributed array of in-line fiber Bragg gratings (FBGs) sensors sensitive to strain, vibration, and acoustic emissions, 2) adaptive spectral demodulation of FBG sensor dynamic signals using two-wave mixing interferometry on photorefractive semiconductors, and 3) integration of all the sensor system passive and active optoelectronic components within a 0.5-cm x 1-cm photonic integrated circuit microchip. The adaptive TWM demodulation methodology allows the measurement of dynamic high frequnency acoustic emission events, while compensating for passive quasi-static strain and temperature drifts. It features a compact, low power, environmentally robust 1-inch x 1-inch x 4-inch small form factor (SFF) package with no moving parts. The FAESense™ interrogation system is microprocessor-controlled using high data rate signal processing electronics for the FBG sensors calibration, temperature compensation and the detection and analysis of acoustic emission signals. Its miniaturized package, low power operation, state-of-the-art data communications, and low cost makes it a very attractive solution for a large number of applications in naval and maritime industries, aerospace, civil structures, the oil and chemical industry, and for homeland security applications.

Evaluation of radiative fluxes over the north Indian Ocean

Science.gov (United States)

Ramesh Kumar, M. R.; Pinker, Rachel T.; Mathew, Simi; Venkatesan, R.; Chen, W.

2018-05-01

Radiative fluxes are a key component of the surface heat budget of the oceans. Yet, observations over oceanic region are sparse due to the complexity of radiation measurements; moreover, certain oceanic regions are substantially under-sampled, such as the north Indian Ocean. The National Institute of Ocean Technology, Chennai, India, under its Ocean Observation Program has deployed an Ocean Moored Network for the Northern Indian Ocean (OMNI) both in the Arabian Sea and the Bay of Bengal. These buoys are equipped with sensors to measure radiation and rainfall, in addition to other basic meteorological parameters. They are also equipped with sensors to measure sub-surface currents, temperature, and conductivity from the surface up to a depth of 500 m. Observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the National Aeronautics and Space Administration (NASA) AQUA and TERRA satellites have been used to infer surface radiation over the north Indian Ocean. In this study, we focus only on the shortwave (SW↓) fluxes. The evaluations of the MODIS-based SW↓ fluxes against the RAMA observing network have shown a very good agreement between them, and therefore, we use the MODIS-derived fluxes as a reference for the evaluation of the OMNI observations. In an early deployment of the OMNI buoys, the radiation sensors were placed at 2 m above the sea surface; subsequently, the height of the sensors was raised to 3 m. In this study, we show that there was a substantial improvement in the agreement between the buoy observations and the satellite estimates, once the sensors were raised to higher levels. The correlation coefficient increased from 0.87 to 0.93, and both the bias and standard deviations decreased substantially.

An Adaptive Data Gathering Scheme for Multi-Hop Wireless Sensor Networks Based on Compressed Sensing and Network Coding.

Science.gov (United States)

Yin, Jun; Yang, Yuwang; Wang, Lei

2016-04-01

Joint design of compressed sensing (CS) and network coding (NC) has been demonstrated to provide a new data gathering paradigm for multi-hop wireless sensor networks (WSNs). By exploiting the correlation of the network sensed data, a variety of data gathering schemes based on NC and CS (Compressed Data Gathering--CDG) have been proposed. However, these schemes assume that the sparsity of the network sensed data is constant and the value of the sparsity is known before starting each data gathering epoch, thus they ignore the variation of the data observed by the WSNs which are deployed in practical circumstances. In this paper, we present a complete design of the feedback CDG scheme where the sink node adaptively queries those interested nodes to acquire an appropriate number of measurements. The adaptive measurement-formation procedure and its termination rules are proposed and analyzed in detail. Moreover, in order to minimize the number of overall transmissions in the formation procedure of each measurement, we have developed a NP-complete model (Maximum Leaf Nodes Minimum Steiner Nodes--MLMS) and realized a scalable greedy algorithm to solve the problem. Experimental results show that the proposed measurement-formation method outperforms previous schemes, and experiments on both datasets from ocean temperature and practical network deployment also prove the effectiveness of our proposed feedback CDG scheme.

OW ASCAT Ocean Surface Winds

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Advanced Scatterometer (ASCAT) sensor onboard the EUMETSAT MetOp polar-orbiting satellite provides ocean surface wind observations by means of radar...

Physical, chemical, and other data collected using meteorological sensors, secchi disk, and bottle casts from the Pacific Ocean as part of the International Decade of Ocean Exploration / North Pacific Experiment (IDOE/NORPAX) project from 18 June 1976 to 14 June 1977 (NODC Accession 8100434)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Physical, chemical, and other data were collected using meteorological sensors, secchi disk, and bottle casts in the Pacific Ocean. Data were collected from the...

Massive Cloud-Based Big Data Processing for Ocean Sensor Networks and Remote Sensing

Science.gov (United States)

Schwehr, K. D.

2017-12-01

Until recently, the work required to integrate and analyze data for global-scale environmental issues was prohibitive both in cost and availability. Traditional desktop processing systems are not able to effectively store and process all the data, and super computer solutions are financially out of the reach of most people. The availability of large-scale cloud computing has created tools that are usable by small groups and individuals regardless of financial resources or locally available computational resources. These systems give scientists and policymakers the ability to see how critical resources are being used across the globe with little or no barrier to entry. Google Earth Engine has the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra, MODIS Aqua, and Global Land Data Assimilation Systems (GLDAS) data catalogs available live online. Here we demonstrate these data to calculate the correlation between lagged chlorophyll and rainfall to identify areas of eutrophication, matching these events to ocean currents from datasets like HYbrid Coordinate Ocean Model (HYCOM) to check if there are constraints from oceanographic configurations. The system can provide addition ground truth with observations from sensor networks like the International Comprehensive Ocean-Atmosphere Data Set / Voluntary Observing Ship (ICOADS/VOS) and Argo floats. This presentation is intended to introduce users to the datasets, programming idioms, and functionality of Earth Engine for large-scale, data-driven oceanography.

Fault Diagnosis for Satellite Sensors and Actuators using Nonlinear Geometric Approach and Adaptive Observers

DEFF Research Database (Denmark)

Baldi, P.; Blanke, Mogens; Castaldi, P.

2018-01-01

This paper presents a novel scheme for diagnosis of faults affecting sensors that measure the satellite attitude, body angular velocity, flywheel spin rates, and defects in control torques from reaction wheel motors. The proposed methodology uses adaptive observers to provide fault estimates that...

Hardware implementation of adaptive filtering using charge-coupled devices. [For perimeter security sensors

Energy Technology Data Exchange (ETDEWEB)

Donohoe, G.W.

1977-01-01

Sandia Laboratories' Digital Systems Division/1734, as part of its work on the Base and Installation Security Systems (BISS) program has been making use of adaptive digital filters to improve the signal-to-noise ratio of perimeter sensor signals. In particular, the Widrow-Hoff least-mean-squares algorithm has been used extensively. This non-recursive linear predictor has been successful in extracting aperiodic signals from periodic noise. The adaptive filter generates a predictor signal which is subtracted from the input signal to produce an error signal. The value of this error is fed back to the filter to improve the quality of the next prediction. Implementation of the Widrow adaptive filter using a Charge-Coupled Device tapped analog delay line, analog voltage multipliers and operational amplifiers is described. The resulting filter adapts to signals with frequency components as high as several megahertz.

An Adaptive Technique for a Redundant-Sensor Navigation System. Ph.D. Thesis

Science.gov (United States)

Chien, T. T.

1972-01-01

An on-line adaptive technique is developed to provide a self-contained redundant-sensor navigation system with a capability to utilize its full potentiality in reliability and performance. The gyro navigation system is modeled as a Gauss-Markov process, with degradation modes defined as changes in characteristics specified by parameters associated with the model. The adaptive system is formulated as a multistage stochastic process: (1) a detection system, (2) an identification system and (3) a compensation system. It is shown that the sufficient statistics for the partially observable process in the detection and identification system is the posterior measure of the state of degradation, conditioned on the measurement history.

Adaptive Pulsed Laser Line Extraction for Terrain Reconstruction using a Dynamic Vision Sensor

Directory of Open Access Journals (Sweden)

Christian eBrandli

2014-01-01

Full Text Available Mobile robots need to know the terrain in which they are moving for path planning and obstacle avoidance. This paper proposes the combination of a bio-inspired, redundancy-suppressing dynamic vision sensor with a pulsed line laser to allow fast terrain reconstruction. A stable laser stripe extraction is achieved by exploiting the sensor’s ability to capture the temporal dynamics in a scene. An adaptive temporal filter for the sensor output allows a reliable reconstruction of 3D terrain surfaces. Laser stripe extractions up to pulsing frequencies of 500Hz were achieved using a line laser of 3mW at a distance of 45cm using an event-based algorithm that exploits the sparseness of the sensor output. As a proof of concept, unstructured rapid prototype terrain samples have been successfully reconstructed with an accuracy of 2mm.

An Efficient and Self-Adapting Localization in Static Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Wei Dong

2009-08-01

Full Text Available Localization is one of the most important subjects in Wireless Sensor Networks (WSNs. To reduce the number of beacons and adopt probabilistic methods, some particle filter-based mobile beacon-assisted localization approaches have been proposed, such as Mobile Beacon-assisted Localization (MBL, Adapting MBL (A-MBL, and the method proposed by Hang et al. Some new significant problems arise in these approaches, however. The first question is which probability distribution should be selected as the dynamic model in the prediction stage. The second is whether the unknown node adopts neighbors’ observation in the update stage. The third is how to find a self-adapting mechanism to achieve more flexibility in the adapting stage. In this paper, we give the theoretical analysis and experimental evaluations to suggest which probability distribution in the dynamic model should be adopted to improve the efficiency in the prediction stage. We also give the condition for whether the unknown node should use the observations from its neighbors to improve the accuracy. Finally, we propose a Self-Adapting Mobile Beacon-assisted Localization (SA-MBL approach to achieve more flexibility and achieve almost the same performance with A-MBL.

A systematic review of gait analysis methods based on inertial sensors and adaptive algorithms.

Science.gov (United States)

Caldas, Rafael; Mundt, Marion; Potthast, Wolfgang; Buarque de Lima Neto, Fernando; Markert, Bernd

2017-09-01

The conventional methods to assess human gait are either expensive or complex to be applied regularly in clinical practice. To reduce the cost and simplify the evaluation, inertial sensors and adaptive algorithms have been utilized, respectively. This paper aims to summarize studies that applied adaptive also called artificial intelligence (AI) algorithms to gait analysis based on inertial sensor data, verifying if they can support the clinical evaluation. Articles were identified through searches of the main databases, which were encompassed from 1968 to October 2016. We have identified 22 studies that met the inclusion criteria. The included papers were analyzed due to their data acquisition and processing methods with specific questionnaires. Concerning the data acquisition, the mean score is 6.1±1.62, what implies that 13 of 22 papers failed to report relevant outcomes. The quality assessment of AI algorithms presents an above-average rating (8.2±1.84). Therefore, AI algorithms seem to be able to support gait analysis based on inertial sensor data. Further research, however, is necessary to enhance and standardize the application in patients, since most of the studies used distinct methods to evaluate healthy subjects. Copyright © 2017 Elsevier B.V. All rights reserved.

Adaptive Opportunistic Cooperative Control Mechanism Based on Combination Forecasting and Multilevel Sensing Technology of Sensors for Mobile Internet of Things

Directory of Open Access Journals (Sweden)

Yong Jin

2014-01-01

Full Text Available In mobile Internet of Things, there are many challenges, including sensing technology of sensors, how and when to join cooperative transmission, and how to select the cooperative sensors. To address these problems, we studied the combination forecasting based on the multilevel sensing technology of sensors, building upon which we proposed the adaptive opportunistic cooperative control mechanism based on the threshold values such as activity probability, distance, transmitting power, and number of relay sensors, in consideration of signal to noise ratio and outage probability. More importantly, the relay sensors would do self-test real time in order to judge whether to join the cooperative transmission, for maintaining the optimal cooperative transmission state with high performance. The mathematical analyses results show that the proposed adaptive opportunistic cooperative control approach could perform better in terms of throughput ratio, packet error rate and delay, and energy efficiency, compared with the direct transmission and opportunistic cooperative approaches.

Soft sensor modelling by time difference, recursive partial least squares and adaptive model updating

International Nuclear Information System (INIS)

Fu, Y; Xu, O; Yang, W; Zhou, L; Wang, J

2017-01-01

To investigate time-variant and nonlinear characteristics in industrial processes, a soft sensor modelling method based on time difference, moving-window recursive partial least square (PLS) and adaptive model updating is proposed. In this method, time difference values of input and output variables are used as training samples to construct the model, which can reduce the effects of the nonlinear characteristic on modelling accuracy and retain the advantages of recursive PLS algorithm. To solve the high updating frequency of the model, a confidence value is introduced, which can be updated adaptively according to the results of the model performance assessment. Once the confidence value is updated, the model can be updated. The proposed method has been used to predict the 4-carboxy-benz-aldehyde (CBA) content in the purified terephthalic acid (PTA) oxidation reaction process. The results show that the proposed soft sensor modelling method can reduce computation effectively, improve prediction accuracy by making use of process information and reflect the process characteristics accurately. (paper)

Variability in global ocean phytoplankton distribution over 1979-2007

Science.gov (United States)

Masotti, I.; Alvain, S.; Moulin, C.; Antoine, D.

2009-04-01

Recently, reanalysis of long-term ocean color data (CZCS and SeaWiFS; Antoine et al., 2005) has shown that world ocean average phytoplankton chlorophyll levels show an increase of 20% over the last two decades. It is however unknown whether this increase is associated with a change in the distribution of phytoplankton groups or if it simply corresponds to an increase of the productivity. Within the framework of the GLOBPHY project, the distribution of the phytoplankton groups was monitored by applying the PHYSAT method (Alvain et al., 2005) to the historical ocean color data series from CZCS, OCTS and SeaWiFS sensors. The PHYSAT algorithm allows identification of several phytoplankton, like nanoeucaryotes, prochlorococcus, synechococcus and diatoms. Because both sensors (OCTS-SeaWiFS) are very similar, OCTS data were processed with the standard PHYSAT algorithm to cover the 1996-1997 period during which a large El Niño event occurred, just before the SeaWiFS era. Our analysis of this dataset (1996-2006) evidences a strong variability in the distribution of phytoplankton groups at both regional and global scales. In the equatorial region (0°-5°S), a three-fold increase of nanoeucaryotes frequency was detected in opposition to a two-fold decrease of synechococcus during the early stages of El Niño conditions (May-June 1997, OCTS). The impact of this El Niño is however not confined to the Equatorial Pacific and has affected the global ocean. The processing of CZCS data with PHYSAT has required several adaptations of this algorithm due to the lower performances and the reduced number of spectral bands of the sensor. Despites higher uncertainties, the phytoplankton groups distribution obtained with CZCS is globally consistent with that of SeaWiFS. A comparison of variability in global phytoplankton distribution between 1979-1982 (CZCS) and 1999-2002 (SeaWiFS) suggests an increase in nanoeucaryotes at high latitudes (>40°) and in the equatorial region (10°S-10�

Proceedings of the Adaptive Sensor Array Processing Workshop (12th) Held in Lexington, MA on 16-18 March 2004 (CD-ROM)

National Research Council Canada - National Science Library

James, F

2004-01-01

...: The twelfth annual workshop on Adaptive Sensor Array Processing presented a diverse agenda featuring new work on adaptive methods for communications, radar and sonar, algorithmic challenges posed...

Modeling UV-B Effects on Primary Production Throughout the Southern Ocean Using Multi-Sensor Satellite Data

Science.gov (United States)

Lubin, Dan

2001-01-01

This study has used a combination of ocean color, backscattered ultraviolet, and passive microwave satellite data to investigate the impact of the springtime Antarctic ozone depletion on the base of the Antarctic marine food web - primary production by phytoplankton. Spectral ultraviolet (UV) radiation fields derived from the satellite data are propagated into the water column where they force physiologically-based numerical models of phytoplankton growth. This large-scale study has been divided into two components: (1) the use of Total Ozone Mapping Spectrometer (TOMS) and Special Sensor Microwave Imager (SSM/I) data in conjunction with radiative transfer theory to derive the surface spectral UV irradiance throughout the Southern Ocean; and (2) the merging of these UV irradiances with the climatology of chlorophyll derived from SeaWiFS data to specify the input data for the physiological models.

Dependence of the compensation error on the error of a sensor and corrector in an adaptive optics phase-conjugating system

International Nuclear Information System (INIS)

Kiyko, V V; Kislov, V I; Ofitserov, E N

2015-01-01

In the framework of a statistical model of an adaptive optics system (AOS) of phase conjugation, three algorithms based on an integrated mathematical approach are considered, each of them intended for minimisation of one of the following characteristics: the sensor error (in the case of an ideal corrector), the corrector error (in the case of ideal measurements) and the compensation error (with regard to discreteness and measurement noises and to incompleteness of a system of response functions of the corrector actuators). Functional and statistical relationships between the algorithms are studied and a relation is derived to ensure calculation of the mean-square compensation error as a function of the errors of the sensor and corrector with an accuracy better than 10%. Because in adjusting the AOS parameters, it is reasonable to proceed from the equality of the sensor and corrector errors, in the case the Hartmann sensor is used as a wavefront sensor, the required number of actuators in the absence of the noise component in the sensor error turns out 1.5 – 2.5 times less than the number of counts, and that difference grows with increasing measurement noise. (adaptive optics)

Dependence of the compensation error on the error of a sensor and corrector in an adaptive optics phase-conjugating system

Energy Technology Data Exchange (ETDEWEB)

Kiyko, V V; Kislov, V I; Ofitserov, E N [A M Prokhorov General Physics Institute, Russian Academy of Sciences, Moscow (Russian Federation)

2015-08-31

In the framework of a statistical model of an adaptive optics system (AOS) of phase conjugation, three algorithms based on an integrated mathematical approach are considered, each of them intended for minimisation of one of the following characteristics: the sensor error (in the case of an ideal corrector), the corrector error (in the case of ideal measurements) and the compensation error (with regard to discreteness and measurement noises and to incompleteness of a system of response functions of the corrector actuators). Functional and statistical relationships between the algorithms are studied and a relation is derived to ensure calculation of the mean-square compensation error as a function of the errors of the sensor and corrector with an accuracy better than 10%. Because in adjusting the AOS parameters, it is reasonable to proceed from the equality of the sensor and corrector errors, in the case the Hartmann sensor is used as a wavefront sensor, the required number of actuators in the absence of the noise component in the sensor error turns out 1.5 – 2.5 times less than the number of counts, and that difference grows with increasing measurement noise. (adaptive optics)

Deep-Sea DuraFET: A Pressure Tolerant pH Sensor Designed for Global Sensor Networks.

Science.gov (United States)

Johnson, Kenneth S; Jannasch, Hans W; Coletti, Luke J; Elrod, Virginia A; Martz, Todd R; Takeshita, Yuichiro; Carlson, Robert J; Connery, James G

2016-03-15

Increasing atmospheric carbon dioxide is driving a long-term decrease in ocean pH which is superimposed on daily to seasonal variability. These changes impact ecosystem processes, and they serve as a record of ecosystem metabolism. However, the temporal variability in pH is observed at only a few locations in the ocean because a ship is required to support pH observations of sufficient precision and accuracy. This paper describes a pressure tolerant Ion Sensitive Field Effect Transistor pH sensor that is based on the Honeywell Durafet ISFET die. When combined with a AgCl pseudoreference sensor that is immersed directly in seawater, the system is capable of operating for years at a time on platforms that cycle from depths of several km to the surface. The paper also describes the calibration scheme developed to allow calibrated pH measurements to be derived from the activity of HCl reported by the sensor system over the range of ocean pressure and temperature. Deployments on vertical profiling platforms enable self-calibration in deep waters where pH values are stable. Measurements with the sensor indicate that it is capable of reporting pH with an accuracy of 0.01 or better on the total proton scale and a precision over multiyear periods of 0.005. This system enables a global ocean observing system for ocean pH.

OW NASA SeaWIFS Ocean Color

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The dataset contains satellite-derived sea-surface ocean color (chlorophyll-a) measurements collected by means of the Sea-viewing Wide Field-of-view Sensor (SeaWiFS)...

A Hybrid Adaptive Routing Algorithm for Event-Driven Wireless Sensor Networks

Science.gov (United States)

Figueiredo, Carlos M. S.; Nakamura, Eduardo F.; Loureiro, Antonio A. F.

2009-01-01

Routing is a basic function in wireless sensor networks (WSNs). For these networks, routing algorithms depend on the characteristics of the applications and, consequently, there is no self-contained algorithm suitable for every case. In some scenarios, the network behavior (traffic load) may vary a lot, such as an event-driven application, favoring different algorithms at different instants. This work presents a hybrid and adaptive algorithm for routing in WSNs, called Multi-MAF, that adapts its behavior autonomously in response to the variation of network conditions. In particular, the proposed algorithm applies both reactive and proactive strategies for routing infrastructure creation, and uses an event-detection estimation model to change between the strategies and save energy. To show the advantages of the proposed approach, it is evaluated through simulations. Comparisons with independent reactive and proactive algorithms show improvements on energy consumption. PMID:22423207

Bayesian model for matching the radiometric measurements of aerospace and field ocean color sensors.

Science.gov (United States)

Salama, Mhd Suhyb; Su, Zhongbo

2010-01-01

A Bayesian model is developed to match aerospace ocean color observation to field measurements and derive the spatial variability of match-up sites. The performance of the model is tested against populations of synthesized spectra and full and reduced resolutions of MERIS data. The model derived the scale difference between synthesized satellite pixel and point measurements with R(2) > 0.88 and relative error < 21% in the spectral range from 400 nm to 695 nm. The sub-pixel variabilities of reduced resolution MERIS image are derived with less than 12% of relative errors in heterogeneous region. The method is generic and applicable to different sensors.

Bayesian Model for Matching the Radiometric Measurements of Aerospace and Field Ocean Color Sensors

Directory of Open Access Journals (Sweden)

Mhd. Suhyb Salama

2010-08-01

Full Text Available A Bayesian model is developed to match aerospace ocean color observation tofield measurements and derive the spatial variability of match-up sites. The performance of the model is tested against populations of synthesized spectra and full and reduced resolutions of MERIS data. The model derived the scale difference between synthesized satellite pixel and point measurements with R2 > 0.88 and relative error < 21% in the spectral range from 400 nm to 695 nm. The sub-pixel variabilities of reduced resolution MERIS image are derived with less than 12% of relative errors in heterogeneous region. The method is generic and applicable to different sensors.

Remote Sensing of Selected Water-Quality Indicators with the Hyperspectral Imager for the Coastal Ocean (HICO) Sensor

Science.gov (United States)

2014-01-01

the bands needed for atmospheric correction. Spectral definition files for AVIRIS, HYDICE, HYMAP, HYPERION, CASI, and AISA sensors are included as...Satellite Visible Imagery – A Review.” In Lecture Notes on Coastal and Estuarine Studies, edited by R. T. Barber, N. K. Mooers, M. J. Bowman, and B...In Proceedings of SPIE Coastal Ocean Remote Sensing, edited by Robert J. Frouin, ZhongPing Lee, Vol. 6680, 668013-1-668013-9. doi:10.1117/12.736845

Self-adapted and tunable graphene strain sensors for detecting both subtle and large human motions.

Science.gov (United States)

Tao, Lu-Qi; Wang, Dan-Yang; Tian, He; Ju, Zhen-Yi; Liu, Ying; Pang, Yu; Chen, Yuan-Quan; Yang, Yi; Ren, Tian-Ling

2017-06-22

Conventional strain sensors rarely have both a high gauge factor and a large strain range simultaneously, so they can only be used in specific situations where only a high sensitivity or a large strain range is required. However, for detecting human motions that include both subtle and large motions, these strain sensors can't meet the diverse demands simultaneously. Here, we come up with laser patterned graphene strain sensors with self-adapted and tunable performance for the first time. A series of strain sensors with either an ultrahigh gauge factor or a preferable strain range can be fabricated simultaneously via one-step laser patterning, and are suitable for detecting all human motions. The strain sensors have a GF of up to 457 with a strain range of 35%, or have a strain range of up to 100% with a GF of 268. Most importantly, the performance of the strain sensors can be easily tuned by adjusting the patterns of the graphene, so that the sensors can meet diverse demands in both subtle and large motion situations. The graphene strain sensors show significant potential in applications such as wearable electronics, health monitoring and intelligent robots. Furthermore, the facile, fast and low-cost fabrication method will make them possible and practical to be used for commercial applications in the future.

Tsunami Simulation Method Assimilating Ocean Bottom Pressure Data Near a Tsunami Source Region

Science.gov (United States)

Tanioka, Yuichiro

2018-02-01

A new method was developed to reproduce the tsunami height distribution in and around the source area, at a certain time, from a large number of ocean bottom pressure sensors, without information on an earthquake source. A dense cabled observation network called S-NET, which consists of 150 ocean bottom pressure sensors, was installed recently along a wide portion of the seafloor off Kanto, Tohoku, and Hokkaido in Japan. However, in the source area, the ocean bottom pressure sensors cannot observe directly an initial ocean surface displacement. Therefore, we developed the new method. The method was tested and functioned well for a synthetic tsunami from a simple rectangular fault with an ocean bottom pressure sensor network using 10 arc-min, or 20 km, intervals. For a test case that is more realistic, ocean bottom pressure sensors with 15 arc-min intervals along the north-south direction and sensors with 30 arc-min intervals along the east-west direction were used. In the test case, the method also functioned well enough to reproduce the tsunami height field in general. These results indicated that the method could be used for tsunami early warning by estimating the tsunami height field just after a great earthquake without the need for earthquake source information.

Adaptive Security in ODMAC for Multihop Energy Harvesting Wireless Sensor Networks

DEFF Research Database (Denmark)

Di Mauro, Alessio; Fafoutis, Xenofon; Dragoni, Nicola

2015-01-01

Energy Harvesting Wireless Sensor Networks (EH-WSNs) represent an interesting new paradigm where individual nodes forming a network are powered by energy sources scavenged from the surrounding environment. This technique provides numerous advantages, but also new design challenges. Securing...... the communications under energy constraints represents one of these key challenges. The amount of energy available is theoretically infinite in the long run but highly variable over short periods of time, and managing it is a crucial aspect. In this paper we present an adaptive approach for security in multihop EH...

Illumination adaptation with rapid-response color sensors

Science.gov (United States)

Zhang, Xinchi; Wang, Quan; Boyer, Kim L.

2014-09-01

Smart lighting solutions based on imaging sensors such as webcams or time-of-flight sensors suffer from rising privacy concerns. In this work, we use low-cost non-imaging color sensors to measure local luminous flux of different colors in an indoor space. These sensors have much higher data acquisition rate and are much cheaper than many o_-the-shelf commercial products. We have developed several applications with these sensors, including illumination feedback control and occupancy-driven lighting.

Monitoring Anthropogenic Ocean Sound from Shipping Using an Acoustic Sensor Network and a Compressive Sensing Approach †

Science.gov (United States)

Harris, Peter; Philip, Rachel; Robinson, Stephen; Wang, Lian

2016-01-01

Monitoring ocean acoustic noise has been the subject of considerable recent study, motivated by the desire to assess the impact of anthropogenic noise on marine life. A combination of measuring ocean sound using an acoustic sensor network and modelling sources of sound and sound propagation has been proposed as an approach to estimating the acoustic noise map within a region of interest. However, strategies for developing a monitoring network are not well established. In this paper, considerations for designing a network are investigated using a simulated scenario based on the measurement of sound from ships in a shipping lane. Using models for the sources of the sound and for sound propagation, a noise map is calculated and measurements of the noise map by a sensor network within the region of interest are simulated. A compressive sensing algorithm, which exploits the sparsity of the representation of the noise map in terms of the sources, is used to estimate the locations and levels of the sources and thence the entire noise map within the region of interest. It is shown that although the spatial resolution to which the sound sources can be identified is generally limited, estimates of aggregated measures of the noise map can be obtained that are more reliable compared with those provided by other approaches. PMID:27011187

A two-hop based adaptive routing protocol for real-time wireless sensor networks.

Science.gov (United States)

Rachamalla, Sandhya; Kancherla, Anitha Sheela

2016-01-01

One of the most important and challenging issues in wireless sensor networks (WSNs) is to optimally manage the limited energy of nodes without degrading the routing efficiency. In this paper, we propose an energy-efficient adaptive routing mechanism for WSNs, which saves energy of nodes by removing the much delayed packets without degrading the real-time performance of the used routing protocol. It uses the adaptive transmission power algorithm which is based on the attenuation of the wireless link to improve the energy efficiency. The proposed routing mechanism can be associated with any geographic routing protocol and its performance is evaluated by integrating with the well known two-hop based real-time routing protocol, PATH and the resulting protocol is energy-efficient adaptive routing protocol (EE-ARP). The EE-ARP performs well in terms of energy consumption, deadline miss ratio, packet drop and end-to-end delay.

Adaptive elimination of optical fiber transmission noise in fiber ocean bottom seismic system

Science.gov (United States)

Zhong, Qiuwen; Hu, Zhengliang; Cao, Chunyan; Dong, Hongsheng

2017-10-01

In this paper, a pressure and acceleration insensitive reference Interferometer is used to obtain laser and public noise introduced by transmission fiber and laser. By using direct subtraction and adaptive filtering, this paper attempts to eliminate and estimation the transmission noise of sensing probe. This paper compares the noise suppression effect of four methods, including the direct subtraction (DS), the least mean square error adaptive elimination (LMS), the normalized least mean square error adaptive elimination (NLMS) and the least square (RLS) adaptive filtering. The experimental results show that the noise reduction effect of RLS and NLMS are almost the same, better than LMS and DS, which can reach 8dB (@100Hz). But considering the workload, RLS is not conducive to the real-time operating system. When it comes to the same treatment effect, the practicability of NLMS is higher than RLS. The noise reduction effect of LMS is slightly worse than that of RLS and NLMS, about 6dB (@100Hz), but its computational complexity is small, which is beneficial to the real time system implementation. It can also be seen that the DS method has the least amount of computational complexity, but the noise suppression effect is worse than that of the adaptive filter due to the difference of the noise amplitude between the RI and the SI, only 4dB (@100Hz) can be reached. The adaptive filter can basically eliminate the influence of the transmission noise, and the simulation signal of the sensor is kept intact.

Satellite Ocean Biology: Past, Present, Future

Science.gov (United States)

McClain, Charles R.

2012-01-01

Since 1978 when the first satellite ocean color proof-of-concept sensor, the Nimbus-7 Coastal Zone Color Scanner, was launched, much progress has been made in refining the basic measurement concept and expanding the research applications of global satellite time series of biological and optical properties such as chlorophyll-a concentrations. The seminar will review the fundamentals of satellite ocean color measurements (sensor design considerations, on-orbit calibration, atmospheric corrections, and bio-optical algorithms), scientific results from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate resolution Imaging Spectroradiometer (MODIS) missions, and the goals of future NASA missions such as PACE, the Aerosol, Cloud, Ecology (ACE), and Geostationary Coastal and Air Pollution Events (GeoCAPE) missions.

Adaptive Sensor Optimization and Cognitive Image Processing Using Autonomous Optical Neuroprocessors; TOPICAL

International Nuclear Information System (INIS)

CAMERON, STEWART M.

2001-01-01

Measurement and signal intelligence demands has created new requirements for information management and interoperability as they affect surveillance and situational awareness. Integration of on-board autonomous learning and adaptive control structures within a remote sensing platform architecture would substantially improve the utility of intelligence collection by facilitating real-time optimization of measurement parameters for variable field conditions. A problem faced by conventional digital implementations of intelligent systems is the conflict between a distributed parallel structure on a sequential serial interface functionally degrading bandwidth and response time. In contrast, optically designed networks exhibit the massive parallelism and interconnect density needed to perform complex cognitive functions within a dynamic asynchronous environment. Recently, all-optical self-organizing neural networks exhibiting emergent collective behavior which mimic perception, recognition, association, and contemplative learning have been realized using photorefractive holography in combination with sensory systems for feature maps, threshold decomposition, image enhancement, and nonlinear matched filters. Such hybrid information processors depart from the classical computational paradigm based on analytic rules-based algorithms and instead utilize unsupervised generalization and perceptron-like exploratory or improvisational behaviors to evolve toward optimized solutions. These systems are robust to instrumental systematics or corrupting noise and can enrich knowledge structures by allowing competition between multiple hypotheses. This property enables them to rapidly adapt or self-compensate for dynamic or imprecise conditions which would be unstable using conventional linear control models. By incorporating an intelligent optical neuroprocessor in the back plane of an imaging sensor, a broad class of high-level cognitive image analysis problems including geometric

Adaptive Multi-Sensor Perception for Driving Automation in Outdoor Contexts

Directory of Open Access Journals (Sweden)

Annalisa Milella

2014-08-01

Full Text Available In this research, adaptive perception for driving automation is discussed so as to enable a vehicle to automatically detect driveable areas and obstacles in the scene. It is especially designed for outdoor contexts where conventional perception systems that rely on a priori knowledge of the terrain's geometric properties, appearance properties, or both, is prone to fail, due to the variability in the terrain properties and environmental conditions. In contrast, the proposed framework uses a self-learning approach to build a model of the ground class that is continuously adjusted online to reflect the latest ground appearance. The system also features high flexibility, as it can work using a single sensor modality or a multi-sensor combination. In the context of this research, different embodiments have been demonstrated using range data coming from either a radar or a stereo camera, and adopting self-supervised strategies where monocular vision is automatically trained by radar or stereo vision. A comprehensive set of experimental results, obtained with different ground vehicles operating in the field, are presented to validate and assess the performance of the system.

Multi-rate sensor fusion-based adaptive discrete finite-time synergetic control for flexible-joint mechanical systems

International Nuclear Information System (INIS)

Xue Guang-Yue; Ren Xue-Mei; Xia Yuan-Qing

2013-01-01

This paper proposes an adaptive discrete finite-time synergetic control (ADFTSC) scheme based on a multi-rate sensor fusion estimator for flexible-joint mechanical systems in the presence of unmeasured states and dynamic uncertainties. Multi-rate sensors are employed to observe the system states which cannot be directly obtained by encoders due to the existence of joint flexibilities. By using an extended Kalman filter (EKF), the finite-time synergetic controller is designed based on a sensor fusion estimator which estimates states and parameters of the mechanical system with multi-rate measurements. The proposed controller can guarantee the finite-time convergence of tracking errors by the theoretical derivation. Simulation and experimental studies are included to validate the effectiveness of the proposed approach. (general)

Robust Adaptive Beamforming with Sensor Position Errors Using Weighted Subspace Fitting-Based Covariance Matrix Reconstruction.

Science.gov (United States)

Chen, Peng; Yang, Yixin; Wang, Yong; Ma, Yuanliang

2018-05-08

When sensor position errors exist, the performance of recently proposed interference-plus-noise covariance matrix (INCM)-based adaptive beamformers may be severely degraded. In this paper, we propose a weighted subspace fitting-based INCM reconstruction algorithm to overcome sensor displacement for linear arrays. By estimating the rough signal directions, we construct a novel possible mismatched steering vector (SV) set. We analyze the proximity of the signal subspace from the sample covariance matrix (SCM) and the space spanned by the possible mismatched SV set. After solving an iterative optimization problem, we reconstruct the INCM using the estimated sensor position errors. Then we estimate the SV of the desired signal by solving an optimization problem with the reconstructed INCM. The main advantage of the proposed algorithm is its robustness against SV mismatches dominated by unknown sensor position errors. Numerical examples show that even if the position errors are up to half of the assumed sensor spacing, the output signal-to-interference-plus-noise ratio is only reduced by 4 dB. Beam patterns plotted using experiment data show that the interference suppression capability of the proposed beamformer outperforms other tested beamformers.

An adaptive secret key-directed cryptographic scheme for secure transmission in wireless sensor networks

International Nuclear Information System (INIS)

Muhammad, K.; Jan, Z.; Khan, Z

2015-01-01

Wireless Sensor Networks (WSNs) are memory and bandwidth limited networks whose main goals are to maximize the network lifetime and minimize the energy consumption and transmission cost. To achieve these goals, different techniques of compression and clustering have been used. However, security is an open and major issue in WSNs for which different approaches are used, both in centralized and distributed WSNs' environments. This paper presents an adaptive cryptographic scheme for secure transmission of various sensitive parameters, sensed by wireless sensors to the fusion center for further processing in WSNs such as military networks. The proposed method encrypts the sensitive captured data of sensor nodes using various encryption procedures (bitxor operation, bits shuffling, and secret key based encryption) and then sends it to the fusion center. At the fusion center, the received encrypted data is decrypted for taking further necessary actions. The experimental results with complexity analysis, validate the effectiveness and feasibility of the proposed method in terms of security in WSNs. (author)

Rapid and highly integrated FPGA-based Shack-Hartmann wavefront sensor for adaptive optics system

Science.gov (United States)

Chen, Yi-Pin; Chang, Chia-Yuan; Chen, Shean-Jen

2018-02-01

In this study, a field programmable gate array (FPGA)-based Shack-Hartmann wavefront sensor (SHWS) programmed on LabVIEW can be highly integrated into customized applications such as adaptive optics system (AOS) for performing real-time wavefront measurement. Further, a Camera Link frame grabber embedded with FPGA is adopted to enhance the sensor speed reacting to variation considering its advantage of the highest data transmission bandwidth. Instead of waiting for a frame image to be captured by the FPGA, the Shack-Hartmann algorithm are implemented in parallel processing blocks design and let the image data transmission synchronize with the wavefront reconstruction. On the other hand, we design a mechanism to control the deformable mirror in the same FPGA and verify the Shack-Hartmann sensor speed by controlling the frequency of the deformable mirror dynamic surface deformation. Currently, this FPGAbead SHWS design can achieve a 266 Hz cyclic speed limited by the camera frame rate as well as leaves 40% logic slices for additionally flexible design.

An Adaptive Time-Spread Multiple-Access Policy for Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Konstantinos Oikonomou

2007-05-01

Full Text Available Sensor networks require a simple and efficient medium access control policy achieving high system throughput with no or limited control overhead in order to increase the network lifetime by minimizing the energy consumed during transmission attempts. Time-spread multiple-access (TSMA policies that have been proposed for ad hoc network environments, can also be employed in sensor networks, since no control overhead is introduced. However, they do not take advantage of any cross-layer information in order to exploit the idiosyncrasies of the particular sensor network environment such as the presence of typically static nodes and a common destination for the forwarded data. An adaptive probabilistic TSMA-based policy, that is proposed and analyzed in this paper, exploits these idiosyncrasies and achieves higher system throughput than the existing TSMA-based policies without any need for extra control overhead. As it is analytically shown in this paper, the proposed policy always outperforms the existing TSMA-based policies, if certain parameter values are properly set; the analysis also provides for these proper values. It is also shown that the proposed policy is characterized by a certain convergence period and that high system throughput is achieved for long convergence periods. The claims and expectations of the provided analysis are supported by simulation results presented in this paper.

A distance-aware replica adaptive data gathering protocol for Delay Tolerant Mobile Sensor Networks.

Science.gov (United States)

Feng, Yong; Gong, Haigang; Fan, Mingyu; Liu, Ming; Wang, Xiaomin

2011-01-01

In Delay Tolerant Mobile Sensor Networks (DTMSNs) that have the inherent features of intermitted connectivity and frequently changing network topology it is reasonable to utilize multi-replica schemes to improve the data gathering performance. However, most existing multi-replica approaches inject a large amount of message copies into the network to increase the probability of message delivery, which may drain each mobile node's limited battery supply faster and result in too much contention for the restricted resources of the DTMSN, so a proper data gathering scheme needs a trade off between the number of replica messages and network performance. In this paper, we propose a new data gathering protocol called DRADG (for Distance-aware Replica Adaptive Data Gathering protocol), which economizes network resource consumption through making use of a self-adapting algorithm to cut down the number of redundant replicas of messages, and achieves a good network performance by leveraging the delivery probabilities of the mobile sensors as main routing metrics. Simulation results have shown that the proposed DRADG protocol achieves comparable or higher message delivery ratios at the cost of the much lower transmission overhead than several current DTMSN data gathering schemes.

Diurnal variability in carbon and nitrogen pools within Chesapeake Bay and northern Gulf of Mexico: implications for future ocean color satellite sensors

Science.gov (United States)

Mannino, A.; Novak, M. G.; Tzortziou, M.; Salisbury, J.

2016-02-01

Relative to their areal extent, estuaries and coastal ocean ecosystems contribute disproportionately more to global biogeochemical cycling of carbon, nitrogen and other elements compared to the open ocean. Applying ocean color satellite data to study biological and biogeochemical processes within coastal ecosystems is challenging due to the complex mixtures of aquatic constituents derived from terrestrial, anthropogenic, and marine sources, human-impacted atmospheric properties, presence of clouds during satellite overpass, fine-scale spatial gradients, and time-varying processes on diurnal scales that cannot be resolved with current sensors. On diurnal scales, biological, photochemical, and biogeochemical processes are regulated by the variation in solar radiation. Other physical factors, such as tides, river discharge, estuarine and coastal ocean circulation, wind-driven mixing, etc., impart further variability on biological and biogeochemical processes on diurnal to multi-day time scales. Efforts to determine the temporal frequency required from a NASA GEO-CAPE ocean color satellite sensor to discern diurnal variability C and N stocks, fluxes and productivity culminated in field campaigns in the Chesapeake Bay and northern Gulf of Mexico. Near-surface drogues were released and tracked in quasi-lagrangian space to monitor hourly changes in community production, C and N stocks, and optical properties. While only small diurnal changes were observed in dissolved organic carbon (DOC) and colored dissolved organic matter (CDOM) absorption in Chesapeake Bay, substantial variation in particulate organic carbon (POC) and nitrogen (PN), chlorophyll-a, and inorganic nitrogen (DIN) were measured. Similar or greater diurnal changes in POC, PN, chlorophyll-a and DIN were found in Gulf of Mexico nearshore and offshore sites. These results suggest that satellite observations at hourly frequency are desirable to capture diurnal variability in carbon and nitrogen stocks, fluxes

Semantic Edge Based Disparity Estimation Using Adaptive Dynamic Programming for Binocular Sensors.

Science.gov (United States)

Zhu, Dongchen; Li, Jiamao; Wang, Xianshun; Peng, Jingquan; Shi, Wenjun; Zhang, Xiaolin

2018-04-03

Disparity calculation is crucial for binocular sensor ranging. The disparity estimation based on edges is an important branch in the research of sparse stereo matching and plays an important role in visual navigation. In this paper, we propose a robust sparse stereo matching method based on the semantic edges. Some simple matching costs are used first, and then a novel adaptive dynamic programming algorithm is proposed to obtain optimal solutions. This algorithm makes use of the disparity or semantic consistency constraint between the stereo images to adaptively search parameters, which can improve the robustness of our method. The proposed method is compared quantitatively and qualitatively with the traditional dynamic programming method, some dense stereo matching methods, and the advanced edge-based method respectively. Experiments show that our method can provide superior performance on the above comparison.

Multimode delta-E effect magnetic field sensors with adapted electrodes

Energy Technology Data Exchange (ETDEWEB)

Zabel, Sebastian; Fichtner, Simon; Kirchhof, Christine; Quandt, Eckhard; Faupel, Franz, E-mail: ff@tf.uni-kiel.de [Faculty of Engineering, Institute for Materials Science, Kiel University, Kaiserstraße 2, 24143 Kiel (Germany); Reermann, Jens; Schmidt, Gerhard [Faculty of Engineering, Institute for Electrical Engineering, Kiel University, Kaiserstraße 2, 24143 Kiel (Germany); Wagner, Bernhard [Fraunhofer Institute for Silicon Technology ISIT, Fraunhoferstraße 1, 25524 Itzehoe (Germany)

2016-05-30

We present an analytical and experimental study on low-noise piezoelectric thin film resonators that utilize the delta-E effect of a magnetostrictive layer to measure magnetic fields at low frequencies. Calculations from a physical model of the electromechanical resonator enable electrode designs to efficiently operate in the first and second transversal bending modes. As predicted by our calculations, the adapted electrode design improves the sensitivity by a factor of 6 and reduces the dynamic range of the sensor output by 16 dB, which significantly eases the requirements on readout electronics. Magnetic measurements show a bandwidth of 100 Hz at a noise level of about 100 pTHz{sup −0.5}.

Ocean outfall plume characterization using an Autonomous Underwater Vehicle.

Science.gov (United States)

Rogowski, Peter; Terrill, Eric; Otero, Mark; Hazard, Lisa; Middleton, William

2013-01-01

A monitoring mission to map and characterize the Point Loma Ocean Outfall (PLOO) wastewater plume using an Autonomous Underwater Vehicle (AUV) was performed on 3 March 2011. The mobility of an AUV provides a significant advantage in surveying discharge plumes over traditional cast-based methods, and when combined with optical and oceanographic sensors, provides a capability for both detecting plumes and assessing their mixing in the near and far-fields. Unique to this study is the measurement of Colored Dissolved Organic Matter (CDOM) in the discharge plume and its application for quantitative estimates of the plume's dilution. AUV mission planning methodologies for discharge plume sampling, plume characterization using onboard optical sensors, and comparison of observational data to model results are presented. The results suggest that even under variable oceanic conditions, properly planned missions for AUVs equipped with an optical CDOM sensor in addition to traditional oceanographic sensors, can accurately characterize and track ocean outfall plumes at higher resolutions than cast-based techniques.

A Long-Distance RF-Powered Sensor Node with Adaptive Power Management for IoT Applications.

Science.gov (United States)

Pizzotti, Matteo; Perilli, Luca; Del Prete, Massimo; Fabbri, Davide; Canegallo, Roberto; Dini, Michele; Masotti, Diego; Costanzo, Alessandra; Franchi Scarselli, Eleonora; Romani, Aldo

2017-07-28

We present a self-sustained battery-less multi-sensor platform with RF harvesting capability down to -17 dBm and implementing a standard DASH7 wireless communication interface. The node operates at distances up to 17 m from a 2 W UHF carrier. RF power transfer allows operation when common energy scavenging sources (e.g., sun, heat, etc.) are not available, while the DASH7 communication protocol makes it fully compatible with a standard IoT infrastructure. An optimized energy-harvesting module has been designed, including a rectifying antenna (rectenna) and an integrated nano-power DC/DC converter performing maximum-power-point-tracking (MPPT). A nonlinear/electromagnetic co-design procedure is adopted to design the rectenna, which is optimized to operate at ultra-low power levels. An ultra-low power microcontroller controls on-board sensors and wireless protocol, to adapt the power consumption to the available detected power by changing wake-up policies. As a result, adaptive behavior can be observed in the designed platform, to the extent that the transmission data rate is dynamically determined by RF power. Among the novel features of the system, we highlight the use of nano-power energy harvesting, the implementation of specific hardware/software wake-up policies, optimized algorithms for best sampling rate implementation, and adaptive behavior by the node based on the power received.

A Long-Distance RF-Powered Sensor Node with Adaptive Power Management for IoT Applications

Directory of Open Access Journals (Sweden)

Matteo Pizzotti

2017-07-01

Full Text Available We present a self-sustained battery-less multi-sensor platform with RF harvesting capability down to −17 dBm and implementing a standard DASH7 wireless communication interface. The node operates at distances up to 17 m from a 2 W UHF carrier. RF power transfer allows operation when common energy scavenging sources (e.g., sun, heat, etc. are not available, while the DASH7 communication protocol makes it fully compatible with a standard IoT infrastructure. An optimized energy-harvesting module has been designed, including a rectifying antenna (rectenna and an integrated nano-power DC/DC converter performing maximum-power-point-tracking (MPPT. A nonlinear/electromagnetic co-design procedure is adopted to design the rectenna, which is optimized to operate at ultra-low power levels. An ultra-low power microcontroller controls on-board sensors and wireless protocol, to adapt the power consumption to the available detected power by changing wake-up policies. As a result, adaptive behavior can be observed in the designed platform, to the extent that the transmission data rate is dynamically determined by RF power. Among the novel features of the system, we highlight the use of nano-power energy harvesting, the implementation of specific hardware/software wake-up policies, optimized algorithms for best sampling rate implementation, and adaptive behavior by the node based on the power received.

Wireless sensor network adaptive cooling

Energy Technology Data Exchange (ETDEWEB)

Mitchell, T. [SynapSense Corp., Folsom, CA (United States)

2009-07-01

Options for reducing data centre cooling energy requirements and their cost savings were discussed with particular reference to a wireless control solution developed by SynapSense Corporation. The wireless sensor network reduces cooling energy use at data centres by providing improved air flow management through the installation of cold aisle containment. The use of this low cost, non-invasive wireless sensor network has reduced the cooling energy use in a data center at BC Hydro by 30 per cent. The system also reduced the server and storage fan energy by 3 per cent by maintaining inlet air temperature below ASHRAE recommended operating range. The distribution of low power, low cost wireless sensors has enabled visualization tools that are changing the way that data centres are managed. The annual savings have been estimated at 4,560,000 kWh and the annual carbon dioxide abatement is approximately 1,400 metric tons. tabs., figs.

Biomimetic micromechanical adaptive flow-sensor arrays

NARCIS (Netherlands)

Krijnen, Gijsbertus J.M.; Floris, J.; Dijkstra, Marcel; Lammerink, Theodorus S.J.; Wiegerink, Remco J.

2007-01-01

We report current developments in biomimetic flow-sensors based on flow sensitive mechano-sensors of crickets. Crickets have one form of acoustic sensing evolved in the form of mechanoreceptive sensory hairs. These filiform hairs are highly perceptive to low-frequency sound with energy sensitivities

Ocean Color and Earth Science Data Records

Science.gov (United States)

Maritorena, S.

2014-12-01

The development of consistent, high quality time series of biogeochemical products from a single ocean color sensor is a difficult task that involves many aspects related to pre- and post-launch instrument calibration and characterization, stability monitoring and the removal of the contribution of the atmosphere which represents most of the signal measured at the sensor. It is even more challenging to build Climate Data Records (CDRs) or Earth Science Data Records (ESDRs) from multiple sensors as design, technology and methodologies (bands, spectral/spatial resolution, Cal/Val, algorithms) differ from sensor to sensor. NASA MEaSUREs, ESA Climate Change Initiative (CCI) and IOCCG Virtual Constellation are some of the underway efforts that investigate or produce ocean color CDRs or ESDRs from the recent and current global missions (SeaWiFS, MODIS, MERIS). These studies look at key aspects of the development of unified data records from multiple sensors, e.g. the concatenation of the "best" individual records vs. the merging of multiple records or band homogenization vs. spectral diversity. The pros and cons of the different approaches are closely dependent upon the overall science purpose of the data record and its temporal resolution. While monthly data are generally adequate for biogeochemical modeling or to assess decadal trends, higher temporal resolution data records are required to look into changes in phenology or the dynamics of phytoplankton blooms. Similarly, short temporal resolution (daily to weekly) time series may benefit more from being built through the merging of data from multiple sensors while a simple concatenation of data from individual sensors might be better suited for longer temporal resolution (e.g. monthly time series). Several Ocean Color ESDRs were developed as part of the NASA MEaSUREs project. Some of these time series are built by merging the reflectance data from SeaWiFS, MODIS-Aqua and Envisat-MERIS in a semi-analytical ocean color

Ship Sensor Observations for Islands in the Stream 2002 - Exploration of Outer Shelf and Slope Habitats off the Coast of North Carolina - Office of Ocean Exploration

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Hourly measurements made by selected ship sensors on the R/V Seward Johnson during the 2002 "Islands in the Stream - Exploration of Outer Shelf and Slope Habitats...

Surface roughness considerations for atmospheric correction of ocean color sensors. I - The Rayleigh-scattering component. II - Error in the retrieved water-leaving radiance

Science.gov (United States)

Gordon, Howard R.; Wang, Menghua

1992-01-01

The first step in the Coastal Zone Color Scanner (CZCS) atmospheric-correction algorithm is the computation of the Rayleigh-scattering (RS) contribution, L sub r, to the radiance leaving the top of the atmosphere over the ocean. In the present algorithm, L sub r is computed by assuming that the ocean surface is flat. Calculations of the radiance leaving an RS atmosphere overlying a rough Fresnel-reflecting ocean are presented to evaluate the radiance error caused by the flat-ocean assumption. Simulations are carried out to evaluate the error incurred when the CZCS-type algorithm is applied to a realistic ocean in which the surface is roughened by the wind. In situations where there is no direct sun glitter, it is concluded that the error induced by ignoring the Rayleigh-aerosol interaction is usually larger than that caused by ignoring the surface roughness. This suggests that, in refining algorithms for future sensors, more effort should be focused on dealing with the Rayleigh-aerosol interaction than on the roughness of the sea surface.

Sensor Data from the NERACOOS SOS Server, 2000-present

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Northeastern Regional Association of Coastal Ocean Observing Systems (NERACOOS) Sensor Observation Service (SOS) The OCEANS IE -- formally approved as an OGC...

Variable self-powered light detection CMOS chip with real-time adaptive tracking digital output based on a novel on-chip sensor.

Science.gov (United States)

Wang, HongYi; Fan, Youyou; Lu, Zhijian; Luo, Tao; Fu, Houqiang; Song, Hongjiang; Zhao, Yuji; Christen, Jennifer Blain

2017-10-02

This paper provides a solution for a self-powered light direction detection with digitized output. Light direction sensors, energy harvesting photodiodes, real-time adaptive tracking digital output unit and other necessary circuits are integrated on a single chip based on a standard 0.18 µm CMOS process. Light direction sensors proposed have an accuracy of 1.8 degree over a 120 degree range. In order to improve the accuracy, a compensation circuit is presented for photodiodes' forward currents. The actual measurement precision of output is approximately 7 ENOB. Besides that, an adaptive under voltage protection circuit is designed for variable supply power which may undulate with temperature and process.

Adaptive neuro-fuzzy based inferential sensor model for estimating the average air temperature in space heating systems

Energy Technology Data Exchange (ETDEWEB)

Jassar, S.; Zhao, L. [Department of Electrical and Computer Engineering, Ryerson University, 350 Victoria Street, Toronto, ON (Canada); Liao, Z. [Department of Architectural Science, Ryerson University (Canada)

2009-08-15

The heating systems are conventionally controlled by open-loop control systems because of the absence of practical methods for estimating average air temperature in the built environment. An inferential sensor model, based on adaptive neuro-fuzzy inference system modeling, for estimating the average air temperature in multi-zone space heating systems is developed. This modeling technique has the advantage of expert knowledge of fuzzy inference systems (FISs) and learning capability of artificial neural networks (ANNs). A hybrid learning algorithm, which combines the least-square method and the back-propagation algorithm, is used to identify the parameters of the network. This paper describes an adaptive network based inferential sensor that can be used to design closed-loop control for space heating systems. The research aims to improve the overall performance of heating systems, in terms of energy efficiency and thermal comfort. The average air temperature results estimated by using the developed model are strongly in agreement with the experimental results. (author)

From global to regional and back again: common climate stressors of marine ecosystems relevant for adaptation across five ocean warming hotspots.

Science.gov (United States)

Popova, Ekaterina; Yool, Andrew; Byfield, Valborg; Cochrane, Kevern; Coward, Andrew C; Salim, Shyam S; Gasalla, Maria A; Henson, Stephanie A; Hobday, Alistair J; Pecl, Gretta T; Sauer, Warwick H; Roberts, Michael J

2016-06-01

Ocean warming 'hotspots' are regions characterized by above-average temperature increases over recent years, for which there are significant consequences for both living marine resources and the societies that depend on them. As such, they represent early warning systems for understanding the impacts of marine climate change, and test-beds for developing adaptation options for coping with those impacts. Here, we examine five hotspots off the coasts of eastern Australia, South Africa, Madagascar, India and Brazil. These particular hotspots have underpinned a large international partnership that is working towards improving community adaptation by characterizing, assessing and projecting the likely future of coastal-marine food resources through the provision and sharing of knowledge. To inform this effort, we employ a high-resolution global ocean model forced by Representative Concentration Pathway 8.5 and simulated to year 2099. In addition to the sea surface temperature, we analyse projected stratification, nutrient supply, primary production, anthropogenic CO2 -driven ocean acidification, deoxygenation and ocean circulation. Our simulation finds that the temperature-defined hotspots studied here will continue to experience warming but, with the exception of eastern Australia, may not remain the fastest warming ocean areas over the next century as the strongest warming is projected to occur in the subpolar and polar areas of the Northern Hemisphere. Additionally, we find that recent rapid change in SST is not necessarily an indicator that these areas are also hotspots of the other climatic stressors examined. However, a consistent facet of the hotspots studied here is that they are all strongly influenced by ocean circulation, which has already shown changes in the recent past and is projected to undergo further strong change into the future. In addition to the fast warming, change in local ocean circulation represents a distinct feature of present and future

NeXOS, developing and evaluating a new generation of insitu ocean observation systems.

Science.gov (United States)

Delory, Eric; del Rio, Joaquin; Golmen, Lars; Roar Hareide, Nils; Pearlman, Jay; Rolin, Jean-Francois; Waldmann, Christoph; Zielinski, Oliver

2017-04-01

Ocean biological, chemical or physical processes occur over widely varying scales in space and time: from micro- to kilometer scales, from less than seconds to centuries. While space systems supply important data and information, insitu data is necessary for comprehensive modeling and forecasting of ocean dynamics. Yet, collection of in-situ observation on these scales is inherently challenging and remains generally difficult and costly in time and resources. This paper address the innovations and significant developments for a new generation of insitu sensors in FP7 European Union project "Next generation, Cost- effective, Compact, Multifunctional Web Enabled Ocean Sensor Systems Empowering Marine, Maritime and Fisheries Management" or "NeXOS" for short. Optical and acoustics sensors are the focus of NeXOS but NeXOS moves beyond just sensors as systems that simultaneously address multiple objectives and applications are becoming increasingly important. Thus NeXOS takes a perspective of both sensors and sensor systems with significant advantages over existing observing capabilities via the implementation of innovations such as multiplatform integration, greater reliability through better antifouling management and greater sensor and data interoperability through use of OGC standards. This presentation will address the sensor system development and field-testing of the new NeXOS sensor systems. This is being done on multiple platforms including profiling floats, gliders, ships, buoys and subsea stations. The implementation of a data system based on SWE and PUCK furthers interoperability across measurements and platforms. This presentation will review the sensor system capabilities, the status of field tests and recommendations for long-term ocean monitoring.

A Least Square-Based Self-Adaptive Localization Method for Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Baoguo Yu

2016-01-01

Full Text Available In the wireless sensor network (WSN localization methods based on Received Signal Strength Indicator (RSSI, it is usually required to determine the parameters of the radio signal propagation model before estimating the distance between the anchor node and an unknown node with reference to their communication RSSI value. And finally we use a localization algorithm to estimate the location of the unknown node. However, this localization method, though high in localization accuracy, has weaknesses such as complex working procedure and poor system versatility. Concerning these defects, a self-adaptive WSN localization method based on least square is proposed, which uses the least square criterion to estimate the parameters of radio signal propagation model, which positively reduces the computation amount in the estimation process. The experimental results show that the proposed self-adaptive localization method outputs a high processing efficiency while satisfying the high localization accuracy requirement. Conclusively, the proposed method is of definite practical value.

Ocean station data collected using bottle casts from ALMIRANTE SALDANHA From Northwest Atlantic and Southwest Atlantic Ocean from 1980-10-30 to 1982-08-21 (NODC Accession 9000164)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Ocean station data were collected using seechi disk, meteorological sensors, and bottle casts in the Northwest Atlantic Ocean (limit-40 W) and Southwest Atlantic...

Ocean station data collected using bottle casts from the ALMIRANTE SALDANHA in the South Atlantic Ocean from 1984-02-19 to 1984-03-26 (NODC Accession 9000034)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Ocean station data were collected using seechi disk, meteorological sensors, and bottle casts in the South Atlantic Ocean from 19 February 1984 to 26 March 1984. The...

Applying Sensor Web Technology to Marine Sensor Data

Science.gov (United States)

Jirka, Simon; del Rio, Joaquin; Mihai Toma, Daniel; Nüst, Daniel; Stasch, Christoph; Delory, Eric

2015-04-01

In this contribution we present two activities illustrating how Sensor Web technology helps to enable a flexible and interoperable sharing of marine observation data based on standards. An important foundation is the Sensor Web Architecture developed by the European FP7 project NeXOS (Next generation Low-Cost Multifunctional Web Enabled Ocean Sensor Systems Empowering Marine, Maritime and Fisheries Management). This architecture relies on the Open Geospatial Consortium's (OGC) Sensor Web Enablement (SWE) framework. It is an exemplary solution for facilitating the interoperable exchange of marine observation data within and between (research) organisations. The architecture addresses a series of functional and non-functional requirements which are fulfilled through different types of OGC SWE components. The diverse functionalities offered by the NeXOS Sensor Web architecture are shown in the following overview: - Pull-based observation data download: This is achieved through the OGC Sensor Observation Service (SOS) 2.0 interface standard. - Push-based delivery of observation data to allow users the subscription to new measurements that are relevant for them: For this purpose there are currently several specification activities under evaluation (e.g. OGC Sensor Event Service, OGC Publish/Subscribe Standards Working Group). - (Web-based) visualisation of marine observation data: Implemented through SOS client applications. - Configuration and controlling of sensor devices: This is ensured through the OGC Sensor Planning Service 2.0 interface. - Bridging between sensors/data loggers and Sensor Web components: For this purpose several components such as the "Smart Electronic Interface for Sensor Interoperability" (SEISI) concept are developed; this is complemented by a more lightweight SOS extension (e.g. based on the W3C Efficient XML Interchange (EXI) format). To further advance this architecture, there is on-going work to develop dedicated profiles of selected OGC

Regional Ocean Data Assimilation

KAUST Repository

Edwards, Christopher A.

2015-01-03

This article reviews the past 15 years of developments in regional ocean data assimilation. A variety of scientific, management, and safety-related objectives motivate marine scientists to characterize many ocean environments, including coastal regions. As in weather prediction, the accurate representation of physical, chemical, and/or biological properties in the ocean is challenging. Models and observations alone provide imperfect representations of the ocean state, but together they can offer improved estimates. Variational and sequential methods are among the most widely used in regional ocean systems, and there have been exciting recent advances in ensemble and four-dimensional variational approaches. These techniques are increasingly being tested and adapted for biogeochemical applications.

Indirect adaptive fuzzy fault-tolerant tracking control for MIMO nonlinear systems with actuator and sensor failures.

Science.gov (United States)

Bounemeur, Abdelhamid; Chemachema, Mohamed; Essounbouli, Najib

2018-05-10

In this paper, an active fuzzy fault tolerant tracking control (AFFTTC) scheme is developed for a class of multi-input multi-output (MIMO) unknown nonlinear systems in the presence of unknown actuator faults, sensor failures and external disturbance. The developed control scheme deals with four kinds of faults for both sensors and actuators. The bias, drift, and loss of accuracy additive faults are considered along with the loss of effectiveness multiplicative fault. A fuzzy adaptive controller based on back-stepping design is developed to deal with actuator failures and unknown system dynamics. However, an additional robust control term is added to deal with sensor faults, approximation errors, and external disturbances. Lyapunov theory is used to prove the stability of the closed loop system. Numerical simulations on a quadrotor are presented to show the effectiveness of the proposed approach. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Dissolved Oxygen Sensor in Animal-Borne Instruments: An Innovation for Monitoring the Health of Oceans and Investigating the Functioning of Marine Ecosystems.

Directory of Open Access Journals (Sweden)

Frederic Bailleul

Full Text Available The current decline in dissolved oxygen concentration within the oceans is a sensitive indicator of the effect of climate change on marine environment. However the impact of its declining on marine life and ecosystems' health is still quite unclear because of the difficulty in obtaining in situ data, especially in remote areas, like the Southern Ocean (SO. Southern elephant seals (Mirounga leonina proved to be a relevant alternative to the traditional oceanographic platforms to measure physical and biogeochemical structure of oceanic regions rarely observed. In this study, we use a new stage of development in biologging technology to draw a picture of dissolved oxygen concentration in the SO. We present the first results obtained from a dissolved oxygen sensor added to Argos CTD-SRDL tags and deployed on 5 female elephant seals at Kerguelen. From October 2010 and October 2011, 742 oxygen profiles associated with temperature and salinity measurements were recorded. Whether a part of the data must be considered cautiously, especially because of offsets and temporal drifts of the sensors, the range of values recorded was consistent with a concomitant survey conducted from a research vessel (Keops-2 project. Once again, elephant seals reinforced the relationship between marine ecology and oceanography, delivering essential information about the water masses properties and the biological status of the Southern Ocean. But more than the presentation of a new stage of development in animal-borne instrumentation, this pilot study opens a new field of investigation in marine ecology and could be enlarged in a near future to other key marine predators, especially large fish species like swordfish, tuna or sharks, for which dissolved oxygen is expected to play a crucial role in distribution and behaviour.

Dissolved Oxygen Sensor in Animal-Borne Instruments: An Innovation for Monitoring the Health of Oceans and Investigating the Functioning of Marine Ecosystems.

Science.gov (United States)

Bailleul, Frederic; Vacquie-Garcia, Jade; Guinet, Christophe

2015-01-01

The current decline in dissolved oxygen concentration within the oceans is a sensitive indicator of the effect of climate change on marine environment. However the impact of its declining on marine life and ecosystems' health is still quite unclear because of the difficulty in obtaining in situ data, especially in remote areas, like the Southern Ocean (SO). Southern elephant seals (Mirounga leonina) proved to be a relevant alternative to the traditional oceanographic platforms to measure physical and biogeochemical structure of oceanic regions rarely observed. In this study, we use a new stage of development in biologging technology to draw a picture of dissolved oxygen concentration in the SO. We present the first results obtained from a dissolved oxygen sensor added to Argos CTD-SRDL tags and deployed on 5 female elephant seals at Kerguelen. From October 2010 and October 2011, 742 oxygen profiles associated with temperature and salinity measurements were recorded. Whether a part of the data must be considered cautiously, especially because of offsets and temporal drifts of the sensors, the range of values recorded was consistent with a concomitant survey conducted from a research vessel (Keops-2 project). Once again, elephant seals reinforced the relationship between marine ecology and oceanography, delivering essential information about the water masses properties and the biological status of the Southern Ocean. But more than the presentation of a new stage of development in animal-borne instrumentation, this pilot study opens a new field of investigation in marine ecology and could be enlarged in a near future to other key marine predators, especially large fish species like swordfish, tuna or sharks, for which dissolved oxygen is expected to play a crucial role in distribution and behaviour.

QOS-aware error recovery in wireless body sensor networks using adaptive network coding.

Science.gov (United States)

Razzaque, Mohammad Abdur; Javadi, Saeideh S; Coulibaly, Yahaya; Hira, Muta Tah

2014-12-29

Wireless body sensor networks (WBSNs) for healthcare and medical applications are real-time and life-critical infrastructures, which require a strict guarantee of quality of service (QoS), in terms of latency, error rate and reliability. Considering the criticality of healthcare and medical applications, WBSNs need to fulfill users/applications and the corresponding network's QoS requirements. For instance, for a real-time application to support on-time data delivery, a WBSN needs to guarantee a constrained delay at the network level. A network coding-based error recovery mechanism is an emerging mechanism that can be used in these systems to support QoS at very low energy, memory and hardware cost. However, in dynamic network environments and user requirements, the original non-adaptive version of network coding fails to support some of the network and user QoS requirements. This work explores the QoS requirements of WBSNs in both perspectives of QoS. Based on these requirements, this paper proposes an adaptive network coding-based, QoS-aware error recovery mechanism for WBSNs. It utilizes network-level and user-/application-level information to make it adaptive in both contexts. Thus, it provides improved QoS support adaptively in terms of reliability, energy efficiency and delay. Simulation results show the potential of the proposed mechanism in terms of adaptability, reliability, real-time data delivery and network lifetime compared to its counterparts.

PacIOOS Nearshore Sensor 06 (NS06): Pohnpei, Micronesia

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The nearshore sensors are part of the Pacific Islands Ocean Observing System (PacIOOS) and are designed to measure a variety of ocean parameters at fixed point...

PacIOOS Nearshore Sensor 08 (NS08): Koror, Palau

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The nearshore sensors are part of the Pacific Islands Ocean Observing System (PacIOOS) and are designed to measure a variety of ocean parameters at fixed point...

PacIOOS Nearshore Sensor 11 (NS11): Saipan, CNMI

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The nearshore sensors are part of the Pacific Islands Ocean Observing System (PacIOOS) and are designed to measure a variety of ocean parameters at fixed point...

Adaptive Naive Bayes classification for wireless sensor networks

NARCIS (Netherlands)

Zwartjes, G.J.

2017-01-01

Wireless Sensor Networks are tiny devices equipped with sensors and wireless communication. These devices observe environments and communicatie about these observations. Machine Learning techniques are of interest for Wireless Sensor Network applications since they can reduce the amount of needed

Intelligent Flood Adaptive Context-aware System: How Wireless Sensors Adapt their Configuration based on Environmental Phenomenon Events

Directory of Open Access Journals (Sweden)

Jie SUN

2016-11-01

Full Text Available Henceforth, new generations of Wireless Sensor Networks (WSN have to be able to adapt their behavior to collect, from the study phenomenon, quality data for long periods of time. We have thus proposed a new formalization for the design and the implementation of context-aware systems relying on a WSN for the data collection. To illustrate this proposal, we also present an environmental use case: the study of flood events in a watershed. In this paper, we detail the simulation tool that we have developed in order to implement our model. We simulate several scenarios of context-aware systems to monitor a watershed. The data used for the simulation are the observation data of the French Orgeval watershed.

Path Planning Algorithms for the Adaptive Sensor Fleet

Science.gov (United States)

Stoneking, Eric; Hosler, Jeff

2005-01-01

The Adaptive Sensor Fleet (ASF) is a general purpose fleet management and planning system being developed by NASA in coordination with NOAA. The current mission of ASF is to provide the capability for autonomous cooperative survey and sampling of dynamic oceanographic phenomena such as current systems and algae blooms. Each ASF vessel is a software model that represents a real world platform that carries a variety of sensors. The OASIS platform will provide the first physical vessel, outfitted with the systems and payloads necessary to execute the oceanographic observations described in this paper. The ASF architecture is being designed for extensibility to accommodate heterogenous fleet elements, and is not limited to using the OASIS platform to acquire data. This paper describes the path planning algorithms developed for the acquisition phase of a typical ASF task. Given a polygonal target region to be surveyed, the region is subdivided according to the number of vessels in the fleet. The subdivision algorithm seeks a solution in which all subregions have equal area and minimum mean radius. Once the subregions are defined, a dynamic programming method is used to find a minimum-time path for each vessel from its initial position to its assigned region. This path plan includes the effects of water currents as well as avoidance of known obstacles. A fleet-level planning algorithm then shuffles the individual vessel assignments to find the overall solution which puts all vessels in their assigned regions in the minimum time. This shuffle algorithm may be described as a process of elimination on the sorted list of permutations of a cost matrix. All these path planning algorithms are facilitated by discretizing the region of interest onto a hexagonal tiling.

Improved laser-based triangulation sensor with enhanced range and resolution through adaptive optics-based active beam control.

Science.gov (United States)

Reza, Syed Azer; Khwaja, Tariq Shamim; Mazhar, Mohsin Ali; Niazi, Haris Khan; Nawab, Rahma

2017-07-20

Various existing target ranging techniques are limited in terms of the dynamic range of operation and measurement resolution. These limitations arise as a result of a particular measurement methodology, the finite processing capability of the hardware components deployed within the sensor module, and the medium through which the target is viewed. Generally, improving the sensor range adversely affects its resolution and vice versa. Often, a distance sensor is designed for an optimal range/resolution setting depending on its intended application. Optical triangulation is broadly classified as a spatial-signal-processing-based ranging technique and measures target distance from the location of the reflected spot on a position sensitive detector (PSD). In most triangulation sensors that use lasers as a light source, beam divergence-which severely affects sensor measurement range-is often ignored in calculations. In this paper, we first discuss in detail the limitations to ranging imposed by beam divergence, which, in effect, sets the sensor dynamic range. Next, we show how the resolution of laser-based triangulation sensors is limited by the interpixel pitch of a finite-sized PSD. In this paper, through the use of tunable focus lenses (TFLs), we propose a novel design of a triangulation-based optical rangefinder that improves both the sensor resolution and its dynamic range through adaptive electronic control of beam propagation parameters. We present the theory and operation of the proposed sensor and clearly demonstrate a range and resolution improvement with the use of TFLs. Experimental results in support of our claims are shown to be in strong agreement with theory.

Near-shore Antarctic pH variability has implications for the design of ocean acidification experiments

Science.gov (United States)

Kapsenberg, Lydia; Kelley, Amanda L.; Shaw, Emily C.; Martz, Todd R.; Hofmann, Gretchen E.

2015-01-01

Understanding how declining seawater pH caused by anthropogenic carbon emissions, or ocean acidification, impacts Southern Ocean biota is limited by a paucity of pH time-series. Here, we present the first high-frequency in-situ pH time-series in near-shore Antarctica from spring to winter under annual sea ice. Observations from autonomous pH sensors revealed a seasonal increase of 0.3 pH units. The summer season was marked by an increase in temporal pH variability relative to spring and early winter, matching coastal pH variability observed at lower latitudes. Using our data, simulations of ocean acidification show a future period of deleterious wintertime pH levels potentially expanding to 7–11 months annually by 2100. Given the presence of (sub)seasonal pH variability, Antarctica marine species have an existing physiological tolerance of temporal pH change that may influence adaptation to future acidification. Yet, pH-induced ecosystem changes remain difficult to characterize in the absence of sufficient physiological data on present-day tolerances. It is therefore essential to incorporate natural and projected temporal pH variability in the design of experiments intended to study ocean acidification biology.

Integrating biogeochemistry and ecology into ocean data assimilation systems

DEFF Research Database (Denmark)

Brasseur, Pierre; Gruber, Nicolas; Barciela, Rosa

2009-01-01

that are not yet considered essential, such as upper-ocean vertical fluxes that are critically important to biological activity. Further, the observing systems will need to be expanded in terms of in situ platforms (with intensified deployments of sensors for O-2 and chlorophyll, and inclusion of new sensors...... for nutrients, zooplankton, micronekton biomass, and others), satellite missions (e.g., hyperspectral instruments for ocean color, lidar systems for mixed-layer depths, and wide-swath altimeters for coastal sea level), and improved methods to assimilate these new measurements....

Evolution of Summer Ocean Mixed Layer Heat Content and Ocean/Ice Fluxes in the Arctic Ocean During the Last Decade

Science.gov (United States)

Stanton, T. P.; Shaw, W. J.

2014-12-01

Since 2002, a series of 28 Autonomous Ocean Flux Buoys have been deployed in the Beaufort Sea and from the North Pole Environmental Observatory. These long-term ice-deployed instrument systems primarily measure vertical turbulent fluxes of heat, salt and momentum at a depth of 2 - 6 m below the ocean/ice interface, while concurrently measuring current profile every 2m down to approximately 40-50m depth, within the seasonal pycnocline. Additional sensors have been added to measure local ice melt rates acoustically, and finescale thermal structure from the eddy correlation flux sensor up into the ice to resolve summer near-surface heating. The AOFB buoys have typically been co-located with Ice Tethered Profilers, that measure the upper ocean T/S structure and ice mass balance instruments. Comparisons of near-surface heat fluxes, heat content and vertical structure over the last decade will be made for buoys in the Beaufort Sea and Transpolar Drift between the North Pole and Spitzbergen. The effects of enhanced basal melting from ice/albedo feedbacks can be clearly seen in the low ice concentration summer conditions found more recently in the Beaufort Sea, while there are less pronounced effects of enhanced summer surface heating in the higher ice concentrations still found in the transpolar drift.

A Cubature-Principle-Assisted IMM-Adaptive UKF Algorithm for Maneuvering Target Tracking Caused by Sensor Faults

Directory of Open Access Journals (Sweden)

Huan Zhou

2017-09-01

Full Text Available Aimed at solving the problem of decreased filtering precision while maneuvering target tracking caused by non-Gaussian distribution and sensor faults, we developed an efficient interacting multiple model-unscented Kalman filter (IMM-UKF algorithm. By dividing the IMM-UKF into two links, the algorithm introduces the cubature principle to approximate the probability density of the random variable, after the interaction, by considering the external link of IMM-UKF, which constitutes the cubature-principle-assisted IMM method (CPIMM for solving the non-Gaussian problem, and leads to an adaptive matrix to balance the contribution of the state. The algorithm provides filtering solutions by considering the internal link of IMM-UKF, which is called a new adaptive UKF algorithm (NAUKF to address sensor faults. The proposed CPIMM-NAUKF is evaluated in a numerical simulation and two practical experiments including one navigation experiment and one maneuvering target tracking experiment. The simulation and experiment results show that the proposed CPIMM-NAUKF has greater filtering precision and faster convergence than the existing IMM-UKF. The proposed algorithm achieves a very good tracking performance, and will be effective and applicable in the field of maneuvering target tracking.

Moored ADCP current data from deployment 2 of the Multi-disciplinary Ocean Sensors for Environmental Analyses and Networks (MOSEAN) project north of Hawaii 2004-2005 (NODC Accession 0116094)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — ADCP data were collected by sensors from seven deployments within 2004-2007 on the HALE-ALOHA mooring, a location about 100 km north of Oahu, Hawaii, USA. The...

An Energy-Efficient Adaptive Clustering Protocol for Wireless Sensor Network

Directory of Open Access Journals (Sweden)

Lü Tao

2013-05-01

Full Text Available An energy-efficient adaptive clustering hierarchy EEACH in wireless sensor networks based on LEACH and LEACH-C is proposed in this paper. The main consideration is the LEACH cluster structure, each cluster is not uniform energy consumption; LEACH-C using a centralized algorithm can achieve better clustering, but do not contribute to the implementation of distributed. In EEACH, we analyzed the effects of different numbers of cluster member node on the network energy consumption; and re-planning time slice to balance the energy consumption of each cluster; and avoid the energy hole problem by reasonable cluster head selection algorithm. Its objective is to balance the energy consumption and maximize the network lifetime. Analysis and simulation results show that EEACH provides more uniform energy consumption among nodes and can prolong network lifetime compared to LEACH and LEACH-C.

A First: Detailed Tracking of an Erupting Undersea Volcano and its Impacts on the Overlying Ocean via a Submarine Electro-Optical Sensor Network.

Science.gov (United States)

Delaney, J. R.

2016-02-01

The scientifically diverse and technologically advanced cabled array component of the NSF's Ocean Observatories Initiative consists of 900 km of electro-optical fiber deployed from Pacific City, OR, across active portions of the Juan de Fuca (JdF) tectonic plate, and upward into the overlying ocean. This array, completed in 2014 on time and under budget, enables real-time, high-bandwidth, 2-way communication with seafloor and water column sensor arrays across: 1. the Cascadia accretionary prism, 2. the JdF spreading center, and, 3. portions of the overlying NE Pacific. Oceanographic processes in coastal waters, the California Current, and up to 400 km offshore, are captured by six remote-controlled, profiling moorings covering full-ocean depths. Currently, 6 primary nodes, 17 junction boxes, and 85% of 150 instruments are transmitting data ashore to the Internet via the Pacific NW Gigapop (http://www.pnwgp.net/). All data are archived at the U. of Washington, pending completion of the OOI CyberInfrastructure in October 2015. In 2014, community requests to access data to assess inflation at Axial Seamount, resulted in NSF releasing real-time data from 7 seismometers and 3 pressure sensors (IRIS: http://www.iris.edu/hq/). On April 20-22, 90 participants, met in Seattle to explore scientific responses to an eruption (http://novae.ocean.washington.edu). On April 24, Axial did erupt; seismic events rose dramatically to many hundreds/hour the Axial caldera floor dropped 2.4 m in 16 hours and water temperatures rose by 0.7°C, then declined in 3 weeks to normal values. Water-borne acoustic signals indicated seafloor activity along the rift zone north of Axial. Water column observations also indicated that a large plume of hydrothermal fluid was released during the eruptions. Follow-on field programs documented a 127 m thick lava flow on the northern rift, and a thin eruption within the caldera. These events signal a new era in Ocean Sciences as instantaneous Internet

Ocean Remote Sensing from Chinese Spaceborne Microwave Sensors

Science.gov (United States)

Yang, J.

2017-12-01

GF-3 (GF stands for GaoFen, which means High Resolution in Chinese) is the China's first C band multi-polarization high resolution microwave remote sensing satellite. It was successfully launched on Aug. 10, 2016 in Taiyuan satellite launch center. The synthetic aperture radar (SAR) on board GF-3 works at incidence angles ranging from 20 to 50 degree with several polarization modes including single-polarization, dual-polarization and quad-polarization. GF-3 SAR is also the world's most imaging modes SAR satellite, with 12 imaging modes consisting of some traditional ones like stripmap and scanSAR modes and some new ones like spotlight, wave and global modes. GF-3 SAR is thus a multi-functional satellite for both land and ocean observation by switching the different imaging modes. TG-2 (TG stands for TianGong, which means Heavenly Palace in Chinese) is a Chinese space laboratory which was launched on 15 Sep. 2016 from Jiuquan Satellite Launch Centre aboard a Long March 2F rocket. The onboard Interferometric Imaging Radar Altimeter (InIRA) is a new generation radar altimeter developed by China and also the first on orbit wide swath imaging radar altimeter, which integrates interferometry, synthetic aperture, and height tracking techniques at small incidence angles and a swath of 30 km. The InIRA was switch on to acquire data during this mission on 22 September. This paper gives some preliminary results for the quantitative remote sensing of ocean winds and waves from the GF-3 SAR and the TG-2 InIRA. The quantitative analysis and ocean wave spectra retrieval have been given from the SAR imagery. The image spectra which contain ocean wave information are first estimated from image's modulation using fast Fourier transform. Then, the wave spectra are retrieved from image spectra based on Hasselmann's classical quasi-linear SAR-ocean wave mapping model and the estimation of three modulation transfer functions (MTFs) including tilt, hydrodynamic and velocity bunching

PacIOOS Nearshore Sensor 13 (NS13): Kahului, Maui, Hawaii

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The nearshore sensors are part of the Pacific Islands Ocean Observing System (PacIOOS) and are designed to measure a variety of ocean parameters at fixed point...

PacIOOS Nearshore Sensor 16 (NS16): Wailupe, Oahu, Hawaii

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The nearshore sensors are part of the Pacific Islands Ocean Observing System (PacIOOS) and are designed to measure a variety of ocean parameters at fixed point...

PacIOOS Nearshore Sensor 09 (NS09): Cetti Bay, Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The nearshore sensors are part of the Pacific Islands Ocean Observing System (PacIOOS) and are designed to measure a variety of ocean parameters at fixed point...

PacIOOS Nearshore Sensor 15 (NS15): Pago Bay, Guam

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The nearshore sensors are part of the Pacific Islands Ocean Observing System (PacIOOS) and are designed to measure a variety of ocean parameters at fixed point...

PacIOOS Nearshore Sensor 07 (NS07): Majuro, Marshall Islands

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The nearshore sensors are part of the Pacific Islands Ocean Observing System (PacIOOS) and are designed to measure a variety of ocean parameters at fixed point...

Empirical algorithms to estimate water column pH in the Southern Ocean

Science.gov (United States)

Williams, N. L.; Juranek, L. W.; Johnson, K. S.; Feely, R. A.; Riser, S. C.; Talley, L. D.; Russell, J. L.; Sarmiento, J. L.; Wanninkhof, R.

2016-04-01

Empirical algorithms are developed using high-quality GO-SHIP hydrographic measurements of commonly measured parameters (temperature, salinity, pressure, nitrate, and oxygen) that estimate pH in the Pacific sector of the Southern Ocean. The coefficients of determination, R2, are 0.98 for pH from nitrate (pHN) and 0.97 for pH from oxygen (pHOx) with RMS errors of 0.010 and 0.008, respectively. These algorithms are applied to Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) biogeochemical profiling floats, which include novel sensors (pH, nitrate, oxygen, fluorescence, and backscatter). These algorithms are used to estimate pH on floats with no pH sensors and to validate and adjust pH sensor data from floats with pH sensors. The adjusted float data provide, for the first time, seasonal cycles in surface pH on weekly resolution that range from 0.05 to 0.08 on weekly resolution for the Pacific sector of the Southern Ocean.

Precipitable water and surface humidity over global oceans from special sensor microwave imager and European Center for Medium Range Weather Forecasts

Science.gov (United States)

Liu, W. T.; Tang, Wenqing; Wentz, Frank J.

1992-01-01

Global fields of precipitable water W from the special sensor microwave imager were compared with those from the European Center for Medium Range Weather Forecasts (ECMWF) model. They agree over most ocean areas; both data sets capture the two annual cycles examined and the interannual anomalies during an ENSO episode. They show significant differences in the dry air masses over the eastern tropical-subtropical oceans, particularly in the Southern Hemisphere. In these regions, comparisons with radiosonde data indicate that overestimation by the ECMWF model accounts for a large part of the differences. As a check on the W differences, surface-level specific humidity Q derived from W, using a statistical relation, was compared with Q from the ECMWF model. The differences in Q were found to be consistent with the differences in W, indirectly validating the Q-W relation. In both W and Q, SSMI was able to discern clearly the equatorial extension of the tongues of dry air in the eastern tropical ocean, while both ECMWF and climatological fields have reduced spatial gradients and weaker intensity.

PCA-based spatially adaptive denoising of CFA images for single-sensor digital cameras.

Science.gov (United States)

Zheng, Lei; Lukac, Rastislav; Wu, Xiaolin; Zhang, David

2009-04-01

Single-sensor digital color cameras use a process called color demosiacking to produce full color images from the data captured by a color filter array (CAF). The quality of demosiacked images is degraded due to the sensor noise introduced during the image acquisition process. The conventional solution to combating CFA sensor noise is demosiacking first, followed by a separate denoising processing. This strategy will generate many noise-caused color artifacts in the demosiacking process, which are hard to remove in the denoising process. Few denoising schemes that work directly on the CFA images have been presented because of the difficulties arisen from the red, green and blue interlaced mosaic pattern, yet a well-designed "denoising first and demosiacking later" scheme can have advantages such as less noise-caused color artifacts and cost-effective implementation. This paper presents a principle component analysis (PCA)-based spatially-adaptive denoising algorithm, which works directly on the CFA data using a supporting window to analyze the local image statistics. By exploiting the spatial and spectral correlations existing in the CFA image, the proposed method can effectively suppress noise while preserving color edges and details. Experiments using both simulated and real CFA images indicate that the proposed scheme outperforms many existing approaches, including those sophisticated demosiacking and denoising schemes, in terms of both objective measurement and visual evaluation.

Improving Decision Making in Ocean Race Sailing using Sensor Data

NARCIS (Netherlands)

van Hillegersberg, Jos; Vroling, Mark; Smit, Floris

While in some sports, experiences have been gained using traditional information and decision support systems, using large sensor datasets for sports analytics is a recent phenomenon. Using sensor data to arrive at effective decision support for sports encompasses various challenges: (1) Sensor data

New Low Cost Structure for Dual Axis Mount Solar Tracking System Using Adaptive Solar Sensor

DEFF Research Database (Denmark)

Argeseanu, Alin; Ritchie, Ewen; Leban, Krisztina Monika

2010-01-01

A solar tracking system is designed to optimize the operation of solar energy receivers. The objective of this paper is proposing a new tracking system structure with two axis. The success strategy of this new project focuses on the economical analysis of solar energy. Therefore it is important...... to determine the most cost effective design, to consider the costs of production and maintenance, and operating. The proposed tracking system uses a new solar sensor position with an adaptive feature....

QoS-Aware Error Recovery in Wireless Body Sensor Networks Using Adaptive Network Coding

Directory of Open Access Journals (Sweden)

Mohammad Abdur Razzaque

2014-12-01

Full Text Available Wireless body sensor networks (WBSNs for healthcare and medical applications are real-time and life-critical infrastructures, which require a strict guarantee of quality of service (QoS, in terms of latency, error rate and reliability. Considering the criticality of healthcare and medical applications, WBSNs need to fulfill users/applications and the corresponding network’s QoS requirements. For instance, for a real-time application to support on-time data delivery, a WBSN needs to guarantee a constrained delay at the network level. A network coding-based error recovery mechanism is an emerging mechanism that can be used in these systems to support QoS at very low energy, memory and hardware cost. However, in dynamic network environments and user requirements, the original non-adaptive version of network coding fails to support some of the network and user QoS requirements. This work explores the QoS requirements of WBSNs in both perspectives of QoS. Based on these requirements, this paper proposes an adaptive network coding-based, QoS-aware error recovery mechanism for WBSNs. It utilizes network-level and user-/application-level information to make it adaptive in both contexts. Thus, it provides improved QoS support adaptively in terms of reliability, energy efficiency and delay. Simulation results show the potential of the proposed mechanism in terms of adaptability, reliability, real-time data delivery and network lifetime compared to its counterparts.

QoS-Aware Error Recovery in Wireless Body Sensor Networks Using Adaptive Network Coding

Science.gov (United States)

Razzaque, Mohammad Abdur; Javadi, Saeideh S.; Coulibaly, Yahaya; Hira, Muta Tah

2015-01-01

Wireless body sensor networks (WBSNs) for healthcare and medical applications are real-time and life-critical infrastructures, which require a strict guarantee of quality of service (QoS), in terms of latency, error rate and reliability. Considering the criticality of healthcare and medical applications, WBSNs need to fulfill users/applications and the corresponding network's QoS requirements. For instance, for a real-time application to support on-time data delivery, a WBSN needs to guarantee a constrained delay at the network level. A network coding-based error recovery mechanism is an emerging mechanism that can be used in these systems to support QoS at very low energy, memory and hardware cost. However, in dynamic network environments and user requirements, the original non-adaptive version of network coding fails to support some of the network and user QoS requirements. This work explores the QoS requirements of WBSNs in both perspectives of QoS. Based on these requirements, this paper proposes an adaptive network coding-based, QoS-aware error recovery mechanism for WBSNs. It utilizes network-level and user-/application-level information to make it adaptive in both contexts. Thus, it provides improved QoS support adaptively in terms of reliability, energy efficiency and delay. Simulation results show the potential of the proposed mechanism in terms of adaptability, reliability, real-time data delivery and network lifetime compared to its counterparts. PMID:25551485

New perspectives in ocean acidification research: editor's introduction to the special feature on ocean acidification.

Science.gov (United States)

Munday, Philip L

2017-09-01

Ocean acidification, caused by the uptake of additional carbon dioxide (CO 2 ) from the atmosphere, will have far-reaching impacts on marine ecosystems (Gattuso & Hansson 2011 Ocean acidification Oxford University Press). The predicted changes in ocean chemistry will affect whole biological communities and will occur within the context of global warming and other anthropogenic stressors; yet much of the biological research conducted to date has tested the short-term responses of single species to ocean acidification conditions alone. While an important starting point, these studies may have limited predictive power because they do not account for possible interactive effects of multiple climate change drivers or for ecological interactions with other species. Furthermore, few studies have considered variation in responses among populations or the evolutionary potential within populations. Therefore, our knowledge about the potential for marine organisms to adapt to ocean acidification is extremely limited. In 2015, two of the pioneers in the field, Ulf Riebesell and Jean-Pierre Gattuso, noted that to move forward as a field of study, future research needed to address critical knowledge gaps in three major areas: (i) multiple environmental drivers, (ii) ecological interactions and (iii) acclimation and adaptation (Riebesell and Gattuso 2015 Nat. Clim. Change 5 , 12-14 (doi:10.1038/nclimate2456)). In May 2016, more than 350 researchers, students and stakeholders met at the 4th International Symposium on the Ocean in a High-CO 2 World in Hobart, Tasmania, to discuss the latest advances in understanding ocean acidification and its biological consequences. Many of the papers presented at the symposium reflected this shift in focus from short-term, single species and single stressor experiments towards multi-stressor and multispecies experiments that address knowledge gaps about the ecological impacts of ocean acidification on marine communities. The nine papers in this

The deep ocean under climate change

Science.gov (United States)

Levin, Lisa A.; Le Bris, Nadine

2015-11-01

The deep ocean absorbs vast amounts of heat and carbon dioxide, providing a critical buffer to climate change but exposing vulnerable ecosystems to combined stresses of warming, ocean acidification, deoxygenation, and altered food inputs. Resulting changes may threaten biodiversity and compromise key ocean services that maintain a healthy planet and human livelihoods. There exist large gaps in understanding of the physical and ecological feedbacks that will occur. Explicit recognition of deep-ocean climate mitigation and inclusion in adaptation planning by the United Nations Framework Convention on Climate Change (UNFCCC) could help to expand deep-ocean research and observation and to protect the integrity and functions of deep-ocean ecosystems.

Special Sensor Microwave Imager/Sounder (SSMIS) Sensor Data Record (SDR) in netCDF

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Special Sensor Microwave Imager/Sounder (SSMIS) is a series of passive microwave conically scanning imagers and sounders onboard the DMSP satellites beginning...

PacIOOS Nearshore Sensor 10 (NS10): Maunalua Bay, Oahu, Hawaii

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The nearshore sensors are part of the Pacific Islands Ocean Observing System (PacIOOS) and are designed to measure a variety of ocean parameters at fixed point...

PacIOOS Nearshore Sensor 05 (NS05): Pago Pago, American Samoa

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The nearshore sensors are part of the Pacific Islands Ocean Observing System (PacIOOS) and are designed to measure a variety of ocean parameters at fixed point...

PacIOOS Nearshore Sensor 04 (NS04): Waikiki Aquarium, Oahu, Hawaii

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The nearshore sensors are part of the Pacific Islands Ocean Observing System (PacIOOS) and are designed to measure a variety of ocean parameters at fixed point...

Preface to: Pan Ocean Remote Sensing Conference (PORSEC)

Digital Repository Service at National Institute of Oceanography (India)

Desa, E.; Brown, R.; Shenoi, S.S.C.; Joseph, G.

Conference (PORSEC), earlier known as the Paci c Ocean Remote Sensing Conference (PORSEC), was formed in 1992 to provide a venue for international cooperation in the increasingly important area of remote sensing of the ocean. Many countries that border... and ocean dynamics, and modeling with satellite sensor (mainly microwave) data. Some of the presentations are of regional interest, while others will nd an audience beyond the satellite remote sensing community. These rst results through their simple...

An LPV Adaptive Observer for Updating a Map Applied to an MAF Sensor in a Diesel Engine.

Science.gov (United States)

Liu, Zhiyuan; Wang, Changhui

2015-10-23

In this paper, a new method for mass air flow (MAF) sensor error compensation and an online updating error map (or lookup table) due to installation and aging in a diesel engine is developed. Since the MAF sensor error is dependent on the engine operating point, the error model is represented as a two-dimensional (2D) map with two inputs, fuel mass injection quantity and engine speed. Meanwhile, the 2D map representing the MAF sensor error is described as a piecewise bilinear interpolation model, which can be written as a dot product between the regression vector and parameter vector using a membership function. With the combination of the 2D map regression model and the diesel engine air path system, an LPV adaptive observer with low computational load is designed to estimate states and parameters jointly. The convergence of the proposed algorithm is proven under the conditions of persistent excitation and given inequalities. The observer is validated against the simulation data from engine software enDYNA provided by Tesis. The results demonstrate that the operating point-dependent error of the MAF sensor can be approximated acceptably by the 2D map from the proposed method.

An Adaptive Channel Access Method for Dynamic Super Dense Wireless Sensor Networks.

Science.gov (United States)

Lei, Chunyang; Bie, Hongxia; Fang, Gengfa; Zhang, Xuekun

2015-12-03

Super dense and distributed wireless sensor networks have become very popular with the development of small cell technology, Internet of Things (IoT), Machine-to-Machine (M2M) communications, Vehicular-to-Vehicular (V2V) communications and public safety networks. While densely deployed wireless networks provide one of the most important and sustainable solutions to improve the accuracy of sensing and spectral efficiency, a new channel access scheme needs to be designed to solve the channel congestion problem introduced by the high dynamics of competing nodes accessing the channel simultaneously. In this paper, we firstly analyzed the channel contention problem using a novel normalized channel contention analysis model which provides information on how to tune the contention window according to the state of channel contention. We then proposed an adaptive channel contention window tuning algorithm in which the contention window tuning rate is set dynamically based on the estimated channel contention level. Simulation results show that our proposed adaptive channel access algorithm based on fast contention window tuning can achieve more than 95 % of the theoretical optimal throughput and 0 . 97 of fairness index especially in dynamic and dense networks.

An Adaptive Channel Access Method for Dynamic Super Dense Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Chunyang Lei

2015-12-01

Full Text Available Super dense and distributed wireless sensor networks have become very popular with the development of small cell technology, Internet of Things (IoT, Machine-to-Machine (M2M communications, Vehicular-to-Vehicular (V2V communications and public safety networks. While densely deployed wireless networks provide one of the most important and sustainable solutions to improve the accuracy of sensing and spectral efficiency, a new channel access scheme needs to be designed to solve the channel congestion problem introduced by the high dynamics of competing nodes accessing the channel simultaneously. In this paper, we firstly analyzed the channel contention problem using a novel normalized channel contention analysis model which provides information on how to tune the contention window according to the state of channel contention. We then proposed an adaptive channel contention window tuning algorithm in which the contention window tuning rate is set dynamically based on the estimated channel contention level. Simulation results show that our proposed adaptive channel access algorithm based on fast contention window tuning can achieve more than 95 % of the theoretical optimal throughput and 0 . 97 of fairness index especially in dynamic and dense networks.

Introduction to adaptive arrays

CERN Document Server

Monzingo, Bob; Haupt, Randy

2011-01-01

This second edition is an extensive modernization of the bestselling introduction to the subject of adaptive array sensor systems. With the number of applications of adaptive array sensor systems growing each year, this look at the principles and fundamental techniques that are critical to these systems is more important than ever before. Introduction to Adaptive Arrays, 2nd Edition is organized as a tutorial, taking the reader by the hand and leading them through the maze of jargon that often surrounds this highly technical subject. It is easy to read and easy to follow as fundamental concept

The deep ocean under climate change.

Science.gov (United States)

Levin, Lisa A; Le Bris, Nadine

2015-11-13

The deep ocean absorbs vast amounts of heat and carbon dioxide, providing a critical buffer to climate change but exposing vulnerable ecosystems to combined stresses of warming, ocean acidification, deoxygenation, and altered food inputs. Resulting changes may threaten biodiversity and compromise key ocean services that maintain a healthy planet and human livelihoods. There exist large gaps in understanding of the physical and ecological feedbacks that will occur. Explicit recognition of deep-ocean climate mitigation and inclusion in adaptation planning by the United Nations Framework Convention on Climate Change (UNFCCC) could help to expand deep-ocean research and observation and to protect the integrity and functions of deep-ocean ecosystems. Copyright © 2015, American Association for the Advancement of Science.

RheoStim: Development of an Adaptive Multi-Sensor to Prevent Venous Stasis

Directory of Open Access Journals (Sweden)

Sören Weyer

2016-03-01

Full Text Available Chronic venous insufficiency of the lower limbs is often underestimated and, in the absence of therapy, results in increasingly severe complications, including therapy-resistant tissue defects. Therefore, early diagnosis and adequate therapy is of particular importance. External counter pulsation (ECP therapy is a method used to assist the venous system. The main principle of ECP is to squeeze the inner leg vessels by muscle contractions, which are evoked by functional electrical stimulation. A new adaptive trigger method is proposed, which improves and supplements the current therapeutic options by means of pulse synchronous electro-stimulation of the muscle pump. For this purpose, blood flow is determined by multi-sensor plethysmography. The hardware design and signal processing of this novel multi-sensor plethysmography device are introduced. The merged signal is used to determine the phase of the cardiac cycle, to ensure stimulation of the muscle pump during the filling phase of the heart. The pulse detection of the system is validated against a gold standard and provides a sensitivity of 98% and a false-negative rate of 2% after physical exertion. Furthermore, flow enhancement of the system has been validated by duplex ultrasonography. The results show a highly increased blood flow in the popliteal vein at the knee.

RheoStim: Development of an Adaptive Multi-Sensor to Prevent Venous Stasis

Science.gov (United States)

Weyer, Sören; Weishaupt, Fabio; Kleeberg, Christian; Leonhardt, Steffen; Teichmann, Daniel

2016-01-01

Chronic venous insufficiency of the lower limbs is often underestimated and, in the absence of therapy, results in increasingly severe complications, including therapy-resistant tissue defects. Therefore, early diagnosis and adequate therapy is of particular importance. External counter pulsation (ECP) therapy is a method used to assist the venous system. The main principle of ECP is to squeeze the inner leg vessels by muscle contractions, which are evoked by functional electrical stimulation. A new adaptive trigger method is proposed, which improves and supplements the current therapeutic options by means of pulse synchronous electro-stimulation of the muscle pump. For this purpose, blood flow is determined by multi-sensor plethysmography. The hardware design and signal processing of this novel multi-sensor plethysmography device are introduced. The merged signal is used to determine the phase of the cardiac cycle, to ensure stimulation of the muscle pump during the filling phase of the heart. The pulse detection of the system is validated against a gold standard and provides a sensitivity of 98% and a false-negative rate of 2% after physical exertion. Furthermore, flow enhancement of the system has been validated by duplex ultrasonography. The results show a highly increased blood flow in the popliteal vein at the knee. PMID:27023544

76 FR 33726 - National Ocean Council; Strategic Action Plan Content Outlines

Science.gov (United States)

2011-06-09

...; Objective 5: Resiliency and Adaptation to Climate Change and Ocean Acidification: Strengthen resiliency of coastal communities and marine and Great Lakes environments and their abilities to adapt to climate change... coastal areas in the face of climate-induced and other environmental changes; and Objective 9: Ocean...

Active and Passive Hybrid Sensor

Science.gov (United States)

Carswell, James R.

2010-01-01

A hybrid ocean wind sensor (HOWS) can map ocean vector wind in low to hurricane-level winds, and non-precipitating and precipitating conditions. It can acquire active and passive measurements through a single aperture at two wavelengths, two polarizations, and multiple incidence angles. Its low profile, compact geometry, and low power consumption permits installation on air craft platforms, including high-altitude unmanned aerial vehicles (UAVs).

Adaptive management of energy consumption, reliability and delay of wireless sensor node: Application to IEEE 802.15.4 wireless sensor node.

Science.gov (United States)

Kone, Cheick Tidjane; Mathias, Jean-Denis; De Sousa, Gil

2017-01-01

Designing a Wireless Sensor Network (WSN) to achieve a high Quality of Service (QoS) (network performance and durability) is a challenging problem. We address it by focusing on the performance of the 802.15.4 communication protocol because the IEEE 802.15.4 Standard is actually considered as one of the reference technologies in WSNs. In this paper, we propose to control the sustainable use of resources (i.e., energy consumption, reliability and timely packet transmission) of a wireless sensor node equipped with photovoltaic cells by an adaptive tuning not only of the MAC (Medium Access Control) parameters but also of the sampling frequency of the node. To do this, we use one of the existing control approaches, namely the viability theory, which aims to preserve the functions and the controls of a dynamic system in a set of desirable states. So, an analytical model, describing the evolution over time of nodal resources, is derived and used by a viability algorithm for the adaptive tuning of the IEEE 802.15.4 MAC protocol. The simulation analysis shows that our solution allows ensuring indefinitely, in the absence of hardware failure, the operations (lifetime duration, reliability and timely packet transmission) of an 802.15.4 WSN and one can temporarily increase the sampling frequency of the node beyond the regular sampling one. This latter brings advantages for agricultural and environmental applications such as precision agriculture, flood or fire prevention. Main results show that our current approach enable to send more information when critical events occur without the node runs out of energy. Finally, we argue that our approach is generic and can be applied to other types of WSN.

A Wave Glider for Studies of Biofouling and Ocean Productivity

Science.gov (United States)

2017-11-07

Report: A Wave Glider for Studies of Biofouling and Ocean Productivity The views, opinions and/or findings contained in this report are those of the...Biofouling and Ocean Productivity Report Term: 0-Other Email: john.breier@utrgv.edu Distribution Statement: 1-Approved for public release; distribution is...sensors, and engineered test surfaces was procured to study controls on ocean productivity , plankton distribution, larval settling, and biofouling. We

Magnetic sensor device

NARCIS (Netherlands)

2009-01-01

The present invention provides a sensor device and a method for detg. the presence and/or amt. of target moieties in a sample fluid, the target moieties being labeled with magnetic or magnetizable objects. The sensor device comprises a magnetic field generating means adapted for applying a retention

Biogeochemical sensor performance in the SOCCOM profiling float array

Science.gov (United States)

Johnson, Kenneth S.; Plant, Joshua N.; Coletti, Luke J.; Jannasch, Hans W.; Sakamoto, Carole M.; Riser, Stephen C.; Swift, Dana D.; Williams, Nancy L.; Boss, Emmanuel; Haëntjens, Nils; Talley, Lynne D.; Sarmiento, Jorge L.

2017-08-01

The Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) program has begun deploying a large array of biogeochemical sensors on profiling floats in the Southern Ocean. As of February 2016, 86 floats have been deployed. Here the focus is on 56 floats with quality-controlled and adjusted data that have been in the water at least 6 months. The floats carry oxygen, nitrate, pH, chlorophyll fluorescence, and optical backscatter sensors. The raw data generated by these sensors can suffer from inaccurate initial calibrations and from sensor drift over time. Procedures to correct the data are defined. The initial accuracy of the adjusted concentrations is assessed by comparing the corrected data to laboratory measurements made on samples collected by a hydrographic cast with a rosette sampler at the float deployment station. The long-term accuracy of the corrected data is compared to the GLODAPv2 data set whenever a float made a profile within 20 km of a GLODAPv2 station. Based on these assessments, the fleet average oxygen data are accurate to 1 ± 1%, nitrate to within 0.5 ± 0.5 µmol kg-1, and pH to 0.005 ± 0.007, where the error limit is 1 standard deviation of the fleet data. The bio-optical measurements of chlorophyll fluorescence and optical backscatter are used to estimate chlorophyll a and particulate organic carbon concentration. The particulate organic carbon concentrations inferred from optical backscatter appear accurate to with 35 mg C m-3 or 20%, whichever is larger. Factors affecting the accuracy of the estimated chlorophyll a concentrations are evaluated.Plain Language SummaryThe ocean science community must move toward greater use of autonomous platforms and sensors if we are to extend our knowledge of the effects of climate driven change within the ocean. Essential to this shift in observing strategies is an understanding of the performance that can be obtained from biogeochemical sensors on platforms deployed for years and the

Adaptive Observatories for Observing Moving Marine Organisms (Invited)

Science.gov (United States)

Bellingham, J. G.; Scholin, C.; Zhang, Y.; Godin, M. A.; Hobson, B.; Frolov, S.

2010-12-01

The ability to characterize the response of small marine organisms to each other, and to their environment, is a demanding observational challenge. Small organisms live in a water reference frame, while existing cable or mooring-based observatories operate in an Earth reference frame. Thus repeated observations from a fixed system observe different populations as currents sweep organisms by the sensors. In contrast, mobile systems are typically optimized for spatial coverage rather than repeated observations of the same water volume. Lagrangian drifters track water mass, but are unable to find or reposition themselves relative to ocean features. We are developing a system capable of finding, following and observing discrete populations of marine organisms over time, leveraging a decade and a half investment in the Autonomous Ocean Sampling Network (AOSN) program. AOSN undertook the development of platforms to enable multi-platform coordinated measurement of ocean properties in the late 1990s, leading to the development of a variety of autonomous underwater vehicles (AUVs) and associated technologies, notably several glider systems, now in common use. Efforts by a number of research groups have focused on methods to employ these networked systems to observe and predict dynamic physical ocean phenomena. For example, periodic large scale field programs in Monterey Bay have progressively integrated these systems with data systems, predictive models, and web-based collaborative portals. We are adapting these approaches to follow and observe the dynamics of marine organisms. Compared to physical processes, the temporal and spatial variability of small marine organisms, particularly micro-organisms, is typical greater. Consequently, while multi-platform observations of physical processes can be coordinated via intermittent communications links from shore, biological observations require a higher degree of adaptability of the observation system in situ. This talk will

PacIOOS Nearshore Sensor 03 (NS03): Hilton Hawaiian Pier, Oahu, Hawaii

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The nearshore sensors are part of the Pacific Islands Ocean Observing System (PacIOOS) and are designed to measure a variety of ocean parameters at fixed point...

PacIOOS Nearshore Sensor 01 (NS01): Waikiki Yacht Club, Oahu, Hawaii

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The nearshore sensors are part of the Pacific Islands Ocean Observing System (PacIOOS) and are designed to measure a variety of ocean parameters at fixed point...

PacIOOS Nearshore Sensor 02 (NS02): Hawaii Yacht Club, Oahu, Hawaii

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The nearshore sensors are part of the Pacific Islands Ocean Observing System (PacIOOS) and are designed to measure a variety of ocean parameters at fixed point...

PacIOOS Nearshore Sensor 12 (NS12): Kalama Beach Park, Maui, Hawaii

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The nearshore sensors are part of the Pacific Islands Ocean Observing System (PacIOOS) and are designed to measure a variety of ocean parameters at fixed point...

Adaptation of a general circulation model to ocean dynamics

Science.gov (United States)

Turner, R. E.; Rees, T. H.; Woodbury, G. E.

1976-01-01

A primitive-variable general circulation model of the ocean was formulated in which fast external gravity waves are suppressed with rigid-lid surface constraint pressires which also provide a means for simulating the effects of large-scale free-surface topography. The surface pressure method is simpler to apply than the conventional stream function models, and the resulting model can be applied to both global ocean and limited region situations. Strengths and weaknesses of the model are also presented.

Ocean surface partitioning strategies using ocean colour remote Sensing: A review

Science.gov (United States)

Krug, Lilian Anne; Platt, Trevor; Sathyendranath, Shubha; Barbosa, Ana B.

2017-06-01

The ocean surface is organized into regions with distinct properties reflecting the complexity of interactions between environmental forcing and biological responses. The delineation of these functional units, each with unique, homogeneous properties and underlying ecosystem structure and dynamics, can be defined as ocean surface partitioning. The main purposes and applications of ocean partitioning include the evaluation of particular marine environments; generation of more accurate satellite ocean colour products; assimilation of data into biogeochemical and climate models; and establishment of ecosystem-based management practices. This paper reviews the diverse approaches implemented for ocean surface partition into functional units, using ocean colour remote sensing (OCRS) data, including their purposes, criteria, methods and scales. OCRS offers a synoptic, high spatial-temporal resolution, multi-decadal coverage of bio-optical properties, relevant to the applications and value of ocean surface partitioning. In combination with other biotic and/or abiotic data, OCRS-derived data (e.g., chlorophyll-a, optical properties) provide a broad and varied source of information that can be analysed using different delineation methods derived from subjective, expert-based to unsupervised learning approaches (e.g., cluster, fuzzy and empirical orthogonal function analyses). Partition schemes are applied at global to mesoscale spatial coverage, with static (time-invariant) or dynamic (time-varying) representations. A case study, the highly heterogeneous area off SW Iberian Peninsula (NE Atlantic), illustrates how the selection of spatial coverage and temporal representation affects the discrimination of distinct environmental drivers of phytoplankton variability. Advances in operational oceanography and in the subject area of satellite ocean colour, including development of new sensors, algorithms and products, are among the potential benefits from extended use, scope and

An efficient and adaptive mutual authentication framework for heterogeneous wireless sensor network-based applications.

Science.gov (United States)

Kumar, Pardeep; Ylianttila, Mika; Gurtov, Andrei; Lee, Sang-Gon; Lee, Hoon-Jae

2014-02-11

Robust security is highly coveted in real wireless sensor network (WSN) applications since wireless sensors' sense critical data from the application environment. This article presents an efficient and adaptive mutual authentication framework that suits real heterogeneous WSN-based applications (such as smart homes, industrial environments, smart grids, and healthcare monitoring). The proposed framework offers: (i) key initialization; (ii) secure network (cluster) formation (i.e., mutual authentication and dynamic key establishment); (iii) key revocation; and (iv) new node addition into the network. The correctness of the proposed scheme is formally verified. An extensive analysis shows the proposed scheme coupled with message confidentiality, mutual authentication and dynamic session key establishment, node privacy, and message freshness. Moreover, the preliminary study also reveals the proposed framework is secure against popular types of attacks, such as impersonation attacks, man-in-the-middle attacks, replay attacks, and information-leakage attacks. As a result, we believe the proposed framework achieves efficiency at reasonable computation and communication costs and it can be a safeguard to real heterogeneous WSN applications.

An Efficient and Adaptive Mutual Authentication Framework for Heterogeneous Wireless Sensor Network-Based Applications

Science.gov (United States)

Kumar, Pardeep; Ylianttila, Mika; Gurtov, Andrei; Lee, Sang-Gon; Lee, Hoon-Jae

2014-01-01

Robust security is highly coveted in real wireless sensor network (WSN) applications since wireless sensors' sense critical data from the application environment. This article presents an efficient and adaptive mutual authentication framework that suits real heterogeneous WSN-based applications (such as smart homes, industrial environments, smart grids, and healthcare monitoring). The proposed framework offers: (i) key initialization; (ii) secure network (cluster) formation (i.e., mutual authentication and dynamic key establishment); (iii) key revocation; and (iv) new node addition into the network. The correctness of the proposed scheme is formally verified. An extensive analysis shows the proposed scheme coupled with message confidentiality, mutual authentication and dynamic session key establishment, node privacy, and message freshness. Moreover, the preliminary study also reveals the proposed framework is secure against popular types of attacks, such as impersonation attacks, man-in-the-middle attacks, replay attacks, and information-leakage attacks. As a result, we believe the proposed framework achieves efficiency at reasonable computation and communication costs and it can be a safeguard to real heterogeneous WSN applications. PMID:24521942

Extended Special Sensor Microwave Imager (SSM/I) Sensor Data Record (SDR) in netCDF

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Special Sensor Microwave Imager (SSM/I) is a seven-channel linearly polarized passive microwave radiometer that operates at frequencies of 19.36 (vertically and...

Adaptive Data Gathering in Mobile Sensor Networks Using Speedy Mobile Elements

Science.gov (United States)

Lai, Yongxuan; Xie, Jinshan; Lin, Ziyu; Wang, Tian; Liao, Minghong

2015-01-01

Data gathering is a key operator for applications in wireless sensor networks; yet it is also a challenging problem in mobile sensor networks when considering that all nodes are mobile and the communications among them are opportunistic. This paper proposes an efficient data gathering scheme called ADG that adopts speedy mobile elements as the mobile data collector and takes advantage of the movement patterns of the network. ADG first extracts the network meta-data at initial epochs, and calculates a set of proxy nodes based on the meta-data. Data gathering is then mapped into the Proxy node Time Slot Allocation (PTSA) problem that schedules the time slots and orders, according to which the data collector could gather the maximal amount of data within a limited period. Finally, the collector follows the schedule and picks up the sensed data from the proxy nodes through one hop of message transmissions. ADG learns the period when nodes are relatively stationary, so that the collector is able to pick up the data from them during the limited data gathering period. Moreover, proxy nodes and data gathering points could also be timely updated so that the collector could adapt to the change of node movements. Extensive experimental results show that the proposed scheme outperforms other data gathering schemes on the cost of message transmissions and the data gathering rate, especially under the constraint of limited data gathering period. PMID:26389903

Adaptive Data Gathering in Mobile Sensor Networks Using Speedy Mobile Elements.

Science.gov (United States)

Lai, Yongxuan; Xie, Jinshan; Lin, Ziyu; Wang, Tian; Liao, Minghong

2015-09-15

Data gathering is a key operator for applications in wireless sensor networks; yet it is also a challenging problem in mobile sensor networks when considering that all nodes are mobile and the communications among them are opportunistic. This paper proposes an efficient data gathering scheme called ADG that adopts speedy mobile elements as the mobile data collector and takes advantage of the movement patterns of the network. ADG first extracts the network meta-data at initial epochs, and calculates a set of proxy nodes based on the meta-data. Data gathering is then mapped into the Proxy node Time Slot Allocation (PTSA) problem that schedules the time slots and orders, according to which the data collector could gather the maximal amount of data within a limited period. Finally, the collector follows the schedule and picks up the sensed data from the proxy nodes through one hop of message transmissions. ADG learns the period when nodes are relatively stationary, so that the collector is able to pick up the data from them during the limited data gathering period. Moreover, proxy nodes and data gathering points could also be timely updated so that the collector could adapt to the change of node movements. Extensive experimental results show that the proposed scheme outperforms other data gathering schemes on the cost of message transmissions and the data gathering rate, especially under the constraint of limited data gathering period.

Self-organising sensor web using cell-fate optimisation

CSIR Research Space (South Africa)

Van Zyl, TL

2009-07-01

Full Text Available The Sensor Web as an open complex adaptive system exhibits many characteristics that are common to self organising systems. One of the characteristics of the Sensor Web is that of self-adaptivity in a changing environment. The changing environment...

Land-Ocean-Atmospheric Coupling Associated with Earthquakes

Science.gov (United States)

Prasad, A. K.; Singh, R. P.; Kumar, S.; Cervone, G.; Kafatos, M.; Zlotnicki, J.

2007-12-01

Earthquakes are well known to occur along the plate boundaries and also on the stable shield. The recent studies have shown existence of strong coupling between land-ocean-atmospheric parameters associated with the earthquakes. We have carried out detailed analysis of multi sensor data (optical and microwave remote) to show existence of strong coupling between land-ocean-atmospheric parameters associated with the earthquakes with focal depth up to 30 km and magnitude greater than 5.5. Complimentary nature of various land, ocean and atmospheric parameters will be demonstrated in getting an early warning information about an impending earthquake.

Retrospective satellite ocean color analysis of purposeful and natural ocean iron fertilization

Science.gov (United States)

Westberry, Toby K.; Behrenfeld, Michael J.; Milligan, Allen J.; Doney, Scott C.

2013-03-01

Significant effort has been invested in understanding the role of iron in marine ecosystems over the past few decades. What began as shipboard amendment experiments quickly grew into a succession of in situ, mesoscale ocean iron fertilization (OIF) experiments carried out in all three high nutrient low chlorophyll (HNLC) regions of the world ocean. Dedicated process studies have also looked at regions of the ocean that are seasonally exposed to iron-replete conditions as natural OIF experiments. However, one problem common to many OIF experiments is determination of biological response beyond the duration of the experiment (typicallyfloristic shifts in the phytoplankton community. Further, a consistent pattern of decreased satellite fluorescence efficiency (FLH:Chl or ϕf) following OIF is observed that is in agreement with current understanding of phytoplankton physiological responses to relief from iron stress. The current study extends our ability to retrieve phytoplankton physiology from space-based sensors, strengthens the link between satellite fluorescence and iron availability, and shows that satellite ocean color analyses provide a unique tool for monitoring OIF experiments.

Efficient Sensor Integration on Platforms (NeXOS)

Science.gov (United States)

Memè, S.; Delory, E.; Del Rio, J.; Jirka, S.; Toma, D. M.; Martinez, E.; Frommhold, L.; Barrera, C.; Pearlman, J.

2016-12-01

In-situ ocean observing platforms provide power and information transmission capability to sensors. Ocean observing platforms can be mobile, such as ships, autonomous underwater vehicles, drifters and profilers, or fixed, such as buoys, moorings and cabled observatories. The process of integrating sensors on platforms can imply substantial engineering time and resources. Constraints range from stringent mechanical constraints to proprietary communication and control firmware. In NeXOS, the implementation of a PUCK plug and play capability is being done with applications to multiple sensors and platforms. This is complemented with a sensor web enablement that addresses the flow of information from sensor to user. Open standards are being tested in order to assess their costs and benefits in existing and future observing systems. Part of the testing implied open-source coding and hardware prototyping of specific control devices in particular for closed commercial platforms where firmware upgrading is not straightforward or possible without prior agreements or service fees. Some platform manufacturers such as European companies ALSEAMAR[1] and NKE Instruments [2] are currently upgrading their control and communication firmware as part of their activities in NeXOS. The sensor development companies Sensorlab[3] SMID[4] and TRIOS [5]upgraded their firmware with this plug and play functionality. Other industrial players in Europe and the US have been sent NeXOS sensors emulators to test the new protocol on their platforms. We are currently demonstrating that with little effort, it is also possible to have such middleware implemented on very low-cost compact computers such as the open Raspberry Pi[6], and have a full end-to-end interoperable communication path from sensor to user with sensor plug and play capability. The result is an increase in sensor integration cost-efficiency and the demonstration will be used to highlight the benefit to users and ocean observatory

Naturally acidified habitat selects for ocean acidification-tolerant mussels.

Science.gov (United States)

Thomsen, Jörn; Stapp, Laura S; Haynert, Kristin; Schade, Hanna; Danelli, Maria; Lannig, Gisela; Wegner, K Mathias; Melzner, Frank

2017-04-01

Ocean acidification severely affects bivalves, especially their larval stages. Consequently, the fate of this ecologically and economically important group depends on the capacity and rate of evolutionary adaptation to altered ocean carbonate chemistry. We document successful settlement of wild mussel larvae ( Mytilus edulis ) in a periodically CO 2 -enriched habitat. The larval fitness of the population originating from the CO 2 -enriched habitat was compared to the response of a population from a nonenriched habitat in a common garden experiment. The high CO 2 -adapted population showed higher fitness under elevated P co 2 (partial pressure of CO 2 ) than the non-adapted cohort, demonstrating, for the first time, an evolutionary response of a natural mussel population to ocean acidification. To assess the rate of adaptation, we performed a selection experiment over three generations. CO 2 tolerance differed substantially between the families within the F 1 generation, and survival was drastically decreased in the highest, yet realistic, P co 2 treatment. Selection of CO 2 -tolerant F 1 animals resulted in higher calcification performance of F 2 larvae during early shell formation but did not improve overall survival. Our results thus reveal significant short-term selective responses of traits directly affected by ocean acidification and long-term adaptation potential in a key bivalve species. Because immediate response to selection did not directly translate into increased fitness, multigenerational studies need to take into consideration the multivariate nature of selection acting in natural habitats. Combinations of short-term selection with long-term adaptation in populations from CO 2 -enriched versus nonenriched natural habitats represent promising approaches for estimating adaptive potential of organisms facing global change.

Adaptation to the electronics of fast and highly efficient fission chambers; Adaptation a l'electronique de chambres a fission rapides et de grande efficacite

Energy Technology Data Exchange (ETDEWEB)

Buisson, Jacques

1968-09-04

When designing a fast and highly efficient sensor, not only optimal values of the sensor per se (nature of the filling gas, pressure, electric field, etc.), but also its adaptation to the cable of connection to the electronics must be taken into account. The author reports the development of the expression of the characteristic impedance of fission chambers and the determination of elementary tubes. He reports the theoretical study of the amplitude of pulses produced by a sensor in the case of a non-adapted sensor and in the case of an adapted sensor. It appears that an adapted chamber does not possess only benefits, but is an interesting solution only when the sensor collection time is very short and when the compliance with its speed is the essential objective. Some recommendations are made for the electronics characteristics, and for the connection cable (very low losses, which means a greater diameter than the current one)

Detecting marine hazardous substances and organisms: sensors for pollutants, toxins, and pathogens

Directory of Open Access Journals (Sweden)

O. Zielinski

2009-09-01

Full Text Available Marine environments are influenced by a wide diversity of anthropogenic and natural substances and organisms that may have adverse effects on human health and ecosystems. Real-time measurements of pollutants, toxins, and pathogens across a range of spatial scales are required to adequately monitor these hazards, manage the consequences, and to understand the processes governing their magnitude and distribution. Significant technological advancements have been made in recent years for the detection and analysis of such marine hazards. In particular, sensors deployed on a variety of mobile and fixed-point observing platforms provide a valuable means to assess hazards. In this review, we present state-of-the-art of sensor technology for the detection of harmful substances and organisms in the ocean. Sensors are classified by their adaptability to various platforms, addressing large, intermediate, or small areal scales. Current gaps and future demands are identified with an indication of the urgent need for new sensors to detect marine hazards at all scales in autonomous real-time mode. Progress in sensor technology is expected to depend on the development of small-scale sensor technologies with a high sensitivity and specificity towards target analytes or organisms. However, deployable systems must comply with platform requirements as these interconnect the three areal scales. Future developments will include the integration of existing methods into complex and operational sensing systems for a comprehensive strategy for long-term monitoring. The combination of sensor techniques on all scales will remain crucial for the demand of large spatial and temporal coverage.

Classification of Hyperspectral or Trichromatic Measurements of Ocean Color Data into Spectral Classes

Directory of Open Access Journals (Sweden)

Dilip K. Prasad

2016-03-01

Full Text Available We propose a method for classifying radiometric oceanic color data measured by hyperspectral satellite sensors into known spectral classes, irrespective of the downwelling irradiance of the particular day, i.e., the illumination conditions. The focus is not on retrieving the inherent optical properties but to classify the pixels according to the known spectral classes of the reflectances from the ocean. The method compensates for the unknown downwelling irradiance by white balancing the radiometric data at the ocean pixels using the radiometric data of bright pixels (typically from clouds. The white-balanced data is compared with the entries in a pre-calibrated lookup table in which each entry represents the spectral properties of one class. The proposed approach is tested on two datasets of in situ measurements and 26 different daylight illumination spectra for medium resolution imaging spectrometer (MERIS, moderate-resolution imaging spectroradiometer (MODIS, sea-viewing wide field-of-view sensor (SeaWiFS, coastal zone color scanner (CZCS, ocean and land colour instrument (OLCI, and visible infrared imaging radiometer suite (VIIRS sensors. Results are also shown for CIMEL’s SeaPRISM sun photometer sensor used on-board field trips. Accuracy of more than 92% is observed on the validation dataset and more than 86% is observed on the other dataset for all satellite sensors. The potential of applying the algorithms to non-satellite and non-multi-spectral sensors mountable on airborne systems is demonstrated by showing classification results for two consumer cameras. Classification on actual MERIS data is also shown. Additional results comparing the spectra of remote sensing reflectance with level 2 MERIS data and chlorophyll concentration estimates of the data are included.

Revealing the timing of ocean stratification using remotely sensed ocean fronts

Science.gov (United States)

Miller, Peter I.; Loveday, Benjamin R.

2017-10-01

Stratification is of critical importance to the circulation, mixing and productivity of the ocean, and is expected to be modified by climate change. Stratification is also understood to affect the surface aggregation of pelagic fish and hence the foraging behaviour and distribution of their predators such as seabirds and cetaceans. Hence it would be prudent to monitor the stratification of the global ocean, though this is currently only possible using in situ sampling, profiling buoys or underwater autonomous vehicles. Earth observation (EO) sensors cannot directly detect stratification, but can observe surface features related to the presence of stratification, for example shelf-sea fronts that separate tidally-mixed water from seasonally stratified water. This paper describes a novel algorithm that accumulates evidence for stratification from a sequence of oceanic front maps, and discusses preliminary results in comparison with in situ data and simulations from 3D hydrodynamic models. In certain regions, this method can reveal the timing of the seasonal onset and breakdown of stratification.

Characteristic vector analysis of inflection ratio spectra: New technique for analysis of ocean color data

Science.gov (United States)

Grew, G. W.

1985-01-01

Characteristic vector analysis applied to inflection ratio spectra is a new approach to analyzing spectral data. The technique applied to remote data collected with the multichannel ocean color sensor (MOCS), a passive sensor, simultaneously maps the distribution of two different phytopigments, chlorophyll alpha and phycoerythrin, the ocean. The data set presented is from a series of warm core ring missions conducted during 1982. The data compare favorably with a theoretical model and with data collected on the same mission by an active sensor, the airborne oceanographic lidar (AOL).

Optical sensor for measuring humidity, strain and temperature

DEFF Research Database (Denmark)

2015-01-01

The present invention relates to an optical sensor (100) adapted to measure at least three physical parameters, said optical sensor comprising a polymer-based optical waveguide structure comprising a first Bragg grating structure (101) being adapted to provide information about a first, a second...

The Ocean's Carbon Factory: Ocean Composition. The Growth Patterns of Phytoplankton Species

Science.gov (United States)

Gregg, Watson

2000-01-01

According to biological data recorded by the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) satellite, the ocean contains nearly half of all the Earth's photosynthesis activity. Through photosynthesis, plant life forms use carbon from the atmosphere, and in return, plants produce the oxygen that life requires. In effect, ocean chlorophyll works like a factory, taking carbon and "manufacturing" the air we breathe. Most ocean-bound photosynthesis is performed by single-celled plants called phytoplankton. "These things are so small," according to Michael Behrenfeld, a researcher at NASA Goddard Space Flight Center, "that if you take hundreds of them and stack them end-to-end, the length of that stack is only the thickness of a penny". The humble phytoplankton species plays a vital role in balancing the amounts of oxygen and carbon dioxide in the atmosphere. Therefore, understanding exactly how phytoplankton growth works is important.

Optical Communication System for Remote Monitoring and Adaptive Control of Distributed Ground Sensors Exhibiting Collective Intelligence

Energy Technology Data Exchange (ETDEWEB)

Cameron, S.M.; Stantz, K.M.; Trahan, M.W.; Wagner, J.S.

1998-11-01

Comprehensive management of the battle-space has created new requirements in information management, communication, and interoperability as they effect surveillance and situational awareness. The objective of this proposal is to expand intelligent controls theory to produce a uniquely powerful implementation of distributed ground-based measurement incorporating both local collective behavior, and interoperative global optimization for sensor fusion and mission oversight. By using a layered hierarchal control architecture to orchestrate adaptive reconfiguration of autonomous robotic agents, we can improve overall robustness and functionality in dynamic tactical environments without information bottlenecks. In this concept, each sensor is equipped with a miniaturized optical reflectance modulator which is interactively monitored as a remote transponder using a covert laser communication protocol from a remote mothership or operative. Robot data-sharing at the ground level can be leveraged with global evaluation criteria, including terrain overlays and remote imaging data. Information sharing and distributed intelli- gence opens up a new class of remote-sensing applications in which small single-function autono- mous observers at the local level can collectively optimize and measure large scale ground-level signals. AS the need for coverage and the number of agents grows to improve spatial resolution, cooperative behavior orchestrated by a global situational awareness umbrella will be an essential ingredient to offset increasing bandwidth requirements within the net. A system of the type described in this proposal will be capable of sensitively detecting, tracking, and mapping spatial distributions of measurement signatures which are non-stationary or obscured by clutter and inter- fering obstacles by virtue of adaptive reconfiguration. This methodology could be used, for example, to field an adaptive ground-penetrating radar for detection of underground structures in

MEMS optical sensor

DEFF Research Database (Denmark)

2013-01-01

The present invention relates to an all-optical sensor utilizing effective index modulation of a waveguide and detection of a wavelength shift of reflected light and a force sensing system accommodating said optical sensor. One embodiment of the invention relates to a sensor system comprising...... at least one multimode light source, one or more optical sensors comprising a multimode sensor optical waveguide accommodating a distributed Bragg reflector, at least one transmitting optical waveguide for guiding light from said at least one light source to said one or more multimode sensor optical...... waveguides, a detector for measuring light reflected from said Bragg reflector in said one or more multimode sensor optical waveguides, and a data processor adapted for analyzing variations in the Bragg wavelength of at least one higher order mode of the reflected light....

Monitoring of ocean storage projects

Energy Technology Data Exchange (ETDEWEB)

Caldeira, K. [Energy and Environment Directorate, Lawrence Livermore National Laboratory, Livermore, CA (United States)

2003-02-01

It has been proposed that atmospheric CO2 accumulation could be slowed by capture of CO2 from point sources and subsequent storage of that CO2 in the ocean. If applied, such sequestration efforts would need to be monitored for compliance, effectiveness, and unintended consequences. Aboveground inspection and monitoring of facilities and practices, combined with ocean observations, could assure compliance with ocean sequestration guidelines and regulations. Ocean observations could be made using a variety of sensors mounted on moorings or underwater gliders. Long-term effectiveness and leakage to the atmosphere must be estimated from models, since on large spatial scales it will be impossible to observationally distinguish carbon stored by a project from variable concentrations of background carbon. Furthermore, the ocean naturally would absorb roughly 80% of fossil fuel CO2 released to the atmosphere within a millennium. This means that most of the CO2 sequestered in the ocean that leaks out to the atmosphere will be reabsorbed by the ocean. However, there is no observational way to distinguish remaining carbon from reabsorbed carbon. The science of monitoring unintended consequences in the deep ocean interior is at a primitive state. Little is understood about ecosystems of the deep ocean interior; and even less is understood about how those ecosystems would respond to added CO2. High priority research objectives should be (1) to improve our understanding of the natural ecosystems of the deep ocean, and (2) to improve our understanding of the response of these ecosystems to increased oceanic CO2 concentrations and decreased ocean pH.

Adaptive Beamforming Based on Complex Quaternion Processes

Directory of Open Access Journals (Sweden)

Jian-wu Tao

2014-01-01

Full Text Available Motivated by the benefits of array signal processing in quaternion domain, we investigate the problem of adaptive beamforming based on complex quaternion processes in this paper. First, a complex quaternion least-mean squares (CQLMS algorithm is proposed and its performance is analyzed. The CQLMS algorithm is suitable for adaptive beamforming of vector-sensor array. The weight vector update of CQLMS algorithm is derived based on the complex gradient, leading to lower computational complexity. Because the complex quaternion can exhibit the orthogonal structure of an electromagnetic vector-sensor in a natural way, a complex quaternion model in time domain is provided for a 3-component vector-sensor array. And the normalized adaptive beamformer using CQLMS is presented. Finally, simulation results are given to validate the performance of the proposed adaptive beamformer.

Adaptive electric potential sensors for smart signal acquisition and processing

International Nuclear Information System (INIS)

Prance, R J; Beardsmore-Rust, S; Prance, H; Harland, C J; Stiffell, P B

2007-01-01

Current applications of the Electric Potential Sensor operate in a strongly (capacitively) coupled limit, with the sensor physically close to or touching the source. This mode of operation screens the sensor effectively from the majority of external noise. To date however the full capability of these sensors operating in a remote mode has not been realised outside of a screened environment (Faraday cage). This paper describes the results of preliminary work in tailoring the response of the sensors to particular signals and so reject background noise, thereby enhancing both the dynamic range and signal to noise ratio significantly

Adaptive electric potential sensors for smart signal acquisition and processing

Science.gov (United States)

Prance, R. J.; Beardsmore-Rust, S.; Prance, H.; Harland, C. J.; Stiffell, P. B.

2007-07-01

Current applications of the Electric Potential Sensor operate in a strongly (capacitively) coupled limit, with the sensor physically close to or touching the source. This mode of operation screens the sensor effectively from the majority of external noise. To date however the full capability of these sensors operating in a remote mode has not been realised outside of a screened environment (Faraday cage). This paper describes the results of preliminary work in tailoring the response of the sensors to particular signals and so reject background noise, thereby enhancing both the dynamic range and signal to noise ratio significantly.

An Adaptive Connectivity-based Centroid Algorithm for Node Positioning in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Aries Pratiarso

2015-06-01

Full Text Available In wireless sensor network applications, the position of nodes is randomly distributed following the contour of the observation area. A simple solution without any measurement tools is provided by range-free method. However, this method yields the coarse estimating position of the nodes. In this paper, we propose Adaptive Connectivity-based (ACC algorithm. This algorithm is a combination of Centroid as range-free based algorithm, and hop-based connectivity algorithm. Nodes have a possibility to estimate their own position based on the connectivity level between them and their reference nodes. Each node divides its communication range into several regions where each of them has a certain weight depends on the received signal strength. The weighted value is used to obtain the estimated position of nodes. Simulation result shows that the proposed algorithm has up to 3 meter error of estimated position on 100x100 square meter observation area, and up to 3 hop counts for 80 meters' communication range. The proposed algorithm performs an average error positioning up to 10 meters better than Weighted Centroid algorithm. Keywords: adaptive, connectivity, centroid, range-free.

RSS SSMIS OCEAN PRODUCT GRIDS DAILY FROM DMSP F17 NETCDF V7

Data.gov (United States)

National Aeronautics and Space Administration — The RSS SSMIS Ocean Product Grids Daily from DMSP F17 netCDF dataset is part of the collection of Special Sensor Microwave/Imager (SSM/I) and Special Sensor...

RSS SSMIS OCEAN PRODUCT GRIDS DAILY FROM DMSP F16 NETCDF V7

Data.gov (United States)

National Aeronautics and Space Administration — The RSS SSMIS Ocean Product Grids Daily from DMSP F16 netCDF dataset is part of the collection of Special Sensor Microwave/Imager (SSM/I) and Special Sensor...

Gene expression changes in the coccolithophore Emiliania huxleyi after 500 generations of selection to ocean acidification.

Science.gov (United States)

Lohbeck, Kai T; Riebesell, Ulf; Reusch, Thorsten B H

2014-07-07

Coccolithophores are unicellular marine algae that produce biogenic calcite scales and substantially contribute to marine primary production and carbon export to the deep ocean. Ongoing ocean acidification particularly impairs calcifying organisms, mostly resulting in decreased growth and calcification. Recent studies revealed that the immediate physiological response in the coccolithophore Emiliania huxleyi to ocean acidification may be partially compensated by evolutionary adaptation, yet the underlying molecular mechanisms are currently unknown. Here, we report on the expression levels of 10 candidate genes putatively relevant to pH regulation, carbon transport, calcification and photosynthesis in E. huxleyi populations short-term exposed to ocean acidification conditions after acclimation (physiological response) and after 500 generations of high CO2 adaptation (adaptive response). The physiological response revealed downregulation of candidate genes, well reflecting the concomitant decrease of growth and calcification. In the adaptive response, putative pH regulation and carbon transport genes were up-regulated, matching partial restoration of growth and calcification in high CO2-adapted populations. Adaptation to ocean acidification in E. huxleyi likely involved improved cellular pH regulation, presumably indirectly affecting calcification. Adaptive evolution may thus have the potential to partially restore cellular pH regulatory capacity and thereby mitigate adverse effects of ocean acidification. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Diurnal changes in ocean color in coastal waters

Science.gov (United States)

Arnone, Robert; Vandermeulen, Ryan; Ladner, Sherwin; Ondrusek, Michael; Kovach, Charles; Yang, Haoping; Salisbury, Joseph

2016-05-01

Coastal processes can change on hourly time scales in response to tides, winds and biological activity, which can influence the color of surface waters. These temporal and spatial ocean color changes require satellite validation for applications using bio-optical products to delineate diurnal processes. The diurnal color change and capability for satellite ocean color response were determined with in situ and satellite observations. Hourly variations in satellite ocean color are dependent on several properties which include: a) sensor characterization b) advection of water masses and c) diurnal response of biological and optical water properties. The in situ diurnal changes in ocean color in a dynamic turbid coastal region in the northern Gulf of Mexico were characterized using above water spectral radiometry from an AErosol RObotic NETwork (AERONET -WavCIS CSI-06) site that provides up to 8-10 observations per day (in 15-30 minute increments). These in situ diurnal changes were used to validate and quantify natural bio-optical fluctuations in satellite ocean color measurements. Satellite capability to detect changes in ocean color was characterized by using overlapping afternoon orbits of the VIIRS-NPP ocean color sensor within 100 minutes. Results show the capability of multiple satellite observations to monitor hourly color changes in dynamic coastal regions that are impacted by tides, re-suspension, and river plume dispersion. Hourly changes in satellite ocean color were validated with in situ observation on multiple occurrences during different times of the afternoon. Also, the spatial variability of VIIRS diurnal changes shows the occurrence and displacement of phytoplankton blooms and decay during the afternoon period. Results suggest that determining the temporal and spatial changes in a color / phytoplankton bloom from the morning to afternoon time period will require additional satellite coverage periods in the coastal zone.

Neural network-based sensor signal accelerator.

Energy Technology Data Exchange (ETDEWEB)

Vogt, M. C.

2000-10-16

A strategy has been developed to computationally accelerate the response time of a generic electronic sensor. The strategy can be deployed as an algorithm in a control system or as a physical interface (on an embedded microcontroller) between a slower responding external sensor and a higher-speed control system. Optional code implementations are available to adjust algorithm performance when computational capability is limited. In one option, the actual sensor signal can be sampled at the slower rate with adaptive linear neural networks predicting the sensor's future output and interpolating intermediate synthetic output values. In another option, a synchronized collection of predictors sequentially controls the corresponding synthetic output voltage. Error is adaptively corrected in both options. The core strategy has been demonstrated with automotive oxygen sensor data. A prototype interface device is under construction. The response speed increase afforded by this strategy could greatly offset the cost of developing a replacement sensor with a faster physical response time.

The Hyperspectral Imager for the Coastal Ocean (HICO (trademark)) Provides a New View of the Coastal Ocean

Science.gov (United States)

2012-02-09

The calibrated data are then sent to NRL Stennis Space Center (NRL-SSC) for further processing using the NRL SSC Automated Processing System (APS...hyperspectral sensor in space we have not previously developed automated processing for hyperspectral ocean color data. The hyperspectral processing branch

Vibration suppression in cutting tools using collocated piezoelectric sensors/actuators with an adaptive control algorithm

Energy Technology Data Exchange (ETDEWEB)

Radecki, Peter P [Los Alamos National Laboratory; Farinholt, Kevin M [Los Alamos National Laboratory; Park, Gyuhae [Los Alamos National Laboratory; Bement, Matthew T [Los Alamos National Laboratory

2008-01-01

The machining process is very important in many engineering applications. In high precision machining, surface finish is strongly correlated with vibrations and the dynamic interactions between the part and the cutting tool. Parameters affecting these vibrations and dynamic interactions, such as spindle speed, cut depth, feed rate, and the part's material properties can vary in real-time, resulting in unexpected or undesirable effects on the surface finish of the machining product. The focus of this research is the development of an improved machining process through the use of active vibration damping. The tool holder employs a high bandwidth piezoelectric actuator with an adaptive positive position feedback control algorithm for vibration and chatter suppression. In addition, instead of using external sensors, the proposed approach investigates the use of a collocated piezoelectric sensor for measuring the dynamic responses from machining processes. The performance of this method is evaluated by comparing the surface finishes obtained with active vibration control versus baseline uncontrolled cuts. Considerable improvement in surface finish (up to 50%) was observed for applications in modern day machining.

Autonomous sensor manager agents (ASMA)

Science.gov (United States)

Osadciw, Lisa A.

2004-04-01

Autonomous sensor manager agents are presented as an algorithm to perform sensor management within a multisensor fusion network. The design of the hybrid ant system/particle swarm agents is described in detail with some insight into their performance. Although the algorithm is designed for the general sensor management problem, a simulation example involving 2 radar systems is presented. Algorithmic parameters are determined by the size of the region covered by the sensor network, the number of sensors, and the number of parameters to be selected. With straight forward modifications, this algorithm can be adapted for most sensor management problems.

Cross-sensor iris recognition through kernel learning.

Science.gov (United States)

Pillai, Jaishanker K; Puertas, Maria; Chellappa, Rama

2014-01-01

Due to the increasing popularity of iris biometrics, new sensors are being developed for acquiring iris images and existing ones are being continuously upgraded. Re-enrolling users every time a new sensor is deployed is expensive and time-consuming, especially in applications with a large number of enrolled users. However, recent studies show that cross-sensor matching, where the test samples are verified using data enrolled with a different sensor, often lead to reduced performance. In this paper, we propose a machine learning technique to mitigate the cross-sensor performance degradation by adapting the iris samples from one sensor to another. We first present a novel optimization framework for learning transformations on iris biometrics. We then utilize this framework for sensor adaptation, by reducing the distance between samples of the same class, and increasing it between samples of different classes, irrespective of the sensors acquiring them. Extensive evaluations on iris data from multiple sensors demonstrate that the proposed method leads to improvement in cross-sensor recognition accuracy. Furthermore, since the proposed technique requires minimal changes to the iris recognition pipeline, it can easily be incorporated into existing iris recognition systems.

Water Sensors

Science.gov (United States)

1992-01-01

Mike Morris, former Associate Director of STAC, formed pHish Doctor, Inc. to develop and sell a pH monitor for home aquariums. The monitor, or pHish Doctor, consists of a sensor strip and color chart that continually measures pH levels in an aquarium. This is important because when the level gets too high, ammonia excreted by fish is highly toxic; at low pH, bacteria that normally break down waste products stop functioning. Sales have run into the tens of thousands of dollars. A NASA Tech Brief Technical Support Package later led to a salt water version of the system and a DoE Small Business Innovation Research (SBIR) grant for development of a sensor for sea buoys. The company, now known as Ocean Optics, Inc., is currently studying the effects of carbon dioxide buildup as well as exploring other commercial applications for the fiber optic sensor.

LPTA: location predictive and time adaptive data gathering scheme with mobile sink for wireless sensor networks.

Science.gov (United States)

Zhu, Chuan; Wang, Yao; Han, Guangjie; Rodrigues, Joel J P C; Lloret, Jaime

2014-01-01

This paper exploits sink mobility to prolong the lifetime of sensor networks while maintaining the data transmission delay relatively low. A location predictive and time adaptive data gathering scheme is proposed. In this paper, we introduce a sink location prediction principle based on loose time synchronization and deduce the time-location formulas of the mobile sink. According to local clocks and the time-location formulas of the mobile sink, nodes in the network are able to calculate the current location of the mobile sink accurately and route data packets timely toward the mobile sink by multihop relay. Considering that data packets generating from different areas may be different greatly, an adaptive dwelling time adjustment method is also proposed to balance energy consumption among nodes in the network. Simulation results show that our data gathering scheme enables data routing with less data transmission time delay and balance energy consumption among nodes.

Autonomous observations of the ocean biological carbon pump

Energy Technology Data Exchange (ETDEWEB)

Bishop, James K.B.

2009-03-01

Prediction of the substantial biologically mediated carbon flows in a rapidly changing and acidifying ocean requires model simulations informed by observations of key carbon cycle processes on the appropriate space and time scales. From 2000 to 2004, the National Oceanographic Partnership Program (NOPP) supported the development of the first low-cost fully-autonomous ocean profiling Carbon Explorers that demonstrated that year-round real-time observations of particulate organic carbon (POC) concentration and sedimentation could be achieved in the world's ocean. NOPP also initiated the development of a sensor for particulate inorganic carbon (PIC) suitable for operational deployment across all oceanographic platforms. As a result, PIC profile characterization that once required shipboard sample collection and shipboard or shore based laboratory analysis, is now possible to full ocean depth in real time using a 0.2W sensor operating at 24 Hz. NOPP developments further spawned US DOE support to develop the Carbon Flux Explorer, a free-vehicle capable of following hourly variations of particulate inorganic and organic carbon sedimentation from near surface to kilometer depths for seasons to years and capable of relaying contemporaneous observations via satellite. We have demonstrated the feasibility of real time - low cost carbon observations which are of fundamental value to carbon prediction and when further developed, will lead to a fully enhanced global carbon observatory capable of real time assessment of the ocean carbon sink, a needed constraint for assessment of carbon management policies on a global scale.

The Wave Glider°: A New Autonomous Surface Vehicle to Augment MBARI's Growing Fleet of Ocean Observing Systems

Science.gov (United States)

Tougher, B. B.

2011-12-01

Monterey Bay Aquarium Research Institute's (MBARI) evolving fleet of ocean observing systems has made it possible to collect information and data about a wide variety of ocean parameters, enabling researchers to better understand marine ecosystems. In collaboration with Liquid Robotics Inc, the designer of the Wave Glider autonomous surface vehicle (ASV), MBARI is adding a new capability to its suite of ocean observing tools. This new technology will augment MBARI research programs that use satellites, ships, moorings, drifters, autonomous underwater vehicles (AUVs) and remotely operated vehicles (ROVs) to improve data collection of temporally and spatially variable oceanographic features. The Wave Glider ASV derives its propulsion from wave energy, while sensors and communications are powered through the use of two solar panels and batteries, enabling it to remain at sea indefinitely. Wave Gliders are remotely controlled via real-time Iridium burst communications, which also permit real-time data telemetry. MBARI has developed Ocean Acidification (OA) moorings to continuously monitor the chemical and physical changes occurring in the ocean as a result of increased levels of atmospheric carbon dioxide (CO2). The moorings are spatially restricted by being anchored to the seafloor, so during the summer of 2011 the ocean acidification sensor suite designed for moorings was integrated into a Wave Glider ASV to increase both temporal and spatial ocean observation capabilities. The OA sensor package enables the measurement of parameters essential to better understanding the changing acidity of the ocean, specifically pCO2, pH, oxygen, salinity and temperature. The Wave Glider will also be equipped with a meteorological sensor suite that will measure air temperature, air pressure, and wind speed and direction. The OA sensor integration into a Wave Glider was part of MBARI's 2011 summer internship program. This project involved designing a new layout for the OA sensors

RSS SSM/I OCEAN PRODUCT GRIDS DAILY FROM DMSP F14 NETCDF V7

Data.gov (United States)

National Aeronautics and Space Administration — The RSS SSM/I Ocean Product Grids Daily from DMSP F14 netCDF dataset is part of the collection of Special Sensor Microwave/Imager (SSM/I) and Special Sensor...

RSS SSM/I OCEAN PRODUCT GRIDS DAILY FROM DMSP F11 NETCDF V7

Data.gov (United States)

National Aeronautics and Space Administration — The RSS SSM/I Ocean Product Grids Daily from DMSP F11 netCDF dataset is part of the collection of Special Sensor Microwave/Imager (SSM/I) and Special Sensor...

RSS SSM/I OCEAN PRODUCT GRIDS DAILY FROM DMSP F13 NETCDF V7

Data.gov (United States)

National Aeronautics and Space Administration — The RSS SSM/I Ocean Product Grids Daily from DMSP F13 netCDF dataset is part of the collection of Special Sensor Microwave/Imager (SSM/I) and Special Sensor...

Ocean acidification

International Nuclear Information System (INIS)

Soubelet, Helene; Veyre, Philippe; Monnoyer-Smith, Laurence

2017-09-01

This brief publication first recalls and outlines that ocean acidification is expected to increase, and will result in severe ecological impacts (more fragile coral reefs, migration of species, and so on), and therefore social and economic impacts. This issue is particularly important for France who possesses the second exclusive maritime area in the world. The various impacts of ocean acidification on living species is described, notably for phytoplankton, coral reefs, algae, molluscs, and fishes. Social and economic impacts are also briefly presented: tourism, protection against risks (notably by coral reefs), shellfish aquaculture and fishing. Issues to be addressed by scientific research are evoked: interaction between elements of an ecosystem and between different ecosystems, multi-stress effects all along organism lifetime, vulnerability and adaptability of human societies

Adaptive Wavelet Transforms

Energy Technology Data Exchange (ETDEWEB)

Szu, H.; Hsu, C. [Univ. of Southwestern Louisiana, Lafayette, LA (United States)

1996-12-31

Human sensors systems (HSS) may be approximately described as an adaptive or self-learning version of the Wavelet Transforms (WT) that are capable to learn from several input-output associative pairs of suitable transform mother wavelets. Such an Adaptive WT (AWT) is a redundant combination of mother wavelets to either represent or classify inputs.

Ocean Observatories and the Integrated Ocean Observing System, IOOS: Developing the Synergy

Science.gov (United States)

Altalo, M. G.

2006-05-01

The National Office for Integrated and Sustained Ocean Observations is responsible for the planning, coordination and development of the U.S. Integrated Ocean Observing System, IOOS, which is both the U.S. contribution to GOOS as well as the ocean component of GEOSS. The IOOS is comprised of global observations as well as regional coastal observations coordinated so as to provide environmental information to optimize societal management decisions including disaster resilience, public health, marine transport, national security, climate and weather impact, and natural resource and ecosystem management. Data comes from distributed sensor systems comprising Federal and state monitoring efforts as well as regional enhancements, which are managed through data management and communications (DMAC) protocols. At present, 11 regional associations oversee the development of the observing System components in their region and are the primary interface with the user community. The ocean observatories are key elements of this National architecture and provide the infrastructure necessary to test new technologies, platforms, methods, models, and practices which, when validated, can transition into the operational components of the IOOS. This allows the IOOS to remain "state of the art" through incorporation of research at all phases. Both the observatories as well as the IOOS will contribute to the enhanced understanding of the ocean and coastal system so as to transform science results into societal solutions.

Wearable sensors for human health monitoring

Science.gov (United States)

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.

ENERGY OPTIMIZATION IN CLUSTER BASED WIRELESS SENSOR NETWORKS

Directory of Open Access Journals (Sweden)

T. SHANKAR

2014-04-01

Full Text Available Wireless sensor networks (WSN are made up of sensor nodes which are usually battery-operated devices, and hence energy saving of sensor nodes is a major design issue. To prolong the networks lifetime, minimization of energy consumption should be implemented at all layers of the network protocol stack starting from the physical to the application layer including cross-layer optimization. Optimizing energy consumption is the main concern for designing and planning the operation of the WSN. Clustering technique is one of the methods utilized to extend lifetime of the network by applying data aggregation and balancing energy consumption among sensor nodes of the network. This paper proposed new version of Low Energy Adaptive Clustering Hierarchy (LEACH, protocols called Advanced Optimized Low Energy Adaptive Clustering Hierarchy (AOLEACH, Optimal Deterministic Low Energy Adaptive Clustering Hierarchy (ODLEACH, and Varying Probability Distance Low Energy Adaptive Clustering Hierarchy (VPDL combination with Shuffled Frog Leap Algorithm (SFLA that enables selecting best optimal adaptive cluster heads using improved threshold energy distribution compared to LEACH protocol and rotating cluster head position for uniform energy dissipation based on energy levels. The proposed algorithm optimizing the life time of the network by increasing the first node death (FND time and number of alive nodes, thereby increasing the life time of the network.

Adaptive Sampling in Autonomous Marine Sensor Networks

National Research Council Canada - National Science Library

Eickstedt, Donald P

2006-01-01

... oceanographic network scenario. This architecture has three major components, an intelligent, logical sensor that provides high-level environmental state information to a behavior-based autonomous vehicle control system, a new...

The use of Saildrones as Long Endurance, Ocean Research Platforms in Remote and Extreme Environments.

Science.gov (United States)

Jenkins, R.; Peacock, D.; Jones, E.

2016-02-01

The world's oceans are experiencing significant change, which will have a profound impact on ecosystems, fish stocks and climate. Furthermore, the areas where some of the biggest changes are occurring are also some of the least measured and understood. This is largely due to their remote location and/or harsh environment, where the cost of deploying sensors is significant. New technologies are required to supplement ships and mooring data to meet the demand for longer, more economical deployments with the ability for real-time data and adaptive sampling. The Saildrone was designed to meet this need, providing the ability to reach almost any part of the world's oceans, without requiring a ship. Deployed from the dock, the unmanned Saildrone navigates autonomously to the area of interest, where it operates for extended periods before returning to shore for servicing and subsequent re-deployment. The Saildrone is propelled by wind power from a 4 m solid wing. Stability is provided by static weight in the keel and outrigger hulls. The 5.8 m hull includes several payload bays, with a payload capacity of 100 kg. Working with the Pacific Marine Environmental Laboratory (PMEL), under a collaborative Research and Development Agreement (CRADA), the Saildrone platform was equipped with a suite of meteorological and oceanographic sensors that would enable a wide variety of ocean research missions to be undertaken. After field tests in San Francisco Bay, a 3 month mission was conducted in the eastern Bering Sea in spring 2015. The mission included rough sea-trials, sensor comparisons in coordination with the NOAAS Oscar Dyson, and a survey of the northern Bering Sea shortly after ice retreat. The mission was completed as planned, with the two Saildrones (SD-126 & SD-128) returning to the dock from which they were deployed after 97 days and each completing 4400 nautical miles. During the second half of 2015, two subsequent missions were conducted in the Gulf of Mexico. Two

Remote Sensing of Ocean Color

Science.gov (United States)

Dierssen, Heidi M.; Randolph, Kaylan

The oceans cover over 70% of the earth's surface and the life inhabiting the oceans play an important role in shaping the earth's climate. Phytoplankton, the microscopic organisms in the surface ocean, are responsible for half of the photosynthesis on the planet. These organisms at the base of the food web take up light and carbon dioxide and fix carbon into biological structures releasing oxygen. Estimating the amount of microscopic phytoplankton and their associated primary productivity over the vast expanses of the ocean is extremely challenging from ships. However, as phytoplankton take up light for photosynthesis, they change the color of the surface ocean from blue to green. Such shifts in ocean color can be measured from sensors placed high above the sea on satellites or aircraft and is called "ocean color remote sensing." In open ocean waters, the ocean color is predominantly driven by the phytoplankton concentration and ocean color remote sensing has been used to estimate the amount of chlorophyll a, the primary light-absorbing pigment in all phytoplankton. For the last few decades, satellite data have been used to estimate large-scale patterns of chlorophyll and to model primary productivity across the global ocean from daily to interannual timescales. Such global estimates of chlorophyll and primary productivity have been integrated into climate models and illustrate the important feedbacks between ocean life and global climate processes. In coastal and estuarine systems, ocean color is significantly influenced by other light-absorbing and light-scattering components besides phytoplankton. New approaches have been developed to evaluate the ocean color in relationship to colored dissolved organic matter, suspended sediments, and even to characterize the bathymetry and composition of the seafloor in optically shallow waters. Ocean color measurements are increasingly being used for environmental monitoring of harmful algal blooms, critical coastal habitats

LPTA: Location Predictive and Time Adaptive Data Gathering Scheme with Mobile Sink for Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Chuan Zhu

2014-01-01

Full Text Available This paper exploits sink mobility to prolong the lifetime of sensor networks while maintaining the data transmission delay relatively low. A location predictive and time adaptive data gathering scheme is proposed. In this paper, we introduce a sink location prediction principle based on loose time synchronization and deduce the time-location formulas of the mobile sink. According to local clocks and the time-location formulas of the mobile sink, nodes in the network are able to calculate the current location of the mobile sink accurately and route data packets timely toward the mobile sink by multihop relay. Considering that data packets generating from different areas may be different greatly, an adaptive dwelling time adjustment method is also proposed to balance energy consumption among nodes in the network. Simulation results show that our data gathering scheme enables data routing with less data transmission time delay and balance energy consumption among nodes.

An Adaptive Orientation Estimation Method for Magnetic and Inertial Sensors in the Presence of Magnetic Disturbances

Directory of Open Access Journals (Sweden)

Bingfei Fan

2017-05-01

Full Text Available Magnetic and inertial sensors have been widely used to estimate the orientation of human segments due to their low cost, compact size and light weight. However, the accuracy of the estimated orientation is easily affected by external factors, especially when the sensor is used in an environment with magnetic disturbances. In this paper, we propose an adaptive method to improve the accuracy of orientation estimations in the presence of magnetic disturbances. The method is based on existing gradient descent algorithms, and it is performed prior to sensor fusion algorithms. The proposed method includes stationary state detection and magnetic disturbance severity determination. The stationary state detection makes this method immune to magnetic disturbances in stationary state, while the magnetic disturbance severity determination helps to determine the credibility of magnetometer data under dynamic conditions, so as to mitigate the negative effect of the magnetic disturbances. The proposed method was validated through experiments performed on a customized three-axis instrumented gimbal with known orientations. The error of the proposed method and the original gradient descent algorithms were calculated and compared. Experimental results demonstrate that in stationary state, the proposed method is completely immune to magnetic disturbances, and in dynamic conditions, the error caused by magnetic disturbance is reduced by 51.2% compared with original MIMU gradient descent algorithm.

An Adaptive Multi-Sensor Data Fusion Method Based on Deep Convolutional Neural Networks for Fault Diagnosis of Planetary Gearbox

Science.gov (United States)

Jing, Luyang; Wang, Taiyong; Zhao, Ming; Wang, Peng

2017-01-01

A fault diagnosis approach based on multi-sensor data fusion is a promising tool to deal with complicated damage detection problems of mechanical systems. Nevertheless, this approach suffers from two challenges, which are (1) the feature extraction from various types of sensory data and (2) the selection of a suitable fusion level. It is usually difficult to choose an optimal feature or fusion level for a specific fault diagnosis task, and extensive domain expertise and human labor are also highly required during these selections. To address these two challenges, we propose an adaptive multi-sensor data fusion method based on deep convolutional neural networks (DCNN) for fault diagnosis. The proposed method can learn features from raw data and optimize a combination of different fusion levels adaptively to satisfy the requirements of any fault diagnosis task. The proposed method is tested through a planetary gearbox test rig. Handcraft features, manual-selected fusion levels, single sensory data, and two traditional intelligent models, back-propagation neural networks (BPNN) and a support vector machine (SVM), are used as comparisons in the experiment. The results demonstrate that the proposed method is able to detect the conditions of the planetary gearbox effectively with the best diagnosis accuracy among all comparative methods in the experiment. PMID:28230767

Contrasting Physiological and Proteomic Adaptations to Iron and/or Copper Limitation in Two Strains of the Same Open Ocean Diatom Thalassiosira oceanica

Science.gov (United States)

Schuback, N.; Hippmann, A.; Maldonado, M. T.; Allen, A. E.; McCrow, J.; Foster, L. J.; Green, B. R.; Alami, M.

2016-02-01

Iron plays a significant role in controlling marine primary productivity. Despite that extremely low dissolved iron (Fe) concentrations are found in Fe-limited regions, some phytoplankton are able to survive and thrive. Two strains of the model oceanic diatom Thalassiosira oceanica, TO 1003 and TO 1005, have both been used in previous studies to characterize adaptations to iron limitation. These studies have shown that T. oceanica has lowered its Fe requirements and increased its Fe acquisition efficiency compared to coastal counterparts. Both strategies may impose a higher cellular copper (Cu) demand. However, the underlying biochemical adaptations in these oceanic diatoms remain unknown. Recently, the genome, as well as the first proteomic and transcriptomic analyses of T. oceanica 1005 grown under different Fe levels, were published. To further our understanding of the interplay between Fe- and Cu- physiology in open ocean diatoms, we examined an array of physiological responses to varying degrees of Fe-, Cu- and Fe/Cu co-limitation in both strains. We also determined the differential expression of proteins using stable isotope labeling and LC-MS/MS proteomic analysis. The two strains, TO 1003 and TO 1005, need markedly different metal concentrations in the media. TO1003 requires 30% less Cu to sustain its optimal growth and less than 1/10th of the minimum Cu that is needed by TO 1005 to survive. In contrast, TO 1005 is able to grow with less Fe available in the media. The physiological and proteomic responses of these two strains when acclimated to low Fe and/or Cu concentrations will be presented. The evolutionary implications will be discussed.

40 CFR 230.6 - Adaptability.

Science.gov (United States)

2010-07-01

... 40 Protection of Environment 24 2010-07-01 2010-07-01 false Adaptability. 230.6 Section 230.6 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) OCEAN DUMPING SECTION 404(b)(1) GUIDELINES FOR SPECIFICATION OF DISPOSAL SITES FOR DREDGED OR FILL MATERIAL General § 230.6 Adaptability. (a...

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

Science.gov (United States)

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.

Seismic Wave Propagation in Icy Ocean Worlds

Science.gov (United States)

Stähler, Simon C.; Panning, Mark P.; Vance, Steven D.; Lorenz, Ralph D.; van Driel, Martin; Nissen-Meyer, Tarje; Kedar, Sharon

2018-01-01

Seismology was developed on Earth and shaped our model of the Earth's interior over the twentieth century. With the exception of the Philae lander, all in situ extraterrestrial seismological effort to date was limited to other terrestrial planets. All have in common a rigid crust above a solid mantle. The coming years may see the installation of seismometers on Europa, Titan, and Enceladus, so it is necessary to adapt seismological concepts to the setting of worlds with global oceans covered in ice. Here we use waveform analyses to identify and classify wave types, developing a lexicon for icy ocean world seismology intended to be useful to both seismologists and planetary scientists. We use results from spectral-element simulations of broadband seismic wavefields to adapt seismological concepts to icy ocean worlds. We present a concise naming scheme for seismic waves and an overview of the features of the seismic wavefield on Europa, Titan, Ganymede, and Enceladus. In close connection with geophysical interior models, we analyze simulated seismic measurements of Europa and Titan that might be used to constrain geochemical parameters governing the habitability of a sub-ice ocean.

An Energy Efficient Adaptive Sampling Algorithm in a Sensor Network for Automated Water Quality Monitoring.

Science.gov (United States)

Shu, Tongxin; Xia, Min; Chen, Jiahong; Silva, Clarence de

2017-11-05

Power management is crucial in the monitoring of a remote environment, especially when long-term monitoring is needed. Renewable energy sources such as solar and wind may be harvested to sustain a monitoring system. However, without proper power management, equipment within the monitoring system may become nonfunctional and, as a consequence, the data or events captured during the monitoring process will become inaccurate as well. This paper develops and applies a novel adaptive sampling algorithm for power management in the automated monitoring of the quality of water in an extensive and remote aquatic environment. Based on the data collected on line using sensor nodes, a data-driven adaptive sampling algorithm (DDASA) is developed for improving the power efficiency while ensuring the accuracy of sampled data. The developed algorithm is evaluated using two distinct key parameters, which are dissolved oxygen (DO) and turbidity. It is found that by dynamically changing the sampling frequency, the battery lifetime can be effectively prolonged while maintaining a required level of sampling accuracy. According to the simulation results, compared to a fixed sampling rate, approximately 30.66% of the battery energy can be saved for three months of continuous water quality monitoring. Using the same dataset to compare with a traditional adaptive sampling algorithm (ASA), while achieving around the same Normalized Mean Error (NME), DDASA is superior in saving 5.31% more battery energy.

A Real-Time Capable Software-Defined Receiver Using GPU for Adaptive Anti-Jam GPS Sensors

Science.gov (United States)

Seo, Jiwon; Chen, Yu-Hsuan; De Lorenzo, David S.; Lo, Sherman; Enge, Per; Akos, Dennis; Lee, Jiyun

2011-01-01

Due to their weak received signal power, Global Positioning System (GPS) signals are vulnerable to radio frequency interference. Adaptive beam and null steering of the gain pattern of a GPS antenna array can significantly increase the resistance of GPS sensors to signal interference and jamming. Since adaptive array processing requires intensive computational power, beamsteering GPS receivers were usually implemented using hardware such as field-programmable gate arrays (FPGAs). However, a software implementation using general-purpose processors is much more desirable because of its flexibility and cost effectiveness. This paper presents a GPS software-defined radio (SDR) with adaptive beamsteering capability for anti-jam applications. The GPS SDR design is based on an optimized desktop parallel processing architecture using a quad-core Central Processing Unit (CPU) coupled with a new generation Graphics Processing Unit (GPU) having massively parallel processors. This GPS SDR demonstrates sufficient computational capability to support a four-element antenna array and future GPS L5 signal processing in real time. After providing the details of our design and optimization schemes for future GPU-based GPS SDR developments, the jamming resistance of our GPS SDR under synthetic wideband jamming is presented. Since the GPS SDR uses commercial-off-the-shelf hardware and processors, it can be easily adopted in civil GPS applications requiring anti-jam capabilities. PMID:22164116

An Energy Efficient Adaptive Sampling Algorithm in a Sensor Network for Automated Water Quality Monitoring

Directory of Open Access Journals (Sweden)

Tongxin Shu

2017-11-01

Full Text Available Power management is crucial in the monitoring of a remote environment, especially when long-term monitoring is needed. Renewable energy sources such as solar and wind may be harvested to sustain a monitoring system. However, without proper power management, equipment within the monitoring system may become nonfunctional and, as a consequence, the data or events captured during the monitoring process will become inaccurate as well. This paper develops and applies a novel adaptive sampling algorithm for power management in the automated monitoring of the quality of water in an extensive and remote aquatic environment. Based on the data collected on line using sensor nodes, a data-driven adaptive sampling algorithm (DDASA is developed for improving the power efficiency while ensuring the accuracy of sampled data. The developed algorithm is evaluated using two distinct key parameters, which are dissolved oxygen (DO and turbidity. It is found that by dynamically changing the sampling frequency, the battery lifetime can be effectively prolonged while maintaining a required level of sampling accuracy. According to the simulation results, compared to a fixed sampling rate, approximately 30.66% of the battery energy can be saved for three months of continuous water quality monitoring. Using the same dataset to compare with a traditional adaptive sampling algorithm (ASA, while achieving around the same Normalized Mean Error (NME, DDASA is superior in saving 5.31% more battery energy.

A Real-Time Capable Software-Defined Receiver Using GPU for Adaptive Anti-Jam GPS Sensors

Directory of Open Access Journals (Sweden)

Dennis Akos

2011-09-01

Full Text Available Due to their weak received signal power, Global Positioning System (GPS signals are vulnerable to radio frequency interference. Adaptive beam and null steering of the gain pattern of a GPS antenna array can significantly increase the resistance of GPS sensors to signal interference and jamming. Since adaptive array processing requires intensive computational power, beamsteering GPS receivers were usually implemented using hardware such as field-programmable gate arrays (FPGAs. However, a software implementation using general-purpose processors is much more desirable because of its flexibility and cost effectiveness. This paper presents a GPS software-defined radio (SDR with adaptive beamsteering capability for anti-jam applications. The GPS SDR design is based on an optimized desktop parallel processing architecture using a quad-core Central Processing Unit (CPU coupled with a new generation Graphics Processing Unit (GPU having massively parallel processors. This GPS SDR demonstrates sufficient computational capability to support a four-element antenna array and future GPS L5 signal processing in real time. After providing the details of our design and optimization schemes for future GPU-based GPS SDR developments, the jamming resistance of our GPS SDR under synthetic wideband jamming is presented. Since the GPS SDR uses commercial-off-the-shelf hardware and processors, it can be easily adopted in civil GPS applications requiring anti-jam capabilities.

Characterization of Prochlorococcus clades from iron-depleted oceanic regions.

Science.gov (United States)

Rusch, Douglas B; Martiny, Adam C; Dupont, Christopher L; Halpern, Aaron L; Venter, J Craig

2010-09-14

Prochlorococcus describes a diverse and abundant genus of marine photosynthetic microbes. It is primarily found in oligotrophic waters across the globe and plays a crucial role in energy and nutrient cycling in the ocean ecosystem. The abundance, global distribution, and availability of isolates make Prochlorococcus a model system for understanding marine microbial diversity and biogeochemical cycling. Analysis of 73 metagenomic samples from the Global Ocean Sampling expedition acquired in the Atlantic, Pacific, and Indian Oceans revealed the presence of two uncharacterized Prochlorococcus clades. A phylogenetic analysis using six different genetic markers places the clades close to known lineages adapted to high-light environments. The two uncharacterized clades consistently cooccur and dominate the surface waters of high-temperature, macronutrient-replete, and low-iron regions of the Eastern Equatorial Pacific upwelling and the tropical Indian Ocean. They are genetically distinct from each other and other high-light Prochlorococcus isolates and likely define a previously unrecognized ecotype. Our detailed genomic analysis indicates that these clades comprise organisms that are adapted to iron-depleted environments by reducing their iron quota through the loss of several iron-containing proteins that likely function as electron sinks in the photosynthetic pathway in other Prochlorococcus clades from high-light environments. The presence and inferred physiology of these clades may explain why Prochlorococcus populations from iron-depleted regions do not respond to iron fertilization experiments and further expand our understanding of how phytoplankton adapt to variations in nutrient availability in the ocean.

In-Orbit Vicarious Calibration for Ocean Color and Aerosol Products

National Research Council Canada - National Science Library

Wang, Menghua

2005-01-01

It is well known that, to accurately retrieve the spectrum of the water-leaving radiance and derive the ocean color products from satellite sensors, a vicarious calibration procedure, which performs...

RSS SSM/I OCEAN PRODUCT GRIDS WEEKLY AVERAGE FROM DMSP F15 NETCDF V7

Data.gov (United States)

National Aeronautics and Space Administration — The RSS SSM/I Ocean Product Grids Weekly Average from DMSP F15 netCDF dataset is part of the collection of Special Sensor Microwave/Imager (SSM/I) and Special Sensor...

RSS SSMIS OCEAN PRODUCT GRIDS 3-DAY AVERAGE FROM DMSP F16 NETCDF V7

Data.gov (United States)

National Aeronautics and Space Administration — The RSS SSMIS Ocean Product Grids 3-Day Average from DMSP F16 netCDF dataset is part of the collection of Special Sensor Microwave/Imager (SSM/I) and Special Sensor...

RSS SSM/I OCEAN PRODUCT GRIDS WEEKLY AVERAGE FROM DMSP F10 NETCDF V7

Data.gov (United States)

National Aeronautics and Space Administration — The RSS SSM/I Ocean Product Grids Weekly Average from DMSP F10 netCDF dataset is part of the collection of Special Sensor Microwave/Imager (SSM/I) and Special Sensor...

RSS SSM/I OCEAN PRODUCT GRIDS WEEKLY AVERAGE FROM DMSP F8 NETCDF V7

Data.gov (United States)

National Aeronautics and Space Administration — The RSS SSM/I Ocean Products Grid Weekly Average from DMSP F8 netCDF dataset is part of the collection of Special Sensor Microwave/Imager (SSM/I) and Special Sensor...

7th China Conference on Wireless Sensor Networks

CERN Document Server

Cui, Li; Guo, Zhongwen

2014-01-01

Advanced Technologies in Ad Hoc and Sensor Networks collects selected papers from the 7th China Conference on Wireless Sensor Networks (CWSN2013) held in Qingdao, October 17-19, 2013. The book features state-of-the-art studies on Sensor Networks in China with the theme of “Advances in wireless sensor networks of China”. The selected works can help promote development of sensor network technology towards interconnectivity, resource sharing, flexibility and high efficiency. Researchers and engineers in the field of sensor networks can benefit from the book. Xue Wang is a professor at Tsinghua University; Li Cui is a professor at Institute of Computing Technology, Chinese Academy of Sciences; Zhongwen Guo is a professor at Ocean University of China.

Ocean acidification 2.0: Managing our Changing Coastal Ocean Chemistry

OpenAIRE

Strong, AL; Kroeker, KJ; Teneva, LT; Mease, LA; Kelly, RP

2014-01-01

Ocean acidification (OA) is rapidly emerging as a significant problem for organisms, ecosystems, and human societies. Globally, addressing OA and its impacts requires international agreements to reduce rising atmospheric carbon dioxide concentrations. However, the complex suite of drivers of changing carbonate chemistry in coastal environments also requires regional policy analysis, mitigation, and adaptation responses. In order to fundamentally address the threat of OA, environmental manager...

Maritime adaptive optics beam control

OpenAIRE

Corley, Melissa S.

2010-01-01

The Navy is interested in developing systems for horizontal, near ocean surface, high-energy laser propagation through the atmosphere. Laser propagation in the maritime environment requires adaptive optics control of aberrations caused by atmospheric distortion. In this research, a multichannel transverse adaptive filter is formulated in Matlab's Simulink environment and compared to a complex lattice filter that has previously been implemented in large system simulations. The adaptive fil...

Routes for GMR-Sensor Design in Non-Destructive Testing

Directory of Open Access Journals (Sweden)

Andreas Schütze

2012-09-01

Full Text Available GMR sensors are widely used in many industrial segments such as information technology, automotive, automation and production, and safety applications. Each area requires an adaption of the sensor arrangement in terms of size adaption and alignment with respect to the field source involved. This paper deals with an analysis of geometric sensor parameters and the arrangement of GMR sensors providing a design roadmap for non-destructive testing (NDT applications. For this purpose we use an analytical model simulating the magnetic flux leakage (MFL distribution of surface breaking defects and investigate the flux leakage signal as a function of various sensor parameters. Our calculations show both the influence of sensor length and height and that when detecting the magnetic flux leakage of µm sized defects a gradiometer base line of 250 µm leads to a signal strength loss of less than 10% in comparison with a magnetometer response. To validate the simulation results we finally performed measurements with a GMR magnetometer sensor on a test plate with artificial µm-range cracks. The differences between simulation and measurement are below 6%. We report on the routes for a GMR gradiometer design as a basis for the fabrication of NDT-adapted sensor arrays. The results are also helpful for the use of GMR in other application when it comes to measure positions, lengths, angles or electrical currents.

Ocean acidification: The little-known impact of CO2 emissions

International Nuclear Information System (INIS)

Madsen, Michael Amdi

2015-01-01

Ocean acidification, like global warming, is a serious consequence of rising carbon dioxide (CO 2 ) emissions and a growing threat to coastal communities. Scientists and economists alike are calling for ocean acidification mitigation and adaptation plans to be included in any future international climate change agreement, arguing that doing so would make any such agreement stronger and facilitate its implementation. The IAEA uses nuclear techniques to measure ocean acidification and has been providing objective information to scientists, economists, and policymakers to make informed decisions. “Recognizing that billions of people are dependent on a healthy ocean for their wellbeing and economic development is the first step,” said Alexandre Magnan of the Institute for Sustainable Development and International Relations in Paris at an IAEA workshop this year. Acknowledging in the legal text of a climate deal the threats facing the oceans could open the door for coastal communities affected by ocean acidification to benefit from financing available under a climate change agreement, he said. This would enable them to adapt to changing social and economic circumstances, improve understanding of the ecological and biophysical changes expected, and pressure further concrete actions by governments, he added.

Ocean acidification: The little-known impact of CO_2 emissions

International Nuclear Information System (INIS)

Madsen, Michael Amdi

2015-01-01

Ocean acidification, like global warming, is a serious consequence of rising carbon dioxide (CO_2) emissions and a growing threat to coastal communities. Scientists and economists alike are calling for ocean acidification mitigation and adaptation plans to be included in any future international climate change agreement, arguing that doing so would make any such agreement stronger and facilitate its implementation. The IAEA uses nuclear techniques to measure ocean acidification and has been providing objective information to scientists, economists, and policymakers to make informed decisions. “Recognizing that billions of people are dependent on a healthy ocean for their wellbeing and economic development is the first step,” said Alexandre Magnan of the Institute for Sustainable Development and International Relations in Paris at an IAEA workshop this year. Acknowledging in the legal text of a climate deal the threats facing the oceans could open the door for coastal communities affected by ocean acidification to benefit from financing available under a climate change agreement, he said. This would enable them to adapt to changing social and economic circumstances, improve understanding of the ecological and biophysical changes expected, and pressure further concrete actions by governments, he added.

Aquantis C-Plane Ocean Current Turbine Project

Energy Technology Data Exchange (ETDEWEB)

Fleming, Alex [Dehlsen Associates, LLC, Santa Barbara, CA (United States)

2015-09-16

The Aquantis 2.5 MW Ocean Current Generation Device technology developed by Dehlsen Associates, LLC (DA) is a derivation of wind power generating technology (a means of harnessing a slow moving fluid) adapted to the ocean environment. The Aquantis Project provides an opportunity for accelerated technological development and early commercialization, since it involves the joining of two mature disciplines: ocean engineering and wind turbine design. The Aquantis Current Plane (C-Plane) technology is an ocean current turbine designed to extract kinetic energy from a current flow. The technology is capable of achieving competitively priced, continuous, base-load, and reliable power generation from a source of renewable energy not before possible in this scale or form.

Climate Modeling: Ocean Cavities below Ice Shelves

Energy Technology Data Exchange (ETDEWEB)

Petersen, Mark Roger [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Computer, Computational, and Statistical Sciences Division

2016-09-12

The Accelerated Climate Model for Energy (ACME), a new initiative by the U.S. Department of Energy, includes unstructured-mesh ocean, land-ice, and sea-ice components using the Model for Prediction Across Scales (MPAS) framework. The ability to run coupled high-resolution global simulations efficiently on large, high-performance computers is a priority for ACME. Sub-ice shelf ocean cavities are a significant new capability in ACME, and will be used to better understand how changing ocean temperature and currents influence glacial melting and retreat. These simulations take advantage of the horizontal variable-resolution mesh and adaptive vertical coordinate in MPAS-Ocean, in order to place high resolution below ice shelves and near grounding lines.

Relational adaptivity - enacting human-centric systems design

DEFF Research Database (Denmark)

Petersen, Kjell Yngve

2016-01-01

Human centered design approaches places the experiencing human at the center of concern, situated in relation to the dynamics of the environmental condition and the variables of the system of control and sensing. Taking the approach of enacted design methods to enforce the experience...... of the inhabitant as core in human-centered design solutions, the intelligence of the connected sensors is suggested to be developed as an actual learning and self-adjusting adaptive environment, where the adaptive system is part of a negotiation with users on the qualities of the environment. We will present...... a fully functional sketching environment for adaptive sensor-control systems, which enable integration of the complex situation of everyday activities and human well-being. The proposed sketching environment allows for the development of sensor systems related to lighting conditions and human occupancy...

Wearable sensors: modalities, challenges, and prospects.

Science.gov (United States)

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.

AN OPTIMALIZATION OF NATURAL LIGHTING BY APPLYING AUTOMATIC LIGHTING USING MOTION SENSOR AND LUX SENSOR FOR HISTORICAL OLD BUILDINGS

Directory of Open Access Journals (Sweden)

Saeful Bahri

2016-07-01

Full Text Available ABSTRACT One of the problems that occurs within city centres, particularly within capital cities, is the existence of many historical old buildings. Historical old buildings within city centres, that have abandoned for years because of their condition, suffer from a lack of utilities, infrastructure and facilities [2][3]. These conditions occur because of low levels of maintenance arising as a consequence of a lack of finance of the owner of a building, be they government or private sector. To solve the problem of abandoned historical old buildings, the concept of adaptive reuse can be adopted and applied. This concept of adaptive reuse may continously cover the cost of building maintenance. The adaptive reuse concept usually covers the interior of a building and its utilities, though the need for utilities depends on the function of a building [4]. By adopting a concept of adaptive reuse, new building functions will be designed as the needs and demand of the market dictate, and which is appropriate for feasibility study. One utility element that has to be designed for historical old buildings is the provision of lighting within a building. To minimize the cost of building maintenance, one of the solutions is to optimize natural lighting and to minimize the use of artificial lighting such as lamps. This paper will discuss the extent to which artificial lighting can be minimized by using automatic lighting; the automatic lighting types discussed in this paper are lighting controlled by motion sensor and lux sensor. Keywords: Natural lighting, automatic lighting, motion sensor, lux sensor, historical old buildings ABSTRAK Salah satu permasalahan yang muncul dalam sebuah kota metropolitan, khususnya sebuah ibukota adalah keberadaan dari banyaknya bangunan-bangunan tua bersejarah. Bangunan-bangunan tua bersejarah dalam sebuah kota besar terutama yang diabaikan selama bertahun-tahun biasanya disebabkan karena kondisinya yang menua, minimnya utilitas

Ocean Response to Tropical Storms as Observed by a Moored Ocean Observing System in the Deep Gulf of Mexico

Science.gov (United States)

Oropeza, F.; Jaramillo, S.; Fan, S.

2013-05-01

As part of the support activities for a deepwater development in the Gulf of Mexico, a moored ocean observing system (OOS) was deployed in a water depth of approximately 2500m, 300km south of the Louisiana Coast. From June 2007 to May 2009, the system comprised seven single point Aanderaa Recording Current Meters (RCM), deployed at 450m, 700m, 1,100m, 1,500m, 2,000m, 2,400m and 2,490m below surface, and an RDI 75kHz Longranger Acoustic Doppler Current Profiler (ADCP), deployed between 249 and 373m below surface in upward-looking mode. Since May 2009, the OOS was upgraded to a Wavescan Buoy based moored system including meteorological sensors for: atmospheric pressure, air temperature, wind speed and direction; directional waves sensor; a Doppler Current Sensor (DCS) at 1.5 m depth for surface currents; and two downward-looking ADCP's covering the upper 1,000m of the water column. This OOS has been operating without interruptions from 2007 to the present and has registered data associated with nine tropical storms, including the direct passage of Hurricane Ike, in September of 2008, and loop current events with speeds of up to 4 knots. It has provided one of the most comprehensive set of velocity observations in the Gulf of Mexico, especially, the near surface currents, during pre-storm conditions, response, and ocean relaxation following hurricanes/tropical storms. Based on these observations the upper ocean responses to the energy input from tropical storms are characterized in terms of the associated mixing processes and momentum balances.

Stratification of archaeal membrane lipids in the ocean and implications for adaptation and chemotaxonomy of planktonic archaea.

Science.gov (United States)

Zhu, Chun; Wakeham, Stuart G; Elling, Felix J; Basse, Andreas; Mollenhauer, Gesine; Versteegh, Gerard J M; Könneke, Martin; Hinrichs, Kai-Uwe

2016-12-01

Membrane lipids of marine planktonic archaea have provided unique insights into archaeal ecology and paleoceanography. However, past studies of archaeal lipids in suspended particulate matter (SPM) and sediments mainly focused on a small class of fully saturated glycerol dibiphytanyl glycerol tetraether (GDGT) homologues identified decades ago. The apparent low structural diversity of GDGTs is in strong contrast to the high diversity of metabolism and taxonomy among planktonic archaea. Furthermore, adaptation of archaeal lipids in the deep ocean remains poorly constrained. We report the archaeal lipidome in SPM from diverse oceanic regimes. We extend the known inventory of planktonic archaeal lipids to include numerous unsaturated archaeal ether lipids (uns-AELs). We further reveal (i) different thermal regulations and polar headgroup compositions of membrane lipids between the epipelagic (≤ 100 m) and deep (>100 m) populations of archaea, (ii) stratification of unsaturated GDGTs with varying redox conditions, and (iii) enrichment of tetra-unsaturated archaeol and fully saturated GDGTs in epipelagic and deep oxygenated waters, respectively. Such stratified lipid patterns are consistent with the typical distribution of archaeal phylotypes in marine environments. We, thus, provide an ecological context for GDGT-based paleoclimatology and bring about the potential use of uns-AELs as biomarkers for planktonic Euryarchaeota. © 2016 Society for Applied Microbiology and John Wiley & Sons Ltd.

Bio-Optical sensors on Argo Floats. Reports of the international ocean-colour coordinating group

CSIR Research Space (South Africa)

Bernard, S

2011-01-01

Full Text Available The International Ocean-Colour Coordinating Group (IOCCG) is an international group of experts in the field of satellite ocean colour, acting as a liaison and communication channel between users, managers and agencies in the ocean-colour arena...

Transforming Ocean Observations of the Carbon Budget, Acidification, Hypoxia, Nutrients, and Biological Productivity: a Global Array of Biogeochemical Argo Floats

Science.gov (United States)

Talley, L. D.; Johnson, K. S.; Claustre, H.; Boss, E.; Emerson, S. R.; Westberry, T. K.; Sarmiento, J. L.; Mazloff, M. R.; Riser, S.; Russell, J. L.

2017-12-01

Our ability to detect changes in biogeochemical (BGC) processes in the ocean that may be driven by increasing atmospheric CO2, as well as by natural climate variability, is greatly hindered by undersampling in vast areas of the open ocean. Argo is a major international program that measures ocean heat content and salinity with about 4000 floats distributed throughout the ocean, profiling to 2000 m every 10 days. Extending this approach to a global BGC-Argo float array, using recent, proven sensor technology, and in close synergy with satellite systems, will drive a transformative shift in observing and predicting the effects of climate change on ocean metabolism, carbon uptake, acidification, deoxygenation, and living marine resource management. BGC-Argo will add sensors for pH, oxygen, nitrate, chlorophyll, suspended particles, and downwelling irradiance, with sufficient accuracy for climate studies. Observing System Simulation Experiments (OSSEs) using BGC models indicate that 1000 BGC floats would provide sufficient coverage, hence equipping 1/4 of the Argo array. BGC-Argo (http://biogeochemical-argo.org) will enhance current sustained observational programs such as Argo, GO-SHIP, and long-term ocean time series. BGC-Argo will benefit from deployments on GO-SHIP vessels, which provide sensor verification. Empirically derived algorithms that relate the observed BGC float parameters to the carbon system parameters will provide global information on seasonal ocean-atmosphere carbon exchange. BGC Argo measurements could be paired with other emerging technology, such as pCO2 measurements from ships of opportunity and wave gliders, to extend and validate exchange estimates. BGC-Argo prototype programs already show the potential of a global observing system that can measure seasonal to decadal variability. Various countries have developed regional BGC arrays: Southern Ocean (SOCCOM), North Atlantic Subpolar Gyre (remOcean), Mediterranean (NAOS), the Kuroshio (INBOX

Intelligent Sensors for Integrated Systems Health Management (ISHM)

Science.gov (United States)

Schmalzel, John L.

2008-01-01

IEEE 1451 Smart Sensors contribute to a number of ISHM goals including cost reduction achieved through: a) Improved configuration management (TEDS); and b) Plug-and-play re-configuration. Intelligent Sensors are adaptation of Smart Sensors to include ISHM algorithms; this offers further benefits: a) Sensor validation. b) Confidence assessment of measurement, and c) Distributed ISHM processing. Space-qualified intelligent sensors are possible a) Size, mass, power constraints. b) Bus structure/protocol.

Ocean Economy and Fault Diagnosis of Electric Submersible Pump applied in Floating platform

Directory of Open Access Journals (Sweden)

Panlong Zhang

2017-04-01

Full Text Available Ocean economy plays a crucial role in the strengthening maritime safety industry and in the welfare of human beings. Electric Submersible Pumps (ESP have been widely used in floating platforms on the sea to provide oil for machines. However, the ESP fault may lead to ocean environment pollution, on the other hand, a timely fault diagnosis of ESP can improve the ocean economy. In order to meet the strict regulations of the ocean economy and environmental protection, the fault diagnosis of ESP system has become more and more popular in many countries. The vibration mechanical models of typical faults have been able to successfully diagnose the faults of ESP. And different types of sensors are used to monitor the vibration signal for the signal analysis and fault diagnosis in the ESP system. Meanwhile, physical sensors would increase the fault diagnosis challenge. Nowadays, the method of neural network for the fault diagnosis of ESP has been applied widely, which can diagnose the fault of an electric pump accurately based on the large database. To reduce the number of sensors and to avoid the large database, in this paper, algorithms are designed based on feature extraction to diagnose the fault of the ESP system. Simulation results show that the algorithms can achieve the prospective objectives superbly.

Multi-Sensor Improved Sea Surface Temperature (MISST) for GODAE

National Research Council Canada - National Science Library

Gentemann, Chelle L; Wick, Gary A; Cummings, James; Bayler, Eric

2004-01-01

...) sensors and to then demonstrate the impact of these improved sea surface temperatures (SSTs) on operational ocean models, numerical weather prediction, and tropical cyclone intensity forecasting...

An application of neural network for Structural Health Monitoring of an adaptive wing with an array of FBG sensors

International Nuclear Information System (INIS)

Mieloszyk, Magdalena; Skarbek, Lukasz; Ostachowicz, Wieslaw; Krawczuk, Marek

2011-01-01

This paper presents an application of neural networks to determinate the level of activation of shape memory alloy actuators of an adaptive wing. In this concept the shape of the wing can be controlled and altered thanks to the wing design and the use of integrated shape memory alloy actuators. The wing is assumed as assembled from a number of wing sections that relative positions can be controlled independently by thermal activation of shape memory actuators. The investigated wing is employed with an array of Fibre Bragg Grating sensors. The Fibre Bragg Grating sensors with combination of a neural network have been used to Structural Health Monitoring of the wing condition. The FBG sensors are a great tool to control the condition of composite structures due to their immunity to electromagnetic fields as well as their small size and weight. They can be mounted onto the surface or embedded into the wing composite material without any significant influence on the wing strength. The paper concentrates on analysis of the determination of the twisting moment produced by an activated shape memory alloy actuator. This has been analysed both numerically using the finite element method by a commercial code ABAQUS (registered) and experimentally using Fibre Bragg Grating sensor measurements. The results of the analysis have been then used by a neural network to determine twisting moments produced by each shape memory alloy actuator.

Sensors and sensor integration; Proceedings of the Meeting, Orlando, FL, Apr. 4, 1991

Science.gov (United States)

Dean, Peter D.

Consideration is given to adaptive control of propellant slosh for launch vehicles, a lidar for expendable launch vehicles, a high-resolution airborne multisensor system, an optical velocity sensor for air data applications, and use of absorption spectroscopy for refined petroleum product discrimination. Attention is also given to edge effects in silicon photodiode arrays, sensing and environment perception for a mobile vehicle, distributed-effect optical fiber sensors for trusses and plates, and instrumentation concepts for multiplexed Bragg grating sensors. (For individual items see A93-21962 to A93-21972)

Observing Crustal Magnetic Anomalies in Remote Ocean Regions: Filling in the Gaps

Science.gov (United States)

Claus, B.; Kinsey, J. C.; Tominaga, M.; Tivey, M.

2016-12-01

The use of long duration ocean observing platforms is necessary for filling in broad gaps in the observational record of magnetic anomaly measurements in the ocean basins -- observations that are necessary for understanding a variety of geophysical processes. Such an instrument would need to gather 1000s of kilometers of magnetic data untended, requiring in-situ calibration methods and minimization of energy usage. In this work an autonomous underwater glider (AUG) has been equipped with a low power flux-gate magnetic sensor. Sensor integration was tested locally in shallow water followed by deep water trials to verify the calibration procedure in June of 2016. During this cruise a 160 kilometer magnetic tow was also collected across the East Coast Shelf Anomaly to the South-East of Cape Cod. Following these tests, the AUG was deployed such that it followed the trajectory of the towed magnetic survey to provide a baseline comparison against a known methodology. For these deployments an in-situ calibration procedure was used whereby the vehicle was commanded to perform descending and ascending spirals with its actuators at various discrete locations. When combined with a temperature model for the sensor the calibrated measurements were found to be in agreement with the towed data to within several 10's of nT. These comparative measurements demonstrate the utility of using directed long duration autonomous ocean observing platforms to gather medium wavelength crustal magnetic anomaly features. This ability is especially desirable for collecting measurements in remote ocean basins, such as the Southern Ocean, where presently only a few ship tracks exist and are likely to never be sampled by conventional research vessels surveys.

Assessment of Adaptive Rate Response Provided by Accelerometer, Minute Ventilation and Dual Sensor Compared with Normal Sinus Rhythm During Exercise: A Self-controlled Study in Chronotropically Competent Subjects

Directory of Open Access Journals (Sweden)

Yuanyuan Cao

2015-01-01

Full Text Available Background: Dual sensor (DS for rate adaption was supposed to be more physiological. To evaluate its superiority, the DS (accelerometer [ACC] and minute ventilation [MV] and normal sinus rate response were compared in a self-controlled way during exercise treadmill testing. Methods: This self-controlled study was performed in atrioventricular block patients with normal sinus function who met the indications of pacemaker implant. Twenty-one patients came to the 1-month follow-up visit. Patients performed a treadmill test 1-month post implant while programmed in DDDR and sensor passive mode. For these patients, sensor response factors were left at default settings (ACC = 8, MV = 3 and sensor indicated rates (SIRs for DS, ACC and MV sensor were retrieved from the pacemaker memories, along with measured sinus node (SN rates from the beginning to 1-minute after the end of the treadmill test, and compared among study groups. Repeated measures analysis of variance and profile analysis, as well as variance analysis of randomized block designs, were used for statistical analysis. Results: Fifteen patients (15/21 were determined to be chronotropically competent. The mean differences between DS SIRs and intrinsic sinus rates during treadmill testing were smaller than those for ACC and MV sensor (mean difference between SIR and SN rate: ACC vs. SN, MV vs. SN, DS vs. SN, respectively, 34.84, 17.60, 16.15 beats/min, though no sensors could mimic sinus rates under the default settings for sensor response factor (ACC vs. SN P-adjusted < 0.001; MV vs. SN P-adjusted = 0.002; DS vs. SN P-adjusted = 0.005. However, both in the range of 1 st minute and first 3 minutes of exercise, only the DS SIR profile did not differ from sinus rates (P-adjusted = 0.09, 0.90, respectively. Conclusions: The DS under default settings provides more physiological rate response during physical activity than the corresponding single sensors (ACC or MV sensor. Further study is needed to

Simple Adaptive Single Differential Coherence Detection of BPSK Signals in IEEE 802.15.4 Wireless Sensor Networks.

Science.gov (United States)

Zhang, Gaoyuan; Wen, Hong; Wang, Longye; Xie, Ping; Song, Liang; Tang, Jie; Liao, Runfa

2017-12-26

In this paper, we propose an adaptive single differential coherent detection (SDCD) scheme for the binary phase shift keying (BPSK) signals in IEEE 802.15.4 Wireless Sensor Networks (WSNs). In particular, the residual carrier frequency offset effect (CFOE) for differential detection is adaptively estimated, with only linear operation, according to the changing channel conditions. It was found that the carrier frequency offset (CFO) and chip signal-to-noise ratio (SNR) conditions do not need a priori knowledge. This partly benefits from that the combination of the trigonometric approximation sin - 1 ( x ) ≈ x and a useful assumption, namely, the asymptotic or high chip SNR, is considered for simplification of the full estimation scheme. Simulation results demonstrate that the proposed algorithm can achieve an accurate estimation and the detection performance can completely meet the requirement of the IEEE 802.15.4 standard, although with a little loss of reliability and robustness as compared with the conventional optimal single-symbol detector.

Late Cretaceous seasonal ocean variability from the Arctic.

Science.gov (United States)

Davies, Andrew; Kemp, Alan E S; Pike, Jennifer

2009-07-09

The modern Arctic Ocean is regarded as a barometer of global change and amplifier of global warming and therefore records of past Arctic change are critical for palaeoclimate reconstruction. Little is known of the state of the Arctic Ocean in the greenhouse period of the Late Cretaceous epoch (65-99 million years ago), yet records from such times may yield important clues to Arctic Ocean behaviour in near-future warmer climates. Here we present a seasonally resolved Cretaceous sedimentary record from the Alpha ridge of the Arctic Ocean. This palaeo-sediment trap provides new insight into the workings of the Cretaceous marine biological carbon pump. Seasonal primary production was dominated by diatom algae but was not related to upwelling as was previously hypothesized. Rather, production occurred within a stratified water column, involving specially adapted species in blooms resembling those of the modern North Pacific subtropical gyre, or those indicated for the Mediterranean sapropels. With increased CO(2) levels and warming currently driving increased stratification in the global ocean, this style of production that is adapted to stratification may become more widespread. Our evidence for seasonal diatom production and flux testify to an ice-free summer, but thin accumulations of terrigenous sediment within the diatom ooze are consistent with the presence of intermittent sea ice in the winter, supporting a wide body of evidence for low temperatures in the Late Cretaceous Arctic Ocean, rather than recent suggestions of a 15 degrees C mean annual temperature at this time.

RSS SSM/I OCEAN PRODUCT GRIDS 3-DAY AVERAGE FROM DMSP F14 NETCDF V7

Data.gov (United States)

National Aeronautics and Space Administration — The RSS SSM/I Ocean Product Grids 3-Day Average from DMSP F14 netCDF dataset is part of the collection of Special Sensor Microwave/Imager (SSM/I) and Special Sensor...

RSS SSM/I OCEAN PRODUCT GRIDS 3-DAY AVERAGE FROM DMSP F10 NETCDF V7

Data.gov (United States)

National Aeronautics and Space Administration — The RSS SSM/I Ocean Product Grids 3-Day Average from DMSP F10 netCDF dataset is part of the collection of Special Sensor Microwave/Imager (SSM/I) and Special Sensor...

An Energy-Efficient Sleep Strategy for Target Tracking Sensor Networks

Directory of Open Access Journals (Sweden)

Juan FENG

2014-02-01

Full Text Available Energy efficiency is very important for sensor networks since sensor nodes have limited energy supply from battery. So far, many researches have been focused on this issue, while less emphasis was placed on the optimal sleep time of each node. This paper proposed an adaptive energy conservation strategy for target tracking based on a grid network structure, where each node autonomously determines when and if to sleep. It allows sensor nodes far away from targets to sleep to save energy and guarantee the tracking accuracy. The proposed approach extend network lifetime by adopting an adaptive sleep scheduling scheme that combines the local power management (PM and the adaptive coordinate PM strategies to schedule the activities of sensor nodes. And each node can choose an optimal sleep time so as to make system adaptive and energy-efficient. We show the performance of our approach in terms of energy drop, comparing it to a naive approach, dynamic PM with fixed sleep time and the coordinate PM strategies. From the experimental results, it is readily seen that the efficiency of the proposed approach.

Revealing the timing of ocean stratification using remotely-sensed ocean fronts: links with marine predators

Science.gov (United States)

Miller, P. I.; Loveday, B. R.

2016-02-01

Stratification is of critical importance to the mixing and productivity of the ocean, though currently it can only be measured using in situ sampling, profiling buoys or underwater autonomous vehicles. Stratification is understood to affect the surface aggregation of pelagic fish and hence the foraging behaviour and distribution of their predators such as seabirds and cetaceans. Satellite Earth observation sensors cannot directly detect stratification, but can observe surface features related to the presence of stratification, for example shelf-sea fronts that separate tidally-mixed water from seasonally stratified water. This presentation describes a novel algorithm that accumulates evidence for stratification from a sequence of oceanic front maps, and in certain regions can reveal the timing of the seasonal onset and breakdown of stratification. Initial comparisons will be made with seabird locations acquired through GPS tagging. If successful, a remotely-sensed stratification timing index would augment the ocean front metrics already developed at PML, that have been applied in over 20 journal articles relating marine predators to ocean fronts. The figure below shows a preliminary remotely-sensed 'stratification' index, for 25-31 Jul. 2010, where red indicates water with stronger evidence for stratification.

Sensor Virtual Adaptable de Concentración de Etanol para Fermentadores Industriales

OpenAIRE

Martínez, Boris; Herrera, Francisco; Peralta, Luis

2009-01-01

Resumen: Los sistemas de control emplean sensores para observar el estado del proceso y tomar decisiones. En ocasiones, se necesita estimar las variables del proceso pues el sensor adecuado no existe, es prohibitivamente costoso o las mediciones son difíciles de realizar. Una solución consiste en inferir las variables no medidas a partir de otras variables mediante sensores virtuales o sensores por software (soft-sensors). En los procesos de fermentación alcohólica, la medición de la concentr...

An Adaptive Directed Query Dissemination Scheme for Wireless Sensor Networks

NARCIS (Netherlands)

Chatterjea, Supriyo; De Luigi, Simone; Havinga, Paul J.M.; Sun, M.T.

This paper describes a directed query dissemination scheme, DirQ that routes queries to the appropriate source nodes based on both constant and dynamicvalued attributes such as sensor types and sensor values. Unlike certain other query dissemination schemes, location information is not essential for

Analyzing the factors affecting network lifetime cluster-based wireless sensor network

International Nuclear Information System (INIS)

Malik, A.S.; Qureshi, A.

2010-01-01

Cluster-based wireless sensor networks enable the efficient utilization of the limited energy resources of the deployed sensor nodes and hence prolong the node as well as network lifetime. Low Energy Adaptive Clustering Hierarchy (Leach) is one of the most promising clustering protocol proposed for wireless sensor networks. This paper provides the energy utilization and lifetime analysis for cluster-based wireless sensor networks based upon LEACH protocol. Simulation results identify some important factors that induce unbalanced energy utilization between the sensor nodes and hence affect the network lifetime in these types of networks. These results highlight the need for a standardized, adaptive and distributed clustering technique that can increase the network lifetime by further balancing the energy utilization among sensor nodes. (author)

Salinibater Ruber as a Model for the Habitability of Europa's Ocean

Science.gov (United States)

Cardona, M. C.; Ramírez, S. I.

2017-11-01

The moon Europa has an ocean enriched with sulfate compounds. This work evaluates the adaptation strategies of Salinibacter ruber, a halophilic bacterium, when subjected to MgSO4 and NaSO4, two of the main salty components of Europás ocean.

Intraspecific variations in responses to ocean acidification in two branching coral species.

Science.gov (United States)

Sekizawa, Ayami; Uechi, Hikaru; Iguchi, Akira; Nakamura, Takashi; Kumagai, Naoki H; Suzuki, Atsushi; Sakai, Kazuhiko; Nojiri, Yukihiro

2017-09-15

Ocean acidification is widely recognised to have a negative impact on marine calcifying organisms by reducing calcifications, but controversy remains over whether such organisms could cope with ocean acidification within a range of phenotypic plasticity and/or adapt to future acidifying ocean. We performed a laboratory rearing experiment using clonal fragments of the common branching corals Montipora digitata and Porites cylindrica under control and acidified seawater (lower pH) conditions (approximately 400 and 900μatm pCO 2 , respectively) and evaluated the intraspecific variations in their responses to ocean acidification. Intra- and interspecific variations in calcification and photosynthetic efficiency were evident according to both pCO 2 conditions and colony, indicating that responses to acidification may be individually variable at the colony level. Our results suggest that some corals may cope with ocean acidification within their present genotypic composition by adaptation through phenotypic plasticity, while others may be placed under selective pressures resulting in population alteration. Copyright © 2017 Elsevier Ltd. All rights reserved.

An energy-efficient adaptive sampling scheme for wireless sensor networks

NARCIS (Netherlands)

Masoum, Alireza; Meratnia, Nirvana; Havinga, Paul J.M.

2013-01-01

Wireless sensor networks are new monitoring platforms. To cope with their resource constraints, in terms of energy and bandwidth, spatial and temporal correlation in sensor data can be exploited to find an optimal sampling strategy to reduce number of sampling nodes and/or sampling frequencies while

Adaptive Information Access on Multiple Applications Support Wireless Sensor Networks

DEFF Research Database (Denmark)

Tobgay, Sonam; Olsen, Rasmus Løvenstein; Prasad, Ramjee

2014-01-01

information is challenged by dynamic nature of information elements. These challenges are more prominent in case of wireless sensor network (WSN) applications, as the information that the sensor node collects are mostly dynamic in nature (say, temperature). Therefore, it is likely that there can be a mismatch...

Adaptive Information Access in Multiple Applications Support Wireless Sensor Network

DEFF Research Database (Denmark)

Tobgay, Sonam; Olsen, Rasmus Løvenstein; Prasad, Ramjee

2012-01-01

Nowadays, due to wide applicability of Wireless Sensor Network (WSN) added by the low cost sensor devices, its popularity among the researchers and industrialists are very much visible. A substantial amount of works can be seen in the literature on WSN which are mainly focused on application...

The Southern Ocean deep sea: first insights into biodiversity and biogeography

DEFF Research Database (Denmark)

Brandt, A.; Brix, S.; Brökeland, W.

2007-01-01

Shallow marine benthic communities around Antarctica show high levels of endemism, gigantism, slow growth, longevity and late maturity, as well as adaptive radiations that have generated considerable biodiversity in some taxa1. The deeper parts of the Southern Ocean exhibit some unique environmen......Shallow marine benthic communities around Antarctica show high levels of endemism, gigantism, slow growth, longevity and late maturity, as well as adaptive radiations that have generated considerable biodiversity in some taxa1. The deeper parts of the Southern Ocean exhibit some unique...

A sun-crown-sensor model and adapted C-correction logic for topographic correction of high resolution forest imagery

Science.gov (United States)

Fan, Yuanchao; Koukal, Tatjana; Weisberg, Peter J.

2014-10-01

Canopy shadowing mediated by topography is an important source of radiometric distortion on remote sensing images of rugged terrain. Topographic correction based on the sun-canopy-sensor (SCS) model significantly improved over those based on the sun-terrain-sensor (STS) model for surfaces with high forest canopy cover, because the SCS model considers and preserves the geotropic nature of trees. The SCS model accounts for sub-pixel canopy shadowing effects and normalizes the sunlit canopy area within a pixel. However, it does not account for mutual shadowing between neighboring pixels. Pixel-to-pixel shadowing is especially apparent for fine resolution satellite images in which individual tree crowns are resolved. This paper proposes a new topographic correction model: the sun-crown-sensor (SCnS) model based on high-resolution satellite imagery (IKONOS) and high-precision LiDAR digital elevation model. An improvement on the C-correction logic with a radiance partitioning method to address the effects of diffuse irradiance is also introduced (SCnS + C). In addition, we incorporate a weighting variable, based on pixel shadow fraction, on the direct and diffuse radiance portions to enhance the retrieval of at-sensor radiance and reflectance of highly shadowed tree pixels and form another variety of SCnS model (SCnS + W). Model evaluation with IKONOS test data showed that the new SCnS model outperformed the STS and SCS models in quantifying the correlation between terrain-regulated illumination factor and at-sensor radiance. Our adapted C-correction logic based on the sun-crown-sensor geometry and radiance partitioning better represented the general additive effects of diffuse radiation than C parameters derived from the STS or SCS models. The weighting factor Wt also significantly enhanced correction results by reducing within-class standard deviation and balancing the mean pixel radiance between sunlit and shaded slopes. We analyzed these improvements with model

Photonic Crystal Slab Sensors in Microfluidics

DEFF Research Database (Denmark)

Sørensen, Kristian Tølbøl

refractive index. The underlying phenomenon is called guidedmode resonance (GMR), which responds to changes in the refractive index of fluids only within the first few hundred nanometers from the sensor surface. PCS sensors can be fabricated entirely out of polymers, and read out using instrumentation...... to provide adaptive resolution. This algorithm can routinely make GMR simulations more than 100 times faster. The second manuscript, submitted to Optics Express, describes the practical application of polymeric PCS sensors. As with any refractive index sensor, the devices are highly sensitive to temperature...

Adaptive Robust Sliding Mode Vibration Control of a Flexible Beam Using Piezoceramic Sensor and Actuator: An Experimental Study

Directory of Open Access Journals (Sweden)

Ruo Lin Wang

2014-01-01

Full Text Available This paper presents an experimental study of an adaptive robust sliding mode control scheme based on the Lyapunov’s direct method for active vibration control of a flexible beam using PZT (lead zirconate titanate sensor and actuator. PZT, a type of piezoceramic material, has the advantages of high reliability, high bandwidth, and solid state actuation and is adopted here in forms of surface-bond patches for vibration control. Two adaptive robust sliding mode controllers for vibration suppression are designed: one uses a discontinuous bang-bang robust compensator and the other uses a smooth compensator with a hyperbolic tangent function. Both controllers guarantee asymptotic stability, as proved by the Lyapunov’s direct method. Experimental results verified the effectiveness and the robustness of both adaptive sliding mode controllers. However, from the experimental results, the bang-bang robust compensator causes small-magnitude chattering because of the discontinuous switching actions. With the smooth compensator, vibration is quickly suppressed and no chattering is induced. Furthermore, the robustness of the controllers is successfully demonstrated with ensured effectiveness in vibration control when masses are added to the flexible beam.

SIMBIOS Normalized Water-Leaving Radiance Calibration and Validation: Sensor Response, Atmospheric Corrections, Stray Light and Sun Glint. Chapter 14

Science.gov (United States)

Mueller, James L.

2001-01-01

This Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) contract supports acquisition of match up radiometric and bio-optical data for validation of Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) and other ocean color satellites, and evaluation of uncertainty budgets and protocols for in situ measurements of normalized water leaving radiances.

Wavefront sensorless adaptive optics ophthalmoscopy in the human eye

Science.gov (United States)

Hofer, Heidi; Sredar, Nripun; Queener, Hope; Li, Chaohong; Porter, Jason

2011-01-01

Wavefront sensor noise and fidelity place a fundamental limit on achievable image quality in current adaptive optics ophthalmoscopes. Additionally, the wavefront sensor ‘beacon’ can interfere with visual experiments. We demonstrate real-time (25 Hz), wavefront sensorless adaptive optics imaging in the living human eye with image quality rivaling that of wavefront sensor based control in the same system. A stochastic parallel gradient descent algorithm directly optimized the mean intensity in retinal image frames acquired with a confocal adaptive optics scanning laser ophthalmoscope (AOSLO). When imaging through natural, undilated pupils, both control methods resulted in comparable mean image intensities. However, when imaging through dilated pupils, image intensity was generally higher following wavefront sensor-based control. Despite the typically reduced intensity, image contrast was higher, on average, with sensorless control. Wavefront sensorless control is a viable option for imaging the living human eye and future refinements of this technique may result in even greater optical gains. PMID:21934779

Siderophore-based microbial adaptations to iron scarcity across the eastern Pacific Ocean

Science.gov (United States)

Boiteau, Rene M.; Mende, Daniel R.; Hawco, Nicholas J.; McIlvin, Matthew R.; Fitzsimmons, Jessica N.; Saito, Mak A.; Sedwick, Peter N.; DeLong, Edward F.; Repeta, Daniel J.

2016-12-01

Nearly all iron dissolved in the ocean is complexed by strong organic ligands of unknown composition. The effect of ligand composition on microbial iron acquisition is poorly understood, but amendment experiments using model ligands show they can facilitate or impede iron uptake depending on their identity. Here we show that siderophores, organic compounds synthesized by microbes to facilitate iron uptake, are a dynamic component of the marine ligand pool in the eastern tropical Pacific Ocean. Siderophore concentrations in iron-deficient waters averaged 9 pM, up to fivefold higher than in iron-rich coastal and nutrient-depleted oligotrophic waters, and were dominated by amphibactins, amphiphilic siderophores with cell membrane affinity. Phylogenetic analysis of amphibactin biosynthetic genes suggests that the ability to produce amphibactins has transferred horizontally across multiple Gammaproteobacteria, potentially driven by pressures to compete for iron. In coastal and oligotrophic regions of the eastern Pacific Ocean, amphibactins were replaced with lower concentrations (1-2 pM) of hydrophilic ferrioxamine siderophores. Our results suggest that organic ligand composition changes across the surface ocean in response to environmental pressures. Hydrophilic siderophores are predominantly found across regions of the ocean where iron is not expected to be the limiting nutrient for the microbial community at large. However, in regions with intense competition for iron, some microbes optimize iron acquisition by producing siderophores that minimize diffusive losses to the environment. These siderophores affect iron bioavailability and thus may be an important component of the marine iron cycle.

Factors challenging our ability to detect long-term trends in ocean chlorophyll

Directory of Open Access Journals (Sweden)

C. Beaulieu

2013-04-01

Full Text Available Global climate change is expected to affect the ocean's biological productivity. The most comprehensive information available about the global distribution of contemporary ocean primary productivity is derived from satellite data. Large spatial patchiness and interannual to multidecadal variability in chlorophyll a concentration challenges efforts to distinguish a global, secular trend given satellite records which are limited in duration and continuity. The longest ocean color satellite record comes from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS, which failed in December 2010. The Moderate Resolution Imaging Spectroradiometer (MODIS ocean color sensors are beyond their originally planned operational lifetime. Successful retrieval of a quality signal from the current Visible Infrared Imager Radiometer Suite (VIIRS instrument, or successful launch of the Ocean and Land Colour Instrument (OLCI expected in 2014 will hopefully extend the ocean color time series and increase the potential for detecting trends in ocean productivity in the future. Alternatively, a potential discontinuity in the time series of ocean chlorophyll a, introduced by a change of instrument without overlap and opportunity for cross-calibration, would make trend detection even more challenging. In this paper, we demonstrate that there are a few regions with statistically significant trends over the ten years of SeaWiFS data, but at a global scale the trend is not large enough to be distinguished from noise. We quantify the degree to which red noise (autocorrelation especially challenges trend detection in these observational time series. We further demonstrate how discontinuities in the time series at various points would affect our ability to detect trends in ocean chlorophyll a. We highlight the importance of maintaining continuous, climate-quality satellite data records for climate-change detection and attribution studies.

A Novel Adaptive Modulation Based on Nondata-Aided Error Vector Magnitude in Non-Line-Of-Sight Condition of Wireless Sensor Network.

Science.gov (United States)

Yang, Fan; Zeng, Xiaoping; Mao, Haiwei; Jian, Xin; Tan, Xiaoheng; Du, Derong

2018-01-15

The high demand for multimedia applications in environmental monitoring, invasion detection, and disaster aid has led to the rise of wireless sensor network (WSN). With the increase of reliability and diversity of information streams, the higher requirements on throughput and quality of service (QoS) have been put forward in data transmission between two sensor nodes. However, lower spectral efficiency becomes a bottleneck in non-line-of-sight (NLOS) transmission of WSN. This paper proposes a novel nondata-aided error vector magnitude based adaptive modulation (NDA-EVM-AM) to solve the problem. NDA-EVM is considered as a new metric to evaluate the quality of NLOS link for adaptive modulation in WSN. By modeling the NLOS scenario as the η - μ fading channel, a closed-form expression for the NDA-EVM of multilevel quadrature amplitude modulation (MQAM) signals over the η - μ fading channel is derived, and the relationship between SER and NDA-EVM is also formulated. Based on these results, NDA-EVM state machine is designed for adaptation strategy. The algorithmic complexity of NDA-EVM-AM is analyzed and the outage capacity of NDA-EVM-AM in an NLOS scenario is also given. The performances of NDA-EVM-AM are compared by simulation, and the results show that NDA-EVM-AM is an effective technique to be used in the NLOS scenarios of WSN. This technique can accurately reflect the channel variations and efficiently adjust modulation order to better match the channel conditions, hence, obtaining better performance in average spectral efficiency.

1 kHz 2D Visual Motion Sensor Using 20 × 20 Silicon Retina Optical Sensor and DSP Microcontroller.

Science.gov (United States)

Liu, Shih-Chii; Yang, MinHao; Steiner, Andreas; Moeckel, Rico; Delbruck, Tobi

2015-04-01

Optical flow sensors have been a long running theme in neuromorphic vision sensors which include circuits that implement the local background intensity adaptation mechanism seen in biological retinas. This paper reports a bio-inspired optical motion sensor aimed towards miniature robotic and aerial platforms. It combines a 20 × 20 continuous-time CMOS silicon retina vision sensor with a DSP microcontroller. The retina sensor has pixels that have local gain control and adapt to background lighting. The system allows the user to validate various motion algorithms without building dedicated custom solutions. Measurements are presented to show that the system can compute global 2D translational motion from complex natural scenes using one particular algorithm: the image interpolation algorithm (I2A). With this algorithm, the system can compute global translational motion vectors at a sample rate of 1 kHz, for speeds up to ±1000 pixels/s, using less than 5 k instruction cycles (12 instructions per pixel) per frame. At 1 kHz sample rate the DSP is 12% occupied with motion computation. The sensor is implemented as a 6 g PCB consuming 170 mW of power.

Tracking Objects with Networked Scattered Directional Sensors

Science.gov (United States)

Plarre, Kurt; Kumar, P. R.

2007-12-01

We study the problem of object tracking using highly directional sensors—sensors whose field of vision is a line or a line segment. A network of such sensors monitors a certain region of the plane. Sporadically, objects moving in straight lines and at a constant speed cross the region. A sensor detects an object when it crosses its line of sight, and records the time of the detection. No distance or angle measurements are available. The task of the sensors is to estimate the directions and speeds of the objects, and the sensor lines, which are unknown a priori. This estimation problem involves the minimization of a highly nonconvex cost function. To overcome this difficulty, we introduce an algorithm, which we call "adaptive basis algorithm." This algorithm is divided into three phases: in the first phase, the algorithm is initialized using data from six sensors and four objects; in the second phase, the estimates are updated as data from more sensors and objects are incorporated. The third phase is an optional coordinated transformation. The estimation is done in an "ad-hoc" coordinate system, which we call "adaptive coordinate system." When more information is available, for example, the location of six sensors, the estimates can be transformed to the "real-world" coordinate system. This constitutes the third phase.

The timescales of global surface-ocean connectivity.

Science.gov (United States)

Jönsson, Bror F; Watson, James R

2016-04-19

Planktonic communities are shaped through a balance of local evolutionary adaptation and ecological succession driven in large part by migration. The timescales over which these processes operate are still largely unresolved. Here we use Lagrangian particle tracking and network theory to quantify the timescale over which surface currents connect different regions of the global ocean. We find that the fastest path between two patches--each randomly located anywhere in the surface ocean--is, on average, less than a decade. These results suggest that marine planktonic communities may keep pace with climate change--increasing temperatures, ocean acidification and changes in stratification over decadal timescales--through the advection of resilient types.

Adapting to a warmer ocean--seasonal shift of baleen whale movements over three decades.

Directory of Open Access Journals (Sweden)

Christian Ramp

Full Text Available Global warming poses particular challenges to migratory species, which face changes to the multiple environments occupied during migration. For many species, the timing of migration between summer and winter grounds and also within-season movements are crucial to maximise exploitation of temporarily abundant prey resources in feeding areas, themselves adapting to the warming planet. We investigated the temporal variation in the occurrence of fin (Balaenoptera physalus and humpback whales (Megaptera novaeangliae in a North Atlantic summer feeding ground, the Gulf of St. Lawrence (Canada, from 1984 to 2010 using a long-term study of individually identifiable animals. These two sympatric species both shifted their date of arrival at a previously undocumented rate of more than 1 day per year earlier over the study period thus maintaining the approximate 2-week difference in arrival of the two species and enabling the maintenance of temporal niche separation. However, the departure date of both species also shifted earlier but at different rates resulting in increasing temporal overlap over the study period indicating that this separation may be starting to erode. Our analysis revealed that the trend in arrival was strongly related to earlier ice break-up and rising sea surface temperature, likely triggering earlier primary production. The observed changes in phenology in response to ocean warming are a remarkable example of phenotypic plasticity and may partly explain how baleen whales were able to survive a number of changes in climate over the last several million years. However, it is questionable whether the observed rate of change in timing can be maintained. Substantial modification to the distribution or annual life cycle of these species might be required to keep up with the ongoing warming of the oceans.

Adaptive Optics for Industry and Medicine

Science.gov (United States)

Dainty, Christopher

2008-01-01

at Iris AO (poster paper) / Michael A. Helmbrecht ... [et al.]. Electrostatic push pull mirror improvernents in visual optics (poster paper) / S. Bonora and L. Poletto. 25cm bimorph mirror for petawatt laser / S. Bonora ... [et al.]. Hysteresis compensation for piezo deformable mirror (poster paper) / H. Song ... [et al.]. Static and dynamic responses of an adaptive optics ferrofluidic mirror (poster paper) / A. Seaman ... [et al.]. New HDTV (1920 x 1080) phase-only SLM (poster paper) / Stefan Osten and Sven Krueger. Monomorph large aperture deformable mirror for laser applications (poster paper) / J-C Sinquin, J-M Lurcon, C. Guillemard. Low cost, high speed for adaptive optics control (oral paper) / Christopher D. Saunter and Gordon D. Love. Open loop woofer-tweeter adaptive control on the LAO multi-conjugate adaptive optics testbed (oral paper) / Edward Laag, Don Gavel and Mark Ammons -- pt. 2. Wavefront sensors. Wave front sensorless adaptive optics for imaging and microscopy (invited paper) / Martin J. Booth, Delphine Débarre and Tony Wilson. A fundamental limit for wavefront sensing (oral paper) / Carl Paterson. Coherent fibre-bundle wavefront sensor (oral paper) / Brian Vohnsen, I. Iglesias and Pablo Artal. Maximum-likelihood methods in wave-front sensing: nuisance parameters (oral paper) / David Lara, Harrison H. Barrett, and Chris Dainty. Real-time wavefront sensing for ultrafast high-power laser beams (oral paper) / Juan M. Bueno ... [et al.]. Wavefront sensing using a random phase screen (oral paper) / M. Loktev, G. Vdovin and O. Soloviev. Quadri-Wave Lateral Shearing Interferometry: a new mature technique for wave front sensing in adaptive optics (oral paper) / Benoit Wattellier ... [et al.]. In vivo measurement of ocular aberrations with a distorted grating wavefront sensor (oral paper) / P. Harrison ... [et al.]. Position-sensitive detector designed with unusual CMOS layout strategies for a Hartman-Shack wavefront sensor (oral Paper) / Davies W. de Lima

Green partial packet recovery in wireless sensor networks

KAUST Repository

Daghistani, Anas; Ben Khalifa, Abderrahman; Showail, Ahmad; Shihada, Basem

2015-01-01

wireless sensor motes. We propose Green-Frag, a novel adaptive partial packet recovery mechanism that is energy friendly. It can help prolonging the battery life of wireless sensor motes that are usually resource constrained. It dynamically partitions

Multi-sensor fusion using an adaptive multi-hypothesis tracking algorithm

NARCIS (Netherlands)

Kester, L.J.H.M.

2003-01-01

The purpose of a tracking algorithm is to associate data measured by one or more (moving) sensors to moving objects in the environment. The state of these objects that can be estimated with the tracking process depends on the type of data that is provided by these sensors. It is discussed how the

Marine organisms and their adaption - Adaptions solve the challenges of existence in the sea.

Digital Repository Service at National Institute of Oceanography (India)

Gonsalves, M.J.B.D.; Das, A.; LokaBharathi, P.A.

in the upper ocean; the size of marine organisms decrease with depth (1) Marine adption includes symbiosis, camouflage, size, contact, communication, defensive and reproductive strategies besides, adaptions to environmental conditions like temperature, light...

Modular sensor network node

Science.gov (United States)

Davis, Jesse Harper Zehring [Berkeley, CA; Stark, Jr., Douglas Paul; Kershaw, Christopher Patrick [Hayward, CA; Kyker, Ronald Dean [Livermore, CA

2008-06-10

A distributed wireless sensor network node is disclosed. The wireless sensor network node includes a plurality of sensor modules coupled to a system bus and configured to sense a parameter. The parameter may be an object, an event or any other parameter. The node collects data representative of the parameter. The node also includes a communication module coupled to the system bus and configured to allow the node to communicate with other nodes. The node also includes a processing module coupled to the system bus and adapted to receive the data from the sensor module and operable to analyze the data. The node also includes a power module connected to the system bus and operable to generate a regulated voltage.

OSOAA: A Vector Radiative Transfer Model of Coupled Atmosphere-Ocean System for a Rough Sea Surface Application to the Estimates of the Directional Variations of the Water Leaving Reflectance to Better Process Multi-angular Satellite Sensors Data Over the Ocean

Science.gov (United States)

Chami, Malik; LaFrance, Bruno; Fougnie, Bertrand; Chowdhary, Jacek; Harmel, Tristan; Waquet, Fabien

2015-01-01

In this study, we present a radiative transfer model, so-called OSOAA, that is able to predict the radiance and degree of polarization within the coupled atmosphere-ocean system in the presence of a rough sea surface. The OSOAA model solves the radiative transfer equation using the successive orders of scattering method. Comparisons with another operational radiative transfer model showed a satisfactory agreement within 0.8%. The OSOAA model has been designed with a graphical user interface to make it user friendly for the community. The radiance and degree of polarization are provided at any level, from the top of atmosphere to the ocean bottom. An application of the OSOAA model is carried out to quantify the directional variations of the water leaving reflectance and degree of polarization for phytoplankton and mineral-like dominated waters. The difference between the water leaving reflectance at a given geometry and that obtained for the nadir direction could reach 40%, thus questioning the Lambertian assumption of the sea surface that is used by inverse satellite algorithms dedicated to multi-angular sensors. It is shown as well that the directional features of the water leaving reflectance are weakly dependent on wind speed. The quantification of the directional variations of the water leaving reflectance obtained in this study should help to correctly exploit the satellite data that will be acquired by the current or forthcoming multi-angular satellite sensors.

Preliminary data for the 20 May 1974, simultaneous evaluation of remote sensors experiment. [water pollution monitoring

Science.gov (United States)

Johnson, R. W.; Batten, C. E.; Bowker, D. E.; Bressette, W. E.; Grew, G. W.

1975-01-01

Several remote sensors were simultaneously used to collect data over the tidal James River from Hopewell to Norfolk, Virginia. Sensors evaluated included the Multichannel-Ocean Color Sensor, multispectral scanners, and multispectral photography. Ground truth measurements and remotely sensed data are given. Preliminary analysis indicates that suspended sediment and concentrated industrial effluent are observable from all sensors.

Low-cost embedded systems for democratizing ocean sensor technology in the coastal zone

Science.gov (United States)

Glazer, B. T.; Lio, H. I.

2017-12-01

Environmental sciences suffer from undersampling. Enabling sustained and unattended data collection in the coastal zone typically involves expensive instrumentation and infrastructure deployed as cabled observatories or moorings with little flexibility in deployment location following initial installation. High costs of commercially-available or custom instruments have limited the number of sensor sites that can be targeted by academic researchers, and have also limited engagement with the public. We have developed a novel, low-cost, open-source sensor and software platform to enable wireless data transfer of biogeochemical sensors in the coastal zone. The platform is centered upon widely available, low-cost, single board computers and microcontrollers. We have used a blend of on-hand research-grade sensors and low-cost open-source electronics that can be assembled by tech-savvy non-engineers. Robust, open-source code that remains customizable for specific miniNode configurations can match a specific site's measurement needs, depending on the scientific research priorities. We have demonstrated prototype capabilities and versatility through lab testing and field deployments of multiple sensor nodes with multiple sensor inputs, all of which are streaming near-real-time data from Kaneohe Bay over wireless RF links to a shore-based base station.

Sensor device and methods for using same

Science.gov (United States)

Rothgeb, Timothy Michael; Gansle, Kristina Marie Rohal; Joyce, Jonathan Livingston; Jordan, James Madison; Rohwer, Tedd Addison; Lockhart, Randal Ray; Smith, Christopher Lawrence; Trinh, Toan; Cipollone, Mark Gary

2005-10-25

A sensor device and method of employment is provided. More specifically, a sensor device adapted to detect, identify and/or measure a chemical and/or physical characteristic upon placement of the device into an environment, especially a liquid medium for which monitoring is sought is provided.

Wireless sensors and sensor networks for homeland security applications.

Science.gov (United States)

Potyrailo, Radislav A; Nagraj, Nandini; Surman, Cheryl; Boudries, Hacene; Lai, Hanh; Slocik, Joseph M; Kelley-Loughnane, Nancy; Naik, Rajesh R

2012-11-01

New sensor technologies for homeland security applications must meet the key requirements of sensitivity to detect agents below risk levels, selectivity to provide minimal false-alarm rates, and response speed to operate in high throughput environments, such as airports, sea ports, and other public places. Chemical detection using existing sensor systems is facing a major challenge of selectivity. In this review, we provide a brief summary of chemical threats of homeland security importance; focus in detail on modern concepts in chemical sensing; examine the origins of the most significant unmet needs in existing chemical sensors; and, analyze opportunities, specific requirements, and challenges for wireless chemical sensors and wireless sensor networks (WSNs). We further review a new approach for selective chemical sensing that involves the combination of a sensing material that has different response mechanisms to different species of interest, with a transducer that has a multi-variable signal-transduction ability. This new selective chemical-sensing approach was realized using an attractive ubiquitous platform of battery-free passive radio-frequency identification (RFID) tags adapted for chemical sensing. We illustrate the performance of RFID sensors developed in measurements of toxic industrial materials, humidity-independent detection of toxic vapors, and detection of chemical-agent simulants, explosives, and strong oxidizers.

Adaptive and Reactive Security for Wireless Sensor Networks

National Research Council Canada - National Science Library

Stankovic, John A

2007-01-01

.... WSNs are also susceptible to malicious, non-random security attacks. For example, a wireless sensor network deployed in remote regions to detect and classify targets could be rendered inoperative by various security attacks...

Advancing Ocean Acidification Biology Using Durafet® pH Electrodes

Directory of Open Access Journals (Sweden)

Lydia Kapsenberg

2017-10-01

Full Text Available Research assessing the biological impacts of global ocean change often requires a burdensome characterization of seawater carbonate chemistry. For laboratory-based ocean acidification research, this impedes the scope of experimental design. Honeywell Durafet® III pH electrodes provide precise and continuous seawater pH measurements. In addition to use in oceanographic sensor packages, Durafets can also be used in the laboratory to track and control seawater treatments via Honeywell Universal Dual Analyzers (UDAs. Here we provide performance data, instructions, and step-by-step recommendations for use of multiple UDA-Durafets. Durafet pH measurements were within ±0.005 units pHT of spectrophotometric measurements and agreement among eight Durafets was better than ±0.005 units pHT. These results indicate equal performance to Durafets in oceanographic sensor packages, but methods for calibration and quality control differ. Use of UDA-Durafets vastly improves time-course documentation of experimental conditions and reduces person-hours dedicated to this activity. Due to the versatility of integrating Durafets in laboratory seawater systems, this technology opens the door to advance the scale of questions that the ocean acidification research community aims to address.

Physical, chemical, and other data collected using meteorological sensors, secchi disk, transmissometer, and CTD casts from the THOMAS WASHINGTON as part of the International Decade of Ocean Exploration / North Pacific Experiment (IDOE/NORPAX) project from 21 January - 17 February 1974 (NODC Accession 7800629)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Physical, chemical, and other data were collected using meteorological sensors, secchi disk, transmissometer, and CTD casts from THOMAS WASHINGTON from January 21,...

Ultra-high resolution coded wavefront sensor

KAUST Repository

Wang, Congli

2017-06-08

Wavefront sensors and more general phase retrieval methods have recently attracted a lot of attention in a host of application domains, ranging from astronomy to scientific imaging and microscopy. In this paper, we introduce a new class of sensor, the Coded Wavefront Sensor, which provides high spatio-temporal resolution using a simple masked sensor under white light illumination. Specifically, we demonstrate megapixel spatial resolution and phase accuracy better than 0.1 wavelengths at reconstruction rates of 50 Hz or more, thus opening up many new applications from high-resolution adaptive optics to real-time phase retrieval in microscopy.

Evaluating and Extending the Ocean Wind Climate Data Record

Science.gov (United States)

Ricciardulli, Lucrezia; Rodriguez, Ernesto; Stiles, Bryan W.; Bourassa, Mark A.; Long, David G.; Hoffman, Ross N.; Stoffelen, Ad; Verhoef, Anton; O'Neill, Larry W.; Farrar, J. Tomas; Vandemark, Douglas; Fore, Alexander G.; Hristova-Veleva, Svetla M.; Turk, F. Joseph; Gaston, Robert; Tyler, Douglas

2017-01-01

Satellite microwave sensors, both active scatterometers and passive radiometers, have been systematically measuring near-surface ocean winds for nearly 40 years, establishing an important legacy in studying and monitoring weather and climate variability. As an aid to such activities, the various wind datasets are being intercalibrated and merged into consistent climate data records (CDRs). The ocean wind CDRs (OW-CDRs) are evaluated by comparisons with ocean buoys and intercomparisons among the different satellite sensors and among the different data providers. Extending the OW-CDR into the future requires exploiting all available datasets, such as OSCAT-2 scheduled to launch in July 2016. Three planned methods of calibrating the OSCAT-2 σo measurements include 1) direct Ku-band σo intercalibration to QuikSCAT and RapidScat; 2) multisensor wind speed intercalibration; and 3) calibration to stable rainforest targets. Unfortunately, RapidScat failed in August 2016 and cannot be used to directly calibrate OSCAT-2. A particular future continuity concern is the absence of scheduled new or continuation radiometer missions capable of measuring wind speed. Specialized model assimilations provide 30-year long high temporal/spatial resolution wind vector grids that composite the satellite wind information from OW-CDRs of multiple satellites viewing the Earth at different local times. PMID:28824741

Spectral interdependence of remote-sensing reflectance and its implications on the design of ocean color satellite sensors.

Science.gov (United States)

Lee, Zhongping; Shang, Shaoling; Hu, Chuanmin; Zibordi, Giuseppe

2014-05-20

storage and handling of large volume hyperspectral data as well as for the design of future ocean color satellite sensors.

Flexible Temperature Sensors on Fibers

Directory of Open Access Journals (Sweden)

Marcin Sloma

2010-08-01

Full Text Available The aim of this paper is to present research dedicated to the elaboration of novel, miniaturized flexible temperature sensors for textronic applications. Examined sensors were manufactured on a single yarn, which ensures their high flexibility and good compatibility with textiles. Stable and linear characteristics were obtained by special technological process and applied temperature profiles. As a thermo-sensitive materials the innovative polymer compositions filled with multiwalled carbon nanotubes were used. Elaborated material was adapted to printing and dip-coating techniques to produce NTC composites. Nanotube sensors were free from tensometric effect typical for other carbon-polymer sensor, and demonstrated TCR of 0.13%/K. Obtained temperature sensors, compatible with textile structure, can be applied in rapidly developing smart textiles and be used for health and protections purposes.

Relational-Based Sensor Data Cleansing

DEFF Research Database (Denmark)

Iftikhar, Nadeem; Liu, Xiufeng; Nordbjerg, Finn Ebertsen

2015-01-01

cleansing approaches, such as classification, prediction and moving average are not suited for embedded sensor devices, due to the limited storage and processing capabilities. In this paper, we propose a sensor data cleansing approach using the relational-based technologies, including constraints, triggers...... and granularity-based data aggregation. The proposed approach is simple but effective to cleanse different types of dirty data, including delayed data, incomplete data, incorrect data, duplicate data and missing data. We evaluate the proposed strategy to verify its efficiency, effectiveness and adaptability.......Today sensors are widely used in many monitoring applications. Due to some random environmental effects and/or sensing failures, the collected sensor data is typically noisy. Thus, it is critical to cleanse the sensor data before using it to answer queries or conduct data analysis. Popular data...

Using SensorML to describe scientific workflows in distributed web service environments

CSIR Research Space (South Africa)

Van Zyl, TL

2009-07-01

Full Text Available for increased collaboration through workflow sharing. The Sensor Web is an open complex adaptive system the pervades the internet and provides access to sensor resources. One mechanism for describing sensor resources is through the use of Sensor ML. It is shown...

Using SensorML to describe scientific workflows in distributed web service environments

CSIR Research Space (South Africa)

Van Zyl, TL

2009-07-01

Full Text Available for increased collaboration through workflow sharing. The Sensor Web is an open complex adaptive system the pervades the internet and provides access to sensor resources. One mechanism for describing sensor resources is through the use of SensorML. It is shown...

Embedded pitch adapters for the ATLAS Tracker Upgrade

International Nuclear Information System (INIS)

Ullan, Miguel; Benitez, Victor; Pellegrini, Giulio; Fleta, Celeste; Lozano, Manuel; Lacasta, Carlos; Soldevila, Urmila; Garcia, Carmen

2013-01-01

In the current ATLAS tracker modules, sensor bonding pads are placed on their corresponding strips and oriented along the strips. This creates a difference in pitch and orientation between sensor bond pads and readout electronics bond pads. Therefore, a pitch adapter (PA), or “fan-in”, is needed. The purpose of these PA is the electrical interconnection of every channel from the detector bonding pads to the read-out chips, adapting the different pad pitch. Our new approach is to build those PAs inside the sensor; this is what we call Embedded Pitch Adapters. The idea is to use an additional metal layer in order to define a new group of pads, connected to the strips via tracks with the second metal. The embedded PAs have been fabricated on 4-in. prototype sensors for the ATLAS-Upgrade Endcap Tracker to test their performance and suitability. The tests confirm proper fabrication of the second metal tracks, and no effects on detector performance. No indication of cross-talk between first and second metal channels has been observed. A small indication of possible signal pick-up from the bulk has been observed in a few channels, which needs to be further investigated

"Going with the flow" or not: evidence of positive rheotaxis in oceanic juvenile loggerhead turtles (Caretta caretta in the South Pacific Ocean Using Satellite Tags and Ocean Circulation Data.

Directory of Open Access Journals (Sweden)

Donald R Kobayashi

Full Text Available The movement of juvenile loggerhead turtles (n = 42 out-fitted with satellite tags and released in oceanic waters off New Caledonia was examined and compared with ocean circulation data. Merging of the daily turtle movement data with drifter buoy movements, OSCAR (Ocean Surface Current Analyses--Real time circulation data, and three different vertical strata (0-5 m, 0-40 m, 0-100 m of HYCOM (HYbrid Coordinate Ocean Model circulation data indicated the turtles were swimming against the prevailing current in a statistically significant pattern. This was not an artifact of prevailing directions of current and swimming, nor was it an artifact of frictional slippage. Generalized additive modeling was used to decompose the pattern of swimming into spatial and temporal components. The findings are indicative of a positive rheotaxis whereby an organism is able to detect the current flow and orient itself to swim into the current flow direction or otherwise slow down its movement. Potential mechanisms for the means and adaptive significance of rheotaxis in oceanic juvenile loggerhead turtles are discussed.

Reactive and adaptive monitoring to secure aggregation in wireless sensor networks

NARCIS (Netherlands)

Labraoui, Nabila; Gueroui, Mourad; Aliouat, Makhlouf; Petit, Jonathan

Data aggregation is considered as one of the fundamental distributed data processing procedures for saving the energy and minimizing the medium access layer contention in wireless sensor networks. However, sensor networks are likely to be deployed in an untrusted environment, which make them

Two-Level Evaluation on Sensor Interoperability of Features in Fingerprint Image Segmentation

Directory of Open Access Journals (Sweden)

Ya-Shuo Li

2012-03-01

Full Text Available Features used in fingerprint segmentation significantly affect the segmentation performance. Various features exhibit different discriminating abilities on fingerprint images derived from different sensors. One feature which has better discriminating ability on images derived from a certain sensor may not adapt to segment images derived from other sensors. This degrades the segmentation performance. This paper empirically analyzes the sensor interoperability problem of segmentation feature, which refers to the feature’s ability to adapt to the raw fingerprints captured by different sensors. To address this issue, this paper presents a two-level feature evaluation method, including the first level feature evaluation based on segmentation error rate and the second level feature evaluation based on decision tree. The proposed method is performed on a number of fingerprint databases which are obtained from various sensors. Experimental results show that the proposed method can effectively evaluate the sensor interoperability of features, and the features with good evaluation results acquire better segmentation accuracies of images originating from different sensors.

Adaptive intrusion data system

International Nuclear Information System (INIS)

Johnson, C.S.

1976-01-01

An Adaptive Intrusion Data System (AIDS) was developed to collect data from intrusion alarm sensors as part of an evaluation system to improve sensor performance. AIDS is a unique digital data compression, storage, and formatting system. It also incorporates capability for video selection and recording for assessment of the sensors monitored by the system. The system is software reprogrammable to numerous configurations that may be utilized for the collection of environmental, bi-level, analog and video data. The output of the system is digital tapes formatted for direct data reduction on a CDC 6400 computer, and video tapes containing timed tagged information that can be correlated with the digital data

A design study for an advanced ocean color scanner system. [spaceborne equipment

Science.gov (United States)

Kim, H. H.; Fraser, R. S.; Thompson, L. L.; Bahethi, O.

1980-01-01

Along with a colorimetric data analysis scheme, the instrumental parameters which need to be optimized in future spaceborne ocean color scanner systems are outlined. With regard to assessing atmospheric effects from ocean colorimetry, attention is given to computing size parameters of the aerosols in the atmosphere, total optical depth measurement, and the aerosol optical thickness. It is suggested that sensors based on the use of linear array technology will meet hardware objectives.

Cross Deployment Networking and Systematic Performance Analysis of Underwater Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Zhengxian Wei

2017-07-01

Full Text Available Underwater wireless sensor networks (UWSNs have become a new hot research area. However, due to the work dynamics and harsh ocean environment, how to obtain an UWSN with the best systematic performance while deploying as few sensor nodes as possible and setting up self-adaptive networking is an urgent problem that needs to be solved. Consequently, sensor deployment, networking, and performance calculation of UWSNs are challenging issues, hence the study in this paper centers on this topic and three relevant methods and models are put forward. Firstly, the normal body-centered cubic lattice to cross body-centered cubic lattice (CBCL has been improved, and a deployment process and topology generation method are built. Then most importantly, a cross deployment networking method (CDNM for UWSNs suitable for the underwater environment is proposed. Furthermore, a systematic quar-performance calculation model (SQPCM is proposed from an integrated perspective, in which the systematic performance of a UWSN includes coverage, connectivity, durability and rapid-reactivity. Besides, measurement models are established based on the relationship between systematic performance and influencing parameters. Finally, the influencing parameters are divided into three types, namely, constraint parameters, device performance and networking parameters. Based on these, a networking parameters adjustment method (NPAM for optimized systematic performance of UWSNs has been presented. The simulation results demonstrate that the approach proposed in this paper is feasible and efficient in networking and performance calculation of UWSNs.

The GULLS project: a comparison of vulnerabilities across selected ocean hotspots and implications for adaptation to global change.

Science.gov (United States)

Cochrane, K.; Hobday, A. J.; Aswani, S.; Byfield, V.; Dutra, L.; Gasalla, M.; Haward, M.; Paytan, A.; Pecl, G.; Plaganyi-Lloyd, E.; Popova, K.; Salim, S. S.; Savage, C.; Sauer, W.; van Putten, I. E.; Visser, N.; Team, T G

2016-12-01

The GULLS project, `Global learning for local solutions: Reducing vulnerability of marine-dependent coastal communities' has been underway since October 2014. The project has been investigating six regional `hotspots': marine areas experiencing rapid warming. These are south-east Australia, Brazil, India, Solomon Islands, South Africa, and the Mozambique Channel and Madagascar. Rapid warming could be expected to have social, cultural and economic impacts that could affect these countries in different ways and may already be doing so. GULLS has focused on contributing to assessing and reducing the vulnerability of coastal communities and other stakeholders dependent on marine resources and to facilitate adaptation to climate change and variability through an integrated and trans-disciplinary approach. It includes participants from Australia, Brazil, India, Madagascar, New Zealand, South Africa, the United Kingdom and the United States of America. The research programme has been divided into six inter-linked components: ocean models, biological and ecological sensitivity analyses, system models, social vulnerability, policy mapping, and communication and education. This presentation will provide a brief overview of each of these components and describe the benefits that have resulted from the collaborative and transdisciplinary approach of GULLS. Following the standard vulnerability elements of exposure, sensitivity and adaptive capacity, the vulnerabilities of coastal communities and other stakeholders dependent on marine resources in the five hotspots will be compared using a set of indicators derived and populated from results of the research programme. The implications of similarities and differences between the hotspots for adaptation planning and options will be described.

An interfacial stress sensor for biomechanical applications

International Nuclear Information System (INIS)

Sundara-Rajan, K; Bestick, A; Rowe, G I; Mamishev, A V; Klute, G K; Ledoux, W R; Wang, H C

2012-01-01

This paper presents a capacitive sensor that measures interfacial forces in prostheses and is promising for other biomedical applications. These sensors can be integrated into prosthetic devices to measure both normal and shear stress simultaneously, allowing for the study of prosthetic limb fit, and ultimately for the ability to better adapt prosthetics to individual users. A sensing cell with a 1.0 cm 2 spatial resolution and a measurement range of 0–220 kPa of shear and 0–2 MPa of pressure was constructed. The cell was load tested and found to be capable of isolating the applied shear and pressure forces. This paper discusses the construction of the prototype, the mechanical and electrode design, fabrication and characterization. The work presented is aimed at creating a class of adaptive prosthetic interfaces using a capacitive sensor. (paper)

MERIS-based ocean colour classification with the discrete Forel-Ule scale

NARCIS (Netherlands)

Wernand, M.R.; Hommersom, A.; van der Woerd, H.J.

2013-01-01

Multispectral information from satellite borne ocean colour sensors is at present used to characterize natural waters via the retrieval of concentrations of the three dominant optical constituents; pigments of phytoplankton, non-algal particles and coloured dissolved organic matter. A limitation of

Adaptive Intrusion Data System (AIDS)

International Nuclear Information System (INIS)

Corlis, N.E.

1980-05-01

The adaptive intrusion data system (AIDS) was developed to collect data from intrusion alarm sensors as part of an evaluation system to improve sensor performance. AIDS is a unique data system which uses computer controlled data systems, video cameras and recorders, analog-to-digital conversion, environmental sensors, and digital recorders to collect sensor data. The data can be viewed either manually or with a special computerized data-reduction system which adds new data to a data base stored on a magnetic disc recorder. This report provides a synoptic account of the AIDS as it presently exists. Modifications to the purchased subsystems are described, and references are made to publications which describe the Sandia-designed subsystems

Power control in wireless sensor networks with variable interference

NARCIS (Netherlands)

Chincoli, M.; Syed, A.A.; Exarchakos, G.; Liotta, A.

2016-01-01

Adaptive transmission power control schemes have been introduced in wireless sensor networks to adjust energy consumption under different network conditions. This is a crucial goal, given the constraints under which sensor communications operate. Power reduction may however have counterproductive

Partner-built ecosystem science - The National Ocean Partnership Program as a builder of EBM Tools and Data

Science.gov (United States)

Hoffman, P. L.; Green, R. E.; Kohanowich, K. M.

2016-12-01

The National Ocean Partnership Program (NOPP) was created in 1997 by federal public law to identify "and carry out partnerships among federal agencies, academia, industry, and other members of the oceanographic scientific community in the areas of data, resources, education, and communications." Since that time, numerous federal agencies have pooled talent, funding, and scientific resources (e.g. ships, aircraft, remote sensors and computing capability) to address pressing ocean science needs which no one entity can manage alone. In this presentation, we will address the ways the National Ocean Policy identifies ecosystem-based management (EBM) as a foundation for providing sound science-based and adaptable management to maintain the health, productivity, and resilience of U.S. ocean, coastal, and Great Lakes ecosystems. Because EBM is an important approach for efficient and effective interagency, multi-jurisdictional, and cross-sectoral marine planning and management, ocean science partnerships such as those provided by NOPP create a pool of regionally-pertinent, nationally-available data from which EBM decision makers can draw to address critical management issues. Specifically, we will provide examples drawn from the last five years of funding to illustrate how the NOPP process works, how it is managed by a federal Interagency Working Group (IWG-OP), and how EBM practitioners can both partner with others through the NOPP and offer guidance on the implementation of projects beneficial to the regional needs of the EBM community. Projects to be discussed have been carried out under the following themes: Arctic Cumulative Impacts: Marine Arctic Ecosystem Study (MARES) - Ecosystem Dynamics and Monitoring of the Beaufort Sea: An Integrated Science Approach. Biodiversity Indicators: Demonstration of a U.S. Marine Biodiversity Observation Network (Marine BON) Long-Term Observations: Coordinated Regional Efforts That Further the U.S. Integrated Ocean Observing System

How can present and future satellite missions support scientific studies that address ocean acidification?

Science.gov (United States)

Salisbury, Joseph; Vandemark, Douglas; Jonsson, Bror; Balch, William; Chakraborty, Sumit; Lohrenz, Steven; Chapron, Bertrand; Hales, Burke; Mannino, Antonio; Mathis, Jeremy T.; Reul, Nicolas; Signorini, Sergio; Wanninkhof, Rik; Yates, Kimberly K.

2016-01-01

Space-based observations offer unique capabilities for studying spatial and temporal dynamics of the upper ocean inorganic carbon cycle and, in turn, supporting research tied to ocean acidification (OA). Satellite sensors measuring sea surface temperature, color, salinity, wind, waves, currents, and sea level enable a fuller understanding of a range of physical, chemical, and biological phenomena that drive regional OA dynamics as well as the potentially varied impacts of carbon cycle change on a broad range of ecosystems. Here, we update and expand on previous work that addresses the benefits of space-based assets for OA and carbonate system studies. Carbonate chemistry and the key processes controlling surface ocean OA variability are reviewed. Synthesis of present satellite data streams and their utility in this arena are discussed, as are opportunities on the horizon for using new satellite sensors with increased spectral, temporal, and/or spatial resolution. We outline applications that include the ability to track the biochemically dynamic nature of water masses, to map coral reefs at higher resolution, to discern functional phytoplankton groups and their relationships to acid perturbations, and to track processes that contribute to acid variation near the land-ocean interface.

Marine Physical Laboratory Multi-Disciplinary Ocean Science and Technology Program

Science.gov (United States)

1991-04-01

ambierit noise were made with the advent of large. of 3800 m. Reflection profiles and drill logs from this hole scale seismome ter arrays." Sensor arrays...Deaion. and S C Webb."A deep-sea differential pressure frequency. The array was too limited in extent to make spa- gauge ." J. Aimos Ocean Tech. 2. 237...75, 847-864 (1985). 2"P. K Spudich andi I A. Orcutt," Petrology and porcisit% of tn oceanic "M E Dougherty and R. A. Stephen."Seismic energy

An Adaptive and Autonomous Sensor Sampling Frequency Control Scheme for Energy-Efficient Data Acquisition in Wireless Sensor Networks

NARCIS (Netherlands)

Chatterjea, Supriyo; Havinga, Paul J.M.; Nikoletseas, S.E.; Chlebus, B.S.; Johnson, D.; Krishnamachari, B.

2008-01-01

Wireless sensor networks are increasingly being used in environmental monitoring applications. Collecting raw data from these networks can lead to excessive energy consumption. This is especially true when the application requires specialized sensors that have very high energy consumption, e.g.

The Hyperspectral Imager for the Coastal Ocean (HICO): Sensor and Data Processing Overview

Science.gov (United States)

2010-01-20

backscattering coefficients, and others. Several of these software modules will be developed within the Automated Processing System (APS), a data... Automated Processing System (APS) NRL developed APS, which processes satellite data into ocean color data products. APS is a collection of methods...used for ocean color processing which provide the tools for the automated processing of satellite imagery [1]. These tools are in the process of

Adaptive self-correcting control system

International Nuclear Information System (INIS)

Ellis, S.H.

1984-01-01

A control system for regulating a controlled device or process, such as a turbofan engine, produces independent multiple estimates of one or more controlled variables of the device or process by combining the signals from a plurality of feedback sensors, which provide information related to the controlled variables, in weighted nonordered pairs. The independent multiple estimates of each controlled variable are combined into a weighted average, and individual estimates which differ by more than a specified amount from the weighted average are edited and temporarily removed from consideration. A revised weighted average value of each controlled variable is then produced, and this value is used to limit or control operation of the device or process. Adaptive trim is provided to compensate for changes in the device or process being controlled, such as engine deterioration, by slowly trimming each individual estimate toward the mean, and includes error compensation which constrains the weighted sum of the adaptive trims to equal zero, thereby preventing the adaptive trim from changing the operating level of the device or process. A secondary editing circuit based on a majority rule principle identifies a failed feedback sensor and permanently excludes all individual estimates of the controlled variable based on the failed sensor. Editing boundaries are increased and adaptive trim rate is varied when a transient occurs in the operation of the device or process. Further transient compensation may be required for a system with more severe transient requirements, and this invention includes compensation to selected feedback parameters such as turbine temperature to account for differences between steady state and transient values

Improvements to the swath-level near-surface atmospheric state parameter retrievals within the NRL Ocean Surface Flux System (NFLUX)

Science.gov (United States)

May, J. C.; Rowley, C. D.; Meyer, H.

2017-12-01

The Naval Research Laboratory (NRL) Ocean Surface Flux System (NFLUX) is an end-to-end data processing and assimilation system used to provide near-real-time satellite-based surface heat flux fields over the global ocean. The first component of NFLUX produces near-real-time swath-level estimates of surface state parameters and downwelling radiative fluxes. The focus here will be on the satellite swath-level state parameter retrievals, namely surface air temperature, surface specific humidity, and surface scalar wind speed over the ocean. Swath-level state parameter retrievals are produced from satellite sensor data records (SDRs) from four passive microwave sensors onboard 10 platforms: the Special Sensor Microwave Imager/Sounder (SSMIS) sensor onboard the DMSP F16, F17, and F18 platforms; the Advanced Microwave Sounding Unit-A (AMSU-A) sensor onboard the NOAA-15, NOAA-18, NOAA-19, Metop-A, and Metop-B platforms; the Advanced Technology Microwave Sounder (ATMS) sensor onboard the S-NPP platform; and the Advanced Microwave Scannin Radiometer 2 (AMSR2) sensor onboard the GCOM-W1 platform. The satellite SDRs are translated into state parameter estimates using multiple polynomial regression algorithms. The coefficients to the algorithms are obtained using a bootstrapping technique with all available brightness temperature channels for a given sensor, in addition to a SST field. For each retrieved parameter for each sensor-platform combination, unique algorithms are developed for ascending and descending orbits, as well as clear vs cloudy conditions. Each of the sensors produces surface air temperature and surface specific humidity retrievals. The SSMIS and AMSR2 sensors also produce surface scalar wind speed retrievals. Improvement is seen in the SSMIS retrievals when separate algorithms are used for the even and odd scans, with the odd scans performing better than the even scans. Currently, NFLUX treats all SSMIS scans as even scans. Additional improvement in all of

Retrieval of sea surface velocities using sequential Ocean Colour

Indian Academy of Sciences (India)

The Indian remote sensing satellite, IRS-P4 (Oceansat-I) launched on May 26th, 1999 carried two sensors on board, i.e., the Ocean Colour Monitor (OCM) and the Multi-frequency Scanning Microwave Radiometer (MSMR) dedicated for oceanographic research. Sequential data of IRS-P4 OCM has been analysed over parts ...

On Some Aspects of Precipitation over Tropical Indian Ocean Using Satellite Data

Digital Repository Service at National Institute of Oceanography (India)

RameshKumar, M.R.; Sreejith, O.P.

The annual and inter-annual variability of precipitation over the tropical Indian Ocean is studied for the period 1979–1997, using satellite data from a variety of sensors. The Climate Prediction Center Merged Analysis Precipitation (CMAP...

Genome architecture enables local adaptation of Atlantic cod despite high connectivity

DEFF Research Database (Denmark)

Barth, Julia M I; Berg, Paul R; Jonsson, Per R.

2017-01-01

Adaptation to local conditions is a fundamental process in evolution; however, mechanisms maintaining local adaptation despite high gene flow are still poorly understood. Marine ecosystems provide a wide array of diverse habitats that frequently promote ecological adaptation even in species...... characterized by strong levels of gene flow. As one example, populations of the marine fish Atlantic cod (Gadus morhua) are highly connected due to immense dispersal capabilities but nevertheless show local adaptation in several key traits. By combining population genomic analyses based on 12K single......-nucleotide polymorphisms with larval dispersal patterns inferred using a biophysical ocean model, we show that Atlantic cod individuals residing in sheltered estuarine habitats of Scandinavian fjords mainly belong to offshore oceanic populations with considerable connectivity between these diverse ecosystems. Nevertheless...

Connecting Coastal Communities with Ocean Science: A Look at Ocean Sense and the Inclusion of Place-based Indigenous Knowledge

Science.gov (United States)

McLean, M. A.; Brown, J.; Hoeberechts, M.

2016-02-01

Ocean Networks Canada (ONC), an initiative of the University of Victoria, develops, operates, and maintains cabled ocean observatory systems. Technologies developed on the world-leading NEPTUNE and VENUS observatories have been adapted for small coastal installations called "community observatories," which enable community members to directly monitor conditions in the local ocean environment. In 2014, ONC pioneered an innovative educational program, Ocean Sense: Local observations, global connections, which introduces students and teachers to the technologies installed on community observatories. The program introduces middle and high school students to research methods in biology, oceanography and ocean engineering through hands-on activities. Ocean Sense includes a variety of resources and opportunities to excite students and spark curiosity about the ocean environment. The program encourages students to connect their local observations to global ocean processes and the observations of students in other geographic regions. The connection to place and local relevance of the program is further enhanced through an emphasis on Indigenous and place-based knowledge. ONC is working with coastal Indigenous communities in a collaborative process to include local knowledge, culture, and language in Ocean Sense materials. For this process to meaningful and culturally appropriate, ONC is relying on the guidance and oversight of Indigenous community educators and knowledge holders. Ocean Sense also includes opportunities for Indigenous youth and teachers in remote communities to connect in person, including an annual Ocean Science Symposium and professional development events for teachers. Building a program which embraces multiple perspectives is effective both in making ocean science more relevant to Indigenous students and in linking Indigenous knowledge and place-based knowledge to ocean science.

Evolutionary genomics of the cold-adapted diatom Fragilariopsis cylindrus

KAUST Repository

Mock, Thomas

2017-01-17

The Southern Ocean houses a diverse and productive community of organisms. Unicellular eukaryotic diatoms are the main primary producers in this environment, where photosynthesis is limited by low concentrations of dissolved iron and large seasonal fluctuations in light, temperature and the extent of sea ice. How diatoms have adapted to this extreme environment is largely unknown. Here we present insights into the genome evolution of a cold-adapted diatom from the Southern Ocean, Fragilariopsis cylindrus, based on a comparison with temperate diatoms. We find that approximately 24.7 per cent of the diploid F. cylindrus genome consists of genetic loci with alleles that are highly divergent (15.1 megabases of the total genome size of 61.1 megabases). These divergent alleles were differentially expressed across environmental conditions, including darkness, low iron, freezing, elevated temperature and increased CO2. Alleles with the largest ratio of non-synonymous to synonymous nucleotide substitutions also show the most pronounced condition-dependent expression, suggesting a correlation between diversifying selection and allelic differentiation. Divergent alleles may be involved in adaptation to environmental fluctuations in the Southern Ocean.

Evolutionary genomics of the cold-adapted diatom Fragilariopsis cylindrus

KAUST Repository

Mock, Thomas; Otillar, Robert P.; Strauss, Jan; McMullan, Mark; Paajanen, Pirita; Schmutz, Jeremy; Salamov, Asaf; Sanges, Remo; Toseland, Andrew; Ward, Ben J.; Allen, Andrew E.; Dupont, Christopher L.; Frickenhaus, Stephan; Maumus, Florian; Veluchamy, Alaguraj; Wu, Taoyang; Barry, Kerrie W.; Falciatore, Angela; Ferrante, Maria I.; Fortunato, Antonio E.; Glö ckner, Gernot; Gruber, Ansgar; Hipkin, Rachel; Janech, Michael G.; Kroth, Peter G.; Leese, Florian; Lindquist, Erika A.; Lyon, Barbara R.; Martin, Joel; Mayer, Christoph; Parker, Micaela; Quesneville, Hadi; Raymond, James A.; Uhlig, Christiane; Valas, Ruben E.; Valentin, Klaus U.; Worden, Alexandra Z.; Armbrust, E. Virginia; Clark, Matthew D.; Bowler, Chris; Green, Beverley R.; Moulton, Vincent; Oosterhout, Cock van; Grigoriev, Igor V.

2017-01-01

The Southern Ocean houses a diverse and productive community of organisms. Unicellular eukaryotic diatoms are the main primary producers in this environment, where photosynthesis is limited by low concentrations of dissolved iron and large seasonal fluctuations in light, temperature and the extent of sea ice. How diatoms have adapted to this extreme environment is largely unknown. Here we present insights into the genome evolution of a cold-adapted diatom from the Southern Ocean, Fragilariopsis cylindrus, based on a comparison with temperate diatoms. We find that approximately 24.7 per cent of the diploid F. cylindrus genome consists of genetic loci with alleles that are highly divergent (15.1 megabases of the total genome size of 61.1 megabases). These divergent alleles were differentially expressed across environmental conditions, including darkness, low iron, freezing, elevated temperature and increased CO2. Alleles with the largest ratio of non-synonymous to synonymous nucleotide substitutions also show the most pronounced condition-dependent expression, suggesting a correlation between diversifying selection and allelic differentiation. Divergent alleles may be involved in adaptation to environmental fluctuations in the Southern Ocean.

Bathymetry of Shallow Coastal Regions Derived from Space-Borne Hyperspectral Sensor

National Research Council Canada - National Science Library

Lee, ZhongPing; Casey, Brandon; Parsons, Rost; Goode, Wesley; Weidemann, Alan; Arnone, Robert

2005-01-01

.... Though Hyperion was not designed for ocean studies, its unique spectral configuration makes it especially attractive to study the effectiveness of such kind of sensor for observing complex coastal waters...

Ocean acidification: the other CO2 problem.

Science.gov (United States)

Doney, Scott C; Fabry, Victoria J; Feely, Richard A; Kleypas, Joan A

2009-01-01

Rising atmospheric carbon dioxide (CO2), primarily from human fossil fuel combustion, reduces ocean pH and causes wholesale shifts in seawater carbonate chemistry. The process of ocean acidification is well documented in field data, and the rate will accelerate over this century unless future CO2 emissions are curbed dramatically. Acidification alters seawater chemical speciation and biogeochemical cycles of many elements and compounds. One well-known effect is the lowering of calcium carbonate saturation states, which impacts shell-forming marine organisms from plankton to benthic molluscs, echinoderms, and corals. Many calcifying species exhibit reduced calcification and growth rates in laboratory experiments under high-CO2 conditions. Ocean acidification also causes an increase in carbon fixation rates in some photosynthetic organisms (both calcifying and noncalcifying). The potential for marine organisms to adapt to increasing CO2 and broader implications for ocean ecosystems are not well known; both are high priorities for future research. Although ocean pH has varied in the geological past, paleo-events may be only imperfect analogs to current conditions.

Individual and population-level responses to ocean acidification.

Science.gov (United States)

Harvey, Ben P; McKeown, Niall J; Rastrick, Samuel P S; Bertolini, Camilla; Foggo, Andy; Graham, Helen; Hall-Spencer, Jason M; Milazzo, Marco; Shaw, Paul W; Small, Daniel P; Moore, Pippa J

2016-01-29

Ocean acidification is predicted to have detrimental effects on many marine organisms and ecological processes. Despite growing evidence for direct impacts on specific species, few studies have simultaneously considered the effects of ocean acidification on individuals (e.g. consequences for energy budgets and resource partitioning) and population level demographic processes. Here we show that ocean acidification increases energetic demands on gastropods resulting in altered energy allocation, i.e. reduced shell size but increased body mass. When scaled up to the population level, long-term exposure to ocean acidification altered population demography, with evidence of a reduction in the proportion of females in the population and genetic signatures of increased variance in reproductive success among individuals. Such increased variance enhances levels of short-term genetic drift which is predicted to inhibit adaptation. Our study indicates that even against a background of high gene flow, ocean acidification is driving individual- and population-level changes that will impact eco-evolutionary trajectories.

Sensor Fusion and Smart Sensor in Sports and Biomedical Applications

Directory of Open Access Journals (Sweden)

José Jair Alves Mendes Jr.

2016-09-01

Full Text Available The following work presents an overview of smart sensors and sensor fusion targeted at biomedical applications and sports areas. In this work, the integration of these areas is demonstrated, promoting a reflection about techniques and applications to collect, quantify and qualify some physical variables associated with the human body. These techniques are presented in various biomedical and sports applications, which cover areas related to diagnostics, rehabilitation, physical monitoring, and the development of performance in athletes, among others. Although some applications are described in only one of two fields of study (biomedicine and sports, it is very likely that the same application fits in both, with small peculiarities or adaptations. To illustrate the contemporaneity of applications, an analysis of specialized papers published in the last six years has been made. In this context, the main characteristic of this review is to present the largest quantity of relevant examples of sensor fusion and smart sensors focusing on their utilization and proposals, without deeply addressing one specific system or technique, to the detriment of the others.

Structural integrated sensor and actuator systems for active flow control

Science.gov (United States)

Behr, Christian; Schwerter, Martin; Leester-Schädel, Monika; Wierach, Peter; Dietzel, Andreas; Sinapius, Michael

2016-04-01

An adaptive flow separation control system is designed and implemented as an essential part of a novel high-lift device for future aircraft. The system consists of MEMS pressure sensors to determine the flow conditions and adaptive lips to regulate the mass flow and the velocity of a wall near stream over the internally blown Coanda flap. By the oscillating lip the mass flow in the blowing slot changes dynamically, consequently the momentum exchange of the boundary layer over a high lift flap required mass flow can be reduced. These new compact and highly integrated systems provide a real-time monitoring and manipulation of the flow conditions. In this context the integration of pressure sensors into flow sensing airfoils of composite material is investigated. Mechanical and electrical properties of the integrated sensors are investigated under mechanical loads during tensile tests. The sensors contain a reference pressure chamber isolated to the ambient by a deformable membrane with integrated piezoresistors connected as a Wheatstone bridge, which outputs voltage signals depending on the ambient pressure. The composite material in which the sensors are embedded consists of 22 individual layers of unidirectional glass fiber reinforced plastic (GFRP) prepreg. The results of the experiments are used for adapting the design of the sensors and the layout of the laminate to ensure an optimized flux of force in highly loaded structures primarily for future aeronautical applications. It can be shown that the pressure sensor withstands the embedding process into fiber composites with full functional capability and predictable behavior under stress.

Adaptive Subband Filtering Method for MEMS Accelerometer Noise Reduction

Directory of Open Access Journals (Sweden)

Piotr PIETRZAK

2008-12-01

Full Text Available Silicon microaccelerometers can be considered as an alternative to high-priced piezoelectric sensors. Unfortunately, relatively high noise floor of commercially available MEMS (Micro-Electro-Mechanical Systems sensors limits the possibility of their usage in condition monitoring systems of rotating machines. The solution of this problem is the method of signal filtering described in the paper. It is based on adaptive subband filtering employing Adaptive Line Enhancer. For filter weights adaptation, two novel algorithms have been developed. They are based on the NLMS algorithm. Both of them significantly simplify its software and hardware implementation and accelerate the adaptation process. The paper also presents the software (Matlab and hardware (FPGA implementation of the proposed noise filter. In addition, the results of the performed tests are reported. They confirm high efficiency of the solution.

Modeling of an Aged Porous Silicon Humidity Sensor Using ANN Technique

Directory of Open Access Journals (Sweden)

Tarikul ISLAM

2006-10-01

Full Text Available Porous silicon (PS sensor based on capacitive technique used for measuring relative humidity has the advantages of low cost, ease of fabrication with controlled structure and CMOS compatibility. But the response of the sensor is nonlinear function of humidity and suffers from errors due to aging and stability. One adaptive linear (ADALINE ANN model has been developed to model the behavior of the sensor with a view to estimate these errors and compensate them. The response of the sensor is represented by third order polynomial basis function whose coefficients are determined by the ANN technique. The drift in sensor output due to aging of PS layer is also modeled by adapting the weights of the polynomial function. ANN based modeling is found to be more suitable than conventional physical modeling of PS humidity sensor in changing environment and drift due to aging. It helps online estimation of nonlinearity as well as monitoring of the fault of the PS humidity sensor using the coefficients of the model.

Dynamic Reconfiguration of a RGBD Sensor Based on QoS and QoC Requirements in Distributed Systems.

Science.gov (United States)

Munera, Eduardo; Poza-Lujan, Jose-Luis; Posadas-Yagüe, Juan-Luis; Simó-Ten, José-Enrique; Noguera, Juan Fco Blanes

2015-07-24

The inclusion of embedded sensors into a networked system provides useful information for many applications. A Distributed Control System (DCS) is one of the clearest examples where processing and communications are constrained by the client's requirements and the capacity of the system. An embedded sensor with advanced processing and communications capabilities supplies high level information, abstracting from the data acquisition process and objects recognition mechanisms. The implementation of an embedded sensor/actuator as a Smart Resource permits clients to access sensor information through distributed network services. Smart resources can offer sensor services as well as computing, communications and peripheral access by implementing a self-aware based adaptation mechanism which adapts the execution profile to the context. On the other hand, information integrity must be ensured when computing processes are dynamically adapted. Therefore, the processing must be adapted to perform tasks in a certain lapse of time but always ensuring a minimum process quality. In the same way, communications must try to reduce the data traffic without excluding relevant information. The main objective of the paper is to present a dynamic configuration mechanism to adapt the sensor processing and communication to the client's requirements in the DCS. This paper describes an implementation of a smart resource based on a Red, Green, Blue, and Depth (RGBD) sensor in order to test the dynamic configuration mechanism presented.

Performance of the NPP CrIS Sensor

Science.gov (United States)

Emch, P. G.; Farrow, S. V.; Gu, D.; Wang, C.; Hagan, D. E.; Sabet-Peyman, F.

2009-12-01

This paper discusses the performance of the first Cross-track Infrared Sounder (CrIS) flight instrument and its data product performance. Together with ATMS, the CrIS sensor is a critical payload for National Polar-orbiting Operational Environmental Satellite System (NPOESS) providing temperature and moisture profiles, and will first fly on the NPOESS Preparatory Project (NPP) mission, the risk reduction flight for NPOESS. NPOESS is the next generation weather and climate monitoring system for the Department of Defense and National Oceanic and Atmospheric Administration (NOAA), being developed under contract by Northrop Grumman Aerospace Systems. The NPP flight sensor has recently completed thermal vacuum, electro-magnetic interference, and vibration testing. By the time of the presentation, the sensor sell-off is expected to have been completed as well. An overview of the sensor, the FM1 measurement performance, and details of the retrieval algorithms will be provided in this presentation.

The Mediterranean Moored Multi-sensor Array (M3A: system development and initial results

Directory of Open Access Journals (Sweden)

K. Nittis

Full Text Available Operational forecasting of ocean circulation and marine ecosystem fluctuations requires multi-parametric real-time measurements of physical and biochemical properties. The architecture of a system that is able to provide such measurements from the upper-thermocline layers of the Mediterranean Sea is described here. The system was developed for the needs of the Mediterranean Forecasting System and incorporates state-of-the-art sensors for optical and chemical measurements in the upper 100 m and physical measurements down to 500 m. Independent moorings that communicate via hydro-acoustic modems are hosting the sensors. The satellite data transfer and the large autonomy allow for the operation of the system in any open-ocean site. The system has been in pre-operational use in the Cretan Sea since January 2000. The results of this pilot phase indicate that multi-parametric real-time observations with the M3A system are feasible, if a consistent maintenance and re-calibration program is followed. The main limitations of the present configuration of M3A are related: (a to bio-fouling that primarily affects the turbidity and secondarily affects the other optical sensors, and (b to the limited throughput of the currently used satellite communication system.

Key words. Atmospheric composition and structure (instruments and techniques. Oceanography: general (ocean prediction Oceanography: physical (upper ocean process

The Mediterranean Moored Multi-sensor Array (M3A: system development and initial results

Directory of Open Access Journals (Sweden)

K. Nittis

2003-01-01

Full Text Available Operational forecasting of ocean circulation and marine ecosystem fluctuations requires multi-parametric real-time measurements of physical and biochemical properties. The architecture of a system that is able to provide such measurements from the upper-thermocline layers of the Mediterranean Sea is described here. The system was developed for the needs of the Mediterranean Forecasting System and incorporates state-of-the-art sensors for optical and chemical measurements in the upper 100 m and physical measurements down to 500 m. Independent moorings that communicate via hydro-acoustic modems are hosting the sensors. The satellite data transfer and the large autonomy allow for the operation of the system in any open-ocean site. The system has been in pre-operational use in the Cretan Sea since January 2000. The results of this pilot phase indicate that multi-parametric real-time observations with the M3A system are feasible, if a consistent maintenance and re-calibration program is followed. The main limitations of the present configuration of M3A are related: (a to bio-fouling that primarily affects the turbidity and secondarily affects the other optical sensors, and (b to the limited throughput of the currently used satellite communication system. Key words. Atmospheric composition and structure (instruments and techniques. Oceanography: general (ocean prediction Oceanography: physical (upper ocean process

76 FR 4139 - National Ocean Council; Development of Strategic Action Plans for the National Policy for the...

Science.gov (United States)

2011-01-24

...: Resiliency and Adaptation to Climate Change and Ocean Acidification: Strengthen resiliency of coastal... coastal areas in the face of climate-induced and other environmental changes; and Objective 9: Ocean... objective can further, including transformative changes in how we address the stewardship of the oceans...

Rayleigh radiance computations for satellite remote sensing: accounting for the effect of sensor spectral response function.

Science.gov (United States)

Wang, Menghua

2016-05-30

To understand and assess the effect of the sensor spectral response function (SRF) on the accuracy of the top of the atmosphere (TOA) Rayleigh-scattering radiance computation, new TOA Rayleigh radiance lookup tables (LUTs) over global oceans and inland waters have been generated. The new Rayleigh LUTs include spectral coverage of 335-2555 nm, all possible solar-sensor geometries, and surface wind speeds of 0-30 m/s. Using the new Rayleigh LUTs, the sensor SRF effect on the accuracy of the TOA Rayleigh radiance computation has been evaluated for spectral bands of the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (SNPP) satellite and the Joint Polar Satellite System (JPSS)-1, showing some important uncertainties for VIIRS-SNPP particularly for large solar- and/or sensor-zenith angles as well as for large Rayleigh optical thicknesses (i.e., short wavelengths) and bands with broad spectral bandwidths. To accurately account for the sensor SRF effect, a new correction algorithm has been developed for VIIRS spectral bands, which improves the TOA Rayleigh radiance accuracy to ~0.01% even for the large solar-zenith angles of 70°-80°, compared with the error of ~0.7% without applying the correction for the VIIRS-SNPP 410 nm band. The same methodology that accounts for the sensor SRF effect on the Rayleigh radiance computation can be used for other satellite sensors. In addition, with the new Rayleigh LUTs, the effect of surface atmospheric pressure variation on the TOA Rayleigh radiance computation can be calculated precisely, and no specific atmospheric pressure correction algorithm is needed. There are some other important applications and advantages to using the new Rayleigh LUTs for satellite remote sensing, including an efficient and accurate TOA Rayleigh radiance computation for hyperspectral satellite remote sensing, detector-based TOA Rayleigh radiance computation, Rayleigh radiance calculations for high altitude

Robust Distributed Kalman Filter for Wireless Sensor Networks with Uncertain Communication Channels

Directory of Open Access Journals (Sweden)

Du Yong Kim

2012-01-01

Full Text Available We address a state estimation problem over a large-scale sensor network with uncertain communication channel. Consensus protocol is usually used to adapt a large-scale sensor network. However, when certain parts of communication channels are broken down, the accuracy performance is seriously degraded. Specifically, outliers in the channel or temporal disconnection are avoided via proposed method for the practical implementation of the distributed estimation over large-scale sensor networks. We handle this practical challenge by using adaptive channel status estimator and robust L1-norm Kalman filter in design of the processor of the individual sensor node. Then, they are incorporated into the consensus algorithm in order to achieve the robust distributed state estimation. The robust property of the proposed algorithm enables the sensor network to selectively weight sensors of normal conditions so that the filter can be practically useful.

Electron beam diagnostic system using computed tomography and an annular sensor

Science.gov (United States)

Elmer, John W.; Teruya, Alan T.

2014-07-29

A system for analyzing an electron beam including a circular electron beam diagnostic sensor adapted to receive the electron beam, the circular electron beam diagnostic sensor having a central axis; an annular sensor structure operatively connected to the circular electron beam diagnostic sensor, wherein the sensor structure receives the electron beam; a system for sweeping the electron beam radially outward from the central axis of the circular electron beam diagnostic sensor to the annular sensor structure wherein the electron beam is intercepted by the annular sensor structure; and a device for measuring the electron beam that is intercepted by the annular sensor structure.

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

Science.gov (United States)

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

2014-01-01

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

Hierarchically Coordinated Power Management for Target Tracking in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Feng Juan

2013-10-01

Full Text Available Energy efficiency is very important for wireless sensor networks (WSNs since sensor nodes have a limited energy supply from a battery. So far, a lot research has focused on this issue, while less emphasis has been placed on the adaptive sleep time for each node with a consideration for the application constraints. In this paper, we propose a hierarchically coordinated power management (HCPM approach, which both addresses the energy conservation problem and reduces the packet forwarding delay for target tracking WSNs based on a virtual-grid-based network structure. We extend the network lifetime by adopting an adaptive sleep scheduling scheme that combines the local power management (PM and the adaptive coordinate PM strategies to schedule the activities of the sensor nodes at the surveillance stage. Furthermore, we propose a hierarchical structure for the tracking stage. Experimental results show that the proposed approach has a greater capability of extending the network lifetime while maintaining a short transmission delay when compared with the protocol which does not consider the application constraints in target tracking sensor networks.

Ocean Sense: Student-Led, Real-Time Research at the Bottom of the Ocean - Without Leaving the Classroom

Science.gov (United States)

Pelz, M.; Hoeberechts, M.; McLean, M. A.; Riddell, D. J.; Ewing, N.; Brown, J. C.

2016-12-01

This presentation outlines the authentic research experiences created by Ocean Networks Canada's Ocean Sense program, a transformative education program that connects students and teachers with place-based, real-time data via the Internet. This program, developed in collaboration with community educators, features student-centric activities, clearly outlined learning outcomes, assessment tools and curriculum aligned content. Ocean Networks Canada (ONC), an initiative of the University of Victoria, develops, operates, and maintains cabled ocean observatory systems. Technologies developed on the world-leading NEPTUNE and VENUS observatories have been adapted for small coastal installations called "community observatories," which enable community members to directly monitor conditions in the local ocean environment. Data from these observatories are fundamental to lessons and activities in the Ocean Sense program. Marketed as Ocean Sense: Local observations, global connections, the program introduces middle and high school students to research methods in biology, oceanography and ocean engineering. It includes a variety of resources and opportunities to excite students and spark curiosity about the ocean environment. The program encourages students to connect their local observations to global ocean processes and the observations of students in other geographic regions. Connection to place and local relevance of the program is enhanced through an emphasis on Indigenous and place-based knowledge. The program promotes of cross-cultural learning with the inclusion of Indigenous knowledge of the ocean. Ocean Sense provides students with an authentic research experience by connecting them to real-time data, often within their own communities. Using the freely accessible data portal, students can curate the data they need from a range of instruments and time periods. Further, students are not restricted to their local community; if their question requires a greater range of

The EuroSITES network: Integrating and enhancing fixed-point open ocean observatories around Europe

Science.gov (United States)

Lampitt, Richard S.; Larkin, Kate E.; EuroSITES Consortium

2010-05-01

EuroSITES is a 3 year (2008-2011) EU collaborative project (3.5MEuro) with the objective to integrate and enhance the nine existing open ocean fixed point observatories around Europe (www.eurosites.info). These observatories are primarily composed of full depth moorings and make multidisciplinary in situ observations within the water column as the European contribution to the global array OceanSITES (www.oceansites.org). In the first 18 months, all 9 observatories have been active and integration has been significant through the maintenance and enhancement of observatory hardware. Highlights include the enhancement of observatories with sensors to measure O2, pCO2, chlorophyll, and nitrate in near real-time from the upper 1000 m. In addition, some seafloor missions are also actively supported. These include seafloor platforms currently deployed in the Mediterranean, one for tsunami detection and one to monitor fluid flow related to seismic activity and slope stability. Upcoming seafloor science missions in 2010 include monitoring benthic biological communities and associated biogeochemistry as indicators of climate change in both the Northeast Atlantic and Mediterranean. EuroSITES also promotes the development of innovative sensors and samplers in order to progress capability to measure climate-relevant properties of the ocean. These include further developing current technologies for autonomous long-term monitoring of oxygen consumption in the mesopelagic, pH and mesozooplankton abundance. Many of these science missions are directly related to complementary activities in other European projects such as EPOCA, HYPOX and ESONET. In 2010 a direct collaboration including in situ field work will take place between ESONET and EuroSITES. The demonstration mission MODOO (funded by ESONET) will be implemented in 2010 at the EuroSITES PAP observatory. Field work will include deployment of a seafloor lander system with various sensors which will send data to shore in real

From silk to satellite: Half a century of ocean colour anomalies in the Northeast Atlantic

KAUST Repository

Raitsos, Dionysios E.

2014-04-23

Changes in phytoplankton dynamics influence marine biogeochemical cycles, climate processes, and food webs, with substantial social and economic consequences. Large-scale estimation of phytoplankton biomass was possible via ocean colour measurements from two remote sensing satellites - the Coastal Zone Colour Scanner (CZCS, 1979-1986) and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS, 1998-2010). Due to the large gap between the two satellite eras and differences in sensor characteristics, comparison of the absolute values retrieved from the two instruments remains challenging. Using a unique in situ ocean colour dataset that spans more than half a century, the two satellite-derived chlorophyll-a (Chl-a) eras are linked to assess concurrent changes in phytoplankton variability and bloom timing over the Northeast Atlantic Ocean and North Sea. Results from this unique re-analysis reflect a clear increasing pattern of Chl-a, a merging of the two seasonal phytoplankton blooms producing a longer growing season and higher seasonal biomass, since the mid-1980s. The broader climate plays a key role in Chl-a variability as the ocean colour anomalies parallel the oscillations of the Northern Hemisphere Temperature (NHT) since 1948. © 2013 John Wiley & Sons Ltd.

From silk to satellite: Half a century of ocean colour anomalies in the Northeast Atlantic

KAUST Repository

Raitsos, Dionysios E.; Pradhan, Yaswant; Lavender, Sam; Hoteit, Ibrahim; McQuatters-Gollop, Abigail L.; Reid, Philip Chris; Richardson, Anthony J.

2014-01-01

Changes in phytoplankton dynamics influence marine biogeochemical cycles, climate processes, and food webs, with substantial social and economic consequences. Large-scale estimation of phytoplankton biomass was possible via ocean colour measurements from two remote sensing satellites - the Coastal Zone Colour Scanner (CZCS, 1979-1986) and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS, 1998-2010). Due to the large gap between the two satellite eras and differences in sensor characteristics, comparison of the absolute values retrieved from the two instruments remains challenging. Using a unique in situ ocean colour dataset that spans more than half a century, the two satellite-derived chlorophyll-a (Chl-a) eras are linked to assess concurrent changes in phytoplankton variability and bloom timing over the Northeast Atlantic Ocean and North Sea. Results from this unique re-analysis reflect a clear increasing pattern of Chl-a, a merging of the two seasonal phytoplankton blooms producing a longer growing season and higher seasonal biomass, since the mid-1980s. The broader climate plays a key role in Chl-a variability as the ocean colour anomalies parallel the oscillations of the Northern Hemisphere Temperature (NHT) since 1948. © 2013 John Wiley & Sons Ltd.

Ocean-Atmosphere Interaction in Climate Changes

Science.gov (United States)

Liu, W. Timothy

1999-01-01

The diagram, which attests the El Nino teleconnection observed by the NASA Scatterometer (NSCAT) in 1997, is an example of the results of our research in air-sea interaction - the core component of our three-part contribution to the Climate Variability Program. We have established an interplay among scientific research, which turns spacebased data into knowledge, a push in instrument technology, which improves observations of climate variability, and an information system, which produces and disseminates new data to support our scientific research. Timothy Liu led the proposal for advanced technology, in response to the NASA Post-2002 Request for Information. The sensor was identified as a possible mission for continuous ocean surface wind measurement at higher spatial resolution, and with the unique capability to measure ocean surface salinity. He is participating in the Instrument Incubator Program to improve the antenna technology, and is initiating a study to integrate the concept on Japanese missions. He and his collaborators have set up a system to produce and disseminate high level (gridded) ocean surface wind/stress data from NSCAT and European missions. The data system is being expanded to produce real-time gridded ocean surface winds from Quikscat, and precipitation and evaporation from the Tropical Rain Measuring Mission. It will form the basis for a spacebased data analysis system which will include momentum, heat and water fluxes. The study on 1997 El Nino teleconnection illustrates our interdisciplinary and multisensor approach to study climate variability. The diagram shows that the collapse of trade wind and the westerly wind anomalies in the central equatorial Pacific led to the equatorial ocean warming. The equatorial wind anomalies are connected to the anomalous cyclonic wind pattern in the northeast Pacific. The anomalous warming along the west coast of the United States is the result of the movement of the pre-existing warm sea surface

Retrieval of sea surface velocities using sequential Ocean Colour Monitor (OCM) data

Digital Repository Service at National Institute of Oceanography (India)

Prasad, J.S.; Rajawat, A.S.; Pradhan, Y.; Chauhan, O.S.; Nayak, S.R.

The Indian remote sensing satellite, IRS-P4 (Oceansat-I) launched on May 26th, 1999 carried two sensors on board, i.e., the Ocean Colour Monitor (OCM) and the Multi-frequency Scanning Microwave Radiometer (MSMR) dedicated for oceanographic research...

An integrative solution for managing, tracing and citing sensor-related information

Science.gov (United States)

Koppe, Roland; Gerchow, Peter; Macario, Ana; Schewe, Ingo; Rehmcke, Steven; Düde, Tobias

2017-04-01

In a data-driven scientific world, the need to capture information on sensors used in the data acquisition process has become increasingly important. Following the recommendations of the Open Geospatial Consortium (OGC), we started by adopting the SensorML standard for describing platforms, devices and sensors. However, it soon became obvious to us that understanding, implementing and filling such standards costs significant effort and cannot be expected from every scientist individually. So we developed a web-based sensor management solution (https://sensor.awi.de) for describing platforms, devices and sensors as hierarchy of systems which supports tracing changes to a system whereas hiding complexity. Each platform contains devices where each device can have sensors associated with specific identifiers, contacts, events, related online resources (e.g. manufacturer factsheets, calibration documentation, data processing documentation), sensor output parameters and geo-location. In order to better understand and address real world requirements, we have closely interacted with field-going scientists in the context of the key national infrastructure project "FRontiers in Arctic marine Monitoring ocean observatory" (FRAM) during the software development. We learned that not only the lineage of observations is crucial for scientists but also alert services using value ranges, flexible output formats and information on data providers (e.g. FTP sources) for example. Mostly important, persistent and citable versions of sensor descriptions are required for traceability and reproducibility allowing seamless integration with existing information systems, e.g. PANGAEA. Within the context of the EU-funded Ocean Data Interoperability Platform project (ODIP II) and in cooperation with 52north we are proving near real-time data via Sensor Observation Services (SOS) along with sensor descriptions based on our sensor management solution. ODIP II also aims to develop a harmonized

Report of the EOS oceans panel to the payload panel

Science.gov (United States)

Abbott, Mark R.; Freilich, Michael H.

1992-11-01

The atmosphere and the ocean are the two great fluids of the earth system. Changes in the coupling of these two fluids will have a profound impact on the Earth's climate and biogeochemical systems. Although changes in atmospheric composition and dynamics are the usual focus of global climate models, it is apparent that the ocean plays a critical role in modulating the magnitude and rate of these changes. The ocean is responsible for nearly half of the poleward heat flux as well as for a significant portion of the uptake of atmospheric carbon dioxide. However, the processes governing the flux of materials and energy between the ocean atmosphere are poorly understood. Such processes include not only physical and chemical dynamics, but also biological processes which act to modify the chemical composition of the ocean as well as the trapping of solar energy as heat in the upper water column. Thus it is essential that the ocean be studied as a complete system of physical, chemical, and biological processes. Overlapping measurements must be made for at least 10-15 years to resolve critical low frequency fluctuations. The present EOS plan relies heavily on non-EOS entities to provide critical data sets for ocean studies. Although such partnerships are usually beneficial, there are risks that must be considered in terms of data coverage, quality, resolution, and availability. A simple replacement of an EOS sensor with a non-EOS sensor based on the fact that they both measure the same quantities will not guarantee that critical measurements will be made to address IPCC priorities in the area of ocean processes. EOS must continue to pursue appropriate methods to ensure that such partner — provided measurements meet scientific requirements. Such methods are analogous to contigencies applied in the area of schedules, cost, and performance for instrument projects. EOS must foster strong ties between US scientists and their foreign counterparts, in order to develop

Impacts of ocean acidification on marine seafood.

Science.gov (United States)

Branch, Trevor A; DeJoseph, Bonnie M; Ray, Liza J; Wagner, Cherie A

2013-03-01

Ocean acidification is a series of chemical reactions due to increased CO(2) emissions. The resulting lower pH impairs the senses of reef fishes and reduces their survival, and might similarly impact commercially targeted fishes that produce most of the seafood eaten by humans. Shelled molluscs will also be negatively affected, whereas cephalopods and crustaceans will remain largely unscathed. Habitat changes will reduce seafood production from coral reefs, but increase production from seagrass and seaweed. Overall effects of ocean acidification on primary productivity and, hence, on food webs will result in hard-to-predict winners and losers. Although adaptation, parental effects, and evolution can mitigate some effects of ocean acidification, future seafood platters will look rather different unless CO(2) emissions are curbed. Copyright © 2012 Elsevier Ltd. All rights reserved.

Novel lineages of Prochlorococcus and Synechococcus in the global oceans.

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Huang, Sijun; Wilhelm, Steven W; Harvey, H Rodger; Taylor, Karen; Jiao, Nianzhi; Chen, Feng

2012-02-01

Picocyanobacteria represented by Prochlorococcus and Synechococcus have an important role in oceanic carbon fixation and nutrient cycling. In this study, we compared the community composition of picocyanobacteria from diverse marine ecosystems ranging from estuary to open oceans, tropical to polar oceans and surface to deep water, based on the sequences of 16S-23S rRNA internal transcribed spacer (ITS). A total of 1339 ITS sequences recovered from 20 samples unveiled diverse and several previously unknown clades of Prochlorococcus and Synechococcus. Six high-light (HL)-adapted Prochlorococcus clades were identified, among which clade HLVI had not been described previously. Prochlorococcus clades HLIII, HLIV and HLV, detected in the Equatorial Pacific samples, could be related to the HNLC clades recently found in the high-nutrient, low-chlorophyll (HNLC), iron-depleted tropical oceans. At least four novel Synechococcus clades (out of six clades in total) in subcluster 5.3 were found in subtropical open oceans and the South China Sea. A niche partitioning with depth was observed in the Synechococcus subcluster 5.3. Members of Synechococcus subcluster 5.2 were dominant in the high-latitude waters (northern Bering Sea and Chukchi Sea), suggesting a possible cold-adaptation of some marine Synechococcus in this subcluster. A distinct shift of the picocyanobacterial community was observed from the Bering Sea to the Chukchi Sea, which reflected the change of water temperature. Our study demonstrates that oceanic systems contain a large pool of diverse picocyanobacteria, and further suggest that new genotypes or ecotypes of picocyanobacteria will continue to emerge, as microbial consortia are explored with advanced sequencing technology.

Responses of the metabolism of the larvae of Pocillopora damicornis to ocean acidification and warming.

Directory of Open Access Journals (Sweden)

Emily B Rivest

Full Text Available Ocean acidification and warming are expected to threaten the persistence of tropical coral reef ecosystems. As coral reefs face multiple stressors, the distribution and abundance of corals will depend on the successful dispersal and settlement of coral larvae under changing environmental conditions. To explore this scenario, we used metabolic rate, at holobiont and molecular levels, as an index for assessing the physiological plasticity of Pocillopora damicornis larvae from this site to conditions of ocean acidity and warming. Larvae were incubated for 6 hours in seawater containing combinations of CO2 concentration (450 and 950 µatm and temperature (28 and 30°C. Rates of larval oxygen consumption were higher at elevated temperatures. In contrast, high CO2 levels elicited depressed metabolic rates, especially for larvae released later in the spawning period. Rates of citrate synthase, a rate-limiting enzyme in aerobic metabolism, suggested a biochemical limit for increasing oxidative capacity in coral larvae in a warming, acidifying ocean. Biological responses were also compared between larvae released from adult colonies on the same day (cohorts. The metabolic physiology of Pocillopora damicornis larvae varied significantly by day of release. Additionally, we used environmental data collected on a reef in Moorea, French Polynesia to provide information about what adult corals and larvae may currently experience in the field. An autonomous pH sensor provided a continuous time series of pH on the natal fringing reef. In February/March, 2011, pH values averaged 8.075 ± 0.023. Our results suggest that without adaptation or acclimatization, only a portion of naïve Pocillopora damicornis larvae may have suitable metabolic phenotypes for maintaining function and fitness in an end-of-the century ocean.

Transgenerational acclimation of fishes to climate change and ocean acidification

OpenAIRE

Munday, Philip L.

2014-01-01

There is growing concern about the impacts of climate change and ocean acidification on marine organisms and ecosystems, yet the potential for acclimation and adaptation to these threats is poorly understood. Whereas many short-term experiments report negative biological effects of ocean warming and acidification, new studies show that some marine species have the capacity to acclimate to warmer and more acidic environments across generations. Consequently, transgenerational plasticity may be...

Vertebrate gravity sensors as dynamic systems

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Ross, M. D.

1985-01-01

This paper considers verterbrate gravity receptors as dynamic sensors. That is, it is hypothesized that gravity is a constant force to which an acceleration-sensing system would readily adapt. Premises are considered in light of the presence of kinocilia on hair cells of vertebrate gravity sensors; differences in loading of the sensors among species; and of possible reduction in loading by inclusion of much organic material in otoconia. Moreover, organic-inorganic interfaces may confer a piezoelectric property upon otoconia, which increase the sensitivity of the sensory system to small accelerations. Comparisons with man-made accelerometers are briefly taken up.

Investigation of the Performance of an Inductive Seawater Conductivity Sensor

Directory of Open Access Journals (Sweden)

WU Sheng

2015-03-01

Full Text Available As one of the factors in marine hydrographic survey, seawater salinity plays an important role in marine scientific research, marine exploitation and military defense. In practical measurement, the salinity is always presented indirectly by seawater conductivity value. Compared with the electrode conductivity sensors, inductive conductivity sensors have an advantage of anti-biofouling, and that is very interested in long term ocean observation device. From the principle point of view, this paper discus the different methods to improve inductive sensor output signal, which is confirmed by the relative experimental results. The basic working system of inductive sensor is described here as well as a calibration in standard seawater. From a wide range of temperature, measurement absolute error and stability are close to those of actual electrode conductivity sensors. Furthermore, in the 1000 meters deep sea experiment, our inductive sensor presents a perfect similarity of conductivity profile like sea- bird sensor, even for some small variations. The performance of our inductive sensor can compete with that of commercially available electrode conductivity sensors.

Euro-Argo: The European contribution to the global Argo ocean observations network

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Gourcuff, Claire

2017-04-01

The international Argo programme is a major element of the global in-situ ocean observing system. More than 3900 floats are now globally measuring temperature and salinity throughout the global oceans, down to 2,000 meters depth and delivering data both in real time for operational users and after careful scientific quality control for climate change research and monitoring. Argo is the single most important in-situ observing system for the Copernicus Marine Service. The Euro-Argo research infrastructure organizes and federates European contribution to Argo. A legal and governance framework (Euro-Argo ERIC) was set up in May 2014; it allows European countries to consolidate and improve their contribution to Argo international. We will provide an overview of the development of Euro-Argo over the past years and present the now agreed Euro-Argo long term organization. The capability of the Euro-Argo infrastructure to organize Argo floats procurement, deployment and processing at European level and to conduct R&D driven by Copernicus needs will be highlighted. During the recent years, within the H2020 E-AIMS project, Euro-Argo carried R&D activities on new Argo floats, equipped with biogeochemical sensors or able to dive up to 4000m, from the floats design up to the analysis of their measurements. European Argo data centers were adapted so that they can handle the new data. Observing System Evaluations and Simulation Experiments were also conducted to provide robust recommendations for the next phase of Argo. One of the main challenges for Euro-Argo is now to implement the next phase of Argo with an extension towards biogeochemistry (e.g. oxygen, biology), the polar oceans, the marginal seas and the deep ocean. Meeting such challenges is essential for the long term sustainability and evolution of the Copernicus Marine Service. We will present Euro-Argo strategy and provide some highlights on the implementation-plan for the years to come and the Argo extensions for the