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Sample records for adaptive sensor optimization

  1. Adaptive Sensor Optimization and Cognitive Image Processing Using Autonomous Optical Neuroprocessors

    Energy Technology Data Exchange (ETDEWEB)

    CAMERON, STEWART M.

    2001-10-01

    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

  2. HEAT Sensor: Harsh Environment Adaptable Thermionic Sensor

    Energy Technology Data Exchange (ETDEWEB)

    Limb, Scott J. [Palo Alto Research Center, Palo Alto, CA (United States)

    2016-05-31

    This document is the final report for the “HARSH ENVIRONMENT ADAPTABLE THERMIONIC SENSOR” project under NETL’s Crosscutting contract DE-FE0013062. This report addresses sensors that can be made with thermionic thin films along with the required high temperature hermetic packaging process. These sensors can be placed in harsh high temperature environments and potentially be wireless and self-powered.

  3. Adaptive reconfigurable distributed sensor architecture

    Science.gov (United States)

    Akey, Mark L.

    1997-07-01

    The infancy of unattended ground based sensors is quickly coming to an end with the arrival of on-board GPS, networking, and multiple sensing capabilities. Unfortunately, their use is only first-order at best: GPS assists with sensor report registration; networks push sensor reports back to the warfighter and forwards control information to the sensors; multispectral sensing is a preset, pre-deployment consideration; and the scalability of large sensor networks is questionable. Current architectures provide little synergy among or within the sensors either before or after deployment, and do not map well to the tactical user's organizational structures and constraints. A new distributed sensor architecture is defined which moves well beyond single sensor, single task architectures. Advantages include: (1) automatic mapping of tactical direction to multiple sensors' tasks; (2) decentralized, distributed management of sensor resources and tasks; (3) software reconfiguration of deployed sensors; (4) network scalability and flexibility to meet the constraints of tactical deployments, and traditional combat organizations and hierarchies; and (5) adaptability to new battlefield communication paradigms such as BADD (Battlefield Analysis and Data Dissemination). The architecture is supported in two areas: a recursive, structural definition of resource configuration and management via loose associations; and a hybridization of intelligent software agents with tele- programming capabilities. The distributed sensor architecture is examined within the context of air-deployed ground sensors with acoustic, communication direction finding, and infra-red capabilities. Advantages and disadvantages of the architecture are examined. Consideration is given to extended sensor life (up to 6 months), post-deployment sensor reconfiguration, limited on- board sensor resources (processor and memory), and bandwidth. It is shown that technical tasking of the sensor suite can be automatically

  4. Optimal sensor placement using machine learning

    CERN Document Server

    Semaan, Richard

    2016-01-01

    A new method for optimal sensor placement based on variable importance of machine learned models is proposed. With its simplicity, adaptivity, and low computational cost, the method offers many advantages over existing approaches. The new method is implemented on an airfoil equipped with a Coanda actuator. The analysis is based on flow field data obtained from 2D unsteady Reynolds averaged Navier-Stokes (URANS) simulations with different actuation conditions. The optimal sensor locations is compared against the current de-facto standard of maximum POD modal amplitude location, and against a brute force approach that scans all possible sensor combinations. The results show that both the flow conditions and the type of sensor have an effect on the optimal sensor placement, whereas the choice of the response function appears to have limited influence.

  5. Adaptive Bacterial Foraging Optimization

    Directory of Open Access Journals (Sweden)

    Hanning Chen

    2011-01-01

    Full Text Available Bacterial Foraging Optimization (BFO is a recently developed nature-inspired optimization algorithm, which is based on the foraging behavior of E. coli bacteria. Up to now, BFO has been applied successfully to some engineering problems due to its simplicity and ease of implementation. However, BFO possesses a poor convergence behavior over complex optimization problems as compared to other nature-inspired optimization techniques. This paper first analyzes how the run-length unit parameter of BFO controls the exploration of the whole search space and the exploitation of the promising areas. Then it presents a variation on the original BFO, called the adaptive bacterial foraging optimization (ABFO, employing the adaptive foraging strategies to improve the performance of the original BFO. This improvement is achieved by enabling the bacterial foraging algorithm to adjust the run-length unit parameter dynamically during algorithm execution in order to balance the exploration/exploitation tradeoff. The experiments compare the performance of two versions of ABFO with the original BFO, the standard particle swarm optimization (PSO and a real-coded genetic algorithm (GA on four widely-used benchmark functions. The proposed ABFO shows a marked improvement in performance over the original BFO and appears to be comparable with the PSO and GA.

  6. Optimal Fusion of Sensors

    DEFF Research Database (Denmark)

    Larsen, Thomas Dall

    within some global frame of reference using a wide variety of sensors providing odometric, inertial and absolute data concerning the robot and its surroundings. Kalman filters have for a long time been widely used to solve this problem. However, when measurements are delayed or the mobile robot...

  7. Desensitized Optimal Filtering and Sensor Fusion Toolkit

    Science.gov (United States)

    Karlgaard, Christopher D.

    2015-01-01

    Analytical Mechanics Associates, Inc., has developed a software toolkit that filters and processes navigational data from multiple sensor sources. A key component of the toolkit is a trajectory optimization technique that reduces the sensitivity of Kalman filters with respect to model parameter uncertainties. The sensor fusion toolkit also integrates recent advances in adaptive Kalman and sigma-point filters for non-Gaussian problems with error statistics. This Phase II effort provides new filtering and sensor fusion techniques in a convenient package that can be used as a stand-alone application for ground support and/or onboard use. Its modular architecture enables ready integration with existing tools. A suite of sensor models and noise distribution as well as Monte Carlo analysis capability are included to enable statistical performance evaluations.

  8. Sensor placement optimization in buildings

    Science.gov (United States)

    Bianco, Simone; Tisato, Francesco

    2012-01-01

    In this work we address the problem of optimal sensor placement for a given region and task. An important issue in designing sensor arrays is the appropriate placement of the sensors such that they achieve a predefined goal. There are many problems that could be considered in the placement of multiple sensors. In this work we focus on the four problems identified by Hörster and Lienhart. To solve these problems, we propose an algorithm based on Direct Search, which is able to approach the global optimal solution within reasonable time and memory consumption. The algorithm is experimentally evaluated and the results are presented on two real floorplans. The experimental results show that our DS algorithm is able to improve the results given by the most performing heuristic introduced in. The algorithm is then extended to work also on continuous solution spaces, and 3D problems.

  9. Optimal sensor configuration for complex systems

    DEFF Research Database (Denmark)

    Sadegh, Payman; Spall, J. C.

    1998-01-01

    Considers the problem of sensor configuration for complex systems. Our approach involves definition of an appropriate optimality criterion or performance measure, and description of an efficient and practical algorithm for achieving the optimality objective. The criterion for optimal sensor...

  10. Adaptive Genetic Algorithm for Sensor Coarse Signal Processing

    Directory of Open Access Journals (Sweden)

    Xuan Huang

    2014-03-01

    Full Text Available As with the development of computer technology and informatization, network technique, sensor technique and communication technology become three necessary components of information industry. As the core technique of sensor application, signal processing mainly determines the sensor performances. For this reason, study on signal processing mode is very important to sensors and the application of sensor network. In this paper, we introduce a new sensor coarse signal processing mode based on adaptive genetic algorithm. This algorithm selects crossover, mutation probability adaptively and compensates multiple operators commutatively to optimize the search process, so that we can obtain the global optimum solution. Based on the proposed algorithm, using auto-correlative characteristic parameter extraction method, it achieves smaller test error in sensor coarse signal processing mode of processing interference signal. We evaluate the proposed approach on a set of data. The experimental results show that, the proposed approach is able to improve the performance in different experimental setting

  11. Sensor Activation and Radius Adaptation (SARA) in Heterogeneous Sensor Networks

    CERN Document Server

    Bartolini, Novella; la Porta, Thomas; Petrioli, Chiara; Silvestri, Simone

    2010-01-01

    In this paper we address the problem of prolonging the lifetime of wireless sensor networks (WSNs) deployed to monitor an area of interest. In this scenario, a helpful approach is to reduce coverage redundancy and therefore the energy expenditure due to coverage. We introduce the first algorithm which reduces coverage redundancy by means of Sensor Activation and sensing Radius Adaptation (SARA)in a general applicative scenario with two classes of devices: sensors that can adapt their sensing range (adjustable sensors) and sensors that cannot (fixed sensors). In particular, SARA activates only a subset of all the available sensors and reduces the sensing range of the adjustable sensors that have been activated. In doing so, SARA also takes possible heterogeneous coverage capabilities of sensors belonging to the same class into account. It specifically addresses device heterogeneity by modeling the coverage problem in the Laguerre geometry through Voronoi-Laguerre diagrams. SARA executes quickly and is guarante...

  12. On Adaptive Optimal Input Design

    NARCIS (Netherlands)

    Stigter, J.D.; Vries, D.; Keesman, K.J.

    2003-01-01

    The problem of optimal input design (OID) for a fed-batch bioreactor case study is solved recursively. Here an adaptive receding horizon optimal control problem, involving the so-called E-criterion, is solved on-line, using the current estimate of the parameter vector at each sample instant {tk, k =

  13. ENERGY OPTIMIZATION IN CLUSTER BASED WIRELESS SENSOR NETWORKS

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    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.

  14. Topology Optimization for Energy Management in Underwater Sensor Networks

    Science.gov (United States)

    2015-02-01

    1 To appear in International Journal of Control as a regular paper Topology Optimization for Energy Management in Underwater Sensor Networks⋆ Devesh... topology that maximizes the probability of successful search (of a target) over a surveillance region. In a two-stage optimization, a genetic algorithm (GA...Adaptation to energy variations across the network is shown to be manifested as a change in the optimal network topology by using sensing and

  15. Adaptive scalarization methods in multiobjective optimization

    CERN Document Server

    Eichfelder, Gabriele

    2008-01-01

    This book presents adaptive solution methods for multiobjective optimization problems based on parameter dependent scalarization approaches. Readers will benefit from the new adaptive methods and ideas for solving multiobjective optimization.

  16. Optimal decision fusion given sensor rules

    Institute of Scientific and Technical Information of China (English)

    Yunmin ZHU; Xiaorong LI

    2005-01-01

    When all the rules of sensor decision are known,the optimal distributed decision fusion,which relies only on the joint conditional probability densities,can be derived for very general decision systems.They include those systems with interdependent sensor observations and any network structure.It is also valid for m-ary Bayesian decision problems and binary problems under the Neyman-Pearson criterion.Local decision rules of a sensor with communication from other sensors that are optimal for the sensor itself are also presented,which take the form of a generalized likelihood ratio test.Numerical examples are given to reveal some interesting phenomena that communication between sensors can improve performance of a senor decision,but cannot guarantee to improve the global fusion performance when sensor rules were given before fusing.

  17. Efficient Sensor Placement Optimization Using Gradient Descent and Probabilistic Coverage

    Directory of Open Access Journals (Sweden)

    Vahab Akbarzadeh

    2014-08-01

    Full Text Available We are proposing an adaptation of the gradient descent method to optimize the position and orientation of sensors for the sensor placement problem. The novelty of the proposed method lies in the combination of gradient descent optimization with a realistic model, which considers both the topography of the environment and a set of sensors with directional probabilistic sensing. The performance of this approach is compared with two other black box optimization methods over area coverage and processing time. Results show that our proposed method produces competitive results on smaller maps and superior results on larger maps, while requiring much less computation than the other optimization methods to which it has been compared.

  18. Optimization of wireless sensor communication channel based on adaptive noise cancellation%基于自适应噪声抵消的无线传感网络信道优化

    Institute of Scientific and Technical Information of China (English)

    龙清; 胡光波

    2016-01-01

    Wireless sensor network communication technology is widely applied in the field of Internet of things near field communication, underwater acoustic communication. The wireless sensor network communication channel often encounter the multi⁃path interference, which lead to an imbalance of channel. Based on the aboved, the paper develops the channel equalization model design. Proposed a wireless sensor communication channel based on adaptive noise cancellation optimization technique. Firstly, build the channel model of wireless sensor network communication. The wireless sensor network communication channel in the process of decay signal loss and various paths of the reorganization, the adaptive noise cancellation algorithm for channel multipath interference filter, combined with the least square ( RLS) criterion algorithm for wireless sensor communications channel equalization design. Simulation results show that using the communication channel equalization technique can effectively improve the quality of the wireless sensor network communication channel, reduce the communication transmission distortion and bit error rate, realize the adaptive channel equalization, therefore improve the anti⁃interference ability of communication.%无线传感器网络通信技术广泛应用在物联网近场通信、水声通信等领域。无线传感网络通信信道受到多途干扰,导致信道失衡,需要进行信道均衡模型设计。提出一种基于自适应噪声抵消的无线传感器网络通信信道优化技术,首先构建了无线传感器网络通信的信道模型,对无线传感器网络信道传播过程中衰减损失和各条路径的信号进行重组,采用自适应噪声抵消算法进行信道的多途干扰滤波,结合最小二乘( RLS)准则算法进行无线传感器网络通信信道均衡设计。仿真结果表明,采用该通信信道均衡技术能有效提高无线传感器网络通信的信道质量,降低通信传

  19. Topology Optimization for Urban Traffic Sensor Network

    Institute of Scientific and Technical Information of China (English)

    HU Jianming; SONG Jingyan; ZHANG Mingchen; KANG Xiaojing

    2008-01-01

    This paper presents an optimized topology for urban traffic sensor networks. Small world theory is used to improve the performance of the wireless communication system with a heterogeneous transmission model and an optimal transmission radius. Furthermore, a series of simulations based on the actual road network around the 2nd Ring Road in Beijing demonstrate the practicability of constructing artificial "small worlds". Moreover, the particle swarm optimization method is used to calculate the globally best distribution of the nodes with the large radius. The methods proposed in this paper will be helpful to the sensor nodes deployment of the new urban traffic sensor networks.

  20. 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.

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

    Science.gov (United States)

    Buchhold, Niels; Baumgartner, Christian

    2017-01-27

    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.

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

    Science.gov (United States)

    Buchhold, Niels; Baumgartner, Christian

    2017-01-01

    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. PMID:28134824

  3. Robust Optimal Adaptive Control Method with Large Adaptive Gain

    Science.gov (United States)

    Nguyen, Nhan T.

    2009-01-01

    In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly. However, a large adaptive gain can lead to high-frequency oscillations which can adversely affect robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient stability robustness. Simulations were conducted for a damaged generic transport aircraft with both standard adaptive control and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model while maintaining a sufficient time delay margin.

  4. Optimization of metal-clad waveguide sensors

    DEFF Research Database (Denmark)

    Skivesen, N.; Horvath, R.; Pedersen, H.C.

    2005-01-01

    The present paper deals with the optimization of metal-clad waveguides for sensor applications to achieve high sensitivity for adlayer and refractive index measurements. By using the Fresnel reflection coefficients both the angular shift and the width of the resonances in the sensorgrams are taken...... into account. Our optimization shows that it is possible for metal-clad waveguides to achieve a sensitivity improvement of 600% compared to surface-plasmon-resonance sensors....

  5. Design of Real-time Communication Adapter for Different Protocol Sensors in Sensor Web

    Directory of Open Access Journals (Sweden)

    Longlong Lu

    2012-09-01

    Full Text Available A real-time communication adapter named SensorAdapter is designed to communicate between different protocols sensors and data service layer in Sensor Web. The adapter is extended and restructured based on SensorBus, an open source project raised by a German company called 52north. By structuring the receiving module and extending the proxies of sensors according to the communication protocols the sensors use, the adapter can receive sensing information detected by different protocols sensors simultaneously. The receiving module identifies a sensor and finds its corresponding proxy in SensorAdapter by sensor ID (SensorID, and then packages the sensing information to XMPP messages and sends them to XMPPServer by invoking the methods in its proxy. At last, an example of SOS is achieved to verify the effect of the adapter.

  6. Adaptive computational resource allocation for sensor networks

    Institute of Scientific and Technical Information of China (English)

    WANG Dian-hong; FEI E; YAN Yu-jie

    2008-01-01

    To efficiently utilize the limited computational resource in real-time sensor networks, this paper focu-ses on the challenge of computational resource allocation in sensor networks and provides a solution with the method of economies. It designs a mieroeconomic system in which the applications distribute their computational resource consumption across sensor networks by virtue of mobile agent. Further, it proposes the market-based computational resource allocation policy named MCRA which satisfies the uniform consumption of computational energy in network and the optimal division of the single computational capacity for multiple tasks. The simula-tion in the scenario of target tracing demonstrates that MCRA realizes an efficient allocation of computational re-sources according to the priority of tasks, achieves the superior allocation performance and equilibrium perform-ance compared to traditional allocation policies, and ultimately prolongs the system lifetime.

  7. Optimal Energy Aware Clustering in Sensor Networks

    Directory of Open Access Journals (Sweden)

    Majid Sarrafzadeh

    2002-07-01

    Full Text Available Sensor networks is among the fastest growing technologies that have the potential of changing our lives drastically. These collaborative, dynamic and distributed computing and communicating systems will be self organizing. They will have capabilities of distributing a task among themselves for efficient computation. There are many challenges in implementation of such systems: energy dissipation and clustering being one of them. In order to maintain a certain degree of service quality and a reasonable system lifetime, energy needs to be optimized at every stage of system operation. Sensor node clustering is another very important optimization problem. Nodes that are clustered together will easily be able to communicate with each other. Considering energy as an optimization parameter while clustering is imperative. In this paper we study the theoretical aspects of the clustering problem in sensor networks with application to energy optimization. We illustrate an optimal algorithm for clustering the sensor nodes such that each cluster (which has a master is balanced and the total distance between sensor nodes and master nodes is minimized. Balancing the clusters is needed for evenly distributing the load on all master nodes. Minimizing the total distance helps in reducing the communication overhead and hence the energy dissipation. This problem (which we call balanced k-clustering is modeled as a mincost flow problem which can be solved optimally using existing techniques.

  8. Optimization of Sensor Monitoring Strategies for Emissions

    Science.gov (United States)

    Klise, K. A.; Laird, C. D.; Downey, N.; Baker Hebert, L.; Blewitt, D.; Smith, G. R.

    2016-12-01

    Continuous or regularly scheduled monitoring has the potential to quickly identify changes in air quality. However, even with low-cost sensors, only a limited number of sensors can be placed to monitor airborne pollutants. The physical placement of these sensors and the sensor technology used can have a large impact on the performance of a monitoring strategy. Furthermore, sensors can be placed for different objectives, including maximum coverage, minimum time to detection or exposure, or to quantify emissions. Different objectives may require different monitoring strategies, which need to be evaluated by stakeholders before sensors are placed in the field. In this presentation, we outline methods to enhance ambient detection programs through optimal design of the monitoring strategy. These methods integrate atmospheric transport models with sensor characteristics, including fixed and mobile sensors, sensor cost and failure rate. The methods use site specific pre-computed scenarios which capture differences in meteorology, terrain, concentration averaging times, gas concentration, and emission characteristics. The pre-computed scenarios become input to a mixed-integer, stochastic programming problem that solves for sensor locations and types that maximize the effectiveness of the detection program. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

  9. Energy optimization in mobile sensor networks

    Science.gov (United States)

    Yu, Shengwei

    Mobile sensor networks are considered to consist of a network of mobile robots, each of which has computation, communication and sensing capabilities. Energy efficiency is a critical issue in mobile sensor networks, especially when mobility (i.e., locomotion control), routing (i.e., communications) and sensing are unique characteristics of mobile robots for energy optimization. This thesis focuses on the problem of energy optimization of mobile robotic sensor networks, and the research results can be extended to energy optimization of a network of mobile robots that monitors the environment, or a team of mobile robots that transports materials from stations to stations in a manufacturing environment. On the energy optimization of mobile robotic sensor networks, our research focuses on the investigation and development of distributed optimization algorithms to exploit the mobility of robotic sensor nodes for network lifetime maximization. In particular, the thesis studies these five problems: 1. Network-lifetime maximization by controlling positions of networked mobile sensor robots based on local information with distributed optimization algorithms; 2. Lifetime maximization of mobile sensor networks with energy harvesting modules; 3. Lifetime maximization using joint design of mobility and routing; 4. Optimal control for network energy minimization; 5. Network lifetime maximization in mobile visual sensor networks. In addressing the first problem, we consider only the mobility strategies of the robotic relay nodes in a mobile sensor network in order to maximize its network lifetime. By using variable substitutions, the original problem is converted into a convex problem, and a variant of the sub-gradient method for saddle-point computation is developed for solving this problem. An optimal solution is obtained by the method. Computer simulations show that mobility of robotic sensors can significantly prolong the lifetime of the whole robotic sensor network while

  10. Phase sensor for solar adaptive-optics

    CERN Document Server

    Kellerer, Aglae

    2011-01-01

    Wavefront sensing in solar adaptive-optics is currently done with correlating Shack-Hartmann sensors, although the spatial- and temporal-resolutions of the phase measurements are then limited by the extremely fast computing required to correlate the sensor signals at the frequencies of daytime atmospheric-fluctuations. To avoid this limitation, a new wavefront-sensing technique is presented, that makes use of the solar brightness and is applicable to extended sources. The wavefront is sent through a modified Mach-Zehnder interferometer. A small, central part of the wavefront is used as reference and is made to interfere with the rest of the wavefront. The contrast of two simultaneously measured interference-patterns provides a direct estimate of the wavefront phase, no additional computation being required. The proposed optical layout shows precise initial alignment to be the critical point in implementing the new wavefront-sensing scheme.

  11. Tier-scalable reconnaissance: the challenge of sensor optimization, sensor deployment, sensor fusion, and sensor interoperability

    Science.gov (United States)

    Fink, Wolfgang; George, Thomas; Tarbell, Mark A.

    2007-04-01

    Robotic reconnaissance operations are called for in extreme environments, not only those such as space, including planetary atmospheres, surfaces, and subsurfaces, but also in potentially hazardous or inaccessible operational areas on Earth, such as mine fields, battlefield environments, enemy occupied territories, terrorist infiltrated environments, or areas that have been exposed to biochemical agents or radiation. Real time reconnaissance enables the identification and characterization of transient events. A fundamentally new mission concept for tier-scalable reconnaissance of operational areas, originated by Fink et al., is aimed at replacing the engineering and safety constrained mission designs of the past. The tier-scalable paradigm integrates multi-tier (orbit atmosphere surface/subsurface) and multi-agent (satellite UAV/blimp surface/subsurface sensing platforms) hierarchical mission architectures, introducing not only mission redundancy and safety, but also enabling and optimizing intelligent, less constrained, and distributed reconnaissance in real time. Given the mass, size, and power constraints faced by such a multi-platform approach, this is an ideal application scenario for a diverse set of MEMS sensors. To support such mission architectures, a high degree of operational autonomy is required. Essential elements of such operational autonomy are: (1) automatic mapping of an operational area from different vantage points (including vehicle health monitoring); (2) automatic feature extraction and target/region-of-interest identification within the mapped operational area; and (3) automatic target prioritization for close-up examination. These requirements imply the optimal deployment of MEMS sensors and sensor platforms, sensor fusion, and sensor interoperability.

  12. Adaptive Uncertainty Resolution in Bayesian Combinatorial Optimization Problems

    CERN Document Server

    Guha, Sudipto

    2008-01-01

    In several applications such as databases, planning, and sensor networks, parameters such as selectivity, load, or sensed values are known only with some associated uncertainty. The performance of such a system (as captured by some objective function over the parameters) is significantly improved if some of these parameters can be probed or observed. In a resource constrained situation, deciding which parameters to observe in order to optimize system performance itself becomes an interesting and important optimization problem. This general problem is the focus of this paper. One of the most important considerations in this framework is whether adaptivity is required for the observations. Adaptive observations introduce blocking or sequential operations in the system whereas non-adaptive observations can be performed in parallel. One of the important questions in this regard is to characterize the benefit of adaptivity for probes and observation. We present general techniques for designing constant factor appr...

  13. Wavefront sensors for adaptive optical systems

    Science.gov (United States)

    Lukin, V. P.; Botygina, N. N.; Emaleev, O. N.; Konyaev, P. A.

    2010-10-01

    A high precision Shack-Hartmann wavefront (WF) sensor has been developed on the basis of a low-aperture off-axis diffraction lens array. The device is capable of measuring WF slopes at array sub-apertures of size 640x640 μm with an error not exceeding 4.80 arcsec (0.15 pixel), which corresponds to the standard deviation equal to 0.017λ at the reconstructed WF with wavelength λ . Also the modification of this sensor for adaptive system of solar telescope using extended scenes as tracking objects, such as sunspot, pores, solar granulation and limb, is presented. The software package developed for the proposed WF sensors includes three algorithms of local WF slopes estimation (modified centroids, normalized cross-correlation and fast Fourier-demodulation), as well as three methods of WF reconstruction (modal Zernike polynomials expansion, deformable mirror response functions expansion and phase unwrapping), that can be selected during operation with accordance to the application.

  14. Optimizing Retransmission Threshold in Wireless Sensor Networks.

    Science.gov (United States)

    Bi, Ran; Li, Yingshu; Tan, Guozhen; Sun, Liang

    2016-05-10

    The retransmission threshold in wireless sensor networks is critical to the latency of data delivery in the networks. However, existing works on data transmission in sensor networks did not consider the optimization of the retransmission threshold, and they simply set the same retransmission threshold for all sensor nodes in advance. The method did not take link quality and delay requirement into account, which decreases the probability of a packet passing its delivery path within a given deadline. This paper investigates the problem of finding optimal retransmission thresholds for relay nodes along a delivery path in a sensor network. The object of optimizing retransmission thresholds is to maximize the summation of the probability of the packet being successfully delivered to the next relay node or destination node in time. A dynamic programming-based distributed algorithm for finding optimal retransmission thresholds for relay nodes along a delivery path in the sensor network is proposed. The time complexity is O n Δ · max 1 ≤ i ≤ n { u i } , where u i is the given upper bound of the retransmission threshold of sensor node i in a given delivery path, n is the length of the delivery path and Δ is the given upper bound of the transmission delay of the delivery path. If Δ is greater than the polynomial, to reduce the time complexity, a linear programming-based ( 1 + p m i n ) -approximation algorithm is proposed. Furthermore, when the ranges of the upper and lower bounds of retransmission thresholds are big enough, a Lagrange multiplier-based distributed O ( 1 ) -approximation algorithm with time complexity O ( 1 ) is proposed. Experimental results show that the proposed algorithms have better performance.

  15. Adaptive and mobile ground sensor array.

    Energy Technology Data Exchange (ETDEWEB)

    Holzrichter, Michael Warren; O' Rourke, William T.; Zenner, Jennifer; Maish, Alexander B.

    2003-12-01

    The goal of this LDRD was to demonstrate the use of robotic vehicles for deploying and autonomously reconfiguring seismic and acoustic sensor arrays with high (centimeter) accuracy to obtain enhancement of our capability to locate and characterize remote targets. The capability to accurately place sensors and then retrieve and reconfigure them allows sensors to be placed in phased arrays in an initial monitoring configuration and then to be reconfigured in an array tuned to the specific frequencies and directions of the selected target. This report reviews the findings and accomplishments achieved during this three-year project. This project successfully demonstrated autonomous deployment and retrieval of a payload package with an accuracy of a few centimeters using differential global positioning system (GPS) signals. It developed an autonomous, multisensor, temporally aligned, radio-frequency communication and signal processing capability, and an array optimization algorithm, which was implemented on a digital signal processor (DSP). Additionally, the project converted the existing single-threaded, monolithic robotic vehicle control code into a multi-threaded, modular control architecture that enhances the reuse of control code in future projects.

  16. Tele-Supervised Adaptive Ocean Sensor Fleet

    Science.gov (United States)

    Lefes, Alberto; Podnar, Gregg W.; Dolan, John M.; Hosler, Jeffrey C.; Ames, Troy J.

    2009-01-01

    The Tele-supervised Adaptive Ocean Sensor Fleet (TAOSF) is a multi-robot science exploration architecture and system that uses a group of robotic boats (the Ocean-Atmosphere Sensor Integration System, or OASIS) to enable in-situ study of ocean surface and subsurface characteristics and the dynamics of such ocean phenomena as coastal pollutants, oil spills, hurricanes, or harmful algal blooms (HABs). The OASIS boats are extended- deployment, autonomous ocean surface vehicles. The TAOSF architecture provides an integrated approach to multi-vehicle coordination and sliding human-vehicle autonomy. One feature of TAOSF is the adaptive re-planning of the activities of the OASIS vessels based on sensor input ( smart sensing) and sensorial coordination among multiple assets. The architecture also incorporates Web-based communications that permit control of the assets over long distances and the sharing of data with remote experts. Autonomous hazard and assistance detection allows the automatic identification of hazards that require human intervention to ensure the safety and integrity of the robotic vehicles, or of science data that require human interpretation and response. Also, the architecture is designed for science analysis of acquired data in order to perform an initial onboard assessment of the presence of specific science signatures of immediate interest. TAOSF integrates and extends five subsystems developed by the participating institutions: Emergent Space Tech - nol ogies, Wallops Flight Facility, NASA s Goddard Space Flight Center (GSFC), Carnegie Mellon University, and Jet Propulsion Laboratory (JPL). The OASIS Autonomous Surface Vehicle (ASV) system, which includes the vessels as well as the land-based control and communications infrastructure developed for them, controls the hardware of each platform (sensors, actuators, etc.), and also provides a low-level waypoint navigation capability. The Multi-Platform Simulation Environment from GSFC is a surrogate

  17. Almost optimal adaptive LQ control: SISO case

    NARCIS (Netherlands)

    Polderman, Jan W.; Daams, Jasper

    2002-01-01

    In this paper an almost optimal indirect adaptive controller for input/output dynamical systems is proposed. The control part of the adaptive control scheme is based on a modified LQ control law: by adding a time-varying gain to the certainty equivalent control law the conflict between

  18. Dynamic optimization and adaptive controller design

    Science.gov (United States)

    Inamdar, S. R.

    2010-10-01

    In this work I present a new type of controller which is an adaptive tracking controller which employs dynamic optimization for optimizing current value of controller action for the temperature control of nonisothermal continuously stirred tank reactor (CSTR). We begin with a two-state model of nonisothermal CSTR which are mass and heat balance equations and then add cooling system dynamics to eliminate input multiplicity. The initial design value is obtained using local stability of steady states where approach temperature for cooling action is specified as a steady state and a design specification. Later we make a correction in the dynamics where material balance is manipulated to use feed concentration as a system parameter as an adaptive control measure in order to avoid actuator saturation for the main control loop. The analysis leading to design of dynamic optimization based parameter adaptive controller is presented. The important component of this mathematical framework is reference trajectory generation to form an adaptive control measure.

  19. Adaptive Submodular Optimization under Matroid Constraints

    CERN Document Server

    Golovin, Daniel

    2011-01-01

    Many important problems in discrete optimization require maximization of a monotonic submodular function subject to matroid constraints. For these problems, a simple greedy algorithm is guaranteed to obtain near-optimal solutions. In this article, we extend this classic result to a general class of adaptive optimization problems under partial observability, where each choice can depend on observations resulting from past choices. Specifically, we prove that a natural adaptive greedy algorithm provides a $1/(p+1)$ approximation for the problem of maximizing an adaptive monotone submodular function subject to $p$ matroid constraints, and more generally over arbitrary $p$-independence systems. We illustrate the usefulness of our result on a complex adaptive match-making application.

  20. Optimal Hops-Based Adaptive Clustering Algorithm

    Science.gov (United States)

    Xuan, Xin; Chen, Jian; Zhen, Shanshan; Kuo, Yonghong

    This paper proposes an optimal hops-based adaptive clustering algorithm (OHACA). The algorithm sets an energy selection threshold before the cluster forms so that the nodes with less energy are more likely to go to sleep immediately. In setup phase, OHACA introduces an adaptive mechanism to adjust cluster head and load balance. And the optimal distance theory is applied to discover the practical optimal routing path to minimize the total energy for transmission. Simulation results show that OHACA prolongs the life of network, improves utilizing rate and transmits more data because of energy balance.

  1. Adaptive and controllable compliant systems with embedded actuators and sensors

    Science.gov (United States)

    Trease, Brian; Kota, Sridhar

    2007-04-01

    We present a framework for the design of a compliant system; i.e. the concurrent design of a compliant mechanism with embedded actuators and embedded sensors. Our methods simultaneously synthesize optimal structural topology and placement of actuators and sensors for maximum energy efficiency and adaptive performance, while satisfying various weight and performance constraints. The goal of this research is to lay an algorithmic framework for distributed actuation and sensing within a compliant active structure. Key features of the methodology include (1) the simultaneous optimization of the location, orientation, and size of actuators concurrent with the compliant transmission topology and (2) the concepts of controllability and observability that arise from the consideration of control, and their implementation in compliant systems design. The methods used include genetic algorithms, graph searches for connectivity, and multiple load cases implemented with linear finite element analysis. Actuators, modeled as both force generators and structural compliant elements, are included as topology variables in the optimization. Results are provided for several studies, including: (1) concurrent actuator placement and topology design for a compliant amplifier and (2) a shape-morphing aircraft wing demonstration with three controlled output nodes. Central to this method is the concept of structural orthogonality, which refers to the unique system response for each actuator it contains. Finally, the results from the controllability problem are used to motivate and describe the analogous extension to observability for sensing.

  2. System Dynamics and Adaptive Control for MEMS Gyroscope Sensor

    OpenAIRE

    Juntao Fei; Hongfei Ding

    2010-01-01

    This paper presents an adaptive control approach for Micro-Electro-Mechanical Systems (MEMS) z-axis gyroscope sensor. The dynamical model of MEMS gyroscope sensor is derived and adaptive state tracking control for MEMS gyroscope is developed. The proposed adaptive control approaches can estimate the angular velocity and the damping and stiffness coefficients including the coupling terms due to the fabrication imperfection. The stability of the closed-loop systems is established with the propo...

  3. System Dynamics and Adaptive Control for MEMS Gyroscope Sensor

    OpenAIRE

    Juntao Fei; Hongfei Ding

    2011-01-01

    This paper presents an adaptive control approach for Micro-Electro-Mechanical Systems (MEMS) z-axis gyroscope sensor. The dynamical model of MEMS gyroscope sensor is derived and adaptive state tracking control for MEMS gyroscope is developed. The proposed adaptive control approaches can estimate the angular velocity and the damping and stiffness coefficients including the coupling terms due to the fabrication imperfection. The stability of the closed-loop systems is established with the propo...

  4. 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.

  5. Adaptive Sensor Activity Scheduling in Distributed Sensor Networks: A Statistical Mechanics Approach

    OpenAIRE

    Abhishek Srivastav; Asok Ray; Shashi Phoha

    2009-01-01

    This article presents an algorithm for adaptive sensor activity scheduling (A-SAS) in distributed sensor networks to enable detection and dynamic footprint tracking of spatial-temporal events. The sensor network is modeled as a Markov random field on a graph, where concepts of Statistical Mechanics are employed to stochastically activate the sensor nodes. Using an Ising-like formulation, the sleep and wake modes of a sensor node are modeled as spins with ferromagnetic neighborhood interaction...

  6. Adaptive cuckoo search algorithm for unconstrained optimization.

    Science.gov (United States)

    Ong, Pauline

    2014-01-01

    Modification of the intensification and diversification approaches in the recently developed cuckoo search algorithm (CSA) is performed. The alteration involves the implementation of adaptive step size adjustment strategy, and thus enabling faster convergence to the global optimal solutions. The feasibility of the proposed algorithm is validated against benchmark optimization functions, where the obtained results demonstrate a marked improvement over the standard CSA, in all the cases.

  7. Optimization of wireless Bluetooth sensor systems.

    Science.gov (United States)

    Lonnblad, J; Castano, J; Ekstrom, M; Linden, M; Backlund, Y

    2004-01-01

    Within this study, three different Bluetooth sensor systems, replacing cables for transmission of biomedical sensor data, have been designed and evaluated. The three sensor architectures are built on 1-, 2- and 3-chip solutions and depending on the monitoring situation and signal character, different solutions are optimal. Essential parameters for all systems have been low physical weight and small size, resistance to interference and interoperability with other technologies as global- or local networks, PC's and mobile phones. Two different biomedical input signals, ECG and PPG (photoplethysmography), have been used to evaluate the three solutions. The study shows that it is possibly to continuously transmit an analogue signal. At low sampling rates and slowly varying parameters, as monitoring the heart rate with PPG, the 1-chip solution is the most suitable, offering low power consumption and thus a longer battery lifetime or a smaller battery, minimizing the weight of the sensor system. On the other hand, when a higher sampling rate is required, as an ECG, the 3-chip architecture, with a FPGA or micro-controller, offers the best solution and performance. Our conclusion is that Bluetooth might be useful in replacing cables of medical monitoring systems.

  8. 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

  9. Particle Swarm Optimization with Adaptive Mutation

    Institute of Scientific and Technical Information of China (English)

    LU Zhen-su; HOU Zhi-rong; DU Juan

    2006-01-01

    A new adaptive mutation particle swarm optimizer,which is based on the variance of the population's fitness,is presented in this paper.During the rtmning time,the mutation probability for the current best particle is determined by two factors:the variance of the population's fitness and the current optimal solution.The ability of particle swarm optimization (PSO) algorithm to break away from the local optimum is greatly improved by the mutation.The experimental results show that the new algorithm not only has great advantage of convergence property over genetic algorithm and PSO,but can also avoid the premature convergence problem effectively.

  10. A Novel Adaptive Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Xiaobing Yu

    2012-07-01

    Full Text Available Particle swarm optimization (PSO is a stochastic search technique for solving optimization problems, which has been proven to be efficient and effective in wide applications. However, the PSO can easily fly into the local optima and lack the ability to jump out of the local optima. A novel adaptive PSO is proposed by evaluating convergence of the fitness value. The novel mechanism is to ensure the diversity of particles. Simulations for benchmark test functions have illustrated that the proposed algorithm possesses better ability to find the global optima than other variants and is an effective global optimization tool.

  11. An asymptotically optimal nonparametric adaptive controller

    Institute of Scientific and Technical Information of China (English)

    郭雷; 谢亮亮

    2000-01-01

    For discrete-time nonlinear stochastic systems with unknown nonparametric structure, a kernel estimation-based nonparametric adaptive controller is constructed based on truncated certainty equivalence principle. Global stability and asymptotic optimality of the closed-loop systems are established without resorting to any external excitations.

  12. Instance Optimality of the Adaptive Maximum Strategy

    NARCIS (Netherlands)

    L. Diening; C. Kreuzer; R. Stevenson

    2016-01-01

    In this paper, we prove that the standard adaptive finite element method with a (modified) maximum marking strategy is instance optimal for the total error, being the square root of the squared energy error plus the squared oscillation. This result will be derived in the model setting of Poisson’s e

  13. An adaptive technique for a redundant-sensor navigation system.

    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. This adaptive system is structured as a multistage stochastic process of detection, identification, and compensation. It is shown that the detection system can be effectively constructed on the basis of a design value, specified by mission requirements, of the unknown parameter in the actual system, and of a degradation mode in the form of a constant bias jump. A suboptimal detection system on the basis of Wald's sequential analysis is developed using the concept of information value and information feedback. The developed system is easily implemented, and demonstrates a performance remarkably close to that of the optimal nonlinear detection system. An invariant transformation is derived to eliminate the effect of nuisance parameters such that the ambiguous identification system can be reduced to a set of disjoint simple hypotheses tests. By application of a technique of decoupled bias estimation in the compensation system the adaptive system can be operated without any complicated reorganization.

  14. Adaptive finite element method for shape optimization

    KAUST Repository

    Morin, Pedro

    2012-01-16

    We examine shape optimization problems in the context of inexact sequential quadratic programming. Inexactness is a consequence of using adaptive finite element methods (AFEM) to approximate the state and adjoint equations (via the dual weighted residual method), update the boundary, and compute the geometric functional. We present a novel algorithm that equidistributes the errors due to shape optimization and discretization, thereby leading to coarse resolution in the early stages and fine resolution upon convergence, and thus optimizing the computational effort. We discuss the ability of the algorithm to detect whether or not geometric singularities such as corners are genuine to the problem or simply due to lack of resolution - a new paradigm in adaptivity. © EDP Sciences, SMAI, 2012.

  15. System Dynamics and Adaptive Control for MEMS Gyroscope Sensor

    Directory of Open Access Journals (Sweden)

    Juntao Fei

    2011-01-01

    Full Text Available This paper presents an adaptive control approach for Micro-Electro-Mechanical Systems (MEMS z-axis gyroscope sensor. The dynamical model of MEMS gyroscope sensor is derived and adaptive state tracking control for MEMS gyroscope is developed. The proposed adaptive control approaches can estimate the angular velocity and the damping and stiffness coefficients including the coupling terms due to the fabrication imperfection. The stability of the closed-loop systems is established with the proposed adaptive control strategy. Numerical simulation is investigated to verify the effectiveness of the proposed control scheme.

  16. Signal coupling to embedded pitch adapters in silicon sensors

    CERN Document Server

    Artuso, Marina; Bezshyiko, Iaroslava; Blusk, Steven R.; Brundler Denzer, Ruth; Bugiel, Szymon; Dasgupta, Roma; Dendek, Adam Mateusz; Dey, Biplab; Ely, Scott Edward; Lionetto, Federica; Petruzzo, Marco; Polyakov, Ivan; Rudolph, Matthew Scott; Schindler, Heinrich; Steinkamp, Olaf; Stone, Sheldon

    2017-01-01

    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.

  17. Adaptive stimulus optimization for sensory systems neuroscience.

    Science.gov (United States)

    DiMattina, Christopher; Zhang, Kechen

    2013-01-01

    In this paper, we review several lines of recent work aimed at developing practical methods for adaptive on-line stimulus generation for sensory neurophysiology. We consider various experimental paradigms where on-line stimulus optimization is utilized, including the classical optimal stimulus paradigm where the goal of experiments is to identify a stimulus which maximizes neural responses, the iso-response paradigm which finds sets of stimuli giving rise to constant responses, and the system identification paradigm where the experimental goal is to estimate and possibly compare sensory processing models. We discuss various theoretical and practical aspects of adaptive firing rate optimization, including optimization with stimulus space constraints, firing rate adaptation, and possible network constraints on the optimal stimulus. We consider the problem of system identification, and show how accurate estimation of non-linear models can be highly dependent on the stimulus set used to probe the network. We suggest that optimizing stimuli for accurate model estimation may make it possible to successfully identify non-linear models which are otherwise intractable, and summarize several recent studies of this type. Finally, we present a two-stage stimulus design procedure which combines the dual goals of model estimation and model comparison and may be especially useful for system identification experiments where the appropriate model is unknown beforehand. We propose that fast, on-line stimulus optimization enabled by increasing computer power can make it practical to move sensory neuroscience away from a descriptive paradigm and toward a new paradigm of real-time model estimation and comparison.

  18. 一种优化WSN节点能耗的自适应多区域分层路由算法%Self-adaptive Routing with Multiple Areas and Layers for Lifetime Optimization in Wireless Sensor Networks

    Institute of Scientific and Technical Information of China (English)

    刘宝礼; 桂若伟; 杨泉

    2012-01-01

    Times new Roman The wireless sensor networks (WSN) comprised of sensor nodes and sink node has become an active research. As the WSN node is battery-powered, the energy consumption of each node may affect the lifetime of the network. Therefore , the research on how to reduce energy consumption of each node and prolong the lifetime of network are very important. Through in-depth analysis of existing technologies, this paper proposes one method to balance the energy consumption and prolong the lifetime of the network. Firstly, we focus on the lifetime optimization model in WSN. And then, we propose a self-adaptive routing with multiple areas and layers (SRMAL) which will balance the energy consumption between nodes. The simulations on MATLAB indicate that SARMAL algorithm performance good for a sparse distribution of nodes or larger regional monitoring network, the algorithm can be used to extend the lifetime of the network.%无线传感器网络由传感节点和sink节点构成,传感节点由于采用电池供电,每个节点的能耗均可能影响整个网络的生命周期,因此,研究降低节点能耗、提高节点生存时间的方法具有重要意义.通过研究网络节点能耗均衡方法,以期提高整个网络的生命周期.首先,研究无线传感器网络的生存时间优化模型,然后设计支持生存时间优化的自适应多区域分层路由算法(SARMAL).MATAB仿真实验表明,对于节点分布较稀疏或监测区域较大的网络,SARMAL算法性能较好,设计的算法可以较好的延长网络生存时间.

  19. Optimization of Microelectronic Devices for Sensor Applications

    Science.gov (United States)

    Cwik, Tom; Klimeck, Gerhard

    2000-01-01

    The NASA/JPL goal to reduce payload in future space missions while increasing mission capability demands miniaturization of active and passive sensors, analytical instruments and communication systems among others. Currently, typical system requirements include the detection of particular spectral lines, associated data processing, and communication of the acquired data to other systems. Advances in lithography and deposition methods result in more advanced devices for space application, while the sub-micron resolution currently available opens a vast design space. Though an experimental exploration of this widening design space-searching for optimized performance by repeated fabrication efforts-is unfeasible, it does motivate the development of reliable software design tools. These tools necessitate models based on fundamental physics and mathematics of the device to accurately model effects such as diffraction and scattering in opto-electronic devices, or bandstructure and scattering in heterostructure devices. The software tools must have convenient turn-around times and interfaces that allow effective usage. The first issue is addressed by the application of high-performance computers and the second by the development of graphical user interfaces driven by properly developed data structures. These tools can then be integrated into an optimization environment, and with the available memory capacity and computational speed of high performance parallel platforms, simulation of optimized components can proceed. In this paper, specific applications of the electromagnetic modeling of infrared filtering, as well as heterostructure device design will be presented using genetic algorithm global optimization methods.

  20. Desensitized Optimal Filtering and Sensor Fusion Tool Kit Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Research on desensitized optimal filtering techniques and a navigation and sensor fusion tool kit using advanced filtering techniques is proposed. Research focuses...

  1. Optimal Sensor Allocation for Fault Detection and Isolation

    Science.gov (United States)

    Azam, Mohammad; Pattipati, Krishna; Patterson-Hine, Ann

    2004-01-01

    Automatic fault diagnostic schemes rely on various types of sensors (e.g., temperature, pressure, vibration, etc) to measure the system parameters. Efficacy of a diagnostic scheme is largely dependent on the amount and quality of information available from these sensors. The reliability of sensors, as well as the weight, volume, power, and cost constraints, often makes it impractical to monitor a large number of system parameters. An optimized sensor allocation that maximizes the fault diagnosibility, subject to specified weight, volume, power, and cost constraints is required. Use of optimal sensor allocation strategies during the design phase can ensure better diagnostics at a reduced cost for a system incorporating a high degree of built-in testing. In this paper, we propose an approach that employs multiple fault diagnosis (MFD) and optimization techniques for optimal sensor placement for fault detection and isolation (FDI) in complex systems. Keywords: sensor allocation, multiple fault diagnosis, Lagrangian relaxation, approximate belief revision, multidimensional knapsack problem.

  2. AUVs as integrated, adaptive acoustic sensors for ocean exploration

    Science.gov (United States)

    Schmidt, Henrik; Edwards, Joseph R.; Liu, Te-Chih; Montanari, Monica

    2001-05-01

    Autonomous underwater vehicles (AUV) are rapidly being transitioned into operational systems for national defense, offshore exploration, and ocean science. AUVs provide excellent sensor platform control, allowing for, e.g., accurate acoustic mapping of seabeds not easily reached by conventional platforms, such as the deep ocean. However, the full potential of the robotic platforms is far from exhausted by such applications. Thus, for example, most seabed-mapping applications use imaging sonar technology, the data volume of which cannot be transmitted back to the operators in real time due to the severe bandwidth limitation of the acoustic communication. The sampling patterns are therefore in general being preprogramed and the data are being stored for postmission analysis. This procedure is therefore associated with indiscriminate distribution of the sampling throughout the area of interest, irrespective of whether features of interest are present or not. However, today's computing technology allows for a significant amount of signal processing and analysis to be performed on the platforms, where the results may then be used for real-time adaptive sampling to optimally concentrate the sampling in area of interest, and compress the results to a few parameters which may be transmitted back to the operators. Such adaptive sensing concepts combining environmental acoustics, signal processing, and robotics are currently being developed for concurrent detection, localization, and classification of buried objects, with application to littoral mine countermeasures, deep ocean seabed characterization, and marine archeology. [Work supported by ONR and NATO Undersea Research Center.

  3. Sensor Calibration Design Based on D-Optimality Criterion

    Directory of Open Access Journals (Sweden)

    Hajiyev Chingiz

    2016-09-01

    Full Text Available In this study, a procedure for optimal selection of measurement points using the D-optimality criterion to find the best calibration curves of measurement sensors is proposed. The coefficients of calibration curve are evaluated by applying the classical Least Squares Method (LSM. As an example, the problem of optimal selection for standard pressure setters when calibrating a differential pressure sensor is solved. The values obtained from the D-optimum measurement points for calibration of the differential pressure sensor are compared with those from actual experiments. Comparison of the calibration errors corresponding to the D-optimal, A-optimal and Equidistant calibration curves is done.

  4. Optimal placement of mobile sensors for data assimilations

    Directory of Open Access Journals (Sweden)

    Wei Kang

    2012-10-01

    Full Text Available We explore the theoretical framework as well as the associated algorithms for the problem of optimally placing mobile observation platforms to maximise the improvement of estimation accuracy. The approach in this study is based on the concept of observability, which is a quantitative measure of the information provided by sensor data and user-knowledge. To find the optimal sensor locations, the observability is maximised using a gradient projection method. The Burgers equation is used to verify this approach. To prove the optimality of the sensor locations, Monte Carlo experimentations are carried out using standard 4D-Var algorithms based on two sets of data, one from equally spaced sensors and the other from the optimal sensor locations. The results show that, relative to equally spaced sensors, the 4D-Var data assimilation achieves significantly improved estimation accuracy if the sensors are placed at the optimal locations. A robustness study is also carried out in which the error covariance matrix is varied by 50% and the sensor noise covariance is varied by 100%. In addition, both Gaussian and uniform probability distributions are used for the sensor noise and initial estimation errors. In all cases, the optimal sensor locations result in significantly improved estimation accuracy.

  5. Optimizing the configuration patterns for heterogeneous distributed sensor fields

    Science.gov (United States)

    Wettergren, Thomas A.; Costa, Russell

    2012-06-01

    When unmanned distributed sensor fields are developed for rapid deployment in hostile areas, the deployment may consist of multiple sensor types. This occurs because of the variations in expected threats and uncertainties about the details of the local environmental conditions. As more detailed information is available at deployment, the quantity and types of sensors are given and fixed, yet the specific pattern for the configuration of their deployment is still variable. We develop a new optimization approach for planning these configurations for this resource constrained sensor application. Our approach takes into account the variety of sensors available and their respective expected performance in the environment, as well as the target uncertainty. Due to the large dimensionality of the design space for this unmanned sensor planning problem, heuristic-based optimizations will provide very sub-optimal solutions and gradient-based methods lack a good quality initialization. Instead, we utilize a robust optimization procedure that combines genetic algorithms with nonlinear programming techniques to create numerical solutions for determining the optimal spatial distribution of sensing effort for each type of sensor. We illustrate the effectiveness of the approach on numerical examples, and also illustrate the qualitative difference in the optimal patterns as a function of the relative numbers of available sensors of each type. We conclude by using the optimization results to discuss the benefits of interspersing the different sensor types, as opposed to creating area sub-segmentations for each type.

  6. Dynamic Hierarchical Energy-Efficient Method Based on Combinatorial Optimization for Wireless Sensor Networks.

    Science.gov (United States)

    Chang, Yuchao; Tang, Hongying; Cheng, Yongbo; Zhao, Qin; Yuan, Baoqing Li andXiaobing

    2017-07-19

    Routing protocols based on topology control are significantly important for improving network longevity in wireless sensor networks (WSNs). Traditionally, some WSN routing protocols distribute uneven network traffic load to sensor nodes, which is not optimal for improving network longevity. Differently to conventional WSN routing protocols, we propose a dynamic hierarchical protocol based on combinatorial optimization (DHCO) to balance energy consumption of sensor nodes and to improve WSN longevity. For each sensor node, the DHCO algorithm obtains the optimal route by establishing a feasible routing set instead of selecting the cluster head or the next hop node. The process of obtaining the optimal route can be formulated as a combinatorial optimization problem. Specifically, the DHCO algorithm is carried out by the following procedures. It employs a hierarchy-based connection mechanism to construct a hierarchical network structure in which each sensor node is assigned to a special hierarchical subset; it utilizes the combinatorial optimization theory to establish the feasible routing set for each sensor node, and takes advantage of the maximum-minimum criterion to obtain their optimal routes to the base station. Various results of simulation experiments show effectiveness and superiority of the DHCO algorithm in comparison with state-of-the-art WSN routing algorithms, including low-energy adaptive clustering hierarchy (LEACH), hybrid energy-efficient distributed clustering (HEED), genetic protocol-based self-organizing network clustering (GASONeC), and double cost function-based routing (DCFR) algorithms.

  7. 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

    2016-03-28

    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.

  8. LinkMind: Link Optimization in Swarming Mobile Sensor Networks

    DEFF Research Database (Denmark)

    Ngo, Trung Dung

    2012-01-01

    optimization of swarming mobile sensor networks. The new method is based on combination of the artificial potential force guaranteeing connectivities of the mobile sensor nodes and the max-flow min-cut theorem of graph theory ensuring optimization of the network link capacity. The developed algorithm...

  9. Sensor Optimization Selection Model Based on Testability Constraint

    Institute of Scientific and Technical Information of China (English)

    YANG Shuming; QIU Jing; LIU Guanjun

    2012-01-01

    Sensor selection and optimization is one of the important parts in design for testability.To address the problems that the traditional sensor optimization selection model does not take the requirements of prognostics and health management especially fault prognostics for testability into account and does not consider the impacts of sensor actual attributes on fault detectability,a novel sensor optimization selection model is proposed.Firstly,a universal architecture for sensor selection and optimization is provided.Secondly,a new testability index named fault predictable rate is defined to describe fault prognostics requirements for testability.Thirdly,a sensor selection and optimization model for prognostics and health management is constructed,which takes sensor cost as objective finction and the defined testability indexes as constraint conditions.Due to NP-hard property of the model,a generic algorithm is designed to obtain the optimal solution.At last,a case study is presented to demonstrate the sensor selection approach for a stable tracking servo platform.The application results and comparison analysis show the proposed model and algorithm are effective and feasible.This approach can be used to select sensors for prognostics and health management of any system.

  10. Sensor Networks Hierarchical Optimization Model for Security Monitoring in High-Speed Railway Transport Hub

    Directory of Open Access Journals (Sweden)

    Zhengyu Xie

    2015-01-01

    Full Text Available We consider the sensor networks hierarchical optimization problem in high-speed railway transport hub (HRTH. The sensor networks are optimized from three hierarchies which are key area sensors optimization, passenger line sensors optimization, and whole area sensors optimization. Case study on a specific HRTH in China showed that the hierarchical optimization method is effective to optimize the sensor networks for security monitoring in HRTH.

  11. Gas pipeline optimization using adaptive algorithms

    Energy Technology Data Exchange (ETDEWEB)

    Smati, A.; Zemmour, N. [INH, Boumerdes (Algeria)

    1996-12-31

    Transmission gas pipeline network consume significant amounts of energy. Then, minimizing the energy requirements is a challenging task. Due to the nonlinearity and poor knowledge of the system states, several results, based on the optimal control theory, are obtained only for simple configurations. In this paper an optimization scheme in the face of varying demand is carried out. It is based on the use of a dynamic simulation program as a plant model and the Pareto set technique to sell out useful experiments. Experiments are used for the identification of regression models based on an original class of functions. The nonlinear programming algorithm results. Its connection with regression models permits the definition off-line, and for a long time horizon, of the optimal discharge pressure trajectory for all the compressor stations. The use of adaptive algorithms, with high frequency, permits one to cancel the effect of unknown disturbances and errors in demand forecasts. In this way, an on-line optimization scheme using data of SCADA system is presented.

  12. 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.

  13. Evolutionary Adaptive Discovery of Phased Array Sensor Signal Identification

    Energy Technology Data Exchange (ETDEWEB)

    Timothy R. McJunkin; Milos Manic

    2011-05-01

    Tomography, used to create images of the internal properties and features of an object, from phased array ultasonics is improved through many sophisiticated methonds of post processing of data. One approach used to improve tomographic results is to prescribe the collection of more data, from different points of few so that data fusion might have a richer data set to work from. This approach can lead to rapid increase in the data needed to be stored and processed. It also does not necessarily lead to have the needed data. This article describes a novel approach to utilizing the data aquired as a basis for adapting the sensors focusing parameters to locate more precisely the features in the material: specifically, two evolutionary methods of autofocusing on a returned signal are coupled with the derivations of the forumulas for spatially locating the feature are given. Test results of the two novel methods of evolutionary based focusing (EBF) illustrate the improved signal strength and correction of the position of feature using the optimized focal timing parameters, called Focused Delay Identification (FoDI).

  14. 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

  15. A Game Theoretic Optimization Method for Energy Efficient Global Connectivity in Hybrid Wireless Sensor Networks.

    Science.gov (United States)

    Lee, JongHyup; Pak, Dohyun

    2016-08-29

    For practical deployment of wireless sensor networks (WSN), WSNs construct clusters, where a sensor node communicates with other nodes in its cluster, and a cluster head support connectivity between the sensor nodes and a sink node. In hybrid WSNs, cluster heads have cellular network interfaces for global connectivity. However, when WSNs are active and the load of cellular networks is high, the optimal assignment of cluster heads to base stations becomes critical. Therefore, in this paper, we propose a game theoretic model to find the optimal assignment of base stations for hybrid WSNs. Since the communication and energy cost is different according to cellular systems, we devise two game models for TDMA/FDMA and CDMA systems employing power prices to adapt to the varying efficiency of recent wireless technologies. The proposed model is defined on the assumptions of the ideal sensing field, but our evaluation shows that the proposed model is more adaptive and energy efficient than local selections.

  16. A Game Theoretic Optimization Method for Energy Efficient Global Connectivity in Hybrid Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    JongHyup Lee

    2016-08-01

    Full Text Available For practical deployment of wireless sensor networks (WSN, WSNs construct clusters, where a sensor node communicates with other nodes in its cluster, and a cluster head support connectivity between the sensor nodes and a sink node. In hybrid WSNs, cluster heads have cellular network interfaces for global connectivity. However, when WSNs are active and the load of cellular networks is high, the optimal assignment of cluster heads to base stations becomes critical. Therefore, in this paper, we propose a game theoretic model to find the optimal assignment of base stations for hybrid WSNs. Since the communication and energy cost is different according to cellular systems, we devise two game models for TDMA/FDMA and CDMA systems employing power prices to adapt to the varying efficiency of recent wireless technologies. The proposed model is defined on the assumptions of the ideal sensing field, but our evaluation shows that the proposed model is more adaptive and energy efficient than local selections.

  17. Optimal Bayesian Adaptive Design for Test-Item Calibration

    NARCIS (Netherlands)

    Linden, van der Wim J.; Ren, Hao

    2015-01-01

    An optimal adaptive design for test-item calibration based on Bayesian optimality criteria is presented. The design adapts the choice of field-test items to the examinees taking an operational adaptive test using both the information in the posterior distributions of their ability parameters and the

  18. 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.

  19. Fiber Bragg grating dynamic strain sensor using an adaptive reflective semiconductor optical amplifier source.

    Science.gov (United States)

    Wei, Heming; Tao, Chuanyi; Zhu, Yinian; Krishnaswamy, Sridhar

    2016-04-01

    In this paper, a reflective semiconductor optical amplifier (RSOA) is configured to demodulate dynamic spectral shifts of a fiber Bragg grating (FBG) dynamic strain sensor. The FBG sensor and the RSOA source form an adaptive fiber cavity laser. As the reflective spectrum of the FBG sensor changes due to dynamic strains, the wavelength of the laser output shifts accordingly, which is subsequently converted into a corresponding phase shift and demodulated by an unbalanced Michelson interferometer. Due to the short transition time of the RSOA, the RSOA-FBG cavity can respond to dynamic strains at high frequencies extending to megahertz. A demodulator using a PID controller is used to compensate for low-frequency drifts induced by temperature and large quasi-static strains. As the sensitivity of the demodulator is a function of the optical path difference and the FBG spectral width, optimal parameters to obtain high sensitivity are presented. Multiplexing to demodulate multiple FBG sensors is also discussed.

  20. Strategy Developed for Selecting Optimal Sensors for Monitoring Engine Health

    Science.gov (United States)

    2004-01-01

    Sensor indications during rocket engine operation are the primary means of assessing engine performance and health. Effective selection and location of sensors in the operating engine environment enables accurate real-time condition monitoring and rapid engine controller response to mitigate critical fault conditions. These capabilities are crucial to ensure crew safety and mission success. Effective sensor selection also facilitates postflight condition assessment, which contributes to efficient engine maintenance and reduced operating costs. Under the Next Generation Launch Technology program, the NASA Glenn Research Center, in partnership with Rocketdyne Propulsion and Power, has developed a model-based procedure for systematically selecting an optimal sensor suite for assessing rocket engine system health. This optimization process is termed the systematic sensor selection strategy. Engine health management (EHM) systems generally employ multiple diagnostic procedures including data validation, anomaly detection, fault-isolation, and information fusion. The effectiveness of each diagnostic component is affected by the quality, availability, and compatibility of sensor data. Therefore systematic sensor selection is an enabling technology for EHM. Information in three categories is required by the systematic sensor selection strategy. The first category consists of targeted engine fault information; including the description and estimated risk-reduction factor for each identified fault. Risk-reduction factors are used to define and rank the potential merit of timely fault diagnoses. The second category is composed of candidate sensor information; including type, location, and estimated variance in normal operation. The final category includes the definition of fault scenarios characteristic of each targeted engine fault. These scenarios are defined in terms of engine model hardware parameters. Values of these parameters define engine simulations that generate

  1. 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....

  2. Adaptive Submodularity: A New Approach to Active Learning and Stochastic Optimization

    CERN Document Server

    Golovin, Daniel

    2010-01-01

    Solving stochastic optimization problems under partial observability, where we need to adaptively make decisions with uncertain outcomes, is a fundamental but notoriously difficult challenge. In this paper, we introduce the concept of adaptive submodularity, generalizing submodular set functions to adaptive policies. We prove that if a problem satisfies this property, a simple adaptive greedy algorithm is guaranteed to be competitive with the optimal policy. We illustrate the usefulness of the concept by giving several examples of adaptive submodular objectives arising in diverse applications including sensor placement, viral marketing and pool-based active learning. Proving adaptive submodularity for these problems allows us to recover existing results in these applications as special cases and leads to natural generalizations.

  3. LinkMind: link optimization in swarming mobile sensor networks.

    Science.gov (United States)

    Ngo, Trung Dung

    2011-01-01

    A swarming mobile sensor network is comprised of a swarm of wirelessly connected mobile robots equipped with various sensors. Such a network can be applied in an uncertain environment for services such as cooperative navigation and exploration, object identification and information gathering. One of the most advantageous properties of the swarming wireless sensor network is that mobile nodes can work cooperatively to organize an ad-hoc network and optimize the network link capacity to maximize the transmission of gathered data from a source to a target. This paper describes a new method of link optimization of swarming mobile sensor networks. The new method is based on combination of the artificial potential force guaranteeing connectivities of the mobile sensor nodes and the max-flow min-cut theorem of graph theory ensuring optimization of the network link capacity. The developed algorithm is demonstrated and evaluated in simulation.

  4. LinkMind: Link Optimization in Swarming Mobile Sensor Networks

    Directory of Open Access Journals (Sweden)

    Trung Dung Ngo

    2011-08-01

    Full Text Available A swarming mobile sensor network is comprised of a swarm of wirelessly connected mobile robots equipped with various sensors. Such a network can be applied in an uncertain environment for services such as cooperative navigation and exploration, object identification and information gathering. One of the most advantageous properties of the swarming wireless sensor network is that mobile nodes can work cooperatively to organize an ad-hoc network and optimize the network link capacity to maximize the transmission of gathered data from a source to a target. This paper describes a new method of link optimization of swarming mobile sensor networks. The new method is based on combination of the artificial potential force guaranteeing connectivities of the mobile sensor nodes and the max-flow min-cut theorem of graph theory ensuring optimization of the network link capacity. The developed algorithm is demonstrated and evaluated in simulation.

  5. Optimization of Surface Acoustic Wave-Based Rate Sensors

    Directory of Open Access Journals (Sweden)

    Fangqian Xu

    2015-10-01

    Full Text Available The optimization of an surface acoustic wave (SAW-based rate sensor incorporating metallic dot arrays was performed by using the approach of partial-wave analysis in layered media. The optimal sensor chip designs, including the material choice of piezoelectric crystals and metallic dots, dot thickness, and sensor operation frequency were determined theoretically. The theoretical predictions were confirmed experimentally by using the developed SAW sensor composed of differential delay line-oscillators and a metallic dot array deposited along the acoustic wave propagation path of the SAW delay lines. A significant improvement in sensor sensitivity was achieved in the case of 128° YX LiNbO3, and a thicker Au dot array, and low operation frequency were used to structure the sensor.

  6. 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.

  7. Desensitized Optimal Filtering and Sensor Fusion Tool Kit Project

    Data.gov (United States)

    National Aeronautics and Space Administration — It is proposed to develop desensitized optimal filtering techniques and to implement these algorithms in a navigation and sensor fusion tool kit. These proposed...

  8. Optimal geometry for a quartz multipurpose SPM sensor

    Directory of Open Access Journals (Sweden)

    Julian Stirling

    2013-06-01

    Full Text Available We propose a geometry for a piezoelectric SPM sensor that can be used for combined AFM/LFM/STM. The sensor utilises symmetry to provide a lateral mode without the need to excite torsional modes. The symmetry allows normal and lateral motion to be completely isolated, even when introducing large tips to tune the dynamic properties to optimal values.

  9. Optimal Magnetic Sensor Vests for Cardiac Source Imaging

    Directory of Open Access Journals (Sweden)

    Stephan Lau

    2016-05-01

    Full Text Available Magnetocardiography (MCG non-invasively provides functional information about the heart. New room-temperature magnetic field sensors, specifically magnetoresistive and optically pumped magnetometers, have reached sensitivities in the ultra-low range of cardiac fields while allowing for free placement around the human torso. Our aim is to optimize positions and orientations of such magnetic sensors in a vest-like arrangement for robust reconstruction of the electric current distributions in the heart. We optimized a set of 32 sensors on the surface of a torso model with respect to a 13-dipole cardiac source model under noise-free conditions. The reconstruction robustness was estimated by the condition of the lead field matrix. Optimization improved the condition of the lead field matrix by approximately two orders of magnitude compared to a regular array at the front of the torso. Optimized setups exhibited distributions of sensors over the whole torso with denser sampling above the heart at the front and back of the torso. Sensors close to the heart were arranged predominantly tangential to the body surface. The optimized sensor setup could facilitate the definition of a standard for sensor placement in MCG and the development of a wearable MCG vest for clinical diagnostics.

  10. ROAMing terrain (Real-time Optimally Adapting Meshes)

    Energy Technology Data Exchange (ETDEWEB)

    Duchaineau, M.; Wolinsky, M.; Sigeti, D.E.; Miller, M.C.; Aldrich, C.; Mineev, M.

    1997-07-01

    Terrain visualization is a difficult problem for applications requiring accurate images of large datasets at high frame rates, such as flight simulation and ground-based aircraft testing using synthetic sensor stimulation. On current graphics hardware, the problem is to maintain dynamic, view-dependent triangle meshes and texture maps that produce good images at the required frame rate. We present an algorithm for constructing triangle meshes that optimizes flexible view-dependent error metrics, produces guaranteed error bounds, achieves specified triangle counts directly, and uses frame-to-frame coherence to operate at high frame rates for thousands of triangles per frame. Our method, dubbed Real-time Optimally Adapting Meshes (ROAM), uses two priority queues to drive split and merge operations that maintain continuous triangulations built from pre-processed bintree triangles. We introduce two additional performance optimizations: incremental triangle stripping and priority-computation deferral lists. ROAM execution time is proportionate to the number of triangle changes per frame, which is typically a few percent of the output mesh size, hence ROAM performance is insensitive to the resolution and extent of the input terrain. Dynamic terrain and simple vertex morphing are supported.

  11. A Green Clustering Protocol for Mobile Sensor Network Using Particle Swarm Optimization

    Institute of Scientific and Technical Information of China (English)

    Nurul Mu’azzah Abdul Latiff; NikNoordini NikAbdMalik; Abdul Halim Abdul Latiff

    2016-01-01

    Abstract-Energy consumption of sensor nodes is one of the crucial issues in prolonging the lifetime of wireless sensor networks. One of the methods that can improve the utilization of sensor nodes batteries is the clustering method. In this paper, we propose a green clustering protocol for mobile sensor networks using particle swarm optimization (PSO) algorithm. We define a new fitness function that can optimize the energy consumption of the whole network and minimize the relative distance between cluster heads and their respective member nodes. We also take into account the mobility factor when defining the cluster membership, so that the sensor nodes can join the cluster that has the similar mobility pattern. The performance of the proposed protocol is compared with well-known clustering protocols developed for wireless sensor networks such as LEACH (low-energy adaptive clustering hierarchy) and protocols designed for sensor networks with mobile nodes called CM-IR (clustering mobility-invalid round). In addition, we also modify the improved version of LEACH called MLEACH-C, so that it is applicable to the mobile sensor nodes environment. Simulation results demonstrate that the proposed protocol using PSO algorithm can improve the energy consumption of the network, achieve better network lifetime, and increase the data delivered at the base station.

  12. DE-FE0013062 Final report PARC NETL DOE Heat sensor heat sensor harsh environment adaptable thermionic sensor

    Energy Technology Data Exchange (ETDEWEB)

    Limb, Scott J. [Palo Alto Research Center Inc., CA (United States)

    2016-05-31

    This document is the final report for the “HARSH ENVIRONMENT ADAPTABLE THERMIONIC SENSOR” project under NETL’s Crosscutting contract DE-FE0013062. This report addresses sensors that can be made with thermionic thin films along with the required high temperature hermetic packaging process. These sensors can be placed in harsh high temperature environments and potentially be wireless and self-powered.

  13. Geometrical optimization of a local ballistic magnetic sensor

    Energy Technology Data Exchange (ETDEWEB)

    Kanda, Yuhsuke; Hara, Masahiro [Graduate School of Science and Technology, Kumamoto University, 2-39-1 Kurokami, Kumamoto 860-8555 (Japan); Nomura, Tatsuya [Advanced Electronics Research Division, INAMORI Frontier Research Center, Kyushu University, 744 Motooka, Fukuoka 819-0395 (Japan); Kimura, Takashi [Advanced Electronics Research Division, INAMORI Frontier Research Center, Kyushu University, 744 Motooka, Fukuoka 819-0395 (Japan); Department of Physics, Kyushu University, 6-10-1 Hakozaki, Fukuoka 812-8581 (Japan)

    2014-04-07

    We have developed a highly sensitive local magnetic sensor by using a ballistic transport property in a two-dimensional conductor. A semiclassical simulation reveals that the sensitivity increases when the geometry of the sensor and the spatial distribution of the local field are optimized. We have also experimentally demonstrated a clear observation of a magnetization process in a permalloy dot whose size is much smaller than the size of an optimized ballistic magnetic sensor fabricated from a GaAs/AlGaAs two-dimensional electron gas.

  14. Optimized placement of nodes for target detection in sensor networks

    Institute of Scientific and Technical Information of China (English)

    HU Ning; ZHANG Deyun

    2007-01-01

    In order to improve the precision of the target detection in wireless sensor networks,a new approach based on genetic algorithm (GA) was proposed to optimize the placement of the sensor.The target location problem was transformed into locating a target at a grid point through modeling the sensor field as a grid of points.Moreover,the sensor placement problem was formulated as a combinatorial optimization problem,which is aimed at minimizing the maximum discrimination error under the restraints of limited cost and complete coverage.The GA approach uses binary coding to represent the location,and both single parent crossover operator and single parent mutation operator are used to improve its speed and efficiency.Experimental results have shown that a global optimal solution can be quickly obtained using the proposed method and the precision requirement for target location is satisfied.

  15. Unsteady flow sensing and optimal sensor placement using machine learning

    Science.gov (United States)

    Semaan, Richard

    2016-11-01

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

  16. Network inference via adaptive optimal design

    Directory of Open Access Journals (Sweden)

    Stigter Johannes D

    2012-09-01

    Full Text Available Abstract Background Current research in network reverse engineering for genetic or metabolic networks very often does not include a proper experimental and/or input design. In this paper we address this issue in more detail and suggest a method that includes an iterative design of experiments based, on the most recent data that become available. The presented approach allows a reliable reconstruction of the network and addresses an important issue, i.e., the analysis and the propagation of uncertainties as they exist in both the data and in our own knowledge. These two types of uncertainties have their immediate ramifications for the uncertainties in the parameter estimates and, hence, are taken into account from the very beginning of our experimental design. Findings The method is demonstrated for two small networks that include a genetic network for mRNA synthesis and degradation and an oscillatory network describing a molecular network underlying adenosine 3’-5’ cyclic monophosphate (cAMP as observed in populations of Dyctyostelium cells. In both cases a substantial reduction in parameter uncertainty was observed. Extension to larger scale networks is possible but needs a more rigorous parameter estimation algorithm that includes sparsity as a constraint in the optimization procedure. Conclusion We conclude that a careful experiment design very often (but not always pays off in terms of reliability in the inferred network topology. For large scale networks a better parameter estimation algorithm is required that includes sparsity as an additional constraint. These algorithms are available in the literature and can also be used in an adaptive optimal design setting as demonstrated in this paper.

  17. 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.

  18. Optimizing Photon Collection from Point Sources with Adaptive Optics

    Science.gov (United States)

    Hill, Alexander; Hervas, David; Nash, Joseph; Graham, Martin; Burgers, Alexander; Paudel, Uttam; Steel, Duncan; Kwiat, Paul

    2015-05-01

    Collection of light from point-like sources is typically poor due to the optical aberrations present with very high numerical-aperture optics. In the case of quantum dots, the emitted mode is nonisotropic and may be quite difficult to couple into single- or even few-mode fiber. Wavefront aberrations can be corrected using adaptive optics at the classical level by analyzing the wavefront directly (e.g., with a Shack-Hartmann sensor); however, these techniques are not feasible at the single-photon level. We present a new technique for adaptive optics with single photons using a genetic algorithm to optimize collection from point emitters with a deformable mirror. We first demonstrate our technique for improving coupling from a subwavelength pinhole, which simulates isotropic emission from a point source. We then apply our technique in situto InAs/GaAs quantum dots, obtaining coupling increases of up to 50% even in the presence of an artificial source of drift.

  19. 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.

  20. Adaptive Optoelectronic Eyes: Hybrid Sensor/Processor Architectures

    Science.gov (United States)

    2006-11-13

    J.  Lange , C. von der Malsburg, R. P. Würtz, and W. Konen, “Distortion Invariant Object Recognition Adaptive Optoelectronic Eyes: Hybrid Sensor...Meeting, Dallas, Texas, (November, 1998). 17.  G. Sáry, G. Kovács, K. Köteles, G.  Benedek , J. Fiser, and I. Biederman, “Selectivity Variations in Monkey

  1. Wavefront sensors and algorithms for adaptive optical systems

    Science.gov (United States)

    Lukin, V. P.; Botygina, N. N.; Emaleev, O. N.; Konyaev, P. A.

    2010-07-01

    The results of recent works related to techniques and algorithms for wave-front (WF) measurement using Shack-Hartmann sensors show their high efficiency in solution of very different problems of applied optics. The goal of this paper was to develop a sensitive Shack-Hartmann sensor with high precision WF measurement capability on the base of modern technology of optical elements making and new efficient methods and computational algorithms of WF reconstruction. The Shack-Hartmann sensors sensitive to small WF aberrations are used for adaptive optical systems, compensating the wave distortions caused by atmospheric turbulence. A high precision Shack-Hartmann WF sensor has been developed on the basis of a low-aperture off-axis diffraction lens array. The device is capable of measuring WF slopes at array sub-apertures of size 640×640 μm with an error not exceeding 4.80 arcsec (0.15 pixel), which corresponds to the standard deviation equal to 0.017λ at the reconstructed WF with wavelength λ . Also the modification of this sensor for adaptive system of solar telescope using extended scenes as tracking objects, such as sunspot, pores, solar granulation and limb, is presented. The software package developed for the proposed WF sensors includes three algorithms of local WF slopes estimation (modified centroids, normalized cross-correlation and fast Fourierdemodulation), as well as three methods of WF reconstruction (modal Zernike polynomials expansion, deformable mirror response functions expansion and phase unwrapping), that can be selected during operation with accordance to the application.

  2. Adaptive Data Filtering of Inertial Sensors with Variable Bandwidth

    Science.gov (United States)

    Alam, Mushfiqul; Rohac, Jan

    2015-01-01

    MEMS (micro-electro-mechanical system)-based inertial sensors, i.e., accelerometers and angular rate sensors, are commonly used as a cost-effective solution for the purposes of navigation in a broad spectrum of terrestrial and aerospace applications. These tri-axial inertial sensors form an inertial measurement unit (IMU), which is a core unit of navigation systems. Even if MEMS sensors have an advantage in their size, cost, weight and power consumption, they suffer from bias instability, noisy output and insufficient resolution. Furthermore, the sensor's behavior can be significantly affected by strong vibration when it operates in harsh environments. All of these constitute conditions require treatment through data processing. As long as the navigation solution is primarily based on using only inertial data, this paper proposes a novel concept in adaptive data pre-processing by using a variable bandwidth filtering. This approach utilizes sinusoidal estimation to continuously adapt the filtering bandwidth of the accelerometer's data in order to reduce the effects of vibration and sensor noise before attitude estimation is processed. Low frequency vibration generally limits the conditions under which the accelerometers can be used to aid the attitude estimation process, which is primarily based on angular rate data and, thus, decreases its accuracy. In contrast, the proposed pre-processing technique enables using accelerometers as an aiding source by effective data smoothing, even when they are affected by low frequency vibration. Verification of the proposed concept is performed on simulation and real-flight data obtained on an ultra-light aircraft. The results of both types of experiments confirm the suitability of the concept for inertial data pre-processing. PMID:25648711

  3. A Multifunctional Joint Angle Sensor with Measurement Adaptability

    Directory of Open Access Journals (Sweden)

    Wei Quan

    2013-11-01

    Full Text Available The paper presents a multifunctional joint sensor with measurement adaptability for biological engineering applications, such as gait analysis, gesture recognition, etc. The adaptability is embodied in both static and dynamic environment measurements, both of body pose and in motion capture. Its multifunctional capabilities lay in its ability of simultaneous measurement of multiple degrees of freedom (MDOF with a single sensor to reduce system complexity. The basic working mode enables 2DOF spatial angle measurement over big ranges and stands out for its applications on different joints of different individuals without recalibration. The optional advanced working mode enables an additional DOF measurement for various applications. By employing corrugated tube as the main body, the sensor is also characterized as flexible and wearable with less restraints. MDOF variations are converted to linear displacements of the sensing elements. The simple reconstruction algorithm and small outputs volume are capable of providing real-time angles and long-term monitoring. The performance assessment of the built prototype is promising enough to indicate the feasibility of the sensor.

  4. Adaptive Particle Filter for Nonparametric Estimation with Measurement Uncertainty in Wireless Sensor Networks.

    Science.gov (United States)

    Li, Xiaofan; Zhao, Yubin; Zhang, Sha; Fan, Xiaopeng

    2016-05-30

    Particle filters (PFs) are widely used for nonlinear signal processing in wireless sensor networks (WSNs). However, the measurement uncertainty makes the WSN observations unreliable to the actual case and also degrades the estimation accuracy of the PFs. In addition to the algorithm design, few works focus on improving the likelihood calculation method, since it can be pre-assumed by a given distribution model. In this paper, we propose a novel PF method, which is based on a new likelihood fusion method for WSNs and can further improve the estimation performance. We firstly use a dynamic Gaussian model to describe the nonparametric features of the measurement uncertainty. Then, we propose a likelihood adaptation method that employs the prior information and a belief factor to reduce the measurement noise. The optimal belief factor is attained by deriving the minimum Kullback-Leibler divergence. The likelihood adaptation method can be integrated into any PFs, and we use our method to develop three versions of adaptive PFs for a target tracking system using wireless sensor network. The simulation and experimental results demonstrate that our likelihood adaptation method has greatly improved the estimation performance of PFs in a high noise environment. In addition, the adaptive PFs are highly adaptable to the environment without imposing computational complexity.

  5. Adaptive Central Force Optimization Algorithm Based on the Stability Analysis

    Directory of Open Access Journals (Sweden)

    Weiyi Qian

    2015-01-01

    Full Text Available In order to enhance the convergence capability of the central force optimization (CFO algorithm, an adaptive central force optimization (ACFO algorithm is presented by introducing an adaptive weight and defining an adaptive gravitational constant. The adaptive weight and gravitational constant are selected based on the stability theory of discrete time-varying dynamic systems. The convergence capability of ACFO algorithm is compared with the other improved CFO algorithm and evolutionary-based algorithm using 23 unimodal and multimodal benchmark functions. Experiments results show that ACFO substantially enhances the performance of CFO in terms of global optimality and solution accuracy.

  6. Field of view selection for optimal airborne imaging sensor performance

    Science.gov (United States)

    Goss, Tristan M.; Barnard, P. Werner; Fildis, Halidun; Erbudak, Mustafa; Senger, Tolga; Alpman, Mehmet E.

    2014-05-01

    The choice of the Field of View (FOV) of imaging sensors used in airborne targeting applications has major impact on the overall performance of the system. Conducting a market survey from published data on sensors used in stabilized airborne targeting systems shows a trend of ever narrowing FOVs housed in smaller and lighter volumes. This approach promotes the ever increasing geometric resolution provided by narrower FOVs, while it seemingly ignores the influences the FOV selection has on the sensor's sensitivity, the effects of diffraction, the influences of sight line jitter and collectively the overall system performance. This paper presents a trade-off methodology to select the optimal FOV for an imaging sensor that is limited in aperture diameter by mechanical constraints (such as space/volume available and window size) by balancing the influences FOV has on sensitivity and resolution and thereby optimizing the system's performance. The methodology may be applied to staring array based imaging sensors across all wavebands from visible/day cameras through to long wave infrared thermal imagers. Some examples of sensor analysis applying the trade-off methodology are given that highlights the performance advantages that can be gained by maximizing the aperture diameters and choosing the optimal FOV for an imaging sensor used in airborne targeting applications.

  7. Optimization of Adaptive Transit Signal Priority Using Parallel Genetic Algorithm

    Institute of Scientific and Technical Information of China (English)

    Guangwei Zhou; Albert Gan; L. David Shen

    2007-01-01

    Optimization of adaptive traffic signal timing is one of the most complex problems in traffic control systems. This paper presents an adaptive transit signal priority (TSP) strategy that applies the parallel genetic algorithm (PGA) to optimize adaptive traffic signal control in the presence of TSP. The method can optimize the phase plan, cycle length, and green splits at isolated intersections with consideration for the performance of both the transit and the general vehicles. A VISSlM (VISual SIMulation) simulation testbed was developed to evaluate the performance of the proposed PGA-based adaptive traffic signal control with TSP.The simulation results show that the PGA-based optimizer for adaptive TSP outperformed the fully actuated NEMA control in all test cases. The results also show that the PGA-based optimizer can produce TSP timing plans that benefit the transit vehicles while minimizing the impact of TSP on the general vehicles.

  8. Optimizing Key Updates in Sensor Networks

    DEFF Research Database (Denmark)

    Yuksel, Ender; Nielson, Hanne Riis; Nielson, Flemming

    2011-01-01

    Sensor networks offer the advantages of simple and low–resource communication. Nevertheless, security is of particular importance in many cases such as when sensitive data is communicated or tamper-resistance is required. Updating the security keys is one of the key points in security, which rest...

  9. Optimal flow sensor placement on wastewater treatment plants.

    Science.gov (United States)

    Villez, Kris; Vanrolleghem, Peter A; Corominas, Lluís

    2016-09-15

    Obtaining high quality data collected on wastewater treatment plants is gaining increasing attention in the wastewater engineering literature. Typical studies focus on recognition of faulty data with a given set of installed sensors on a wastewater treatment plant. Little attention is however given to how one can install sensors in such a way that fault detection and identification can be improved. In this work, we develop a method to obtain Pareto optimal sensor layouts in terms of cost, observability, and redundancy. Most importantly, the resulting method allows reducing the large set of possibilities to a minimal set of sensor layouts efficiently for any wastewater treatment plant on the basis of structural criteria only, with limited sensor information, and without prior data collection. In addition, the developed optimization scheme is fast. Practically important is that the number of sensors needed for both observability of all flows and redundancy of all flow sensors is only one more compared to the number of sensors needed for observability of all flows in the studied wastewater treatment plant configurations.

  10. Optimized quantum sensing with a single electron spin using real-time adaptive measurements

    Science.gov (United States)

    Bonato, C.; Blok, M. S.; Dinani, H. T.; Berry, D. W.; Markham, M. L.; Twitchen, D. J.; Hanson, R.

    2016-03-01

    Quantum sensors based on single solid-state spins promise a unique combination of sensitivity and spatial resolution. The key challenge in sensing is to achieve minimum estimation uncertainty within a given time and with high dynamic range. Adaptive strategies have been proposed to achieve optimal performance, but their implementation in solid-state systems has been hindered by the demanding experimental requirements. Here, we realize adaptive d.c. sensing by combining single-shot readout of an electron spin in diamond with fast feedback. By adapting the spin readout basis in real time based on previous outcomes, we demonstrate a sensitivity in Ramsey interferometry surpassing the standard measurement limit. Furthermore, we find by simulations and experiments that adaptive protocols offer a distinctive advantage over the best known non-adaptive protocols when overhead and limited estimation time are taken into account. Using an optimized adaptive protocol we achieve a magnetic field sensitivity of 6.1 ± 1.7 nT Hz-1/2 over a wide range of 1.78 mT. These results open up a new class of experiments for solid-state sensors in which real-time knowledge of the measurement history is exploited to obtain optimal performance.

  11. 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.

  12. 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.

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

    Science.gov (United States)

    Ullán, M.; Allport, P. P.; Baca, M.; Broughton, J.; Chisholm, A.; Nikolopoulos, K.; Pyatt, S.; Thomas, J. P.; Wilson, J. A.; Kierstead, J.; Kuczewski, P.; Lynn, D.; Hommels, L. B. A.; Fleta, C.; Fernandez-Tejero, J.; Quirion, D.; Bloch, I.; Díez, S.; Gregor, I. M.; Lohwasser, K.; Poley, L.; Tackmann, K.; Hauser, M.; Jakobs, K.; Kuehn, S.; Mahboubi, K.; Mori, R.; Parzefall, U.; Clark, A.; Ferrere, D.; Gonzalez Sevilla, S.; Ashby, J.; Blue, A.; Bates, R.; Buttar, C.; Doherty, F.; McMullen, T.; McEwan, F.; O'Shea, V.; Kamada, S.; Yamamura, K.; Ikegami, Y.; Nakamura, K.; Takubo, Y.; Unno, Y.; Takashima, R.; Chilingarov, A.; Fox, H.; Affolder, A. A.; Casse, G.; Dervan, P.; Forshaw, D.; Greenall, A.; Wonsak, S.; Wormald, M.; Cindro, V.; Kramberger, G.; Mandić, I.; Mikuž, M.; Gorelov, I.; Hoeferkamp, M.; Palni, P.; Seidel, S.; Taylor, A.; Toms, K.; Wang, R.; Hessey, N. P.; Valencic, N.; Hanagaki, K.; Dolezal, Z.; Kodys, P.; Bohm, J.; Mikestikova, M.; Bevan, A.; Beck, G.; Milke, C.; Domingo, M.; Fadeyev, V.; Galloway, Z.; Hibbard-Lubow, D.; Liang, Z.; Sadrozinski, H. F.-W.; Seiden, A.; To, K.; French, R.; Hodgson, P.; Marin-Reyes, H.; Parker, K.; Jinnouchi, O.; Hara, K.; Bernabeu, J.; Civera, J. V.; Garcia, C.; Lacasta, C.; Marti i Garcia, S.; Rodriguez, D.; Santoyo, D.; Solaz, C.; Soldevila, U.

    2016-09-01

    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.

  14. Optimized algorithm for balancing clusters in wireless sensor networks

    Institute of Scientific and Technical Information of China (English)

    Mucheol KIM; Sun-hong KIM; Hyungjin BYUN; Sang-yong HAN

    2009-01-01

    Wireless sensor networks consist of hundreds or thousands of sensor nodes that involve numerous restrictions including computation capability and battery capacity. Topology control is an important issue for achieving a balanced placement of sensor nodes. The clustering scheme is a widely known and efficient means of topology control for transmitting information to the base station in two hops. The automatic routing scheme of the self-organizing technique is another critical element of wireless sensor networks. In this paper we propose an optimal algorithm with cluster balance taken into consideration, and compare it with three well known and widely used approaches, I.e., LEACH, MEER, and VAP-E, in performance evaluation. Experimental results show that the proposed approach increases the overall network lifetime, indicating that the amount of energy required for communication to the base station will be reduced for locating an optimal cluster.

  15. Adaptive Data Filtering of Inertial Sensors with Variable Bandwidth

    Directory of Open Access Journals (Sweden)

    Mushfiqul Alam

    2015-02-01

    Full Text Available MEMS (micro-electro-mechanical system-based inertial sensors, i.e., accelerometers and angular rate sensors, are commonly used as a cost-effective solution for the purposes of navigation in a broad spectrum of terrestrial and aerospace applications. These tri-axial inertial sensors form an inertial measurement unit (IMU, which is a core unit of navigation systems. Even if MEMS sensors have an advantage in their size, cost, weight and power consumption, they suffer from bias instability, noisy output and insufficient resolution. Furthermore, the sensor’s behavior can be significantly affected by strong vibration when it operates in harsh environments. All of these constitute conditions require treatment through data processing. As long as the navigation solution is primarily based on using only inertial data, this paper proposes a novel concept in adaptive data pre-processing by using a variable bandwidth filtering. This approach utilizes sinusoidal estimation to continuously adapt the filtering bandwidth of the accelerometer’s data in order to reduce the effects of vibration and sensor noise before attitude estimation is processed. Low frequency vibration generally limits the conditions under which the accelerometers can be used to aid the attitude estimation process, which is primarily based on angular rate data and, thus, decreases its accuracy. In contrast, the proposed pre-processing technique enables using accelerometers as an aiding source by effective data smoothing, even when they are affected by low frequency vibration. Verification of the proposed concept is performed on simulation and real-flight data obtained on an ultra-light aircraft. The results of both types of experiments confirm the suitability of the concept for inertial data pre-processing.

  16. Adaptive Multipath Key Reinforcement for Energy Harvesting Wireless Sensor Networks

    DEFF Research Database (Denmark)

    Di Mauro, Alessio; Dragoni, Nicola

    2015-01-01

    on the design of the security protocols for such networks, as the nodes have to adapt and optimize their behaviour according to the available energy. Traditional key management schemes do not take energy into account, making them not suitable for EH-WSNs. In this paper we propose a new multipath key...

  17. Blade Shape Optimization of Liquid Turbine Flow Sensor

    Institute of Scientific and Technical Information of China (English)

    郭素娜; 张涛; 孙立军; 杨振; 杨文量

    2016-01-01

    Based on the characteristic curve analysis, the method using 2D(K ) square difference of meter factor at different flow rates was developed to evaluate the performance of turbine flow sensor in this study. Then according to the distribution of entrance velocity, it was supposed that reducing the blade area near the tip could decrease the linearity error of a sensor. Therefore, the influence of different blade shape parameters on the performance of the sensor was investigated by combining computational fluid dynamics(CFD)simulation with experimental test. The experimental results showed that, for the liquid turbine flow sensor with a diameter of 10 mm, the linearity error was smallest, and the performance of sensor was optimal when blade shape parameter equaled 0.25.

  18. Optimal Sensor Networks Scheduling in Identification of Distributed Parameter Systems

    CERN Document Server

    Patan, Maciej

    2012-01-01

    Sensor networks have recently come into prominence because they hold the potential to revolutionize a wide spectrum of both civilian and military applications. An ingenious characteristic of sensor networks is the distributed nature of data acquisition. Therefore they seem to be ideally prepared for the task of monitoring processes with spatio-temporal dynamics which constitute one of most general and important classes of systems in modelling of the real-world phenomena. It is clear that careful deployment and activation of sensor nodes are critical for collecting the most valuable information from the observed environment. Optimal Sensor Network Scheduling in Identification of Distributed Parameter Systems discusses the characteristic features of the sensor scheduling problem, analyzes classical and recent approaches, and proposes a wide range of original solutions, especially dedicated for networks with mobile and scanning nodes. Both researchers and practitioners will find the case studies, the proposed al...

  19. NEAR OPTIMAL CLUSTER-HEAD SELECTION FOR WIRELESS SENSOR NETWORKS

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Clustering in wireless sensor networks is an effective way to save energy and reuse bandwidth. To our best knowledge, most of the clustering protocols proposed in literature are of a dynamic type, where cluster heads are selected in each period, followed by cluster formation. In this paper, a new static type clustering method called Hausdorff clustering, which is based on the location of sensor nodes as well as communication efficiency and network connectivity, is proposed. The cluster head, however,is rotated within the cluster by a fuzzy logic algorithm that optimizes the network lifetime. Simulation results show that this approach can significantly increase the lifetime of the sensor network.

  20. Optimal configuration of redundant inertial sensors for navigation and FDI performance.

    Science.gov (United States)

    Shim, Duk-Sun; Yang, Cheol-Kwan

    2010-01-01

    This paper considers the optimal sensor configuration for inertial navigation systems which have redundant inertial sensors such as gyroscopes and accelerometers. We suggest a method to determine the optimal sensor configuration which considers both the navigation and FDI performance. Monte Carlo simulations are performed to show the performance of the suggested optimal sensor configuration method.

  1. Adaptive optical design in surface plasma resonance sensor

    Institute of Scientific and Technical Information of China (English)

    ZHANG Feng; ZHONG Jin-gang

    2006-01-01

    A double-prism adaptive optical design in surface plasma resonance (SPR) sensor is proposed,which consists of two identical isosceles right-triangular prisms. One prism is used as a component of Kretschmann configuration,and the other is for regulation of the optical path. When double-prism structure is angle-scanned by an immovable incident ray,the output ray will be always parallel with the incident ray and just has a small displacement with the shift of output point.The output ray can be focused on a fixed photodetector by a convex lens.Thus it can be avoided that a prism and a photodetector rotate by θ and 2θ respectively in conventional angular scanning SPR sensor.This new design reduces the number of the movable components,makes the structure simple and compact,and makes the manipulation convenient.

  2. Optimal Sensor Decision Based on Particle Filter

    Institute of Scientific and Technical Information of China (English)

    XU Meng; WANG Hong-wei; HU Shi-qiang

    2006-01-01

    A novel infrared and radar synergistic tracking algorithm, which is based on the idea of closed loop control, and target's motion model identification and particle filter approach, was put forward. In order to improve the observability and filtering divergence of infrared search and tracking, the unscented Kalman filter algorithm that has stronger ability of non-linear approximation was adopted. The polynomial and least square method based on radar and IRST measurements to identify the parameters of the model was proposed, and a "pseudo sensor" was suggested to estimate the target position according to the identified model even if the radar is turned off. At last,the average Kullback-Leibler discrimination distance based on particle filter was used to measure the tracking performance, based on tracking performance and fuzzy stochastic decision, the idea of closed loop was used to retrieve the module parameter of "pseudo sensor". The experimental result indicates that the algorithm can not only limit the radar activity effectively but also keep the tracking accuracy of active/passive system well.

  3. Optimizing Systems of Threshold Detection Sensors

    Science.gov (United States)

    2008-03-01

    maximization problem, a globally optimal solution is not guaranteed on the basis of quasiconvexity of the objective function alone. ( Bazaraa et al., 1993...application in everyday situations. International Journal of Quality & Reliability Management 22(4): 376-392. Bazaraa , M.S., H.D. Sherali, C.M

  4. Influence of model errors in optimal sensor placement

    Science.gov (United States)

    Vincenzi, Loris; Simonini, Laura

    2017-02-01

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

  5. OPTIMAL TARGET TRAJECTORY ESTIMATION AND FILTERING USING NETWORKED SENSORS

    Institute of Scientific and Technical Information of China (English)

    Jiangping HU; Xiaoming HU

    2008-01-01

    Target tracking using distributed sensor network is in general a challenging problem because it always needs to deal with real-time processing of noisy information. In this paper the problem of using nonlinear sensors such as distance and direction sensors for estimating a moving target is studied.The problem is formulated as a prudent design of nonlinear filters for a linear system subject to noisy nonlinear measurements and partially unknown input, which is generated by an exogenous system.In the worst case where the input is completely unknown, the exogenous dynamics is reduced to the random walk model. It can be shown that the nonlinear filter will have optimal convergence if the number of the sensors are large enough and the convergence rate will be highly improved if the sensors are deployed appropriately. This actually raises an interesting issue on active sensing: how to optimally move the sensors if they are considered as mobile multi-agent systems? Finally, a simulation example is given to illustrate and validate the construction of our filter.

  6. 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......-changing environmental energy sources. In this paper, we present an improved and extended version of ODMAC and we analyze it by means of an analytical model that can approximate several performance metrics in an arbitrary network topology. The simulations and the analytical experiments show ODMAC's ability to satisfy...... three key properties of EH-WSNs: adaptability of energy consumption, distributed energy-aware load balancing and support for different application-specific requirements....

  7. Energy-Constrained Optimal Quantization for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Georgios B. Giannakis

    2008-02-01

    Full Text Available As low power, low cost, and longevity of transceivers are major requirements in wireless sensor networks, optimizing their design under energy constraints is of paramount importance. To this end, we develop quantizers under strict energy constraints to effect optimal reconstruction at the fusion center. Propagation, modulation, as well as transmitter and receiver structures are jointly accounted for using a binary symmetric channel model. We first optimize quantization for reconstructing a single sensor's measurement, and deriving the optimal number of quantization levels as well as the optimal energy allocation across bits. The constraints take into account not only the transmission energy but also the energy consumed by the transceiver's circuitry. Furthermore, we consider multiple sensors collaborating to estimate a deterministic parameter in noise. Similarly, optimum energy allocation and optimum number of quantization bits are derived and tested with simulated examples. Finally, we study the effect of channel coding on the reconstruction performance under strict energy constraints and jointly optimize the number of quantization levels as well as the number of channel uses.

  8. Computation of Optimal Actuator/Sensor Locations

    Science.gov (United States)

    2013-12-26

    systematically addressed. A mechatronic approach where controller design is integrated with actuator location was used. This effort was complicated by the... Mechatronics Engineering University of Waterloo Overview Many systems, such as acoustic noise and structural vibrations are distributed in space. (See Figure 1...either impossible, or else is unlikely to lead to locations that are close to optimal. A mechatronic approach where controller design is integrated

  9. Iterative implementation of the adaptive regularization yields optimality

    Institute of Scientific and Technical Information of China (English)

    MA; Qinghua; WANG; Yanfei

    2005-01-01

    The adaptive regularization method is first proposed by Ryzhikov et al. for the deconvolution in elimination of multiples. This method is stronger than the Tikhonov regularization in the sense that itis adaptive, i.e. it eliminates the small eigenvalues of theadjoint operator when it is nearly singular. We will show in this paper that the adaptive regularization can be implemented iterately. Some properties of the proposed non-stationary iterated adaptive regularization method are analyzed. The rate of convergence for inexact data is proved. Therefore the iterative implementation of the adaptive regularization can yield optimality.

  10. Adaptive optimization of agile organization of command and control resource

    Institute of Scientific and Technical Information of China (English)

    Yang Chunhui; Liu Junxian; Chen Honghui; Luo Xueshan

    2009-01-01

    Adaptive optimization is one of the means that agile organization of command and control resource (AOC2R) adapts for the dynamic battlefield environment. A math model of the adaptive optimization of AOC2R is put forward by analyzing the interrelating concept and research. The model takes the adaptive process as a multi-stage decision making problem. The 2-phases method is presented to calculate the model, which obtains the related parameters by running the colored Petri net (CPN) model of AOC2R and then searches for the result by ant colony optimization (ACO) algorithm integrated with genetic optimization techniques. The simulation results demonstrate that the proposed algorithm greatly improves the performance of AOC2R.

  11. Collaborative Object Framework for Adaptive System Optimization Project

    Data.gov (United States)

    National Aeronautics and Space Administration — TeamVision proposes that we research the feasibility of incorporating an adaptive object based optimization system into an existing multi-user object oriented...

  12. Optimization of the silicon sensors for the CMS tracker

    Energy Technology Data Exchange (ETDEWEB)

    Albergo, S.; Angarano, M.; Azzi, P.; Babucci, E.; Bacchetta, N.; Bader, A.; Bagliesi, G.; Basti, A.; Biggeri, U.; Biino, C.; Bilei, G.M.; Bisello, D.; Boemi, D.; Bosi, F.; Borello, L.; Braibant, S.; Breuker, H.; Brunetti, M.T.; Bruzzi, M.; Buffini, A.; Busoni, S.; Candelori, A.; Caner, A.; Castaldi, R.; Castro, A.; Catacchini, E.; Checcucci, B.; Ciampolini, P.; Civinini, C.; Costa, M.; Creanza, D.; D' Alessandro, R.; DeMaria, N.; Palma, M. de; Dell' Orso, R.; Dutta, S.; Favro, G.; Fiore, L.; Focardi, E.; French, M.; Freudenreich, K.; Frey, A. E-mail: ariane.frey@cern.ch; Friedl, M.; Fuertjes, A.; Giassi, A.; Giorgi, M.; Giraldo, A.; Glessing, W.; Gu, W.H.; Hall, G.; Hammarstrom, R.; Hebbeker, T.; Honkanen, A.; Honma, A.; Hrubec, J.; Huhtinen, M.; Kaminsky, A.; Karimaki, V.; Koenig, St.; Krammer, M.; Lariccia, P.; Lenzi, M.; Loreti, M.; Luebelsmeyer, K.; Lustermann, W.; Maettig, P.; Maggi, G.; Mannelli, M.; Mantovani, G.; Marchioro, A.; Mariotti, C.; Martignon, G.; Mc Evoy, B.; Meschini, M.; Messineo, A.; Migliore, E.; My, S.; Neviani, A.; Paccagnella, A.; Palla, F.; Pandoulas, D.; Papi, A.; Parrini, G.; Passeri, D.; Pernicka, M.; Pieri, M.; Piperov, S.; Potenza, R.; Radicci, V.; Raffaelli, F.; Raymond, M.; Rizzo, F.; Santocchia, A.; Segneri, G.; Selvaggi, G.; Servoli, L.; Sguazzoni, G.; Siedling, R.; Silvestris, L.; Starodumov, A.; Stavitski, I.; Surrow, B.; Tempesta, P.; Tonelli, G.; Tricomi, A.; Tuominiemi, J.; Tuuva, T.; Verdini, P.G.; Viertel, G.; Xie, Z.; Yahong, Li; Watts, S.; Wittmer, B

    2001-07-01

    The CMS experiment at the LHC will comprise a large silicon strip tracker. This article highlights some of the results obtained in the R and D studies for the optimization of its silicon sensors. Measurements of the capacitances and of the high voltage stability of the devices are presented before and after irradiation to the dose expected after the full lifetime of the tracker.

  13. Optimization of Pd Surface Plasmon Resonance sensors for hydrogen detection

    NARCIS (Netherlands)

    Perrotton, C.; Javahiraly, N.; Slaman, M.; Schreuders, H.; Dam, B.; Meyrueis, P.

    2011-01-01

    A design to optimize a fiber optic Surface Plasmon Resonance (SPR) sensor using Palladium as a sensitive layer for hydrogen detection is presented. In this approach, the sensitive layer is deposited on the core of a multimode fiber, after removing the optical cladding. The light is injected in the f

  14. Optimization of Pd Surface Plasmon Resonance sensors for hydrogen detection

    NARCIS (Netherlands)

    Perrotton, C.; Javahiraly, N.; Slaman, M.; Schreuders, H.; Dam, B.; Meyrueis, P.

    2011-01-01

    A design to optimize a fiber optic Surface Plasmon Resonance (SPR) sensor using Palladium as a sensitive layer for hydrogen detection is presented. In this approach, the sensitive layer is deposited on the core of a multimode fiber, after removing the optical cladding. The light is injected in the f

  15. Hardware Abstraction and Protocol Optimization for Coded Sensor Networks

    DEFF Research Database (Denmark)

    Nistor, Maricica; Roetter, Daniel Enrique Lucani; Barros, João

    2015-01-01

    -efficient protocols that use such an abstraction, as well as mechanisms to optimize a communication protocol in terms of energy consumption. The problem is modeled for different feedback-based techniques, where sensors are connected to a base station, either directly or through relays. We show that for four example......The design of the communication protocols in wireless sensor networks (WSNs) often neglects several key characteristics of the sensor's hardware, while assuming that the number of transmitted bits is the dominating factor behind the system's energy consumption. A closer look at the hardware...... platforms, the use of relays may decrease up to 4.5 times the total energy consumption when the protocol and the hardware are carefully matched. We conclude that: 1) the energy budget for a communication protocol varies significantly on different sensor platforms; and 2) the protocols can be judiciously...

  16. Optimize Etching Based Single Mode Fiber Optic Temperature Sensor

    Directory of Open Access Journals (Sweden)

    Ajay Kumar

    2014-02-01

    Full Text Available This paper presents a description of etching process for fabrication single mode optical fiber sensors. The process of fabrication demonstrates an optimized etching based method to fabricate single mode fiber (SMF optic sensors in specified constant time and temperature. We propose a single mode optical fiber based temperature sensor, where the temperature sensing region is obtained by etching its cladding diameter over small length to a critical value. It is observed that the light transmission through etched fiber at 1550 nm wavelength optical source becomes highly temperature sensitive, compared to the temperature insensitive behavior observed in un-etched fiber for the range on 30ºC to 100ºC at 1550 nm. The sensor response under temperature cycling is repeatable and, proposed to be useful for low frequency analogue signal transmission over optical fiber by means of inline thermal modulation approach.

  17. Adaptive Mixed Finite Element Methods for Parabolic Optimal Control Problems

    OpenAIRE

    Zuliang Lu

    2011-01-01

    We will investigate the adaptive mixed finite element methods for parabolic optimal control problems. The state and the costate are approximated by the lowest-order Raviart-Thomas mixed finite element spaces, and the control is approximated by piecewise constant elements. We derive a posteriori error estimates of the mixed finite element solutions for optimal control problems. Such a posteriori error estimates can be used to construct more efficient and reliable adaptive mixed finite element ...

  18. Optimism and adaptation to multiple sclerosis: what does optimism mean?

    NARCIS (Netherlands)

    Fournier, M.; Ridder, D. de; Bensing, J.

    1999-01-01

    The aim of the present study was to determine the meaning of optimism by explicating the dimensions underlying the notion and their links to adjusting to MS. Seventy-three patients responded to optimism questionnaires (i.e., the LOT, Generalized Self-Efficacy Scale) and outcome questionnaires. In co

  19. Optimism and Adaptation to Multiple Sclerosis: What Does Optimism Mean?

    NARCIS (Netherlands)

    Fournier, M.; Ridder, D.T.D. de; Bensing, J.

    1999-01-01

    The aim of the present study was to determine the meaning of optimism by explicating the dimensions underlying the notion and their links to adjusting to MS. Seventy-three patients responded to optimism questionnaire s (i.e., the LOT, Generalized Self-Efficacy Scale) and outcome questionnaires. In c

  20. Optimism and adaptation to multiple sclerosis: what does optimism mean?

    NARCIS (Netherlands)

    Fournier, M.; Ridder, D. de; Bensing, J.

    1999-01-01

    The aim of the present study was to determine the meaning of optimism by explicating the dimensions underlying the notion and their links to adjusting to MS. Seventy-three patients responded to optimism questionnaires (i.e., the LOT, Generalized Self-Efficacy Scale) and outcome questionnaires. In

  1. Optimization of autonomous magnetic field sensor consisting of giant magnetoimpedance sensor and surface acoustic wave transducer

    KAUST Repository

    Li, Bodong

    2012-11-01

    This paper presents a novel autonomous thin film magnetic field sensor consisting of a tri-layer giant magnetoimpedance sensor and a surface acoustic wave transponder. Double and single electrode interdigital transducer (IDT) designs are employed and compared. The integrated sensor is fabricated using standard microfabrication technology. The results show the double electrode IDT has an advantage in terms of the sensitivity. In order to optimize the matching component, a simulation based on P-matrix is carried out. A maximum change of 2.4 dB of the reflection amplitude and a sensitivity of 0.34 dB/Oe are obtained experimentally. © 2012 IEEE.

  2. LIMIT THEOREMS AND OPTIMAL DESIGN WITH ADAPTIVE URN MODELS

    Institute of Scientific and Technical Information of China (English)

    CHEN Guijing; ZHU Chunhua; WANG Yao-hung

    2005-01-01

    In this paper we study urn model, using some available estimates of successes probabilities, and adding particle parameter, we establish adaptive models. We obtain some strong convergence theorems, rates of convergence, asymptotic normality of components in the urn, and estimates. With these asymptotical results, we show that the adaptive designs given in this paper are asymptotically optimal designs.

  3. Optimization of floodplain monitoring sensors through an entropy approach

    Science.gov (United States)

    Ridolfi, E.; Yan, K.; Alfonso, L.; Di Baldassarre, G.; Napolitano, F.; Russo, F.; Bates, P. D.

    2012-04-01

    To support the decision making processes of flood risk management and long term floodplain planning, a significant issue is the availability of data to build appropriate and reliable models. Often the required data for model building, calibration and validation are not sufficient or available. A unique opportunity is offered nowadays by the globally available data, which can be freely downloaded from internet. However, there remains the question of what is the real potential of those global remote sensing data, characterized by different accuracies, for global inundation monitoring and how to integrate them with inundation models. In order to monitor a reach of the River Dee (UK), a network of cheap wireless sensors (GridStix) was deployed both in the channel and in the floodplain. These sensors measure the water depth, supplying the input data for flood mapping. Besides their accuracy and reliability, their location represents a big issue, having the purpose of providing as much information as possible and at the same time as low redundancy as possible. In order to update their layout, the initial number of six sensors has been increased up to create a redundant network over the area. Through an entropy approach, the most informative and the least redundant sensors have been chosen among all. First, a simple raster-based inundation model (LISFLOOD-FP) is used to generate a synthetic GridStix data set of water stages. The Digital Elevation Model (DEM) used for hydraulic model building is the globally and freely available SRTM DEM. Second, the information content of each sensor has been compared by evaluating their marginal entropy. Those with a low marginal entropy are excluded from the process because of their low capability to provide information. Then the number of sensors has been optimized considering a Multi-Objective Optimization Problem (MOOP) with two objectives, namely maximization of the joint entropy (a measure of the information content) and

  4. Designing and Optimizing Future Spaceborne Multi-angular, Polarimetric Sensors

    Science.gov (United States)

    Petroy, S. B.; Nicholson, R. E.; D'Entremont, R. P.; Snell, H. E.

    2004-05-01

    Polarimetric measurements in the visible/near-infrared spectral region improve aerosol and cloud microphysical and compositional retrievals. The retrieval approaches exploit the unique polarimetric signatures of aerosols and clouds as function of scattering angle, thereby driving the requirement for data collection over a large range of scattering angles (ideally between 0 and 180 degrees). Scattering angle coverage is a function both of the sensor/sun/target geometry and the sensor architectural approach toward acquiring multi-angular data. These two functions must be considered when designing and implementing a spaceborne, multi-angular polarimetric sensor. The orbital geometry trade is dictated by the range of possible orbits and will quickly reduce to a subset of optimal orbital scenarios. However, the desired parameter of interest (aerosols vs. clouds properties), its spatial variability, and global extent must be considered when selecting an optimal orbit. For example, while a noon-equatorial crossing-time provides the best scattering angle coverage for the retrievals, the increased presence of clouds may preclude use of much of the data for characterizing aerosols. The sensor architectural trade investigates differing sensor approaches to providing sufficient scattering angle coverage. Current polarimetric sensor designs include both the over-lapping imagery approach (e.g. POLarization and Directionality of the Earth's Reflectances - POLDER) and the single-pixel, scanning approach (e.g. Research Scanning Polarimeter - RSP). POLDER (a spaceborne sensor) traded the benefit of image data with a large swath width against the collection of simultaneous polarimetry. RSP (an airborne sensor) collects multi-angular data by scanning the air mass during over-flight with a set of polarimetric compensating mirrors. The RSP design allows for simultaneous polarimetry and potentially very large scattering angle ranges on orbit, but is restricted to a single-pixel detector

  5. Adaptive optimization and control using neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Mead, W.C.; Brown, S.K.; Jones, R.D.; Bowling, P.S.; Barnes, C.W.

    1993-10-22

    Recent work has demonstrated the ability of neural-network-based controllers to optimize and control machines with complex, non-linear, relatively unknown control spaces. We present a brief overview of neural networks via a taxonomy illustrating some capabilities of different kinds of neural networks. We present some successful control examples, particularly the optimization and control of a small-angle negative ion source.

  6. Adaptive UAV attitude estimation employing unscented Kalman Filter, FOAM and low-cost MEMS sensors.

    Science.gov (United States)

    de Marina, Héctor García; Espinosa, Felipe; Santos, Carlos

    2012-01-01

    Navigation employing low cost MicroElectroMechanical Systems (MEMS) sensors in Unmanned Aerial Vehicles (UAVs) is an uprising challenge. One important part of this navigation is the right estimation of the attitude angles. Most of the existent algorithms handle the sensor readings in a fixed way, leading to large errors in different mission stages like take-off aerobatic maneuvers. This paper presents an adaptive method to estimate these angles using off-the-shelf components. This paper introduces an Attitude Heading Reference System (AHRS) based on the Unscented Kalman Filter (UKF) using the Fast Optimal Attitude Matrix (FOAM) algorithm as the observation model. The performance of the method is assessed through simulations. Moreover, field experiments are presented using a real fixed-wing UAV. The proposed low cost solution, implemented in a microcontroller, shows a satisfactory real time performance.

  7. High-speed SPGD wavefront controller for an adaptive optics system without wavefront sensor

    Science.gov (United States)

    Wang, Caixia; Li, Xinyang; Li, Mei; Ye, Jongwei; Chen, Bo

    2010-10-01

    A non-conventional adaptive optics system based on direct system performance metric optimization is illustrated. The system does not require wave-front sensor which is difficult to work under the poor condition such as beam cleanup for the anomalous light beam. The system comprises a high speed wavefront controller based on Stochastic Parallel Gradient Descent (SPGD) Algorithm, a deformable mirror, a tip/tilt mirror and a far-field system performance metric sensor. The architecture of the wave-front controller is based on a combination of Field Programmable Gate Array (FPGA) and floating-point Digital Signal Processor (DSP). The Zernike coefficient information is applied to improve the iteration speed. The experimental results show that the beam cleanup system based on SPGD keep a high iteration speed. The controller can compensate the wavefront aberration and tilt excursion effectively.

  8. Optimal Sensor Layouts in Underwater Locomotory Systems

    Science.gov (United States)

    Colvert, Brendan; Kanso, Eva

    2015-11-01

    Retrieving and understanding global flow characteristics from local sensory measurements is a challenging but extremely relevant problem in fields such as defense, robotics, and biomimetics. It is an inverse problem in that the goal is to translate local information into global flow properties. In this talk we present techniques for optimization of sensory layouts within the context of an idealized underwater locomotory system. Using techniques from fluid mechanics and control theory, we show that, under certain conditions, local measurements can inform the submerged body about its orientation relative to the ambient flow, and allow it to recognize local properties of shear flows. We conclude by commenting on the relevance of these findings to underwater navigation in engineered systems and live organisms.

  9. Computer simulation of optimal sensor locations in loading identification

    Science.gov (United States)

    Li, Dong-Sheng; Li, Hong-Nan; Guo, Xing L.

    2003-07-01

    A method is presented for the selection of a set of sensor locations from a larger candidate sent for the purpose of structural loading identification. The method ranks the candidate sensor locations according to their effectiveness for identifying the given known loadings. Measurement locations that yield abnormal jumps in identification results or increase the condition number of the frequency response function are removed. The final sensor configuration tends to minimize the error of the loading identification results and the condition number of the frequency response function. The initial candidate set is selected based on the modal kinetic energy distribution that gives a measure of the dynamic contribution of each physical degree freedom to each of the target mode shapes of interest. In addition, excitation location is considered when selecting appropriate response measurement locations. This method was successfully applied to the optimal sensor location selection and loading identification of a uniform cantilever beam in experiment. It is shown that computer simulation is a good way to select the optimal sensor location for loading identification.

  10. Placement optimization of actuators and sensors for gyroelastic body

    Directory of Open Access Journals (Sweden)

    Quan Hu

    2015-03-01

    Full Text Available Gyroelastic body refers to a flexible structure with a distribution of stored angular momentum provided by fly wheels or control moment gyroscopes. The angular momentum devices can exert active torques to the structure for vibration suppression or shape control. This article mainly focuses on the placement optimization issue of the actuators and sensors on the gyroelastic body. The control moment gyroscopes and angular rate sensors are adopted as actuators and sensors, respectively. The equations of motion of the gyroelastic body incorporating the detailed actuator dynamics are linearized to a loosely coupled state-space model. Two optimization approaches are developed for both constrained and unconstrained gyroelastic bodies. The first is based on the controllability and observability matrices of the system. It is only applicable to the collocated actuator and sensor pairs. The second criterion is formulated from the concept of controllable and observable subspaces. It is capable of handling the cases of both collocated and noncollocated actuator and sensor pairs. The illustrative examples of a cantilevered beam and an unconstrained plate demonstrate the clear physical meaning and rationality of the two proposed methods.

  11. Geometry optimization for micro-pressure sensor considering dynamic interference.

    Science.gov (United States)

    Yu, Zhongliang; Zhao, Yulong; Li, Lili; Tian, Bian; Li, Cun

    2014-09-01

    Presented is the geometry optimization for piezoresistive absolute micro-pressure sensor. A figure of merit called the performance factor (PF) is defined as a quantitative index to describe the comprehensive performances of a sensor including sensitivity, resonant frequency, and acceleration interference. Three geometries are proposed through introducing islands and sensitive beams into typical flat diaphragm. The stress distributions of sensitive elements are analyzed by finite element method. Multivariate fittings based on ANSYS simulation results are performed to establish the equations about surface stress, deflection, and resonant frequency. Optimization by MATLAB is carried out to determine the dimensions of the geometries. Convex corner undercutting is evaluated. Each PF of the three geometries with the determined dimensions is calculated and compared. Silicon bulk micromachining is utilized to fabricate the prototypes of the sensors. The outputs of the sensors under both static and dynamic conditions are tested. Experimental results demonstrate the rationality of the defined performance factor and reveal that the geometry with quad islands presents the highest PF of 210.947 Hz(1/4). The favorable overall performances enable the sensor more suitable for altimetry.

  12. On adaptive optimal input design: A bioreactor case study

    NARCIS (Netherlands)

    Stigter, J.D.; Vries, D.; Keesman, K.J.

    2006-01-01

    The problem of optimal input design (OID) for a fed-batch bioreactor case study is solved recursively. Here an adaptive receding horizon optimal control problem, involving the so-called E-criterion, is solved on-line, using the current estimate of the parameter vector at each sample instant {tk, k =

  13. Optimization of fingernail sensor design based on fingernail imaging

    Science.gov (United States)

    Abu-Khalaf, Jumana M.; Mascaro, Stephen A.

    2010-08-01

    This paper describes the optimization of fingernail sensors for measuring fingertip touch forces for human-computer interaction. The fingernail sensor uses optical reflectance photoplethysmography to measure the change in blood perfusion in the fingernail bed when the fingerpad touches a surface with various forces. In the original fingernail sensor, color changes observed through the fingernail have been measured by mounting an array of six LEDs (Light Emitting Diodes) and eight photodetectors on the fingernail in a laterally symmetric configuration. The optical components were located such that each photodiode had at least one neighboring LED. The role of each of the photodetectors was investigated in terms of the effect of removing one or more photodetectors on force prediction estimation. The analysis suggested designing the next generation of fingernail sensors with less than eight photodetectors. This paper proposes an optimal redesign by analyzing a photographic catalog composed of six different force poses, representing average fingernail coloration patterns of fifteen human subjects. It also introduces an optical model that describes light transmission between an LED and a photodiode, and predicts the optimal locations of the optoelectronic devices in the fingernail area.

  14. Optimal Sensor and Actuator Location for Unstable Systems

    DEFF Research Database (Denmark)

    Shaker, Hamid Reza; Tahavori, Maryamsadat

    2013-01-01

    on the processes. Dually the problem of placing actuators on the processes is equally important. In this paper, the problem of determining optimal sensor and actuator locations for the linear systems is addressed. The problem of the sensor locations is viewed as the problem of maximizing the output energy...... proposed so far, only support stable systems. However, in industrial practices it is often the case that the system, which is needed to be controlled, is not stable. The method which is proposed in this paper is a general method in the sense that it supports both stable and unstable systems. The technique...

  15. Optimal sensor fusion for land vehicle navigation

    Energy Technology Data Exchange (ETDEWEB)

    Morrow, J.D.

    1990-10-01

    Position location is a fundamental requirement in autonomous mobile robots which record and subsequently follow x,y paths. The Dept. of Energy, Office of Safeguards and Security, Robotic Security Vehicle (RSV) program involves the development of an autonomous mobile robot for patrolling a structured exterior environment. A straight-forward method for autonomous path-following has been adopted and requires digitizing'' the desired road network by storing x,y coordinates every 2m along the roads. The position location system used to define the locations consists of a radio beacon system which triangulates position off two known transponders, and dead reckoning with compass and odometer. This paper addresses the problem of combining these two measurements to arrive at a best estimate of position. Two algorithms are proposed: the optimal'' algorithm treats the measurements as random variables and minimizes the estimate variance, while the average error'' algorithm considers the bias in dead reckoning and attempts to guarantee an average error. Data collected on the algorithms indicate that both work well in practice. 2 refs., 7 figs.

  16. Extragalactic Fields Optimized for Adaptive Optics

    Science.gov (United States)

    2011-03-01

    DAVID MONETIO Received 2010 luly 19; accepted 2010 December 30; published 2011 March 1 ABSTRACT. In this article we present the coordinates of 67 55’ x...fields. In some cases adaptive optics observations undertaken in the fields given in this article would be orders of magnitude more efficient than...expectations of considerable pro- gress in this subject with the advent of 30 m class extremely large telescopes ( ELTs ). A basic problem with unde1taking

  17. AREA OPTIMIZED FPGA IMPLEMENTATION OF ADAPTIVE BEAMFORMER

    Directory of Open Access Journals (Sweden)

    Harpreet Kaur

    2012-06-01

    Full Text Available Quadratic Rotation decomposition (QRD based recursive least squares (RLS algorithm can be used in variety of communication applications and its low complexity implementation can be of interest. In this paper we have presented an application of QRD based RLS algorithm using Coordinate Rotation by Digital Computer (CORDIC operator for implementing an adaptive beamformer. FPGA resource estimates along with actual implementation results have been presented and are being compared with its existing implementation.

  18. 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.

  19. Noise in adaptive interferometric fiber sensor based on population dynamic grating in erbium-doped fiber.

    Science.gov (United States)

    Stepanov, Serguei; Sánchez, Marcos Plata; Hernández, Eliseo Hernández

    2016-09-10

    Experimental investigations of the main noise sources that limit the sensitivity of the adaptive interferometric all-fiber sensors operating in the communication wavelength region are reported. Adaptive properties (i.e., the autostabilization of an optimal operation point of the interferometer) are enabled by the dynamic population grating recorded in a segment of the erbium-doped fiber (EDF) at milliwatt-scale cw power in the 1480-1560 nm spectral range. The utilized symmetric Sagnac configuration with low light internal reflections ensures reduced sensitivity of the sensor to phase noise of the laser, while intensity noise is reduced to an insignificant level by the balanced detection scheme. It is shown that the fluorescence from the erbium ions, excited by the counterpropagating waves recording the grating, increases the noise level from the fundamental shot noise approximately by a factor of 2-3 only. It is also shown that conventional communication distributed feedback (DFB) semiconductor lasers with megahertz linewidth are not suitable for high-sensitivity applications of such sensors. Because of inevitable backreflections from the output terminal devices (photodiodes, insulators, circulator), the above-mentioned fundamental noise level is increased by 2 orders of magnitude due to high phase noise of the DFB laser.

  20. A self-optimizing scheme for energy balanced routing in Wireless Sensor Networks using SensorAnt.

    Science.gov (United States)

    Shamsan Saleh, Ahmed M; Ali, Borhanuddin Mohd; Rasid, Mohd Fadlee A; Ismail, Alyani

    2012-01-01

    Planning of energy-efficient protocols is critical for Wireless Sensor Networks (WSNs) because of the constraints on the sensor nodes' energy. The routing protocol should be able to provide uniform power dissipation during transmission to the sink node. In this paper, we present a self-optimization scheme for WSNs which is able to utilize and optimize the sensor nodes' resources, especially the batteries, to achieve balanced energy consumption across all sensor nodes. This method is based on the Ant Colony Optimization (ACO) metaheuristic which is adopted to enhance the paths with the best quality function. The assessment of this function depends on multi-criteria metrics such as the minimum residual battery power, hop count and average energy of both route and network. This method also distributes the traffic load of sensor nodes throughout the WSN leading to reduced energy usage, extended network life time and reduced packet loss. Simulation results show that our scheme performs much better than the Energy Efficient Ant-Based Routing (EEABR) in terms of energy consumption, balancing and efficiency.

  1. A Self-Optimizing Scheme for Energy Balanced Routing in Wireless Sensor Networks Using SensorAnt

    Directory of Open Access Journals (Sweden)

    Alyani Ismail

    2012-08-01

    Full Text Available Planning of energy-efficient protocols is critical for Wireless Sensor Networks (WSNs because of the constraints on the sensor nodes’ energy. The routing protocol should be able to provide uniform power dissipation during transmission to the sink node. In this paper, we present a self-optimization scheme for WSNs which is able to utilize and optimize the sensor nodes’ resources, especially the batteries, to achieve balanced energy consumption across all sensor nodes. This method is based on the Ant Colony Optimization (ACO metaheuristic which is adopted to enhance the paths with the best quality function. The assessment of this function depends on multi-criteria metrics such as the minimum residual battery power, hop count and average energy of both route and network. This method also distributes the traffic load of sensor nodes throughout the WSN leading to reduced energy usage, extended network life time and reduced packet loss. Simulation results show that our scheme performs much better than the Energy Efficient Ant-Based Routing (EEABR in terms of energy consumption, balancing and efficiency.

  2. Selection of optimal sensors for predicting performance of polymer electrolyte membrane fuel cell

    Science.gov (United States)

    Mao, Lei; Jackson, Lisa

    2016-10-01

    In this paper, sensor selection algorithms are investigated based on a sensitivity analysis, and the capability of optimal sensors in predicting PEM fuel cell performance is also studied using test data. The fuel cell model is developed for generating the sensitivity matrix relating sensor measurements and fuel cell health parameters. From the sensitivity matrix, two sensor selection approaches, including the largest gap method, and exhaustive brute force searching technique, are applied to find the optimal sensors providing reliable predictions. Based on the results, a sensor selection approach considering both sensor sensitivity and noise resistance is proposed to find the optimal sensor set with minimum size. Furthermore, the performance of the optimal sensor set is studied to predict fuel cell performance using test data from a PEM fuel cell system. Results demonstrate that with optimal sensors, the performance of PEM fuel cell can be predicted with good quality.

  3. Particle swarm optimization for optimal sensor placement in ultrasonic SHM systems

    Science.gov (United States)

    Blanloeuil, Philippe; Nurhazli, Nur A. E.; Veidt, Martin

    2016-04-01

    A Particle Swarm Optimization (PSO) algorithm is used to improve sensors placement in an ultrasonic Structural Health Monitoring (SHM) system where the detection is performed through the beam-forming imaging algorithm. The imaging algorithm reconstructs the defect image and estimates its location based on analytically generated signals, considering circular through hole damage in an aluminum plate as the tested structure. Then, the PSO algorithm changes the position of sensors to improve the accuracy of the detection. Thus, the two algorithms are working together iteratively to optimize the system configuration, taking into account a complete modeling of the SHM system. It is shown that this approach can provide good sensors placements for detection of multiple defects in the target area, and for different numbers of sensors.

  4. Adaptive Sampling for Learning Gaussian Processes Using Mobile Sensor Networks

    Directory of Open Access Journals (Sweden)

    Yunfei Xu

    2011-03-01

    Full Text Available This paper presents a novel class of self-organizing sensing agents that adaptively learn an anisotropic, spatio-temporal Gaussian process using noisy measurements and move in order to improve the quality of the estimated covariance function. This approach is based on a class of anisotropic covariance functions of Gaussian processes introduced to model a broad range of spatio-temporal physical phenomena. The covariance function is assumed to be unknown a priori. Hence, it is estimated by the maximum a posteriori probability (MAP estimator. The prediction of the field of interest is then obtained based on the MAP estimate of the covariance function. An optimal sampling strategy is proposed to minimize the information-theoretic cost function of the Fisher Information Matrix. Simulation results demonstrate the effectiveness and the adaptability of the proposed scheme.

  5. Optimization of wireless sensor networks based on chicken swarm optimization algorithm

    Science.gov (United States)

    Wang, Qingxi; Zhu, Lihua

    2017-05-01

    In order to reduce the energy consumption of wireless sensor network and improve the survival time of network, the clustering routing protocol of wireless sensor networks based on chicken swarm optimization algorithm was proposed. On the basis of LEACH agreement, it was improved and perfected that the points on the cluster and the selection of cluster head using the chicken group optimization algorithm, and update the location of chicken which fall into the local optimum by Levy flight, enhance population diversity, ensure the global search capability of the algorithm. The new protocol avoided the die of partial node of intensive using by making balanced use of the network nodes, improved the survival time of wireless sensor network. The simulation experiments proved that the protocol is better than LEACH protocol on energy consumption, also is better than that of clustering routing protocol based on particle swarm optimization algorithm.

  6. Hybrid and adaptive meta-model-based global optimization

    Science.gov (United States)

    Gu, J.; Li, G. Y.; Dong, Z.

    2012-01-01

    As an efficient and robust technique for global optimization, meta-model-based search methods have been increasingly used in solving complex and computation intensive design optimization problems. In this work, a hybrid and adaptive meta-model-based global optimization method that can automatically select appropriate meta-modelling techniques during the search process to improve search efficiency is introduced. The search initially applies three representative meta-models concurrently. Progress towards a better performing model is then introduced by selecting sample data points adaptively according to the calculated values of the three meta-models to improve modelling accuracy and search efficiency. To demonstrate the superior performance of the new algorithm over existing search methods, the new method is tested using various benchmark global optimization problems and applied to a real industrial design optimization example involving vehicle crash simulation. The method is particularly suitable for design problems involving computation intensive, black-box analyses and simulations.

  7. Optimal adaptation to extreme rainfalls under climate change

    Science.gov (United States)

    Rosbjerg, Dan

    2017-04-01

    More intense and frequent rainfalls have increased the number of urban flooding events in recent years, prompting adaptation efforts. Economic optimization is considered an efficient tool to decide on the design level for adaptation. The costs associated with a flooding to the T-year level and the annual capital and operational costs of adapting to this level are described with log-linear relations. The total flooding costs are developed as the expected annual damage of flooding above the T-year level plus the annual capital and operational costs for ensuring no flooding below the T-year level. The value of the return period T that corresponds to the minimum of the sum of these costs will then be the optimal adaptation level. The change in climate, however, is expected to continue in the next century, which calls for expansion of the above model. The change can be expressed in terms of a climate factor (the ratio between the future and the current design level) which is assumed to increase in time. This implies increasing costs of flooding in the future for many places in the world. The optimal adaptation level is found for immediate as well as for delayed adaptation. In these cases the optimum is determined by considering the net present value of the incurred costs during a sufficiently long time span. Immediate as well as delayed adaptation is considered.

  8. Optimal adaptation to extreme rainfalls in current and future climate

    Science.gov (United States)

    Rosbjerg, Dan

    2017-01-01

    More intense and frequent rainfalls have increased the number of urban flooding events in recent years, prompting adaptation efforts. Economic optimization is considered an efficient tool to decide on the design level for adaptation. The costs associated with a flooding to the T-year level and the annual capital and operational costs of adapting to this level are described with log-linear relations. The total flooding costs are developed as the expected annual damage of flooding above the T-year level plus the annual capital and operational costs for ensuring no flooding below the T-year level. The value of the return period T that corresponds to the minimum of the sum of these costs will then be the optimal adaptation level. The change in climate, however, is expected to continue in the next century, which calls for expansion of the above model. The change can be expressed in terms of a climate factor (the ratio between the future and the current design level) which is assumed to increase in time. This implies increasing costs of flooding in the future for many places in the world. The optimal adaptation level is found for immediate as well as for delayed adaptation. In these cases, the optimum is determined by considering the net present value of the incurred costs during a sufficiently long time-span. Immediate as well as delayed adaptation is considered.

  9. Optimizing the Materials Response in Humidity Capacitive Sensors

    Directory of Open Access Journals (Sweden)

    Elham Noroozi Afshar

    2015-10-01

    Full Text Available The number of humidity outputs on the cap of a cylindrical capacitance sensor is optimized by designing three different probes with direct and indirect windows. The time interval is measured within which 30-70 % humidity can influence the dielectric constant and conductivity of the capacitance when exposed to a range of relative humidity. It is then compared with a simple set-up including a simplified equivalent circuit. The direct probes had four and double outputs on the window of the cylindrical capacitive sensor while the indirect probe had a thin plastic layer only. We observed that the dielectric constant and its conductivity depend closely to the humidity outgoing pathway and also to the increasing rate of humidity between the capacitance plates. The final variation in the materials properties alters the capacitance of the sensor which is measured simply by a LCR. This technique presents a simple method for tracking the recovery and reliability of the humidity sensors over time and assists in optimizing and controlling the materials response to the relative environment humidity. As a result, by controlling the environment humidity rate (0.02 %/s., we could measure the increment rate of capacitance with accuracy of 0.01 pf/%.

  10. Optimization of the silicon sensors for the CMS tracker

    CERN Document Server

    Albergo, S; Azzi, P; Babucci, E; Bacchetta, N; Bader, A J; Bagliesi, G; Basti, A; Biggeri, U; Biino, C; Bilei, G M; Bisello, D; Boemi, D; Bosi, F; Borello, L; Braibant, S; Breuker, Horst; Unettib, M T; Bruzzi, Mara; Buffini, A; Busoni, S; Candelori, A; Caner, A; Castaldi, R; Castro, A; Catacchini, E; Checcucci, B; Ciampolini, P; Civinini, C; Costa, M; Creanza, D; D'Alessandro, R; Demaria, N; De Palma, M; Dell'Orso, R; Dutta, S; Favro, G; Fiore, L; Focardi, E; French, M; Freudenreich, Klaus; Frey, A; Friedl, M; Fürtjes, A; Giassi, A; Giorgi, M A; Giraldo, A; Glessing, W D; Gu, W H; Hall, G; Hammarström, R; Hebbeker, T; Honkanen, A; Honma, A; Hrubec, Josef; Huhtinen, M; Kaminski, A; Karimäki, V; König, S; Krammer, Manfred; Lariccia, P; Lenzi, M; Loreti, M; Lübelsmeyer, K; Lustermann, W; Mättig, P; Maggi, G; Mannelli, M; Mantovani, G C; Marchioro, A; Mariotti, C; Martignon, G; McEvoy, B; Meschini, M; Messineo, A; Migliore, E; My, S; Neviani, A; Paccagella, A; Palla, Fabrizio; Pandoulas, D; Papi, A; Parrini, G; Passeri, D; Pernicka, Manfred; Pieri, M; Piperov, S; Potenza, R; Radicci, V; Raffaelli, F; Raymond, M; Siedling, R; Silvestris, L; Starodumov, Andrei; Stavitski, I; Surrow, B; Tempesta, P; Tonelli, G; Tricomi, A; Tuominiemi, Jorma; Tuuva, T; Verdini, P G; Viertel, Gert M; Xie, Z; Yahong, L; Watts, S; Wittmer, B

    2001-01-01

    The CMS experiment at the LHC will comprise a large silicon strip tracker. This article highlights some of the results obtained in the R&D studies for the optimization of its silicon sensors. Measurements of the capacitances and of the high voltage stability of the devices are presented before and after irradiation to the dose expected after the full lifetime of the tracker. (7 refs).

  11. Design of transition edge sensor microcalorimeters for optimal performance

    Energy Technology Data Exchange (ETDEWEB)

    Bandler, S.R. E-mail: sbandler@milkyway.gsfc.nasa.gov; Figueroa-Feliciano, E.; Stahle, C.K.; Boyce, K.; Brekosky, R.; Chervenak, J.; Finkbeiner, F.; Kelley, R.; Lindeman, M.; Porter, F.S.; Saab, T

    2004-03-11

    We have developed a model for transition edge sensors to optimize performance under a variety of different conditions. There are three design trade-offs when engineering a microcalorimeter for a particular application: energy resolution, energy range and maximum count rate. All three are interdependent and are determined by various design parameters such as the detector heat capacity, the sharpness of the transition, and the thermal conductance of the detector to the frame. Our model includes all known sources of intrinsic noise in our calorimeters including the observed broad band excess noise. We will present the results of this model, and its predictions for optimally designed microcalorimeters.

  12. An Optimal Control Modification to Model-Reference Adaptive Control for Fast Adaptation

    Science.gov (United States)

    Nguyen, Nhan T.; Krishnakumar, Kalmanje; Boskovic, Jovan

    2008-01-01

    This paper presents a method that can achieve fast adaptation for a class of model-reference adaptive control. It is well-known that standard model-reference adaptive control exhibits high-gain control behaviors when a large adaptive gain is used to achieve fast adaptation in order to reduce tracking error rapidly. High gain control creates high-frequency oscillations that can excite unmodeled dynamics and can lead to instability. The fast adaptation approach is based on the minimization of the squares of the tracking error, which is formulated as an optimal control problem. The necessary condition of optimality is used to derive an adaptive law using the gradient method. This adaptive law is shown to result in uniform boundedness of the tracking error by means of the Lyapunov s direct method. Furthermore, this adaptive law allows a large adaptive gain to be used without causing undesired high-gain control effects. The method is shown to be more robust than standard model-reference adaptive control. Simulations demonstrate the effectiveness of the proposed method.

  13. On the Optimal Location of Sensors for Parametric Identification of Linear Systems

    DEFF Research Database (Denmark)

    Kirkegaard, Poul Henning; Brincker, Rune

    1994-01-01

    An outline of the field of optimal location of sensors for parametric identification of linear structural systems is presented. There are few papers devoted to the case of optimal location of sensors in which the measurements are modeled by a random field with non-trivial covariance function...... with variations in the number and location of sensors. Further, the influence of noise on the optimal location of the sensors is investigated. It is found that the optimal locations of sensors seem to become less sensitive to e.g. the noise-to-signal ratio within increasing number of sensors....

  14. Optimized Feature Extraction for Temperature-Modulated Gas Sensors

    Directory of Open Access Journals (Sweden)

    Alexander Vergara

    2009-01-01

    Full Text Available One of the most serious limitations to the practical utilization of solid-state gas sensors is the drift of their signal. Even if drift is rooted in the chemical and physical processes occurring in the sensor, improved signal processing is generally considered as a methodology to increase sensors stability. Several studies evidenced the augmented stability of time variable signals elicited by the modulation of either the gas concentration or the operating temperature. Furthermore, when time-variable signals are used, the extraction of features can be accomplished in shorter time with respect to the time necessary to calculate the usual features defined in steady-state conditions. In this paper, we discuss the stability properties of distinct dynamic features using an array of metal oxide semiconductors gas sensors whose working temperature is modulated with optimized multisinusoidal signals. Experiments were aimed at measuring the dispersion of sensors features in repeated sequences of a limited number of experimental conditions. Results evidenced that the features extracted during the temperature modulation reduce the multidimensional data dispersion among repeated measurements. In particular, the Energy Signal Vector provided an almost constant classification rate along the time with respect to the temperature modulation.

  15. Optimal sensor placement using FRFs-based clustering method

    Science.gov (United States)

    Li, Shiqi; Zhang, Heng; Liu, Shiping; Zhang, Zhe

    2016-12-01

    The purpose of this work is to develop an optimal sensor placement method by selecting the most relevant degrees of freedom as actual measure position. Based on observation matrix of a structure's frequency response, two optimal criteria are used to avoid the information redundancy of the candidate degrees of freedom. By using principal component analysis, the frequency response matrix can be decomposed into principal directions and their corresponding singular. A relatively small number of principal directions will maintain a system's dominant response information. According to the dynamic similarity of each degree of freedom, the k-means clustering algorithm is designed to classify the degrees of freedom, and effective independence method deletes the sensors which are redundant of each cluster. Finally, two numerical examples and a modal test are included to demonstrate the efficient of the derived method. It is shown that the proposed method provides a way to extract sub-optimal sets and the selected sensors are well distributed on the whole structure.

  16. Adaptive Techniques to find Optimal Planar Boxes

    CERN Document Server

    Barbay, J; Pérez-Lantero, P

    2012-01-01

    Given a set $P$ of $n$ planar points, two axes and a real-valued score function $f()$ on subsets of $P$, the Optimal Planar Box problem consists in finding a box (i.e. axis-aligned rectangle) $H$ maximizing $f(H\\cap P)$. We consider the case where $f()$ is monotone decomposable, i.e. there exists a composition function $g()$ monotone in its two arguments such that $f(A)=g(f(A_1),f(A_2))$ for every subset $A\\subseteq P$ and every partition $\\{A_1,A_2\\}$ of $A$. In this context we propose a solution for the Optimal Planar Box problem which performs in the worst case $O(n^2\\lg n)$ score compositions and coordinate comparisons, and much less on other classes of instances defined by various measures of difficulty. A side result of its own interest is a fully dynamic \\textit{MCS Splay tree} data structure supporting insertions and deletions with the \\emph{dynamic finger} property, improving upon previous results [Cort\\'es et al., J.Alg. 2009].

  17. Towards an Optimal Energy Consumption for Unattended Mobile Sensor Networks through Autonomous Sensor Redeployment

    Directory of Open Access Journals (Sweden)

    Jian Chen

    2014-01-01

    Full Text Available Energy hole is an inherent problem caused by heavier traffic loads of sensor nodes nearer the sink because of more frequent data transmission, which is strongly dependent on the topology induced by the sensor deployment. In this paper, we propose an autonomous sensor redeployment algorithm to balance energy consumption and mitigate energy hole for unattended mobile sensor networks. First, with the target area divided into several equal width coronas, we present a mathematical problem modeling sensor node layout as well as transmission pattern to maximize network coverage and reduce communication cost. And then, by calculating the optimal node density for each corona to avoid energy hole, a fully distributed movement algorithm is proposed, which can achieve an optimal distribution quickly only by pushing or pulling its one-hop neighbors. The simulation results demonstrate that our algorithm achieves a much smaller average moving distance and a much longer network lifetime than existing algorithms and can eliminate the energy hole problem effectively.

  18. Optimizing Input/Output Using Adaptive File System Policies

    Science.gov (United States)

    Madhyastha, Tara M.; Elford, Christopher L.; Reed, Daniel A.

    1996-01-01

    Parallel input/output characterization studies and experiments with flexible resource management algorithms indicate that adaptivity is crucial to file system performance. In this paper we propose an automatic technique for selecting and refining file system policies based on application access patterns and execution environment. An automatic classification framework allows the file system to select appropriate caching and pre-fetching policies, while performance sensors provide feedback used to tune policy parameters for specific system environments. To illustrate the potential performance improvements possible using adaptive file system policies, we present results from experiments involving classification-based and performance-based steering.

  19. Optimal adaptive sequential designs for crossover bioequivalence studies.

    Science.gov (United States)

    Xu, Jialin; Audet, Charles; DiLiberti, Charles E; Hauck, Walter W; Montague, Timothy H; Parr, Alan F; Potvin, Diane; Schuirmann, Donald J

    2016-01-01

    In prior works, this group demonstrated the feasibility of valid adaptive sequential designs for crossover bioequivalence studies. In this paper, we extend the prior work to optimize adaptive sequential designs over a range of geometric mean test/reference ratios (GMRs) of 70-143% within each of two ranges of intra-subject coefficient of variation (10-30% and 30-55%). These designs also introduce a futility decision for stopping the study after the first stage if there is sufficiently low likelihood of meeting bioequivalence criteria if the second stage were completed, as well as an upper limit on total study size. The optimized designs exhibited substantially improved performance characteristics over our previous adaptive sequential designs. Even though the optimized designs avoided undue inflation of type I error and maintained power at ≥ 80%, their average sample sizes were similar to or less than those of conventional single stage designs.

  20. Optimal adaptation to extreme rainfalls in current and future climate

    DEFF Research Database (Denmark)

    Rosbjerg, Dan

    2017-01-01

    and the annual capital and operational costs of adapting to this level are described with log-linear relations. The total flooding costs are developed as the expected annual damage of flooding above the T-year level plus the annual capital and operational costs for ensuring no flooding below the T-year level......More intense and frequent rainfalls have increased the number of urban flooding events in recent years, prompting adaptation efforts. Economic optimization is considered an efficient tool to decide on the design level for adaptation. The costs associated with a flooding to the T-year level....... The value of the return period T that corresponds to the minimum of the sum of these costs will then be the optimal adaptation level. The change in climate, however, is expected to continue in the next century, which calls for expansion of the above model. The change can be expressed in terms of a climate...

  1. Parameterization adaption for 3D shape optimization in aerodynamics

    Directory of Open Access Journals (Sweden)

    Badr Abou El Majd

    2013-10-01

    Full Text Available When solving a PDE problem numerically, a certain mesh-refinement process is always implicit, and very classically, mesh adaptivity is a very effective means to accelerate grid convergence. Similarly, when optimizing a shape by means of an explicit geometrical representation, it is natural to seek for an analogous concept of parameterization adaptivity. We propose here an adaptive parameterization for three-dimensional optimum design in aerodynamics by using the so-called “Free-Form Deformation” approach based on 3D tensorial Bézier parameterization. The proposed procedure leads to efficient numerical simulations with highly reduced computational costs.[How to cite this article:  Majd, B.A.. 2014. Parameterization adaption for 3D shape optimization in aerodynamics. International Journal of Science and Engineering, 6(1:61-69. Doi: 10.12777/ijse.6.1.61-69

  2. Optimal Bayesian Adaptive Design for Test-Item Calibration.

    Science.gov (United States)

    van der Linden, Wim J; Ren, Hao

    2015-06-01

    An optimal adaptive design for test-item calibration based on Bayesian optimality criteria is presented. The design adapts the choice of field-test items to the examinees taking an operational adaptive test using both the information in the posterior distributions of their ability parameters and the current posterior distributions of the field-test parameters. Different criteria of optimality based on the two types of posterior distributions are possible. The design can be implemented using an MCMC scheme with alternating stages of sampling from the posterior distributions of the test takers' ability parameters and the parameters of the field-test items while reusing samples from earlier posterior distributions of the other parameters. Results from a simulation study demonstrated the feasibility of the proposed MCMC implementation for operational item calibration. A comparison of performances for different optimality criteria showed faster calibration of substantial numbers of items for the criterion of D-optimality relative to A-optimality, a special case of c-optimality, and random assignment of items to the test takers.

  3. Multivariable adaptive optimization of a continuous bioreactor with a constraint

    Energy Technology Data Exchange (ETDEWEB)

    Chang, Y.K.

    1987-01-01

    A single-variable on-line adaptive optimization algorithm using a bilevel forgetting factor was developed. Also a modified version of this algorithm was developed to handle a quality constraint. Both algorithms were tested in simulation studies on a continuous bakers' yeast culture for optimization speed and accuracy, reoptimization capability, and long term operational stability. The above algorithms were extended to a multivariable on-line adaptive optimization and tested in simulated optimization studies with and without a constraint on the residual ethanol concentration. The dilution rate (D) and the temperature (T) were manipulated to maximize the cellular productivity (DX). It took about 80 hours to optimize the culture and the attained steady state was very close to the optimum. When tested with a big step change in the feed substrate concentration it took 60 to 80 hours to drive and maintain the cellular productivity close to the new optimum value. Long term operational stability was also tested. The multivariable algorithm was experimentally applied to an actual bakers' yeast culture. Only unconstrained optimization was carried out. The optimization required 50 to 90 hours. The attained steady state was D = 0.301 1/hr, T = 32.8 C, and DX = 1.500 g/l/hr. A fast inferential optimization algorithm based on one of the fast responding off-gas data, the carbon dioxide evolution rate (CER), was proposed. In simulation and experimental studies this new algorithm is 2 to 3 times faster in optimization speed.

  4. Novel adaptive laser scanning sensor for reverse engineering measurement

    Institute of Scientific and Technical Information of China (English)

    Zhao Ji; Ma Zi; Lin Na; Zhu Quanmin

    2007-01-01

    In this paper, a series of new techniques are used to optimize typical laser scanning sensor. The integrated prototype is compared with traditional approach to demonstrate the much improved performance. In the research and development, camera calibration is achieved by extracting characteristic points of the laser plane, so that the calibration efficiency is improved significantly. With feedback control of its intensity, the laser is automatically adjusted for different material. A modified algorithm is presented to improve the accuracy of laser stripe extraction. The fusion of data extracted from left and right camera is completed with re-sampling technique. The scanner is integrated with a robot arm and some other machinery for on-line measurement and inspection, which provides a flexible measurement tool for reverse engineering.

  5. Channel adaptive rate control for energy optimization

    Institute of Scientific and Technical Information of China (English)

    BLANCH Carolina; POLLIN Sofie; LAFRUIT Gauthier; EBERLE Wolfgang

    2006-01-01

    Low energy consumption is one of the main challenges for wireless video transmission on battery limited devices. The energy invested at the lower layers of the protocol stack involved in data communication, such as link and physical layer, represent an important part of the total energy consumption. This communication energy highly depends on the channel conditions and on the transmission data rate. Traditionally, video coding is unaware of varying channel conditions. In this paper, we propose a cross-layer approach in which the rate control mechanism of the video codec becomes channel-aware and steers the instantaneous output rate according to the channel conditions to reduce the communication energy. Our results show that energy savings of up to30% can be obtained with a reduction of barely 0.1 dB on the average video quality. The impact of feedback delays is shown to be small. In addition, this adaptive mechanism has low complexity, which makes it suitable for real-time applications.

  6. A triaxial accelerometer monkey algorithm for optimal sensor placement in structural health monitoring

    Science.gov (United States)

    Jia, Jingqing; Feng, Shuo; Liu, Wei

    2015-06-01

    Optimal sensor placement (OSP) technique is a vital part of the field of structural health monitoring (SHM). Triaxial accelerometers have been widely used in the SHM of large-scale structures in recent years. Triaxial accelerometers must be placed in such a way that all of the important dynamic information is obtained. At the same time, the sensor configuration must be optimal, so that the test resources are conserved. The recommended practice is to select proper degrees of freedom (DOF) based upon several criteria and the triaxial accelerometers are placed at the nodes corresponding to these DOFs. This results in non-optimal placement of many accelerometers. A ‘triaxial accelerometer monkey algorithm’ (TAMA) is presented in this paper to solve OSP problems of triaxial accelerometers. The EFI3 measurement theory is modified and involved in the objective function to make it more adaptable in the OSP technique of triaxial accelerometers. A method of calculating the threshold value based on probability theory is proposed to improve the healthy rate of monkeys in a troop generation process. Meanwhile, the processes of harmony ladder climb and scanning watch jump are proposed and given in detail. Finally, Xinghai NO.1 Bridge in Dalian is implemented to demonstrate the effectiveness of TAMA. The final results obtained by TAMA are compared with those of the original monkey algorithm and EFI3 measurement, which show that TAMA can improve computational efficiency and get a better sensor configuration.

  7. Adaptive Multi-Objective Optimization Based on Feedback Design

    Institute of Scientific and Technical Information of China (English)

    窦立谦; 宗群; 吉月辉; 曾凡琳

    2010-01-01

    The problem of adaptive multi-objective optimization(AMOO) has received extensive attention due to its practical significance.An important issue in optimizing a multi-objective system is adjusting the weighting coefficients of multiple objectives so as to keep track of various conditions.In this paper,a feedback structure for AMOO is designed.Moreover,the reinforcement learning combined with hidden biasing information is applied to online tuning weighting coefficients of objective functions.Finally,the prop...

  8. 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

  9. Exploiting node mobility for energy optimization in wireless sensor networks

    Science.gov (United States)

    El-Moukaddem, Fatme Mohammad

    Wireless Sensor Networks (WSNs) have become increasingly available for data-intensive applications such as micro-climate monitoring, precision agriculture, and audio/video surveillance. A key challenge faced by data-intensive WSNs is to transmit the sheer amount of data generated within an application's lifetime to the base station despite the fact that sensor nodes have limited power supplies such as batteries or small solar panels. The availability of numerous low-cost robotic units (e.g. Robomote and Khepera) has made it possible to construct sensor networks consisting of mobile sensor nodes. It has been shown that the controlled mobility offered by mobile sensors can be exploited to improve the energy efficiency of a network. In this thesis, we propose schemes that use mobile sensor nodes to reduce the energy consumption of data-intensive WSNs. Our approaches differ from previous work in two main aspects. First, our approaches do not require complex motion planning of mobile nodes, and hence can be implemented on a number of low-cost mobile sensor platforms. Second, we integrate the energy consumption due to both mobility and wireless communications into a holistic optimization framework. We consider three problems arising from the limited energy in the sensor nodes. In the first problem, the network consists of mostly static nodes and contains only a few mobile nodes. In the second and third problems, we assume essentially that all nodes in the WSN are mobile. We first study a new problem called max-data mobile relay configuration (MMRC ) that finds the positions of a set of mobile sensors, referred to as relays, that maximize the total amount of data gathered by the network during its lifetime. We show that the MMRC problem is surprisingly complex even for a trivial network topology due to the joint consideration of the energy consumption of both wireless communication and mechanical locomotion. We present optimal MMRC algorithms and practical distributed

  10. Electrical impedance tomography with an optimized calculable square sensor.

    Science.gov (United States)

    Cao, Zhang; Wang, Huaxiang; Xu, Lijun

    2008-10-01

    Electrical impedance tomography is a technique that reconstructs the medium distribution in a region of interest through electrical measurements on its boundary. In this paper, an optimized square sensor was designed for electrical impedance tomography in order to obtain maximum information over the cross section of interest, e.g., circulating fluidized beds, in the sense of Shannon information entropy. An analytical model of the sensor was obtained using the conformal transformation. The model indicates that the square sensor possesses calculable property, which allows the calculation of standard values of the sensor directly from a single dimensional measurement that can be made traceable to the SI unit of length. Based on the model, the sensitivity maps and electrical field lines can be calculated in less than a second. Two model based algorithms for image reconstruction, i.e., back projection algorithm based on electrical field lines and iterative Lavrentiev regularization algorithm based on the sensitivity map, were introduced. Simulated results and experimental results validate the feasibility of the algorithms.

  11. 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.

  12. Correlations in state space can cause sub-optimal adaptation of optimal feedback control models.

    Science.gov (United States)

    Aprasoff, Jonathan; Donchin, Opher

    2012-04-01

    Control of our movements is apparently facilitated by an adaptive internal model in the cerebellum. It was long thought that this internal model implemented an adaptive inverse model and generated motor commands, but recently many reject that idea in favor of a forward model hypothesis. In theory, the forward model predicts upcoming state during reaching movements so the motor cortex can generate appropriate motor commands. Recent computational models of this process rely on the optimal feedback control (OFC) framework of control theory. OFC is a powerful tool for describing motor control, it does not describe adaptation. Some assume that adaptation of the forward model alone could explain motor adaptation, but this is widely understood to be overly simplistic. However, an adaptive optimal controller is difficult to implement. A reasonable alternative is to allow forward model adaptation to 're-tune' the controller. Our simulations show that, as expected, forward model adaptation alone does not produce optimal trajectories during reaching movements perturbed by force fields. However, they also show that re-optimizing the controller from the forward model can be sub-optimal. This is because, in a system with state correlations or redundancies, accurate prediction requires different information than optimal control. We find that adding noise to the movements that matches noise found in human data is enough to overcome this problem. However, since the state space for control of real movements is far more complex than in our simple simulations, the effects of correlations on re-adaptation of the controller from the forward model cannot be overlooked.

  13. The optimal joint power and rate adaptation for mobile multicast

    DEFF Research Database (Denmark)

    Wang, Haibo; Schwefel, Hans-Peter; Toftegaard, Thomas S.

    2008-01-01

    In this paper we have investigated the joint power and rate adaptation strategies for multicast services for downlink communication. We have proposed a theoretical framework to find out the achievable spectrum efficiency upper boundary of such a scenario and the corresponding optimal solution for...

  14. Weighted Optimization-Based Distributed Kalman Filter for Nonlinear Target Tracking in Collaborative Sensor Networks.

    Science.gov (United States)

    Chen, Jie; Li, Jiahong; Yang, Shuanghua; Deng, Fang

    2016-07-21

    The identification of the nonlinearity and coupling is crucial in nonlinear target tracking problem in collaborative sensor networks. According to the adaptive Kalman filtering (KF) method, the nonlinearity and coupling can be regarded as the model noise covariance, and estimated by minimizing the innovation or residual errors of the states. However, the method requires large time window of data to achieve reliable covariance measurement, making it impractical for nonlinear systems which are rapidly changing. To deal with the problem, a weighted optimization-based distributed KF algorithm (WODKF) is proposed in this paper. The algorithm enlarges the data size of each sensor by the received measurements and state estimates from its connected sensors instead of the time window. A new cost function is set as the weighted sum of the bias and oscillation of the state to estimate the "best" estimate of the model noise covariance. The bias and oscillation of the state of each sensor are estimated by polynomial fitting a time window of state estimates and measurements of the sensor and its neighbors weighted by the measurement noise covariance. The best estimate of the model noise covariance is computed by minimizing the weighted cost function using the exhaustive method. The sensor selection method is in addition to the algorithm to decrease the computation load of the filter and increase the scalability of the sensor network. The existence, suboptimality and stability analysis of the algorithm are given. The local probability data association method is used in the proposed algorithm for the multitarget tracking case. The algorithm is demonstrated in simulations on tracking examples for a random signal, one nonlinear target, and four nonlinear targets. Results show the feasibility and superiority of WODKF against other filtering algorithms for a large class of systems.

  15. Optimal Node Placement in Underwater Wireless Sensor Networks

    KAUST Repository

    Felamban, M.

    2013-03-25

    Wireless Sensor Networks (WSN) are expected to play a vital role in the exploration and monitoring of underwater areas which are not easily reachable by humans. However, underwater communication via acoustic waves is subject to several performance limitations that are very different from those used for terresstrial networks. In this paper, we investigate node placement for building an initial underwater WSN infrastructure. We formulate this problem as a nonlinear mathematical program with the objective of minimizing the total transmission loss under a given number of sensor nodes and targeted coverage volume. The obtained solution is the location of each node represented via a truncated octahedron to fill out the 3D space. Experiments are conducted to verify the proposed formulation, which is solved using Matlab optimization tool. Simulation is also conducted using an ns-3 simulator, and the simulation results are consistent with the obtained results from mathematical model with less than 10% error.

  16. Optimal feedback control of a bioreactor with a remote sensor

    Science.gov (United States)

    Niranjan, S. C.; San, K. Y.

    1988-01-01

    Sensors used to monitor bioreactor conditions directly often perform poorly in the face of adverse nonphysiological conditions. One way to circumvent this is to use a remote sensor block. However, such a configuration usually causes a significant time lag between measurements and the actual state values. Here, the problem of implementing feedback control strategies for such systems, described by nonlinear equations, is addressed. The problem is posed as an optimal control problem with a linear quadratic performance index. The linear control law so obtained is used to implement feedback. A global linearization technique as well as an expansion using Taylor series is used to linearize the nonlinear system, and the feedback is subsequently implemented.

  17. Adaptive Routing Protocol with Energy Efficiency and Event Clustering for Wireless Sensor Networks

    Science.gov (United States)

    Tran Quang, Vinh; Miyoshi, Takumi

    Wireless sensor network (WSN) is a promising approach for a variety of applications. Routing protocol for WSNs is very challenging because it should be simple, scalable, energy-efficient, and robust to deal with a very large number of nodes, and also self-configurable to node failures and changes of the network topology dynamically. Recently, many researchers have focused on developing hierarchical protocols for WSNs. However, most protocols in the literatures cannot scale well to large sensor networks and difficult to apply in the real applications. In this paper, we propose a novel adaptive routing protocol for WSNs called ARPEES. The main design features of the proposed method are: energy efficiency, dynamic event clustering, and multi-hop relay considering the trade-off relationship between the residual energy available of relay nodes and distance from the relay node to the base station. With a distributed and light overhead traffic approach, we spread energy consumption required for aggregating data and relaying them to different sensor nodes to prolong the lifetime of the whole network. In this method, we consider energy and distance as the parameters in the proposed function to select relay nodes and finally select the optimal path among cluster heads, relay nodes and the base station. The simulation results show that our routing protocol achieves better performance than other previous routing protocols.

  18. Discrete Time Optimal Adaptive Control for Linear Stochastic Systems

    Institute of Scientific and Technical Information of China (English)

    JIANG Rui; LUO Guiming

    2007-01-01

    The least-squares(LS)algorithm has been used for system modeling for a long time. Without any excitation conditions, only the convergence rate of the common LS algorithm can be obtained. This paper analyzed the weighted least-squares(WLS)algorithm and described the good properties of the WLS algorithm. The WLS algorithm was then used for daptive control of linear stochastic systems to show that the linear closed-loop system was globally stable and that the system identification was consistent. Compared to the past optimal adaptive controller,this controller does not impose restricted conditions on the coefficients of the system, such as knowing the first coefficient before the controller. Without any persistent excitation conditions, the analysis shows that, with the regulation of the adaptive control, the closed-loop system was globally stable and the adaptive controller converged to the one-step-ahead optimal controller in some sense.

  19. An Adaptive Unified Differential Evolution Algorithm for Global Optimization

    Energy Technology Data Exchange (ETDEWEB)

    Qiang, Ji; Mitchell, Chad

    2014-11-03

    In this paper, we propose a new adaptive unified differential evolution algorithm for single-objective global optimization. Instead of the multiple mutation strate- gies proposed in conventional differential evolution algorithms, this algorithm employs a single equation unifying multiple strategies into one expression. It has the virtue of mathematical simplicity and also provides users the flexibility for broader exploration of the space of mutation operators. By making all control parameters in the proposed algorithm self-adaptively evolve during the process of optimization, it frees the application users from the burden of choosing appro- priate control parameters and also improves the performance of the algorithm. In numerical tests using thirteen basic unimodal and multimodal functions, the proposed adaptive unified algorithm shows promising performance in compari- son to several conventional differential evolution algorithms.

  20. Optimal Pid Controller Design Using Adaptive Vurpso Algorithm

    Science.gov (United States)

    Zirkohi, Majid Moradi

    2015-04-01

    The purpose of this paper is to improve theVelocity Update Relaxation Particle Swarm Optimization algorithm (VURPSO). The improved algorithm is called Adaptive VURPSO (AVURPSO) algorithm. Then, an optimal design of a Proportional-Integral-Derivative (PID) controller is obtained using the AVURPSO algorithm. An adaptive momentum factor is used to regulate a trade-off between the global and the local exploration abilities in the proposed algorithm. This operation helps the system to reach the optimal solution quickly and saves the computation time. Comparisons on the optimal PID controller design confirm the superiority of AVURPSO algorithm to the optimization algorithms mentioned in this paper namely the VURPSO algorithm, the Ant Colony algorithm, and the conventional approach. Comparisons on the speed of convergence confirm that the proposed algorithm has a faster convergence in a less computation time to yield a global optimum value. The proposed AVURPSO can be used in the diverse areas of optimization problems such as industrial planning, resource allocation, scheduling, decision making, pattern recognition and machine learning. The proposed AVURPSO algorithm is efficiently used to design an optimal PID controller.

  1. Hybrid swarm intelligence optimization approach for optimal data storage position identification in wireless sensor networks.

    Science.gov (United States)

    Mohanasundaram, Ranganathan; Periasamy, Pappampalayam Sanmugam

    2015-01-01

    The current high profile debate with regard to data storage and its growth have become strategic task in the world of networking. It mainly depends on the sensor nodes called producers, base stations, and also the consumers (users and sensor nodes) to retrieve and use the data. The main concern dealt here is to find an optimal data storage position in wireless sensor networks. The works that have been carried out earlier did not utilize swarm intelligence based optimization approaches to find the optimal data storage positions. To achieve this goal, an efficient swam intelligence approach is used to choose suitable positions for a storage node. Thus, hybrid particle swarm optimization algorithm has been used to find the suitable positions for storage nodes while the total energy cost of data transmission is minimized. Clustering-based distributed data storage is utilized to solve clustering problem using fuzzy-C-means algorithm. This research work also considers the data rates and locations of multiple producers and consumers to find optimal data storage positions. The algorithm is implemented in a network simulator and the experimental results show that the proposed clustering and swarm intelligence based ODS strategy is more effective than the earlier approaches.

  2. Hybrid Swarm Intelligence Optimization Approach for Optimal Data Storage Position Identification in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Ranganathan Mohanasundaram

    2015-01-01

    Full Text Available The current high profile debate with regard to data storage and its growth have become strategic task in the world of networking. It mainly depends on the sensor nodes called producers, base stations, and also the consumers (users and sensor nodes to retrieve and use the data. The main concern dealt here is to find an optimal data storage position in wireless sensor networks. The works that have been carried out earlier did not utilize swarm intelligence based optimization approaches to find the optimal data storage positions. To achieve this goal, an efficient swam intelligence approach is used to choose suitable positions for a storage node. Thus, hybrid particle swarm optimization algorithm has been used to find the suitable positions for storage nodes while the total energy cost of data transmission is minimized. Clustering-based distributed data storage is utilized to solve clustering problem using fuzzy-C-means algorithm. This research work also considers the data rates and locations of multiple producers and consumers to find optimal data storage positions. The algorithm is implemented in a network simulator and the experimental results show that the proposed clustering and swarm intelligence based ODS strategy is more effective than the earlier approaches.

  3. Design and performance optimization of fiber optic adaptive filters.

    Science.gov (United States)

    Paparao, P; Ghosh, A; Allen, S D

    1991-05-10

    There is a great need for easy-to-fabricate and versatile fiber optic signal processing systems in which optical fibers are used for the delay and storage of wideband guided lightwave signals. We describe the design of the least-mean-square algorithm-based fiber optic adaptive filters for processing guided lightwave signals in real time. Fiber optic adaptive filters can learn to change their parameters or to process a set of characteristics of the input signal. In our realization we employ as few electronic devices as possible and use optical computation to utilize the advantages of optics in the processing speed, parallelism, and interconnection. Many schemes for optical adaptive filtering of electronic signals are available in the literature. The new optical adaptive filters described in this paper are for optical processing of guided lightwave signals, not electronic signals. We analyzed the convergence or learning characteristics of the adaptive filtering process as a function of the filter parameters and the fiber optic hardware errors. From this analysis we found that the effects of the optical round-off errors and noise can be reduced, and the learning speed can be comparatively increased in our design through an optimal selection of the filter parameters. A general knowledge of the fiber optic hardware, the statistics of the lightwave signal, and the desired goal of the adaptive processing are enough for this optimum selection of the parameters. Detailed computer simulations validate the theoretical results of performance optimization.

  4. THE ADAPTIVE SMOOTHING FILTERS OF SENSOR SIGNALS IN THE MICROAVIONIC SYSTEMS

    Directory of Open Access Journals (Sweden)

    V. A. Malkin

    2012-01-01

    Full Text Available The adaptive for intensivity of measuring noise filters for smooth of sensor signals are considered. The adaptation are realized at the expense of the statistical processing of the filtering errors. The algorithm of adaptive filter coefficients calculation and modeling results are presented.

  5. Adaptive double chain quantum genetic algorithm for constrained optimization problems

    Directory of Open Access Journals (Sweden)

    Kong Haipeng

    2015-02-01

    Full Text Available Optimization problems are often highly constrained and evolutionary algorithms (EAs are effective methods to tackle this kind of problems. To further improve search efficiency and convergence rate of EAs, this paper presents an adaptive double chain quantum genetic algorithm (ADCQGA for solving constrained optimization problems. ADCQGA makes use of double-individuals to represent solutions that are classified as feasible and infeasible solutions. Fitness (or evaluation functions are defined for both types of solutions. Based on the fitness function, three types of step evolution (SE are defined and utilized for judging evolutionary individuals. An adaptive rotation is proposed and used to facilitate updating individuals in different solutions. To further improve the search capability and convergence rate, ADCQGA utilizes an adaptive evolution process (AEP, adaptive mutation and replacement techniques. ADCQGA was first tested on a widely used benchmark function to illustrate the relationship between initial parameter values and the convergence rate/search capability. Then the proposed ADCQGA is successfully applied to solve other twelve benchmark functions and five well-known constrained engineering design problems. Multi-aircraft cooperative target allocation problem is a typical constrained optimization problem and requires efficient methods to tackle. Finally, ADCQGA is successfully applied to solving the target allocation problem.

  6. Adaptive double chain quantum genetic algorithm for constrained optimization problems

    Institute of Scientific and Technical Information of China (English)

    Kong Haipeng; Li Ni; Shen Yuzhong

    2015-01-01

    Optimization problems are often highly constrained and evolutionary algorithms (EAs) are effective methods to tackle this kind of problems. To further improve search efficiency and con-vergence rate of EAs, this paper presents an adaptive double chain quantum genetic algorithm (ADCQGA) for solving constrained optimization problems. ADCQGA makes use of double-individuals to represent solutions that are classified as feasible and infeasible solutions. Fitness (or evaluation) functions are defined for both types of solutions. Based on the fitness function, three types of step evolution (SE) are defined and utilized for judging evolutionary individuals. An adaptive rotation is proposed and used to facilitate updating individuals in different solutions. To further improve the search capability and convergence rate, ADCQGA utilizes an adaptive evolution process (AEP), adaptive mutation and replacement techniques. ADCQGA was first tested on a widely used benchmark function to illustrate the relationship between initial parameter values and the convergence rate/search capability. Then the proposed ADCQGA is successfully applied to solve other twelve benchmark functions and five well-known constrained engineering design problems. Multi-aircraft cooperative target allocation problem is a typical constrained optimization problem and requires efficient methods to tackle. Finally, ADCQGA is successfully applied to solving the target allocation problem.

  7. Multihopping Multilevel Clustering Heterogeneity-Sensitive Optimized Routing Protocol for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Muhammad Aslam

    2017-01-01

    Full Text Available Effective utilization of energy resources in Wireless Sensor Networks (WSNs has become challenging under uncertain distributed cluster-formation and single-hop intercluster communication capabilities. So, sensor nodes are forced to operate at expensive full rate transmission power level continuously during whole network operation. These challenging network environments experience unwanted phenomena of drastic energy consumption and packet drop. In this paper, we propose an adaptive immune Multihopping Multilevel Clustering (MHMLC protocol that executes a Hybrid Clustering Algorithm (HCA to perform optimal centralized selection of Cluster-Heads (CHs within radius of centrally located Base Station (BS and distributed CHs selection in the rest of network area. HCA of MHMLC also produces optimal intermediate CHs for intercluster multihop communications that develop heterogeneity-aware economical links. This hybrid cluster-formation facilitates the sensors to function at short range transmission power level that enhances link quality and avoids packet drop. The simulation environments produce fair comparison among proposed MHMLC and existing state-of-the-art routing protocols. Experimental results give significant evidence of better performance of the proposed model in terms of network lifetime, stability period, and data delivery ratio.

  8. AH-MAC: Adaptive Hierarchical MAC Protocol for Low-Rate Wireless Sensor Network Applications

    Directory of Open Access Journals (Sweden)

    Adnan Ismail Al-Sulaifanie

    2017-01-01

    Full Text Available This paper proposes an adaptive hierarchical MAC protocol (AH-MAC with cross-layer optimization for low-rate and large-scale wireless sensor networks. The main goal of the proposed protocol is to combine the strengths of LEACH and IEEE 802.15.4 while offsetting their weaknesses. The predetermined cluster heads are supported with an energy harvesting circuit, while the normal nodes are battery-operated. To prolong the network’s operational lifetime, the proposed protocol transfers most of the network’s activities to the cluster heads while minimizing the node’s activity. Some of the main features of this protocol include energy efficiency, self-configurability, scalability, and self-healing. The simulation results showed great improvement of the AH-MAC over LEACH protocol in terms of energy consumption and throughput. AH-MAC consumes eight times less energy while improving throughput via acknowledgment support.

  9. Optimizing Concentric Circular Antenna Arrays for High-Altitude Platforms Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Yasser Albagory

    2014-04-01

    Full Text Available Wireless Sensor Networks (WSN has gained interest in many applications and it becomes important to improve its performance. Antennas and communication performance are most important issues of WSN. In this paper, an adaptive concentric circular array (CCA is proposed to improve the link between the sink and sensor nodes. This technique is applied to the new High – Altitude Platform (HAP Wireless Sensor Network (WSN. The proposed array technique is applied for two coverage scenarios; a wider coverage cell of 30 km radius and a smaller cell of 8 km radius. The feasibility of the link is discussed where it shows the possibility of communications between the HAP sink station and sensor nodes located on the ground. The proposed CCA array is optimized using a modified Dolph-Chebyshev feeding function. A comparison with conventional antenna models in literature shows that the link performance in terms of bit energy to noise power spectral density ratio can be improved by up to 11.37 dB for cells of 8 km radius and 16.8 dB in the case of 30 km radius cells that make the link at 2.4 GHz feasible and realizable compared to using conventional antenna techniques.

  10. Topology optimization of pressure adaptive honeycomb for a morphing flap

    Science.gov (United States)

    Vos, Roelof; Scheepstra, Jan; Barrett, Ron

    2011-03-01

    The paper begins with a brief historical overview of pressure adaptive materials and structures. By examining avian anatomy, it is seen that pressure-adaptive structures have been used successfully in the Natural world to hold structural positions for extended periods of time and yet allow for dynamic shape changes from one flight state to the next. More modern pneumatic actuators, including FAA certified autopilot servoactuators are frequently used by aircraft around the world. Pneumatic artificial muscles (PAM) show good promise as aircraft actuators, but follow the traditional model of load concentration and distribution commonly found in aircraft. A new system is proposed which leaves distributed loads distributed and manipulates structures through a distributed actuator. By using Pressure Adaptive Honeycomb (PAH), it is shown that large structural deformations in excess of 50% strains can be achieved while maintaining full structural integrity and enabling secondary flight control mechanisms like flaps. The successful implementation of pressure-adaptive honeycomb in the trailing edge of a wing section sparked the motivation for subsequent research into the optimal topology of the pressure adaptive honeycomb within the trailing edge of a morphing flap. As an input for the optimization two known shapes are required: a desired shape in cruise configuration and a desired shape in landing configuration. In addition, the boundary conditions and load cases (including aerodynamic loads and internal pressure loads) should be specified for each condition. Finally, a set of six design variables is specified relating to the honeycomb and upper skin topology of the morphing flap. A finite-element model of the pressure-adaptive honeycomb structure is developed specifically tailored to generate fast but reliable results for a given combination of external loading, input variables, and boundary conditions. Based on two bench tests it is shown that this model correlates well

  11. Multidisciplinary design optimization of adaptive wing leading edge

    Institute of Scientific and Technical Information of China (English)

    SUN; RuJie; CHEN; GuoPing; ZHOU; Chen; ZHOU; LanWei; JIANG; JinHui

    2013-01-01

    Adaptive wing can significantly enhance aircraft aerodynamic performance, which refers to aerodynamic and structural opti-mization designs. This paper introduces a two-step approach to solve the interrelated problems of the adaptive leading edge. In the first step, the procedure of airfoil optimization is carried out with an initial configuration of NACA 0006. On the basis of the combination of design of experiment (DOE), response surface method (RSM) and genetic algorithm (GA), an adaptive air-foil can be obtained whose lift-to-drag ratio is larger than the baseline airfoil’s at the given angle of attack and subsonic speed.The next step is to design a compliant structure to achieve the target airfoil shape, which is the optimization result of the previous step. In order to minimize the deviation of the deformed shape from the target shape, the load path representation topology method is presented. This method is developed by way of GA, with size and shape optimization incorporated in it simul-taneously. Finally, a comparison study with the Solid Isotropic Material with Penalization (SIMP) method in Altair OptiStruct is conducted, and the results demonstrate the validity and effectiveness of the proposed approach.

  12. Optimal sensor placement for modal testing on wind turbines

    Science.gov (United States)

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

    2016-09-01

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

  13. Optimal Node Placement in Underwater Acoustic Sensor Network

    KAUST Repository

    Felemban, Muhamad

    2011-10-01

    Almost 70% of planet Earth is covered by water. A large percentage of underwater environment is unexplored. In the past two decades, there has been an increase in the interest of exploring and monitoring underwater life among scientists and in industry. Underwater operations are extremely difficult due to the lack of cheap and efficient means. Recently, Wireless Sensor Networks have been introduced in underwater environment applications. However, underwater communication via acoustic waves is subject to several performance limitations, which makes the relevant research issues very different from those on land. In this thesis, we investigate node placement for building an initial Underwater Wireless Sensor Network infrastructure. Firstly, we formulated the problem into a nonlinear mathematic program with objectives of minimizing the total transmission loss under a given number of sensor nodes and targeted volume. We conducted experiments to verify the proposed formulation, which is solved using Matlab optimization tool. We represented each node with a truncated octahedron to fill out the 3D space. The truncated octahedrons are tiled in the 3D space with each node in the center where locations of the nodes are given using 3D coordinates. Results are supported using ns-3 simulator. Results from simulation are consistent with the obtained results from mathematical model with less than 10% error.

  14. Optimized Reputable Sensing Participants Extraction for Participatory Sensor Networks

    Directory of Open Access Journals (Sweden)

    Weiwei Yuan

    2014-01-01

    Full Text Available By collecting data via sensors embedded personal smart devices, sensing participants play a key role in participatory sensor networks. Using information provided by reputable sensing participants ensures the reliability of participatory sensing data. Setting a threshold for the reputation, and those whose reputations are bigger than this value are regarded as reputable. The bigger the threshold value is, the more reliable the extracted reputable sensing participant is. However, if the threshold value is too big, only very limited participatory sensing data can be involved. This may cause unexpected bias in information collection. Existing works did not consider the relationship between the reliability of extracted reputable sensing participants and the ratio of usable participatory sensing data. In this work, we propose a criterion for optimized reputable sensing participant extraction in participatory sensor networks. This is achieved based on the mathematical analysis on the ratio of available participatory sensing data and the reliability of extracted reputable sensing participants. Our suggested threshold value for reputable sensing participant extraction is only related to the power of sensing participant’s reputation distribution. It is easy to be applied in real applications. Simulation results tested on real application data further verified the effectiveness of our proposed method.

  15. Multiobjective Optimization Method Based on Adaptive Parameter Harmony Search Algorithm

    Directory of Open Access Journals (Sweden)

    P. Sabarinath

    2015-01-01

    Full Text Available The present trend in industries is to improve the techniques currently used in design and manufacture of products in order to meet the challenges of the competitive market. The crucial task nowadays is to find the optimal design and machining parameters so as to minimize the production costs. Design optimization involves more numbers of design variables with multiple and conflicting objectives, subjected to complex nonlinear constraints. The complexity of optimal design of machine elements creates the requirement for increasingly effective algorithms. Solving a nonlinear multiobjective optimization problem requires significant computing effort. From the literature it is evident that metaheuristic algorithms are performing better in dealing with multiobjective optimization. In this paper, we extend the recently developed parameter adaptive harmony search algorithm to solve multiobjective design optimization problems using the weighted sum approach. To determine the best weightage set for this analysis, a performance index based on least average error is used to determine the index of each weightage set. The proposed approach is applied to solve a biobjective design optimization of disc brake problem and a newly formulated biobjective design optimization of helical spring problem. The results reveal that the proposed approach is performing better than other algorithms.

  16. Adaptation to optimal cell growth through self-organized criticality.

    Science.gov (United States)

    Furusawa, Chikara; Kaneko, Kunihiko

    2012-05-18

    A simple cell model consisting of a catalytic reaction network is studied to show that cellular states are self-organized in a critical state for achieving optimal growth; we consider the catalytic network dynamics over a wide range of environmental conditions, through the spontaneous regulation of nutrient transport into the cell. Furthermore, we find that the adaptability of cellular growth to reach a critical state depends only on the extent of environmental changes, while all chemical species in the cell exhibit correlated partial adaptation. These results are in remarkable agreement with the recent experimental observations of the present cells.

  17. A fully adaptive hybrid optimization of aircraft engine blades

    Science.gov (United States)

    Dumas, L.; Druez, B.; Lecerf, N.

    2009-10-01

    A new fully adaptive hybrid optimization method (AHM) has been developed and applied to an industrial problem in the field of the aircraft engine industry. The adaptivity of the coupling between a global search by a population-based method (Genetic Algorithms or Evolution Strategies) and the local search by a descent method has been particularly emphasized. On various analytical test cases, the AHM method overperforms the original global search method in terms of computational time and accuracy. The results obtained on the industrial case have also confirmed the interest of AHM for the design of new and original solutions in an affordable time.

  18. Optimal Sparse Upstream Sensor Placement for Hydrokinetic Turbines

    Science.gov (United States)

    Cavagnaro, Robert; Strom, Benjamin; Ross, Hannah; Hill, Craig; Polagye, Brian

    2016-11-01

    Accurate measurement of the flow field incident upon a hydrokinetic turbine is critical for performance evaluation during testing and setting boundary conditions in simulation. Additionally, turbine controllers may leverage real-time flow measurements. Particle image velocimetry (PIV) is capable of rendering a flow field over a wide spatial domain in a controlled, laboratory environment. However, PIV's lack of suitability for natural marine environments, high cost, and intensive post-processing diminish its potential for control applications. Conversely, sensors such as acoustic Doppler velocimeters (ADVs), are designed for field deployment and real-time measurement, but over a small spatial domain. Sparsity-promoting regression analysis such as LASSO is utilized to improve the efficacy of point measurements for real-time applications by determining optimal spatial placement for a small number of ADVs using a training set of PIV velocity fields and turbine data. The study is conducted in a flume (0.8 m2 cross-sectional area, 1 m/s flow) with laboratory-scale axial and cross-flow turbines. Predicted turbine performance utilizing the optimal sparse sensor network and associated regression model is compared to actual performance with corresponding PIV measurements.

  19. Optimization by GRASP greedy randomized adaptive search procedures

    CERN Document Server

    Resende, Mauricio G C

    2016-01-01

    This is the first book to cover GRASP (Greedy Randomized Adaptive Search Procedures), a metaheuristic that has enjoyed wide success in practice with a broad range of applications to real-world combinatorial optimization problems. The state-of-the-art coverage and carefully crafted pedagogical style lends this book highly accessible as an introductory text not only to GRASP, but also to combinatorial optimization, greedy algorithms, local search, and path-relinking, as well as to heuristics and metaheuristics, in general. The focus is on algorithmic and computational aspects of applied optimization with GRASP with emphasis given to the end-user, providing sufficient information on the broad spectrum of advances in applied optimization with GRASP. For the more advanced reader, chapters on hybridization with path-relinking and parallel and continuous GRASP present these topics in a clear and concise fashion. Additionally, the book offers a very complete annotated bibliography of GRASP and combinatorial optimizat...

  20. Optimized Solar Energy Power Supply for Remote Wireless Sensors Based on IEEE 802.15.4 Standard

    Directory of Open Access Journals (Sweden)

    Ondrej Krejcar

    2012-01-01

    Full Text Available Powering of intelligent wireless sensors without a permanent electric connection is a general problem which is often solved by adopting alternative power sources. One of the most commonly used sources is solar energy in the form of solar panel and charging circuits. However, it is not possible to find a solution in the markets for operation in changeable weather conditions, where sun intensity is not so high. This fact leads us to the development of optimized solar panel and all circuits for reliable power supply of wireless sensors. A special charging circuit for Li-ION battery and DC-DC adapter circuit for stabilization of wireless sensor working voltage were developed and optimized for very low energy consumption and high efficiency.

  1. The effect of prediction error correlation on optimal sensor placement in structural dynamics

    Science.gov (United States)

    Papadimitriou, Costas; Lombaert, Geert

    2012-04-01

    The problem of estimating the optimal sensor locations for parameter estimation in structural dynamics is re-visited. The effect of spatially correlated prediction errors on the optimal sensor placement is investigated. The information entropy is used as a performance measure of the sensor configuration. The optimal sensor location is formulated as an optimization problem involving discrete-valued variables, which is solved using computationally efficient sequential sensor placement algorithms. Asymptotic estimates for the information entropy are used to develop useful properties that provide insight into the dependence of the information entropy on the number and location of sensors. A theoretical analysis shows that the spatial correlation length of the prediction errors controls the minimum distance between the sensors and should be taken into account when designing optimal sensor locations with potential sensor distances up to the order of the characteristic length of the dynamic problem considered. Implementation issues for modal identification and structural-related model parameter estimation are addressed. Theoretical and computational developments are illustrated by designing the optimal sensor configurations for a continuous beam model, a discrete chain-like stiffness-mass model and a finite element model of a footbridge in Wetteren (Belgium). Results point out the crucial effect the spatial correlation of the prediction errors have on the design of optimal sensor locations for structural dynamics applications, revealing simultaneously potential inadequacies of spatially uncorrelated prediction errors models.

  2. Adaptive particle swarm optimization for optimal orbital elements of binary stars

    Science.gov (United States)

    Attia, Abdel-Fattah

    2016-12-01

    The paper presents an adaptive particle swarm optimization (APSO) as an alternative method to determine the optimal orbital elements of the star η Bootis of MK type G0 IV. The proposed algorithm transforms the problem of finding periodic orbits into the problem of detecting global minimizers as a function, to get a best fit of Keplerian and Phase curves. The experimental results demonstrate that the proposed approach of APSO generally more accurate than the standard particle swarm optimization (PSO) and other published optimization algorithms, in terms of solution accuracy, convergence speed and algorithm reliability.

  3. Optimizing Distributed Sensor Placement for Border Patrol Interdiction Using Microsoft Excel

    Science.gov (United States)

    2007-04-01

    aimed at optimizing the number of sensors and determining their placement to support distributed sensor networks. The optimization framework is...Minimalistic Grid Coverage. Dhillon, Chakrabarty, and Iyengar present a resource bounded optimization framework for sensor resource management under the...engines” to extend the capability of the Excel Solver. Specifically, the OptQuest solver (one of the field-installable engines) “employs metaheuristics

  4. Routing Protocol with Optimal Location of Aggregation Point in Wireless Sensor Networks

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    A wireless sensor network is typically composed of hundreds, even thousands of tiny sensors used to monitor physical phenomena. As data collected by the sensors are often redundant, data aggregation is important for conserving energy. In this paper, we present a new routing protocol with optimal data aggregation. This routing protocol has good performance due to its optimal selection of aggregation point locations. This paper details the optimal selection of aggregation point locations.

  5. Adaptive dynamic programming with applications in optimal control

    CERN Document Server

    Liu, Derong; Wang, Ding; Yang, Xiong; Li, Hongliang

    2017-01-01

    This book covers the most recent developments in adaptive dynamic programming (ADP). The text begins with a thorough background review of ADP making sure that readers are sufficiently familiar with the fundamentals. In the core of the book, the authors address first discrete- and then continuous-time systems. Coverage of discrete-time systems starts with a more general form of value iteration to demonstrate its convergence, optimality, and stability with complete and thorough theoretical analysis. A more realistic form of value iteration is studied where value function approximations are assumed to have finite errors. Adaptive Dynamic Programming also details another avenue of the ADP approach: policy iteration. Both basic and generalized forms of policy-iteration-based ADP are studied with complete and thorough theoretical analysis in terms of convergence, optimality, stability, and error bounds. Among continuous-time systems, the control of affine and nonaffine nonlinear systems is studied using the ADP app...

  6. Optimal Power Flow Using Adaptive Fuzzy Logic Controllers

    Directory of Open Access Journals (Sweden)

    Abdullah M. Abusorrah

    2013-01-01

    Full Text Available This paper presents an approach for optimum reactive power dispatch through the power network with flexible AC transmission systems (FACTSs devices, using adaptive fuzzy logic controller (AFLC driven by adaptive fuzzy sets (AFSs. The membership functions of AFLC are optimized based on 2nd-order fuzzy set specifications. The operation of FACTS devices (particularly, static VAR compensator (SVC and the setting of their control parameters (QSVC are optimized dynamically based on the proposed AFLC to enhance the power system stability in addition to their main function of power flow control. The proposed AFLC is compared with a static fuzzy logic controller (SFLC, driven by a fixed fuzzy set (FFS. Simulation studies were carried out and validated on the standard IEEE 30-bus test system.

  7. Adaptive Estimation of Intravascular Shear Rate Based on Parameter Optimization

    Science.gov (United States)

    Nitta, Naotaka; Takeda, Naoto

    2008-05-01

    The relationships between the intravascular wall shear stress, controlled by flow dynamics, and the progress of arteriosclerosis plaque have been clarified by various studies. Since the shear stress is determined by the viscosity coefficient and shear rate, both factors must be estimated accurately. In this paper, an adaptive method for improving the accuracy of quantitative shear rate estimation was investigated. First, the parameter dependence of the estimated shear rate was investigated in terms of the differential window width and the number of averaged velocity profiles based on simulation and experimental data, and then the shear rate calculation was optimized. The optimized result revealed that the proposed adaptive method of shear rate estimation was effective for improving the accuracy of shear rate calculation.

  8. Optimal and adaptive methods of processing hydroacoustic signals (review)

    Science.gov (United States)

    Malyshkin, G. S.; Sidel'nikov, G. B.

    2014-09-01

    Different methods of optimal and adaptive processing of hydroacoustic signals for multipath propagation and scattering are considered. Advantages and drawbacks of the classical adaptive (Capon, MUSIC, and Johnson) algorithms and "fast" projection algorithms are analyzed for the case of multipath propagation and scattering of strong signals. The classical optimal approaches to detecting multipath signals are presented. A mechanism of controlled normalization of strong signals is proposed to automatically detect weak signals. The results of simulating the operation of different detection algorithms for a linear equidistant array under multipath propagation and scattering are presented. An automatic detector is analyzed, which is based on classical or fast projection algorithms, which estimates the background proceeding from median filtering or the method of bilateral spatial contrast.

  9. Low Complexity Integer Transform and Adaptive Quantization Optimization

    Institute of Scientific and Technical Information of China (English)

    Si-Wei Ma; Wen Gao

    2006-01-01

    In this paper, a new low complexity integer transform is proposed, which has been adopted by AVS1-PT. The proposed transform can enable AVS1-P7 to share the same quantization/dequantization table with AVS1-P2. As the bases of the proposed transform coefficients are very close, the transform normalization can be implemented only on the encoder side and the dequantization table size can be reduced compared with the transform used in H.264/MPEG-4 AVC. Along with the feature of the proposed transform, adaptive dead-zone quantization optimization for the proposed transform is studied.Experimental results show that the proposed integer transform has similar coding performance compared with the transform used in H.264/MPEG-4 AVC, and would gain near 0.1dB with the adaptive dead-zone quantization optimization.

  10. 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.

  11. 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.

  12. Adapting Predictive Feedback Chaos Control for Optimal Convergence Speed

    CERN Document Server

    Bick, Christian; Kolodziejski, Christoph

    2012-01-01

    Stabilizing unstable periodic orbits in a chaotic invariant set not only reveals information about its structure but also leads to various interesting applications. For the successful application of a chaos control scheme, convergence speed is of crucial importance. Here we present a predictive feedback chaos control method that adapts a control parameter online to yield optimal asymptotic convergence speed. We study the adaptive control map both analytically and numerically and prove that it converges at least linearly to a value determined by the spectral radius of the control map at the periodic orbit to be stabilized. The method is easy to implement algorithmically and may find applications for adaptive online control of biological and engineering systems.

  13. Discrete Particle Swarm Optimization Routing Protocol for Wireless Sensor Networks with Multiple Mobile Sinks

    Directory of Open Access Journals (Sweden)

    Jin Yang

    2016-07-01

    Full Text Available Mobile sinks can achieve load-balancing and energy-consumption balancing across the wireless sensor networks (WSNs. However, the frequent change of the paths between source nodes and the sinks caused by sink mobility introduces significant overhead in terms of energy and packet delays. To enhance network performance of WSNs with mobile sinks (MWSNs, we present an efficient routing strategy, which is formulated as an optimization problem and employs the particle swarm optimization algorithm (PSO to build the optimal routing paths. However, the conventional PSO is insufficient to solve discrete routing optimization problems. Therefore, a novel greedy discrete particle swarm optimization with memory (GMDPSO is put forward to address this problem. In the GMDPSO, particle’s position and velocity of traditional PSO are redefined under discrete MWSNs scenario. Particle updating rule is also reconsidered based on the subnetwork topology of MWSNs. Besides, by improving the greedy forwarding routing, a greedy search strategy is designed to drive particles to find a better position quickly. Furthermore, searching history is memorized to accelerate convergence. Simulation results demonstrate that our new protocol significantly improves the robustness and adapts to rapid topological changes with multiple mobile sinks, while efficiently reducing the communication overhead and the energy consumption.

  14. Discrete Particle Swarm Optimization Routing Protocol for Wireless Sensor Networks with Multiple Mobile Sinks.

    Science.gov (United States)

    Yang, Jin; Liu, Fagui; Cao, Jianneng; Wang, Liangming

    2016-07-14

    Mobile sinks can achieve load-balancing and energy-consumption balancing across the wireless sensor networks (WSNs). However, the frequent change of the paths between source nodes and the sinks caused by sink mobility introduces significant overhead in terms of energy and packet delays. To enhance network performance of WSNs with mobile sinks (MWSNs), we present an efficient routing strategy, which is formulated as an optimization problem and employs the particle swarm optimization algorithm (PSO) to build the optimal routing paths. However, the conventional PSO is insufficient to solve discrete routing optimization problems. Therefore, a novel greedy discrete particle swarm optimization with memory (GMDPSO) is put forward to address this problem. In the GMDPSO, particle's position and velocity of traditional PSO are redefined under discrete MWSNs scenario. Particle updating rule is also reconsidered based on the subnetwork topology of MWSNs. Besides, by improving the greedy forwarding routing, a greedy search strategy is designed to drive particles to find a better position quickly. Furthermore, searching history is memorized to accelerate convergence. Simulation results demonstrate that our new protocol significantly improves the robustness and adapts to rapid topological changes with multiple mobile sinks, while efficiently reducing the communication overhead and the energy consumption.

  15. 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...

  16. 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...

  17. A novel adaptive Cuckoo search for optimal query plan generation.

    Science.gov (United States)

    Gomathi, Ramalingam; Sharmila, Dhandapani

    2014-01-01

    The emergence of multiple web pages day by day leads to the development of the semantic web technology. A World Wide Web Consortium (W3C) standard for storing semantic web data is the resource description framework (RDF). To enhance the efficiency in the execution time for querying large RDF graphs, the evolving metaheuristic algorithms become an alternate to the traditional query optimization methods. This paper focuses on the problem of query optimization of semantic web data. An efficient algorithm called adaptive Cuckoo search (ACS) for querying and generating optimal query plan for large RDF graphs is designed in this research. Experiments were conducted on different datasets with varying number of predicates. The experimental results have exposed that the proposed approach has provided significant results in terms of query execution time. The extent to which the algorithm is efficient is tested and the results are documented.

  18. A Novel Adaptive Cuckoo Search for Optimal Query Plan Generation

    Directory of Open Access Journals (Sweden)

    Ramalingam Gomathi

    2014-01-01

    Full Text Available The emergence of multiple web pages day by day leads to the development of the semantic web technology. A World Wide Web Consortium (W3C standard for storing semantic web data is the resource description framework (RDF. To enhance the efficiency in the execution time for querying large RDF graphs, the evolving metaheuristic algorithms become an alternate to the traditional query optimization methods. This paper focuses on the problem of query optimization of semantic web data. An efficient algorithm called adaptive Cuckoo search (ACS for querying and generating optimal query plan for large RDF graphs is designed in this research. Experiments were conducted on different datasets with varying number of predicates. The experimental results have exposed that the proposed approach has provided significant results in terms of query execution time. The extent to which the algorithm is efficient is tested and the results are documented.

  19. Adaptive neuro-fuzzy estimation of optimal lens system parameters

    Science.gov (United States)

    Petković, Dalibor; Pavlović, Nenad T.; Shamshirband, Shahaboddin; Mat Kiah, Miss Laiha; Badrul Anuar, Nor; Idna Idris, Mohd Yamani

    2014-04-01

    Due to the popularization of digital technology, the demand for high-quality digital products has become critical. The quantitative assessment of image quality is an important consideration in any type of imaging system. Therefore, developing a design that combines the requirements of good image quality is desirable. Lens system design represents a crucial factor for good image quality. Optimization procedure is the main part of the lens system design methodology. Lens system optimization is a complex non-linear optimization task, often with intricate physical constraints, for which there is no analytical solutions. Therefore lens system design provides ideal problems for intelligent optimization algorithms. There are many tools which can be used to measure optical performance. One very useful tool is the spot diagram. The spot diagram gives an indication of the image of a point object. In this paper, one optimization criterion for lens system, the spot size radius, is considered. This paper presents new lens optimization methods based on adaptive neuro-fuzzy inference strategy (ANFIS). This intelligent estimator is implemented using Matlab/Simulink and the performances are investigated.

  20. Adaptive Multi-Agent Systems for Constrained Optimization

    Science.gov (United States)

    Macready, William; Bieniawski, Stefan; Wolpert, David H.

    2004-01-01

    Product Distribution (PD) theory is a new framework for analyzing and controlling distributed systems. Here we demonstrate its use for distributed stochastic optimization. First we review one motivation of PD theory, as the information-theoretic extension of conventional full-rationality game theory to the case of bounded rational agents. In this extension the equilibrium of the game is the optimizer of a Lagrangian of the (probability distribution of) the joint state of the agents. When the game in question is a team game with constraints, that equilibrium optimizes the expected value of the team game utility, subject to those constraints. The updating of the Lagrange parameters in the Lagrangian can be viewed as a form of automated annealing, that focuses the MAS more and more on the optimal pure strategy. This provides a simple way to map the solution of any constrained optimization problem onto the equilibrium of a Multi-Agent System (MAS). We present computer experiments involving both the Queen s problem and K-SAT validating the predictions of PD theory and its use for off-the-shelf distributed adaptive optimization.

  1. Support Vector Machine Based on Adaptive Acceleration Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Mohammed Hasan Abdulameer

    2014-01-01

    Full Text Available Existing face recognition methods utilize particle swarm optimizer (PSO and opposition based particle swarm optimizer (OPSO to optimize the parameters of SVM. However, the utilization of random values in the velocity calculation decreases the performance of these techniques; that is, during the velocity computation, we normally use random values for the acceleration coefficients and this creates randomness in the solution. To address this problem, an adaptive acceleration particle swarm optimization (AAPSO technique is proposed. To evaluate our proposed method, we employ both face and iris recognition based on AAPSO with SVM (AAPSO-SVM. In the face and iris recognition systems, performance is evaluated using two human face databases, YALE and CASIA, and the UBiris dataset. In this method, we initially perform feature extraction and then recognition on the extracted features. In the recognition process, the extracted features are used for SVM training and testing. During the training and testing, the SVM parameters are optimized with the AAPSO technique, and in AAPSO, the acceleration coefficients are computed using the particle fitness values. The parameters in SVM, which are optimized by AAPSO, perform efficiently for both face and iris recognition. A comparative analysis between our proposed AAPSO-SVM and the PSO-SVM technique is presented.

  2. Design and analysis of self-adapted task scheduling strategies in wireless sensor networks.

    Science.gov (United States)

    Guo, Wenzhong; Xiong, Naixue; Chao, Han-Chieh; Hussain, Sajid; Chen, Guolong

    2011-01-01

    In a wireless sensor network (WSN), the usage of resources is usually highly related to the execution of tasks which consume a certain amount of computing and communication bandwidth. Parallel processing among sensors is a promising solution to provide the demanded computation capacity in WSNs. Task allocation and scheduling is a typical problem in the area of high performance computing. Although task allocation and scheduling in wired processor networks has been well studied in the past, their counterparts for WSNs remain largely unexplored. Existing traditional high performance computing solutions cannot be directly implemented in WSNs due to the limitations of WSNs such as limited resource availability and the shared communication medium. In this paper, a self-adapted task scheduling strategy for WSNs is presented. First, a multi-agent-based architecture for WSNs is proposed and a mathematical model of dynamic alliance is constructed for the task allocation problem. Then an effective discrete particle swarm optimization (PSO) algorithm for the dynamic alliance (DPSO-DA) with a well-designed particle position code and fitness function is proposed. A mutation operator which can effectively improve the algorithm's ability of global search and population diversity is also introduced in this algorithm. Finally, the simulation results show that the proposed solution can achieve significant better performance than other algorithms.

  3. Design and Analysis of Self-Adapted Task Scheduling Strategies in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Sajid Hussain

    2011-06-01

    Full Text Available In a wireless sensor network (WSN, the usage of resources is usually highly related to the execution of tasks which consume a certain amount of computing and communication bandwidth. Parallel processing among sensors is a promising solution to provide the demanded computation capacity in WSNs. Task allocation and  scheduling is a typical problem in the area of high performance computing. Although task allocation and scheduling in wired processor networks has been well studied in the past, their counterparts for WSNs remain largely unexplored. Existing traditional high performance computing solutions cannot be directly implemented in WSNs due to the limitations of WSNs such as limited resource availability and the shared communication medium. In this paper, a self-adapted task scheduling strategy for WSNs is presented. First, a multi-agent-based architecture for WSNs is proposed and a mathematical model of dynamic alliance is constructed for the task allocation problem. Then an effective discrete particle swarm optimization (PSO algorithm for the dynamic alliance (DPSO-DA with a well-designed particle position code and fitness function is proposed. A mutation operator which can effectively improve the algorithm’s ability of global search and population diversity is also introduced in this algorithm. Finally, the simulation results show that the proposed solution can achieve significant better performance than other algorithms.

  4. Energy-Optimal Scheduling in Low Duty Cycle Sensor Networks

    CERN Document Server

    Aydin, Nursen; Ercetin, Ozgur

    2011-01-01

    Energy consumption of a wireless sensor node mainly depends on the amount of time the node spends in each of the high power active (e.g., transmit, receive) and low power sleep modes. It has been well established that in order to prolong node's lifetime the duty-cycle of the node should be low. However, low power sleep modes usually have low current draw but high energy cost while switching to the active mode with a higher current draw. In this work, we investigate a MaxWeightlike opportunistic sleep-active scheduling algorithm that takes into account time- varying channel and traffic conditions. We show that our algorithm is energy optimal in the sense that the proposed ESS algorithm can achieve an energy consumption which is arbitrarily close to the global minimum solution. Simulation studies are provided to confirm the theoretical results.

  5. Temporally optimized spanwise vorticity sensor measurements in turbulent boundary layers

    Science.gov (United States)

    Morrill-Winter, C.; Klewicki, J.; Baidya, R.; Marusic, I.

    2015-12-01

    Multi-element hot-wire anemometry was used to measure spanwise vorticity fluctuations in turbulent boundary layers. Smooth wall boundary layer profiles, with very good spatial and temporal resolution, were acquired over a Kármán number range of 2000-12,700 at the Melbourne Wind Tunnel at the University of Melbourne and the University of New Hampshire's Flow Physics Facility. A custom hot-wire probe was necessary to simultaneously obtain velocity and spanwise vorticity measurements centered at a fixed point in space. A custom calibration/processing scheme was developed to utilize single-wall-parallel wires to optimize the accuracy of the measured wall-normal velocity fluctuations derived from the sensor's ×-array.

  6. Energy Optimal Transmission Scheduling in Wireless Sensor Networks

    CERN Document Server

    Srivastava, Rahul

    2010-01-01

    One of the main issues in the design of sensor networks is energy efficient communication of time-critical data. Energy wastage can be caused by failed packet transmission attempts at each node due to channel dynamics and interference. Therefore transmission control techniques that are unaware of the channel dynamics can lead to suboptimal channel use patterns. In this paper we propose a transmission controller that utilizes different "grades" of channel side information to schedule packet transmissions in an optimal way, while meeting a deadline constraint for all packets waiting in the transmission queue. The wireless channel is modeled as a finite-state Markov channel. We are specifically interested in the case where the transmitter has low-grade channel side information that can be obtained based solely on the ACK/NAK sequence for the previous transmissions. Our scheduler is readily implementable and it is based on the dynamic programming solution to the finite-horizon transmission control problem. We als...

  7. Analysis and optimization of Love wave liquid sensors.

    Science.gov (United States)

    Jakoby, B; Vellekoop, M J

    1998-01-01

    Love wave sensors are highly sensitive microacoustic devices, which are well suited for liquid sensing applications thanks to the shear polarization of the wave. The sensing mechanism thereby relies on the mechanical (or acoustic) interaction of the device with the liquid. The successful utilization of Love wave devices for this purpose requires proper shielding to avoid unwanted electric interaction of the liquid with the wave and the transducers. In this work we describe the effects of this electric interaction and the proper design of a shield to prevent it. We present analysis methods, which illustrate the impact of the interaction and which help to obtain an optimized design of the proposed shield. We also present experimental results for devices that have been fabricated according to these design rules.

  8. An Adaptive Fuzzy Control Approach for the Robust Tracking of a MEMS Gyroscope Sensor

    Directory of Open Access Journals (Sweden)

    Juntao Fei

    2011-11-01

    Full Text Available In this paper, a direct adaptive fuzzy control using a supervisory compensator is designed for the robust tracking of a MEMS gyroscope sensor. The parameters of the membership functions are adjusted according to the designed adaptive law for the purpose of tracking a reference trajectory. A fuzzy controller that can approximate the unknown nonlinear function and compensate the system

  9. Optimization of an Autonomous Car Controller using a Self-Adaptive Evolutionary Strategy

    Directory of Open Access Journals (Sweden)

    Tae Seong Kim

    2012-09-01

    Full Text Available Autonomous cars control the steering wheel, acceleration and the brake pedal, the gears and the clutch using sensory information from multiple sources. Like a human driver, it understands the current situation on the roads from the live streaming of sensory values. The decision‐making module often suffers from the limited range of sensors and complexity due to the large number of sensors and actuators. Because it is tedious and difficult to design the controller manually from trial‐and‐error, it is desirable to use intelligent optimization algorithms. In this work, we propose optimizing the parameters of an autonomous car controller using self‐ adaptive evolutionary strategies (SAESs which co‐evolve solutions and mutation steps for each parameter. We also describe how the most generalized parameter set can be retrieved from the process of optimization. Open‐source car racing simulation software (TORCS is used to test the goodness of the proposed methods on 6 different tracks. Experimental results show that the SAES is competitive with the manual design of authors and a simple ES.

  10. Optimization of an Autonomous Car Controller Using a Self-Adaptive Evolutionary Strategy

    Directory of Open Access Journals (Sweden)

    Tae Seong Kim

    2012-09-01

    Full Text Available Autonomous cars control the steering wheel, acceleration and the brake pedal, the gears and the clutch using sensory information from multiple sources. Like a human driver, it understands the current situation on the roads from the live streaming of sensory values. The decision-making module often suffers from the limited range of sensors and complexity due to the large number of sensors and actuators. Because it is tedious and difficult to design the controller manually from trial-and-error, it is desirable to use intelligent optimization algorithms. In this work, we propose optimizing the parameters of an autonomous car controller using self-adaptive evolutionary strategies (SAESs which co-evolve solutions and mutation steps for each parameter. We also describe how the most generalized parameter set can be retrieved from the process of optimization. Open-source car racing simulation software (TORCS is used to test the goodness of the proposed methods on 6 different tracks. Experimental results show that the SAES is competitive with the manual design of authors and a simple ES.

  11. Sensor Location Problem Optimization for Traffic Network with Different Spatial Distributions of Traffic Information.

    Science.gov (United States)

    Bao, Xu; Li, Haijian; Qin, Lingqiao; Xu, Dongwei; Ran, Bin; Rong, Jian

    2016-10-27

    To obtain adequate traffic information, the density of traffic sensors should be sufficiently high to cover the entire transportation network. However, deploying sensors densely over the entire network may not be realistic for practical applications due to the budgetary constraints of traffic management agencies. This paper describes several possible spatial distributions of traffic information credibility and proposes corresponding different sensor information credibility functions to describe these spatial distribution properties. A maximum benefit model and its simplified model are proposed to solve the traffic sensor location problem. The relationships between the benefit and the number of sensors are formulated with different sensor information credibility functions. Next, expanding models and algorithms in analytic results are performed. For each case, the maximum benefit, the optimal number and spacing of sensors are obtained and the analytic formulations of the optimal sensor locations are derived as well. Finally, a numerical example is proposed to verify the validity and availability of the proposed models for solving a network sensor location problem. The results show that the optimal number of sensors of segments with different model parameters in an entire freeway network can be calculated. Besides, it can also be concluded that the optimal sensor spacing is independent of end restrictions but dependent on the values of model parameters that represent the physical conditions of sensors and roads.

  12. Adaptive symbiotic organisms search (SOS algorithm for structural design optimization

    Directory of Open Access Journals (Sweden)

    Ghanshyam G. Tejani

    2016-07-01

    Full Text Available The symbiotic organisms search (SOS algorithm is an effective metaheuristic developed in 2014, which mimics the symbiotic relationship among the living beings, such as mutualism, commensalism, and parasitism, to survive in the ecosystem. In this study, three modified versions of the SOS algorithm are proposed by introducing adaptive benefit factors in the basic SOS algorithm to improve its efficiency. The basic SOS algorithm only considers benefit factors, whereas the proposed variants of the SOS algorithm, consider effective combinations of adaptive benefit factors and benefit factors to study their competence to lay down a good balance between exploration and exploitation of the search space. The proposed algorithms are tested to suit its applications to the engineering structures subjected to dynamic excitation, which may lead to undesirable vibrations. Structure optimization problems become more challenging if the shape and size variables are taken into account along with the frequency. To check the feasibility and effectiveness of the proposed algorithms, six different planar and space trusses are subjected to experimental analysis. The results obtained using the proposed methods are compared with those obtained using other optimization methods well established in the literature. The results reveal that the adaptive SOS algorithm is more reliable and efficient than the basic SOS algorithm and other state-of-the-art algorithms.

  13. 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.

  14. An adaptive jitter mechanism for reactive route discovery in sensor networks.

    Science.gov (United States)

    Cordero, Juan Antonio; Yi, Jiazi; Clausen, Thomas

    2014-08-08

    This paper analyses the impact of jitter when applied to route discovery in reactive (on-demand) routing protocols. In multi-hop non-synchronized wireless networks, jitter--a small, random variation in the timing of message emission--is commonly employed, as a means to avoid collisions of simultaneous transmissions by adjacent routers over the same channel. In a reactive routing protocol for sensor and ad hoc networks, jitter is recommended during the route discovery process, specifically, during the network-wide flooding of route request messages, in order to avoid collisions. Commonly, a simple uniform jitter is recommended. Alas, this is not without drawbacks: when applying uniform jitter to the route discovery process, an effect called delay inversion is observed. This paper, first, studies and quantifies this delay inversion effect. Second, this paper proposes an adaptive jitter mechanism, designed to alleviate the delay inversion effect and thereby to reduce the route discovery overhead and (ultimately) allow the routing protocol to find more optimal paths, as compared to uniform jitter. This paper presents both analytical and simulation studies, showing that the proposed adaptive jitter can effectively decrease the cost of route discovery and increase the path quality.

  15. An Adaptive Jitter Mechanism for Reactive Route Discovery in Sensor Networks

    Directory of Open Access Journals (Sweden)

    Juan Antonio Cordero

    2014-08-01

    Full Text Available This paper analyses the impact of jitter when applied to route discovery in reactive (on-demand routing protocols. In multi-hop non-synchronized wireless networks, jitter—a small, random variation in the timing of message emission—is commonly employed, as a means to avoid collisions of simultaneous transmissions by adjacent routers over the same channel. In a reactive routing protocol for sensor and ad hoc networks, jitter is recommended during the route discovery process, specifically, during the network-wide flooding of route request messages, in order to avoid collisions. Commonly, a simple uniform jitter is recommended. Alas, this is not without drawbacks: when applying uniform jitter to the route discovery process, an effect called delay inversion is observed. This paper, first, studies and quantifies this delay inversion effect. Second, this paper proposes an adaptive jitter mechanism, designed to alleviate the delay inversion effect and thereby to reduce the route discovery overhead and (ultimately allow the routing protocol to find more optimal paths, as compared to uniform jitter. This paper presents both analytical and simulation studies, showing that the proposed adaptive jitter can effectively decrease the cost of route discovery and increase the path quality.

  16. 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.

  17. Adaptive Piezoelectric Circuitry Sensor Network with High-Frequency Harmonics Interrogation for Structural Damage Detection

    Science.gov (United States)

    2014-09-17

    AFRL-OSR-VA-TR-2014-0255 ADAPTIVE PIEZOELECTRIC CIRCUITRY SENSOR NETWORK KON-WELL WANG MICHIGAN UNIV ANN ARBOR Final Report 09/17/2014 DISTRIBUTION A...by ANSI Std. Z39.18 09-09-2014 Final Performance Report 06-01-2011 - 05-31-2014 Adaptive Piezoelectric Circuitry Sensor Network with High-Frequency...approach. Specifically, we propose to create a new concept of adaptive high-frequency piezoelectric self-sensing interrogation by means of tunable

  18. Analytical approach to cross-layer protocol optimization in wireless sensor networks

    Science.gov (United States)

    Hortos, William S.

    2008-04-01

    terms of the concatenated protocol parameters. New source-to-destination routes are sought that optimize cross-layer interdependencies to achieve the "best available" performance in the WSN. The protocol design, modified from a known reactive protocol, adapts the achievable performance to the transient network conditions and resource levels. Control of network behavior is realized through the conditional rates of the MVPPs. Optimal cross-layer protocol parameters are determined by stochastic dynamic programming conditions derived from models of transient packetized sensor data flows. Moreover, the defining conditions for WSN configurations, grouping sensor nodes into clusters and establishing data aggregation at processing nodes within those clusters, lead to computationally tractable solutions to the stochastic differential equations that describe network dynamics. Closed-form solution characteristics provide an alternative to the "directed diffusion" methods for resource-efficient WSN protocols published previously by other researchers. Performance verification of the resulting cross-layer designs is found by embedding the optimality conditions for the protocols in actual WSN scenarios replicated in a wireless network simulation environment. Performance tradeoffs among protocol parameters remain for a sequel to the paper.

  19. 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

  20. Planar Thinned Arrays: Optimization and Subarray Based Adaptive Processing

    Directory of Open Access Journals (Sweden)

    P. Lombardo

    2013-01-01

    Full Text Available A new approach is presented for the optimized design of a planar thinned array; the proposed strategy works with single antenna elements or with small sets of different subarray types, properly located on a planar surface. The optimization approach is based on the maximization of an objective function accounting for side lobe level and considering a fixed number of active elements/subarrays. The proposed technique is suitable for different shapes of the desired output array, allowing the achievement of the desired directivity properties on the corresponding antenna pattern. The use of subarrays with a limited number of different shapes is relevant for industrial production, which would benefit from reduced design and manufacturing costs. The resulting modularity allows scalable antenna designs for different applications. Moreover, subarrays can be arranged in a set of subapertures, each connected to an independent receiving channel. Therefore, adaptive processing techniques could be applied to cope with and mitigate clutter echoes and external electromagnetic interferences. The performance of adaptive techniques with subapertures taken from the optimized thinned array is evaluated against assigned clutter and jamming scenarios and compared to the performance achievable considering a subarray based filled array with the same number of active elements.

  1. Covariance matrix adaptation for multi-objective optimization.

    Science.gov (United States)

    Igel, Christian; Hansen, Nikolaus; Roth, Stefan

    2007-01-01

    The covariance matrix adaptation evolution strategy (CMA-ES) is one of the most powerful evolutionary algorithms for real-valued single-objective optimization. In this paper, we develop a variant of the CMA-ES for multi-objective optimization (MOO). We first introduce a single-objective, elitist CMA-ES using plus-selection and step size control based on a success rule. This algorithm is compared to the standard CMA-ES. The elitist CMA-ES turns out to be slightly faster on unimodal functions, but is more prone to getting stuck in sub-optimal local minima. In the new multi-objective CMAES (MO-CMA-ES) a population of individuals that adapt their search strategy as in the elitist CMA-ES is maintained. These are subject to multi-objective selection. The selection is based on non-dominated sorting using either the crowding-distance or the contributing hypervolume as second sorting criterion. Both the elitist single-objective CMA-ES and the MO-CMA-ES inherit important invariance properties, in particular invariance against rotation of the search space, from the original CMA-ES. The benefits of the new MO-CMA-ES in comparison to the well-known NSGA-II and to NSDE, a multi-objective differential evolution algorithm, are experimentally shown.

  2. 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...... information access mechanism and show how trade-off between energy consumption and information reliability can be achieved....

  3. Sensor-less aberration correction in optical imaging systems using blind optimization

    Science.gov (United States)

    Avanaki, Mohammad R. N.; Mazraeh Khoshki, R.; Hojjatoleslami, S. A.; Podoleanu, A. Gh.

    2012-02-01

    The imperfection of optical devices in an optical imaging system deteriorates wavefront which results in aberration. This reduces the optical signal to noise ratio of the imaging system and the quality of the produced images. Adaptive optics composed of wavefront sensor (WFS) and deformable mirror (DM) is a straightforward solution for this problem. The need for a WFS in an AO system, raises the cost of the overall system, and there are also instances when they cannot be used, such as in microscopy. Moreover stray reflections from lens surfaces affect the performance of the WFS. In this paper, we describe a blind optimization technique with an in-expensive electronics without using the WFS to correct the aberration in order to achieve better quality images. The correction system includes an electromagnetic DM from Imagine, Mirao52d, with 52 actuators which are controlled by particle swarm optimization (PSO) algorithm. The results of the application of simulated annealing (SA), and genetic algorithm (GA) techniques that we have implemented in the sensor-less AO are used for comparison.

  4. Optimal distributed resource allocation in a wireless sensor network for control systems

    Institute of Scientific and Technical Information of China (English)

    MAO Jian-lin; WU Zhi-ming

    2007-01-01

    Wireless technology is applied increasingly in networked control systems. A new form of wireless network called wireless sensor network can bring control systems some advantages, such as flexibility and feasibility of network deployment at low costs, while it also raises some new challenges. First, the communication resources shared by all the control loops are limited.Second, the wireless and multi-hop character of sensor network makes the resources scheduling more difficult. Thus, how to effectively allocate the limited communication resources for those control loops is an important problem. In this paper, this problem is formulated as an optimal sampling frequency assignment problem, where the objective function is to maximize the utility of control systems, subject to channel capacity constraints. Then an iterative distributed algorithm based on local buffer information is proposed. Finally, the simulation results show that the proposed algorithm can effectively allocate the limited communication resource in a distributed way. It can achieve the optimal quality of the control system and adapt to the network load changes.

  5. Optimal search: a practical interpretation of information-driven sensor management

    NARCIS (Netherlands)

    Katsilieris, F.; Boers, Y.

    We consider the problem of scheduling an agile sensor for performing optimal search for a target. A probability density function is created for representing our knowledge about where the target might be and it is utilized by the proposed sensor management criteria for finding optimal search

  6. Optimal sensor placement for multi-setup modal analysis of structures

    Science.gov (United States)

    Zhang, Jie; Maes, Kristof; De Roeck, Guido; Reynders, Edwin; Papadimitriou, Costas; Lombaert, Geert

    2017-08-01

    Modal tests on large structures are often performed in multiple setups for practical reasons. Several sensors are kept fixed as reference sensors over all setups, while the other, so called roving sensors, are moved from one setup to another. This paper develops an optimal sensor placement strategy for multi-setup modal identification, which simultaneously optimizes the locations of the reference sensors and roving sensors. As an optimality criterion, the Information Entropy is adopted, which is a scalar measure of uncertainty in the Bayesian framework. The focus in the application goes to repetitive structures where modes typically occur in clusters, with closely spaced natural frequencies and similar wavelengths. The proposed strategy is illustrated for selecting optimal positions of uni-axial sensors for a repetitive frame structure. The influence of the number of reference sensors and two strategies for positioning roving sensors, i.e. a cluster and a uniform distribution of roving sensors, are investigated. The number of reference sensors is found to be preferably equal to or larger than the number of modes to be identified. In this case, the information content, as quantified by the Information Entropy, is not very sensitive to the roving sensor strategy. If less reference sensors are used, it is highly preferred to distribute the roving sensors uniformly over the structure instead of clustering them. The proposed strategy has been validated by an experimental modal test on a floor of an office building of KU Leuven, which has a nearly repetitive structural layout. The results show how optimally locating sensors allows extracting more information from the data. Though the focus is on applications involving repetitive structures, the proposed strategy can be applied to multi-setup modal identification of any large structure.

  7. An Artificial Measurements-Based Adaptive Filter for Energy-Efficient Target Tracking via Underwater Wireless Sensor Networks.

    Science.gov (United States)

    Chen, Huayan; Zhang, Senlin; Liu, Meiqin; Zhang, Qunfei

    2017-04-27

    We study the problem of energy-efficient target tracking in underwater wireless sensor networks (UWSNs). Since sensors of UWSNs are battery-powered, it is impracticable to replace the batteries when exhausted. This means that the battery life affects the lifetime of the whole network. In order to extend the network lifetime, it is worth reducing the energy consumption on the premise of sufficient tracking accuracy. This paper proposes an energy-efficient filter that implements the tradeoff between communication cost and tracking accuracy. Under the distributed fusion framework, local sensors should not send their weak information to the fusion center if their measurement residuals are smaller than the pre-given threshold. In order to guarantee the target tracking accuracy, artificial measurements are generated to compensate for those unsent real measurements. Then, an adaptive scheme is derived to take full advantages of the artificial measurements-based filter in terms of energy-efficiency. Furthermore, a computationally efficient optimal sensor selection scheme is proposed to improve tracking accuracy on the premise of employing the same number of sensors. Simulation demonstrates that our scheme has superior advantages in the tradeoff between communication cost and tracking accuracy. It saves much energy while loosing little tracking accuracy or improves tracking performance with less additional energy cost.

  8. Adaptive nonmonotone line search method for unconstrained optimization

    Institute of Scientific and Technical Information of China (English)

    Qunyan ZHOU; Wenyu SUN

    2008-01-01

    In this paper, an adaptive nonmonotone line search method for unconstrained minimization problems is proposed. At every iteration, the new algorithm selects only one of the two directions: a Newton-type direc-tion and a negative curvature direction, to perform the line search. The nonmonotone technique is included in the backtracking line search when the Newton-type direction is the search direction. Furthermore, if the negative curvature direction is the search direction, we increase the steplength un-der certain conditions. The global convergence to a stationary point with second-order optimality conditions is established. Some numerical results which show the efficiency of the new algorithm are reported.

  9. Point spread function optimization for STORM using adaptive optics

    Science.gov (United States)

    Forouhesh Tehrani, Kayvan; Kner, Peter

    2014-03-01

    Stochastic Optical Reconstruction Microscopy (STORM) requires a high Strehl ratio point spread function (PSF) to achieve high resolution, especially in the presence of background fluorescence. The PSF is degraded by aberrations caused by imperfections in the optics, the refractive index mismatch between the sample and coverslip, and the refractive index variations of the sample. These aberrations distort the shape of the PSF and increase the PSF width directly reducing the resolution of STORM. Here we discuss the use of Adaptive Optics (AO) to correct aberrations, maintaining a high Strehl ratio even in thick tissue. Because the intensity fluctuates strongly from frame to frame, image intensity is not a reliable measure of PSF quality, and the choice of a robust optimization metric is critical. We demonstrate the use of genetic algorithms with single molecule imaging for optimization of the wavefront and introduce a metric that is relatively insensitive to image intensity. We demonstrate the correction of the wavefront from measurements of single quantum dots.

  10. Circadian clocks optimally adapt to sunlight for reliable synchronization

    CERN Document Server

    Hasegawa, Yoshihiko

    2014-01-01

    Circadian oscillation provides selection advantages through synchronization to the daylight cycle. However, a reliable clock must be designed through two conflicting properties: entrainability to properly respond to external stimuli such as sunlight, and regularity to oscillate with a precise period. These two aspects do not easily coexist because better entrainability favors higher sensitivity, which may sacrifice the regularity. To investigate conditions for satisfying the two properties, we analytically calculated the optimal phase-response curve with a variational method. Our result indicates an existence of a dead zone, i.e., a time during which external stimuli neither advance nor delay the clock. This result is independent of model details and a dead zone appears only when the input stimuli obey the time course of actual insolation. Our calculation demonstrates that every circadian clock with a dead zone is optimally adapted to the daylight cycle. Our result also explains the lack of a dead zone in osc...

  11. Adaptive backtracking search optimization algorithm with pattern search for numerical optimization

    Institute of Scientific and Technical Information of China (English)

    Shu Wang; Xinyu Da; Mudong Li; Tong Han

    2016-01-01

    Thebacktracking search optimization algorithm (BSA) is one of the most recently proposed population-based evolutionary algorithms for global optimization. Due to its memory ability and simple structure, BSA has powerful capa-bility to find global optimal solutions. However, the algorithm is stil insufficient in balancing the exploration and the exploita-tion. Therefore, an improved adaptive backtracking search optimization algorithm combined with modified Hooke-Jeeves pattern search is proposed for numerical global optimization. It has two main parts: the BSA is used for the exploration phase and the modified pattern search method completes the ex-ploitation phase. In particular, a simple but effective strategy of adapting one of BSA’s important control parameters is intro-duced. The proposed algorithm is compared with standard BSA, three state-of-the-art evolutionary algorithms and three superior algorithms in IEEE Congress on Evolutionary Com-putation 2014 (IEEE CEC2014) over six widely-used bench-marks and 22 real-parameter single objective numerical opti-mization benchmarks in IEEE CEC2014. The results of ex-periment and statistical analysis demonstrate the effective-ness and efficiency of the proposed algorithm.

  12. Objectively Optimized Observation Direction System Providing Situational Awareness for a Sensor Web

    Science.gov (United States)

    Aulov, O.; Lary, D. J.

    2010-12-01

    There is great utility in having a flexible and automated objective observation direction system for the decadal survey missions and beyond. Such a system allows us to optimize the observations made by suite of sensors to address specific goals from long term monitoring to rapid response. We have developed such a prototype using a network of communicating software elements to control a heterogeneous network of sensor systems, which can have multiple modes and flexible viewing geometries. Our system makes sensor systems intelligent and situationally aware. Together they form a sensor web of multiple sensors working together and capable of automated target selection, i.e. the sensors “know” where they are, what they are able to observe, what targets and with what priorities they should observe. This system is implemented in three components. The first component is a Sensor Web simulator. The Sensor Web simulator describes the capabilities and locations of each sensor as a function of time, whether they are orbital, sub-orbital, or ground based. The simulator has been implemented using AGIs Satellite Tool Kit (STK). STK makes it easy to analyze and visualize optimal solutions for complex space scenarios, and perform complex analysis of land, sea, air, space assets, and shares results in one integrated solution. The second component is target scheduler that was implemented with STK Scheduler. STK Scheduler is powered by a scheduling engine that finds better solutions in a shorter amount of time than traditional heuristic algorithms. The global search algorithm within this engine is based on neural network technology that is capable of finding solutions to larger and more complex problems and maximizing the value of limited resources. The third component is a modeling and data assimilation system. It provides situational awareness by supplying the time evolution of uncertainty and information content metrics that are used to tell us what we need to observe and the

  13. Improving the Forecast Accuracy of an Ocean Observation and Prediction System by Adaptive Control of the Sensor Network

    Science.gov (United States)

    Talukder, A.; Panangadan, A. V.; Blumberg, A. F.; Herrington, T.; Georgas, N.

    2008-12-01

    The New York Harbor Observation and Prediction System (NYHOPS) is a real-time, estuarine and coastal ocean observing and modeling system for the New York Harbor and surrounding waters. Real-time measurements from in-situ mobile and stationary sensors in the NYHOPS networks are assimilated into marine forecasts in order to reduce the discrepancy with ground truth. The forecasts are obtained from the ECOMSED hydrodynamic model, a shallow water derivative of the Princeton Ocean Model. Currently, all sensors in the NYHOPS system are operated in a fixed mode with uniform sampling rates. This technology infusion effort demonstrates the use of Model Predictive Control (MPC) to autonomously adapt the operation of both mobile and stationary sensors in response to changing events that are -automatically detected from the ECOMSED forecasts. The controller focuses sensing resources on those regions that are expected to be impacted by the detected events. The MPC approach involves formulating the problem of calculating the optimal sensor parameters as a constrained multi-objective optimization problem. We have developed an objective function that takes into account the spatiotemporal relationship of the in-situ sensor locations and the locations of events detected by the model. Experiments in simulation were carried out using data collected during a freshwater flooding event. The location of the resulting freshwater plume was calculated from the corresponding model forecasts and was used by the MPC controller to derive control parameters for the sensing assets. The operational parameters that are controlled include the sampling rates of stationary sensors, paths of unmanned underwater vehicles (UUVs), and data transfer routes between sensors and the central modeling computer. The simulation experiments show that MPC-based sensor control reduces the RMS error in the forecast by a factor of 380% as compared to uniform sampling. The paths of multiple UUVs were simultaneously

  14. Real-sky adaptive optics experiments on optimal control of tip-tilt modes

    Science.gov (United States)

    Doelman, Niek; Fraanje, Rufus; den Breeje, Remco

    2011-09-01

    In recent years various researchers have concentrated on control performance improvement for adaptive optics systems by using more sophisticated design methods. These approaches account for the inherent spatial and temporal correlations in the wavefront sensor data. Several control schemes have been proposed, of which the common essence is the minimization of a criterion function, yielding so-called 'optimal' or LQG control solutions. These are in some cases also referred to as 'predictive control'. Following the H2-optimal control design approach proposed by Hinnen [JOSA A Vol. 24, 2007], a real-sky experiment has been carried out on the McMath-Pierce solar telescope on Kitt Peak, Arizona. The purpose of the experiment was to validate the favourable results of optimal control, as obtained in simulations and laboratory experiments, on a real-time AO system on a telescope with real-sky turbulence. During the experimental week, it appeared that the deformable mirror did not have sufficient stroke to cope with the strong wavefront aberrations as measured by the AO wavefront sensor. Therefore, it was decided to focus on optimal control of the lower aberration modes tip and tilt only (using the separate TT-mirror). The control experiments demonstrate that for the particular AO system and seeing conditions (Nov 14, 2010) real-time optimal control can reduce the tip and tilt amplitudes by an additional factor of about 2 (RMS), compared to the common integrator control of the tip and tilt modes. For the low frequency band the improvement ranges from 10 to 20 dB. This performance agrees reasonably well with the predicted performance which is based on off-line analysis of the WFS data. The paper will discuss the experimental results in detail and also address important aspects like the non-stationarity of the wavefront aberrations, coupled versus decoupled tip-tilt control and measures to increase the robustness of the controller.

  15. Spacecraft Component Adaptive Layout Environment (SCALE): An efficient optimization tool

    Science.gov (United States)

    Fakoor, Mahdi; Ghoreishi, Seyed Mohammad Navid; Sabaghzadeh, Hossein

    2016-11-01

    For finding the optimum layout of spacecraft subsystems, important factors such as the center of gravity, moments of inertia, thermal distribution, natural frequencies, etc. should be taken into account. This large number of effective parameters makes the optimum layout process of spacecraft subsystems complex and time consuming. In this paper, an automatic tool, based on multi-objective optimization methods, is proposed for a three dimensional layout of spacecraft subsystems. In this regard, an efficient Spacecraft Component Adaptive Layout Environment (SCALE) is produced by integration of some modeling, FEM, and optimization software. SCALE automatically provides optimal solutions for a three dimensional layout of spacecraft subsystems with considering important constraints such as center of gravity, moment of inertia, thermal distribution, natural frequencies and structural strength. In order to show the superiority and efficiency of SCALE, layout of a telecommunication spacecraft and a remote sensing spacecraft are performed. The results show that, the objective functions values for obtained layouts by using SCALE are in a much better condition than traditional one i.e. Reference Baseline Solution (RBS) which is proposed by the engineering system team. This indicates the good performance and ability of SCALE for finding the optimal layout of spacecraft subsystems.

  16. Planar Hall effect sensor bridge geometries optimized for magnetic bead detection

    DEFF Research Database (Denmark)

    Østerberg, Frederik Westergaard; Rizzi, Giovanni; Henriksen, Anders Dahl

    2014-01-01

    Novel designs of planar Hall effect bridge sensors optimized for magnetic bead detection are presented and characterized. By constructing the sensor geometries appropriately, the sensors can be tailored to be sensitive to an external magnetic field, the magnetic field due to beads being magnetized...... by the sensor self-field or a combination thereof. The sensors can be made nominally insensitive to small external magnetic fields, while being maximally sensitive to magnetic beads, magnetized by the sensor self-field. Thus, the sensor designs can be tailored towards specific applications with minimal...... influence of external variables. Three different sensor designs are analyzed theoretically. To experimentally validate the theoretical signals, two sets of measurements are performed. First, the sensor signals are characterized as function of an externally applied magnetic field. Then, measurements...

  17. Multi-Sensor Detection with Particle Swarm Optimization for Time-Frequency Coded Cooperative WSNs Based on MC-CDMA for Underground Coal Mines.

    Science.gov (United States)

    Xu, Jingjing; Yang, Wei; Zhang, Linyuan; Han, Ruisong; Shao, Xiaotao

    2015-08-27

    In this paper, a wireless sensor network (WSN) technology adapted to underground channel conditions is developed, which has important theoretical and practical value for safety monitoring in underground coal mines. According to the characteristics that the space, time and frequency resources of underground tunnel are open, it is proposed to constitute wireless sensor nodes based on multicarrier code division multiple access (MC-CDMA) to make full use of these resources. To improve the wireless transmission performance of source sensor nodes, it is also proposed to utilize cooperative sensors with good channel conditions from the sink node to assist source sensors with poor channel conditions. Moreover, the total power of the source sensor and its cooperative sensors is allocated on the basis of their channel conditions to increase the energy efficiency of the WSN. To solve the problem that multiple access interference (MAI) arises when multiple source sensors transmit monitoring information simultaneously, a kind of multi-sensor detection (MSD) algorithm with particle swarm optimization (PSO), namely D-PSO, is proposed for the time-frequency coded cooperative MC-CDMA WSN. Simulation results show that the average bit error rate (BER) performance of the proposed WSN in an underground coal mine is improved significantly by using wireless sensor nodes based on MC-CDMA, adopting time-frequency coded cooperative transmission and D-PSO algorithm with particle swarm optimization.

  18. Multi-Sensor Detection with Particle Swarm Optimization for Time-Frequency Coded Cooperative WSNs Based on MC-CDMA for Underground Coal Mines

    Directory of Open Access Journals (Sweden)

    Jingjing Xu

    2015-08-01

    Full Text Available In this paper, a wireless sensor network (WSN technology adapted to underground channel conditions is developed, which has important theoretical and practical value for safety monitoring in underground coal mines. According to the characteristics that the space, time and frequency resources of underground tunnel are open, it is proposed to constitute wireless sensor nodes based on multicarrier code division multiple access (MC-CDMA to make full use of these resources. To improve the wireless transmission performance of source sensor nodes, it is also proposed to utilize cooperative sensors with good channel conditions from the sink node to assist source sensors with poor channel conditions. Moreover, the total power of the source sensor and its cooperative sensors is allocated on the basis of their channel conditions to increase the energy efficiency of the WSN. To solve the problem that multiple access interference (MAI arises when multiple source sensors transmit monitoring information simultaneously, a kind of multi-sensor detection (MSD algorithm with particle swarm optimization (PSO, namely D-PSO, is proposed for the time-frequency coded cooperative MC-CDMA WSN. Simulation results show that the average bit error rate (BER performance of the proposed WSN in an underground coal mine is improved significantly by using wireless sensor nodes based on MC-CDMA, adopting time-frequency coded cooperative transmission and D-PSO algorithm with particle swarm optimization.

  19. BLOSSOMS: Building Lightweight Optimized Sensor Systems on a Massive Scale

    Institute of Scientific and Technical Information of China (English)

    Wen Gao; Lionel M. Ni; Zhi-Wei Xu; S. C. Cheung; Li Cui; Qiong Luo

    2005-01-01

    As a joint effort between the Chinese Academy of Sciences and the Hong Kong University of Science and Technology, the BLOSSOMS sensor network project aims to identify research issues at all levels from practical applications down to the design of sensor nodes. In this project, a heterogeneous sensor array including different types of application-dependent sensors as well as monitoring sensors and intruding sensors are being developed. Application-dependent power-aware communication protocols are also being studied for communications among sensor nodes. An ontology-based middleware is built to relieve the burden of application developers from collecting, classifying and processing messy sensing contexts. This project is also developing a set of tools allowing researchers to model, simulate/emulate, analyze, and monitor various functions of sensor networks.

  20. Efficient retrieval of landscape Hessian: forced optimal covariance adaptive learning.

    Science.gov (United States)

    Shir, Ofer M; Roslund, Jonathan; Whitley, Darrell; Rabitz, Herschel

    2014-06-01

    Knowledge of the Hessian matrix at the landscape optimum of a controlled physical observable offers valuable information about the system robustness to control noise. The Hessian can also assist in physical landscape characterization, which is of particular interest in quantum system control experiments. The recently developed landscape theoretical analysis motivated the compilation of an automated method to learn the Hessian matrix about the global optimum without derivative measurements from noisy data. The current study introduces the forced optimal covariance adaptive learning (FOCAL) technique for this purpose. FOCAL relies on the covariance matrix adaptation evolution strategy (CMA-ES) that exploits covariance information amongst the control variables by means of principal component analysis. The FOCAL technique is designed to operate with experimental optimization, generally involving continuous high-dimensional search landscapes (≳30) with large Hessian condition numbers (≳10^{4}). This paper introduces the theoretical foundations of the inverse relationship between the covariance learned by the evolution strategy and the actual Hessian matrix of the landscape. FOCAL is presented and demonstrated to retrieve the Hessian matrix with high fidelity on both model landscapes and quantum control experiments, which are observed to possess nonseparable, nonquadratic search landscapes. The recovered Hessian forms were corroborated by physical knowledge of the systems. The implications of FOCAL extend beyond the investigated studies to potentially cover other physically motivated multivariate landscapes.

  1. Transitions in optimal adaptive strategies for populations in fluctuating environments

    Science.gov (United States)

    Mayer, Andreas; Mora, Thierry; Rivoire, Olivier; Walczak, Aleksandra M.

    2017-09-01

    Biological populations are subject to fluctuating environmental conditions. Different adaptive strategies can allow them to cope with these fluctuations: specialization to one particular environmental condition, adoption of a generalist phenotype that compromises between conditions, or population-wise diversification (bet hedging). Which strategy provides the largest selective advantage in the long run depends on the range of accessible phenotypes and the statistics of the environmental fluctuations. Here, we analyze this problem in a simple mathematical model of population growth. First, we review and extend a graphical method to identify the nature of the optimal strategy when the environmental fluctuations are uncorrelated. Temporal correlations in environmental fluctuations open up new strategies that rely on memory but are mathematically challenging to study: We present analytical results to address this challenge. We illustrate our general approach by analyzing optimal adaptive strategies in the presence of trade-offs that constrain the range of accessible phenotypes. Our results extend several previous studies and have applications to a variety of biological phenomena, from antibiotic resistance in bacteria to immune responses in vertebrates.

  2. Adaptive optimal spectral range for dynamically changing scene

    Science.gov (United States)

    Pinsky, Ephi; Siman-tov, Avihay; Peles, David

    2012-06-01

    A novel multispectral video system that continuously optimizes both its spectral range channels and the exposure time of each channel autonomously, under dynamic scenes, varying from short range-clear scene to long range-poor visibility, is currently being developed. Transparency and contrast of high scattering medium of channels with spectral ranges in the near infrared is superior to the visible channels, particularly to the blue range. Longer wavelength spectral ranges that induce higher contrast are therefore favored. Images of 3 spectral channels are fused and displayed for (pseudo) color visualization, as an integrated high contrast video stream. In addition to the dynamic optimization of the spectral channels, optimal real-time exposure time is adjusted simultaneously and autonomously for each channel. A criterion of maximum average signal, derived dynamically from previous frames of the video stream is used (Patent Application - International Publication Number: WO2009/093110 A2, 30.07.2009). This configuration enables dynamic compatibility with the optimal exposure time of a dynamically changing scene. It also maximizes the signal to noise ratio and compensates each channel for the specified value of daylight reflections and sensors response for each spectral range. A possible implementation is a color video camera based on 4 synchronized, highly responsive, CCD imaging detectors, attached to a 4CCD dichroic prism and combined with a common, color corrected, lens. Principal Components Analysis (PCA) technique is then applied for real time "dimensional collapse" in color space, in order to select and fuse, for clear color visualization, the 3 most significant principal channels out of at least 4 characterized by high contrast and rich details in the image data.

  3. Performance Optimization of Multiple Interconnected Heterogeneous Sensor Networks via Collaborative Information Sharing

    CERN Document Server

    Pal, Sougata; Bellalta, Boris; Oliver, Miquel

    2012-01-01

    Interconnecting multiple sensor networks is a relatively new research field which has emerged in the Wireless Sensor Network domain. Wireless Sensor Networks (WSNs) have typically been seen as logically separate, and few works have considered interconnection and interaction between them. Interconnecting multiple heterogeneous sensor networks therefore opens up a new field besides more traditional research on, e.g., routing, self organization, or MAC layer development. Up to now, some approaches have been proposed for interconnecting multiple sensor networks with goals like information sharing or monitoring multiple sensor networks. In this paper, we propose to utilize inter-WSN communication to enable Collaborative Performance Optimization, i.e., our approach aims to optimize the performance of individual WSNs by taking into account measured information from others. The parameters to be optimized are energy consumption on the one hand and sensing quality on the other.

  4. Statistical-mechanics-inspired optimization of sensor field configuration for detection of mobile targets.

    Science.gov (United States)

    Mukherjee, Kushal; Gupta, Shalabh; Ray, Asok; Wettergren, Thomas A

    2011-06-01

    This paper presents a statistical-mechanics-inspired procedure for optimization of the sensor field configuration to detect mobile targets. The key idea is to capture the low-dimensional behavior of the sensor field configurations across the Pareto front in a multiobjective scenario for optimal sensor deployment, where the nondominated points are concentrated within a small region of the large-dimensional decision space. The sensor distribution is constructed using location-dependent energy-like functions and intensive temperature-like parameters in the sense of statistical mechanics. This low-dimensional representation is shown to permit rapid optimization of the sensor field distribution on a high-fidelity simulation test bed of distributed sensor networks.

  5. Approximation Algorithms for Optimal Decision Trees and Adaptive TSP Problems

    CERN Document Server

    Gupta, Anupam; Nagarajan, Viswanath; Ravi, R

    2010-01-01

    We consider the problem of constructing optimal decision trees: given a collection of tests which can disambiguate between a set of $m$ possible diseases, each test having a cost, and the a-priori likelihood of the patient having any particular disease, what is a good adaptive strategy to perform these tests to minimize the expected cost to identify the disease? We settle the approximability of this problem by giving a tight $O(\\log m)$-approximation algorithm. We also consider a more substantial generalization, the Adaptive TSP problem. Given an underlying metric space, a random subset $S$ of cities is drawn from a known distribution, but $S$ is initially unknown to us--we get information about whether any city is in $S$ only when we visit the city in question. What is a good adaptive way of visiting all the cities in the random subset $S$ while minimizing the expected distance traveled? For this problem, we give the first poly-logarithmic approximation, and show that this algorithm is best possible unless w...

  6. Optimizing Satellite Communications With Adaptive and Phased Array Antennas

    Science.gov (United States)

    Ingram, Mary Ann; Romanofsky, Robert; Lee, Richard Q.; Miranda, Felix; Popovic, Zoya; Langley, John; Barott, William C.; Ahmed, M. Usman; Mandl, Dan

    2004-01-01

    A new adaptive antenna array architecture for low-earth-orbiting satellite ground stations is being investigated. These ground stations are intended to have no moving parts and could potentially be operated in populated areas, where terrestrial interference is likely. The architecture includes multiple, moderately directive phased arrays. The phased arrays, each steered in the approximate direction of the satellite, are adaptively combined to enhance the Signal-to-Noise and Interference-Ratio (SNIR) of the desired satellite. The size of each phased array is to be traded-off with the number of phased arrays, to optimize cost, while meeting a bit-error-rate threshold. Also, two phased array architectures are being prototyped: a spacefed lens array and a reflect-array. If two co-channel satellites are in the field of view of the phased arrays, then multi-user detection techniques may enable simultaneous demodulation of the satellite signals, also known as Space Division Multiple Access (SDMA). We report on Phase I of the project, in which fixed directional elements are adaptively combined in a prototype to demodulate the S-band downlink of the EO-1 satellite, which is part of the New Millennium Program at NASA.

  7. Routing in Wireless Sensor Networks Using an Ant Colony Optimization (ACO) Router Chip

    OpenAIRE

    Dervis Karaboga; Selcuk Okdem

    2009-01-01

    Wireless Sensor Networks consisting of nodes with limited power are deployed to gather useful information from the field. In WSNs it is critical to collect the information in an energy efficient manner. Ant Colony Optimization, a swarm intelligence based optimization technique, is widely used in network routing. A novel routing approach using an Ant Colony Optimization algorithm is proposed for Wireless Sensor Networks consisting of stable nodes. Illustrative examples, detailed descriptions a...

  8. A new hybrid optimization method inspired from swarm intelligence: Fuzzy adaptive swallow swarm optimization algorithm (FASSO

    Directory of Open Access Journals (Sweden)

    Mehdi Neshat

    2015-11-01

    Full Text Available In this article, the objective was to present effective and optimal strategies aimed at improving the Swallow Swarm Optimization (SSO method. The SSO is one of the best optimization methods based on swarm intelligence which is inspired by the intelligent behaviors of swallows. It has been able to offer a relatively strong method for solving optimization problems. However, despite its many advantages, the SSO suffers from two shortcomings. Firstly, particles movement speed is not controlled satisfactorily during the search due to the lack of an inertia weight. Secondly, the variables of the acceleration coefficient are not able to strike a balance between the local and the global searches because they are not sufficiently flexible in complex environments. Therefore, the SSO algorithm does not provide adequate results when it searches in functions such as the Step or Quadric function. Hence, the fuzzy adaptive Swallow Swarm Optimization (FASSO method was introduced to deal with these problems. Meanwhile, results enjoy high accuracy which are obtained by using an adaptive inertia weight and through combining two fuzzy logic systems to accurately calculate the acceleration coefficients. High speed of convergence, avoidance from falling into local extremum, and high level of error tolerance are the advantages of proposed method. The FASSO was compared with eleven of the best PSO methods and SSO in 18 benchmark functions. Finally, significant results were obtained.

  9. Optimization of Thermal Neutron Converter in SiC Sensors for Spectral Radiation Measurements

    Energy Technology Data Exchange (ETDEWEB)

    Krolikowski, Igor; Cetnar, Jerzy [Department of Nuclear Energy, Faculty of Energy and Fuels at AGH University of Science and Technology, Al. Mickiewicza 30, 30-059 Cracow (Poland); Issa, Fatima; Ferrone, Raffaello; Ottaviani, Laurent [IM2NP, UMR CNRS 7334, Aix-Marseille University, Case 231, 13397 Marseille Cedex 20 (France); Szalkai, Dora; Klix, Axel [KIT- Karlsruhe Institute of Technology, Institute of Neutron Physics and Reactor Technology, Karlsruhe 76344 (Germany); Vermeeren, Ludo [SCK-CEN, Boeretang 200, B-2400 Mol (Belgium); Lyoussi, Abdalla [CEA, DEN, DER, Instrumentation Sensors and Dosimetry Laboratory, Cadarache, F-13108 St-Paul-Lez-Durance (France); Saenger, Richard [Etudes et Productions Schlumberger, Clamart (France)

    2015-07-01

    Optimization of the neutron converter in SiC sensors is presented. The sensors are used for spectral radiation measurements of thermal and fast neutrons and optionally gamma ray at elevated temperature in harsh radiation environment. The neutron converter, which is based on 10B, allows to detect thermal neutrons by means of neutron capture reaction. Two construction of the sensors were used to measure radiation in experiments. Sensor responses collected in experiments have been reproduced by the computer tool created by authors, it allows to validate the tool. The tool creates the response matrix function describing the characteristic of the sensors and it was used for detailed analyses of the sensor responses. Obtained results help to optimize the neutron converter in order to increase thermal neutron detection. Several enhanced construction of the sensors, which includes the neutron converter based on {sup 10}B or {sup 6}Li, were proposed. (authors)

  10. Adaptive sensor-fault tolerant control for a class of multivariable uncertain nonlinear systems.

    Science.gov (United States)

    Khebbache, Hicham; Tadjine, Mohamed; Labiod, Salim; Boulkroune, Abdesselem

    2015-03-01

    This paper deals with the active fault tolerant control (AFTC) problem for a class of multiple-input multiple-output (MIMO) uncertain nonlinear systems subject to sensor faults and external disturbances. The proposed AFTC method can tolerate three additive (bias, drift and loss of accuracy) and one multiplicative (loss of effectiveness) sensor faults. By employing backstepping technique, a novel adaptive backstepping-based AFTC scheme is developed using the fact that sensor faults and system uncertainties (including external disturbances and unexpected nonlinear functions caused by sensor faults) can be on-line estimated and compensated via robust adaptive schemes. The stability analysis of the closed-loop system is rigorously proven using a Lyapunov approach. The effectiveness of the proposed controller is illustrated by two simulation examples.

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

    Science.gov (United States)

    Iida, Fumiya; Nurzaman, Surya G

    2016-08-01

    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.

  12. On the Optimal Location of Sensors for Parametric Identification of Linear Structural Systems

    DEFF Research Database (Denmark)

    Kirkegaard, Poul Henning; Brincker, Rune

    A survey of the field of optimal location of sensors for parametric identification of linear structural systems is presented. The survey shows that few papers are devoted to the case of optimal location sensors in which the measurements are modelled by a random field with non-trivial covariance...... function. Most often it is assumed that the results of the measurements are statistically independent variables. In an example the importance of considering the measurements as statistically dependent random variables is shown. The example is concerned with optimal location of sensors for parametric...... identification of modal parameters for a vibrating beam under random loading. The covariance of the modal parameters expected to be obtained is investigated to variations of number and location of sensors. Further, the influence of the noise on the optimal location of the sensors is investigated....

  13. The Study of Cross-layer Optimization for Wireless Rechargeable Sensor Networks Implemented in Coal Mines.

    Science.gov (United States)

    Ding, Xu; Shi, Lei; Han, Jianghong; Lu, Jingting

    2016-01-28

    Wireless sensor networks deployed in coal mines could help companies provide workers working in coal mines with more qualified working conditions. With the underground information collected by sensor nodes at hand, the underground working conditions could be evaluated more precisely. However, sensor nodes may tend to malfunction due to their limited energy supply. In this paper, we study the cross-layer optimization problem for wireless rechargeable sensor networks implemented in coal mines, of which the energy could be replenished through the newly-brewed wireless energy transfer technique. The main results of this article are two-fold: firstly, we obtain the optimal relay nodes' placement according to the minimum overall energy consumption criterion through the Lagrange dual problem and KKT conditions; secondly, the optimal strategies for recharging locomotives and wireless sensor networks are acquired by solving a cross-layer optimization problem. The cyclic nature of these strategies is also manifested through simulations in this paper.

  14. Adaptive AOA-aided TOA self-positioning for mobile wireless sensor networks.

    Science.gov (United States)

    Wen, Chih-Yu; Chan, Fu-Kai

    2010-01-01

    Location-awareness is crucial and becoming increasingly important to many applications in wireless sensor networks. This paper presents a network-based positioning system and outlines recent work in which we have developed an efficient principled approach to localize a mobile sensor using time of arrival (TOA) and angle of arrival (AOA) information employing multiple seeds in the line-of-sight scenario. By receiving the periodic broadcasts from the seeds, the mobile target sensors can obtain adequate observations and localize themselves automatically. The proposed positioning scheme performs location estimation in three phases: (I) AOA-aided TOA measurement, (II) Geometrical positioning with particle filter, and (III) Adaptive fuzzy control. Based on the distance measurements and the initial position estimate, adaptive fuzzy control scheme is applied to solve the localization adjustment problem. The simulations show that the proposed approach provides adaptive flexibility and robust improvement in position estimation.

  15. Urban-Climate Adaptation Tool: Optimizing Green Infrastructure

    Science.gov (United States)

    Fellows, J. D.; Bhaduri, B. L.

    2016-12-01

    Cities have an opportunity to become more resilient to future climate change and green through investments made in urban infrastructure today. However, most cities lack access to credible high-resolution climate change projection and other environmental information needed to assess and address potential vulnerabilities from future climate variability. Therefore, we present an integrated framework for developing an urban climate adaptation tool (Urban-CAT). The initial focus of Urban-CAT is to optimize the placement of green infrastructure (e.g., green roofs, porous pavements, retention basins, etc.) to be better control stormwater runoff and lower the ambient urban temperature. Urban-CAT consists of four modules. Firstly, it provides climate projections at different spatial resolutions for quantifying urban landscape. Secondly, this projected data is combined with socio-economic and other environmental data using leading and lagging indicators for assessing landscape vulnerability to climate extremes (e.g., urban flooding). Thirdly, a neighborhood scale modeling approach is presented for identifying candidate areas for adaptation strategies (e.g., green infrastructure as an adaptation strategy for urban flooding). Finally, all these capabilities are made available as a web-based tool to support decision-making and communication at the neighborhood and city levels. This presentation will highlight the methods that drive each of the modules, demo some of the capabilities using Knoxville Tennessee as a case study, and discuss the challenges of working with communities to incorporate climate change into their planning. Next steps on Urban-CAT is to additional capabilities to create a comprehensive climate adaptation tool, including energy, transportation, health, and other key urban services.

  16. Fuzzy Adaptive Particle Swarm Optimization for Power Loss Minimisation in Distribution Systems Using Optimal Load Response

    DEFF Research Database (Denmark)

    Hu, Weihao; Chen, Zhe; Bak-Jensen, Birgitte;

    2014-01-01

    power loss minimization in distribution systems. In this paper, a new method to achieve power loss minimization in distribution systems by using a price signal to guide the demand side management is proposed. A fuzzy adaptive particle swarm optimization (FAPSO) is used as a tool for the power loss...... minimization study. Simulation results show that the proposed approach is an effective measure to achieve power loss minimization in distribution systems....

  17. Wavefront sensorless adaptive optics versus sensor-based adaptive optics for in vivo fluorescence retinal imaging (Conference Presentation)

    Science.gov (United States)

    Wahl, Daniel J.; Zhang, Pengfei; Jian, Yifan; Bonora, Stefano; Sarunic, Marinko V.; Zawadzki, Robert J.

    2017-02-01

    Adaptive optics (AO) is essential for achieving diffraction limited resolution in large numerical aperture (NA) in-vivo retinal imaging in small animals. Cellular-resolution in-vivo imaging of fluorescently labeled cells is highly desirable for studying pathophysiology in animal models of retina diseases in pre-clinical vision research. Currently, wavefront sensor-based (WFS-based) AO is widely used for retinal imaging and has demonstrated great success. However, the performance can be limited by several factors including common path errors, wavefront reconstruction errors and an ill-defined reference plane on the retina. Wavefront sensorless (WFS-less) AO has the advantage of avoiding these issues at the cost of algorithmic execution time. We have investigated WFS-less AO on a fluorescence scanning laser ophthalmoscopy (fSLO) system that was originally designed for WFS-based AO. The WFS-based AO uses a Shack-Hartmann WFS and a continuous surface deformable mirror in a closed-loop control system to measure and correct for aberrations induced by the mouse eye. The WFS-less AO performs an open-loop modal optimization with an image quality metric. After WFS-less AO aberration correction, the WFS was used as a control of the closed-loop WFS-less AO operation. We can easily switch between WFS-based and WFS-less control of the deformable mirror multiple times within an imaging session for the same mouse. This allows for a direct comparison between these two types of AO correction for fSLO. Our results demonstrate volumetric AO-fSLO imaging of mouse retinal cells labeled with GFP. Most significantly, we have analyzed and compared the aberration correction results for WFS-based and WFS-less AO imaging.

  18. On the effect of phenotypic dimensionality on adaptation and optimality.

    Science.gov (United States)

    Brun-Usan, M; Marin-Riera, M; Salazar-Ciudad, I

    2014-12-01

    What proportion of the traits of individuals has been optimally shaped by natural selection and what has not? Here, we estimate the maximal number of those traits using a mathematical model for natural selection in multitrait organisms. The model represents the most ideal conditions for natural selection: a simple genotype-phenotype map and independent variation between traits. The model is also used to disentangle the influence of fitness functions and the number of traits, n, per se on the efficiency of natural selection. We also allow n to evolve. Our simulations show that, for all fitness functions and even in the best conditions optimal phenotypes are rarely encountered, only for n = 1, and that a large proportion of traits are always far from their optimum, specially for large n. This happens to different degrees depending on the fitness functions (additive linear, additive nonlinear, Gaussian and multiplicative). The traits that arise earlier in evolution account for a larger proportion of the absolute fitness of individuals. Thus, complex phenotypes have, in proportion, more traits that are far from optimal and the closeness to the optimum correlates with the age of the trait. Based on estimated population sizes, mutation rates and selection coefficients, we provide an upper estimation of the number of traits that can become and remain adapted by direct natural selection.

  19. SARA: a self-adaptive and resource-aware approach towards secure wireless ad hoc and sensor networks

    Science.gov (United States)

    Chigan, Chunxiao; Li, Leiyuan

    2005-05-01

    Providing security is essential for mission critical Wireless Ad Hoc and Sensor Networks (WAHSN) applications. Often a highly secure mechanism inevitably consumes a rather large amount of system resources, which in turn may unintentionally cause a Security Service Denial of Service (SSDoS) attack. This paper proposes a self-adaptive resource-aware (SARA) security provisioning approach for WAHSNs. For resource scarce WAHSNs, SARA strives to provide the optimal tradeoff between the sufficient security (which is reflected by the Security Index (SI)) and the acceptable network performance degradation (which is reflected by the Performance Index (PI)). With the support of the offline optimal secure protocol selection module and the online self-adaptive security control module, SARA is capable of employing different combinations of secure protocol sets to satisfy different security need at different condition for different applications. To determine the security index SI of a secure protocol set, a heuristic cross-layer security-service mapping mechanism is presented. Furthermore, we evaluate performance index PI of a secure protocol set via simulation followed by Analysis of Variance (ANOVA). Consequently, the proposed self-adaptive security provisioning based on both SI and PI achieves the maximum overall network security services and network performance services, without causing the SSDoS attack. Furthermore, this self-adaptive mechanism is capable of switching from one secure protocol set to another while keeping similar level of security and performance, it thus provides additional security by security service hopping.

  20. The Wireless Sensor Networks Base Layout and Density Optimization Oriented towards Traffic Information Collection

    Directory of Open Access Journals (Sweden)

    Musong Gu

    2015-01-01

    Full Text Available Wireless sensor networks (WSN are applied in Intelligent Transport System for data collection. For the low redundancy rate of the wireless sensor networks nodes of traffic information collection, the senor nodes should be deployed reasonably for the WSN nodes to work effectively, and, thus, the base network structure and the density optimization of the sensor network are one of the main problems of WSN application. This paper establishes the wireless sensor networks design optimization model oriented to the traffic information collection, solving the design optimization model with the chemical reaction optimization (CRO algorithm. The experimental results show that CRO algorithm outperforms the traditional particle swarm optimization (PSO in solving the wireless sensor network design optimization oriented to the traffic information collection, capable of optimizing the wireless sensor network deployment of traffic information collection to contribute to the great improvement of the comprehensive value of the network performance. The reasonable design of the wireless sensor network nodes has great significance for the information collection, post-maintenance-and-extension, and cost saving of a monitoring system.

  1. ADEX optimized adaptive controllers and systems from research to industrial practice

    CERN Document Server

    Martín-Sánchez, Juan M

    2015-01-01

    This book is a didactic explanation of the developments of predictive, adaptive predictive and optimized adaptive control, including the latest methodology of adaptive predictive expert (ADEX) control, and their practical applications. It is focused on the stability perspective, used in the introduction of these methodologies, and is divided into six parts, with exercises and real-time simulations provided for the reader as appropriate. ADEX Optimized Adaptive Controllers and Systems begins with the conceptual and intuitive knowledge of the technology and derives the stability conditions to be verified by the driver block and the adaptive mechanism of the optimized adaptive controller to guarantee achievement of desired control performance. The second and third parts are centered on the design of the driver block and adaptive mechanism, which verify these stability conditions. The authors then proceed to detail the stability theory that supports predictive, adaptive predictive and optimized adaptive control m...

  2. Secure Tracking in Sensor Networks using Adaptive Extended Kalman Filter

    CERN Document Server

    Fard, Ali P

    2012-01-01

    Location information of sensor nodes has become an essential part of many applications in Wireless Sensor Networks (WSN). The importance of location estimation and object tracking has made them the target of many security attacks. Various methods have tried to provide location information with high accuracy, while lots of them have neglected the fact that WSNs may be deployed in hostile environments. In this paper, we address the problem of securely tracking a Mobile Node (MN) which has been noticed very little previously. A novel secure tracking algorithm is proposed based on Extended Kalman Filter (EKF) that is capable of tracking a Mobile Node (MN) with high resolution in the presence of compromised or colluding malicious beacon nodes. It filters out and identifies the malicious beacon data in the process of tracking. The proposed method considerably outperforms the previously proposed secure algorithms in terms of either detection rate or MSE. The experimental data based on different settings for the netw...

  3. Adaptive localization and tracking of objects in a sensor network

    OpenAIRE

    2014-01-01

    [ANGLÈS] Wireless Sensor Networks (WSNs) are used to monitor physical or environmental conditions, and to pass their data through the network to a central location. These networks have applications in diverse areas including environmental, health monitoring, home automation or military. The devices that form the network have limited resources, such as power and computational capacity.\\par This thesis focus on the localization and tracking problem, presenting a method that can be used with obj...

  4. Adaptive Noise Reduction Techniques for Airborne Acoustic Sensors

    Science.gov (United States)

    2012-01-01

    8 2.3.3 Low Cost Scout UAV Acoustics System ( LOSAS ) . . . . . . . . . . . . . 8 2.3.4 Shot Spotter...detecting supersonic projectiles. 2.3.3 Low Cost Scout UAV Acoustics System ( LOSAS ) SARA, Inc. has developed an acoustic sensor package that is...www.armytimes.com/legacy/new/0-ARMYPAPER-620646.php [25] (2012) Sara, inc. [Online]. Available: http://www.sara.com/ISR/acoustic sensing/ LOSAS . html [26

  5. Sensor fault diagnosis of time-delay systems based on adaptive observer

    Institute of Scientific and Technical Information of China (English)

    YOU Fu-qiang; TIAN Zuo-hua; SHI Song-jiao

    2006-01-01

    Presents a novel approach for the sensor fault diagnosis of time-delay systems by using an adaptive observer technique. The sensor fault is modeled as an additive perturbation described by a time varying function. Systems without model uncertainty are initially considered, followed by a discussion of a general situation where the system is subjected to either model uncertainty or external disturbance. An adaptive diagnostic algorithm is developed to diagnose the fault, and a modified version is proposed for general system to improve robustness. The stability of fault diagnosis system is proved. Finally, a numerical example is given to illustrate the efficiency of the proposed method.

  6. Determining the Optimal Placement of Sensors on a Concrete Arch Dam Using a Quantum Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Kai Zhu

    2016-01-01

    Full Text Available Structural modal identification has become increasingly important in health monitoring, fault diagnosis, vibration control, and dynamic analysis of engineering structures in recent years. Based on an analysis of traditional optimization algorithms, this paper proposes a novel sensor optimization criterion that combines the effective independence (EFI method with the modal strain energy (MSE method. Considering the complex structure and enormous degrees of freedom (DOFs of modern concrete arch dam, a quantum genetic algorithm (QGA is used to optimize the corresponding sensor network on the upstream surface of a dam. Finally, this study uses a specific concrete arch dam as an example and determines the optimal sensor placement using the proposed method. By comparing the results with the traditional optimization methods, the proposed method is shown to maximize the spatial intersection angle among the modal vectors of sensor network and can effectively resist ambient perturbations, which will make the identified modal parameters more precise.

  7. Theoretical model and optimization of a novel temperature sensor based on quartz tuning fork resonators

    Science.gov (United States)

    Jun, Xu; Bo, You; Xin, Li; Juan, Cui

    2007-12-01

    To accurately measure temperatures, a novel temperature sensor based on a quartz tuning fork resonator has been designed. The principle of the quartz tuning fork temperature sensor is that the resonant frequency of the quartz resonator changes with the variation in temperature. This type of tuning fork resonator has been designed with a new doubly rotated cut work at flexural vibration mode as temperature sensor. The characteristics of the temperature sensor were evaluated and the results sufficiently met the target of development for temperature sensor. The theoretical model for temperature sensing has been developed and built. The sensor structure was analysed by finite element method (FEM) and optimized, including tuning fork geometry, tine electrode pattern and the sensor's elements size. The performance curve of output versus measured temperature is given. The results from theoretical analysis and experiments indicate that the sensor's sensitivity can reach 60 ppm °C-1 with the measured temperature range varying from 0 to 100 °C.

  8. Cooperative control of multi-agent systems optimal and adaptive design approaches

    CERN Document Server

    Lewis, Frank L; Hengster-Movric, Kristian; Das, Abhijit

    2014-01-01

    Task complexity, communication constraints, flexibility and energy-saving concerns are all factors that may require a group of autonomous agents to work together in a cooperative manner. Applications involving such complications include mobile robots, wireless sensor networks, unmanned aerial vehicles (UAVs), spacecraft, and so on. In such networked multi-agent scenarios, the restrictions imposed by the communication graph topology can pose severe problems in the design of cooperative feedback control systems.  Cooperative control of multi-agent systems is a challenging topic for both control theorists and practitioners and has been the subject of significant recent research. Cooperative Control of Multi-Agent Systems extends optimal control and adaptive control design methods to multi-agent systems on communication graphs.  It develops Riccati design techniques for general linear dynamics for cooperative state feedback design, cooperative observer design, and cooperative dynamic output feedback design.  B...

  9. Adaptive preheating duration control for low-power ambient air quality sensor networks.

    Science.gov (United States)

    Baek, Yoonchul; Atiq, Mahin K; Kim, Hyung Seok

    2014-03-20

    Ceramic gas sensors used for measuring ambient air quality have features suitable for practical applications such as healthcare and air quality management, but have a major drawback-large power consumption to preheat the sensor for accurate measurements. In this paper; the adaptive preheating duration control (APC) method is proposed to reduce the power consumption of ambient air quality sensor networks. APC reduces the duration of unnecessary preheating, thereby alleviating power consumption. Furthermore, the APC can allow systems to meet user requirements such as accuracy and periodicity factor when detecting the concentration of a target gas. A performance evaluation of the power consumption of gas sensors is conducted with various user requirements and factors that affect the preheating duration of the gas sensor. This shows that the power consumption of the APC is lower than that of continuous power supply methods and constant power supply/cutoff methods.

  10. Adaptive Preheating Duration Control for Low-Power Ambient Air Quality Sensor Networks

    Directory of Open Access Journals (Sweden)

    Yoonchul Baek

    2014-03-01

    Full Text Available Ceramic gas sensors used for measuring ambient air quality have features suitable for practical applications such as healthcare and air quality management, but have a major drawback—large power consumption to preheat the sensor for accurate measurements. In this paper; the adaptive preheating duration control (APC method is proposed to reduce the power consumption of ambient air quality sensor networks. APC reduces the duration of unnecessary preheating, thereby alleviating power consumption. Furthermore, the APC can allow systems to meet user requirements such as accuracy and periodicity factor when detecting the concentration of a target gas. A performance evaluation of the power consumption of gas sensors is conducted with various user requirements and factors that affect the preheating duration of the gas sensor. This shows that the power consumption of the APC is lower than that of continuous power supply methods and constant power supply/cutoff methods.

  11. Secure adaptive topology control for wireless ad-hoc sensor networks.

    Science.gov (United States)

    Hsueh, Ching-Tsung; Li, Yu-Wei; Wen, Chih-Yu; Ouyang, Yen-Chieh

    2010-01-01

    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.

  12. 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

  13. Improving Kinematic Accuracy of Soft Wearable Data Gloves by Optimizing Sensor Locations.

    Science.gov (United States)

    Kim, Dong Hyun; Lee, Sang Wook; Park, Hyung-Soon

    2016-05-26

    Bending sensors enable compact, wearable designs when used for measuring hand configurations in data gloves. While existing data gloves can accurately measure angular displacement of the finger and distal thumb joints, accurate measurement of thumb carpometacarpal (CMC) joint movements remains challenging due to crosstalk between the multi-sensor outputs required to measure the degrees of freedom (DOF). To properly measure CMC-joint configurations, sensor locations that minimize sensor crosstalk must be identified. This paper presents a novel approach to identifying optimal sensor locations. Three-dimensional hand surface data from ten subjects was collected in multiple thumb postures with varied CMC-joint flexion and abduction angles. For each posture, scanned CMC-joint contours were used to estimate CMC-joint flexion and abduction angles by varying the positions and orientations of two bending sensors. Optimal sensor locations were estimated by the least squares method, which minimized the difference between the true CMC-joint angles and the joint angle estimates. Finally, the resultant optimal sensor locations were experimentally validated. Placing sensors at the optimal locations, CMC-joint angle measurement accuracies improved (flexion, 2.8° ± 1.9°; abduction, 1.9° ± 1.2°). The proposed method for improving the accuracy of the sensing system can be extended to other types of soft wearable measurement devices.

  14. Improving Kinematic Accuracy of Soft Wearable Data Gloves by Optimizing Sensor Locations

    Directory of Open Access Journals (Sweden)

    Dong Hyun Kim

    2016-05-01

    Full Text Available Bending sensors enable compact, wearable designs when used for measuring hand configurations in data gloves. While existing data gloves can accurately measure angular displacement of the finger and distal thumb joints, accurate measurement of thumb carpometacarpal (CMC joint movements remains challenging due to crosstalk between the multi-sensor outputs required to measure the degrees of freedom (DOF. To properly measure CMC-joint configurations, sensor locations that minimize sensor crosstalk must be identified. This paper presents a novel approach to identifying optimal sensor locations. Three-dimensional hand surface data from ten subjects was collected in multiple thumb postures with varied CMC-joint flexion and abduction angles. For each posture, scanned CMC-joint contours were used to estimate CMC-joint flexion and abduction angles by varying the positions and orientations of two bending sensors. Optimal sensor locations were estimated by the least squares method, which minimized the difference between the true CMC-joint angles and the joint angle estimates. Finally, the resultant optimal sensor locations were experimentally validated. Placing sensors at the optimal locations, CMC-joint angle measurement accuracies improved (flexion, 2.8° ± 1.9°; abduction, 1.9° ± 1.2°. The proposed method for improving the accuracy of the sensing system can be extended to other types of soft wearable measurement devices.

  15. Adaptive Home System Using Wireless Sensor Network And Multi Agent System

    Directory of Open Access Journals (Sweden)

    Jayarani Kamble

    2014-03-01

    Full Text Available 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 wireless sensor network used to efficiently deliver solution for an energy management and efficiency for adaptive home. An algorithm used in adaptive home system is based on software agent approach that reduce the energy consumption at home by considering the user’s occupancy, temperature and user’s preferences as input to the system.

  16. Characterization and optimization of an ultrasonic piezo-optical ring sensor

    Science.gov (United States)

    Frankforter, Erik; Lin, Bin; Giurgiutiu, Victor

    2016-04-01

    A resonant piezo-optical ring sensor with both piezoelectric and fiber Bragg grating (FBG) sensing elements was assessed for ultrasonic wave detection. The ring sensor is an existing device that has been shown experimentally to exhibit a number of sensing features: omnidirectionality, mode selectivity, and frequency tunability. The present study uses finite element modeling to understand these features as a means to characterize and optimize the sensor. A combined vibration-wave propagation modeling approach was used, where the vibrational modeling provided a basis for understanding sensing features, and the wave propagation modeling provided predictive power for sensor performance. The sensor features corresponded to the fundamental vibrational mode of the sensor, particularly to the base motion of this mode. The vibrational modeling was also used to guide sensor optimization, with an emphasis on the FBG and piezoelectric sensing elements. It was found that sensor symmetry and nodes of extraneous resonance modes could be exploited to provide a single-resonance response. A series of pitch-catch guided wave experiments were performed on a thin aluminum plate to assess the optimized sensor configuration. Tuning curves showed a single-frequency response to a Lamb wave and mechanical filtering away from the dominant frequency; the sensor capability for mechanical amplification of a Lamb wave and mechanical amplification of a pencil-lead-break acoustic emission event were also demonstrated.

  17. Pursuing optimal electric machines transient diagnosis: The adaptive slope transform

    Science.gov (United States)

    Pons-Llinares, Joan; Riera-Guasp, Martín; Antonino-Daviu, Jose A.; Habetler, Thomas G.

    2016-12-01

    The aim of this paper is to introduce a new linear time-frequency transform to improve the detection of fault components in electric machines transient currents. Linear transforms are analysed from the perspective of the atoms used. A criterion to select the atoms at every point of the time-frequency plane is proposed, taking into account the characteristics of the searched component at each point. This criterion leads to the definition of the Adaptive Slope Transform, which enables a complete and optimal capture of the different components evolutions in a transient current. A comparison with conventional linear transforms (Short-Time Fourier Transform and Wavelet Transform) is carried out, showing their inherent limitations. The approach is tested with laboratory and field motors, and the Lower Sideband Harmonic is captured for the first time during an induction motor startup and subsequent load oscillations, accurately tracking its evolution.

  18. An optimal adaptive quantization index modulation watermarking algorithm

    Institute of Scientific and Technical Information of China (English)

    Shaomin Zhu; Jianming Liu

    2009-01-01

    A novel adaptive watermarking algorithm in discrete wavelet transform (DWT) based on quantization index modulation (QIM) technique is presented. The host image is decomposed into wavelet subbands, and then the approximation subband is divided into non-overlapping small embedding blocks. The secret watermark bit is embedded into singular value vector of each embedding block by applying QIM. To improve the invisibility and robustness of watermarking system, the quantization step for each embedding block is set by combining statistical model with particle swarm optimization (PSO) algorithm. The experimental results show that the proposed algorithm not only preserves the high perceptual quality, but also effectively stands against joint photographic experts group (JPEG) compression, low-pass filtering, noise addition, scaling, and cropping attacks, etc. The comparison analysis demonstrates that our scheme has better performance than the previously reported watermarking algorithms.

  19. Adaptive Cooperative FEC Based on Combination of Network Coding and Channel Coding for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Yong Jin

    2014-02-01

    Full Text Available The data delivery over wireless links with QoS-guarantee is a big challenge because of the unreliable and dynamic characteristics of wireless sensor networks, as well as QoS diversity requirements of applications. In this paper, we propose an adaptive cooperative Forward Error Correction algorithm based on network coding, in the hope quality of experience could be satisfied on receivers with high quality. The algorithm, based on wireless link and distance, adjusts the RS coder parameter and selects the optimal relay nodes. On the other hand, we combine the channel coding and network coding technology at the data link layer to fulfil the requirements of QoS diversity. Both mathematical analysis and NS simulation results demonstrate the proposed mechanism is superior to the traditional FEC and cooperative FEC alone at the reliability, real time performance and energy efficiency. In addition, the proposed mechanism can significantly improve quality of media streaming, in terms of playable frame rate on the receiving side. 

  20. Adaptive ant-based routing in wireless sensor networks using Energy Delay metrics

    Institute of Scientific and Technical Information of China (English)

    Yao-feng WEN; Yu-quan CHEN; Min PAN

    2008-01-01

    To find the optimal routing is always an important topic in wireless sensor networks (WSNs). Considering a WSN where the nodes have limited energy, we propose a novel Energy*Delay model based on ant algorithms ("E&D ANTS" for short)to minimize the time delay in transferring a fixed number of data packets in an energy-constrained manner in one round. Our goal is not only to maximize the lifetime of the network but also to provide real-time data transmission services. However, because of the tradeoff of energy and delay in wireless network systems, the reinforcement learning (RL) algorithm is introduced to train the model. In this survey, the paradigm of E&D ANTS is explicated and compared to other ant-based routing algorithms like AntNet and AntChain about the issues of routing information, routing overhead and adaptation. Simulation results show that our method performs about seven times better than AntNet and also outperforms AntChain by more than 150% in terms of energy cost and delay per round.

  1. AN ADAPTIVE MEMBRANE ALGORITHM FOR SOLVING COMBINATORIAL OPTIMIZATION PROBLEMS

    Institute of Scientific and Technical Information of China (English)

    Juanjuan HE; Jianhua XIAO; Zehui SHAO

    2014-01-01

    Membrane algorithms (MAs), which inherit from P systems, constitute a new parallel and distribute framework for approximate computation. In the paper, a membrane algorithm is proposed with the improvement that the involved parameters can be adaptively chosen. In the algorithm, some membranes can evolve dynamically during the computing process to specify the values of the requested parameters. The new algorithm is tested on a well-known combinatorial optimization problem, the travelling salesman problem. The em-pirical evidence suggests that the proposed approach is efficient and reliable when dealing with 11 benchmark instances, particularly obtaining the best of the known solutions in eight instances. Compared with the genetic algorithm, simulated annealing algorithm, neural net-work and a fine-tuned non-adaptive membrane algorithm, our algorithm performs better than them. In practice, to design the airline network that minimize the total routing cost on the CAB data with twenty-five US cities, we can quickly obtain high quality solutions using our algorithm.

  2. Optimization and Validation of Rotating Current Excitation with GMR Array Sensors for Riveted Structures Inspection

    Directory of Open Access Journals (Sweden)

    Chaofeng Ye

    2016-09-01

    Full Text Available In eddy current non-destructive testing of a multi-layered riveted structure, rotating current excitation, generated by orthogonal coils, is advantageous in providing sensitivity to defects of all orientations. However, when used with linear array sensors, the exciting magnetic flux density ( B x of the orthogonal coils is not uniform over the sensor region, resulting in an output signal magnitude that depends on the relative location of the defect to the sensor array. In this paper, the rotating excitation coil is optimized to achieve a uniform B x field in the sensor array area and minimize the probe size. The current density distribution of the coil is optimized using the polynomial approximation method. A non-uniform coil design is derived from the optimized current density distribution. Simulation results, using both an optimized coil and a conventional coil, are generated using the finite element method (FEM model. The signal magnitude for an optimized coil is seen to be more robust with respect to offset of defects from the coil center. A novel multilayer coil structure, fabricated on a multi-layer printed circuit board, is used to build the optimized coil. A prototype probe with the optimized coil and 32 giant magnetoresistive (GMR sensors is built and tested on a two-layer riveted aluminum sample. Experimental results show that the optimized probe has better defect detection capability compared with a conventional non-optimized coil.

  3. CPAC: Energy-Efficient Data Collection through Adaptive Selection of Compression Algorithms for Sensor Networks

    Directory of Open Access Journals (Sweden)

    HyungJune Lee

    2014-04-01

    Full Text Available We propose a technique to optimize the energy efficiency of data collection in sensor networks by exploiting a selective data compression. To achieve such an aim, we need to make optimal decisions regarding two aspects: (1 which sensor nodes should execute compression; and (2 which compression algorithm should be used by the selected sensor nodes. We formulate this problem into binary integer programs, which provide an energy-optimal solution under the given latency constraint. Our simulation results show that the optimization algorithm significantly reduces the overall network-wide energy consumption for data collection. In the environment having a stationary sink from stationary sensor nodes, the optimized data collection shows 47% energy savings compared to the state-of-the-art collection protocol (CTP. More importantly, we demonstrate that our optimized data collection provides the best performance in an intermittent network under high interference. In such networks, we found that the selective compression for frequent packet retransmissions saves up to 55% energy compared to the best known protocol.

  4. Pliable Cognitive MAC for Heterogeneous Adaptive Cognitive Radio Sensor Networks.

    Directory of Open Access Journals (Sweden)

    Mohammed Al-Medhwahi

    Full Text Available The rapid expansion of wireless monitoring and surveillance applications in several domains reinforces the trend of exploiting emerging technologies such as the cognitive radio. However, these technologies have to adjust their working concepts to consider the common characteristics of conventional wireless sensor networks (WSNs. The cognitive radio sensor network (CRSN, still an immature technology, has to deal with new networks that might have different types of data, traffic patterns, or quality of service (QoS requirements. In this paper, we design and model a new cognitive radio-based medium access control (MAC algorithm dealing with the heterogeneous nature of the developed networks in terms of either the traffic pattern or the required QoS for the node applications. The proposed algorithm decreases the consumed power on several fronts, provides satisfactory levels of latency and spectrum utilization with efficient scheduling, and manages the radio resources for various traffic conditions. An intensive performance evaluation is conducted to study the impact of key parameters such as the channel idle time length, node density, and the number of available channels. The performance evaluation of the proposed algorithm shows a better performance than the comparable protocols. Moreover, the results manifest that the proposed algorithm is suitable for real time monitoring applications.

  5. Pliable Cognitive MAC for Heterogeneous Adaptive Cognitive Radio Sensor Networks.

    Science.gov (United States)

    Al-Medhwahi, Mohammed; Hashim, Fazirulhisyam; Ali, Borhanuddin Mohd; Sali, Aduwati

    2016-01-01

    The rapid expansion of wireless monitoring and surveillance applications in several domains reinforces the trend of exploiting emerging technologies such as the cognitive radio. However, these technologies have to adjust their working concepts to consider the common characteristics of conventional wireless sensor networks (WSNs). The cognitive radio sensor network (CRSN), still an immature technology, has to deal with new networks that might have different types of data, traffic patterns, or quality of service (QoS) requirements. In this paper, we design and model a new cognitive radio-based medium access control (MAC) algorithm dealing with the heterogeneous nature of the developed networks in terms of either the traffic pattern or the required QoS for the node applications. The proposed algorithm decreases the consumed power on several fronts, provides satisfactory levels of latency and spectrum utilization with efficient scheduling, and manages the radio resources for various traffic conditions. An intensive performance evaluation is conducted to study the impact of key parameters such as the channel idle time length, node density, and the number of available channels. The performance evaluation of the proposed algorithm shows a better performance than the comparable protocols. Moreover, the results manifest that the proposed algorithm is suitable for real time monitoring applications.

  6. An adaptive /N-body algorithm of optimal order

    Science.gov (United States)

    Pruett, C. David; Rudmin, Joseph W.; Lacy, Justin M.

    2003-05-01

    Picard iteration is normally considered a theoretical tool whose primary utility is to establish the existence and uniqueness of solutions to first-order systems of ordinary differential equations (ODEs). However, in 1996, Parker and Sochacki [Neural, Parallel, Sci. Comput. 4 (1996)] published a practical numerical method for a certain class of ODEs, based upon modified Picard iteration, that generates the Maclaurin series of the solution to arbitrarily high order. The applicable class of ODEs consists of first-order, autonomous systems whose right-hand side functions (generators) are projectively polynomial; that is, they can be written as polynomials in the unknowns. The class is wider than might be expected. The method is ideally suited to the classical N-body problem, which is projectively polynomial. Here, we recast the N-body problem in polynomial form and develop a Picard-based algorithm for its solution. The algorithm is highly accurate, parameter-free, and simultaneously adaptive in time and order. Test cases for both benign and chaotic N-body systems reveal that optimal order is dynamic. That is, in addition to dependency upon N and the desired accuracy, optimal order depends upon the configuration of the bodies at any instant.

  7. AN ADAPTIVE TRUST REGION METHOD FOR EQUALITY CONSTRAINED OPTIMIZATION

    Institute of Scientific and Technical Information of China (English)

    ZHANG Juliang; ZHANG Xiangsun; ZHUO Xinjian

    2003-01-01

    In this paper, a trust region method for equality constrained optimization based on nondifferentiable exact penalty is proposed. In this algorithm, the trail step is characterized by computation of its normal component being separated from computation of its tangential component, i.e., only the tangential component of the trail step is constrained by trust radius while the normal component and trail step itself have no constraints. The other main characteristic of the algorithm is the decision of trust region radius. Here, the decision of trust region radius uses the information of the gradient of objective function and reduced Hessian. However, Maratos effect will occur when we use the nondifferentiable exact penalty function as the merit function. In order to obtain the superlinear convergence of the algorithm, we use the twice order correction technique. Because of the speciality of the adaptive trust region method, we use twice order correction when p = 0 (the definition is as in Section 2) and this is different from the traditional trust region methods for equality constrained optimization. So the computation of the algorithm in this paper is reduced. What is more, we can prove that the algorithm is globally and superlinearly convergent.

  8. A hybrid method for optimization of the adaptive Goldstein filter

    Science.gov (United States)

    Jiang, Mi; Ding, Xiaoli; Tian, Xin; Malhotra, Rakesh; Kong, Weixue

    2014-12-01

    The Goldstein filter is a well-known filter for interferometric filtering in the frequency domain. The main parameter of this filter, alpha, is set as a power of the filtering function. Depending on it, considered areas are strongly or weakly filtered. Several variants have been developed to adaptively determine alpha using different indicators such as the coherence, and phase standard deviation. The common objective of these methods is to prevent areas with low noise from being over filtered while simultaneously allowing stronger filtering over areas with high noise. However, the estimators of these indicators are biased in the real world and the optimal model to accurately determine the functional relationship between the indicators and alpha is also not clear. As a result, the filter always under- or over-filters and is rarely correct. The study presented in this paper aims to achieve accurate alpha estimation by correcting the biased estimator using homogeneous pixel selection and bootstrapping algorithms, and by developing an optimal nonlinear model to determine alpha. In addition, an iteration is also merged into the filtering procedure to suppress the high noise over incoherent areas. The experimental results from synthetic and real data show that the new filter works well under a variety of conditions and offers better and more reliable performance when compared to existing approaches.

  9. Expected treatment dose construction and adaptive inverse planning optimization: Implementation for offline head and neck cancer adaptive radiotherapy

    Energy Technology Data Exchange (ETDEWEB)

    Yan Di; Liang Jian [Department of Radiation Oncology, Beaumont Health System, Royal Oak, Michigan 48073 (United States)

    2013-02-15

    Purpose: To construct expected treatment dose for adaptive inverse planning optimization, and evaluate it on head and neck (h and n) cancer adaptive treatment modification. Methods: Adaptive inverse planning engine was developed and integrated in our in-house adaptive treatment control system. The adaptive inverse planning engine includes an expected treatment dose constructed using the daily cone beam (CB) CT images in its objective and constrains. Feasibility of the adaptive inverse planning optimization was evaluated retrospectively using daily CBCT images obtained from the image guided IMRT treatment of 19 h and n cancer patients. Adaptive treatment modification strategies with respect to the time and the number of adaptive inverse planning optimization during the treatment course were evaluated using the cumulative treatment dose in organs of interest constructed using all daily CBCT images. Results: Expected treatment dose was constructed to include both the delivered dose, to date, and the estimated dose for the remaining treatment during the adaptive treatment course. It was used in treatment evaluation, as well as in constructing the objective and constraints for adaptive inverse planning optimization. The optimization engine is feasible to perform planning optimization based on preassigned treatment modification schedule. Compared to the conventional IMRT, the adaptive treatment for h and n cancer illustrated clear dose-volume improvement for all critical normal organs. The dose-volume reductions of right and left parotid glands, spine cord, brain stem and mandible were (17 {+-} 6)%, (14 {+-} 6)%, (11 {+-} 6)%, (12 {+-} 8)%, and (5 {+-} 3)% respectively with the single adaptive modification performed after the second treatment week; (24 {+-} 6)%, (22 {+-} 8)%, (21 {+-} 5)%, (19 {+-} 8)%, and (10 {+-} 6)% with three weekly modifications; and (28 {+-} 5)%, (25 {+-} 9)%, (26 {+-} 5)%, (24 {+-} 8)%, and (15 {+-} 9)% with five weekly modifications. Conclusions

  10. Adaptive ultrasonic sensor using a fiber ring laser with tandem fiber Bragg gratings.

    Science.gov (United States)

    Liu, Tongqing; Hu, Lingling; Han, Ming

    2014-08-01

    We propose and demonstrate an intensity-demodulated fiber-optic ultrasonic sensor system that can be self-adaptive to large quasi-static background strain perturbations. The sensor system is based on a fiber ring laser (FRL) whose laser cavity includes a pair of fiber Bragg gratings (FBGs). Self-adaptive ultrasonic detection is achieved by a tandem design where the two FBGs are engineered to have differential spectral responses to ultrasonic waves and are installed side-by-side at the same location on a structure. As a result, ultrasonic waves lead to relative spectral shifts of the FBGs and modulations to the cold-cavity loss of the FRL. Ultrasonic waves can then be detected directly from the laser intensity variations in response to the cold-cavity loss modulation. The sensor system is insensitive to quasi-static background strains because they lead to identical responses of the tandem FBGs. Based on the principle, a FRL sensor system was demonstrated and tested for adaptive ultrasonic detection when large static strains as well as dynamic sinusoidal vibrations were applied to the sensor.

  11. LinkMind: Link Optimization in Swarming Mobile Sensor Networks

    DEFF Research Database (Denmark)

    Ngo, Trung Dung

    2012-01-01

    A swarming mobile sensor network is comprised of a swarm of wirelessly connected mobile robots equipped with various sensors. Such a network can be applied in an uncertain environment for services such as cooperative navigation and exploration, object identification and information gathering. One...

  12. Optimal Adaptive Control of a Class of Stochastic Systems Using Game Theory

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    This paper attempts to study a optimal adaptive con tr ol problem using game theory, and proposes an important practical result that an adaptive processes is a set of sufficient conditions under which pure strategy is essentially complete, and thus the fact that yield a very useful desirable pu re optimal control rule.Optimal Adaptive Control of a Class of Stochastic Systems Using Game Theory

  13. Ant Colony Optimization For Improving Network Lifetime In Wireless Sensor Networks

    OpenAIRE

    Sunny Behal; Mr. Amandeep Singh

    2013-01-01

    Wireless sensor networks is very important field in today’s technology and one may concern about the life time of sensors as they have no facility to change the battery of those sensors inside the field. Wireless Sensor Networks are prone to node failure due to power loss. In order to provide reliable service through the network, the network should be self-adjusting and must have adaptable properties as required from time to time. Here in this research we have proposed a new algorithm which i...

  14. Optimal Sensor placement for acoustic range-based underwater robotic positioning

    Digital Repository Service at National Institute of Oceanography (India)

    Glotzbach, T.; Moreno-Salinas, D.; Aranda, J.; Pascoal, A.M.

    This paper addresses the problem of optimal sensor placement for acoustic range-based underwater target positioning. In particular, we focus on the experimental set-up whereby target positioning is performed by measuring...

  15. New Optimal Sensor Suite for Ultrahigh Temperature Fossil Fuel Applications

    Energy Technology Data Exchange (ETDEWEB)

    John Coggin; Jonas Ivasauskas; Russell G. May; Michael B. Miller; Rena Wilson

    2006-09-30

    Accomplishments during Phase II of a program to develop and demonstrate photonic sensor technology for the instrumentation of advanced powerplants are described. The goal of this project is the research and development of advanced, robust photonic sensors based on improved sapphire optical waveguides, and the identification and demonstration of applications of the new sensors in advanced fossil fuel power plants, where the new technology will contribute to improvements in process control and monitoring. During this program work period, major progress has been experienced in the development of the sensor hardware, and the planning of the system installation and operation. The major focus of the next work period will be the installation of sensors in the Hamilton, Ohio power plant, and demonstration of high-temperature strain gages during mechanical testing of SOFC components.

  16. 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...

  17. An Adaptive Fault-Tolerant Communication Scheme for Body Sensor Networks

    CERN Document Server

    Wu, Guowei; Xia, Feng; Xu, Zichuan; 10.3390/s101109590

    2010-01-01

    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.

  18. 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.

  19. Layout Optimization of Sensor-based Reconstruction of Explosion Overpressure Field Based on the Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Miaomiao Bai

    2014-11-01

    Full Text Available In underwater blasting experiment, the layout of the sensor has always been highly concerned. From the perspective of reconstruction with explosion overpressure field, the paper presents four indicators, which can obtain the optimal sensor layout scheme and guide sensor layout in practical experiment, combining with the genetic algorithm with global search. Then, a multi-scale model in every subregion of underwater blasting field was established to be used simulation experiments. By Matlab, the variation of these four indicators with different sensor layout, and reconstruction accuracy are analyzed and discussed. Finally, a conclusion has been raised through the analysis and comparison of simulation results, that the program can get a better sensor layout. It requires fewer number of sensors to be able to get good results with high accuracy. In the actual test explosions, we can refer to this scheme laid sensors.

  20. Smart image sensor with adaptive correction of brightness

    Science.gov (United States)

    Paindavoine, Michel; Ngoua, Auguste; Brousse, Olivier; Clerc, Cédric

    2012-03-01

    Today, intelligent image sensors require the integration in the focal plane (or near the focal plane) of complex algorithms for image processing. Such devices must meet the constraints related to the quality of acquired images, speed and performance of embedded processing, as well as low power consumption. To achieve these objectives, analog pre-processing are essential, on the one hand, to improve the quality of the images making them usable whatever the light conditions, and secondly, to detect regions of interest (ROIs) to limit the amount of pixels to be transmitted to a digital processor performing the high-level processing such as feature extraction for pattern recognition. To show that it is possible to implement analog pre-processing in the focal plane, we have designed and implemented in 130nm CMOS technology, a test circuit with groups of 4, 16 and 144 pixels, each incorporating analog average calculations.

  1. Design and Optimization of a Low Power Pressure Sensor for Wireless Biomedical Applications

    Directory of Open Access Journals (Sweden)

    J. Sosa

    2015-01-01

    (ADC are designed, optimized, and integrated in the same substrate using a commercial 1 μm CMOS technology. As result of the optimization, we obtained a digital sensor with high sensitivity, low noise (0.002 μV/Hz, and low power consumption (358 μW. Finally, the piezoresistance noise does not affect the pressure sensor application since its value is lower than half least significant bit (LSB of the ADC.

  2. Optimal multi-sensor Kalman smoothing fusion for discrete multichannel ARMA signals

    Institute of Scientific and Technical Information of China (English)

    Shuli SUN

    2005-01-01

    Based on the multi-sensor optimal information fusion criterion weighted by matrices in the linear minimum variance sense,using white noise estimators,an optimal fusion distributed Kalman smoother is given for discrete multi-channel ARMA (autoregressive moving average) signals.The smoothing error cross-covariance matrices between any two sensors are given for measurement noises.Furthermore,the fusion smoother gives higher precision than any local smoother does.

  3. 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.

  4. 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.

  5. Performance Evaluation and Optimization of Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Dr Jayant Dubey

    2013-06-01

    Full Text Available A wireless sensor network (WSN is an ad-hoc network composed of small sensor nodes deployed in large numbers to sense the physical world. Wireless sensor networks have very broad application prospects including both military and civilian usage. They include surveillance, tracking at critical facilities, or monitoring animal habitats. Sensor networks have the potential to radically change the way people observe and interact with their environment. With current wireless sensor network technology, people will gain advanced knowledge of physical and social systems, and the advent of a ubiquitous sensing era is coming. In-network processing or data aggregation is an essential function of WSNs to collect raw sensory data and get aggregated statistics about the measured environment, and help queries capture the major feature or changes of the measured systems. As more and more applications of WSNs collect sensitive measurements of people’s everyday life, privacy and security concerns draw more and more attention. If privacy of sensory content is not preserved, it is not feasible to deploy the WSNs for information collection. On the other hand, if integrity of the collected sensory information is not protected, no queries or users can trust and/or use the collected information. Hence, two important issues should be addressed before wireless sensor network systems can realize their promise in civilian applications: (1 protect data privacy, so the deployment of the wireless sensor network systems is feasible; (2 enforce integrity, so users can trust the collected or aggregated information.

  6. Design and optimization of a flexible arrayed eddy current sensor

    Science.gov (United States)

    Sun, Zhenguo; Cai, Dong; Zou, Cheng; Zhang, Wenzeng; Chen, Qiang

    2017-04-01

    The inspection of the hollow axle inner surfaces is a key process to guarantee the safety of high-speed trains. A novel flexible arrayed eddy current sensor was developed to improve the reliability of the non-destructive testing of the hollow axle inner surfaces, whose main innovative aspect was the new design of excitation/sensing traces to achieve a differential and arrayed configuration. Only two independent excitation traces were used in the sensor to induce eddy currents, which can be detected by 16 differential sensing elements. The lift-off effects and the influence of the excitation frequency and geometrical parameters of the proposed sensor was investigated and presented in this paper. Finite element models were built to analyze the effects of each parameter on the sensor response amplitude. Experimental validations were conducted using a representative set of sensors. Results from experiments and simulations were consistent with each other, which showed that the sensor design can substantially suppress the lift-off effects and modifications of the studied parameters can substantially improve the sensor performance.

  7. Enabling the dynamic coupling between sensor web and Earth system models - The Self-Adaptive Earth Predictive Systems (SEPS) framework

    Science.gov (United States)

    di, L.; Yu, G.; Chen, N.

    2007-12-01

    The self-adaptation concept is the central piece of the control theory widely and successfully used in engineering and military systems. Such a system contains a predictor and a measurer. The predictor takes initial condition and makes an initial prediction and the measurer then measures the state of a real world phenomenon. A feedback mechanism is built in that automatically feeds the measurement back to the predictor. The predictor takes the measurement against the prediction to calculate the prediction error and adjust its internal state based on the error. Thus, the predictor learns from the error and makes a more accurate prediction in the next step. By adopting the self-adaptation concept, we proposed the Self-adaptive Earth Predictive System (SEPS) concept for enabling the dynamic coupling between the sensor web and the Earth system models. The concept treats Earth System Models (ESM) and Earth Observations (EO) as integral components of the SEPS coupled by the SEPS framework. EO measures the Earth system state while ESM predicts the evolution of the state. A feedback mechanism processes EO measurements and feeds them into ESM during model runs or as initial conditions. A feed-forward mechanism analyzes the ESM predictions against science goals for scheduling optimized/targeted observations. The SEPS framework automates the Feedback and Feed-forward mechanisms (the FF-loop). Based on open consensus-based standards, a general SEPS framework can be developed for supporting the dynamic, interoperable coupling between ESMs and EO. Such a framework can support the plug-in-and-play capability of both ESMs and diverse sensors and data systems as long as they support the standard interfaces. This presentation discusses the SEPS concept, the service-oriented architecture (SOA) of SEPS framework, standards of choices for the framework, and the implementation. The presentation also presents examples of SEPS to demonstrate dynamic, interoperable, and live coupling of

  8. SA-MAC:Self-Stabilizing Adaptive MAC Protocol for Wireless Sensor Networks

    Institute of Scientific and Technical Information of China (English)

    波澄; 韩君泽; 李向阳; 王昱; 肖波

    2014-01-01

    A common method of prolonging the lifetime of wireless sensor networks is to use low power duty cycling protocol. Existing protocols consist of two categories: sender-initiated and receiver-initiated. In this paper, we present SA-MAC, a self-stabilizing adaptive MAC protocol for wireless sensor networks. SA-MAC dynamically adjusts the transmission time-slot, waking up time-slot, and packet detection pattern according to current network working condition, such as packet length and wake-up patterns of neighboring nodes. In the long run, every sensor node will find its own transmission phase so that the network will enter a stable stage when the network load and qualities are static. We conduct extensive experiments to evaluate the energy consumption, packet reception rate of SA-MAC in real sensor networking systems. Our results indicate that SA-MAC outperforms other existing protocols.

  9. 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.

  10. Performance Optimizing Multi-Objective Adaptive Control with Time-Varying Model Reference Modification

    Science.gov (United States)

    Nguyen, Nhan T.; Hashemi, Kelley E.; Yucelen, Tansel; Arabi, Ehsan

    2017-01-01

    This paper presents a new adaptive control approach that involves a performance optimization objective. The problem is cast as a multi-objective optimal control. The control synthesis involves the design of a performance optimizing controller from a subset of control inputs. The effect of the performance optimizing controller is to introduce an uncertainty into the system that can degrade tracking of the reference model. An adaptive controller from the remaining control inputs is designed to reduce the effect of the uncertainty while maintaining a notion of performance optimization in the adaptive control system.

  11. Optimal Control Problem of Feeding Adaptations of Daphnia and Neural Network Simulation

    Science.gov (United States)

    Kmet', Tibor; Kmet'ov, Mria

    2010-09-01

    A neural network based optimal control synthesis is presented for solving optimal control problems with control and state constraints and open final time. The optimal control problem is transcribed into nonlinear programming problem, which is implemented with adaptive critic neural network [9] and recurrent neural network for solving nonlinear proprojection equations [10]. The proposed simulation methods is illustrated by the optimal control problem of feeding adaptation of filter feeders of Daphnia. Results show that adaptive critic based systematic approach and neural network solving of nonlinear equations hold promise for obtaining the optimal control with control and state constraints and open final time.

  12. An optimized, universal hardware-based adaptive correlation receiver architecture

    Science.gov (United States)

    Zhu, Zaidi; Suarez, Hernan; Zhang, Yan; Wang, Shang

    2014-05-01

    The traditional radar RF transceivers, similar to communication transceivers, have the basic elements such as baseband waveform processing, IF/RF up-down conversion, transmitter power circuits, receiver front-ends, and antennas, which are shown in the upper half of Figure 1. For modern radars with diversified and sophisticated waveforms, we can frequently observe that the transceiver behaviors, especially nonlinear behaviors, are depending on the waveform amplitudes, frequency contents and instantaneous phases. Usually, it is a troublesome process to tune an RF transceiver to optimum when different waveforms are used. Another issue arises from the interference caused by the waveforms - for example, the range side-lobe (RSL) caused by the waveforms, once the signals pass through the entire transceiver chain, may be further increased due to distortions. This study is inspired by the two existing solutions from commercial communication industry, digital pre-distortion (DPD) and adaptive channel estimation and Interference Mitigation (AIM), while combining these technologies into a single chip or board that can be inserted into the existing transceiver system. This device is then named RF Transceiver Optimizer (RTO). The lower half of Figure 1 shows the basic element of RTO. With RTO, the digital baseband processing does not need to take into account the transceiver performance with diversified waveforms, such as the transmitter efficiency and chain distortion (and the intermodulation products caused by distortions). Neither does it need to concern the pulse compression (or correlation receiver) process and the related mitigation. The focus is simply the information about the ground truth carried by the main peak of correlation receiver outputs. RTO can be considered as an extension of the existing calibration process, while it has the benefits of automatic, adaptive and universal. Currently, the main techniques to implement the RTO are the digital pre- or -post

  13. A novel optimal sensitivity design scheme for yarn tension sensor using surface acoustic wave device.

    Science.gov (United States)

    Lei, Bingbing; Lu, Wenke; Zhu, Changchun; Liu, Qinghong; Zhang, Haoxin

    2014-08-01

    In this paper, we propose a novel optimal sensitivity design scheme for the yarn tension sensor using surface acoustic wave (SAW) device. In order to obtain the best sensitivity, the regression model between the size of the SAW yarn tension sensor substrate and the sensitivity of the SAW yarn tension sensor was established using the least square method. The model was validated too. Through analyzing the correspondence between the regression function monotonicity and its partial derivative sign, the effect of the SAW yarn tension sensor substrate size on the sensitivity of the SAW yarn tension sensor was investigated. Based on the regression model, a linear programming model was established to gain the optimal sensitivity of the SAW yarn tension sensor. The linear programming result shows that the maximum sensitivity will be achieved when the SAW yarn tension sensor substrate length is equal to 15 mm and its width is equal to 3mm within a fixed interval of the substrate size. An experiment of SAW yarn tension sensor about 15 mm long and 3mm wide was presented. Experimental results show that the maximum sensitivity 1982.39 Hz/g was accomplished, which confirms that the optimal sensitivity design scheme is useful and effective. Copyright © 2014. Published by Elsevier B.V.

  14. Optimization of self-directed target coverage in wireless multimedia sensor network.

    Science.gov (United States)

    Yang, Yang; Wang, Yufei; Pi, Dechang; Wang, Ruchuan

    2014-01-01

    Video and image sensors in wireless multimedia sensor networks (WMSNs) have directed view and limited sensing angle. So the methods to solve target coverage problem for traditional sensor networks, which use circle sensing model, are not suitable for WMSNs. Based on the FoV (field of view) sensing model and FoV disk model proposed, how expected multimedia sensor covers the target is defined by the deflection angle between target and the sensor's current orientation and the distance between target and the sensor. Then target coverage optimization algorithms based on expected coverage value are presented for single-sensor single-target, multisensor single-target, and single-sensor multitargets problems distinguishingly. Selecting the orientation that sensor rotated to cover every target falling in the FoV disk of that sensor for candidate orientations and using genetic algorithm to multisensor multitargets problem, which has NP-complete complexity, then result in the approximated minimum subset of sensors which covers all the targets in networks. Simulation results show the algorithm's performance and the effect of number of targets on the resulting subset.

  15. An Enhanced PSO-Based Clustering Energy Optimization Algorithm for Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    C. Vimalarani

    2016-01-01

    Full Text Available Wireless Sensor Network (WSN is a network which formed with a maximum number of sensor nodes which are positioned in an application environment to monitor the physical entities in a target area, for example, temperature monitoring environment, water level, monitoring pressure, and health care, and various military applications. Mostly sensor nodes are equipped with self-supported battery power through which they can perform adequate operations and communication among neighboring nodes. Maximizing the lifetime of the Wireless Sensor networks, energy conservation measures are essential for improving the performance of WSNs. This paper proposes an Enhanced PSO-Based Clustering Energy Optimization (EPSO-CEO algorithm for Wireless Sensor Network in which clustering and clustering head selection are done by using Particle Swarm Optimization (PSO algorithm with respect to minimizing the power consumption in WSN. The performance metrics are evaluated and results are compared with competitive clustering algorithm to validate the reduction in energy consumption.

  16. An Enhanced PSO-Based Clustering Energy Optimization Algorithm for Wireless Sensor Network.

    Science.gov (United States)

    Vimalarani, C; Subramanian, R; Sivanandam, S N

    2016-01-01

    Wireless Sensor Network (WSN) is a network which formed with a maximum number of sensor nodes which are positioned in an application environment to monitor the physical entities in a target area, for example, temperature monitoring environment, water level, monitoring pressure, and health care, and various military applications. Mostly sensor nodes are equipped with self-supported battery power through which they can perform adequate operations and communication among neighboring nodes. Maximizing the lifetime of the Wireless Sensor networks, energy conservation measures are essential for improving the performance of WSNs. This paper proposes an Enhanced PSO-Based Clustering Energy Optimization (EPSO-CEO) algorithm for Wireless Sensor Network in which clustering and clustering head selection are done by using Particle Swarm Optimization (PSO) algorithm with respect to minimizing the power consumption in WSN. The performance metrics are evaluated and results are compared with competitive clustering algorithm to validate the reduction in energy consumption.

  17. Traffic-adaptive duty cycle adaptation in TR-MAC protocol for wireless sensor networks

    NARCIS (Netherlands)

    Morshed, Sarwar; Baratchi, Mitra; Heijenk, Geert

    2016-01-01

    The Medium Access Control (MAC) layer can influence the energy consumption of a wireless sensor network (WSN) to a significant level. TR-MAC is an energy-efficient preamble sampling based MAC protocol for low power WSNs suitable for low data rate and low duty cycle scenario. However, low data rate i

  18. Advances in sensor adaptation to changes in ambient light: a bio-inspired solution - biomed 2010.

    Science.gov (United States)

    Dean, Brian; Wright, Cameron H G; Barrett, Stephen F

    2010-01-01

    Fly-inspired sensors have been shown to have many interesting qualities such as hyperacuity (or an ability to achieve movement resolution beyond the theoretical limit), extreme sensitivity to motion, and (through software simulation) image edge extraction, motion detection, and orientation and location of a line. Many of these qualities are beyond the ability of traditional computer vision sensors such as charge-coupled device (CCD) arrays. To obtain these characteristics, a prototype fly-inspired sensor has been built and tested in a laboratory environment and shows promise. Any sophisticated visual system, whether man made or natural, must adequately adapt to lighting conditions; therefore, light adaptation is a vital milestone in getting the fly eye vision sensor prototype working in real-world conditions. A design based on the common house fly, Musca domestica, was suggested in a paper presented to RMBS 2009 and showed an ability to remove 72-86% of effects due to ambient light changes. In this paper, a more advanced version of this design is discussed. This new design is able to remove 97-99% of the effects due to changes in ambient light, by more accurately approximating the light adaptation process used by the common house fly.

  19. The Homogeneity of Optimal Sensor Placement Across Multiple Winged Insect Species

    Science.gov (United States)

    Jenkins, Abigail L.

    Taking inspiration from biology, control algorithms can be implemented to imitate the naturally occurring control systems present in nature. This research is primarily concerned with insect flight and optimal wing sensor placement. Many winged insects with halteres are equipped with mechanoreceptors termed campaniform sensilla. Although the exact information these receptors provide to the insect's nervous system is unknown, it is thought to have the capability of measuring inertial rotation forces. During flight, when the wing bends, the information measured by the campaniform sensilla is received by the central nervous system, and provides the insect necessary data to control flight. This research compares three insect species - the hawkmoth Manduca sexta, the honeybee Apis mellifera, and the fruit fly Drosophila melanogaster. Using an observability-based sensor placement algorithm, the optimal sensor placement for these three species is determined. Simulations resolve if this optimal sensor placement corresponds to the insect's campaniform sensilla, as well as if placement is homogeneous across species.

  20. Dynamic Deployment of Wireless Sensor Networks by Biogeography Based Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Luo Liu

    2012-06-01

    Full Text Available As the usage and development of wireless sensor networks increases, problems related to these networks are becoming apparent. Dynamic deployment is one of the main topics that directly affects the performance of the wireless sensor networks. In this paper, biogeography-based optimization is applied to the dynamic deployment of static and mobile sensor networks to achieve better performance by trying to increase the coverage area of the network. A binary detection model is considered to obtain realistic results while computing the effectively covered area. Performance of the algorithm is compared with that of the artificial bee colony algorithm, Homo-H-VFCPSO and stud genetic algorithm that are also population-based optimization algorithms. Results show biogeography-based optimization can be preferable in the dynamic deployment of wireless sensor networks.

  1. Function-valued adaptive dynamics and optimal control theory.

    Science.gov (United States)

    Parvinen, Kalle; Heino, Mikko; Dieckmann, Ulf

    2013-09-01

    In this article we further develop the theory of adaptive dynamics of function-valued traits. Previous work has concentrated on models for which invasion fitness can be written as an integral in which the integrand for each argument value is a function of the strategy value at that argument value only. For this type of models of direct effect, singular strategies can be found using the calculus of variations, with singular strategies needing to satisfy Euler's equation with environmental feedback. In a broader, more mechanistically oriented class of models, the function-valued strategy affects a process described by differential equations, and fitness can be expressed as an integral in which the integrand for each argument value depends both on the strategy and on process variables at that argument value. In general, the calculus of variations cannot help analyzing this much broader class of models. Here we explain how to find singular strategies in this class of process-mediated models using optimal control theory. In particular, we show that singular strategies need to satisfy Pontryagin's maximum principle with environmental feedback. We demonstrate the utility of this approach by studying the evolution of strategies determining seasonal flowering schedules.

  2. Optimal adaptive normalized matched filter for large antenna arrays

    KAUST Repository

    Kammoun, Abla

    2016-09-13

    This paper focuses on the problem of detecting a target in the presence of a compound Gaussian clutter with unknown statistics. To this end, we focus on the design of the adaptive normalized matched filter (ANMF) detector which uses the regularized Tyler estimator (RTE) built from N-dimensional observations x, · · ·, x in order to estimate the clutter covariance matrix. The choice for the RTE is motivated by its possessing two major attributes: first its resilience to the presence of outliers, and second its regularization parameter that makes it more suitable to handle the scarcity in observations. In order to facilitate the design of the ANMF detector, we consider the regime in which n and N are both large. This allows us to derive closed-form expressions for the asymptotic false alarm and detection probabilities. Based on these expressions, we propose an asymptotically optimal setting for the regularization parameter of the RTE that maximizes the asymptotic detection probability while keeping the asymptotic false alarm probability below a certain threshold. Numerical results are provided in order to illustrate the gain of the proposed detector over a recently proposed setting of the regularization parameter.

  3. Adaptive surrogate model based multi-objective transfer trajectory optimization between different libration points

    Science.gov (United States)

    Peng, Haijun; Wang, Wei

    2016-10-01

    An adaptive surrogate model-based multi-objective optimization strategy that combines the benefits of invariant manifolds and low-thrust control toward developing a low-computational-cost transfer trajectory between libration orbits around the L1 and L2 libration points in the Sun-Earth system has been proposed in this paper. A new structure for a multi-objective transfer trajectory optimization model that divides the transfer trajectory into several segments and gives the dominations for invariant manifolds and low-thrust control in different segments has been established. To reduce the computational cost of multi-objective transfer trajectory optimization, a mixed sampling strategy-based adaptive surrogate model has been proposed. Numerical simulations show that the results obtained from the adaptive surrogate-based multi-objective optimization are in agreement with the results obtained using direct multi-objective optimization methods, and the computational workload of the adaptive surrogate-based multi-objective optimization is only approximately 10% of that of direct multi-objective optimization. Furthermore, the generating efficiency of the Pareto points of the adaptive surrogate-based multi-objective optimization is approximately 8 times that of the direct multi-objective optimization. Therefore, the proposed adaptive surrogate-based multi-objective optimization provides obvious advantages over direct multi-objective optimization methods.

  4. Spatiotemporal and geometric optimization of sensor arrays for detecting analytes in fluids

    Science.gov (United States)

    Lewis, Nathan S [La Canada, CA; Freund, Michael S [Winnipeg, CA; Briglin, Shawn S [Chittenango, NY; Tokumaru, Phillip [Moorpark, CA; Martin, Charles R [Gainesville, FL; Mitchell, David [Newtown, PA

    2009-09-29

    Sensor arrays and sensor array systems for detecting analytes in fluids. Sensors configured to generate a response upon introduction of a fluid containing one or more analytes can be located on one or more surfaces relative to one or more fluid channels in an array. Fluid channels can take the form of pores or holes in a substrate material. Fluid channels can be formed between one or more substrate plates. Sensor can be fabricated with substantially optimized sensor volumes to generate a response having a substantially maximized signal to noise ratio upon introduction of a fluid containing one or more target analytes. Methods of fabricating and using such sensor arrays and systems are also disclosed.

  5. Spatiotemporal and geometric optimization of sensor arrays for detecting analytes in fluids

    Energy Technology Data Exchange (ETDEWEB)

    Lewis, Nathan S. (La Canada, CA); Freund, Michael S. (Winnipeg, CA); Briglin, Shawn S. (Chittenango, NY); Tokumaru, Phillip (Moorpark, CA); Martin, Charles R. (Gainesville, FL); Mitchell, David (Newtown, PA)

    2009-09-29

    Sensor arrays and sensor array systems for detecting analytes in fluids. Sensors configured to generate a response upon introduction of a fluid containing one or more analytes can be located on one or more surfaces relative to one or more fluid channels in an array. Fluid channels can take the form of pores or holes in a substrate material. Fluid channels can be formed between one or more substrate plates. Sensor can be fabricated with substantially optimized sensor volumes to generate a response having a substantially maximized signal to noise ratio upon introduction of a fluid containing one or more target analytes. Methods of fabricating and using such sensor arrays and systems are also disclosed.

  6. Parameter Selection and Performance Comparison of Particle Swarm Optimization in Sensor Networks Localization.

    Science.gov (United States)

    Cui, Huanqing; Shu, Minglei; Song, Min; Wang, Yinglong

    2017-03-01

    Localization is a key technology in wireless sensor networks. Faced with the challenges of the sensors' memory, computational constraints, and limited energy, particle swarm optimization has been widely applied in the localization of wireless sensor networks, demonstrating better performance than other optimization methods. In particle swarm optimization-based localization algorithms, the variants and parameters should be chosen elaborately to achieve the best performance. However, there is a lack of guidance on how to choose these variants and parameters. Further, there is no comprehensive performance comparison among particle swarm optimization algorithms. The main contribution of this paper is three-fold. First, it surveys the popular particle swarm optimization variants and particle swarm optimization-based localization algorithms for wireless sensor networks. Secondly, it presents parameter selection of nine particle swarm optimization variants and six types of swarm topologies by extensive simulations. Thirdly, it comprehensively compares the performance of these algorithms. The results show that the particle swarm optimization with constriction coefficient using ring topology outperforms other variants and swarm topologies, and it performs better than the second-order cone programming algorithm.

  7. SLEACH: Secure Low- Energy Adaptive Clustering Hierarchy Protocol for Wireless Sensor Networks

    Institute of Scientific and Technical Information of China (English)

    WANG Xiao-yun; YANG Li-zhen; CHEN Ke-fei

    2005-01-01

    LEACH (Low-Energy Adaptive Clustering Hierarchy) protocol is a basic clustering-based routing protocol of sensor networks. In this paper, we present the design of SLEACH, a secure extension for the LEACH protocol. We divide SLEACH into four phases and fit inexpensive cryptographic operations to each part of the protocol functionality to create an efficient, practical protocol. Then we give security analyses of SLEACH. Our security analyses show that our scheme is robust against any external attacker or compromised nodes in the sensor network

  8. A UAV routing and sensor control optimization algorithm for target search

    Science.gov (United States)

    Collins, Gaemus E.; Riehl, James R.; Vegdahl, Philip S.

    2007-04-01

    An important problem in unmanned air vehicle (UAV) and UAV-mounted sensor control is the target search problem: locating target(s) in minimum time. Current methods solve the optimization of UAV routing control and sensor management independently. While this decoupled approach makes the target search problem computationally tractable, it is suboptimal. In this paper, we explore the target search and classification problems by formulating and solving a joint UAV routing and sensor control optimization problem. The routing problem is solved on a graph using receding horizon optimal control. The graph is dynamically adjusted based on the target probability distribution function (PDF). The objective function for the routing optimization is the solution of a sensor control optimization problem. An optimal sensor schedule (in the sense of maximizing the viewed target probability mass) is constructed for each candidate flight path in the routing control problem. The PDF of the target state is represented with a particle filter and an "occupancy map" for any undiscovered targets. The tradeoff between searching for undiscovered targets and locating tracks is handled automatically and dynamically by the use of an appropriate objective function. In particular, the objective function is based on the expected amount of target probability mass to be viewed.

  9. ROOT: Energy Efficient Routing through Optimized Tree in Sensor Networks

    CERN Document Server

    Chakraborty, Kaushik; Mitra, Swarup Kumar; Naskar, Mrinal Kanti

    2011-01-01

    Due to limitation of battery power, wireless sensor nodes are highly energy constrained. So, to enhance the network lifetime, the protocols which are used in wireless sensor network should be energy efficient. The LEACH and PEGASIS protocols which are elegant solutions to this problem try to minimize the overall energy dissipation by the nodes in the network. While the LEACH protocol randomizes cluster heads to achieve equal energy dissemination, the PEGASIS protocol forms a chain of cluster heads taking rounds in transmitting to the base station. In this paper we propose an energy efficient protocol which combines and thus enhances the performance of LEACH and PEGASIS. Here the base station is located at variable distances from each node due to the random deployment of the sensor nodes. So, each node actually dissipates a different amount of energy during its turn of transmission to the base station. This energy difference between the various nodes keeps on increasing with resulting in poorer network perform...

  10. Bi-Objective Optimal Control Modification Adaptive Control for Systems with Input Uncertainty

    Science.gov (United States)

    Nguyen, Nhan T.

    2012-01-01

    This paper presents a new model-reference adaptive control method based on a bi-objective optimal control formulation for systems with input uncertainty. A parallel predictor model is constructed to relate the predictor error to the estimation error of the control effectiveness matrix. In this work, we develop an optimal control modification adaptive control approach that seeks to minimize a bi-objective linear quadratic cost function of both the tracking error norm and predictor error norm simultaneously. The resulting adaptive laws for the parametric uncertainty and control effectiveness uncertainty are dependent on both the tracking error and predictor error, while the adaptive laws for the feedback gain and command feedforward gain are only dependent on the tracking error. The optimal control modification term provides robustness to the adaptive laws naturally from the optimal control framework. Simulations demonstrate the effectiveness of the proposed adaptive control approach.

  11. Chemical process dynamic optimization based on the differential evolution algorithm with an adaptive scheduling mutation strategy

    Science.gov (United States)

    Zhu, Jun; Yan, Xuefeng; Zhao, Weixiang

    2013-10-01

    To solve chemical process dynamic optimization problems, a differential evolution algorithm integrated with adaptive scheduling mutation strategy (ASDE) is proposed. According to the evolution feedback information, ASDE, with adaptive control parameters, adopts the round-robin scheduling algorithm to adaptively schedule different mutation strategies. By employing an adaptive mutation strategy and control parameters, the real-time optimal control parameters and mutation strategy are obtained to improve the optimization performance. The performance of ASDE is evaluated using a suite of 14 benchmark functions. The results demonstrate that ASDE performs better than four conventional differential evolution (DE) algorithm variants with different mutation strategies, and that the whole performance of ASDE is equivalent to a self-adaptive DE algorithm variant and better than five conventional DE algorithm variants. Furthermore, ASDE was applied to solve a typical dynamic optimization problem of a chemical process. The obtained results indicate that ASDE is a feasible and competitive optimizer for this kind of problem.

  12. Optimization of actuator/sensor position of multi-body system with quick startup and brake

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    A new method was put forward to optimize the position of actuator/sensor of multi-body system with quick startup and brake. Dynamical equation was established for the system with intelligent structure of piezoelectric actuators. According to the property of the modes varying with time, the performance index function was developed based on the optimal configuration principle of energy maximal dissipation, and the relevant optimal model was obtained. According to its characteristic, a float-encoding genetic algorithm, which is efficient, simple and excellent for solving the global-optimal solution of this problem, was adopted. Taking the plane manipulator as an example, the result of numerical calculation shows that, after the actuator/sensor position being optimized,the vibration amplitude of the multi-body system is reduced by 35% compared with that without optimization.

  13. An Architecture for Performance Optimization in a Collaborative Knowledge-Based Approach for  Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Juan Ramon Velasco

    2011-09-01

    Full Text Available Over the past few years, Intelligent Spaces (ISs have received the attention of many Wireless Sensor Network researchers. Recently, several studies have been devoted to identify their common capacities and to set up ISs over these networks. However, little attention has been paid to integrating Fuzzy Rule-Based Systems into collaborative Wireless Sensor Networks for the purpose of implementing ISs. This work presents a distributed architecture proposal for collaborative Fuzzy Rule-Based Systems embedded in Wireless Sensor Networks, which has been designed to optimize the implementation of ISs. This architecture includes the following: (a an optimized design for the inference engine; (b a visual interface; (c a module to reduce the redundancy and complexity of the knowledge bases; (d a module to evaluate the accuracy of the new knowledge base; (e a module to adapt the format of the rules to the structure used by the inference engine; and (f a communications protocol. As a real-world application of this architecture and the proposed methodologies, we show an application to the problem of modeling two plagues of the olive tree: prays (olive moth, Prays oleae Bern. and repilo (caused by the fungus Spilocaea oleagina. The results show that the architecture presented in this paper significantly decreases the consumption of resources (memory, CPU and battery without a substantial decrease in the accuracy of the inferred values.

  14. Robust optimal sensor placement for operational modal analysis based on maximum expected utility

    Science.gov (United States)

    Li, Binbin; Der Kiureghian, Armen

    2016-06-01

    Optimal sensor placement is essentially a decision problem under uncertainty. The maximum expected utility theory and a Bayesian linear model are used in this paper for robust sensor placement aimed at operational modal identification. To avoid nonlinear relations between modal parameters and measured responses, we choose to optimize the sensor locations relative to identifying modal responses. Since the modal responses contain all the information necessary to identify the modal parameters, the optimal sensor locations for modal response estimation provide at least a suboptimal solution for identification of modal parameters. First, a probabilistic model for sensor placement considering model uncertainty, load uncertainty and measurement error is proposed. The maximum expected utility theory is then applied with this model by considering utility functions based on three principles: quadratic loss, Shannon information, and K-L divergence. In addition, the prior covariance of modal responses under band-limited white-noise excitation is derived and the nearest Kronecker product approximation is employed to accelerate evaluation of the utility function. As demonstration and validation examples, sensor placements in a 16-degrees-of-freedom shear-type building and in Guangzhou TV Tower under ground motion and wind load are considered. Placements of individual displacement meter, velocimeter, accelerometer and placement of mixed sensors are illustrated.

  15. Bio-Mimic Optimization Strategies in Wireless Sensor Networks: A Survey

    Directory of Open Access Journals (Sweden)

    Md. Akhtaruzzaman Adnan

    2013-12-01

    Full Text Available For the past 20 years, many authors have focused their investigations on wireless sensor networks. Various issues related to wireless sensor networks such as energy minimization (optimization, compression schemes, self-organizing network algorithms, routing protocols, quality of service management, security, energy harvesting, etc., have been extensively explored. The three most important issues among these are energy efficiency, quality of service and security management. To get the best possible results in one or more of these issues in wireless sensor networks optimization is necessary. Furthermore, in number of applications (e.g., body area sensor networks, vehicular ad hoc networks these issues might conflict and require a trade-off amongst them. Due to the high energy consumption and data processing requirements, the use of classical algorithms has historically been disregarded. In this context contemporary researchers started using bio-mimetic strategy-based optimization techniques in the field of wireless sensor networks. These techniques are diverse and involve many different optimization algorithms. As far as we know, most existing works tend to focus only on optimization of one specific issue of the three mentioned above. It is high time that these individual efforts are put into perspective and a more holistic view is taken. In this paper we take a step in that direction by presenting a survey of the literature in the area of wireless sensor network optimization concentrating especially on the three most widely used bio-mimetic algorithms, namely, particle swarm optimization, ant colony optimization and genetic algorithm. In addition, to stimulate new research and development interests in this field, open research issues, challenges and future research directions are highlighted.

  16. Bio-mimic optimization strategies in wireless sensor networks: a survey.

    Science.gov (United States)

    Adnan, Md Akhtaruzzaman; Abdur Razzaque, Mohammd; Ahmed, Ishtiaque; Isnin, Ismail Fauzi

    2013-12-24

    For the past 20 years, many authors have focused their investigations on wireless sensor networks. Various issues related to wireless sensor networks such as energy minimization (optimization), compression schemes, self-organizing network algorithms, routing protocols, quality of service management, security, energy harvesting, etc., have been extensively explored. The three most important issues among these are energy efficiency, quality of service and security management. To get the best possible results in one or more of these issues in wireless sensor networks optimization is necessary. Furthermore, in number of applications (e.g., body area sensor networks, vehicular ad hoc networks) these issues might conflict and require a trade-off amongst them. Due to the high energy consumption and data processing requirements, the use of classical algorithms has historically been disregarded. In this context contemporary researchers started using bio-mimetic strategy-based optimization techniques in the field of wireless sensor networks. These techniques are diverse and involve many different optimization algorithms. As far as we know, most existing works tend to focus only on optimization of one specific issue of the three mentioned above. It is high time that these individual efforts are put into perspective and a more holistic view is taken. In this paper we take a step in that direction by presenting a survey of the literature in the area of wireless sensor network optimization concentrating especially on the three most widely used bio-mimetic algorithms, namely, particle swarm optimization, ant colony optimization and genetic algorithm. In addition, to stimulate new research and development interests in this field, open research issues, challenges and future research directions are highlighted.

  17. Optimized Quality of Service for Real-Time Wireless Sensor Networks Using a Partitioning Multipath Routing Approach

    Directory of Open Access Journals (Sweden)

    Mohammed Zaki Hasan

    2013-01-01

    Full Text Available Multimedia sensor networks for real-time applications have strict constraints on delay, packet loss, and energy consumption requirements. For example, video streaming in a disaster-management scenario requires careful handling to ensure that the end-to-end delay is within the acceptable range and the video is received properly without any distortion. The failure to transmit a video stream effectively occurs for many reasons, including sensor function limitations, excessive power consumption, and a lack of routing reliability. We propose a novel mathematical model for quality of service (QoS route determination that enables a sensor to determine the optimal path for minimising resource use while satisfying the required QoS constraints. The proposed mathematical model uses the Lagrangian relaxation mixed integer programming technique to define critical parameters and appropriate objective functions for controlling the adaptive QoS constrained route discovery process. Performance trade-offs between QoS requirements and energy efficiency were simulated using the LINGO mathematical programming language. The proposed approach significantly improves the network lifetime, while reducing energy consumption and decreasing average end-to-end delays within the sensor network via optimised resource sharing in intermediate nodes compared with existing routing algorithms.

  18. On Optimal Multi-Sensor Network Configuration for 3D Registration

    Directory of Open Access Journals (Sweden)

    Hadi Aliakbarpour

    2015-11-01

    Full Text Available Multi-sensor networks provide complementary information for various taskslike object detection, movement analysis and tracking. One of the important ingredientsfor efficient multi-sensor network actualization is the optimal configuration of sensors.In this work, we consider the problem of optimal configuration of a network of coupledcamera-inertial sensors for 3D data registration and reconstruction to determine humanmovement analysis. For this purpose, we utilize a genetic algorithm (GA based optimizationwhich involves geometric visibility constraints. Our approach obtains optimal configurationmaximizing visibility in smart sensor networks, and we provide a systematic study usingedge visibility criteria, a GA for optimal placement, and extension from 2D to 3D.Experimental results on both simulated data and real camera-inertial fused data indicate weobtain promising results. The method is scalable and can also be applied to other smartnetwork of sensors. We provide an application in distributed coupled video-inertial sensorbased 3D reconstruction for human movement analysis in real time.

  19. Using a validated transmission model for the optimization of bundled fiber optic displacement sensors.

    Science.gov (United States)

    Moro, Erik A; Todd, Michael D; Puckett, Anthony D

    2011-12-10

    A variety of intensity-modulated optical displacement sensor architectures have been proposed for use in noncontacting sensing applications, with one of the most widely implemented architectures being the bundled displacement sensor. To the best of the authors' knowledge, the arrangement of measurement fibers in previously reported bundled displacement sensors has not been configured with the use of a validated optical transmission model. Such a model has utility in accurately describing the sensor's performance a priori and thereby guides the arrangement of the fibers within the bundle to meet application-specific performance needs. In this paper, a recently validated transmission model is used for these purposes, and an optimization approach that employs a genetic algorithm efficiently explores the design space of the proposed bundle sensor architecture. From the converged output of the optimization routine, a bundled displacement sensor configuration is designed and experimentally tested, offering linear performance with a sensitivity of -0.066 μm(-1) and displacement measurement error of 223 μm over the axial displacement range of 6-8 mm. It is shown that this optimization approach may be generalized to determine optimized bundle configurations that offer high-sensitivity performance, with an acceptable error level, over a variety of axial displacement ranges. This document has been approved by Los Alamos National Laboratory for unlimited public release (LA-UR 11-03413). © 2011 Optical Society of America

  20. Field-Based Optimal Placement of Antennas for Body-Worn Wireless Sensors.

    Science.gov (United States)

    Januszkiewicz, Łukasz; Di Barba, Paolo; Hausman, Sławomir

    2016-05-17

    We investigate a case of automated energy-budget-aware optimization of the physical position of nodes (sensors) in a Wireless Body Area Network (WBAN). This problem has not been presented in the literature yet, as opposed to antenna and routing optimization, which are relatively well-addressed. In our research, which was inspired by a safety-critical application for firefighters, the sensor network consists of three nodes located on the human body. The nodes communicate over a radio link operating in the 2.4 GHz or 5.8 GHz ISM frequency band. Two sensors have a fixed location: one on the head (earlobe pulse oximetry) and one on the arm (with accelerometers, temperature and humidity sensors, and a GPS receiver), while the position of the third sensor can be adjusted within a predefined region on the wearer's chest. The path loss between each node pair strongly depends on the location of the nodes and is difficult to predict without performing a full-wave electromagnetic simulation. Our optimization scheme employs evolutionary computing. The novelty of our approach lies not only in the formulation of the problem but also in linking a fully automated optimization procedure with an electromagnetic simulator and a simplified human body model. This combination turns out to be a computationally effective solution, which, depending on the initial placement, has a potential to improve performance of our example sensor network setup by up to about 20 dB with respect to the path loss between selected nodes.

  1. On the Optimization of a Probabilistic Data Aggregation Framework for Energy Efficiency in Wireless Sensor Networks.

    Science.gov (United States)

    Kafetzoglou, Stella; Aristomenopoulos, Giorgos; Papavassiliou, Symeon

    2015-08-11

    Among the key aspects of the Internet of Things (IoT) is the integration of heterogeneous sensors in a distributed system that performs actions on the physical world based on environmental information gathered by sensors and application-related constraints and requirements. Numerous applications of Wireless Sensor Networks (WSNs) have appeared in various fields, from environmental monitoring, to tactical fields, and healthcare at home, promising to change our quality of life and facilitating the vision of sensor network enabled smart cities. Given the enormous requirements that emerge in such a setting-both in terms of data and energy-data aggregation appears as a key element in reducing the amount of traffic in wireless sensor networks and achieving energy conservation. Probabilistic frameworks have been introduced as operational efficient and performance effective solutions for data aggregation in distributed sensor networks. In this work, we introduce an overall optimization approach that improves and complements such frameworks towards identifying the optimal probability for a node to aggregate packets as well as the optimal aggregation period that a node should wait for performing aggregation, so as to minimize the overall energy consumption, while satisfying certain imposed delay constraints. Primal dual decomposition is employed to solve the corresponding optimization problem while simulation results demonstrate the operational efficiency of the proposed approach under different traffic and topology scenarios.

  2. A Coverage Dominance Approach for Sensor Deployment Optimization

    Science.gov (United States)

    2011-07-01

    Wireless Networks, 2003. [19] S. Kumar, T. H. Lai, and J. Balogh, On k-coverage in a mostly sleeping sensor network. Wireless Network, no. 14, pp. 277 – 294...Polyhedral Terrain in Polynomial Time. Image and Vision Computing, vol. 18, pp. 773 – 780, 2000. [22] S. Meguerdichian, F. Koushanfar, M. Potkonjak, and M

  3. Integrating Optimal Heterogeneous Sensor Deployment and Operation Strategies for Dynamic Origin-Destination Demand Estimation.

    Science.gov (United States)

    Zhu, Senlai; Guo, Yuntao; Chen, Jingxu; Li, Dawei; Cheng, Lin

    2017-08-02

    Most existing network sensor location problem (NSLP) models are designed to identify the number of sensors with fixed costs and installation locations, and sensors are assumed to be installed permanently. However, sometimes sensors are carried by individuals to collect traffic data measurements manually at fixed locations. Hence, their duration of operation for which traffic data measurements are collected is limited, and their costs are not fixed as they are correlated with the duration of operation. This paper proposes a NSLP model that integrates optimal heterogeneous sensor deployment and operation strategies for the dynamic O-D demand estimates under budget constraints. The deployment strategy consists of the numbers of link and node sensors and their installation locations. The operation strategy includes sensors' start time and duration of operation, which has not been addressed in previous studies. An algorithm is developed to solve the proposed model. Numerical experiments performed on a network from a part of Chennai, India show that the proposed model can identify the optimal heterogeneous sensor deployment and operation strategies with the maximum dynamic O-D demand estimation accuracy.

  4. Design optimization of high pressure and high temperature piezoresistive pressure sensor for high sensitivity

    Science.gov (United States)

    Niu, Zhe; Zhao, Yulong; Tian, Bian

    2014-01-01

    This paper describes a design method for optimizing sensitivity of piezoresistive pressure sensor in high-pressure and high-temperature environment. In order to prove the method, a piezoresistive pressure sensor (HPTSS) is designed. With the purpose of increasing sensitivity and to improve the measurement range, the piezoresistive sensor adopts rectangular membrane and thick film structure. The configuration of piezoresistors is arranged according to the characteristic of the rectangular membrane. The structure and configuration of the sensor chip are analyzed theoretically and simulated by the finite element method. This design enables the sensor chip to operate in high pressure condition (such as 150 MPa) with a high sensitivity and accuracy. The silicon on insulator wafer is selected to guarantee the thermo stability of the sensor chip. In order to optimize the fabrication and improve the yield of production, an electric conduction step is devised. Series of experiments demonstrates a favorable linearity of 0.13% and a high accuracy of 0.48%. And the sensitivity of HTPSS is about six times as high as a conventional square-membrane sensor chip in the experiment. Compared with the square-membrane pressure sensor and current production, the strength of HPTTS lies in sensitivity and measurement. The performance of the HPTSS indicates that it could be an ideal candidate for high-pressure and high-temperature sensing in real application.

  5. Design optimization of high pressure and high temperature piezoresistive pressure sensor for high sensitivity.

    Science.gov (United States)

    Niu, Zhe; Zhao, Yulong; Tian, Bian

    2014-01-01

    This paper describes a design method for optimizing sensitivity of piezoresistive pressure sensor in high-pressure and high-temperature environment. In order to prove the method, a piezoresistive pressure sensor (HPTSS) is designed. With the purpose of increasing sensitivity and to improve the measurement range, the piezoresistive sensor adopts rectangular membrane and thick film structure. The configuration of piezoresistors is arranged according to the characteristic of the rectangular membrane. The structure and configuration of the sensor chip are analyzed theoretically and simulated by the finite element method. This design enables the sensor chip to operate in high pressure condition (such as 150 MPa) with a high sensitivity and accuracy. The silicon on insulator wafer is selected to guarantee the thermo stability of the sensor chip. In order to optimize the fabrication and improve the yield of production, an electric conduction step is devised. Series of experiments demonstrates a favorable linearity of 0.13% and a high accuracy of 0.48%. And the sensitivity of HTPSS is about six times as high as a conventional square-membrane sensor chip in the experiment. Compared with the square-membrane pressure sensor and current production, the strength of HPTTS lies in sensitivity and measurement. The performance of the HPTSS indicates that it could be an ideal candidate for high-pressure and high-temperature sensing in real application.

  6. Combination Adaptive Traffic Algorithm and Coordinated Sleeping in Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    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.

  7. 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.

  8. QoS Adaptive Topology Configuration in Synchronous Wireless Sensor Networks

    Institute of Scientific and Technical Information of China (English)

    杨挺; 武娇雯; 李昂; 张志东

    2010-01-01

    By using hyper-graph theory,this paper proposes a QoS adaptive topology configuration(QATC) algorithm to effectively control large-scale topology and achieve robust data transmitting in synchronous wireless sensor networks.Firstly,a concise hyper-graph model is abstracted to analyze the large-scale and high-connectivity network.Secondly,based on the control theory of biologic "Cell Mergence",a novel self-adaptive topology configuration algorithm is used to build homologous perceptive data logic sub-network ...

  9. VLA-MAC: A Variable Load Adaptive MAC Protocol for Wireless Sensor Networks

    Science.gov (United States)

    Yao, Guoliang; Liu, Hao; Chen, Hao; Shi, Longxin

    This letter presents VLA-MAC, a novel adaptive MAC protocol for wireless sensor networks that can achieve high energy efficiency and low latency in variable load conditions. In VLA-MAC, traffic load is measured online and utilized for adaptive adjustment. VLA-MAC transmits packets via a burst style to alleviate packets accumulation problem and achieve low latency in high load condition. Furthermore, it also saves obvious energy by removing unnecessary listen period in low load condition. Unlike current approach, VLA-MAC does not need to adjust duty-cycle according to load online. Simulation results based on ns-2 show the performance improvements of our protocol.

  10. Conjugate adaptive optics in widefield microscopy with an extended-source wavefront sensor

    CERN Document Server

    Li, Jiang; Paudel, Hari; Barankov, Roman; Bifano, Thomas; Mertz, Jerome

    2015-01-01

    Adaptive optics is a strategy to compensate for sample-induced aberrations in microscopy applications. Generally, it requires the presence of "guide stars" in the sample to serve as localized reference targets. We describe an implementation of conjugate adaptive optics that is amenable to widefield (i.e. non-scanning) microscopy, and can provide aberration corrections over potentially large fields of view without the use of guide stars. A unique feature of our implementation is that it is based on wavefront sensing with a single-shot partitioned-aperture sensor that provides large dynamic range compatible with extended samples. Combined information provided by this sensor and the imaging camera enable robust image de-blurring based on a rapid estimation of sample and aberrations obtained by closed-loop feedback. We present the theoretical principle of our technique and proof of concept experimental demonstrations.

  11. 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.

  12. Forecasting routes and self-adaptation in multi-hop wireless sensor networks

    Science.gov (United States)

    Bourdenas, Themistoklis; Bergamaschi, Flavio; Wood, David; Zerfos, Petros; Sloman, Morris

    2011-06-01

    Sensor networks find application in many tactical ISR/ISTAR processes and applications. However, these processes and applications depend on reliable collection, distribution and delivery of information that, typically, travels over multiple interconnecting nodes to reach processing centres, and are susceptible to various disruptions such as the ones caused caused by message drops, packet loss and loss of connectivity due to high traffic volumes and noise on the wireless medium. In this paper, we investigate and present approaches to pro-actively adapt routing over such networks by forecasting potential faulty regions of the network based on previous trends and reorganising routing paths. We have prototyped this approach in the ITA Sensor Fabric, an evolving middleware infrastructure for sensor networks. We, further, provide some preliminary results based on simulations.

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

    Directory of Open Access Journals (Sweden)

    Chen Min

    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.

  14. Optimal Power Allocation of a Wireless Sensor Node under Different Rate Constraints

    KAUST Repository

    Solares, Jose

    2011-07-01

    Wireless sensor networks consist of the placement of sensors over a broad area in order to acquire data. Depending on the application, different design criteria should be considered in the construction of the sensors but among all of them, the battery life-cycle is of crucial interest. Power minimization is a problem that has been addressed from different approaches which include an analysis from an architectural perspective and with bit error rate and/or discrete instantaneous transmission rate constraints, among others. In this work, the optimal transmit power of a sensor node while satisfying different rate constraints is derived. First, an optimization problem with an instantaneous transmission rate constraint is addressed. Next, the optimal power is analyzed, but now with an average transmission rate constraint. The optimal solution for a class of fading channels, in terms of system parameters, is presented and a suboptimal solution is also proposed for an easier, yet efficient, implementation. Insightful asymptotical analysis for both schemes, considering a Rayleigh fading channel, are shown. Furthermore, the optimal power allocation for a sensor node in a cognitive radio environment is analyzed where an optimum solution for a class of fading channels is again derived. In all cases, numerical results are provided for either Rayleigh or Nakagami-m fading channels. The results obtained are extended to scenarios where we have either one transmitter-multiple receivers or multiple transmitters-one receiver.

  15. Adaptive grating interferometric sensor for NDE metrology in high energy electromagnetic environment

    Science.gov (United States)

    Dovgalenko, George; Altintepe, Kadir; Bodnar, Michael; Prokop, Joseph

    2016-08-01

    CCD cameras and CMOS devices are the major electronic components of industrial metrology, which are vulnerable to high level electromagnetic exposure. Typical sources of exposure of electronics to ionizing radiation are the Van Allen radiation belts for satellites, nuclear reactors in power plants for sensors and control circuits, particle accelerators for control electronics particularly particle detector devices, residual radiation from isotopes in chip packaging materials, cosmic radiation for spacecraft and highaltitude aircraft, and nuclear explosions for potentially all military and civilian electronics. A total dose 5 ×103 rad was delivered to silicon-based devices in seconds to minutes caused long-term degradation. We demonstrated adaptive grating, 3D image sensor for NDE metrology which is non vulnerable for high level X-Ray1 and 3 × 106 rad gamma radiation exposure. Sensor is based on adaptive holographic grating generated by 632.8 nm He-Ne laser - in doped electro optic Bismuth Titanate (BTO) monocrystal. Mathematical algorithm of bipolar model conductivity in BTO crystal has been applied for experimental analyses. Applications of proposed sensor for airspace, military, nuclear and civil engineering industries have been discussed.

  16. Integration and bench testing for the GRAVITY Coudé IR adaptive optics (CIAO) wavefront sensor

    Science.gov (United States)

    Deen, C.; Yang, P.; Huber, A.; Suarez-Valles, M.; Hippler, S.; Brandner, W.; Gendron, E.; Clénet, Y.; Kendrew, S.; Glauser, A.; Klein, R.; Laun, W.; Lenzen, R.; Neumann, U.; Panduro, J.; Ramos, J.; Rohloff, R.-R.; Salzinger, A.; Zimmerman, N.; Henning, T.; Perraut, K.; Perrin, G.; Straubmeier, C.; Amorim, A.; Eisenhauer, F.

    2014-08-01

    GRAVITY, a second generation instrument for the Very Large Telescope Interferometer (VLTI), will provide an astrometric precision of order 10 micro-arcseconds, an imaging resolution of 4 milli-arcseconds, and low/medium resolution spectro-interferometry. These improvements to the VLTI represent a major upgrade to its current infrared interferometric capabilities, allowing detailed study of obscured environments (e.g. the Galactic Center, young dusty planet-forming disks, dense stellar cores, AGN, etc...). Crucial to the final performance of GRAVITY, the Coudé IR Adaptive Optics (CIAO) system will correct for the effects of the atmosphere at each of the VLT Unit Telescopes. CIAO consists of four new infrared Shack-Hartmann wavefront sensors (WFS) and associated real-time computers/software which will provide infrared wavefront sensing from 1.45-2.45 microns, allowing AO corrections even in regions where optically bright reference sources are scarce. We present here the latest progress on the GRAVITY wavefront sensors. We describe the adaptation and testing of a light-weight version of the ESO Standard Platform for Adaptive optics Real Time Applications (SPARTA-Light) software architecture to the needs of GRAVITY. We also describe the latest integration and test milestones for construction of the initial wave front sensor.

  17. 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.

  18. Predictive simulations and optimization of nanowire field-effect PSA sensors including screening

    KAUST Repository

    Baumgartner, Stefan

    2013-05-03

    We apply our self-consistent PDE model for the electrical response of field-effect sensors to the 3D simulation of nanowire PSA (prostate-specific antigen) sensors. The charge concentration in the biofunctionalized boundary layer at the semiconductor-electrolyte interface is calculated using the propka algorithm, and the screening of the biomolecules by the free ions in the liquid is modeled by a sensitivity factor. This comprehensive approach yields excellent agreement with experimental current-voltage characteristics without any fitting parameters. Having verified the numerical model in this manner, we study the sensitivity of nanowire PSA sensors by changing device parameters, making it possible to optimize the devices and revealing the attributes of the optimal field-effect sensor. © 2013 IOP Publishing Ltd.

  19. Performance optimization of high-order Lamb wave sensors based on silicon carbide substrates.

    Science.gov (United States)

    Chen, Zhe; Fan, Li; Zhang, Shu-yi; Zhang, Hui

    2016-02-01

    Silicon carbide (SiC), as a new type of material for substrates in micro-electromechanical system (MEMS), was given high consideration in virtue of the properties of high acoustic velocity, low loss, chemical resistance, and etc. In this work, five performance parameters, which are electromechanical coupling coefficients, mass sensitivities, conductivity sensitivities, insert losses and minimum detectable masses, are theoretically investigated in Lamb wave chemical sensors for gas sensing based on SiC substrates. It is presented that higher performance can be achieved based on high-order modes other than fundamental modes, and the abovementioned five parameters can be simultaneously optimized. Then, according to the optimized operating conditions, operating parameters of the SiC-based high-order Lamb wave sensors are designed, which can be easily realized in MEMS technology. Finally, it is demonstrates that the SiC-based sensor exhibits better performance than that of the sensor with a conventional silicon substrate.

  20. A Parameter Communication Optimization Strategy for Distributed Machine Learning in Sensors

    Directory of Open Access Journals (Sweden)

    Jilin Zhang

    2017-09-01

    Full Text Available In order to utilize the distributed characteristic of sensors, distributed machine learning has become the mainstream approach, but the different computing capability of sensors and network delays greatly influence the accuracy and the convergence rate of the machine learning model. Our paper describes a reasonable parameter communication optimization strategy to balance the training overhead and the communication overhead. We extend the fault tolerance of iterative-convergent machine learning algorithms and propose the Dynamic Finite Fault Tolerance (DFFT. Based on the DFFT, we implement a parameter communication optimization strategy for distributed machine learning, named Dynamic Synchronous Parallel Strategy (DSP, which uses the performance monitoring model to dynamically adjust the parameter synchronization strategy between worker nodes and the Parameter Server (PS. This strategy makes full use of the computing power of each sensor, ensures the accuracy of the machine learning model, and avoids the situation that the model training is disturbed by any tasks unrelated to the sensors.

  1. Optimal Design of a Polyaniline-Coated Surface Acoustic Wave Based Humidity Sensor

    Science.gov (United States)

    Wang, Wen; Xie, Xiao; He, Shitang

    2013-01-01

    This paper presents an optimal design for a new humidity sensor composed of a dual-resonator oscillator configuration with an operation frequency of 300 MHz, and a polyaniline (PANI) coating deposited along the resonation cavity of the sensing device. To improve the corrosion resistance of the sensor chip, Al/Au electrodes were used to form the SAW resonator. Prior to device fabrication, the coupling of modes (COM) model was used for the performance prediction and optimal design parameters determination. Two SAW resonators with Al/Au electrodes were fabricated on an ST-X quartz substrate, and used as the frequency control element in the feedback path of an oscillator circuit. A PANI thin coating was deposited onto the resonator cavity of the sensing device by a spinning approach as the sensor material for relative humidity (RH) detection. High detection sensitivity, quick response, good repeatability and stability were observed from the sensor experiments at room temperature.

  2. Optimal Design of a Polyaniline-Coated Surface Acoustic Wave Based Humidity Sensor

    Directory of Open Access Journals (Sweden)

    Wen Wang

    2013-12-01

    Full Text Available This paper presents an optimal design for a new humidity sensor composed of a dual-resonator oscillator configuration with an operation frequency of 300 MHz, and a polyaniline (PANI coating deposited along the resonation cavity of the sensing device. To improve the corrosion resistance of the sensor chip, Al/Au electrodes were used to form the SAW resonator. Prior to device fabrication, the coupling of modes (COM model was used for the performance prediction and optimal design parameters determination. Two SAW resonators with Al/Au electrodes were fabricated on an ST-X quartz substrate, and used as the frequency control element in the feedback path of an oscillator circuit. A PANI thin coating was deposited onto the resonator cavity of the sensing device by a spinning approach as the sensor material for relative humidity (RH detection. High detection sensitivity, quick response, good repeatability and stability were observed from the sensor experiments at room temperature.

  3. A Parameter Communication Optimization Strategy for Distributed Machine Learning in Sensors.

    Science.gov (United States)

    Zhang, Jilin; Tu, Hangdi; Ren, Yongjian; Wan, Jian; Zhou, Li; Li, Mingwei; Wang, Jue; Yu, Lifeng; Zhao, Chang; Zhang, Lei

    2017-09-21

    In order to utilize the distributed characteristic of sensors, distributed machine learning has become the mainstream approach, but the different computing capability of sensors and network delays greatly influence the accuracy and the convergence rate of the machine learning model. Our paper describes a reasonable parameter communication optimization strategy to balance the training overhead and the communication overhead. We extend the fault tolerance of iterative-convergent machine learning algorithms and propose the Dynamic Finite Fault Tolerance (DFFT). Based on the DFFT, we implement a parameter communication optimization strategy for distributed machine learning, named Dynamic Synchronous Parallel Strategy (DSP), which uses the performance monitoring model to dynamically adjust the parameter synchronization strategy between worker nodes and the Parameter Server (PS). This strategy makes full use of the computing power of each sensor, ensures the accuracy of the machine learning model, and avoids the situation that the model training is disturbed by any tasks unrelated to the sensors.

  4. The economics of optimal adaptation to climate change

    Energy Technology Data Exchange (ETDEWEB)

    Callaway, J.M.; Ringius, L.

    2002-07-01

    This paper has set out to provide a consistent theoretical framework for understanding how consumers, producers and factor agents respond to the impacts of climate change, with a primary focus on the production and consumption of, and investment in, market goods and services under competitive conditions. However, we have also pointed out that this theory can be extended to economies where individuals and groups pursue other well-defined objectives, and we have provided some examples that show the consistency in adaptation behaviour between economic terms and those who maximise the objective of household nutrition. We have defined adaptation as the changes that economic agents make in the allocation of resources to consumption, production and investment to offset the effects of weather variability or climate change on their welfare. This definition is broad enough to encompass almost every conceivable kind of adaptation behaviour. Further, we have followed the distinction between adaptation that is autonomous and adaptation actions that are undertaken by governments in the form of adaptation strategies. Autonomous adaptation is adaptation that economic agents will undertake to change, without the assistance of government, to improve their welfare due to incentives that are built into the political economy of a country. Adaptation strategies involve conscious decisions by governments to undertake actions and implement projects to avoid (or benefit from) weather variability and climate change. We show how the extent to which economic activities are adapted to existing climate variability will affect how much autonomous adaptation will need to occur once the pure effect of climate change is taken into account. In this paper we argue that the ability of economic activities to adapt once the pure effect of climate change can be accounted for by the following factors: Presence of well-developed markets for inputs and outputs; Ability and competitiveness to produce

  5. Optimized 425MHz passive wireless magnetic field sensor

    KAUST Repository

    Li, Bodong

    2014-06-01

    A passive, magnetic field sensor consisting of a 425 MHz surface acoustic wave device loaded with a giant magnetoimpedance element is developed. The GMI element with a multilayer structure composed of Ni80Fe 20/Cu/Ni80Fe20, is fabricated on a 128° Y-X cut LiNbO3 LiNbO3 substrate. The integrated sensor is characterized with a network analyzer through an S-parameter measurement. Upon the application of a magnetic field, a maximum magnitude change and phase shift of 7.8 dB and 27 degree, respectively, are observed. Within the linear region, the magnetic sensitivity is 1.6 dB/Oe and 5 deg/Oe. © 2014 IEEE.

  6. Optimization of the magnetic properties of materials for fluxgate sensors

    Directory of Open Access Journals (Sweden)

    Luiz Carlos de Carvalho Benyosef

    2008-06-01

    Full Text Available A study was made of the variation of the magnetic properties of cobalt-based alloys using different compositions of CoFeSiB and CoFeSiBCr systems, which were produced by the melt-spinning technique and some of them subjected to a stress annealing treatment. A comparative study of core geometry and supporting material was also performed in order to obtain low noise fluxgate sensor core using amorphous magnetic ribbons of these alloys. The best alloy was a stress annealed Co67.5Fe3.5Si17.4B11.6 sample, which yielded fluxgate sensors with lower noise levels than those of commercial crystalline materials.

  7. Optimal replicator factor control in wireless sensor networks

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    For TDMA MAC protocols in wireless sensor networks (WSNs), redundancy and retransmission are two important methods to provide high end-to-end transmission reliability. Since reliable transmissions will lead to more energy consumption, there exists an intrinsic tradeoff between transmission reliability and energy efficiency. For each link, we name the number of its reserved time slots in each MAC superframe as a replicator factor. In the following paper, we propose a reliability-lifetime tradeoff framework (...

  8. Micro-calorimetric sensor for vapour phase explosive detection with optimized heat profile

    OpenAIRE

    2009-01-01

    A heater design, used in a micro-calorimetric sensor, has been optimized for temperature uniformity and the sensor has been used for detection of trace amounts of explosives. In this abstract the design, characterization and functionality is described. The performance of the novel heater design is characterized by measuring the temperature coefficient of resistivity (TCR) values and by mapping the temperature distribution using Raman spectroscopy. The new heater design has increased the tempe...

  9. Optimal Layout of Sensors on Wind Turbine Blade Based on Combinational Algorithm

    OpenAIRE

    Guimei Gu; Yu Zhao; Xin Zhang

    2016-01-01

    This work proposes a comprehensive combinational algorithm for sensor layout to solve the problem that unreasonable sensor layout affects the effectiveness of data selection and reduces the accuracy of monitoring system in healthy monitoring system of wind turbine blade structure. This algorithm integrates the advantages of kinetic energy method, effective independence method, modal assurance criterion (MAC), and many other optimal methods. In order to avoid information redundancy caused by p...

  10. Optimizing Coverage of Three-Dimensional Wireless Sensor Networks by Means of Photon Mapping

    Science.gov (United States)

    2013-12-01

    minimal number of simulated bistatic sensors such that they cover as much of the single-source-illuminated virtual environment as possible. SPOQ...presents the Sensor Placement Optimization via Queries (SPOQ) simulation algorithm. It determines where to place the minimal number of simulated bistatic ...15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT Same as Report ( SAR ) 18. NUMBER OF PAGES 12 19a. NAME OF

  11. An Umeclidinium membrane sensor; Two-step optimization strategy for improved responses.

    Science.gov (United States)

    Yehia, Ali M; Monir, Hany H

    2017-09-01

    In the scientific context of membrane sensors and improved experimentation, we devised an experimentally designed protocol for sensor optimization. Two-step strategy was implemented for Umeclidinium bromide (UMEC) analysis which is a novel quinuclidine-based muscarinic antagonist used for maintenance treatment of symptoms accompanied with chronic obstructive pulmonary disease. In the first place, membrane components were screened for ideal ion exchanger, ionophore and plasticizer using three categorical factors at three levels in Taguchi design. Secondly, experimentally designed optimization was followed in order to tune the sensor up for finest responses. Twelve experiments were randomly carried out in a continuous factor design. Nernstian response, detection limit and selectivity were assigned as responses in these designs. The optimized membrane sensor contained tetrakis-[3,5-bis(trifluoro- methyl)phenyl] borate (0.44wt%) and calix[6]arene (0.43wt%) in 50.00% PVC plasticized with 49.13wt% 2-ni-tro-phenyl octylether. This sensor, along with an optimum concentration of inner filling solution (2×10(-4)molL(-1) UMEC) and 2h of soaking time, attained the design objectives. Nernstian response approached 59.7mV/decade and detection limit decreased by about two order of magnitude (8×10(-8)mol L(-1)) through this optimization protocol. The proposed sensor was validated for UMEC determination in its linear range (3.16×10(-7) -1×10(-3)mol L(-1)) and challenged for selective discrimination of other congeners and inorganic cations. Results of INCRUSE ELLIPTA(®) inhalation powder analyses obtained from the proposed sensor and manufacturer's UPLC were statistically compared. Moreover the proposed sensor was successfully used for the determination of UMEC in plasma samples. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. Optimization of Cricket-inspired, Biomimetic Artificial Hair Sensors for Flow Sensing

    CERN Document Server

    Izadi, N; Floris, J; Krijnen, G

    2008-01-01

    High density arrays of artificial hair sensors, biomimicking the extremely sensitive mechanoreceptive filiform hairs found on cerci of crickets have been fabricated successfully. We assess the sensitivity of these artificial sensors and present a scheme for further optimization addressing the deteriorating effects of stress in the structures. We show that, by removing a portion of chromium electrodes close to the torsional beams, the upward lift at the edges of the membrane due to the stress, will decrease hence increase the sensitivity.

  13. An Adaptive Finite Element Method Based on Optimal Error Estimates for Linear Elliptic Problems

    Institute of Scientific and Technical Information of China (English)

    汤雁

    2004-01-01

    The subject of the work is to propose a series of papers about adaptive finite element methods based on optimal error control estimate. This paper is the third part in a series of papers on adaptive finite element methods based on optimal error estimates for linear elliptic problems on the concave corner domains. In the preceding two papers (part 1:Adaptive finite element method based on optimal error estimate for linear elliptic problems on concave corner domain; part 2:Adaptive finite element method based on optimal error estimate for linear elliptic problems on nonconvex polygonal domains), we presented adaptive finite element methods based on the energy norm and the maximum norm. In this paper, an important result is presented and analyzed. The algorithm for error control in the energy norm and maximum norm in part 1 and part 2 in this series of papers is based on this result.

  14. A multiobjective optimization approach to obtain decision thresholds for distributed detection in wireless sensor networks.

    Science.gov (United States)

    Masazade, Engin; Rajagopalan, Ramesh; Varshney, Pramod K; Mohan, Chilukuri K; Sendur, Gullu Kiziltas; Keskinoz, Mehmet

    2010-04-01

    For distributed detection in a wireless sensor network, sensors arrive at decisions about a specific event that are then sent to a central fusion center that makes global inference about the event. For such systems, the determination of the decision thresholds for local sensors is an essential task. In this paper, we study the distributed detection problem and evaluate the sensor thresholds by formulating and solving a multiobjective optimization problem, where the objectives are to minimize the probability of error and the total energy consumption of the network. The problem is investigated and solved for two types of fusion schemes: 1) parallel decision fusion and 2) serial decision fusion. The Pareto optimal solutions are obtained using two different multiobjective optimization techniques. The normal boundary intersection (NBI) method converts the multiobjective problem into a number of single objective-constrained subproblems, where each subproblem can be solved with appropriate optimization methods and nondominating sorting genetic algorithm-II (NSGA-II), which is a multiobjective evolutionary algorithm. In our simulations, NBI yielded better and evenly distributed Pareto optimal solutions in a shorter time as compared with NSGA-II. The simulation results show that, instead of only minimizing the probability of error, multiobjective optimization provides a number of design alternatives, which achieve significant energy savings at the cost of slightly increasing the best achievable decision error probability. The simulation results also show that the parallel fusion model achieves better error probability, but the serial fusion model is more efficient in terms of energy consumption.

  15. Sensor Placement Optimization of Vibration Test on Medium-Speed Mill

    Directory of Open Access Journals (Sweden)

    Lihua Zhu

    2015-01-01

    Full Text Available Condition assessment and decision making are important tasks of vibration test on dynamic machines, and the accuracy of dynamic response can be achieved by the sensors placed on the structure reasonably. The common methods and evaluation criteria of optimal sensor placement (OSP were summarized. In order to test the vibration characteristic of medium-speed mill in the thermal power plants, the optimal placement of 12 candidate measuring points in X, Y, and Z directions on the mill was discussed for different targeted modal shapes, respectively. The OSP of medium-speed mill was conducted using the effective independence method (EfI and QR decomposition algorithm. The results showed that the order of modal shapes had an important influence on the optimization results. The difference of these two methods on the sensor placement optimization became smaller with the decrease of the number of target modes. The final scheme of OSP was determined based on the optimal results and the actual test requirements. The field test results were basically consistent with the finite element analysis results, which indicated the sensor placement optimization for vibration test on the medium-speed mill was feasible.

  16. Optimal power allocation of a sensor node under different rate constraints

    KAUST Repository

    Ayala Solares, Jose Roberto

    2012-06-01

    The optimal transmit power of a sensor node while satisfying different rate constraints is derived. First, an optimization problem with an instantaneous transmission rate constraint is addressed. Next, the optimal power is analyzed, but now with an average transmission rate constraint. The optimal solution for a class of fading channels, in terms of system parameters, is presented and a suboptimal solution is also proposed for an easier, yet efficient, implementation. Insightful asymptotical analysis for both schemes, considering a Rayleigh fading channel, are shown. Finally, the optimal power allocation for a sensor node in a cognitive radio environment is analyzed where an optimum solution for a class of fading channels is again derived. In all cases, numerical results are provided for either Rayleigh or Nakagami-m fading channels. © 2012 IEEE.

  17. Optimal design of a spectral readout type planar waveguide-mode sensor with a monolithic structure.

    Science.gov (United States)

    Wang, Xiaomin; Fujimaki, Makoto; Kato, Takafumi; Nomura, Ken-Ichi; Awazu, Koichi; Ohki, Yoshimichi

    2011-10-10

    Optical planar waveguide-mode sensor is a promising candidate for highly sensitive biosensing techniques in fields such as protein adsorption, receptor-ligand interaction and surface bacteria adhesion. To make the waveguide-mode sensor system more realistic, a spectral readout type waveguide sensor is proposed to take advantage of its high speed, compactness and low cost. Based on our previously proposed monolithic waveguide-mode sensor composed of a SiO2 waveguide layer and a single crystalline Si layer [1], the mechanism for achieving high sensitivity is revealed by numerical simulations. The optimal achievable sensitivities for a series of waveguide structures are summarized in a contour map, and they are found to be better than those of previously reported angle-scan type waveguide sensors.

  18. Parameter Selection and Performance Comparison of Particle Swarm Optimization in Sensor Networks Localization

    Directory of Open Access Journals (Sweden)

    Huanqing Cui

    2017-03-01

    Full Text Available Localization is a key technology in wireless sensor networks. Faced with the challenges of the sensors’ memory, computational constraints, and limited energy, particle swarm optimization has been widely applied in the localization of wireless sensor networks, demonstrating better performance than other optimization methods. In particle swarm optimization-based localization algorithms, the variants and parameters should be chosen elaborately to achieve the best performance. However, there is a lack of guidance on how to choose these variants and parameters. Further, there is no comprehensive performance comparison among particle swarm optimization algorithms. The main contribution of this paper is three-fold. First, it surveys the popular particle swarm optimization variants and particle swarm optimization-based localization algorithms for wireless sensor networks. Secondly, it presents parameter selection of nine particle swarm optimization variants and six types of swarm topologies by extensive simulations. Thirdly, it comprehensively compares the performance of these algorithms. The results show that the particle swarm optimization with constriction coefficient using ring topology outperforms other variants and swarm topologies, and it performs better than the second-order cone programming algorithm.

  19. Parameter Selection and Performance Comparison of Particle Swarm Optimization in Sensor Networks Localization

    Science.gov (United States)

    Cui, Huanqing; Shu, Minglei; Song, Min; Wang, Yinglong

    2017-01-01

    Localization is a key technology in wireless sensor networks. Faced with the challenges of the sensors’ memory, computational constraints, and limited energy, particle swarm optimization has been widely applied in the localization of wireless sensor networks, demonstrating better performance than other optimization methods. In particle swarm optimization-based localization algorithms, the variants and parameters should be chosen elaborately to achieve the best performance. However, there is a lack of guidance on how to choose these variants and parameters. Further, there is no comprehensive performance comparison among particle swarm optimization algorithms. The main contribution of this paper is three-fold. First, it surveys the popular particle swarm optimization variants and particle swarm optimization-based localization algorithms for wireless sensor networks. Secondly, it presents parameter selection of nine particle swarm optimization variants and six types of swarm topologies by extensive simulations. Thirdly, it comprehensively compares the performance of these algorithms. The results show that the particle swarm optimization with constriction coefficient using ring topology outperforms other variants and swarm topologies, and it performs better than the second-order cone programming algorithm. PMID:28257060

  20. Binary particle swarm optimization algorithm assisted to design of plasmonic nanospheres sensor

    Science.gov (United States)

    Kaboli, Milad; Akhlaghi, Majid; Shahmirzaee, Hossein

    2016-04-01

    In this study, a coherent perfect absorption (CPA)-type sensor based on plasmonic nanoparticles is proposed. It consists of a plasmonic nanospheres array on top of a quartz substrate. The refractive index changes above the sensor surface, which is due to the appearance of gas or the absorption of biomolecules, can be detected by measuring the resulting spectral shifts of the absorption coefficient. Since the CPA efficiency depends strongly on the number of plasmonic nanoparticles and the locations of nanoparticles, binary particle swarm optimization (BPSO) algorithm is used to design an optimized array of the plasmonic nanospheres. This optimized structure should be maximizing the absorption coefficient only in the one frequency. BPSO algorithm, a swarm of birds including a matrix with binary entries responsible for controlling nanospheres in the array, shows the presence with symbol of ('1') and the absence with ('0'). The sensor can be used for sensing both gas and low refractive index materials in an aqueous environment.

  1. Optimal sensor placement for maximum area coverage (MAC) for damage localization in composite structures

    Science.gov (United States)

    Thiene, M.; Sharif Khodaei, Z.; Aliabadi, M. H.

    2016-09-01

    In this paper an optimal sensor placement algorithm for attaining the maximum area coverage (MAC) within a sensor network is presented. The proposed novel approach takes into account physical properties of Lamb wave propagation (attenuation profile, direction dependant group velocity due to material anisotropy) and geometrical complexities (boundary reflections, presence of openings) of the structure. A feature of the proposed optimization approach lies in the fact that it is independent of characteristics of the damage detection algorithm (e.g. probability of detection) making it readily up-scalable to large complex composite structures such as aircraft stiffened composite panel. The proposed fitness function (MAC) is independent of damage parameters (type, severity, location). Statistical analysis carried out shows that the proposed optimum sensor network with MAC results in high probability of damage localization. Genetic algorithm is coupled with the fitness function to provide an efficient optimization strategy.

  2. Optimal Power Control in Wireless Powered Sensor Networks: A Dynamic Game-Based Approach

    Science.gov (United States)

    Xu, Haitao; Guo, Chao; Zhang, Long

    2017-01-01

    In wireless powered sensor networks (WPSN), it is essential to research uplink transmit power control in order to achieve throughput performance balancing and energy scheduling. Each sensor should have an optimal transmit power level for revenue maximization. In this paper, we discuss a dynamic game-based algorithm for optimal power control in WPSN. The main idea is to use the non-cooperative differential game to control the uplink transmit power of wireless sensors in WPSN, to extend their working hours and to meet QoS (Quality of Services) requirements. Subsequently, the Nash equilibrium solutions are obtained through Bellman dynamic programming. At the same time, an uplink power control algorithm is proposed in a distributed manner. Through numerical simulations, we demonstrate that our algorithm can obtain optimal power control and reach convergence for an infinite horizon. PMID:28282945

  3. Adaptive hybrid optimization strategy for calibration and parameter estimation of physical models

    CERN Document Server

    Vesselinov, Velimir V

    2011-01-01

    A new adaptive hybrid optimization strategy, entitled squads, is proposed for complex inverse analysis of computationally intensive physical models. The new strategy is designed to be computationally efficient and robust in identification of the global optimum (e.g. maximum or minimum value of an objective function). It integrates a global Adaptive Particle Swarm Optimization (APSO) strategy with a local Levenberg-Marquardt (LM) optimization strategy using adaptive rules based on runtime performance. The global strategy optimizes the location of a set of solutions (particles) in the parameter space. The LM strategy is applied only to a subset of the particles at different stages of the optimization based on the adaptive rules. After the LM adjustment of the subset of particle positions, the updated particles are returned to the APSO strategy. The advantages of coupling APSO and LM in the manner implemented in squads is demonstrated by comparisons of squads performance against Levenberg-Marquardt (LM), Particl...

  4. Optimal Geometry of CMOS Voltage-Mode and Current-Mode Vertical Magnetic Hall Sensors

    OpenAIRE

    2015-01-01

    Four different geometries of a vertical Hall sensor\\ud are presented and studied in this paper. The current spinning\\ud technique compensates for the offset and the sensors, driven in\\ud current-mode, provide a differential signal current for a possible\\ud capacitive integration over a defined time-slot. The sensors have\\ud been fabricated using a 6-metal 0.18-μm CMOS technology and\\ud fully experimentally tested. The optimal solution will be further\\ud investigated for bendable electronics. ...

  5. Optimizing floating guard ring designs for FASPAX N-in-P silicon sensors

    CERN Document Server

    Shin, Kyung-Wook; Lipton, Ronald; Deptuch, Gregory; Fahim, Farah; Madden, Tim; Zimmerman, Tom

    2016-01-01

    FASPAX (Fermi-Argonne Semiconducting Pixel Array X-ray detector) is being developed as a fast integrating area detector with wide dynamic range for time resolved applications at the upgraded Advanced Photon Source (APS.) A burst mode detector with intended $\\mbox{13 $MHz$}$ image rate, FASPAX will also incorporate a novel integration circuit to achieve wide dynamic range, from single photon sensitivity to $10^{\\text{5}}$ x-rays/pixel/pulse. To achieve these ambitious goals, a novel silicon sensor design is required. This paper will detail early design of the FASPAX sensor. Results from TCAD optimization studies, and characterization of prototype sensors will be presented.

  6. Topology optimization of pressure adaptive honeycomb for a morphing flap

    NARCIS (Netherlands)

    Vos, R.; Scheepstra, J.; Barrett, R.

    2011-01-01

    The paper begins with a brief historical overview of pressure adaptive materials and structures. By examining avian anatomy, it is seen that pressure-adaptive structures have been used successfully in the Natural world to hold structural positions for extended periods of time and yet allow for dynam

  7. Topology optimization of pressure adaptive honeycomb for a morphing flap

    NARCIS (Netherlands)

    Vos, R.; Scheepstra, J.; Barrett, R.

    2011-01-01

    The paper begins with a brief historical overview of pressure adaptive materials and structures. By examining avian anatomy, it is seen that pressure-adaptive structures have been used successfully in the Natural world to hold structural positions for extended periods of time and yet allow for dynam

  8. Finding Robust Assailant Using Optimization Functions (FiRAO-PG in Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    Piyush Kumar Shukla

    2015-01-01

    Full Text Available Wireless sensor network consists of hundreds or thousands of low cost, low power, and self-organizing tiny sensor nodes that are deployed within the sensor network. Sensor network is susceptible to physical attacks due to deprived power and restricted resource capability and is exposed to external environment for transmitting and receiving data. Node capture attack is one of the most menacing attack in the wireless sensor network and may be physically captured by an adversary for extracting confidential information regarding cryptographic keys, node’s unique id, and so forth, from its memory to eliminate the confidentiality and integrity of the wireless links. Node capture attack suffers from severe security breach and tremendous network cost. We propose an empirically designed multiple objectives node capture attack algorithm based on optimization functions as an effective solution against the attacking efficiency of node capture attack. Finding robust assailant optimization-particle swarm optimization and genetic algorithm (FiRAO-PG consists of multiple objectives: maximum node participation, maximum key participation, and minimum resource expenditure to find optimal nodes using PSO and GA. It will leverage a comprehensive tool to destroy maximum portion of the network realizing cost-effectiveness and higher attacking efficiency. The simulation results manifest that FiRAO-PG can provide higher fraction of compromised traffic than matrix algorithm (MA so the attacking efficiency of FiRAO-PG is higher.

  9. A Survey on Optimal Signal Processing Techniques Applied to Improve the Performance of Mechanical Sensors in Automotive Applications

    Science.gov (United States)

    Hernandez, Wilmar

    2007-01-01

    In this paper a survey on recent applications of optimal signal processing techniques to improve the performance of mechanical sensors is made. Here, a comparison between classical filters and optimal filters for automotive sensors is made, and the current state of the art of the application of robust and optimal control and signal processing techniques to the design of the intelligent (or smart) sensors that today's cars need is presented through several experimental results that show that the fusion of intelligent sensors and optimal signal processing techniques is the clear way to go. However, the switch between the traditional methods of designing automotive sensors and the new ones cannot be done overnight because there are some open research issues that have to be solved. This paper draws attention to one of the open research issues and tries to arouse researcher's interest in the fusion of intelligent sensors and optimal signal processing techniques.

  10. Optimal contrast function in the unbalanced fiber optic Michelson interferometer for dislocation sensor

    Science.gov (United States)

    Szustakowski, Mieczyslaw; Palka, Norbert; Ciurapinski, Wieslaw M.

    2004-09-01

    Theoretical description of a contrast in an unbalanced fiber optic Michelson's interferometer with a multimode laser was shown. Periodic contrast oscillations, which depend on a laser spectrum, occur if a measuring arm of the interferometer is elongated. Required characteristic features of the contrast for an elongation sensor were determined. Influences of laser spectrum parameters (wavelength, halfwidth and mode spacing) as well as laser mode amplitudes on the contrast were simulated. Optimal spectrum for the dislocation sensor was determined theoretically. A laser which parameters fulfilled the requirements was found and its spectrum was measured. The measured contrast function was very similar to the optimal theoretical plot what proves correctness of the calculations.

  11. Optimization of Graphene Sensors to Detect Biological Warfare Agents

    Science.gov (United States)

    2014-03-27

    low-cost sensors. 1.2 Research Topic Manoor showed it is possible to detect Gram-positive and Gram-negative bacteria via antimicrobial peptides ...This unit was placed into copper etchant to dissolve the copper and leave a PMMA/graphene layer for transfer to a 500nm SiO2 layer on a circuit...electron transport properties, ssDNA binding properties, and simple production. The CVD copper growth method was used to grow the graphene for transfer

  12. A Particle Swarm Optimization with Adaptive Multi-Swarm Strategy for Capacitated Vehicle Routing Problem

    Directory of Open Access Journals (Sweden)

    Kui-Ting CHEN

    2015-12-01

    Full Text Available Capacitated vehicle routing problem with pickups and deliveries (CVRPPD is one of the most challenging combinatorial optimization problems which include goods delivery/pickup optimization, vehicle number optimization, routing path optimization and transportation cost minimization. The conventional particle swarm optimization (PSO is difficult to find an optimal solution of the CVRPPD due to its simple search strategy. A PSO with adaptive multi-swarm strategy (AMSPSO is proposed to solve the CVRPPD in this paper. The proposed AMSPSO employs multiple PSO algorithms and an adaptive algorithm with punishment mechanism to search the optimal solution, which can deal with large-scale optimization problems. The simulation results prove that the proposed AMSPSO can solve the CVRPPD with the least number of vehicles and less transportation cost, simultaneously.

  13. Optimal sensor configuration for flexible structures with multi-dimensional mode shapes

    Science.gov (United States)

    Chang, Minwoo; Pakzad, Shamim N.

    2015-05-01

    A framework for deciding the optimal sensor configuration is implemented for civil structures with multi-dimensional mode shapes, which enhances the applicability of structural health monitoring for existing structures. Optimal sensor placement (OSP) algorithms are used to determine the best sensor configuration for structures with a priori knowledge of modal information. The signal strength at each node is evaluated by effective independence and modified variance methods. Euclidean norm of signal strength indices associated with each node is used to expand OSP applicability into flexible structures. The number of sensors for each method is determined using the threshold for modal assurance criterion (MAC) between estimated (from a set of observations) and target mode shapes. Kriging is utilized to infer the modal estimates for unobserved locations with a weighted sum of known neighbors. A Kriging model can be expressed as a sum of linear regression and random error which is assumed as the realization of a stochastic process. This study presents the effects of Kriging parameters for the accurate estimation of mode shapes and the minimum number of sensors. The feasible ranges to satisfy MAC criteria are investigated and used to suggest the adequate searching bounds for associated parameters. The finite element model of a tall building is used to demonstrate the application of optimal sensor configuration. The dynamic modes of flexible structure at centroid are appropriately interpreted into the outermost sensor locations when OSP methods are implemented. Kriging is successfully used to interpolate the mode shapes from a set of sensors and to monitor structures associated with multi-dimensional mode shapes.

  14. Development of Ammonia Gas Sensor Using Optimized Organometallic Reagent

    Directory of Open Access Journals (Sweden)

    J. Aubrecht

    2016-01-01

    Full Text Available Reliable, continuous, and spatially distributed monitoring of dangerous or irritating chemical substances belongs to standard functions of contemporary industrial and public security systems. Fiber-optic-based detection provides feasible platform to fulfill such aims. This paper deals with characterization of ammonia sensing elements based on multimode polysiloxane-clad silica-core optical fibers sensitized with 5-(4′-dioctylamino phenylimino quinoline-8-1 cobalt bromide complex reagent immobilized into the cross-linked polymer matrix from a proper mixture of organic solvents and a radical scavenger contributing to the desired long-term stability of optical properties. The applied sensing mechanism combines optical detection principle with chemical reaction of the reagent and ammonia resulting in changes in the visible near-infrared optical absorption spectrum of the cladding layer, influencing via evanescent optical field interactions the spectral distribution of the guided light intensity. Reaction kinetics of short fiber sections exposed to ammonia/nitrogen mixture of various ammonia concentrations is tested and evaluated. The obtained sensitivity, limit of detection, and forward response time of the prepared sensors amount to 1.52⁎10-5 ppm−1, 31 ppm, and 25 s, respectively. The obtained results are promising for fabrication of distributed fiber-optic sensors applicable to detection and location of ammonia gas leaks in industrial as well as general public premises.

  15. Collaborative Object Framework for Adaptive System Optimization Project

    Data.gov (United States)

    National Aeronautics and Space Administration — The proposed innovation is to combine traditional and cutting edge optimization techniques into an existing powerful object based organic enterprise decision network...

  16. Adaptive differential evolution a robust approach to multimodal problem optimization

    CERN Document Server

    Zhang, Jingqiao; Zhang, Jingqiao

    2009-01-01

    The fundamental theme of this book is theoretical study of differential evolution and algorithmic analysis of parameter adaptive schemes. The book offers real-world insights into a variety of large-scale complex industrial applications.

  17. Mesh Adaptation and Shape Optimization on Unstructured Meshes Project

    Data.gov (United States)

    National Aeronautics and Space Administration — In this SBIR CRM proposes to implement the entropy adjoint method for solution adaptive mesh refinement into the Loci/CHEM unstructured flow solver. The scheme will...

  18. Optimal Rate Based Image Transmission Scheme in Multi-rate Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Mr. Jayachandran.A ,

    2011-06-01

    Full Text Available In image transmission application over WSN energy efficiency and image quality are both important factor for joint optimization. The large size image transmission cause bottleneck in WSN due to the limited energy resources and network capacity. Since some sensor are in similar viewing directions the images they are capture likely exhibit certain level of correlation among themselves. This optimization scheme allows each image sensor to transmit optimal functions of the overlapped images through appropriate multiple rate oriented routing paths. Moreover, we use unused segment loss protection with erasure codes of different strength to maximize the expected quality at the destination and propose a fast algorithm that find nearly optimal transmission strategies simulation results show that proposed the scheme achieves high energy efficiency in WSN enhancing the image transmission quality.

  19. Model Based Optimal Sensor Network Design for Condition Monitoring in an IGCC Plant

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, Rajeeva; Kumar, Aditya; Dai, Dan; Seenumani, Gayathri; Down, John; Lopez, Rodrigo

    2012-12-31

    This report summarizes the achievements and final results of this program. The objective of this program is to develop a general model-based sensor network design methodology and tools to address key issues in the design of an optimal sensor network configuration: the type, location and number of sensors used in a network, for online condition monitoring. In particular, the focus in this work is to develop software tools for optimal sensor placement (OSP) and use these tools to design optimal sensor network configuration for online condition monitoring of gasifier refractory wear and radiant syngas cooler (RSC) fouling. The methodology developed will be applicable to sensing system design for online condition monitoring for broad range of applications. The overall approach consists of (i) defining condition monitoring requirement in terms of OSP and mapping these requirements in mathematical terms for OSP algorithm, (ii) analyzing trade-off of alternate OSP algorithms, down selecting the most relevant ones and developing them for IGCC applications (iii) enhancing the gasifier and RSC models as required by OSP algorithms, (iv) applying the developed OSP algorithm to design the optimal sensor network required for the condition monitoring of an IGCC gasifier refractory and RSC fouling. Two key requirements for OSP for condition monitoring are desired precision for the monitoring variables (e.g. refractory wear) and reliability of the proposed sensor network in the presence of expected sensor failures. The OSP problem is naturally posed within a Kalman filtering approach as an integer programming problem where the key requirements of precision and reliability are imposed as constraints. The optimization is performed over the overall network cost. Based on extensive literature survey two formulations were identified as being relevant to OSP for condition monitoring; one based on LMI formulation and the other being standard INLP formulation. Various algorithms to solve

  20. A new model based on adaptation of the external loop to compensate the hysteresis of tactile sensors.

    Science.gov (United States)

    Sánchez-Durán, José A; Vidal-Verdú, Fernando; Oballe-Peinado, Óscar; Castellanos-Ramos, Julián; Hidalgo-López, José A

    2015-10-15

    This paper presents a novel method to compensate for hysteresis nonlinearities observed in the response of a tactile sensor. The External Loop Adaptation Method (ELAM) performs a piecewise linear mapping of the experimentally measured external curves of the hysteresis loop to obtain all possible internal cycles. The optimal division of the input interval where the curve is approximated is provided by the error minimization algorithm. This process is carried out off line and provides parameters to compute the split point in real time. A different linear transformation is then performed at the left and right of this point and a more precise fitting is achieved. The models obtained with the ELAM method are compared with those obtained from three other approaches. The results show that the ELAM method achieves a more accurate fitting. Moreover, the involved mathematical operations are simpler and therefore easier to implement in devices such as Field Programmable Gate Array (FPGAs) for real time applications. Furthermore, the method needs to identify fewer parameters and requires no previous selection process of operators or functions. Finally, the method can be applied to other sensors or actuators with complex hysteresis loop shapes.

  1. An Energy-efficient Rate Adaptive Media Access Protocol (RA-MAC for Long-lived Sensor Networks

    Directory of Open Access Journals (Sweden)

    Wen Hu

    2010-06-01

    Full Text Available We introduce an energy-efficient Rate Adaptive Media Access Control (RA-MAC algorithm for long-lived Wireless Sensor Networks (WSNs. Previous research shows that the dynamic and lossy nature of wireless communications is one of the major challenges to reliable data delivery in WSNs. RA-MAC achieves high link reliability in such situations by dynamically trading off data rate for channel gain. The extra gain that can be achieved reduces the packet loss rate which contributes to reduced energy expenditure through a reduced numbers of retransmissions. We achieve this at the expense of raw bit rate which generally far exceeds the application’s link requirement. To minimize communication energy consumption, RA-MAC selects the optimal data rate based on the estimated link quality at each data rate and an analytical model of the energy consumption. Our model shows how the selected data rate depends on different channel conditions in order to minimize energy consumption. We have implemented RA-MAC in TinyOS for an off-the-shelf sensor platform (the TinyNode on top of a state-of-the-art WSN Media Access Control Protocol, SCP-MAC, and evaluated its performance by comparing our implementation with the original SCP-MAC using both simulation and experiment.

  2. A New Model Based on Adaptation of the External Loop to Compensate the Hysteresis of Tactile Sensors

    Directory of Open Access Journals (Sweden)

    José A. Sánchez-Durán

    2015-10-01

    Full Text Available This paper presents a novel method to compensate for hysteresis nonlinearities observed in the response of a tactile sensor. The External Loop Adaptation Method (ELAM performs a piecewise linear mapping of the experimentally measured external curves of the hysteresis loop to obtain all possible internal cycles. The optimal division of the input interval where the curve is approximated is provided by the error minimization algorithm. This process is carried out off line and provides parameters to compute the split point in real time. A different linear transformation is then performed at the left and right of this point and a more precise fitting is achieved. The models obtained with the ELAM method are compared with those obtained from three other approaches. The results show that the ELAM method achieves a more accurate fitting. Moreover, the involved mathematical operations are simpler and therefore easier to implement in devices such as Field Programmable Gate Array (FPGAs for real time applications. Furthermore, the method needs to identify fewer parameters and requires no previous selection process of operators or functions. Finally, the method can be applied to other sensors or actuators with complex hysteresis loop shapes.

  3. Real time implementation of adaptive sliding mode observer based speed sensor less vector control of induction motor

    Directory of Open Access Journals (Sweden)

    Negadi Karim

    2010-01-01

    Full Text Available Sensor less induction motor drives are widely used in industry for their reliability and flexibility. However, rotor flux and speed sensors are required for vector control of induction motor. These sensors are sources of trouble, mainly in hostile environments, and their application reduces the drive robustness. The cost of the sensors is not also negligible. All the reasons lead to development of different sensor less methods for rotor flux and mechanical speed estimation in electrical drives. The paper deals with the speed estimators for applications in sensor less induction motor drive with vector control, which are based on application of model adaptive, based sliding mode observer methods. This paper presents the development and DSP implementation of the speed estimators for applications in sensor less drives with induction motor.

  4. Topology Optimization of Nano-Mechanical Cantilever Sensors Using a C0 Discontinuous Galerkin-Type Approach

    DEFF Research Database (Denmark)

    Marhadi, Kun Saptohartyadi; Evgrafov, Anton; Sørensen, Mads Peter

    2011-01-01

    We demonstrate the use of a C0 discontinuous Galerkin method for topology optimization of nano-mechanical sensors, namely temperature, surface stress, and mass sensors. The sensors are modeled using classical thin plate theory, which requires C1 basis functions in the standard finite element method...

  5. Nonlinear optimal filter technique for analyzing energy depositions in TES sensors driven into saturation

    Directory of Open Access Journals (Sweden)

    B. Shank

    2014-11-01

    Full Text Available We present a detailed thermal and electrical model of superconducting transition edge sensors (TESs connected to quasiparticle (qp traps, such as the W TESs connected to Al qp traps used for CDMS (Cryogenic Dark Matter Search Ge and Si detectors. We show that this improved model, together with a straightforward time-domain optimal filter, can be used to analyze pulses well into the nonlinear saturation region and reconstruct absorbed energies with optimal energy resolution.

  6. Nonlinear Optimal Filter Technique For Analyzing Energy Depositions In TES Sensors Driven Into Saturation

    CERN Document Server

    Shank, B; Cabrera, B; Kreikebaum, J M; Moffatt, R; Redl, P; Young, B A; Brink, P L; Cherry, M; Tomada, A

    2014-01-01

    We present a detailed thermal and electrical model of superconducting transition edge sensors (TESs) connected to quasiparticle (qp) traps, such as the W TESs connected to Al qp traps used for CDMS (Cryogenic Dark Matter Search) Ge and Si detectors. We show that this improved model, together with a straightforward time-domain optimal filter, can be used to analyze pulses well into the nonlinear saturation region and reconstruct absorbed energies with optimal energy resolution.

  7. Almost-Optimal Sensor Tasking using Auction Methods

    Science.gov (United States)

    Hujsak, R.

    2010-09-01

    The problem for efficient use of radar assets for space surveillance is unsolved. Partial solutions have been developed, such as covariance based tasking algorithms, but not all operational requirements for tracking support are quantified by accuracy, for example monitoring a non-cooperative maneuvering satellite for purposes of conjunction assessment. The following effort exposes a different approach, where competing requirements, each with quite different metrics, can compete for sensor resources and an efficient decision making process will provide for economic use of radar resources and thereby allowing greater use of the radar sites for other missions. The Auction we employ here is somewhat naïve, as compared to sophisticated methods employed by domain experts, and yet provides evidence that the method can be quite useful for making assignments where competing requirements can stress the tracking systems.

  8. Deployment-based lifetime optimization model for homogeneous Wireless Sensor Network under retransmission.

    Science.gov (United States)

    Li, Ruiying; Liu, Xiaoxi; Xie, Wei; Huang, Ning

    2014-12-10

    Sensor-deployment-based lifetime optimization is one of the most effective methods used to prolong the lifetime of Wireless Sensor Network (WSN) by reducing the distance-sensitive energy consumption. In this paper, data retransmission, a major consumption factor that is usually neglected in the previous work, is considered. For a homogeneous WSN, monitoring a circular target area with a centered base station, a sensor deployment model based on regular hexagonal grids is analyzed. To maximize the WSN lifetime, optimization models for both uniform and non-uniform deployment schemes are proposed by constraining on coverage, connectivity and success transmission rate. Based on the data transmission analysis in a data gathering cycle, the WSN lifetime in the model can be obtained through quantifying the energy consumption at each sensor location. The results of case studies show that it is meaningful to consider data retransmission in the lifetime optimization. In particular, our investigations indicate that, with the same lifetime requirement, the number of sensors needed in a non-uniform topology is much less than that in a uniform one. Finally, compared with a random scheme, simulation results further verify the advantage of our deployment model.

  9. Statistical-QoS Guaranteed Energy Efficiency Optimization for Energy Harvesting Wireless Sensor Networks.

    Science.gov (United States)

    Gao, Ya; Cheng, Wenchi; Zhang, Hailin

    2017-08-23

    Energy harvesting, which offers a never-ending energy supply, has emerged as a prominent technology to prolong the lifetime and reduce costs for the battery-powered wireless sensor networks. However, how to improve the energy efficiency while guaranteeing the quality of service (QoS) for energy harvesting based wireless sensor networks is still an open problem. In this paper, we develop statistical delay-bounded QoS-driven power control policies to maximize the effective energy efficiency (EEE), which is defined as the spectrum efficiency under given specified QoS constraints per unit harvested energy, for energy harvesting based wireless sensor networks. For the battery-infinite wireless sensor networks, our developed QoS-driven power control policy converges to the Energy harvesting Water Filling (E-WF) scheme and the Energy harvesting Channel Inversion (E-CI) scheme under the very loose and stringent QoS constraints, respectively. For the battery-finite wireless sensor networks, our developed QoS-driven power control policy becomes the Truncated energy harvesting Water Filling (T-WF) scheme and the Truncated energy harvesting Channel Inversion (T-CI) scheme under the very loose and stringent QoS constraints, respectively. Furthermore, we evaluate the outage probabilities to theoretically analyze the performance of our developed QoS-driven power control policies. The obtained numerical results validate our analysis and show that our developed optimal power control policies can optimize the EEE over energy harvesting based wireless sensor networks.

  10. Optimized Node Deployment Algorithm and Parameter Investigation in a Mobile Sensor Network for Robotic Systems

    Directory of Open Access Journals (Sweden)

    Rongxin Tang

    2015-10-01

    Full Text Available Mobile sensor networks are an important part of modern robotics systems and are widely used in robotics applications. Therefore, sensor deployment is a key issue in current robotics systems research. Since it is one of the most popular deployment methods, in recent years the virtual force algorithm has been studied in detail by many scientists. In this paper, we focus on the virtual force algorithm and present a corresponding parameter investigation for mobile sensor deployment. We introduce an optimized virtual force algorithm based on the exchange force, in which a new shielding rule grounded in Delaunay triangulation is adopted. The algorithm employs a new performance metric called ’pair-correlation diversion’, designed to evaluate the uniformity and topology of the sensor distribution. We also discuss the implementation of the algorithm’s computation and analyse the influence of experimental parameters on the algorithm. Our results indicate that the area ratio, φs, and the exchange force constant, G, influence the final performance of the sensor deployment in terms of the coverage rate, the convergence time and topology uniformity. Using simulations, we were able to verify the effectiveness of our algorithm and we obtained an optimal region for the (φs, G-parameter space which, in the future, could be utilized as an aid for experiments in robotic sensor deployment.

  11. Geometry Optimization Approaches of Inductively Coupled Printed Spiral Coils for Remote Powering of Implantable Biomedical Sensors

    Directory of Open Access Journals (Sweden)

    Sondos Mehri

    2016-01-01

    Full Text Available Electronic biomedical implantable sensors need power to perform. Among the main reported approaches, inductive link is the most commonly used method for remote powering of such devices. Power efficiency is the most important characteristic to be considered when designing inductive links to transfer energy to implantable biomedical sensors. The maximum power efficiency is obtained for maximum coupling and quality factors of the coils and is generally limited as the coupling between the inductors is usually very small. This paper is dealing with geometry optimization of inductively coupled printed spiral coils for powering a given implantable sensor system. For this aim, Iterative Procedure (IP and Genetic Algorithm (GA analytic based optimization approaches are proposed. Both of these approaches implement simple mathematical models that approximate the coil parameters and the link efficiency values. Using numerical simulations based on Finite Element Method (FEM and with experimental validation, the proposed analytic approaches are shown to have improved accurate performance results in comparison with the obtained performance of a reference design case. The analytical GA and IP optimization methods are also compared to a purely Finite Element Method based on numerical optimization approach (GA-FEM. Numerical and experimental validations confirmed the accuracy and the effectiveness of the analytical optimization approaches to design the optimal coil geometries for the best values of efficiency.

  12. Policy Gradient Adaptive Dynamic Programming for Data-Based Optimal Control.

    Science.gov (United States)

    Luo, Biao; Liu, Derong; Wu, Huai-Ning; Wang, Ding; Lewis, Frank L

    2016-11-22

    The model-free optimal control problem of general discrete-time nonlinear systems is considered in this paper, and a data-based policy gradient adaptive dynamic programming (PGADP) algorithm is developed to design an adaptive optimal controller method. By using offline and online data rather than the mathematical system model, the PGADP algorithm improves control policy with a gradient descent scheme. The convergence of the PGADP algorithm is proved by demonstrating that the constructed.

  13. Coordinated Optimization of Aircraft Routes and Locations of Ground Sensors

    Science.gov (United States)

    2014-09-17

    optimization approaches allowing minimization of the total cost subject to linear inequality constraints can be formulated in terms of the binary...the calculations are not trivial. ERDC/CRREL TR-14-20 9 3.1 Coverage matrix for aircraft Coverage matrix A enters the inequality coverage...of target (a person versus a car): 8 ± 2 px • Identification of the target (a woman versus a man, a specific car): 13 ± 3 px; These criteria

  14. Torsional Ultrasound Sensor Optimization for Soft Tissue Characterization

    Directory of Open Access Journals (Sweden)

    Juan Melchor

    2017-06-01

    Full Text Available Torsion mechanical waves have the capability to characterize shear stiffness moduli of soft tissue. Under this hypothesis, a computational methodology is proposed to design and optimize a piezoelectrics-based transmitter and receiver to generate and measure the response of torsional ultrasonic waves. The procedure employed is divided into two steps: (i a finite element method (FEM is developed to obtain a transmitted and received waveform as well as a resonance frequency of a previous geometry validated with a semi-analytical simplified model and (ii a probabilistic optimality criteria of the design based on inverse problem from the estimation of robust probability of detection (RPOD to maximize the detection of the pathology defined in terms of changes of shear stiffness. This study collects different options of design in two separated models, in transmission and contact, respectively. The main contribution of this work describes a framework to establish such as forward, inverse and optimization procedures to choose a set of appropriate parameters of a transducer. This methodological framework may be generalizable for other different applications.

  15. On the Design of Smart Parking Networks in the Smart Cities: An Optimal Sensor Placement Model

    Directory of Open Access Journals (Sweden)

    Antoine Bagula

    2015-06-01

    Full Text Available Smart parking is a typical IoT application that can benefit from advances in sensor, actuator and RFID technologies to provide many services to its users and parking owners of a smart city. This paper considers a smart parking infrastructure where sensors are laid down on the parking spots to detect car presence and RFID readers are embedded into parking gates to identify cars and help in the billing of the smart parking. Both types of devices are endowed with wired and wireless communication capabilities for reporting to a gateway where the situation recognition is performed. The sensor devices are tasked to play one of the three roles: (1 slave sensor nodes located on the parking spot to detect car presence/absence; (2 master nodes located at one of the edges of a parking lot to detect presence and collect the sensor readings from the slave nodes; and (3 repeater sensor nodes, also called “anchor” nodes, located strategically at specific locations in the parking lot to increase the coverage and connectivity of the wireless sensor network. While slave and master nodes are placed based on geographic constraints, the optimal placement of the relay/anchor sensor nodes in smart parking is an important parameter upon which the cost and efficiency of the parking system depends. We formulate the optimal placement of sensors in smart parking as an integer linear programming multi-objective problem optimizing the sensor network engineering efficiency in terms of coverage and lifetime maximization, as well as its economic gain in terms of the number of sensors deployed for a specific coverage and lifetime. We propose an exact solution to the node placement problem using single-step and two-step solutions implemented in the Mosel language based on the Xpress-MPsuite of libraries. Experimental results reveal the relative efficiency of the single-step compared to the two-step model on different performance parameters. These results are consolidated by

  16. On the Design of Smart Parking Networks in the Smart Cities: An Optimal Sensor Placement Model.

    Science.gov (United States)

    Bagula, Antoine; Castelli, Lorenzo; Zennaro, Marco

    2015-06-30

    Smart parking is a typical IoT application that can benefit from advances in sensor, actuator and RFID technologies to provide many services to its users and parking owners of a smart city. This paper considers a smart parking infrastructure where sensors are laid down on the parking spots to detect car presence and RFID readers are embedded into parking gates to identify cars and help in the billing of the smart parking. Both types of devices are endowed with wired and wireless communication capabilities for reporting to a gateway where the situation recognition is performed. The sensor devices are tasked to play one of the three roles: (1) slave sensor nodes located on the parking spot to detect car presence/absence; (2) master nodes located at one of the edges of a parking lot to detect presence and collect the sensor readings from the slave nodes; and (3) repeater sensor nodes, also called "anchor" nodes, located strategically at specific locations in the parking lot to increase the coverage and connectivity of the wireless sensor network. While slave and master nodes are placed based on geographic constraints, the optimal placement of the relay/anchor sensor nodes in smart parking is an important parameter upon which the cost and efficiency of the parking system depends. We formulate the optimal placement of sensors in smart parking as an integer linear programming multi-objective problem optimizing the sensor network engineering efficiency in terms of coverage and lifetime maximization, as well as its economic gain in terms of the number of sensors deployed for a specific coverage and lifetime. We propose an exact solution to the node placement problem using single-step and two-step solutions implemented in the Mosel language based on the Xpress-MPsuite of libraries. Experimental results reveal the relative efficiency of the single-step compared to the two-step model on different performance parameters. These results are consolidated by simulation results

  17. 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.

  18. Adaptive compression of slowly varying images transmitted over Wireless Sensor Networks.

    Science.gov (United States)

    Nikolakopoulos, George; Kandris, Dionisis; Tzes, Anthony

    2010-01-01

    In this article a scheme for image transmission over Wireless Sensor Networks (WSN) with an adaptive compression factor is introduced. The proposed control architecture affects the quality of the transmitted images according to: (a) the traffic load within the network and (b) the level of details contained in an image frame. Given an approximate transmission period, the adaptive compression mechanism applies Quad Tree Decomposition (QTD) with a varying decomposition compression factor based on a gradient adaptive approach. For the initialization of the proposed control scheme, the desired a priori maximum bound for the transmission time delay is being set, while a tradeoff among the quality of the decomposed image frame and the time needed for completing the transmission of the frame should be taken under consideration. Based on the proposed control mechanism, the quality of the slowly varying transmitted image frames is adaptively deviated based on the measured time delay in the transmission. The efficacy of the adaptive compression control scheme is validated through extended experimental results.

  19. Adaptive Compression of Slowly Varying Images Transmitted over Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Anthony Tzes

    2010-07-01

    Full Text Available In this article a scheme for image transmission over Wireless Sensor Networks (WSN with an adaptive compression factor is introduced. The proposed control architecture affects the quality of the transmitted images according to: (a the traffic load within the network and (b the level of details contained in an image frame. Given an approximate transmission period, the adaptive compression mechanism applies Quad Tree Decomposition (QTD with a varying decomposition compression factor based on a gradient adaptive approach. For the initialization of the proposed control scheme, the desired a priori maximum bound for the transmission time delay is being set, while a tradeoff among the quality of the decomposed image frame and the time needed for completing the transmission of the frame should be taken under consideration. Based on the proposed control mechanism, the quality of the slowly varying transmitted image frames is adaptively deviated based on the measured time delay in the transmission. The efficacy of the adaptive compression control scheme is validated through extended experimental results.

  20. Addressing practical challenges in utility optimization of mobile wireless sensor networks

    Science.gov (United States)

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

    2008-04-01

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

  1. Distance-Based and Low Energy Adaptive Clustering Protocol for Wireless Sensor Networks

    Science.gov (United States)

    Gani, Abdullah; Anisi, Mohammad Hossein; Ab Hamid, Siti Hafizah; Akhunzada, Adnan; Khan, Muhammad Khurram

    2016-01-01

    A wireless sensor network (WSN) comprises small sensor nodes with limited energy capabilities. The power constraints of WSNs necessitate efficient energy utilization to extend the overall network lifetime of these networks. We propose a distance-based and low-energy adaptive clustering (DISCPLN) protocol to streamline the green issue of efficient energy utilization in WSNs. We also enhance our proposed protocol into the multi-hop-DISCPLN protocol to increase the lifetime of the network in terms of high throughput with minimum delay time and packet loss. We also propose the mobile-DISCPLN protocol to maintain the stability of the network. The modelling and comparison of these protocols with their corresponding benchmarks exhibit promising results. PMID:27658194

  2. Distance-Based and Low Energy Adaptive Clustering Protocol for Wireless Sensor Networks.

    Science.gov (United States)

    Liaqat, Misbah; Gani, Abdullah; Anisi, Mohammad Hossein; Ab Hamid, Siti Hafizah; Akhunzada, Adnan; Khan, Muhammad Khurram; Ali, Rana Liaqat

    A wireless sensor network (WSN) comprises small sensor nodes with limited energy capabilities. The power constraints of WSNs necessitate efficient energy utilization to extend the overall network lifetime of these networks. We propose a distance-based and low-energy adaptive clustering (DISCPLN) protocol to streamline the green issue of efficient energy utilization in WSNs. We also enhance our proposed protocol into the multi-hop-DISCPLN protocol to increase the lifetime of the network in terms of high throughput with minimum delay time and packet loss. We also propose the mobile-DISCPLN protocol to maintain the stability of the network. The modelling and comparison of these protocols with their corresponding benchmarks exhibit promising results.

  3. Optimized Distributed Feedback Dye Laser Sensor for Real-Time Monitoring of Small Molecule Diffusion

    DEFF Research Database (Denmark)

    Vannahme, Christoph; Smith, Cameron; Dufva, Martin

    2014-01-01

    Nanoimprinted distributed feedback dye laser sensors featuring multilayer slab waveguides are presented. A simple yet precise analytical model is used to optimize the lasers in order to give highest sensitivity and it is found that the thickness of a high index TiO2 top layer is the most importan...

  4. An Energy Efficient Scheme for Data Gathering in Wireless Sensor Networks Using Particle Swarm Optimization

    CERN Document Server

    Chakraborty, Ayon; Mitra, Swarup Kumar; Naskar, M K

    2010-01-01

    Energy Efficiency of sensor nodes is a sizzling issue, given the severe resource constraints of sensor nodes and pervasive nature of sensor networks. The base station being located at variable distances from the nodes in the sensor field, each node actually dissipates a different amount of energy to transmit data to the same. The LEACH [4] and PEGASIS [5] protocols provide elegant solutions to this problem, but may not always result in optimal performance. In this paper we have proposed a novel data gathering protocol for enhancing the network lifetime by optimizing energy dissipation in the nodes. To achieve our design objective we have applied particle swarm optimization (PSO) with Simulated Annealing (SA) to form a sub-optimal data gathering chain and devised a method for selecting an efficient leader for communicating to the base station. In our scheme each node only communicates with a close neighbor and takes turns in being the leader depending on its residual energy and location. This helps to rule out...

  5. Micro-calorimetric sensor for vapor phase explosive detection with optimized heat profile

    DEFF Research Database (Denmark)

    Greve, Anders; Olsen, J.; Privorotskaya, N.

    2010-01-01

    A heater design, used in a micro-calorimetric sensor, has been optimized for temperature uniformity in order to increase the sensitivity and reliability of detection of trace amounts of explosives. In this abstract the design, fabrication and characterization is described. The performance of the ...

  6. Selecting Optimal Parameters of Random Linear Network Coding for Wireless Sensor Networks

    DEFF Research Database (Denmark)

    Heide, Janus; Zhang, Qi; Fitzek, Frank

    2013-01-01

    This work studies how to select optimal code parameters of Random Linear Network Coding (RLNC) in Wireless Sensor Networks (WSNs). With Rateless Deluge [1] the authors proposed to apply Network Coding (NC) for Over-the-Air Programming (OAP) in WSNs, and demonstrated that with NC a significant...

  7. An Optimal Algorithm towards Successive Location Privacy in Sensor Networks with Dynamic Programming

    Science.gov (United States)

    Zhao, Baokang; Wang, Dan; Shao, Zili; Cao, Jiannong; Chan, Keith C. C.; Su, Jinshu

    In wireless sensor networks, preserving location privacy under successive inference attacks is extremely critical. Although this problem is NP-complete in general cases, we propose a dynamic programming based algorithm and prove it is optimal in special cases where the correlation only exists between p immediate adjacent observations.

  8. Identification of Damage in IR-Structures from Earthquake Records - Optimal Location of Sensors

    DEFF Research Database (Denmark)

    Nielsen, Søren R.K.; Skjærbæk, P. S.; Cakmak, A. S.

    of the optimal location of measurements sensors, i.e. at which locations along the structure the most information about the damage distribution is gained. In all cases it is assumed that measurements are performed at top storey and ground surface, and the investigations are concentrated on putting one or two...

  9. Optimization of an integrated-optical ring-resonator slow-light-based sensor

    NARCIS (Netherlands)

    Uranus, H.P.; Hoekman, M.; Dijkstra, M.; Hoekstra, H.J.W.M.; stoffer, R.

    2008-01-01

    A 3-D, vectorial, and multimodal model that incorporates realistic losses was developed to study the performance of Si3N4 based integrated-optical ring-resonator slow-light-based refractometric sensor. Efficient optimization of the coupler gap and tolerance analysis were also performed using the mod

  10. Energy Balanced Dynamic Deployment Optimization to Enhance Reliable Lifetime of Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    J.Roselin

    2013-08-01

    Full Text Available In Wireless Sensor Networks (WSNs, the available energy of sensor nodes is limited and hard to renew. The energy supervision is also very critical. In Mission Critical Surveillance application, due tonode’s battery depletion, coverage hole may be created. Hole at Critical Point (CP leads to performance degradation of overall network. It is merely impossible, to redeploy sensor nodes or to recharge the battery in middle run during monitoring. The proposed Energy Balanced-Dynamic Deployment (EB-DD Optimization approach, positions the self deployable mobile sensors towards CP according to its Energy Density. This balances the Energy Density of the network thereby increasing the Reliable Lifetime. The simulation results show the effectiveness of the approach in terms of balanced Energy Density around CPs with less mobility.

  11. An Energy Consumption Optimized Clustering Algorithm for Radar Sensor Networks Based on an Ant Colony Algorithm

    Directory of Open Access Journals (Sweden)

    Jiang Ting

    2010-01-01

    Full Text Available We optimize the cluster structure to solve problems such as the uneven energy consumption of the radar sensor nodes and random cluster head selection in the traditional clustering routing algorithm. According to the defined cost function for clusters, we present the clustering algorithm which is based on radio-free space path loss. In addition, we propose the energy and distance pheromones based on the residual energy and aggregation of the radar sensor nodes. According to bionic heuristic algorithm, a new ant colony-based clustering algorithm for radar sensor networks is also proposed. Simulation results show that this algorithm can get a better balance of the energy consumption and then remarkably prolong the lifetime of the radar sensor network.

  12. Optimization of adaptive radiation therapy in cervical cancer: Solutions for photon and proton therapy

    NARCIS (Netherlands)

    van de Schoot, A.J.A.J.

    2016-01-01

    In cervical cancer radiation therapy, an adaptive strategy is required to compensate for interfraction anatomical variations in order to achieve adequate dose delivery. In this thesis, we have aimed at optimizing adaptive radiation therapy in cervical cancer to improve treatment efficiency and

  13. Optimization of adaptive radiation therapy in cervical cancer: Solutions for photon and proton therapy

    NARCIS (Netherlands)

    van de Schoot, A.J.A.J.

    2016-01-01

    In cervical cancer radiation therapy, an adaptive strategy is required to compensate for interfraction anatomical variations in order to achieve adequate dose delivery. In this thesis, we have aimed at optimizing adaptive radiation therapy in cervical cancer to improve treatment efficiency and reduc

  14. Real-Time Game Adaptation for Optimizing Player Satisfaction

    DEFF Research Database (Denmark)

    Yannakakis, Georgios; Hallam, John

    2009-01-01

    preferences for augmented-reality game players. An adaptive mechanism then adjusts controllable game parameters in real time in order to improve the entertainment value of the game for the player. The basic approach presented here applies gradient ascent to the user model to suggest the direction of parameter...... adjustment that leads toward games of higher entertainment value. A simple rule set exploits the derivative information to adjust specific game parameters to augment the entertainment value. Those adjustments take place frequently during the game with interadjustment intervals that maintain the user model......'s accuracy. Performance of the adaptation mechanism is evaluated using a game survey experiment. Results indicate the efficacy and robustness of the mechanism in adapting the game according to a user's individual playing features and enhancing the gameplay experience. The limitations and the use...

  15. Cross-layer protocol design for QoS optimization in real-time wireless sensor networks

    Science.gov (United States)

    Hortos, William S.

    2010-04-01

    The metrics of quality of service (QoS) for each sensor type in a wireless sensor network can be associated with metrics for multimedia that describe the quality of fused information, e.g., throughput, delay, jitter, packet error rate, information correlation, etc. These QoS metrics are typically set at the highest, or application, layer of the protocol stack to ensure that performance requirements for each type of sensor data are satisfied. Application-layer metrics, in turn, depend on the support of the lower protocol layers: session, transport, network, data link (MAC), and physical. The dependencies of the QoS metrics on the performance of the higher layers of the Open System Interconnection (OSI) reference model of the WSN protocol, together with that of the lower three layers, are the basis for a comprehensive approach to QoS optimization for multiple sensor types in a general WSN model. The cross-layer design accounts for the distributed power consumption along energy-constrained routes and their constituent nodes. Following the author's previous work, the cross-layer interactions in the WSN protocol are represented by a set of concatenated protocol parameters and enabling resource levels. The "best" cross-layer designs to achieve optimal QoS are established by applying the general theory of martingale representations to the parameterized multivariate point processes (MVPPs) for discrete random events occurring in the WSN. Adaptive control of network behavior through the cross-layer design is realized through the parametric factorization of the stochastic conditional rates of the MVPPs. The cross-layer protocol parameters for optimal QoS are determined in terms of solutions to stochastic dynamic programming conditions derived from models of transient flows for heterogeneous sensor data and aggregate information over a finite time horizon. Markov state processes, embedded within the complex combinatorial history of WSN events, are more computationally

  16. Field-Based Optimal Placement of Antennas for Body-Worn Wireless Sensors

    Directory of Open Access Journals (Sweden)

    Łukasz Januszkiewicz

    2016-05-01

    Full Text Available We investigate a case of automated energy-budget-aware optimization of the physical position of nodes (sensors in a Wireless Body Area Network (WBAN. This problem has not been presented in the literature yet, as opposed to antenna and routing optimization, which are relatively well-addressed. In our research, which was inspired by a safety-critical application for firefighters, the sensor network consists of three nodes located on the human body. The nodes communicate over a radio link operating in the 2.4 GHz or 5.8 GHz ISM frequency band. Two sensors have a fixed location: one on the head (earlobe pulse oximetry and one on the arm (with accelerometers, temperature and humidity sensors, and a GPS receiver, while the position of the third sensor can be adjusted within a predefined region on the wearer’s chest. The path loss between each node pair strongly depends on the location of the nodes and is difficult to predict without performing a full-wave electromagnetic simulation. Our optimization scheme employs evolutionary computing. The novelty of our approach lies not only in the formulation of the problem but also in linking a fully automated optimization procedure with an electromagnetic simulator and a simplified human body model. This combination turns out to be a computationally effective solution, which, depending on the initial placement, has a potential to improve performance of our example sensor network setup by up to about 20 dB with respect to the path loss between selected nodes.

  17. Energy Constrained Reliable Routing Optimized Cluster Head Protocol for Multihop under Water Acoustic Sensor Networks

    Directory of Open Access Journals (Sweden)

    Padmavathy.T.V

    2012-06-01

    Full Text Available Underwater acoustic sensor network is an emerging technique consisting of sensor nodes, and AUVs all working together to sense various phenomenon, converts the sensed information into digital data, storethe digital data and communicate to the base stations through the intermediate nodes. Also UnderwaterAcoustic Sensor Networks are playing a main role in ocean applications. Unfortunately the efficiency of underwater Acoustic Sensor Networks is inferior to that of terrestrial sensor networks due to the longpropagation delay, narrow bandwidth and high error rates. Also battery life and storage capacity of node is limited. Many routing protocols are proposed to improve the efficiency of Under Water Acoustic Sensor Networks. However their improvement is not enough, so there is a need of suitable routing protocol that consider all these limitations and makes communication in underwater network viable. In this paper, we propose a protocol called Reliable Routing Optimized Cluster Head (RROCH protocol, a network coding approach for multihop topologies. We used performance metrics like packet delivery ratio, energy consumption, end-to-end delay and throughput of sensor nodes. LEACH, HMR-LEACH, LEACH-M are compared for their performance at different traffic conditions, number of nodes and depth. By analyzing our simulation results we found that RROCH protocol may be used for denser network with low traffic and HMR- LEACH protocol is suitable for higher traffic with less number of nodes.

  18. Impedance adaptation for optimal robot-environment interaction

    Science.gov (United States)

    Ge, Shuzhi Sam; Li, Yanan; Wang, Chen

    2014-02-01

    In this paper, impedance adaptation is investigated for robots interacting with unknown environments. Impedance control is employed for the physical interaction between robots and environments, subject to unknown and uncertain environments dynamics. The unknown environments are described as linear systems with unknown dynamics, based on which the desired impedance model is obtained. A cost function that measures the tracking error and interaction force is defined, and the critical impedance parameters are found to minimise it. Without requiring the information of the environments dynamics, the proposed impedance adaptation is feasible in a large number of applications where robots physically interact with unknown environments. The validity of the proposed method is verified through simulation studies.

  19. SELECT OF OPTIMAL SLEEP STATE IN ADAPTIVE SMAC USING DPM

    National Research Council Canada - National Science Library

    Elham Hajian; Kamal Jamshidi; Ali Bohlooli

    2010-01-01

    .... Therefore, optimal energy consumption for wsn protocols is a necessity. In a number of proposed protocols periodic sleep and wake is used for energy use reduction but these protocols result in increased end to end delay...

  20. Online Algorithms for Adaptive Optimization in Heterogeneous Delay Tolerant Networks

    Directory of Open Access Journals (Sweden)

    Wissam Chahin

    2013-12-01

    Full Text Available Delay Tolerant Networks (DTNs are an emerging type of networks which do not need a predefined infrastructure. In fact, data forwarding in DTNs relies on the contacts among nodes which may possess different features, radio range, battery consumption and radio interfaces. On the other hand, efficient message delivery under limited resources, e.g., battery or storage, requires to optimize forwarding policies. We tackle optimal forwarding control for a DTN composed of nodes of different types, forming a so-called heterogeneous network. Using our model, we characterize the optimal policies and provide a suitable framework to design a new class of multi-dimensional stochastic approximation algorithms working for heterogeneous DTNs. Crucially, our proposed algorithms drive online the source node to the optimal operating point without requiring explicit estimation of network parameters. A thorough analysis of the convergence properties and stability of our algorithms is presented.

  1. Real-Time Game Adaptation for Optimizing Player Satisfaction

    DEFF Research Database (Denmark)

    Yannakakis, Georgios; Hallam, John

    2009-01-01

    A methodology for optimizing player satisfaction in games on the "playware" physical interactive platform is demonstrated in this paper. Previously constructed artificial neural network user models, reported in the literature, map individual playing characteristics to reported entertainment...

  2. Optimized Autonomous Space In-situ Sensor-Web for volcano monitoring

    Science.gov (United States)

    Song, W.-Z.; Shirazi, B.; Kedar, S.; Chien, S.; Webb, F.; Tran, D.; Davis, A.; Pieri, D.; LaHusen, R.; Pallister, J.; Dzurisin, D.; Moran, S.; Lisowski, M.

    2008-01-01

    In response to NASA's announced requirement for Earth hazard monitoring sensor-web technology, a multidisciplinary team involving sensor-network experts (Washington State University), space scientists (JPL), and Earth scientists (USGS Cascade Volcano Observatory (CVO)), is developing a prototype dynamic and scaleable hazard monitoring sensor-web and applying it to volcano monitoring. The combined Optimized Autonomous Space -In-situ Sensor-web (OASIS) will have two-way communication capability between ground and space assets, use both space and ground data for optimal allocation of limited power and bandwidth resources on the ground, and use smart management of competing demands for limited space assets. It will also enable scalability and seamless infusion of future space and in-situ assets into the sensor-web. The prototype will be focused on volcano hazard monitoring at Mount St. Helens, which has been active since October 2004. The system is designed to be flexible and easily configurable for many other applications as well. The primary goals of the project are: 1) integrating complementary space (i.e., Earth Observing One (EO-1) satellite) and in-situ (ground-based) elements into an interactive, autonomous sensor-web; 2) advancing sensor-web power and communication resource management technology; and 3) enabling scalability for seamless infusion of future space and in-situ assets into the sensor-web. To meet these goals, we are developing: 1) a test-bed in-situ array with smart sensor nodes capable of making autonomous data acquisition decisions; 2) efficient self-organization algorithm of sensor-web topology to support efficient data communication and command control; 3) smart bandwidth allocation algorithms in which sensor nodes autonomously determine packet priorities based on mission needs and local bandwidth information in real-time; and 4) remote network management and reprogramming tools. The space and in-situ control components of the system will be

  3. Strategies and Tools for Deployment and Optimization of Wireless Sensor Networks

    OpenAIRE

    Mujica Rojas, Gabriel Noe

    2017-01-01

    El campo de investigación de las Redes de Sensores Inalámbricas (en inglés Wireless Sensor Networks, WSN) ha experimentado un importante y progresivo proceso de maduración que ha involucrado la definición de nuevas tecnologías a nivel hardware y software con el fin de abordar escenarios de aplicación mucho más demandantes, en los que plataformas flexibles y adaptables juegan un papel fundamental para la consecución de los requisitos de aplicación y provisión de servicios dentro de diversos en...

  4. A uniquely adaptable pore is consistent with NALCN being an ion sensor.

    Science.gov (United States)

    Senatore, Adriano; Spafford, J David

    2013-01-01

    NALCN is an intriguing, orphan ion channel among the 4x6TM family of related voltage-gated cation channels, sharing a common architecture of four homologous domains consisting of six transmembrane helices, separated by three cytoplasmic linkers and delimited by N and C-terminal ends. NALCN is one of the shortest 4x6TM family members, lacking much of the variation that provides the diverse palate of gating features, and tissue specific adaptations of sodium and calcium channels. NALCN's most distinctive feature is that that it possesses a highly adaptable pore with a calcium-like EEEE selectivity filter in radially symmetrical animals and a more sodium-like EEKE or EKEE selectivity filter in bilaterally symmetrical animals including vertebrates. Two lineages of animals evolved alternative calcium-like EEEE and sodium-like EEKE / EKEE pores, spliced to regulate NALCN functions in differing cellular environments, such as muscle (heart and skeletal) and secretory tissue (brain and glands), respectively. A highly adaptable pore in an otherwise conserved ion channel in the 4x6TM channel family is not consistent with a role for NALCN in directly gating a significant ion conductance that can be either sodium ions or calcium ions. NALCN was proposed to be an expressible Gd ( 3+) -sensitive, NMDG (+) -impermeant, non-selective and ohmic leak conductance in HEK-293T cells, but we were unable to distinguish these reported currents from leaky patch currents (ILP) in control HEK-293T cells. We suggest that NALCN functions as a sensor for the much larger UNC80/UNC79 complex, in a manner consistent with the coupling mechanism known for other weakly or non-conducting 4x6TM channel sensor proteins such as Nax or Cav 1.1. We propose that NALCN serves as a variable sensor that responds to calcium or sodium ion flux, depending on whether the total cellular current density is generated more from calcium-selective or sodium-selective channels.

  5. Optimal Relay Selection with Channel Probing in Wireless Sensor Networks

    CERN Document Server

    Naveen, K P

    2011-01-01

    Motivated by the problem of distributed geographical packet forwarding in a wireless sensor network with sleep-wake cycling nodes, we propose a local forwarding model comprising a node that wishes to forward a packet towards a destination, and a set of next-hop relay nodes, each of which is associated with a reward that summarises the cost/benefit of forwarding the packet through that relay. The relays wake up at random times, at which instants they reveal only the probability distributions of their rewards (e.g., by revealing their locations). To determine a relay's exact reward, the forwarding node has to further probe the relay, incurring a probing cost. Thus, at each relay wake-up instant, the source, given a set of relay reward distributions, has to decide whether to stop (and forward the packet to an already probed relay), continue waiting for further relays to wake-up, or probe an unprobed relay. We formulate the problem as a Markov decision process, with the objective being to minimize the packet forw...

  6. Optimal sink placement in backbone assisted wireless sensor networks

    Directory of Open Access Journals (Sweden)

    I. Snigdh

    2016-07-01

    Full Text Available This article proposes a scheme for selecting the best site for sink placement in WSN applications employing backbone assisted communications. By placing the sink at a specific position, energy scavenging and delay constraints can effectively be controlled. In contrast to the conventional scheme for base station placement at the geographical centre or random placement at the end of the region of interest, the proposed scheme places the base station at either the graph theoretical centre or centroid of the backbone connecting nodes in the region of interest. This strategy shows a considerable reduction in the total number of hops that each packet needs to travel to reach the sink. The proposed scheme is applied on all the families of graphs prevalent in backbone assisted sensor networks to confirm the performance consistency and improvement in network parameters of the communication backbone measured in terms of delay, the carried load and the total energy consumption, eventually affected by the average number of hops for the message to reach the sink.

  7. Neural adaptive observer-based sensor and actuator fault detection in nonlinear systems: Application in UAV.

    Science.gov (United States)

    Abbaspour, Alireza; Aboutalebi, Payam; Yen, Kang K; Sargolzaei, Arman

    2017-03-01

    A new online detection strategy is developed to detect faults in sensors and actuators of unmanned aerial vehicle (UAV) systems. In this design, the weighting parameters of the Neural Network (NN) are updated by using the Extended Kalman Filter (EKF). Online adaptation of these weighting parameters helps to detect abrupt, intermittent, and incipient faults accurately. We apply the proposed fault detection system to a nonlinear dynamic model of the WVU YF-22 unmanned aircraft for its evaluation. The simulation results show that the new method has better performance in comparison with conventional recurrent neural network-based fault detection strategies.

  8. Active control of smart structures with optimal actuator and sensor locations

    Science.gov (United States)

    Liu, Pengxiang; Rao, Vittal S.; Derriso, Mark M.

    2002-07-01

    Sensors and actuators used in active control of smart structures have to be located appropriately in order to ensure maximum control and measurement effectiveness. Many placement techniques are based on the structure itself and overlook the effects of the applied control law. The optimal locations determined from open-loop system can not guarantee the best performance of the closed-loop system because the performance is closely related with the design requirements and applied controller. In this paper, we presented a method of obtaining the optimal locations of actuators/sensors by combining the open-loop and closed-loop optimal criterions. First, for open-loop system, location indices of the controlled modes are calculated on the basis of modal controllability and observability. The controlled modes are weighted based on the controller design requirements. To reduce the spill-over effect of uncontrolled modes, the location index values of uncontrolled modes are added as penalty terms. Locations with high index values are chosen as candidate locations of actuator/sensor for the next determining step on the closed-loop system. Three control techniques, optimal H2, H(infinity ) norms and optimal pole-placement, are utilized for two different control objectives, disturbance rejection and damping property enhancement. Linear matrix inequality (LMI) techniques are utilized to formulate the control problems and synthesize the controllers. For each candidate location of actuator/sensor, a controller is designed and the obtained performance is taken as location index. By solving the location problem in two steps, we reduced the computational burden and ensured good control performance of the closed-loop system. The proposed method is tested on a clamped plate with piezoelectric actuators and sensors.

  9. 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

  10. Optimization-based wavefront sensorless adaptive optics for multiphoton microscopy

    NARCIS (Netherlands)

    Antonello, J.; Werkhoven, T. van; Verhaegen, M.; Truong, H.H.; Keller, C.U.; Gerritsen, H.C.

    2014-01-01

    Optical aberrations have detrimental effects in multiphoton microscopy. These effects can be curtailed by implementing model-based wavefront sensorless adaptive optics, which only requires the addition of a wavefront shaping device, such as a deformable mirror (DM) to an existing microscope. The abe

  11. Optimal adaptive control for a class of stochastic systems

    NARCIS (Netherlands)

    Bagchi, Arunabha; Chen, Han-Fu

    1997-01-01

    We study linear-quadratic adaptive tracking problems for a special class of stochastic systems expressed in the state-space form. This is a long-standing problem in the control of aircraft flying through atmospheric turbulence. Using an ELS-based algorithm and introducing dither in the control law w

  12. Data-Driven Optimal Control for Adaptive Optics

    NARCIS (Netherlands)

    Hinnen, K.J.G.

    2007-01-01

    Adaptive optics (AO) is a technique to actively correct the wavefront distortions introduced in a light beam as it propagates through a turbulent medium. Nowadays, it is commonly applied in ground-based telescopes to counteract the devastating effect of atmospheric turbulence. This thesis focuses on

  13. Time Optimized Algorithm for Web Document Presentation Adaptation

    DEFF Research Database (Denmark)

    Pan, Rong; Dolog, Peter

    2010-01-01

    Currently information on the web is accessed through different devices. Each device has its own properties such as resolution, size, and capabilities to display information in different format and so on. This calls for adaptation of information presentation for such platforms. This paper proposes...

  14. Systematic description of direct push sensor systems: A conceptual framework for system decomposition as a basis for the optimal sensor system design

    Science.gov (United States)

    Bumberger, Jan; Paasche, Hendrik; Dietrich, Peter

    2015-11-01

    Systematic decomposition and evaluation of existing sensor systems as well as the optimal design of future generations of direct push probes are of high importance for optimized geophysical experiments since the employed equipment is a constrain on the data space. Direct push technologies became established methods in the field of geophysical, geotechnical, hydrogeological, and environmental sciences for the investigation of the near subsurface. By using direct push sensor systems it is possible to measure in-situ parameters with high vertical resolution. Such information is frequently used for quantitative geophysical model calibration of interpretation of geotechnical and hydrological subsurface conditions. Most of the available direct push sensor systems are largely based on empirical testing and consecutively evaluated under field conditions. Approaches suitable to identify specific characteristics and problems of direct push sensor systems have not been established, yet. We develop a general systematic approach for the classification, analysis, and optimization of direct push sensor systems. First, a classification is presented for different existing sensor systems. The following systematic description, which is based on the conceptual decomposition of an existing sensor system into subsystems, is a suitable way to analyze and explore the transfer behavior of the system components and therefore of the complete system. Also, this approach may serve as guideline for the synthesis and the design of new and optimized direct push sensor systems.

  15. Optimization of NEMS pressure sensors with a multilayered diaphragm using silicon nanowires as piezoresistive sensing elements

    Science.gov (United States)

    Lou, Liang; Zhang, Songsong; Park, Woo-Tae; Tsai, J. M.; Kwong, Dim-Lee; Lee, Chengkuo

    2012-05-01

    A pressure sensor with a 200 µm diaphragm using silicon nanowires (SiNWs) as a piezoresistive sensing element is developed and optimized. The SiNWs are embedded in a multilayered diaphragm structure comprising silicon nitride (SiNx) and silicon oxide (SiO2). Optimizations were performed on both SiNWs and the diaphragm structure. The diaphragm with a 1.2 µm SiNx layer is considered to be an optimized design in terms of small initial central deflection (0.1 µm), relatively high sensitivity (0.6% psi-1) and good linearity within our measurement range.

  16. Energy-Aware Adaptive Cooperative FEC Protocol in MIMO Channel for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Yong Jin

    2013-01-01

    Full Text Available We propose an adaptive cooperative forward error correction (ACFEC based on energy efficiency combining Reed-Solomon (RS coder algorithm and multiple input multiple output (MIMO channel technology with monitoring signal-to-noise ratio (SNR in wireless sensor networks. First, we propose a new Markov chain model for FEC based on RS codes and derive the expressions for QoS on the basis of this model, which comprise four metrics: throughput, packet error rate, delay, and energy efficiency. Then, we apply RS codes with the MIMO channel technology to the cross-layer design. Numerical and simulation results show that the joint design of MIMO and adaptive cooperative FEC based on RS codes can achieve considerable spectral efficiency gain, real-time performance, reliability, and energy utility.

  17. Experience with wavefront sensor and deformable mirror interfaces for wide-field adaptive optics systems

    CERN Document Server

    Basden, A G; Bharmal, N A; Bitenc, U; Brangier, M; Buey, T; Butterley, T; Cano, D; Chemla, F; Clark, P; Cohen, M; Conan, J -M; de Cos, F J; Dickson, C; Dipper, N A; Dunlop, C N; Feautrier, P; Fusco, T; Gach, J L; Gendron, E; Geng, D; Goodsell, S J; Gratadour, D; Greenaway, A H; Guesalaga, A; Guzman, C D; Henry, D; Holck, D; Hubert, Z; Huet, J M; Kellerer, A; Kulcsar, C; Laporte, P; Roux, B Le; Looker, N; Longmore, A J; Marteaud, M; Martin, O; Meimon, S; Morel, C; Morris, T J; Myers, R M; Osborn, J; Perret, D; Petit, C; Raynaud, H; Reeves, A P; Rousset, G; Lasheras, F Sanchez; Rodriguez, M Sanchez; Santos, J D; Sevin, A; Sivo, G; Stadler, E; Stobie, B; Talbot, G; Todd, S; Vidal, F; Younger, E J

    2016-01-01

    Recent advances in adaptive optics (AO) have led to the implementation of wide field-of-view AO systems. A number of wide-field AO systems are also planned for the forthcoming Extremely Large Telescopes. Such systems have multiple wavefront sensors of different types, and usually multiple deformable mirrors (DMs). Here, we report on our experience integrating cameras and DMs with the real-time control systems of two wide-field AO systems. These are CANARY, which has been operating on-sky since 2010, and DRAGON, which is a laboratory adaptive optics real-time demonstrator instrument. We detail the issues and difficulties that arose, along with the solutions we developed. We also provide recommendations for consideration when developing future wide-field AO systems.

  18. Performance simulation of the ERIS pyramid wavefront sensor module in the VLT adaptive optics facility

    Science.gov (United States)

    Quirós-Pacheco, Fernando; Agapito, Guido; Riccardi, Armando; Esposito, Simone; Le Louarn, Miska; Marchetti, Enrico

    2012-07-01

    This paper presents the performance analysis based on numerical simulations of the Pyramid Wavefront sensor Module (PWM) to be included in ERIS, the new Adaptive Optics (AO) instrument for the Adaptive Optics Facility (AOF). We have analyzed the performance of the PWM working either in a low-order or in a high-order wavefront sensing mode of operation. We show that the PWM in the high-order sensing mode can provide SR > 90% in K band using bright guide stars under median seeing conditions (0.85 arcsec seeing and 15 m/s of wind speed). In the low-order sensing mode, the PWM can sense and correct Tip-Tilt (and if requested also Focus mode) with the precision required to assist the LGS observations to get an SR > 60% and > 20% in K band, using up to a ~16.5 and ~19.5 R-magnitude guide star, respectively.

  19. 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.

  20. QoS Adaptive Topology Configuration in Synchronous Wireless Sensor Networks

    Institute of Scientific and Technical Information of China (English)

    YANG Ting; WU Jiaowen; LI Ang; ZHANG Zhidong

    2010-01-01

    By using hyper-graph theory,this paper proposes a QoS adaptive topology configuration(QATC)algorithm to effectively control large-scale topology and achieve robust data transmitting in synchronous wireless sensor networks.Firstly,a concise hyper-graph model is abstracted to analyze the large-scale and high-connectivity network.Secondly,based on the control theory of biologic "Cell Mergence",a novel self-adaptive topology configuration algorithm is used to build homologous perceptive data logic sub-network for data aggregation.Compared with Flooding,Directed Diffusion,and Energy Aware Directed Diffusion protocols,the simulation proved that QATC algorithm can save more energy,e.g.,about 23.7% in a large size network,and has less delay than the other algorithms.In dynamic experiments,QATC keeps a robust transmitting quality with 10%,20% and 30% random failure nodes.