Model-Based Design of Tree WSNs for Decentralized Detection †

PubMed Central

Tantawy, Ashraf; Koutsoukos, Xenofon; Biswas, Gautam

2015-01-01

The classical decentralized detection problem of finding the optimal decision rules at the sensor and fusion center, as well as variants that introduce physical channel impairments have been studied extensively in the literature. The deployment of WSNs in decentralized detection applications brings new challenges to the field. Protocols for different communication layers have to be co-designed to optimize the detection performance. In this paper, we consider the communication network design problem for a tree WSN. We pursue a system-level approach where a complete model for the system is developed that captures the interactions between different layers, as well as different sensor quality measures. For network optimization, we propose a hierarchical optimization algorithm that lends itself to the tree structure, requiring only local network information. The proposed design approach shows superior performance over several contentionless and contention-based network design approaches. PMID:26307989

Optimal Sensor Location Design for Reliable Fault Detection in Presence of False Alarms

PubMed Central

Yang, Fan; Xiao, Deyun; Shah, Sirish L.

2009-01-01

To improve fault detection reliability, sensor location should be designed according to an optimization criterion with constraints imposed by issues of detectability and identifiability. Reliability requires the minimization of undetectability and false alarm probability due to random factors on sensor readings, which is not only related with sensor readings but also affected by fault propagation. This paper introduces the reliability criteria expression based on the missed/false alarm probability of each sensor and system topology or connectivity derived from the directed graph. The algorithm for the optimization problem is presented as a heuristic procedure. Finally, a boiler system is illustrated using the proposed method. PMID:22291524

Optimal Sensor Allocation for Fault Detection and Isolation

NASA Technical Reports Server (NTRS)

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

2004-01-01

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

Optimal Attack Strategies Subject to Detection Constraints Against Cyber-Physical Systems

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

Chen, Yuan; Kar, Soummya; Moura, Jose M. F.

This paper studies an attacker against a cyberphysical system (CPS) whose goal is to move the state of a CPS to a target state while ensuring that his or her probability of being detected does not exceed a given bound. The attacker’s probability of being detected is related to the nonnegative bias induced by his or her attack on the CPS’s detection statistic. We formulate a linear quadratic cost function that captures the attacker’s control goal and establish constraints on the induced bias that reflect the attacker’s detection-avoidance objectives. When the attacker is constrained to be detected at the false-alarmmore » rate of the detector, we show that the optimal attack strategy reduces to a linear feedback of the attacker’s state estimate. In the case that the attacker’s bias is upper bounded by a positive constant, we provide two algorithms – an optimal algorithm and a sub-optimal, less computationally intensive algorithm – to find suitable attack sequences. Lastly, we illustrate our attack strategies in numerical examples based on a remotely-controlled helicopter under attack.« less

Optimal Attack Strategies Subject to Detection Constraints Against Cyber-Physical Systems

DOE PAGES

Chen, Yuan; Kar, Soummya; Moura, Jose M. F.

2017-03-31

This paper studies an attacker against a cyberphysical system (CPS) whose goal is to move the state of a CPS to a target state while ensuring that his or her probability of being detected does not exceed a given bound. The attacker’s probability of being detected is related to the nonnegative bias induced by his or her attack on the CPS’s detection statistic. We formulate a linear quadratic cost function that captures the attacker’s control goal and establish constraints on the induced bias that reflect the attacker’s detection-avoidance objectives. When the attacker is constrained to be detected at the false-alarmmore » rate of the detector, we show that the optimal attack strategy reduces to a linear feedback of the attacker’s state estimate. In the case that the attacker’s bias is upper bounded by a positive constant, we provide two algorithms – an optimal algorithm and a sub-optimal, less computationally intensive algorithm – to find suitable attack sequences. Lastly, we illustrate our attack strategies in numerical examples based on a remotely-controlled helicopter under attack.« less

Upconverting nanoparticles for optimizing scintillator based detection systems

DOEpatents

Kross, Brian; McKisson, John E; McKisson, John; Weisenberger, Andrew; Xi, Wenze; Zom, Carl

2013-09-17

An upconverting device for a scintillation detection system is provided. The detection system comprises a scintillator material, a sensor, a light transmission path between the scintillator material and the sensor, and a plurality of upconverting nanoparticles particles positioned in the light transmission path.

Spectral anomaly methods for aerial detection using KUT nuisance rejection

NASA Astrophysics Data System (ADS)

Detwiler, R. S.; Pfund, D. M.; Myjak, M. J.; Kulisek, J. A.; Seifert, C. E.

2015-06-01

This work discusses the application and optimization of a spectral anomaly method for the real-time detection of gamma radiation sources from an aerial helicopter platform. Aerial detection presents several key challenges over ground-based detection. For one, larger and more rapid background fluctuations are typical due to higher speeds, larger field of view, and geographically induced background changes. As well, the possible large altitude or stand-off distance variations cause significant steps in background count rate as well as spectral changes due to increased gamma-ray scatter with detection at higher altitudes. The work here details the adaptation and optimization of the PNNL-developed algorithm Nuisance-Rejecting Spectral Comparison Ratios for Anomaly Detection (NSCRAD), a spectral anomaly method previously developed for ground-based applications, for an aerial platform. The algorithm has been optimized for two multi-detector systems; a NaI(Tl)-detector-based system and a CsI detector array. The optimization here details the adaptation of the spectral windows for a particular set of target sources to aerial detection and the tailoring for the specific detectors. As well, the methodology and results for background rejection methods optimized for the aerial gamma-ray detection using Potassium, Uranium and Thorium (KUT) nuisance rejection are shown. Results indicate that use of a realistic KUT nuisance rejection may eliminate metric rises due to background magnitude and spectral steps encountered in aerial detection due to altitude changes and geographically induced steps such as at land-water interfaces.

Adaptive algorithm of selecting optimal variant of errors detection system for digital means of automation facility of oil and gas complex

NASA Astrophysics Data System (ADS)

Poluyan, A. Y.; Fugarov, D. D.; Purchina, O. A.; Nesterchuk, V. V.; Smirnova, O. V.; Petrenkova, S. B.

2018-05-01

To date, the problems associated with the detection of errors in digital equipment (DE) systems for the automation of explosive objects of the oil and gas complex are extremely actual. Especially this problem is actual for facilities where a violation of the accuracy of the DE will inevitably lead to man-made disasters and essential material damage, at such facilities, the diagnostics of the accuracy of the DE operation is one of the main elements of the industrial safety management system. In the work, the solution of the problem of selecting the optimal variant of the errors detection system of errors detection by a validation criterion. Known methods for solving these problems have an exponential valuation of labor intensity. Thus, with a view to reduce time for solving the problem, a validation criterion is compiled as an adaptive bionic algorithm. Bionic algorithms (BA) have proven effective in solving optimization problems. The advantages of bionic search include adaptability, learning ability, parallelism, the ability to build hybrid systems based on combining. [1].

Parallel Molecular Distributed Detection With Brownian Motion.

PubMed

Rogers, Uri; Koh, Min-Sung

2016-12-01

This paper explores the in vivo distributed detection of an undesired biological agent's (BAs) biomarkers by a group of biological sized nanomachines in an aqueous medium under drift. The term distributed, indicates that the system information relative to the BAs presence is dispersed across the collection of nanomachines, where each nanomachine possesses limited communication, computation, and movement capabilities. Using Brownian motion with drift, a probabilistic detection and optimal data fusion framework, coined molecular distributed detection, will be introduced that combines theory from both molecular communication and distributed detection. Using the optimal data fusion framework as a guide, simulation indicates that a sub-optimal fusion method exists, allowing for a significant reduction in implementation complexity while retaining BA detection accuracy.

WE-EF-207-03: Design and Optimization of a CBCT Head Scanner for Detection of Acute Intracranial Hemorrhage

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

Xu, J; Sisniega, A; Zbijewski, W

Purpose: To design a dedicated x-ray cone-beam CT (CBCT) system suitable to deployment at the point-of-care and offering reliable detection of acute intracranial hemorrhage (ICH), traumatic brain injury (TBI), stroke, and other head and neck injuries. Methods: A comprehensive task-based image quality model was developed to guide system design and optimization of a prototype head scanner suitable to imaging of acute TBI and ICH. Previously reported models were expanded to include the effects of x-ray scatter correction necessary for detection of low contrast ICH and the contribution of bit depth (digitization noise) to imaging performance. Task-based detectablity index provided themore » objective function for optimization of system geometry, x-ray source, detector type, anti-scatter grid, and technique at 10–25 mGy dose. Optimal characteristics were experimentally validated using a custom head phantom with 50 HU contrast ICH inserts imaged on a CBCT imaging bench allowing variation of system geometry, focal spot size, detector, grid selection, and x-ray technique. Results: The model guided selection of system geometry with a nominal source-detector distance 1100 mm and optimal magnification of 1.50. Focal spot size ∼0.6 mm was sufficient for spatial resolution requirements in ICH detection. Imaging at 90 kVp yielded the best tradeoff between noise and contrast. The model provided quantitation of tradeoffs between flat-panel and CMOS detectors with respect to electronic noise, field of view, and readout speed required for imaging of ICH. An anti-scatter grid was shown to provide modest benefit in conjunction with post-acquisition scatter correction. Images of the head phantom demonstrate visualization of millimeter-scale simulated ICH. Conclusions: Performance consistent with acute TBI and ICH detection is feasible with model-based system design and robust artifact correction in a dedicated head CBCT system. Further improvements can be achieved with incorporation of model-based iterative reconstruction techniques also within the scope of the task-based optimization framework. David Foos and Xiaohui Wang are employees of Carestream Health.« less

Detection of proximal caries using digital radiographic systems with different resolutions.

PubMed

Nikneshan, Sima; Abbas, Fatemeh Mashhadi; Sabbagh, Sedigheh

2015-01-01

Dental radiography is an important tool for detection of caries and digital radiography is the latest advancement in this regard. Spatial resolution is a characteristic of digital receptors used for describing the quality of images. This study was aimed to compare the diagnostic accuracy of two digital radiographic systems with three different resolutions for detection of noncavitated proximal caries. Diagnostic accuracy. Seventy premolar teeth were mounted in 14 gypsum blocks. Digora; Optime and RVG Access were used for obtaining digital radiographs. Six observers evaluated the proximal surfaces in radiographs for each resolution in order to determine the depth of caries based on a 4-point scale. The teeth were then histologically sectioned, and the results of histologic analysis were considered as the gold standard. Data were entered using SPSS version 18 software and the Kruskal-Wallis test was used for data analysis. P <0.05 was considered as statistically significant. No significant difference was found between different resolutions for detection of proximal caries (P > 0.05). RVG access system had the highest specificity (87.7%) and Digora; Optime at high resolution had the lowest specificity (84.2%). Furthermore, Digora; Optime had higher sensitivity for detection of caries exceeding outer half of enamel. Judgment of oral radiologists for detection of the depth of caries had higher reliability than that of restorative dentistry specialists. The three resolutions of Digora; Optime and RVG access had similar accuracy in detection of noncavitated proximal caries.

Applications of Elpasolites as a Multimode Radiation Sensor

NASA Astrophysics Data System (ADS)

Guckes, Amber

This study consists of both computational and experimental investigations. The computational results enabled detector design selections and confirmed experimental results. The experimental results determined that the CLYC scintillation detector can be applied as a functional and field-deployable multimode radiation sensor. The computational study utilized MCNP6 code to investigate the response of CLYC to various incident radiations and to determine the feasibility of its application as a handheld multimode sensor and as a single-scintillator collimated directional detection system. These simulations include: • Characterization of the response of the CLYC scintillator to gamma-rays and neutrons; • Study of the isotopic enrichment of 7Li versus 6Li in the CLYC for optimal detection of both thermal neutrons and fast neutrons; • Analysis of collimator designs to determine the optimal collimator for the single CLYC sensor directional detection system to assay gamma rays and neutrons; Simulations of a handheld CLYC multimode sensor and a single CLYC scintillator collimated directional detection system with the optimized collimator to determine the feasibility of detecting nuclear materials that could be encountered during field operations. These nuclear materials include depleted uranium, natural uranium, low-enriched uranium, highly-enriched uranium, reactor-grade plutonium, and weapons-grade plutonium. The experimental study includes the design, construction, and testing of both a handheld CLYC multimode sensor and a single CLYC scintillator collimated directional detection system. Both were designed in the Inventor CAD software and based on results of the computational study to optimize its performance. The handheld CLYC multimode sensor is modular, scalable, low?power, and optimized for high count rates. Commercial?off?the?shelf components were used where possible in order to optimize size, increase robustness, and minimize cost. The handheld CLYC multimode sensor was successfully tested to confirm its ability for gamma-ray and neutron detection, and gamma?ray and neutron spectroscopy. The sensor utilizes wireless data transfer for possible radiation mapping and network?centric deployment. The handheld multimode sensor was tested by performing laboratory measurements with various gamma-ray sources and neutron sources. The single CLYC scintillator collimated directional detection system is portable, robust, and capable of source localization and identification. The collimator was designed based on the results of the computational study and is constructed with high density polyethylene (HDPE) and lead (Pb). The collimator design and construction allows for the directional detection of gamma rays and fast neutrons utilizing only one scintillator which is interchangeable. For this study, a CLYC-7 scintillator was used. The collimated directional detection system was tested by performing laboratory directional measurements with various gamma-ray sources, 252Cf and a 239PuBe source.

Optimization of single photon detection model based on GM-APD

NASA Astrophysics Data System (ADS)

Chen, Yu; Yang, Yi; Hao, Peiyu

2017-11-01

One hundred kilometers high precision laser ranging hopes the detector has very strong detection ability for very weak light. At present, Geiger-Mode of Avalanche Photodiode has more use. It has high sensitivity and high photoelectric conversion efficiency. Selecting and designing the detector parameters according to the system index is of great importance to the improvement of photon detection efficiency. Design optimization requires a good model. In this paper, we research the existing Poisson distribution model, and consider the important detector parameters of dark count rate, dead time, quantum efficiency and so on. We improve the optimization of detection model, select the appropriate parameters to achieve optimal photon detection efficiency. The simulation is carried out by using Matlab and compared with the actual test results. The rationality of the model is verified. It has certain reference value in engineering applications.

Investigating the detection of multi-homed devices independent of operating systems

DTIC Science & Technology

2017-09-01

timestamp data was used to estimate clock skews using linear regression and linear optimization methods. Analysis revealed that detection depends on...the consistency of the estimated clock skew. Through vertical testing, it was also shown that clock skew consistency depends on the installed...optimization methods. Analysis revealed that detection depends on the consistency of the estimated clock skew. Through vertical testing, it was also

DQE and system optimization for indirect-detection flat-panel imagers in diagnostic radiology

NASA Astrophysics Data System (ADS)

Siewerdsen, Jeffrey H.; Antonuk, Larry E.

1998-07-01

The performance of indirect-detection flat-panel imagers incorporating CsI:Tl x-ray converters is examined through calculation of the detective quantum efficiency (DQE) under conditions of chest radiography, fluoroscopy, and mammography. Calculations are based upon a cascaded systems model which has demonstrated excellent agreement with empirical signal, noise- power spectra, and DQE results. For each application, the DQE is calculated as a function of spatial-frequency and CsI:Tl thickness. A preliminary investigation into the optimization of flat-panel imaging systems is described, wherein the x-ray converter thickness which provides optimal DQE for a given imaging task is estimated. For each application, a number of example tasks involving detection of an object of variable size and contrast against a noisy background are considered. The method described is fairly general and can be extended to account for a variety of imaging tasks. For the specific examples considered, the preliminary results estimate optimal CsI:Tl thicknesses of approximately 450 micrometer (approximately 200 mg/cm2), approximately 320 micrometer (approximately 140 mg/cm2), and approximately 200 micrometer (approximately 90 mg/cm2) for chest radiography, fluoroscopy, and mammography, respectively. These results are expected to depend upon the imaging task as well as upon the quality of available CsI:Tl, and future improvements in scintillator fabrication could result in increased optimal thickness and DQE.

[Optimized application of nested PCR method for detection of malaria].

PubMed

Yao-Guang, Z; Li, J; Zhen-Yu, W; Li, C

2017-04-28

Objective To optimize the application of the nested PCR method for the detection of malaria according to the working practice, so as to improve the efficiency of malaria detection. Methods Premixing solution of PCR, internal primers for further amplification and new designed primers that aimed at two Plasmodium ovale subspecies were employed to optimize the reaction system, reaction condition and specific primers of P . ovale on basis of routine nested PCR. Then the specificity and the sensitivity of the optimized method were analyzed. The positive blood samples and examination samples of malaria were detected by the routine nested PCR and the optimized method simultaneously, and the detection results were compared and analyzed. Results The optimized method showed good specificity, and its sensitivity could reach the pg to fg level. The two methods were used to detect the same positive malarial blood samples simultaneously, the results indicated that the PCR products of the two methods had no significant difference, but the non-specific amplification reduced obviously and the detection rates of P . ovale subspecies improved, as well as the total specificity also increased through the use of the optimized method. The actual detection results of 111 cases of malarial blood samples showed that the sensitivity and specificity of the routine nested PCR were 94.57% and 86.96%, respectively, and those of the optimized method were both 93.48%, and there was no statistically significant difference between the two methods in the sensitivity ( P > 0.05), but there was a statistically significant difference between the two methods in the specificity ( P < 0.05). Conclusion The optimized PCR can improve the specificity without reducing the sensitivity on the basis of the routine nested PCR, it also can save the cost and increase the efficiency of malaria detection as less experiment links.

Active marks structure optimization for optical-electronic systems of spatial position control of industrial objects

NASA Astrophysics Data System (ADS)

Sycheva, Elena A.; Vasilev, Aleksandr S.; Lashmanov, Oleg U.; Korotaev, Valery V.

2017-06-01

The article is devoted to the optimization of optoelectronic systems of the spatial position of objects. Probabilistic characteristics of the detection of an active structured mark on a random noisy background are investigated. The developed computer model and the results of the study allow us to estimate the probabilistic characteristics of detection of a complex structured mark on a random gradient background, and estimate the error of spatial coordinates. The results of the study make it possible to improve the accuracy of measuring the coordinates of the object. Based on the research recommendations are given on the choice of parameters of the optimal mark structure for use in opticalelectronic systems for monitoring the spatial position of large-sized structures.

Integration of Microdialysis Sampling and Microchip Electrophoresis with Electrochemical Detection

PubMed Central

Mecker, Laura C.; Martin, R. Scott

2009-01-01

Here we describe the fabrication, optimization, and application of a microfluidic device that integrates microdialysis (MD) sampling, microchip electrophoresis (ME), and electrochemical detection (EC). The manner in which the chip is produced is reproducible and enables the fixed alignment of the MD/ME and ME/EC interfaces. Poly(dimethylsiloxane) (PDMS) -based valves were used for the discrete injection of sample from the hydrodynamic MD dialysate stream into a separation channel for analysis with ME. To enable the integration of ME with EC detection, a palladium decoupler was used to isolate the high voltages associated with electrophoresis from micron-sized carbon ink detection electrodes. Optimization of the ME/EC interface was needed to allow the use of biologically appropriate perfusate buffers containing high salt content. This optimization included changes in the fabrication procedure, increases in the decoupler surface area, and a programmed voltage shutoff. The ability of the MD/ME/EC system to sample a biological system was demonstrated by using a linear probe to monitor the stimulated release of dopamine from a confluent layer of PC 12 cells. To our knowledge, this is the first report of a microchip-based system that couples microdialysis sampling with microchip electrophoresis and electrochemical detection. PMID:19551945

Optimized Strategies for Detecting Extrasolar Space Weather

NASA Astrophysics Data System (ADS)

Hallinan, Gregg

2018-06-01

Fully understanding the implications of space weather for the young solar system, as well as the wider population of planet-hosting stars, requires remote sensing of space weather in other stellar systems. Solar coronal mass ejections can be accompanied by bright radio bursts at low frequencies (typically <100 MHz), that are produced as the resulting shockwave propagates through the corona and interplanetary medium.; searches for similar emissions are ongoing from nearby stellar systems. Exoplanets that encounter CMEs can increase in radio luminosity by orders of magnitude at kHz-MHz frequencies. A detection of this radio emission allows the direct measurement of the magnetic field strength of the planet, informing on whether the atmosphere of the planet can survive the intense magnetic activity of its host star. However, both stellar and planetary radio emission are highly variable and optimal strategies for detection of these emissions requires the capability to monitor 1000s of nearby stellar/planetary systems simultaneously. I will discuss optimized strategies for both ground and space-based experiments to take advantage of the highly variable nature of the radio emissions powered by extrasolar space weather to enable detection of stellar CMEs and planetary magnetospheres.

Study on optimization method of test conditions for fatigue crack detection using lock-in vibrothermography

NASA Astrophysics Data System (ADS)

Min, Qing-xu; Zhu, Jun-zhen; Feng, Fu-zhou; Xu, Chao; Sun, Ji-wei

2017-06-01

In this paper, the lock-in vibrothermography (LVT) is utilized for defect detection. Specifically, for a metal plate with an artificial fatigue crack, the temperature rise of the defective area is used for analyzing the influence of different test conditions, i.e. engagement force, excitation intensity, and modulated frequency. The multivariate nonlinear and logistic regression models are employed to estimate the POD (probability of detection) and POA (probability of alarm) of fatigue crack, respectively. The resulting optimal selection of test conditions is presented. The study aims to provide an optimized selection method of the test conditions in the vibrothermography system with the enhanced detection ability.

Power-limited low-thrust trajectory optimization with operation point detection

NASA Astrophysics Data System (ADS)

Chi, Zhemin; Li, Haiyang; Jiang, Fanghua; Li, Junfeng

2018-06-01

The power-limited solar electric propulsion system is considered more practical in mission design. An accurate mathematical model of the propulsion system, based on experimental data of the power generation system, is used in this paper. An indirect method is used to deal with the time-optimal and fuel-optimal control problems, in which the solar electric propulsion system is described using a finite number of operation points, which are characterized by different pairs of thruster input power. In order to guarantee the integral accuracy for the discrete power-limited problem, a power operation detection technique is embedded in the fourth-order Runge-Kutta algorithm with fixed step. Moreover, the logarithmic homotopy method and normalization technique are employed to overcome the difficulties caused by using indirect methods. Three numerical simulations with actual propulsion systems are given to substantiate the feasibility and efficiency of the proposed method.

Automatic threshold optimization in nonlinear energy operator based spike detection.

PubMed

Malik, Muhammad H; Saeed, Maryam; Kamboh, Awais M

2016-08-01

In neural spike sorting systems, the performance of the spike detector has to be maximized because it affects the performance of all subsequent blocks. Non-linear energy operator (NEO), is a popular spike detector due to its detection accuracy and its hardware friendly architecture. However, it involves a thresholding stage, whose value is usually approximated and is thus not optimal. This approximation deteriorates the performance in real-time systems where signal to noise ratio (SNR) estimation is a challenge, especially at lower SNRs. In this paper, we propose an automatic and robust threshold calculation method using an empirical gradient technique. The method is tested on two different datasets. The results show that our optimized threshold improves the detection accuracy in both high SNR and low SNR signals. Boxplots are presented that provide a statistical analysis of improvements in accuracy, for instance, the 75th percentile was at 98.7% and 93.5% for the optimized NEO threshold and traditional NEO threshold, respectively.

Influence of infectious disease seasonality on the performance of the outbreak detection algorithm in the China Infectious Disease Automated-alert and Response System

PubMed Central

Wang, Ruiping; Jiang, Yonggen; Guo, Xiaoqin; Wu, Yiling; Zhao, Genming

2017-01-01

Objective The Chinese Center for Disease Control and Prevention developed the China Infectious Disease Automated-alert and Response System (CIDARS) in 2008. The CIDARS can detect outbreak signals in a timely manner but generates many false-positive signals, especially for diseases with seasonality. We assessed the influence of seasonality on infectious disease outbreak detection performance. Methods Chickenpox surveillance data in Songjiang District, Shanghai were used. The optimized early alert thresholds for chickenpox were selected according to three algorithm evaluation indexes: sensitivity (Se), false alarm rate (FAR), and time to detection (TTD). Performance of selected proper thresholds was assessed by data external to the study period. Results The optimized early alert threshold for chickenpox during the epidemic season was the percentile P65, which demonstrated an Se of 93.33%, FAR of 0%, and TTD of 0 days. The optimized early alert threshold in the nonepidemic season was P50, demonstrating an Se of 100%, FAR of 18.94%, and TTD was 2.5 days. The performance evaluation demonstrated that the use of an optimized threshold adjusted for seasonality could reduce the FAR and shorten the TTD. Conclusions Selection of optimized early alert thresholds based on local infectious disease seasonality could improve the performance of the CIDARS. PMID:28728470

Influence of infectious disease seasonality on the performance of the outbreak detection algorithm in the China Infectious Disease Automated-alert and Response System.

PubMed

Wang, Ruiping; Jiang, Yonggen; Guo, Xiaoqin; Wu, Yiling; Zhao, Genming

2018-01-01

Objective The Chinese Center for Disease Control and Prevention developed the China Infectious Disease Automated-alert and Response System (CIDARS) in 2008. The CIDARS can detect outbreak signals in a timely manner but generates many false-positive signals, especially for diseases with seasonality. We assessed the influence of seasonality on infectious disease outbreak detection performance. Methods Chickenpox surveillance data in Songjiang District, Shanghai were used. The optimized early alert thresholds for chickenpox were selected according to three algorithm evaluation indexes: sensitivity (Se), false alarm rate (FAR), and time to detection (TTD). Performance of selected proper thresholds was assessed by data external to the study period. Results The optimized early alert threshold for chickenpox during the epidemic season was the percentile P65, which demonstrated an Se of 93.33%, FAR of 0%, and TTD of 0 days. The optimized early alert threshold in the nonepidemic season was P50, demonstrating an Se of 100%, FAR of 18.94%, and TTD was 2.5 days. The performance evaluation demonstrated that the use of an optimized threshold adjusted for seasonality could reduce the FAR and shorten the TTD. Conclusions Selection of optimized early alert thresholds based on local infectious disease seasonality could improve the performance of the CIDARS.

Development of a multispectral structured-illumination reflectance imaging (SIRI) system and its application to bruise detection of apples

USDA-ARS?s Scientific Manuscript database

Structured-illumination reflectance imaging (SIRI) is a new, promising imaging modality for enhancing quality detection of food. A liquid-crystal tunable filter (LCTF)-based multispectral SIRI system was developed and used for selecting optimal wavebands to detect bruising in apples. Immediately aft...

CFD modelling of sampling locations for early detection of spontaneous combustion in long-wall gob areas.

PubMed

Yuan, Liming; Smith, Alex C

In this study, computational fluid dynamics (CFD) modeling was conducted to optimize gas sampling locations for the early detection of spontaneous heating in longwall gob areas. Initial simulations were carried out to predict carbon monoxide (CO) concentrations at various regulators in the gob using a bleeder ventilation system. Measured CO concentration values at these regulators were then used to calibrate the CFD model. The calibrated CFD model was used to simulate CO concentrations at eight sampling locations in the gob using a bleederless ventilation system to determine the optimal sampling locations for early detection of spontaneous combustion.

Evaluation of load flow and grid expansion in a unit-commitment and expansion optimization model SciGRID International Conference on Power Grid Modelling

NASA Astrophysics Data System (ADS)

Senkpiel, Charlotte; Biener, Wolfgang; Shammugam, Shivenes; Längle, Sven

2018-02-01

Energy system models serve as a basis for long term system planning. Joint optimization of electricity generating technologies, storage systems and the electricity grid leads to lower total system cost compared to an approach in which the grid expansion follows a given technology portfolio and their distribution. Modelers often face the problem of finding a good tradeoff between computational time and the level of detail that can be modeled. This paper analyses the differences between a transport model and a DC load flow model to evaluate the validity of using a simple but faster transport model within the system optimization model in terms of system reliability. The main findings in this paper are that a higher regional resolution of a system leads to better results compared to an approach in which regions are clustered as more overloads can be detected. An aggregation of lines between two model regions compared to a line sharp representation has little influence on grid expansion within a system optimizer. In a DC load flow model overloads can be detected in a line sharp case, which is therefore preferred. Overall the regions that need to reinforce the grid are identified within the system optimizer. Finally the paper recommends the usage of a load-flow model to test the validity of the model results.

TU-EF-204-03: Task-Based KV and MAs Optimization for Radiation Dose Reduction in CT: From FBP to Statistical Model-Based Iterative Reconstruction (MBIR)

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

Gomez-Cardona, D; Li, K; Lubner, M G

Purpose: The introduction of the highly nonlinear MBIR algorithm to clinical CT systems has made CNR an invalid metric for kV optimization. The purpose of this work was to develop a task-based framework to unify kV and mAs optimization for both FBP- and MBIR-based CT systems. Methods: The kV-mAs optimization was formulated as a constrained minimization problem: to select kV and mAs to minimize dose under the constraint of maintaining the detection performance as clinically prescribed. To experimentally solve this optimization problem, exhaustive measurements of detectability index (d’) for a hepatic lesion detection task were performed at 15 different mAmore » levels and 4 kV levels using an anthropomorphic phantom. The measured d’ values were used to generate an iso-detectability map; similarly, dose levels recorded at different kV-mAs combinations were used to generate an iso-dose map. The iso-detectability map was overlaid on top of the iso-dose map so that for a prescribed detectability level d’, the optimal kV-mA can be determined from the crossing between the d’ contour and the dose contour that corresponds to the minimum dose. Results: Taking d’=16 as an example: the kV-mAs combinations on the measured iso-d’ line of MBIR are 80–150 (3.8), 100–140 (6.6), 120–150 (11.3), and 140–160 (17.2), where values in the parentheses are measured dose values. As a Result, the optimal kV was 80 and optimal mA was 150. In comparison, the optimal kV and mA for FBP were 100 and 500, which corresponded to a dose level of 24 mGy. Results of in vivo animal experiments were consistent with the phantom results. Conclusion: A new method to optimize kV and mAs selection has been developed. This method is applicable to both linear and nonlinear CT systems such as those using MBIR. Additional dose savings can be achieved by combining MBIR with this method. This work was partially supported by an NIH grant R01CA169331 and GE Healthcare. K. Li, D. Gomez-Cardona, M. G. Lubner: Nothing to disclose. P. J. Pickhardt: Co-founder, VirtuoCTC, LLC Stockholder, Cellectar Biosciences, Inc. G.-H. Chen: Research funded, GE Healthcare; Research funded, Siemens AX.« less

Quantifying Performance Bias in Label Fusion

DTIC Science & Technology

2012-08-21

detect ), may provide the end-user with the means to appropriately adjust the performance and optimal thresholds for performance by fusing legacy systems...boolean combination of classification systems in ROC space: An application to anomaly detection with HMMs. Pattern Recognition, 43(8), 2732-2752. 10...Shamsuddin, S. (2009). An overview of neural networks use in anomaly intrusion detection systems. Paper presented at the Research and Development (SCOReD

Development of a FI-HG-ICP-OES solid phase preconcentration system for inorganic selenium speciation in Argentinean beverages.

PubMed

Escudero, Luis A; Pacheco, Pablo H; Gasquez, José A; Salonia, José A

2015-02-15

A preconcentration system has been developed to determine inorganic selenium species. Selenium was retained by a column filled with polyvinyl chloride (PVC) with lanthanum hydroxide co-precipitation. Speciation was achieved by selective photoreduction previous Se preconcentration. The retention pH was optimized at 10.0. Two multivariate calibrations and a central composite design were employed for optimization of the system. Sample, reagents and acid flow rates are significant variables affecting the system. Employing HG-ICP-OES as detection, the optimized system reached a detection limit of 0.03μg/L, and an enhancement factor of 14875 (25 for preconcentration system, 595 for hydride generation). To verify the method' accuracy, two certified reference materials, BCR® 414 Plankton & IRMM-804 Rice Flour, were analysed. The system was applied to inorganic selenium speciation in several Argentinean beverages to estimate their selenium contribution to diet. Copyright © 2014 Elsevier Ltd. All rights reserved.

Detection of highly toxic elements (lead and chromium) in commercially available eyeliner (kohl) using laser induced break down spectroscopy

NASA Astrophysics Data System (ADS)

Gondal, M. A.; Dastageer, M. A.; Al-Adel, F. F.; Naqvi, A. A.; Habibullah, Y. B.

2015-12-01

A sensitive laser induced breakdown spectroscopic system was developed and optimized for using it as a sensor for the detection of trace levels of lead and chromium present in the cosmetic eyeliner (kohl) of different price ranges (brands) available in the local market. Kohl is widely used in developing countries for babies as well adults for beautification as well eyes protection. The atomic transition lines at 405.7 nm and 425.4 nm were used as the marker lines for the detection of lead and chromium respectively. The detection system was optimized by finding the appropriate gate delay between the laser excitation and the data acquisition system and also by achieving optically thin plasma near the target by establishing the local thermodynamic equilibrium condition. The detection system was calibrated for these two hazardous elements and the kohl samples under investigation showed 8-15 ppm by mass of lead and 4-9 ppm by mass of Chromium, which are higher than the safe permissible levels of these elements. The limits of detection of the LIBS system for lead and chromium were found to be 1 and 2 ppm respectively.

Optimization of medical imaging display systems: using the channelized Hotelling observer for detecting lung nodules: experimental study

NASA Astrophysics Data System (ADS)

Platisa, Ljiljana; Vansteenkiste, Ewout; Goossens, Bart; Marchessoux, Cédric; Kimpe, Tom; Philips, Wilfried

2009-02-01

Medical-imaging systems are designed to aid medical specialists in a specific task. Therefore, the physical parameters of a system need to optimize the task performance of a human observer. This requires measurements of human performance in a given task during the system optimization. Typically, psychophysical studies are conducted for this purpose. Numerical observer models have been successfully used to predict human performance in several detection tasks. Especially, the task of signal detection using a channelized Hotelling observer (CHO) in simulated images has been widely explored. However, there are few studies done for clinically acquired images that also contain anatomic noise. In this paper, we investigate the performance of a CHO in the task of detecting lung nodules in real radiographic images of the chest. To evaluate variability introduced by the limited available data, we employ a commonly used study of a multi-reader multi-case (MRMC) scenario. It accounts for both case and reader variability. Finally, we use the "oneshot" methods to estimate the MRMC variance of the area under the ROC curve (AUC). The obtained AUC compares well to those reported for human observer study on a similar data set. Furthermore, the "one-shot" analysis implies a fairly consistent performance of the CHO with the variance of AUC below 0.002. This indicates promising potential for numerical observers in optimization of medical imaging displays and encourages further investigation on the subject.

Intersection video detection field handbook : an update.

DOT National Transportation Integrated Search

2010-12-01

This handbook is intended to assist engineers and technicians with the design, layout, and : operation of a video imaging vehicle detection system (VIVDS). This assistance is provided in : three ways. First, the handbook identifies the optimal detect...

Optimal feedback control infinite dimensional parabolic evolution systems: Approximation techniques

NASA Technical Reports Server (NTRS)

Banks, H. T.; Wang, C.

1989-01-01

A general approximation framework is discussed for computation of optimal feedback controls in linear quadratic regular problems for nonautonomous parabolic distributed parameter systems. This is done in the context of a theoretical framework using general evolution systems in infinite dimensional Hilbert spaces. Conditions are discussed for preservation under approximation of stabilizability and detectability hypotheses on the infinite dimensional system. The special case of periodic systems is also treated.

Performance evaluation and optimization of multiband phase-modulated radio over IsOWC link with balanced coherent homodyne detection

NASA Astrophysics Data System (ADS)

Zong, Kang; Zhu, Jiang

2018-04-01

In this paper, we present a multiband phase-modulated (PM) radio over intersatellite optical wireless communication (IsOWC) link with balanced coherent homodyne detection. The proposed system can provide the transparent transport of multiband radio frequency (RF) signals with higher linearity and better receiver sensitivity than intensity modulated with direct detection (IM/DD) system. The expressions of RF gain, noise figure (NF) and third-order spurious-free dynamic range (SFDR) are derived considering the third-order intermodulation product and amplifier spontaneous emission (ASE) noise. The optimal power of local oscillator (LO) optical signal is also derived theoretically. Numerical results for RF gain, NF and third-order SFDR are given for demonstration. Results indicate that the gain of the optical preamplifier and the power of LO optical signal should be optimized to obtain the satisfactory performance.

Reduced electrical bandwidth receivers for direct detection 4-ary PPM optical communication intersatellite links

NASA Technical Reports Server (NTRS)

Davidson, Frederic M.; Sun, Xiaoli

1993-01-01

One of the major sources of noise in a direct detection optical communication receiver is the shot noise due to the quantum nature of the photodetector. The shot noise is signal dependent and is neither Gaussian nor wide sense stationary. When a photomultiplier tube (PMT) or an avalanche photodiode (APD) is used, there is also a multiplicative excess noise due to the randomness of the internal photodetector gain. Generally speaking, the radio frequency (RF) communication theory cannot be applied to direct detection optical communication systems because noise in RF communication systems is usually additive and Gaussian. A receiver structure which is mathematically optimal for signal dependent shot noise is derived. Several suboptimal receiver structures are discussed and compared with the optimal receiver. The objective is to find a receiver structure which is easy to implement and gives close to optimal performance.

Real-time optimizations for integrated smart network camera

NASA Astrophysics Data System (ADS)

Desurmont, Xavier; Lienard, Bruno; Meessen, Jerome; Delaigle, Jean-Francois

2005-02-01

We present an integrated real-time smart network camera. This system is composed of an image sensor, an embedded PC based electronic card for image processing and some network capabilities. The application detects events of interest in visual scenes, highlights alarms and computes statistics. The system also produces meta-data information that could be shared between other cameras in a network. We describe the requirements of such a system and then show how the design of the system is optimized to process and compress video in real-time. Indeed, typical video-surveillance algorithms as background differencing, tracking and event detection should be highly optimized and simplified to be used in this hardware. To have a good adequation between hardware and software in this light embedded system, the software management is written on top of the java based middle-ware specification established by the OSGi alliance. We can integrate easily software and hardware in complex environments thanks to the Java Real-Time specification for the virtual machine and some network and service oriented java specifications (like RMI and Jini). Finally, we will report some outcomes and typical case studies of such a camera like counter-flow detection.

Study on detection geometry and detector shielding for portable PGNAA system using PHITS

NASA Astrophysics Data System (ADS)

Ithnin, H.; Dahing, L. N. S.; Lip, N. M.; Rashid, I. Q. Abd; Mohamad, E. J.

2018-01-01

Prompt gamma-ray neutron activation analysis (PGNAA) measurements require efficient detectors for gamma-ray detection. Apart from experimental studies, the Monte Carlo (MC) method has become one of the most popular tools in detector studies. The absolute efficiency for a 2 × 2 inch cylindrical Sodium Iodide (NaI) detector has been modelled using the PHITS software and compared with previous studies in literature. In the present work, PHITS code is used for optimization of portable PGNAA system using the validated NaI detector. The detection geometry is optimized by moving the detector along the sample to find the highest intensity of the prompt gamma generated from the sample. Shielding material for the validated NaI detector is also studied to find the best option for the PGNAA system setup. The result shows the optimum distance for detector is on the surface of the sample and around 15 cm from the source. The results specify that this process can be followed to determine the best setup for PGNAA system for a different sample size and detector type. It can be concluded that data from PHITS code is a strong tool not only for efficiency studies but also for optimization of PGNAA system.

Analysis and design of a capsule landing system and surface vehicle control system for Mars exploration

NASA Technical Reports Server (NTRS)

Frederick, D. K.; Lashmet, P. K.; Sandor, G. N.; Shen, C. N.; Smith, E. V.; Yerazunis, S. W.

1973-01-01

Problems related to the design and control of a mobile planetary vehicle to implement a systematic plan for the exploration of Mars are reported. Problem areas include: vehicle configuration, control, dynamics, systems and propulsion; systems analysis, terrain modeling and path selection; and chemical analysis of specimens. These tasks are summarized: vehicle model design, mathematical model of vehicle dynamics, experimental vehicle dynamics, obstacle negotiation, electrochemical controls, remote control, collapsibility and deployment, construction of a wheel tester, wheel analysis, payload design, system design optimization, effect of design assumptions, accessory optimal design, on-board computer subsystem, laser range measurement, discrete obstacle detection, obstacle detection systems, terrain modeling, path selection system simulation and evaluation, gas chromatograph/mass spectrometer system concepts, and chromatograph model evaluation and improvement.

Stochastic optimization for the detection of changes in maternal heart rate kinetics during pregnancy

NASA Astrophysics Data System (ADS)

Zakynthinaki, M. S.; Barakat, R. O.; Cordente Martínez, C. A.; Sampedro Molinuevo, J.

2011-03-01

The stochastic optimization method ALOPEX IV has been successfully applied to the problem of detecting possible changes in the maternal heart rate kinetics during pregnancy. For this reason, maternal heart rate data were recorded before, during and after gestation, during sessions of exercises of constant mild intensity; ALOPEX IV stochastic optimization was used to calculate the parameter values that optimally fit a dynamical systems model to the experimental data. The results not only demonstrate the effectiveness of ALOPEX IV stochastic optimization, but also have important implications in the area of exercise physiology, as they reveal important changes in the maternal cardiovascular dynamics, as a result of pregnancy.

A systematic FPGA acceleration design for applications based on convolutional neural networks

NASA Astrophysics Data System (ADS)

Dong, Hao; Jiang, Li; Li, Tianjian; Liang, Xiaoyao

2018-04-01

Most FPGA accelerators for convolutional neural network are designed to optimize the inner acceleration and are ignored of the optimization for the data path between the inner accelerator and the outer system. This could lead to poor performance in applications like real time video object detection. We propose a brand new systematic FPFA acceleration design to solve this problem. This design takes the data path optimization between the inner accelerator and the outer system into consideration and optimizes the data path using techniques like hardware format transformation, frame compression. It also takes fixed-point, new pipeline technique to optimize the inner accelerator. All these make the final system's performance very good, reaching about 10 times the performance comparing with the original system.

Adaptive Integration and Optimization of Automated and Neural Processing Systems - Establishing Neural and Behavioral Benchmarks of Optimized Performance

DTIC Science & Technology

2012-07-01

detection only condition followed either face detection only or dual task, thus ensuring that participants were practiced in face detection before...1 ARMY RSCH LABORATORY – HRED RDRL HRM C A DAVISON 320 MANSCEN LOOP STE 115 FORT LEONARD WOOD MO 65473 2 ARMY RSCH LABORATORY...HRED RDRL HRM DI T DAVIS J HANSBERGER BLDG 5400 RM C242 REDSTONE ARSENAL AL 35898-7290 1 ARMY RSCH LABORATORY – HRED RDRL HRS

Optimization of a two-dimensional liquid chromatography-supercritical fluid chromatography-mass spectrometry (2D-LC-SFS-MS) system to assess "in-vivo" inter-conversion of chiral drug molecules.

PubMed

Goel, Meenakshi; Larson, Eli; Venkatramani, C J; Al-Sayah, Mohammad A

2018-05-01

Enantioselective analysis is an essential requirement during the pharmaceutical development of chiral drug molecules. In pre-clinical and clinical studies, the Food and Drug Administration (FDA) mandates the assessment of "in vivo" inter-conversion of chiral drugs to determine their physiological effects. In-vivo analysis of the active pharmaceutical ingredient (API) and its potential metabolites could be quite challenging due to their low abundance (ng/mL levels) and matrix interferences. Therefore, highly selective and sensitive analytical techniques are required to separate the API and its metabolites from the matrix components and one another. Additionally, for chiral APIs, further analytical separation is required to resolve the API and its potential metabolites from their corresponding enantiomers. In this work, we demonstrate the optimization of our previously designed two-dimensional liquid chromatography-supercritical fluid chromatography-mass spectrometry (2D-LC-SFC -MS) system to achieve 10 ng/mL detection limit [1]. The first LC dimension, used as a desalting step, could efficiently separate the API from its potential metabolites and matrix components. The API and its metabolites were then trapped/focused on small trapping columns and transferred onto the second SFC dimension for chiral separation. Detection can be achieved by ultra-violet (UV) or MS detection. Different system parameters such as column dimensions, transfer volumes, trapping column stationary phase, system tubing internal diameter (i.d.), and detection techniques, were optimized to enhance the sensitivity of the 2D-LC-SFC-MS system. The limit of detection was determined to be 10 ng/mL. An application is described where a mouse hepatocyte treated sample was analyzed using the optimized 2D-LC-SFC-MS system with successful assessment of the ratio of API to its metabolite (1D-LC), as well as the corresponding enantiomeric excess values (% e.e.) of each (2D-SFC). Copyright © 2018 Elsevier B.V. All rights reserved.

An improved NSGA - II algorithm for mixed model assembly line balancing

NASA Astrophysics Data System (ADS)

Wu, Yongming; Xu, Yanxia; Luo, Lifei; Zhang, Han; Zhao, Xudong

2018-05-01

Aiming at the problems of assembly line balancing and path optimization for material vehicles in mixed model manufacturing system, a multi-objective mixed model assembly line (MMAL), which is based on optimization objectives, influencing factors and constraints, is established. According to the specific situation, an improved NSGA-II algorithm based on ecological evolution strategy is designed. An environment self-detecting operator, which is used to detect whether the environment changes, is adopted in the algorithm. Finally, the effectiveness of proposed model and algorithm is verified by examples in a concrete mixing system.

Multiband phase-modulated radio over IsOWC link with balanced coherent homodyne detection

NASA Astrophysics Data System (ADS)

Zong, Kang; Zhu, Jiang

2017-11-01

In this paper, we present a multiband phase-modulated radio over intersatellite optical wireless communication (IsOWC) link with balanced coherent homodyne detection. The proposed system can provide high linearity for transparent transport of multiband radio frequency (RF) signals and better receiver sensitivity than intensity modulated with direct detection (IM/DD) system. The exact analytical expression of signal to noise and distortion ratio (SNDR) is derived considering the third-order intermodulation product and amplifier spontaneous emission (ASE) noise. Numerical results of SNDR with various number of subchannels and modulation index are given. Results indicate that the optimal modulation index exists to maximize the SNDR. With the same system parameters, the value of the optimal modulation index will decrease with the increase of number of subchannels.

GPU based cloud system for high-performance arrhythmia detection with parallel k-NN algorithm.

PubMed

Tae Joon Jun; Hyun Ji Park; Hyuk Yoo; Young-Hak Kim; Daeyoung Kim

2016-08-01

In this paper, we propose an GPU based Cloud system for high-performance arrhythmia detection. Pan-Tompkins algorithm is used for QRS detection and we optimized beat classification algorithm with K-Nearest Neighbor (K-NN). To support high performance beat classification on the system, we parallelized beat classification algorithm with CUDA to execute the algorithm on virtualized GPU devices on the Cloud system. MIT-BIH Arrhythmia database is used for validation of the algorithm. The system achieved about 93.5% of detection rate which is comparable to previous researches while our algorithm shows 2.5 times faster execution time compared to CPU only detection algorithm.

Smart LED lighting for major reductions in power and energy use for plant lighting in space

NASA Astrophysics Data System (ADS)

Poulet, Lucie

Launching or resupplying food, oxygen, and water into space for long-duration, crewed missions to distant destinations, such as Mars, is currently impossible. Bioregenerative life-support systems under development worldwide involving photoautotrophic organisms offer a solution to the food dilemma. However, using traditional Earth-based lighting methods, growth of food crops consumes copious energy, and since sunlight will not always be available at different space destinations, efficient electric lighting solutions are badly needed to reduce the Equivalent System Mass (ESM) of life-support infrastructure to be launched and transported to future space destinations with sustainable human habitats. The scope of the present study was to demonstrate that using LEDs coupled to plant detection, and optimizing spectral and irradiance parameters of LED light, the model crop lettuce (Lactuca sativa L. cv. Waldmann's Green) can be grown with significantly lower electrical energy for plant lighting than using traditional lighting sources. Initial experiments aimed at adapting and troubleshooting a first-generation "smart" plant-detection system coupled to LED arrays resulted in optimizing the detection process for plant position and size to the limits of its current design. Lettuce crops were grown hydroponically in a growth chamber, where temperature, relative humidity, and CO2 level are controlled. Optimal irradiance and red/blue ratio of LED lighting were determined for plant growth during both lag and exponential phases of crop growth. Under optimizing conditions, the efficiency of the automatic detection system was integrated with LED switching and compared to a system in which all LEDs were energized throughout a crop-production cycle. At the end of each cropping cycle, plant fresh and dry weights and leaf area were measured and correlated with the amount of electrical energy (kWh) consumed. Preliminary results indicated that lettuce plants grown under optimizing conditions with red and blue LED lighting required 12 times less energy than with a traditional high-intensity discharge lighting system. This study paves the way for refinement of the smart lighting system and further, major reductions in ESM for space life-support systems and for ground-based controlled-environment agriculture. Project supported by NASA grant number NNX09AL99G.

The disagreement between the ideal observer and human observers in hardware and software imaging system optimization: theoretical explanations and evidence

NASA Astrophysics Data System (ADS)

He, Xin

2017-03-01

The ideal observer is widely used in imaging system optimization. One practical question remains open: do the ideal and human observers have the same preference in system optimization and evaluation? Based on the ideal observer's mathematical properties proposed by Barrett et. al. and the empirical properties of human observers investigated by Myers et. al., I attempt to pursue the general rules regarding the applicability of the ideal observer in system optimization. Particularly, in software optimization, the ideal observer pursues data conservation while humans pursue data presentation or perception. In hardware optimization, the ideal observer pursues a system with the maximum total information, while humans pursue a system with the maximum selected (e.g., certain frequency bands) information. These different objectives may result in different system optimizations between human and the ideal observers. Thus, an ideal observer optimized system is not necessarily optimal for humans. I cite empirical evidence in search and detection tasks, in hardware and software evaluation, in X-ray CT, pinhole imaging, as well as emission computed tomography to corroborate the claims. (Disclaimer: the views expressed in this work do not necessarily represent those of the FDA)

Experimental task-based optimization of a four-camera variable-pinhole small-animal SPECT system

NASA Astrophysics Data System (ADS)

Hesterman, Jacob Y.; Kupinski, Matthew A.; Furenlid, Lars R.; Wilson, Donald W.

2005-04-01

We have previously utilized lumpy object models and simulated imaging systems in conjunction with the ideal observer to compute figures of merit for hardware optimization. In this paper, we describe the development of methods and phantoms necessary to validate or experimentally carry out these optimizations. Our study was conducted on a four-camera small-animal SPECT system that employs interchangeable pinhole plates to operate under a variety of pinhole configurations and magnifications (representing optimizable system parameters). We developed a small-animal phantom capable of producing random backgrounds for each image sequence. The task chosen for the study was the detection of a 2mm diameter sphere within the phantom-generated random background. A total of 138 projection images were used, half of which included the signal. As our observer, we employed the channelized Hotelling observer (CHO) with Laguerre-Gauss channels. The signal-to-noise (SNR) of this observer was used to compare different system configurations. Results indicate agreement between experimental and simulated data with higher detectability rates found for multiple-camera, multiple-pinhole, and high-magnification systems, although it was found that mixtures of magnifications often outperform systems employing a single magnification. This work will serve as a basis for future studies pertaining to system hardware optimization.

Control optimization, stabilization and computer algorithms for aircraft applications

NASA Technical Reports Server (NTRS)

1975-01-01

Research related to reliable aircraft design is summarized. Topics discussed include systems reliability optimization, failure detection algorithms, analysis of nonlinear filters, design of compensators incorporating time delays, digital compensator design, estimation for systems with echoes, low-order compensator design, descent-phase controller for 4-D navigation, infinite dimensional mathematical programming problems and optimal control problems with constraints, robust compensator design, numerical methods for the Lyapunov equations, and perturbation methods in linear filtering and control.

SNM detection with an optimized water Cherenkov neutron detector

NASA Astrophysics Data System (ADS)

Dazeley, S.; Sweany, M.; Bernstein, A.

2012-11-01

Special Nuclear Material (SNM) can either spontaneously fission or be induced to do so: either case results in neutron emission. For this reason, neutron detection performs a crucial role in the functionality of Radiation Portal Monitoring (RPM) devices. Since neutrons are highly penetrating and difficult to shield, they could potentially be detected escaping even a well-shielded cargo container. If the shielding were sophisticated, detecting escaping neutrons would require a highly efficient detector with close to full solid angle coverage. In 2008, we reported the successful detection of neutrons with a 250 liter (l) gadolinium doped water Cherenkov prototype [1]—a technology that could potentially be employed cost effectively with full solid angle coverage. More recently we have built and tested both 1-kl and 3.5-kl versions [2], demonstrating that very large, cost effective, non-flammable and environmentally benign neutron detectors can be operated efficiently without being overwhelmed by background. In this paper, we present a new design for a modular system of water-based neutron detectors that could be deployed as a real RPM. The modules contain a number of optimizations that have not previously been combined within a single system. We present simulations of the new system, based on the performance of our previous detectors. Our simulations indicate that an optimized system such as is presented here could achieve SNM sensitivity competitive with a large 3He-based system. Moreover, the realization of large, cost effective neutron detectors could, for the first time, enable the detection of multiple neutrons per fission from within a large object such as a cargo container. Such a signal would provide a robust indication of the presence of fissioning material, reducing the frequency of false alarms while increasing sensitivity.

SNM Detection with an Optimized Water Cherenkov Neutron Detector

DOE PAGES

Dazeley, S.; Sweany, M.; Bernstein, A.

2012-07-23

Special Nuclear Material (SNM) can either spontaneously fission or be induced to do so: either case results in neutron emission. For this reason, neutron detection performs a crucial role in the functionality of Radiation Portal Monitoring (RPM) devices. Since neutrons are highly penetrating and difficult to shield, they could potentially be detected escaping even a well-shielded cargo container. If the shielding were sophisticated, detecting escaping neutrons would require a highly efficient detector with close to full solid angle coverage. In 2008, we reported the successful detection of neutrons with a 250 liter (l) gadolinium doped water Cherenkov prototype—a technology thatmore » could potentially be employed cost effectively with full solid angle coverage. More recently we have built and tested both 1-kl and 3.5-kl versions, demonstrating that very large, cost effective, non-flammable and environmentally benign neutron detectors can be operated efficiently without being overwhelmed by background. In our paper, we present a new design for a modular system of water-based neutron detectors that could be deployed as a real RPM. The modules contain a number of optimizations that have not previously been combined within a single system. We present simulations of the new system, based on the performance of our previous detectors. These simulations indicate that an optimized system such as is presented here could achieve SNM sensitivity competitive with a large 3He-based system. Moreover, the realization of large, cost effective neutron detectors could, for the first time, enable the detection of multiple neutrons per fission from within a large object such as a cargo container. Such a signal would provide a robust indication of the presence of fissioning material, reducing the frequency of false alarms while increasing sensitivity.« less

A hybrid nonlinear programming method for design optimization

NASA Technical Reports Server (NTRS)

Rajan, S. D.

1986-01-01

Solutions to engineering design problems formulated as nonlinear programming (NLP) problems usually require the use of more than one optimization technique. Moreover, the interaction between the user (analysis/synthesis) program and the NLP system can lead to interface, scaling, or convergence problems. An NLP solution system is presented that seeks to solve these problems by providing a programming system to ease the user-system interface. A simple set of rules is used to select an optimization technique or to switch from one technique to another in an attempt to detect, diagnose, and solve some potential problems. Numerical examples involving finite element based optimal design of space trusses and rotor bearing systems are used to illustrate the applicability of the proposed methodology.

A State-Space Approach to Optimal Level-Crossing Prediction for Linear Gaussian Processes

NASA Technical Reports Server (NTRS)

Martin, Rodney Alexander

2009-01-01

In many complex engineered systems, the ability to give an alarm prior to impending critical events is of great importance. These critical events may have varying degrees of severity, and in fact they may occur during normal system operation. In this article, we investigate approximations to theoretically optimal methods of designing alarm systems for the prediction of level-crossings by a zero-mean stationary linear dynamic system driven by Gaussian noise. An optimal alarm system is designed to elicit the fewest false alarms for a fixed detection probability. This work introduces the use of Kalman filtering in tandem with the optimal level-crossing problem. It is shown that there is a negligible loss in overall accuracy when using approximations to the theoretically optimal predictor, at the advantage of greatly reduced computational complexity. I

Analysis and design of a capsule landing system and surface vehicle control system for Mars exporation

NASA Technical Reports Server (NTRS)

Frederick, D. K.; Lashmet, P. K.; Sandor, G. N.; Shen, C. N.; Smith, E. J.; Yerazunis, S. W.

1972-01-01

The problems related to the design and control of a mobile planetary vehicle to implement a systematic plan for the exploration of Mars were investigated. Problem areas receiving attention include: vehicle configuration, control, dynamics, systems and propulsion; systems analysis; navigation, terrain modeling and path selection; and chemical analysis of specimens. The following specific tasks were studied: vehicle model design, mathematical modeling of dynamic vehicle, experimental vehicle dynamics, obstacle negotiation, electromechanical controls, collapsibility and deployment, construction of a wheel tester, wheel analysis, payload design, system design optimization, effect of design assumptions, accessory optimal design, on-board computer subsystem, laser range measurement, discrete obstacle detection, obstacle detection systems, terrain modeling, path selection system simulation and evaluation, gas chromatograph/mass spectrometer system concepts, chromatograph model evaluation and improvement and transport parameter evaluation.

Analysis and design of a capsule landing system and surface vehicle control system for Mars exploration

NASA Technical Reports Server (NTRS)

Frederick, D. K.; Lashmet, P. K.; Sandor, G. N.; Shen, C. N.; Smith, E. J.; Yerazunis, S. W.

1972-01-01

Investigation of problems related to the design and control of a mobile planetary vehicle to implement a systematic plan for the exploration of Mars has been undertaken. Problem areas receiving attention include: vehicle configuration, control, dynamics, systems and propulsion; systems analysis; terrain modeling and path selection; and chemical analysis of specimens. The following specific tasks have been under study: vehicle model design, mathematical modeling of a dynamic vehicle, experimental vehicle dynamics, obstacle negotiation, electromechanical controls, collapsibility and deployment, construction of a wheel tester, wheel analysis, payload design, system design optimization, effect of design assumptions, accessory optimal design, on-board computer sybsystem, laser range measurement, discrete obstacle detection, obstacle detection systems, terrain modeling, path selection system simulation and evaluation, gas chromatograph/mass spectrometer system concepts, chromatograph model evaluation and improvement.

Design and characterization of an optimized simultaneous color and near-infrared fluorescence rigid endoscopic imaging system

NASA Astrophysics Data System (ADS)

Venugopal, Vivek; Park, Minho; Ashitate, Yoshitomo; Neacsu, Florin; Kettenring, Frank; Frangioni, John V.; Gangadharan, Sidhu P.; Gioux, Sylvain

2013-12-01

We report the design, characterization, and validation of an optimized simultaneous color and near-infrared (NIR) fluorescence rigid endoscopic imaging system for minimally invasive surgery. This system is optimized for illumination and collection of NIR wavelengths allowing the simultaneous acquisition of both color and NIR fluorescence at frame rates higher than 6.8 fps with high sensitivity. The system employs a custom 10-mm diameter rigid endoscope optimized for NIR transmission. A dual-channel light source compatible with the constraints of an endoscope was built and includes a plasma source for white light illumination and NIR laser diodes for fluorescence excitation. A prism-based 2-CCD camera was customized for simultaneous color and NIR detection with a highly efficient filtration scheme for fluorescence imaging of both 700- and 800-nm emission dyes. The performance characterization studies indicate that the endoscope can efficiently detect fluorescence signal from both indocyanine green and methylene blue in dimethyl sulfoxide at the concentrations of 100 to 185 nM depending on the background optical properties. Finally, we performed the validation of this imaging system in vivo during a minimally invasive procedure for thoracic sentinel lymph node mapping in a porcine model.

Optimization of an Optical Inspection System Based on the Taguchi Method for Quantitative Analysis of Point-of-Care Testing

PubMed Central

Yeh, Chia-Hsien; Zhao, Zi-Qi; Shen, Pi-Lan; Lin, Yu-Cheng

2014-01-01

This study presents an optical inspection system for detecting a commercial point-of-care testing product and a new detection model covering from qualitative to quantitative analysis. Human chorionic gonadotropin (hCG) strips (cut-off value of the hCG commercial product is 25 mIU/mL) were the detection target in our study. We used a complementary metal-oxide semiconductor (CMOS) sensor to detect the colors of the test line and control line in the specific strips and to reduce the observation errors by the naked eye. To achieve better linearity between the grayscale and the concentration, and to decrease the standard deviation (increase the signal to noise ratio, S/N), the Taguchi method was used to find the optimal parameters for the optical inspection system. The pregnancy test used the principles of the lateral flow immunoassay, and the colors of the test and control line were caused by the gold nanoparticles. Because of the sandwich immunoassay model, the color of the gold nanoparticles in the test line was darkened by increasing the hCG concentration. As the results reveal, the S/N increased from 43.48 dB to 53.38 dB, and the hCG concentration detection increased from 6.25 to 50 mIU/mL with a standard deviation of less than 10%. With the optimal parameters to decrease the detection limit and to increase the linearity determined by the Taguchi method, the optical inspection system can be applied to various commercial rapid tests for the detection of ketamine, troponin I, and fatty acid binding protein (FABP). PMID:25256108

Least-mean-square spatial filter for IR sensors.

PubMed

Takken, E H; Friedman, D; Milton, A F; Nitzberg, R

1979-12-15

A new least-mean-square filter is defined for signal-detection problems. The technique is proposed for scanning IR surveillance systems operating in poorly characterized but primarily low-frequency clutter interference. Near-optimal detection of point-source targets is predicted both for continuous-time and sampled-data systems.

Combined optimization of image-gathering and image-processing systems for scene feature detection

NASA Technical Reports Server (NTRS)

Halyo, Nesim; Arduini, Robert F.; Samms, Richard W.

1987-01-01

The relationship between the image gathering and image processing systems for minimum mean squared error estimation of scene characteristics is investigated. A stochastic optimization problem is formulated where the objective is to determine a spatial characteristic of the scene rather than a feature of the already blurred, sampled and noisy image data. An analytical solution for the optimal characteristic image processor is developed. The Wiener filter for the sampled image case is obtained as a special case, where the desired characteristic is scene restoration. Optimal edge detection is investigated using the Laplacian operator x G as the desired characteristic, where G is a two dimensional Gaussian distribution function. It is shown that the optimal edge detector compensates for the blurring introduced by the image gathering optics, and notably, that it is not circularly symmetric. The lack of circular symmetry is largely due to the geometric effects of the sampling lattice used in image acquisition. The optimal image gathering optical transfer function is also investigated and the results of a sensitivity analysis are shown.

Detection of Oil Chestnuts Infected by Blue Mold Using Near-Infrared Hyperspectral Imaging Combined with Artificial Neural Networks.

PubMed

Feng, Lei; Zhu, Susu; Lin, Fucheng; Su, Zhenzhu; Yuan, Kangpei; Zhao, Yiying; He, Yong; Zhang, Chu

2018-06-15

Mildew damage is a major reason for chestnut poor quality and yield loss. In this study, a near-infrared hyperspectral imaging system in the 874⁻1734 nm spectral range was applied to detect the mildew damage to chestnuts caused by blue mold. Principal component analysis (PCA) scored images were firstly employed to qualitatively and intuitively distinguish moldy chestnuts from healthy chestnuts. Spectral data were extracted from the hyperspectral images. A successive projections algorithm (SPA) was used to select 12 optimal wavelengths. Artificial neural networks, including back propagation neural network (BPNN), evolutionary neural network (ENN), extreme learning machine (ELM), general regression neural network (GRNN) and radial basis neural network (RBNN) were used to build models using the full spectra and optimal wavelengths to distinguish moldy chestnuts. BPNN and ENN models using full spectra and optimal wavelengths obtained satisfactory performances, with classification accuracies all surpassing 99%. The results indicate the potential for the rapid and non-destructive detection of moldy chestnuts by hyperspectral imaging, which would help to develop online detection system for healthy and blue mold infected chestnuts.

Optimization of Breast Tomosynthesis Imaging Systems for Computer-Aided Detection

DTIC Science & Technology

2011-05-01

R. Saunders, E. Samei, C. Badea, H. Yuan, K. Ghaghada, Y. Qi, L. Hedlund, and S. Mukundan, “Optimization of dual energy contrast enhanced breast...14 4 1 Introduction This is the final report for this body of research. Screen-film mammography and...digital mammography have been used for over 30 years in the early detection of cancer. The combination of screening and adjuvant therapies have led to

Optimal sampling strategies for detecting zoonotic disease epidemics.

PubMed

Ferguson, Jake M; Langebrake, Jessica B; Cannataro, Vincent L; Garcia, Andres J; Hamman, Elizabeth A; Martcheva, Maia; Osenberg, Craig W

2014-06-01

The early detection of disease epidemics reduces the chance of successful introductions into new locales, minimizes the number of infections, and reduces the financial impact. We develop a framework to determine the optimal sampling strategy for disease detection in zoonotic host-vector epidemiological systems when a disease goes from below detectable levels to an epidemic. We find that if the time of disease introduction is known then the optimal sampling strategy can switch abruptly between sampling only from the vector population to sampling only from the host population. We also construct time-independent optimal sampling strategies when conducting periodic sampling that can involve sampling both the host and the vector populations simultaneously. Both time-dependent and -independent solutions can be useful for sampling design, depending on whether the time of introduction of the disease is known or not. We illustrate the approach with West Nile virus, a globally-spreading zoonotic arbovirus. Though our analytical results are based on a linearization of the dynamical systems, the sampling rules appear robust over a wide range of parameter space when compared to nonlinear simulation models. Our results suggest some simple rules that can be used by practitioners when developing surveillance programs. These rules require knowledge of transition rates between epidemiological compartments, which population was initially infected, and of the cost per sample for serological tests.

Configuration of electro-optic fire source detection system

NASA Astrophysics Data System (ADS)

Fabian, Ram Z.; Steiner, Zeev; Hofman, Nir

2007-04-01

The recent fighting activities in various parts of the world have highlighted the need for accurate fire source detection on one hand and fast "sensor to shooter cycle" capabilities on the other. Both needs can be met by the SPOTLITE system which dramatically enhances the capability to rapidly engage hostile fire source with a minimum of casualties to friendly force and to innocent bystanders. Modular system design enable to meet each customer specific requirements and enable excellent future growth and upgrade potential. The design and built of a fire source detection system is governed by sets of requirements issued by the operators. This can be translated into the following design criteria: I) Long range, fast and accurate fire source detection capability. II) Different threat detection and classification capability. III) Threat investigation capability. IV) Fire source data distribution capability (Location, direction, video image, voice). V) Men portability. ) In order to meet these design criteria, an optimized concept was presented and exercised for the SPOTLITE system. Three major modular components were defined: I) Electro Optical Unit -Including FLIR camera, CCD camera, Laser Range Finder and Marker II) Electronic Unit -including system computer and electronic. III) Controller Station Unit - Including the HMI of the system. This article discusses the system's components definition and optimization processes, and also show how SPOTLITE designers successfully managed to introduce excellent solutions for other system parameters.

Medical diagnosis using adaptive perceptive particle swarm optimization and its hardware realization using field programmable gate array.

PubMed

Chowdhury, Shubhajit Roy; Chakrabarti, Dipankar; Hiranmay, Saha

2009-12-01

The paper proposes to develop a field programmable gate array (FPGA) based low cost, low power and high speed novel diagnostic system that can detect in absence of the physician the approaching critical condition of a patient at an early stage and is thus suitable for diagnosis of patients in the rural areas of developing countries where availability of physicians and availability of power is really scarce. The diagnostic system could be installed in health care centres of rural areas where patients can register themselves for periodic diagnoses and thereby detect potential health hazards at an early stage. Multiple pathophysiological parameters with different weights are involved in diagnosing a particular disease. A novel variation of particle swarm optimization called as adaptive perceptive particle swarm optimization has been proposed to determine the optimal weights of these pathophysiological parameters for a more accurate diagnosis. The FPGA based smart system has been applied for early detection of renal criticality of patients. For renal diagnosis, body mass index, glucose, urea, creatinine, systolic and diastolic blood pressures have been considered as pathophysiological parameters. The detection of approaching critical condition of a patient by the instrument has also been validated with the standard Cockford Gault Equation to verify whether the patient is really approaching a critical condition or not. Using Bayesian analysis on the population of 80 patients under study an accuracy of up to 97.5% in renal diagnosis has been obtained.

Instrumentation and optimization of intra-cavity fiber laser gas absorption sensing system

NASA Astrophysics Data System (ADS)

Liu, Kun; Liu, Tiegen; Jiang, Junfeng; Liang, Xiao; Zhang, Yimo

2011-11-01

Detection of pollution, inflammable, explosive gases such as methane, acetylene, carbon monoxide and so on is very important for many areas, such as environmental, mining and petrochemical industry. Intra-cavity gas absorption sensing technique (ICGAST) based on Erbium-doped fiber ring laser (EDFRL) is one of novel methods for trace gas with higher precision. It has attracted considerable attention, and many research institutes focus on it. Instrumentation and optimization of ICGAST was reported in this paper. The system consists of five parts, which are variable gain module, intelligent frequency-selection module, gas cell, DAQ module and computer respectively. Variable gain module and intelligent frequency-selection module are combined to establish the intra-cavity of the ring laser. Gas cell is used as gas sensor. DAQ module is used to realize data acquisition synchronously. And gas demodulation is finished in the computer finally. The system was optimized by adjusting the sequence of the components. Take experimental simulation as an example, the absorptance of gas was increased five times after optimization, and the sensitivity enhancement factor can reach more than twenty. By using Fabry-Perot (F-P) etalon, the absorption wavelength of the detected gas can be obtained, with error less than 20 pm. The spectra of the detected gas can be swept continuously to obtain several absorption lines in one loop. The coefficient of variation (CV) was used to show the repeatability of gas concentration detection. And results of CV value can be less than 0.014.

Practical scheme for optimal measurement in quantum interferometric devices

NASA Astrophysics Data System (ADS)

Takeoka, Masahiro; Ban, Masashi; Sasaki, Masahide

2003-06-01

We apply a Kennedy-type detection scheme, which was originally proposed for a binary communications system, to interferometric sensing devices. We show that the minimum detectable perturbation of the proposed system reaches the ultimate precision bound which is predicted by quantum Neyman-Pearson hypothesis testing. To provide concrete examples, we apply our interferometric scheme to phase shift detection by using coherent and squeezed probe fields.

Finite-Time Performance of Local Search Algorithms: Theory and Application

DTIC Science & Technology

2010-06-10

security devices deployed at airport security checkpoints are used to detect prohibited items (e.g., guns, knives, explosives). Each security device...security devices are deployed, the practical issue of determining how to optimally use them can be difficult. For an airport security system design...checked baggage), explosive detection systems (designed to detect explosives in checked baggage), and detailed hand search by an airport security official

Simple summation rule for optimal fixation selection in visual search.

PubMed

Najemnik, Jiri; Geisler, Wilson S

2009-06-01

When searching for a known target in a natural texture, practiced humans achieve near-optimal performance compared to a Bayesian ideal searcher constrained with the human map of target detectability across the visual field [Najemnik, J., & Geisler, W. S. (2005). Optimal eye movement strategies in visual search. Nature, 434, 387-391]. To do so, humans must be good at choosing where to fixate during the search [Najemnik, J., & Geisler, W.S. (2008). Eye movement statistics in humans are consistent with an optimal strategy. Journal of Vision, 8(3), 1-14. 4]; however, it seems unlikely that a biological nervous system would implement the computations for the Bayesian ideal fixation selection because of their complexity. Here we derive and test a simple heuristic for optimal fixation selection that appears to be a much better candidate for implementation within a biological nervous system. Specifically, we show that the near-optimal fixation location is the maximum of the current posterior probability distribution for target location after the distribution is filtered by (convolved with) the square of the retinotopic target detectability map. We term the model that uses this strategy the entropy limit minimization (ELM) searcher. We show that when constrained with human-like retinotopic map of target detectability and human search error rates, the ELM searcher performs as well as the Bayesian ideal searcher, and produces fixation statistics similar to human.

Detecting recurrence domains of dynamical systems by symbolic dynamics.

PubMed

beim Graben, Peter; Hutt, Axel

2013-04-12

We propose an algorithm for the detection of recurrence domains of complex dynamical systems from time series. Our approach exploits the characteristic checkerboard texture of recurrence domains exhibited in recurrence plots. In phase space, recurrence plots yield intersecting balls around sampling points that could be merged into cells of a phase space partition. We construct this partition by a rewriting grammar applied to the symbolic dynamics of time indices. A maximum entropy principle defines the optimal size of intersecting balls. The final application to high-dimensional brain signals yields an optimal symbolic recurrence plot revealing functional components of the signal.

Contrast-enhanced spectral mammography with a photon-counting detector.

PubMed

Fredenberg, Erik; Hemmendorff, Magnus; Cederström, Björn; Aslund, Magnus; Danielsson, Mats

2010-05-01

Spectral imaging is a method in medical x-ray imaging to extract information about the object constituents by the material-specific energy dependence of x-ray attenuation. The authors have investigated a photon-counting spectral imaging system with two energy bins for contrast-enhanced mammography. System optimization and the potential benefit compared to conventional non-energy-resolved absorption imaging was studied. A framework for system characterization was set up that included quantum and anatomical noise and a theoretical model of the system was benchmarked to phantom measurements. Optimal combination of the energy-resolved images corresponded approximately to minimization of the anatomical noise, which is commonly referred to as energy subtraction. In that case, an ideal-observer detectability index could be improved close to 50% compared to absorption imaging in the phantom study. Optimization with respect to the signal-to-quantum-noise ratio, commonly referred to as energy weighting, yielded only a minute improvement. In a simulation of a clinically more realistic case, spectral imaging was predicted to perform approximately 30% better than absorption imaging for an average glandularity breast with an average level of anatomical noise. For dense breast tissue and a high level of anatomical noise, however, a rise in detectability by a factor of 6 was predicted. Another approximately 70%-90% improvement was found to be within reach for an optimized system. Contrast-enhanced spectral mammography is feasible and beneficial with the current system, and there is room for additional improvements. Inclusion of anatomical noise is essential for optimizing spectral imaging systems.

Missed, Misused, or Mismanaged: Improving Early Detection Systems to Optimize Child Outcomes

ERIC Educational Resources Information Center

Macy, Marisa; Marks, Kevin; Towle, Alexander

2014-01-01

Early detection efforts have been shown to vary greatly in practice, and there is a general lack of systematic accountability built into monitoring early detection effort impact. This article reviews current early detection practices and the drawbacks of these practices, with particular attention given to prevalent issues of mismeasurement,…

On the pilot's behavior of detecting a system parameter change

NASA Technical Reports Server (NTRS)

Morizumi, N.; Kimura, H.

1986-01-01

The reaction of a human pilot, engaged in compensatory control, to a sudden change in the controlled element's characteristics is described. Taking the case where the change manifests itself as a variance change of the monitored signal, it is shown that the detection time, defined to be the time elapsed until the pilot detects the change, is related to the monitored signal and its derivative. Then, the detection behavior is modeled by an optimal controller, an optimal estimator, and a variance-ratio test mechanism that is performed for the monitored signal and its derivative. Results of a digital simulation show that the pilot's detection behavior can be well represented by the model proposed here.

Establishment and application of cross-priming isothermal amplification coupled with lateral flow dipstick (CPA-LFD) for rapid and specific detection of red-spotted grouper nervous necrosis virus.

PubMed

Su, Zi Dan; Shi, Cheng Yin; Huang, Jie; Shen, Gui Ming; Li, Jin; Wang, Sheng Qiang; Fan, Chao

2015-09-26

Red-spotted grouper nervous necrosis virus (RGNNV) is an important pathogen that causes diseases in many species of fish in marine aquaculture. The larvae and juveniles are more easily infected by RGNNV and the cumulative mortality is as high as 100 % after being infected with RGNNV. This virus imposes a serious threat to aquaculture of grouper fry. This study aimed to establish a simple, accurate and highly sensitive method for rapid detection of RGNNV on the spot. In this study, the primers specifically targeting RGNNV were designed and cross-priming isothermal amplification (CPA) system was established. The product amplified by CPA was detected through visualization with lateral flow dipstick (LFD). Three important parameters, including the amplification temperature, the concentration of dNTPs and the concentration of Mg(2+) for the CPA system, were optimized. The sensitivity and specificity of this method for RGNNV were tested and compared with those of the conventional RT-PCR and real-time quantitative RT-PCR (qRT-PCR). The optimized conditions for the CPA amplification system were determined as follows: the optimal amplification temperature, the optimized concentration of dNTPs and the concentration for Mg(2+) were 69 °C, 1.2 mmol/L and 5 mmol/L, respectively. The lowest limit of detection (LLOD) of this method for RGNNV was 10(1) copies/μL of RNA sample, which was 10 times lower than that of conventional RT-PCR and comparable to that of RT-qPCR. This method was specific for RGNNV in combination with SJNNV and had no cross-reactions with 8 types of virus and bacterial strains tested. This method was successfully applied to detect RGNNV in fish samples. This study established a CPA-LFD method for detection of RGNNV. This method is simple and rapid with high sensitivity and good specificity and can be widely applied for rapid detection of this virus on the spot.

Development and Translation of Hybrid Optoacoustic/Ultrasonic Tomography for Early Breast Cancer Detection

DTIC Science & Technology

2014-09-01

to develop an optimized system design and associated image reconstruction algorithms for a hybrid three-dimensional (3D) breast imaging system that...research is to develop an optimized system design and associated image reconstruction algorithms for a hybrid three-dimensional (3D) breast imaging ...i) developed time-of- flight extraction algorithms to perform USCT, (ii) developing image reconstruction algorithms for USCT, (iii) developed

Multi-Stage System for Automatic Target Recognition

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin; Lu, Thomas T.; Ye, David; Edens, Weston; Johnson, Oliver

2010-01-01

A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feedforward back-propagation neural network (NN) is then trained to classify each feature vector and to remove false positives. The system parameter optimizations process has been developed to adapt to various targets and datasets. The objective was to design an efficient computer vision system that can learn to detect multiple targets in large images with unknown backgrounds. Because the target size is small relative to the image size in this problem, there are many regions of the image that could potentially contain the target. A cursory analysis of every region can be computationally efficient, but may yield too many false positives. On the other hand, a detailed analysis of every region can yield better results, but may be computationally inefficient. The multi-stage ATR system was designed to achieve an optimal balance between accuracy and computational efficiency by incorporating both models. The detection stage first identifies potential ROIs where the target may be present by performing a fast Fourier domain OT-MACH filter-based correlation. Because threshold for this stage is chosen with the goal of detecting all true positives, a number of false positives are also detected as ROIs. The verification stage then transforms the regions of interest into feature space, and eliminates false positives using an artificial neural network classifier. The multi-stage system allows tuning the detection sensitivity and the identification specificity individually in each stage. It is easier to achieve optimized ATR operation based on its specific goal. The test results show that the system was successful in substantially reducing the false positive rate when tested on a sonar and video image datasets.

Big Data Analysis of Manufacturing Processes

NASA Astrophysics Data System (ADS)

Windmann, Stefan; Maier, Alexander; Niggemann, Oliver; Frey, Christian; Bernardi, Ansgar; Gu, Ying; Pfrommer, Holger; Steckel, Thilo; Krüger, Michael; Kraus, Robert

2015-11-01

The high complexity of manufacturing processes and the continuously growing amount of data lead to excessive demands on the users with respect to process monitoring, data analysis and fault detection. For these reasons, problems and faults are often detected too late, maintenance intervals are chosen too short and optimization potential for higher output and increased energy efficiency is not sufficiently used. A possibility to cope with these challenges is the development of self-learning assistance systems, which identify relevant relationships by observation of complex manufacturing processes so that failures, anomalies and need for optimization are automatically detected. The assistance system developed in the present work accomplishes data acquisition, process monitoring and anomaly detection in industrial and agricultural processes. The assistance system is evaluated in three application cases: Large distillation columns, agricultural harvesting processes and large-scale sorting plants. In this paper, the developed infrastructures for data acquisition in these application cases are described as well as the developed algorithms and initial evaluation results.

Optimal pulse design for communication-oriented slow-light pulse detection.

PubMed

Stenner, Michael D; Neifeld, Mark A

2008-01-21

We present techniques for designing pulses for linear slow-light delay systems which are optimal in the sense that they maximize the signal-to-noise ratio (SNR) and signal-to-noise-plus-interference ratio (SNIR) of the detected pulse energy. Given a communication model in which input pulses are created in a finite temporal window and output pulse energy in measured in a temporally-offset output window, the SNIR-optimal pulses achieve typical improvements of 10 dB compared to traditional pulse shapes for a given output window offset. Alternatively, for fixed SNR or SNIR, window offset (detection delay) can be increased by 0.3 times the window width. This approach also invites a communication-based model for delay and signal fidelity.

Hybrid feature selection for supporting lightweight intrusion detection systems

NASA Astrophysics Data System (ADS)

Song, Jianglong; Zhao, Wentao; Liu, Qiang; Wang, Xin

2017-08-01

Redundant and irrelevant features not only cause high resource consumption but also degrade the performance of Intrusion Detection Systems (IDS), especially when coping with big data. These features slow down the process of training and testing in network traffic classification. Therefore, a hybrid feature selection approach in combination with wrapper and filter selection is designed in this paper to build a lightweight intrusion detection system. Two main phases are involved in this method. The first phase conducts a preliminary search for an optimal subset of features, in which the chi-square feature selection is utilized. The selected set of features from the previous phase is further refined in the second phase in a wrapper manner, in which the Random Forest(RF) is used to guide the selection process and retain an optimized set of features. After that, we build an RF-based detection model and make a fair comparison with other approaches. The experimental results on NSL-KDD datasets show that our approach results are in higher detection accuracy as well as faster training and testing processes.

Motion compensated image processing and optimal parameters for egg crack detection using modified pressure

USDA-ARS?s Scientific Manuscript database

Shell eggs with microcracks are often undetected during egg grading processes. In the past, a modified pressure imaging system was developed to detect eggs with microcracks without adversely affecting the quality of normal intact eggs. The basic idea of the modified pressure imaging system was to ap...

Statistical model based iterative reconstruction in clinical CT systems. Part III. Task-based kV/mAs optimization for radiation dose reduction

PubMed Central

Li, Ke; Gomez-Cardona, Daniel; Hsieh, Jiang; Lubner, Meghan G.; Pickhardt, Perry J.; Chen, Guang-Hong

2015-01-01

Purpose: For a given imaging task and patient size, the optimal selection of x-ray tube potential (kV) and tube current-rotation time product (mAs) is pivotal in achieving the maximal radiation dose reduction while maintaining the needed diagnostic performance. Although contrast-to-noise (CNR)-based strategies can be used to optimize kV/mAs for computed tomography (CT) imaging systems employing the linear filtered backprojection (FBP) reconstruction method, a more general framework needs to be developed for systems using the nonlinear statistical model-based iterative reconstruction (MBIR) method. The purpose of this paper is to present such a unified framework for the optimization of kV/mAs selection for both FBP- and MBIR-based CT systems. Methods: The optimal selection of kV and mAs was formulated as a constrained optimization problem to minimize the objective function, Dose(kV,mAs), under the constraint that the achievable detectability index d′(kV,mAs) is not lower than the prescribed value of d℞′ for a given imaging task. Since it is difficult to analytically model the dependence of d′ on kV and mAs for the highly nonlinear MBIR method, this constrained optimization problem is solved with comprehensive measurements of Dose(kV,mAs) and d′(kV,mAs) at a variety of kV–mAs combinations, after which the overlay of the dose contours and d′ contours is used to graphically determine the optimal kV–mAs combination to achieve the lowest dose while maintaining the needed detectability for the given imaging task. As an example, d′ for a 17 mm hypoattenuating liver lesion detection task was experimentally measured with an anthropomorphic abdominal phantom at four tube potentials (80, 100, 120, and 140 kV) and fifteen mA levels (25 and 50–700) with a sampling interval of 50 mA at a fixed rotation time of 0.5 s, which corresponded to a dose (CTDIvol) range of [0.6, 70] mGy. Using the proposed method, the optimal kV and mA that minimized dose for the prescribed detectability level of d℞′=16 were determined. As another example, the optimal kV and mA for an 8 mm hyperattenuating liver lesion detection task were also measured using the developed framework. Both an in vivo animal and human subject study were used as demonstrations of how the developed framework can be applied to the clinical work flow. Results: For the first task, the optimal kV and mAs were measured to be 100 and 500, respectively, for FBP, which corresponded to a dose level of 24 mGy. In comparison, the optimal kV and mAs for MBIR were 80 and 150, respectively, which corresponded to a dose level of 4 mGy. The topographies of the iso-d′ map and the iso-CNR map were the same for FBP; thus, the use of d′- and CNR-based optimization methods generated the same results for FBP. However, the topographies of the iso-d′ and iso-CNR map were significantly different in MBIR; the CNR-based method overestimated the performance of MBIR, predicting an overly aggressive dose reduction factor. For the second task, the developed framework generated the following optimization results: for FBP, kV = 140, mA = 350, dose = 37.5 mGy; for MBIR, kV = 120, mA = 250, dose = 18.8 mGy. Again, the CNR-based method overestimated the performance of MBIR. Results of the preliminary in vivo studies were consistent with those of the phantom experiments. Conclusions: A unified and task-driven kV/mAs optimization framework has been developed in this work. The framework is applicable to both linear and nonlinear CT systems such as those using the MBIR method. As expected, the developed framework can be reduced to the conventional CNR-based kV/mAs optimization frameworks if the system is linear. For MBIR-based nonlinear CT systems, however, the developed task-based kV/mAs optimization framework is needed to achieve the maximal dose reduction while maintaining the desired diagnostic performance. PMID:26328971

Peak tree: a new tool for multiscale hierarchical representation and peak detection of mass spectrometry data.

PubMed

Zhang, Peng; Li, Houqiang; Wang, Honghui; Wong, Stephen T C; Zhou, Xiaobo

2011-01-01

Peak detection is one of the most important steps in mass spectrometry (MS) analysis. However, the detection result is greatly affected by severe spectrum variations. Unfortunately, most current peak detection methods are neither flexible enough to revise false detection results nor robust enough to resist spectrum variations. To improve flexibility, we introduce peak tree to represent the peak information in MS spectra. Each tree node is a peak judgment on a range of scales, and each tree decomposition, as a set of nodes, is a candidate peak detection result. To improve robustness, we combine peak detection and common peak alignment into a closed-loop framework, which finds the optimal decomposition via both peak intensity and common peak information. The common peak information is derived and loopily refined from the density clustering of the latest peak detection result. Finally, we present an improved ant colony optimization biomarker selection method to build a whole MS analysis system. Experiment shows that our peak detection method can better resist spectrum variations and provide higher sensitivity and lower false detection rates than conventional methods. The benefits from our peak-tree-based system for MS disease analysis are also proved on real SELDI data.

Liquid scintillator composition optimization for use in ultra-high energy cosmic ray detector systems

NASA Astrophysics Data System (ADS)

Beznosko, Dmitriy; Batyrkhanov, Ayan; Iakovlev, Alexander; Yelshibekov, Khalykbek

2017-06-01

The Horizon-T (HT) detector system and the currently under R&D HT-KZ detector system are designed for the detection of Extensive Air Showers (EAS) with energies above ˜1016 eV (˜1017 eV for HT-KZ). The main challenges in both detector systems are the fast time resolutions needed for studying the temporary structure of EAS, and the extremely wide dynamic range needed to study the spatial distribution of charged particles in EAS disks. In order to detect the low-density of charged particles far from the EAS axis, a large-area detector is needed. Liquid scintillator with low cost would be a possible solution for such a detector, including the recently developed safe and low-cost water-based liquid scintillators. Liquid organic scintillators give a fast and high light yield (LY) for charged particle detection. It is similar to plastic scintillator in properties but is cost effective for large volumes. With liquid scintillator, one can create detection volumes that are symmetric and yet retain high LY detection. Different wavelength shifters affect the scintillation light by changing the output spectrum into the best detection region. Results of the latest studies of the components optimization in the liquid scintillator formulae are presented.

Adaptive Self-Tuning Networks

NASA Astrophysics Data System (ADS)

Knox, H. A.; Draelos, T.; Young, C. J.; Lawry, B.; Chael, E. P.; Faust, A.; Peterson, M. G.

2015-12-01

The quality of automatic detections from seismic sensor networks depends on a large number of data processing parameters that interact in complex ways. The largely manual process of identifying effective parameters is painstaking and does not guarantee that the resulting controls are the optimal configuration settings. Yet, achieving superior automatic detection of seismic events is closely related to these parameters. We present an automated sensor tuning (AST) system that learns near-optimal parameter settings for each event type using neuro-dynamic programming (reinforcement learning) trained with historic data. AST learns to test the raw signal against all event-settings and automatically self-tunes to an emerging event in real-time. The overall goal is to reduce the number of missed legitimate event detections and the number of false event detections. Reducing false alarms early in the seismic pipeline processing will have a significant impact on this goal. Applicable both for existing sensor performance boosting and new sensor deployment, this system provides an important new method to automatically tune complex remote sensing systems. Systems tuned in this way will achieve better performance than is currently possible by manual tuning, and with much less time and effort devoted to the tuning process. With ground truth on detections in seismic waveforms from a network of stations, we show that AST increases the probability of detection while decreasing false alarms.

Application of Islanding Detection and Classification of Power Quality Disturbance in Hybrid Energy System

NASA Astrophysics Data System (ADS)

Sun, L. B.; Wu, Z. S.; Yang, K. K.

2018-04-01

Islanding and power quality (PQ) disturbances in hybrid energy system become more serious with the application of renewable energy sources. In this paper, a novel method based on wavelet transform (WT) and modified feed forward neural network (FNN) is proposed to detect islanding and classify PQ problems. First, the performance indices, i.e., the energy content and SD of the transformed signal are extracted from the negative sequence component of the voltage signal at PCC using WT. Afterward, WT indices are fed to train FNNs midfield by Particle Swarm Optimization (PSO) which is a novel heuristic optimization method. Then, the results of simulation based on WT-PSOFNN are discussed in MATLAB/SIMULINK. Simulations on the hybrid power system show that the accuracy can be significantly improved by the proposed method in detecting and classifying of different disturbances connected to multiple distributed generations.

Maximizing the Biochemical Resolving Power of Fluorescence Microscopy

PubMed Central

Esposito, Alessandro; Popleteeva, Marina; Venkitaraman, Ashok R.

2013-01-01

Most recent advances in fluorescence microscopy have focused on achieving spatial resolutions below the diffraction limit. However, the inherent capability of fluorescence microscopy to non-invasively resolve different biochemical or physical environments in biological samples has not yet been formally described, because an adequate and general theoretical framework is lacking. Here, we develop a mathematical characterization of the biochemical resolution in fluorescence detection with Fisher information analysis. To improve the precision and the resolution of quantitative imaging methods, we demonstrate strategies for the optimization of fluorescence lifetime, fluorescence anisotropy and hyperspectral detection, as well as different multi-dimensional techniques. We describe optimized imaging protocols, provide optimization algorithms and describe precision and resolving power in biochemical imaging thanks to the analysis of the general properties of Fisher information in fluorescence detection. These strategies enable the optimal use of the information content available within the limited photon-budget typically available in fluorescence microscopy. This theoretical foundation leads to a generalized strategy for the optimization of multi-dimensional optical detection, and demonstrates how the parallel detection of all properties of fluorescence can maximize the biochemical resolving power of fluorescence microscopy, an approach we term Hyper Dimensional Imaging Microscopy (HDIM). Our work provides a theoretical framework for the description of the biochemical resolution in fluorescence microscopy, irrespective of spatial resolution, and for the development of a new class of microscopes that exploit multi-parametric detection systems. PMID:24204821

An improved real time image detection system for elephant intrusion along the forest border areas.

PubMed

Sugumar, S J; Jayaparvathy, R

2014-01-01

Human-elephant conflict is a major problem leading to crop damage, human death and injuries caused by elephants, and elephants being killed by humans. In this paper, we propose an automated unsupervised elephant image detection system (EIDS) as a solution to human-elephant conflict in the context of elephant conservation. The elephant's image is captured in the forest border areas and is sent to a base station via an RF network. The received image is decomposed using Haar wavelet to obtain multilevel wavelet coefficients, with which we perform image feature extraction and similarity match between the elephant query image and the database image using image vision algorithms. A GSM message is sent to the forest officials indicating that an elephant has been detected in the forest border and is approaching human habitat. We propose an optimized distance metric to improve the image retrieval time from the database. We compare the optimized distance metric with the popular Euclidean and Manhattan distance methods. The proposed optimized distance metric retrieves more images with lesser retrieval time than the other distance metrics which makes the optimized distance method more efficient and reliable.

Noninvasive detection of cardiovascular pulsations by optical Doppler techniques

NASA Astrophysics Data System (ADS)

Hong, HyunDae; Fox, Martin D.

1997-10-01

A system has been developed based on the measurement of skin surface vibration that can be used to detect the underlying vascular wall motion of superficial arteries and the chest wall. Data obtained from tissue phantoms suggested that the detected signals were related to intravascular pressure, an important clinical and physiological parameter. Unlike the conventional optical Doppler techniques that have been used to measure blood perfusion in skin layers and blood flow within superficial arteries, the present system was optimized to pick up skin vibrations. An optical interferometer with a 633-nm He:Ne laser was utilized to detect micrometer displacements of the skin surface. Motion velocity profiles of the skin surface near each superficial artery and auscultation points on a chest for the two heart valve sounds exhibited distinctive profiles. The theoretical and experimental results demonstrated that the system detected the velocity of skin movement, which is related to the time derivative of the pressure. The system also reduces the loading effect on the pulsation signals and heart sounds produced by the conventional piezoelectric vibration sensors. The system's sensitivity, which could be optimized further, was 366.2 micrometers /s for the present research. Overall, optical cardiovascular vibrometry has the potential to become a simple noninvasive approach to cardiovascular screening.

Small unmanned aircraft system for remote contour mapping of a nuclear radiation field

NASA Astrophysics Data System (ADS)

Guss, Paul; McCall, Karen; Malchow, Russell; Fischer, Rick; Lukens, Michael; Adan, Mark; Park, Ki; Abbott, Roy; Howard, Michael; Wagner, Eric; Trainham, Clifford P.; Luke, Tanushree; Mukhopadhyay, Sanjoy; Oh, Paul; Brahmbhatt, Pareshkumar; Henderson, Eric; Han, Jinlu; Huang, Justin; Huang, Casey; Daniels, Jon

2017-09-01

For nuclear disasters involving radioactive contamination, small unmanned aircraft systems (sUASs) equipped with nuclear radiation detection and monitoring capability can be very important tools. Among the advantages of a sUAS are quick deployment, low-altitude flying that enhances sensitivity, wide area coverage, no radiation exposure health safety restriction, and the ability to access highly hazardous or radioactive areas. Additionally, the sUAS can be configured with the nuclear detecting sensor optimized to measure the radiation associated with the event. In this investigation, sUAS platforms were obtained for the installation of sensor payloads for radiation detection and electro-optical systems that were specifically developed for sUAS research, development, and operational testing. The sensor payloads were optimized for the contour mapping of a nuclear radiation field, which will result in a formula for low-cost sUAS platform operations with built-in formation flight control. Additional emphases of the investigation were to develop the relevant contouring algorithms; initiate the sUAS comprehensive testing using the Unmanned Systems, Inc. (USI) Sandstorm platforms and other acquired platforms; and both acquire and optimize the sensors for detection and localization. We demonstrated contour mapping through simulation and validated waypoint detection. We mounted a detector on a sUAS and operated it initially in the counts per second (cps) mode to perform field and flight tests to demonstrate that the equipment was functioning as designed. We performed ground truth measurements to determine the response of the detector as a function of source-to-detector distance. Operation of the radiation detector was tested using different unshielded sources.

An opto-electronic joint detection system based on DSP aiming at early cervical cancer screening

NASA Astrophysics Data System (ADS)

Wang, Weiya; Jia, Mengyu; Gao, Feng; Yang, Lihong; Qu, Pengpeng; Zou, Changping; Liu, Pengxi; Zhao, Huijuan

2015-02-01

The cervical cancer screening at a pre-cancer stage is beneficial to reduce the mortality of women. An opto-electronic joint detection system based on DSP aiming at early cervical cancer screening is introduced in this paper. In this system, three electrodes alternately discharge to the cervical tissue and three light emitting diodes in different wavelengths alternately irradiate the cervical tissue. Then the relative optical reflectance and electrical voltage attenuation curve are obtained by optical and electrical detection, respectively. The system is based on DSP to attain the portable and cheap instrument. By adopting the relative reflectance and the voltage attenuation constant, the classification algorithm based on Support Vector Machine (SVM) discriminates abnormal cervical tissue from normal. We use particle swarm optimization to optimize the two key parameters of SVM, i.e. nuclear factor and cost factor. The clinical data were collected on 313 patients to build a clinical database of tissue responses under optical and electrical stimulations with the histopathologic examination as the gold standard. The classification result shows that the opto-electronic joint detection has higher total coincidence rate than separate optical detection or separate electrical detection. The sensitivity, specificity, and total coincidence rate increase with the increasing of sample numbers in the training set. The average total coincidence rate of the system can reach 85.1% compared with the histopathologic examination.

Time and frequency constrained sonar signal design for optimal detection of elastic objects.

PubMed

Hamschin, Brandon; Loughlin, Patrick J

2013-04-01

In this paper, the task of model-based transmit signal design for optimizing detection is considered. Building on past work that designs the spectral magnitude for optimizing detection, two methods for synthesizing minimum duration signals with this spectral magnitude are developed. The methods are applied to the design of signals that are optimal for detecting elastic objects in the presence of additive noise and self-noise. Elastic objects are modeled as linear time-invariant systems with known impulse responses, while additive noise (e.g., ocean noise or receiver noise) and acoustic self-noise (e.g., reverberation or clutter) are modeled as stationary Gaussian random processes with known power spectral densities. The first approach finds the waveform that preserves the optimal spectral magnitude while achieving the minimum temporal duration. The second approach yields a finite-length time-domain sequence by maximizing temporal energy concentration, subject to the constraint that the spectral magnitude is close (in a least-squares sense) to the optimal spectral magnitude. The two approaches are then connected analytically, showing the former is a limiting case of the latter. Simulation examples that illustrate the theory are accompanied by discussions that address practical applicability and how one might satisfy the need for target and environmental models in the real-world.

ECG Based Heart Arrhythmia Detection Using Wavelet Coherence and Bat Algorithm

NASA Astrophysics Data System (ADS)

Kora, Padmavathi; Sri Rama Krishna, K.

2016-12-01

Atrial fibrillation (AF) is a type of heart abnormality, during the AF electrical discharges in the atrium are rapid, results in abnormal heart beat. The morphology of ECG changes due to the abnormalities in the heart. This paper consists of three major steps for the detection of heart diseases: signal pre-processing, feature extraction and classification. Feature extraction is the key process in detecting the heart abnormality. Most of the ECG detection systems depend on the time domain features for cardiac signal classification. In this paper we proposed a wavelet coherence (WTC) technique for ECG signal analysis. The WTC calculates the similarity between two waveforms in frequency domain. Parameters extracted from WTC function is used as the features of the ECG signal. These features are optimized using Bat algorithm. The Levenberg Marquardt neural network classifier is used to classify the optimized features. The performance of the classifier can be improved with the optimized features.

A Simple Method for Amplifying RNA Targets (SMART)

PubMed Central

McCalla, Stephanie E.; Ong, Carmichael; Sarma, Aartik; Opal, Steven M.; Artenstein, Andrew W.; Tripathi, Anubhav

2012-01-01

We present a novel and simple method for amplifying RNA targets (named by its acronym, SMART), and for detection, using engineered amplification probes that overcome existing limitations of current RNA-based technologies. This system amplifies and detects optimal engineered ssDNA probes that hybridize to target RNA. The amplifiable probe-target RNA complex is captured on magnetic beads using a sequence-specific capture probe and is separated from unbound probe using a novel microfluidic technique. Hybridization sequences are not constrained as they are in conventional target-amplification reactions such as nucleic acid sequence amplification (NASBA). Our engineered ssDNA probe was amplified both off-chip and in a microchip reservoir at the end of the separation microchannel using isothermal NASBA. Optimal solution conditions for ssDNA amplification were investigated. Although KCl and MgCl2 are typically found in NASBA reactions, replacing 70 mmol/L of the 82 mmol/L total chloride ions with acetate resulted in optimal reaction conditions, particularly for low but clinically relevant probe concentrations (≤100 fmol/L). With the optimal probe design and solution conditions, we also successfully removed the initial heating step of NASBA, thus achieving a true isothermal reaction. The SMART assay using a synthetic model influenza DNA target sequence served as a fundamental demonstration of the efficacy of the capture and microfluidic separation system, thus bridging our system to a clinically relevant detection problem. PMID:22691910

Fault detection for piecewise affine systems with application to ship propulsion systems.

PubMed

Yang, Ying; Linlin, Li; Ding, Steven X; Qiu, Jianbin; Peng, Kaixiang

2017-09-09

In this paper, the design approach of non-synchronized diagnostic observer-based fault detection (FD) systems is investigated for piecewise affine processes via continuous piecewise Lyapunov functions. Considering that the dynamics of piecewise affine systems in different regions can be considerably different, the weighting matrices are used to weight the residual of each region, so as to optimize the fault detectability. A numerical example and a case study on a ship propulsion system are presented in the end to demonstrate the effectiveness of the proposed results. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Optimal frequency domain textural edge detection filter

NASA Technical Reports Server (NTRS)

Townsend, J. K.; Shanmugan, K. S.; Frost, V. S.

1985-01-01

An optimal frequency domain textural edge detection filter is developed and its performance evaluated. For the given model and filter bandwidth, the filter maximizes the amount of output image energy placed within a specified resolution interval centered on the textural edge. Filter derivation is based on relating textural edge detection to tonal edge detection via the complex low-pass equivalent representation of narrowband bandpass signals and systems. The filter is specified in terms of the prolate spheroidal wave functions translated in frequency. Performance is evaluated using the asymptotic approximation version of the filter. This evaluation demonstrates satisfactory filter performance for ideal and nonideal textures. In addition, the filter can be adjusted to detect textural edges in noisy images at the expense of edge resolution.

Cyber-Physical Attacks With Control Objectives

DOE PAGES

Chen, Yuan; Kar, Soummya; Moura, Jose M. F.

2017-08-18

This study studies attackers with control objectives against cyber-physical systems (CPSs). The goal of the attacker is to counteract the CPS's controller and move the system to a target state while evading detection. We formulate a cost function that reflects the attacker's goals, and, using dynamic programming, we show that the optimal attack strategy reduces to a linear feedback of the attacker's state estimate. By changing the parameters of the cost function, we show how an attacker can design optimal attacks to balance the control objective and the detection avoidance objective. In conclusion, we provide a numerical illustration based onmore » a remotely controlled helicopter under attack.« less

Cyber-Physical Attacks With Control Objectives

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

Chen, Yuan; Kar, Soummya; Moura, Jose M. F.

This study studies attackers with control objectives against cyber-physical systems (CPSs). The goal of the attacker is to counteract the CPS's controller and move the system to a target state while evading detection. We formulate a cost function that reflects the attacker's goals, and, using dynamic programming, we show that the optimal attack strategy reduces to a linear feedback of the attacker's state estimate. By changing the parameters of the cost function, we show how an attacker can design optimal attacks to balance the control objective and the detection avoidance objective. In conclusion, we provide a numerical illustration based onmore » a remotely controlled helicopter under attack.« less

Analysis of Eddy Current Capabilities for the Detection of Outer Diameter Stress Corrosion Cracking in Small Bore Metallic Structures

NASA Technical Reports Server (NTRS)

Wincheski, Buzz; Williams, Phillip; Simpson, John

2007-01-01

The use of eddy current techniques for the detection of outer diameter damage in tubing and many complex aerospace structures often requires the use of an inner diameter probe due to a lack of access to the outside of the part. In small bore structures the probe size and orientation are constrained by the inner diameter of the part, complicating the optimization of the inspection technique. Detection of flaws through a significant remaining wall thickness becomes limited not only by the standard depth of penetration, but also geometrical aspects of the probe. Recently, an orthogonal eddy current probe was developed for detection of such flaws in Space Shuttle Primary Reaction Control System (PRCS) Thrusters. In this case, the detection of deeply buried stress corrosion cracking by an inner diameter eddy current probe was sought. Probe optimization was performed based upon the limiting spatial dimensions, flaw orientation, and required detection sensitivity. Analysis of the probe/flaw interaction was performed through the use of finite and boundary element modeling techniques. Experimental data for the flaw detection capabilities, including a probability of detection study, will be presented along with the simulation data. The results of this work have led to the successful deployment of an inspection system for the detection of stress corrosion cracking in Space Shuttle Primary Reaction Control System (PRCS) Thrusters.

Fault Detection of Bearing Systems through EEMD and Optimization Algorithm

PubMed Central

Lee, Dong-Han; Ahn, Jong-Hyo; Koh, Bong-Hwan

2017-01-01

This study proposes a fault detection and diagnosis method for bearing systems using ensemble empirical mode decomposition (EEMD) based feature extraction, in conjunction with particle swarm optimization (PSO), principal component analysis (PCA), and Isomap. First, a mathematical model is assumed to generate vibration signals from damaged bearing components, such as the inner-race, outer-race, and rolling elements. The process of decomposing vibration signals into intrinsic mode functions (IMFs) and extracting statistical features is introduced to develop a damage-sensitive parameter vector. Finally, PCA and Isomap algorithm are used to classify and visualize this parameter vector, to separate damage characteristics from healthy bearing components. Moreover, the PSO-based optimization algorithm improves the classification performance by selecting proper weightings for the parameter vector, to maximize the visualization effect of separating and grouping of parameter vectors in three-dimensional space. PMID:29143772

Classification and Evaluation of Coherent Synchronous Sampled-Data Telemetry Systems

NASA Technical Reports Server (NTRS)

Viterbi, Andrew

1961-01-01

This paper analyzes the various types of continuous wave and pulse modulation for the transmission of sampled data over channels perturbed by white gaussian noise. Optimal coherent synchronous detection schemes for all the different modulation methods are shown to belong to one of two general classes: linear synchronous detection and correlation detection. The figures of merit, mean-square signal-to-error ratio and bandwidth occupancy, are determined for each system and compared.

Double closed-loop control of integrated optical resonance gyroscope with mean-square exponential stability.

PubMed

Li, Hui; Liu, Liying; Lin, Zhili; Wang, Qiwei; Wang, Xiao; Feng, Lishuang

2018-01-22

A new double closed-loop control system with mean-square exponential stability is firstly proposed to optimize the detection accuracy and dynamic response characteristic of the integrated optical resonance gyroscope (IORG). The influence mechanism of optical nonlinear effects on system detection sensitivity is investigated to optimize the demodulation gain, the maximum sensitivity and the linear work region of a gyro system. Especially, we analyze the effect of optical parameter fluctuation on the parameter uncertainty of system, and investigate the influence principle of laser locking-frequency noise on the closed-loop detection accuracy of angular velocity. The stochastic disturbance model of double closed-loop IORG is established that takes the unfavorable factors such as optical effect nonlinearity, disturbed disturbance, optical parameter fluctuation and unavoidable system noise into consideration. A robust control algorithm is also designed to guarantee the mean-square exponential stability of system with a prescribed H ∞ performance in order to improve the detection accuracy and dynamic performance of IORG. The conducted experiment results demonstrate that the IORG has a dynamic response time less than 76us, a long-term bias stability 7.04°/h with an integration time of 10s over one-hour test, and the corresponding bias stability 1.841°/h based on Allan deviation, which validate the effectiveness and usefulness of the proposed detection scheme.

System principles, mathematical models and methods to ensure high reliability of safety systems

NASA Astrophysics Data System (ADS)

Zaslavskyi, V.

2017-04-01

Modern safety and security systems are composed of a large number of various components designed for detection, localization, tracking, collecting, and processing of information from the systems of monitoring, telemetry, control, etc. They are required to be highly reliable in a view to correctly perform data aggregation, processing and analysis for subsequent decision making support. On design and construction phases of the manufacturing of such systems a various types of components (elements, devices, and subsystems) are considered and used to ensure high reliability of signals detection, noise isolation, and erroneous commands reduction. When generating design solutions for highly reliable systems a number of restrictions and conditions such as types of components and various constrains on resources should be considered. Various types of components perform identical functions; however, they are implemented using diverse principles, approaches and have distinct technical and economic indicators such as cost or power consumption. The systematic use of different component types increases the probability of tasks performing and eliminates the common cause failure. We consider type-variety principle as an engineering principle of system analysis, mathematical models based on this principle, and algorithms for solving optimization problems of highly reliable safety and security systems design. Mathematical models are formalized in a class of two-level discrete optimization problems of large dimension. The proposed approach, mathematical models, algorithms can be used for problem solving of optimal redundancy on the basis of a variety of methods and control devices for fault and defects detection in technical systems, telecommunication networks, and energy systems.

FPGA based hardware optimized implementation of signal processing system for LFM pulsed radar

NASA Astrophysics Data System (ADS)

Azim, Noor ul; Jun, Wang

2016-11-01

Signal processing is one of the main parts of any radar system. Different signal processing algorithms are used to extract information about different parameters like range, speed, direction etc, of a target in the field of radar communication. This paper presents LFM (Linear Frequency Modulation) pulsed radar signal processing algorithms which are used to improve target detection, range resolution and to estimate the speed of a target. Firstly, these algorithms are simulated in MATLAB to verify the concept and theory. After the conceptual verification in MATLAB, the simulation is converted into implementation on hardware using Xilinx FPGA. Chosen FPGA is Xilinx Virtex-6 (XC6LVX75T). For hardware implementation pipeline optimization is adopted and also other factors are considered for resources optimization in the process of implementation. Focusing algorithms in this work for improving target detection, range resolution and speed estimation are hardware optimized fast convolution processing based pulse compression and pulse Doppler processing.

Optimal joint detection and estimation that maximizes ROC-type curves

PubMed Central

Wunderlich, Adam; Goossens, Bart; Abbey, Craig K.

2017-01-01

Combined detection-estimation tasks are frequently encountered in medical imaging. Optimal methods for joint detection and estimation are of interest because they provide upper bounds on observer performance, and can potentially be utilized for imaging system optimization, evaluation of observer efficiency, and development of image formation algorithms. We present a unified Bayesian framework for decision rules that maximize receiver operating characteristic (ROC)-type summary curves, including ROC, localization ROC (LROC), estimation ROC (EROC), free-response ROC (FROC), alternative free-response ROC (AFROC), and exponentially-transformed FROC (EFROC) curves, succinctly summarizing previous results. The approach relies on an interpretation of ROC-type summary curves as plots of an expected utility versus an expected disutility (or penalty) for signal-present decisions. We propose a general utility structure that is flexible enough to encompass many ROC variants and yet sufficiently constrained to allow derivation of a linear expected utility equation that is similar to that for simple binary detection. We illustrate our theory with an example comparing decision strategies for joint detection-estimation of a known signal with unknown amplitude. In addition, building on insights from our utility framework, we propose new ROC-type summary curves and associated optimal decision rules for joint detection-estimation tasks with an unknown, potentially-multiple, number of signals in each observation. PMID:27093544

Optimal Joint Detection and Estimation That Maximizes ROC-Type Curves.

PubMed

Wunderlich, Adam; Goossens, Bart; Abbey, Craig K

2016-09-01

Combined detection-estimation tasks are frequently encountered in medical imaging. Optimal methods for joint detection and estimation are of interest because they provide upper bounds on observer performance, and can potentially be utilized for imaging system optimization, evaluation of observer efficiency, and development of image formation algorithms. We present a unified Bayesian framework for decision rules that maximize receiver operating characteristic (ROC)-type summary curves, including ROC, localization ROC (LROC), estimation ROC (EROC), free-response ROC (FROC), alternative free-response ROC (AFROC), and exponentially-transformed FROC (EFROC) curves, succinctly summarizing previous results. The approach relies on an interpretation of ROC-type summary curves as plots of an expected utility versus an expected disutility (or penalty) for signal-present decisions. We propose a general utility structure that is flexible enough to encompass many ROC variants and yet sufficiently constrained to allow derivation of a linear expected utility equation that is similar to that for simple binary detection. We illustrate our theory with an example comparing decision strategies for joint detection-estimation of a known signal with unknown amplitude. In addition, building on insights from our utility framework, we propose new ROC-type summary curves and associated optimal decision rules for joint detection-estimation tasks with an unknown, potentially-multiple, number of signals in each observation.

Selection of optimal multispectral imaging system parameters for small joint arthritis detection

NASA Astrophysics Data System (ADS)

Dolenec, Rok; Laistler, Elmar; Stergar, Jost; Milanic, Matija

2018-02-01

Early detection and treatment of arthritis is essential for a successful outcome of the treatment, but it has proven to be very challenging with existing diagnostic methods. Novel methods based on the optical imaging of the affected joints are becoming an attractive alternative. A non-contact multispectral imaging (MSI) system for imaging of small joints of human hands and feet is being developed. In this work, a numerical simulation of the MSI system is presented. The purpose of the simulation is to determine the optimal design parameters. Inflamed and unaffected human joint models were constructed with a realistic geometry and tissue distributions, based on a MRI scan of a human finger with a spatial resolution of 0.2 mm. The light transport simulation is based on a weighted-photon 3D Monte Carlo method utilizing CUDA GPU acceleration. An uniform illumination of the finger within the 400-1100 nm spectral range was simulated and the photons exiting the joint were recorded using different acceptance angles. From the obtained reflectance and transmittance images the spectral and spatial features most indicative of inflammation were identified. Optimal acceptance angle and spectral bands were determined. This study demonstrates that proper selection of MSI system parameters critically affects ability of a MSI system to discriminate the unaffected and inflamed joints. The presented system design optimization approach could be applied to other pathologies.

Optimal space-time attacks on system state estimation under a sparsity constraint

NASA Astrophysics Data System (ADS)

Lu, Jingyang; Niu, Ruixin; Han, Puxiao

2016-05-01

System state estimation in the presence of an adversary that injects false information into sensor readings has attracted much attention in wide application areas, such as target tracking with compromised sensors, secure monitoring of dynamic electric power systems, secure driverless cars, and radar tracking and detection in the presence of jammers. From a malicious adversary's perspective, the optimal strategy for attacking a multi-sensor dynamic system over sensors and over time is investigated. It is assumed that the system defender can perfectly detect the attacks and identify and remove sensor data once they are corrupted by false information injected by the adversary. With this in mind, the adversary's goal is to maximize the covariance matrix of the system state estimate by the end of attack period under a sparse attack constraint such that the adversary can only attack the system a few times over time and over sensors. The sparsity assumption is due to the adversary's limited resources and his/her intention to reduce the chance of being detected by the system defender. This becomes an integer programming problem and its optimal solution, the exhaustive search, is intractable with a prohibitive complexity, especially for a system with a large number of sensors and over a large number of time steps. Several suboptimal solutions, such as those based on greedy search and dynamic programming are proposed to find the attack strategies. Examples and numerical results are provided in order to illustrate the effectiveness and the reduced computational complexities of the proposed attack strategies.

Optimized static and video EEG rapid serial visual presentation (RSVP) paradigm based on motion surprise computation

NASA Astrophysics Data System (ADS)

Khosla, Deepak; Huber, David J.; Bhattacharyya, Rajan

2017-05-01

In this paper, we describe an algorithm and system for optimizing search and detection performance for "items of interest" (IOI) in large-sized images and videos that employ the Rapid Serial Visual Presentation (RSVP) based EEG paradigm and surprise algorithms that incorporate motion processing to determine whether static or video RSVP is used. The system works by first computing a motion surprise map on image sub-regions (chips) of incoming sensor video data and then uses those surprise maps to label the chips as either "static" or "moving". This information tells the system whether to use a static or video RSVP presentation and decoding algorithm in order to optimize EEG based detection of IOI in each chip. Using this method, we are able to demonstrate classification of a series of image regions from video with an azimuth value of 1, indicating perfect classification, over a range of display frequencies and video speeds.

Evaluation of 5 different labeled polymer immunohistochemical detection systems.

PubMed

Skaland, Ivar; Nordhus, Marit; Gudlaugsson, Einar; Klos, Jan; Kjellevold, Kjell H; Janssen, Emiel A M; Baak, Jan P A

2010-01-01

Immunohistochemical staining is important for diagnosis and therapeutic decision making but the results may vary when different detection systems are used. To analyze this, 5 different labeled polymer immunohistochemical detection systems, REAL EnVision, EnVision Flex, EnVision Flex+ (Dako, Glostrup, Denmark), NovoLink (Novocastra Laboratories Ltd, Newcastle Upon Tyne, UK) and UltraVision ONE (Thermo Fisher Scientific, Fremont, CA) were tested using 12 different, widely used mouse and rabbit primary antibodies, detecting nuclear, cytoplasmic, and membrane antigens. Serial sections of multitissue blocks containing 4% formaldehyde fixed paraffin embedded material were selected for their weak, moderate, and strong staining for each antibody. Specificity and sensitivity were evaluated by subjective scoring and digital image analysis. At optimal primary antibody dilution, digital image analysis showed that EnVision Flex+ was the most sensitive system (P < 0.005), with means of 8.3, 13.4, 20.2, and 41.8 gray scale values stronger staining than REAL EnVision, EnVision Flex, NovoLink, and UltraVision ONE, respectively. NovoLink was the second most sensitive system for mouse antibodies, but showed low sensitivity for rabbit antibodies. Due to low sensitivity, 2 cases with UltraVision ONE and 1 case with NovoLink stained false negatively. None of the detection systems showed any distinct false positivity, but UltraVision ONE and NovoLink consistently showed weak background staining both in negative controls and at optimal primary antibody dilution. We conclude that there are significant differences in sensitivity, specificity, costs, and total assay time in the immunohistochemical detection systems currently in use.

Fault tolerant filtering and fault detection for quantum systems driven by fields in single photon states

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

Gao, Qing, E-mail: qing.gao.chance@gmail.com; Dong, Daoyi, E-mail: daoyidong@gmail.com; Petersen, Ian R., E-mail: i.r.petersen@gmai.com

The purpose of this paper is to solve the fault tolerant filtering and fault detection problem for a class of open quantum systems driven by a continuous-mode bosonic input field in single photon states when the systems are subject to stochastic faults. Optimal estimates of both the system observables and the fault process are simultaneously calculated and characterized by a set of coupled recursive quantum stochastic differential equations.

C-SPECT - a Clinical Cardiac SPECT/Tct Platform: Design Concepts and Performance Potential

PubMed Central

Chang, Wei; Ordonez, Caesar E.; Liang, Haoning; Li, Yusheng; Liu, Jingai

2013-01-01

Because of scarcity of photons emitted from the heart, clinical cardiac SPECT imaging is mainly limited by photon statistics. The sub-optimal detection efficiency of current SPECT systems not only limits the quality of clinical cardiac SPECT imaging but also makes more advanced potential applications difficult to be realized. We propose a high-performance system platform - C-SPECT, which has its sampling geometry optimized for detection of emitted photons in quality and quantity. The C-SPECT has a stationary C-shaped gantry that surrounds the left-front side of a patient’s thorax. The stationary C-shaped collimator and detector systems in the gantry provide effective and efficient detection and sampling of photon emission. For cardiac imaging, the C-SPECT platform could achieve 2 to 4 times the system geometric efficiency of conventional SPECT systems at the same sampling resolution. This platform also includes an integrated transmission CT for attenuation correction. The ability of C-SPECT systems to perform sequential high-quality emission and transmission imaging could bring cost-effective high-performance to clinical imaging. In addition, a C-SPECT system could provide high detection efficiency to accommodate fast acquisition rate for gated and dynamic cardiac imaging. This paper describes the design concepts and performance potential of C-SPECT, and illustrates how these concepts can be implemented in a basic system. PMID:23885129

Using advanced computer vision algorithms on small mobile robots

NASA Astrophysics Data System (ADS)

Kogut, G.; Birchmore, F.; Biagtan Pacis, E.; Everett, H. R.

2006-05-01

The Technology Transfer project employs a spiral development process to enhance the functionality and autonomy of mobile robot systems in the Joint Robotics Program (JRP) Robotic Systems Pool by converging existing component technologies onto a transition platform for optimization. An example of this approach is the implementation of advanced computer vision algorithms on small mobile robots. We demonstrate the implementation and testing of the following two algorithms useful on mobile robots: 1) object classification using a boosted Cascade of classifiers trained with the Adaboost training algorithm, and 2) human presence detection from a moving platform. Object classification is performed with an Adaboost training system developed at the University of California, San Diego (UCSD) Computer Vision Lab. This classification algorithm has been used to successfully detect the license plates of automobiles in motion in real-time. While working towards a solution to increase the robustness of this system to perform generic object recognition, this paper demonstrates an extension to this application by detecting soda cans in a cluttered indoor environment. The human presence detection from a moving platform system uses a data fusion algorithm which combines results from a scanning laser and a thermal imager. The system is able to detect the presence of humans while both the humans and the robot are moving simultaneously. In both systems, the two aforementioned algorithms were implemented on embedded hardware and optimized for use in real-time. Test results are shown for a variety of environments.

Autonomous Component Health Management with Failed Component Detection, Identification, and Avoidance

NASA Technical Reports Server (NTRS)

Davis, Robert N.; Polites, Michael E.; Trevino, Luis C.

2004-01-01

This paper details a novel scheme for autonomous component health management (ACHM) with failed actuator detection and failed sensor detection, identification, and avoidance. This new scheme has features that far exceed the performance of systems with triple-redundant sensing and voting, yet requires fewer sensors and could be applied to any system with redundant sensing. Relevant background to the ACHM scheme is provided, and the simulation results for the application of that scheme to a single-axis spacecraft attitude control system with a 3rd order plant and dual-redundant measurement of system states are presented. ACHM fulfills key functions needed by an integrated vehicle health monitoring (IVHM) system. It is: autonomous; adaptive; works in realtime; provides optimal state estimation; identifies failed components; avoids failed components; reconfigures for multiple failures; reconfigures for intermittent failures; works for hard-over, soft, and zero-output failures; and works for both open- and closed-loop systems. The ACHM scheme combines a prefilter that generates preliminary state estimates, detects and identifies failed sensors and actuators, and avoids the use of failed sensors in state estimation with a fixed-gain Kalman filter that generates optimal state estimates and provides model-based state estimates that comprise an integral part of the failure detection logic. The results show that ACHM successfully isolates multiple persistent and intermittent hard-over, soft, and zero-output failures. It is now ready to be tested on a computer model of an actual system.

Optimal estimation of recurrence structures from time series

NASA Astrophysics Data System (ADS)

beim Graben, Peter; Sellers, Kristin K.; Fröhlich, Flavio; Hutt, Axel

2016-05-01

Recurrent temporal dynamics is a phenomenon observed frequently in high-dimensional complex systems and its detection is a challenging task. Recurrence quantification analysis utilizing recurrence plots may extract such dynamics, however it still encounters an unsolved pertinent problem: the optimal selection of distance thresholds for estimating the recurrence structure of dynamical systems. The present work proposes a stochastic Markov model for the recurrent dynamics that allows for the analytical derivation of a criterion for the optimal distance threshold. The goodness of fit is assessed by a utility function which assumes a local maximum for that threshold reflecting the optimal estimate of the system's recurrence structure. We validate our approach by means of the nonlinear Lorenz system and its linearized stochastic surrogates. The final application to neurophysiological time series obtained from anesthetized animals illustrates the method and reveals novel dynamic features of the underlying system. We propose the number of optimal recurrence domains as a statistic for classifying an animals' state of consciousness.

Image gathering and processing - Information and fidelity

NASA Technical Reports Server (NTRS)

Huck, F. O.; Fales, C. L.; Halyo, N.; Samms, R. W.; Stacy, K.

1985-01-01

In this paper we formulate and use information and fidelity criteria to assess image gathering and processing, combining optical design with image-forming and edge-detection algorithms. The optical design of the image-gathering system revolves around the relationship among sampling passband, spatial response, and signal-to-noise ratio (SNR). Our formulations of information, fidelity, and optimal (Wiener) restoration account for the insufficient sampling (i.e., aliasing) common in image gathering as well as for the blurring and noise that conventional formulations account for. Performance analyses and simulations for ordinary optical-design constraints and random scences indicate that (1) different image-forming algorithms prefer different optical designs; (2) informationally optimized designs maximize the robustness of optimal image restorations and lead to the highest-spatial-frequency channel (relative to the sampling passband) for which edge detection is reliable (if the SNR is sufficiently high); and (3) combining the informationally optimized design with a 3 by 3 lateral-inhibitory image-plane-processing algorithm leads to a spatial-response shape that approximates the optimal edge-detection response of (Marr's model of) human vision and thus reduces the data preprocessing and transmission required for machine vision.

Joint Sensing/Sampling Optimization for Surface Drifting Mine Detection with High-Resolution Drift Model

DTIC Science & Technology

2012-09-01

as potential tools for large area detection coverage while being moderately inexpensive (Wettergren, Performance of Search via Track - Before - Detect for...via Track - Before - Detect for Distribute 34 Sensor Networks, 2008). These statements highlight three specific needs to further sensor network research...Bay hydrography. Journal of Marine Systems, 12, 221–236. Wettergren, T. A. (2008). Performance of search via track - before - detect for distributed

A fiber-based quasi-continuous-wave quantum key distribution system

PubMed Central

Shen, Yong; Chen, Yan; Zou, Hongxin; Yuan, Jianmin

2014-01-01

We report a fiber-based quasi-continuous-wave (CW) quantum key distribution (QKD) system with continuous variables (CV). This system employs coherent light pulses and time multiplexing to maximally reduce cross talk in the fiber. No-switching detection scheme is adopted to optimize the repetition rate. Information is encoded on the sideband of the pulsed coherent light to fully exploit the continuous wave nature of laser field. With this configuration, high secret key rate can be achieved. For the 50 MHz detected bandwidth in our experiment, when the multidimensional reconciliation protocol is applied, a secret key rate of 187 kb/s can be achieved over 50 km of optical fiber against collective attacks, which have been shown to be asymptotically optimal. Moreover, recently studied loopholes have been fixed in our system. PMID:24691409

An embedded real-time red peach detection system based on an OV7670 camera, ARM cortex-M4 processor and 3D look-up tables.

PubMed

Teixidó, Mercè; Font, Davinia; Pallejà, Tomàs; Tresanchez, Marcel; Nogués, Miquel; Palacín, Jordi

2012-10-22

This work proposes the development of an embedded real-time fruit detection system for future automatic fruit harvesting. The proposed embedded system is based on an ARM Cortex-M4 (STM32F407VGT6) processor and an Omnivision OV7670 color camera. The future goal of this embedded vision system will be to control a robotized arm to automatically select and pick some fruit directly from the tree. The complete embedded system has been designed to be placed directly in the gripper tool of the future robotized harvesting arm. The embedded system will be able to perform real-time fruit detection and tracking by using a three-dimensional look-up-table (LUT) defined in the RGB color space and optimized for fruit picking. Additionally, two different methodologies for creating optimized 3D LUTs based on existing linear color models and fruit histograms were implemented in this work and compared for the case of red peaches. The resulting system is able to acquire general and zoomed orchard images and to update the relative tracking information of a red peach in the tree ten times per second.

An Embedded Real-Time Red Peach Detection System Based on an OV7670 Camera, ARM Cortex-M4 Processor and 3D Look-Up Tables

PubMed Central

Teixidó, Mercè; Font, Davinia; Pallejà, Tomàs; Tresanchez, Marcel; Nogués, Miquel; Palacín, Jordi

2012-01-01

This work proposes the development of an embedded real-time fruit detection system for future automatic fruit harvesting. The proposed embedded system is based on an ARM Cortex-M4 (STM32F407VGT6) processor and an Omnivision OV7670 color camera. The future goal of this embedded vision system will be to control a robotized arm to automatically select and pick some fruit directly from the tree. The complete embedded system has been designed to be placed directly in the gripper tool of the future robotized harvesting arm. The embedded system will be able to perform real-time fruit detection and tracking by using a three-dimensional look-up-table (LUT) defined in the RGB color space and optimized for fruit picking. Additionally, two different methodologies for creating optimized 3D LUTs based on existing linear color models and fruit histograms were implemented in this work and compared for the case of red peaches. The resulting system is able to acquire general and zoomed orchard images and to update the relative tracking information of a red peach in the tree ten times per second. PMID:23202040

Optimization design of the angle detecting system used in the fast steering mirror

NASA Astrophysics Data System (ADS)

Ni, Ying-xue; Wu, Jia-bin; San, Xiao-gang; Gao, Shi-jie; Ding, Shao-hang; Wang, Jing; Wang, Tao; Wang, Hui-xian

2018-01-01

In this paper, in order to design a fast steering mirror (FSM) with large deflection angle and high linearity, a deflection angle detecting system (DADS) using quadrant detector (QD) is developed. And the mathematical model describing DADS is established by analyzing the principle of position detecting and error characteristics of QD. Based on this mathematical model, the variation tendencies of deflection angle and linearity of FSM are simulated. Then, by changing the parameters of the DADS, the optimization of deflection angle and linearity of FSM is demonstrated. Finally, a QD-based FSM is designed based on this method, which achieves ±2° deflection angle and 0.72% and 0.68% linearity along x and y axis, respectively. Moreover, this method will be beneficial to the design of large deflection angle and high linearity FSM.

Optimization of metabolite detection by quantum mechanics simulations in magnetic resonance spectroscopy.

PubMed

Gambarota, Giulio

2017-07-15

Magnetic resonance spectroscopy (MRS) is a well established modality for investigating tissue metabolism in vivo. In recent years, many efforts by the scientific community have been directed towards the improvement of metabolite detection and quantitation. Quantum mechanics simulations allow for investigations of the MR signal behaviour of metabolites; thus, they provide an essential tool in the optimization of metabolite detection. In this review, we will examine quantum mechanics simulations based on the density matrix formalism. The density matrix was introduced by von Neumann in 1927 to take into account statistical effects within the theory of quantum mechanics. We will discuss the main steps of the density matrix simulation of an arbitrary spin system and show some examples for the strongly coupled two spin system. Copyright © 2016 Elsevier Inc. All rights reserved.

Label-Free Toxin Detection by Means of Time-Resolved Electrochemical Impedance Spectroscopy

PubMed Central

Chai, Changhoon; Takhistov, Paul

2010-01-01

The real-time detection of trace concentrations of biological toxins requires significant improvement of the detection methods from those reported in the literature. To develop a highly sensitive and selective detection device it is necessary to determine the optimal measuring conditions for the electrochemical sensor in three domains: time, frequency and polarization potential. In this work we utilized a time-resolved electrochemical impedance spectroscopy for the detection of trace concentrations of Staphylococcus enterotoxin B (SEB). An anti-SEB antibody has been attached to the nano-porous aluminum surface using 3-aminopropyltriethoxysilane/glutaraldehyde coupling system. This immobilization method allows fabrication of a highly reproducible and stable sensing device. Using developed immobilization procedure and optimized detection regime, it is possible to determine the presence of SEB at the levels as low as 10 pg/mL in 15 minutes. PMID:22315560

Fusion of Optimized Indicators from Advanced Driver Assistance Systems (ADAS) for Driver Drowsiness Detection

PubMed Central

Daza, Iván G.; Bergasa, Luis M.; Bronte, Sebastián; Yebes, J. Javier; Almazán, Javier; Arroyo, Roberto

2014-01-01

This paper presents a non-intrusive approach for monitoring driver drowsiness using the fusion of several optimized indicators based on driver physical and driving performance measures, obtained from ADAS (Advanced Driver Assistant Systems) in simulated conditions. The paper is focused on real-time drowsiness detection technology rather than on long-term sleep/awake regulation prediction technology. We have developed our own vision system in order to obtain robust and optimized driver indicators able to be used in simulators and future real environments. These indicators are principally based on driver physical and driving performance skills. The fusion of several indicators, proposed in the literature, is evaluated using a neural network and a stochastic optimization method to obtain the best combination. We propose a new method for ground-truth generation based on a supervised Karolinska Sleepiness Scale (KSS). An extensive evaluation of indicators, derived from trials over a third generation simulator with several test subjects during different driving sessions, was performed. The main conclusions about the performance of single indicators and the best combinations of them are included, as well as the future works derived from this study. PMID:24412904

Communications and tracking expert systems study

NASA Technical Reports Server (NTRS)

Leibfried, T. F.; Feagin, Terry; Overland, David

1987-01-01

The original objectives of the study consisted of five broad areas of investigation: criteria and issues for explanation of communication and tracking system anomaly detection, isolation, and recovery; data storage simplification issues for fault detection expert systems; data selection procedures for decision tree pruning and optimization to enhance the abstraction of pertinent information for clear explanation; criteria for establishing levels of explanation suited to needs; and analysis of expert system interaction and modularization. Progress was made in all areas, but to a lesser extent in the criteria for establishing levels of explanation suited to needs. Among the types of expert systems studied were those related to anomaly or fault detection, isolation, and recovery.

Study on development system of increasing gearbox for high-performance wind-power generator

NASA Astrophysics Data System (ADS)

Xu, Hongbin; Yan, Kejun; Zhao, Junyu

2005-12-01

Based on the analysis of the development potentiality of wind-power generator and domestic manufacture of its key parts in China, an independent development system of the Increasing Gearbox for High-performance Wind-power Generator (IGHPWG) was introduced. The main elements of the system were studied, including the procedure design, design analysis system, manufacturing technology and detecting system, and the relative important technologies were analyzed such as mixed optimal joint transmission structure of the first planetary drive with two grade parallel axle drive based on equal strength, tooth root round cutting technology before milling hard tooth surface, high-precise tooth grinding technology, heat treatment optimal technology and complex surface technique, and rig test and detection technique of IGHPWG. The development conception was advanced the data share and quality assurance system through all the elements of the development system. The increasing Gearboxes for 600KW and 1MW Wind-power Generator have been successfully developed through the application of the development system.

Robust Video Stabilization Using Particle Keypoint Update and l1-Optimized Camera Path

PubMed Central

Jeon, Semi; Yoon, Inhye; Jang, Jinbeum; Yang, Seungji; Kim, Jisung; Paik, Joonki

2017-01-01

Acquisition of stabilized video is an important issue for various type of digital cameras. This paper presents an adaptive camera path estimation method using robust feature detection to remove shaky artifacts in a video. The proposed algorithm consists of three steps: (i) robust feature detection using particle keypoints between adjacent frames; (ii) camera path estimation and smoothing; and (iii) rendering to reconstruct a stabilized video. As a result, the proposed algorithm can estimate the optimal homography by redefining important feature points in the flat region using particle keypoints. In addition, stabilized frames with less holes can be generated from the optimal, adaptive camera path that minimizes a temporal total variation (TV). The proposed video stabilization method is suitable for enhancing the visual quality for various portable cameras and can be applied to robot vision, driving assistant systems, and visual surveillance systems. PMID:28208622

Lab-on-a-chip sensor for measuring Zn by stripping voltammetry

NASA Astrophysics Data System (ADS)

Pei, Xing; Kang, Wenjing; Yue, Wei; Bange, Adam; Wong, Hector R.; Heineman, William R.; Papautsky, Ian

2012-03-01

This work reports on continuing development of a lab-on-a-chip sensor for electrochemical detection of heavy metal zinc in blood serum. The sensor consists of a three electrode system, including an environmentally-friendly bismuth working electrode, a Ag/AgCl reference electrode, and a gold auxiliary electrode. By optimizing the electrodeposition of bismuth film, better control of fabrication steps and improving interface between the sensor and potentiostat, repeatability and sensitivity of the lab-on-a-chip sensor has been improved. Through optimization of electrolyte and stripping voltammetry parameters, limits of detection were greatly improved. The optimized sensor was able to measure zinc in in the physiological range of 65-95 μg/dL. Ultimately, with further development and integrated sample preparation sensor system will permit rapid (min) measurements of zinc from a sub-mL sample (a few drops of blood) for bedside monitoring.

A coupled classification - evolutionary optimization model for contamination event detection in water distribution systems.

PubMed

Oliker, Nurit; Ostfeld, Avi

2014-03-15

This study describes a decision support system, alerts for contamination events in water distribution systems. The developed model comprises a weighted support vector machine (SVM) for the detection of outliers, and a following sequence analysis for the classification of contamination events. The contribution of this study is an improvement of contamination events detection ability and a multi-dimensional analysis of the data, differing from the parallel one-dimensional analysis conducted so far. The multivariate analysis examines the relationships between water quality parameters and detects changes in their mutual patterns. The weights of the SVM model accomplish two goals: blurring the difference between sizes of the two classes' data sets (as there are much more normal/regular than event time measurements), and adhering the time factor attribute by a time decay coefficient, ascribing higher importance to recent observations when classifying a time step measurement. All model parameters were determined by data driven optimization so the calibration of the model was completely autonomic. The model was trained and tested on a real water distribution system (WDS) data set with randomly simulated events superimposed on the original measurements. The model is prominent in its ability to detect events that were only partly expressed in the data (i.e., affecting only some of the measured parameters). The model showed high accuracy and better detection ability as compared to previous modeling attempts of contamination event detection. Copyright © 2013 Elsevier Ltd. All rights reserved.

Optimal Design of Integrated Systems Health Management (ISHM) Systems for improving safety in NASA's Exploration Vehicles: A Two-Level Multidisciplinary Design Approach

NASA Technical Reports Server (NTRS)

Mehr, Ali Farhang; Tumer, Irem; Barszcz, Eric

2005-01-01

Integrated Vehicle Health Management (ISHM) systems are used to detect, assess, and isolate functional failures in order to improve safety of space systems such as Orbital Space Planes (OSPs). An ISHM system, as a whole, consists of several subsystems that monitor different components of an OSP including: Spacecraft, Launch Vehicle, Ground Control, and the International Space Station. In this research, therefore, we propose a new methodology to design and optimize ISHM as a distributed system with multiple disciplines (that correspond to different subsystems of OSP safety). A paramount amount of interest has been given in the literature to the multidisciplinary design optimization of problems with such architecture (as will be reviewed in the full paper).

Spatiotemporal and geometric optimization of sensor arrays for detecting analytes fluids

DOEpatents

Lewis, Nathan S.; Freund, Michael S.; Briglin, Shawn M.; Tokumaru, Phil; Martin, Charles R.; Mitchell, David T.

2006-10-17

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.

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

DOEpatents

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.

Automated Detection of Clinically Significant Prostate Cancer in mp-MRI Images Based on an End-to-End Deep Neural Network.

PubMed

Wang, Zhiwei; Liu, Chaoyue; Cheng, Danpeng; Wang, Liang; Yang, Xin; Cheng, Kwang-Ting

2018-05-01

Automated methods for detecting clinically significant (CS) prostate cancer (PCa) in multi-parameter magnetic resonance images (mp-MRI) are of high demand. Existing methods typically employ several separate steps, each of which is optimized individually without considering the error tolerance of other steps. As a result, they could either involve unnecessary computational cost or suffer from errors accumulated over steps. In this paper, we present an automated CS PCa detection system, where all steps are optimized jointly in an end-to-end trainable deep neural network. The proposed neural network consists of concatenated subnets: 1) a novel tissue deformation network (TDN) for automated prostate detection and multimodal registration and 2) a dual-path convolutional neural network (CNN) for CS PCa detection. Three types of loss functions, i.e., classification loss, inconsistency loss, and overlap loss, are employed for optimizing all parameters of the proposed TDN and CNN. In the training phase, the two nets mutually affect each other and effectively guide registration and extraction of representative CS PCa-relevant features to achieve results with sufficient accuracy. The entire network is trained in a weakly supervised manner by providing only image-level annotations (i.e., presence/absence of PCa) without exact priors of lesions' locations. Compared with most existing systems which require supervised labels, e.g., manual delineation of PCa lesions, it is much more convenient for clinical usage. Comprehensive evaluation based on fivefold cross validation using 360 patient data demonstrates that our system achieves a high accuracy for CS PCa detection, i.e., a sensitivity of 0.6374 and 0.8978 at 0.1 and 1 false positives per normal/benign patient.

Observer model optimization of a spectral mammography system

NASA Astrophysics Data System (ADS)

Fredenberg, Erik; Åslund, Magnus; Cederström, Björn; Lundqvist, Mats; Danielsson, Mats

2010-04-01

Spectral imaging is a method in medical x-ray imaging to extract information about the object constituents by the material-specific energy dependence of x-ray attenuation. Contrast-enhanced spectral imaging has been thoroughly investigated, but unenhanced imaging may be more useful because it comes as a bonus to the conventional non-energy-resolved absorption image at screening; there is no additional radiation dose and no need for contrast medium. We have used a previously developed theoretical framework and system model that include quantum and anatomical noise to characterize the performance of a photon-counting spectral mammography system with two energy bins for unenhanced imaging. The theoretical framework was validated with synthesized images. Optimal combination of the energy-resolved images for detecting large unenhanced tumors corresponded closely, but not exactly, to minimization of the anatomical noise, which is commonly referred to as energy subtraction. In that case, an ideal-observer detectability index could be improved close to 50% compared to absorption imaging. Optimization with respect to the signal-to-quantum-noise ratio, commonly referred to as energy weighting, deteriorated detectability. For small microcalcifications or tumors on uniform backgrounds, however, energy subtraction was suboptimal whereas energy weighting provided a minute improvement. The performance was largely independent of beam quality, detector energy resolution, and bin count fraction. It is clear that inclusion of anatomical noise and imaging task in spectral optimization may yield completely different results than an analysis based solely on quantum noise.

Detecting Tie2, an endothelial growth factor receptor, by using immunohistochemistry in mouse lungs.

PubMed

Guha, Prajna P; David, Sascha A; Ghosh, Chandra C

2014-01-01

Immunohistochemical (IHC) staining is an invaluable, sensitive, and effective method to detect the presence and localization of proteins in the cellular compartment in tissues. The basic concept of IHC is detecting the antigen in tissues by means of specific antibody binding, which is then demonstrated with a colored histochemical reaction that can be observed under a light microscope. The most challenging aspect of IHC techniques is optimizing the precise experimental conditions that are required to get a specific and a strong signal. The critical steps of IHC are specimen acquisition, fixation, permeabilization, detection system, and selection of the antigen specific antibody and its optimization. Here, we elaborate the technique using the endothelial growth factor binding receptor Tie2 in mouse lungs.

Expanding the detection efficiency of silicon drift detectors

NASA Astrophysics Data System (ADS)

Schlosser, D. M.; Lechner, P.; Lutz, G.; Niculae, A.; Soltau, H.; Strüder, L.; Eckhardt, R.; Hermenau, K.; Schaller, G.; Schopper, F.; Jaritschin, O.; Liebel, A.; Simsek, A.; Fiorini, C.; Longoni, A.

2010-12-01

To expand the detection efficiency Silicon Drift Detectors (SDDs) with various customized radiation entrance windows, optimized detector areas and geometries have been developed. Optimum values for energy resolution, peak to background ratio (P/B) and high count rate capability support the development. Detailed results on sensors optimized for light element detection down to Boron or even lower will be reported. New developments for detecting medium and high X-ray energies by increasing the effective detector thickness will be presented. Gamma-ray detectors consisting of a SDD coupled to scintillators like CsI(Tl) and LaBr 3(Ce) have been examined. Results of the energy resolution for the 137Cs 662 keV line and the light yield (LY) of such detector systems will be reported.

A Fluorescent Tile DNA Diagnocode System for In Situ Rapid and Selective Diagnosis of Cytosolic RNA Cancer Markers

PubMed Central

Park, Kyung Soo; Shin, Seung Won; Jang, Min Su; Shin, Woojung; Yang, Kisuk; Min, Junhong; Cho, Seung-Woo; Oh, Byung-Keun; Bae, Jong Wook; Jung, Sunghwan; Choi, Jeong-Woo; Um, Soong Ho

2015-01-01

Accurate cancer diagnosis often requires extraction and purification of genetic materials from cells, and sophisticated instrumentations that follow. Otherwise in order to directly treat the diagnostic materials to cells, multiple steps to optimize dose concentration and treatment time are necessary due to diversity in cellular behaviors. These processes may offer high precision but hinder fast analysis of cancer, especially in clinical situations that need rapid detection and characterization of cancer. Here we present a novel fluorescent tile DNA nanostructure delivered to cancer cytosol by employing nanoparticle technology. Its structural anisotropicity offers easy manipulation for multifunctionalities, enabling the novel DNA nanostructure to detect intracellular cancer RNA markers with high specificity within 30 minutes post treatment, while the nanoparticle property bypasses the requirement of treatment optimization, effectively reducing the complexity of applying the system for cancer diagnosis. Altogether, the system offers a precise and rapid detection of cancer, suggesting the future use in the clinical fields. PMID:26678430

Evaluation of Gene Expression Endpoints in the Context of a Xenopus laevis Metamorphosis-based Bioassay to Detect Thyroid Hormone Disruptors

EPA Science Inventory

This study accentuates the need to examine multiple tissues and provides critical information required for optimization of exposure regimens and endpoint assessments that focus on the detection of disruption in TH-regulatory systems.

Neural-network-based navigation and control of unmanned aerial vehicles for detecting unintended emissions

NASA Astrophysics Data System (ADS)

Zargarzadeh, H.; Nodland, David; Thotla, V.; Jagannathan, S.; Agarwal, S.

2012-06-01

Unmanned Aerial Vehicles (UAVs) are versatile aircraft with many applications, including the potential for use to detect unintended electromagnetic emissions from electronic devices. A particular area of recent interest has been helicopter unmanned aerial vehicles. Because of the nature of these helicopters' dynamics, high-performance controller design for them presents a challenge. This paper introduces an optimal controller design via output feedback control for trajectory tracking of a helicopter UAV using a neural network (NN). The output-feedback control system utilizes the backstepping methodology, employing kinematic, virtual, and dynamic controllers and an observer. Optimal tracking is accomplished with a single NN utilized for cost function approximation. The controller positions the helicopter, which is equipped with an antenna, such that the antenna can detect unintended emissions. The overall closed-loop system stability with the proposed controller is demonstrated by using Lyapunov analysis. Finally, results are provided to demonstrate the effectiveness of the proposed control design for positioning the helicopter for unintended emissions detection.

OPTIMAL SCHEDULING OF BOOSTER DISINFECTION IN WATER DISTRIBUTION SYSTEMS

EPA Science Inventory

Booster disinfection is the addition of disinfectant at locations distributed throughout a water distribution system. Such a strategy can reduce the mass of disinfectant required to maintain a detectable residual at points of consumption in the distribution system, which may lea...

All-automatic swimmer tracking system based on an optimized scaled composite JTC technique

NASA Astrophysics Data System (ADS)

Benarab, D.; Napoléon, T.; Alfalou, A.; Verney, A.; Hellard, P.

2016-04-01

In this paper, an all-automatic optimized JTC based swimmer tracking system is proposed and evaluated on real video database outcome from national and international swimming competitions (French National Championship, Limoges 2015, FINA World Championships, Barcelona 2013 and Kazan 2015). First, we proposed to calibrate the swimming pool using the DLT algorithm (Direct Linear Transformation). DLT calculates the homography matrix given a sufficient set of correspondence points between pixels and metric coordinates: i.e. DLT takes into account the dimensions of the swimming pool and the type of the swim. Once the swimming pool is calibrated, we extract the lane. Then we apply a motion detection approach to detect globally the swimmer in this lane. Next, we apply our optimized Scaled Composite JTC which consists of creating an adapted input plane that contains the predicted region and the head reference image. This latter is generated using a composite filter of fin images chosen from the database. The dimension of this reference will be scaled according to the ratio between the head's dimension and the width of the swimming lane. Finally, applying the proposed approach improves the performances of our previous tracking method by adding a detection module in order to achieve an all-automatic swimmer tracking system.

Computational intelligence-based optimization of maximally stable extremal region segmentation for object detection

NASA Astrophysics Data System (ADS)

Davis, Jeremy E.; Bednar, Amy E.; Goodin, Christopher T.; Durst, Phillip J.; Anderson, Derek T.; Bethel, Cindy L.

2017-05-01

Particle swarm optimization (PSO) and genetic algorithms (GAs) are two optimization techniques from the field of computational intelligence (CI) for search problems where a direct solution can not easily be obtained. One such problem is finding an optimal set of parameters for the maximally stable extremal region (MSER) algorithm to detect areas of interest in imagery. Specifically, this paper describes the design of a GA and PSO for optimizing MSER parameters to detect stop signs in imagery produced via simulation for use in an autonomous vehicle navigation system. Several additions to the GA and PSO are required to successfully detect stop signs in simulated images. These additions are a primary focus of this paper and include: the identification of an appropriate fitness function, the creation of a variable mutation operator for the GA, an anytime algorithm modification to allow the GA to compute a solution quickly, the addition of an exponential velocity decay function to the PSO, the addition of an "execution best" omnipresent particle to the PSO, and the addition of an attractive force component to the PSO velocity update equation. Experimentation was performed with the GA using various combinations of selection, crossover, and mutation operators and experimentation was also performed with the PSO using various combinations of neighborhood topologies, swarm sizes, cognitive influence scalars, and social influence scalars. The results of both the GA and PSO optimized parameter sets are presented. This paper details the benefits and drawbacks of each algorithm in terms of detection accuracy, execution speed, and additions required to generate successful problem specific parameter sets.

Size-dependent scanning parameters (kVp and mAs) for photon-counting spectral CT system in pediatric imaging: simulation study

NASA Astrophysics Data System (ADS)

Chen, Han; Danielsson, Mats; Xu, Cheng

2016-06-01

We are developing a photon-counting spectral CT detector with a small pixel size of 0.4× 0.5 mm2, offering a potential advantage for better visualization of small structures in pediatric patients. The purpose of this study is to determine the patient size dependent scanning parameters (kVp and mAs) for pediatric CT in two imaging cases: adipose imaging and iodinated blood imaging. Cylindrical soft-tissue phantoms of diameters between 10-25 cm were used to mimic patients of different ages from 0 to 15 y. For adipose imaging, a 5 mm diameter adipose sphere was assumed as an imaging target, while in the case of iodinated imaging, an iodinated blood sphere of 1 mm in diameter was assumed. By applying the geometry of a commercial CT scanner (GE Lightspeed VCT), simulations were carried out to calculate the detectability index, {{d}\\prime 2} , with tube potentials varying from 40 to 140 kVp. The optimal kVp for each phantom in each imaging case was determined such that the dose-normalized detectability index, {{d}\\prime 2}/ dose, is maximized. With the assumption that the detectability index in pediatric imaging is required the same as in typical adult imaging, the value of mAs at optimal kVp for each phantom was selected to achieve a reference detectability index that was obtained by scanning an adult phantom (30 cm in diameter) in a typical adult CT procedure (120 kVp and 200 mAs) using a modeled energy-integrating system. For adipose imaging, the optimal kVps are 50, 60, 80, and 120 kVp, respectively, for phantoms of 10, 15, 20, and 25 cm in diameter. The corresponding mAs values required to achieve the reference detectability index are only 9%, 23%, 24%, and 54% of the mAs that is used for adult patients at 120 kVp, for 10, 15, 20, and 25 cm diameter phantoms, respectively. In the case of iodinated imaging, a tube potential of 60 kVp was found optimal for all phantoms investigated, and the mAs values required to achieve the reference detectability index are 2%, 9%, 37%, and 109% of the adult mAs. The results also indicate that with the use of respective optimal kVps, the photon-counting spectral system offers up to 30% higher {{d}\\prime 2}/ dose than the modeled energy-integrating system for adipose imaging, and 70% for iodinated imaging.

JPRS report: Science and technology. Central Eurasia

NASA Astrophysics Data System (ADS)

1994-05-01

Translated articles cover the following topics: optimal systems to detect and classify moving objects; multiple identification of optical readings in multisensor information and measurement system; method of first integrals in synthesis of optimal control; study of the development of turbulence in the region of a break above a triangular wing; electroerosion machining in aviation engine construction; and cumulation of a flat shock wave in a tube by a thin parietal gas layer of lower density.

Analysis of the restricting factors of laser countermeasure active detection technology

NASA Astrophysics Data System (ADS)

Zhang, Yufa; Sun, Xiaoquan

2016-07-01

The detection effect of laser active detection system is affected by various kinds of factors. In view of the application requirement of laser active detection, the influence factors for laser active detection are analyzed. The mathematical model of cat eye target detection distance has been built, influence of the parameters of laser detection system and the environment on detection range and the detection efficiency are analyzed. Various parameters constraint detection performance is simulated. The results show that the discovery distance of laser active detection is affected by the laser divergence angle, the incident angle and the visibility of the atmosphere. For a given detection range, the laser divergence angle and the detection efficiency are mutually restricted. Therefore, in view of specific application environment, it is necessary to select appropriate laser detection parameters to achieve optimal detection effect.

[Optimization and assessment of a reverse hybridization system for the detection of HBV drug-resistant mutations].

PubMed

Liu, Yan-chen; Huang, Ai-long; Hu, Yuan; Hu, Jie-li; Lai, Guo-qi; Zhang, Wen-lu

2011-12-01

To establish a detection method for HBV drug-resistant mutations related to lamivudine, adefovir and entecavir by optimization and assessment of reverse hybridization system. 26 degenerated probes covering 10 drug-resistant hotspots of 3 drugs were synthesized and immobilized on the same positively charged nylon membrane. PCR products labeled with digoxigenin were hybridized with corresponding probes. To improve the sensitivity and specificity, 4 reaction steps of reverse hybridization were optimized including the number of labeled digoxigenin, the energy intensity of UV cross-linking, hybridization and stringency wash conditions. To prove the feasibility, the specificity, sensitivity and accuracy of this system were assessed respectively. Sensitive and specific results are obtained by the optimization of the following 4 reaction steps: the primers labeled with 3 digoxigenin, energy intensity of UV cross-linking for 1500 x 0.1 mJ/cm², hybridization at 42 degrees C and stringency wash with 0.5 x SSC and 0.1% SDS solution at 44 degrees C for 30 min. In the assessment of system, the majority of probes have high specificity. The quantity of PCR product with a concentration of 10 ng/μl or above can be detected by this method. The concordant rate between reverse hybridization and direct sequencing is 93.9% in the clinical sample test. Though the specificity of several probes needs to be improved further, it is a simple, rapid and sensitive method which can detect HBV resistant mutations related to lamivudine, adefovir and entecavir simultaneously. Due to the short distance between 180 and 181, likewise 202 and 204, the sequence of the same probe covers two codon positions, and hybridization will be interfered by each other. To avoid such interference, the possible solution is that probes are designed by arranging and combining various forms of two near codons.

Flight elements: Fault detection and fault management

NASA Technical Reports Server (NTRS)

Lum, H.; Patterson-Hine, A.; Edge, J. T.; Lawler, D.

1990-01-01

Fault management for an intelligent computational system must be developed using a top down integrated engineering approach. An approach proposed includes integrating the overall environment involving sensors and their associated data; design knowledge capture; operations; fault detection, identification, and reconfiguration; testability; causal models including digraph matrix analysis; and overall performance impacts on the hardware and software architecture. Implementation of the concept to achieve a real time intelligent fault detection and management system will be accomplished via the implementation of several objectives, which are: Development of fault tolerant/FDIR requirement and specification from a systems level which will carry through from conceptual design through implementation and mission operations; Implementation of monitoring, diagnosis, and reconfiguration at all system levels providing fault isolation and system integration; Optimize system operations to manage degraded system performance through system integration; and Lower development and operations costs through the implementation of an intelligent real time fault detection and fault management system and an information management system.

Directed Design of Experiments for Validating Probability of Detection Capability of a Testing System

NASA Technical Reports Server (NTRS)

Generazio, Edward R. (Inventor)

2012-01-01

A method of validating a probability of detection (POD) testing system using directed design of experiments (DOE) includes recording an input data set of observed hit and miss or analog data for sample components as a function of size of a flaw in the components. The method also includes processing the input data set to generate an output data set having an optimal class width, assigning a case number to the output data set, and generating validation instructions based on the assigned case number. An apparatus includes a host machine for receiving the input data set from the testing system and an algorithm for executing DOE to validate the test system. The algorithm applies DOE to the input data set to determine a data set having an optimal class width, assigns a case number to that data set, and generates validation instructions based on the case number.

Diversity-optimal power loading for intensity modulated MIMO optical wireless communications.

PubMed

Zhang, Yan-Yu; Yu, Hong-Yi; Zhang, Jian-Kang; Zhu, Yi-Jun

2016-04-18

In this paper, we consider the design of space code for an intensity modulated direct detection multi-input-multi-output optical wireless communication (IM/DD MIMO-OWC) system, in which channel coefficients are independent and non-identically log-normal distributed, with variances and means known at the transmitter and channel state information available at the receiver. Utilizing the existing space code design criterion for IM/DD MIMO-OWC with a maximum likelihood (ML) detector, we design a diversity-optimal space code (DOSC) that maximizes both large-scale diversity and small-scale diversity gains and prove that the spatial repetition code (RC) with a diversity-optimized power allocation is diversity-optimal among all the high dimensional nonnegative space code schemes under a commonly used optical power constraint. In addition, we show that one of significant advantages of the DOSC is to allow low-complexity ML detection. Simulation results indicate that in high signal-to-noise ratio (SNR) regimes, our proposed DOSC significantly outperforms RC, which is the best space code currently available for such system.

A competitive chemiluminescence enzyme immunoassay for rapid and sensitive determination of enrofloxacin

NASA Astrophysics Data System (ADS)

Yu, Fei; Wu, Yongjun; Yu, Songcheng; Zhang, Huili; Zhang, Hongquan; Qu, Lingbo; Harrington, Peter de B.

With alkaline phosphatase (ALP)-adamantane (AMPPD) system as the chemiluminescence (CL) detection system, a highly sensitive, specific and simple competitive chemiluminescence enzyme immunoassay (CLEIA) was developed for the measurement of enrofloxacin (ENR). The physicochemical parameters, such as the chemiluminescent assay mediums, the dilution buffer of ENR-McAb, the volume of dilution buffer, the monoclonal antibody concentration, the incubation time, and other relevant variables of the immunoassay have been optimized. Under the optimal conditions, the detection linear range of 350-1000 pg/mL and the detection limit of 0.24 ng/mL were provided by the proposed method. The relative standard deviations were less than 15% for both intra and inter-assay precision. This method has been successfully applied to determine ENR in spiked samples with the recovery of 103%-96%. It showed that CLEIA was a good potential method in the analysis of residues of veterinary drugs after treatment of related diseases.

Real-time vibration-based structural damage detection using one-dimensional convolutional neural networks

NASA Astrophysics Data System (ADS)

Abdeljaber, Osama; Avci, Onur; Kiranyaz, Serkan; Gabbouj, Moncef; Inman, Daniel J.

2017-02-01

Structural health monitoring (SHM) and vibration-based structural damage detection have been a continuous interest for civil, mechanical and aerospace engineers over the decades. Early and meticulous damage detection has always been one of the principal objectives of SHM applications. The performance of a classical damage detection system predominantly depends on the choice of the features and the classifier. While the fixed and hand-crafted features may either be a sub-optimal choice for a particular structure or fail to achieve the same level of performance on another structure, they usually require a large computation power which may hinder their usage for real-time structural damage detection. This paper presents a novel, fast and accurate structural damage detection system using 1D Convolutional Neural Networks (CNNs) that has an inherent adaptive design to fuse both feature extraction and classification blocks into a single and compact learning body. The proposed method performs vibration-based damage detection and localization of the damage in real-time. The advantage of this approach is its ability to extract optimal damage-sensitive features automatically from the raw acceleration signals. Large-scale experiments conducted on a grandstand simulator revealed an outstanding performance and verified the computational efficiency of the proposed real-time damage detection method.

Technology forecasting for space communication. Task one report: Cost and weight tradeoff studies for EOS and TDRS

NASA Technical Reports Server (NTRS)

1974-01-01

Weight and cost optimized EOS communication links are determined for 2.25, 7.25, 14.5, 21, and 60 GHz systems and for a 10.6 micron homodyne detection laser system. EOS to ground links are examined for 556, 834, and 1112 km EOS orbits, with ground terminals at the Network Test and Tracking Facility and at Goldstone. Optimized 21 GHz and 10.6 micron links are also examined. For the EOS to Tracking and Data Relay Satellite to ground link, signal-to-noise ratios of the uplink and downlink are also optimized for minimum overall cost or spaceborne weight. Finally, the optimized 21 GHz EOS to ground link is determined for various precipitation rates. All system performance parameters and mission dependent constraints are presented, as are the system cost and weight functional dependencies. The features and capabilities of the computer program to perform the foregoing analyses are described.

A Genetic Algorithm and Fuzzy Logic Approach for Video Shot Boundary Detection

PubMed Central

Thounaojam, Dalton Meitei; Khelchandra, Thongam; Singh, Kh. Manglem; Roy, Sudipta

2016-01-01

This paper proposed a shot boundary detection approach using Genetic Algorithm and Fuzzy Logic. In this, the membership functions of the fuzzy system are calculated using Genetic Algorithm by taking preobserved actual values for shot boundaries. The classification of the types of shot transitions is done by the fuzzy system. Experimental results show that the accuracy of the shot boundary detection increases with the increase in iterations or generations of the GA optimization process. The proposed system is compared to latest techniques and yields better result in terms of F1score parameter. PMID:27127500

ADAPTIVE WATER SENSOR SIGNAL PROCESSING: EXPERIMENTAL RESULTS AND IMPLICATIONS FOR ONLINE CONTAMINANT WARNING SYSTEMS

EPA Science Inventory

A contaminant detection technique and its optimization algorithms have two principal functions. One is the adaptive signal treatment that suppresses background noise and enhances contaminant signals, leading to a promising detection of water quality changes at a false rate as low...

BlueDetect: An iBeacon-Enabled Scheme for Accurate and Energy-Efficient Indoor-Outdoor Detection and Seamless Location-Based Service

PubMed Central

Zou, Han; Jiang, Hao; Luo, Yiwen; Zhu, Jianjie; Lu, Xiaoxuan; Xie, Lihua

2016-01-01

The location and contextual status (indoor or outdoor) is fundamental and critical information for upper-layer applications, such as activity recognition and location-based services (LBS) for individuals. In addition, optimizations of building management systems (BMS), such as the pre-cooling or heating process of the air-conditioning system according to the human traffic entering or exiting a building, can utilize the information, as well. The emerging mobile devices, which are equipped with various sensors, become a feasible and flexible platform to perform indoor-outdoor (IO) detection. However, power-hungry sensors, such as GPS and WiFi, should be used with caution due to the constrained battery storage on mobile device. We propose BlueDetect: an accurate, fast response and energy-efficient scheme for IO detection and seamless LBS running on the mobile device based on the emerging low-power iBeacon technology. By leveraging the on-broad Bluetooth module and our proposed algorithms, BlueDetect provides a precise IO detection service that can turn on/off on-board power-hungry sensors smartly and automatically, optimize their performances and reduce the power consumption of mobile devices simultaneously. Moreover, seamless positioning and navigation services can be realized by it, especially in a semi-outdoor environment, which cannot be achieved by GPS or an indoor positioning system (IPS) easily. We prototype BlueDetect on Android mobile devices and evaluate its performance comprehensively. The experimental results have validated the superiority of BlueDetect in terms of IO detection accuracy, localization accuracy and energy consumption. PMID:26907295

Channel modeling, signal processing and coding for perpendicular magnetic recording

NASA Astrophysics Data System (ADS)

Wu, Zheng

With the increasing areal density in magnetic recording systems, perpendicular recording has replaced longitudinal recording to overcome the superparamagnetic limit. Studies on perpendicular recording channels including aspects of channel modeling, signal processing and coding techniques are presented in this dissertation. To optimize a high density perpendicular magnetic recording system, one needs to know the tradeoffs between various components of the system including the read/write transducers, the magnetic medium, and the read channel. We extend the work by Chaichanavong on the parameter optimization for systems via design curves. Different signal processing and coding techniques are studied. Information-theoretic tools are utilized to determine the acceptable region for the channel parameters when optimal detection and linear coding techniques are used. Our results show that a considerable gain can be achieved by the optimal detection and coding techniques. The read-write process in perpendicular magnetic recording channels includes a number of nonlinear effects. Nonlinear transition shift (NLTS) is one of them. The signal distortion induced by NLTS can be reduced by write precompensation during data recording. We numerically evaluate the effect of NLTS on the read-back signal and examine the effectiveness of several write precompensation schemes in combating NLTS in a channel characterized by both transition jitter noise and additive white Gaussian electronics noise. We also present an analytical method to estimate the bit-error-rate and use it to help determine the optimal write precompensation values in multi-level precompensation schemes. We propose a mean-adjusted pattern-dependent noise predictive (PDNP) detection algorithm for use on the channel with NLTS. We show that this detector can offer significant improvements in bit-error-rate (BER) compared to conventional Viterbi and PDNP detectors. Moreover, the system performance can be further improved by combining the new detector with a simple write precompensation scheme. Soft-decision decoding for algebraic codes can improve performance for magnetic recording systems. In this dissertation, we propose two soft-decision decoding methods for tensor-product parity codes. We also present a list decoding algorithm for generalized error locating codes.

Specific detection of rinderpest virus by real-time reverse transcription-PCR in preclincal and clinical samples of experimentally infected cattle

USDA-ARS?s Scientific Manuscript database

A highly sensitive detection test for Rinderpest virus (RPV), based on a real-time reverse transcription-PCR (RT-PR) system, was developed. Five different RPV genomic targets were examined, and one was selected and optimized to detect viral RNA in infected tissue culture fluid with a level of detec...

An overload behavior detection system for engineering transport vehicles based on deep learning

NASA Astrophysics Data System (ADS)

Zhou, Libo; Wu, Gang

2018-04-01

This paper builds an overloaded truck detect system called ITMD to help traffic department automatically identify the engineering transport vehicles (commonly known as `dirt truck') in CCTV and determine whether the truck is overloaded or not. We build the ITMD system based on the Single Shot MultiBox Detector (SSD) model. By constructing the image dataset of the truck and adjusting hyper-parameters of the original SSD neural network, we successfully trained a basic network model which the ITMD system depends on. The basic ITMD system achieves 83.01% mAP on classifying overload/non-overload truck, which is a not bad result. Still, some shortcomings of basic ITMD system have been targeted to enhance: it is easy for the ITMD system to misclassify other similar vehicle as truck. In response to this problem, we optimized the basic ITMD system, which effectively reduced basic model's false recognition rate. The optimized ITMD system achieved 86.18% mAP on the test set, which is better than the 83.01% mAP of the basic ITMD system.

The research of autonomous obstacle avoidance of mobile robot based on multi-sensor integration

NASA Astrophysics Data System (ADS)

Zhao, Ming; Han, Baoling

2016-11-01

The object of this study is the bionic quadruped mobile robot. The study has proposed a system design plan for mobile robot obstacle avoidance with the binocular stereo visual sensor and the self-control 3D Lidar integrated with modified ant colony optimization path planning to realize the reconstruction of the environmental map. Because the working condition of a mobile robot is complex, the result of the 3D reconstruction with a single binocular sensor is undesirable when feature points are few and the light condition is poor. Therefore, this system integrates the stereo vision sensor blumblebee2 and the Lidar sensor together to detect the cloud information of 3D points of environmental obstacles. This paper proposes the sensor information fusion technology to rebuild the environment map. Firstly, according to the Lidar data and visual data on obstacle detection respectively, and then consider two methods respectively to detect the distribution of obstacles. Finally fusing the data to get the more complete, more accurate distribution of obstacles in the scene. Then the thesis introduces ant colony algorithm. It has analyzed advantages and disadvantages of the ant colony optimization and its formation cause deeply, and then improved the system with the help of the ant colony optimization to increase the rate of convergence and precision of the algorithm in robot path planning. Such improvements and integrations overcome the shortcomings of the ant colony optimization like involving into the local optimal solution easily, slow search speed and poor search results. This experiment deals with images and programs the motor drive under the compiling environment of Matlab and Visual Studio and establishes the visual 2.5D grid map. Finally it plans a global path for the mobile robot according to the ant colony algorithm. The feasibility and effectiveness of the system are confirmed by ROS and simulation platform of Linux.

The role of optimality in characterizing CO2 seepage from geological carbon sequestration sites

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

Cortis, Andrea; Oldenburg, Curtis M.; Benson, Sally M.

Storage of large amounts of carbon dioxide (CO{sub 2}) in deep geological formations for greenhouse gas mitigation is gaining momentum and moving from its conceptual and testing stages towards widespread application. In this work we explore various optimization strategies for characterizing surface leakage (seepage) using near-surface measurement approaches such as accumulation chambers and eddy covariance towers. Seepage characterization objectives and limitations need to be defined carefully from the outset especially in light of large natural background variations that can mask seepage. The cost and sensitivity of seepage detection are related to four critical length scales pertaining to the size ofmore » the: (1) region that needs to be monitored; (2) footprint of the measurement approach, and (3) main seepage zone; and (4) region in which concentrations or fluxes are influenced by seepage. Seepage characterization objectives may include one or all of the tasks of detecting, locating, and quantifying seepage. Each of these tasks has its own optimal strategy. Detecting and locating seepage in a region in which there is no expected or preferred location for seepage nor existing evidence for seepage requires monitoring on a fixed grid, e.g., using eddy covariance towers. The fixed-grid approaches needed to detect seepage are expected to require large numbers of eddy covariance towers for large-scale geologic CO{sub 2} storage. Once seepage has been detected and roughly located, seepage zones and features can be optimally pinpointed through a dynamic search strategy, e.g., employing accumulation chambers and/or soil-gas sampling. Quantification of seepage rates can be done through measurements on a localized fixed grid once the seepage is pinpointed. Background measurements are essential for seepage detection in natural ecosystems. Artificial neural networks are considered as regression models useful for distinguishing natural system behavior from anomalous behavior suggestive of CO{sub 2} seepage without need for detailed understanding of natural system processes. Because of the local extrema in CO{sub 2} fluxes and concentrations in natural systems, simple steepest-descent algorithms are not effective and evolutionary computation algorithms are proposed as a paradigm for dynamic monitoring networks to pinpoint CO{sub 2} seepage areas.« less

Quality detection system and method of micro-accessory based on microscopic vision

NASA Astrophysics Data System (ADS)

Li, Dongjie; Wang, Shiwei; Fu, Yu

2017-10-01

Considering that the traditional manual detection of micro-accessory has some problems, such as heavy workload, low efficiency and large artificial error, a kind of quality inspection system of micro-accessory has been designed. Micro-vision technology has been used to inspect quality, which optimizes the structure of the detection system. The stepper motor is used to drive the rotating micro-platform to transfer quarantine device and the microscopic vision system is applied to get graphic information of micro-accessory. The methods of image processing and pattern matching, the variable scale Sobel differential edge detection algorithm and the improved Zernike moments sub-pixel edge detection algorithm are combined in the system in order to achieve a more detailed and accurate edge of the defect detection. The grade at the edge of the complex signal can be achieved accurately by extracting through the proposed system, and then it can distinguish the qualified products and unqualified products with high precision recognition.

Optimal Artificial Boundary Condition Configurations for Sensitivity-Based Model Updating and Damage Detection

DTIC Science & Technology

2010-09-01

matrix is used in many methods, like Jacobi or Gauss Seidel , for solving linear systems. Also, no partial pivoting is necessary for a strictly column...problems that arise during the procedure, which in general, converges to the solving of a linear system. The most common issue with the solution is the... iterative procedure to find an appropriate subset of parameters that produce an optimal solution commonly known as forward selection. Then, the

Optimal optical filters of fluorescence excitation and emission for poultry fecal detection

USDA-ARS?s Scientific Manuscript database

Purpose: An analytic method to design excitation and emission filters of a multispectral fluorescence imaging system is proposed and was demonstrated in an application to poultry fecal inspection. Methods: A mathematical model of a multispectral imaging system is proposed and its system parameters, ...

SNR Improvement of QEPAS System by Preamplifier Circuit Optimization and Frequency Locked Technique

NASA Astrophysics Data System (ADS)

Zhang, Qinduan; Chang, Jun; Wang, Zongliang; Wang, Fupeng; Jiang, Fengting; Wang, Mengyao

2018-06-01

Preamplifier circuit noise is of great importance in quartz enhanced photoacoustic spectroscopy (QEPAS) system. In this paper, several noise sources are evaluated and discussed in detail. Based on the noise characteristics, the corresponding noise reduction method is proposed. In addition, a frequency locked technique is introduced to further optimize the QEPAS system noise and improve signal, which achieves a better performance than the conventional frequency scan method. As a result, the signal-to-noise ratio (SNR) could be increased 14 times by utilizing frequency locked technique and numerical averaging technique in the QEPAS system for water vapor detection.

NASA Electronic Library System (NELS) optimization

NASA Technical Reports Server (NTRS)

Pribyl, William L.

1993-01-01

This is a compilation of NELS (NASA Electronic Library System) Optimization progress/problem, interim, and final reports for all phases. The NELS database was examined, particularly in the memory, disk contention, and CPU, to discover bottlenecks. Methods to increase the speed of NELS code were investigated. The tasks included restructuring the existing code to interact with others more effectively. An error reporting code to help detect and remove bugs in the NELS was added. Report writing tools were recommended to integrate with the ASV3 system. The Oracle database management system and tools were to be installed on a Sun workstation, intended for demonstration purposes.

[Early detection on the onset of scarlet fever epidemics in Beijing, using the Cumulative Sum].

PubMed

Li, Jing; Yang, Peng; Wu, Shuang-sheng; Wang, Xiao-li; Liu, Shuang; Wang, Quan-yi

2013-05-01

Based on data related to scarlet fever which was collected from the Disease Surveillance Information Reporting System in Beijing from 2005 to 2011, to explore the efficiency of Cumulative Sum (CUSUM) in detecting the onset of scarlet fever epidemics. Models as C1-MILD (C1), C2-MEDIUM (C2) and C3-ULTRA (C3) were used. Tools for evaluation as Youden's index and detection time were calculated to optimize the parameters and optimal model. Data on 2011 scarlet fever surveillance was used to verify the efficacy of these models. C1 (k = 0.5, H = 2σ), C2 (k = 0.7, H = 2σ), C3 (k = 1.1, H = 2σ) appeared to be the optimal parameters among these models. Youden's index of C1 was 83.0% and detection time being 0.64 weeks, Youden's index of C2 was 85.4% and detection time being 1.27 weeks, Youden's index of C1 was 85.1% and detection time being 1.36 weeks. Among the three early warning detection models, C1 had the highest efficacy. Three models all triggered the signals within 4 weeks after the onset of scarlet fever epidemics. The early warning detection model of CUSUM could be used to detect the onset of scarlet fever epidemics, with good efficacy.

Fault detection and isolation in GPS receiver autonomous integrity monitoring based on chaos particle swarm optimization-particle filter algorithm

NASA Astrophysics Data System (ADS)

Wang, Ershen; Jia, Chaoying; Tong, Gang; Qu, Pingping; Lan, Xiaoyu; Pang, Tao

2018-03-01

The receiver autonomous integrity monitoring (RAIM) is one of the most important parts in an avionic navigation system. Two problems need to be addressed to improve this system, namely, the degeneracy phenomenon and lack of samples for the standard particle filter (PF). However, the number of samples cannot adequately express the real distribution of the probability density function (i.e., sample impoverishment). This study presents a GPS receiver autonomous integrity monitoring (RAIM) method based on a chaos particle swarm optimization particle filter (CPSO-PF) algorithm with a log likelihood ratio. The chaos sequence generates a set of chaotic variables, which are mapped to the interval of optimization variables to improve particle quality. This chaos perturbation overcomes the potential for the search to become trapped in a local optimum in the particle swarm optimization (PSO) algorithm. Test statistics are configured based on a likelihood ratio, and satellite fault detection is then conducted by checking the consistency between the state estimate of the main PF and those of the auxiliary PFs. Based on GPS data, the experimental results demonstrate that the proposed algorithm can effectively detect and isolate satellite faults under conditions of non-Gaussian measurement noise. Moreover, the performance of the proposed novel method is better than that of RAIM based on the PF or PSO-PF algorithm.

Optimal Power Allocation Strategy in a Joint Bistatic Radar and Communication System Based on Low Probability of Intercept

PubMed Central

Wang, Fei; Salous, Sana; Zhou, Jianjiang

2017-01-01

In this paper, we investigate a low probability of intercept (LPI)-based optimal power allocation strategy for a joint bistatic radar and communication system, which is composed of a dedicated transmitter, a radar receiver, and a communication receiver. The joint system is capable of fulfilling the requirements of both radar and communications simultaneously. First, assuming that the signal-to-noise ratio (SNR) corresponding to the target surveillance path is much weaker than that corresponding to the line of sight path at radar receiver, the analytically closed-form expression for the probability of false alarm is calculated, whereas the closed-form expression for the probability of detection is not analytically tractable and is approximated due to the fact that the received signals are not zero-mean Gaussian under target presence hypothesis. Then, an LPI-based optimal power allocation strategy is presented to minimize the total transmission power for information signal and radar waveform, which is constrained by a specified information rate for the communication receiver and the desired probabilities of detection and false alarm for the radar receiver. The well-known bisection search method is employed to solve the resulting constrained optimization problem. Finally, numerical simulations are provided to reveal the effects of several system parameters on the power allocation results. It is also demonstrated that the LPI performance of the joint bistatic radar and communication system can be markedly improved by utilizing the proposed scheme. PMID:29186850

Optimal Power Allocation Strategy in a Joint Bistatic Radar and Communication System Based on Low Probability of Intercept.

PubMed

Shi, Chenguang; Wang, Fei; Salous, Sana; Zhou, Jianjiang

2017-11-25

In this paper, we investigate a low probability of intercept (LPI)-based optimal power allocation strategy for a joint bistatic radar and communication system, which is composed of a dedicated transmitter, a radar receiver, and a communication receiver. The joint system is capable of fulfilling the requirements of both radar and communications simultaneously. First, assuming that the signal-to-noise ratio (SNR) corresponding to the target surveillance path is much weaker than that corresponding to the line of sight path at radar receiver, the analytically closed-form expression for the probability of false alarm is calculated, whereas the closed-form expression for the probability of detection is not analytically tractable and is approximated due to the fact that the received signals are not zero-mean Gaussian under target presence hypothesis. Then, an LPI-based optimal power allocation strategy is presented to minimize the total transmission power for information signal and radar waveform, which is constrained by a specified information rate for the communication receiver and the desired probabilities of detection and false alarm for the radar receiver. The well-known bisection search method is employed to solve the resulting constrained optimization problem. Finally, numerical simulations are provided to reveal the effects of several system parameters on the power allocation results. It is also demonstrated that the LPI performance of the joint bistatic radar and communication system can be markedly improved by utilizing the proposed scheme.

Optimizing Robinson Operator with Ant Colony Optimization As a Digital Image Edge Detection Method

NASA Astrophysics Data System (ADS)

Yanti Nasution, Tarida; Zarlis, Muhammad; K. M Nasution, Mahyuddin

2017-12-01

Edge detection serves to identify the boundaries of an object against a background of mutual overlap. One of the classic method for edge detection is operator Robinson. Operator Robinson produces a thin, not assertive and grey line edge. To overcome these deficiencies, the proposed improvements to edge detection method with the approach graph with Ant Colony Optimization algorithm. The repairs may be performed are thicken the edge and connect the edges cut off. Edge detection research aims to do optimization of operator Robinson with Ant Colony Optimization then compare the output and generated the inferred extent of Ant Colony Optimization can improve result of edge detection that has not been optimized and improve the accuracy of the results of Robinson edge detection. The parameters used in performance measurement of edge detection are morphology of the resulting edge line, MSE and PSNR. The result showed that Robinson and Ant Colony Optimization method produces images with a more assertive and thick edge. Ant Colony Optimization method is able to be used as a method for optimizing operator Robinson by improving the image result of Robinson detection average 16.77 % than classic Robinson result.

A Joint Optimization Criterion for Blind DS-CDMA Detection

NASA Astrophysics Data System (ADS)

Durán-Díaz, Iván; Cruces-Alvarez, Sergio A.

2006-12-01

This paper addresses the problem of the blind detection of a desired user in an asynchronous DS-CDMA communications system with multipath propagation channels. Starting from the inverse filter criterion introduced by Tugnait and Li in 2001, we propose to tackle the problem in the context of the blind signal extraction methods for ICA. In order to improve the performance of the detector, we present a criterion based on the joint optimization of several higher-order statistics of the outputs. An algorithm that optimizes the proposed criterion is described, and its improved performance and robustness with respect to the near-far problem are corroborated through simulations. Additionally, a simulation using measurements on a real software-radio platform at 5 GHz has also been performed.

Study on the Application of an Ultra-High-Frequency Fractal Antenna to Partial Discharge Detection in Switchgears

PubMed Central

Yao, Chenguo; Chen, Pan; Huang, Congjian; Chen, Yu; Qiao, Panpan

2013-01-01

The ultra-high-frequency (UHF) method is used to analyze the insulation condition of electric equipment by detecting the UHF electromagnetic (EM) waves excited by partial discharge (PD). As part of the UHF detection system, the UHF sensor determines the detection system performance in signal extraction and recognition. In this paper, a UHF antenna sensor with the fractal structure for PD detection in switchgears was designed by means of modeling, simulation and optimization. This sensor, with a flat-plate structure, had two resonance frequencies of 583 MHz and 732 MHz. In the laboratory, four kinds of insulation defect models were positioned in the testing switchgear for typical PD tests. The results show that the sensor could reproduce the electromagnetic waves well. Furthermore, to optimize the installation position of the inner sensor for achieving best detection performance, the precise simulation model of switchgear was developed to study the propagation characteristics of UHF signals in switchgear by finite-difference time-domain (FDTD) method. According to the results of simulation and verification test, the sensor should be positioned at the right side of bottom plate in the front cabinet. This research established the foundation for the further study on the application of UHF technique in switchgear PD online detection. PMID:24351641

Implementing a Parallel Image Edge Detection Algorithm Based on the Otsu-Canny Operator on the Hadoop Platform.

PubMed

Cao, Jianfang; Chen, Lichao; Wang, Min; Tian, Yun

2018-01-01

The Canny operator is widely used to detect edges in images. However, as the size of the image dataset increases, the edge detection performance of the Canny operator decreases and its runtime becomes excessive. To improve the runtime and edge detection performance of the Canny operator, in this paper, we propose a parallel design and implementation for an Otsu-optimized Canny operator using a MapReduce parallel programming model that runs on the Hadoop platform. The Otsu algorithm is used to optimize the Canny operator's dual threshold and improve the edge detection performance, while the MapReduce parallel programming model facilitates parallel processing for the Canny operator to solve the processing speed and communication cost problems that occur when the Canny edge detection algorithm is applied to big data. For the experiments, we constructed datasets of different scales from the Pascal VOC2012 image database. The proposed parallel Otsu-Canny edge detection algorithm performs better than other traditional edge detection algorithms. The parallel approach reduced the running time by approximately 67.2% on a Hadoop cluster architecture consisting of 5 nodes with a dataset of 60,000 images. Overall, our approach system speeds up the system by approximately 3.4 times when processing large-scale datasets, which demonstrates the obvious superiority of our method. The proposed algorithm in this study demonstrates both better edge detection performance and improved time performance.

Performance optimization of spectral amplitude coding OCDMA system using new enhanced multi diagonal code

NASA Astrophysics Data System (ADS)

Imtiaz, Waqas A.; Ilyas, M.; Khan, Yousaf

2016-11-01

This paper propose a new code to optimize the performance of spectral amplitude coding-optical code division multiple access (SAC-OCDMA) system. The unique two-matrix structure of the proposed enhanced multi diagonal (EMD) code and effective correlation properties, between intended and interfering subscribers, significantly elevates the performance of SAC-OCDMA system by negating multiple access interference (MAI) and associated phase induce intensity noise (PIIN). Performance of SAC-OCDMA system based on the proposed code is thoroughly analyzed for two detection techniques through analytic and simulation analysis by referring to bit error rate (BER), signal to noise ratio (SNR) and eye patterns at the receiving end. It is shown that EMD code while using SDD technique provides high transmission capacity, reduces the receiver complexity, and provides better performance as compared to complementary subtraction detection (CSD) technique. Furthermore, analysis shows that, for a minimum acceptable BER of 10-9 , the proposed system supports 64 subscribers at data rates of up to 2 Gbps for both up-down link transmission.

Designing lymphocyte functional structure for optimal signal detection: voilà, T cells.

PubMed

Noest, A J

2000-11-21

One basic task of immune systems is to detect signals from unknown "intruders" amidst a noisy background of harmless signals. To clarify the functional importance of many observed lymphocyte properties, I ask: What properties would a cell have if one designed it according to the theory of optimal detection, with minimal regard for biological constraints? Sparse and reasonable assumptions about the statistics of available signals prove sufficient for deriving many features of the optimal functional structure, in an incremental and modular design. The use of one common formalism guarantees that all parts of the design collaborate to solve the detection task. Detection performance is computed at several stages of the design. Comparison between design variants reveals e.g. the importance of controlling the signal integration time. This predicts that an appropriate control mechanism should exist. Comparing the design to reality, I find a striking similarity with many features of T cells. For example, the formalism dictates clonal specificity, serial receptor triggering, (grades of) anergy, negative and positive selection, co-stimulation, high-zone tolerance, and clonal production of cytokines. Serious mismatches should be found if T cells were hindered by mechanistic constraints or vestiges of their (co-)evolutionary history, but I have not found clear examples. By contrast, fundamental mismatches abound when comparing the design to immune systems of e.g. invertebrates. The wide-ranging differences seem to hinge on the (in)ability to generate a large diversity of receptors. Copyright 2000 Academic Press.

Construction of a novel peptide nucleic acid piezoelectric gene sensor microarray detection system.

PubMed

Chen, Ming; Liu, Minghua; Yu, Lili; Cai, Guoru; Chen, Qinghai; Wu, Rong; Wang, Feng; Zhang, Bo; Jiang, Tianlun; Fu, Welling

2005-08-01

A novel 2 x 5 clamped style piezoelectric gene sensor microarray has been successfully constructed. Every crystal unit of the fabricated gene sensor can oscillate independently without interfering with each other. The bis-peptide nucleic acid (bis-PNA) probe, which can combine with target DNA or RNA sequences more effectively and specifically than a DNA probe, was designed and immobilized on the surface of the gene sensor microarray to substitute the conventional DNA probe for direct detection of the hepatitis B virus (HBV) genomic DNA. Detection conditions were then explored and optimized. Results showed that PBS buffer of pH 6.8, an ion concentration of 20 mmol/liter, and a probe concentration of 1.5 micromol/liter were optimal for the detection system. Under such optimized experimental conditions, the specificity of bis-PNA was proved much higher than that of DNA probe. The relationship between quantity of target and decrease of frequency showed a typical saturation curve when concentrations of target HBV DNA varied from 10 pg/liter to 100 microg/liter, and 10 microg/liter was the watershed, with a statistic linear regression equation of I gC = -2.7455 + 0.0691 deltaF and the correlating coefficient of 0.9923. Fortunately, this is exactly the most ordinary variant range of the HBV virus concentration in clinical hepatitis samples. So, a good technical platform is successfully constructed and it will be applied to detect HBV quantitatively in clinical samples.

Design of a modular digital computer system

NASA Technical Reports Server (NTRS)

1973-01-01

A design tradeoff study is reported for a modular spaceborne computer system that is responsive to many mission types and phases. The computer uses redundancy to maximize reliability, and multiprocessing to maximize processing capacity. Fault detection and recovery features provide optimal reliability.

Multiple-modality program for standoff detection of roadside hazards

NASA Astrophysics Data System (ADS)

Williams, Kathryn; Middleton, Seth; Close, Ryan; Luke, Robert H.; Suri, Rajiv

2016-05-01

The U.S. Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate (NVESD) is executing a program to assess the performance of a variety of sensor modalities for standoff detection of roadside explosive hazards. The program objective is to identify an optimal sensor or combination of fused sensors to incorporate with autonomous detection algorithms into a system of systems for use in future route clearance operations. This paper provides an overview of the program, including a description of the sensors under consideration, sensor test events, and ongoing data analysis.

A novel forward and backward scattering wave measurement system for optimizing GPR standoff mine/IED detector

NASA Astrophysics Data System (ADS)

Fuse, Yukinori

2012-06-01

Standoff detection of mines and improvised explosive devices by ground penetrating radar has advantages in terms of safety and efficiency. However, the reflected signals from buried targets are often disturbed by those from the ground surface, which vary with the antennas angle, making it more difficult to detect at a safe distance. An understanding of the forward and backward scattering wave is thus essential for improving standoff detection capability. We present some experimental results from using our measurement system for such an analysis.

Enzymatic Activity Detection via Electrochemistry for Enceladus

NASA Technical Reports Server (NTRS)

Studemeister, Lucy; Koehne, Jessica; Quinn, Richard

2017-01-01

Electrochemical detection of biological molecules is a pertinent topic and application in many fields such as medicine, environmental spills, and life detection in space. Proteases, a class of molecules of interest in the search for life, catalyze the hydrolysis of peptides. Trypsin, a specific protease, was chosen to investigate an optimized enzyme detection system using electrochemistry. This study aims at providing the ideal functionalization of an electrode that can reliably detect a signal indicative of an enzymatic reaction from an Enceladus sample.

Applying Monte-Carlo simulations to optimize an inelastic neutron scattering system for soil carbon analysis

USDA-ARS?s Scientific Manuscript database

Computer Monte-Carlo (MC) simulations (Geant4) of neutron propagation and acquisition of gamma response from soil samples was applied to evaluate INS system performance characteristic [sensitivity, minimal detectable level (MDL)] for soil carbon measurement. The INS system model with best performanc...

Automated Power-Distribution System

NASA Technical Reports Server (NTRS)

Ashworth, Barry; Riedesel, Joel; Myers, Chris; Miller, William; Jones, Ellen F.; Freeman, Kenneth; Walsh, Richard; Walls, Bryan K.; Weeks, David J.; Bechtel, Robert T.

1992-01-01

Autonomous power-distribution system includes power-control equipment and automation equipment. System automatically schedules connection of power to loads and reconfigures itself when it detects fault. Potential terrestrial applications include optimization of consumption of power in homes, power supplies for autonomous land vehicles and vessels, and power supplies for automated industrial processes.

Optimally robust redundancy relations for failure detection in uncertain systems

NASA Technical Reports Server (NTRS)

Lou, X.-C.; Willsky, A. S.; Verghese, G. C.

1986-01-01

All failure detection methods are based, either explicitly or implicitly, on the use of redundancy, i.e. on (possibly dynamic) relations among the measured variables. The robustness of the failure detection process consequently depends to a great degree on the reliability of the redundancy relations, which in turn is affected by the inevitable presence of model uncertainties. In this paper the problem of determining redundancy relations that are optimally robust is addressed in a sense that includes several major issues of importance in practical failure detection and that provides a significant amount of intuition concerning the geometry of robust failure detection. A procedure is given involving the construction of a single matrix and its singular value decomposition for the determination of a complete sequence of redundancy relations, ordered in terms of their level of robustness. This procedure also provides the basis for comparing levels of robustness in redundancy provided by different sets of sensors.

Detecting the QTL-allele system of seed isoflavone content in Chinese soybean landrace population for optimal cross design and gene system exploration.

PubMed

Meng, Shan; He, Jianbo; Zhao, Tuanjie; Xing, Guangnan; Li, Yan; Yang, Shouping; Lu, Jiangjie; Wang, Yufeng; Gai, Junyi

2016-08-01

Utilizing an innovative GWAS in CSLRP, 44 QTL 199 alleles with 72.2 % contribution to SIFC variation were detected and organized into a QTL-allele matrix for cross design and gene annotation. The seed isoflavone content (SIFC) of soybeans is of great importance to health care. The Chinese soybean landrace population (CSLRP) as a genetic reservoir was studied for its whole-genome quantitative trait loci (QTL) system of the SIFC using an innovative restricted two-stage multi-locus genome-wide association study procedure (RTM-GWAS). A sample of 366 landraces was tested under four environments and sequenced using RAD-seq (restriction-site-associated DNA sequencing) technique to obtain 116,769 single nucleotide polymorphisms (SNPs) then organized into 29,119 SNP linkage disequilibrium blocks (SNPLDBs) for GWAS. The detected 44 QTL 199 alleles on 16 chromosomes (explaining 72.2 % of the total phenotypic variation) with the allele effects (92 positive and 107 negative) of the CSLRP were organized into a QTL-allele matrix showing the SIFC population genetic structure. Additional differentiation among eco-regions due to the SIFC in addition to that of genome-wide markers was found. All accessions comprised both positive and negative alleles, implying a great potential for recombination within the population. The optimal crosses were predicted from the matrices, showing transgressive potentials in the CSLRP. From the detected QTL system, 55 candidate genes related to 11 biological processes were χ (2)-tested as an SIFC candidate gene system. The present study explored the genome-wide SIFC QTL/gene system with the innovative RTM-GWAS and found the potentials of the QTL-allele matrix in optimal cross design and population genetic and genomic studies, which may have provided a solution to match the breeding by design strategy at both QTL and gene levels in breeding programs.

An optimized ensemble local mean decomposition method for fault detection of mechanical components

NASA Astrophysics Data System (ADS)

Zhang, Chao; Li, Zhixiong; Hu, Chao; Chen, Shuai; Wang, Jianguo; Zhang, Xiaogang

2017-03-01

Mechanical transmission systems have been widely adopted in most of industrial applications, and issues related to the maintenance of these systems have attracted considerable attention in the past few decades. The recently developed ensemble local mean decomposition (ELMD) method shows satisfactory performance in fault detection of mechanical components for preventing catastrophic failures and reducing maintenance costs. However, the performance of ELMD often heavily depends on proper selection of its model parameters. To this end, this paper proposes an optimized ensemble local mean decomposition (OELMD) method to determinate an optimum set of ELMD parameters for vibration signal analysis. In OELMD, an error index termed the relative root-mean-square error (Relative RMSE) is used to evaluate the decomposition performance of ELMD with a certain amplitude of the added white noise. Once a maximum Relative RMSE, corresponding to an optimal noise amplitude, is determined, OELMD then identifies optimal noise bandwidth and ensemble number based on the Relative RMSE and signal-to-noise ratio (SNR), respectively. Thus, all three critical parameters of ELMD (i.e. noise amplitude and bandwidth, and ensemble number) are optimized by OELMD. The effectiveness of OELMD was evaluated using experimental vibration signals measured from three different mechanical components (i.e. the rolling bearing, gear and diesel engine) under faulty operation conditions.

A CO trace gas detection system based on continuous wave DFB-QCL

NASA Astrophysics Data System (ADS)

Dang, Jingmin; Yu, Haiye; Sun, Yujing; Wang, Yiding

2017-05-01

A compact and mobile system was demonstrated for the detection of carbon monoxide (CO) at trace level. This system adopted a high-power, continuous wave (CW), distributed feedback quantum cascade laser (DFB-QCL) operating at ∼22 °C as excitation source. Wavelength modulation spectroscopy (WMS) as well as second harmonic detection was used to isolate complex, overlapping spectral absorption features typical of ambient pressures and to achieve excellent specificity and high detection sensitivity. For the selected P(11) absorption line of CO molecule, located at 2099.083 cm-1, a limit of detection (LoD) of 26 ppb by volume (ppbv) at atmospheric pressure was achieved with a 1 s acquisition time. Allan deviation analysis was performed to investigate the long term performance of the CO detection system, and a measurement precision of 3.4 ppbv was observed with an optimal integration time of approximate 114 s, which verified the reliable and robust operation of the developed system.

Optimization of the sensitivity/doses relationship for a bench-top EDXRF system used for in vivo quantification of gold nanoparticles.

PubMed

Santibáñez, M; Saavedra, R; Vásquez, M; Malano, F; Pérez, P; Valente, M; Figueroa, R G

2017-11-01

The present work is devoted to optimizing the sensitivity-doses relationship of a bench-top EDXRF system, with the aim of achieving a detection limit of 0.010mg/ml of gold nanoparticles in tumor tissue (clinical values expected), for doses below 10mGy (value fixed for in vivo application). Tumor phantoms of 0.3cm 3 made of a suspension of gold nanoparticles (15nm AurovistTM, Nanoprobes Inc.) were studied at depths of 0-4mm in a tissue equivalent cylindrical phantom. The optimization process was implemented configuring several tube voltages and aluminum filters, to obtain non-symmetrical narrow spectra with fixed FWHM of 5keV and centered among the 11.2-20.3keV. The used statistical figure of merit was the obtained sensitivity (with each spectrum at each depth) weighted by the delivered surface doses. The detection limit of the system was determined measuring several gold nanoparticles concentrations ranging from 0.0010 to 5.0mg/ml and a blank sample into tumor phantoms, considering a statistical fluctuation within 95% of confidence. The results show the possibility of obtaining a detection limit for gold nanoparticles concentrations around 0.010mg/ml for surface tumor phantoms requiring doses around 2mGy. Copyright © 2017 Elsevier Ltd. All rights reserved.

Retro-detective control structures for free-space optical communication links.

PubMed

Jin, Xian; Barg, Jason E; Holzman, Jonathan F

2009-12-21

A corner-cube-based retro-detection photocell is introduced. The structure consists of three independent and mutually perpendicular photodiodes (PDs), whose differential photocurrents can be used to probe the alignment state of incident beams. These differential photocurrents are used in an actively-controlled triangulation procedure to optimize the communication channel alignment in a free-space optical (FSO) system. The active downlink and passive uplink communication capabilities of this system are demonstrated.

Auto-Calibration and Fault Detection and Isolation of Skewed Redundant Accelerometers in Measurement While Drilling Systems.

PubMed

Seyed Moosavi, Seyed Mohsen; Moaveni, Bijan; Moshiri, Behzad; Arvan, Mohammad Reza

2018-02-27

The present study designed skewed redundant accelerometers for a Measurement While Drilling (MWD) tool and executed auto-calibration, fault diagnosis and isolation of accelerometers in this tool. The optimal structure includes four accelerometers was selected and designed precisely in accordance with the physical shape of the existing MWD tool. A new four-accelerometer structure was designed, implemented and installed on the current system, replacing the conventional orthogonal structure. Auto-calibration operation of skewed redundant accelerometers and all combinations of three accelerometers have been done. Consequently, biases, scale factors, and misalignment factors of accelerometers have been successfully estimated. By defecting the sensors in the new optimal skewed redundant structure, the fault was detected using the proposed FDI method and the faulty sensor was diagnosed and isolated. The results indicate that the system can continue to operate with at least three correct sensors.

Auto-Calibration and Fault Detection and Isolation of Skewed Redundant Accelerometers in Measurement While Drilling Systems

PubMed Central

Seyed Moosavi, Seyed Mohsen; Moshiri, Behzad; Arvan, Mohammad Reza

2018-01-01

The present study designed skewed redundant accelerometers for a Measurement While Drilling (MWD) tool and executed auto-calibration, fault diagnosis and isolation of accelerometers in this tool. The optimal structure includes four accelerometers was selected and designed precisely in accordance with the physical shape of the existing MWD tool. A new four-accelerometer structure was designed, implemented and installed on the current system, replacing the conventional orthogonal structure. Auto-calibration operation of skewed redundant accelerometers and all combinations of three accelerometers have been done. Consequently, biases, scale factors, and misalignment factors of accelerometers have been successfully estimated. By defecting the sensors in the new optimal skewed redundant structure, the fault was detected using the proposed FDI method and the faulty sensor was diagnosed and isolated. The results indicate that the system can continue to operate with at least three correct sensors. PMID:29495434

40 CFR 51.363 - Quality assurance.

Code of Federal Regulations, 2011 CFR

2011-07-01

... test, the evaporative system tests, and emission control component checks (as applicable); (vi...) A check of the Constant Volume Sampler flow calibration; (5) A check for the optimization of the... selection, and power absorption; (9) A check of the system's ability to accurately detect background...

Improved Microseismicity Detection During Newberry EGS Stimulations

DOE Data Explorer

Templeton, Dennise

2013-10-01

Effective enhanced geothermal systems (EGS) require optimal fracture networks for efficient heat transfer between hot rock and fluid. Microseismic mapping is a key tool used to infer the subsurface fracture geometry. Traditional earthquake detection and location techniques are often employed to identify microearthquakes in geothermal regions. However, most commonly used algorithms may miss events if the seismic signal of an earthquake is small relative to the background noise level or if a microearthquake occurs within the coda of a larger event. Consequently, we have developed a set of algorithms that provide improved microearthquake detection. Our objective is to investigate the microseismicity at the DOE Newberry EGS site to better image the active regions of the underground fracture network during and immediately after the EGS stimulation. Detection of more microearthquakes during EGS stimulations will allow for better seismic delineation of the active regions of the underground fracture system. This improved knowledge of the reservoir network will improve our understanding of subsurface conditions, and allow improvement of the stimulation strategy that will optimize heat extraction and maximize economic return.

Improved Microseismicity Detection During Newberry EGS Stimulations

DOE Data Explorer

Templeton, Dennise

2013-11-01

Effective enhanced geothermal systems (EGS) require optimal fracture networks for efficient heat transfer between hot rock and fluid. Microseismic mapping is a key tool used to infer the subsurface fracture geometry. Traditional earthquake detection and location techniques are often employed to identify microearthquakes in geothermal regions. However, most commonly used algorithms may miss events if the seismic signal of an earthquake is small relative to the background noise level or if a microearthquake occurs within the coda of a larger event. Consequently, we have developed a set of algorithms that provide improved microearthquake detection. Our objective is to investigate the microseismicity at the DOE Newberry EGS site to better image the active regions of the underground fracture network during and immediately after the EGS stimulation. Detection of more microearthquakes during EGS stimulations will allow for better seismic delineation of the active regions of the underground fracture system. This improved knowledge of the reservoir network will improve our understanding of subsurface conditions, and allow improvement of the stimulation strategy that will optimize heat extraction and maximize economic return.

A Hypergraph and Arithmetic Residue-based Probabilistic Neural Network for classification in Intrusion Detection Systems.

PubMed

Raman, M R Gauthama; Somu, Nivethitha; Kirthivasan, Kannan; Sriram, V S Shankar

2017-08-01

Over the past few decades, the design of an intelligent Intrusion Detection System (IDS) remains an open challenge to the research community. Continuous efforts by the researchers have resulted in the development of several learning models based on Artificial Neural Network (ANN) to improve the performance of the IDSs. However, there exists a tradeoff with respect to the stability of ANN architecture and the detection rate for less frequent attacks. This paper presents a novel approach based on Helly property of Hypergraph and Arithmetic Residue-based Probabilistic Neural Network (HG AR-PNN) to address the classification problem in IDS. The Helly property of Hypergraph was exploited for the identification of the optimal feature subset and the arithmetic residue of the optimal feature subset was used to train the PNN. The performance of HG AR-PNN was evaluated using KDD CUP 1999 intrusion dataset. Experimental results prove the dominance of HG AR-PNN classifier over the existing classifiers with respect to the stability and improved detection rate for less frequent attacks. Copyright © 2017 Elsevier Ltd. All rights reserved.

Boosting-Based Optimization as a Generic Framework for Novelty and Fraud Detection in Complex Strategies

NASA Astrophysics Data System (ADS)

Gavrishchaka, Valeriy V.; Kovbasinskaya, Maria; Monina, Maria

2008-11-01

Novelty detection is a very desirable additional feature of any practical classification or forecasting system. Novelty and rare patterns detection is the main objective in such applications as fault/abnormality discovery in complex technical and biological systems, fraud detection and risk management in financial and insurance industry. Although many interdisciplinary approaches for rare event modeling and novelty detection have been proposed, significant data incompleteness due to the nature of the problem makes it difficult to find a universal solution. Even more challenging and much less formalized problem is novelty detection in complex strategies and models where practical performance criteria are usually multi-objective and the best state-of-the-art solution is often not known due to the complexity of the task and/or proprietary nature of the application area. For example, it is much more difficult to detect a series of small insider trading or other illegal transactions mixed with valid operations and distributed over long time period according to a well-designed strategy than a single, large fraudulent transaction. Recently proposed boosting-based optimization was shown to be an effective generic tool for the discovery of stable multi-component strategies/models from the existing parsimonious base strategies/models in financial and other applications. Here we outline how the same framework can be used for novelty and fraud detection in complex strategies and models.

Dynamic malware containment under an epidemic model with alert

NASA Astrophysics Data System (ADS)

Zhang, Tianrui; Yang, Lu-Xing; Yang, Xiaofan; Wu, Yingbo; Tang, Yuan Yan

2017-03-01

Alerting at the early stage of malware invasion turns out to be an important complement to malware detection and elimination. This paper addresses the issue of how to dynamically contain the prevalence of malware at a lower cost, provided alerting is feasible. A controlled epidemic model with alert is established, and an optimal control problem based on the epidemic model is formulated. The optimality system for the optimal control problem is derived. The structure of an optimal control for the proposed optimal control problem is characterized under some conditions. Numerical examples show that the cost-efficiency of an optimal control strategy can be enhanced by adjusting the upper and lower bounds on admissible controls.

Adapting Ground Penetrating Radar for Non-Destructive In-Situ Root and Tuber Assessment

NASA Astrophysics Data System (ADS)

Teare, B. L.; Hays, D. B.; Delgado, A.; Dobreva, I. D.; Bishop, M. P.; Lacey, R.; Huo, D.; Wang, X.

2017-12-01

Ground penetrating radar (GPR) is a rapidly evolving technology extensively used in geoscience, civil science, archeology, and military, and has become a novel application in agricultural systems. One promising application of GPR is for root and tuber detection and measurement. Current commercial GPR systems have been used for detection of large roots, but few studies have attempted to detect agronomic roots, and even fewer have attempted to measure and quantify the total root mass. The ability to monitor and measure root and tuber mass and architecture in an agricultural setting would have far-reaching effects. A few of these include the potential for breeding higher yielding root and tuber crops, rapid bulking roots, discovery of crops with greater carbon sequestration, discovery of plant varieties which have greater ability to stabilize slopes against erosion and slope failure, and drought tolerant varieties. Despite the possible benefits and the current maturity of GPR technology, several challenges remain in the attempt to optimize its use for root and tuber detection. These challenges center on three categories: spatial resolution, data processing, and field-deployable hardware configuration. This study is centered around tuber measurement and its objectives are to i) identify ideal antenna array configurations, frequency, and pulse density; ii) develop novel processing techniques which leverage powerful computer technologies to provide highly accurate measurements of detected features; and iii) develop a cart system which is appropriate for agricultural fields and non-destructive sampling. Already, a 2 GHz multiarray antenna has been identified as an optimal system for tuber detection. Software and processing algorithm development is ongoing, but has already shown improvement over current software offerings. Recent field activity suggest that carts should be width adjustable and sport independent suspension systems to maintain antenna orientation.

Cyber Security Audit and Attack Detection Toolkit

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

Peterson, Dale

2012-05-31

This goal of this project was to develop cyber security audit and attack detection tools for industrial control systems (ICS). Digital Bond developed and released a tool named Bandolier that audits ICS components commonly used in the energy sector against an optimal security configuration. The Portaledge Project developed a capability for the PI Historian, the most widely used Historian in the energy sector, to aggregate security events and detect cyber attacks.

Multi-Parameter Scattering Sensor and Methods

NASA Technical Reports Server (NTRS)

Greenberg, Paul S. (Inventor); Fischer, David G. (Inventor)

2016-01-01

Methods, detectors and systems detect particles and/or measure particle properties. According to one embodiment, a detector for detecting particles comprises: a sensor for receiving radiation scattered by an ensemble of particles; and a processor for determining a physical parameter for the detector, or an optimal detection angle or a bound for an optimal detection angle, for measuring at least one moment or integrated moment of the ensemble of particles, the physical parameter, or detection angle, or detection angle bound being determined based on one or more of properties (a) and/or (b) and/or (c) and/or (d) or ranges for one or more of properties (a) and/or (b) and/or (c) and/or (d), wherein (a)-(d) are the following: (a) is a wavelength of light incident on the particles, (b) is a count median diameter or other characteristic size parameter of the particle size distribution, (c) is a standard deviation or other characteristic width parameter of the particle size distribution, and (d) is a refractive index of particles.

Real-time optical monitoring of microbial growth using optimal combination of light-emitting diodes

NASA Astrophysics Data System (ADS)

Kobayashi, Ken-ichi; Yamada, Takeshi; Hiraishi, Akira; Nakauchi, Shigeki

2012-12-01

We developed a real-time optical monitoring system consisting of a monochrome complementary metal-oxide semiconductor (CMOS) camera and two light-emitting diodes (LEDs) with a constant temperature incubator for the rapid detection of microbial growth on solid media. As a target organism, we used Alicyclobacillus acidocaldarius, which is an acidophilic thermophilic endospore-forming bacterium able to survive in pasteurization processes and grow in acidic drink products such as apple juice. This bacterium was cultured on agar medium with a redox dye applied to improve detection sensitivity. On the basis of spectroscopic properties of the colony, medium, and LEDs, an optimal combination of two LED illuminations was selected to maximize the contrast between the colony and medium areas. We measured A. acidocaldarius and Escherichia coli at two different dilution levels using these two LEDs. From the results of time-course changes in the number of detected pixels in the detection images, a similar growth rate was estimated amongst the same species of microbes, regardless of the dilution level. This system has the ability to detect a colony of approximately 26 μm in diameter in a detection image, and it can be interpreted that the size corresponds to less than 20 μm diameter in visual inspection.

DyHAP: Dynamic Hybrid ANFIS-PSO Approach for Predicting Mobile Malware.

PubMed

Afifi, Firdaus; Anuar, Nor Badrul; Shamshirband, Shahaboddin; Choo, Kim-Kwang Raymond

2016-01-01

To deal with the large number of malicious mobile applications (e.g. mobile malware), a number of malware detection systems have been proposed in the literature. In this paper, we propose a hybrid method to find the optimum parameters that can be used to facilitate mobile malware identification. We also present a multi agent system architecture comprising three system agents (i.e. sniffer, extraction and selection agent) to capture and manage the pcap file for data preparation phase. In our hybrid approach, we combine an adaptive neuro fuzzy inference system (ANFIS) and particle swarm optimization (PSO). Evaluations using data captured on a real-world Android device and the MalGenome dataset demonstrate the effectiveness of our approach, in comparison to two hybrid optimization methods which are differential evolution (ANFIS-DE) and ant colony optimization (ANFIS-ACO).

DyHAP: Dynamic Hybrid ANFIS-PSO Approach for Predicting Mobile Malware

PubMed Central

Afifi, Firdaus; Anuar, Nor Badrul; Shamshirband, Shahaboddin

2016-01-01

To deal with the large number of malicious mobile applications (e.g. mobile malware), a number of malware detection systems have been proposed in the literature. In this paper, we propose a hybrid method to find the optimum parameters that can be used to facilitate mobile malware identification. We also present a multi agent system architecture comprising three system agents (i.e. sniffer, extraction and selection agent) to capture and manage the pcap file for data preparation phase. In our hybrid approach, we combine an adaptive neuro fuzzy inference system (ANFIS) and particle swarm optimization (PSO). Evaluations using data captured on a real-world Android device and the MalGenome dataset demonstrate the effectiveness of our approach, in comparison to two hybrid optimization methods which are differential evolution (ANFIS-DE) and ant colony optimization (ANFIS-ACO). PMID:27611312

Performance and evaluation of real-time multicomputer control systems

NASA Technical Reports Server (NTRS)

Shin, K. G.

1983-01-01

New performance measures, detailed examples, modeling of error detection process, performance evaluation of rollback recovery methods, experiments on FTMP, and optimal size of an NMR cluster are discussed.

Automated Discovery of Elementary Chemical Reaction Steps Using Freezing String and Berny Optimization Methods.

PubMed

Suleimanov, Yury V; Green, William H

2015-09-08

We present a simple protocol which allows fully automated discovery of elementary chemical reaction steps using in cooperation double- and single-ended transition-state optimization algorithms--the freezing string and Berny optimization methods, respectively. To demonstrate the utility of the proposed approach, the reactivity of several single-molecule systems of combustion and atmospheric chemistry importance is investigated. The proposed algorithm allowed us to detect without any human intervention not only "known" reaction pathways, manually detected in the previous studies, but also new, previously "unknown", reaction pathways which involve significant atom rearrangements. We believe that applying such a systematic approach to elementary reaction path finding will greatly accelerate the discovery of new chemistry and will lead to more accurate computer simulations of various chemical processes.

Instrument response measurements of ion mobility spectrometers in situ: maintaining optimal system performance of fielded systems

NASA Astrophysics Data System (ADS)

Wallis, Eric; Griffin, Todd M.; Popkie, Norm, Jr.; Eagan, Michael A.; McAtee, Robert F.; Vrazel, Danet; McKinly, Jim

2005-05-01

Ion Mobility Spectroscopy (IMS) is the most widespread detection technique in use by the military for the detection of chemical warfare agents, explosives, and other threat agents. Moreover, its role in homeland security and force protection has expanded due, in part, to its good sensitivity, low power, lightweight, and reasonable cost. With the increased use of IMS systems as continuous monitors, it becomes necessary to develop tools and methodologies to ensure optimal performance over a wide range of conditions and extended periods of time. Namely, instrument calibration is needed to ensure proper sensitivity and to correct for matrix or environmental effects. We have developed methodologies to deal with the semi-quantitative nature of IMS and allow us to generate response curves that allow a gauge of instrument performance and maintenance requirements. This instrumentation communicates to the IMS systems via a software interface that was developed in-house. The software measures system response, logs information to a database, and generates the response curves. This paper will discuss the instrumentation, software, data collected, and initial results from fielded systems.

Seizure detection, seizure prediction, and closed-loop warning systems in epilepsy.

PubMed

Ramgopal, Sriram; Thome-Souza, Sigride; Jackson, Michele; Kadish, Navah Ester; Sánchez Fernández, Iván; Klehm, Jacquelyn; Bosl, William; Reinsberger, Claus; Schachter, Steven; Loddenkemper, Tobias

2014-08-01

Nearly one-third of patients with epilepsy continue to have seizures despite optimal medication management. Systems employed to detect seizures may have the potential to improve outcomes in these patients by allowing more tailored therapies and might, additionally, have a role in accident and SUDEP prevention. Automated seizure detection and prediction require algorithms which employ feature computation and subsequent classification. Over the last few decades, methods have been developed to detect seizures utilizing scalp and intracranial EEG, electrocardiography, accelerometry and motion sensors, electrodermal activity, and audio/video captures. To date, it is unclear which combination of detection technologies yields the best results, and approaches may ultimately need to be individualized. This review presents an overview of seizure detection and related prediction methods and discusses their potential uses in closed-loop warning systems in epilepsy. Copyright © 2014. Published by Elsevier Inc.

Optimizing the response to surveillance alerts in automated surveillance systems.

PubMed

Izadi, Masoumeh; Buckeridge, David L

2011-02-28

Although much research effort has been directed toward refining algorithms for disease outbreak alerting, considerably less attention has been given to the response to alerts generated from statistical detection algorithms. Given the inherent inaccuracy in alerting, it is imperative to develop methods that help public health personnel identify optimal policies in response to alerts. This study evaluates the application of dynamic decision making models to the problem of responding to outbreak detection methods, using anthrax surveillance as an example. Adaptive optimization through approximate dynamic programming is used to generate a policy for decision making following outbreak detection. We investigate the degree to which the model can tolerate noise theoretically, in order to keep near optimal behavior. We also evaluate the policy from our model empirically and compare it with current approaches in routine public health practice for investigating alerts. Timeliness of outbreak confirmation and total costs associated with the decisions made are used as performance measures. Using our approach, on average, 80 per cent of outbreaks were confirmed prior to the fifth day of post-attack with considerably less cost compared to response strategies currently in use. Experimental results are also provided to illustrate the robustness of the adaptive optimization approach and to show the realization of the derived error bounds in practice. Copyright © 2011 John Wiley & Sons, Ltd.

Monitoring Of Air Quality Parameters For Construction Of Fire Risk Detection Systems

NASA Astrophysics Data System (ADS)

Romancov, I. I.; Dashkovky, A. G.; Panin, V. F.; Melkov, D. N.

2017-01-01

The analysis of fire developmental process is given, which showed that there are seven stages of fire development, a set of phenomena (factors, signs) of fire risk condition, characterized by a set of defined parameters, corresponds to each stage. Observed that the registration of high staging factors (high ambient temperature, content of CO2, etc.) means the registration of actual low staging fire (thermal destruction of materials gases, fumes, etc.) - fire risk situation. It is shown that the decrease of registered factor staging leads to construction of fire preventive and diagnostic systems as the lower is registered stage, the more uncertain is connection between the fact of its detection and a fire. It is indicated that with development of electronic equipment the staging of fire situations factors used for detection is reducing in whole, and also it is noted that for each control object it is necessary to choose (identify) the optimal factor, in particular, in many ways the optimal factor for aircrafts are smokes and their TV image.

Optimization and validation of moving average quality control procedures using bias detection curves and moving average validation charts.

PubMed

van Rossum, Huub H; Kemperman, Hans

2017-02-01

To date, no practical tools are available to obtain optimal settings for moving average (MA) as a continuous analytical quality control instrument. Also, there is no knowledge of the true bias detection properties of applied MA. We describe the use of bias detection curves for MA optimization and MA validation charts for validation of MA. MA optimization was performed on a data set of previously obtained consecutive assay results. Bias introduction and MA bias detection were simulated for multiple MA procedures (combination of truncation limits, calculation algorithms and control limits) and performed for various biases. Bias detection curves were generated by plotting the median number of test results needed for bias detection against the simulated introduced bias. In MA validation charts the minimum, median, and maximum numbers of assay results required for MA bias detection are shown for various bias. Their use was demonstrated for sodium, potassium, and albumin. Bias detection curves allowed optimization of MA settings by graphical comparison of bias detection properties of multiple MA. The optimal MA was selected based on the bias detection characteristics obtained. MA validation charts were generated for selected optimal MA and provided insight into the range of results required for MA bias detection. Bias detection curves and MA validation charts are useful tools for optimization and validation of MA procedures.

Detectability Thresholds and Optimal Algorithms for Community Structure in Dynamic Networks

NASA Astrophysics Data System (ADS)

Ghasemian, Amir; Zhang, Pan; Clauset, Aaron; Moore, Cristopher; Peel, Leto

2016-07-01

The detection of communities within a dynamic network is a common means for obtaining a coarse-grained view of a complex system and for investigating its underlying processes. While a number of methods have been proposed in the machine learning and physics literature, we lack a theoretical analysis of their strengths and weaknesses, or of the ultimate limits on when communities can be detected. Here, we study the fundamental limits of detecting community structure in dynamic networks. Specifically, we analyze the limits of detectability for a dynamic stochastic block model where nodes change their community memberships over time, but where edges are generated independently at each time step. Using the cavity method, we derive a precise detectability threshold as a function of the rate of change and the strength of the communities. Below this sharp threshold, we claim that no efficient algorithm can identify the communities better than chance. We then give two algorithms that are optimal in the sense that they succeed all the way down to this threshold. The first uses belief propagation, which gives asymptotically optimal accuracy, and the second is a fast spectral clustering algorithm, based on linearizing the belief propagation equations. These results extend our understanding of the limits of community detection in an important direction, and introduce new mathematical tools for similar extensions to networks with other types of auxiliary information.

Accurate Natural Trail Detection Using a Combination of a Deep Neural Network and Dynamic Programming.

PubMed

Adhikari, Shyam Prasad; Yang, Changju; Slot, Krzysztof; Kim, Hyongsuk

2018-01-10

This paper presents a vision sensor-based solution to the challenging problem of detecting and following trails in highly unstructured natural environments like forests, rural areas and mountains, using a combination of a deep neural network and dynamic programming. The deep neural network (DNN) concept has recently emerged as a very effective tool for processing vision sensor signals. A patch-based DNN is trained with supervised data to classify fixed-size image patches into "trail" and "non-trail" categories, and reshaped to a fully convolutional architecture to produce trail segmentation map for arbitrary-sized input images. As trail and non-trail patches do not exhibit clearly defined shapes or forms, the patch-based classifier is prone to misclassification, and produces sub-optimal trail segmentation maps. Dynamic programming is introduced to find an optimal trail on the sub-optimal DNN output map. Experimental results showing accurate trail detection for real-world trail datasets captured with a head mounted vision system are presented.

Magnetic Enzymatic Platform for Organophosphate Pesticide Detection Using Boron-doped Diamond Electrodes.

PubMed

Pino, Flavio; Ivandini, Tribidasari A; Nakata, Kazuya; Fujishima, Akira; Merkoçi, Arben; Einaga, Yasuaki

2015-01-01

A simple and reliable enzymatic system for organophosporus pesticide detection was successfully developed, by exploiting the synergy between the magnetic beads collection capacity and the outstanding electrochemistry property of boron-doped diamond electrodes. The determination of an organophosphate pesticide, chlorpyrifos (CPF), was performed based on the inhibition system of the enzyme acetylcholinesterase bonded to magnetic beads through a biotin-streptavidin complex system. A better sensitivity was found for a system with magnetic beads in the concentration range of 10(-9) to 10(-5) M. The estimated limits of detection based on IC10 (10% acetylcholinesterase (AChE) inhibition) have been detected and optimized to be 5.7 × 10(-10) M CPF. Spiked samples of water of Yokohama (Japan) have been measured to validate the efficiency of the enzymatic system. The results suggested that the use of magnetic beads to immobilize biomolecules or biosensing agents is suitable to maintain the superiority of BDD electrodes.

Optimization of A 2-Micron Laser Frequency Stabilization System for a Double-Pulse CO2 Differential Absorption Lidar

NASA Technical Reports Server (NTRS)

Chen, Songsheng; Yu, Jirong; Bai, Yingsin; Koch, Grady; Petros, Mulugeta; Trieu, Bo; Petzar, Paul; Singh, Upendra N.; Kavaya, Michael J.; Beyon, Jeffrey

2010-01-01

A carbon dioxide (CO2) Differential Absorption Lidar (DIAL) for accurate CO2 concentration measurement requires a frequency locking system to achieve high frequency locking precision and stability. We describe the frequency locking system utilizing Frequency Modulation (FM), Phase Sensitive Detection (PSD), and Proportional Integration Derivative (PID) feedback servo loop, and report the optimization of the sensitivity of the system for the feed back loop based on the characteristics of a variable path-length CO2 gas cell. The CO2 gas cell is characterized with HITRAN database (2004). The method can be applied for any other frequency locking systems referring to gas absorption line.

Digital flight control systems

NASA Technical Reports Server (NTRS)

Caglayan, A. K.; Vanlandingham, H. F.

1977-01-01

The design of stable feedback control laws for sampled-data systems with variable rate sampling was investigated. These types of sampled-data systems arise naturally in digital flight control systems which use digital actuators where it is desirable to decrease the number of control computer output commands in order to save wear and tear of the associated equipment. The design of aircraft control systems which are optimally tolerant of sensor and actuator failures was also studied. Detection of the failed sensor or actuator must be resolved and if the estimate of the state is used in the control law, then it is also desirable to have an estimator which will give the optimal state estimate even under the failed conditions.

Implementing a Parallel Image Edge Detection Algorithm Based on the Otsu-Canny Operator on the Hadoop Platform

PubMed Central

Wang, Min; Tian, Yun

2018-01-01

The Canny operator is widely used to detect edges in images. However, as the size of the image dataset increases, the edge detection performance of the Canny operator decreases and its runtime becomes excessive. To improve the runtime and edge detection performance of the Canny operator, in this paper, we propose a parallel design and implementation for an Otsu-optimized Canny operator using a MapReduce parallel programming model that runs on the Hadoop platform. The Otsu algorithm is used to optimize the Canny operator's dual threshold and improve the edge detection performance, while the MapReduce parallel programming model facilitates parallel processing for the Canny operator to solve the processing speed and communication cost problems that occur when the Canny edge detection algorithm is applied to big data. For the experiments, we constructed datasets of different scales from the Pascal VOC2012 image database. The proposed parallel Otsu-Canny edge detection algorithm performs better than other traditional edge detection algorithms. The parallel approach reduced the running time by approximately 67.2% on a Hadoop cluster architecture consisting of 5 nodes with a dataset of 60,000 images. Overall, our approach system speeds up the system by approximately 3.4 times when processing large-scale datasets, which demonstrates the obvious superiority of our method. The proposed algorithm in this study demonstrates both better edge detection performance and improved time performance. PMID:29861711

The simulation study on optical target laser active detection performance

NASA Astrophysics Data System (ADS)

Li, Ying-chun; Hou, Zhao-fei; Fan, Youchen

2014-12-01

According to the working principle of laser active detection system, the paper establishes the optical target laser active detection simulation system, carry out the simulation study on the detection process and detection performance of the system. For instance, the performance model such as the laser emitting, the laser propagation in the atmosphere, the reflection of optical target, the receiver detection system, the signal processing and recognition. We focus on the analysis and modeling the relationship between the laser emitting angle and defocus amount and "cat eye" effect echo laser in the reflection of optical target. Further, in the paper some performance index such as operating range, SNR and the probability of the system have been simulated. The parameters including laser emitting parameters, the reflection of the optical target and the laser propagation in the atmosphere which make a great influence on the performance of the optical target laser active detection system. Finally, using the object-oriented software design methods, the laser active detection system with the opening type, complete function and operating platform, realizes the process simulation that the detection system detect and recognize the optical target, complete the performance simulation of each subsystem, and generate the data report and the graph. It can make the laser active detection system performance models more intuitive because of the visible simulation process. The simulation data obtained from the system provide a reference to adjust the structure of the system parameters. And it provides theoretical and technical support for the top level design of the optical target laser active detection system and performance index optimization.

A computational imaging target specific detectivity metric

NASA Astrophysics Data System (ADS)

Preece, Bradley L.; Nehmetallah, George

2017-05-01

Due to the large quantity of low-cost, high-speed computational processing available today, computational imaging (CI) systems are expected to have a major role for next generation multifunctional cameras. The purpose of this work is to quantify the performance of theses CI systems in a standardized manner. Due to the diversity of CI system designs that are available today or proposed in the near future, significant challenges in modeling and calculating a standardized detection signal-to-noise ratio (SNR) to measure the performance of these systems. In this paper, we developed a path forward for a standardized detectivity metric for CI systems. The detectivity metric is designed to evaluate the performance of a CI system searching for a specific known target or signal of interest, and is defined as the optimal linear matched filter SNR, similar to the Hotelling SNR, calculated in computational space with special considerations for standardization. Therefore, the detectivity metric is designed to be flexible, in order to handle various types of CI systems and specific targets, while keeping the complexity and assumptions of the systems to a minimum.

Lens-free imaging of magnetic particles in DNA assays.

PubMed

Colle, Frederik; Vercruysse, Dries; Peeters, Sara; Liu, Chengxun; Stakenborg, Tim; Lagae, Liesbet; Del-Favero, Jurgen

2013-11-07

We present a novel opto-magnetic system for the fast and sensitive detection of nucleic acids. The system is based on a lens-free imaging approach resulting in a compact and cheap optical readout of surface hybridized DNA fragments. In our system magnetic particles are attracted towards the detection surface thereby completing the labeling step in less than 1 min. An optimized surface functionalization combined with magnetic manipulation was used to remove all nonspecifically bound magnetic particles from the detection surface. A lens-free image of the specifically bound magnetic particles on the detection surface was recorded by a CMOS imager. This recorded interference pattern was reconstructed in software, to represent the particle image at the focal distance, using little computational power. As a result we were able to detect DNA concentrations down to 10 pM with single particle sensitivity. The possibility of integrated sample preparation by manipulation of magnetic particles, combined with the cheap and highly compact lens-free detection makes our system an ideal candidate for point-of-care diagnostic applications.

Bio-inspired photon detection using chromophore/nanotube hybrids (Conference Presentation)

NASA Astrophysics Data System (ADS)

Léonard, François

2017-05-01

The human eye is an exquisite optical system with the ability to detect individual photons at room temperature. However, the complexity of this system, optimized over millions of years, has been difficult to reproduce using synthetic techniques. Here we discuss a bio-inspired approach for photon detection based on chromophore/nanotube hybrids, where the chromophore plays a similar role to the retinal molecule in the human eye, and the signal transduction is provided by electronic transport in the carbon nanotube. In this presentation, I will present the concept and discuss our progress in realizing this type of photodetection mechanism.

Design and Performance of the Astro-E/XRS Signal Processing System

NASA Technical Reports Server (NTRS)

Boyce, Kevin R.; Audley, M. D.; Baker, R. G.; Dumonthier, J. J.; Fujimoto, R.; Gendreau, K. C.; Ishisaki, Y.; Kelley, R. L.; Stahle, C. K.; Szymkowiak, A. E.

1999-01-01

We describe the signal processing system of the Astro-E XRS instrument. The Calorimeter Analog Processor (CAP) provides bias and power for the detectors and amplifies the detector signals by a factor of 20,000. The Calorimeter Digital Processor (CDP) performs the digital processing of the calorimeter signals, detecting X-ray pulses and analyzing them by optimal filtering. We describe the operation of pulse detection, Pulse height analysis. and risetime determination. We also discuss performance, including the three event grades (hi-res mid-res, and low-res). anticoincidence detection, counting rate dependence, and noise rejection.

Minimal time change detection algorithm for reconfigurable control system and application to aerospace

NASA Technical Reports Server (NTRS)

Kim, Sungwan

1994-01-01

System parameters should be tracked on-line to build a reconfigurable control system even though there exists an abrupt change. For this purpose, a new performance index that we are studying is the speed of adaptation- how quickly does the system determine that a change has occurred? In this paper, a new, robust algorithm that is optimized to minimize the time delay in detecting a change for fixed false alarm probability is proposed. Simulation results for the aircraft lateral motion with a known or unknown change in control gain matrices, in the presence of doublet input, indicate that the algorithm works fairly well. One of its distinguishing properties is that detection delay of this algorithm is superior to that of Whiteness Test.

Intelligent Tires Based on Measurement of Tire Deformation

NASA Astrophysics Data System (ADS)

Matsuzaki, Ryosuke; Todoroki, Akira

From a traffic safety point-of-view, there is an urgent need for intelligent tires as a warning system for road conditions, for optimized braking control on poor road surfaces and as a tire fault detection system. Intelligent tires, equipped with sensors for monitoring applied strain, are effective in improving reliability and control systems such as anti-lock braking systems (ABSs). In previous studies, we developed a direct tire deformation or strain measurement system with sufficiently low stiffness and high elongation for practical use, and a wireless communication system between tires and vehicle that operates without a battery. The present study investigates the application of strain data for an optimized braking control and road condition warning system. The relationships between strain sensor outputs and tire mechanical parameters, including braking torque, effective radius and contact patch length, are calculated using finite element analysis. Finally, we suggested the possibility of optimized braking control and road condition warning systems. Optimized braking control can be achieved by keeping the slip ratio constant. The road condition warning would be actuated if the recorded friction coefficient at a certain slip ratio is lower than a ‘safe’ reference value.

Intelligent tires for improved tire safety using wireless strain measurement

NASA Astrophysics Data System (ADS)

Matsuzaki, Ryosuke; Todoroki, Akira

2008-03-01

From a traffic safety point-of-view, there is an urgent need for intelligent tires as a warning system for road conditions, for optimized braking control on poor road surfaces and as a tire fault detection system. Intelligent tires, equipped with sensors for monitoring applied strain, are effective in improving reliability and control systems such as anti-lock braking systems (ABSs). In previous studies, we developed a direct tire deformation or strain measurement system with sufficiently low stiffness and high elongation for practical use, and a wireless communication system between tires and vehicle that operates without a battery. The present study investigates the application of strain data for an optimized braking control and road condition warning system. The relationships between strain sensor outputs and tire mechanical parameters, including braking torque, effective radius and contact patch length, are calculated using finite element analysis. Finally, we suggested the possibility of optimized braking control and road condition warning systems. Optimized braking control can be achieved by keeping the slip ratio constant. The road condition warning would be actuated if the recorded friction coefficient at a certain slip ratio is lower than a 'safe' reference value.

Adaptive road crack detection system by pavement classification.

PubMed

Gavilán, Miguel; Balcones, David; Marcos, Oscar; Llorca, David F; Sotelo, Miguel A; Parra, Ignacio; Ocaña, Manuel; Aliseda, Pedro; Yarza, Pedro; Amírola, Alejandro

2011-01-01

This paper presents a road distress detection system involving the phases needed to properly deal with fully automatic road distress assessment. A vehicle equipped with line scan cameras, laser illumination and acquisition HW-SW is used to storage the digital images that will be further processed to identify road cracks. Pre-processing is firstly carried out to both smooth the texture and enhance the linear features. Non-crack features detection is then applied to mask areas of the images with joints, sealed cracks and white painting, that usually generate false positive cracking. A seed-based approach is proposed to deal with road crack detection, combining Multiple Directional Non-Minimum Suppression (MDNMS) with a symmetry check. Seeds are linked by computing the paths with the lowest cost that meet the symmetry restrictions. The whole detection process involves the use of several parameters. A correct setting becomes essential to get optimal results without manual intervention. A fully automatic approach by means of a linear SVM-based classifier ensemble able to distinguish between up to 10 different types of pavement that appear in the Spanish roads is proposed. The optimal feature vector includes different texture-based features. The parameters are then tuned depending on the output provided by the classifier. Regarding non-crack features detection, results show that the introduction of such module reduces the impact of false positives due to non-crack features up to a factor of 2. In addition, the observed performance of the crack detection system is significantly boosted by adapting the parameters to the type of pavement.

Adaptive Road Crack Detection System by Pavement Classification

PubMed Central

Gavilán, Miguel; Balcones, David; Marcos, Oscar; Llorca, David F.; Sotelo, Miguel A.; Parra, Ignacio; Ocaña, Manuel; Aliseda, Pedro; Yarza, Pedro; Amírola, Alejandro

2011-01-01

This paper presents a road distress detection system involving the phases needed to properly deal with fully automatic road distress assessment. A vehicle equipped with line scan cameras, laser illumination and acquisition HW-SW is used to storage the digital images that will be further processed to identify road cracks. Pre-processing is firstly carried out to both smooth the texture and enhance the linear features. Non-crack features detection is then applied to mask areas of the images with joints, sealed cracks and white painting, that usually generate false positive cracking. A seed-based approach is proposed to deal with road crack detection, combining Multiple Directional Non-Minimum Suppression (MDNMS) with a symmetry check. Seeds are linked by computing the paths with the lowest cost that meet the symmetry restrictions. The whole detection process involves the use of several parameters. A correct setting becomes essential to get optimal results without manual intervention. A fully automatic approach by means of a linear SVM-based classifier ensemble able to distinguish between up to 10 different types of pavement that appear in the Spanish roads is proposed. The optimal feature vector includes different texture-based features. The parameters are then tuned depending on the output provided by the classifier. Regarding non-crack features detection, results show that the introduction of such module reduces the impact of false positives due to non-crack features up to a factor of 2. In addition, the observed performance of the crack detection system is significantly boosted by adapting the parameters to the type of pavement. PMID:22163717

Optimizing microwave photodetection: input-output theory

NASA Astrophysics Data System (ADS)

Schöndorf, M.; Govia, L. C. G.; Vavilov, M. G.; McDermott, R.; Wilhelm, F. K.

2018-04-01

High fidelity microwave photon counting is an important tool for various areas from background radiation analysis in astronomy to the implementation of circuit quantum electrodynamic architectures for the realization of a scalable quantum information processor. In this work we describe a microwave photon counter coupled to a semi-infinite transmission line. We employ input-output theory to examine a continuously driven transmission line as well as traveling photon wave packets. Using analytic and numerical methods, we calculate the conditions on the system parameters necessary to optimize measurement and achieve high detection efficiency. With this we can derive a general matching condition depending on the different system rates, under which the measurement process is optimal.

Research Challenges in Water Infrastructure Condition Assessment, Rehabilitation and System Optimization – The U.S. Perspective

EPA Science Inventory

This presentation first provides an overview of U.S.EPA research activities on water infrastructure condition assessment, system rehabilitation, and asset management. It then describes in detail specific activities in pipe leak detection, water conservation and the advanced wate...

Fukunaga-Koontz feature transformation for statistical structural damage detection and hierarchical neuro-fuzzy damage localisation

NASA Astrophysics Data System (ADS)

Hoell, Simon; Omenzetter, Piotr

2017-07-01

Considering jointly damage sensitive features (DSFs) of signals recorded by multiple sensors, applying advanced transformations to these DSFs and assessing systematically their contribution to damage detectability and localisation can significantly enhance the performance of structural health monitoring systems. This philosophy is explored here for partial autocorrelation coefficients (PACCs) of acceleration responses. They are interrogated with the help of the linear discriminant analysis based on the Fukunaga-Koontz transformation using datasets of the healthy and selected reference damage states. Then, a simple but efficient fast forward selection procedure is applied to rank the DSF components with respect to statistical distance measures specialised for either damage detection or localisation. For the damage detection task, the optimal feature subsets are identified based on the statistical hypothesis testing. For damage localisation, a hierarchical neuro-fuzzy tool is developed that uses the DSF ranking to establish its own optimal architecture. The proposed approaches are evaluated experimentally on data from non-destructively simulated damage in a laboratory scale wind turbine blade. The results support our claim of being able to enhance damage detectability and localisation performance by transforming and optimally selecting DSFs. It is demonstrated that the optimally selected PACCs from multiple sensors or their Fukunaga-Koontz transformed versions can not only improve the detectability of damage via statistical hypothesis testing but also increase the accuracy of damage localisation when used as inputs into a hierarchical neuro-fuzzy network. Furthermore, the computational effort of employing these advanced soft computing models for damage localisation can be significantly reduced by using transformed DSFs.

Root System Water Consumption Pattern Identification on Time Series Data.

PubMed

Figueroa, Manuel; Pope, Christopher

2017-06-16

In agriculture, soil and meteorological sensors are used along low power networks to capture data, which allows for optimal resource usage and minimizing environmental impact. This study uses time series analysis methods for outliers' detection and pattern recognition on soil moisture sensor data to identify irrigation and consumption patterns and to improve a soil moisture prediction and irrigation system. This study compares three new algorithms with the current detection technique in the project; the results greatly decrease the number of false positives detected. The best result is obtained by the Series Strings Comparison (SSC) algorithm averaging a precision of 0.872 on the testing sets, vastly improving the current system's 0.348 precision.

The Role of Optimality in Characterizing CO2 Seepage from Geological Carbon Sequestration Sites

NASA Astrophysics Data System (ADS)

Cortis, A.; Oldenburg, C. M.; Benson, S. M.

2007-12-01

Storage of large amounts of carbon dioxide (CO2) in deep geological formations for greenhouse-gas mitigation is gaining momentum and moving from its conceptual and testing stages towards widespread application. In this talk we explore various optimization strategies for characterizing surface leakage (seepage) using near-surface measurement approaches such as accumulation chambers and eddy covariance towers. Seepage characterization objectives and limitations need to be defined carefully from the outset especially in light of large natural background variations that can mask seepage. The cost and sensitivity of seepage detection are related to four critical length scales pertaining to the size of the: (1) region that needs to be monitored; (2) footprint of the measurement approach; (3) main seepage zone; and (4) region in which concentrations or fluxes are influenced by seepage. Seepage characterization objectives may include one or all of the tasks of detecting, locating, and quantifying seepage. Each of these tasks has its own optimal strategy. Detecting and locating seepage in a region in which there is no expected or preferred location for seepage nor existing evidence for seepage requires monitoring on a fixed grid, e.g., using eddy covariance towers. The fixed-grid approaches needed to detect seepage are expected to require large numbers of eddy covariance towers for large-scale geologic CO2 storage. Once seepage has been detected and roughly located, seepage zones and features can be optimally pinpointed through a dynamic search strategy, e.g., employing accumulation chambers and/or soil-gas sampling. Quantification of seepage rates can be done through measurements on a localized fixed grid once the seepage is pinpointed. Background measurements are essential for seepage detection in natural ecosystems. Artificial neural networks are considered as regression models useful for distinguishing natural system behavior from anomalous behavior suggestive of CO2 seepage without need for detailed understanding of natural system processes. Because of the local extrema in CO2 fluxes and concentrations in natural systems, simple steepest-descent algorithms are not effective and evolutionary computation algorithms are proposed as a paradigm for dynamic monitoring networks to pinpoint CO2 seepage areas. This work was carried out within the ZERT project, funded by the Assistant Secretary for Fossil Energy, Office of Sequestration, Hydrogen, and Clean Coal Fuels, National Energy Technology Laboratory, of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231.

WE-EF-207-01: FEATURED PRESENTATION and BEST IN PHYSICS (IMAGING): Task-Driven Imaging for Cone-Beam CT in Interventional Guidance

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

Gang, G; Stayman, J; Ouadah, S

2015-06-15

Purpose: This work introduces a task-driven imaging framework that utilizes a patient-specific anatomical model, mathematical definition of the imaging task, and a model of the imaging system to prospectively design acquisition and reconstruction techniques that maximize task-based imaging performance. Utility of the framework is demonstrated in the joint optimization of tube current modulation and view-dependent reconstruction kernel in filtered-backprojection reconstruction and non-circular orbit design in model-based reconstruction. Methods: The system model is based on a cascaded systems analysis of cone-beam CT capable of predicting the spatially varying noise and resolution characteristics as a function of the anatomical model and amore » wide range of imaging parameters. Detectability index for a non-prewhitening observer model is used as the objective function in a task-driven optimization. The combination of tube current and reconstruction kernel modulation profiles were identified through an alternating optimization algorithm where tube current was updated analytically followed by a gradient-based optimization of reconstruction kernel. The non-circular orbit is first parameterized as a linear combination of bases functions and the coefficients were then optimized using an evolutionary algorithm. The task-driven strategy was compared with conventional acquisitions without modulation, using automatic exposure control, and in a circular orbit. Results: The task-driven strategy outperformed conventional techniques in all tasks investigated, improving the detectability of a spherical lesion detection task by an average of 50% in the interior of a pelvis phantom. The non-circular orbit design successfully mitigated photon starvation effects arising from a dense embolization coil in a head phantom, improving the conspicuity of an intracranial hemorrhage proximal to the coil. Conclusion: The task-driven imaging framework leverages a knowledge of the imaging task within a patient-specific anatomical model to optimize image acquisition and reconstruction techniques, thereby improving imaging performance beyond that achievable with conventional approaches. 2R01-CA-112163; R01-EB-017226; U01-EB-018758; Siemens Healthcare (Forcheim, Germany)« less

Attacks and Countermeasures in Communications and Power Networks

DTIC Science & Technology

2014-01-01

the victim. This strategy is often used to confuse the intrusion detection system about the adversary’s location. If the adversary compromises a pair...1.2 Detection of Information Flows Detection of information flows between a pair of nodes has been studied in the context of network intrusion ...Theo- rem 3.3.4 were derived purely based on the condition for undetectability. Hence, the same optimality statements hold for the noisy measurement

Detection of Prohibited Fish Drugs Using Silver Nanowires as Substrate for Surface-Enhanced Raman Scattering

PubMed Central

Song, Jia; Huang, Yiqun; Fan, Yuxia; Zhao, Zhihui; Yu, Wansong; Rasco, Barbara A.; Lai, Keqiang

2016-01-01

Surface-enhanced Raman scattering or surface-enhanced Raman spectroscopy (SERS) is a promising detection technology, and has captured increasing attention. Silver nanowires were synthesized using a rapid polyol method and optimized through adjustment of the molar ratio of poly(vinyl pyrrolidone) and silver nitrate in a glycerol system. Ultraviolet-visible spectrometry, X-ray diffraction, and transmission electron microscopy were used to characterize the silver nanowires. The optimal silver nanowires were used as a SERS substrate to detect prohibited fish drugs, including malachite green, crystal violet, furazolidone, and chloramphenicol. The SERS spectra of crystal violet could be clearly identified at concentrations as low as 0.01 ng/mL. The minimum detectable concentration for malachite green was 0.05 ng/mL, and for both furazolidone and chloramphenicol were 0.1 μg/mL. The results showed that the as-prepared Ag nanowires SERS substrate exhibits high sensitivity and activity. PMID:28335303

Preformulation studies and optimization of sodium alginate based floating drug delivery system for eradication of Helicobacter pylori.

PubMed

Diós, Péter; Nagy, Sándor; Pál, Szilárd; Pernecker, Tivadar; Kocsis, Béla; Budán, Ferenc; Horváth, Ildikó; Szigeti, Krisztián; Bölcskei, Kata; Máthé, Domokos; Dévay, Attila

2015-10-01

The aim of this study was to design a local, floating, mucoadhesive drug delivery system containing metronidazole for Helicobacter pylori eradication. Face-centered central composite design (with three factors, in three levels) was used for evaluation and optimization of in vitro floating and dissolution studies. Sodium alginate (X1), low substituted hydroxypropyl cellulose (L-HPC B1, X2) and sodium bicarbonate (X3) concentrations were the independent variables in the development of effervescent floating tablets. All tablets showed acceptable physicochemical properties. Statistical analysis revealed that tablets with 5.00% sodium alginate, 38.63% L-HPC B1 and 8.45% sodium bicarbonate content showed promising in vitro floating and dissolution properties for further examinations. Optimized floating tablets expressed remarkable floating force. Their in vitro dissolution studies were compared with two commercially available non-floating metronidazole products and then microbiologically detected dissolution, ex vivo detachment force, rheological mucoadhesion studies and compatibility studies were carried out. Remarkable similarity (f1, f2) between in vitro spectrophotometrically and microbiologically detected dissolutions was found. Studies revealed significant ex vivo mucoadhesion of optimized tablets, which was considerably increased by L-HPC. In vivo X-ray CT studies of optimized tablets showed 8h gastroretention in rats represented by an animation prepared by special CT technique. Copyright © 2015 Elsevier B.V. All rights reserved.

Optimization of digital breast tomosynthesis (DBT) acquisition parameters for human observers: effect of reconstruction algorithms

NASA Astrophysics Data System (ADS)

Zeng, Rongping; Badano, Aldo; Myers, Kyle J.

2017-04-01

We showed in our earlier work that the choice of reconstruction methods does not affect the optimization of DBT acquisition parameters (angular span and number of views) using simulated breast phantom images in detecting lesions with a channelized Hotelling observer (CHO). In this work we investigate whether the model-observer based conclusion is valid when using humans to interpret images. We used previously generated DBT breast phantom images and recruited human readers to find the optimal geometry settings associated with two reconstruction algorithms, filtered back projection (FBP) and simultaneous algebraic reconstruction technique (SART). The human reader results show that image quality trends as a function of the acquisition parameters are consistent between FBP and SART reconstructions. The consistent trends confirm that the optimization of DBT system geometry is insensitive to the choice of reconstruction algorithm. The results also show that humans perform better in SART reconstructed images than in FBP reconstructed images. In addition, we applied CHOs with three commonly used channel models, Laguerre-Gauss (LG) channels, square (SQR) channels and sparse difference-of-Gaussian (sDOG) channels. We found that LG channels predict human performance trends better than SQR and sDOG channel models for the task of detecting lesions in tomosynthesis backgrounds. Overall, this work confirms that the choice of reconstruction algorithm is not critical for optimizing DBT system acquisition parameters.

Stochastic resonance in attention control

NASA Astrophysics Data System (ADS)

Kitajo, K.; Yamanaka, K.; Ward, L. M.; Yamamoto, Y.

2006-12-01

We investigated the beneficial role of noise in a human higher brain function, namely visual attention control. We asked subjects to detect a weak gray-level target inside a marker box either in the left or the right visual field. Signal detection performance was optimized by presenting a low level of randomly flickering gray-level noise between and outside the two possible target locations. Further, we found that an increase in eye movement (saccade) rate helped to compensate for the usual deterioration in detection performance at higher noise levels. To our knowledge, this is the first experimental evidence that noise can optimize a higher brain function which involves distinct brain regions above the level of primary sensory systems -- switching behavior between multi-stable attention states -- via the mechanism of stochastic resonance.

Fundamentals and practice for ultrasensitive laser-induced fluorescence detection in microanalytical systems.

PubMed

Johnson, Mitchell E; Landers, James P

2004-11-01

Laser-induced fluorescence is an extremely sensitive method for detection in chemical separations. In addition, it is well-suited to detection in small volumes, and as such is widely used for capillary electrophoresis and microchip-based separations. This review explores the detailed instrumental conditions required for sub-zeptomole, sub-picomolar detection limits. The key to achieving the best sensitivity is to use an excitation and emission volume that is matched to the separation system and that, simultaneously, will keep scattering and luminescence background to a minimum. We discuss how this is accomplished with confocal detection, 90 degrees on-capillary detection, and sheath-flow detection. It is shown that each of these methods have their advantages and disadvantages, but that all can be used to produce extremely sensitive detectors for capillary- or microchip-based separations. Analysis of these capabilities allows prediction of the optimal means of achieving ultrasensitive detection on microchips.

Optimizing searches for electromagnetic counterparts of gravitational wave triggers

NASA Astrophysics Data System (ADS)

Coughlin, Michael W.; Tao, Duo; Chan, Man Leong; Chatterjee, Deep; Christensen, Nelson; Ghosh, Shaon; Greco, Giuseppe; Hu, Yiming; Kapadia, Shasvath; Rana, Javed; Salafia, Om Sharan; Stubbs11, Christopher

2018-04-01

With the detection of a binary neutron star system and its corresponding electromagnetic counterparts, a new window of transient astronomy has opened. Due to the size of the sky localization regions, which can span hundreds to thousands of square degrees, there are significant benefits to optimizing tilings for these large sky areas. The rich science promised by gravitational-wave astronomy has led to the proposal for a variety of proposed tiling and time allocation schemes, and for the first time, we make a systematic comparison of some of these methods. We find that differences of a factor of 2 or more in efficiency are possible, depending on the algorithm employed. For this reason, with future surveys searching for electromagnetic counterparts, care should be taken when selecting tiling, time allocation, and scheduling algorithms to optimize counterpart detection.

Optimizing searches for electromagnetic counterparts of gravitational wave triggers

NASA Astrophysics Data System (ADS)

Coughlin, Michael W.; Tao, Duo; Chan, Man Leong; Chatterjee, Deep; Christensen, Nelson; Ghosh, Shaon; Greco, Giuseppe; Hu, Yiming; Kapadia, Shasvath; Rana, Javed; Salafia, Om Sharan; Stubbs, Christopher W.

2018-07-01

With the detection of a binary neutron star system and its corresponding electromagnetic counterparts, a new window of transient astronomy has opened. Due to the size of the sky localization regions, which can span hundreds to thousands of square degrees, there are significant benefits to optimizing tilings for these large sky areas. The rich science promised by gravitational wave astronomy has led to the proposal for a variety of proposed tiling and time allocation schemes, and for the first time, we make a systematic comparison of some of these methods. We find that differences of a factor of 2 or more in efficiency are possible, depending on the algorithm employed. For this reason, with future surveys searching for electromagnetic counterparts, care should be taken when selecting tiling, time allocation, and scheduling algorithms to optimize counterpart detection.

An adaptive technique for a redundant-sensor navigation system.

NASA Technical Reports Server (NTRS)

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.

Improving compliance in remote healthcare systems through smartphone battery optimization.

PubMed

Alshurafa, Nabil; Eastwood, Jo-Ann; Nyamathi, Suneil; Liu, Jason J; Xu, Wenyao; Ghasemzadeh, Hassan; Pourhomayoun, Mohammad; Sarrafzadeh, Majid

2015-01-01

Remote health monitoring (RHM) has emerged as a solution to help reduce the cost burden of unhealthy lifestyles and aging populations. Enhancing compliance to prescribed medical regimens is an essential challenge to many systems, even those using smartphone technology. In this paper, we provide a technique to improve smartphone battery consumption and examine the effects of smartphone battery lifetime on compliance, in an attempt to enhance users' adherence to remote monitoring systems. We deploy WANDA-CVD, an RHM system for patients at risk of cardiovascular disease (CVD), using a wearable smartphone for detection of physical activity. We tested the battery optimization technique in an in-lab pilot study and validated its effects on compliance in the Women's Heart Health Study. The battery optimization technique enhanced the battery lifetime by 192% on average, resulting in a 53% increase in compliance in the study. A system like WANDA-CVD can help increase smartphone battery lifetime for RHM systems monitoring physical activity.

Gear-box fault detection using time-frequency based methods

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

Odgaard, Peter Fogh; Stoustrup, Jakob

2015-01-01

Gear-box fault monitoring and detection is important for optimization of power generation and availability of wind turbines. The current industrial approach is to use condition monitoring systems, which runs in parallel with the wind turbine control system, using expensive additional sensors. An alternative would be to use the existing measurements which are normally available for the wind turbine control system. The usage of these sensors instead would cut down the cost of the wind turbine by not using additional sensors. One of these available measurements is the generator speed, in which changes in the gear-box resonance frequency can be detected.more » Two different time-frequency based approaches are presented in this paper. One is a filter based approach and the other is based on a Karhunen-Loeve basis. Both of them detects the gear-box fault with an acceptable detection delay.« less

Underwater single beam circumferentially scanning detection system using range-gated receiver and adaptive filter

NASA Astrophysics Data System (ADS)

Tan, Yayun; Zhang, He; Zha, Bingting

2017-09-01

Underwater target detection and ranging in seawater are of interest in unmanned underwater vehicles. This study presents an underwater detection system that synchronously scans a collimated laser beam and a narrow field of view to circumferentially detect an underwater target. Hybrid methods of range-gated and variable step-size least mean squares (VSS-LMS) adaptive filter are proposed to suppress water backscattering. The range-gated receiver eliminates the backscattering of near-field water. The VSS-LMS filter extracts the target echo in the remaining backscattering and the constant fraction discriminator timing method is used to improve ranging accuracy. The optimal constant fraction is selected by analysing the jitter noise and slope of the target echo. The prototype of the underwater detection system is constructed and tested in coastal seawater, then the effectiveness of backscattering suppression and high-ranging accuracy is verified through experimental results and analysis discussed in this paper.

Locally optimum nonlinearities for DCT watermark detection.

PubMed

Briassouli, Alexia; Strintzis, Michael G

2004-12-01

The issue of copyright protection of digital multimedia data has attracted a lot of attention during the last decade. An efficient copyright protection method that has been gaining popularity is watermarking, i.e., the embedding of a signature in a digital document that can be detected only by its rightful owner. Watermarks are usually blindly detected using correlating structures, which would be optimal in the case of Gaussian data. However, in the case of DCT-domain image watermarking, the data is more heavy-tailed and the correlator is clearly suboptimal. Nonlinear receivers have been shown to be particularly well suited for the detection of weak signals in heavy-tailed noise, as they are locally optimal. This motivates the use of the Gaussian-tailed zero-memory nonlinearity, as well as the locally optimal Cauchy nonlinearity for the detection of watermarks in DCT transformed images. We analyze the performance of these schemes theoretically and compare it to that of the traditionally used Gaussian correlator, but also to the recently proposed generalized Gaussian detector, which outperforms the correlator. The theoretical analysis and the actual performance of these systems is assessed through experiments, which verify the theoretical analysis and also justify the use of nonlinear structures for watermark detection. The performance of the correlator and the nonlinear detectors in the presence of quantization is also analyzed, using results from dither theory, and also verified experimentally.

Spatial-Temporal Synchrophasor Data Characterization and Analytics in Smart Grid Fault Detection, Identification, and Impact Causal Analysis

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

Jiang, Huaiguang; Dai, Xiaoxiao; Gao, David Wenzhong

An approach of big data characterization for smart grids (SGs) and its applications in fault detection, identification, and causal impact analysis is proposed in this paper, which aims to provide substantial data volume reduction while keeping comprehensive information from synchrophasor measurements in spatial and temporal domains. Especially, based on secondary voltage control (SVC) and local SG observation algorithm, a two-layer dynamic optimal synchrophasor measurement devices selection algorithm (OSMDSA) is proposed to determine SVC zones, their corresponding pilot buses, and the optimal synchrophasor measurement devices. Combining the two-layer dynamic OSMDSA and matching pursuit decomposition, the synchrophasor data is completely characterized inmore » the spatial-temporal domain. To demonstrate the effectiveness of the proposed characterization approach, SG situational awareness is investigated based on hidden Markov model based fault detection and identification using the spatial-temporal characteristics generated from the reduced data. To identify the major impact buses, the weighted Granger causality for SGs is proposed to investigate the causal relationship of buses during system disturbance. The IEEE 39-bus system and IEEE 118-bus system are employed to validate and evaluate the proposed approach.« less

Integrated explosive preconcentrator and electrochemical detection system for 2,4,6-trinitrotoluene (TNT) vapor.

PubMed

Cizek, Karel; Prior, Chad; Thammakhet, Chongdee; Galik, Michal; Linker, Kevin; Tsui, Ray; Cagan, Avi; Wake, John; La Belle, Jeff; Wang, Joseph

2010-02-19

This article reports on an integrated explosive-preconcentration/electrochemical detection system for 2,4,6-trinitrotoluene (TNT) vapor. The challenges involved in such system integration are discussed. A hydrogel-coated screen-printed electrode is used for the detection of the thermally desorbed TNT from a preconcentration device using rapid square wave voltammetry. Optimization of the preconcentration system for desorption of TNT and subsequent electrochemical detection was conducted yielding a desorption temperature of 120 degrees C under a flow rate of 500 mL min(-1). Such conditions resulted in a characteristic electrochemical signal for TNT representing the multi-step reduction process. Quantitative measurements produced a linear signal dependence on TNT quantity exposed to the preconcentrator from 0.25 to 10 microg. Finally, the integrated device was successfully demonstrated using a sample of solid TNT located upstream of the preconcentrator. Copyright 2009 Elsevier B.V. All rights reserved.

NASA Tech Briefs, April 2010

NASA Technical Reports Server (NTRS)

2010-01-01

Topics covered include: Active and Passive Hybrid Sensor; Quick-Response Thermal Actuator for Use as a Heat Switch; System for Hydrogen Sensing; Method for Detecting Perlite Compaction in Large Cryogenic Tanks; Using Thin-Film Thermometers as Heaters in Thermal Control Applications; Directional Spherical Cherenkov Detector; AlGaN Ultraviolet Detectors for Dual-Band UV Detection; K-Band Traveling-Wave Tube Amplifier; Simplified Load-Following Control for a Fuel Cell System; Modified Phase-meter for a Heterodyne Laser Interferometer; Loosely Coupled GPS-Aided Inertial Navigation System for Range Safety; Sideband-Separating, Millimeter-Wave Heterodyne Receiver; Coaxial Propellant Injectors With Faceplate Annulus Control; Adaptable Diffraction Gratings With Wavefront Transformation; Optimizing a Laser Process for Making Carbon Nanotubes; Thermogravimetric Analysis of Single-Wall Carbon Nanotubes; Robotic Arm Comprising Two Bending Segments; Magnetostrictive Brake; Low-Friction, Low-Profile, High-Moment Two-Axis Joint; Foil Gas Thrust Bearings for High-Speed Turbomachinery; Miniature Multi-Axis Mechanism for Hand Controllers; Digitally Enhanced Heterodyne Interferometry; Focusing Light Beams To Improve Atomic-Vapor Optical Buffers; Landmark Detection in Orbital Images Using Salience Histograms; Efficient Bit-to-Symbol Likelihood Mappings; Capacity Maximizing Constellations; Natural-Language Parser for PBEM; Policy Process Editor for P(sup 3)BM Software; A Quality System Database; Trajectory Optimization: OTIS 4; and Computer Software Configuration Item-Specific Flight Software Image Transfer Script Generator.

Optimal discrete-time LQR problems for parabolic systems with unbounded input: Approximation and convergence

NASA Technical Reports Server (NTRS)

Rosen, I. G.

1988-01-01

An abstract approximation and convergence theory for the closed-loop solution of discrete-time linear-quadratic regulator problems for parabolic systems with unbounded input is developed. Under relatively mild stabilizability and detectability assumptions, functional analytic, operator techniques are used to demonstrate the norm convergence of Galerkin-based approximations to the optimal feedback control gains. The application of the general theory to a class of abstract boundary control systems is considered. Two examples, one involving the Neumann boundary control of a one-dimensional heat equation, and the other, the vibration control of a cantilevered viscoelastic beam via shear input at the free end, are discussed.

Method of multi-dimensional moment analysis for the characterization of signal peaks

DOEpatents

Pfeifer, Kent B; Yelton, William G; Kerr, Dayle R; Bouchier, Francis A

2012-10-23

A method of multi-dimensional moment analysis for the characterization of signal peaks can be used to optimize the operation of an analytical system. With a two-dimensional Peclet analysis, the quality and signal fidelity of peaks in a two-dimensional experimental space can be analyzed and scored. This method is particularly useful in determining optimum operational parameters for an analytical system which requires the automated analysis of large numbers of analyte data peaks. For example, the method can be used to optimize analytical systems including an ion mobility spectrometer that uses a temperature stepped desorption technique for the detection of explosive mixtures.

A statistical, task-based evaluation method for three-dimensional x-ray breast imaging systems using variable-background phantoms

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

Park, Subok; Jennings, Robert; Liu Haimo

Purpose: For the last few years, development and optimization of three-dimensional (3D) x-ray breast imaging systems, such as digital breast tomosynthesis (DBT) and computed tomography, have drawn much attention from the medical imaging community, either academia or industry. However, there is still much room for understanding how to best optimize and evaluate the devices over a large space of many different system parameters and geometries. Current evaluation methods, which work well for 2D systems, do not incorporate the depth information from the 3D imaging systems. Therefore, it is critical to develop a statistically sound evaluation method to investigate the usefulnessmore » of inclusion of depth and background-variability information into the assessment and optimization of the 3D systems. Methods: In this paper, we present a mathematical framework for a statistical assessment of planar and 3D x-ray breast imaging systems. Our method is based on statistical decision theory, in particular, making use of the ideal linear observer called the Hotelling observer. We also present a physical phantom that consists of spheres of different sizes and materials for producing an ensemble of randomly varying backgrounds to be imaged for a given patient class. Lastly, we demonstrate our evaluation method in comparing laboratory mammography and three-angle DBT systems for signal detection tasks using the phantom's projection data. We compare the variable phantom case to that of a phantom of the same dimensions filled with water, which we call the uniform phantom, based on the performance of the Hotelling observer as a function of signal size and intensity. Results: Detectability trends calculated using the variable and uniform phantom methods are different from each other for both mammography and DBT systems. Conclusions: Our results indicate that measuring the system's detection performance with consideration of background variability may lead to differences in system performance estimates and comparisons. For the assessment of 3D systems, to accurately determine trade offs between image quality and radiation dose, it is critical to incorporate randomness arising from the imaging chain including background variability into system performance calculations.« less

Optimized acoustic biochip integrated with microfluidics for biomarkers detection in molecular diagnostics.

PubMed

Papadakis, G; Friedt, J M; Eck, M; Rabus, D; Jobst, G; Gizeli, E

2017-09-01

The development of integrated platforms incorporating an acoustic device as the detection element requires addressing simultaneously several challenges of technological and scientific nature. The present work was focused on the design of a microfluidic module, which, combined with a dual or array type Love wave acoustic chip could be applied to biomedical applications and molecular diagnostics. Based on a systematic study we optimized the mechanics of the flow cell attachment and the sealing material so that fluidic interfacing/encapsulation would impose minimal losses to the acoustic wave. We have also investigated combinations of operating frequencies with waveguide materials and thicknesses for maximum sensitivity during the detection of protein and DNA biomarkers. Within our investigations neutravidin was used as a model protein biomarker and unpurified PCR amplified Salmonella DNA as the model genetic target. Our results clearly indicate the need for experimental verification of the optimum engineering and analytical parameters, in order to develop commercially viable systems for integrated analysis. The good reproducibility of the signal together with the ability of the array biochip to detect multiple samples hold promise for the future use of the integrated system in a Lab-on-a-Chip platform for application to molecular diagnostics.

Monitoring/Verification using DMS: TATP Example

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

Stephan Weeks, Kevin Kyle, Manuel Manard

Field-rugged and field-programmable differential mobility spectrometry (DMS) networks provide highly selective, universal monitoring of vapors and aerosols at detectable levels from persons or areas involved with illicit chemical/biological/explosives (CBE) production. CBE sensor motes used in conjunction with automated fast gas chromatography with DMS detection (GC/DMS) verification instrumentation integrated into situational operations-management systems can be readily deployed and optimized for changing application scenarios. The feasibility of developing selective DMS motes for a “smart dust” sampling approach with guided, highly selective, fast GC/DMS verification analysis is a compelling approach to minimize or prevent the illegal use of explosives or chemical and biologicalmore » materials. DMS is currently one of the foremost emerging technologies for field separation and detection of gas-phase chemical species. This is due to trace-level detection limits, high selectivity, and small size. Fast GC is the leading field analytical method for gas phase separation of chemical species in complex mixtures. Low-thermal-mass GC columns have led to compact, low-power field systems capable of complete analyses in 15–300 seconds. A collaborative effort optimized a handheld, fast GC/DMS, equipped with a non-rad ionization source, for peroxide-based explosive measurements.« less

Monitoring/Verification Using DMS: TATP Example

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

Kevin Kyle; Stephan Weeks

Field-rugged and field-programmable differential mobility spectrometry (DMS) networks provide highly selective, universal monitoring of vapors and aerosols at detectable levels from persons or areas involved with illicit chemical/biological/explosives (CBE) production. CBE sensor motes used in conjunction with automated fast gas chromatography with DMS detection (GC/DMS) verification instrumentation integrated into situational operationsmanagement systems can be readily deployed and optimized for changing application scenarios. The feasibility of developing selective DMS motes for a “smart dust” sampling approach with guided, highly selective, fast GC/DMS verification analysis is a compelling approach to minimize or prevent the illegal use of explosives or chemical and biologicalmore » materials. DMS is currently one of the foremost emerging technologies for field separation and detection of gas-phase chemical species. This is due to trace-level detection limits, high selectivity, and small size. GC is the leading analytical method for the separation of chemical species in complex mixtures. Low-thermal-mass GC columns have led to compact, low-power field systems capable of complete analyses in 15–300 seconds. A collaborative effort optimized a handheld, fast GC/DMS, equipped with a non-rad ionization source, for peroxide-based explosive measurements.« less

Multi-probe-based resonance-frequency electrical impedance spectroscopy for detection of suspicious breast lesions: improving performance using partial ROC optimization

NASA Astrophysics Data System (ADS)

Lederman, Dror; Zheng, Bin; Wang, Xingwei; Wang, Xiao Hui; Gur, David

2011-03-01

We have developed a multi-probe resonance-frequency electrical impedance spectroscope (REIS) system to detect breast abnormalities. Based on assessing asymmetry in REIS signals acquired between left and right breasts, we developed several machine learning classifiers to classify younger women (i.e., under 50YO) into two groups of having high and low risk for developing breast cancer. In this study, we investigated a new method to optimize performance based on the area under a selected partial receiver operating characteristic (ROC) curve when optimizing an artificial neural network (ANN), and tested whether it could improve classification performance. From an ongoing prospective study, we selected a dataset of 174 cases for whom we have both REIS signals and diagnostic status verification. The dataset includes 66 "positive" cases recommended for biopsy due to detection of highly suspicious breast lesions and 108 "negative" cases determined by imaging based examinations. A set of REIS-based feature differences, extracted from the two breasts using a mirror-matched approach, was computed and constituted an initial feature pool. Using a leave-one-case-out cross-validation method, we applied a genetic algorithm (GA) to train the ANN with an optimal subset of features. Two optimization criteria were separately used in GA optimization, namely the area under the entire ROC curve (AUC) and the partial area under the ROC curve, up to a predetermined threshold (i.e., 90% specificity). The results showed that although the ANN optimized using the entire AUC yielded higher overall performance (AUC = 0.83 versus 0.76), the ANN optimized using the partial ROC area criterion achieved substantially higher operational performance (i.e., increasing sensitivity level from 28% to 48% at 95% specificity and/ or from 48% to 58% at 90% specificity).

Single-molecule fluorescence detection: autocorrelation criterion and experimental realization with phycoerythrin.

PubMed Central

Peck, K; Stryer, L; Glazer, A N; Mathies, R A

1989-01-01

A theory for single-molecule fluorescence detection is developed and then used to analyze data from subpicomolar solutions of B-phycoerythrin (PE). The distribution of detected counts is the convolution of a Poissonian continuous background with bursts arising from the passage of individual fluorophores through the focused laser beam. The autocorrelation function reveals single-molecule events and provides a criterion for optimizing experimental parameters. The transit time of fluorescent molecules through the 120-fl imaged volume was 800 microseconds. The optimal laser power (32 mW at 514.5 nm) gave an incident intensity of 1.8 x 10(23) photons.cm-2.s-1, corresponding to a mean time of 1.1 ns between absorptions. The mean incremental count rate was 1.5 per 100 microseconds for PE monomers and 3.0 for PE dimers above a background count rate of 1.0. The distribution of counts and the autocorrelation function for 200 fM monomer and 100 fM dimer demonstrate that single-molecule detection was achieved. At this concentration, the mean occupancy was 0.014 monomer molecules in the probed volume. A hard-wired version of this detection system was used to measure the concentration of PE down to 1 fM. This single-molecule counter is 3 orders of magnitude more sensitive than conventional fluorescence detection systems. PMID:2726766

Optimization of Second Fault Detection Thresholds to Maximize Mission POS

NASA Technical Reports Server (NTRS)

Anzalone, Evan

2018-01-01

In order to support manned spaceflight safety requirements, the Space Launch System (SLS) has defined program-level requirements for key systems to ensure successful operation under single fault conditions. To accommodate this with regards to Navigation, the SLS utilizes an internally redundant Inertial Navigation System (INS) with built-in capability to detect, isolate, and recover from first failure conditions and still maintain adherence to performance requirements. The unit utilizes multiple hardware- and software-level techniques to enable detection, isolation, and recovery from these events in terms of its built-in Fault Detection, Isolation, and Recovery (FDIR) algorithms. Successful operation is defined in terms of sufficient navigation accuracy at insertion while operating under worst case single sensor outages (gyroscope and accelerometer faults at launch). In addition to first fault detection and recovery, the SLS program has also levied requirements relating to the capability of the INS to detect a second fault, tracking any unacceptable uncertainty in knowledge of the vehicle's state. This detection functionality is required in order to feed abort analysis and ensure crew safety. Increases in navigation state error and sensor faults can drive the vehicle outside of its operational as-designed environments and outside of its performance envelope causing loss of mission, or worse, loss of crew. The criteria for operation under second faults allows for a larger set of achievable missions in terms of potential fault conditions, due to the INS operating at the edge of its capability. As this performance is defined and controlled at the vehicle level, it allows for the use of system level margins to increase probability of mission success on the operational edges of the design space. Due to the implications of the vehicle response to abort conditions (such as a potentially failed INS), it is important to consider a wide range of failure scenarios in terms of both magnitude and time. As such, the Navigation team is taking advantage of the INS's capability to schedule and change fault detection thresholds in flight. These values are optimized along a nominal trajectory in order to maximize probability of mission success, and reducing the probability of false positives (defined as when the INS would report a second fault condition resulting in loss of mission, but the vehicle would still meet insertion requirements within system-level margins). This paper will describe an optimization approach using Genetic Algorithms to tune the threshold parameters to maximize vehicle resilience to second fault events as a function of potential fault magnitude and time of fault over an ascent mission profile. The analysis approach, and performance assessment of the results will be presented to demonstrate the applicability of this process to second fault detection to maximize mission probability of success.

Co-generating synthetic parts toward a self-replicating system

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

Li, Jun; Haas, Wilhelm; Jackson, Kirsten

To build replicating systems with new functions, the engineering of existing biological machineries requires a sensible strategy. Protein synthesis Using Recombinant Elements (PURE) system consists of the desired components for transcription, translation, aminoacylation and energy regeneration. PURE, might be the basis for a radically alterable, lifelike system after optimization. Here, we regenerated 54 E. coli ribosomal (r-) proteins individually from DNA templates in the PURE system. We show that using stable isotope labeling with amino acids, mass spectrometry based quantitative proteomics could detect 26 of the 33 50S and 20 of the 21 30S subunit r-proteins when co-expressed in batchmore » format PURE system. By optimizing DNA template concentrations and adapting a miniaturized Fluid Array Device with optimized feeding solution, we were able to cogenerate and detect at least 29 of the 33 50S and all of the 21 30S subunit r-proteins in one pot. The boost on yield of a single r-protein in co-expression pool varied from ~1.5 to 5-fold compared to the batch mode, with up to ~ 2.4 µM yield for a single r-protein. Reconstituted ribosomes under physiological condition from PURE system synthesized 30S r-proteins and native 16S rRNA showed ~13% activity of native 70S ribosomes, which increased to 21% when supplemented with GroEL/ES. As a result, this work also points to what is still needed to obtain self-replicating synthetic ribosomes in-situ in the PURE system.« less

Co-generating synthetic parts toward a self-replicating system

DOE PAGES

Li, Jun; Haas, Wilhelm; Jackson, Kirsten; ...

2017-03-23

To build replicating systems with new functions, the engineering of existing biological machineries requires a sensible strategy. Protein synthesis Using Recombinant Elements (PURE) system consists of the desired components for transcription, translation, aminoacylation and energy regeneration. PURE, might be the basis for a radically alterable, lifelike system after optimization. Here, we regenerated 54 E. coli ribosomal (r-) proteins individually from DNA templates in the PURE system. We show that using stable isotope labeling with amino acids, mass spectrometry based quantitative proteomics could detect 26 of the 33 50S and 20 of the 21 30S subunit r-proteins when co-expressed in batchmore » format PURE system. By optimizing DNA template concentrations and adapting a miniaturized Fluid Array Device with optimized feeding solution, we were able to cogenerate and detect at least 29 of the 33 50S and all of the 21 30S subunit r-proteins in one pot. The boost on yield of a single r-protein in co-expression pool varied from ~1.5 to 5-fold compared to the batch mode, with up to ~ 2.4 µM yield for a single r-protein. Reconstituted ribosomes under physiological condition from PURE system synthesized 30S r-proteins and native 16S rRNA showed ~13% activity of native 70S ribosomes, which increased to 21% when supplemented with GroEL/ES. As a result, this work also points to what is still needed to obtain self-replicating synthetic ribosomes in-situ in the PURE system.« less

Computer object segmentation by nonlinear image enhancement, multidimensional clustering, and geometrically constrained contour optimization

NASA Astrophysics Data System (ADS)

Bruynooghe, Michel M.

1998-04-01

In this paper, we present a robust method for automatic object detection and delineation in noisy complex images. The proposed procedure is a three stage process that integrates image segmentation by multidimensional pixel clustering and geometrically constrained optimization of deformable contours. The first step is to enhance the original image by nonlinear unsharp masking. The second step is to segment the enhanced image by multidimensional pixel clustering, using our reducible neighborhoods clustering algorithm that has a very interesting theoretical maximal complexity. Then, candidate objects are extracted and initially delineated by an optimized region merging algorithm, that is based on ascendant hierarchical clustering with contiguity constraints and on the maximization of average contour gradients. The third step is to optimize the delineation of previously extracted and initially delineated objects. Deformable object contours have been modeled by cubic splines. An affine invariant has been used to control the undesired formation of cusps and loops. Non linear constrained optimization has been used to maximize the external energy. This avoids the difficult and non reproducible choice of regularization parameters, that are required by classical snake models. The proposed method has been applied successfully to the detection of fine and subtle microcalcifications in X-ray mammographic images, to defect detection by moire image analysis, and to the analysis of microrugosities of thin metallic films. The later implementation of the proposed method on a digital signal processor associated to a vector coprocessor would allow the design of a real-time object detection and delineation system for applications in medical imaging and in industrial computer vision.

Architectural design for a low cost FPGA-based traffic signal detection system in vehicles

NASA Astrophysics Data System (ADS)

López, Ignacio; Salvador, Rubén; Alarcón, Jaime; Moreno, Félix

2007-05-01

In this paper we propose an architecture for an embedded traffic signal detection system. Development of Advanced Driver Assistance Systems (ADAS) is one of the major trends of research in automotion nowadays. Examples of past and ongoing projects in the field are CHAMELEON ("Pre-Crash Application all around the vehicle" IST 1999-10108), PREVENT (Preventive and Active Safety Applications, FP6-507075, http://www.prevent-ip.org/) and AVRT in the US (Advanced Vision-Radar Threat Detection (AVRT): A Pre-Crash Detection and Active Safety System). It can be observed a major interest in systems for real-time analysis of complex driving scenarios, evaluating risk and anticipating collisions. The system will use a low cost CCD camera on the dashboard facing the road. The images will be processed by an Altera Cyclone family FPGA. The board does median and Sobel filtering of the incoming frames at PAL rate, and analyzes them for several categories of signals. The result is conveyed to the driver. The scarce resources provided by the hardware require an architecture developed for optimal use. The system will use a combination of neural networks and an adapted blackboard architecture. Several neural networks will be used in sequence for image analysis, by reconfiguring a single, generic hardware neural network in the FPGA. This generic network is optimized for speed, in order to admit several executions within the frame rate. The sequence will follow the execution cycle of the blackboard architecture. The global, blackboard architecture being developed and the hardware architecture for the generic, reconfigurable FPGA perceptron will be explained in this paper. The project is still at an early stage. However, some hardware implementation results are already available and will be offered in the paper.

A multiscale optimization approach to detect exudates in the macula.

PubMed

Agurto, Carla; Murray, Victor; Yu, Honggang; Wigdahl, Jeffrey; Pattichis, Marios; Nemeth, Sheila; Barriga, E Simon; Soliz, Peter

2014-07-01

Pathologies that occur on or near the fovea, such as clinically significant macular edema (CSME), represent high risk for vision loss. The presence of exudates, lipid residues of serous leakage from damaged capillaries, has been associated with CSME, in particular if they are located one optic disc-diameter away from the fovea. In this paper, we present an automatic system to detect exudates in the macula. Our approach uses optimal thresholding of instantaneous amplitude (IA) components that are extracted from multiple frequency scales to generate candidate exudate regions. For each candidate region, we extract color, shape, and texture features that are used for classification. Classification is performed using partial least squares (PLS). We tested the performance of the system on two different databases of 652 and 400 images. The system achieved an area under the receiver operator characteristic curve (AUC) of 0.96 for the combination of both databases and an AUC of 0.97 for each of them when they were evaluated independently.

Design of optical axis jitter control system for multi beam lasers based on FPGA

NASA Astrophysics Data System (ADS)

Ou, Long; Li, Guohui; Xie, Chuanlin; Zhou, Zhiqiang

2018-02-01

A design of optical axis closed-loop control system for multi beam lasers coherent combining based on FPGA was introduced. The system uses piezoelectric ceramics Fast Steering Mirrors (FSM) as actuator, the Fairfield spot detection of multi beam lasers by the high speed CMOS camera for optical detecting, a control system based on FPGA for real-time optical axis jitter suppression. The algorithm for optical axis centroid detecting and PID of anti-Integral saturation were realized by FPGA. Optimize the structure of logic circuit by reuse resource and pipeline, as a result of reducing logic resource but reduced the delay time, and the closed-loop bandwidth increases to 100Hz. The jitter of laser less than 40Hz was reduced 40dB. The cost of the system is low but it works stably.

Image quality, threshold contrast and mean glandular dose in CR mammography

NASA Astrophysics Data System (ADS)

Jakubiak, R. R.; Gamba, H. R.; Neves, E. B.; Peixoto, J. E.

2013-09-01

In many countries, computed radiography (CR) systems represent the majority of equipment used in digital mammography. This study presents a method for optimizing image quality and dose in CR mammography of patients with breast thicknesses between 45 and 75 mm. Initially, clinical images of 67 patients (group 1) were analyzed by three experienced radiologists, reporting about anatomical structures, noise and contrast in low and high pixel value areas, and image sharpness and contrast. Exposure parameters (kV, mAs and target/filter combination) used in the examinations of these patients were reproduced to determine the contrast-to-noise ratio (CNR) and mean glandular dose (MGD). The parameters were also used to radiograph a CDMAM (version 3.4) phantom (Artinis Medical Systems, The Netherlands) for image threshold contrast evaluation. After that, different breast thicknesses were simulated with polymethylmethacrylate layers and various sets of exposure parameters were used in order to determine optimal radiographic parameters. For each simulated breast thickness, optimal beam quality was defined as giving a target CNR to reach the threshold contrast of CDMAM images for acceptable MGD. These results were used for adjustments in the automatic exposure control (AEC) by the maintenance team. Using optimized exposure parameters, clinical images of 63 patients (group 2) were evaluated as described above. Threshold contrast, CNR and MGD for such exposure parameters were also determined. Results showed that the proposed optimization method was effective for all breast thicknesses studied in phantoms. The best result was found for breasts of 75 mm. While in group 1 there was no detection of the 0.1 mm critical diameter detail with threshold contrast below 23%, after the optimization, detection occurred in 47.6% of the images. There was also an average MGD reduction of 7.5%. The clinical image quality criteria were attended in 91.7% for all breast thicknesses evaluated in both patient groups. Finally, this study also concluded that the use of the AEC of the x-ray unit based on the constant dose to the detector may bring some difficulties to CR systems to operate under optimal conditions. More studies must be performed, so that the compatibility between systems and optimization methodologies can be evaluated, as well as this optimization method. Most methods are developed for phantoms, so comparative studies including clinical images must be developed.

Detection of melamine in milk powder using MCT-based short-wave infrared hyperspectral imaging system.

PubMed

Lee, Hoonsoo; Kim, Moon S; Lohumi, Santosh; Cho, Byoung-Kwan

2018-06-05

Extensive research has been conducted on non-destructive and rapid detection of melamine in powdered foods in the last decade. While Raman and near-infrared hyperspectral imaging techniques have been successful in terms of non-destructive and rapid measurement, they have limitations with respect to measurement time and detection capability, respectively. Therefore, the objective of this study was to develop a mercury cadmium telluride (MCT)-based short-wave infrared (SWIR) hyperspectral imaging system and algorithm to detect melamine quantitatively in milk powder. The SWIR hyperspectral imaging system consisted of a custom-designed illumination system, a SWIR hyperspectral camera, a data acquisition module and a sample transfer table. SWIR hyperspectral images were obtained for melamine-milk samples with different melamine concentrations, pure melamine and pure milk powder. Analysis of variance and the partial least squares regression method over the 1000-2500 nm wavelength region were used to develop an optimal model for detection. The results showed that a melamine concentration as low as 50 ppm in melamine-milk powder samples could be detected. Thus, the MCT-based SWIR hyperspectral imaging system has the potential for quantitative and qualitative detection of adulterants in powder samples.

Research and Development Trend of Shape Control for Cold Rolling Strip

NASA Astrophysics Data System (ADS)

Wang, Dong-Cheng; Liu, Hong-Min; Liu, Jun

2017-09-01

Shape is an important quality index of cold rolling strip. Up to now, many problems in the shape control domain have not been solved satisfactorily, and a review on the research progress in the shape control domain can help to seek new breakthrough directions. In the past 10 years, researches and applications of shape control models, shape control means, shape detection technology, and shape control system have achieved significant progress. In the aspect of shape control models, the researches in the past improve the accuracy, speed and robustness of the models. The intelligentization of shape control models should be strengthened in the future. In the aspect of the shape control means, the researches in the past focus on the roll optimization, mill type selection, process optimization, local strip shape control, edge drop control, and so on. In the future, more attention should be paid to the coordination control of both strip shape and other quality indexes, and the refinement of control objective should be strengthened. In the aspects of shape detection technology and shape control system, some new types of shape detection meters and shape control systems are developed and have successfully industrial applications. In the future, the standardization of shape detection technology and shape control system should be promoted to solve the problem of compatibility. In general, the four expected development trends of shape control for cold rolling strip in the future are intelligentization, coordination, refinement, and standardization. The proposed research provides new breakthrough directions for improving shape quality.

Damage Detection Based on Static Strain Responses Using FBG in a Wind Turbine Blade.

PubMed

Tian, Shaohua; Yang, Zhibo; Chen, Xuefeng; Xie, Yong

2015-08-14

The damage detection of a wind turbine blade enables better operation of the turbines, and provides an early alert to the destroyed events of the blade in order to avoid catastrophic losses. A new non-baseline damage detection method based on the Fiber Bragg grating (FBG) in a wind turbine blade is developed in this paper. Firstly, the Chi-square distribution is proven to be an effective damage-sensitive feature which is adopted as the individual information source for the local decision. In order to obtain the global and optimal decision for the damage detection, the feature information fusion (FIF) method is proposed to fuse and optimize information in above individual information sources, and the damage is detected accurately through of the global decision. Then a 13.2 m wind turbine blade with the distributed strain sensor system is adopted to describe the feasibility of the proposed method, and the strain energy method (SEM) is used to describe the advantage of the proposed method. Finally results show that the proposed method can deliver encouraging results of the damage detection in the wind turbine blade.

Optimized feature-detection for on-board vision-based surveillance

NASA Astrophysics Data System (ADS)

Gond, Laetitia; Monnin, David; Schneider, Armin

2012-06-01

The detection and matching of robust features in images is an important step in many computer vision applications. In this paper, the importance of the keypoint detection algorithms and their inherent parameters in the particular context of an image-based change detection system for IED detection is studied. Through extensive application-oriented experiments, we draw an evaluation and comparison of the most popular feature detectors proposed by the computer vision community. We analyze how to automatically adjust these algorithms to changing imaging conditions and suggest improvements in order to achieve more exibility and robustness in their practical implementation.

Adaptive model-based control systems and methods for controlling a gas turbine

NASA Technical Reports Server (NTRS)

Brunell, Brent Jerome (Inventor); Mathews, Jr., Harry Kirk (Inventor); Kumar, Aditya (Inventor)

2004-01-01

Adaptive model-based control systems and methods are described so that performance and/or operability of a gas turbine in an aircraft engine, power plant, marine propulsion, or industrial application can be optimized under normal, deteriorated, faulted, failed and/or damaged operation. First, a model of each relevant system or component is created, and the model is adapted to the engine. Then, if/when deterioration, a fault, a failure or some kind of damage to an engine component or system is detected, that information is input to the model-based control as changes to the model, constraints, objective function, or other control parameters. With all the information about the engine condition, and state and directives on the control goals in terms of an objective function and constraints, the control then solves an optimization so the optimal control action can be determined and taken. This model and control may be updated in real-time to account for engine-to-engine variation, deterioration, damage, faults and/or failures using optimal corrective control action command(s).

Optimization of Multiple Pathogen Detection Using the TaqMan Array Card: Application for a Population-Based Study of Neonatal Infection

PubMed Central

Diaz, Maureen H.; Waller, Jessica L.; Napoliello, Rebecca A.; Islam, Md. Shahidul; Wolff, Bernard J.; Burken, Daniel J.; Holden, Rhiannon L.; Srinivasan, Velusamy; Arvay, Melissa; McGee, Lesley; Oberste, M. Steven; Whitney, Cynthia G.; Schrag, Stephanie J.; Winchell, Jonas M.; Saha, Samir K.

2013-01-01

Identification of etiology remains a significant challenge in the diagnosis of infectious diseases, particularly in resource-poor settings. Viral, bacterial, and fungal pathogens, as well as parasites, play a role for many syndromes, and optimizing a single diagnostic system to detect a range of pathogens is challenging. The TaqMan Array Card (TAC) is a multiple-pathogen detection method that has previously been identified as a valuable technique for determining etiology of infections and holds promise for expanded use in clinical microbiology laboratories and surveillance studies. We selected TAC for use in the Aetiology of Neonatal Infection in South Asia (ANISA) study for identifying etiologies of severe disease in neonates in Bangladesh, India, and Pakistan. Here we report optimization of TAC to improve pathogen detection and overcome technical challenges associated with use of this technology in a large-scale surveillance study. Specifically, we increased the number of assay replicates, implemented a more robust RT-qPCR enzyme formulation, and adopted a more efficient method for extraction of total nucleic acid from blood specimens. We also report the development and analytical validation of ten new assays for use in the ANISA study. Based on these data, we revised the study-specific TACs for detection of 22 pathogens in NP/OP swabs and 12 pathogens in blood specimens as well as two control reactions (internal positive control and human nucleic acid control) for each specimen type. The cumulative improvements realized through these optimization studies will benefit ANISA and perhaps other studies utilizing multiple-pathogen detection approaches. These lessons may also contribute to the expansion of TAC technology to the clinical setting. PMID:23805203

Throughput of Coded Optical CDMA Systems with AND Detectors

NASA Astrophysics Data System (ADS)

Memon, Kehkashan A.; Umrani, Fahim A.; Umrani, A. W.; Umrani, Naveed A.

2012-09-01

Conventional detection techniques used in optical code-division multiple access (OCDMA) systems are not optimal and result in poor bit error rate performance. This paper analyzes the coded performance of optical CDMA systems with AND detectors for enhanced throughput efficiencies and improved error rate performance. The results show that the use of AND detectors significantly improve the performance of an optical channel.

Optimized Vibration Chamber for Landslide Sensory and Alarm System

NASA Astrophysics Data System (ADS)

Ismail, Eliza Sabira Binti; Hadi Habaebi, Mohamed; Daoud, Jamal I.; Rafiqul Islam, Md

2017-11-01

Landslide is one of natural hazard that is not unfamiliar disaster in Malaysia. Malaysia has experienced this disaster many times since 1969. This natural hazard has become a major research concern for Malaysian government when many people were injured badly and even had been killed. Many previous research works published in the open literature aimed at designing a system that could detect landslide in early stage before the landslide becomes catastrophic. This paper presents the early works on a major work-in-progress landslide early warning system for Malaysian environment. The aim of this system is to develop the most efficiently reliable cost-effective system in which slight earth movements are monitored continuously. The challenge this work aims at is to work with a low budget system that produces efficient performance. Hence, the material used is off-the-shelf. Early design optimization results of the vibration sensor used is quite promising detecting the slightest faint tremors, which are amplified using the best vibration chamber available. It is shown that the choice of proper pipe length and diameter dimensions in combination to a gravel to exaggerate the produced higher sensitivity level noise of 5 dB.

Conditions for NIR fluorescence-guided tumor resectioning in preclinical lung cancer model (Conference Presentation)

NASA Astrophysics Data System (ADS)

Kim, Minji; Quan, Yuhua; Choi, Byeong Hyun; Choi, Yeonho; Kim, Hyun Koo; Kim, Beop-Min

2016-03-01

Pulmonary nodule could be identified by intraoperative fluorescence imaging system from systemic injection of indocyanine green (ICG) which achieves enhanced permeability and retention (EPR) effects. This study was performed to evaluate optimal injection time of ICG for detecting cancer during surgery in rabbit lung cancer model. VX2 carcinoma cell was injected in rabbit lung under fluoroscopic computed tomography-guidance. Solitary lung cancer was confirmed on positron emitting tomography with CT (PET/CT) 2 weeks after inoculation. ICG was administered intravenously and fluorescent intensity of lung tumor was measured using the custom-built intraoperative color and fluorescence merged imaging system (ICFIS) for 15 hours. Solitary lung cancer was resected through thoracoscopic version of ICFIS. ICG was observed in all animals. Because Lung has fast blood pulmonary circulation, Fluorescent signal showed maximum intensity earlier than previous studies in other organs. Fluorescent intensity showed maximum intensity within 6-9 hours in rabbit lung cancer. Overall, Fluorescent intensity decreased with increasing time, however, all tumors were detectable using fluorescent images until 12 hours. In conclusion, while there had been studies in other organs showed that optimal injection time was at least 24 hours before operation, this study showed shorter optimal injection time at lung cancer. Since fluorescent signal showed the maximum intensity within 6-9 hours, cancer resection could be performed during this time. This data informed us that optimal injection time of ICG should be evaluated in each different solid organ tumor for fluorescent image guided surgery.

Pure sources and efficient detectors for optical quantum information processing

NASA Astrophysics Data System (ADS)

Zielnicki, Kevin

Over the last sixty years, classical information theory has revolutionized the understanding of the nature of information, and how it can be quantified and manipulated. Quantum information processing extends these lessons to quantum systems, where the properties of intrinsic uncertainty and entanglement fundamentally defy classical explanation. This growing field has many potential applications, including computing, cryptography, communication, and metrology. As inherently mobile quantum particles, photons are likely to play an important role in any mature large-scale quantum information processing system. However, the available methods for producing and detecting complex multi-photon states place practical limits on the feasibility of sophisticated optical quantum information processing experiments. In a typical quantum information protocol, a source first produces an interesting or useful quantum state (or set of states), perhaps involving superposition or entanglement. Then, some manipulations are performed on this state, perhaps involving quantum logic gates which further manipulate or entangle the intial state. Finally, the state must be detected, obtaining some desired measurement result, e.g., for secure communication or computationally efficient factoring. The work presented here concerns the first and last stages of this process as they relate to photons: sources and detectors. Our work on sources is based on the need for optimized non-classical states of light delivered at high rates, particularly of single photons in a pure quantum state. We seek to better understand the properties of spontaneous parameteric downconversion (SPDC) sources of photon pairs, and in doing so, produce such an optimized source. We report an SPDC source which produces pure heralded single photons with little or no spectral filtering, allowing a significant rate enhancement. Our work on detectors is based on the need to reliably measure single-photon states. We have focused on optimizing the detection efficiency of visible light photon counters (VLPCs), a single-photon detection technology that is also capable of resolving photon number states. We report a record-breaking quantum efficiency of 91 +/- 3% observed with our detection system. Both sources and detectors are independently interesting physical systems worthy of study, but together they promise to enable entire new classes and applications of information based on quantum mechanics.

Detection of the level of fluoride in the commercially available toothpaste using laser induced breakdown spectroscopy with the marker atomic transition line of neutral fluorine at 731.1 nm

NASA Astrophysics Data System (ADS)

Gondal, M. A.; Maganda, Y. W.; Dastageer, M. A.; Al Adel, F. F.; Naqvi, A. A.; Qahtan, T. F.

2014-04-01

Fourth harmonic of a pulsed Nd:YAG laser (wavelength 266 nm) in combination with high resolution spectrograph equipped with Gated ICCD camera has been employed to design a high sensitive analytical system. This detection system is based on Laser Induced Breakdown Spectroscopy and has been tested first time for analysis of semi-fluid samples to detect fluoride content present in the commercially available toothpaste samples. The experimental parameters were optimized to achieve an optically thin and in local thermo dynamic equilibrium plasma. This improved the limits of detection of fluoride present in tooth paste samples. The strong atomic transition line of fluorine at 731.102 nm was used as the marker line to quantify the fluoride concentration levels. Our LIBS system was able to detect fluoride concentration levels in the range of 1300-1750 ppm with a detection limit of 156 ppm.

Design of optimal collimation for dedicated molecular breast imaging systems

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

Weinmann, Amanda L.; Hruska, Carrie B.; O'Connor, Michael K.

2009-03-15

Molecular breast imaging (MBI) is a functional imaging technique that uses specialized small field-of-view gamma cameras to detect the preferential uptake of a radiotracer in breast lesions. MBI has potential to be a useful adjunct method to screening mammography for the detection of occult breast cancer. However, a current limitation of MBI is the high radiation dose (a factor of 7-10 times that of screening mammography) associated with current technology. The purpose of this study was to optimize the gamma camera collimation with the aim of improving sensitivity while retaining adequate resolution for the detection of sub-10-mm lesions. Square-hole collimatorsmore » with holes matched to the pixilated cadmium zinc telluride detector elements of the MBI system were designed. Data from MBI patient studies and parameters of existing dual-head MBI systems were used to guide the range of desired collimator resolutions, source-to-collimator distances, pixel sizes, and collimator materials that were examined. General equations describing collimator performance for a conventional gamma camera were used in the design process along with several important adjustments to account for the specialized imaging geometry of the MBI system. Both theoretical calculations and a Monte Carlo model were used to measure the geometric efficiency (or sensitivity) and resolution of each designed collimator. Results showed that through optimal collimation, collimator sensitivity could be improved by factors of 1.5-3.2, while maintaining a collimator resolution of either {<=}5 or {<=}7.5 mm at a distance of 3 cm from the collimator face. These gains in collimator sensitivity permit an inversely proportional drop in the required dose to perform MBI.« less

Optimization of a Light Collection System for use in the Neutron Lifetime Project

NASA Astrophysics Data System (ADS)

Taylor, C.; O'Shaughnessy, C.; Mumm, P.; Thompson, A.; Huffman, P.

2007-10-01

The Ultracold Neutron (UCN) Lifetime Project is an ongoing experiment with the objective of improving the average measurement of the neutron beta-decay lifetime. A more accurate measurement may increase our understanding of the electroweak interaction and improve astrophysical/cosmological theories on Big Bang nucleosynthesis. The current apparatus uses 0.89 nm cold neutrons to produce UCN through inelastic collisions with superfluid 4He in the superthermal process. The lifetime of the UCN is measured by detection of scintillation light from superfluid 4He created by electrons produced in neutron decay. Competing criteria of high detection efficiency outside of the apparatus and minimum heating of the experimental cell has led to the design of an acrylic light collection system. Initial designs were based on previous generations of the apparatus. ANSYS was used to optimize the cooling system for the light guide by checking simulated end conditions based on width of contact area, number of contact points, and location on the guide itself. SolidWorks and AutoCAD were used for design. The current system is in the production process.

Signal detectability in diffusive media using phased arrays in conjunction with detector arrays.

PubMed

Kang, Dongyel; Kupinski, Matthew A

2011-06-20

We investigate Hotelling observer performance (i.e., signal detectability) of a phased array system for tasks of detecting small inhomogeneities and distinguishing adjacent abnormalities in uniform diffusive media. Unlike conventional phased array systems where a single detector is located on the interface between two sources, we consider a detector array, such as a CCD, on a phantom exit surface for calculating the Hotelling observer detectability. The signal detectability for adjacent small abnormalities (2 mm displacement) for the CCD-based phased array is related to the resolution of reconstructed images. Simulations show that acquiring high-dimensional data from a detector array in a phased array system dramatically improves the detectability for both tasks when compared to conventional single detector measurements, especially at low modulation frequencies. It is also observed in all studied cases that there exists the modulation frequency optimizing CCD-based phased array systems, where detectability for both tasks is consistently high. These results imply that the CCD-based phased array has the potential to achieve high resolution and signal detectability in tomographic diffusive imaging while operating at a very low modulation frequency. The effect of other configuration parameters, such as a detector pixel size, on the observer performance is also discussed.

Waveform design for detection of weapons based on signature exploitation

NASA Astrophysics Data System (ADS)

Ahmad, Fauzia; Amin, Moeness G.; Dogaru, Traian

2010-04-01

We present waveform design based on signature exploitation techniques for improved detection of weapons in urban sensing applications. A single-antenna monostatic radar system is considered. Under the assumption of exact knowledge of the target orientation and, hence, known impulse response, matched illumination approach is used for optimal target detection. For the case of unknown target orientation, we analyze the target signatures as random processes and perform signal-to-noise-ratio based waveform optimization. Numerical electromagnetic modeling is used to provide the impulse responses of an AK-47 assault rifle for various target aspect angles relative to the radar. Simulation results depict an improvement in the signal-to-noise-ratio at the output of the matched filter receiver for both matched illumination and stochastic waveforms as compared to a chirp waveform of the same duration and energy.

Optimal surveillance strategy for invasive species management when surveys stop after detection.

PubMed

Guillera-Arroita, Gurutzeta; Hauser, Cindy E; McCarthy, Michael A

2014-05-01

Invasive species are a cause for concern in natural and economic systems and require both monitoring and management. There is a trade-off between the amount of resources spent on surveying for the species and conducting early management of occupied sites, and the resources that are ultimately spent in delayed management at sites where the species was present but undetected. Previous work addressed this optimal resource allocation problem assuming that surveys continue despite detection until the initially planned survey effort is consumed. However, a more realistic scenario is often that surveys stop after detection (i.e., follow a "removal" sampling design) and then management begins. Such an approach will indicate a different optimal survey design and can be expected to be more efficient. We analyze this case and compare the expected efficiency of invasive species management programs under both survey methods. We also evaluate the impact of mis-specifying the type of sampling approach during the program design phase. We derive analytical expressions that optimize resource allocation between monitoring and management in surveillance programs when surveys stop after detection. We do this under a scenario of unconstrained resources and scenarios where survey budget is constrained. The efficiency of surveillance programs is greater if a "removal survey" design is used, with larger gains obtained when savings from early detection are high, occupancy is high, and survey costs are not much lower than early management costs at a site. Designing a surveillance program disregarding that surveys stop after detection can result in an efficiency loss. Our results help guide the design of future surveillance programs for invasive species. Addressing program design within a decision-theoretic framework can lead to a better use of available resources. We show how species prevalence, its detectability, and the benefits derived from early detection can be considered.

Immobilization, stabilization and patterning techniques for enzyme based sensor systems.

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

Flounders, A.W.; Carichner, S.C.; Singh, A.K.

1997-01-01

Sandia National Laboratories has recently opened the Chemical and Radiation Detection Laboratory (CRDL) in Livermore CA to address the detection needs of a variety of government agencies (e.g., Department of Energy, Environmental Protection Agency, Department of Agriculture) as well as provide a fertile environment for the cooperative development of new industrial technologies. This laboratory consolidates a variety of existing chemical and radiation detection efforts and enables Sandia to expand into the novel area of biochemically based sensors. One aspect of this biosensor effort is further development and optimization of enzyme modified field effect transistors (EnFETs). Recent work has focused uponmore » covalent attachment of enzymes to silicon dioxide and silicon nitride surfaces for EnFET fabrication. They are also investigating methods to pattern immobilized proteins; a critical component for development of array-based sensor systems. Novel enzyme stabilization procedures are key to patterning immobilized enzyme layers while maintaining enzyme activity. Results related to maximized enzyme loading, optimized enzyme activity and fluorescent imaging of patterned surfaces will be presented.« less

NEMA NU 4-Optimized Reconstructions for Therapy Assessment in Cancer Research with the Inveon Small Animal PET/CT System.

PubMed

Lasnon, Charline; Dugue, Audrey Emmanuelle; Briand, Mélanie; Blanc-Fournier, Cécile; Dutoit, Soizic; Louis, Marie-Hélène; Aide, Nicolas

2015-06-01

We compared conventional filtered back-projection (FBP), two-dimensional-ordered subsets expectation maximization (OSEM) and maximum a posteriori (MAP) NEMA NU 4-optimized reconstructions for therapy assessment. Varying reconstruction settings were used to determine the parameters for optimal image quality with two NEMA NU 4 phantom acquisitions. Subsequently, data from two experiments in which nude rats bearing subcutaneous tumors had received a dual PI3K/mTOR inhibitor were reconstructed with the NEMA NU 4-optimized parameters. Mann-Whitney tests were used to compare mean standardized uptake value (SUV(mean)) variations among groups. All NEMA NU 4-optimized reconstructions showed the same 2-deoxy-2-[(18)F]fluoro-D-glucose ([(18)F]FDG) kinetic patterns and detected a significant difference in SUV(mean) relative to day 0 between controls and treated groups for all time points with comparable p values. In the framework of therapy assessment in rats bearing subcutaneous tumors, all algorithms available on the Inveon system performed equally.

Fault Detection of Roller-Bearings Using Signal Processing and Optimization Algorithms

PubMed Central

Kwak, Dae-Ho; Lee, Dong-Han; Ahn, Jong-Hyo; Koh, Bong-Hwan

2014-01-01

This study presents a fault detection of roller bearings through signal processing and optimization techniques. After the occurrence of scratch-type defects on the inner race of bearings, variations of kurtosis values are investigated in terms of two different data processing techniques: minimum entropy deconvolution (MED), and the Teager-Kaiser Energy Operator (TKEO). MED and the TKEO are employed to qualitatively enhance the discrimination of defect-induced repeating peaks on bearing vibration data with measurement noise. Given the perspective of the execution sequence of MED and the TKEO, the study found that the kurtosis sensitivity towards a defect on bearings could be highly improved. Also, the vibration signal from both healthy and damaged bearings is decomposed into multiple intrinsic mode functions (IMFs), through empirical mode decomposition (EMD). The weight vectors of IMFs become design variables for a genetic algorithm (GA). The weights of each IMF can be optimized through the genetic algorithm, to enhance the sensitivity of kurtosis on damaged bearing signals. Experimental results show that the EMD-GA approach successfully improved the resolution of detectability between a roller bearing with defect, and an intact system. PMID:24368701

SVM classifier on chip for melanoma detection.

PubMed

Afifi, Shereen; GholamHosseini, Hamid; Sinha, Roopak

2017-07-01

Support Vector Machine (SVM) is a common classifier used for efficient classification with high accuracy. SVM shows high accuracy for classifying melanoma (skin cancer) clinical images within computer-aided diagnosis systems used by skin cancer specialists to detect melanoma early and save lives. We aim to develop a medical low-cost handheld device that runs a real-time embedded SVM-based diagnosis system for use in primary care for early detection of melanoma. In this paper, an optimized SVM classifier is implemented onto a recent FPGA platform using the latest design methodology to be embedded into the proposed device for realizing online efficient melanoma detection on a single system on chip/device. The hardware implementation results demonstrate a high classification accuracy of 97.9% and a significant acceleration factor of 26 from equivalent software implementation on an embedded processor, with 34% of resources utilization and 2 watts for power consumption. Consequently, the implemented system meets crucial embedded systems constraints of high performance and low cost, resources utilization and power consumption, while achieving high classification accuracy.

An interactive machine-learning approach for defect detection in computed tomogaraphy (CT) images of hardwood logs

Treesearch

Erol Sarigul; A. Lynn Abbott; Daniel L. Schmoldt; Philip A. Araman

2005-01-01

This paper describes recent progress in the analysis of computed tomography (CT) images of hardwood logs. The long-term goal of the work is to develop a system that is capable of autonomous (or semiautonomous) detection of internal defects, so that log breakdown decisions can be optimized based on defect locations. The problem is difficult because wood exhibits large...

The ROC Curves of Fused Independent Classification Systems

DTIC Science & Technology

2008-09-01

spectral settings arises in many fields of study; in medicine, the detection of a cancer; in marketing , the detection of the best customer base; in the...p ≤ 0.4 p/3 + 2/3, 0.4 ≤ p ≤ 1.0 fB(p) = tanh( 4p ) fC(p) = p1/3 The following plots will show how these ROC curves combine, and how the optimal

[Development of an optimal scheme for calculating results of the use of an immunoenzyme test-system for determining the antigenic activity of a cultured antirabies vaccine].

PubMed

Tsetlin, E M; Volkova, R A

1996-01-01

Ninety-eight lots of commercial antirabies vaccine manufactured by Immunopreparat Research and Production Amalgamation have been tested using enzyme immunoassay system for the detection of rabies virus antigens. Comparison of different variants of interpreting and expressing the results helped define the optimal method for assessment of vaccine titer and reference values: optical density value equal to 0.2 is taken as the cut-off. Antigenic activity of the vaccine may be expressed in international units, similarly as immunogenic activity.

Design considerations for highly effective fluorescence excitation and detection optical systems for molecular diagnostics

NASA Astrophysics Data System (ADS)

Kasper, Axel; Van Hille, Herbert; Kuk, Sola

2018-02-01

Modern instruments for molecular diagnostics are continuously optimized for diagnostic accuracy, versatility and throughput. The latest progress in LED technology together with tailored optics solutions allows developing highly efficient photonics engines perfectly adapted to the sample under test. Super-bright chip-on-board LED light sources are a key component for such instruments providing maximum luminous intensities in a multitude of narrow spectral bands. In particular the combination of white LEDs with other narrow band LEDs allows achieving optimum efficiency outperforming traditional Xenon light sources in terms of energy consumption, heat dissipation in the system, and switching time between spectral channels. Maximum sensitivity of the diagnostic system can only be achieved with an optimized optics system for the illumination and imaging of the sample. The illumination beam path must be designed for optimum homogeneity across the field while precisely limiting the angular distribution of the excitation light. This is a necessity for avoiding spill-over to the detection beam path and guaranteeing the efficiency of the spectral filtering. The imaging optics must combine high spatial resolution, high light collection efficiency and optimized suppression of excitation light for good signal-to-noise ratio. In order to achieve minimum cross-talk between individual wells in the sample, the optics design must also consider the generation of stray light and the formation of ghost images. We discuss what parameters and limitations have to be considered in an integrated system design approach covering the full path from the light source to the detector.

Vehicle Mode and Driving Activity Detection Based on Analyzing Sensor Data of Smartphones.

PubMed

Lu, Dang-Nhac; Nguyen, Duc-Nhan; Nguyen, Thi-Hau; Nguyen, Ha-Nam

2018-03-29

In this paper, we present a flexible combined system, namely the Vehicle mode-driving Activity Detection System (VADS), that is capable of detecting either the current vehicle mode or the current driving activity of travelers. Our proposed system is designed to be lightweight in computation and very fast in response to the changes of travelers' vehicle modes or driving events. The vehicle mode detection module is responsible for recognizing both motorized vehicles, such as cars, buses, and motorbikes, and non-motorized ones, for instance, walking, and bikes. It relies only on accelerometer data in order to minimize the energy consumption of smartphones. By contrast, the driving activity detection module uses the data collected from the accelerometer, gyroscope, and magnetometer of a smartphone to detect various driving activities, i.e., stopping, going straight, turning left, and turning right. Furthermore, we propose a method to compute the optimized data window size and the optimized overlapping ratio for each vehicle mode and each driving event from the training datasets. The experimental results show that this strategy significantly increases the overall prediction accuracy. Additionally, numerous experiments are carried out to compare the impact of different feature sets (time domain features, frequency domain features, Hjorth features) as well as the impact of various classification algorithms (Random Forest, Naïve Bayes, Decision tree J48, K Nearest Neighbor, Support Vector Machine) contributing to the prediction accuracy. Our system achieves an average accuracy of 98.33% in detecting the vehicle modes and an average accuracy of 98.95% in recognizing the driving events of motorcyclists when using the Random Forest classifier and a feature set containing time domain features, frequency domain features, and Hjorth features. Moreover, on a public dataset of HTC company in New Taipei, Taiwan, our framework obtains the overall accuracy of 97.33% that is considerably higher than that of the state-of the art.

A bio-inspired structural health monitoring system based on ambient vibration

NASA Astrophysics Data System (ADS)

Lin, Tzu-Kang; Kiremidjian, Anne; Lei, Chi-Yang

2010-11-01

A structural health monitoring (SHM) system based on naïve Bayesian (NB) damage classification and DNA-like expression data was developed in this research. Adapted from the deoxyribonucleic acid (DNA) array concept in molecular biology, the proposed structural health monitoring system is constructed utilizing a double-tier regression process to extract the expression array from the structural time history recorded during external excitations. The extracted array is symbolized as the various genes of the structure from the viewpoint of molecular biology and reflects the possible damage conditions prevalent in the structure. A scaled down, six-story steel building mounted on the shaking table of the National Center for Research on Earthquake Engineering (NCREE) was used as the benchmark. The structural response at different damage levels and locations under ambient vibration was collected to support the database for the proposed SHM system. To improve the precision of detection in practical applications, the system was enhanced by an optimization process using the likelihood selection method. The obtained array representing the DNA array of the health condition of the structure was first evaluated and ranked. A total of 12 groups of expression arrays were regenerated from a combination of four damage conditions. To keep the length of the array unchanged, the best 16 coefficients from every expression array were selected to form the optimized SHM system. Test results from the ambient vibrations showed that the detection accuracy of the structural damage could be greatly enhanced by the optimized expression array, when compared to the original system. Practical verification also demonstrated that a rapid and reliable result could be given by the final system within 1 min. The proposed system implements the idea of transplanting the DNA array concept from molecular biology into the field of SHM.

Study on UKF based federal integrated navigation for high dynamic aviation

NASA Astrophysics Data System (ADS)

Zhao, Gang; Shao, Wei; Chen, Kai; Yan, Jie

2011-08-01

High dynamic aircraft is a very attractive new generation vehicles, in which provides near space aviation with large flight envelope both speed and altitude, for example the hypersonic vehicles. The complex flight environments for high dynamic vehicles require high accuracy and stability navigation scheme. Since the conventional Strapdown Inertial Navigation System (SINS) and Global Position System (GPS) federal integrated scheme based on EKF (Extended Kalman Filter) is invalidation in GPS single blackout situation because of high speed flight, a new high precision and stability integrated navigation approach is presented in this paper, in which the SINS, GPS and Celestial Navigation System (CNS) is combined as a federal information fusion configuration based on nonlinear Unscented Kalman Filter (UKF) algorithm. Firstly, the new integrated system state error is modeled. According to this error model, the SINS system is used as the navigation solution mathematic platform. The SINS combine with GPS constitute one error estimation filter subsystem based on UKF to obtain local optimal estimation, and the SINS combine with CNS constitute another error estimation subsystem. A non-reset federated configuration filter based on partial information is proposed to fuse two local optimal estimations to get global optimal error estimation, and the global optimal estimation is used to correct the SINS navigation solution. The χ 2 fault detection method is used to detect the subsystem fault, and the fault subsystem is isolation through fault interval to protect system away from the divergence. The integrated system takes advantages of SINS, GPS and CNS to an immense improvement for high accuracy and reliably high dynamic navigation application. Simulation result shows that federated fusion of using GPS and CNS to revise SINS solution is reasonable and availably with good estimation performance, which are satisfied with the demands of high dynamic flight navigation. The UKF is superior than EKF based integrated scheme, in which has smaller estimation error and quickly convergence rate.

Cascaded systems analysis of noise and detectability in dual-energy cone-beam CT

PubMed Central

Gang, Grace J.; Zbijewski, Wojciech; Webster Stayman, J.; Siewerdsen, Jeffrey H.

2012-01-01

Purpose: Dual-energy computed tomography and dual-energy cone-beam computed tomography (DE-CBCT) are promising modalities for applications ranging from vascular to breast, renal, hepatic, and musculoskeletal imaging. Accordingly, the optimization of imaging techniques for such applications would benefit significantly from a general theoretical description of image quality that properly incorporates factors of acquisition, reconstruction, and tissue decomposition in DE tomography. This work reports a cascaded systems analysis model that includes the Poisson statistics of x rays (quantum noise), detector model (flat-panel detectors), anatomical background, image reconstruction (filtered backprojection), DE decomposition (weighted subtraction), and simple observer models to yield a task-based framework for DE technique optimization. Methods: The theoretical framework extends previous modeling of DE projection radiography and CBCT. Signal and noise transfer characteristics are propagated through physical and mathematical stages of image formation and reconstruction. Dual-energy decomposition was modeled according to weighted subtraction of low- and high-energy images to yield the 3D DE noise-power spectrum (NPS) and noise-equivalent quanta (NEQ), which, in combination with observer models and the imaging task, yields the dual-energy detectability index (d′). Model calculations were validated with NPS and NEQ measurements from an experimental imaging bench simulating the geometry of a dedicated musculoskeletal extremities scanner. Imaging techniques, including kVp pair and dose allocation, were optimized using d′ as an objective function for three example imaging tasks: (1) kidney stone discrimination; (2) iodine vs bone in a uniform, soft-tissue background; and (3) soft tissue tumor detection on power-law anatomical background. Results: Theoretical calculations of DE NPS and NEQ demonstrated good agreement with experimental measurements over a broad range of imaging conditions. Optimization results suggest a lower fraction of total dose imparted by the low-energy acquisition, a finding consistent with previous literature. The selection of optimal kVp pair reveals the combined effect of both quantum noise and contrast in the kidney stone discrimination and soft-tissue tumor detection tasks, whereas the K-edge effect of iodine was the dominant factor in determining kVp pairs in the iodine vs bone task. The soft-tissue tumor task illustrated the benefit of dual-energy imaging in eliminating anatomical background noise and improving detectability beyond that achievable by single-energy scans. Conclusions: This work established a task-based theoretical framework that is predictive of DE image quality. The model can be utilized in optimizing a broad range of parameters in image acquisition, reconstruction, and decomposition, providing a useful tool for maximizing DE-CBCT image quality and reducing dose. PMID:22894440

Tire-road friction estimation and traction control strategy for motorized electric vehicle.

PubMed

Jin, Li-Qiang; Ling, Mingze; Yue, Weiqiang

2017-01-01

In this paper, an optimal longitudinal slip ratio system for real-time identification of electric vehicle (EV) with motored wheels is proposed based on the adhesion between tire and road surface. First and foremost, the optimal longitudinal slip rate torque control can be identified in real time by calculating the derivative and slip rate of the adhesion coefficient. Secondly, the vehicle speed estimation method is also brought. Thirdly, an ideal vehicle simulation model is proposed to verify the algorithm with simulation, and we find that the slip ratio corresponds to the detection of the adhesion limit in real time. Finally, the proposed strategy is applied to traction control system (TCS). The results showed that the method can effectively identify the state of wheel and calculate the optimal slip ratio without wheel speed sensor; in the meantime, it can improve the accelerated stability of electric vehicle with traction control system (TCS).

Tire-road friction estimation and traction control strategy for motorized electric vehicle

PubMed Central

Jin, Li-Qiang; Yue, Weiqiang

2017-01-01

In this paper, an optimal longitudinal slip ratio system for real-time identification of electric vehicle (EV) with motored wheels is proposed based on the adhesion between tire and road surface. First and foremost, the optimal longitudinal slip rate torque control can be identified in real time by calculating the derivative and slip rate of the adhesion coefficient. Secondly, the vehicle speed estimation method is also brought. Thirdly, an ideal vehicle simulation model is proposed to verify the algorithm with simulation, and we find that the slip ratio corresponds to the detection of the adhesion limit in real time. Finally, the proposed strategy is applied to traction control system (TCS). The results showed that the method can effectively identify the state of wheel and calculate the optimal slip ratio without wheel speed sensor; in the meantime, it can improve the accelerated stability of electric vehicle with traction control system (TCS). PMID:28662053

Dual fluorescence/contactless conductivity detection for microfluidic chip.

PubMed

Liu, Cui; Mo, Yun-yan; Chen, Zuan-guang; Li, Xiang; Li, Ou-lian; Zhou, Xie

2008-07-28

A new dual detection system for microchip is reported. Both fluorescence detector (FD) and contactless conductivity detector (CCD) were combined together and integrated on a microfluidic chip. They shared a common detection position and responded simultaneously. A blue light-emitting diode was used as excitation source and a small planar photodiode was used to collect the emitted fluorescence in fluorescence detection, which made the device more compact and portable. The coupling of the fluorescence and contactless conductivity modes at the same position of a single separation channel enhanced the detection characterization of sample and offered simultaneous detection information of both fluorescent and charged specimen. The detection conditions of the system were optimized. K(+), Na(+), fluorescein sodium, fluorescein isothiocyanate (FITC) and FITC-labeled amino acids were used to evaluate the performance of the dual detection system. The limits of detection (LOD) of FD for fluorescein Na(+), FITC, FITC-labeled arginine (Arg), glycine (Gly) and phenylalanine (Phe) were 0.02micromolL(-1), 0.05micromolL(-1), 0.16micromolL(-1), 0.15micromolL(-1), 0.12micromolL(-1) respectively, and the limits of detection (LOD) of CCD achieved 0.58micromolL(-1) and 0.39micromolL(-1) for K(+) and Na(+) respectively.

Detection of plum pox potyviral protein-protein interactions in planta using an optimized mRFP-based bimolecular fluorescence complementation system.

PubMed

Zilian, Eva; Maiss, Edgar

2011-12-01

In previous studies, protein interaction maps of different potyviruses have been generated using yeast two-hybrid (YTH) systems, and these maps have demonstrated a high diversity of interactions of potyviral proteins. Using an optimized bimolecular fluorescence complementation (BiFC) system, a complete interaction matrix for proteins of a potyvirus was developed for the first time under in planta conditions with ten proteins from plum pox virus (PPV). In total, 52 of 100 possible interactions were detected, including the self-interactions of CI, 6K2, VPg, NIa-Pro, NIb and CP, which is more interactions than have ever been detected for any other potyvirus in a YTH approach. Moreover, the BiFC system was shown to be able to localize the protein interactions, which was typified for the protein self-interactions indicated above. Additionally, experiments were carried out with the P3N-PIPO protein, revealing an interaction with CI but not with CP and supporting the involvement of P3N-PIPO in the cell-to-cell movement of potyviruses. No self-interaction of the PPV helper component-proteinase (HC-Pro) was detected using BiFC in planta. Therefore, additional experiments with turnip mosaic virus (TuMV) HC-Pro, PPV_HC-Pro and their mutants were conducted. The self-interaction of TuMV_HCpro, as recently demonstrated, and the self-interaction of the TuMV_ and PPV_HC-Pro mutants were shown by BiFC in planta, indicating that HC-Pro self-interactions may be species-specific. BiFC is a very useful and reliable method for the detection and localization of protein interactions in planta, thus enabling investigations under more natural conditions than studies in yeast cells.

Optimal Stimulus Amplitude for Vestibular Stochastic Stimulation to Improve Sensorimotor Function

NASA Technical Reports Server (NTRS)

Goel, R.; Kofman, I.; DeDios, Y. E.; Jeevarajan, J.; Stepanyan, V.; Nair, M.; Congdon, S.; Fregia, M.; Cohen, H.; Bloomberg, J. J.;

Wavelet Fusion for Concealed Object Detection Using Passive Millimeter Wave Sequence Images

NASA Astrophysics Data System (ADS)

Chen, Y.; Pang, L.; Liu, H.; Xu, X.

2018-04-01

PMMW imaging system can create interpretable imagery on the objects concealed under clothing, which gives the great advantage to the security check system. Paper addresses wavelet fusion to detect concealed objects using passive millimeter wave (PMMW) sequence images. According to PMMW real-time imager acquired image characteristics and storage methods firstly, using the sum of squared difference (SSD) as the image-related parameters to screen the sequence images. Secondly, the selected images are optimized using wavelet fusion algorithm. Finally, the concealed objects are detected by mean filter, threshold segmentation and edge detection. The experimental results show that this method improves the detection effect of concealed objects by selecting the most relevant images from PMMW sequence images and using wavelet fusion to enhance the information of the concealed objects. The method can be effectively applied to human body concealed object detection in millimeter wave video.

A framework for optimizing micro-CT in dual-modality micro-CT/XFCT small-animal imaging system

NASA Astrophysics Data System (ADS)

Vedantham, Srinivasan; Shrestha, Suman; Karellas, Andrew; Cho, Sang Hyun

2017-09-01

Dual-modality Computed Tomography (CT)/X-ray Fluorescence Computed Tomography (XFCT) can be a valuable tool for imaging and quantifying the organ and tissue distribution of small concentrations of high atomic number materials in small-animal system. In this work, the framework for optimizing the micro-CT imaging system component of the dual-modality system is described, either when the micro-CT images are concurrently acquired with XFCT and using the x-ray spectral conditions for XFCT, or when the micro-CT images are acquired sequentially and independently of XFCT. This framework utilizes the cascaded systems analysis for task-specific determination of the detectability index using numerical observer models at a given radiation dose, where the radiation dose is determined using Monte Carlo simulations.

Modeling the Performance of Direct-Detection Doppler Lidar Systems in Real Atmospheres

NASA Technical Reports Server (NTRS)

McGill, Matthew J.; Hart, William D.; McKay, Jack A.; Spinhirne, James D.

1999-01-01

Previous modeling of the performance of spaceborne direct-detection Doppler lidar systems has assumed extremely idealized atmospheric models. Here we develop a technique for modeling the performance of these systems in a more realistic atmosphere, based on actual airborne lidar observations. The resulting atmospheric model contains cloud and aerosol variability that is absent in other simulations of spaceborne Doppler lidar instruments. To produce a realistic simulation of daytime performance, we include solar radiance values that are based on actual measurements and are allowed to vary as the viewing scene changes. Simulations are performed for two types of direct-detection Doppler lidar systems: the double-edge and the multi-channel techniques. Both systems were optimized to measure winds from Rayleigh backscatter at 355 nm. Simulations show that the measurement uncertainty during daytime is degraded by only about 10-20% compared to nighttime performance, provided a proper solar filter is included in the instrument design.

Design and analysis of x-ray vision systems for high-speed detection of foreign body contamination in food

NASA Astrophysics Data System (ADS)

Graves, Mark; Smith, Alexander; Batchelor, Bruce G.; Palmer, Stephen C.

1994-10-01

In the food industry there is an ever increasing need to control and monitor food quality. In recent years fully automated x-ray inspection systems have been used to detect food on-line for foreign body contamination. These systems involve a complex integration of x- ray imaging components with state of the art high speed image processing. The quality of the x-ray image obtained by such systems is very poor compared with images obtained from other inspection processes, this makes reliable detection of very small, low contrast defects extremely difficult. It is therefore extremely important to optimize the x-ray imaging components to give the very best image possible. In this paper we present a method of analyzing the x-ray imaging system in order to consider the contrast obtained when viewing small defects.

Modeling the performance of direct-detection Doppler lidar systems including cloud and solar background variability.

PubMed

McGill, M J; Hart, W D; McKay, J A; Spinhirne, J D

1999-10-20

Previous modeling of the performance of spaceborne direct-detection Doppler lidar systems assumed extremely idealized atmospheric models. Here we develop a technique for modeling the performance of these systems in a more realistic atmosphere, based on actual airborne lidar observations. The resulting atmospheric model contains cloud and aerosol variability that is absent in other simulations of spaceborne Doppler lidar instruments. To produce a realistic simulation of daytime performance, we include solar radiance values that are based on actual measurements and are allowed to vary as the viewing scene changes. Simulations are performed for two types of direct-detection Doppler lidar system: the double-edge and the multichannel techniques. Both systems were optimized to measure winds from Rayleigh backscatter at 355 nm. Simulations show that the measurement uncertainty during daytime is degraded by only approximately 10-20% compared with nighttime performance, provided that a proper solar filter is included in the instrument design.

Smart detection of microRNAs through fluorescence enhancement on a photonic crystal.

PubMed

Pasquardini, L; Potrich, C; Vaghi, V; Lunelli, L; Frascella, F; Descrovi, E; Pirri, C F; Pederzolli, C

2016-04-01

The detection of low abundant biomarkers, such as circulating microRNAs, demands innovative detection methods with increased resolution, sensitivity and specificity. Here, a biofunctional surface was implemented for the selective capture of microRNAs, which were detected through fluorescence enhancement directly on a photonic crystal. To set up the optimal biofunctional surface, epoxy-coated commercially available microscope slides were spotted with specific anti-microRNA probes. The optimal concentration of probe as well as of passivating agent were selected and employed for titrating the microRNA hybridization. Cross-hybridization of different microRNAs was also tested, resulting negligible. Once optimized, the protocol was adapted to the photonic crystal surface, where fluorescent synthetic miR-16 was hybridized and imaged with a dedicated equipment. The photonic crystal consists of a dielectric multilayer patterned with a grating structure. In this way, it is possible to take advantage from both a resonant excitation of fluorophores and an angularly redirection of the emitted radiation. As a result, a significant fluorescence enhancement due to the resonant structure is collected from the patterned photonic crystal with respect to the outer non-structured surface. The dedicated read-out system is compact and based on a wide-field imaging detection, with little or no optical alignment issues, which makes this approach particularly interesting for further development such as for example in microarray-type bioassays. Copyright © 2016 Elsevier B.V. All rights reserved.

Feasibility Study of a Generalized Framework for Developing Computer-Aided Detection Systems-a New Paradigm.

PubMed

Nemoto, Mitsutaka; Hayashi, Naoto; Hanaoka, Shouhei; Nomura, Yukihiro; Miki, Soichiro; Yoshikawa, Takeharu

2017-10-01

We propose a generalized framework for developing computer-aided detection (CADe) systems whose characteristics depend only on those of the training dataset. The purpose of this study is to show the feasibility of the framework. Two different CADe systems were experimentally developed by a prototype of the framework, but with different training datasets. The CADe systems include four components; preprocessing, candidate area extraction, candidate detection, and candidate classification. Four pretrained algorithms with dedicated optimization/setting methods corresponding to the respective components were prepared in advance. The pretrained algorithms were sequentially trained in the order of processing of the components. In this study, two different datasets, brain MRA with cerebral aneurysms and chest CT with lung nodules, were collected to develop two different types of CADe systems in the framework. The performances of the developed CADe systems were evaluated by threefold cross-validation. The CADe systems for detecting cerebral aneurysms in brain MRAs and for detecting lung nodules in chest CTs were successfully developed using the respective datasets. The framework was shown to be feasible by the successful development of the two different types of CADe systems. The feasibility of this framework shows promise for a new paradigm in the development of CADe systems: development of CADe systems without any lesion specific algorithm designing.

Coherent receiver design based on digital signal processing in optical high-speed intersatellite links with M-phase-shift keying

NASA Astrophysics Data System (ADS)

Schaefer, Semjon; Gregory, Mark; Rosenkranz, Werner

2016-11-01

We present simulative and experimental investigations of different coherent receiver designs for high-speed optical intersatellite links. We focus on frequency offset (FO) compensation in homodyne and intradyne detection systems. The considered laser communication terminal uses an optical phase-locked loop (OPLL), which ensures stable homodyne detection. However, the hardware complexity increases with the modulation order. Therefore, we show that software-based intradyne detection is an attractive alternative for OPLL-based homodyne systems. Our approach is based on digital FO and phase noise compensation, in order to achieve a more flexible coherent detection scheme. Analytic results will further show the theoretical impact of the different detection schemes on the receiver sensitivity. Finally, we compare the schemes in terms of bit error ratio measurements and optimal receiver design.

Adaptive waveform optimization design for target detection in cognitive radar

NASA Astrophysics Data System (ADS)

Zhang, Xiaowen; Wang, Kaizhi; Liu, Xingzhao

2017-01-01

The problem of adaptive waveform design for target detection in cognitive radar (CR) is investigated. This problem is analyzed in signal-dependent interference, as well as additive channel noise for extended target with unknown target impulse response (TIR). In order to estimate the TIR accurately, the Kalman filter is used in target tracking. In each Kalman filtering iteration, a flexible online waveform spectrum optimization design taking both detection and range resolution into account is modeled in Fourier domain. Unlike existing CR waveform, the proposed waveform can be simultaneously updated according to the environment information fed back by receiver and radar performance demands. Moreover, the influence of waveform spectral phase to radar performance is analyzed. Simulation results demonstrate that CR with the proposed waveform performs better than a traditional radar system with a fixed waveform and offers more flexibility and suitability. In addition, waveform spectral phase will not influence tracking, detection, and range resolution performance but will greatly influence waveform forming speed and peak-to-average power ratio.

A Hybrid Swarm Intelligence Algorithm for Intrusion Detection Using Significant Features.

PubMed

Amudha, P; Karthik, S; Sivakumari, S

2015-01-01

Intrusion detection has become a main part of network security due to the huge number of attacks which affects the computers. This is due to the extensive growth of internet connectivity and accessibility to information systems worldwide. To deal with this problem, in this paper a hybrid algorithm is proposed to integrate Modified Artificial Bee Colony (MABC) with Enhanced Particle Swarm Optimization (EPSO) to predict the intrusion detection problem. The algorithms are combined together to find out better optimization results and the classification accuracies are obtained by 10-fold cross-validation method. The purpose of this paper is to select the most relevant features that can represent the pattern of the network traffic and test its effect on the success of the proposed hybrid classification algorithm. To investigate the performance of the proposed method, intrusion detection KDDCup'99 benchmark dataset from the UCI Machine Learning repository is used. The performance of the proposed method is compared with the other machine learning algorithms and found to be significantly different.

A Hybrid Swarm Intelligence Algorithm for Intrusion Detection Using Significant Features

PubMed Central

Amudha, P.; Karthik, S.; Sivakumari, S.

2015-01-01

Intrusion detection has become a main part of network security due to the huge number of attacks which affects the computers. This is due to the extensive growth of internet connectivity and accessibility to information systems worldwide. To deal with this problem, in this paper a hybrid algorithm is proposed to integrate Modified Artificial Bee Colony (MABC) with Enhanced Particle Swarm Optimization (EPSO) to predict the intrusion detection problem. The algorithms are combined together to find out better optimization results and the classification accuracies are obtained by 10-fold cross-validation method. The purpose of this paper is to select the most relevant features that can represent the pattern of the network traffic and test its effect on the success of the proposed hybrid classification algorithm. To investigate the performance of the proposed method, intrusion detection KDDCup'99 benchmark dataset from the UCI Machine Learning repository is used. The performance of the proposed method is compared with the other machine learning algorithms and found to be significantly different. PMID:26221625

TwitterSensing: An Event-Based Approach for Wireless Sensor Networks Optimization Exploiting Social Media in Smart City Applications

PubMed Central

2018-01-01

Modern cities are subject to periodic or unexpected critical events, which may bring economic losses or even put people in danger. When some monitoring systems based on wireless sensor networks are deployed, sensing and transmission configurations of sensor nodes may be adjusted exploiting the relevance of the considered events, but efficient detection and classification of events of interest may be hard to achieve. In Smart City environments, several people spontaneously post information in social media about some event that is being observed and such information may be mined and processed for detection and classification of critical events. This article proposes an integrated approach to detect and classify events of interest posted in social media, notably in Twitter, and the assignment of sensing priorities to source nodes. By doing so, wireless sensor networks deployed in Smart City scenarios can be optimized for higher efficiency when monitoring areas under the influence of the detected events. PMID:29614060

TwitterSensing: An Event-Based Approach for Wireless Sensor Networks Optimization Exploiting Social Media in Smart City Applications.

PubMed

Costa, Daniel G; Duran-Faundez, Cristian; Andrade, Daniel C; Rocha-Junior, João B; Peixoto, João Paulo Just

2018-04-03

Modern cities are subject to periodic or unexpected critical events, which may bring economic losses or even put people in danger. When some monitoring systems based on wireless sensor networks are deployed, sensing and transmission configurations of sensor nodes may be adjusted exploiting the relevance of the considered events, but efficient detection and classification of events of interest may be hard to achieve. In Smart City environments, several people spontaneously post information in social media about some event that is being observed and such information may be mined and processed for detection and classification of critical events. This article proposes an integrated approach to detect and classify events of interest posted in social media, notably in Twitter , and the assignment of sensing priorities to source nodes. By doing so, wireless sensor networks deployed in Smart City scenarios can be optimized for higher efficiency when monitoring areas under the influence of the detected events.

Distributed gas sensing with optical fibre photothermal interferometry.

PubMed

Lin, Yuechuan; Liu, Fei; He, Xiangge; Jin, Wei; Zhang, Min; Yang, Fan; Ho, Hoi Lut; Tan, Yanzhen; Gu, Lijuan

2017-12-11

We report the first distributed optical fibre trace-gas detection system based on photothermal interferometry (PTI) in a hollow-core photonic bandgap fibre (HC-PBF). Absorption of a modulated pump propagating in the gas-filled HC-PBF generates distributed phase modulation along the fibre, which is detected by a dual-pulse heterodyne phase-sensitive optical time-domain reflectometry (OTDR) system. Quasi-distributed sensing experiment with two 28-meter-long HC-PBF sensing sections connected by single-mode transmission fibres demonstrated a limit of detection (LOD) of ∼10 ppb acetylene with a pump power level of 55 mW and an effective noise bandwidth (ENBW) of 0.01 Hz, corresponding to a normalized detection limit of 5.5ppb⋅W/Hz. Distributed sensing experiment over a 200-meter-long sensing cable made of serially connected HC-PBFs demonstrated a LOD of ∼ 5 ppm with 62.5 mW peak pump power and 11.8 Hz ENBW, or a normalized detection limit of 312ppb⋅W/Hz. The spatial resolution of the current distributed detection system is limited to ∼ 30 m, but it is possible to reduce down to 1 meter or smaller by optimizing the phase detection system.

Monte Carlo simulation of explosive detection system based on a Deuterium-Deuterium (D-D) neutron generator.

PubMed

Bergaoui, K; Reguigui, N; Gary, C K; Brown, C; Cremer, J T; Vainionpaa, J H; Piestrup, M A

2014-12-01

An explosive detection system based on a Deuterium-Deuterium (D-D) neutron generator has been simulated using the Monte Carlo N-Particle Transport Code (MCNP5). Nuclear-based explosive detection methods can detect explosives by identifying their elemental components, especially nitrogen. Thermal neutron capture reactions have been used for detecting prompt gamma emission (10.82MeV) following radiative neutron capture by (14)N nuclei. The explosive detection system was built based on a fully high-voltage-shielded, axial D-D neutron generator with a radio frequency (RF) driven ion source and nominal yield of about 10(10) fast neutrons per second (E=2.5MeV). Polyethylene and paraffin were used as moderators with borated polyethylene and lead as neutron and gamma ray shielding, respectively. The shape and the thickness of the moderators and shields are optimized to produce the highest thermal neutron flux at the position of the explosive and the minimum total dose at the outer surfaces of the explosive detection system walls. In addition, simulation of the response functions of NaI, BGO, and LaBr3-based γ-ray detectors to different explosives is described. Copyright © 2014 Elsevier Ltd. All rights reserved.

Use of diaminofluoresceins to detect and measure nitric oxide in low level generating human immune cells.

PubMed

Tiscornia, Adriana; Cairoli, Ernesto; Marquez, Maria; Denicola, Ana; Pritsch, Otto; Cayota, Alfonso

2009-03-15

Nitric oxide ((*)NO) has been implicated in multiple physiological and pathological immune processes. Different methods have been developed to detect and quantify (*)NO, where one of the principal difficulties are the accurately detection in cellular system with low levels of (*)NO production. The choice of the (*)NO detection method to be used depends on the characteristics of the experimental system and the levels of (*)NO production which depend on either the organism source of samples or the experimental conditions. Recently, high sensitive methods to detect and image (*)NO have been reported using 4,5-diaminofluorescein-based fluorescent probes (DAF) and its derivate 4,5-diaminofluorescein diacetate (DAF-2 DA). This work was aimed to adapt and optimize the use of DAF probes to detect and quantify the (*)NO production in systems of high, moderate and low out-put production, especially in human PBMC and their subpopulations. Here, we report an original experimental design which is useful to detect and estimate (*)NO fluxes in human PBMC and their subpopulations with high specificity and sensitivity.

Tunable sensitivity phase detection of transmitted-type dual-channel guided-mode resonance sensor based on phase-shift interferometry.

PubMed

Kuo, Wen-Kai; Syu, Siang-He; Lin, Peng-Zhi; Yu, Hsin Her

2016-02-01

This paper reports on a transmitted-type dual-channel guided-mode resonance (GMR) sensor system that uses phase-shifting interferometry (PSI) to achieve tunable phase detection sensitivity. Five interference images are captured for the PSI phase calculation within ∼15  s by using a liquid crystal retarder and a USB web camera. The GMR sensor structure is formed by a nanoimprinting process, and the dual-channel sensor device structure for molding is fabricated using a 3D printer. By changing the rotation angle of the analyzer in front of the camera in the PSI system, the sensor detection sensitivity can be tuned. The proposed system may achieve high throughput as well as high sensitivity. The experimental results show that an optimal detection sensitivity of 6.82×10(-4)  RIU can be achieved.

Efficient surveillance for healthcare-associated infections spreading between hospitals

PubMed Central

Ciccolini, Mariano; Donker, Tjibbe; Grundmann, Hajo; Bonten, Marc J. M.; Woolhouse, Mark E. J.

2014-01-01

Early detection of new or novel variants of nosocomial pathogens is a public health priority. We show that, for healthcare-associated infections that spread between hospitals as a result of patient movements, it is possible to design an effective surveillance system based on a relatively small number of sentinel hospitals. We apply recently developed mathematical models to patient admission data from the national healthcare systems of England and The Netherlands. Relatively short detection times are achieved once 10–20% hospitals are recruited as sentinels and only modest reductions are seen as more hospitals are recruited thereafter. Using a heuristic optimization approach to sentinel selection, the same expected time to detection can be achieved by recruiting approximately half as many hospitals. Our study provides a robust evidence base to underpin the design of an efficient sentinel hospital surveillance system for novel nosocomial pathogens, delivering early detection times for reduced expenditure and effort. PMID:24469791

Accelerated wavefront determination technique for optical imaging through scattering medium

NASA Astrophysics Data System (ADS)

He, Hexiang; Wong, Kam Sing

2016-03-01

Wavefront shaping applied on scattering light is a promising optical imaging method in biological systems. Normally, optimized modulation can be obtained by a Liquid-Crystal Spatial Light Modulator (LC-SLM) and CCD hardware iteration. Here we introduce an improved method for this optimization process. The core of the proposed method is to firstly detect the disturbed wavefront, and then to calculate the modulation phase pattern by computer simulation. In particular, phase retrieval method together with phase conjugation is most effective. In this way, the LC-SLM based system can complete the wavefront optimization and imaging restoration within several seconds which is two orders of magnitude faster than the conventional technique. The experimental results show good imaging quality and may contribute to real time imaging recovery in scattering medium.

Design of polarization imaging system based on CIS and FPGA

NASA Astrophysics Data System (ADS)

Zeng, Yan-an; Liu, Li-gang; Yang, Kun-tao; Chang, Da-ding

2008-02-01

As polarization is an important characteristic of light, polarization image detecting is a new image detecting technology of combining polarimetric and image processing technology. Contrasting traditional image detecting in ray radiation, polarization image detecting could acquire a lot of very important information which traditional image detecting couldn't. Polarization image detecting will be widely used in civilian field and military field. As polarization image detecting could resolve some problem which couldn't be resolved by traditional image detecting, it has been researched widely around the world. The paper introduces polarization image detecting in physical theory at first, then especially introduces image collecting and polarization image process based on CIS (CMOS image sensor) and FPGA. There are two parts including hardware and software for polarization imaging system. The part of hardware include drive module of CMOS image sensor, VGA display module, SRAM access module and the real-time image data collecting system based on FPGA. The circuit diagram and PCB was designed. Stokes vector and polarization angle computing method are analyzed in the part of software. The float multiply of Stokes vector is optimized into just shift and addition operation. The result of the experiment shows that real time image collecting system could collect and display image data from CMOS image sensor in real-time.

Direct and sensitive detection of foodborne pathogens within fresh produce samples using a field-deployable handheld device.

PubMed

You, David J; Geshell, Kenneth J; Yoon, Jeong-Yeol

2011-10-15

Direct and sensitive detection of foodborne pathogens from fresh produce samples was accomplished using a handheld lab-on-a-chip device, requiring little to no sample processing and enrichment steps for a near-real-time detection and truly field-deployable device. The detection of Escherichia coli K12 and O157:H7 in iceberg lettuce was achieved utilizing optimized Mie light scatter parameters with a latex particle immunoagglutination assay. The system exhibited good sensitivity, with a limit of detection of 10 CFU mL(-1) and an assay time of <6 min. Minimal pretreatment with no detrimental effects on assay sensitivity and reproducibility was accomplished with a simple and cost-effective KimWipes filter and disposable syringe. Mie simulations were used to determine the optimal parameters (particle size d, wavelength λ, and scatter angle θ) for the assay that maximize light scatter intensity of agglutinated latex microparticles and minimize light scatter intensity of the tissue fragments of iceberg lettuce, which were experimentally validated. This introduces a powerful method for detecting foodborne pathogens in fresh produce and other potential sample matrices. The integration of a multi-channel microfluidic chip allowed for differential detection of the agglutinated particles in the presence of the antigen, revealing a true field-deployable detection system with decreased assay time and improved robustness over comparable benchtop systems. Additionally, two sample preparation methods were evaluated through simulated field studies based on overall sensitivity, protocol complexity, and assay time. Preparation of the plant tissue sample by grinding resulted in a two-fold improvement in scatter intensity over washing, accompanied with a significant increase in assay time: ∼5 min (grinding) versus ∼1 min (washing). Specificity studies demonstrated binding of E. coli O157:H7 EDL933 to only O157:H7 antibody conjugated particles, with no cross-reactivity to K12. This suggests the adaptability of the system for use with a wide variety of pathogens, and the potential to detect in a variety of biological matrices with little to no sample pretreatment. Copyright © 2011 Elsevier B.V. All rights reserved.

DART-MS analysis of inorganic explosives using high temperature thermal desorption†‡

PubMed Central

Sisco, Edward; Staymates, Matthew; Gillen, Greg

2018-01-01

An ambient mass spectrometry (MS) platform coupling resistive Joule heating thermal desorption (JHTD) and direct analysis in real time (DART) was implemented for the analysis of inorganic nitrite, nitrate, chlorate, and perchlorate salts. The resistive heating component generated discrete and rapid heating ramps and elevated temperatures, up to approximately 400 °C s−1 and 750 °C, by passing a few amperes of DC current through a nichrome wire. JHTD enhanced the utility and capabilities of traditional DART-MS for the trace detection of previously difficult to detect inorganic compounds. A partial factorial design of experiments (DOE) was implemented for the systematic evaluation of five system parameters. A base set of conditions for JHTD-DART-MS was derived from this evaluation, demonstrating sensitive detection of a range of inorganic oxidizer salts, down to single nanogram levels. DOE also identified JHTD filament current and in-source collision induced dissociation (CID) energy as inducing the greatest effect on system response. Tuning of JHTD current provided a method for controlling the relative degrees of thermal desorption and thermal decomposition. Furthermore, in-source CID provided manipulation of adduct and cluster fragmentation, optimizing the detection of molecular anion species. Finally, the differential thermal desorption nature of the JHTD-DART platform demonstrated efficient desorption and detection of organic and inorganic explosive mixtures, with each desorbing at its respective optimal temperature. PMID:29651308

Optimization of loop-mediated isothermal amplification (LAMP) assays for the detection of Leishmania DNA in human blood samples.

PubMed

Abbasi, Ibrahim; Kirstein, Oscar D; Hailu, Asrat; Warburg, Alon

2016-10-01

Visceral leishmaniasis (VL), one of the most important neglected tropical diseases, is caused by Leishmania donovani eukaryotic protozoan parasite of the genus Leishmania, the disease is prevalent mainly in the Indian sub-continent, East Africa and Brazil. VL can be diagnosed by PCR amplifying ITS1 and/or kDNA genes. The current study involved the optimization of Loop-mediated isothermal amplification (LAMP) for the detection of Leishmania DNA in human blood or tissue samples. Three LAMP systems were developed; in two of those the primers were designed based on shared regions of the ITS1 gene among different Leishmania species, while the primers for the third LAMP system were derived from a newly identified repeated region in the Leishmania genome. The LAMP tests were shown to be sufficiently sensitive to detect 0.1pg of DNA from most Leishmania species. The green nucleic acid stain SYTO16, was used here for the first time to allow real-time monitoring of LAMP amplification. The advantage of real time-LAMP using SYTO 16 over end-point LAMP product detection is discussed. The efficacy of the real time-LAMP tests for detecting Leishmania DNA in dried blood samples from volunteers living in endemic areas, was compared with that of qRT-kDNA PCR. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

A System-Oriented Approach for the Optimal Control of Process Chains under Stochastic Influences

NASA Astrophysics Data System (ADS)

Senn, Melanie; Schäfer, Julian; Pollak, Jürgen; Link, Norbert

2011-09-01

Process chains in manufacturing consist of multiple connected processes in terms of dynamic systems. The properties of a product passing through such a process chain are influenced by the transformation of each single process. There exist various methods for the control of individual processes, such as classical state controllers from cybernetics or function mapping approaches realized by statistical learning. These controllers ensure that a desired state is obtained at process end despite of variations in the input and disturbances. The interactions between the single processes are thereby neglected, but play an important role in the optimization of the entire process chain. We divide the overall optimization into two phases: (1) the solution of the optimization problem by Dynamic Programming to find the optimal control variable values for each process for any encountered end state of its predecessor and (2) the application of the optimal control variables at runtime for the detected initial process state. The optimization problem is solved by selecting adequate control variables for each process in the chain backwards based on predefined quality requirements for the final product. For the demonstration of the proposed concept, we have chosen a process chain from sheet metal manufacturing with simplified transformation functions.

Rotorcraft Diagnostics

NASA Technical Reports Server (NTRS)

Haste, Deepak; Azam, Mohammad; Ghoshal, Sudipto; Monte, James

2012-01-01

Health management (HM) in any engineering systems requires adequate understanding about the system s functioning; a sufficient amount of monitored data; the capability to extract, analyze, and collate information; and the capability to combine understanding and information for HM-related estimation and decision-making. Rotorcraft systems are, in general, highly complex. Obtaining adequate understanding about functioning of such systems is quite difficult, because of the proprietary (restricted access) nature of their designs and dynamic models. Development of an EIM (exact inverse map) solution for rotorcraft requires a process that can overcome the abovementioned difficulties and maximally utilize monitored information for HM facilitation via employing advanced analytic techniques. The goal was to develop a versatile HM solution for rotorcraft for facilitation of the Condition Based Maintenance Plus (CBM+) capabilities. The effort was geared towards developing analytic and reasoning techniques, and proving the ability to embed the required capabilities on a rotorcraft platform, paving the way for implementing the solution on an aircraft-level system for consolidation and reporting. The solution for rotorcraft can he used offboard or embedded directly onto a rotorcraft system. The envisioned solution utilizes available monitored and archived data for real-time fault detection and identification, failure precursor identification, and offline fault detection and diagnostics, health condition forecasting, optimal guided troubleshooting, and maintenance decision support. A variant of the onboard version is a self-contained hardware and software (HW+SW) package that can be embedded on rotorcraft systems. The HM solution comprises components that gather/ingest data and information, perform information/feature extraction, analyze information in conjunction with the dependency/diagnostic model of the target system, facilitate optimal guided troubleshooting, and offer decision support for optimal maintenance.

Helicopter TEM parameters analysis and system optimization based on time constant

NASA Astrophysics Data System (ADS)

Xiao, Pan; Wu, Xin; Shi, Zongyang; Li, Jutao; Liu, Lihua; Fang, Guangyou

2018-03-01

Helicopter transient electromagnetic (TEM) method is a kind of common geophysical prospecting method, widely used in mineral detection, underground water exploration and environment investigation. In order to develop an efficient helicopter TEM system, it is necessary to analyze and optimize the system parameters. In this paper, a simple and quantitative method is proposed to analyze the system parameters, such as waveform, power, base frequency, measured field and sampling time. A wire loop model is used to define a comprehensive 'time constant domain' that shows a range of time constant, analogous to a range of conductance, after which the characteristics of the system parameters in this domain is obtained. It is found that the distortion caused by the transmitting base frequency is less than 5% when the ratio of the transmitting period to the target time constant is greater than 6. When the sampling time window is less than the target time constant, the distortion caused by the sampling time window is less than 5%. According to this method, a helicopter TEM system, called CASHTEM, is designed, and flight test has been carried out in the known mining area. The test results show that the system has good detection performance, verifying the effectiveness of the method.

An integrated logit model for contamination event detection in water distribution systems.

PubMed

Housh, Mashor; Ostfeld, Avi

2015-05-15

The problem of contamination event detection in water distribution systems has become one of the most challenging research topics in water distribution systems analysis. Current attempts for event detection utilize a variety of approaches including statistical, heuristics, machine learning, and optimization methods. Several existing event detection systems share a common feature in which alarms are obtained separately for each of the water quality indicators. Unifying those single alarms from different indicators is usually performed by means of simple heuristics. A salient feature of the current developed approach is using a statistically oriented model for discrete choice prediction which is estimated using the maximum likelihood method for integrating the single alarms. The discrete choice model is jointly calibrated with other components of the event detection system framework in a training data set using genetic algorithms. The fusing process of each indicator probabilities, which is left out of focus in many existing event detection system models, is confirmed to be a crucial part of the system which could be modelled by exploiting a discrete choice model for improving its performance. The developed methodology is tested on real water quality data, showing improved performances in decreasing the number of false positive alarms and in its ability to detect events with higher probabilities, compared to previous studies. Copyright © 2015 Elsevier Ltd. All rights reserved.

Spatio-temporal Hotelling observer for signal detection from image sequences

PubMed Central

Caucci, Luca; Barrett, Harrison H.; Rodríguez, Jeffrey J.

2010-01-01

Detection of signals in noisy images is necessary in many applications, including astronomy and medical imaging. The optimal linear observer for performing a detection task, called the Hotelling observer in the medical literature, can be regarded as a generalization of the familiar prewhitening matched filter. Performance on the detection task is limited by randomness in the image data, which stems from randomness in the object, randomness in the imaging system, and randomness in the detector outputs due to photon and readout noise, and the Hotelling observer accounts for all of these effects in an optimal way. If multiple temporal frames of images are acquired, the resulting data set is a spatio-temporal random process, and the Hotelling observer becomes a spatio-temporal linear operator. This paper discusses the theory of the spatio-temporal Hotelling observer and estimation of the required spatio-temporal covariance matrices. It also presents a parallel implementation of the observer on a cluster of Sony PLAYSTATION 3 gaming consoles. As an example, we consider the use of the spatio-temporal Hotelling observer for exoplanet detection. PMID:19550494

Spatio-temporal Hotelling observer for signal detection from image sequences.

PubMed

Caucci, Luca; Barrett, Harrison H; Rodriguez, Jeffrey J

2009-06-22

Detection of signals in noisy images is necessary in many applications, including astronomy and medical imaging. The optimal linear observer for performing a detection task, called the Hotelling observer in the medical literature, can be regarded as a generalization of the familiar prewhitening matched filter. Performance on the detection task is limited by randomness in the image data, which stems from randomness in the object, randomness in the imaging system, and randomness in the detector outputs due to photon and readout noise, and the Hotelling observer accounts for all of these effects in an optimal way. If multiple temporal frames of images are acquired, the resulting data set is a spatio-temporal random process, and the Hotelling observer becomes a spatio-temporal linear operator. This paper discusses the theory of the spatio-temporal Hotelling observer and estimation of the required spatio-temporal covariance matrices. It also presents a parallel implementation of the observer on a cluster of Sony PLAYSTATION 3 gaming consoles. As an example, we consider the use of the spatio-temporal Hotelling observer for exoplanet detection.

Nanomechanical recognition of prognostic biomarker suPAR with DVD-ROM optical technology.

PubMed

Bache, Michael; Bosco, Filippo G; Brøgger, Anna L; Frøhling, Kasper B; Alstrøm, Tommy Sonne; Hwu, En-Te; Chen, Ching-Hsiu; Eugen-Olsen, Jesper; Hwang, Ing-Shouh; Boisen, Anja

2013-11-08

In this work the use of a high-throughput nanomechanical detection system based on a DVD-ROM optical drive and cantilever sensors is presented for the detection of urokinase plasminogen activator receptor inflammatory biomarker (uPAR). Several large scale studies have linked elevated levels of soluble uPAR (suPAR) to infectious diseases, such as HIV, and certain types of cancer. Using hundreds of cantilevers and a DVD-based platform, cantilever deflection response from antibody-antigen recognition is investigated as a function of suPAR concentration. The goal is to provide a cheap and portable detection platform which can carry valuable prognostic information. In order to optimize the cantilever response the antibody immobilization and unspecific binding are initially characterized using quartz crystal microbalance technology. Also, the choice of antibody is explored in order to generate the largest surface stress on the cantilevers, thus increasing the signal. Using optimized experimental conditions the lowest detectable suPAR concentration is currently around 5 nM. The results reveal promising research strategies for the implementation of specific biochemical assays in a portable and high-throughput microsensor-based detection platform.

Root System Water Consumption Pattern Identification on Time Series Data

PubMed Central

Figueroa, Manuel; Pope, Christopher

2017-01-01

In agriculture, soil and meteorological sensors are used along low power networks to capture data, which allows for optimal resource usage and minimizing environmental impact. This study uses time series analysis methods for outliers’ detection and pattern recognition on soil moisture sensor data to identify irrigation and consumption patterns and to improve a soil moisture prediction and irrigation system. This study compares three new algorithms with the current detection technique in the project; the results greatly decrease the number of false positives detected. The best result is obtained by the Series Strings Comparison (SSC) algorithm averaging a precision of 0.872 on the testing sets, vastly improving the current system’s 0.348 precision. PMID:28621739

Optimize the Coverage Probability of Prediction Interval for Anomaly Detection of Sensor-Based Monitoring Series

PubMed Central

Liu, Datong; Peng, Yu; Peng, Xiyuan

2018-01-01

Effective anomaly detection of sensing data is essential for identifying potential system failures. Because they require no prior knowledge or accumulated labels, and provide uncertainty presentation, the probability prediction methods (e.g., Gaussian process regression (GPR) and relevance vector machine (RVM)) are especially adaptable to perform anomaly detection for sensing series. Generally, one key parameter of prediction models is coverage probability (CP), which controls the judging threshold of the testing sample and is generally set to a default value (e.g., 90% or 95%). There are few criteria to determine the optimal CP for anomaly detection. Therefore, this paper designs a graphic indicator of the receiver operating characteristic curve of prediction interval (ROC-PI) based on the definition of the ROC curve which can depict the trade-off between the PI width and PI coverage probability across a series of cut-off points. Furthermore, the Youden index is modified to assess the performance of different CPs, by the minimization of which the optimal CP is derived by the simulated annealing (SA) algorithm. Experiments conducted on two simulation datasets demonstrate the validity of the proposed method. Especially, an actual case study on sensing series from an on-orbit satellite illustrates its significant performance in practical application. PMID:29587372

Particle Swarm Optimization approach to defect detection in armour ceramics.

PubMed

Kesharaju, Manasa; Nagarajah, Romesh

2017-03-01

In this research, various extracted features were used in the development of an automated ultrasonic sensor based inspection system that enables defect classification in each ceramic component prior to despatch to the field. Classification is an important task and large number of irrelevant, redundant features commonly introduced to a dataset reduces the classifiers performance. Feature selection aims to reduce the dimensionality of the dataset while improving the performance of a classification system. In the context of a multi-criteria optimization problem (i.e. to minimize classification error rate and reduce number of features) such as one discussed in this research, the literature suggests that evolutionary algorithms offer good results. Besides, it is noted that Particle Swarm Optimization (PSO) has not been explored especially in the field of classification of high frequency ultrasonic signals. Hence, a binary coded Particle Swarm Optimization (BPSO) technique is investigated in the implementation of feature subset selection and to optimize the classification error rate. In the proposed method, the population data is used as input to an Artificial Neural Network (ANN) based classification system to obtain the error rate, as ANN serves as an evaluator of PSO fitness function. Copyright © 2016. Published by Elsevier B.V.

Automated Nucleic Acid Extraction Systems for Detecting Cytomegalovirus and Epstein-Barr Virus Using Real-Time PCR: A Comparison Study Between the QIAsymphony RGQ and QIAcube Systems.

PubMed

Kim, Hanah; Hur, Mina; Kim, Ji Young; Moon, Hee Won; Yun, Yeo Min; Cho, Hyun Chan

2017-03-01

Cytomegalovirus (CMV) and Epstein-Barr virus (EBV) are increasingly important in immunocompromised patients. Nucleic acid extraction methods could affect the results of viral nucleic acid amplification tests. We compared two automated nucleic acid extraction systems for detecting CMV and EBV using real-time PCR assays. One hundred and fifty-three whole blood (WB) samples were tested for CMV detection, and 117 WB samples were tested for EBV detection. Viral nucleic acid was extracted in parallel by using QIAsymphony RGQ and QIAcube (Qiagen GmbH, Germany), and real-time PCR assays for CMV and EBV were performed with a Rotor-Gene Q real-time PCR cycler (Qiagen). Detection rates for CMV and EBV were compared, and agreements between the two systems were analyzed. The detection rate of CMV and EBV differed significantly between the QIAsymphony RGQ and QIAcube systems (CMV, 59.5% [91/153] vs 43.8% [67/153], P=0.0005; EBV, 59.0% [69/117] vs 42.7% [50/117], P=0.0008). The two systems showed moderate agreement for CMV and EBV detection (kappa=0.43 and 0.52, respectively). QIAsymphony RGQ showed a negligible correlation with QIAcube for quantitative EBV detection. QIAcube exhibited EBV PCR inhibition in 23.9% (28/117) of samples. Automated nucleic acid extraction systems have different performances and significantly affect the detection of viral pathogens. The QIAsymphony RGQ system appears to be superior to the QIAcube system for detecting CMV and EBV. A suitable sample preparation system should be considered for optimized nucleic acid amplification in clinical laboratories.

PleurAlert: an augmented chest drainage system with electronic sensing, automated alerts and internet connectivity.

PubMed

Leeson, Cory E; Weaver, Robert A; Bissell, Taylor; Hoyer, Rachel; McClain, Corinne; Nelson, Douglas A; Samosky, Joseph T

2012-01-01

We have enhanced a common medical device, the chest tube drainage container, with electronic sensing of fluid volume, automated detection of critical alarm conditions and the ability to automatically send alert text messages to a nurse's cell phone. The PleurAlert system provides a simple touch-screen interface and can graphically display chest tube output over time. Our design augments a device whose basic function dates back 50 years by adding technology to automate and optimize a monitoring process that can be time consuming and inconvenient for nurses. The system may also enhance detection of emergency conditions and speed response time.

Seismic Characterizations of Fractures: Dynamic Diagnostics

NASA Astrophysics Data System (ADS)

Pyrak-Nolte, L. J.

2017-12-01

Fracture geometry controls fluid flow in a fracture, affects mechanical stability and influences energy partitioning that affects wave scattering. Our ability to detect and monitor fracture evolution is controlled by the frequency of the signal used to probe a fracture system, i.e. frequency selects the scales. No matter the frequency chosen, some set of discontinuities will be optimal for detection because different wavelengths sample different subsets of fractures. The select subset of fractures is based on the stiffness of the fractures which in turn is linked to fluid flow. A goal is obtaining information from scales outside the optimal detection regime. Fracture geometry trajectories are a potential approach to drive a fracture system across observation scales, i.e. moving systems between effective medium and scattering regimes. Dynamic trajectories (such as perturbing stress, fluid pressure, chemical alteration, etc.) can be used to perturb fracture geometry to enhance scattering or give rise to discrete modes that are intimately related to the micro-structural evolution of a fracture. However, identification of these signal features will require methods for identifying these micro-structural signatures in complicated scattered fields. Acknowledgment: This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, Geosciences Research Program under Award Number (DE-FG02-09ER16022).

A method to optimize the processing algorithm of a computed radiography system for chest radiography.

PubMed

Moore, C S; Liney, G P; Beavis, A W; Saunderson, J R

2007-09-01

A test methodology using an anthropomorphic-equivalent chest phantom is described for the optimization of the Agfa computed radiography "MUSICA" processing algorithm for chest radiography. The contrast-to-noise ratio (CNR) in the lung, heart and diaphragm regions of the phantom, and the "system modulation transfer function" (sMTF) in the lung region, were measured using test tools embedded in the phantom. Using these parameters the MUSICA processing algorithm was optimized with respect to low-contrast detectability and spatial resolution. Two optimum "MUSICA parameter sets" were derived respectively for maximizing the CNR and sMTF in each region of the phantom. Further work is required to find the relative importance of low-contrast detectability and spatial resolution in chest images, from which the definitive optimum MUSICA parameter set can then be derived. Prior to this further work, a compromised optimum MUSICA parameter set was applied to a range of clinical images. A group of experienced image evaluators scored these images alongside images produced from the same radiographs using the MUSICA parameter set in clinical use at the time. The compromised optimum MUSICA parameter set was shown to produce measurably better images.

Simplex optimization of the variables influencing the determination of pefloxacin by time-resolved chemiluminescence

NASA Astrophysics Data System (ADS)

Murillo Pulgarín, José A.; Alañón Molina, Aurelia; Jiménez García, Elisa

2018-03-01

A new chemiluminescence (CL) detection system combined with flow injection analysis (FIA) for the determination of Pefloxacin is proposed. The determination is based on an energy transfer from Pefloxacin to terbium (III). The metal ion enhances the weak CL signal produced by the KMnO4/H2SO3/Pefloxacin system. A modified simplex method was used to optimize chemical and instrumental variables. The influence of the interaction of the permanganate, Tb (III), sodium sulphite and sulphuric acid concentrations, flow rate and injected sample volume was thoroughly investigated by using a modified simplex optimization procedure. The results revealed a strong direct relationship between flow rate and CL intensity throughout the studied range that was confirmed by a gamma test. The response factor for the CL emission intensity was used to assess performance in order to identify the optimum conditions for maximization of the response. Under such conditions, the CL response was proportional to the Pefloxacin concentration over a wide range. The detection limit as calculated according to Clayton's criterion 13.7 μg L- 1. The analyte was successfully determined in milk samples with an average recovery of 100.6 ± 9.8%.

System geometry optimization for molecular breast tomosynthesis with focusing multi-pinhole collimators

NASA Astrophysics Data System (ADS)

van Roosmalen, Jarno; Beekman, Freek J.; Goorden, Marlies C.

2018-01-01

Imaging of 99mTc-labelled tracers is gaining popularity for detecting breast tumours. Recently, we proposed a novel design for molecular breast tomosynthesis (MBT) based on two sliding focusing multi-pinhole collimators that scan a modestly compressed breast. Simulation studies indicate that MBT has the potential to improve the tumour-to-background contrast-to-noise ratio significantly over state-of-the-art planar molecular breast imaging. The aim of the present paper is to optimize the collimator-detector geometry of MBT. Using analytical models, we first optimized sensitivity at different fixed system resolutions (ranging from 5 to 12 mm) by tuning the pinhole diameters and the distance between breast and detector for a whole series of automatically generated multi-pinhole designs. We evaluated both MBT with a conventional continuous crystal detector with 3.2 mm intrinsic resolution and with a pixelated detector with 1.6 mm pixels. Subsequently, full system simulations of a breast phantom containing several lesions were performed for the optimized geometry at each system resolution for both types of detector. From these simulations, we found that tumour-to-background contrast-to-noise ratio was highest for systems in the 7 mm-10 mm system resolution range over which it hardly varied. No significant differences between the two detector types were found.

Microwave-based medical diagnosis using particle swarm optimization algorithm

NASA Astrophysics Data System (ADS)

Modiri, Arezoo

This dissertation proposes and investigates a novel architecture intended for microwave-based medical diagnosis (MBMD). Furthermore, this investigation proposes novel modifications of particle swarm optimization algorithm for achieving enhanced convergence performance. MBMD has been investigated through a variety of innovative techniques in the literature since the 1990's and has shown significant promise in early detection of some specific health threats. In comparison to the X-ray- and gamma-ray-based diagnostic tools, MBMD does not expose patients to ionizing radiation; and due to the maturity of microwave technology, it lends itself to miniaturization of the supporting systems. This modality has been shown to be effective in detecting breast malignancy, and hence, this study focuses on the same modality. A novel radiator device and detection technique is proposed and investigated in this dissertation. As expected, hardware design and implementation are of paramount importance in such a study, and a good deal of research, analysis, and evaluation has been done in this regard which will be reported in ensuing chapters of this dissertation. It is noteworthy that an important element of any detection system is the algorithm used for extracting signatures. Herein, the strong intrinsic potential of the swarm-intelligence-based algorithms in solving complicated electromagnetic problems is brought to bear. This task is accomplished through addressing both mathematical and electromagnetic problems. These problems are called benchmark problems throughout this dissertation, since they have known answers. After evaluating the performance of the algorithm for the chosen benchmark problems, the algorithm is applied to MBMD tumor detection problem. The chosen benchmark problems have already been tackled by solution techniques other than particle swarm optimization (PSO) algorithm, the results of which can be found in the literature. However, due to the relatively high level of complexity and randomness inherent to the selection of electromagnetic benchmark problems, a trend to resort to oversimplification in order to arrive at reasonable solutions has been taken in literature when utilizing analytical techniques. Here, an attempt has been made to avoid oversimplification when using the proposed swarm-based optimization algorithms.

Frequency-Modulated, Continuous-Wave Laser Ranging Using Photon-Counting Detectors

NASA Technical Reports Server (NTRS)

Erkmen, Baris I.; Barber, Zeb W.; Dahl, Jason

2014-01-01

Optical ranging is a problem of estimating the round-trip flight time of a phase- or amplitude-modulated optical beam that reflects off of a target. Frequency- modulated, continuous-wave (FMCW) ranging systems obtain this estimate by performing an interferometric measurement between a local frequency- modulated laser beam and a delayed copy returning from the target. The range estimate is formed by mixing the target-return field with the local reference field on a beamsplitter and detecting the resultant beat modulation. In conventional FMCW ranging, the source modulation is linear in instantaneous frequency, the reference-arm field has many more photons than the target-return field, and the time-of-flight estimate is generated by balanced difference- detection of the beamsplitter output, followed by a frequency-domain peak search. This work focused on determining the maximum-likelihood (ML) estimation algorithm when continuous-time photoncounting detectors are used. It is founded on a rigorous statistical characterization of the (random) photoelectron emission times as a function of the incident optical field, including the deleterious effects caused by dark current and dead time. These statistics enable derivation of the Cramér-Rao lower bound (CRB) on the accuracy of FMCW ranging, and derivation of the ML estimator, whose performance approaches this bound at high photon flux. The estimation algorithm was developed, and its optimality properties were shown in simulation. Experimental data show that it performs better than the conventional estimation algorithms used. The demonstrated improvement is a factor of 1.414 over frequency-domainbased estimation. If the target interrogating photons and the local reference field photons are costed equally, the optimal allocation of photons between these two arms is to have them equally distributed. This is different than the state of the art, in which the local field is stronger than the target return. The optimal processing of the photocurrent processes at the outputs of the two detectors is to perform log-matched filtering followed by a summation and peak detection. This implies that neither difference detection, nor Fourier-domain peak detection, which are the staples of the state-of-the-art systems, is optimal when a weak local oscillator is employed.

Concurrently adjusting interrelated control parameters to achieve optimal engine performance

DOEpatents

Jiang, Li; Lee, Donghoon; Yilmaz, Hakan; Stefanopoulou, Anna

2015-12-01

Methods and systems for real-time engine control optimization are provided. A value of an engine performance variable is determined, a value of a first operating condition and a value of a second operating condition of a vehicle engine are detected, and initial values for a first engine control parameter and a second engine control parameter are determined based on the detected first operating condition and the detected second operating condition. The initial values for the first engine control parameter and the second engine control parameter are adjusted based on the determined value of the engine performance variable to cause the engine performance variable to approach a target engine performance variable. In order to cause the engine performance variable to approach the target engine performance variable, adjusting the initial value for the first engine control parameter necessitates a corresponding adjustment of the initial value for the second engine control parameter.

Structural damage detection-oriented multi-type sensor placement with multi-objective optimization

NASA Astrophysics Data System (ADS)

Lin, Jian-Fu; Xu, You-Lin; Law, Siu-Seong

2018-05-01

A structural damage detection-oriented multi-type sensor placement method with multi-objective optimization is developed in this study. The multi-type response covariance sensitivity-based damage detection method is first introduced. Two objective functions for optimal sensor placement are then introduced in terms of the response covariance sensitivity and the response independence. The multi-objective optimization problem is formed by using the two objective functions, and the non-dominated sorting genetic algorithm (NSGA)-II is adopted to find the solution for the optimal multi-type sensor placement to achieve the best structural damage detection. The proposed method is finally applied to a nine-bay three-dimensional frame structure. Numerical results show that the optimal multi-type sensor placement determined by the proposed method can avoid redundant sensors and provide satisfactory results for structural damage detection. The restriction on the number of each type of sensors in the optimization can reduce the searching space in the optimization to make the proposed method more effective. Moreover, how to select a most optimal sensor placement from the Pareto solutions via the utility function and the knee point method is demonstrated in the case study.

Never Use the Complete Search Space: a Concept to Enhance the Optimization Procedure for Monitoring Networks

NASA Astrophysics Data System (ADS)

Bode, F.; Reuschen, S.; Nowak, W.

2015-12-01

Drinking-water well catchments include many potential sources of contaminations like gas stations or agriculture. Finding optimal positions of early-warning monitoring wells is challenging because there are various parameters (and their uncertainties) that influence the reliability and optimality of any suggested monitoring location or monitoring network.The overall goal of this project is to develop and establish a concept to assess, design and optimize early-warning systems within well catchments. Such optimal monitoring networks need to optimize three competing objectives: a high detection probability, which can be reached by maximizing the "field of vision" of the monitoring network, a long early-warning time such that there is enough time left to install counter measures after first detection, and the overall operating costs of the monitoring network, which should ideally be reduced to a minimum. The method is based on numerical simulation of flow and transport in heterogeneous porous media coupled with geostatistics and Monte-Carlo, scenario analyses for real data, respectively, wrapped up within the framework of formal multi-objective optimization using a genetic algorithm.In order to speed up the optimization process and to better explore the Pareto-front, we developed a concept that forces the algorithm to search only in regions of the search space where promising solutions can be expected. We are going to show how to define these regions beforehand, using knowledge of the optimization problem, but also how to define them independently of problem attributes. With that, our method can be used with and/or without detailed knowledge of the objective functions.In summary, our study helps to improve optimization results in less optimization time by meaningful restrictions of the search space. These restrictions can be done independently of the optimization problem, but also in a problem-specific manner.

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

Zhang, Z.; Pike, R.W.; Hertwig, T.A.

An effective approach for source reduction in chemical plants has been demonstrated using on-line optimization with flowsheeting (ASPEN PLUS) for process optimization and parameter estimation and the Tjao-Biegler algorithm implemented in a mathematical programming language (GAMS/MINOS) for data reconciliation and gross error detection. Results for a Monsanto sulfuric acid plant with a Bailey distributed control system showed a 25% reduction in the sulfur dioxide emissions and a 17% improvement in the profit over the current operating conditions. Details of the methods used are described.

A Locally Optimal Algorithm for Estimating a Generating Partition from an Observed Time Series and Its Application to Anomaly Detection.

PubMed

Ghalyan, Najah F; Miller, David J; Ray, Asok

2018-06-12

Estimation of a generating partition is critical for symbolization of measurements from discrete-time dynamical systems, where a sequence of symbols from a (finite-cardinality) alphabet may uniquely specify the underlying time series. Such symbolization is useful for computing measures (e.g., Kolmogorov-Sinai entropy) to identify or characterize the (possibly unknown) dynamical system. It is also useful for time series classification and anomaly detection. The seminal work of Hirata, Judd, and Kilminster (2004) derives a novel objective function, akin to a clustering objective, that measures the discrepancy between a set of reconstruction values and the points from the time series. They cast estimation of a generating partition via the minimization of their objective function. Unfortunately, their proposed algorithm is nonconvergent, with no guarantee of finding even locally optimal solutions with respect to their objective. The difficulty is a heuristic-nearest neighbor symbol assignment step. Alternatively, we develop a novel, locally optimal algorithm for their objective. We apply iterative nearest-neighbor symbol assignments with guaranteed discrepancy descent, by which joint, locally optimal symbolization of the entire time series is achieved. While most previous approaches frame generating partition estimation as a state-space partitioning problem, we recognize that minimizing the Hirata et al. (2004) objective function does not induce an explicit partitioning of the state space, but rather the space consisting of the entire time series (effectively, clustering in a (countably) infinite-dimensional space). Our approach also amounts to a novel type of sliding block lossy source coding. Improvement, with respect to several measures, is demonstrated over popular methods for symbolizing chaotic maps. We also apply our approach to time-series anomaly detection, considering both chaotic maps and failure application in a polycrystalline alloy material.

Towards Real-Time Maneuver Detection: Automatic State and Dynamics Estimation with the Adaptive Optimal Control Based Estimator

NASA Astrophysics Data System (ADS)

Lubey, D.; Scheeres, D.

Tracking objects in Earth orbit is fraught with complications. This is due to the large population of orbiting spacecraft and debris that continues to grow, passive (i.e. no direct communication) and data-sparse observations, and the presence of maneuvers and dynamics mismodeling. Accurate orbit determination in this environment requires an algorithm to capture both a system's state and its state dynamics in order to account for mismodelings. Previous studies by the authors yielded an algorithm called the Optimal Control Based Estimator (OCBE) - an algorithm that simultaneously estimates a system's state and optimal control policies that represent dynamic mismodeling in the system for an arbitrary orbit-observer setup. The stochastic properties of these estimated controls are then used to determine the presence of mismodelings (maneuver detection), as well as characterize and reconstruct the mismodelings. The purpose of this paper is to develop the OCBE into an accurate real-time orbit tracking and maneuver detection algorithm by automating the algorithm and removing its linear assumptions. This results in a nonlinear adaptive estimator. In its original form the OCBE had a parameter called the assumed dynamic uncertainty, which is selected by the user with each new measurement to reflect the level of dynamic mismodeling in the system. This human-in-the-loop approach precludes real-time application to orbit tracking problems due to their complexity. This paper focuses on the Adaptive OCBE, a version of the estimator where the assumed dynamic uncertainty is chosen automatically with each new measurement using maneuver detection results to ensure that state uncertainties are properly adjusted to account for all dynamic mismodelings. The paper also focuses on a nonlinear implementation of the estimator. Originally, the OCBE was derived from a nonlinear cost function then linearized about a nominal trajectory, which is assumed to be ballistic (i.e. the nominal optimal control policy is zero for all times). In this paper, we relax this assumption on the nominal trajectory in order to allow for controlled nominal trajectories. This allows the estimator to be iterated to obtain a more accurate nonlinear solution for both the state and control estimates. Beyond these developments to the estimator, this paper also introduces a modified distance metric for maneuver detection. The original metric used in the OCBE only accounted for the estimated control and its uncertainty. This new metric accounts for measurement deviation and a priori state deviations, such that it accounts for all three major forms of uncertainty in orbit determination. This allows the user to understand the contributions of each source of uncertainty toward the total system mismodeling so that the user can properly account for them. Together these developments create an accurate orbit determination algorithm that is automated, robust to mismodeling, and capable of detecting and reconstructing the presence of mismodeling. These qualities make this algorithm a good foundation from which to approach the problem of real-time maneuver detection and reconstruction for Space Situational Awareness applications. This is further strengthened by the algorithm's general formulation that allows it to be applied to problems with an arbitrary target and observer.

A probabilistic method for the estimation of residual risk in donated blood.

PubMed

Bish, Ebru K; Ragavan, Prasanna K; Bish, Douglas R; Slonim, Anthony D; Stramer, Susan L

2014-10-01

The residual risk (RR) of transfusion-transmitted infections, including the human immunodeficiency virus and hepatitis B and C viruses, is typically estimated by the incidence[Formula: see text]window period model, which relies on the following restrictive assumptions: Each screening test, with probability 1, (1) detects an infected unit outside of the test's window period; (2) fails to detect an infected unit within the window period; and (3) correctly identifies an infection-free unit. These assumptions need not hold in practice due to random or systemic errors and individual variations in the window period. We develop a probability model that accurately estimates the RR by relaxing these assumptions, and quantify their impact using a published cost-effectiveness study and also within an optimization model. These assumptions lead to inaccurate estimates in cost-effectiveness studies and to sub-optimal solutions in the optimization model. The testing solution generated by the optimization model translates into fewer expected infections without an increase in the testing cost. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Development of GEM detector for plasma diagnostics application: simulations addressing optimization of its performance

NASA Astrophysics Data System (ADS)

Chernyshova, M.; Malinowski, K.; Kowalska-Strzęciwilk, E.; Czarski, T.; Linczuk, P.; Wojeński, A.; Krawczyk, R. D.

2017-12-01

The advanced Soft X-ray (SXR) diagnostics setup devoted to studies of the SXR plasma emissivity is at the moment a highly relevant and important for ITER/DEMO application. Especially focusing on the energy range of tungsten emission lines, as plasma contamination by W and its transport in the plasma must be understood and monitored for W plasma-facing material. The Gas Electron Multiplier, with a spatial and energy-resolved photon detecting chamber, based SXR radiation detection system under development by our group may become such a diagnostic setup considering and solving many physical, technical and technological aspects. This work presents the results of simulations aimed to optimize a design of the detector's internal chamber and its performance. The study of the effect of electrodes alignment allowed choosing the gap distances which maximizes electron transmission and choosing the optimal magnitudes of the applied electric fields. Finally, the optimal readout structure design was identified suitable to collect a total formed charge effectively, basing on the range of the simulated electron cloud at the readout plane which was in the order of ~ 2 mm.

A fundamental study of laser-induced breakdown spectroscopy using fiber optics for remote measurements of trace metals. Interim progress report

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

Goode, S.R.; Angel, S.M.

1997-01-01

'The long-term goal of this project is to develop a system to measure the elemental composition of unprepared samples using laser-induced breakdown spectroscopy, LIBS, with a fiber-optic probe. From images shown in this report it is evident that the temporal and spatial behavior of laser-induced plasmas IS a complex process. However, through the use of spectral imaging, optimal conditions can be determined for collecting the atomic emission signal in these plasmas. By tailoring signal collection to the regions of the plasma that contain the highest emission signal with the least amount of background interference both the detection limits and themore » precision of LIBS measurements could be improved. The optimal regions for both gated and possibly non-gated LIBS measurements have been shown to correspond to the inner regions and outer regions, respectively, in an axial plasma. By using this data fiber-optic LIBS probe designs can be optimized for collecting plasma emission at the optimal regions for improved detection limits and precision in a LIBS measurement.'« less

VLSI Design of SVM-Based Seizure Detection System With On-Chip Learning Capability.

PubMed

Feng, Lichen; Li, Zunchao; Wang, Yuanfa

2018-02-01

Portable automatic seizure detection system is very convenient for epilepsy patients to carry. In order to make the system on-chip trainable with high efficiency and attain high detection accuracy, this paper presents a very large scale integration (VLSI) design based on the nonlinear support vector machine (SVM). The proposed design mainly consists of a feature extraction (FE) module and an SVM module. The FE module performs the three-level Daubechies discrete wavelet transform to fit the physiological bands of the electroencephalogram (EEG) signal and extracts the time-frequency domain features reflecting the nonstationary signal properties. The SVM module integrates the modified sequential minimal optimization algorithm with the table-driven-based Gaussian kernel to enable efficient on-chip learning. The presented design is verified on an Altera Cyclone II field-programmable gate array and tested using the two publicly available EEG datasets. Experiment results show that the designed VLSI system improves the detection accuracy and training efficiency.

Advanced Doppler radar physiological sensing technique for drone detection

NASA Astrophysics Data System (ADS)

Yoon, Ji Hwan; Xu, Hao; Garcia Carrillo, Luis R.

2017-05-01

A 24 GHz medium-range human detecting sensor, using the Doppler Radar Physiological Sensing (DRPS) technique, which can also detect unmanned aerial vehicles (UAVs or drones), is currently under development for potential rescue and anti-drone applications. DRPS systems are specifically designed to remotely monitor small movements of non-metallic human tissues such as cardiopulmonary activity and respiration. Once optimized, the unique capabilities of DRPS could be used to detect UAVs. Initial measurements have shown that DRPS technology is able to detect moving and stationary humans, as well as largely non-metallic multi-rotor drone helicopters. Further data processing will incorporate pattern recognition to detect multiple signatures (motor vibration and hovering patterns) of UAVs.

SU-D-206-06: Task-Specific Optimization of Scintillator Thickness for CMOS-Detector Based Cone-Beam Breast CT

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

Vedantham, S; Shrestha, S; Shi, L

Purpose: To optimize the cesium iodide (CsI:Tl) scintillator thickness in a complimentary metal-oxide semiconductor (CMOS)-based detector for use in dedicated cone-beam breast CT. Methods: The imaging task considered was the detection of a microcalcification cluster comprising six 220µm diameter calcium carbonate spheres, arranged in the form of a regular pentagon with 2 mm spacing on its sides and a central calcification, similar to that in ACR-recommended mammography accreditation phantom, at a mean glandular dose of 4.5 mGy. Generalized parallel-cascades based linear systems analysis was used to determine Fourier-domain image quality metrics in reconstructed object space, from which the detectability indexmore » inclusive of anatomical noise was determined for a non-prewhitening numerical observer. For 300 projections over 2π, magnification-associated focal-spot blur, Monte Carlo derived x-ray scatter, K-fluorescent emission and reabsorption within CsI:Tl, CsI:Tl quantum efficiency and optical blur, fiberoptic plate transmission efficiency and blur, CMOS quantum efficiency, pixel aperture function and additive noise, and filtered back-projection to isotropic 105µm voxel pitch with bilinear interpolation were modeled. Imaging geometry of a clinical prototype breast CT system, a 60 kV Cu/Al filtered x-ray spectrum from 0.3 mm focal spot incident on a 14 cm diameter semi-ellipsoidal breast were used to determine the detectability index for 300–600 µm thick (75µm increments) CsI:Tl. The CsI:Tl thickness that maximized the detectability index was considered optimal. Results: The limiting resolution (10% modulation transfer function, MTF) progressively decreased with increasing CsI:Tl thickness. The zero-frequency detective quantum efficiency, DQE(0), in projection space increased with increasing CsI:Tl thickness. The maximum detectability index was achieved with 525µm thick CsI:Tl scintillator. Reduced MTF at mid-to-high frequencies for 600µm thick CsI:Tl lowered the detectability index than 525µm CsI:Tl. Conclusion: For the x-ray spectrum and imaging conditions considered, a 525µm thick CsI:Tl scintillator integrated with the CMOS detector is optimal for detecting microcalcification cluster. Funding support: Supported in part by NIH R01 CA195512. The contents are solely the responsibility of the authors and do not reflect the official views of the NIH or the NCI. Disclosures: SV, GV and AK - Research collaboration, Koning Corp., West Henrietta, NY.« less

Design and Optimization of an EEG-Based Brain Machine Interface (BMI) to an Upper-Limb Exoskeleton for Stroke Survivors

PubMed Central

Bhagat, Nikunj A.; Venkatakrishnan, Anusha; Abibullaev, Berdakh; Artz, Edward J.; Yozbatiran, Nuray; Blank, Amy A.; French, James; Karmonik, Christof; Grossman, Robert G.; O'Malley, Marcia K.; Francisco, Gerard E.; Contreras-Vidal, Jose L.

2016-01-01

This study demonstrates the feasibility of detecting motor intent from brain activity of chronic stroke patients using an asynchronous electroencephalography (EEG)-based brain machine interface (BMI). Intent was inferred from movement related cortical potentials (MRCPs) measured over an optimized set of EEG electrodes. Successful intent detection triggered the motion of an upper-limb exoskeleton (MAHI Exo-II), to guide movement and to encourage active user participation by providing instantaneous sensory feedback. Several BMI design features were optimized to increase system performance in the presence of single-trial variability of MRCPs in the injured brain: (1) an adaptive time window was used for extracting features during BMI calibration; (2) training data from two consecutive days were pooled for BMI calibration to increase robustness to handle the day-to-day variations typical of EEG, and (3) BMI predictions were gated by residual electromyography (EMG) activity from the impaired arm, to reduce the number of false positives. This patient-specific BMI calibration approach can accommodate a broad spectrum of stroke patients with diverse motor capabilities. Following BMI optimization on day 3, testing of the closed-loop BMI-MAHI exoskeleton, on 4th and 5th days of the study, showed consistent BMI performance with overall mean true positive rate (TPR) = 62.7 ± 21.4% on day 4 and 67.1 ± 14.6% on day 5. The overall false positive rate (FPR) across subjects was 27.74 ± 37.46% on day 4 and 27.5 ± 35.64% on day 5; however for two subjects who had residual motor function and could benefit from the EMG-gated BMI, the mean FPR was quite low (< 10%). On average, motor intent was detected −367 ± 328 ms before movement onset during closed-loop operation. These findings provide evidence that closed-loop EEG-based BMI for stroke patients can be designed and optimized to perform well across multiple days without system recalibration. PMID:27065787

A risk-based multi-objective model for optimal placement of sensors in water distribution system

NASA Astrophysics Data System (ADS)

Naserizade, Sareh S.; Nikoo, Mohammad Reza; Montaseri, Hossein

2018-02-01

In this study, a new stochastic model based on Conditional Value at Risk (CVaR) and multi-objective optimization methods is developed for optimal placement of sensors in water distribution system (WDS). This model determines minimization of risk which is caused by simultaneous multi-point contamination injection in WDS using CVaR approach. The CVaR considers uncertainties of contamination injection in the form of probability distribution function and calculates low-probability extreme events. In this approach, extreme losses occur at tail of the losses distribution function. Four-objective optimization model based on NSGA-II algorithm is developed to minimize losses of contamination injection (through CVaR of affected population and detection time) and also minimize the two other main criteria of optimal placement of sensors including probability of undetected events and cost. Finally, to determine the best solution, Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE), as a subgroup of Multi Criteria Decision Making (MCDM) approach, is utilized to rank the alternatives on the trade-off curve among objective functions. Also, sensitivity analysis is done to investigate the importance of each criterion on PROMETHEE results considering three relative weighting scenarios. The effectiveness of the proposed methodology is examined through applying it to Lamerd WDS in the southwestern part of Iran. The PROMETHEE suggests 6 sensors with suitable distribution that approximately cover all regions of WDS. Optimal values related to CVaR of affected population and detection time as well as probability of undetected events for the best optimal solution are equal to 17,055 persons, 31 mins and 0.045%, respectively. The obtained results of the proposed methodology in Lamerd WDS show applicability of CVaR-based multi-objective simulation-optimization model for incorporating the main uncertainties of contamination injection in order to evaluate extreme value of losses in WDS.

Detecting and locating light atoms from high-resolution STEM images: The quest for a single optimal design.

PubMed

Gonnissen, J; De Backer, A; den Dekker, A J; Sijbers, J; Van Aert, S

2016-11-01

In the present paper, the optimal detector design is investigated for both detecting and locating light atoms from high resolution scanning transmission electron microscopy (HR STEM) images. The principles of detection theory are used to quantify the probability of error for the detection of light atoms from HR STEM images. To determine the optimal experiment design for locating light atoms, use is made of the so-called Cramér-Rao Lower Bound (CRLB). It is investigated if a single optimal design can be found for both the detection and location problem of light atoms. Furthermore, the incoming electron dose is optimised for both research goals and it is shown that picometre range precision is feasible for the estimation of the atom positions when using an appropriate incoming electron dose under the optimal detector settings to detect light atoms. Copyright © 2016 Elsevier B.V. All rights reserved.

Image-Based 3D Face Modeling System

NASA Astrophysics Data System (ADS)

Park, In Kyu; Zhang, Hui; Vezhnevets, Vladimir

2005-12-01

This paper describes an automatic system for 3D face modeling using frontal and profile images taken by an ordinary digital camera. The system consists of four subsystems including frontal feature detection, profile feature detection, shape deformation, and texture generation modules. The frontal and profile feature detection modules automatically extract the facial parts such as the eye, nose, mouth, and ear. The shape deformation module utilizes the detected features to deform the generic head mesh model such that the deformed model coincides with the detected features. A texture is created by combining the facial textures augmented from the input images and the synthesized texture and mapped onto the deformed generic head model. This paper provides a practical system for 3D face modeling, which is highly automated by aggregating, customizing, and optimizing a bunch of individual computer vision algorithms. The experimental results show a highly automated process of modeling, which is sufficiently robust to various imaging conditions. The whole model creation including all the optional manual corrections takes only 2[InlineEquation not available: see fulltext.]3 minutes.

An efficient multi-objective optimization method for water quality sensor placement within water distribution systems considering contamination probability variations.

PubMed

He, Guilin; Zhang, Tuqiao; Zheng, Feifei; Zhang, Qingzhou

2018-06-20

Water quality security within water distribution systems (WDSs) has been an important issue due to their inherent vulnerability associated with contamination intrusion. This motivates intensive studies to identify optimal water quality sensor placement (WQSP) strategies, aimed to timely/effectively detect (un)intentional intrusion events. However, these available WQSP optimization methods have consistently presumed that each WDS node has an equal contamination probability. While being simple in implementation, this assumption may do not conform to the fact that the nodal contamination probability may be significantly regionally varied owing to variations in population density and user properties. Furthermore, the low computational efficiency is another important factor that has seriously hampered the practical applications of the currently available WQSP optimization approaches. To address these two issues, this paper proposes an efficient multi-objective WQSP optimization method to explicitly account for contamination probability variations. Four different contamination probability functions (CPFs) are proposed to represent the potential variations of nodal contamination probabilities within the WDS. Two real-world WDSs are used to demonstrate the utility of the proposed method. Results show that WQSP strategies can be significantly affected by the choice of the CPF. For example, when the proposed method is applied to the large case study with the CPF accounting for user properties, the event detection probabilities of the resultant solutions are approximately 65%, while these values are around 25% for the traditional approach, and such design solutions are achieved approximately 10,000 times faster than the traditional method. This paper provides an alternative method to identify optimal WQSP solutions for the WDS, and also builds knowledge regarding the impacts of different CPFs on sensor deployments. Copyright © 2018 Elsevier Ltd. All rights reserved.

Optimizing spectral CT parameters for material classification tasks

NASA Astrophysics Data System (ADS)

Rigie, D. S.; La Rivière, P. J.

2016-06-01

In this work, we propose a framework for optimizing spectral CT imaging parameters and hardware design with regard to material classification tasks. Compared with conventional CT, many more parameters must be considered when designing spectral CT systems and protocols. These choices will impact material classification performance in a non-obvious, task-dependent way with direct implications for radiation dose reduction. In light of this, we adapt Hotelling Observer formalisms typically applied to signal detection tasks to the spectral CT, material-classification problem. The result is a rapidly computable metric that makes it possible to sweep out many system configurations, generating parameter optimization curves (POC’s) that can be used to select optimal settings. The proposed model avoids restrictive assumptions about the basis-material decomposition (e.g. linearity) and incorporates signal uncertainty with a stochastic object model. This technique is demonstrated on dual-kVp and photon-counting systems for two different, clinically motivated material classification tasks (kidney stone classification and plaque removal). We show that the POC’s predicted with the proposed analytic model agree well with those derived from computationally intensive numerical simulation studies.

Optimizing Spectral CT Parameters for Material Classification Tasks

PubMed Central

Rigie, D. S.; La Rivière, P. J.

2017-01-01

In this work, we propose a framework for optimizing spectral CT imaging parameters and hardware design with regard to material classification tasks. Compared with conventional CT, many more parameters must be considered when designing spectral CT systems and protocols. These choices will impact material classification performance in a non-obvious, task-dependent way with direct implications for radiation dose reduction. In light of this, we adapt Hotelling Observer formalisms typically applied to signal detection tasks to the spectral CT, material-classification problem. The result is a rapidly computable metric that makes it possible to sweep out many system configurations, generating parameter optimization curves (POC’s) that can be used to select optimal settings. The proposed model avoids restrictive assumptions about the basis-material decomposition (e.g. linearity) and incorporates signal uncertainty with a stochastic object model. This technique is demonstrated on dual-kVp and photon-counting systems for two different, clinically motivated material classification tasks (kidney stone classification and plaque removal). We show that the POC’s predicted with the proposed analytic model agree well with those derived from computationally intensive numerical simulation studies. PMID:27227430

A proposal of optimal sampling design using a modularity strategy

NASA Astrophysics Data System (ADS)

Simone, A.; Giustolisi, O.; Laucelli, D. B.

2016-08-01

In real water distribution networks (WDNs) are present thousands nodes and optimal placement of pressure and flow observations is a relevant issue for different management tasks. The planning of pressure observations in terms of spatial distribution and number is named sampling design and it was faced considering model calibration. Nowadays, the design of system monitoring is a relevant issue for water utilities e.g., in order to manage background leakages, to detect anomalies and bursts, to guarantee service quality, etc. In recent years, the optimal location of flow observations related to design of optimal district metering areas (DMAs) and leakage management purposes has been faced considering optimal network segmentation and the modularity index using a multiobjective strategy. Optimal network segmentation is the basis to identify network modules by means of optimal conceptual cuts, which are the candidate locations of closed gates or flow meters creating the DMAs. Starting from the WDN-oriented modularity index, as a metric for WDN segmentation, this paper proposes a new way to perform the sampling design, i.e., the optimal location of pressure meters, using newly developed sampling-oriented modularity index. The strategy optimizes the pressure monitoring system mainly based on network topology and weights assigned to pipes according to the specific technical tasks. A multiobjective optimization minimizes the cost of pressure meters while maximizing the sampling-oriented modularity index. The methodology is presented and discussed using the Apulian and Exnet networks.

Development of systems for detection, early warning, and control of pipeline leakage in drinking water distribution: a case study.

PubMed

Li, Weifeng; Ling, Wencui; Liu, Suoxiang; Zhao, Jing; Liu, Ruiping; Chen, Qiuwen; Qiang, Zhimin; Qu, Jiuhui

2011-01-01

Water leakage in drinking water distribution systems is a serious problem for many cities and a huge challenge for water utilities. An integrated system for the detection, early warning, and control of pipeline leakage has been developed and successfully used to manage the pipeline networks in selected areas of Beijing. A method based on the geographic information system has been proposed to quickly and automatically optimize the layout of the instruments which detect leaks. Methods are also proposed to estimate the probability of each pipe segment leaking (on the basis of historic leakage data), and to assist in locating the leakage points (based on leakage signals). The district metering area (DMA) strategy is used. Guidelines and a flowchart for establishing a DMA to manage the large-scale looped networks in Beijing are proposed. These different functions have been implemented into a central software system to simplify the day-to-day use of the system. In 2007 the system detected 102 non-obvious leakages (i.e., 14.2% of the total detected in Beijing) in the selected areas, which was estimated to save a total volume of 2,385,000 m3 of water. These results indicate the feasibility, efficiency and wider applicability of this system.

Damage Detection Based on Static Strain Responses Using FBG in a Wind Turbine Blade

PubMed Central

Tian, Shaohua; Yang, Zhibo; Chen, Xuefeng; Xie, Yong

2015-01-01

The damage detection of a wind turbine blade enables better operation of the turbines, and provides an early alert to the destroyed events of the blade in order to avoid catastrophic losses. A new non-baseline damage detection method based on the Fiber Bragg grating (FBG) in a wind turbine blade is developed in this paper. Firstly, the Chi-square distribution is proven to be an effective damage-sensitive feature which is adopted as the individual information source for the local decision. In order to obtain the global and optimal decision for the damage detection, the feature information fusion (FIF) method is proposed to fuse and optimize information in above individual information sources, and the damage is detected accurately through of the global decision. Then a 13.2 m wind turbine blade with the distributed strain sensor system is adopted to describe the feasibility of the proposed method, and the strain energy method (SEM) is used to describe the advantage of the proposed method. Finally results show that the proposed method can deliver encouraging results of the damage detection in the wind turbine blade. PMID:26287200

Remote-controlled robotic platform ORPHEUS as a new tool for detection of bacteria in the environment.

PubMed

Nejdl, Lukas; Kudr, Jiri; Cihalova, Kristyna; Chudobova, Dagmar; Zurek, Michal; Zalud, Ludek; Kopecny, Lukas; Burian, Frantisek; Ruttkay-Nedecky, Branislav; Krizkova, Sona; Konecna, Marie; Hynek, David; Kopel, Pavel; Prasek, Jan; Adam, Vojtech; Kizek, Rene

2014-08-01

Remote-controlled robotic systems are being used for analysis of various types of analytes in hostile environment including those called extraterrestrial. The aim of our study was to develop a remote-controlled robotic platform (ORPHEUS-HOPE) for bacterial detection. For the platform ORPHEUS-HOPE a 3D printed flow chip was designed and created with a culture chamber with volume 600 μL. The flow rate was optimized to 500 μL/min. The chip was tested primarily for detection of 1-naphthol by differential pulse voltammetry with detection limit (S/N = 3) as 20 nM. Further, the way how to capture bacteria was optimized. To capture bacterial cells (Staphylococcus aureus), maghemite nanoparticles (1 mg/mL) were prepared and modified with collagen, glucose, graphene, gold, hyaluronic acid, and graphene with gold or graphene with glucose (20 mg/mL). The most up to 50% of the bacteria were captured by graphene nanoparticles modified with glucose. The detection limit of the whole assay, which included capturing of bacteria and their detection under remote control operation, was estimated as 30 bacteria per μL. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Implementing a bubble memory hierarchy system

NASA Technical Reports Server (NTRS)

Segura, R.; Nichols, C. D.

1979-01-01

This paper reports on implementation of a magnetic bubble memory in a two-level hierarchial system. The hierarchy used a major-minor loop device and RAM under microprocessor control. Dynamic memory addressing, dual bus primary memory, and hardware data modification detection are incorporated in the system to minimize access time. It is the objective of the system to incorporate the advantages of bipolar memory with that of bubble domain memory to provide a smart, optimal memory system which is easy to interface and independent of user's system.

Fluorescence quencher improves SCANSYSTEM for rapid bacterial detection.

PubMed

Schmidt, M; Hourfar, M K; Wahl, A; Nicol, S-B; Montag, T; Roth, W K; Seifried, E

2006-05-01

The optimized scansystem could detect contaminated platelet products within 24 h. However, the system's sensitivity was reduced by a high fluorescence background even in sterile samples, which led to the necessity of a well-trained staff for confirmation of microscope results. A new protocol of the optimized scansystem with the addition of a fluorescence quencher was evaluated. Pool platelet concentrates contaminated with five transfusion-relevant bacterial strains were tested in a blind study. In conjunction with new analysis software, the new quenching dye was able to reduce significantly unspecific background fluorescence. Sensitivity was best for Bacillus cereus and Escherichia coli (3 CFU/ml). The application of a fluorescence quencher enables automated discrimination of positive and negative test results in 60% of all analysed samples.

Comparison of spike-sorting algorithms for future hardware implementation.

PubMed

Gibson, Sarah; Judy, Jack W; Markovic, Dejan

2008-01-01

Applications such as brain-machine interfaces require hardware spike sorting in order to (1) obtain single-unit activity and (2) perform data reduction for wireless transmission of data. Such systems must be low-power, low-area, high-accuracy, automatic, and able to operate in real time. Several detection and feature extraction algorithms for spike sorting are described briefly and evaluated in terms of accuracy versus computational complexity. The nonlinear energy operator method is chosen as the optimal spike detection algorithm, being most robust over noise and relatively simple. The discrete derivatives method [1] is chosen as the optimal feature extraction method, maintaining high accuracy across SNRs with a complexity orders of magnitude less than that of traditional methods such as PCA.

Optimization of energy window and evaluation of scatter compensation methods in MPS using the ideal observer with model mismatch

NASA Astrophysics Data System (ADS)

Ghaly, Michael; Links, Jonathan M.; Frey, Eric

2015-03-01

In this work, we used the ideal observer (IO) and IO with model mismatch (IO-MM) applied in the projection domain and an anthropomorphic Channelized Hotelling Observer (CHO) applied to reconstructed images to optimize the acquisition energy window width and evaluate various scatter compensation methods in the context of a myocardial perfusion SPECT defect detection task. The IO has perfect knowledge of the image formation process and thus reflects performance with perfect compensation for image-degrading factors. Thus, using the IO to optimize imaging systems could lead to suboptimal parameters compared to those optimized for humans interpreting SPECT images reconstructed with imperfect or no compensation. The IO-MM allows incorporating imperfect system models into the IO optimization process. We found that with near-perfect scatter compensation, the optimal energy window for the IO and CHO were similar; in its absence the IO-MM gave a better prediction of the optimal energy window for the CHO using different scatter compensation methods. These data suggest that the IO-MM may be useful for projection-domain optimization when model mismatch is significant, and that the IO is useful when followed by reconstruction with good models of the image formation process.

Evaluation of seven cosubstrates in the quantification of horseradish peroxidase enzyme by square wave voltammetry.

PubMed

Kergaravat, Silvina V; Pividori, Maria Isabel; Hernandez, Silvia R

2012-01-15

The electrochemical detection for horseradish peroxidase-cosubstrate-H(2)O(2) systems was optimized. o-Phenilendiamine, phenol, hydroquinone, pyrocatechol, p-chlorophenol, p-aminophenol and 3,3'-5,5'-tetramethylbenzidine were evaluated as cosubstrates of horseradish peroxidase (HRP) enzyme. Therefore, the reaction time, the addition sequence of the substrates, the cosubstrate:H(2)O(2) ratio and the electrochemical techniques were elected by one-factor optimization assays while the buffer pH, the enzymatic activity and cosubstrate and H(2)O(2) concentrations for each system were selected simultaneously by response surface methodology. Then, the calibration curves for seven horseradish peroxidase-cosubstrate-H(2)O(2) systems were built and the analytic parameters were analyzed. o-Phenilendiamine was selected as the best cosubstrate for the HRP enzyme. For this system the reaction time of 60s, the phosphate buffer pH 6.0, and the concentrations of 2.5×10(-4)molL(-1) o-phenilendiamine and of 1.25×10(-4)molL(-1) H(2)O(2) were chosen as the optimal conditions. In these conditions, the calibration curve of horseradish peroxidase by square wave voltammetry showed a linearity range from 9.5×10(-11) to 1.9×10(-8)molL(-1) and the limit of detection of 3.8×10(-11)molL(-1) with RSD% of 0.03% (n=3). Copyright © 2011 Elsevier B.V. All rights reserved.

Improving tsunami warning systems with remote sensing and geographical information system input.

PubMed

Wang, Jin-Feng; Li, Lian-Fa

2008-12-01

An optimal and integrative tsunami warning system is introduced that takes full advantage of remote sensing and geographical information systems (GIS) in monitoring, forecasting, detection, loss evaluation, and relief management for tsunamis. Using the primary impact zone in Banda Aceh, Indonesia as the pilot area, we conducted three simulations that showed that while the December 26, 2004 Indian Ocean tsunami claimed about 300,000 lives because there was no tsunami warning system at all, it is possible that only about 15,000 lives could have been lost if the area had used a tsunami warning system like that currently in use in the Pacific Ocean. The simulations further calculated that the death toll could have been about 3,000 deaths if there had been a disaster system further optimized with full use of remote sensing and GIS, although the number of badly damaged or destroyed houses (29,545) could have likely remained unchanged.

Model development and system performance optimization for staring infrared search and track (IRST) sensors

NASA Astrophysics Data System (ADS)

Olson, Craig; Theisen, Michael; Pace, Teresa; Halford, Carl; Driggers, Ronald

2016-05-01

The mission of an Infrared Search and Track (IRST) system is to detect and locate (sometimes called find and fix) enemy aircraft at significant ranges. Two extreme opposite examples of IRST applications are 1) long range offensive aircraft detection when electronic warfare equipment is jammed, compromised, or intentionally turned off, and 2) distributed aperture systems where enemy aircraft may be in the proximity of the host aircraft. Past IRST systems have been primarily long range offensive systems that were based on the LWIR second generation thermal imager. The new IRST systems are primarily based on staring infrared focal planes and sensors. In the same manner that FLIR92 did not work well in the design of staring infrared cameras (NVTherm was developed to address staring infrared sensor performance), current modeling techniques do not adequately describe the performance of a staring IRST sensor. There are no standard military IRST models (per AFRL and NAVAIR), and each program appears to perform their own modeling. For this reason, L-3 has decided to develop a corporate model, working with AFRL and NAVAIR, for the analysis, design, and evaluation of IRST concepts, programs, and solutions. This paper provides some of the first analyses in the L-3 IRST model development program for the optimization of staring IRST sensors.

Influence of grid control and object detection on radiation exposure and image quality using mobile C-arms - first results.

PubMed

Gosch, D; Ratzmer, A; Berauer, P; Kahn, T

2007-09-01

The objective of this study was to examine the extent to which the image quality on mobile C-arms can be improved by an innovative exposure rate control system (grid control). In addition, the possible dose reduction in the pulsed fluoroscopy mode using 25 pulses/sec produced by automatic adjustment of the pulse rate through motion detection was to be determined. As opposed to conventional exposure rate control systems, which use a measuring circle in the center of the field of view, grid control is based on a fine mesh of square cells which are overlaid on the entire fluoroscopic image. The system uses only those cells for exposure control that are covered by the object to be visualized. This is intended to ensure optimally exposed images, regardless of the size, shape and position of the object to be visualized. The system also automatically detects any motion of the object. If a pulse rate of 25 pulses/sec is selected and no changes in the image are observed, the pulse rate used for pulsed fluoroscopy is gradually reduced. This may decrease the radiation exposure. The influence of grid control on image quality was examined using an anthropomorphic phantom. The dose reduction achieved with the help of object detection was determined by evaluating the examination data of 146 patients from 5 different countries. The image of the static phantom made with grid control was always optimally exposed, regardless of the position of the object to be visualized. The average dose reduction when using 25 pulses/sec resulting from object detection and automatic down-pulsing was 21 %, and the maximum dose reduction was 60 %. Grid control facilitates C-arm operation, since optimum image exposure can be obtained independently of object positioning. Object detection may lead to a reduction in radiation exposure for the patient and operating staff.

Modeling and design of a cone-beam CT head scanner using task-based imaging performance optimization

NASA Astrophysics Data System (ADS)

Xu, J.; Sisniega, A.; Zbijewski, W.; Dang, H.; Stayman, J. W.; Wang, X.; Foos, D. H.; Aygun, N.; Koliatsos, V. E.; Siewerdsen, J. H.

2016-04-01

Detection of acute intracranial hemorrhage (ICH) is important for diagnosis and treatment of traumatic brain injury, stroke, postoperative bleeding, and other head and neck injuries. This paper details the design and development of a cone-beam CT (CBCT) system developed specifically for the detection of low-contrast ICH in a form suitable for application at the point of care. Recognizing such a low-contrast imaging task to be a major challenge in CBCT, the system design began with a rigorous analysis of task-based detectability including critical aspects of system geometry, hardware configuration, and artifact correction. The imaging performance model described the three-dimensional (3D) noise-equivalent quanta using a cascaded systems model that included the effects of scatter, scatter correction, hardware considerations of complementary metal-oxide semiconductor (CMOS) and flat-panel detectors (FPDs), and digitization bit depth. The performance was analyzed with respect to a low-contrast (40-80 HU), medium-frequency task representing acute ICH detection. The task-based detectability index was computed using a non-prewhitening observer model. The optimization was performed with respect to four major design considerations: (1) system geometry (including source-to-detector distance (SDD) and source-to-axis distance (SAD)); (2) factors related to the x-ray source (including focal spot size, kVp, dose, and tube power); (3) scatter correction and selection of an antiscatter grid; and (4) x-ray detector configuration (including pixel size, additive electronics noise, field of view (FOV), and frame rate, including both CMOS and a-Si:H FPDs). Optimal design choices were also considered with respect to practical constraints and available hardware components. The model was verified in comparison to measurements on a CBCT imaging bench as a function of the numerous design parameters mentioned above. An extended geometry (SAD  =  750 mm, SDD  =  1100 mm) was found to be advantageous in terms of patient dose (20 mGy) and scatter reduction, while a more isocentric configuration (SAD  =  550 mm, SDD  =  1000 mm) was found to give a more compact and mechanically favorable configuration with minor tradeoff in detectability. An x-ray source with a 0.6 mm focal spot size provided the best compromise between spatial resolution requirements and x-ray tube power. Use of a modest anti-scatter grid (8:1 GR) at a 20 mGy dose provided slight improvement (~5-10%) in the detectability index, but the benefit was lost at reduced dose. The potential advantages of CMOS detectors over FPDs were quantified, showing that both detectors provided sufficient spatial resolution for ICH detection, while the former provided a potentially superior low-dose performance, and the latter provided the requisite FOV for volumetric imaging in a centered-detector geometry. Task-based imaging performance modeling provides an important starting point for CBCT system design, especially for the challenging task of ICH detection, which is somewhat beyond the capabilities of existing CBCT platforms. The model identifies important tradeoffs in system geometry and hardware configuration, and it supports the development of a dedicated CBCT system for point-of-care application. A prototype suitable for clinical studies is in development based on this analysis.

Microfluidics-based integrated airborne pathogen detection systems

NASA Astrophysics Data System (ADS)

Northrup, M. Allen; Alleman-Sposito, Jennifer; Austin, Todd; Devitt, Amy; Fong, Donna; Lin, Phil; Nakao, Brian; Pourahmadi, Farzad; Vinas, Mary; Yuan, Bob

2006-09-01

Microfluidic Systems is focused on building microfluidic platforms that interface front-end mesofluidics to handle real world sample volumes for optimal sensitivity coupled to microfluidic circuitry to process small liquid volumes for complex reagent metering, mixing, and biochemical analysis, particularly for pathogens. MFSI is the prime contractor on two programs for the US Department of Homeland Security: BAND (Bioagent Autonomous Networked Detector) and IBADS (Instantaneous Bio-Aerosol Detection System). The goal of BAND is to develop an autonomous system for monitoring the air for known biological agents. This consists of air collection, sample lysis, sample purification, detection of DNA, RNA, and toxins, and a networked interface to report the results. For IBADS, MFSI is developing the confirmatory device which must verify the presence of a pathogen with 5 minutes of an air collector/trigger sounding an alarm. Instrument designs and biological assay results from both BAND and IBADS will be presented.

Detection of bulk explosives using the GPR only portion of the HSTAMIDS system

NASA Astrophysics Data System (ADS)

Tabony, Joshua; Carlson, Douglas O.; Duvoisin, Herbert A., III; Torres-Rosario, Juan

2010-04-01

The legacy AN/PSS-14 (Army-Navy Portable Special Search-14) Handheld Mine Detecting Set (also called HSTAMIDS for Handheld Standoff Mine Detection System) has proven itself over the last 7 years as the state-of-the-art in land mine detection, both for the US Army and for Humanitarian Demining groups. Its dual GPR (Ground Penetrating Radar) and MD (Metal Detection) sensor has provided receiver operating characteristic curves (probability of detection or Pd versus false alarm rate or FAR) that routinely set the mark for such devices. Since its inception and type-classification in 2003 as the US (United States) Army standard, the desire for use of the AN/PSS-14 against alternate threats - such as bulk explosives - has recently become paramount. To this end, L-3 CyTerra has developed and tested bulk explosive detection and discrimination algorithms using only the Stepped Frequency Continuous Wave (SFCW) Ground Penetrating Radar (GPR) portion of the system, versus the fused version that is used to optimally detect land mines. Performance of the new bulk explosive algorithm against representative zero-metal bulk explosive target and clutter emplacements is depicted, with the utility to the operator also described.

Power-Aware Intrusion Detection in Mobile Ad Hoc Networks

NASA Astrophysics Data System (ADS)

Şen, Sevil; Clark, John A.; Tapiador, Juan E.

Mobile ad hoc networks (MANETs) are a highly promising new form of networking. However they are more vulnerable to attacks than wired networks. In addition, conventional intrusion detection systems (IDS) are ineffective and inefficient for highly dynamic and resource-constrained environments. Achieving an effective operational MANET requires tradeoffs to be made between functional and non-functional criteria. In this paper we show how Genetic Programming (GP) together with a Multi-Objective Evolutionary Algorithm (MOEA) can be used to synthesise intrusion detection programs that make optimal tradeoffs between security criteria and the power they consume.

Strategies and limitations for fluorescence detection of XAFS at high flux beamlines

DOE PAGES

Heald, Steve M.

2015-02-17

The issue of detecting the XAFS signal from dilute samples is discussed in detail with the aim of making best use of high flux beamlines that provide up to 10 13 photons -1. Various detection methods are compared, including filters with slits, solid state detectors, crystal analyzers and combinations of these. These comparisons rely on simulations that use experimentally determined parameters. It is found that inelastic scattering places a fundamental limit on detection, and that it is important to take proper account of the polarization dependence of the signals. The combination of a filter–slit system with a solid state detectormore » is a promising approach. With an optimized system good performance can be obtained even if the total count rate is limited to 10 7 Hz. Detection schemes with better energy resolution can help at the largest dilutions if their collection efficiency and count rate limits can be improved.« less

Strategies and limitations for fluorescence detection of XAFS at high flux beamlines

PubMed Central

Heald, Steve M.

2015-01-01

The issue of detecting the XAFS signal from dilute samples is discussed in detail with the aim of making best use of high flux beamlines that provide up to 1013 photons s−1. Various detection methods are compared, including filters with slits, solid state detectors, crystal analyzers and combinations of these. These comparisons rely on simulations that use experimentally determined parameters. It is found that inelastic scattering places a fundamental limit on detection, and that it is important to take proper account of the polarization dependence of the signals. The combination of a filter–slit system with a solid state detector is a promising approach. With an optimized system good performance can be obtained even if the total count rate is limited to 107 Hz. Detection schemes with better energy resolution can help at the largest dilutions if their collection efficiency and count rate limits can be improved. PMID:25723945

Optimization of an acoustic telemetry array for detecting transmitter-implanted fish

USGS Publications Warehouse

Clements, S.; Jepsen, D.; Karnowski, M.; Schreck, C.B.

2005-01-01

The development of miniature acoustic transmitters and economical, robust automated receivers has enabled researchers to study the movement patterns and survival of teleosts in estuarine and ocean environments, including many species and age-classes that were previously considered too small for implantation. During 2001-2003, we optimized a receiver mooring system to minimize gear and data loss in areas where current action or wave action and acoustic noise are high. In addition, we conducted extensive tests to determine (1) the performance of a transmitter and receiver (Vemco, Ltd.) that are widely used, particularly in North America and Europe and (2) the optimal placement of receivers for recording the passage of fish past a point in a linear-flow environment. Our results suggest that in most locations the mooring system performs well with little loss of data; however, boat traffic remains a concern due to entanglement with the mooring system. We also found that the reception efficiency of the receivers depends largely on the method and location of deployment. In many cases, we observed a range of 0-100% reception efficiency (the percentage of known transmissions that are detected while the receiver is within range of the transmitter) when using a conventional method of mooring. The efficiency was improved by removal of the mounting bar and obstructions from the mooring line. ?? Copyright by the American Fisheries Society 2005.

Investigating the feasibility of using partial least squares as a method of extracting salient information for the evaluation of digital breast tomosynthesis

NASA Astrophysics Data System (ADS)

Zhang, George Z.; Myers, Kyle J.; Park, Subok

2013-03-01

Digital breast tomosynthesis (DBT) has shown promise for improving the detection of breast cancer, but it has not yet been fully optimized due to a large space of system parameters to explore. A task-based statistical approach1 is a rigorous method for evaluating and optimizing this promising imaging technique with the use of optimal observers such as the Hotelling observer (HO). However, the high data dimensionality found in DBT has been the bottleneck for the use of a task-based approach in DBT evaluation. To reduce data dimensionality while extracting salient information for performing a given task, efficient channels have to be used for the HO. In the past few years, 2D Laguerre-Gauss (LG) channels, which are a complete basis for stationary backgrounds and rotationally symmetric signals, have been utilized for DBT evaluation2, 3 . But since background and signal statistics from DBT data are neither stationary nor rotationally symmetric, LG channels may not be efficient in providing reliable performance trends as a function of system parameters. Recently, partial least squares (PLS) has been shown to generate efficient channels for the Hotelling observer in detection tasks involving random backgrounds and signals.4 In this study, we investigate the use of PLS as a method for extracting salient information from DBT in order to better evaluate such systems.

Interlaced photoacoustic and ultrasound imaging system with real-time coregistration for ovarian tissue characterization

NASA Astrophysics Data System (ADS)

Alqasemi, Umar; Li, Hai; Yuan, Guangqian; Kumavor, Patrick; Zanganeh, Saeid; Zhu, Quing

2014-07-01

Coregistered ultrasound (US) and photoacoustic imaging are emerging techniques for mapping the echogenic anatomical structure of tissue and its corresponding optical absorption. We report a 128-channel imaging system with real-time coregistration of the two modalities, which provides up to 15 coregistered frames per second limited by the laser pulse repetition rate. In addition, the system integrates a compact transvaginal imaging probe with a custom-designed fiber optic assembly for in vivo detection and characterization of human ovarian tissue. We present the coregistered US and photoacoustic imaging system structure, the optimal design of the PC interfacing software, and the reconfigurable field programmable gate array operation and optimization. Phantom experiments of system lateral resolution and axial sensitivity evaluation, examples of the real-time scanning of a tumor-bearing mouse, and ex vivo human ovaries studies are demonstrated.

Developing an Automated Machine Learning Marine Oil Spill Detection System with Synthetic Aperture Radar

NASA Astrophysics Data System (ADS)

Pinales, J. C.; Graber, H. C.; Hargrove, J. T.; Caruso, M. J.

2016-02-01

Previous studies have demonstrated the ability to detect and classify marine hydrocarbon films with spaceborne synthetic aperture radar (SAR) imagery. The dampening effects of hydrocarbon discharges on small surface capillary-gravity waves renders the ocean surface "radar dark" compared with the standard wind-borne ocean surfaces. Given the scope and impact of events like the Deepwater Horizon oil spill, the need for improved, automated and expedient monitoring of hydrocarbon-related marine anomalies has become a pressing and complex issue for governments and the extraction industry. The research presented here describes the development, training, and utilization of an algorithm that detects marine oil spills in an automated, semi-supervised manner, utilizing X-, C-, or L-band SAR data as the primary input. Ancillary datasets include related radar-borne variables (incidence angle, etc.), environmental data (wind speed, etc.) and textural descriptors. Shapefiles produced by an experienced human-analyst served as targets (validation) during the training portion of the investigation. Training and testing datasets were chosen for development and assessment of algorithm effectiveness as well as optimal conditions for oil detection in SAR data. The algorithm detects oil spills by following a 3-step methodology: object detection, feature extraction, and classification. Previous oil spill detection and classification methodologies such as machine learning algorithms, artificial neural networks (ANN), and multivariate classification methods like partial least squares-discriminant analysis (PLS-DA) are evaluated and compared. Statistical, transform, and model-based image texture techniques, commonly used for object mapping directly or as inputs for more complex methodologies, are explored to determine optimal textures for an oil spill detection system. The influence of the ancillary variables is explored, with a particular focus on the role of strong vs. weak wind forcing.

Breath detection by transcutaneous electromyography of the diaphragm and the Graseby capsule in preterm infants.

PubMed

de Waal, Cornelia G; Kraaijenga, Juliette V; Hutten, Gerard J; de Jongh, Frans H; van Kaam, Anton H

2017-12-01

To compare triggering, breath detection and delay time of the Graseby capsule (GC) and transcutaneous electromyography of the diaphragm (dEMG) in spontaneous breathing preterm infants. In this observational study, a 30 minutes respiration measurement was conducted by respiratory inductance plethysmography (RIP), the GC, and dEMG in stable preterm infants. Triggering was investigated with an in vitro set-up using the Infant Flow ® SiPAP TM system. The possibility to optimize breath detection was tested by developing new algorithms with the abdominal RIP band (RIP AB ) as gold standard. In a subset of breaths, the delay time was calculated between the inspiratory onset in the RIP AB signal and in the GC and dEMG signal. Fifteen preterm infants with a mean gestational age of 28 ± 2 weeks and a mean birth weight of 1086 ± 317 g were included. In total, 14 773 breaths were analyzed. Based on the GC and dEMG signal, the Infant Flow ® SiPAP™ system, respectively, triggered 67.8% and 62.6% of the breaths. Breath detection was improved to 99.9% for the GC and 113.4% for dEMG in new algorithms. In 1492 stable breaths, the median delay time of inspiratory onset detection was +154 ms (IQR +118 to +164) in the GC and -50 ms (IQR -90 to -22) in the dEMG signal. Breath detection using the GC can be improved by optimizing the algorithm. Transcutaneous dEMG provides similar breath detection but with the advantage of detecting the onset of inspiration earlier than the GC. © 2017 Wiley Periodicals, Inc.

The effect of decentralized behavioral decision making on system-level risk.

PubMed

Kaivanto, Kim

2014-12-01

Certain classes of system-level risk depend partly on decentralized lay decision making. For instance, an organization's network security risk depends partly on its employees' responses to phishing attacks. On a larger scale, the risk within a financial system depends partly on households' responses to mortgage sales pitches. Behavioral economics shows that lay decisionmakers typically depart in systematic ways from the normative rationality of expected utility (EU), and instead display heuristics and biases as captured in the more descriptively accurate prospect theory (PT). In turn, psychological studies show that successful deception ploys eschew direct logical argumentation and instead employ peripheral-route persuasion, manipulation of visceral emotions, urgency, and familiar contextual cues. The detection of phishing emails and inappropriate mortgage contracts may be framed as a binary classification task. Signal detection theory (SDT) offers the standard normative solution, formulated as an optimal cutoff threshold, for distinguishing between good/bad emails or mortgages. In this article, we extend SDT behaviorally by rederiving the optimal cutoff threshold under PT. Furthermore, we incorporate the psychology of deception into determination of SDT's discriminability parameter. With the neo-additive probability weighting function, the optimal cutoff threshold under PT is rendered unique under well-behaved sampling distributions, tractable in computation, and transparent in interpretation. The PT-based cutoff threshold is (i) independent of loss aversion and (ii) more conservative than the classical SDT cutoff threshold. Independently of any possible misalignment between individual-level and system-level misclassification costs, decentralized behavioral decisionmakers are biased toward underdetection, and system-level risk is consequently greater than in analyses predicated upon normative rationality. © 2014 Society for Risk Analysis.

Optimization of mass spectrometry acquisition parameters for determination of polycarbonate additives, degradation products, and colorants migrating from food contact materials to chocolate.

PubMed

Bignardi, Chiara; Cavazza, Antonella; Laganà, Carmen; Salvadeo, Paola; Corradini, Claudio

2018-01-01

The interest towards "substances of emerging concerns" referred to objects intended to come into contact with food is recently growing. Such substances can be found in traces in simulants and in food products put in contact with plastic materials. In this context, it is important to set up analytical systems characterized by high sensitivity and to improve detection parameters to enhance signals. This work was aimed at optimizing a method based on UHPLC coupled to high resolution mass spectrometry to quantify the most common plastic additives, and able to detect the presence of polymers degradation products and coloring agents migrating from plastic re-usable containers. The optimization of mass spectrometric parameter settings for quantitative analysis of additives has been achieved by a chemometric approach, using a full factorial and d-optimal experimental designs, allowing to evaluate possible interactions between the investigated parameters. Results showed that the optimized method was characterized by improved features in terms of sensitivity respect to existing methods and was successfully applied to the analysis of a complex model food system such as chocolate put in contact with 14 polycarbonate tableware samples. A new procedure for sample pre-treatment was carried out and validated, showing high reliability. Results reported, for the first time, the presence of several molecules migrating to chocolate, in particular belonging to plastic additives, such Cyasorb UV5411, Tinuvin 234, Uvitex OB, and oligomers, whose amount was found to be correlated to age and degree of damage of the containers. Copyright © 2017 John Wiley & Sons, Ltd.

Analytical validation of BRAF mutation testing from circulating free DNA using the amplification refractory mutation testing system.

PubMed

Aung, Kyaw L; Donald, Emma; Ellison, Gillian; Bujac, Sarah; Fletcher, Lynn; Cantarini, Mireille; Brady, Ged; Orr, Maria; Clack, Glen; Ranson, Malcolm; Dive, Caroline; Hughes, Andrew

2014-05-01

BRAF mutation testing from circulating free DNA (cfDNA) using the amplification refractory mutation testing system (ARMS) holds potential as a surrogate for tumor mutation testing. Robust assay validation is needed to establish the optimal clinical matrix for measurement and cfDNA-specific mutation calling criteria. Plasma- and serum-derived cfDNA samples from 221 advanced melanoma patients were analyzed for BRAF c.1799T>A (p.V600E) mutation using ARMS in two stages in a blinded fashion. cfDNA-specific mutation calling criteria were defined in stage 1 and validated in stage 2. cfDNA concentrations in serum and plasma, and the sensitivities and specificities of BRAF mutation detection in these two clinical matrices were compared. Sensitivity of BRAF c.1799T>A (p.V600E) mutation detection in cfDNA was increased by using mutation calling criteria optimized for cfDNA (these criteria were adjusted from those used for archival tumor biopsies) without compromising specificity. Sensitivity of BRAF mutation detection in serum was 44% (95% CI, 35% to 53%) and in plasma 52% (95% CI, 43% to 61%). Specificity was 96% (95% CI, 90% to 99%) in both matrices. Serum contains significantly higher total cfDNA than plasma, whereas the proportion of tumor-derived mutant DNA was significantly higher in plasma. Using mutation calling criteria optimized for cfDNA improves sensitivity of BRAF c.1799T>A (p.V600E) mutation detection. The proportion of tumor-derived cfDNA in plasma was significantly higher than in serum. Copyright © 2014 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

2007 Beyond SBIR Phase II: Bringing Technology Edge to the Warfighter

DTIC Science & Technology

2007-08-23

Systems Trade-Off Analysis and Optimization Verification and Validation On-Board Diagnostics and Self - healing Security and Anti-Tampering Rapid...verification; Safety and reliability analysis of flight and mission critical systems On-Board Diagnostics and Self - Healing Model-based monitoring and... self - healing On-board diagnostics and self - healing ; Autonomic computing; Network intrusion detection and prevention Anti-Tampering and Trust

Automated grading, upgrading, and cuttings prediction of surfaced dry hardwood lumber

Treesearch

Sang-Mook Lee; Phil Araman; A.Lynn Abbott; Matthew F. Winn

2010-01-01

This paper concerns the scanning, sawing, and grading of kiln-dried hardwood lumber. A prototype system is described that uses laser sources and a video camera to scan boards. The system automatically detects defects and wane, searches for optimal sawing solutions, and then estimates the grades of the boards that would result. The goal is to derive maximum commercial...

Control systems and coordination protocols of the secretory pathway.

PubMed

Luini, Alberto; Mavelli, Gabriella; Jung, Juan; Cancino, Jorge

2014-01-01

Like other cellular modules, the secretory pathway and the Golgi complex are likely to be supervised by control systems that support homeostasis and optimal functionality under all conditions, including external and internal perturbations. Moreover, the secretory apparatus must be functionally connected with other cellular modules, such as energy metabolism and protein degradation, via specific rules of interaction, or "coordination protocols". These regulatory devices are of fundamental importance for optimal function; however, they are generally "hidden" at steady state. The molecular components and the architecture of the control systems and coordination protocols of the secretory pathway are beginning to emerge through studies based on the use of controlled transport-specific perturbations aimed specifically at the detection and analysis of these internal regulatory devices.

Development of glucose measurement system based on pulsed laser-induced ultrasonic method

NASA Astrophysics Data System (ADS)

Ren, Zhong; Wan, Bin; Liu, Guodong; Xiong, Zhihua

2016-09-01

In this study, a kind of glucose measurement system based on pulsed-induced ultrasonic technique was established. In this system, the lateral detection mode was used, the Nd: YAG pumped optical parametric oscillator (OPO) pulsed laser was used as the excitation source, the high sensitivity ultrasonic transducer was used as the signal detector to capture the photoacoustic signals of the glucose. In the experiments, the real-time photoacoustic signals of glucose aqueous solutions with different concentrations were captured by ultrasonic transducer and digital oscilloscope. Moreover, the photoacoustic peak-to-peak values were gotten in the wavelength range from 1300nm to 2300nm. The characteristic absorption wavelengths of glucose were determined via the difference spectral method and second derivative method. In addition, the prediction models of predicting glucose concentrations were established via the multivariable linear regression algorithm and the optimal prediction model of corresponding optimal wavelengths. Results showed that the performance of the glucose system based on the pulsed-induced ultrasonic detection method was feasible. Therefore, the measurement scheme and prediction model have some potential value in the fields of non-invasive monitoring the concentration of the glucose gradient, especially in the food safety and biomedical fields.

Zika virus RNA polymerase chain reaction on the utility channel of a commercial nucleic acid testing system.

PubMed

Boujnan, Mohamed; Duits, Ashley J; Koppelman, Marco H G M

2018-03-01

Several countries have implemented safety strategies to reduce the risk of Zika virus (ZIKV) transmission through blood transfusion. These strategies have included nucleic acid amplification testing (NAT) of blood donations. In this study, a new real-time polymerase chain reaction (PCR) assay including internal control for the detection of ZIKV on the cobas omni Utility Channel (UC) on the cobas 6800 system is presented. PCR conditions and primer/probe concentrations were optimized on the LightCycler 480 instrument. Optimized conditions were transferred to the cobas omni UC on the cobas 6800 system. Subsequently, the limit of detection (LOD) in plasma and urine, genotype inclusivity, specificity, cross-reactivity, and clinical sensitivity were determined. The 95% LOD of the ZIKV PCR assay on the cobas 6800 system was 23.0 IU/mL (95% confidence interval [CI], 16.5-37.5) in plasma and 24.5 IU/mL (95% CI, 13.4-92.9) in urine. The assay detected African and Asian lineages of ZIKV. The specificity was 100%. The clinical concordance between the newly developed ZIKV PCR assay and the investigational Roche cobas Zika NAT test was 83% (24/29). We developed a sensitive ZIKV PCR assay on the cobas omni UC on the cobas 6800 system. The assay can be used for large-scale screening of blood donations for ZIKV or for testing of blood donors returning from areas with ZIKV to avoid temporal deferral. This study also demonstrates that the cobas omni UC on the cobas 6800 system can be used for in-house-developed PCR assays. © 2018 AABB.

Fault Detection and Diagnosis System for the Air-conditioning

NASA Astrophysics Data System (ADS)

Nakahara, Nobuo

The fault detection and diagnosis system, the FDD system, for the HVAC was initiated around the middle of 1970s in Japan but it still remains at the elementary stage. The HVAC is really one of the most complicated and large scaled system for the FDD system. Besides, the maintenance engineering was never focussed as the target of the academic study since after the war, but the FDD system for some kinds of the components and subsystems has been developed for the sake of the practical industrial needs. Recently, international cooperative study in the IEA Annex 25 on the energy conservation for the building and community targetted on the BOFD, the building optimization, fault detection and diagnosis. Not a few academic peaple from various engineering field got interested and, moreover, some national projects seem to start in the European countries. The author has reviewed the state of the art of the FDD and BO as well based on the references and the experience at the IEA study.

A Control Allocation System for Automatic Detection and Compensation of Phase Shift Due to Actuator Rate Limiting

NASA Technical Reports Server (NTRS)

Yildiz, Yidiray; Kolmanovsky, Ilya V.; Acosta, Diana

2011-01-01

This paper proposes a control allocation system that can detect and compensate the phase shift between the desired and the actual total control effort due to rate limiting of the actuators. Phase shifting is an important problem in control system applications since it effectively introduces a time delay which may destabilize the closed loop dynamics. A relevant example comes from flight control where aggressive pilot commands, high gain of the flight control system or some anomaly in the system may cause actuator rate limiting and effective time delay introduction. This time delay can instigate Pilot Induced Oscillations (PIO), which is an abnormal coupling between the pilot and the aircraft resulting in unintentional and undesired oscillations. The proposed control allocation system reduces the effective time delay by first detecting the phase shift and then minimizing it using constrained optimization techniques. Flight control simulation results for an unstable aircraft with inertial cross coupling are reported, which demonstrate phase shift minimization and recovery from a PIO event.

Analytical redundancy and the design of robust failure detection systems

NASA Technical Reports Server (NTRS)

Chow, E. Y.; Willsky, A. S.

1984-01-01

The Failure Detection and Identification (FDI) process is viewed as consisting of two stages: residual generation and decision making. It is argued that a robust FDI system can be achieved by designing a robust residual generation process. Analytical redundancy, the basis for residual generation, is characterized in terms of a parity space. Using the concept of parity relations, residuals can be generated in a number of ways and the design of a robust residual generation process can be formulated as a minimax optimization problem. An example is included to illustrate this design methodology. Previously announcedd in STAR as N83-20653

A high-fidelity airbus benchmark for system fault detection and isolation and flight control law clearance

NASA Astrophysics Data System (ADS)

Goupil, Ph.; Puyou, G.

2013-12-01

This paper presents a high-fidelity generic twin engine civil aircraft model developed by Airbus for advanced flight control system research. The main features of this benchmark are described to make the reader aware of the model complexity and representativeness. It is a complete representation including the nonlinear rigid-body aircraft model with a full set of control surfaces, actuator models, sensor models, flight control laws (FCL), and pilot inputs. Two applications of this benchmark in the framework of European projects are presented: FCL clearance using optimization and advanced fault detection and diagnosis (FDD).

Optimized Lateral Flow Immunoassay Reader for the Detection of Infectious Diseases in Developing Countries.

PubMed

Pilavaki, Evdokia; Demosthenous, Andreas

2017-11-20

Detection and control of infectious diseases is a major problem, especially in developing countries. Lateral flow immunoassays can be used with great success for the detection of infectious diseases. However, for the quantification of their results an electronic reader is required. This paper presents an optimized handheld electronic reader for developing countries. It features a potentially low-cost, low-power, battery-operated device with no added optical accessories. The operation of this proof of concept device is based on measuring the reflected light from the lateral flow immunoassay and translating it into the concentration of the specific analyte of interest. Characterization of the surface of the lateral flow immunoassay has been performed in order to accurately model its response to the incident light. Ray trace simulations have been performed to optimize the system and achieve maximum sensitivity by placing all the components in optimum positions. A microcontroller enables all the signal processing to be performed on the device and a Bluetooth module allows transmission of the results wirelessly to a mobile phone app. Its performance has been validated using lateral flow immunoassays with influenza A nucleoprotein in the concentration range of 0.5 ng/mL to 200 ng/mL.

Nonlinear optimization-based device-free localization with outlier link rejection.

PubMed

Xiao, Wendong; Song, Biao; Yu, Xiting; Chen, Peiyuan

2015-04-07

Device-free localization (DFL) is an emerging wireless technique for estimating the location of target that does not have any attached electronic device. It has found extensive use in Smart City applications such as healthcare at home and hospitals, location-based services at smart spaces, city emergency response and infrastructure security. In DFL, wireless devices are used as sensors that can sense the target by transmitting and receiving wireless signals collaboratively. Many DFL systems are implemented based on received signal strength (RSS) measurements and the location of the target is estimated by detecting the changes of the RSS measurements of the wireless links. Due to the uncertainty of the wireless channel, certain links may be seriously polluted and result in erroneous detection. In this paper, we propose a novel nonlinear optimization approach with outlier link rejection (NOOLR) for RSS-based DFL. It consists of three key strategies, including: (1) affected link identification by differential RSS detection; (2) outlier link rejection via geometrical positional relationship among links; (3) target location estimation by formulating and solving a nonlinear optimization problem. Experimental results demonstrate that NOOLR is robust to the fluctuation of the wireless signals with superior localization accuracy compared with the existing Radio Tomographic Imaging (RTI) approach.

Using evolutionary computation to optimize an SVM used in detecting buried objects in FLIR imagery

NASA Astrophysics Data System (ADS)

Paino, Alex; Popescu, Mihail; Keller, James M.; Stone, Kevin

2013-06-01

In this paper we describe an approach for optimizing the parameters of a Support Vector Machine (SVM) as part of an algorithm used to detect buried objects in forward looking infrared (FLIR) imagery captured by a camera installed on a moving vehicle. The overall algorithm consists of a spot-finding procedure (to look for potential targets) followed by the extraction of several features from the neighborhood of each spot. The features include local binary pattern (LBP) and histogram of oriented gradients (HOG) as these are good at detecting texture classes. Finally, we project and sum each hit into UTM space along with its confidence value (obtained from the SVM), producing a confidence map for ROC analysis. In this work, we use an Evolutionary Computation Algorithm (ECA) to optimize various parameters involved in the system, such as the combination of features used, parameters on the Canny edge detector, the SVM kernel, and various HOG and LBP parameters. To validate our approach, we compare results obtained from an SVM using parameters obtained through our ECA technique with those previously selected by hand through several iterations of "guess and check".

The Assessment of Liver Reserve Function by Spectrophotometry based on Determination of Phenacetin and Paracetamol.

PubMed

Ren, Rui; Ma, Yongmei; Ma, Wanshan; Lu, Sumei

2015-01-01

To establish a technical system for assessing liver reserve function based on spectrophotometry by detection of phenacetin and paracetamol in blood samples. Taking detected contents of phenacetin and paracetamol by high performance liquid chromatography (HPLC) as standard, which was proved to be able to detect drug concentrations with high resolution and accuracy, we established a technical system based on the spectrophotometric technique to assay phenacetin and paracetamol, including the color system, the maximum absorption wavelength, the influence factors of color system, and the optimal conditions for hydrolysis. Then we verified our established system compared with that under HPLC by recovery test. This study established a technical system to detect phenacetin and paracetamol in blood samples using spectrophotometry. Mainly, 3 mol/L hydrochloric acid (HCl) was added to samples for hydrolysis for 30 minutes, then, adding 0.02% 1,2-naphthoquinone-4-sulfonate (NQS), 1% cetyltrimethyl ammonium bromide (CTA) and 2% sodium hydroxide (or 3% sodium carbonate) (ratio of 1:6:1:2 or 3), and the absorbance was measured at 500 nm and 570 nm to calculate their concentrations. Using an established spectrophotometric system to detect phenacetin and paracetamol in blood samples could assess liver reserve function, which was proved comparable with HPLC in resolution and repeatability.

Optimization of the performance of the polymerase chain reaction in silicon-based microstructures.

PubMed Central

Taylor, T B; Winn-Deen, E S; Picozza, E; Woudenberg, T M; Albin, M

1997-01-01

We have demonstrated the ability to perform real-time homogeneous, sequence specific detection of PCR products in silicon microstructures. Optimal design/ processing result in equivalent performance (yield and specificity) for high surface-to-volume silicon structures as compared to larger volume reactions in polypropylene tubes. Amplifications in volumes as small as 0.5 microl and thermal cycling times reduced as much as 5-fold from that of conventional systems have been demonstrated for the microstructures. PMID:9224619

Estimation of an Optimal Stimulus Amplitude for Using Vestibular Stochastic Stimulation to Improve Balance Function

NASA Technical Reports Server (NTRS)

Goel, R.; Kofman, I.; DeDios, Y. E.; Jeevarajan, J.; Stepanyan, V.; Nair, M.; Congdon, S.; Fregia, M.; Peters, B.; Cohen, H.;

Pseudorange Measurement Method Based on AIS Signals.

PubMed

Zhang, Jingbo; Zhang, Shufang; Wang, Jinpeng

2017-05-22

In order to use the existing automatic identification system (AIS) to provide additional navigation and positioning services, a complete pseudorange measurements solution is presented in this paper. Through the mathematical analysis of the AIS signal, the bit-0-phases in the digital sequences were determined as the timestamps. Monte Carlo simulation was carried out to compare the accuracy of the zero-crossing and differential peak, which are two timestamp detection methods in the additive white Gaussian noise (AWGN) channel. Considering the low-speed and low-dynamic motion characteristics of ships, an optimal estimation method based on the minimum mean square error is proposed to improve detection accuracy. Furthermore, the α difference filter algorithm was used to achieve the fusion of the optimal estimation results of the two detection methods. The results show that the algorithm can greatly improve the accuracy of pseudorange estimation under low signal-to-noise ratio (SNR) conditions. In order to verify the effectiveness of the scheme, prototypes containing the measurement scheme were developed and field tests in Xinghai Bay of Dalian (China) were performed. The test results show that the pseudorange measurement accuracy was better than 28 m (σ) without any modification of the existing AIS system.

Pseudorange Measurement Method Based on AIS Signals

PubMed Central

Zhang, Jingbo; Zhang, Shufang; Wang, Jinpeng

2017-01-01

In order to use the existing automatic identification system (AIS) to provide additional navigation and positioning services, a complete pseudorange measurements solution is presented in this paper. Through the mathematical analysis of the AIS signal, the bit-0-phases in the digital sequences were determined as the timestamps. Monte Carlo simulation was carried out to compare the accuracy of the zero-crossing and differential peak, which are two timestamp detection methods in the additive white Gaussian noise (AWGN) channel. Considering the low-speed and low-dynamic motion characteristics of ships, an optimal estimation method based on the minimum mean square error is proposed to improve detection accuracy. Furthermore, the α difference filter algorithm was used to achieve the fusion of the optimal estimation results of the two detection methods. The results show that the algorithm can greatly improve the accuracy of pseudorange estimation under low signal-to-noise ratio (SNR) conditions. In order to verify the effectiveness of the scheme, prototypes containing the measurement scheme were developed and field tests in Xinghai Bay of Dalian (China) were performed. The test results show that the pseudorange measurement accuracy was better than 28 m (σ) without any modification of the existing AIS system. PMID:28531153

Development of the disable software reporting system on the basis of the neural network

NASA Astrophysics Data System (ADS)

Gavrylenko, S.; Babenko, O.; Ignatova, E.

2018-04-01

The PE structure of malicious and secure software is analyzed, features are highlighted, binary sign vectors are obtained and used as inputs for training the neural network. A software model for detecting malware based on the ART-1 neural network was developed, optimal similarity coefficients were found, and testing was performed. The obtained research results showed the possibility of using the developed system of identifying malicious software in computer systems protection systems

Photooxidation of 3-substituted pyrroles:  a postcolumn reaction detection system for singlet molecular oxygen in HPLC.

PubMed

Denham, K; Milofsky, R E

1998-10-01

A postcolumn photochemical reaction detection scheme, based on the reaction of 3-substituted pyrroles with singlet molecular oxygen ((1)O(2)), has been developed. The method is selective and sensitive for the determination of a class of organic compounds called (1)O(2)-sensitizers and is readily coupled to HPLC. Following separation by HPLC, analytes ((1)O(2)-sensitizers) are excited by a Hg pen-ray lamp. Analytes that are efficient (1)O(2)-sensitizers promote ground-state O(2) ((3)Σ(g)(-)) to an excited state ((1)Σ(g)(+) or (1)Δ(g)), which reacts rapidly with tert-butyl-3,4,5-trimethylpyrrolecarboxylate (BTMPC) or N-benzyl-3-methoxypyrrole-2-tert-carboxylate (BMPC), which is added to the mobile phase. Detection is based on the loss of pyrrole (BTMPC or BMPC). The reaction is catalytic in nature since one analyte molecule may absorb light many times, producing large amounts of (1)O(2). Detection limits for several (1)O(2)-sensitizers were improved by 1-2 orders of magnitude over optimized UV-absorbance detection. This paper discusses the optimization of the reaction conditions for this photochemical reaction detection scheme and its application to the detection of PCBs, nitrogen heterocycles, nitro and chloro aromatics, and other substituted aromatic compounds.

Comparison of detection techniques for capillary electrophoresis analysis of gold nanoparticles.

PubMed

Matczuk, Magdalena; Aleksenko, Svetlana S; Matysik, Frank-Michael; Jarosz, Maciej; Timerbaev, Andrei R

2015-05-01

As metallic nanoparticles are growing in importance as analytes in CE, increases an interest in appropriate detection methods for their quantification in various samples. For gold nanoparticles (AuNPs), the most common UV detection poses intricacy of inadequate sensitivity that hinders the applicability of CE. With the objective of resolving this challenge, UV detection was compared with C(4) D and ICP-MS as alternative modes of detection for AuNPs. A C(4) D detector, applied under pressure-driven conditions, exhibited better sensitivity than a UV detector. However, C(4) D turned to be unsatisfactory to differentiate the signal of AuNPs at common CE conditions despite varying the nature of BGE and detection conditions. Due to intrinsic sensitivity and low background levels typical to Au, ICP-MS greatly surpasses UV detection. After optimization trials, CE-ICP-MS gained the LOD of AuNPs as low as 2 × 10(-15) M, as well as an excellent performance in terms of signal stability and linearity. Also importantly, the optimized BGE appears to be well matched to explore the behavior of AuNPs in biologically relevant systems. This was demonstrated by probing the interaction between AuNPs and the main blood-transporting protein, HSA. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

NASA Tech Briefs, April 2009

NASA Technical Reports Server (NTRS)

2009-01-01

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

Disposable pen-shaped capillary gel electrophoresis cartridge for fluorescence detection of bio-molecules

NASA Astrophysics Data System (ADS)

Amirkhanian, Varoujan; Tsai, Shou-Kuan

2014-03-01

We introduce a novel and cost-effective capillary gel electrophoresis (CGE) system utilizing disposable pen-shaped gelcartridges for highly efficient, high speed, high throughput fluorescence detection of bio-molecules. The CGE system has been integrated with dual excitation and emission optical-fibers with micro-ball end design for fluorescence detection of bio-molecules separated and detected in a disposable pen-shaped capillary gel electrophoresis cartridge. The high-performance capillary gel electrophoresis (CGE) analyzer has been optimized for glycoprotein analysis type applications. Using commercially available labeling agent such as ANTS (8-aminonapthalene-1,3,6- trisulfonate) as an indicator, the capillary gel electrophoresis-based glycan analyzer provides high detection sensitivity and high resolving power in 2-5 minutes of separations. The system can hold total of 96 samples, which can be automatically analyzed within 4-5 hours. This affordable fiber optic based fluorescence detection system provides fast run times (4 minutes vs. 20 minutes with other CE systems), provides improved peak resolution, good linear dynamic range and reproducible migration times, that can be used in laboratories for high speed glycan (N-glycan) profiling applications. The CGE-based glycan analyzer will significantly increase the pace at which glycoprotein research is performed in the labs, saving hours of preparation time and assuring accurate, consistent and economical results.

Simultaneous fault detection and control design for switched systems with two quantized signals.

PubMed

Li, Jian; Park, Ju H; Ye, Dan

2017-01-01

The problem of simultaneous fault detection and control design for switched systems with two quantized signals is presented in this paper. Dynamic quantizers are employed, respectively, before the output is passed to fault detector, and before the control input is transmitted to the switched system. Taking the quantized errors into account, the robust performance for this kind of system is given. Furthermore, sufficient conditions for the existence of fault detector/controller are presented in the framework of linear matrix inequalities, and fault detector/controller gains and the supremum of quantizer range are derived by a convex optimized method. Finally, two illustrative examples demonstrate the effectiveness of the proposed method. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

MIMO-OFDM signal optimization for SAR imaging radar

NASA Astrophysics Data System (ADS)

Baudais, J.-Y.; Méric, S.; Riché, V.; Pottier, É.

2016-12-01

This paper investigates the optimization of the coded orthogonal frequency division multiplexing (OFDM) transmitted signal in a synthetic aperture radar (SAR) context. We propose to design OFDM signals to achieve range ambiguity mitigation. Indeed, range ambiguities are well known to be a limitation for SAR systems which operates with pulsed transmitted signal. The ambiguous reflected signal corresponding to one pulse is then detected when the radar has already transmitted the next pulse. In this paper, we demonstrate that the range ambiguity mitigation is possible by using orthogonal transmitted wave as OFDM pulses. The coded OFDM signal is optimized through genetic optimization procedures based on radar image quality parameters. Moreover, we propose to design a multiple-input multiple-output (MIMO) configuration to enhance the noise robustness of a radar system and this configuration is mainly efficient in the case of using orthogonal waves as OFDM pulses. The results we obtain show that OFDM signals outperform conventional radar chirps for range ambiguity suppression and for robustness enhancement in 2 ×2 MIMO configuration.

Analysis of power management and system latency in wireless sensor networks

NASA Astrophysics Data System (ADS)

Oswald, Matthew T.; Rohwer, Judd A.; Forman, Michael A.

2004-08-01

Successful power management in a wireless sensor network requires optimization of the protocols which affect energy-consumption on each node and the aggregate effects across the larger network. System optimization for a given deployment scenario requires an analysis and trade off of desired node and network features with their associated costs. The sleep protocol for an energy-efficient wireless sensor network for event detection, target classification, and target tracking developed at Sandia National Laboratories is presented. The dynamic source routing (DSR) algorithm is chosen to reduce network maintenance overhead, while providing a self-configuring and self-healing network architecture. A method for determining the optimal sleep time is developed and presented, providing reference data which spans several orders of magnitude. Message timing diagrams show, that a node in a five-node cluster, employing an optimal cyclic single-radio sleep protocol, consumes 3% more energy and incurs a 16-s increase latency than nodes employing the more complex dual-radio STEM protocol.

OPAD-EDIFIS Real-Time Processing

NASA Technical Reports Server (NTRS)

Katsinis, Constantine

1997-01-01

The Optical Plume Anomaly Detection (OPAD) detects engine hardware degradation of flight vehicles through identification and quantification of elemental species found in the plume by analyzing the plume emission spectra in a real-time mode. Real-time performance of OPAD relies on extensive software which must report metal amounts in the plume faster than once every 0.5 sec. OPAD software previously written by NASA scientists performed most necessary functions at speeds which were far below what is needed for real-time operation. The research presented in this report improved the execution speed of the software by optimizing the code without changing the algorithms and converting it into a parallelized form which is executed in a shared-memory multiprocessor system. The resulting code was subjected to extensive timing analysis. The report also provides suggestions for further performance improvement by (1) identifying areas of algorithm optimization, (2) recommending commercially available multiprocessor architectures and operating systems to support real-time execution and (3) presenting an initial study of fault-tolerance requirements.

Sensitive Adsorptive Voltammetric Method for Determination of Bisphenol A by Gold Nanoparticle/Polyvinylpyrrolidone-Modified Pencil Graphite Electrode

PubMed Central

Yaman, Yesim Tugce; Abaci, Serdar

2016-01-01

A novel electrochemical sensor gold nanoparticle (AuNP)/polyvinylpyrrolidone (PVP) modified pencil graphite electrode (PGE) was developed for the ultrasensitive determination of Bisphenol A (BPA). The gold nanoparticles were electrodeposited by constant potential electrolysis and PVP was attached by passive adsorption onto the electrode surface. The electrode surfaces were characterized by electrochemical impedance spectroscopy (EIS) and scanning electron microscopy (SEM). The parameters that affected the experimental conditions were researched and optimized. The AuNP/PVP/PGE sensor provided high sensitivity and selectivity for BPA recognition by using square wave adsorptive stripping voltammetry (SWAdSV). Under optimized conditions, the detection limit was found to be 1.0 nM. This new sensor system offered the advantages of simple fabrication which aided the expeditious replication, low cost, fast response, high sensitivity and low background current for BPA. This new sensor system was successfully tested for the detection of the amount of BPA in bottled drinking water with high reliability. PMID:27231912

Optical filtering in directly modulated/detected OOFDM systems.

PubMed

Sánchez, C; Ortega, B; Wei, J L; Capmany, J

2013-12-16

This work presents a theoretical investigation on the performance of directly modulated/detected (DM/DD) optical orthogonal frequency division multiplexed (OOFDM) systems subject to optical filtering. The impact of both linear and nonlinear distortion effects are taken into account to calculate the effective signal-to-noise ratio of each subcarrier. These results are then employed to optimize the design parameters of two simple optical filtering structures: a Mach Zehnder interferometer and a uniform fiber Bragg grating, leading to a significant optical power budget improvement given by 3.3 and 3dB, respectively. These can be further increased to 5.5 and 4.2dB respectively when balanced detection configurations are employed. We find as well that this improvement is highly dependent on the clipping ratio.

Multi-sensor millimeter-wave system for hidden objects detection by non-collaborative screening

NASA Astrophysics Data System (ADS)

Zouaoui, Rhalem; Czarny, Romain; Diaz, Frédéric; Khy, Antoine; Lamarque, Thierry

2011-05-01

In this work, we present the development of a multi-sensor system for the detection of objects concealed under clothes using passive and active millimeter-wave (mmW) technologies. This study concerns both the optimization of a commercial passive mmW imager at 94 GHz using a phase mask and the development of an active mmW detector at 77 GHz based on synthetic aperture radar (SAR). A first wide-field inspection is done by the passive imager while the person is walking. If a suspicious area is detected, the active imager is switched-on and focused on this area in order to obtain more accurate data (shape of the object, nature of the material ...).

Deflection angle detecting system for the large-angle and high-linearity fast steering mirror using quadrant detector

NASA Astrophysics Data System (ADS)

Ni, Yingxue; Wu, Jiabin; San, Xiaogang; Gao, Shijie; Ding, Shaohang; Wang, Jing; Wang, Tao

2018-02-01

A deflection angle detecting system (DADS) using a quadrant detector (QD) is developed to achieve the large deflection angle and high linearity for the fast steering mirror (FSM). The mathematical model of the DADS is established by analyzing the principle of position detecting and error characteristics of the QD. Based on this mathematical model, the method of optimizing deflection angle and linearity of FSM is demonstrated, which is proved feasible by simulation and experimental results. Finally, a QD-based FSM is designed and tested. The results show that it achieves 0.72% nonlinearity, ±2.0 deg deflection angle, and 1.11-μrad resolution. Therefore, the application of this method will be beneficial to design the FSM.

Capillary electrophoresis-electrochemistry microfluidic system for the determination of organic peroxides

NASA Technical Reports Server (NTRS)

Wang, Joseph; Escarpa, Alberto; Pumera, Martin; Feldman, Jason; Svehla, D. (Principal Investigator)

2002-01-01

A microfluidic analytical system for the separation and detection of organic peroxides, based on a microchip capillary electrophoresis device with an integrated amperometric detector, was developed. The new microsystem relies on the reductive detection of both organic acid peroxides and hydroperoxides at -700 mV (vs. Ag wire/AgCl). Factors influencing the separation and detection processes were examined and optimized. The integrated microsystem offers rapid measurements (within 130 s) of these organic-peroxide compounds, down to micromolar levels. A highly stable response for repetitive injections (RSD 0.35-3.12%; n = 12) reflects the negligible electrode passivation. Such a "lab-on-a-chip" device should be attractive for on-site analysis of organic peroxides, as desired for environmental screening and industrial monitoring.

Contrast based band selection for optimized weathered oil detection in hyperspectral images

NASA Astrophysics Data System (ADS)

Levaux, Florian; Bostater, Charles R., Jr.; Neyt, Xavier

2012-09-01

Hyperspectral imagery offers unique benefits for detection of land and water features due to the information contained in reflectance signatures such as the bi-directional reflectance distribution function or BRDF. The reflectance signature directly shows the relative absorption and backscattering features of targets. These features can be very useful in shoreline monitoring or surveillance applications, for example to detect weathered oil. In real-time detection applications, processing of hyperspectral data can be an important tool and Optimal band selection is thus important in real time applications in order to select the essential bands using the absorption and backscatter information. In the present paper, band selection is based upon the optimization of target detection using contrast algorithms. The common definition of the contrast (using only one band out of all possible combinations available within a hyperspectral image) is generalized in order to consider all the possible combinations of wavelength dependent contrasts using hyperspectral images. The inflection (defined here as an approximation of the second derivative) is also used in order to enhance the variations in the reflectance spectra as well as in the contrast spectrua in order to assist in optimal band selection. The results of the selection in term of target detection (false alarms and missed detection) are also compared with a previous method to perform feature detection, namely the matched filter. In this paper, imagery is acquired using a pushbroom hyperspectral sensor mounted at the bow of a small vessel. The sensor is mechanically rotated using an optical rotation stage. This opto-mechanical scanning system produces hyperspectral images with pixel sizes on the order of mm to cm scales, depending upon the distance between the sensor and the shoreline being monitored. The motion of the platform during the acquisition induces distortions in the collected HSI imagery. It is therefore necessary to apply a motion correction to the imagery. In this paper, imagery is corrected for the pitching motion of a vessel, which causes most of the deformation when the vessel is anchored at 2 points (bow and stern) during the acquisition of the hyperspectral imagry.

The symbiosis of photometry and radial-velocity measurements

NASA Technical Reports Server (NTRS)

Cochran, William D.

1994-01-01

The FRESIP mission is optimized to detect the inner planets of a planetary system. According to the current paradigm of planet formation, these planets will probably be small Earth-sized objects. Ground-based radial-velocity programs now have the sensitivity to detect Jovian-mass planets in orbit around bright solar-type stars. We expect the more massive planets to form in the outer regions of a proto-stellar nebula. These two types of measurements will very nicely complement each other, as they have highest detection probability for very different types of planets. The combination of FRESIP photometry and ground-based spectra will provide independent confirmation of the existence of planetary systems in orbit around other stars. Such detection of both terrestrial and Jovian planets in orbit around the same star is essential to test our understanding of planet formation.

Method and system for detecting a failure or performance degradation in a dynamic system such as a flight vehicle

NASA Technical Reports Server (NTRS)

Miller, Robert H. (Inventor); Ribbens, William B. (Inventor)

2003-01-01

A method and system for detecting a failure or performance degradation in a dynamic system having sensors for measuring state variables and providing corresponding output signals in response to one or more system input signals are provided. The method includes calculating estimated gains of a filter and selecting an appropriate linear model for processing the output signals based on the input signals. The step of calculating utilizes one or more models of the dynamic system to obtain estimated signals. The method further includes calculating output error residuals based on the output signals and the estimated signals. The method also includes detecting one or more hypothesized failures or performance degradations of a component or subsystem of the dynamic system based on the error residuals. The step of calculating the estimated values is performed optimally with respect to one or more of: noise, uncertainty of parameters of the models and un-modeled dynamics of the dynamic system which may be a flight vehicle or financial market or modeled financial system.

A practical and highly sensitive C3N4-TYR fluorescent probe for convenient detection of dopamine

NASA Astrophysics Data System (ADS)

Li, Hao; Yang, Manman; Liu, Juan; Zhang, Yalin; Yang, Yanmei; Huang, Hui; Liu, Yang; Kang, Zhenhui

2015-07-01

The C3N4-tyrosinase (TYR) hybrid is a highly accurate, sensitive and simple fluorescent probe for the detection of dopamine (DOPA). Under optimized conditions, the relative fluorescence intensity of C3N4-TYR is proportional to the DOPA concentration in the range from 1 × 10-3 to 3 × 10-8 mol L-1 with a correlation coefficient of 0.995. In the present system, the detection limit achieved is as low as 3 × 10-8 mol L-1. Notably, these quantitative detection results for clinical samples are comparable to those of high performance liquid chromatography. Moreover, the enzyme-encapsulated C3N4 sensing arrays on both glass slide and test paper were evaluated, which revealed sensitive detection and excellent stability. The results reported here provide a new approach for the design of a multifunctional nanosensor for the detection of bio-molecules.The C3N4-tyrosinase (TYR) hybrid is a highly accurate, sensitive and simple fluorescent probe for the detection of dopamine (DOPA). Under optimized conditions, the relative fluorescence intensity of C3N4-TYR is proportional to the DOPA concentration in the range from 1 × 10-3 to 3 × 10-8 mol L-1 with a correlation coefficient of 0.995. In the present system, the detection limit achieved is as low as 3 × 10-8 mol L-1. Notably, these quantitative detection results for clinical samples are comparable to those of high performance liquid chromatography. Moreover, the enzyme-encapsulated C3N4 sensing arrays on both glass slide and test paper were evaluated, which revealed sensitive detection and excellent stability. The results reported here provide a new approach for the design of a multifunctional nanosensor for the detection of bio-molecules. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr03316k

Human body motion tracking based on quantum-inspired immune cloning algorithm

NASA Astrophysics Data System (ADS)

Han, Hong; Yue, Lichuan; Jiao, Licheng; Wu, Xing

2009-10-01

In a static monocular camera system, to gain a perfect 3D human body posture is a great challenge for Computer Vision technology now. This paper presented human postures recognition from video sequences using the Quantum-Inspired Immune Cloning Algorithm (QICA). The algorithm included three parts. Firstly, prior knowledge of human beings was used, the key joint points of human could be detected automatically from the human contours and skeletons which could be thinning from the contours; And due to the complexity of human movement, a forecasting mechanism of occlusion joint points was addressed to get optimum 2D key joint points of human body; And then pose estimation recovered by optimizing between the 2D projection of 3D human key joint points and 2D detection key joint points using QICA, which recovered the movement of human body perfectly, because this algorithm could acquire not only the global optimal solution, but the local optimal solution.

Active Correction of Aperture Discontinuities-Optimized Stroke Minimization. II. Optimization for Future Missions

NASA Astrophysics Data System (ADS)

Mazoyer, J.; Pueyo, L.; N'Diaye, M.; Fogarty, K.; Zimmerman, N.; Soummer, R.; Shaklan, S.; Norman, C.

2018-01-01

High-contrast imaging and spectroscopy provide unique constraints for exoplanet formation models as well as for planetary atmosphere models. Instrumentation techniques in this field have greatly improved over the last two decades, with the development of stellar coronagraphy, in parallel with specific methods of wavefront sensing and control. Next generation space- and ground-based telescopes will enable the characterization of cold solar-system-like planets for the first time and maybe even in situ detection of bio-markers. However, the growth of primary mirror diameters, necessary for these detections, comes with an increase of their complexity (segmentation, secondary mirror features). These discontinuities in the aperture can greatly limit the performance of coronagraphic instruments. In this context, we introduced a new technique, Active Correction of Aperture Discontinuities-Optimized Stroke Minimization (ACAD-OSM), to correct for the diffractive effects of aperture discontinuities in the final image plane of a coronagraph, using deformable mirrors. In this paper, we present several tools that can be used to optimize the performance of this technique for its application to future large missions. In particular, we analyzed the influence of the deformable setup (size and separating distance) and found that there is an optimal point for this setup, optimizing the performance of the instrument in contrast and throughput while minimizing the strokes applied to the deformable mirrors. These results will help us design future coronagraphic instruments to obtain the best performance.

Dual-balanced detection scheme with optical hard-limiters in an optical code division multiple access system

NASA Astrophysics Data System (ADS)

Liu, Maw-Yang; Hsu, Yi-Kai

2017-03-01

Three-arm dual-balanced detection scheme is studied in an optical code division multiple access system. As the MAI and beat noise are the main deleterious source of system performance, we utilize optical hard-limiters to alleviate such channel impairment. In addition, once the channel condition is improved effectively, the proposed two-dimensional error correction code can remarkably enhance the system performance. In our proposed scheme, the optimal thresholds of optical hard-limiters and decision circuitry are fixed, and they will not change with other system parameters. Our proposed scheme can accommodate a large number of users simultaneously and is suitable for burst traffic with asynchronous transmission. Therefore, it is highly recommended as the platform for broadband optical access network.

Optical sensing: recognition elements and devices

NASA Astrophysics Data System (ADS)

Gauglitz, Guenter G.

2012-09-01

The requirements in chemical and biochemical sensing with respect to recognition elements, avoiding non-specific interactions, and high loading of the surface for detection of low concentrations as well as optimized detection systems are discussed. Among the many detection principles the optical techniques are classified. Methods using labeled compounds like Total Internal Reflection Fluorescence (TIRF) and direct optical methods like micro reflectometry or refractometry are discussed in comparison. Reflectometric Interference Spectroscopy (RIfS) is presented as a robust simple method for biosensing. As applications, trace analysis of endocrine disruptors in water, hormones in food, detection of viruses and bacteria in food and clinical diagnostics are discussed.

Science simulations for the New Worlds Observer

NASA Astrophysics Data System (ADS)

Schindhelm, Eric; Cash, Webster; Seager, Sara

2005-08-01

The New Worlds Observer, currently studied under a NASA Institute for Advanced Concepts grant, will be a pinhole camera in space designed to directly detect and study extrasolar terrestrial planets. An apodized occultor or pinhole creates an image of the planetary system in the focal plane far away, where a second telescope craft orbits to detect the light. In this study we simulate the expected signal of NWO to find the optimal configuration and specifications of the two craft. The efficiency of direct detection through photometric imaging depends strongly on occulter and telescope size, while preliminary studies on absorption biomarker detection and photometric variability measurements are summarized.

A test strip platform based on DNA-functionalized gold nanoparticles for on-site detection of mercury (II) ions.

PubMed

Guo, Zhiyong; Duan, Jing; Yang, Fei; Li, Min; Hao, Tingting; Wang, Sui; Wei, Danyi

2012-05-15

A test strip, based on DNA-functionalized gold nanoparticles for Hg(2+) detection, has been developed, optimized and validated. The developed colorimetric mercury sensor system exhibited a highly sensitive and selective response to mercury. The measurement principle is based on thymine-Hg(2+)-thymine (T-Hg(2+)-T) coordination chemistry and streptavidin-biotin interaction. A biotin-labeled and thiolated DNA was immobilized on the gold nanoparticles (AuNPs) surface through a self-assembling method. Another thymine-rich DNA, which was introduced to form DNA duplexes on the AuNPs surface with thymine-Hg(2+)-thymine (T-Hg(2+)-T) coordination in the presence of Hg(2+), was immobilized on the nitrocellulose membrane as the test zone. When Hg(2+) ions were introduced into this system, they induced the two strands of DNA to intertwist by forming T-Hg(2+)-T bonds resulting in a red line at the test zone. The biotin-labeled and thiolated DNA-functionalized AuNPs could be captured by streptavidin which was immobilized on the nitrocellulose membrane as the control zone. Under optimized conditions, the detection limit for Hg(2+) was 3 nM, which is lower than the 10nM, maximum contaminant limit defined by the US Environmental Protection Agency (EPA) for drinking water. A parallel analysis of Hg(2+) in pool water samples using cold vapor atomic absorption spectrometry showed comparable results to those obtained from the strip test. Therefore, the results obtained in this study could be used as basic research for the development of Hg(2+) detection, and the method developed could be a potential on-site screening tool for the rapid detection of Hg(2+) in different water samples without special instrumentation. All experimental variables that influence the test strip response were optimized and reported. Copyright © 2012 Elsevier B.V. All rights reserved.

High voltage spark carbon fiber detection system

NASA Technical Reports Server (NTRS)

Yang, L. C.

1980-01-01

The pulse discharge technique was used to determine the length and density of carbon fibers released from fiber composite materials during a fire or aircraft accident. Specifications are given for the system which uses the ability of a carbon fiber to initiate spark discharge across a high voltage biased grid to achieve accurate counting and sizing of fibers. The design of the system was optimized, and prototype hardware proved satisfactory in laboratory and field tests.

River water quality analysis via headspace detection of volatile organic compounds

NASA Astrophysics Data System (ADS)

Tang, Johnny Jock Lee; Nishi, Phyllis Jacqueline; Chong, Gabriel Eng Wee; Wong, Martin Gideon; Chua, Hong Siang; Persaud, Krishna; Ng, Sing Muk

2017-03-01

Human civilization has intensified the interaction between the community and the environment. This increases the threat on the environm ent for being over exploited and contaminated with m anmade products and synthetic chemicals. Of all, clean water is one of the resources that can be easily contaminated since it is a universal solvent and of high mobility. This work reports the development and optimization of a water quality monitoring system based on metal oxide sensors. The system is intended to a ssist the detection of volatile organic compounds (VOCs) present in water sources online and onsite. The sampling mechanism was based on contactless mode, where headspace partial pressure of the VOCs formed above the water body in a close chamber was drawn for detection at the sensor platform. Pure toluene was used as standard to represent the broad spectrum of VOCs, and the sensor dynamic range was achieved from 1-1000 ppb. Several sensing parameters such as sampling time, headspace volume, and sensor recovery were s tudied and optimized. Besides direct detection of VOC contaminants in the water, the work has also been extended to detect VOCs produced by microbial communities and to c orrelate the size of the communities with the reading of V OCs recorded. This can serve to give b etter indication of water quality, not only on the conce ntration of VOCs c ontamination from chemicals, but also the content of microbes, which some can have severe effect on human health.

Accuracy assessment and characterization of x-ray coded aperture coherent scatter spectral imaging for breast cancer classification

PubMed Central

Lakshmanan, Manu N.; Greenberg, Joel A.; Samei, Ehsan; Kapadia, Anuj J.

2017-01-01

Abstract. Although transmission-based x-ray imaging is the most commonly used imaging approach for breast cancer detection, it exhibits false negative rates higher than 15%. To improve cancer detection accuracy, x-ray coherent scatter computed tomography (CSCT) has been explored to potentially detect cancer with greater consistency. However, the 10-min scan duration of CSCT limits its possible clinical applications. The coded aperture coherent scatter spectral imaging (CACSSI) technique has been shown to reduce scan time through enabling single-angle imaging while providing high detection accuracy. Here, we use Monte Carlo simulations to test analytical optimization studies of the CACSSI technique, specifically for detecting cancer in ex vivo breast samples. An anthropomorphic breast tissue phantom was modeled, a CACSSI imaging system was virtually simulated to image the phantom, a diagnostic voxel classification algorithm was applied to all reconstructed voxels in the phantom, and receiver-operator characteristics analysis of the voxel classification was used to evaluate and characterize the imaging system for a range of parameters that have been optimized in a prior analytical study. The results indicate that CACSSI is able to identify the distribution of cancerous and healthy tissues (i.e., fibroglandular, adipose, or a mix of the two) in tissue samples with a cancerous voxel identification area-under-the-curve of 0.94 through a scan lasting less than 10 s per slice. These results show that coded aperture scatter imaging has the potential to provide scatter images that automatically differentiate cancerous and healthy tissue within ex vivo samples. Furthermore, the results indicate potential CACSSI imaging system configurations for implementation in subsequent imaging development studies. PMID:28331884

A four parameter optimization and troubleshooting of a RPLC - charged aerosol detection stability indicating method for determination of S-lysophosphatidylcholines in a phospholipid formulation.

PubMed

Tam, James; Ahmad, Imad A Haidar; Blasko, Andrei

2018-06-05

A four parameter optimization of a stability indicating method for non-chromophoric degradation products of 1,2-distearoyl-sn-glycero-3-phosphocholine (DSPC), 1-stearoyl-sn-glycero-3-phosphocholine and 2-stearoyl-sn-glycero-3-phosphocholine was achieved using a reverse phase liquid chromatography-charged aerosol detection (RPLC-CAD) technique. Using the hydrophobic subtraction model of selectivity, a core-shell, polar embedded RPLC column was selected followed by gradient-temperature optimization, resulting in ideal relative peak placements for a robust, stability indicating separation. The CAD instrument parameters, power function value (PFV) and evaporator temperature were optimized for lysophosphatidylcholines to give UV absorbance detector-like linearity performance within a defined concentration range. The two lysophosphatidylcholines gave the same response factor in the selected conditions. System specific power function values needed to be set for the two RPLC-CAD instruments used. A custom flow-divert profile, sending only a portion of the column effluent to the detector, was necessary to mitigate detector response drifting effects. The importance of the PFV optimization for each instrument of identical build and how to overcome recovery issues brought on by the matrix effects from the lipid-RP stationary phase interaction is reported. Copyright © 2018 Elsevier B.V. All rights reserved.

Fabrication and characterization of a chemically oxidized-nanostructured porous silicon based biosensor implementing orienting protein A.

PubMed

Naveas, Nelson; Hernandez-Montelongo, Jacobo; Pulido, Ruth; Torres-Costa, Vicente; Villanueva-Guerrero, Raúl; Predestinación García Ruiz, Josefa; Manso-Silván, Miguel

2014-03-01

Nanostructured porous silicon (PSi) elicits as a very attractive material for future biosensing systems due to its high surface area, biocompatibility and well-established fabrication methods. In order to engineer its performance as a biosensor transducer platform, the density of immunoglobulins properly immobilized and oriented onto the surface needs to be optimized. In this work we fabricated and characterized a novel biosensing system focusing on the improvement of the biofunctionalization cascade. The system consists on a chemically oxidized PSi platform derivatized with 3-aminopropyltriethoxysilane (APTS) that is coupled to Staphylococcus protein A (SpA). The chemical oxidation has previously demonstrated to enhance the biofunctionalization process and here "by implementing SpA" a molecularly oriented immunosensor is achieved. The biosensor system is characterized in terms of its chemical composition, wettability and optical reflectance. Finally, this system is successfully exploited to develop a biosensor for detecting asymmetric dimethylarginine (ADMA), an endogenous molecule involved in cardiovascular diseases. Therefore, this work is relevant from the point of view of design and optimization of the biomolecular immobilization cascade on PSi surfaces with the added value of contribution to the development of new assays for detecting ADMA with a view on prevention of cardiovascular diseases. Copyright © 2013 Elsevier B.V. All rights reserved.

Dual-energy in mammography: feasibility study

NASA Astrophysics Data System (ADS)

Jafroudi, Hamid; Lo, Shih-Chung B.; Li, Huai; Steller Artz, Dorothy E.; Freedman, Matthew T.; Mun, Seong K.

1996-04-01

The purpose of this work is to examine the feasibility of dual-energy techniques to enhance the detection of microcalcifications in digital mammography. The digital mammography system used in this study consists of two different mammography systems; one is the conventional mammography system with molybdenum target and Mo filtration and the other is the clinical version of a low dose x-ray system with tungsten target and aluminum filtration. The low dose system is optimized for screen-film mammography with a highly efficient scatter rejection device built by Fischer Imaging Systems for evaluation at NIH. The system was designed by the University of Southern California based on multiparameter optimization techniques. Prototypes of this system have been constructed and evaluated at the Center for Devices and Radiological Health. The digital radiography system is based on the Fuji 9000 computed radiography (CR) system which uses a storage phosphor imaging plate as the receptor. High resolution plates (HR-V) are used in this study. Dual-energy is one technique to reduce the structured noise associated with the complexity of the background of normal anatomy surrounding a lesion. This can be done by taking the advantage of the x-ray attenuation characteristics of two different structures such as soft tissue and bone in chest radiography. We have applied this technique to the detection of microcalcifications in mammography. The overall system performance based on this technique is evaluated. Results presented are based on the evaluation of phantom images.

Colorimetric detection of melamine in milk by using gold nanoparticles-based LSPR via optical fibers

PubMed Central

Chang, Keke; Wang, Shun; Zhang, Hao; Guo, Qingqian; Hu, Xinran; Lin, Zhili; Sun, Haifeng; Jiang, Min

2017-01-01

A biosensing system with optical fibers is proposed for the colorimetric detection of melamine in liquid milk samples by using the localized surface plasmon resonance (LSPR) of unmodified gold nanoparticles (AuNPs). The biosensing system consists of a broadband light source that covers the spectral range from 200 nm to 1700 nm, an optical attenuator, three types of 600 μm premium optical fibers with SMA905 connectors and a miniature spectrometer with a linear charge coupled device (CCD) array. The biosensing system with optical fibers is low-cost, simple and is well-proven for the detection of melamine. Its working principle is based on the color changes of AuNPs solution from wine-red to blue due to the inter-particle coupling effect that causes the shifts of wavelength and absorbance in LSPR band after the to-be-measured melamine samples were added. Under the optimized conditions, the detection response of the LSPR biosensing system was found to be linear in melamine detection in the concentration range from 0μM to 0.9 μM with a correlation coefficient (R2) 0.99 and a detection limit 33 nM. The experimental results obtained from the established LSPR biosensing system in the actual detection of melamine concentration in liquid milk samples show that this technique is highly specific and sensitive and would have a huge application prospects. PMID:28475597

Design and Optimization of a Dual-HPGe Gamma Spectrometer and Its Cosmic Veto System

NASA Astrophysics Data System (ADS)

Zhang, Weihua; Ro, Hyunje; Liu, Chuanlei; Hoffman, Ian; Ungar, Kurt

2017-03-01

In this paper, a dual high purity germanium (HPGe) gamma spectrometer detection system with an increased solid angle was developed. The detection system consists of a pair of Broad Energy Germanium (BE-5030p) detectors and an XIA LLC digital gamma finder/Pixie-4 data-acquisition system. A data file processor was developed containing five modules that parses Pixie-4 list-mode data output files and classifies detections into anticoincident/coincident events and their specific coincidence types (double/triple/quadruple) for further analysis. A novel cosmic veto system was installed in the detection system. It was designed to be easy to install around an existing system while still providing sufficient cosmic veto shielding comparable to other designs. This paper describes the coverage and efficiency of this cosmic veto and the data processing system. It has been demonstrated that the cosmic veto system can provide a mean background reduction of 66.1%, which results in a mean MDA improvement of 58.3%. The counting time to meet the required MDA for specific radionuclide can be reduced by a factor of 2-3 compared to those using a conventional HPGe system. This paper also provides an initial overview of coincidence timing distributions between an incoming event from a cosmic veto plate and HPGe detector.

Research of the chemiluminescence detection apparatus for nutrients

NASA Astrophysics Data System (ADS)

Xu, Xiaoyi; Wang, Yu; Ni, Xuxiang; Yan, Huimin

2016-10-01

The multifunctional nutrition analyzer, which integrates four detection functions, can make fast, accurate, quantitative analysis for a variety of nutrients. In this article we focus on researching the luminescence detection system. Compared with other means, luminescence detection needs no excitation light, and the detection sensitivity is improved due to the reduction of the background light. The apparatus consists of an displacement platform, a microporous plate, a combination of an aspheric lens and a plano-convex lens, an optical fiber and a photon counter connected with a computer. A theoretical light intensity formula is established as a reference and a comparison of the experimental data. In the experiment we applies ATP detection reagent as the experimental reagent, whose magnitudes of concentration are from 10-6 mol/L to 10-12 mol/L. The sensitivity of the apparatus could reach a magnitude of concentration of 0.1nmol/L, and it is estimated to be further improved by at least two magnitudes in theory with the system and the reagent optimized.

Gain and power optimization of the wireless optical system with multilevel modulation.

PubMed

Liu, Xian

2008-06-01

When used in an outdoor environment to expedite networking access, the performance of wireless optical communication systems is affected by transmitter sway. In the design of such systems, much attention has been paid to developing power-efficient schemes. However, the bandwidth efficiency is also an important issue. One of the most natural approaches to promote bandwidth efficiency is to use multilevel modulation. This leads to multilevel pulse amplitude modulation in the context of intensity modulation and direct detection. We develop a model based on the four-level pulse amplitude modulation. We show that the model can be formulated as an optimization problem in terms of the transmitter power, bit error probability, transmitter gain, and receiver gain. The technical challenges raised by modeling and solving the problem include the analytical and numerical treatments for the improper integrals of the Gaussian functions coupled with the erfc function. The results demonstrate that, at the optimal points, the power penalty paid to the doubled bandwidth efficiency is around 3 dB.

Response surface optimized peroxyoxalate chemiluminescence of octahydro-Schiff base derivative as new luminophor and study of the quenching effect of some cations, amino acids and cholesterol.

PubMed

Yeganeh Faal, Ali; Jamalyan, Bahare; Bordbar, Maryam; Shayeste, Tavakol Heidary; Salavati-Niasari, Masoud

2014-12-01

We report the first detailed study of the characteristics of an octahydro-Schiff base derivative as a new luminophor in the peroxyoxalate chemiluminescence (POCL) system. The effect of reagents on this new POCL system was investigated. In addition, the response surface methodology was used for evaluating the relative significance of variables in this POCL system, establishing models and determining optimal conditions. The quenching effect of some cations and compounds such as Cu(2+), Fe(3+), Hg(2+), imidazole, histidine and cholesterol on an optimized POCL reaction were studied. The dynamic ranges were up to approximaterly 100 and 175 × 10(-6) M for Cu(2+) and cholesterol respectively. The detection limits were 3.3 × 10(-6) m and 2.58 × 10(-6) m for Cu(2+) and histidine, respectively. In all cases the relative standard deviations were 4-5% (n = 4). Copyright © 2014 John Wiley & Sons, Ltd.

Deterministic Reconfigurable Control Design for the X-33 Vehicle

NASA Technical Reports Server (NTRS)

Wagner, Elaine A.; Burken, John J.; Hanson, Curtis E.; Wohletz, Jerry M.

1998-01-01

In the event of a control surface failure, the purpose of a reconfigurable control system is to redistribute the control effort among the remaining working surfaces such that satisfactory stability and performance are retained. Four reconfigurable control design methods were investigated for the X-33 vehicle: Redistributed Pseudo-Inverse, General Constrained Optimization, Automated Failure Dependent Gain Schedule, and an Off-line Nonlinear General Constrained Optimization. The Off-line Nonlinear General Constrained Optimization approach was chosen for implementation on the X-33. Two example failures are shown, a right outboard elevon jam at 25 deg. at a Mach 3 entry condition, and a left rudder jam at 30 degrees. Note however, that reconfigurable control laws have been designed for the entire flight envelope. Comparisons between responses with the nominal controller and reconfigurable controllers show the benefits of reconfiguration. Single jam aerosurface failures were considered, and failure detection and identification is considered accomplished in the actuator controller. The X-33 flight control system will incorporate reconfigurable flight control in the baseline system.

An automatic system to detect and extract texts in medical images for de-identification

NASA Astrophysics Data System (ADS)

Zhu, Yingxuan; Singh, P. D.; Siddiqui, Khan; Gillam, Michael

2010-03-01

Recently, there is an increasing need to share medical images for research purpose. In order to respect and preserve patient privacy, most of the medical images are de-identified with protected health information (PHI) before research sharing. Since manual de-identification is time-consuming and tedious, so an automatic de-identification system is necessary and helpful for the doctors to remove text from medical images. A lot of papers have been written about algorithms of text detection and extraction, however, little has been applied to de-identification of medical images. Since the de-identification system is designed for end-users, it should be effective, accurate and fast. This paper proposes an automatic system to detect and extract text from medical images for de-identification purposes, while keeping the anatomic structures intact. First, considering the text have a remarkable contrast with the background, a region variance based algorithm is used to detect the text regions. In post processing, geometric constraints are applied to the detected text regions to eliminate over-segmentation, e.g., lines and anatomic structures. After that, a region based level set method is used to extract text from the detected text regions. A GUI for the prototype application of the text detection and extraction system is implemented, which shows that our method can detect most of the text in the images. Experimental results validate that our method can detect and extract text in medical images with a 99% recall rate. Future research of this system includes algorithm improvement, performance evaluation, and computation optimization.

Detection of buried magnetic objects by a SQUID gradiometer system

NASA Astrophysics Data System (ADS)

Meyer, Hans-Georg; Hartung, Konrad; Linzen, Sven; Schneider, Michael; Stolz, Ronny; Fried, Wolfgang; Hauspurg, Sebastian

2009-05-01

We present a magnetic detection system based on superconducting gradiometric sensors (SQUID gradiometers). The system provides a unique fast mapping of large areas with a high resolution of the magnetic field gradient as well as the local position. A main part of this work is the localization and classification of magnetic objects in the ground by automatic interpretation of geomagnetic field gradients, measured by the SQUID system. In accordance with specific features the field is decomposed into segments, which allow inferences to possible objects in the ground. The global consideration of object describing properties and their optimization using error minimization methods allows the reconstruction of superimposed features and detection of buried objects. The analysis system of measured geomagnetic fields works fully automatically. By a given surface of area-measured gradients the algorithm determines within numerical limits the absolute position of objects including depth with sub-pixel accuracy and allows an arbitrary position and attitude of sources. Several SQUID gradiometer data sets were used to show the applicability of the analysis algorithm.

Research on the system performance evaluation of minimum-shift keying in uplink ground-to-satellite with gamma-gamma distribution

NASA Astrophysics Data System (ADS)

Wang, Yi; Zhang, Ao; Ma, Jing

2017-07-01

Minimum-shift keying (MSK) has the advantages of constant envelope, continuous phase, and high spectral efficiency, and it is applied in radio communication and optical fiber communication. MSK modulation of coherent detection is proposed in the ground-to-satellite laser communication system; in addition, considering the inherent noise of uplink, such as intensity scintillation and beam wander, the communication performance of the MSK modulation system with coherent detection is studied in the uplink ground-to-satellite laser. Based on the gamma-gamma channel model, the closed form of bit error rate (BER) of MSK modulation with coherent detection is derived. In weak, medium, and strong turbulence, the BER performance of the MSK modulation system is simulated and analyzed. To meet the requirements of the ground-to-satellite coherent MSK system to optimize the parameters and configuration of the transmitter and receiver, the influence of the beam divergence angle, the zenith angle, the transmitter beam radius, and the receiver diameter are studied.

High-performance dual-energy imaging with a flat-panel detector: imaging physics from blackboard to benchtop to bedside

NASA Astrophysics Data System (ADS)

Siewerdsen, J. H.; Shkumat, N. A.; Dhanantwari, A. C.; Williams, D. B.; Richard, S.; Daly, M. J.; Paul, N. S.; Moseley, D. J.; Jaffray, D. A.; Yorkston, J.; Van Metter, R.

2006-03-01

The application of high-performance flat-panel detectors (FPDs) to dual-energy (DE) imaging offers the potential for dramatically improved detection and characterization of subtle lesions through reduction of "anatomical noise," with applications ranging from thoracic imaging to image-guided interventions. In this work, we investigate DE imaging performance from first principles of image science to preclinical implementation, including: 1.) generalized task-based formulation of NEQ and detectability as a guide to system optimization; 2.) measurements of imaging performance on a DE imaging benchtop; and 3.) a preclinical system developed in our laboratory for cardiac-gated DE chest imaging in a research cohort of 160 patients. Theoretical and benchtop studies directly guide clinical implementation, including the advantages of double-shot versus single-shot DE imaging, the value of differential added filtration between low- and high-kVp projections, and optimal selection of kVp pairs, filtration, and dose allocation. Evaluation of task-based NEQ indicates that the detectability of subtle lung nodules in double-shot DE imaging can exceed that of single-shot DE imaging by a factor of 4 or greater. Filter materials are investigated that not only harden the high-kVp beam (e.g., Cu or Ag) but also soften the low-kVp beam (e.g., Ce or Gd), leading to significantly increased contrast in DE images. A preclinical imaging system suitable for human studies has been constructed based upon insights gained from these theoretical and experimental studies. An important component of the system is a simple and robust means of cardiac-gated DE image acquisition, implemented here using a fingertip pulse oximeter. Timing schemes that provide cardiac-gated image acquisition on the same or successive heartbeats is described. Preclinical DE images to be acquired under research protocol will afford valuable testing of optimal deployment, facilitate the development of DE CAD, and support comparison of DE diagnostic imaging performance to low-dose CT and radiography.

Effect of parameters in moving average method for event detection enhancement using phase sensitive OTDR

NASA Astrophysics Data System (ADS)

Kwon, Yong-Seok; Naeem, Khurram; Jeon, Min Yong; Kwon, Il-bum

2017-04-01

We analyze the relations of parameters in moving average method to enhance the event detectability of phase sensitive optical time domain reflectometer (OTDR). If the external events have unique frequency of vibration, then the control parameters of moving average method should be optimized in order to detect these events efficiently. A phase sensitive OTDR was implemented by a pulsed light source, which is composed of a laser diode, a semiconductor optical amplifier, an erbium-doped fiber amplifier, a fiber Bragg grating filter, and a light receiving part, which has a photo-detector and high speed data acquisition system. The moving average method is operated with the control parameters: total number of raw traces, M, number of averaged traces, N, and step size of moving, n. The raw traces are obtained by the phase sensitive OTDR with sound signals generated by a speaker. Using these trace data, the relation of the control parameters is analyzed. In the result, if the event signal has one frequency, then the optimal values of N, n are existed to detect the event efficiently.

Detection of caffeine in tea, instant coffee, green tea beverage, and soft drink by direct analysis in real time (DART) source coupled to single-quadrupole mass spectrometry.

PubMed

Wang, Lei; Zhao, Pengyue; Zhang, Fengzu; Bai, Aijuan; Pan, Canping

2013-01-01

Ambient ionization direct analysis in real time (DART) coupled to single-quadrupole MS (DART-MS) was evaluated for rapid detection of caffeine in commercial samples without chromatographic separation or sample preparation. Four commercial samples were examined: tea, instant coffee, green tea beverage, and soft drink. The response-related parameters were optimized for the DART temperature and MS fragmentor. Under optimal conditions, the molecular ion (M+H)+ was the major ion for identification of caffeine. The results showed that DART-MS is a promising tool for the quick analysis of important marker molecules in commercial samples. Furthermore, this system has demonstrated significant potential for high sample throughput and real-time analysis.

Automated Detection of Sepsis Using Electronic Medical Record Data: A Systematic Review.

PubMed

Despins, Laurel A

Severe sepsis and septic shock are global issues with high mortality rates. Early recognition and intervention are essential to optimize patient outcomes. Automated detection using electronic medical record (EMR) data can assist this process. This review describes automated sepsis detection using EMR data. PubMed retrieved publications between January 1, 2005 and January 31, 2015. Thirteen studies met study criteria: described an automated detection approach with the potential to detect sepsis or sepsis-related deterioration in real or near-real time; focused on emergency department and hospitalized neonatal, pediatric, or adult patients; and provided performance measures or results indicating the impact of automated sepsis detection. Detection algorithms incorporated systemic inflammatory response and organ dysfunction criteria. Systems in nine studies generated study or care team alerts. Care team alerts did not consistently lead to earlier interventions. Earlier interventions did not consistently translate to improved patient outcomes. Performance measures were inconsistent. Automated sepsis detection is potentially a means to enable early sepsis-related therapy but current performance variability highlights the need for further research.

360 degree vision system: opportunities in transportation

NASA Astrophysics Data System (ADS)

Thibault, Simon

2007-09-01

Panoramic technologies are experiencing new and exciting opportunities in the transportation industries. The advantages of panoramic imagers are numerous: increased areas coverage with fewer cameras, imaging of multiple target simultaneously, instantaneous full horizon detection, easier integration of various applications on the same imager and others. This paper reports our work on panomorph optics and potential usage in transportation applications. The novel panomorph lens is a new type of high resolution panoramic imager perfectly suitable for the transportation industries. The panomorph lens uses optimization techniques to improve the performance of a customized optical system for specific applications. By adding a custom angle to pixel relation at the optical design stage, the optical system provides an ideal image coverage which is designed to reduce and optimize the processing. The optics can be customized for the visible, near infra-red (NIR) or infra-red (IR) wavebands. The panomorph lens is designed to optimize the cost per pixel which is particularly important in the IR. We discuss the use of the 360 vision system which can enhance on board collision avoidance systems, intelligent cruise controls and parking assistance. 360 panoramic vision systems might enable safer highways and significant reduction in casualties.

Polarization for Background Reduction in EDXRF - The Technique That Would Not Work

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

Ryon, R W

2002-07-24

As with all electromagnet radiation, polarization of x-rays is a general phenomenon. Such polarization has been known since the classic experiments of Barkla in 1906. The general implementation of polarization to x-ray analysis had to await the fixed geometry of energy-dispersive systems. The means of optimizing these systems is shown in this review paper. Improved detection limits are the result.

Using Machine Learning in Adversarial Environments.

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

Warren Leon Davis

Intrusion/anomaly detection systems are among the first lines of cyber defense. Commonly, they either use signatures or machine learning (ML) to identify threats, but fail to account for sophisticated attackers trying to circumvent them. We propose to embed machine learning within a game theoretic framework that performs adversarial modeling, develops methods for optimizing operational response based on ML, and integrates the resulting optimization codebase into the existing ML infrastructure developed by the Hybrid LDRD. Our approach addresses three key shortcomings of ML in adversarial settings: 1) resulting classifiers are typically deterministic and, therefore, easy to reverse engineer; 2) ML approachesmore » only address the prediction problem, but do not prescribe how one should operationalize predictions, nor account for operational costs and constraints; and 3) ML approaches do not model attackers’ response and can be circumvented by sophisticated adversaries. The principal novelty of our approach is to construct an optimization framework that blends ML, operational considerations, and a model predicting attackers reaction, with the goal of computing optimal moving target defense. One important challenge is to construct a realistic model of an adversary that is tractable, yet realistic. We aim to advance the science of attacker modeling by considering game-theoretic methods, and by engaging experimental subjects with red teaming experience in trying to actively circumvent an intrusion detection system, and learning a predictive model of such circumvention activities. In addition, we will generate metrics to test that a particular model of an adversary is consistent with available data.« less

Debris mapping sensor technology project summary: Technology flight experiments program area of the space platforms technology program

NASA Technical Reports Server (NTRS)

1991-01-01

The topics presented are covered in viewgraph form. Programmatic objectives are: (1) to improve characterization of the orbital debris environment; and (2) to provide a passive sensor test bed for debris collision detection systems. Technical objectives are: (1) to study LEO debris altitude, size and temperature distribution down to 1 mm particles; (2) to quantify ground based radar and optical data ambiguities; and (3) to optimize debris detection strategies.

Optimally Robust Redundancy Relations for Failure Detection in Uncertain Systems,

DTIC Science & Technology

1983-04-01

particular applications. While the general methods provide the basis for what in principle should be a widely applicable failure detection methodology...modifications to this result which overcome them at no fundmental increase in complexity. 4.1 Scaling A critical problem with the criteria of the preceding...criterion which takes scaling into account L 2 s[ (45) As in (38), we can multiply the C. by positive scalars to take into account unequal weightings on

Root Exploit Detection and Features Optimization: Mobile Device and Blockchain Based Medical Data Management.

PubMed

Firdaus, Ahmad; Anuar, Nor Badrul; Razak, Mohd Faizal Ab; Hashem, Ibrahim Abaker Targio; Bachok, Syafiq; Sangaiah, Arun Kumar

2018-05-04

The increasing demand for Android mobile devices and blockchain has motivated malware creators to develop mobile malware to compromise the blockchain. Although the blockchain is secure, attackers have managed to gain access into the blockchain as legal users, thereby comprising important and crucial information. Examples of mobile malware include root exploit, botnets, and Trojans and root exploit is one of the most dangerous malware. It compromises the operating system kernel in order to gain root privileges which are then used by attackers to bypass the security mechanisms, to gain complete control of the operating system, to install other possible types of malware to the devices, and finally, to steal victims' private keys linked to the blockchain. For the purpose of maximizing the security of the blockchain-based medical data management (BMDM), it is crucial to investigate the novel features and approaches contained in root exploit malware. This study proposes to use the bio-inspired method of practical swarm optimization (PSO) which automatically select the exclusive features that contain the novel android debug bridge (ADB). This study also adopts boosting (adaboost, realadaboost, logitboost, and multiboost) to enhance the machine learning prediction that detects unknown root exploit, and scrutinized three categories of features including (1) system command, (2) directory path and (3) code-based. The evaluation gathered from this study suggests a marked accuracy value of 93% with Logitboost in the simulation. Logitboost also helped to predicted all the root exploit samples in our developed system, the root exploit detection system (RODS).

Evaluation of three fully automated immunoassay systems for detection of IgA anti-beta 2-glycoprotein I antibodies.

PubMed

Pérez, D; Martínez-Flores, J A; Serrano, M; Lora, D; Paz-Artal, E; Morales, J M; Serrano, A

2016-10-01

In recent years, we have been witnessing increased clinical interest in the determination of IgA anti-beta 2-glycoprotein I (aB2GPI) antibodies as well as increased demand for this test. Some ELISA-based diagnostic systems for IgA aB2GPI antibodies detection are suboptimal to detect it. The aim of our study was to determine whether the diagnostic yield of modern detection systems based on automatic platforms to measure IgA aB2GPI is equivalent to that of the well-optimized ELISA-based assays. In total, 130 patients were analyzed for IgA aB2GPI by three fully automated immunoassays using an ELISA-based assay as reference. The three systems were also analyzed for IgG aB2GPI with 58 patients. System 1 was able to detect IgA aB2GPI with good sensitivity and kappa index (99% and 0.72, respectively). The other two systems had also poor sensitivity (20% and 15%) and kappa index (0.10 and 0.07), respectively. On the other hand, kappa index for IgG aB2GPI was >0.89 in the three systems. Some analytical methods to detect IgA aB2GPI are suboptimal as well as some ELISA-based diagnostic systems. It is important that the scientific community work to standardize analytical methods to determine IgA aB2GPI antibodies. © 2016 John Wiley & Sons Ltd.

Selection of Noisy Sensors and Actuators for Regulation of Linear Systems.

DTIC Science & Technology

1983-08-01

and the inability of (5.8) to account for the possibility of the loss of controllability or stabilizability of the system If a particular actuator is...design by performing the checks tThe condition q4 can result only when a stabilizable , detectable system Is not obtput controllable and one of the...M.R., and Installe, M.J., "Optimal sensors’ allocation strategies for a class of stochastic distributed systems ," Int. J. Control , 1975, Vol. 22, No. 2

Impacts of Intelligent Automated Quality Control on a Small Animal APD-Based Digital PET Scanner

NASA Astrophysics Data System (ADS)

Charest, Jonathan; Beaudoin, Jean-François; Bergeron, Mélanie; Cadorette, Jules; Arpin, Louis; Lecomte, Roger; Brunet, Charles-Antoine; Fontaine, Réjean

2016-10-01

Stable system performance is mandatory to warrant the accuracy and reliability of biological results relying on small animal positron emission tomography (PET) imaging studies. This simple requirement sets the ground for imposing routine quality control (QC) procedures to keep PET scanners at a reliable optimal performance level. However, such procedures can become burdensome to implement for scanner operators, especially taking into account the increasing number of data acquisition channels in newer generation PET scanners. In systems using pixel detectors to achieve enhanced spatial resolution and contrast-to-noise ratio (CNR), the QC workload rapidly increases to unmanageable levels due to the number of independent channels involved. An artificial intelligence based QC system, referred to as Scanner Intelligent Diagnosis for Optimal Performance (SIDOP), was proposed to help reducing the QC workload by performing automatic channel fault detection and diagnosis. SIDOP consists of four high-level modules that employ machine learning methods to perform their tasks: Parameter Extraction, Channel Fault Detection, Fault Prioritization, and Fault Diagnosis. Ultimately, SIDOP submits a prioritized faulty channel list to the operator and proposes actions to correct them. To validate that SIDOP can perform QC procedures adequately, it was deployed on a LabPET™ scanner and multiple performance metrics were extracted. After multiple corrections on sub-optimal scanner settings, a 8.5% (with a 95% confidence interval (CI) of [7.6, 9.3]) improvement in the CNR, a 17.0% (CI: [15.3, 18.7]) decrease of the uniformity percentage standard deviation, and a 6.8% gain in global sensitivity were observed. These results confirm that SIDOP can indeed be of assistance in performing QC procedures and restore performance to optimal figures.

Developing interpretable models with optimized set reduction for identifying high risk software components

NASA Technical Reports Server (NTRS)

Briand, Lionel C.; Basili, Victor R.; Hetmanski, Christopher J.

1993-01-01

Applying equal testing and verification effort to all parts of a software system is not very efficient, especially when resources are limited and scheduling is tight. Therefore, one needs to be able to differentiate low/high fault frequency components so that testing/verification effort can be concentrated where needed. Such a strategy is expected to detect more faults and thus improve the resulting reliability of the overall system. This paper presents the Optimized Set Reduction approach for constructing such models, intended to fulfill specific software engineering needs. Our approach to classification is to measure the software system and build multivariate stochastic models for predicting high risk system components. We present experimental results obtained by classifying Ada components into two classes: is or is not likely to generate faults during system and acceptance test. Also, we evaluate the accuracy of the model and the insights it provides into the error making process.

Directed Design of Experiments for Validating Probability of Detection Capability of NDE Systems (DOEPOD)

NASA Technical Reports Server (NTRS)

Generazio, Edward R.

2015-01-01

Directed Design of Experiments for Validating Probability of Detection Capability of NDE Systems (DOEPOD) Manual v.1.2 The capability of an inspection system is established by applications of various methodologies to determine the probability of detection (POD). One accepted metric of an adequate inspection system is that there is 95% confidence that the POD is greater than 90% (90/95 POD). Design of experiments for validating probability of detection capability of nondestructive evaluation (NDE) systems (DOEPOD) is a methodology that is implemented via software to serve as a diagnostic tool providing detailed analysis of POD test data, guidance on establishing data distribution requirements, and resolving test issues. DOEPOD demands utilization of observance of occurrences. The DOEPOD capability has been developed to provide an efficient and accurate methodology that yields observed POD and confidence bounds for both Hit-Miss or signal amplitude testing. DOEPOD does not assume prescribed POD logarithmic or similar functions with assumed adequacy over a wide range of flaw sizes and inspection system technologies, so that multi-parameter curve fitting or model optimization approaches to generate a POD curve are not required. DOEPOD applications for supporting inspector qualifications is included.

Rendezvous missions with minimoons from L1

NASA Astrophysics Data System (ADS)

Chyba, M.; Haberkorn, T.; Patterson, G.

2014-07-01

We propose to present asteroid capture missions with the so-called minimoons. Minimoons are small asteroids that are temporarily captured objects on orbits in the Earth-Moon system. It has been suggested that, despite their small capture probability, at any time there are one or two meter diameter minimoons, and progressively greater numbers at smaller diameters. The minimoons orbits differ significantly from elliptical orbits which renders a rendezvous mission more challenging, however they offer many advantages for such missions that overcome this fact. First, they are already on geocentric orbits which results in short duration missions with low Delta-v, this translates in cost efficiency and low-risk targets. Second, beside their close proximity to Earth, an advantage is their small size since it provides us with the luxury to retrieve the entire asteroid and not only a sample of material. Accessing the interior structure of a near-Earth satellite in its morphological context is crucial to an in-depth analysis of the structure of the asteroid. Historically, 2006 RH120 is the only minimoon that has been detected but work is ongoing to determine which modifications to current observation facilities is necessary to provide detection algorithm capabilities. In the event that detection is successful, an efficient algorithm to produce a space mission to rendezvous with the detected minimoon is highly desirable to take advantage of this opportunity. This is the main focus of our work. For the design of the mission we propose the following. The spacecraft is first placed in hibernation on a Lissajoux orbit around the liberation point L1 of the Earth-Moon system. We focus on eight-shaped Lissajoux orbits to take advantage of the stability properties of their invariant manifolds for our transfers since the cost to minimize is the spacecraft fuel consumption. Once a minimoon has been detected we must choose a point on its orbit to rendezvous (in position and velocities) with the spacecraft. This is determined using a combination of distance between the minimoon's orbit to L1 and its energy level with respect to the Lissajoux orbit on which the spacecraft is hibernating. Once the spacecraft rendezvous with the minimoon, it will escort the temporarily captured object to analyze it until the withdrawal time when the spacecraft exits the orbit to return to its hibernating location awaiting for another minimoon to be detected. The entire mission including the return portion can be stated as an optimal control problem, however we choose to break it into smaller sub-problems as a first step to be refined later. To model our control system, we use the circular three-body problem since it provides a good approximation in the vicinity of the Earth-Moon dynamics. Expansion to more refined models will be considered once the problem has been solved for this first approximation. The problem is solved in several steps. First, we consider the time minimal problem since we will use a multiple of it for the minimal fuel consumption problem with fixed time. The techniques used to produce the transfers involve an indirect method based on the necessary optimality condition of the Pontriagyn maximum principle coupled with a continuation method to address the sensitivity of the numerical algorithm to initial values. Time local optimality is verified by computing the Jacobi fields of the Hamiltonian system associated to our optimal control problem to check the second-order conditions of optimality and determine the non-existence of conjugate points.

Radiograph and passive data analysis using mixed variable optimization

DOEpatents

Temple, Brian A.; Armstrong, Jerawan C.; Buescher, Kevin L.; Favorite, Jeffrey A.

2015-06-02

Disclosed herein are representative embodiments of methods, apparatus, and systems for performing radiography analysis. For example, certain embodiments perform radiographic analysis using mixed variable computation techniques. One exemplary system comprises a radiation source, a two-dimensional detector for detecting radiation transmitted through a object between the radiation source and detector, and a computer. In this embodiment, the computer is configured to input the radiographic image data from the two-dimensional detector and to determine one or more materials that form the object by using an iterative analysis technique that selects the one or more materials from hierarchically arranged solution spaces of discrete material possibilities and selects the layer interfaces from the optimization of the continuous interface data.

Communication theory of quantum systems. Ph.D. Thesis, 1970

NASA Technical Reports Server (NTRS)

Yuen, H. P. H.

1971-01-01

Communication theory problems incorporating quantum effects for optical-frequency applications are discussed. Under suitable conditions, a unique quantum channel model corresponding to a given classical space-time varying linear random channel is established. A procedure is described by which a proper density-operator representation applicable to any receiver configuration can be constructed directly from the channel output field. Some examples illustrating the application of our methods to the development of optical quantum channel representations are given. Optimizations of communication system performance under different criteria are considered. In particular, certain necessary and sufficient conditions on the optimal detector in M-ary quantum signal detection are derived. Some examples are presented. Parameter estimation and channel capacity are discussed briefly.

Stable and general-purpose chemiluminescent detection system for horseradish peroxidase employing a thiazole compound enhancer and some additives.

PubMed

Iwata, R; Ito, H; Hayashi, T; Sekine, Y; Koyama, N; Yamaki, M

1995-10-10

A stable and highly sensitive chemiluminescent detection system for horseradish peroxidase (HRP)/luminol/hydrogen peroxide using a newly designed thiazole compound enhancer has been established. Some additives for the chemiluminescent reaction were explored to overcome some defects of the reaction such as rapid decay and high background of light emission. Recrystallization of luminol and the addition of several detergents into the reacting solution were effective to increase specific light emissions. The addition of skim milk into the reacting solution reduced the background. Consequently, skim milk combined with a detergent increased the signal to noise ratio about 20 times compared with the reactions in the absence of both additives. The optimal concentration of enhancer and the addition of egg albumin stabilized the emission. In the new method, 6x 10(-18) mol of HRP was detectable. This would be the most sensitive enhanced chemiluminescent detection system for HRP. Furthermore, we could detect picogram per milliliter (10(-17) mol) concentrations of a trace component in biological materials such as endothelin-1 by employing this reaction.

The technology on noise reduction of the APD detection circuit

NASA Astrophysics Data System (ADS)

Wu, Xue-ying; Zheng, Yong-chao; Cui, Jian-yong

2013-09-01

The laser pulse detection is widely used in the field of laser range finders, laser communications, laser radar, laser Identification Friend or Foe, et al, for the laser pulse detection has the advantage of high accuracy, high sensitivity and strong anti-interference. The avalanche photodiodes (APD) has the advantage of high quantum efficiency, high response speed and huge gain. The APD is particularly suitable for weak signal detection. The technology that APD acts as the photodetector for weak signal reception and amplification is widely used in laser pulse detection. The APD will convert the laser signal to weak electrical signal. The weak signal is amplified, processed and exported by the circuit. In the circuit design, the optimal signal detection is one key point in photoelectric detection system. The issue discusses how to reduce the noise of the photoelectric signal detection circuit and how to improve the signal-to-noise ratio, related analysis and practice included. The essay analyzes the mathematical model of the signal-to-noise ratio for photoelectric conversion and the noise of the APD photoelectric detection system. By analysis the bandwidth of the detection system is determined, and the circuit devices are selected that match the APD. In the circuit design separated devices with low noise are combined with integrated operational amplifier for the purpose of noise reduction. The methods can effectively suppress the noise, and improve the detection sensitivity.

The Handbook of Medical Image Perception and Techniques

NASA Astrophysics Data System (ADS)

Samei, Ehsan; Krupinski, Elizabeth

2014-07-01

1. Medical image perception Ehsan Samei and Elizabeth Krupinski; Part I. Historical Reflections and Theoretical Foundations: 2. A short history of image perception in medical radiology Harold Kundel and Calvin Nodine; 3. Spatial vision research without noise Arthur Burgess; 4. Signal detection theory, a brief history Arthur Burgess; 5. Signal detection in radiology Arthur Burgess; 6. Lessons from dinners with the giants of modern image science Robert Wagner; Part II. Science of Image Perception: 7. Perceptual factors in reading medical images Elizabeth Krupinski; 8. Cognitive factors in reading medical images David Manning; 9. Satisfaction of search in traditional radiographic imaging Kevin Berbaum, Edmund Franken, Robert Caldwell and Kevin Schartz; 10. The role of expertise in radiologic image interpretation Calvin Nodine and Claudia Mello-Thoms; 11. A primer of image quality and its perceptual relevance Robert Saunders and Ehsan Samei; 12. Beyond the limitations of human vision Maria Petrou; Part III. Perception Metrology: 13. Logistical issues in designing perception experiments Ehsan Samei and Xiang Li; 14. ROC analysis: basic concepts and practical applications Georgia Tourassi; 15. Multi-reader ROC Steve Hillis; 16. Recent developments in FROC methodology Dev Chakraborty; 17. Observer models as a surrogate to perception experiments Craig Abbey and Miguel Eckstein; 18. Implementation of observer models Matthew Kupinski; Part IV. Decision Support and Computer Aided Detection: 19. CAD: an image perception perspective Maryellen Giger and Weijie Chen; 20. Common designs of CAD studies Yulei Jiang; 21. Perceptual effect of CAD in reading chest images Matthew Freedman and Teresa Osicka; 22. Perceptual issues in mammography and CAD Michael Ulissey; 23. How perceptual factors affect the use and accuracy of CAD for interpretation of CT images Ronald Summers; 24. CAD: risks and benefits for radiologists' decisions Eugenio Alberdi, Andrey Povyakalo, Lorenzo Strigini and Peter Ayton; Part V. Optimization and Practical Issues: 25. Optimization of 2D and 3D radiographic systems Jeff Siewerdson; 26. Applications of AFC methodology in optimization of CT imaging systems Kent Ogden and Walter Huda; 27. Perceptual issues in reading mammograms Margarita Zuley; 28. Perceptual optimization of display processing techniques Richard Van Metter; 29. Optimization of display systems Elizabeth Krupinski and Hans Roehrig; 30. Ergonomic radiologist workplaces in the PACS environment Carl Zylack; Part VI. Epilogue: 31. Future prospects of medical image perception Ehsan Samei and Elizabeth Krupinski; Index.

The Handbook of Medical Image Perception and Techniques

NASA Astrophysics Data System (ADS)

Samei, Ehsan; Krupinski, Elizabeth

2009-12-01

1. Medical image perception Ehsan Samei and Elizabeth Krupinski; Part I. Historical Reflections and Theoretical Foundations: 2. A short history of image perception in medical radiology Harold Kundel and Calvin Nodine; 3. Spatial vision research without noise Arthur Burgess; 4. Signal detection theory, a brief history Arthur Burgess; 5. Signal detection in radiology Arthur Burgess; 6. Lessons from dinners with the giants of modern image science Robert Wagner; Part II. Science of Image Perception: 7. Perceptual factors in reading medical images Elizabeth Krupinski; 8. Cognitive factors in reading medical images David Manning; 9. Satisfaction of search in traditional radiographic imaging Kevin Berbaum, Edmund Franken, Robert Caldwell and Kevin Schartz; 10. The role of expertise in radiologic image interpretation Calvin Nodine and Claudia Mello-Thoms; 11. A primer of image quality and its perceptual relevance Robert Saunders and Ehsan Samei; 12. Beyond the limitations of human vision Maria Petrou; Part III. Perception Metrology: 13. Logistical issues in designing perception experiments Ehsan Samei and Xiang Li; 14. ROC analysis: basic concepts and practical applications Georgia Tourassi; 15. Multi-reader ROC Steve Hillis; 16. Recent developments in FROC methodology Dev Chakraborty; 17. Observer models as a surrogate to perception experiments Craig Abbey and Miguel Eckstein; 18. Implementation of observer models Matthew Kupinski; Part IV. Decision Support and Computer Aided Detection: 19. CAD: an image perception perspective Maryellen Giger and Weijie Chen; 20. Common designs of CAD studies Yulei Jiang; 21. Perceptual effect of CAD in reading chest images Matthew Freedman and Teresa Osicka; 22. Perceptual issues in mammography and CAD Michael Ulissey; 23. How perceptual factors affect the use and accuracy of CAD for interpretation of CT images Ronald Summers; 24. CAD: risks and benefits for radiologists' decisions Eugenio Alberdi, Andrey Povyakalo, Lorenzo Strigini and Peter Ayton; Part V. Optimization and Practical Issues: 25. Optimization of 2D and 3D radiographic systems Jeff Siewerdson; 26. Applications of AFC methodology in optimization of CT imaging systems Kent Ogden and Walter Huda; 27. Perceptual issues in reading mammograms Margarita Zuley; 28. Perceptual optimization of display processing techniques Richard Van Metter; 29. Optimization of display systems Elizabeth Krupinski and Hans Roehrig; 30. Ergonomic radiologist workplaces in the PACS environment Carl Zylack; Part VI. Epilogue: 31. Future prospects of medical image perception Ehsan Samei and Elizabeth Krupinski; Index.

Experimental research of UWB over fiber system employing 128-QAM and ISFA-optimized scheme

NASA Astrophysics Data System (ADS)

He, Jing; Xiang, Changqing; Long, Fengting; Chen, Zuo

2018-05-01

In this paper, an optimized intra-symbol frequency-domain averaging (ISFA) scheme is proposed and experimentally demonstrated in intensity-modulation and direct-detection (IMDD) multiband orthogonal frequency division multiplexing (MB-OFDM) ultra-wideband over fiber (UWBoF) system. According to the channel responses of three MB-OFDM UWB sub-bands, the optimal ISFA window size for each sub-band is investigated. After 60-km standard single mode fiber (SSMF) transmission, the experimental results show that, at the bit error rate (BER) of 3.8 × 10-3, the receiver sensitivity of 128-quadrature amplitude modulation (QAM) can be improved by 1.9 dB using the proposed enhanced ISFA combined with training sequence (TS)-based channel estimation scheme, compared with the conventional TS-based channel estimation. Moreover, the spectral efficiency (SE) is up to 5.39 bit/s/Hz.

Light emitting diode, photodiode-based fluorescence detection system for DNA analysis with microchip electrophoresis.

PubMed

Hall, Gordon H; Glerum, D Moira; Backhouse, Christopher J

2016-02-01

Electrophoretic separation of fluorescently end-labeled DNA after a PCR serves as a gold standard in genetic diagnostics. Because of their size and cost, instruments for this type of analysis have had limited market uptake, particularly for point-of-care applications. This might be changed through a higher level of system integration and lower instrument costs that can be realized through the use of LEDs for excitation and photodiodes for detection--if they provide sufficient sensitivity. Here, we demonstrate an optimized microchip electrophoresis instrument using polymeric fluidic chips with fluorescence detection of end-labeled DNA with a LOD of 0.15 nM of Alexa Fluor 532. This represents orders of magnitude improvement over previously reported instruments of this type. We demonstrate the system with an electrophoretic separation of two PCR products and their respective primers. We believe that this is the first LED-induced fluorescence microchip electrophoresis system with photodiode-based detection that could be used for standard applications of PCR and electrophoresis. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A food contaminant detection system based on high-Tc SQUIDs

NASA Astrophysics Data System (ADS)

Tanaka, Saburo; Fujita, H.; Hatsukade, Y.; Nagaishi, T.; Nishi, K.; Ota, H.; Otani, T.; Suzuki, S.

2006-05-01

We have designed and constructed a computer controlled food contaminant detection system for practical use, based on high-Tc SQUID detectors. The system, which features waterproof stainless steel construction, is acceptable under the HACCP (Hazard Analysis and Critical Control Point) programme guidelines. The outer dimensions of the system are 1500 mm length × 477 mm width × 1445 mm height, and it can accept objects up to 200 mm wide × 80 mm high. An automatic liquid nitrogen filling system was installed in the standard model. This system employed a double-layered permeable metallic shield with a thickness of 1 mm as a magnetically shielded box. The distribution of the magnetic field in the box was simulated by FEM; the gap between each shield layer was optimized before fabrication. A shielding factor of 732 in the Z-component was achieved. This value is high enough to safely operate the system in a non-laboratory environment, i.e., a factory. During testing, we successfully detected a steel contaminant as small as 0.3 mm in diameter at a distance of 75 mm.

Research on the strategy of underwater united detection fusion and communication using multi-sensor

NASA Astrophysics Data System (ADS)

Xu, Zhenhua; Huang, Jianguo; Huang, Hai; Zhang, Qunfei

2011-09-01

In order to solve the distributed detection fusion problem of underwater target detection, when the signal to noise ratio (SNR) of the acoustic channel is low, a new strategy for united detection fusion and communication using multiple sensors was proposed. The performance of detection fusion was studied and compared based on the Neyman-Pearson principle when the binary phase shift keying (BPSK) and on-off keying (OOK) modes were used by the local sensors. The comparative simulation and analysis between the optimal likelihood ratio test and the proposed strategy was completed, and both the theoretical analysis and simulation indicate that using the proposed new strategy could improve the detection performance effectively. In theory, the proposed strategy of united detection fusion and communication is of great significance to the establishment of an underwater target detection system.

Optical tomograph optimized for tumor detection inside highly absorbent organs

NASA Astrophysics Data System (ADS)

Boutet, Jérôme; Koenig, Anne; Hervé, Lionel; Berger, Michel; Dinten, Jean-Marc; Josserand, Véronique; Coll, Jean-Luc

2011-05-01

This paper presents a tomograph for small animal fluorescence imaging. The compact and cost-effective system described in this article was designed to address the problem of tumor detection inside highly absorbent heterogeneous organs, such as lungs. To validate the tomograph's ability to detect cancerous nodules inside lungs, in vivo tumor growth was studied on seven cancerous mice bearing murine mammary tumors marked with Alexa Fluor 700. They were successively imaged 10, 12, and 14 days after the primary tumor implantation. The fluorescence maps were compared over this time period. As expected, the reconstructed fluorescence increases with the tumor growth stage.

Multiple Detector Optimization for Hidden Radiation Source Detection

DTIC Science & Technology

2015-03-26

important in achieving operationally useful methods for optimizing detector emplacement, the 2-D attenuation model approach promises to speed up the...process of hidden source detection significantly. The model focused on detection of the full energy peak of a radiation source. Methods to optimize... radioisotope identification is possible without using a computationally intensive stochastic model such as the Monte Carlo n-Particle (MCNP) code

Method for Vibration Response Simulation and Sensor Placement Optimization of a Machine Tool Spindle System with a Bearing Defect

PubMed Central

Cao, Hongrui; Niu, Linkai; He, Zhengjia

2012-01-01

Bearing defects are one of the most important mechanical sources for vibration and noise generation in machine tool spindles. In this study, an integrated finite element (FE) model is proposed to predict the vibration responses of a spindle bearing system with localized bearing defects and then the sensor placement for better detection of bearing faults is optimized. A nonlinear bearing model is developed based on Jones' bearing theory, while the drawbar, shaft and housing are modeled as Timoshenko's beam. The bearing model is then integrated into the FE model of drawbar/shaft/housing by assembling equations of motion. The Newmark time integration method is used to solve the vibration responses numerically. The FE model of the spindle-bearing system was verified by conducting dynamic tests. Then, the localized bearing defects were modeled and vibration responses generated by the outer ring defect were simulated as an illustration. The optimization scheme of the sensor placement was carried out on the test spindle. The results proved that, the optimal sensor placement depends on the vibration modes under different boundary conditions and the transfer path between the excitation and the response. PMID:23012514

Note: A manifold ranking based saliency detection method for camera.

PubMed

Zhang, Libo; Sun, Yihan; Luo, Tiejian; Rahman, Mohammad Muntasir

2016-09-01

Research focused on salient object region in natural scenes has attracted a lot in computer vision and has widely been used in many applications like object detection and segmentation. However, an accurate focusing on the salient region, while taking photographs of the real-world scenery, is still a challenging task. In order to deal with the problem, this paper presents a novel approach based on human visual system, which works better with the usage of both background prior and compactness prior. In the proposed method, we eliminate the unsuitable boundary with a fixed threshold to optimize the image boundary selection which can provide more precise estimations. Then, the object detection, which is optimized with compactness prior, is obtained by ranking with background queries. Salient objects are generally grouped together into connected areas that have compact spatial distributions. The experimental results on three public datasets demonstrate that the precision and robustness of the proposed algorithm have been improved obviously.

A survey about methods dedicated to epistasis detection.

PubMed

Niel, Clément; Sinoquet, Christine; Dina, Christian; Rocheleau, Ghislain

2015-01-01

During the past decade, findings of genome-wide association studies (GWAS) improved our knowledge and understanding of disease genetics. To date, thousands of SNPs have been associated with diseases and other complex traits. Statistical analysis typically looks for association between a phenotype and a SNP taken individually via single-locus tests. However, geneticists admit this is an oversimplified approach to tackle the complexity of underlying biological mechanisms. Interaction between SNPs, namely epistasis, must be considered. Unfortunately, epistasis detection gives rise to analytic challenges since analyzing every SNP combination is at present impractical at a genome-wide scale. In this review, we will present the main strategies recently proposed to detect epistatic interactions, along with their operating principle. Some of these methods are exhaustive, such as multifactor dimensionality reduction, likelihood ratio-based tests or receiver operating characteristic curve analysis; some are non-exhaustive, such as machine learning techniques (random forests, Bayesian networks) or combinatorial optimization approaches (ant colony optimization, computational evolution system).

Optimizing Monitoring Designs under Alternative Objectives

DOE PAGES

Gastelum, Jason A.; USA, Richland Washington; Porter, Ellen A.; ...

2014-12-31

This paper describes an approach to identify monitoring designs that optimize detection of CO2 leakage from a carbon capture and sequestration (CCS) reservoir and compares the results generated under two alternative objective functions. The first objective function minimizes the expected time to first detection of CO2 leakage, the second more conservative objective function minimizes the maximum time to leakage detection across the set of realizations. The approach applies a simulated annealing algorithm that searches the solution space by iteratively mutating the incumbent monitoring design. The approach takes into account uncertainty by evaluating the performance of potential monitoring designs across amore » set of simulated leakage realizations. The approach relies on a flexible two-tiered signature to infer that CO2 leakage has occurred. This research is part of the National Risk Assessment Partnership, a U.S. Department of Energy (DOE) project tasked with conducting risk and uncertainty analysis in the areas of reservoir performance, natural leakage pathways, wellbore integrity, groundwater protection, monitoring, and systems level modeling.« less

Airborne Detection and Tracking of Geologic Leakage Sites

NASA Astrophysics Data System (ADS)

Jacob, Jamey; Allamraju, Rakshit; Axelrod, Allan; Brown, Calvin; Chowdhary, Girish; Mitchell, Taylor

2014-11-01

Safe storage of CO2 to reduce greenhouse gas emissions without adversely affecting energy use or hindering economic growth requires development of monitoring technology that is capable of validating storage permanence while ensuring the integrity of sequestration operations. Soil gas monitoring has difficulty accurately distinguishing gas flux signals related to leakage from those associated with meteorologically driven changes of soil moisture and temperature. Integrated ground and airborne monitoring systems are being deployed capable of directly detecting CO2 concentration in storage sites. Two complimentary approaches to detecting leaks in the carbon sequestration fields are presented. The first approach focuses on reducing the requisite network communication for fusing individual Gaussian Process (GP) CO2 sensing models into a global GP CO2 model. The GP fusion approach learns how to optimally allocate the static and mobile sensors. The second approach leverages a hierarchical GP-Sigmoidal Gaussian Cox Process for airborne predictive mission planning to optimally reducing the entropy of the global CO2 model. Results from the approaches will be presented.

A landsat data tiling and compositing approach optimized for change detection in the conterminous United States

USGS Publications Warehouse

Nelson, Kurtis; Steinwand, Daniel R.

2015-01-01

Annual disturbance maps are produced by the LANDFIRE program across the conterminous United States (CONUS). Existing LANDFIRE disturbance data from 1999 to 2010 are available and current efforts will produce disturbance data through 2012. A tiling and compositing approach was developed to produce bi-annual images optimized for change detection. A tiled grid of 10,000 × 10,000 30 m pixels was defined for CONUS and adjusted to consolidate smaller tiles along national borders, resulting in 98 non-overlapping tiles. Data from Landsat-5,-7, and -8 were re-projected to the tile extents, masked to remove clouds, shadows, water, and snow/ice, then composited using a cosine similarity approach. The resultant images were used in a change detection algorithm to determine areas of vegetation change. This approach enabled more efficient processing compared to using single Landsat scenes, by taking advantage of overlap between adjacent paths, and allowed an automated system to be developed for the entire process.

Apple flower detection using deep convolutional networks

USDA-ARS?s Scientific Manuscript database

In order to optimize fruit production, a portion of the flowers and fruitlets of apple trees must be removed early in the growing season. The proportion to be removed is determined by the bloom intensity, i.e., the number of flowers present in the orchard. Several automated computer vision systems...

Harmful algal bloom smart device application: using image analysis and machine learning techniques for early classification of harmful algal blooms

EPA Science Inventory

The Ecological Stewardship Institute at Northern Kentucky University and the U.S. Environmental Protection Agency are collaborating to optimize a harmful algal bloom detection algorithm that estimates the presence and count of cyanobacteria in freshwater systems by image analysis...

Diffraction measurements using the LHC Beam Loss Monitoring System

NASA Astrophysics Data System (ADS)

Kalliokoski, Matti

2017-03-01

The Beam Loss Monitoring (BLM) system of the Large Hadron Collider protects the machine from beam induced damage by measuring the absorbed dose rates of beam losses, and by triggering beam dump if the rates increase above the allowed threshold limits. Although the detection time scales are optimized for multi-turn losses, information on fast losses can be recovered from the loss data. In this paper, methods in using the BLM system in diffraction studies are discussed.

Automated position control of a surface array relative to a liquid microjunction surface sampler

DOEpatents

Van Berkel, Gary J.; Kertesz, Vilmos; Ford, Michael James

2007-11-13

A system and method utilizes an image analysis approach for controlling the probe-to-surface distance of a liquid junction-based surface sampling system for use with mass spectrometric detection. Such an approach enables a hands-free formation of the liquid microjunction used to sample solution composition from the surface and for re-optimization, as necessary, of the microjunction thickness during a surface scan to achieve a fully automated surface sampling system.

TU-FG-209-11: Validation of a Channelized Hotelling Observer to Optimize Chest Radiography Image Processing for Nodule Detection: A Human Observer Study

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

Sanchez, A; Little, K; Chung, J

Purpose: To validate the use of a Channelized Hotelling Observer (CHO) model for guiding image processing parameter selection and enable improved nodule detection in digital chest radiography. Methods: In a previous study, an anthropomorphic chest phantom was imaged with and without PMMA simulated nodules using a GE Discovery XR656 digital radiography system. The impact of image processing parameters was then explored using a CHO with 10 Laguerre-Gauss channels. In this work, we validate the CHO’s trend in nodule detectability as a function of two processing parameters by conducting a signal-known-exactly, multi-reader-multi-case (MRMC) ROC observer study. Five naive readers scored confidencemore » of nodule visualization in 384 images with 50% nodule prevalence. The image backgrounds were regions-of-interest extracted from 6 normal patient scans, and the digitally inserted simulated nodules were obtained from phantom data in previous work. Each patient image was processed with both a near-optimal and a worst-case parameter combination, as determined by the CHO for nodule detection. The same 192 ROIs were used for each image processing method, with 32 randomly selected lung ROIs per patient image. Finally, the MRMC data was analyzed using the freely available iMRMC software of Gallas et al. Results: The image processing parameters which were optimized for the CHO led to a statistically significant improvement (p=0.049) in human observer AUC from 0.78 to 0.86, relative to the image processing implementation which produced the lowest CHO performance. Conclusion: Differences in user-selectable image processing methods on a commercially available digital radiography system were shown to have a marked impact on performance of human observers in the task of lung nodule detection. Further, the effect of processing on humans was similar to the effect on CHO performance. Future work will expand this study to include a wider range of detection/classification tasks and more observers, including experienced chest radiologists.« less

A robust approach to optimal matched filter design in ultrasonic non-destructive evaluation (NDE)

NASA Astrophysics Data System (ADS)

Li, Minghui; Hayward, Gordon

2017-02-01

The matched filter was demonstrated to be a powerful yet efficient technique to enhance defect detection and imaging in ultrasonic non-destructive evaluation (NDE) of coarse grain materials, provided that the filter was properly designed and optimized. In the literature, in order to accurately approximate the defect echoes, the design utilized the real excitation signals, which made it time consuming and less straightforward to implement in practice. In this paper, we present a more robust and flexible approach to optimal matched filter design using the simulated excitation signals, and the control parameters are chosen and optimized based on the real scenario of array transducer, transmitter-receiver system response, and the test sample, as a result, the filter response is optimized and depends on the material characteristics. Experiments on industrial samples are conducted and the results confirm the great benefits of the method.

Particle swarm optimization based space debris surveillance network scheduling

NASA Astrophysics Data System (ADS)

Jiang, Hai; Liu, Jing; Cheng, Hao-Wen; Zhang, Yao

2017-02-01

The increasing number of space debris has created an orbital debris environment that poses increasing impact risks to existing space systems and human space flights. For the safety of in-orbit spacecrafts, we should optimally schedule surveillance tasks for the existing facilities to allocate resources in a manner that most significantly improves the ability to predict and detect events involving affected spacecrafts. This paper analyzes two criteria that mainly affect the performance of a scheduling scheme and introduces an artificial intelligence algorithm into the scheduling of tasks of the space debris surveillance network. A new scheduling algorithm based on the particle swarm optimization algorithm is proposed, which can be implemented in two different ways: individual optimization and joint optimization. Numerical experiments with multiple facilities and objects are conducted based on the proposed algorithm, and simulation results have demonstrated the effectiveness of the proposed algorithm.

Real space channelization for generic DBT system image quality evaluation with channelized Hotelling observer

NASA Astrophysics Data System (ADS)

Petrov, Dimitar; Cockmartin, Lesley; Marshall, Nicholas; Vancoillie, Liesbeth; Young, Kenneth; Bosmans, Hilde

2017-03-01

Digital breast tomosynthesis (DBT) is a relatively new 3D mammography technique that promises better detection of low contrast masses than conventional 2D mammography. The parameter space for DBT is large however and finding an optimal balance between dose and image quality remains challenging. Given the large number of conditions and images required in optimization studies, the use of human observers (HO) is time consuming and certainly not feasible for the tuning of all degrees of freedom. Our goal was to develop a model observer (MO) that could predict human detectability for clinically relevant details embedded within a newly developed structured phantom for DBT applications. DBT series were acquired on GE SenoClaire 3D, Giotto Class, Fujifilm AMULET Innovality and Philips MicroDose systems at different dose levels, Siemens Inspiration DBT acquisitions were reconstructed with different algorithms, while a larger set of DBT series was acquired on Hologic Dimensions system for first reproducibility testing. A channelized Hotelling observer (CHO) with Gabor channels was developed The parameters of the Gabor channels were tuned on all systems at standard scanning conditions and the candidate that produced the best fit for all systems was chosen. After tuning, the MO was applied to all systems and conditions. Linear regression lines between MO and HO scores were calculated, giving correlation coefficients between 0.87 and 0.99 for all tested conditions.

Automated tracking for advanced satellite laser ranging systems

NASA Astrophysics Data System (ADS)

McGarry, Jan F.; Degnan, John J.; Titterton, Paul J., Sr.; Sweeney, Harold E.; Conklin, Brion P.; Dunn, Peter J.

1996-06-01

NASA's Satellite Laser Ranging Network was originally developed during the 1970's to track satellites carrying corner cube reflectors. Today eight NASA systems, achieving millimeter ranging precision, are part of a global network of more than 40 stations that track 17 international satellites. To meet the tracking demands of a steadily growing satellite constellation within existing resources, NASA is embarking on a major automation program. While manpower on the current systems will be reduced to a single operator, the fully automated SLR2000 system is being designed to operate for months without human intervention. Because SLR2000 must be eyesafe and operate in daylight, tracking is often performed in a low probability of detection and high noise environment. The goal is to automatically select the satellite, setup the tracking and ranging hardware, verify acquisition, and close the tracking loop to optimize data yield. TO accomplish the autotracking tasks, we are investigating (1) improved satellite force models, (2) more frequent updates of orbital ephemerides, (3) lunar laser ranging data processing techniques to distinguish satellite returns from noise, and (4) angular detection and search techniques to acquire the satellite. A Monte Carlo simulator has been developed to allow optimization of the autotracking algorithms by modeling the relevant system errors and then checking performance against system truth. A combination of simulator and preliminary field results will be presented.