Research on Aircraft Target Detection Algorithm Based on Improved Radial Gradient Transformation

NASA Astrophysics Data System (ADS)

Zhao, Z. M.; Gao, X. M.; Jiang, D. N.; Zhang, Y. Q.

2018-04-01

Aiming at the problem that the target may have different orientation in the unmanned aerial vehicle (UAV) image, the target detection algorithm based on the rotation invariant feature is studied, and this paper proposes a method of RIFF (Rotation-Invariant Fast Features) based on look up table and polar coordinate acceleration to be used for aircraft target detection. The experiment shows that the detection performance of this method is basically equal to the RIFF, and the operation efficiency is greatly improved.

Dimension-based attention in visual short-term memory.

PubMed

Pilling, Michael; Barrett, Doug J K

2016-07-01

We investigated how dimension-based attention influences visual short-term memory (VSTM). This was done through examining the effects of cueing a feature dimension in two perceptual comparison tasks (change detection and sameness detection). In both tasks, a memory array and a test array consisting of a number of colored shapes were presented successively, interleaved by a blank interstimulus interval (ISI). In Experiment 1 (change detection), the critical event was a feature change in one item across the memory and test arrays. In Experiment 2 (sameness detection), the critical event was the absence of a feature change in one item across the two arrays. Auditory cues indicated the feature dimension (color or shape) of the critical event with 80 % validity; the cues were presented either prior to the memory array, during the ISI, or simultaneously with the test array. In Experiment 1, the cue validity influenced sensitivity only when the cue was given at the earliest position; in Experiment 2, the cue validity influenced sensitivity at all three cue positions. We attributed the greater effectiveness of top-down guidance by cues in the sameness detection task to the more active nature of the comparison process required to detect sameness events (Hyun, Woodman, Vogel, Hollingworth, & Luck, Journal of Experimental Psychology: Human Perception and Performance, 35; 1140-1160, 2009).

Assessing autobiographical memory: the web-based autobiographical Implicit Association Test.

PubMed

Verschuere, Bruno; Kleinberg, Bennett

2017-04-01

By assessing the association strength with TRUE and FALSE, the autobiographical Implicit Association Test (aIAT) [Sartori, G., Agosta, S., Zogmaister, C., Ferrara, S. D., & Castiello, U. (2008). How to accurately detect autobiographical events. Psychological Science, 19, 772-780. doi: 10.1111/j.1467-9280.2008.02156.x ] aims to determine which of two contrasting statements is true. To efficiently run well-powered aIAT experiments, we propose a web-based aIAT (web-aIAT). Experiment 1 (n = 522) is a web-based replication study of the first published aIAT study [Sartori, G., Agosta, S., Zogmaister, C., Ferrara, S. D., & Castiello, U. (2008). How to accurately detect autobiographical events. Psychological Science, 19, 772-780. doi: 10.1111/j.1467-9280.2008.02156.x ; Experiment 1]. We conclude that the replication was successful as the web-based aIAT could accurately detect which of two playing cards participants chose (AUC = .88; Hit rate = 81%). In Experiment 2 (n = 424), we investigated whether the use of affirmative versus negative sentences may partly explain the variability in aIAT accuracy findings. The aIAT could detect the chosen card when using affirmative (AUC = .90; Hit rate = 81%), but not when using negative sentences (AUC = .60; Hit rate = 53%). The web-based aIAT seems to be a valuable tool to facilitate aIAT research and may help to further identify moderators of the test's accuracy.

An immunity-based anomaly detection system with sensor agents.

PubMed

Okamoto, Takeshi; Ishida, Yoshiteru

2009-01-01

This paper proposes an immunity-based anomaly detection system with sensor agents based on the specificity and diversity of the immune system. Each agent is specialized to react to the behavior of a specific user. Multiple diverse agents decide whether the behavior is normal or abnormal. Conventional systems have used only a single sensor to detect anomalies, while the immunity-based system makes use of multiple sensors, which leads to improvements in detection accuracy. In addition, we propose an evaluation framework for the anomaly detection system, which is capable of evaluating the differences in detection accuracy between internal and external anomalies. This paper focuses on anomaly detection in user's command sequences on UNIX-like systems. In experiments, the immunity-based system outperformed some of the best conventional systems.

Implementation of a custom time-domain firmware trigger for RADAR-based cosmic ray detection

NASA Astrophysics Data System (ADS)

Prohira, S.; Besson, D.; Kunwar, S.; Ratzlaff, K.; Young, R.

2018-05-01

Interest in Radio-based detection schemes for ultra-high energy cosmic rays (UHECR) has surged in recent years, owing to the potentially very low cost/detection ratio. The method of radio-frequency (RF) scatter has been proposed as potentially the most economical detection technology. Though the first dedicated experiment to employ this method, the Telescope Array RADAR experiment (TARA) reported no signal, efforts to develop more robust and sensitive trigger techniques continue. This paper details the development of a time-domain firmware trigger that exploits characteristics of the expected scattered signal from an UHECR extensive-air shower (EAS). The improved sensitivity of this trigger is discussed, as well as implementation in two separate field deployments from 2016 to 2017.

ROS-based ground stereo vision detection: implementation and experiments.

PubMed

Hu, Tianjiang; Zhao, Boxin; Tang, Dengqing; Zhang, Daibing; Kong, Weiwei; Shen, Lincheng

This article concentrates on open-source implementation on flying object detection in cluttered scenes. It is of significance for ground stereo-aided autonomous landing of unmanned aerial vehicles. The ground stereo vision guidance system is presented with details on system architecture and workflow. The Chan-Vese detection algorithm is further considered and implemented in the robot operating systems (ROS) environment. A data-driven interactive scheme is developed to collect datasets for parameter tuning and performance evaluating. The flying vehicle outdoor experiments capture the stereo sequential images dataset and record the simultaneous data from pan-and-tilt unit, onboard sensors and differential GPS. Experimental results by using the collected dataset validate the effectiveness of the published ROS-based detection algorithm.

Irradiation effects on antibody performance in the frame of biochip-based instruments development for space exploration

NASA Astrophysics Data System (ADS)

Baqué, M.; Dobrijevic, M.; Le Postollec, A.; Moreau, T.; Faye, C.; Vigier, F.; Incerti, S.; Coussot, G.; Caron, J.; Vandenabeele-Trambouze, O.

2017-01-01

Several instruments based on immunoassay techniques have been proposed for life-detection experiments in the framework of planetary exploration but few experiments have been conducted so far to test the resistance of antibodies against cosmic ray particles. We present several irradiation experiments carried out on both grafted and free antibodies for different types of incident particles (protons, neutrons, electrons and 12C) at different energies (between 9 MeV and 50 MeV) and different fluences. No loss of antibodies activity was detected for the whole set of experiments except when considering protons with energy between 20 and 30 MeV (on free and grafted antibodies) and fluences much greater than expected for a typical planetary mission to Mars for instance. Our results on grafted antibodies suggest that biochip-based instruments must be carefully designed according to the expected radiation environment for a given mission. In particular, a surface density of antibodies much larger than the expected proton fluence would prevent significant loss of antibodies activity and thus assuring a successful detection.

A rapid low-cost high-density DNA-based multi-detection test for routine inspection of meat species.

PubMed

Lin, Chun Chi; Fung, Lai Ling; Chan, Po Kwok; Lee, Cheuk Man; Chow, Kwok Fai; Cheng, Shuk Han

2014-02-01

The increasing occurrence of food frauds suggests that species identification should be part of food authentication. Current molecular-based species identification methods have their own limitations or drawbacks, such as relatively time-consuming experimental steps, expensive equipment and, in particular, these methods cannot identify mixed species in a single experiment. This project proposes an improved method involving PCR amplification of the COI gene and detection of species-specific sequences by hybridisation. Major innovative breakthrough lies in the detection of multiple species, including pork, beef, lamb, horse, cat, dog and mouse, from a mixed sample within a single experiment. The probes used are species-specific either in sole or mixed species samples. As little as 5 pg of DNA template in the PCR is detectable in the proposed method. By designing species-specific probes and adopting reverse dot blot hybridisation and flow-through hybridisation, a low-cost high-density DNA-based multi-detection test suitable for routine inspection of meat species was developed. © 2013.

Sea Ice Detection Based on an Improved Similarity Measurement Method Using Hyperspectral Data.

PubMed

Han, Yanling; Li, Jue; Zhang, Yun; Hong, Zhonghua; Wang, Jing

2017-05-15

Hyperspectral remote sensing technology can acquire nearly continuous spectrum information and rich sea ice image information, thus providing an important means of sea ice detection. However, the correlation and redundancy among hyperspectral bands reduce the accuracy of traditional sea ice detection methods. Based on the spectral characteristics of sea ice, this study presents an improved similarity measurement method based on linear prediction (ISMLP) to detect sea ice. First, the first original band with a large amount of information is determined based on mutual information theory. Subsequently, a second original band with the least similarity is chosen by the spectral correlation measuring method. Finally, subsequent bands are selected through the linear prediction method, and a support vector machine classifier model is applied to classify sea ice. In experiments performed on images of Baffin Bay and Bohai Bay, comparative analyses were conducted to compare the proposed method and traditional sea ice detection methods. Our proposed ISMLP method achieved the highest classification accuracies (91.18% and 94.22%) in both experiments. From these results the ISMLP method exhibits better performance overall than other methods and can be effectively applied to hyperspectral sea ice detection.

Sea Ice Detection Based on an Improved Similarity Measurement Method Using Hyperspectral Data

PubMed Central

Han, Yanling; Li, Jue; Zhang, Yun; Hong, Zhonghua; Wang, Jing

2017-01-01

Hyperspectral remote sensing technology can acquire nearly continuous spectrum information and rich sea ice image information, thus providing an important means of sea ice detection. However, the correlation and redundancy among hyperspectral bands reduce the accuracy of traditional sea ice detection methods. Based on the spectral characteristics of sea ice, this study presents an improved similarity measurement method based on linear prediction (ISMLP) to detect sea ice. First, the first original band with a large amount of information is determined based on mutual information theory. Subsequently, a second original band with the least similarity is chosen by the spectral correlation measuring method. Finally, subsequent bands are selected through the linear prediction method, and a support vector machine classifier model is applied to classify sea ice. In experiments performed on images of Baffin Bay and Bohai Bay, comparative analyses were conducted to compare the proposed method and traditional sea ice detection methods. Our proposed ISMLP method achieved the highest classification accuracies (91.18% and 94.22%) in both experiments. From these results the ISMLP method exhibits better performance overall than other methods and can be effectively applied to hyperspectral sea ice detection. PMID:28505135

Adapting Local Features for Face Detection in Thermal Image.

PubMed

Ma, Chao; Trung, Ngo Thanh; Uchiyama, Hideaki; Nagahara, Hajime; Shimada, Atsushi; Taniguchi, Rin-Ichiro

2017-11-27

A thermal camera captures the temperature distribution of a scene as a thermal image. In thermal images, facial appearances of different people under different lighting conditions are similar. This is because facial temperature distribution is generally constant and not affected by lighting condition. This similarity in face appearances is advantageous for face detection. To detect faces in thermal images, cascade classifiers with Haar-like features are generally used. However, there are few studies exploring the local features for face detection in thermal images. In this paper, we introduce two approaches relying on local features for face detection in thermal images. First, we create new feature types by extending Multi-Block LBP. We consider a margin around the reference and the generally constant distribution of facial temperature. In this way, we make the features more robust to image noise and more effective for face detection in thermal images. Second, we propose an AdaBoost-based training method to get cascade classifiers with multiple types of local features. These feature types have different advantages. In this way we enhance the description power of local features. We did a hold-out validation experiment and a field experiment. In the hold-out validation experiment, we captured a dataset from 20 participants, comprising 14 males and 6 females. For each participant, we captured 420 images with 10 variations in camera distance, 21 poses, and 2 appearances (participant with/without glasses). We compared the performance of cascade classifiers trained by different sets of the features. The experiment results showed that the proposed approaches effectively improve the performance of face detection in thermal images. In the field experiment, we compared the face detection performance in realistic scenes using thermal and RGB images, and gave discussion based on the results.

Research on moving object detection based on frog's eyes

NASA Astrophysics Data System (ADS)

Fu, Hongwei; Li, Dongguang; Zhang, Xinyuan

2008-12-01

On the basis of object's information processing mechanism with frog's eyes, this paper discussed a bionic detection technology which suitable for object's information processing based on frog's vision. First, the bionics detection theory by imitating frog vision is established, it is an parallel processing mechanism which including pick-up and pretreatment of object's information, parallel separating of digital image, parallel processing, and information synthesis. The computer vision detection system is described to detect moving objects which has special color, special shape, the experiment indicates that it can scheme out the detecting result in the certain interfered background can be detected. A moving objects detection electro-model by imitating biologic vision based on frog's eyes is established, the video simulative signal is digital firstly in this system, then the digital signal is parallel separated by FPGA. IN the parallel processing, the video information can be caught, processed and displayed in the same time, the information fusion is taken by DSP HPI ports, in order to transmit the data which processed by DSP. This system can watch the bigger visual field and get higher image resolution than ordinary monitor systems. In summary, simulative experiments for edge detection of moving object with canny algorithm based on this system indicate that this system can detect the edge of moving objects in real time, the feasibility of bionic model was fully demonstrated in the engineering system, and it laid a solid foundation for the future study of detection technology by imitating biologic vision.

Plant Ethylene Detection Using Laser-Based Photo-Acoustic Spectroscopy.

PubMed

Van de Poel, Bram; Van Der Straeten, Dominique

2017-01-01

Analytical detection of the plant hormone ethylene is an important prerequisite in physiological studies. Real-time and super sensitive detection of trace amounts of ethylene gas is possible using laser-based photo-acoustic spectroscopy. This Chapter will provide some background on the technique, compare it with conventional gas chromatography, and provide a detailed user-friendly hand-out on how to operate the machine and the software. In addition, this Chapter provides some tips and tricks for designing and performing physiological experiments suited for ethylene detection with laser-based photo-acoustic spectroscopy.

Morphological observation and analysis using automated image cytometry for the comparison of trypan blue and fluorescence-based viability detection method.

PubMed

Chan, Leo Li-Ying; Kuksin, Dmitry; Laverty, Daniel J; Saldi, Stephanie; Qiu, Jean

2015-05-01

The ability to accurately determine cell viability is essential to performing a well-controlled biological experiment. Typical experiments range from standard cell culturing to advanced cell-based assays that may require cell viability measurement for downstream experiments. The traditional cell viability measurement method has been the trypan blue (TB) exclusion assay. However, since the introduction of fluorescence-based dyes for cell viability measurement using flow or image-based cytometry systems, there have been numerous publications comparing the two detection methods. Although previous studies have shown discrepancies between TB exclusion and fluorescence-based viability measurements, image-based morphological analysis was not performed in order to examine the viability discrepancies. In this work, we compared TB exclusion and fluorescence-based viability detection methods using image cytometry to observe morphological changes due to the effect of TB on dead cells. Imaging results showed that as the viability of a naturally-dying Jurkat cell sample decreased below 70 %, many TB-stained cells began to exhibit non-uniform morphological characteristics. Dead cells with these characteristics may be difficult to count under light microscopy, thus generating an artificially higher viability measurement compared to fluorescence-based method. These morphological observations can potentially explain the differences in viability measurement between the two methods.

On-Line Database of Vibration-Based Damage Detection Experiments

NASA Technical Reports Server (NTRS)

Pappa, Richard S.; Doebling, Scott W.; Kholwad, Tina D.

2000-01-01

This paper describes a new, on-line bibliographic database of vibration-based damage detection experiments. Publications in the database discuss experiments conducted on actual structures as well as those conducted with simulated data. The database can be searched and sorted in many ways, and it provides photographs of test structures when available. It currently contains 100 publications, which is estimated to be about 5-10% of the number of papers written to date on this subject. Additional entries are forthcoming. This database is available for public use on the Internet at the following address: http://sdbpappa-mac.larc.nasa.gov. Click on the link named "dd_experiments.fp3" and then type "guest" as the password. No user name is required.

A universal TaqMan-based RT-PCR protocol for cost-efficient detection of small noncoding RNA.

PubMed

Jung, Ulrike; Jiang, Xiaoou; Kaufmann, Stefan H E; Patzel, Volker

2013-12-01

Several methods for the detection of RNA have been developed over time. For small RNA detection, a stem-loop reverse primer-based protocol relying on TaqMan RT-PCR has been described. This protocol requires an individual specific TaqMan probe for each target RNA and, hence, is highly cost-intensive for experiments with small sample sizes or large numbers of different samples. We describe a universal TaqMan-based probe protocol which can be used to detect any target sequence and demonstrate its applicability for the detection of endogenous as well as artificial eukaryotic and bacterial small RNAs. While the specific and the universal probe-based protocol showed the same sensitivity, the absolute sensitivity of detection was found to be more than 100-fold lower for both than previously reported. In subsequent experiments, we found previously unknown limitations intrinsic to the method affecting its feasibility in determination of mature template RISC incorporation as well as in multiplexing. Both protocols were equally specific in discriminating between correct and incorrect small RNA targets or between mature miRNA and its unprocessed RNA precursor, indicating the stem-loop RT-primer, but not the TaqMan probe, triggers target specificity. The presented universal TaqMan-based RT-PCR protocol represents a cost-efficient method for the detection of small RNAs.

Quantifying (dis)agreement between direct detection experiments in a halo-independent way

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

Feldstein, Brian; Kahlhoefer, Felix, E-mail: brian.feldstein@physics.ox.ac.uk, E-mail: felix.kahlhoefer@physics.ox.ac.uk

We propose an improved method to study recent and near-future dark matter direct detection experiments with small numbers of observed events. Our method determines in a quantitative and halo-independent way whether the experiments point towards a consistent dark matter signal and identifies the best-fit dark matter parameters. To achieve true halo independence, we apply a recently developed method based on finding the velocity distribution that best describes a given set of data. For a quantitative global analysis we construct a likelihood function suitable for small numbers of events, which allows us to determine the best-fit particle physics properties of darkmore » matter considering all experiments simultaneously. Based on this likelihood function we propose a new test statistic that quantifies how well the proposed model fits the data and how large the tension between different direct detection experiments is. We perform Monte Carlo simulations in order to determine the probability distribution function of this test statistic and to calculate the p-value for both the dark matter hypothesis and the background-only hypothesis.« less

Developing a discrete choice experiment in Malawi: eliciting preferences for breast cancer early detection services.

PubMed

Kohler, Racquel E; Lee, Clara N; Gopal, Satish; Reeve, Bryce B; Weiner, Bryan J; Wheeler, Stephanie B

2015-01-01

In Malawi, routine breast cancer screening is not available and little is known about women's preferences regarding early detection services. Discrete choice experiments are increasingly used to reveal preferences about new health services; however, selecting appropriate attributes that describe a new health service is imperative to ensure validity of the choice experiment. To identify important factors that are relevant to Malawian women's preferences for breast cancer detection services and to select attributes and levels for a discrete choice experiment in a setting where both breast cancer early detection and choice experiments are rare. We reviewed the literature to establish an initial list of potential attributes and levels for a discrete choice experiment and conducted qualitative interviews with health workers and community women to explore relevant local factors affecting decisions to use cancer detection services. We tested the design through cognitive interviews and refined the levels, descriptions, and designs. Themes that emerged from interviews provided critical information about breast cancer detection services, specifically, that breast cancer interventions should be integrated into other health services because asymptomatic screening may not be practical as an individual service. Based on participants' responses, the final attributes of the choice experiment included travel time, health encounter, health worker type and sex, and breast cancer early detection strategy. Cognitive testing confirmed the acceptability of the final attributes, comprehension of choice tasks, and women's abilities to make trade-offs. Applying a discrete choice experiment for breast cancer early detection was feasible with appropriate tailoring for a low-income, low-literacy African setting.

Interplay and characterization of Dark Matter searches at colliders and in direct detection experiments

DOE PAGES

Malik, Sarah A.; McCabe, Christopher; Araujo, Henrique; ...

2015-05-18

In our White Paper we present and discuss a concrete proposal for the consistent interpretation of Dark Matter searches at colliders and in direct detection experiments. Furthermore, based on a specific implementation of simplified models of vector and axial-vector mediator exchanges, this proposal demonstrates how the two search strategies can be compared on an equal footing.

Unsupervised malaria parasite detection based on phase spectrum.

PubMed

Fang, Yuming; Xiong, Wei; Lin, Weisi; Chen, Zhenzhong

2011-01-01

In this paper, we propose a novel method for malaria parasite detection based on phase spectrum. The method first obtains the amplitude spectrum and phase spectrum for blood smear images through Quaternion Fourier Transform (QFT). Then it gets the reconstructed image based on Inverse Quaternion Fourier transform (IQFT) on a constant amplitude spectrum and the original phase spectrum. The malaria parasite areas can be detected easily from the reconstructed blood smear images. Extensive experiments have demonstrated the effectiveness of this novel method.

Discriminating Famous from Fictional Names Based on Lifetime Experience: Evidence in Support of a Signal-Detection Model Based on Finite Mixture Distributions

ERIC Educational Resources Information Center

Bowles, Ben; Harlow, Iain M.; Meeking, Melissa M.; Kohler, Stefan

2012-01-01

It is widely accepted that signal-detection mechanisms contribute to item-recognition memory decisions that involve discriminations between targets and lures based on a controlled laboratory study episode. Here, the authors employed mathematical modeling of receiver operating characteristics (ROC) to determine whether and how a signal-detection…

Terahertz wave electro-optic measurements with optical spectral filtering

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

Ilyakov, I. E., E-mail: igor-ilyakov@mail.ru; Shishkin, B. V.; Kitaeva, G. Kh.

We propose electro-optic detection techniques based on variations of the laser pulse spectrum induced during pulse co-propagation with terahertz wave radiation in a nonlinear crystal. Quantitative comparison with two other detection methods is made. Substantial improvement of the sensitivity compared to the standard electro-optic detection technique (at high frequencies) and to the previously shown technique based on laser pulse energy changes is demonstrated in experiment.

Drivers' and non-drivers' performance in a change detection task with static driving scenes: is there a benefit of experience?

PubMed

Zhao, Nan; Chen, Wenfeng; Xuan, Yuming; Mehler, Bruce; Reimer, Bryan; Fu, Xiaolan

2014-01-01

The 'looked-but-failed-to-see' phenomenon is crucial to driving safety. Previous research utilising change detection tasks related to driving has reported inconsistent effects of driver experience on the ability to detect changes in static driving scenes. Reviewing these conflicting results, we suggest that drivers' increased ability to detect changes will only appear when the task requires a pattern of visual attention distribution typical of actual driving. By adding a distant fixation point on the road image, we developed a modified change blindness paradigm and measured detection performance of drivers and non-drivers. Drivers performed better than non-drivers only in scenes with a fixation point. Furthermore, experience effect interacted with the location of the change and the relevance of the change to driving. These results suggest that learning associated with driving experience reflects increased skill in the efficient distribution of visual attention across both the central focus area and peripheral objects. This article provides an explanation for the previously conflicting reports of driving experience effects in change detection tasks. We observed a measurable benefit of experience in static driving scenes, using a modified change blindness paradigm. These results have translational opportunities for picture-based training and testing tools to improve driver skill.

The carbon-assimilation experiment - The Viking Mars Lander.

NASA Technical Reports Server (NTRS)

Horowitz, N. H.; Hubbard, J. S.; Hobby, G. L.

1972-01-01

The carbon-assimilation experiment detects life in soils by measuring the incorporation of carbon from carbon-14 monoxide and carbon-14 dioxide into organic matter. It is based on the premise that Martian life, if it exists, is carbonaceous and exchanges carbon with the atmosphere, as do all terrestrial organisms. It is especially sensitive for photosynthesizing cells, but it detects heterotrophs also. The experiment has the particular advantage that it can be carried out under essentially Martian conditions of temperature, pressure, atmospheric composition, and water abundance.

Driver fatigue alarm based on eye detection and gaze estimation

NASA Astrophysics Data System (ADS)

Sun, Xinghua; Xu, Lu; Yang, Jingyu

2007-11-01

The driver assistant system has attracted much attention as an essential component of intelligent transportation systems. One task of driver assistant system is to prevent the drivers from fatigue. For the fatigue detection it is natural that the information about eyes should be utilized. The driver fatigue can be divided into two types, one is the sleep with eyes close and another is the sleep with eyes open. Considering that the fatigue detection is related with the prior knowledge and probabilistic statistics, the dynamic Bayesian network is used as the analysis tool to perform the reasoning of fatigue. Two kinds of experiments are performed to verify the system effectiveness, one is based on the video got from the laboratory and another is based on the video got from the real driving situation. Ten persons participate in the test and the experimental result is that, in the laboratory all the fatigue events can be detected, and in the practical vehicle the detection ratio is about 85%. Experiments show that in most of situations the proposed system works and the corresponding performance is satisfying.

Study of detecting mechanism of carbon nanotubes gas sensor based on multi-stable stochastic resonance model.

PubMed

Jingyi, Zhu

2015-01-01

The detecting mechanism of carbon nanotubes gas sensor based on multi-stable stochastic resonance (MSR) model was studied in this paper. A numerically stimulating model based on MSR was established. And gas-ionizing experiment by adding electronic white noise to induce 1.65 MHz periodic component in the carbon nanotubes gas sensor was performed. It was found that the signal-to-noise ratio (SNR) spectrum displayed 2 maximal values, which accorded to the change of the broken-line potential function. The experimental results of gas-ionizing experiment demonstrated that periodic component of 1.65 MHz had multiple MSR phenomena, which was in accordance with the numerical stimulation results. In this way, the numerical stimulation method provides an innovative method for the detecting mechanism research of carbon nanotubes gas sensor.

Towards an integrated defense system for cyber security situation awareness experiment

NASA Astrophysics Data System (ADS)

Zhang, Hanlin; Wei, Sixiao; Ge, Linqiang; Shen, Dan; Yu, Wei; Blasch, Erik P.; Pham, Khanh D.; Chen, Genshe

2015-05-01

In this paper, an implemented defense system is demonstrated to carry out cyber security situation awareness. The developed system consists of distributed passive and active network sensors designed to effectively capture suspicious information associated with cyber threats, effective detection schemes to accurately distinguish attacks, and network actors to rapidly mitigate attacks. Based on the collected data from network sensors, image-based and signals-based detection schemes are implemented to detect attacks. To further mitigate attacks, deployed dynamic firewalls on hosts dynamically update detection information reported from the detection schemes and block attacks. The experimental results show the effectiveness of the proposed system. A future plan to design an effective defense system is also discussed based on system theory.

A study on new method of noninvasive esophageal venous pressure measurement based on the airflow and laser detection technology.

PubMed

Hu, Chenghuan; Huang, Feizhou; Zhang, Rui; Zhu, Shaihong; Nie, Wanpin; Liu, Xunyang; Liu, Yinglong; Li, Peng

2015-01-01

Using optics combined with automatic control and computer real-time image detection technology, a novel noninvasive method of noncontact pressure manometry was developed based on the airflow and laser detection technology in this study. The new esophageal venous pressure measurement system was tested in-vitro experiments. A stable and adjustable pulse stream was produced from a self-developed pump and a laser emitting apparatus could generate optical signals which can be captured by image acquisition and analysis system program. A synchronization system simultaneous measured the changes of air pressure and the deformation of the vein wall to capture the vascular deformation while simultaneously record the current pressure value. The results of this study indicated that the pressure values tested by the new method have good correlation with the actual pressure value in animal experiments. The new method of noninvasive pressure measurement based on the airflow and laser detection technology is accurate, feasible, repeatable and has a good application prospects.

Automatic road sign detecion and classification based on support vector machines and HOG descriptos

NASA Astrophysics Data System (ADS)

Adam, A.; Ioannidis, C.

2014-05-01

This paper examines the detection and classification of road signs in color-images acquired by a low cost camera mounted on a moving vehicle. A new method for the detection and classification of road signs is proposed based on color based detection, in order to locate regions of interest. Then, a circular Hough transform is applied to complete detection taking advantage of the shape properties of the road signs. The regions of interest are finally represented using HOG descriptors and are fed into trained Support Vector Machines (SVMs) in order to be recognized. For the training procedure, a database with several training examples depicting Greek road sings has been developed. Many experiments have been conducted and are presented, to measure the efficiency of the proposed methodology especially under adverse weather conditions and poor illumination. For the experiments training datasets consisting of different number of examples were used and the results are presented, along with some possible extensions of this work.

Polydiacetylene-Based Liposomes: An "Optical Tongue" for Bacteria Detection and Identification

ERIC Educational Resources Information Center

West, Matthew R.; Hanks, Timothy W.; Watson, Rhett T.

2009-01-01

Food- and water-borne bacteria are a major health concern worldwide. Current detection methods are time-consuming and require sophisticated equipment that is not always readily available. However, new techniques based on nanotechnology are under development that will result in a new generation of sensors. In this experiment, liposomes are…

Trained neurons-based motion detection in optical camera communications

NASA Astrophysics Data System (ADS)

Teli, Shivani; Cahyadi, Willy Anugrah; Chung, Yeon Ho

2018-04-01

A concept of trained neurons-based motion detection (TNMD) in optical camera communications (OCC) is proposed. The proposed TNMD is based on neurons present in a neural network that perform repetitive analysis in order to provide efficient and reliable motion detection in OCC. This efficient motion detection can be considered another functionality of OCC in addition to two traditional functionalities of illumination and communication. To verify the proposed TNMD, the experiments were conducted in an indoor static downlink OCC, where a mobile phone front camera is employed as the receiver and an 8 × 8 red, green, and blue (RGB) light-emitting diode array as the transmitter. The motion is detected by observing the user's finger movement in the form of centroid through the OCC link via a camera. Unlike conventional trained neurons approaches, the proposed TNMD is trained not with motion itself but with centroid data samples, thus providing more accurate detection and far less complex detection algorithm. The experiment results demonstrate that the TNMD can detect all considered motions accurately with acceptable bit error rate (BER) performances at a transmission distance of up to 175 cm. In addition, while the TNMD is performed, a maximum data rate of 3.759 kbps over the OCC link is obtained. The OCC with the proposed TNMD combined can be considered an efficient indoor OCC system that provides illumination, communication, and motion detection in a convenient smart home environment.

Research on intrusion detection based on Kohonen network and support vector machine

NASA Astrophysics Data System (ADS)

Shuai, Chunyan; Yang, Hengcheng; Gong, Zeweiyi

2018-05-01

In view of the problem of low detection accuracy and the long detection time of support vector machine, which directly applied to the network intrusion detection system. Optimization of SVM parameters can greatly improve the detection accuracy, but it can not be applied to high-speed network because of the long detection time. a method based on Kohonen neural network feature selection is proposed to reduce the optimization time of support vector machine parameters. Firstly, this paper is to calculate the weights of the KDD99 network intrusion data by Kohonen network and select feature by weight. Then, after the feature selection is completed, genetic algorithm (GA) and grid search method are used for parameter optimization to find the appropriate parameters and classify them by support vector machines. By comparing experiments, it is concluded that feature selection can reduce the time of parameter optimization, which has little influence on the accuracy of classification. The experiments suggest that the support vector machine can be used in the network intrusion detection system and reduce the missing rate.

Shadow detection of moving objects based on multisource information in Internet of things

NASA Astrophysics Data System (ADS)

Ma, Zhen; Zhang, De-gan; Chen, Jie; Hou, Yue-xian

2017-05-01

Moving object detection is an important part in intelligent video surveillance under the banner of Internet of things. The detection of moving target's shadow is also an important step in moving object detection. On the accuracy of shadow detection will affect the detection results of the object directly. Based on the variety of shadow detection method, we find that only using one feature can't make the result of detection accurately. Then we present a new method for shadow detection which contains colour information, the invariance of optical and texture feature. Through the comprehensive analysis of the detecting results of three kinds of information, the shadow was effectively determined. It gets ideal effect in the experiment when combining advantages of various methods.

Design of a Multi-Sensor Cooperation Travel Environment Perception System for Autonomous Vehicle

PubMed Central

Chen, Long; Li, Qingquan; Li, Ming; Zhang, Liang; Mao, Qingzhou

2012-01-01

This paper describes the environment perception system designed for intelligent vehicle SmartV-II, which won the 2010 Future Challenge. This system utilizes the cooperation of multiple lasers and cameras to realize several necessary functions of autonomous navigation: road curb detection, lane detection and traffic sign recognition. Multiple single scan lasers are integrated to detect the road curb based on Z-variance method. Vision based lane detection is realized by two scans method combining with image model. Haar-like feature based method is applied for traffic sign detection and SURF matching method is used for sign classification. The results of experiments validate the effectiveness of the proposed algorithms and the whole system.

Amylin Detection with a Miniature Optical-Fiber Based Sensor

NASA Astrophysics Data System (ADS)

Liu, Zhaowen; Ann, Matsko; Hughes, Adam; Reeves, Mark

We present results of a biosensor based on shifts in the localized surface plasmon resonance of gold nanoparticles self-assembled on the end of an optical fiber. This system allows for detection of protein expression in low sensing volumes and for scanning in cell cultures and tissue samples. Positive and negative controls were done using biotin/avidin and the BSA/Anti-BSA system. These demonstrate that detection is specific and sensitive to nanomolar levels. Sensing of amylin, an important protein for pancreatic function, was performed with polyclonal and monoclonal antibodies. The measured data demonstrates the difference in sensitivity to the two types of antibodies, and titration experiments establish the sensitivity of the sensor. Further experiments demonstrate that the sensor can be regenerated and then reused.

Dual-Phase Lock-In Amplifier Based on FPGA for Low-Frequencies Experiments

PubMed Central

Macias-Bobadilla, Gonzalo; Rodríguez-Reséndiz, Juvenal; Mota-Valtierra, Georgina; Soto-Zarazúa, Genaro; Méndez-Loyola, Maurino; Garduño-Aparicio, Mariano

2016-01-01

Photothermal techniques allow the detection of characteristics of material without invading it. Researchers have developed hardware for some specific Phase and Amplitude detection (Lock-In Function) applications, eliminating space and unnecessary electronic functions, among others. This work shows the development of a Digital Lock-In Amplifier based on a Field Programmable Gate Array (FPGA) for low-frequency applications. This system allows selecting and generating the appropriated frequency depending on the kind of experiment or material studied. The results show good frequency stability in the order of 1.0 × 10−9 Hz, which is considered good linearity and repeatability response for the most common Laboratory Amplitude and Phase Shift detection devices, with a low error and standard deviation. PMID:26999138

Dual-Phase Lock-In Amplifier Based on FPGA for Low-Frequencies Experiments.

PubMed

Macias-Bobadilla, Gonzalo; Rodríguez-Reséndiz, Juvenal; Mota-Valtierra, Georgina; Soto-Zarazúa, Genaro; Méndez-Loyola, Maurino; Garduño-Aparicio, Mariano

2016-03-16

Photothermal techniques allow the detection of characteristics of material without invading it. Researchers have developed hardware for some specific Phase and Amplitude detection (Lock-In Function) applications, eliminating space and unnecessary electronic functions, among others. This work shows the development of a Digital Lock-In Amplifier based on a Field Programmable Gate Array (FPGA) for low-frequency applications. This system allows selecting and generating the appropriated frequency depending on the kind of experiment or material studied. The results show good frequency stability in the order of 1.0 × 10(-9) Hz, which is considered good linearity and repeatability response for the most common Laboratory Amplitude and Phase Shift detection devices, with a low error and standard deviation.

A habituation based approach for detection of visual changes in surveillance camera

NASA Astrophysics Data System (ADS)

Sha'abani, M. N. A. H.; Adan, N. F.; Sabani, M. S. M.; Abdullah, F.; Nadira, J. H. S.; Yasin, M. S. M.

2017-09-01

This paper investigates a habituation based approach in detecting visual changes using video surveillance systems in a passive environment. Various techniques have been introduced for dynamic environment such as motion detection, object classification and behaviour analysis. However, in a passive environment, most of the scenes recorded by the surveillance system are normal. Therefore, implementing a complex analysis all the time in the passive environment resulting on computationally expensive, especially when using a high video resolution. Thus, a mechanism of attention is required, where the system only responds to an abnormal event. This paper proposed a novelty detection mechanism in detecting visual changes and a habituation based approach to measure the level of novelty. The objective of the paper is to investigate the feasibility of the habituation based approach in detecting visual changes. Experiment results show that the approach are able to accurately detect the presence of novelty as deviations from the learned knowledge.

a New Object-Based Framework to Detect Shodows in High-Resolution Satellite Imagery Over Urban Areas

NASA Astrophysics Data System (ADS)

Tatar, N.; Saadatseresht, M.; Arefi, H.; Hadavand, A.

2015-12-01

In this paper a new object-based framework to detect shadow areas in high resolution satellite images is proposed. To produce shadow map in pixel level state of the art supervised machine learning algorithms are employed. Automatic ground truth generation based on Otsu thresholding on shadow and non-shadow indices is used to train the classifiers. It is followed by segmenting the image scene and create image objects. To detect shadow objects, a majority voting on pixel-based shadow detection result is designed. GeoEye-1 multi-spectral image over an urban area in Qom city of Iran is used in the experiments. Results shows the superiority of our proposed method over traditional pixel-based, visually and quantitatively.

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.

Decision-making by experienced rugby referees: use of perceptual information and episodic memory.

PubMed

MacMahon, Clare; Ste-Marie, Diane M

2002-10-01

The expertise paradigm was used in two studies to examine decision-making by rugby referees. Videoclips were used to assess infraction detection and knowledge base, or sources of information used. In Study 1, referees of high and low experience were compared, and in Study 2 referees and players were compared. Analysis by signal detection used a framework to classify types of information. Study 1 yielded no differences in detection of infractions as a function of experience, however, referees of high experience used significantly more sources of information than the group with low experience across all categories of information. In Study 2, there were no significant differences between referees and players, with the exception that referees displayed greater use of episodic memory information in decision-making.

Electrocardiographic signals and swarm-based support vector machine for hypoglycemia detection.

PubMed

Nuryani, Nuryani; Ling, Steve S H; Nguyen, H T

2012-04-01

Cardiac arrhythmia relating to hypoglycemia is suggested as a cause of death in diabetic patients. This article introduces electrocardiographic (ECG) parameters for artificially induced hypoglycemia detection. In addition, a hybrid technique of swarm-based support vector machine (SVM) is introduced for hypoglycemia detection using the ECG parameters as inputs. In this technique, a particle swarm optimization (PSO) is proposed to optimize the SVM to detect hypoglycemia. In an experiment using medical data of patients with Type 1 diabetes, the introduced ECG parameters show significant contributions to the performance of the hypoglycemia detection and the proposed detection technique performs well in terms of sensitivity and specificity.

Pump-probe experiments at the TEMPO beamline using the low-α operation mode of Synchrotron SOLEIL.

PubMed

Silly, Mathieu G; Ferté, Tom; Tordeux, Marie Agnes; Pierucci, Debora; Beaulieu, Nathan; Chauvet, Christian; Pressacco, Federico; Sirotti, Fausto; Popescu, Horia; Lopez-Flores, Victor; Tortarolo, Marina; Sacchi, Maurizio; Jaouen, Nicolas; Hollander, Philippe; Ricaud, Jean Paul; Bergeard, Nicolas; Boeglin, Christine; Tudu, Bharati; Delaunay, Renaud; Luning, Jan; Malinowski, Gregory; Hehn, Michel; Baumier, Cédric; Fortuna, Franck; Krizmancic, Damjan; Stebel, Luigi; Sergo, Rudi; Cautero, Giuseppe

2017-07-01

The SOLEIL synchrotron radiation source is regularly operated in special filling modes dedicated to pump-probe experiments. Among others, the low-α mode operation is characterized by shorter pulse duration and represents the natural bridge between 50 ps synchrotron pulses and femtosecond experiments. Here, the capabilities in low-α mode of the experimental set-ups developed at the TEMPO beamline to perform pump-probe experiments with soft X-rays based on photoelectron or photon detection are presented. A 282 kHz repetition-rate femtosecond laser is synchronized with the synchrotron radiation time structure to induce fast electronic and/or magnetic excitations. Detection is performed using a two-dimensional space resolution plus time resolution detector based on microchannel plates equipped with a delay line. Results of time-resolved photoelectron spectroscopy, circular dichroism and magnetic scattering experiments are reported, and their respective advantages and limitations in the framework of high-time-resolution pump-probe experiments compared and discussed.

A 16-Channel Nonparametric Spike Detection ASIC Based on EC-PC Decomposition.

PubMed

Wu, Tong; Xu, Jian; Lian, Yong; Khalili, Azam; Rastegarnia, Amir; Guan, Cuntai; Yang, Zhi

2016-02-01

In extracellular neural recording experiments, detecting neural spikes is an important step for reliable information decoding. A successful implementation in integrated circuits can achieve substantial data volume reduction, potentially enabling a wireless operation and closed-loop system. In this paper, we report a 16-channel neural spike detection chip based on a customized spike detection method named as exponential component-polynomial component (EC-PC) algorithm. This algorithm features a reliable prediction of spikes by applying a probability threshold. The chip takes raw data as input and outputs three data streams simultaneously: field potentials, band-pass filtered neural data, and spiking probability maps. The algorithm parameters are on-chip configured automatically based on input data, which avoids manual parameter tuning. The chip has been tested with both in vivo experiments for functional verification and bench-top experiments for quantitative performance assessment. The system has a total power consumption of 1.36 mW and occupies an area of 6.71 mm (2) for 16 channels. When tested on synthesized datasets with spikes and noise segments extracted from in vivo preparations and scaled according to required precisions, the chip outperforms other detectors. A credit card sized prototype board is developed to provide power and data management through a USB port.

Detection of cat-eye effect echo based on unit APD

NASA Astrophysics Data System (ADS)

Wu, Dong-Sheng; Zhang, Peng; Hu, Wen-Gang; Ying, Jia-Ju; Liu, Jie

2016-10-01

The cat-eye effect echo of optical system can be detected based on CCD, but the detection range is limited within several kilometers. In order to achieve long-range even ultra-long-range detection, it ought to select APD as detector because of the high sensitivity of APD. The detection system of cat-eye effect echo based on unit APD is designed in paper. The implementation scheme and key technology of the detection system is presented. The detection performances of the detection system including detection range, detection probability and false alarm probability are modeled. Based on the model, the performances of the detection system are analyzed using typical parameters. The results of numerical calculation show that the echo signal-to-noise ratio is greater than six, the detection probability is greater than 99.9% and the false alarm probability is less tan 0.1% within 20 km detection range. In order to verify the detection effect, we built the experimental platform of detection system according to the design scheme and carry out the field experiments. The experimental results agree well with the results of numerical calculation, which prove that the detection system based on the unit APD is feasible to realize remote detection for cat-eye effect echo.

The Stanford equivalence principle program

NASA Technical Reports Server (NTRS)

Worden, Paul W., Jr.; Everitt, C. W. Francis; Bye, M.

1989-01-01

The Stanford Equivalence Principle Program (Worden, Jr. 1983) is intended to test the uniqueness of free fall to the ultimate possible accuracy. The program is being conducted in two phases: first, a ground-based version of the experiment, which should have a sensitivity to differences in rate of fall of one part in 10(exp 12); followed by an orbital experiment with a sensitivity of one part in 10(exp 17) or better. The ground-based experiment, although a sensitive equivalence principle test in its own right, is being used for technology development for the orbital experiment. A secondary goal of the experiment is a search for exotic forces. The instrument is very well suited for this search, which would be conducted mostly with the ground-based apparatus. The short range predicted for these forces means that forces originating in the Earth would not be detectable in orbit. But detection of Yukawa-type exotic forces from a nearby large satellite (such as Space Station) is feasible, and gives a very sensitive and controllable test for little more effort than the orbiting equivalence principle test itself.

Single-molecule detection: applications to ultrasensitive biochemical analysis

NASA Astrophysics Data System (ADS)

Castro, Alonso; Shera, E. Brooks

1995-06-01

Recent developments in laser-based detection of fluorescent molecules have made possible the implementation of very sensitive techniques for biochemical analysis. We present and discuss our experiments on the applications of our recently developed technique of single-molecule detection to the analysis of molecules of biological interest. These newly developed methods are capable of detecting and identifying biomolecules at the single-molecule level of sensitivity. In one case, identification is based on measuring fluorescence brightness from single molecules. In another, molecules are classified by determining their electrophoretic velocities.

Design of fire detection equipment based on ultraviolet detection technology

NASA Astrophysics Data System (ADS)

Liu, Zhenji; Liu, Jin; Chu, Sheng; Ping, Chao; Yuan, Xiaobing

2015-03-01

Utilized the feature of wide bandgap semiconductor of MgZnO, researched and developed a kind of Mid-Ultraviolet-Band(MUV) ultraviolet detector which has passed the simulation experiment in the sun circumstance. Based on the ultraviolet detector, it gives out a design scheme of gun-shot detection device, which is composed of twelve ultraviolet detectors, signal amplifier, processor, annunciator , azimuth indicator and the bracket. Through Analysing the feature of solar blind, ultraviolet responsivity, fire feature of gunshots and detection distance, the feasibility of this design scheme is proved.

Non-contact detection of cardiac rate based on visible light imaging device

NASA Astrophysics Data System (ADS)

Zhu, Huishi; Zhao, Yuejin; Dong, Liquan

2012-10-01

We have developed a non-contact method to detect human cardiac rate at a distance. This detection is based on the general lighting condition. Using the video signal of human face region captured by webcam, we acquire the cardiac rate based on the PhotoPlethysmoGraphy theory. In this paper, the cardiac rate detecting method is mainly in view of the blood's different absorptivities of the lights various wavelengths. Firstly, we discompose the video signal into RGB three color signal channels and choose the face region as region of interest to take average gray value. Then, we draw three gray-mean curves on each color channel with time as variable. When the imaging device has good fidelity of color, the green channel signal shows the PhotoPlethysmoGraphy information most clearly. But the red and blue channel signals can provide more other physiological information on the account of their light absorptive characteristics of blood. We divide red channel signal by green channel signal to acquire the pulse wave. With the passband from 0.67Hz to 3Hz as a filter of the pulse wave signal and the frequency spectrum superimposed algorithm, we design frequency extracted algorithm to achieve the cardiac rate. Finally, we experiment with 30 volunteers, containing different genders and different ages. The results of the experiments are all relatively agreeable. The difference is about 2bmp. Through the experiment, we deduce that the PhotoPlethysmoGraphy theory based on visible light can also be used to detect other physiological information.

Enhancing Risk Detection Among Homeless Youth: A Randomized Clinical Trial of a Promising Pilot Intervention.

PubMed

Bender, Kimberly A; DePrince, Anne; Begun, Stephanie; Hathaway, Jessica; Haffejee, Badiah; Schau, Nicholas

2016-03-02

Homeless youth frequently experience victimization, and youth with histories of trauma often fail to detect danger risks, making them vulnerable to subsequent victimization. The current study describes a pilot test of a skills-based intervention designed to improve risk detection among homeless youth through focusing attention to internal, interpersonal, and environmental cues. Youth aged 18 to 21 years (N = 74) were recruited from a shelter and randomly assigned to receive usual case management services or usual services plus a 3-day manualized risk detection intervention. Pretest and posttest interviews assessed youths' risk detection abilities through vignettes describing risky situations and asking youth to identify risk cues present. Separate 2 (intervention vs. control) × 2 (pretest vs. posttest) mixed ANOVAs found significant interaction effects, as intervention youth significantly improved in overall risk detection compared with control youth. Post hoc subgroup analyses found the intervention had a greater effect for youth without previous experiences of indirect victimization than those with previous indirect victimization experiences. © The Author(s) 2016.

A malware detection scheme based on mining format information.

PubMed

Bai, Jinrong; Wang, Junfeng; Zou, Guozhong

2014-01-01

Malware has become one of the most serious threats to computer information system and the current malware detection technology still has very significant limitations. In this paper, we proposed a malware detection approach by mining format information of PE (portable executable) files. Based on in-depth analysis of the static format information of the PE files, we extracted 197 features from format information of PE files and applied feature selection methods to reduce the dimensionality of the features and achieve acceptable high performance. When the selected features were trained using classification algorithms, the results of our experiments indicate that the accuracy of the top classification algorithm is 99.1% and the value of the AUC is 0.998. We designed three experiments to evaluate the performance of our detection scheme and the ability of detecting unknown and new malware. Although the experimental results of identifying new malware are not perfect, our method is still able to identify 97.6% of new malware with 1.3% false positive rates.

A Malware Detection Scheme Based on Mining Format Information

PubMed Central

Bai, Jinrong; Wang, Junfeng; Zou, Guozhong

2014-01-01

Malware has become one of the most serious threats to computer information system and the current malware detection technology still has very significant limitations. In this paper, we proposed a malware detection approach by mining format information of PE (portable executable) files. Based on in-depth analysis of the static format information of the PE files, we extracted 197 features from format information of PE files and applied feature selection methods to reduce the dimensionality of the features and achieve acceptable high performance. When the selected features were trained using classification algorithms, the results of our experiments indicate that the accuracy of the top classification algorithm is 99.1% and the value of the AUC is 0.998. We designed three experiments to evaluate the performance of our detection scheme and the ability of detecting unknown and new malware. Although the experimental results of identifying new malware are not perfect, our method is still able to identify 97.6% of new malware with 1.3% false positive rates. PMID:24991639

Damage Detection Using Lamb Waves for Structural Health Monitoring

DTIC Science & Technology

2007-03-01

experiments have been reported by Seth Kessler [8]. 2.2 Large Aluminum Plate The second experiment included a 2024-0 aluminum plate with dimensions of...Mechanical Engineering Congress , (IMECE2002- 39017) (17-22 November 2002). 6. Kessler , Seth S. Piezoelectric-Based In-Situ Damage Detection of...Composite Materials for Structural Health Monitoring Systems. Ph.D. thesis, Massachusetts Institute of Technology, January 2002. 7. Kessler , Seth S. “Metis

Highly Portable, Sensor-Based System for Human Fall Monitoring.

PubMed

Mao, Aihua; Ma, Xuedong; He, Yinan; Luo, Jie

2017-09-13

Falls are a very dangerous situation especially among elderly people, because they may lead to fractures, concussion, and other injuries. Without timely rescue, falls may even endanger their lives. The existing optical sensor-based fall monitoring systems have some disadvantages, such as limited monitoring range and inconvenience to carry for users. Furthermore, the fall detection system based only on an accelerometer often mistakenly determines some activities of daily living (ADL) as falls, leading to low accuracy in fall detection. We propose a human fall monitoring system consisting of a highly portable sensor unit including a triaxis accelerometer, a triaxis gyroscope, and a triaxis magnetometer, and a mobile phone. With the data from these sensors, we obtain the acceleration and Euler angle (yaw, pitch, and roll), which represents the orientation of the user's body. Then, a proposed fall detection algorithm was used to detect falls based on the acceleration and Euler angle. With this monitoring system, we design a series of simulated falls and ADL and conduct the experiment by placing the sensors on the shoulder, waist, and foot of the subjects. Through the experiment, we re-identify the threshold of acceleration for accurate fall detection and verify the best body location to place the sensors by comparing the detection performance on different body segments. We also compared this monitoring system with other similar works and found that better fall detection accuracy and portability can be achieved by our system.

Highly Portable, Sensor-Based System for Human Fall Monitoring

PubMed Central

Mao, Aihua; Ma, Xuedong; He, Yinan; Luo, Jie

2017-01-01

Falls are a very dangerous situation especially among elderly people, because they may lead to fractures, concussion, and other injuries. Without timely rescue, falls may even endanger their lives. The existing optical sensor-based fall monitoring systems have some disadvantages, such as limited monitoring range and inconvenience to carry for users. Furthermore, the fall detection system based only on an accelerometer often mistakenly determines some activities of daily living (ADL) as falls, leading to low accuracy in fall detection. We propose a human fall monitoring system consisting of a highly portable sensor unit including a triaxis accelerometer, a triaxis gyroscope, and a triaxis magnetometer, and a mobile phone. With the data from these sensors, we obtain the acceleration and Euler angle (yaw, pitch, and roll), which represents the orientation of the user’s body. Then, a proposed fall detection algorithm was used to detect falls based on the acceleration and Euler angle. With this monitoring system, we design a series of simulated falls and ADL and conduct the experiment by placing the sensors on the shoulder, waist, and foot of the subjects. Through the experiment, we re-identify the threshold of acceleration for accurate fall detection and verify the best body location to place the sensors by comparing the detection performance on different body segments. We also compared this monitoring system with other similar works and found that better fall detection accuracy and portability can be achieved by our system. PMID:28902149

Exploring "fringe" consciousness: the subjective experience of perceptual fluency and its objective bases.

PubMed

Reber, Rolf; Wurtz, Pascal; Zimmermann, Thomas D

2004-03-01

Perceptual fluency is the subjective experience of ease with which an incoming stimulus is processed. Although perceptual fluency is assessed by speed of processing, it remains unclear how objective speed is related to subjective experiences of fluency. We present evidence that speed at different stages of the perceptual process contributes to perceptual fluency. In an experiment, figure-ground contrast influenced detection of briefly presented words, but not their identification at longer exposure durations. Conversely, font in which the word was written influenced identification, but not detection. Both contrast and font influenced subjective fluency. These findings suggest that speed of processing at different stages condensed into a unified subjective experience of perceptual fluency.

[The design and experiment of multi-parameter water quality monitoring microsystem based on MOEMS microspectrometer].

PubMed

Wei, Kang-Lin; Wen, Zhi-Yu; Guo, Jian; Chen, Song-Bo

2012-07-01

Aiming at the monitoring and protecting of water resource environment, a multi-parameter water quality monitoring microsystem based on microspectrometer was put forward in the present paper. The microsystem is mainly composed of MOEMS microspectrometer, flow paths system and embedded measuring & controlling system. It has the functions of self-injecting samples and detection regents, automatic constant temperature, self -stirring, self- cleaning and samples' spectrum detection. The principle prototype machine of the microsystem was developed, and its structure principle was introduced in the paper. Through experiment research, it was proved that the principle prototype machine can rapidly detect quite a few water quality parameters and can meet the demands of on-line water quality monitoring, moreover, the principle prototype machine has strong function expansibility.

Standoff detection of explosives: a challenging approach for optical technologies

NASA Astrophysics Data System (ADS)

Désilets, S.; Hô, N.; Mathieu, P.; Simard, J. R.; Puckrin, E.; Thériault, J. M.; Lavoie, H.; Théberge, F.; Babin, F.; Gay, D.; Forest, R.; Maheux, J.; Roy, G.; Châteauneuf, M.

2011-06-01

Standoff detection of explosives residues on surfaces at few meters was made using optical technologies based on Raman scattering, Laser-Induced Breakdown Spectroscopy (LIBS) and passive standoff FTIR radiometry. By comparison, detection and analysis of nanogram samples of different explosives was made with a microscope system where Raman scattering from a micron-size single point illuminated crystal of explosive was observed. Results from standoff detection experiments using a telescope were compared to experiments using a microscope to find out important parameters leading to the detection. While detection and spectral identification of the micron-size explosive particles was possible with a microscope, standoff detection of these particles was very challenging due to undesired light reflected and produced by the background surface or light coming from other contaminants. Results illustrated the challenging approach of detecting at a standoff distance the presence of low amount of micron or submicron explosive particles.

Echogenicity based approach to detect, segment and track the common carotid artery in 2D ultrasound images.

PubMed

Narayan, Nikhil S; Marziliano, Pina

2015-08-01

Automatic detection and segmentation of the common carotid artery in transverse ultrasound (US) images of the thyroid gland play a vital role in the success of US guided intervention procedures. We propose in this paper a novel method to accurately detect, segment and track the carotid in 2D and 2D+t US images of the thyroid gland using concepts based on tissue echogenicity and ultrasound image formation. We first segment the hypoechoic anatomical regions of interest using local phase and energy in the input image. We then make use of a Hessian based blob like analysis to detect the carotid within the segmented hypoechoic regions. The carotid artery is segmented by making use of least squares ellipse fit for the edge points around the detected carotid candidate. Experiments performed on a multivendor dataset of 41 images show that the proposed algorithm can segment the carotid artery with high sensitivity (99.6 ±m 0.2%) and specificity (92.9 ±m 0.1%). Further experiments on a public database containing 971 images of the carotid artery showed that the proposed algorithm can achieve a detection accuracy of 95.2% with a 2% increase in performance when compared to the state-of-the-art method.

Capacitor-based detection of nuclear magnetization: nuclear quadrupole resonance of surfaces.

PubMed

Gregorovič, Alan; Apih, Tomaž; Kvasić, Ivan; Lužnik, Janko; Pirnat, Janez; Trontelj, Zvonko; Strle, Drago; Muševič, Igor

2011-03-01

We demonstrate excitation and detection of nuclear magnetization in a nuclear quadrupole resonance (NQR) experiment with a parallel plate capacitor, where the sample is located between the two capacitor plates and not in a coil as usually. While the sensitivity of this capacitor-based detection is found lower compared to an optimal coil-based detection of the same amount of sample, it becomes comparable in the case of very thin samples and even advantageous in the proximity of conducting bodies. This capacitor-based setup may find its application in acquisition of NQR signals from the surface layers on conducting bodies or in a portable tightly integrated nuclear magnetic resonance sensor. Copyright © 2010 Elsevier Inc. All rights reserved.

An interaural-correlation-based approach that accounts for a wide variety of binaural detection data.

PubMed

Bernstein, Leslie R; Trahiotis, Constantine

2017-02-01

Interaural cross-correlation-based models of binaural processing have accounted successfully for a wide variety of binaural phenomena, including binaural detection, binaural discrimination, and measures of extents of laterality based on interaural temporal disparities, interaural intensitive disparities, and their combination. This report focuses on quantitative accounts of data obtained from binaural detection experiments published over five decades. Particular emphasis is placed on stimulus contexts for which commonly used correlation-based approaches fail to provide adequate explanations of the data. One such context concerns binaural detection of signals masked by certain noises that are narrow-band and/or interaurally partially correlated. It is shown that a cross-correlation-based model that includes stages of peripheral auditory processing can, when coupled with an appropriate decision variable, account well for a wide variety of classic and recently published binaural detection data including those that have, heretofore, proven to be problematic.

A fuzzy pattern matching method based on graph kernel for lithography hotspot detection

NASA Astrophysics Data System (ADS)

Nitta, Izumi; Kanazawa, Yuzi; Ishida, Tsutomu; Banno, Koji

2017-03-01

In advanced technology nodes, lithography hotspot detection has become one of the most significant issues in design for manufacturability. Recently, machine learning based lithography hotspot detection has been widely investigated, but it has trade-off between detection accuracy and false alarm. To apply machine learning based technique to the physical verification phase, designers require minimizing undetected hotspots to avoid yield degradation. They also need a ranking of similar known patterns with a detected hotspot to prioritize layout pattern to be corrected. To achieve high detection accuracy and to prioritize detected hotspots, we propose a novel lithography hotspot detection method using Delaunay triangulation and graph kernel based machine learning. Delaunay triangulation extracts features of hotspot patterns where polygons locate irregularly and closely one another, and graph kernel expresses inner structure of graphs. Additionally, our method provides similarity between two patterns and creates a list of similar training patterns with a detected hotspot. Experiments results on ICCAD 2012 benchmarks show that our method achieves high accuracy with allowable range of false alarm. We also show the ranking of the similar known patterns with a detected hotspot.

Development of Smartphone based Optical Device

NASA Astrophysics Data System (ADS)

Jung, Youngkee

Due to the economy of scale, smartphones are becoming more affordable while their computing powers are increasing dramatically every year. Here we propose a ubiquitous and portable instrument for analyte quantitation by utilizing the characteristics of typical smartphone imaging system and specific design of transducers for different applications. Three testbeds included in this work are: quantitative colorimetric analysis, ultra-low radiant flux detection, and portable spectrometer. As a proof-of-principle for each device, 3-D printed cradle and theoretical simulation with MATLAB have been implemented. First example utilizes the native CMOS camera with their respective RGB channel data and perform an analyte quantitation for typical lateral flow devices (LFD). Histogram analysis method has been employed to detect the analyte concentration and calibration results show good correlation between perceived color change and analyte concentration. The second example shows the possibility of using a conventional CMOS camera for pico Watt level photon flux detection. Since most of consumer grade CMOS cameras cannot detect this level of light intensity and their dark current are relatively higher, a new algorithm called NREA (Noise Reduction by Ensemble Averaging) algorithm was developed to effectively reduce the noise level and increase the SNR (signal to noise ratio). This technique is effective for bioanalytical assays that has lower flux intensity such as fluorescence and luminescence. As a proof-of-principle, we tested the device with Pseudomonas fluorescens M3A and achieved a limit of detection of high 10? CFU/ml. In addition to basic schematic of detection model, another experiment with a silicon photomultiplier (SiPM) has been studied for more sensitive light detectability. Based on both the laser experiment and tw bioluminescent experiments, named Pseudomonas fluorescens M3A and NanoLuc, we found that the miniSM based device has a superior ability than the smartphone to detect the low light intensity. Finally, smartphone based spectrometers have been developed and experiments have been performed to demonstrate its availability. Smartphone spectrometers were designed with two kinds of spectrometer functions, absorbance and reflection spectrometer. Based on the diffraction theory, the experimental results were compared with simulation results and demonstrated the feasibility as a spectrometer. Peak locations were calibrated with diode lasers in three wavelengths (405 nm, 532 nm and 635 nm) and specific software application was developed to capture a spectrum. A Biuret test was done to test its feasibility as an absorbance spectrometer. To show the possibility as a reflection spectrometer, the real meat test was done using a standard experimental process of meat freshness analysis.

Integration of Nanoparticle-Based Paper Sensors into the Classroom: An Example of Application for Rapid Colorimetric Analysis of Antioxidants

ERIC Educational Resources Information Center

Sharpe, Erica; Andreescu, Silvana

2015-01-01

We describe a laboratory experiment that employs the Nanoceria Reducing Antioxidant Capacity (or NanoCerac) Assay to introduce students to portable nanoparticle-based paper sensors for rapid analysis and field detection of polyphenol antioxidants. The experiment gives students a hands-on opportunity to utilize nanoparticle chemistry to develop…

Students Doing Chemistry: A Hand-On Experience for K-12

ERIC Educational Resources Information Center

Selco, Jodye I.; Bruno, Mary; Chan, Sue

2012-01-01

A hands-on, minds-on inquiry chemistry experiment was developed for use in K-12 schools that enables students to combine the chemicals of their choice and observe the results. The chemistry involved is water based and builds upon acid-base, double displacement, and iodometric detection of starch reactions. Chemicals readily available in the…

Pooling of Immunomagnetic Separation Beads Does Not Affect Detection Sensitivity of Six Major Serogroups of Shiga Toxin-Producing Escherichia coli in Cattle Feces.

PubMed

Noll, Lance W; Baumgartner, William C; Shridhar, Pragathi B; Cull, Charley A; Dewsbury, Diana M; Shi, Xiaorong; Cernicchiaro, Natalia; Renter, David G; Nagaraja, T G

2016-01-01

Shiga toxin-producing Escherichia coli (STEC) of the serogroups O26, O45, O103, O111, O121, and O145, often called non-O157 STEC, are foodborne pathogens. Cattle are asymptomatic reservoirs for STEC; the organisms reside in the hindgut and are shed in the feces, which serve as the source of food product contaminations. Culture-based detection of non-O157 STEC involves an immunomagnetic separation (IMS) step to capture the specific serogroups in complex matrices, such as feces. The IMS procedure is time consuming and labor intensive because of the need to subject each fecal sample to six individual beads. Therefore, our objective was to evaluate whether pooling of IMS beads affects sensitivity of non-O157 STEC detection compared with using individual IMS beads. The evaluation was done by comparing detection of serogroups in feces spiked with pure cultures (experiments 1 and 2) and from feces (n = 384) of naturally shedding cattle (experiment 3). In spiked fecal samples, detection with pools of three, four, six, or seven beads was similar to, or at times higher than, detection with individual IMS beads. In experiment 3, the proportions of fecal samples that tested positive for the six serogroups as detected by individual or pooled beads were similar. Based on noninferiority tests, detection with pooled beads was not substantially inferior to detection with individual beads (P > 0.05). In conclusion, the pooling of IMS beads is a better option for detection of STEC serogroups in fecal samples compared with individual beads because the procedure saves time and labor and has the prospect of a higher throughput.

Latest Progress of Fault Detection and Localization in Complex Electrical Engineering

NASA Astrophysics Data System (ADS)

Zhao, Zheng; Wang, Can; Zhang, Yagang; Sun, Yi

2014-01-01

In the researches of complex electrical engineering, efficient fault detection and localization schemes are essential to quickly detect and locate faults so that appropriate and timely corrective mitigating and maintenance actions can be taken. In this paper, under the current measurement precision of PMU, we will put forward a new type of fault detection and localization technology based on fault factor feature extraction. Lots of simulating experiments indicate that, although there are disturbances of white Gaussian stochastic noise, based on fault factor feature extraction principal, the fault detection and localization results are still accurate and reliable, which also identifies that the fault detection and localization technology has strong anti-interference ability and great redundancy.

Efficient detection of dangling pointer error for C/C++ programs

NASA Astrophysics Data System (ADS)

Zhang, Wenzhe

2017-08-01

Dangling pointer error is pervasive in C/C++ programs and it is very hard to detect. This paper introduces an efficient detector to detect dangling pointer error in C/C++ programs. By selectively leave some memory accesses unmonitored, our method could reduce the memory monitoring overhead and thus achieves better performance over previous methods. Experiments show that our method could achieve an average speed up of 9% over previous compiler instrumentation based method and more than 50% over previous page protection based method.

False star detection and isolation during star tracking based on improved chi-square tests.

PubMed

Zhang, Hao; Niu, Yanxiong; Lu, Jiazhen; Yang, Yanqiang; Su, Guohua

2017-08-01

The star sensor is a precise attitude measurement device for a spacecraft. Star tracking is the main and key working mode for a star sensor. However, during star tracking, false stars become an inevitable interference for star sensor applications, which may result in declined measurement accuracy. A false star detection and isolation algorithm in star tracking based on improved chi-square tests is proposed in this paper. Two estimations are established based on a Kalman filter and a priori information, respectively. The false star detection is operated through adopting the global state chi-square test in a Kalman filter. The false star isolation is achieved using a local state chi-square test. Semi-physical experiments under different trajectories with various false stars are designed for verification. Experiment results show that various false stars can be detected and isolated from navigation stars during star tracking, and the attitude measurement accuracy is hardly influenced by false stars. The proposed algorithm is proved to have an excellent performance in terms of speed, stability, and robustness.

Magnetoelastic Effect-Based Transmissive Stress Detection for Steel Strips: Theory and Experiment

PubMed Central

Zhang, Qingdong; Su, Yuanxiao; Zhang, Liyuan; Bi, Jia; Luo, Jiang

2016-01-01

For the deficiencies of traditional stress detection methods for steel strips in industrial production, this paper proposes a non-contact stress detection scheme based on the magnetoelastic effect. The theoretical model of the transmission-type stress detection is established, in which the output voltage and the tested stress obey a linear relation. Then, a stress detection device is built for the experiment, and Q235 steel under uniaxial tension is tested as an example. The result shows that the output voltage rises linearly with the increase of the tensile stress, consistent with the theoretical prediction. To ensure the accuracy of the stress detection method in actual application, the temperature compensation, magnetic shielding and some other key technologies are investigated to reduce the interference of the external factors, such as environment temperature and surrounding magnetic field. The present research develops the theoretical and experimental foundations for the magnetic stress detection system, which can be used for online non-contact monitoring of strip flatness-related stress (tension distribution or longitudinal residual stress) in the steel strip rolling process, the quality evaluation of strip flatness after rolling, the life and safety assessment of metal construction and other industrial production links. PMID:27589742

Region Based CNN for Foreign Object Debris Detection on Airfield Pavement

PubMed Central

Cao, Xiaoguang; Wang, Peng; Meng, Cai; Gong, Guoping; Liu, Miaoming; Qi, Jun

2018-01-01

In this paper, a novel algorithm based on convolutional neural network (CNN) is proposed to detect foreign object debris (FOD) based on optical imaging sensors. It contains two modules, the improved region proposal network (RPN) and spatial transformer network (STN) based CNN classifier. In the improved RPN, some extra select rules are designed and deployed to generate high quality candidates with fewer numbers. Moreover, the efficiency of CNN detector is significantly improved by introducing STN layer. Compared to faster R-CNN and single shot multiBox detector (SSD), the proposed algorithm achieves better result for FOD detection on airfield pavement in the experiment. PMID:29494524

Region Based CNN for Foreign Object Debris Detection on Airfield Pavement.

PubMed

Cao, Xiaoguang; Wang, Peng; Meng, Cai; Bai, Xiangzhi; Gong, Guoping; Liu, Miaoming; Qi, Jun

2018-03-01

In this paper, a novel algorithm based on convolutional neural network (CNN) is proposed to detect foreign object debris (FOD) based on optical imaging sensors. It contains two modules, the improved region proposal network (RPN) and spatial transformer network (STN) based CNN classifier. In the improved RPN, some extra select rules are designed and deployed to generate high quality candidates with fewer numbers. Moreover, the efficiency of CNN detector is significantly improved by introducing STN layer. Compared to faster R-CNN and single shot multiBox detector (SSD), the proposed algorithm achieves better result for FOD detection on airfield pavement in the experiment.

Design of a Golf Swing Injury Detection and Evaluation open service platform with Ontology-oriented clustering case-based reasoning mechanism.

PubMed

Ku, Hao-Hsiang

2015-01-01

Nowadays, people can easily use a smartphone to get wanted information and requested services. Hence, this study designs and proposes a Golf Swing Injury Detection and Evaluation open service platform with Ontology-oritened clustering case-based reasoning mechanism, which is called GoSIDE, based on Arduino and Open Service Gateway initative (OSGi). GoSIDE is a three-tier architecture, which is composed of Mobile Users, Application Servers and a Cloud-based Digital Convergence Server. A mobile user is with a smartphone and Kinect sensors to detect the user's Golf swing actions and to interact with iDTV. An application server is with Intelligent Golf Swing Posture Analysis Model (iGoSPAM) to check a user's Golf swing actions and to alter this user when he is with error actions. Cloud-based Digital Convergence Server is with Ontology-oriented Clustering Case-based Reasoning (CBR) for Quality of Experiences (OCC4QoE), which is designed to provide QoE services by QoE-based Ontology strategies, rules and events for this user. Furthermore, GoSIDE will automatically trigger OCC4QoE and deliver popular rules for a new user. Experiment results illustrate that GoSIDE can provide appropriate detections for Golfers. Finally, GoSIDE can be a reference model for researchers and engineers.

The SPQR experiment: detecting damage to orbiting spacecraft with ground-based telescopes

NASA Astrophysics Data System (ADS)

Paolozzi, Antonio; Porfilio, Manfredi; Currie, Douglas G.; Dantowitz, Ronald F.

2007-09-01

The objective of the Specular Point-like Quick Reference (SPQR) experiment was to evaluate the possibility of improving the resolution of ground-based telescopic imaging of manned spacecraft in orbit. The concept was to reduce image distortions due to atmospheric turbulence by evaluating the Point Spread Function (PSF) of a point-like light reference and processing the spacecraft image accordingly. The target spacecraft was the International Space Station (ISS) and the point-like reference was provided by a laser beam emitted by the ground station and reflected back to the telescope by a Cube Corner Reflector (CCR) mounted on an ISS window. The ultimate objective of the experiment was to demonstrate that it is possible to image spacecraft in Low Earth Orbit (LEO) with a resolution of 20 cm, which would have probably been sufficient to detect the damage which caused the Columbia disaster. The experiment was successfully performed from March to May 2005. The paper provides an overview of the SPQR experiment.

[Research on early fire detection with CO-CO2 FTIR-spectroscopy].

PubMed

Du, Jian-hua; Zhang, Ren-cheng; Huang, Xiang-ying; Gong, Xue; Zhang, Xiao-hua

2007-05-01

A new fire detection method is put forward based on the theory of FTIR spectroscopy through analyzing all kinds of detection methods, in which CO and CO2 are chosen as early fire detection objects, and an early fire experiment system has been set up. The concentration characters of CO and CO2 were obtained through early fire experiments including real alarm sources and nuisance alarm sources. In real alarm sources there are abundant CO and CO2 which change regularly. In nuisance alarm sources there is almost no CO. So it's feasible to reduce the false alarms and increase the sensitivity of early fire detectors through analyzing the concentration characters of CO and CO2.

Image denoising based on noise detection

NASA Astrophysics Data System (ADS)

Jiang, Yuanxiang; Yuan, Rui; Sun, Yuqiu; Tian, Jinwen

2018-03-01

Because of the noise points in the images, any operation of denoising would change the original information of non-noise pixel. A noise detection algorithm based on fractional calculus was proposed to denoise in this paper. Convolution of the image was made to gain direction gradient masks firstly. Then, the mean gray was calculated to obtain the gradient detection maps. Logical product was made to acquire noise position image next. Comparisons in the visual effect and evaluation parameters after processing, the results of experiment showed that the denoising algorithms based on noise were better than that of traditional methods in both subjective and objective aspects.

A Cyber-Attack Detection Model Based on Multivariate Analyses

NASA Astrophysics Data System (ADS)

Sakai, Yuto; Rinsaka, Koichiro; Dohi, Tadashi

In the present paper, we propose a novel cyber-attack detection model based on two multivariate-analysis methods to the audit data observed on a host machine. The statistical techniques used here are the well-known Hayashi's quantification method IV and cluster analysis method. We quantify the observed qualitative audit event sequence via the quantification method IV, and collect similar audit event sequence in the same groups based on the cluster analysis. It is shown in simulation experiments that our model can improve the cyber-attack detection accuracy in some realistic cases where both normal and attack activities are intermingled.

Multiple targets detection method in detection of UWB through-wall radar

NASA Astrophysics Data System (ADS)

Yang, Xiuwei; Yang, Chuanfa; Zhao, Xingwen; Tian, Xianzhong

2017-11-01

In this paper, the problems and difficulties encountered in the detection of multiple moving targets by UWB radar are analyzed. The experimental environment and the penetrating radar system are established. An adaptive threshold method based on local area is proposed to effectively filter out clutter interference The objective of the moving target is analyzed, and the false target is further filtered out by extracting the target feature. Based on the correlation between the targets, the target matching algorithm is proposed to improve the detection accuracy. Finally, the effectiveness of the above method is verified by practical experiment.

[Research on Detection Method with Wearable Respiration Device Based on the Theory of Bio-impedance].

PubMed

Liu, Guangda; Wang, Xianzhong; Cai, Jing; Wang, Wei; Zha, Yutong

2016-12-01

Considering the importance of the human respiratory signal detection and based on the Cole-Cole bio-impedance model,we developed a wearable device for detecting human respiratory signal.The device can be used to analyze the impedance characteristics of human body at different frequencies based on the bio-impedance theory.The device is also based on the method of proportion measurement to design a high signal to noise ratio(SNR)circuit to get human respiratory signal.In order to obtain the waveform of the respiratory signal and the value of the respiration rate,we used the techniques of discrete Fourier transform(DFT)and dynamic difference threshold peak detection.Experiments showed that this system was valid,and we could see that it could accurately detect the waveform of respiration and the detection accuracy rate of respiratory wave peak point detection results was over 98%.So it can meet the needs of the actual breath test.

An uncertainty-based distributed fault detection mechanism for wireless sensor networks.

PubMed

Yang, Yang; Gao, Zhipeng; Zhou, Hang; Qiu, Xuesong

2014-04-25

Exchanging too many messages for fault detection will cause not only a degradation of the network quality of service, but also represents a huge burden on the limited energy of sensors. Therefore, we propose an uncertainty-based distributed fault detection through aided judgment of neighbors for wireless sensor networks. The algorithm considers the serious influence of sensing measurement loss and therefore uses Markov decision processes for filling in missing data. Most important of all, fault misjudgments caused by uncertainty conditions are the main drawbacks of traditional distributed fault detection mechanisms. We draw on the experience of evidence fusion rules based on information entropy theory and the degree of disagreement function to increase the accuracy of fault detection. Simulation results demonstrate our algorithm can effectively reduce communication energy overhead due to message exchanges and provide a higher detection accuracy ratio.

Automated Thermal Sample Acquisition with Applications

NASA Astrophysics Data System (ADS)

Kooshesh, K. A.; Lineberger, D. H.

2012-03-01

We created an Arduino®-based robot to detect samples subject to an experiment, perform measurements once each sample is located, and store the results for further analysis. We then relate the robot’s performance to an experiment on thermal inertia.

Resolution Enhanced Magnetic Sensing System for Wide Coverage Real Time UXO Detection

NASA Astrophysics Data System (ADS)

Zalevsky, Zeev; Bregman, Yuri; Salomonski, Nizan; Zafrir, Hovav

2012-09-01

In this paper we present a new high resolution automatic detection algorithm based upon a Wavelet transform and then validate it in marine related experiments. The proposed approach allows obtaining an automatic detection in a very low signal to noise ratios. The amount of calculations is reduced, the magnetic trend is depressed and the probability of detection/ false alarm rate can easily be controlled. Moreover, the algorithm enables to distinguish between close targets. In the algorithm we use the physical dependence of the magnetic field of a magnetic dipole in order to define a Wavelet mother function that later on can detect magnetic targets modeled as dipoles and embedded in noisy surrounding, at improved resolution. The proposed algorithm was realized on synthesized targets and then validated in field experiments involving a marine surface-floating system for wide coverage real time unexploded ordinance (UXO) detection and mapping. The detection probability achieved in the marine experiment was above 90%. The horizontal radial error of most of the detected targets was only 16 m and two baseline targets that were immersed about 20 m one to another could easily be distinguished.

Detection of network attacks based on adaptive resonance theory

NASA Astrophysics Data System (ADS)

Bukhanov, D. G.; Polyakov, V. M.

2018-05-01

The paper considers an approach to intrusion detection systems using a neural network of adaptive resonant theory. It suggests the structure of an intrusion detection system consisting of two types of program modules. The first module manages connections of user applications by preventing the undesirable ones. The second analyzes the incoming network traffic parameters to check potential network attacks. After attack detection, it notifies the required stations using a secure transmission channel. The paper describes the experiment on the detection and recognition of network attacks using the test selection. It also compares the obtained results with similar experiments carried out by other authors. It gives findings and conclusions on the sufficiency of the proposed approach. The obtained information confirms the sufficiency of applying the neural networks of adaptive resonant theory to analyze network traffic within the intrusion detection system.

Robust vehicle detection under various environmental conditions using an infrared thermal camera and its application to road traffic flow monitoring.

PubMed

Iwasaki, Yoichiro; Misumi, Masato; Nakamiya, Toshiyuki

2013-06-17

We have already proposed a method for detecting vehicle positions and their movements (henceforth referred to as "our previous method") using thermal images taken with an infrared thermal camera. Our experiments have shown that our previous method detects vehicles robustly under four different environmental conditions which involve poor visibility conditions in snow and thick fog. Our previous method uses the windshield and its surroundings as the target of the Viola-Jones detector. Some experiments in winter show that the vehicle detection accuracy decreases because the temperatures of many windshields approximate those of the exterior of the windshields. In this paper, we propose a new vehicle detection method (henceforth referred to as "our new method"). Our new method detects vehicles based on tires' thermal energy reflection. We have done experiments using three series of thermal images for which the vehicle detection accuracies of our previous method are low. Our new method detects 1,417 vehicles (92.8%) out of 1,527 vehicles, and the number of false detection is 52 in total. Therefore, by combining our two methods, high vehicle detection accuracies are maintained under various environmental conditions. Finally, we apply the traffic information obtained by our two methods to traffic flow automatic monitoring, and show the effectiveness of our proposal.

Detecting Life and Biology-Related Parameters on Mars

NASA Technical Reports Server (NTRS)

Levin, Gilbet V.; Miller, Joseph D.; Straat, Patricia A.; Lodder, Robert; Hoover, Richard B.

2007-01-01

An integrated, miniaturized, low-power instrument capable of the detection and early characterization of microbial life in the soil of Mars is proposed. Based on the detection apd monitoring of on-going metabolism as being the surest evidence for extant life, the experiments will probe for chirality in metabolism, for circadian rhythm, and for photosynthesis. However, the instrument package will also be able to detect biosignatures and a variety of other physical and chemical parameters of the Martian surface that have significance for life. These include the presence and the physical state of water, the existence of an oxidant, the pH and the penetrability of the soil. Using the legacy of the 1976 Viking Labeled Release (LR) life detection experiment in conjunction with state-of-the-art laser diode spectral analysis, the instrument can be flown stand-alone, with or without a rover, or as part of an MSL-type mission. Sterility for experiment integrity and for planetary protection is provided.

Efficient method of image edge detection based on FSVM

NASA Astrophysics Data System (ADS)

Cai, Aiping; Xiong, Xiaomei

2013-07-01

For efficient object cover edge detection in digital images, this paper studied traditional methods and algorithm based on SVM. It analyzed Canny edge detection algorithm existed some pseudo-edge and poor anti-noise capability. In order to provide a reliable edge extraction method, propose a new detection algorithm based on FSVM. Which contains several steps: first, trains classify sample and gives the different membership function to different samples. Then, a new training sample is formed by increase the punishment some wrong sub-sample, and use the new FSVM classification model for train and test them. Finally the edges are extracted of the object image by using the model. Experimental result shows that good edge detection image will be obtained and adding noise experiments results show that this method has good anti-noise.

Neutron Detection in the A2 Collaboration Experiment on Neutral Pion Photo-production on Neutron

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

Bulychjov, S. A.; Kudryavtsev, A. E.; Kulikov, V. V.

Neutron detection is of crucial importance for the neutral pion photo-production study on a neutron target that now is in progress at MAMI. Two electro-magnetic calorimeters, based on NaI and BaF 2 crystals, are used in the A2 experiment. While these calorimeters are optimized for pion decay photon detection, they have a reason able efficiency for neutron detection also. The paper describes the method, which has been used to measure this efficiency using the same data taken for pion photo-production study on deuterium target with tagged photon been of 800 MeV maximal energy. As a result, the detection efficiency ismore » a rising function of neutron momentum that reaches 40% near 1 GeV/c.« less

Neutron Detection in the A2 Collaboration Experiment on Neutral Pion Photo-production on Neutron

DOE PAGES

Bulychjov, S. A.; Kudryavtsev, A. E.; Kulikov, V. V.; ...

2018-04-09

Neutron detection is of crucial importance for the neutral pion photo-production study on a neutron target that now is in progress at MAMI. Two electro-magnetic calorimeters, based on NaI and BaF 2 crystals, are used in the A2 experiment. While these calorimeters are optimized for pion decay photon detection, they have a reason able efficiency for neutron detection also. The paper describes the method, which has been used to measure this efficiency using the same data taken for pion photo-production study on deuterium target with tagged photon been of 800 MeV maximal energy. As a result, the detection efficiency ismore » a rising function of neutron momentum that reaches 40% near 1 GeV/c.« less

Optical fiber extrinsic Fabry-Perot interferometer sensors for ultrasound detection

NASA Astrophysics Data System (ADS)

Sun, Qingguo; Chen, Na; Ding, Yuetong; Chen, Zhenyi; Wang, Tingyun

2009-11-01

In this paper, a new method is proposed to fabricate an optical fiber extrinsic Fabry-Perot interferometer (EFPI) as an ultrasonic sensor. An acoustic emission detecting system is constructed based on multiple EFPI sensors and demodulation circuit. Ultrasound detection experiments were done from both traditional piezoelectric transducer (PZT) and high voltage discharge. In the experiments, strong ultrasound signals were detected in both cases. The signal attenuation related to the distance and the angle between the acoustic emission source and the FP sensor are obtained. The results indicate that the receiving angle of the FP sensor is nearly 90° and the maximum detection distance in the air is more than 200cm. Furthermore, four sensors are used to locate the position of the ultrasound source produced by high voltage discharge.

Conversation Thread Extraction and Topic Detection in Text-Based Chat

DTIC Science & Technology

2008-09-01

conversation extraction task. Multiple conversations in a session are interleaved. The goal in extraction is to select only those posts that belong...others. Our first-phase experiments quite clearly show the value of using time-distance as a feature in conversation thread extraction . In this set of... EXTRACTION AND TOPIC DETECTION IN TEXT-BASED CHAT by Paige Holland Adams September 2008 Thesis Advisor

Investigating the Effects of Multimodal Feedback through Tracking State in Pen-Based Interfaces

ERIC Educational Resources Information Center

Sun, Minghui; Ren, Xiangshi

2011-01-01

A tracking state increases the bandwidth of pen-based interfaces. However, this state is difficult to detect with default visual feedback. This paper reports on two experiments that are designed to evaluate multimodal feedback for pointing tasks (both 1D and 2D) in tracking state. In 1D pointing experiments, results show that there is a…

Far-Infrared Based Pedestrian Detection for Driver-Assistance Systems Based on Candidate Filters, Gradient-Based Feature and Multi-Frame Approval Matching

PubMed Central

Wang, Guohua; Liu, Qiong

2015-01-01

Far-infrared pedestrian detection approaches for advanced driver-assistance systems based on high-dimensional features fail to simultaneously achieve robust and real-time detection. We propose a robust and real-time pedestrian detection system characterized by novel candidate filters, novel pedestrian features and multi-frame approval matching in a coarse-to-fine fashion. Firstly, we design two filters based on the pedestrians’ head and the road to select the candidates after applying a pedestrian segmentation algorithm to reduce false alarms. Secondly, we propose a novel feature encapsulating both the relationship of oriented gradient distribution and the code of oriented gradient to deal with the enormous variance in pedestrians’ size and appearance. Thirdly, we introduce a multi-frame approval matching approach utilizing the spatiotemporal continuity of pedestrians to increase the detection rate. Large-scale experiments indicate that the system works in real time and the accuracy has improved about 9% compared with approaches based on high-dimensional features only. PMID:26703611

Far-Infrared Based Pedestrian Detection for Driver-Assistance Systems Based on Candidate Filters, Gradient-Based Feature and Multi-Frame Approval Matching.

PubMed

Wang, Guohua; Liu, Qiong

2015-12-21

Far-infrared pedestrian detection approaches for advanced driver-assistance systems based on high-dimensional features fail to simultaneously achieve robust and real-time detection. We propose a robust and real-time pedestrian detection system characterized by novel candidate filters, novel pedestrian features and multi-frame approval matching in a coarse-to-fine fashion. Firstly, we design two filters based on the pedestrians' head and the road to select the candidates after applying a pedestrian segmentation algorithm to reduce false alarms. Secondly, we propose a novel feature encapsulating both the relationship of oriented gradient distribution and the code of oriented gradient to deal with the enormous variance in pedestrians' size and appearance. Thirdly, we introduce a multi-frame approval matching approach utilizing the spatiotemporal continuity of pedestrians to increase the detection rate. Large-scale experiments indicate that the system works in real time and the accuracy has improved about 9% compared with approaches based on high-dimensional features only.

Theory and experiments in model-based space system anomaly management

NASA Astrophysics Data System (ADS)

Kitts, Christopher Adam

This research program consists of an experimental study of model-based reasoning methods for detecting, diagnosing and resolving anomalies that occur when operating a comprehensive space system. Using a first principles approach, several extensions were made to the existing field of model-based fault detection and diagnosis in order to develop a general theory of model-based anomaly management. Based on this theory, a suite of algorithms were developed and computationally implemented in order to detect, diagnose and identify resolutions for anomalous conditions occurring within an engineering system. The theory and software suite were experimentally verified and validated in the context of a simple but comprehensive, student-developed, end-to-end space system, which was developed specifically to support such demonstrations. This space system consisted of the Sapphire microsatellite which was launched in 2001, several geographically distributed and Internet-enabled communication ground stations, and a centralized mission control complex located in the Space Technology Center in the NASA Ames Research Park. Results of both ground-based and on-board experiments demonstrate the speed, accuracy, and value of the algorithms compared to human operators, and they highlight future improvements required to mature this technology.

A Two-Stage Composition Method for Danger-Aware Services Based on Context Similarity

NASA Astrophysics Data System (ADS)

Wang, Junbo; Cheng, Zixue; Jing, Lei; Ota, Kaoru; Kansen, Mizuo

Context-aware systems detect user's physical and social contexts based on sensor networks, and provide services that adapt to the user accordingly. Representing, detecting, and managing the contexts are important issues in context-aware systems. Composition of contexts is a useful method for these works, since it can detect a context by automatically composing small pieces of information to discover service. Danger-aware services are a kind of context-aware services which need description of relations between a user and his/her surrounding objects and between users. However when applying the existing composition methods to danger-aware services, they show the following shortcomings that (1) they have not provided an explicit method for representing composition of multi-user' contexts, (2) there is no flexible reasoning mechanism based on similarity of contexts, so that they can just provide services exactly following the predefined context reasoning rules. Therefore, in this paper, we propose a two-stage composition method based on context similarity to solve the above problems. The first stage is composition of the useful information to represent the context for a single user. The second stage is composition of multi-users' contexts to provide services by considering the relation of users. Finally the danger degree of the detected context is computed by using context similarity between the detected context and the predefined context. Context is dynamically represented based on two-stage composition rules and a Situation theory based Ontology, which combines the advantages of Ontology and Situation theory. We implement the system in an indoor ubiquitous environment, and evaluate the system through two experiments with the support of subjects. The experiment results show the method is effective, and the accuracy of danger detection is acceptable to a danger-aware system.

Track-based event recognition in a realistic crowded environment

NASA Astrophysics Data System (ADS)

van Huis, Jasper R.; Bouma, Henri; Baan, Jan; Burghouts, Gertjan J.; Eendebak, Pieter T.; den Hollander, Richard J. M.; Dijk, Judith; van Rest, Jeroen H.

2014-10-01

Automatic detection of abnormal behavior in CCTV cameras is important to improve the security in crowded environments, such as shopping malls, airports and railway stations. This behavior can be characterized at different time scales, e.g., by small-scale subtle and obvious actions or by large-scale walking patterns and interactions between people. For example, pickpocketing can be recognized by the actual snatch (small scale), when he follows the victim, or when he interacts with an accomplice before and after the incident (longer time scale). This paper focusses on event recognition by detecting large-scale track-based patterns. Our event recognition method consists of several steps: pedestrian detection, object tracking, track-based feature computation and rule-based event classification. In the experiment, we focused on single track actions (walk, run, loiter, stop, turn) and track interactions (pass, meet, merge, split). The experiment includes a controlled setup, where 10 actors perform these actions. The method is also applied to all tracks that are generated in a crowded shopping mall in a selected time frame. The results show that most of the actions can be detected reliably (on average 90%) at a low false positive rate (1.1%), and that the interactions obtain lower detection rates (70% at 0.3% FP). This method may become one of the components that assists operators to find threatening behavior and enrich the selection of videos that are to be observed.

A pdf-Free Change Detection Test Based on Density Difference Estimation.

PubMed

Bu, Li; Alippi, Cesare; Zhao, Dongbin

2018-02-01

The ability to detect online changes in stationarity or time variance in a data stream is a hot research topic with striking implications. In this paper, we propose a novel probability density function-free change detection test, which is based on the least squares density-difference estimation method and operates online on multidimensional inputs. The test does not require any assumption about the underlying data distribution, and is able to operate immediately after having been configured by adopting a reservoir sampling mechanism. Thresholds requested to detect a change are automatically derived once a false positive rate is set by the application designer. Comprehensive experiments validate the effectiveness in detection of the proposed method both in terms of detection promptness and accuracy.

Maintaining Academic Integrity in On-Line Education.

ERIC Educational Resources Information Center

Heberling, Michael

2002-01-01

Discussion of academic cheating and plagiarism focuses on occurrences in online courses, based on experiences at Baker College (Michigan). Highlights include tools to fight plagiarism; using search engines to detect plagiarism; digital paper mills; plagiarism detection companies; and the role of administrators and faculty. (LRW)

Impedance-based detection of corrosion in post-tensioned cables : phase 2 extension of sensor development.

DOT National Transportation Integrated Search

2014-08-01

A proof of concept was established for a sensor capable of using indirect impedance spectroscopy to : detect the existence of corrosion in post-tensioned tendons. This development was supported by a : combination of bench-top experiments performed on...

Edge detection for optical synthetic aperture based on deep neural network

NASA Astrophysics Data System (ADS)

Tan, Wenjie; Hui, Mei; Liu, Ming; Kong, Lingqin; Dong, Liquan; Zhao, Yuejin

2017-09-01

Synthetic aperture optics systems can meet the demands of the next-generation space telescopes being lighter, larger and foldable. However, the boundaries of segmented aperture systems are much more complex than that of the whole aperture. More edge regions mean more imaging edge pixels, which are often mixed and discretized. In order to achieve high-resolution imaging, it is necessary to identify the gaps between the sub-apertures and the edges of the projected fringes. In this work, we introduced the algorithm of Deep Neural Network into the edge detection of optical synthetic aperture imaging. According to the detection needs, we constructed image sets by experiments and simulations. Based on MatConvNet, a toolbox of MATLAB, we ran the neural network, trained it on training image set and tested its performance on validation set. The training was stopped when the test error on validation set stopped declining. As an input image is given, each intra-neighbor area around the pixel is taken into the network, and scanned pixel by pixel with the trained multi-hidden layers. The network outputs make a judgment on whether the center of the input block is on edge of fringes. We experimented with various pre-processing and post-processing techniques to reveal their influence on edge detection performance. Compared with the traditional algorithms or their improvements, our method makes decision on a much larger intra-neighbor, and is more global and comprehensive. Experiments on more than 2,000 images are also given to prove that our method outperforms classical algorithms in optical images-based edge detection.

Comparative psychophysics of bumblebee and honeybee colour discrimination and object detection.

PubMed

Dyer, Adrian G; Spaethe, Johannes; Prack, Sabina

2008-07-01

Bumblebee (Bombus terrestris) discrimination of targets with broadband reflectance spectra was tested using simultaneous viewing conditions, enabling an accurate determination of the perceptual limit of colour discrimination excluding confounds from memory coding (experiment 1). The level of colour discrimination in bumblebees, and honeybees (Apis mellifera) (based upon previous observations), exceeds predictions of models considering receptor noise in the honeybee. Bumblebee and honeybee photoreceptors are similar in spectral shape and spacing, but bumblebees exhibit significantly poorer colour discrimination in behavioural tests, suggesting possible differences in spatial or temporal signal processing. Detection of stimuli in a Y-maze was evaluated for bumblebees (experiment 2) and honeybees (experiment 3). Honeybees detected stimuli containing both green-receptor-contrast and colour contrast at a visual angle of approximately 5 degrees , whilst stimuli that contained only colour contrast were only detected at a visual angle of 15 degrees . Bumblebees were able to detect these stimuli at a visual angle of 2.3 degrees and 2.7 degrees , respectively. A comparison of the experiments suggests a tradeoff between colour discrimination and colour detection in these two species, limited by the need to pool colour signals to overcome receptor noise. We discuss the colour processing differences and possible adaptations to specific ecological habitats.

The AMIDAS Website: An Online Tool for Direct Dark Matter Detection Experiments

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

Shan, Chung-Lin

2010-02-10

Following our long-erm work on development of model-independent data analysis methods for reconstructing the one-dimensional velocity distribution function of halo WIMPs as well as for determining their mass and couplings on nucleons by using data from direct Dark Matter detection experiments directly, we combined the simulation programs to a compact system: AMIDAS (A Model-Independent Data Analysis System). For users' convenience an online system has also been established at the same time. AMIDAS has the ability to do full Monte Carlo simulations, faster theoretical estimations, as well as to analyze (real) data sets recorded in direct detection experiments without modifying themore » source code. In this article, I give an overview of functions of the AMIDAS code based on the use of its website.« less

Noninvasive and label-free detection of circulating melanoma cells by in vivo photoacoustic flow cytometry

NASA Astrophysics Data System (ADS)

Yang, Ping; Liu, Rongrong; Niu, Zhenyu; Suo, Yuanzhen; He, Hao; Wei, Xunbin

2015-03-01

Melanoma is a malignant tumor of melanocytes. Circulating melanoma cell has high light absorption due to melanin highly contained in melanoma cells. This property is employed for the detection of circulating melanoma cell by in vivo photoacoustic flow cytometry (PAFC). PAFC is based on photoacoustic effect. Compared to in vivo flow cytometry based on fluorescence, PAFC can employ high melanin content of melanoma cells as endogenous biomarkers to detect circulating melanoma cells in vivo. In our research, we developed in vitro experiments to prove the ability of PAFC system of detecting PA signals from melanoma cells. For in vivo experiments, we constructed a model of melanoma tumor bearing mice by inoculating highly metastatic murine melanoma cancer cells B16F10 with subcutaneous injection. PA signals were detected in the blood vessels of mouse ears in vivo. By counting circulating melanoma cells termly, we obtained the number variation of circulating melanoma cells as melanoma metastasized. Those results show that PAFC is a noninvasive and label-free method to detect melanoma metastases in blood or lymph circulation. Our PAFC system is an efficient tool to monitor melanoma metastases, cancer recurrence and therapeutic efficacy.

An IEEE802.15.4-Based System for Locating Children on Their School Commutes

NASA Astrophysics Data System (ADS)

Sugiura, Akihiko; Baba, Ryoichi; Kobayashi, Hideyuki

With the increasing number of crimes and accidents in which children are becoming involved, there is a growing demand for devices to safeguard children's security by detecting their locations on their way to and from school. This paper proposes a system that uses an IEEE802.15.4-standard network to detect children's locations. To overcome the susceptibility of radio interference from nearby wireless LANs, frequency division multiplexing is applied to this IEEE802.15.4-based network, toward improving data acquisition from terminal units. The effectiveness of the system was field-tested with elementary school students who used about 400 IEEE 802.15.4-compliant terminal units. An experiment verified that the use of frequency division multiplexing in an environment where radio interference by wireless LANs is strong allowed the network to double the success rate of information communication from terminal units relative to that without frequency division multiplexing. In the experiment for detecting elementary schoolers' arrival at and departure from school, the terminal detection rate was 99% and the terminal detection rate on the designated school routes was 90%. These results prove the effectiveness of the system in detecting locations.

Robust Vehicle Detection in Aerial Images Based on Cascaded Convolutional Neural Networks.

PubMed

Zhong, Jiandan; Lei, Tao; Yao, Guangle

2017-11-24

Vehicle detection in aerial images is an important and challenging task. Traditionally, many target detection models based on sliding-window fashion were developed and achieved acceptable performance, but these models are time-consuming in the detection phase. Recently, with the great success of convolutional neural networks (CNNs) in computer vision, many state-of-the-art detectors have been designed based on deep CNNs. However, these CNN-based detectors are inefficient when applied in aerial image data due to the fact that the existing CNN-based models struggle with small-size object detection and precise localization. To improve the detection accuracy without decreasing speed, we propose a CNN-based detection model combining two independent convolutional neural networks, where the first network is applied to generate a set of vehicle-like regions from multi-feature maps of different hierarchies and scales. Because the multi-feature maps combine the advantage of the deep and shallow convolutional layer, the first network performs well on locating the small targets in aerial image data. Then, the generated candidate regions are fed into the second network for feature extraction and decision making. Comprehensive experiments are conducted on the Vehicle Detection in Aerial Imagery (VEDAI) dataset and Munich vehicle dataset. The proposed cascaded detection model yields high performance, not only in detection accuracy but also in detection speed.

Robust Vehicle Detection in Aerial Images Based on Cascaded Convolutional Neural Networks

PubMed Central

Zhong, Jiandan; Lei, Tao; Yao, Guangle

2017-01-01

Vehicle detection in aerial images is an important and challenging task. Traditionally, many target detection models based on sliding-window fashion were developed and achieved acceptable performance, but these models are time-consuming in the detection phase. Recently, with the great success of convolutional neural networks (CNNs) in computer vision, many state-of-the-art detectors have been designed based on deep CNNs. However, these CNN-based detectors are inefficient when applied in aerial image data due to the fact that the existing CNN-based models struggle with small-size object detection and precise localization. To improve the detection accuracy without decreasing speed, we propose a CNN-based detection model combining two independent convolutional neural networks, where the first network is applied to generate a set of vehicle-like regions from multi-feature maps of different hierarchies and scales. Because the multi-feature maps combine the advantage of the deep and shallow convolutional layer, the first network performs well on locating the small targets in aerial image data. Then, the generated candidate regions are fed into the second network for feature extraction and decision making. Comprehensive experiments are conducted on the Vehicle Detection in Aerial Imagery (VEDAI) dataset and Munich vehicle dataset. The proposed cascaded detection model yields high performance, not only in detection accuracy but also in detection speed. PMID:29186756

Dust Observations by Faraday Cups Onboard Spektr-R

NASA Astrophysics Data System (ADS)

Pavlu, J.; Kociscak, S.; Safrankova, J.; Nemecek, Z.; Prech, L.

2017-12-01

Dust of both interstellar and interplanetary origins was reported in many in-situ experiments devoted to dust detection during past tens of years. Recently, a number of reports employed unintended devices to observe dust (Voyager, Cassini, STEREO …). Most of such observations is based on impact ionization occurring when hypervelocity grains hit a surface being vaporized together with a portion of the surface material. The thermal ionization generates a plasma plume and the dust detection is based on collection of plasma particles by, e.g., antennas. In this contribution, we apply a similar approach to dust impact detection using the multi Faraday cup instrument (BMSW) onboard the Spektr-R spacecraft. It is orbiting the Earth along the highly elliptical trajectory with perigee of 2 and apogee of 50 Re. The BMSW instrument consists of 6 Faraday cups measuring local environmental properties with a rate as high as 30 Hz, i.e., high enough to detect aforementioned plasma plumes. The advantages of the multiple Faraday cup instrument include an easy recognition of dust impacts among plasma disturbances/solitons — dust grain impact can be detected only by one Faraday cup at a given time. We analyze Faraday cup waveforms applying simple criteria on impact spike shape and find a number of dust impact candidates. Based on this experience, we suggest a modification of future devices with a similar detection system.

A study on real-time low-quality content detection on Twitter from the users' perspective.

PubMed

Chen, Weiling; Yeo, Chai Kiat; Lau, Chiew Tong; Lee, Bu Sung

2017-01-01

Detection techniques of malicious content such as spam and phishing on Online Social Networks (OSN) are common with little attention paid to other types of low-quality content which actually impacts users' content browsing experience most. The aim of our work is to detect low-quality content from the users' perspective in real time. To define low-quality content comprehensibly, Expectation Maximization (EM) algorithm is first used to coarsely classify low-quality tweets into four categories. Based on this preliminary study, a survey is carefully designed to gather users' opinions on different categories of low-quality content. Both direct and indirect features including newly proposed features are identified to characterize all types of low-quality content. We then further combine word level analysis with the identified features and build a keyword blacklist dictionary to improve the detection performance. We manually label an extensive Twitter dataset of 100,000 tweets and perform low-quality content detection in real time based on the characterized significant features and word level analysis. The results of our research show that our method has a high accuracy of 0.9711 and a good F1 of 0.8379 based on a random forest classifier with real time performance in the detection of low-quality content in tweets. Our work therefore achieves a positive impact in improving user experience in browsing social media content.

A study on real-time low-quality content detection on Twitter from the users’ perspective

PubMed Central

Yeo, Chai Kiat; Lau, Chiew Tong; Lee, Bu Sung

2017-01-01

Detection techniques of malicious content such as spam and phishing on Online Social Networks (OSN) are common with little attention paid to other types of low-quality content which actually impacts users’ content browsing experience most. The aim of our work is to detect low-quality content from the users’ perspective in real time. To define low-quality content comprehensibly, Expectation Maximization (EM) algorithm is first used to coarsely classify low-quality tweets into four categories. Based on this preliminary study, a survey is carefully designed to gather users’ opinions on different categories of low-quality content. Both direct and indirect features including newly proposed features are identified to characterize all types of low-quality content. We then further combine word level analysis with the identified features and build a keyword blacklist dictionary to improve the detection performance. We manually label an extensive Twitter dataset of 100,000 tweets and perform low-quality content detection in real time based on the characterized significant features and word level analysis. The results of our research show that our method has a high accuracy of 0.9711 and a good F1 of 0.8379 based on a random forest classifier with real time performance in the detection of low-quality content in tweets. Our work therefore achieves a positive impact in improving user experience in browsing social media content. PMID:28793347

A cloud shadow detection method combined with cloud height iteration and spectral analysis for Landsat 8 OLI data

NASA Astrophysics Data System (ADS)

Sun, Lin; Liu, Xinyan; Yang, Yikun; Chen, TingTing; Wang, Quan; Zhou, Xueying

2018-04-01

Although enhanced over prior Landsat instruments, Landsat 8 OLI can obtain very high cloud detection precisions, but for the detection of cloud shadows, it still faces great challenges. Geometry-based cloud shadow detection methods are considered the most effective and are being improved constantly. The Function of Mask (Fmask) cloud shadow detection method is one of the most representative geometry-based methods that has been used for cloud shadow detection with Landsat 8 OLI. However, the Fmask method estimates cloud height employing fixed temperature rates, which are highly uncertain, and errors of large area cloud shadow detection can be caused by errors in estimations of cloud height. This article improves the geometry-based cloud shadow detection method for Landsat OLI from the following two aspects. (1) Cloud height no longer depends on the brightness temperature of the thermal infrared band but uses a possible dynamic range from 200 m to 12,000 m. In this case, cloud shadow is not a specific location but a possible range. Further analysis was carried out in the possible range based on the spectrum to determine cloud shadow location. This effectively avoids the cloud shadow leakage caused by the error in the height determination of a cloud. (2) Object-based and pixel spectral analyses are combined to detect cloud shadows, which can realize cloud shadow detection from two aspects of target scale and pixel scale. Based on the analysis of the spectral differences between the cloud shadow and typical ground objects, the best cloud shadow detection bands of Landsat 8 OLI were determined. The combined use of spectrum and shape can effectively improve the detection precision of cloud shadows produced by thin clouds. Several cloud shadow detection experiments were carried out, and the results were verified by the results of artificial recognition. The results of these experiments indicated that this method can identify cloud shadows in different regions with correct accuracy exceeding 80%, approximately 5% of the areas were wrongly identified, and approximately 10% of the cloud shadow areas were missing. The accuracy of this method is obviously higher than the recognition accuracy of Fmask, which has correct accuracy lower than 60%, and the missing recognition is approximately 40%.

Remote sensing of atmospheric chemistry; Proceedings of the Meeting, Orlando, FL, Apr. 1-3, 1991

NASA Technical Reports Server (NTRS)

Mcelroy, James L. (Editor); Mcneal, Robert J. (Editor)

1991-01-01

The present volume on remote sensing of atmospheric chemistry discusses special remote sensing space observations and field experiments to study chemical change in the atmosphere, network monitoring for detection of stratospheric chemical change, stratospheric chemistry studies, and the combining of model, in situ, and remote sensing in atmospheric chemistry. Attention is given to the measurement of tropospheric carbon monoxide using gas filter radiometers, long-path differential absorption measurements of tropospheric molecules, air quality monitoring with the differential optical absorption spectrometer, and a characterization of tropospheric methane through space-based remote sensing. Topics addressed include microwave limb sounder experiments for UARS and EOS, an overview of the spectroscopy of the atmosphere using an FIR emission experiment, the detection of stratospheric ozone trends by ground-based microwave observations, and a FIR Fabry-Perot spectrometer for OH measurements.

The biometric-based module of smart grid system

NASA Astrophysics Data System (ADS)

Engel, E.; Kovalev, I. V.; Ermoshkina, A.

2015-10-01

Within Smart Grid concept the flexible biometric-based module base on Principal Component Analysis (PCA) and selective Neural Network is developed. The formation of the selective Neural Network the biometric-based module uses the method which includes three main stages: preliminary processing of the image, face localization and face recognition. Experiments on the Yale face database show that (i) selective Neural Network exhibits promising classification capability for face detection, recognition problems; and (ii) the proposed biometric-based module achieves near real-time face detection, recognition speed and the competitive performance, as compared to some existing subspaces-based methods.

An Uncertainty-Based Distributed Fault Detection Mechanism for Wireless Sensor Networks

PubMed Central

Yang, Yang; Gao, Zhipeng; Zhou, Hang; Qiu, Xuesong

2014-01-01

Exchanging too many messages for fault detection will cause not only a degradation of the network quality of service, but also represents a huge burden on the limited energy of sensors. Therefore, we propose an uncertainty-based distributed fault detection through aided judgment of neighbors for wireless sensor networks. The algorithm considers the serious influence of sensing measurement loss and therefore uses Markov decision processes for filling in missing data. Most important of all, fault misjudgments caused by uncertainty conditions are the main drawbacks of traditional distributed fault detection mechanisms. We draw on the experience of evidence fusion rules based on information entropy theory and the degree of disagreement function to increase the accuracy of fault detection. Simulation results demonstrate our algorithm can effectively reduce communication energy overhead due to message exchanges and provide a higher detection accuracy ratio. PMID:24776937

Infrared small target detection based on Danger Theory

NASA Astrophysics Data System (ADS)

Lan, Jinhui; Yang, Xiao

2009-11-01

To solve the problem that traditional method can't detect the small objects whose local SNR is less than 2 in IR images, a Danger Theory-based model to detect infrared small target is presented in this paper. First, on the analog with immunology, the definition is given, in this paper, to such terms as dangerous signal, antigens, APC, antibodies. Besides, matching rule between antigen and antibody is improved. Prior to training the detection model and detecting the targets, the IR images are processed utilizing adaptive smooth filter to decrease the stochastic noise. Then at the training process, deleting rule, generating rule, crossover rule and the mutation rule are established after a large number of experiments in order to realize immediate convergence and obtain good antibodies. The Danger Theory-based model is built after the training process, and this model can detect the target whose local SNR is only 1.5.

Real-time detection and discrimination of visual perception using electrocorticographic signals

NASA Astrophysics Data System (ADS)

Kapeller, C.; Ogawa, H.; Schalk, G.; Kunii, N.; Coon, W. G.; Scharinger, J.; Guger, C.; Kamada, K.

2018-06-01

Objective. Several neuroimaging studies have demonstrated that the ventral temporal cortex contains specialized regions that process visual stimuli. This study investigated the spatial and temporal dynamics of electrocorticographic (ECoG) responses to different types and colors of visual stimulation that were presented to four human participants, and demonstrated a real-time decoder that detects and discriminates responses to untrained natural images. Approach. ECoG signals from the participants were recorded while they were shown colored and greyscale versions of seven types of visual stimuli (images of faces, objects, bodies, line drawings, digits, and kanji and hiragana characters), resulting in 14 classes for discrimination (experiment I). Additionally, a real-time system asynchronously classified ECoG responses to faces, kanji and black screens presented via a monitor (experiment II), or to natural scenes (i.e. the face of an experimenter, natural images of faces and kanji, and a mirror) (experiment III). Outcome measures in all experiments included the discrimination performance across types based on broadband γ activity. Main results. Experiment I demonstrated an offline classification accuracy of 72.9% when discriminating among the seven types (without color separation). Further discrimination of grey versus colored images reached an accuracy of 67.1%. Discriminating all colors and types (14 classes) yielded an accuracy of 52.1%. In experiment II and III, the real-time decoder correctly detected 73.7% responses to face, kanji and black computer stimuli and 74.8% responses to presented natural scenes. Significance. Seven different types and their color information (either grey or color) could be detected and discriminated using broadband γ activity. Discrimination performance maximized for combined spatial-temporal information. The discrimination of stimulus color information provided the first ECoG-based evidence for color-related population-level cortical broadband γ responses in humans. Stimulus categories can be detected by their ECoG responses in real time within 500 ms with respect to stimulus onset.

Investigation of a Moire Based Crack Detection Technique for Propulsion Health Monitoring

NASA Technical Reports Server (NTRS)

Woike, Mark R.; Abudl-Aziz, Ali; Fralick, Gustave C.; Wrbanek, John D.

2012-01-01

The development of techniques for the health monitoring of the rotating components in gas turbine engines is of major interest to NASA s Aviation Safety Program. As part of this on-going effort several experiments utilizing a novel optical Moir based concept along with external blade tip clearance and shaft displacement instrumentation were conducted on a simulated turbine engine disk as a means of demonstrating a potential optical crack detection technique. A Moir pattern results from the overlap of two repetitive patterns with slightly different periods. With this technique, it is possible to detect very small differences in spacing and hence radial growth in a rotating disk due to a flaw such as a crack. The experiment involved etching a circular reference pattern on a subscale engine disk that had a 50.8 mm (2 in.) long notch machined into it to simulate a crack. The disk was operated at speeds up to 12 000 rpm and the Moir pattern due to the shift with respect to the reference pattern was monitored as a means of detecting the radial growth of the disk due to the defect. In addition, blade displacement data were acquired using external blade tip clearance and shaft displacement sensors as a means of confirming the data obtained from the optical technique. The results of the crack detection experiments and its associated analysis are presented in this paper.

Gas leak detection in infrared video with background modeling

NASA Astrophysics Data System (ADS)

Zeng, Xiaoxia; Huang, Likun

2018-03-01

Background modeling plays an important role in the task of gas detection based on infrared video. VIBE algorithm is a widely used background modeling algorithm in recent years. However, the processing speed of the VIBE algorithm sometimes cannot meet the requirements of some real time detection applications. Therefore, based on the traditional VIBE algorithm, we propose a fast prospect model and optimize the results by combining the connected domain algorithm and the nine-spaces algorithm in the following processing steps. Experiments show the effectiveness of the proposed method.

Detecting Pulsing Denial-of-Service Attacks with Nondeterministic Attack Intervals

NASA Astrophysics Data System (ADS)

Luo, Xiapu; Chan, Edmond W. W.; Chang, Rocky K. C.

2009-12-01

This paper addresses the important problem of detecting pulsing denial of service (PDoS) attacks which send a sequence of attack pulses to reduce TCP throughput. Unlike previous works which focused on a restricted form of attacks, we consider a very broad class of attacks. In particular, our attack model admits any attack interval between two adjacent pulses, whether deterministic or not. It also includes the traditional flooding-based attacks as a limiting case (i.e., zero attack interval). Our main contribution is Vanguard, a new anomaly-based detection scheme for this class of PDoS attacks. The Vanguard detection is based on three traffic anomalies induced by the attacks, and it detects them using a CUSUM algorithm. We have prototyped Vanguard and evaluated it on a testbed. The experiment results show that Vanguard is more effective than the previous methods that are based on other traffic anomalies (after a transformation using wavelet transform, Fourier transform, and autocorrelation) and detection algorithms (e.g., dynamic time warping).

Performance comparison of TDR-based systems for permanent and diffused detection of water content and leaks

NASA Astrophysics Data System (ADS)

Cataldo, A.; De Benedetto, E.; Cannazza, G.; Huebner, C.; Trebbels, D.

2017-01-01

In this work, the performance of three time domain reflectometry (TDR) instruments (with different hardware architectures, specifications and costs) is comparatively assessed. The goal is to evaluate the performance of low-cost TDR instrumentation, in view of the development of a completely permanent TDR-based monitoring solution, wherein the costs of the instrument is so low, that it can be left on-site, even unguarded, and controlled remotely. Without losing generality, the applications considered for the comparative experiments are the TDR-based detection of leaks in underground pipes and, more in general, of soil water content variations. For this reason, both laboratory and in-the-field experiments are carried out by comparatively using three TDR instruments, in conjunction with wire-like sensing elements (SEs).

Electrical detection of nuclear spins in organic light-emitting diodes

NASA Astrophysics Data System (ADS)

Malissa, H.; Kavand, M.; Waters, D. P.; Lupton, J. M.; Vardeny, Z. V.; Saam, B.; Boehme, C.

2014-03-01

We present pulsed combined electrically detected electron paramagnetic and nuclear magnetic resonance experiments on MEH-PPV OLEDs. Spin dynamics in these structures are governed by hyperfine interactions between charge carriers and the surrounding hydrogen nuclei, which are abundant in these materials. Hyperfine coupling has been observed by monitoring the device current during coherent spin excitation. Electron spin echoes (ESEs) are detected by applying one additional readout pulse at the time of echo formation. This allows for the application of high-resolution spectroscopy based on ESE detection, such as electron spin echo envelope modulation (ESEEM) and electron nuclear double resonance (ENDOR) available for electrical detection schemes. We conduct electrically detected ESEEM and ENDOR experiments and show how hyperfine interactions in MEH-PPV with and without deuterated polymer side groups can be observed by device current measurements. We acknowledge support by the Department of Energy, Office of Basic Energy Sciences under Award #DE-SC0000909.

Adaptive Automation for Human Supervision of Multiple Uninhabited Vehicles: Effects on Change Detection, Situation Awareness, and Mental Workload

DTIC Science & Technology

2009-01-01

transient was present. BASELINE EXPERIMENT Methods Participants Sixteen young adults (9 women , 7 men ) aged 18–26 years (mean = 20.5) partic- ipated...Sixteen young adults (8 women , 8 men ) aged 18–28 years (mean = 21.9) partici- pated. The experiment lasted approximately 2 hours and participants were...based on the operator’s change detection performance. Mis- sion scenarios involved supervision of multiple UVs and required multitasking . Effects of

Imagining Counterfactual Worlds in Autism Spectrum Disorder.

PubMed

Black, Jo; Williams, David; Ferguson, Heather J

2018-02-01

Two experiments are presented that explore online counterfactual processing in autism spectrum disorder (ASD) using eye-tracking. Participants' eye movements were tracked while they read factual and counterfactual sentences in an anomaly detection task. In Experiment 1, the sentences depicted everyday counterfactual situations (e.g., If Joanne had remembered her umbrella, her hair would have been dry/wet when she arrived home). Sentences in Experiment 2 depicted counterfactual versions of real world events (e.g., If the Titanic had not hit an iceberg, it would have survived/sunk along with all the passengers). Results from both experiments suggest that counterfactual understanding is undiminished in adults with ASD. In fact, participants with ASD were faster than Typically Developing (TD) participants to detect anomalies within realistic, discourse-based counterfactuals (Experiment 1). Detection was comparable for TD and ASD groups when understanding could be grounded in knowledge about reality (Experiment 2), though the 2 groups used subtly different strategies for responding to and recovering from counterfactual inconsistent words. These data argue against general difficulties in global coherence and complex integration in ASD. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

An attentional bias for LEGO® people using a change detection task: Are LEGO® people animate?

PubMed

LaPointe, Mitchell R P; Cullen, Rachael; Baltaretu, Bianca; Campos, Melissa; Michalski, Natalie; Sri Satgunarajah, Suja; Cadieux, Michelle L; Pachai, Matthew V; Shore, David I

2016-09-01

Animate objects have been shown to elicit attentional priority in a change detection task. This benefit has been seen for both human and nonhuman animals compared with inanimate objects. One explanation for these results has been based on the importance animate objects have served over the course of our species' history. In the present set of experiments, we present stimuli, which could be perceived as animate, but with which our distant ancestors would have had no experience, and natural selection could have no direct pressure on their prioritization. In the first experiment, we compared LEGO® "people" with LEGO "nonpeople" in a change detection task. In a second experiment, we attempt to control the heterogeneity of the nonanimate objects by using LEGO blocks, matched in size and colour to LEGO people. In the third experiment, we occlude the faces of the LEGO people to control for facial pattern recognition. In the final 2 experiments, we attempt to obscure high-level categorical information processing of the stimuli by inverting and blurring the scenes. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Design and experiment of a neural signal detection using a FES driving system.

PubMed

Zonghao, Huang; Zhigong, Wang; Xiaoying, Lu; Wenyuan, Li; Xiaoyan, Shen; Xintai, Zhao; Shushan, Xie; Haixian, Pan; Cunliang, Zhu

2010-01-01

The channel bridging, signal regenerating, and functional rebuilding of injured nerves is one of the most important issues in life science research. In recent years, some progresses in the research area have been made in repairing injured nerves with microelectronic neural bridge. Based on the previous work, this paper presents a neural signal detection and functional electrical stimulation (FES) driving system with using high performance operational amplifiers, which has been realized. The experimental results show that the designed system meets requirements. In animal experiments, sciatic nerve signal detection, regeneration and function rebuilding between two toads have been accomplished successfully by using the designed system.

VOLUMETRIC LEAK DETECTION IN LARGE UNDERGROUND STORAGE TANKS - VOLUME II: APPENDICES A-E

EPA Science Inventory

The program of experiments conducted at Griffiss Air Force Base was devised to expand the understanding of large underground storage tank behavior as it impacts the performance of volumetric leak detection testing. The report addresses three important questions about testing the ...

A highly selective fluorescent probe based on coumarin for the imaging of N2H4 in living cells

NASA Astrophysics Data System (ADS)

Chen, Song; Hou, Peng; Wang, Jing; Liu, Lei; Zhang, Qi

2017-02-01

A turn-on fluorescence probe for highly sensitive and selective detection of N2H4 was developed based on hydrazine-triggered a substitution- cyclization-elimination cascade. Upon the treatment with N2H4, probe 1, 4-methyl-coumarin-7-yl bromobutanoate, displayed a remarkable fluorescence enhancement (25-fold) with a maximum at 450 nm. This probe can quantitatively detect N2H4 with a extremely low detection limit as 7 × 10- 8 M. Moreover, cell imaging experiments have indicated that probe 1 has potential ability to detect and image N2H4 in biological systems.

Moving target detection method based on improved Gaussian mixture model

NASA Astrophysics Data System (ADS)

Ma, J. Y.; Jie, F. R.; Hu, Y. J.

2017-07-01

Gaussian Mixture Model is often employed to build background model in background difference methods for moving target detection. This paper puts forward an adaptive moving target detection algorithm based on improved Gaussian Mixture Model. According to the graylevel convergence for each pixel, adaptively choose the number of Gaussian distribution to learn and update background model. Morphological reconstruction method is adopted to eliminate the shadow.. Experiment proved that the proposed method not only has good robustness and detection effect, but also has good adaptability. Even for the special cases when the grayscale changes greatly and so on, the proposed method can also make outstanding performance.

A Mass Spectrometric Analysis Method Based on PPCA and SVM for Early Detection of Ovarian Cancer.

PubMed

Wu, Jiang; Ji, Yanju; Zhao, Ling; Ji, Mengying; Ye, Zhuang; Li, Suyi

2016-01-01

Background. Surfaced-enhanced laser desorption-ionization-time of flight mass spectrometry (SELDI-TOF-MS) technology plays an important role in the early diagnosis of ovarian cancer. However, the raw MS data is highly dimensional and redundant. Therefore, it is necessary to study rapid and accurate detection methods from the massive MS data. Methods. The clinical data set used in the experiments for early cancer detection consisted of 216 SELDI-TOF-MS samples. An MS analysis method based on probabilistic principal components analysis (PPCA) and support vector machine (SVM) was proposed and applied to the ovarian cancer early classification in the data set. Additionally, by the same data set, we also established a traditional PCA-SVM model. Finally we compared the two models in detection accuracy, specificity, and sensitivity. Results. Using independent training and testing experiments 10 times to evaluate the ovarian cancer detection models, the average prediction accuracy, sensitivity, and specificity of the PCA-SVM model were 83.34%, 82.70%, and 83.88%, respectively. In contrast, those of the PPCA-SVM model were 90.80%, 92.98%, and 88.97%, respectively. Conclusions. The PPCA-SVM model had better detection performance. And the model combined with the SELDI-TOF-MS technology had a prospect in early clinical detection and diagnosis of ovarian cancer.

Accelerator-based neutrino oscillation experiments

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

Harris, Deborah A.; /Fermilab

2007-12-01

Neutrino oscillations were first discovered by experiments looking at neutrinos coming from extra-terrestrial sources, namely the sun and the atmosphere, but we will be depending on earth-based sources to take many of the next steps in this field. This article describes what has been learned so far from accelerator-based neutrino oscillation experiments, and then describe very generally what the next accelerator-based steps are. In section 2 the article discusses how one uses an accelerator to make a neutrino beam, in particular, one made from decays in flight of charged pions. There are several different neutrino detection methods currently in use,more » or under development. In section 3 these are presented, with a description of the general concept, an example of such a detector, and then a brief discussion of the outstanding issues associated with this detection technique. Finally, section 4 describes how the measurements of oscillation probabilities are made. This includes a description of the near detector technique and how it can be used to make the most precise measurements of neutrino oscillations.« less

Automatic Polyp Detection via A Novel Unified Bottom-up and Top-down Saliency Approach.

PubMed

Yuan, Yixuan; Li, Dengwang; Meng, Max Q-H

2017-07-31

In this paper, we propose a novel automatic computer-aided method to detect polyps for colonoscopy videos. To find the perceptually and semantically meaningful salient polyp regions, we first segment images into multilevel superpixels. Each level corresponds to different sizes of superpixels. Rather than adopting hand-designed features to describe these superpixels in images, we employ sparse autoencoder (SAE) to learn discriminative features in an unsupervised way. Then a novel unified bottom-up and top-down saliency method is proposed to detect polyps. In the first stage, we propose a weak bottom-up (WBU) saliency map by fusing the contrast based saliency and object-center based saliency together. The contrast based saliency map highlights image parts that show different appearances compared with surrounding areas while the object-center based saliency map emphasizes the center of the salient object. In the second stage, a strong classifier with Multiple Kernel Boosting (MKB) is learned to calculate the strong top-down (STD) saliency map based on samples directly from the obtained multi-level WBU saliency maps. We finally integrate these two stage saliency maps from all levels together to highlight polyps. Experiment results achieve 0.818 recall for saliency calculation, validating the effectiveness of our method. Extensive experiments on public polyp datasets demonstrate that the proposed saliency algorithm performs favorably against state-of-the-art saliency methods to detect polyps.

Magneto-motive detection of tissue-based macrophages by differential phase optical coherence tomography.

PubMed

Oh, Junghwan; Feldman, Marc D; Kim, Jihoon; Kang, Hyun Wook; Sanghi, Pramod; Milner, Thomas E

2007-03-01

A novel method to detect tissue-based macrophages using a combination of superparamagnetic iron oxide (SPIO) nanoparticles and differential phase optical coherence tomography (DP-OCT) with an external oscillating magnetic field is reported. Magnetic force acting on iron-laden tissue-based macrophages was varied by applying a sinusoidal current to a solenoid containing a conical iron core that substantially focused and increased magnetic flux density. Nanoparticle motion was detected with DP-OCT, which can detect tissue movement with nanometer resolution. Frequency response of iron-laden tissue movement was twice the modulation frequency since the magnetic force is proportional to the product of magnetic flux density and gradient. Results of our experiments indicate that DP-OCT can be used to identify tissue-based macrophage when excited by an external focused oscillating magnetic field. (c) 2007 Wiley-Liss, Inc

Robust Vehicle Detection under Various Environmental Conditions Using an Infrared Thermal Camera and Its Application to Road Traffic Flow Monitoring

PubMed Central

Iwasaki, Yoichiro; Misumi, Masato; Nakamiya, Toshiyuki

2013-01-01

We have already proposed a method for detecting vehicle positions and their movements (henceforth referred to as “our previous method”) using thermal images taken with an infrared thermal camera. Our experiments have shown that our previous method detects vehicles robustly under four different environmental conditions which involve poor visibility conditions in snow and thick fog. Our previous method uses the windshield and its surroundings as the target of the Viola-Jones detector. Some experiments in winter show that the vehicle detection accuracy decreases because the temperatures of many windshields approximate those of the exterior of the windshields. In this paper, we propose a new vehicle detection method (henceforth referred to as “our new method”). Our new method detects vehicles based on tires' thermal energy reflection. We have done experiments using three series of thermal images for which the vehicle detection accuracies of our previous method are low. Our new method detects 1,417 vehicles (92.8%) out of 1,527 vehicles, and the number of false detection is 52 in total. Therefore, by combining our two methods, high vehicle detection accuracies are maintained under various environmental conditions. Finally, we apply the traffic information obtained by our two methods to traffic flow automatic monitoring, and show the effectiveness of our proposal. PMID:23774988

Research on Debonding Defects in Thermal Barrier Coatings Structure by Thermal-Wave Radar Imaging (TWRI)

NASA Astrophysics Data System (ADS)

Wang, Fei; Liu, Junyan; Mohummad, Oliullah; Wang, Yang

2018-06-01

In this paper, thermal-wave radar imaging (TWRI) is introduced to detect debonding defects in SiC-coated Ni-based superalloy plates. Linear frequency modulation signal (chirp) is used as the excitation signal which has a large time-bandwidth product. Artificial debonding defects in SiC coating are excited by the laser beam with the light intensity modulated by a chirp signal. Cross-correlation algorithm and chirp lock-in algorithm are introduced to extract the thermal-wave signal characteristic. The comparative experiment between TWRI reflection mode and transmission mode was carried out. Experiments are conducted to investigate the influence of laser power density, chirp period, and excitation frequency. Experimental results illustrate that chirp lock-in phase has a better detection capability than other characteristic parameters. TWRI can effectively detect simulated debonding defects of SiC-coated Ni-based superalloy plates.

The valence of event-based prospective memory cues or the context in which they occur affects their detection.

PubMed

Clark-Foos, Arlo; Brewer, Gene A; Marsh, Richard L; Meeks, J Thadeus; Cook, Gabriel I

2009-01-01

Event-based prospective memory tasks entail detecting cues or reminders in our environment related to previously established intentions. If they are detected at an opportune time, then the intention can be fulfilled. In Experiments 1a-1c, we gave people 3 different nonfocal intentions (e.g., respond to words denoting animals) and discovered that negatively valenced cues delivered the intention to mind less frequently than positively valenced cues. In Experiment 2, this effect was extended to valenced and neutral sentential contexts with convergent results that cues embedded in negatively valenced sentences evoked remembering the intention less often than in positive contexts. In addition, both classes of valence caused the intention to be forgotten more often than a more neutral context. We propose that valence has the ability to usurp attentional resources that otherwise would have supported successful prospective memory performance.

Noninvasive monitoring of Pirenoxine Sodium concentration in aqueous humor based on dual-wavelength iris imaging technique

PubMed Central

Zhou, Yong; Hu, Ye; Zeng, Nan; Ji, Yanhong; Dai, Xiangsong; Li, Peng; Ma, Hui; He, Yonghong

2011-01-01

We present a noninvasive method of detecting substance concentration in the aqueous humor based on dual-wavelength iris imaging technology. Two light sources, one centered within (392 nm) and the other centered outside (850 nm) of an absorption band of Pirenoxine Sodium, a common type of drugs in eye disease treatment, were used for dual-wavelength iris imaging measurement. After passing through the aqueous humor twice, the back-scattering light was detected by a charge-coupled device (CCD). The detected images were then used to calculate the concentration of Pirenoxine Sodium. In eye model experiment, a resolution of 0.6525 ppm was achieved. Meanwhile, at least 4 ppm can be distinguished in in vivo experiment. These results demonstrated that our method can measure Pirenoxine Sodium concentration in the aqueous humor and its potential ability to monitor other materials’ concentration in the aqueous humor. PMID:21339869

Discovering the Highest Energy Neutrinos Using a Radio Phased Array

NASA Astrophysics Data System (ADS)

Vieregg, Abigail

2018-06-01

The detection of high energy neutrinos is an important step toward understanding the most energetic cosmic accelerators and would enable tests of fundamental physics at energy scales that cannot easily be achieved on Earth. IceCube has detected astrophysical neutrinos at lower energies, and at higher energies the best limits to date on the flux comes from IceCube and the ANITA experiment, a NASA balloon-borne radio telescope designed to detect coherent radio Cherenkov emission from cosmogenic ultra-high energy neutrinos. I will discuss a new radio phased array design that will push the achievable sensitivity and lower the energy threshold. I will discuss the initial deployment and performance of an 8-channel system in a ground-based experiment at the South Pole (ARA), and the plans for scaling to O(100) channels and lowering the power consumption for future balloon-borne and ground-based applications.

Whisker Contact Detection of Rodents Based on Slow and Fast Mechanical Inputs

PubMed Central

Claverie, Laure N.; Boubenec, Yves; Debrégeas, Georges; Prevost, Alexis M.; Wandersman, Elie

2017-01-01

Rodents use their whiskers to locate nearby objects with an extreme precision. To perform such tasks, they need to detect whisker/object contacts with a high temporal accuracy. This contact detection is conveyed by classes of mechanoreceptors whose neural activity is sensitive to either slow or fast time varying mechanical stresses acting at the base of the whiskers. We developed a biomimetic approach to separate and characterize slow quasi-static and fast vibrational stress signals acting on a whisker base in realistic exploratory phases, using experiments on both real and artificial whiskers. Both slow and fast mechanical inputs are successfully captured using a mechanical model of the whisker. We present and discuss consequences of the whisking process in purely mechanical terms and hypothesize that free whisking in air sets a mechanical threshold for contact detection. The time resolution and robustness of the contact detection strategies based on either slow or fast stress signals are determined. Contact detection based on the vibrational signal is faster and more robust to exploratory conditions than the slow quasi-static component, although both slow/fast components allow localizing the object. PMID:28119582

The influence of performance on action-effect integration in sense of agency.

PubMed

Wen, Wen; Yamashita, Atsushi; Asama, Hajime

2017-08-01

Sense of agency refers to the subjective feeling of being able to control an outcome through one's own actions or will. Prior studies have shown that both sensory processing (e.g., comparisons between sensory feedbacks and predictions basing on one's motor intentions) and high-level cognitive/constructive processes (e.g., inferences based on one's performance or the consequences of one's actions) contribute to judgments of sense of agency. However, it remains unclear how these two types of processes interact, which is important for clarifying the mechanisms underlying sense of agency. Thus, we examined whether performance-based inferences influence action-effect integration in sense of agency using a delay detection paradigm in two experiments. In both experiments, participants pressed left and right arrow keys to control the direction in which a moving dot was travelling. The dot's response delay was manipulated randomly on 7 levels (0-480ms) between the trials; for each trial, participants were asked to judge whether the dot response was delayed and to rate their level of agency over the dot. In Experiment 1, participants tried to direct the dot to reach a destination on the screen as quickly as possible. Furthermore, the computer assisted participants by ignoring erroneous commands for half of the trials (assisted condition), while in the other half, all of the participants' commands were executed (self-control condition). In Experiment 2, participants directed the dot as they pleased (without a specific goal), but, in half of the trials, the computer randomly ignored 32% of their commands (disturbed condition) rather than assisted them. The results from the two experiments showed that performance enhanced action-effect integration. Specifically, when task performance was improved through the computer's assistance in Experiment 1, delay detection was reduced in the 480-ms delay condition, despite the fact that 32% of participants' commands were ignored. Conversely, when no feedback on task performance was given (as in Experiment 2), the participants reported greater delay when some of their commands were randomly ignored. Furthermore, the results of a logistic regression analysis showed that the threshold of delay detection was greater in the assisted condition than in the self-control condition in Experiment 1, which suggests a wider time window for action-effect integration. A multivariate analysis also revealed that assistance was related to reduced delay detection via task performance, while reduced delay detection was directly correlated with a better sense of agency. These results indicate an association between the implicit and explicit aspects of sense of agency. Copyright © 2017 Elsevier Inc. All rights reserved.

Raman spectroscopy-based detection of chemical contaminants in food powders

NASA Astrophysics Data System (ADS)

Chao, Kuanglin; Dhakal, Sagar; Qin, Jianwei; Kim, Moon; Bae, Abigail

2016-05-01

Raman spectroscopy technique has proven to be a reliable method for qualitative detection of chemical contaminants in food ingredients and products. For quantitative imaging-based detection, each contaminant particle in a food sample must be detected and it is important to determine the necessary spatial resolution needed to effectively detect the contaminant particles. This study examined the effective spatial resolution required for detection of maleic acid in tapioca starch and benzoyl peroxide in wheat flour. Each chemical contaminant was mixed into its corresponding food powder at a concentration of 1% (w/w). Raman spectral images were collected for each sample, leveled across a 45 mm x 45 mm area, using different spatial resolutions. Based on analysis of these images, a spatial resolution of 0.5mm was selected as effective spatial resolution for detection of maleic acid in starch and benzoyl peroxide in flour. An experiment was then conducted using the 0.5mm spatial resolution to demonstrate Raman imaging-based quantitative detection of these contaminants for samples prepared at 0.1%, 0.3%, and 0.5% (w/w) concentrations. The results showed a linear correlation between the detected numbers of contaminant pixels and the actual concentrations of contaminant.

Accurate inclusion mass screening: a bridge from unbiased discovery to targeted assay development for biomarker verification.

PubMed

Jaffe, Jacob D; Keshishian, Hasmik; Chang, Betty; Addona, Theresa A; Gillette, Michael A; Carr, Steven A

2008-10-01

Verification of candidate biomarker proteins in blood is typically done using multiple reaction monitoring (MRM) of peptides by LC-MS/MS on triple quadrupole MS systems. MRM assay development for each protein requires significant time and cost, much of which is likely to be of little value if the candidate biomarker is below the detection limit in blood or a false positive in the original discovery data. Here we present a new technology, accurate inclusion mass screening (AIMS), designed to provide a bridge from unbiased discovery to MS-based targeted assay development. Masses on the software inclusion list are monitored in each scan on the Orbitrap MS system, and MS/MS spectra for sequence confirmation are acquired only when a peptide from the list is detected with both the correct accurate mass and charge state. The AIMS experiment confirms that a given peptide (and thus the protein from which it is derived) is present in the plasma. Throughput of the method is sufficient to qualify up to a hundred proteins/week. The sensitivity of AIMS is similar to MRM on a triple quadrupole MS system using optimized sample preparation methods (low tens of ng/ml in plasma), and MS/MS data from the AIMS experiments on the Orbitrap can be directly used to configure MRM assays. The method was shown to be at least 4-fold more efficient at detecting peptides of interest than undirected LC-MS/MS experiments using the same instrumentation, and relative quantitation information can be obtained by AIMS in case versus control experiments. Detection by AIMS ensures that a quantitative MRM-based assay can be configured for that protein. The method has the potential to qualify large number of biomarker candidates based on their detection in plasma prior to committing to the time- and resource-intensive steps of establishing a quantitative assay.

Spacecraft Fire Safety Research at NASA Glenn Research Center

NASA Technical Reports Server (NTRS)

Meyer, Marit

2016-01-01

Appropriate design of fire detection systems requires knowledge of both the expected fire signature and the background aerosol levels. Terrestrial fire detection systems have been developed based on extensive study of terrestrial fires. Unfortunately there is no corresponding data set for spacecraft fires and consequently the fire detectors in current spacecraft were developed based upon terrestrial designs. In low gravity, buoyant flow is negligible which causes particles to concentrate at the smoke source, increasing their residence time, and increasing the transport time to smoke detectors. Microgravity fires have significantly different structure than those in 1-g which can change the formation history of the smoke particles. Finally the materials used in spacecraft are different from typical terrestrial environments where smoke properties have been evaluated. It is critically important to detect a fire in its early phase before a flame is established, given the fixed volume of air on any spacecraft. Consequently, the primary target for spacecraft fire detection is pyrolysis products rather than soot. Experimental investigations have been performed at three different NASA facilities which characterize smoke aerosols from overheating common spacecraft materials. The earliest effort consists of aerosol measurements in low gravity, called the Smoke Aerosol Measurement Experiment (SAME), and subsequent ground-based testing of SAME smoke in 55-gallon drums with an aerosol reference instrument. Another set of experiments were performed at NASAs Johnson Space Center White Sands Test Facility (WSTF), with additional fuels and an alternate smoke production method. Measurements of these smoke products include mass and number concentration, and a thermal precipitator was designed for this investigation to capture particles for microscopic analysis. The final experiments presented are from NASAs Gases and Aerosols from Smoldering Polymers (GASP) Laboratory, with selected results focusing on realistic fuel preparations and heating profiles with regards to early detection of smoke. SAFFIRE is the upcoming large-scale fire experiment which will be executed in a Cygnus vehicle after it undocks from the ISS.

Experiments in Coherent Change Detection for Synthetic Aperture Sonar

DTIC Science & Technology

2010-06-01

data from synthetic aperture sonars mounted on autonomous undersea ve- hicles and actively navigated tow bodies. A noncoherent example carried out...III of this paper describe approaches for au- tomatic change detection and introduces CCD. Section IV pro- vides an example of noncoherent change...registration insufficiently robust to support correlation-based change detection (whether cohe- rent or noncoherent ). Fig. 6. Baseline (a) and

Grapheme-colour synaesthesia improves detection of embedded shapes, but without pre-attentive 'pop-out' of synaesthetic colour.

PubMed

Ward, Jamie; Jonas, Clare; Dienes, Zoltan; Seth, Anil

2010-04-07

For people with synaesthesia letters and numbers may evoke experiences of colour. It has been previously demonstrated that these synaesthetes may be better at detecting a triangle made of 2s among a background of 5s if they perceive 5 and 2 as having different synaesthetic colours. However, other studies using this task (or tasks based on the same principle) have failed to replicate the effect or have suggested alternative explanations of the effect. In this study, we repeat the original study on a larger group of synaesthetes (n = 36) and include, for the first time, an assessment of their self-reported colour experiences. We show that synaesthetes do have a general advantage over controls on this task. However, many synaesthetes report no colour experiences at all during the task. Synaesthetes who do report colour typically experience around one third of the graphemes in the display as coloured. This is more consistent with theories of synaesthesia in which spatial attention needs to be deployed to graphemes for conscious colour experiences to emerge than the interpretation based on 'pop-out'.

Dimension- and space-based intertrial effects in visual pop-out search: modulation by task demands for focal-attentional processing.

PubMed

Krummenacher, Joseph; Müller, Hermann J; Zehetleitner, Michael; Geyer, Thomas

2009-03-01

Two experiments compared reaction times (RTs) in visual search for singleton feature targets defined, variably across trials, in either the color or the orientation dimension. Experiment 1 required observers to simply discern target presence versus absence (simple-detection task); Experiment 2 required them to respond to a detection-irrelevant form attribute of the target (compound-search task). Experiment 1 revealed a marked dimensional intertrial effect of 34 ms for an target defined in a changed versus a repeated dimension, and an intertrial target distance effect, with an 4-ms increase in RTs (per unit of distance) as the separation of the current relative to the preceding target increased. Conversely, in Experiment 2, the dimension change effect was markedly reduced (11 ms), while the intertrial target distance effect was markedly increased (11 ms per unit of distance). The results suggest that dimension change/repetition effects are modulated by the amount of attentional focusing required by the task, with space-based attention altering the integration of dimension-specific feature contrast signals at the level of the overall-saliency map.

Development of an embedded instrument for autofocus and polarization alignment of polarization maintaining fiber

NASA Astrophysics Data System (ADS)

Feng, Di; Fang, Qimeng; Huang, Huaibo; Zhao, Zhengqi; Song, Ningfang

2017-12-01

The development and implementation of a practical instrument based on an embedded technique for autofocus and polarization alignment of polarization maintaining fiber is presented. For focusing efficiency and stability, an image-based focusing algorithm fully considering the image definition evaluation and the focusing search strategy was used to accomplish autofocus. For improving the alignment accuracy, various image-based algorithms of alignment detection were developed with high calculation speed and strong robustness. The instrument can be operated as a standalone device with real-time processing and convenience operations. The hardware construction, software interface, and image-based algorithms of main modules are described. Additionally, several image simulation experiments were also carried out to analyze the accuracy of the above alignment detection algorithms. Both the simulation results and experiment results indicate that the instrument can achieve the accuracy of polarization alignment <±0.1 deg.

Molecular Detection of EMT Markers in Circulating Tumor Cells from Metastatic Non-Small Cell Lung Cancer Patients: Potential Role in Clinical Practice

PubMed Central

Milano, Annalisa; Mazzetta, Francesca; Valente, Sabatino; Ranieri, Danilo; Leone, Laura; Botticelli, Andrea; Lauro, Salvatore; Torrisi, Maria Rosaria; Marchetti, Paolo

2018-01-01

Background Non-small cell lung cancer (NSCLC) is the most common cause of cancer-related mortality; nevertheless, there are few data regarding detection of circulating tumor cells (CTCs) in NSCLC, compared to other kinds of cancers in which their prognostic roles have already been defined. This difference is likely due to detection methods based on the epithelial marker expression which ignore CTCs undergoing epithelial-mesenchymal transition (CTCsEMT). Methods After optimization of the test with spiking experiments of A549 cells undergoing TGF-β1-induced EMT (A549EMT), the CTCsEMT were enriched by immunomagnetic depletion of leukocytes and then characterized by a RT-PCR assay based on the retrieval of epithelial and EMT-related genes. Blood samples from ten metastatic NSCLC patients before starting treatment and during chemotherapy were used to test this approach by longitudinal monitoring. Ten age- and sex-matched healthy subjects were also enrolled as controls. Results Recovery experiments of spiked A549EMT cells showed that the RT-PCR assay is a reliable method for detection of CTCsEMT. CTCsEMT were detected in three patients at baseline and in six patients after four cycles of cysplatin-based chemotherapy. Longitudinal monitoring of three patients showed that the CTCsEMT detection is related to poor therapeutic response. Conclusions The RT-PCR-based approach for the evaluation of CTCsEMT phenotype could be a promising and inexpensive tool to predict the prognosis and the therapeutic response in NSCLC patients. PMID:29682444

Organics on Mars?

NASA Astrophysics Data System (ADS)

ten Kate, Inge L.

2010-08-01

Organics are expected to exist on Mars based on meteorite infall, in situ production, and any possible biological sources. Yet they have not been detected on the martian surface; are they there, or are we not capable enough to detect them? The Viking gas chromatograph-mass spectrometer did not detect organics in the headspace of heated soil samples with a detection limit of parts per billion. This null result strongly influenced the interpretation of the reactivity seen in the Viking biology experiments and led to the conclusion that life was not present and, instead, that there was some chemical reactivity in the soil. The detection of perchlorates in the martian soil by instruments on the Phoenix lander and the reports of methane in the martian atmosphere suggest that it may be time to reconsider the question of organics. The high-temperature oxidizing properties of perchlorate will promote combustion of organics in pyrolytic experiments and may have affected the ability of both Phoenix's organic analysis experiment and the Viking mass spectrometer experiments to detect organics. So the question of organics on Mars remains open. A primary focus of the upcoming Mars Science Laboratory will be the detection and identification of organic molecules by means of thermal volatilization, followed by gas chromatography - mass spectrometry - as was done on Viking. However, to enhance organic detectability, some of the samples will be processed with liquid derivatization agents that will dissolve organics from the soil before pyrolysis, which may separate them from the soil perchlorates. Nonetheless, the problem of organics on Mars is not solved, and for future missions other organic detection techniques should therefore be considered as well.

Organics on Mars?

PubMed

ten Kate, Inge L

2010-01-01

Organics are expected to exist on Mars based on meteorite infall, in situ production, and any possible biological sources. Yet they have not been detected on the martian surface; are they there, or are we not capable enough to detect them? The Viking gas chromatograph-mass spectrometer did not detect organics in the headspace of heated soil samples with a detection limit of parts per billion. This null result strongly influenced the interpretation of the reactivity seen in the Viking biology experiments and led to the conclusion that life was not present and, instead, that there was some chemical reactivity in the soil. The detection of perchlorates in the martian soil by instruments on the Phoenix lander and the reports of methane in the martian atmosphere suggest that it may be time to reconsider the question of organics. The high-temperature oxidizing properties of perchlorate will promote combustion of organics in pyrolytic experiments and may have affected the ability of both Phoenix's organic analysis experiment and the Viking mass spectrometer experiments to detect organics. So the question of organics on Mars remains open. A primary focus of the upcoming Mars Science Laboratory will be the detection and identification of organic molecules by means of thermal volatilization, followed by gas chromatography-mass spectrometry--as was done on Viking. However, to enhance organic detectability, some of the samples will be processed with liquid derivatization agents that will dissolve organics from the soil before pyrolysis, which may separate them from the soil perchlorates. Nonetheless, the problem of organics on Mars is not solved, and for future missions other organic detection techniques should therefore be considered as well.

Intra-procedural Path-insensitve Grams (I-GRAMS) and Disassembly Based Features for Packer Tool Classification and Detection

DTIC Science & Technology

2012-06-14

executable file is packed is a critical step in software security. This research uses machine learning methods to build the Polymorphic and Non-Polymorphic...Packer Detection (PNPD) system that detects whether an executable is packed by either ASPack, UPX, Metasploit’s polymorphic msfencode, or is packed in...detect packed executables used in experiments. Overall, it is discovered i-grams provide the best results with accuracies above 99.5%, average true

[System design of open-path natural gas leakage detection based on Fresnel lens].

PubMed

Xia, Hui; Liu, Wen-Qing; Zhang, Yu-Jun; Kan, Rui-Feng; Cui, Yi-Ben; Wang, Min; He, Ying; Cui, Xiao-Juan; Ruan, Jun; Geng, Hui

2009-03-01

Based on the technology of tunable diode laser absorption spectroscopy (TDLAS) in conjunction with second harmonic wave detection, a long open-path TDLAS system using a 1.65 microm InGaAsP distributed feedback laser was developed, which is used for detecting pipeline leakage. In this system, a high cost performance Fresnel lens is used as the receiving optical system, which receives the laser-beam reflected by a solid corner cube reflector, and focuses the receiving laser-beam to the InGaAs detector. At the same time, the influences of the concentration to the fluctuation of light intensity were taken into account in the process of measurement, and were eliminated by the method of normalized light intensity. As a result, the measurement error caused by the fluctuation of light intensity was made less than 1%. The experiment of natural gas leakage detection was simulated, and the detection sensitivity is 0.1 x 10(-6) (ratio by volume) with a total path of 320 m. According to the receiving light efficiency of the optical system and the detectable minimum light intensity of the detector, the detectable maximal optical path of the system was counted to be 2 000 m. The results of experiment show that it is a feasible design to use the Fresnel lens as the receiving optical system and can satisfy the demand of the leakage detection of natural gas.

Shuttle wave experiments. [space plasma investigations: design and instrumentation

NASA Technical Reports Server (NTRS)

Calvert, W.

1976-01-01

Wave experiments on shuttle are needed to verify dispersion relations, to study nonlinear and exotic phenomena, to support other plasma experiments, and to test engineering designs. Techniques based on coherent detection and bistatic geometry are described. New instrumentation required to provide modules for a variety of missions and to incorporate advanced signal processing and control techniques is discussed. An experiment for Z to 0 coupling is included.

Detection of honeycomb cell walls from measurement data based on Harris corner detection algorithm

NASA Astrophysics Data System (ADS)

Qin, Yan; Dong, Zhigang; Kang, Renke; Yang, Jie; Ayinde, Babajide O.

2018-06-01

A honeycomb core is a discontinuous material with a thin-wall structure—a characteristic that makes accurate surface measurement difficult. This paper presents a cell wall detection method based on the Harris corner detection algorithm using laser measurement data. The vertexes of honeycomb cores are recognized with two different methods: one method is the reduction of data density, and the other is the optimization of the threshold of the Harris corner detection algorithm. Each cell wall is then identified in accordance with the neighboring relationships of its vertexes. Experiments were carried out for different types and surface shapes of honeycomb cores, where the proposed method was proved effective in dealing with noise due to burrs and/or deformation of cell walls.

Adaboost multi-view face detection based on YCgCr skin color model

NASA Astrophysics Data System (ADS)

Lan, Qi; Xu, Zhiyong

2016-09-01

Traditional Adaboost face detection algorithm uses Haar-like features training face classifiers, whose detection error rate is low in the face region. While under the complex background, the classifiers will make wrong detection easily to the background regions with the similar faces gray level distribution, which leads to the error detection rate of traditional Adaboost algorithm is high. As one of the most important features of a face, skin in YCgCr color space has good clustering. We can fast exclude the non-face areas through the skin color model. Therefore, combining with the advantages of the Adaboost algorithm and skin color detection algorithm, this paper proposes Adaboost face detection algorithm method that bases on YCgCr skin color model. Experiments show that, compared with traditional algorithm, the method we proposed has improved significantly in the detection accuracy and errors.

Detection of impulsive sources from an aerostat-based acoustic array data collection system

NASA Astrophysics Data System (ADS)

Prather, Wayne E.; Clark, Robert C.; Strickland, Joshua; Frazier, Wm. Garth; Singleton, Jere

2009-05-01

An aerostat based acoustic array data collection system was deployed at the NATO TG-53 "Acoustic Detection of Weapon Firing" Joint Field Experiment conducted in Bourges, France during the final two weeks of June 2008. A variety of impulsive sources including mortar, artillery, gunfire, RPG, and explosive devices were fired during the test. Results from the aerostat acoustic array will be presented against the entire range of sources.

Studies related to the development of the Viking 1975 labeled release experiment

NASA Technical Reports Server (NTRS)

Devincenzi, D. L.; Deal, P. H.

1976-01-01

The labeled release life detection experiment on the Viking 1975 Mars mission is based on the concept that microorganisms will metabolize radioactive organic substrates in a nutrient medium and release radioactive carbon dioxide. Several experiments, using laboratory equipment, were carried out to evaluate various aspects of the concept. Results indicate: (1) label is released by sterilization-treated soil, (2) substantial quantities of label are retained in solution under basic conditions, (3) the substrate used, as well as position of label in the molecule, affect release of label, (4) label release is depressed by radiolytic decomposition of substrates, and (5) About 100,000 organisms are required to produce a detectable response. These results, suggest additional areas for testing, add to the data base for interpretation of flight results, and have significance for broader application of this technique for assessing microbial activity.

Eye gazing direction inspection based on image processing technique

NASA Astrophysics Data System (ADS)

Hao, Qun; Song, Yong

2005-02-01

According to the research result in neural biology, human eyes can obtain high resolution only at the center of view of field. In the research of Virtual Reality helmet, we design to detect the gazing direction of human eyes in real time and feed it back to the control system to improve the resolution of the graph at the center of field of view. In the case of current display instruments, this method can both give attention to the view field of virtual scene and resolution, and improve the immersion of virtual system greatly. Therefore, detecting the gazing direction of human eyes rapidly and exactly is the basis of realizing the design scheme of this novel VR helmet. In this paper, the conventional method of gazing direction detection that based on Purklinje spot is introduced firstly. In order to overcome the disadvantage of the method based on Purklinje spot, this paper proposed a method based on image processing to realize the detection and determination of the gazing direction. The locations of pupils and shapes of eye sockets change with the gazing directions. With the aid of these changes, analyzing the images of eyes captured by the cameras, gazing direction of human eyes can be determined finally. In this paper, experiments have been done to validate the efficiency of this method by analyzing the images. The algorithm can carry out the detection of gazing direction base on normal eye image directly, and it eliminates the need of special hardware. Experiment results show that the method is easy to implement and have high precision.

High-Performance Sensors Based on Resistance Fluctuations of Single-Layer-Graphene Transistors.

PubMed

Amin, Kazi Rafsanjani; Bid, Aveek

2015-09-09

One of the most interesting predicted applications of graphene-monolayer-based devices is as high-quality sensors. In this article, we show, through systematic experiments, a chemical vapor sensor based on the measurement of low-frequency resistance fluctuations of single-layer-graphene field-effect-transistor devices. The sensor has extremely high sensitivity, very high specificity, high fidelity, and fast response times. The performance of the device using this scheme of measurement (which uses resistance fluctuations as the detection parameter) is more than 2 orders of magnitude better than a detection scheme in which changes in the average value of the resistance is monitored. We propose a number-density-fluctuation-based model to explain the superior characteristics of a noise-measurement-based detection scheme presented in this article.

Genetic Particle Swarm Optimization-Based Feature Selection for Very-High-Resolution Remotely Sensed Imagery Object Change Detection.

PubMed

Chen, Qiang; Chen, Yunhao; Jiang, Weiguo

2016-07-30

In the field of multiple features Object-Based Change Detection (OBCD) for very-high-resolution remotely sensed images, image objects have abundant features and feature selection affects the precision and efficiency of OBCD. Through object-based image analysis, this paper proposes a Genetic Particle Swarm Optimization (GPSO)-based feature selection algorithm to solve the optimization problem of feature selection in multiple features OBCD. We select the Ratio of Mean to Variance (RMV) as the fitness function of GPSO, and apply the proposed algorithm to the object-based hybrid multivariate alternative detection model. Two experiment cases on Worldview-2/3 images confirm that GPSO can significantly improve the speed of convergence, and effectively avoid the problem of premature convergence, relative to other feature selection algorithms. According to the accuracy evaluation of OBCD, GPSO is superior at overall accuracy (84.17% and 83.59%) and Kappa coefficient (0.6771 and 0.6314) than other algorithms. Moreover, the sensitivity analysis results show that the proposed algorithm is not easily influenced by the initial parameters, but the number of features to be selected and the size of the particle swarm would affect the algorithm. The comparison experiment results reveal that RMV is more suitable than other functions as the fitness function of GPSO-based feature selection algorithm.

Detection system for neutron β decay correlations in the UCNB and Nab experiments

DOE PAGES

Broussard, L. J.; Oak Ridge National Lab.; Zeck, B. A.; ...

2016-12-19

Here, we describe a detection system designed to precisely measure multiple correlations in neutron β decay. Furthermore, the system is based on thick, large area, highly segmented silicon detectors developed in collaboration with Micron Semiconductor, Ltd. The prototype system meets specifications of energy thresholds below 10 keV, energy resolution of ~3 keV FWHM, and rise time of ~50 ns with 19 of the 127 detector pixels instrumented. We have demonstrated the coincident detection of β particles and recoil protons from neutron β decay, using ultracold neutrons at the Los Alamos Neutron Science Center, . The fully instrumented detection system willmore » be implemented in the UCNB and Nab experiments, to determine the neutron β decay parameters B, a, and b.« less

Detecting unresolved binary stars in Euclid VIS images

NASA Astrophysics Data System (ADS)

Kuntzer, T.; Courbin, F.

2017-10-01

Measuring a weak gravitational lensing signal to the level required by the next generation of space-based surveys demands exquisite reconstruction of the point-spread function (PSF). However, unresolved binary stars can significantly distort the PSF shape. In an effort to mitigate this bias, we aim at detecting unresolved binaries in realistic Euclid stellar populations. We tested methods in numerical experiments where (I) the PSF shape is known to Euclid requirements across the field of view; and (II) the PSF shape is unknown. We drew simulated catalogues of PSF shapes for this proof-of-concept paper. Following the Euclid survey plan, the objects were observed four times. We propose three methods to detect unresolved binary stars. The detection is based on the systematic and correlated biases between exposures of the same object. One method is a simple correlation analysis, while the two others use supervised machine-learning algorithms (random forest and artificial neural network). In both experiments, we demonstrate the ability of our methods to detect unresolved binary stars in simulated catalogues. The performance depends on the level of prior knowledge of the PSF shape and the shape measurement errors. Good detection performances are observed in both experiments. Full complexity, in terms of the images and the survey design, is not included, but key aspects of a more mature pipeline are discussed. Finding unresolved binaries in objects used for PSF reconstruction increases the quality of the PSF determination at arbitrary positions. We show, using different approaches, that we are able to detect at least binary stars that are most damaging for the PSF reconstruction process. The code corresponding to the algorithms used in this work and all scripts to reproduce the results are publicly available from a GitHub repository accessible via http://lastro.epfl.ch/software

Lane Detection on the iPhone

NASA Astrophysics Data System (ADS)

Ren, Feixiang; Huang, Jinsheng; Terauchi, Mutsuhiro; Jiang, Ruyi; Klette, Reinhard

A robust and efficient lane detection system is an essential component of Lane Departure Warning Systems, which are commonly used in many vision-based Driver Assistance Systems (DAS) in intelligent transportation. Various computation platforms have been proposed in the past few years for the implementation of driver assistance systems (e.g., PC, laptop, integrated chips, PlayStation, and so on). In this paper, we propose a new platform for the implementation of lane detection, which is based on a mobile phone (the iPhone). Due to physical limitations of the iPhone w.r.t. memory and computing power, a simple and efficient lane detection algorithm using a Hough transform is developed and implemented on the iPhone, as existing algorithms developed based on the PC platform are not suitable for mobile phone devices (currently). Experiments of the lane detection algorithm are made both on PC and on iPhone.

Prototype fiber Bragg Grattings (FBG) sensor based on intensity modulation of the laser diode low frequency vibrations measurement

NASA Astrophysics Data System (ADS)

Setiono, Andi; Ula, Rini Khamimatul; Hanto, Dwi; Widiyatmoko, Bambang; Purnamaningsih, Retno Wigajatri

2016-02-01

In general, Fiber Bragg Grating (FBG) sensor works based on observation of spectral response characteristic to detect the desired parameter. In this research, we studied intensity response characteristic of FBG to detect the dynamic strain. Experiment result show that the reflected intensity had linier relationships with dynamic strain. Based on these characteristics, we developed the FBG sensor to detect low frequency vibration. This sensor is designed by attaching the FBG on the bronze cantilever with dimensions of 85×3×0.5 mm. Measurement results showed that the sensor was able to detect vibrations in the frequency range of 7-10 Hz at temperature range of 25-45 ˚C. The measured frequency range is still within the frequency range of digging activity, therefore this vibration sensor can be applied for oil pipelines vandalisation detection system.

Experience with dynamic reinforcement rates decreases resistance to extinction.

PubMed

Craig, Andrew R; Shahan, Timothy A

2016-03-01

The ability of organisms to detect reinforcer-rate changes in choice preparations is positively related to two factors: the magnitude of the change in rate and the frequency with which rates change. Gallistel (2012) suggested similar rate-detection processes are responsible for decreases in responding during operant extinction. Although effects of magnitude of change in reinforcer rate on resistance to extinction are well known (e.g., the partial-reinforcement-extinction effect), effects of frequency of changes in rate prior to extinction are unknown. Thus, the present experiments examined whether frequency of changes in baseline reinforcer rates impacts resistance to extinction. Pigeons pecked keys for variable-interval food under conditions where reinforcer rates were stable and where they changed within and between sessions. Overall reinforcer rates between conditions were controlled. In Experiment 1, resistance to extinction was lower following exposure to dynamic reinforcement schedules than to static schedules. Experiment 2 showed that resistance to presession feeding, a disruptor that should not involve change-detection processes, was unaffected by baseline-schedule dynamics. These findings are consistent with the suggestion that change detection contributes to extinction. We discuss implications of change-detection processes for extinction of simple and discriminated operant behavior and relate these processes to the behavioral-momentum based approach to understanding extinction. © 2016 Society for the Experimental Analysis of Behavior.

SEMICONDUCTOR TECHNOLOGY A signal processing method for the friction-based endpoint detection system of a CMP process

NASA Astrophysics Data System (ADS)

Chi, Xu; Dongming, Guo; Zhuji, Jin; Renke, Kang

2010-12-01

A signal processing method for the friction-based endpoint detection system of a chemical mechanical polishing (CMP) process is presented. The signal process method uses the wavelet threshold denoising method to reduce the noise contained in the measured original signal, extracts the Kalman filter innovation from the denoised signal as the feature signal, and judges the CMP endpoint based on the feature of the Kalman filter innovation sequence during the CMP process. Applying the signal processing method, the endpoint detection experiments of the Cu CMP process were carried out. The results show that the signal processing method can judge the endpoint of the Cu CMP process.

Phase synchronization based on a Dual-Tree Complex Wavelet Transform

NASA Astrophysics Data System (ADS)

Ferreira, Maria Teodora; Domingues, Margarete Oliveira; Macau, Elbert E. N.

2016-11-01

In this work, we show the applicability of our Discrete Complex Wavelet Approach (DCWA) to verify the phenomenon of phase synchronization transition in two coupled chaotic Lorenz systems. DCWA is based on the phase assignment from complex wavelet coefficients obtained by using a Dual-Tree Complex Wavelet Transform (DT-CWT). We analyzed two coupled chaotic Lorenz systems, aiming to detect the transition from non-phase synchronization to phase synchronization. In addition, we check how good is the method in detecting periods of 2π phase-slips. In all experiments, DCWA is compared with classical phase detection methods such as the ones based on arctangent and Hilbert transform showing a much better performance.

Performances of a HGCDTE APD based direct detection lidar at 2 μm. Application to dial measurements

NASA Astrophysics Data System (ADS)

Gibert, Fabien; Dumas, Arnaud; Rothman, Johan; Edouart, Dimitri; Cénac, Claire; Pellegrino, Jessica

2018-04-01

A lidar receiver with a direct detection chain adapted to a HgCdTe APD based detector with electric cooling is associated to a 2.05 μm Ho :YLF pulsed dual wavelength single mode transmitter to provide the first atmospheric lidar measurements using this technology. Experiments confirm the outstanding sensitivity of the detector and hightligth its huge potential for DIAL measurements of trace gas (CO2 and H2O) in this spectral domain. Performances of coherent vs direct detection at 2.05 μm is assessed.

Detecting both melanoma depth and volume in vivo with a handheld photoacoustic probe

NASA Astrophysics Data System (ADS)

Zhou, Yong; Li, Guo; Zhu, Liren; Li, Chiye; Cornelius, Lynn A.; Wang, Lihong V.

2016-03-01

We applied a linear-array-based photoacoustic probe to detect the tumor depth and volume of melanin-containing melanoma in nude mice in vivo. We demonstrated the ability of this linear-array-based system to measure both the depth and volume of melanoma through phantom, ex vivo, and in vivo experiments. The volume detection ability also enables us to accurately calculate the rate of growth of the tumor, which is important in quantifying tumor activity. Our results show that this system can be used for clinical melanoma diagnosis and treatment at the bedside.

Mechanical Damage Detection of Indonesia Local Citrus Based on Fluorescence Imaging

NASA Astrophysics Data System (ADS)

Siregar, T. H.; Ahmad, U.; Sutrisno; Maddu, A.

2018-05-01

Citrus experienced physical damage in peel will produce essential oils that contain polymethoxylated flavone. Polymethoxylated flavone is fluorescence substance; thus can be detected by fluorescence imaging. This study aims to study the fluorescence spectra characteristic and to determine the damage region in citrus peel based on fluorescence image. Pulung citrus from Batu district, East Java, as a famous citrus production area in Indonesia, was used in the experiment. It was observed that the image processing could detect the mechanical damage region. Fluorescence imaging can be used to classify the citrus into two categories, sound and defect citruses.

Neutrino oscillation processes in a quantum-field-theoretical approach

NASA Astrophysics Data System (ADS)

Egorov, Vadim O.; Volobuev, Igor P.

2018-05-01

It is shown that neutrino oscillation processes can be consistently described in the framework of quantum field theory using only the plane wave states of the particles. Namely, the oscillating electron survival probabilities in experiments with neutrino detection by charged-current and neutral-current interactions are calculated in the quantum field-theoretical approach to neutrino oscillations based on a modification of the Feynman propagator in the momentum representation. The approach is most similar to the standard Feynman diagram technique. It is found that the oscillating distance-dependent probabilities of detecting an electron in experiments with neutrino detection by charged-current and neutral-current interactions exactly coincide with the corresponding probabilities calculated in the standard approach.

A visual model for object detection based on active contours and level-set method.

PubMed

Satoh, Shunji

2006-09-01

A visual model for object detection is proposed. In order to make the detection ability comparable with existing technical methods for object detection, an evolution equation of neurons in the model is derived from the computational principle of active contours. The hierarchical structure of the model emerges naturally from the evolution equation. One drawback involved with initial values of active contours is alleviated by introducing and formulating convexity, which is a visual property. Numerical experiments show that the proposed model detects objects with complex topologies and that it is tolerant of noise. A visual attention model is introduced into the proposed model. Other simulations show that the visual properties of the model are consistent with the results of psychological experiments that disclose the relation between figure-ground reversal and visual attention. We also demonstrate that the model tends to perceive smaller regions as figures, which is a characteristic observed in human visual perception.

Chatter detection in milling process based on VMD and energy entropy

NASA Astrophysics Data System (ADS)

Liu, Changfu; Zhu, Lida; Ni, Chenbing

2018-05-01

This paper presents a novel approach to detect the milling chatter based on Variational Mode Decomposition (VMD) and energy entropy. VMD has already been employed in feature extraction from non-stationary signals. The parameters like number of modes (K) and the quadratic penalty (α) need to be selected empirically when raw signal is decomposed by VMD. Aimed at solving the problem how to select K and α, the automatic selection method of VMD's based on kurtosis is proposed in this paper. When chatter occurs in the milling process, energy will be absorbed to chatter frequency bands. To detect the chatter frequency bands automatically, the chatter detection method based on energy entropy is presented. The vibration signal containing chatter frequency is simulated and three groups of experiments which represent three cutting conditions are conducted. To verify the effectiveness of method presented by this paper, chatter feather extraction has been successfully employed on simulation signals and experimental signals. The simulation and experimental results show that the proposed method can effectively detect the chatter.

Precisely detecting atomic position of atomic intensity images.

PubMed

Wang, Zhijun; Guo, Yaolin; Tang, Sai; Li, Junjie; Wang, Jincheng; Zhou, Yaohe

2015-03-01

We proposed a quantitative method to detect atomic position in atomic intensity images from experiments such as high-resolution transmission electron microscopy, atomic force microscopy, and simulation such as phase field crystal modeling. The evaluation of detection accuracy proves the excellent performance of the method. This method provides a chance to precisely determine atomic interactions based on the detected atomic positions from the atomic intensity image, and hence to investigate the related physical, chemical and electrical properties. Copyright © 2014 Elsevier B.V. All rights reserved.

Water Leak Detection by Using Ground Penetrating Radar, Synthetic Simulation and Four-Dimensional Visualization

NASA Astrophysics Data System (ADS)

Al-Shukri, H.; Eyuboglu, S.; Mahdi, H.

2005-12-01

Many geophysical techniques have been suggested as candidates for detecting water leakage in water distribution system, including ground penetrating radar (GPR), acoustic devices, and gas sampling devices. A series of laboratory experiments were conducted to determine the validity and effectiveness of GPR in detecting water leakage in metal and plastic PVC pipes. The goal was to derive a practical and robust procedure for detecting such leakage. Initially, prototype laboratory experiments were designed to simulate leaks in both PVC and metal pipe. The experiments were very well controlled and results obtained indicate that GPR is effective in detecting subsurface water leaks. This was followed by an outdoor life size experiments. 50 feet by 30 feet by 5 feet test bed was constructed using local soil and commercial water distribution pipes. A 400 MHz antenna was used to collect three-dimensional GPR data as a function of time for a number of experiments using different type of pipes. Advanced imaging and visualization technology was used to further analyze the data. The UALR Virtual Reality Center CAVE facilities were utilized to accomplish this test. Results obtained indicate that GPR is effective in detecting subsurface water leaks in both pipes. Synthetic models of the GPR signals based on Finite Difference Time Domain Method (FDTD) were built to help select an appropriate equipment configuration (frequency band, type of antenna, and real-time imaging software) prior to data acquisition. The simulation software was used to determine the near-field radiation characteristics of the GPR antenna. Different experimental models were adapted for which observational GPR data was previously collected. Matlab regression analysis was used to generate the incident waves for each model to ensure highly accurate and controlled experiments.

Development of a high-sensitivity and portable cell using Helmholtz resonance for noninvasive blood glucose-level measurement based on photoacoustic spectroscopy.

PubMed

Tachibana, K; Okada, K; Kobayashi, R; Ishihara, Y

2016-08-01

We describe the possibility of high-sensitivity noninvasive blood glucose measurement based on photoacoustic spectroscopy (PAS). The demand for noninvasive blood glucose-level measurement has increased due to the explosive increase in diabetic patients. We have developed a noninvasive blood glucose-level measurement based on PAS. The conventional method uses a straight-type resonant cell. However, the cell volume is large, which results in a low detection sensitivity and difficult portability. In this paper, a small-sized Helmholtz-type resonant cell is proposed to improve detection sensitivity and portability by reducing the cell dead volume. First, the acoustic property of the small-sized Helmholtz-type resonant cell was evaluated by performing an experiment using a silicone rubber. As a result, the detection sensitivity of the small-sized Helmholtz-type resonant cell was approximately two times larger than that of the conventional straight-type resonant cell. In addition, the inside volume was approximately 30 times smaller. Second, the detection limits of glucose concentration were estimated by performing an experiment using glucose solutions. The experimental results showed that a glucose concentration of approximately 1% was detected by the small-sized Helmholtz-type resonant cell. Although these results on the sensitivity of blood glucose-level measurement are currently insufficient, they suggest that miniaturization of a resonance cell is effective in the application of noninvasive blood glucose-level measurement.

A novel framework for intelligent surveillance system based on abnormal human activity detection in academic environments.

PubMed

Al-Nawashi, Malek; Al-Hazaimeh, Obaida M; Saraee, Mohamad

2017-01-01

Abnormal activity detection plays a crucial role in surveillance applications, and a surveillance system that can perform robustly in an academic environment has become an urgent need. In this paper, we propose a novel framework for an automatic real-time video-based surveillance system which can simultaneously perform the tracking, semantic scene learning, and abnormality detection in an academic environment. To develop our system, we have divided the work into three phases: preprocessing phase, abnormal human activity detection phase, and content-based image retrieval phase. For motion object detection, we used the temporal-differencing algorithm and then located the motions region using the Gaussian function. Furthermore, the shape model based on OMEGA equation was used as a filter for the detected objects (i.e., human and non-human). For object activities analysis, we evaluated and analyzed the human activities of the detected objects. We classified the human activities into two groups: normal activities and abnormal activities based on the support vector machine. The machine then provides an automatic warning in case of abnormal human activities. It also embeds a method to retrieve the detected object from the database for object recognition and identification using content-based image retrieval. Finally, a software-based simulation using MATLAB was performed and the results of the conducted experiments showed an excellent surveillance system that can simultaneously perform the tracking, semantic scene learning, and abnormality detection in an academic environment with no human intervention.

Detection of deception: Event-related potential markers of attention and cognitive control during intentional false responses.

PubMed

Gibbons, Henning; Schnuerch, Robert; Wittinghofer, Christina; Armbrecht, Anne-Simone; Stahl, Jutta

2018-06-01

Successful deception requires the coordination of multiple mental processes, such as attention, conflict monitoring, and the regulation of emotion. We employed a simple classification task, assessing ERPs to further investigate the attentional and cognitive control components of (instructed) deception. In Experiment 1, 20 participants repeatedly categorized visually presented names of five animals and five plants. Prior to the experiment, however, each participant covertly selected one animal and one plant for deliberate misclassification. For these critical items, we observed significantly increased response times (RTs), error rates, and amplitudes of three ERP components: anterior P3a indicating the processing of task relevance, medial-frontal negativity reflecting conflict monitoring, and posterior P3b indicating sustained visual attention. In a blind identification of the individual critical words based on a priori defined criteria, an algorithm using two behavioral and two ERP measures combined showed a sensitivity of 0.73 and a specificity of 0.95, thus performing far above chance (0.2/0.2). Experiment 2 used five clothing and five furniture names and successfully replicated the findings of Experiment 1 in 25 new participants. For detection of the critical words, the algorithm from Experiment 1 was reused with only slight adjustments of the ERP time windows. This resulted in a very high detection performance (sensitivity 0.88, specificity 0.94) and significantly outperformed an algorithm based on RT alone. Thus, at least under controlled laboratory conditions, a highly accurate detection of instructed lies via the attentional and cognitive control components is feasible, and benefits strongly from combined behavioral and ERP measures. © 2017 Society for Psychophysiological Research.

Methodology for the Determination of the Photon Detection Efficiency of Large-Area Multi-Pixel Photon Counters

NASA Astrophysics Data System (ADS)

Beattie, T.; Lolos, G. J.; Papandreou, Z.; Semenov, A. Yu.; Teigrob, L. A.

2015-08-01

Large-area, multi-pixel photon counters will be used for the electromagnetic Barrel Calorimeter of the GlueX experiment at Jefferson Lab. These photo sensors are based on a 3 ×3 mm2 cell populated by 50 μm pixels, with 16 such cells tiled in a 4 ×4 arrangement in the array. The 16 cells are summed electronically and the signals are amplified. The photon detection efficiency of a group of first-article units at room temperature under conditions similar to those of the experiment was extracted to be (28 ±2(stat) ±2(syst))%, by employing an analysis methodology based on Poisson statistics carried out on the summed energy signals from the units.

Computer Assisted Thermography And Its Application In Ovulation Detection

NASA Astrophysics Data System (ADS)

Rao, K. H.; Shah, A. V.

1984-08-01

Hardware and software of a computer-assisted image analyzing system used for infrared images in medical applications are discussed. The application of computer-assisted thermography (CAT) as a complementary diagnostic tool in centralized diagnostic management is proposed. The authors adopted 'Computer Assisted Thermography' to study physiological changes in the breasts related to the hormones characterizing the menstrual cycle of a woman. Based on clinical experi-ments followed by thermal image analysis, they suggest that 'differential skin temperature (DST)1 be measured to detect the fertility interval in the menstrual cycle of a woman.

Electrokinetic Enrichment and Detection of Neuropeptide for Performance Monitor

DTIC Science & Technology

2016-06-14

conditions for key neurological biomarkers of interest, by using nanoparticles and aptamers to enhance specificity. Additionally, biomarker...conditions for key neurological biomarkers of interest, by using nanoparticles and aptamers to enhance specificity. Additionally, biomarker...nanoparticle immunoassays and aptamer -based approaches for enhancing detection specificity. Experiment: Towards addressing AFRL’s grand challenge of

Electrokinetic enrichment and detection of neuropeptide for performance monitoring

DTIC Science & Technology

2016-06-14

conditions for key neurological biomarkers of interest, by using nanoparticles and aptamers to enhance specificity. Additionally, biomarker...conditions for key neurological biomarkers of interest, by using nanoparticles and aptamers to enhance specificity. Additionally, biomarker...nanoparticle immunoassays and aptamer -based approaches for enhancing detection specificity. Experiment: Towards addressing AFRL’s grand challenge of

Investigating Strength and Frequency Effects in Recognition Memory Using Type-2 Signal Detection Theory

ERIC Educational Resources Information Center

Higham, Philip A.; Perfect, Timothy J.; Bruno, Davide

2009-01-01

Criterion- versus distribution-shift accounts of frequency and strength effects in recognition memory were investigated with Type-2 signal detection receiver operating characteristic (ROC) analysis, which provides a measure of metacognitive monitoring. Experiment 1 demonstrated a frequency-based mirror effect, with a higher hit rate and lower…

Fuzzy Kernel k-Medoids algorithm for anomaly detection problems

NASA Astrophysics Data System (ADS)

Rustam, Z.; Talita, A. S.

2017-07-01

Intrusion Detection System (IDS) is an essential part of security systems to strengthen the security of information systems. IDS can be used to detect the abuse by intruders who try to get into the network system in order to access and utilize the available data sources in the system. There are two approaches of IDS, Misuse Detection and Anomaly Detection (behavior-based intrusion detection). Fuzzy clustering-based methods have been widely used to solve Anomaly Detection problems. Other than using fuzzy membership concept to determine the object to a cluster, other approaches as in combining fuzzy and possibilistic membership or feature-weighted based methods are also used. We propose Fuzzy Kernel k-Medoids that combining fuzzy and possibilistic membership as a powerful method to solve anomaly detection problem since on numerical experiment it is able to classify IDS benchmark data into five different classes simultaneously. We classify IDS benchmark data KDDCup'99 data set into five different classes simultaneously with the best performance was achieved by using 30 % of training data with clustering accuracy reached 90.28 percent.

A Survey on Anomaly Based Host Intrusion Detection System

NASA Astrophysics Data System (ADS)

Jose, Shijoe; Malathi, D.; Reddy, Bharath; Jayaseeli, Dorathi

2018-04-01

An intrusion detection system (IDS) is hardware, software or a combination of two, for monitoring network or system activities to detect malicious signs. In computer security, designing a robust intrusion detection system is one of the most fundamental and important problems. The primary function of system is detecting intrusion and gives alerts when user tries to intrusion on timely manner. In these techniques when IDS find out intrusion it will send alert massage to the system administrator. Anomaly detection is an important problem that has been researched within diverse research areas and application domains. This survey tries to provide a structured and comprehensive overview of the research on anomaly detection. From the existing anomaly detection techniques, each technique has relative strengths and weaknesses. The current state of the experiment practice in the field of anomaly-based intrusion detection is reviewed and survey recent studies in this. This survey provides a study of existing anomaly detection techniques, and how the techniques used in one area can be applied in another application domain.

Complete scanpaths analysis toolbox.

PubMed

Augustyniak, Piotr; Mikrut, Zbigniew

2006-01-01

This paper presents a complete open software environment for control, data processing and assessment of visual experiments. Visual experiments are widely used in research on human perception physiology and the results are applicable to various visual information-based man-machine interfacing, human-emulated automatic visual systems or scanpath-based learning of perceptual habits. The toolbox is designed for Matlab platform and supports infra-red reflection-based eyetracker in calibration and scanpath analysis modes. Toolbox procedures are organized in three layers: the lower one, communicating with the eyetracker output file, the middle detecting scanpath events on a physiological background and the one upper consisting of experiment schedule scripts, statistics and summaries. Several examples of visual experiments carried out with use of the presented toolbox complete the paper.

Novel vehicle detection system based on stacked DoG kernel and AdaBoost

PubMed Central

Kang, Hyun Ho; Lee, Seo Won; You, Sung Hyun

2018-01-01

This paper proposes a novel vehicle detection system that can overcome some limitations of typical vehicle detection systems using AdaBoost-based methods. The performance of the AdaBoost-based vehicle detection system is dependent on its training data. Thus, its performance decreases when the shape of a target differs from its training data, or the pattern of a preceding vehicle is not visible in the image due to the light conditions. A stacked Difference of Gaussian (DoG)–based feature extraction algorithm is proposed to address this issue by recognizing common characteristics, such as the shadow and rear wheels beneath vehicles—of vehicles under various conditions. The common characteristics of vehicles are extracted by applying the stacked DoG shaped kernel obtained from the 3D plot of an image through a convolution method and investigating only certain regions that have a similar patterns. A new vehicle detection system is constructed by combining the novel stacked DoG feature extraction algorithm with the AdaBoost method. Experiments are provided to demonstrate the effectiveness of the proposed vehicle detection system under different conditions. PMID:29513727

Study on nondestructive detection system based on x-ray for wire ropes conveyer belt

NASA Astrophysics Data System (ADS)

Miao, Changyun; Shi, Boya; Wan, Peng; Li, Jie

2008-03-01

A nondestructive detection system based on X-ray for wire ropes conveyer belt is designed by X-ray detection technology. In this paper X-ray detection principle is analyzed, a design scheme of the system is presented; image processing of conveyer belt is researched and image processing algorithms are given; X-ray acquisition receiving board is designed with the use of FPGA and DSP; the software of the system is programmed by C#.NET on WINXP/WIN2000 platform. The experiment indicates the system can implement remote real-time detection of wire ropes conveyer belt images, find faults and give an alarm in time. The system is direct perceived, strong real-time and high accurate. It can be used for fault detection of wire ropes conveyer belts in mines, ports, terminals and other fields.

Infrared dim target detection based on visual attention

NASA Astrophysics Data System (ADS)

Wang, Xin; Lv, Guofang; Xu, Lizhong

2012-11-01

Accurate and fast detection of infrared (IR) dim target has very important meaning for infrared precise guidance, early warning, video surveillance, etc. Based on human visual attention mechanisms, an automatic detection algorithm for infrared dim target is presented. After analyzing the characteristics of infrared dim target images, the method firstly designs Difference of Gaussians (DoG) filters to compute the saliency map. Then the salient regions where the potential targets exist in are extracted by searching through the saliency map with a control mechanism of winner-take-all (WTA) competition and inhibition-of-return (IOR). At last, these regions are identified by the characteristics of the dim IR targets, so the true targets are detected, and the spurious objects are rejected. The experiments are performed for some real-life IR images, and the results prove that the proposed method has satisfying detection effectiveness and robustness. Meanwhile, it has high detection efficiency and can be used for real-time detection.

Background suppression of infrared small target image based on inter-frame registration

NASA Astrophysics Data System (ADS)

Ye, Xiubo; Xue, Bindang

2018-04-01

We propose a multi-frame background suppression method for remote infrared small target detection. Inter-frame information is necessary when the heavy background clutters make it difficult to distinguish real targets and false alarms. A registration procedure based on points matching in image patches is used to compensate the local deformation of background. Then the target can be separated by background subtraction. Experiments show our method serves as an effective preliminary of target detection.

Determination of the Potential Benefit of Time-Frequency Gain Manipulation

PubMed Central

Anzalone, Michael C.; Calandruccio, Lauren; Doherty, Karen A.; Carney, Laurel H.

2008-01-01

Objective The purpose of this study was to determine the maximum benefit provided by a time-frequency gain-manipulation algorithm for noise-reduction (NR) based on an ideal detector of speech energy. The amount of detected energy necessary to show benefit using this type of NR algorithm was examined, as well as the necessary speed and frequency resolution of the gain manipulation. Design NR was performed using time-frequency gain manipulation, wherein the gains of individual frequency bands depended on the absence or presence of speech energy within each band. Three different experiments were performed: (1) NR using ideal detectors, (2) NR with nonideal detectors, and (3) NR with ideal detectors and different processing speeds and frequency resolutions. All experiments were performed using the Hearing-in-Noise test (HINT). A total of 6 listeners with normal hearing and 14 listeners with hearing loss were tested. Results HINT thresholds improved for all listeners with NR based on the ideal detectors used in Experiment I. The nonideal detectors of Experiment II required detection of at least 90% of the speech energy before an improvement was seen in HINT thresholds. The results of Experiment III demonstrated that relatively high temporal resolution (<100 msec) was required by the NR algorithm to improve HINT thresholds. Conclusions The results indicated that a single-microphone NR system based on time-frequency gain manipulation improved the HINT thresholds of listeners. However, to obtain benefit in speech intelligibility, the detectors used in such a strategy were required to detect an unrealistically high percentage of the speech energy and to perform the gain manipulations on a fast temporal basis. PMID:16957499

A P2P Botnet detection scheme based on decision tree and adaptive multilayer neural networks.

PubMed

Alauthaman, Mohammad; Aslam, Nauman; Zhang, Li; Alasem, Rafe; Hossain, M A

2018-01-01

In recent years, Botnets have been adopted as a popular method to carry and spread many malicious codes on the Internet. These malicious codes pave the way to execute many fraudulent activities including spam mail, distributed denial-of-service attacks and click fraud. While many Botnets are set up using centralized communication architecture, the peer-to-peer (P2P) Botnets can adopt a decentralized architecture using an overlay network for exchanging command and control data making their detection even more difficult. This work presents a method of P2P Bot detection based on an adaptive multilayer feed-forward neural network in cooperation with decision trees. A classification and regression tree is applied as a feature selection technique to select relevant features. With these features, a multilayer feed-forward neural network training model is created using a resilient back-propagation learning algorithm. A comparison of feature set selection based on the decision tree, principal component analysis and the ReliefF algorithm indicated that the neural network model with features selection based on decision tree has a better identification accuracy along with lower rates of false positives. The usefulness of the proposed approach is demonstrated by conducting experiments on real network traffic datasets. In these experiments, an average detection rate of 99.08 % with false positive rate of 0.75 % was observed.

Automatically generated acceptance test: A software reliability experiment

NASA Technical Reports Server (NTRS)

Protzel, Peter W.

1988-01-01

This study presents results of a software reliability experiment investigating the feasibility of a new error detection method. The method can be used as an acceptance test and is solely based on empirical data about the behavior of internal states of a program. The experimental design uses the existing environment of a multi-version experiment previously conducted at the NASA Langley Research Center, in which the launch interceptor problem is used as a model. This allows the controlled experimental investigation of versions with well-known single and multiple faults, and the availability of an oracle permits the determination of the error detection performance of the test. Fault interaction phenomena are observed that have an amplifying effect on the number of error occurrences. Preliminary results indicate that all faults examined so far are detected by the acceptance test. This shows promise for further investigations, and for the employment of this test method on other applications.

A fast image retrieval method based on SVM and imbalanced samples in filtering multimedia message spam

NASA Astrophysics Data System (ADS)

Chen, Zhang; Peng, Zhenming; Peng, Lingbing; Liao, Dongyi; He, Xin

2011-11-01

With the swift and violent development of the Multimedia Messaging Service (MMS), it becomes an urgent task to filter the Multimedia Message (MM) spam effectively in real-time. For the fact that most MMs contain images or videos, a method based on retrieving images is given in this paper for filtering MM spam. The detection method used in this paper is a combination of skin-color detection, texture detection, and face detection, and the classifier for this imbalanced problem is a very fast multi-classification combining Support vector machine (SVM) with unilateral binary decision tree. The experiments on 3 test sets show that the proposed method is effective, with the interception rate up to 60% and the average detection time for each image less than 1 second.

[Detecting fire smoke based on the multispectral image].

PubMed

Wei, Ying-Zhuo; Zhang, Shao-Wu; Liu, Yan-Wei

2010-04-01

Smoke detection is very important for preventing forest-fire in the fire early process. Because the traditional technologies based on video and image processing are easily affected by the background dynamic information, three limitations exist in these technologies, i. e. lower anti-interference ability, higher false detection rate and the fire smoke and water fog being not easily distinguished. A novel detection method for detecting smoke based on the multispectral image was proposed in the present paper. Using the multispectral digital imaging technique, the multispectral image series of fire smoke and water fog were obtained in the band scope of 400 to 720 nm, and the images were divided into bins. The Euclidian distance among the bins was taken as a measurement for showing the difference of spectrogram. After obtaining the spectral feature vectors of dynamic region, the regions of fire smoke and water fog were extracted according to the spectrogram feature difference between target and background. The indoor and outdoor experiments show that the smoke detection method based on multispectral image can be applied to the smoke detection, which can effectively distinguish the fire smoke and water fog. Combined with video image processing method, the multispectral image detection method can also be applied to the forest fire surveillance, reducing the false alarm rate in forest fire detection.

On resilience studies of system detection and recovery techniques against stealthy insider attacks

NASA Astrophysics Data System (ADS)

Wei, Sixiao; Zhang, Hanlin; Chen, Genshe; Shen, Dan; Yu, Wei; Pham, Khanh D.; Blasch, Erik P.; Cruz, Jose B.

2016-05-01

With the explosive growth of network technologies, insider attacks have become a major concern to business operations that largely rely on computer networks. To better detect insider attacks that marginally manipulate network traffic over time, and to recover the system from attacks, in this paper we implement a temporal-based detection scheme using the sequential hypothesis testing technique. Two hypothetical states are considered: the null hypothesis that the collected information is from benign historical traffic and the alternative hypothesis that the network is under attack. The objective of such a detection scheme is to recognize the change within the shortest time by comparing the two defined hypotheses. In addition, once the attack is detected, a server migration-based system recovery scheme can be triggered to recover the system to the state prior to the attack. To understand mitigation of insider attacks, a multi-functional web display of the detection analysis was developed for real-time analytic. Experiments using real-world traffic traces evaluate the effectiveness of Detection System and Recovery (DeSyAR) scheme. The evaluation data validates the detection scheme based on sequential hypothesis testing and the server migration-based system recovery scheme can perform well in effectively detecting insider attacks and recovering the system under attack.

Highly sensitive and selective detection of Al(III) ions in aqueous buffered solution with fluorescent peptide-based sensor.

PubMed

In, Byunggyu; Hwang, Gi Won; Lee, Keun-Hyeung

2016-09-15

A fluorescent sensor based on a tripeptide (SerGluGlu) with a dansyl fluorophore detected selectively Al(III) among 16 metal ions in aqueous buffered solutions without any organic cosolvent. The peptide-based sensor showed a highly sensitive turn on response to aluminium ion with high binding affinity (1.84×10(4)M(-1)) in aqueous buffered solutions. The detection limit (230nM, 5.98ppb) of the peptide-based sensor was much lower than the maximum allowable level (7.41μM) of aluminium ions in drinking water demanded by EPA. The binding mode of the peptide sensor with aluminium ions was characterized using ESI mass spectrometry, NMR titration, and pH titration experiments. Copyright © 2016 Elsevier Ltd. All rights reserved.

Using constrained information entropy to detect rare adverse drug reactions from medical forums.

PubMed

Yi Zheng; Chaowang Lan; Hui Peng; Jinyan Li

2016-08-01

Adverse drug reactions (ADRs) detection is critical to avoid malpractices yet challenging due to its uncertainty in pre-marketing review and the underreporting in post-marketing surveillance. To conquer this predicament, social media based ADRs detection methods have been proposed recently. However, existing researches are mostly co-occurrence based methods and face several issues, in particularly, leaving out the rare ADRs and unable to distinguish irrelevant ADRs. In this work, we introduce a constrained information entropy (CIE) method to solve these problems. CIE first recognizes the drug-related adverse reactions using a predefined keyword dictionary and then captures high- and low-frequency (rare) ADRs by information entropy. Extensive experiments on medical forums dataset demonstrate that CIE outperforms the state-of-the-art co-occurrence based methods, especially in rare ADRs detection.

Development of a grating-based interferometer for six-degree-of-freedom displacement and angle measurements.

PubMed

Hsieh, Hung-Lin; Pan, Ssu-Wen

2015-02-09

A grating-based interferometer for 6-DOF displacement and angle measurement is proposed in this study. The proposed interferometer is composed of three identical detection parts sharing the same light source. Each detection part utilizes three techniques: heterodyne, grating shearing, and Michelson interferometries. Displacement information in the three perpendicular directions (X, Y, Z) can be sensed simultaneously by each detection part. Furthermore, angle information (θX, θY, θZ) can be obtained by comparing the displacement measurement results between two corresponding detection parts. The feasibility and performance of the proposed grating-based interferometer are evaluated in displacement and angle measurement experiments. In comparison with the internal capacitance sensor built into the commercial piezo-stage, the measurement resolutions of the displacement and angle of our proposed interferometer are about 2 nm and 0.05 μrad.

Fabrication of optical fiber sensor based on double-layer SU-8 diaphragm and the partial discharge detection

NASA Astrophysics Data System (ADS)

Shang, Ya-na; Ni, Qing-yan; Ding, Ding; Chen, Na; Wang, Ting-yun

2015-01-01

In this paper, a partial discharge detection system is proposed using an optical fiber Fabry-Perot (FP) interferometric sensor, which is fabricated by photolithography. SU-8 photoresist is employed due to its low Young's modulus and potentially high sensitivity for ultrasound detection. The FP cavity is formed by coating the fiber end face with two layers of SU-8 so that the cavity can be controlled by the thickness of the middle layer of SU-8. Static pressure measurement experiments are done to estimate the sensing performance. The results show that the SU-8 based sensor has a sensitivity of 154.8 nm/kPa, which is much higher than that of silica based sensor under the same condition. Moreover, the sensor is demonstrated successfully to detect ultrasound from electrode discharge.

Vision-Based People Detection System for Heavy Machine Applications

PubMed Central

Fremont, Vincent; Bui, Manh Tuan; Boukerroui, Djamal; Letort, Pierrick

2016-01-01

This paper presents a vision-based people detection system for improving safety in heavy machines. We propose a perception system composed of a monocular fisheye camera and a LiDAR. Fisheye cameras have the advantage of a wide field-of-view, but the strong distortions that they create must be handled at the detection stage. Since people detection in fisheye images has not been well studied, we focus on investigating and quantifying the impact that strong radial distortions have on the appearance of people, and we propose approaches for handling this specificity, adapted from state-of-the-art people detection approaches. These adaptive approaches nevertheless have the drawback of high computational cost and complexity. Consequently, we also present a framework for harnessing the LiDAR modality in order to enhance the detection algorithm for different camera positions. A sequential LiDAR-based fusion architecture is used, which addresses directly the problem of reducing false detections and computational cost in an exclusively vision-based system. A heavy machine dataset was built, and different experiments were carried out to evaluate the performance of the system. The results are promising, in terms of both processing speed and performance. PMID:26805838

Vision-Based People Detection System for Heavy Machine Applications.

PubMed

Fremont, Vincent; Bui, Manh Tuan; Boukerroui, Djamal; Letort, Pierrick

2016-01-20

This paper presents a vision-based people detection system for improving safety in heavy machines. We propose a perception system composed of a monocular fisheye camera and a LiDAR. Fisheye cameras have the advantage of a wide field-of-view, but the strong distortions that they create must be handled at the detection stage. Since people detection in fisheye images has not been well studied, we focus on investigating and quantifying the impact that strong radial distortions have on the appearance of people, and we propose approaches for handling this specificity, adapted from state-of-the-art people detection approaches. These adaptive approaches nevertheless have the drawback of high computational cost and complexity. Consequently, we also present a framework for harnessing the LiDAR modality in order to enhance the detection algorithm for different camera positions. A sequential LiDAR-based fusion architecture is used, which addresses directly the problem of reducing false detections and computational cost in an exclusively vision-based system. A heavy machine dataset was built, and different experiments were carried out to evaluate the performance of the system. The results are promising, in terms of both processing speed and performance.

An Unobtrusive Fall Detection and Alerting System Based on Kalman Filter and Bayes Network Classifier.

PubMed

He, Jian; Bai, Shuang; Wang, Xiaoyi

2017-06-16

Falls are one of the main health risks among the elderly. A fall detection system based on inertial sensors can automatically detect fall event and alert a caregiver for immediate assistance, so as to reduce injuries causing by falls. Nevertheless, most inertial sensor-based fall detection technologies have focused on the accuracy of detection while neglecting quantization noise caused by inertial sensor. In this paper, an activity model based on tri-axial acceleration and gyroscope is proposed, and the difference between activities of daily living (ADLs) and falls is analyzed. Meanwhile, a Kalman filter is proposed to preprocess the raw data so as to reduce noise. A sliding window and Bayes network classifier are introduced to develop a wearable fall detection system, which is composed of a wearable motion sensor and a smart phone. The experiment shows that the proposed system distinguishes simulated falls from ADLs with a high accuracy of 95.67%, while sensitivity and specificity are 99.0% and 95.0%, respectively. Furthermore, the smart phone can issue an alarm to caregivers so as to provide timely and accurate help for the elderly, as soon as the system detects a fall.

Effective Heart Disease Detection Based on Quantitative Computerized Traditional Chinese Medicine Using Representation Based Classifiers.

PubMed

Shu, Ting; Zhang, Bob; Tang, Yuan Yan

2017-01-01

At present, heart disease is the number one cause of death worldwide. Traditionally, heart disease is commonly detected using blood tests, electrocardiogram, cardiac computerized tomography scan, cardiac magnetic resonance imaging, and so on. However, these traditional diagnostic methods are time consuming and/or invasive. In this paper, we propose an effective noninvasive computerized method based on facial images to quantitatively detect heart disease. Specifically, facial key block color features are extracted from facial images and analyzed using the Probabilistic Collaborative Representation Based Classifier. The idea of facial key block color analysis is founded in Traditional Chinese Medicine. A new dataset consisting of 581 heart disease and 581 healthy samples was experimented by the proposed method. In order to optimize the Probabilistic Collaborative Representation Based Classifier, an analysis of its parameters was performed. According to the experimental results, the proposed method obtains the highest accuracy compared with other classifiers and is proven to be effective at heart disease detection.

Remote Oil Spill Detection and Monitoring Beneath Sea Ice

NASA Astrophysics Data System (ADS)

Polak, Adam; Marshall, Stephen; Ren, Jinchang; Hwang, Byongjun (Phil); Hagan, Bernard; Stothard, David J. M.

2016-08-01

The spillage of oil in Polar Regions is particularly serious due to the threat to the environment and the difficulties in detecting and tracking the full extent of the oil seepage beneath the sea ice. Development of fast and reliable sensing techniques is highly desirable. In this paper hyperspectral imaging combined with signal processing and classification techniques are proposed as a potential tool to detect the presence of oil beneath the sea ice. A small sample, lab based experiment, serving as a proof of concept, resulted in the successful identification of oil presence beneath the thin ice layer as opposed to the other sample with ice only. The paper demonstrates the results of this experiment that granted a financial support to execute full feasibility study of this technology for oil spill detection beneath the sea ice.

25 Years of Self-organized Criticality: Numerical Detection Methods

NASA Astrophysics Data System (ADS)

McAteer, R. T. James; Aschwanden, Markus J.; Dimitropoulou, Michaila; Georgoulis, Manolis K.; Pruessner, Gunnar; Morales, Laura; Ireland, Jack; Abramenko, Valentyna

2016-01-01

The detection and characterization of self-organized criticality (SOC), in both real and simulated data, has undergone many significant revisions over the past 25 years. The explosive advances in the many numerical methods available for detecting, discriminating, and ultimately testing, SOC have played a critical role in developing our understanding of how systems experience and exhibit SOC. In this article, methods of detecting SOC are reviewed; from correlations to complexity to critical quantities. A description of the basic autocorrelation method leads into a detailed analysis of application-oriented methods developed in the last 25 years. In the second half of this manuscript space-based, time-based and spatial-temporal methods are reviewed and the prevalence of power laws in nature is described, with an emphasis on event detection and characterization. The search for numerical methods to clearly and unambiguously detect SOC in data often leads us outside the comfort zone of our own disciplines—the answers to these questions are often obtained by studying the advances made in other fields of study. In addition, numerical detection methods often provide the optimum link between simulations and experiments in scientific research. We seek to explore this boundary where the rubber meets the road, to review this expanding field of research of numerical detection of SOC systems over the past 25 years, and to iterate forwards so as to provide some foresight and guidance into developing breakthroughs in this subject over the next quarter of a century.

Robust obstacle detection for unmanned surface vehicles

NASA Astrophysics Data System (ADS)

Qin, Yueming; Zhang, Xiuzhi

2018-03-01

Obstacle detection is of essential importance for Unmanned Surface Vehicles (USV). Although some obstacles (e.g., ships, islands) can be detected by Radar, there are many other obstacles (e.g., floating pieces of woods, swimmers) which are difficult to be detected via Radar because these obstacles have low radar cross section. Therefore, detecting obstacle from images taken onboard is an effective supplement. In this paper, a robust vision-based obstacle detection method for USVs is developed. The proposed method employs the monocular image sequence captured by the camera on the USVs and detects obstacles on the sea surface from the image sequence. The experiment results show that the proposed scheme is efficient to fulfill the obstacle detection task.

Emotion-Related Consciousness Detection in Patients With Disorders of Consciousness Through an EEG-Based BCI System

PubMed Central

Pan, Jiahui; Xie, Qiuyou; Huang, Haiyun; He, Yanbin; Sun, Yuping; Yu, Ronghao; Li, Yuanqing

2018-01-01

For patients with disorders of consciousness (DOC), such as vegetative state (VS) and minimally conscious state (MCS), detecting and assessing the residual cognitive functions of the brain remain challenging. Emotion-related cognitive functions are difficult to detect in patients with DOC using motor response-based clinical assessment scales such as the Coma Recovery Scale-Revised (CRS-R) because DOC patients have motor impairments and are unable to provide sufficient motor responses for emotion-related communication. In this study, we proposed an EEG-based brain-computer interface (BCI) system for emotion recognition in patients with DOC. Eight patients with DOC (5 VS and 3 MCS) and eight healthy controls participated in the BCI-based experiment. During the experiment, two movie clips flashed (appearing and disappearing) eight times with a random interstimulus interval between flashes to evoke P300 potentials. The subjects were instructed to focus on the crying or laughing movie clip and to count the flashes of the corresponding movie clip cued by instruction. The BCI system performed online P300 detection to determine which movie clip the patients responsed to and presented the result as feedback. Three of the eight patients and all eight healthy controls achieved online accuracies based on P300 detection that were significantly greater than chance level. P300 potentials were observed in the EEG signals from the three patients. These results indicated the three patients had abilities of emotion recognition and command following. Through spectral analysis, common spatial pattern (CSP) and differential entropy (DE) features in the delta, theta, alpha, beta, and gamma frequency bands were employed to classify the EEG signals during the crying and laughing movie clips. Two patients and all eight healthy controls achieved offline accuracies significantly greater than chance levels in the spectral analysis. Furthermore, stable topographic distribution patterns of CSP and DE features were observed in both the healthy subjects and these two patients. Our results suggest that cognitive experiments may be conducted using BCI systems in patients with DOC despite the inability of such patients to provide sufficient behavioral responses. PMID:29867421

Emotion-Related Consciousness Detection in Patients With Disorders of Consciousness Through an EEG-Based BCI System.

PubMed

Pan, Jiahui; Xie, Qiuyou; Huang, Haiyun; He, Yanbin; Sun, Yuping; Yu, Ronghao; Li, Yuanqing

2018-01-01

For patients with disorders of consciousness (DOC), such as vegetative state (VS) and minimally conscious state (MCS), detecting and assessing the residual cognitive functions of the brain remain challenging. Emotion-related cognitive functions are difficult to detect in patients with DOC using motor response-based clinical assessment scales such as the Coma Recovery Scale-Revised (CRS-R) because DOC patients have motor impairments and are unable to provide sufficient motor responses for emotion-related communication. In this study, we proposed an EEG-based brain-computer interface (BCI) system for emotion recognition in patients with DOC. Eight patients with DOC (5 VS and 3 MCS) and eight healthy controls participated in the BCI-based experiment. During the experiment, two movie clips flashed (appearing and disappearing) eight times with a random interstimulus interval between flashes to evoke P300 potentials. The subjects were instructed to focus on the crying or laughing movie clip and to count the flashes of the corresponding movie clip cued by instruction. The BCI system performed online P300 detection to determine which movie clip the patients responsed to and presented the result as feedback. Three of the eight patients and all eight healthy controls achieved online accuracies based on P300 detection that were significantly greater than chance level. P300 potentials were observed in the EEG signals from the three patients. These results indicated the three patients had abilities of emotion recognition and command following. Through spectral analysis, common spatial pattern (CSP) and differential entropy (DE) features in the delta, theta, alpha, beta, and gamma frequency bands were employed to classify the EEG signals during the crying and laughing movie clips. Two patients and all eight healthy controls achieved offline accuracies significantly greater than chance levels in the spectral analysis. Furthermore, stable topographic distribution patterns of CSP and DE features were observed in both the healthy subjects and these two patients. Our results suggest that cognitive experiments may be conducted using BCI systems in patients with DOC despite the inability of such patients to provide sufficient behavioral responses.

Prevention, early detection and containment of invasive, nonnative plants in the Hawaiian Islands: current efforts and needs

USGS Publications Warehouse

Christoph Kueffer,; Loope, Lloyd

2009-01-01

This report documents these achievements and experiences and provides a range of perspectives on how to further develop prevention, early detection and containment of invasive species in Hawaii. The report is based on a symposium and workshop held at the 2008 Hawaii Conservation Conference in Honolulu on 31 July 2008.

Pulsar observations with the MAGIC Telescope

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

Lopez, M.; Contreras, J. L.; Otte, N.

2007-07-12

Pulsars were detected by EGRET up to energies below 20 GeV. Observations at higher energies with ground-based experiments, including MAGIC, so far failed to detect pulsars, indicating a sharp cutoff of the pulsed emission. Here we present, in particular, the results of the search for very high {gamma}-ray emission from the pulsar PSR B1951+32.

Camouflage, detection and identification of moving targets

PubMed Central

Hall, Joanna R.; Cuthill, Innes C.; Baddeley, Roland; Shohet, Adam J.; Scott-Samuel, Nicholas E.

2013-01-01

Nearly all research on camouflage has investigated its effectiveness for concealing stationary objects. However, animals have to move, and patterns that only work when the subject is static will heavily constrain behaviour. We investigated the effects of different camouflages on the three stages of predation—detection, identification and capture—in a computer-based task with humans. An initial experiment tested seven camouflage strategies on static stimuli. In line with previous literature, background-matching and disruptive patterns were found to be most successful. Experiment 2 showed that if stimuli move, an isolated moving object on a stationary background cannot avoid detection or capture regardless of the type of camouflage. Experiment 3 used an identification task and showed that while camouflage is unable to slow detection or capture, camouflaged targets are harder to identify than uncamouflaged targets when similar background objects are present. The specific details of the camouflage patterns have little impact on this effect. If one has to move, camouflage cannot impede detection; but if one is surrounded by similar targets (e.g. other animals in a herd, or moving background distractors), then camouflage can slow identification. Despite previous assumptions, motion does not entirely ‘break’ camouflage. PMID:23486439

Camouflage, detection and identification of moving targets.

PubMed

Hall, Joanna R; Cuthill, Innes C; Baddeley, Roland; Shohet, Adam J; Scott-Samuel, Nicholas E

2013-05-07

Nearly all research on camouflage has investigated its effectiveness for concealing stationary objects. However, animals have to move, and patterns that only work when the subject is static will heavily constrain behaviour. We investigated the effects of different camouflages on the three stages of predation-detection, identification and capture-in a computer-based task with humans. An initial experiment tested seven camouflage strategies on static stimuli. In line with previous literature, background-matching and disruptive patterns were found to be most successful. Experiment 2 showed that if stimuli move, an isolated moving object on a stationary background cannot avoid detection or capture regardless of the type of camouflage. Experiment 3 used an identification task and showed that while camouflage is unable to slow detection or capture, camouflaged targets are harder to identify than uncamouflaged targets when similar background objects are present. The specific details of the camouflage patterns have little impact on this effect. If one has to move, camouflage cannot impede detection; but if one is surrounded by similar targets (e.g. other animals in a herd, or moving background distractors), then camouflage can slow identification. Despite previous assumptions, motion does not entirely 'break' camouflage.

Remote detection of carbon monoxide by FTIR for simulating field detection in industrial process

NASA Astrophysics Data System (ADS)

Gao, Qiankun; Liu, Wenqing; Zhang, Yujun; Gao, Mingguang; Xu, Liang; Li, Xiangxian; Jin, Ling

2016-10-01

In order to monitor carbon monoxide in industrial production, we developed a passive gas radiation measurement system based on Fourier transform infrared spectroscopy and carried out infrared radiation measurement experiment of carbon monoxide detection in simulated industrial production environment by this system. The principle, condition, device and data processing method of the experiment are introduced in this paper. In order to solve the problem of light path jitter in the actual industrial field, we simulated the noise in the industrial environment. We combine the advantages of MATHEMATICA software in the aspects of graph processing and symbolic computation to data processing to improve the signal noise ratio and noise suppression. Based on the HITRAN database, the nonlinear least square fitting method was used to calculate the concentration of the CO spectra before and after the data processing. By comparing the calculated concentration, the data processed by MATHEMATICA is reliable and necessary in the industrial production environment.

Motion-based threat detection using microrods: experiments and numerical simulations.

PubMed

Ezhilan, Barath; Gao, Wei; Pei, Allen; Rozen, Isaac; Dong, Renfeng; Jurado-Sanchez, Beatriz; Wang, Joseph; Saintillan, David

2015-05-07

Motion-based chemical sensing using microscale particles has attracted considerable recent attention. In this paper, we report on new experiments and Brownian dynamics simulations that cast light on the dynamics of both passive and active microrods (gold wires and gold-platinum micromotors) in a silver ion gradient. We demonstrate that such microrods can be used for threat detection in the form of a silver ion source, allowing for the determination of both the location of the source and concentration of silver. This threat detection strategy relies on the diffusiophoretic motion of both passive and active microrods in the ionic gradient and on the speed acceleration of the Au-Pt micromotors in the presence of silver ions. A Langevin model describing the microrod dynamics and accounting for all of these effects is presented, and key model parameters are extracted from the experimental data, thereby providing a reliable estimate for the full spatiotemporal distribution of the silver ions in the vicinity of the source.

Direct detection of sub-GeV dark matter with semiconductor targets

DOE PAGES

Essig, Rouven; Fernández-Serra, Marivi; Mardon, Jeremy; ...

2016-05-09

Dark matter in the sub-GeV mass range is a theoretically motivated but largely unexplored paradigm. Such light masses are out of reach for conventional nuclear recoil direct detection experiments, but may be detected through the small ionization signals caused by dark matter-electron scattering. Semiconductors are well-studied and are particularly promising target materials because their O(1 eV) band gaps allow for ionization signals from dark matter particles as light as a few hundred keV. Current direct detection technologies are being adapted for dark matter-electron scattering. In this paper, we provide the theoretical calculations for dark matter-electron scattering rate in semiconductors, overcomingmore » several complications that stem from the many-body nature of the problem. We use density functional theory to numerically calculate the rates for dark matter-electron scattering in silicon and germanium, and estimate the sensitivity for upcoming experiments such as DAMIC and SuperCDMS. We find that the reach for these upcoming experiments has the potential to be orders of magnitude beyond current direct detection constraints and that sub-GeV dark matter has a sizable modulation signal. We also give the first direct detection limits on sub-GeV dark matter from its scattering off electrons in a semiconductor target (silicon) based on published results from DAMIC. We make available publicly our code, QEdark, with which we calculate our results. Our results can be used by experimental collaborations to calculate their own sensitivities based on their specific setup. In conclusion, the searches we propose will probe vast new regions of unexplored dark matter model and parameter space.« less

Risk-Based Fire Safety Experiment Definition for Manned Spacecraft

NASA Technical Reports Server (NTRS)

Apostolakis, G. E.; Ho, V. S.; Marcus, E.; Perry, A. T.; Thompson, S. L.

1989-01-01

Risk methodology is used to define experiments to be conducted in space which will help to construct and test the models required for accident sequence identification. The development of accident scenarios is based on the realization that whether damage occurs depends on the time competition of two processes: the ignition and creation of an adverse environment, and the detection and suppression activities. If the fire grows and causes damage faster than it is detected and suppressed, then an accident occurred. The proposed integrated experiments will provide information on individual models that apply to each of the above processes, as well as previously unidentified interactions and processes, if any. Initially, models that are used in terrestrial fire risk assessments are considered. These include heat and smoke release models, detection and suppression models, as well as damage models. In cases where the absence of gravity substantially invalidates a model, alternate models will be developed. Models that depend on buoyancy effects, such as the multizone compartment fire models, are included in these cases. The experiments will be performed in a variety of geometries simulating habitable areas, racks, and other spaces. These simulations will necessitate theoretical studies of scaling effects. Sensitivity studies will also be carried out including the effects of varying oxygen concentrations, pressures, fuel orientation and geometry, and air flow rates. The experimental apparatus described herein includes three major modules: the combustion, the fluids, and the command and power modules.

Automatic Detection of Welding Defects using Deep Neural Network

NASA Astrophysics Data System (ADS)

Hou, Wenhui; Wei, Ye; Guo, Jie; Jin, Yi; Zhu, Chang'an

2018-01-01

In this paper, we propose an automatic detection schema including three stages for weld defects in x-ray images. Firstly, the preprocessing procedure for the image is implemented to locate the weld region; Then a classification model which is trained and tested by the patches cropped from x-ray images is constructed based on deep neural network. And this model can learn the intrinsic feature of images without extra calculation; Finally, the sliding-window approach is utilized to detect the whole images based on the trained model. In order to evaluate the performance of the model, we carry out several experiments. The results demonstrate that the classification model we proposed is effective in the detection of welded joints quality.

An integrated knowledge system for the Space Shuttle hazardous gas detection system

NASA Technical Reports Server (NTRS)

Lo, Ching F.; Shi, George Z.; Bangasser, Carl; Fensky, Connie; Cegielski, Eric; Overbey, Glenn

1993-01-01

A computer-based integrated Knowledge-Based System, the Intelligent Hypertext Manual (IHM), was developed for the Space Shuttle Hazardous Gas Detection System (HGDS) at NASA Marshall Space Flight Center (MSFC). The IHM stores HGDS related knowledge and presents it in an interactive and intuitive manner. This manual is a combination of hypertext and an expert system which store experts' knowledge and experience in hazardous gas detection and analysis. The IHM's purpose is to provide HGDS personnel with the capabilities of: locating applicable documentation related to procedures, constraints, and previous fault histories; assisting in the training of personnel; enhancing the interpretation of real time data; and recognizing and identifying possible faults in the Space Shuttle sub-systems related to hazardous gas detection.

Corner detection and sorting method based on improved Harris algorithm in camera calibration

NASA Astrophysics Data System (ADS)

Xiao, Ying; Wang, Yonghong; Dan, Xizuo; Huang, Anqi; Hu, Yue; Yang, Lianxiang

2016-11-01

In traditional Harris corner detection algorithm, the appropriate threshold which is used to eliminate false corners is selected manually. In order to detect corners automatically, an improved algorithm which combines Harris and circular boundary theory of corners is proposed in this paper. After detecting accurate corner coordinates by using Harris algorithm and Forstner algorithm, false corners within chessboard pattern of the calibration plate can be eliminated automatically by using circular boundary theory. Moreover, a corner sorting method based on an improved calibration plate is proposed to eliminate false background corners and sort remaining corners in order. Experiment results show that the proposed algorithms can eliminate all false corners and sort remaining corners correctly and automatically.

A Novel Zero Velocity Interval Detection Algorithm for Self-Contained Pedestrian Navigation System with Inertial Sensors

PubMed Central

Tian, Xiaochun; Chen, Jiabin; Han, Yongqiang; Shang, Jianyu; Li, Nan

2016-01-01

Zero velocity update (ZUPT) plays an important role in pedestrian navigation algorithms with the premise that the zero velocity interval (ZVI) should be detected accurately and effectively. A novel adaptive ZVI detection algorithm based on a smoothed pseudo Wigner–Ville distribution to remove multiple frequencies intelligently (SPWVD-RMFI) is proposed in this paper. The novel algorithm adopts the SPWVD-RMFI method to extract the pedestrian gait frequency and to calculate the optimal ZVI detection threshold in real time by establishing the function relationships between the thresholds and the gait frequency; then, the adaptive adjustment of thresholds with gait frequency is realized and improves the ZVI detection precision. To put it into practice, a ZVI detection experiment is carried out; the result shows that compared with the traditional fixed threshold ZVI detection method, the adaptive ZVI detection algorithm can effectively reduce the false and missed detection rate of ZVI; this indicates that the novel algorithm has high detection precision and good robustness. Furthermore, pedestrian trajectory positioning experiments at different walking speeds are carried out to evaluate the influence of the novel algorithm on positioning precision. The results show that the ZVI detected by the adaptive ZVI detection algorithm for pedestrian trajectory calculation can achieve better performance. PMID:27669266

Model-Based Detection of Radioactive Contraband for Harbor Defense Incorporating Compton Scattering Physics

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

Candy, J V; Chambers, D H; Breitfeller, E F

2010-03-02

The detection of radioactive contraband is a critical problem is maintaining national security for any country. Photon emissions from threat materials challenge both detection and measurement technologies especially when concealed by various types of shielding complicating the transport physics significantly. This problem becomes especially important when ships are intercepted by U.S. Coast Guard harbor patrols searching for contraband. The development of a sequential model-based processor that captures both the underlying transport physics of gamma-ray emissions including Compton scattering and the measurement of photon energies offers a physics-based approach to attack this challenging problem. The inclusion of a basic radionuclide representationmore » of absorbed/scattered photons at a given energy along with interarrival times is used to extract the physics information available from the noisy measurements portable radiation detection systems used to interdict contraband. It is shown that this physics representation can incorporated scattering physics leading to an 'extended' model-based structure that can be used to develop an effective sequential detection technique. The resulting model-based processor is shown to perform quite well based on data obtained from a controlled experiment.« less

Improved wavelet de-noising method of rail vibration signal for wheel tread detection

NASA Astrophysics Data System (ADS)

Zhao, Quan-ke; Zhao, Quanke; Gao, Xiao-rong; Luo, Lin

2011-12-01

The irregularities of wheel tread can be detected by processing acceleration vibration signal of railway. Various kinds of noise from different sources such as wheel-rail resonance, bad weather and artificial reasons are the key factors influencing detection accuracy. A method which uses wavelet threshold de-noising is investigated to reduce noise in the detection signal, and an improved signal processing algorithm based on it has been established. The results of simulations and field experiments show that the proposed method can increase signal-to-noise ratio (SNR) of the rail vibration signal effectively, and improve the detection accuracy.

Damage Detection and Verification System (DDVS) for In-Situ Health Monitoring

NASA Technical Reports Server (NTRS)

Williams, Martha K.; Lewis, Mark; Szafran, J.; Shelton, C.; Ludwig, L.; Gibson, T.; Lane, J.; Trautwein, T.

2015-01-01

Project presentation for Game Changing Program Smart Book Release. Detection and Verification System (DDVS) expands the Flat Surface Damage Detection System (FSDDS) sensory panels damage detection capabilities and includes an autonomous inspection capability utilizing cameras and dynamic computer vision algorithms to verify system health. Objectives of this formulation task are to establish the concept of operations, formulate the system requirements for a potential ISS flight experiment, and develop a preliminary design of an autonomous inspection capability system that will be demonstrated as a proof-of-concept ground based damage detection and inspection system.

Genetic Particle Swarm Optimization–Based Feature Selection for Very-High-Resolution Remotely Sensed Imagery Object Change Detection

PubMed Central

Chen, Qiang; Chen, Yunhao; Jiang, Weiguo

2016-01-01

In the field of multiple features Object-Based Change Detection (OBCD) for very-high-resolution remotely sensed images, image objects have abundant features and feature selection affects the precision and efficiency of OBCD. Through object-based image analysis, this paper proposes a Genetic Particle Swarm Optimization (GPSO)-based feature selection algorithm to solve the optimization problem of feature selection in multiple features OBCD. We select the Ratio of Mean to Variance (RMV) as the fitness function of GPSO, and apply the proposed algorithm to the object-based hybrid multivariate alternative detection model. Two experiment cases on Worldview-2/3 images confirm that GPSO can significantly improve the speed of convergence, and effectively avoid the problem of premature convergence, relative to other feature selection algorithms. According to the accuracy evaluation of OBCD, GPSO is superior at overall accuracy (84.17% and 83.59%) and Kappa coefficient (0.6771 and 0.6314) than other algorithms. Moreover, the sensitivity analysis results show that the proposed algorithm is not easily influenced by the initial parameters, but the number of features to be selected and the size of the particle swarm would affect the algorithm. The comparison experiment results reveal that RMV is more suitable than other functions as the fitness function of GPSO-based feature selection algorithm. PMID:27483285

Implementation of a model based fault detection and diagnosis for actuation faults of the Space Shuttle main engine

NASA Technical Reports Server (NTRS)

Duyar, A.; Guo, T.-H.; Merrill, W.; Musgrave, J.

1992-01-01

In a previous study, Guo, Merrill and Duyar, 1990, reported a conceptual development of a fault detection and diagnosis system for actuation faults of the space shuttle main engine. This study, which is a continuation of the previous work, implements the developed fault detection and diagnosis scheme for the real time actuation fault diagnosis of the space shuttle main engine. The scheme will be used as an integral part of an intelligent control system demonstration experiment at NASA Lewis. The diagnosis system utilizes a model based method with real time identification and hypothesis testing for actuation, sensor, and performance degradation faults.

Detecting nonsense for Chinese comments based on logistic regression

NASA Astrophysics Data System (ADS)

Zhuolin, Ren; Guang, Chen; Shu, Chen

2016-07-01

To understand cyber citizens' opinion accurately from Chinese news comments, the clear definition on nonsense is present, and a detection model based on logistic regression (LR) is proposed. The detection of nonsense can be treated as a binary-classification problem. Besides of traditional lexical features, we propose three kinds of features in terms of emotion, structure and relevance. By these features, we train an LR model and demonstrate its effect in understanding Chinese news comments. We find that each of proposed features can significantly promote the result. In our experiments, we achieve a prediction accuracy of 84.3% which improves the baseline 77.3% by 7%.

Acoustic thermometry for detecting quenches in superconducting coils and conductor stacks

NASA Astrophysics Data System (ADS)

Marchevsky, M.; Gourlay, S. A.

2017-01-01

Quench detection capability is essential for reliable operation and protection of superconducting magnets, coils, cables, and machinery. We propose a quench detection technique based on sensing local temperature variations in the bulk of a superconducting winding by monitoring its transient acoustic response. Our approach is primarily aimed at coils and devices built with high-temperature superconductor materials where quench detection using standard voltage-based techniques may be inefficient due to the slow velocity of quench propagation. The acoustic sensing technique is non-invasive, fast, and capable of detecting temperature variations of less than 1 K in the interior of the superconductor cable stack in a 77 K cryogenic environment. We show results of finite element modeling and experiments conducted on a model superconductor stack demonstrating viability of the technique for practical quench detection, discuss sensitivity limits of the technique, and its various applications.

Small Arrays for Seismic Intruder Detections: A Simulation Based Experiment

NASA Astrophysics Data System (ADS)

Pitarka, A.

2014-12-01

Seismic sensors such as geophones and fiber optic have been increasingly recognized as promising technologies for intelligence surveillance, including intruder detection and perimeter defense systems. Geophone arrays have the capability to provide cost effective intruder detection in protecting assets with large perimeters. A seismic intruder detection system uses one or multiple arrays of geophones design to record seismic signals from footsteps and ground vehicles. Using a series of real-time signal processing algorithms the system detects, classify and monitors the intruder's movement. We have carried out numerical experiments to demonstrate the capability of a seismic array to detect moving targets that generate seismic signals. The seismic source is modeled as a vertical force acting on the ground that generates continuous impulsive seismic signals with different predominant frequencies. Frequency-wave number analysis of the synthetic array data was used to demonstrate the array's capability at accurately determining intruder's movement direction. The performance of the array was also analyzed in detecting two or more objects moving at the same time. One of the drawbacks of using a single array system is its inefficiency at detecting seismic signals deflected by large underground objects. We will show simulation results of the effect of an underground concrete block at shielding the seismic signal coming from an intruder. Based on simulations we found that multiple small arrays can greatly improve the system's detection capability in the presence of underground structures. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344

Image Registration-Based Bolt Loosening Detection of Steel Joints

PubMed Central

2018-01-01

Self-loosening of bolts caused by repetitive loads and vibrations is one of the common defects that can weaken the structural integrity of bolted steel joints in civil structures. Many existing approaches for detecting loosening bolts are based on physical sensors and, hence, require extensive sensor deployment, which limit their abilities to cost-effectively detect loosened bolts in a large number of steel joints. Recently, computer vision-based structural health monitoring (SHM) technologies have demonstrated great potential for damage detection due to the benefits of being low cost, easy to deploy, and contactless. In this study, we propose a vision-based non-contact bolt loosening detection method that uses a consumer-grade digital camera. Two images of the monitored steel joint are first collected during different inspection periods and then aligned through two image registration processes. If the bolt experiences rotation between inspections, it will introduce differential features in the registration errors, serving as a good indicator for bolt loosening detection. The performance and robustness of this approach have been validated through a series of experimental investigations using three laboratory setups including a gusset plate on a cross frame, a column flange, and a girder web. The bolt loosening detection results are presented for easy interpretation such that informed decisions can be made about the detected loosened bolts. PMID:29597264

Illumination Invariant Change Detection (iicd): from Earth to Mars

NASA Astrophysics Data System (ADS)

Wan, X.; Liu, J.; Qin, M.; Li, S. Y.

2018-04-01

Multi-temporal Earth Observation and Mars orbital imagery data with frequent repeat coverage provide great capability for planetary surface change detection. When comparing two images taken at different times of day or in different seasons for change detection, the variation of topographic shades and shadows caused by the change of sunlight angle can be so significant that it overwhelms the real object and environmental changes, making automatic detection unreliable. An effective change detection algorithm therefore has to be robust to the illumination variation. This paper presents our research on developing and testing an Illumination Invariant Change Detection (IICD) method based on the robustness of phase correlation (PC) to the variation of solar illumination for image matching. The IICD is based on two key functions: i) initial change detection based on a saliency map derived from pixel-wise dense PC matching and ii) change quantization which combines change type identification, motion estimation and precise appearance change identification. Experiment using multi-temporal Landsat 7 ETM+ satellite images, Rapid eye satellite images and Mars HiRiSE images demonstrate that our frequency based image matching method can reach sub-pixel accuracy and thus the proposed IICD method can effectively detect and precisely segment large scale change such as landslide as well as small object change such as Mars rover, under daily and seasonal sunlight changes.

Image Registration-Based Bolt Loosening Detection of Steel Joints.

PubMed

Kong, Xiangxiong; Li, Jian

2018-03-28

Self-loosening of bolts caused by repetitive loads and vibrations is one of the common defects that can weaken the structural integrity of bolted steel joints in civil structures. Many existing approaches for detecting loosening bolts are based on physical sensors and, hence, require extensive sensor deployment, which limit their abilities to cost-effectively detect loosened bolts in a large number of steel joints. Recently, computer vision-based structural health monitoring (SHM) technologies have demonstrated great potential for damage detection due to the benefits of being low cost, easy to deploy, and contactless. In this study, we propose a vision-based non-contact bolt loosening detection method that uses a consumer-grade digital camera. Two images of the monitored steel joint are first collected during different inspection periods and then aligned through two image registration processes. If the bolt experiences rotation between inspections, it will introduce differential features in the registration errors, serving as a good indicator for bolt loosening detection. The performance and robustness of this approach have been validated through a series of experimental investigations using three laboratory setups including a gusset plate on a cross frame, a column flange, and a girder web. The bolt loosening detection results are presented for easy interpretation such that informed decisions can be made about the detected loosened bolts.

Experimental Study for Automatic Colony Counting System Based Onimage Processing

NASA Astrophysics Data System (ADS)

Fang, Junlong; Li, Wenzhe; Wang, Guoxin

Colony counting in many colony experiments is detected by manual method at present, therefore it is difficult for man to execute the method quickly and accurately .A new automatic colony counting system was developed. Making use of image-processing technology, a study was made on the feasibility of distinguishing objectively white bacterial colonies from clear plates according to the RGB color theory. An optimal chromatic value was obtained based upon a lot of experiments on the distribution of the chromatic value. It has been proved that the method greatly improves the accuracy and efficiency of the colony counting and the counting result is not affected by using inoculation, shape or size of the colony. It is revealed that automatic detection of colony quantity using image-processing technology could be an effective way.

Surface based detection schemes for molecular interferometry experiments - implications and possible applications

NASA Astrophysics Data System (ADS)

Juffmann, Thomas; Milic, Adriana; Muellneritsch, Michael; Arndt, Markus

2011-03-01

Surface based detection schemes for molecular interferometry experiments might be crucial in the search for the quantum properties of larger and larger objects since they provide single particle sensitivity. Here we report on molecular interferograms of different biomolecules imaged using fluorescence microscopy. Being able to watch the build-up of an interferogram live and in situ reveals the matter-wave behavior of these complex molecules in an unprecedented way. We examine several problems encountered due to van-der-Waals forces between the molecules and the diffraction grating and discuss possible ways to circumvent these. Especially the advent of ultra-thin (1-100 atomic layers) diffraction masks might path the way towards molecular holography. We also discuss other possible applications such as coherent molecular microscopy.

The influence of FMRI lie detection evidence on juror decision-making.

PubMed

McCabe, David P; Castel, Alan D; Rhodes, Matthew G

2011-01-01

In the current study, we report on an experiment examining whether functional magnetic resonance imaging (fMRI) lie detection evidence would influence potential jurors' assessment of guilt in a criminal trial. Potential jurors (N = 330) read a vignette summarizing a trial, with some versions of the vignette including lie detection evidence indicating that the defendant was lying about having committed the crime. Lie detector evidence was based on evidence from the polygraph, fMRI (functional brain imaging), or thermal facial imaging. Results showed that fMRI lie detection evidence led to more guilty verdicts than lie detection evidence based on polygraph evidence, thermal facial imaging, or a control condition that did not include lie detection evidence. However, when the validity of the fMRI lie detection evidence was called into question on cross-examination, guilty verdicts were reduced to the level of the control condition. These results provide important information about the influence of lie detection evidence in legal settings. Copyright © 2011 John Wiley & Sons, Ltd.

An improved three-dimensional non-scanning laser imaging system based on digital micromirror device

NASA Astrophysics Data System (ADS)

Xia, Wenze; Han, Shaokun; Lei, Jieyu; Zhai, Yu; Timofeev, Alexander N.

2018-01-01

Nowadays, there are two main methods to realize three-dimensional non-scanning laser imaging detection, which are detection method based on APD and detection method based on Streak Tube. However, the detection method based on APD possesses some disadvantages, such as small number of pixels, big pixel interval and complex supporting circuit. The detection method based on Streak Tube possesses some disadvantages, such as big volume, bad reliability and high cost. In order to resolve the above questions, this paper proposes an improved three-dimensional non-scanning laser imaging system based on Digital Micromirror Device. In this imaging system, accurate control of laser beams and compact design of imaging structure are realized by several quarter-wave plates and a polarizing beam splitter. The remapping fiber optics is used to sample the image plane of receiving optical lens, and transform the image into line light resource, which can realize the non-scanning imaging principle. The Digital Micromirror Device is used to convert laser pulses from temporal domain to spatial domain. The CCD with strong sensitivity is used to detect the final reflected laser pulses. In this paper, we also use an algorithm which is used to simulate this improved laser imaging system. In the last, the simulated imaging experiment demonstrates that this improved laser imaging system can realize three-dimensional non-scanning laser imaging detection.

Atmospheric modeling of Mars CH4 subsurface clathrates releases mimicking SAM and 2003 Earth-based detections

NASA Astrophysics Data System (ADS)

Pla-Garcia, Jorge

2017-10-01

The aim of this work is to establish the amount of mixing during all martian seasons to test whether CH4 releases inside or outside of Gale crater are consistent with MSL-SAM observations. Several modeling scenarios were configured, including instantaneous and steady releases, both inside and outside the crater. A simulation to mimic the 2003 Earth-based detections (Mumma et al. 2009 or M09) was also performed. In the instantaneous release inside Gale experiments, Ls270 was shown to be the faster mixing season when air within and outside the crater was well mixed: all tracer mass inside the crater is diluted after just 8 hours. The mixing of near surface crater air with the external environment in the rest of the year is potentially rapid but slower than Ls270. In the instantaneous release outside Gale (NW) experiment, in just 12 hours the CH4 that makes it to the MSL landing location is diluted by six orders of magnitude. The timescale of mixing in the model is on the order of 1 sol regardless of season. The duration of the CH4 peak observed by SAM is 100 sols. Therefore there is a steady release inside the crater, or there is a large magnitude steady release outside the crater. In the steady release Gale experiments, CH4 flux rate from ground is 1.8 kg m-2 s-1 (Gloesener et al. 2017) and it is not predictive. In these experiments, ~200 times lower CH4 values detected by SAM are modeled around MSL location. There are CH4 concentration variations of orders of magnitude depending on the hour, so timing of SAM measurements is important. With a larger (but further away) outside crater release area compared to inside, similar CH4 values around MSL are modeled, so distance to source is important. In the steady experiments mimicking M09 detection release area, only 12 times lower CH4 values detected by SAM are modeled around MSL. The highest value in the M09 modeled scenario (0.6 ppbv) is reached in Ls270. This value is the highest of all modeled experiments. With our initial conditions, SAM should not be able to detect CH4, but if we multiply flux by 12, increase the release area or move it closer to MSL (or all of above), it may be possible to get CH4 values that SAM could detect regardless where it comes from.

Rapid culture-independent microbial analysis aboard the international space station (ISS) stage two: quantifying three microbial biomarkers.

PubMed

Morris, Heather C; Damon, Michael; Maule, Jake; Monaco, Lisa A; Wainwright, Norm

2012-09-01

Abstract A portable, rapid, microbial detection unit, the Lab-On-a-Chip Application Development Portable Test System (LOCAD-PTS), was launched to the International Space Station (ISS) as a technology demonstration unit in December 2006. Results from the first series of experiments designed to detect Gram-negative bacteria on ISS surfaces by quantifying a single microbial biomarker lipopolysaccharide (LPS) were reported in a previous article. Herein, we report additional technology demonstration experiments expanding the on-orbit capabilities of the LOCAD-PTS to detecting three different microbial biomarkers on ISS surfaces. Six different astronauts on more than 20 occasions participated in these experiments, which were designed to test the new beta-glucan (fungal cell wall molecule) and lipoteichoic acid (LTA; Gram-positive bacterial cell wall component) cartridges individually and in tandem with the existing Limulus Amebocyte Lysate (LAL; Gram-negative bacterial LPS detection) cartridges. Additionally, we conducted the sampling side by side with the standard culture-based detection method currently used on the ISS. Therefore, we present data on the distribution of three microbial biomarkers collected from various surfaces in every module present on the ISS at the time of sampling. In accordance with our previous experiments, we determined that spacecraft surfaces known to be frequently in contact with crew members demonstrated higher values of all three microbial molecules. Key Words: Planetary protection-Spaceflight-Microbiology-Biosensor. Astrobiology 12, 830-840.

Cold-Rolled Strip Steel Stress Detection Technology Based on a Magnetoresistance Sensor and the Magnetoelastic Effect

PubMed Central

Guan, Ben; Zang, Yong; Han, Xiaohui; Zheng, Kailun

2018-01-01

Driven by the demands for contactless stress detection, technologies are being used for shape control when producing cold-rolled strips. This paper presents a novel contactless stress detection technology based on a magnetoresistance sensor and the magnetoelastic effect, enabling the detection of internal stress in manufactured cold-rolled strips. An experimental device was designed and produced. Characteristics of this detection technology were investigated through experiments assisted by theoretical analysis. Theoretically, a linear correlation exists between the internal stress of strip steel and the voltage output of a magneto-resistive sensor. Therefore, for this stress detection system, the sensitivity of the stress detection was adjusted by adjusting the supply voltage of the magnetoresistance sensor, detection distance, and other relevant parameters. The stress detection experimental results showed that this detection system has good repeatability and linearity. The detection error was controlled within 1.5%. Moreover, the intrinsic factors of the detected strip steel, including thickness, carbon percentage, and crystal orientation, also affected the sensitivity of the detection system. The detection technology proposed in this research enables online contactless detection and meets the requirements for cold-rolled steel strips. PMID:29883387

Cold-Rolled Strip Steel Stress Detection Technology Based on a Magnetoresistance Sensor and the Magnetoelastic Effect.

PubMed

Guan, Ben; Zang, Yong; Han, Xiaohui; Zheng, Kailun

2018-05-21

Driven by the demands for contactless stress detection, technologies are being used for shape control when producing cold-rolled strips. This paper presents a novel contactless stress detection technology based on a magnetoresistance sensor and the magnetoelastic effect, enabling the detection of internal stress in manufactured cold-rolled strips. An experimental device was designed and produced. Characteristics of this detection technology were investigated through experiments assisted by theoretical analysis. Theoretically, a linear correlation exists between the internal stress of strip steel and the voltage output of a magneto-resistive sensor. Therefore, for this stress detection system, the sensitivity of the stress detection was adjusted by adjusting the supply voltage of the magnetoresistance sensor, detection distance, and other relevant parameters. The stress detection experimental results showed that this detection system has good repeatability and linearity. The detection error was controlled within 1.5%. Moreover, the intrinsic factors of the detected strip steel, including thickness, carbon percentage, and crystal orientation, also affected the sensitivity of the detection system. The detection technology proposed in this research enables online contactless detection and meets the requirements for cold-rolled steel strips.

Rod-cone based color vision in seals under photopic conditions.

PubMed

Oppermann, Daniela; Schramme, Jürgen; Neumeyer, Christa

2016-08-01

Marine mammals have lost the ability to express S-cone opsin, and possess only one type of M/L-cone in addition to numerous rods. As they are cone monochromats they should be color blind. However, early behavioral experiments with fur seals and sea lions indicated discrimination ability between many shades of grey and blue or green. On the other hand, most recent training experiments with harbor seals under "mesopic" conditions demonstrated rod based color blindness (Scholtyssek et al., 2015). In our experiments we trained two harbor seals (Phoca vitulina) and two South African fur seals (Arctocephalus pusillus) with surface colors under photopic conditions. The seals had to detect a triangle on grey background shown on one of three test fields while the other two test fields were homogeneously grey. In a first series of experiments we determined brightness detection. We found a luminance contrast of >3% sufficient for correctly choosing the triangle. In the tests for color vision the triangle was blue, green or yellow in grey surround. The results show that the animals could see the colored triangle despite minimal or zero brightness contrast. Thus, seals have color vision based on the contribution of cones and rods even in bright daylight. Copyright © 2016 Elsevier Ltd. All rights reserved.

Taking the CCDs to the ultimate performance for low threshold experiments

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

Haro, Miguel; Moroni, Guillermo; Tiffenberg, Javier

2016-11-14

Scientific grade CCDs show atractive capabilities for the detection of particles with small energy deposition in matter. Their very low threshold of approximately 40 eV and their good spatial reconstruction of the event are key properties for currently running experiments: CONNIE and DAMIC. Both experiments can benefit from any increase of the detection efficiency of nuclear recoils at low energy. In this work we present two different approaches to increase this efficiency by increasing the SNR of events. The first one is based on the reduction of the readout noise of the device, which is the main contribution of uncertaintymore » to the signal measurement. New studies on the electronic noise from the integrated output amplifier and the readout electronics will be presented together with result of a new configuration showing a lower limit on the readout noise which can be implemented on the current setup of the CCD based experiments. A second approach to increase the SNR of events at low energy that will be presented is the studies of the spatial conformation of nuclear recoil events at different depth in the active volume by studies of new effects that differ from expected models based on not interacting diffusion model of electrons in the semiconductor.« less

Operational wind shear detection and warning - The 'CLAWS' experience at Denver and future objectives

NASA Technical Reports Server (NTRS)

Mccarthy, John; Wilson, James W.; Hjelmfelt, Mark R.

1986-01-01

An operational wind shear detection and warning experiment was conducted at Denver's Stapleton International Airport in summer 1984. Based on meteorological interpretation of scope displays from a Doppler weather radar, warnings were transmitted to the air traffic control tower via voice radio. Analyses of results indicated real skill in daily microburst forecasts and very short-term (less than 5-min) warnings. Wind shift advisories with 15-30 min forecasts, permitted more efficient runway reconfigurations. Potential fuel savings were estimated at $875,000/yr at Stapleton. The philosophy of future development toward an automated, operational system is discussed.

Experiment to Detect Accelerating Modes in a Photonic Bandgap Fiber

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

England, R.J.; /SLAC; Colby, E.R.

An experimental effort is currently underway at the E-163 test beamline at Stanford Linear Accelerator Center to use a hollow-core photonic bandgap (PBG) fiber as a high-gradient laser-based accelerating structure for electron bunches. For the initial stage of this experiment, a 50pC, 60 MeV electron beam will be coupled into the fiber core and the excited modes will be detected using a spectrograph to resolve their frequency signatures in the wakefield radiation generated by the beam. They will describe the experimental plan and recent simulation studies of candidate fibers.

Testing the Rotation Stage in the ARIADNE Axion Experiment

NASA Astrophysics Data System (ADS)

Dargert, Jordan; Lohmeyer, Chloe; Harkness, Mindy; Cunningham, Mark; Fosbinder-Elkins, Harry; Geraci, Andrew; Ariadne Collaboration

2017-04-01

The Axion Resonant InterAction Detection Experiment (ARIADNE) will search for the Peccei-Quinn (PQ) axion, a hypothetical particle that is a dark matter candidate. Using a new technique based on Nuclear Magnetic Resonance, this new method can probe well into the allowed PQ axion mass range. Additionally, it does not rely on cosmological assumptions, meaning that the PQ Axion would be sourced locally. Our project relies on the stability of a rotating segmented source mass and superconducting magnetic shielding. Superconducting shielding is essential for limiting magnetic noise, thus allowing a feasible level of sensitivity required for PQ Axion detection. Progress on testing the stability of the rotary mechanism will be reported, and the design for the superconducting shielding in the experiment will be discussed, along with plans for moving the experiment forward. NSF Grant PHY-1509176.

Automatic detection of suspicious behavior of pickpockets with track-based features in a shopping mall

NASA Astrophysics Data System (ADS)

Bouma, Henri; Baan, Jan; Burghouts, Gertjan J.; Eendebak, Pieter T.; van Huis, Jasper R.; Dijk, Judith; van Rest, Jeroen H. C.

2014-10-01

Proactive detection of incidents is required to decrease the cost of security incidents. This paper focusses on the automatic early detection of suspicious behavior of pickpockets with track-based features in a crowded shopping mall. Our method consists of several steps: pedestrian tracking, feature computation and pickpocket recognition. This is challenging because the environment is crowded, people move freely through areas which cannot be covered by a single camera, because the actual snatch is a subtle action, and because collaboration is complex social behavior. We carried out an experiment with more than 20 validated pickpocket incidents. We used a top-down approach to translate expert knowledge in features and rules, and a bottom-up approach to learn discriminating patterns with a classifier. The classifier was used to separate the pickpockets from normal passers-by who are shopping in the mall. We performed a cross validation to train and evaluate our system. In this paper, we describe our method, identify the most valuable features, and analyze the results that were obtained in the experiment. We estimate the quality of these features and the performance of automatic detection of (collaborating) pickpockets. The results show that many of the pickpockets can be detected at a low false alarm rate.

Multi-object detection and tracking technology based on hexagonal opto-electronic detector

NASA Astrophysics Data System (ADS)

Song, Yong; Hao, Qun; Li, Xiang

2008-02-01

A novel multi-object detection and tracking technology based on hexagonal opto-electronic detector is proposed, in which (1) a new hexagonal detector, which is composed of 6 linear CCDs, has been firstly developed to achieve the field of view of 360 degree, (2) to achieve the detection and tracking of multi-object with high speed, the object recognition criterions of Object Signal Width Criterion (OSWC) and Horizontal Scale Ratio Criterion (HSRC) are proposed. In this paper, Simulated Experiments have been carried out to verify the validity of the proposed technology, which show that the detection and tracking of multi-object can be achieved with high speed by using the proposed hexagonal detector and the criterions of OSWC and HSRC, indicating that the technology offers significant advantages in Photo-electric Detection, Computer Vision, Virtual Reality, Augment Reality, etc.

Experiments And Model Development For The Investigation Of Sooting And Radiation Effects In Microgravity Droplet Combustion

NASA Technical Reports Server (NTRS)

Yozgatligil, Ahmet; Choi, Mun Young; Dryer, Frederick L.; Kazakov, Andrei; Dobashi, Ritsu

2003-01-01

This study involves flight experiments (for droplets between 1.5 to 5 mm) and supportive ground-based experiments, with concurrent numerical model development and validation. The experiments involve two fuels: n-heptane, and ethanol. The diagnostic measurements include light extinction for soot volume fraction, two-wavelength pyrometry and thin-filament pyrometry for temperature, spectral detection for OH chemiluminescence, broadband radiometry for flame emission, and thermophoretic sampling with subsequent transmission electron microscopy for soot aerosol property calculations.

Working Group Report: Dark Matter Complementarity (Dark Matter in the Coming Decade: Complementary Paths to Discovery and Beyond)

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

Arrenberg, Sebastian; et al.,

2013-10-31

In this Report we discuss the four complementary searches for the identity of dark matter: direct detection experiments that look for dark matter interacting in the lab, indirect detection experiments that connect lab signals to dark matter in our own and other galaxies, collider experiments that elucidate the particle properties of dark matter, and astrophysical probes sensitive to non-gravitational interactions of dark matter. The complementarity among the different dark matter searches is discussed qualitatively and illustrated quantitatively in several theoretical scenarios. Our primary conclusion is that the diversity of possible dark matter candidates requires a balanced program based on allmore » four of those approaches.« less

Consequences of recent loophole-free experiments on a relaxation of measurement independence

NASA Astrophysics Data System (ADS)

Hnilo, Alejandro A.

2017-02-01

Recent experiments using innovative optical detectors and techniques have strongly increased the capacity of testing the violation of the Bell's inequalities in Nature. Most of them have used the Eberhard's inequality (EI) to close the "detection" loophole. Closing the "locality" loophole has been attempted by spacelike separated detections and fast changes of the bases of observation, driven by random number generators of new design. Also, pulsed pumping and time-resolved data recording to close the "time-coincidence" loophole, and sophisticated statistical methods to close the "memory" loophole, have been used. In this paper, the meaning of the EI is reviewed. A simple hidden variables theory based on a relaxation of the condition of "measurement independence," which was devised long ago for the Clauser-Horne-Shimony and Holt inequality, is adapted to the EI case. It is used here to evaluate the significance of the results of the recent experiments, which are briefly described. A table summarizes the main results.

Reflection symmetry detection using locally affine invariant edge correspondence.

PubMed

Wang, Zhaozhong; Tang, Zesheng; Zhang, Xiao

2015-04-01

Reflection symmetry detection receives increasing attentions in recent years. The state-of-the-art algorithms mainly use the matching of intensity-based features (such as the SIFT) within a single image to find symmetry axes. This paper proposes a novel approach by establishing the correspondence of locally affine invariant edge-based features, which are superior to the intensity based in the aspects that it is insensitive to illumination variations, and applicable to textureless objects. The locally affine invariance is achieved by simple linear algebra for efficient and robust computations, making the algorithm suitable for detections under object distortions like perspective projection. Commonly used edge detectors and a voting process are, respectively, used before and after the edge description and matching steps to form a complete reflection detection pipeline. Experiments are performed using synthetic and real-world images with both multiple and single reflection symmetry axis. The test results are compared with existing algorithms to validate the proposed method.

Detection scheme for a partially occluded pedestrian based on occluded depth in lidar-radar sensor fusion

NASA Astrophysics Data System (ADS)

Kwon, Seong Kyung; Hyun, Eugin; Lee, Jin-Hee; Lee, Jonghun; Son, Sang Hyuk

2017-11-01

Object detections are critical technologies for the safety of pedestrians and drivers in autonomous vehicles. Above all, occluded pedestrian detection is still a challenging topic. We propose a new detection scheme for occluded pedestrian detection by means of lidar-radar sensor fusion. In the proposed method, the lidar and radar regions of interest (RoIs) have been selected based on the respective sensor measurement. Occluded depth is a new means to determine whether an occluded target exists or not. The occluded depth is a region projected out by expanding the longitudinal distance with maintaining the angle formed by the outermost two end points of the lidar RoI. The occlusion RoI is the overlapped region made by superimposing the radar RoI and the occluded depth. The object within the occlusion RoI is detected by the radar measurement information and the occluded object is estimated as a pedestrian based on human Doppler distribution. Additionally, various experiments are performed in detecting a partially occluded pedestrian in outdoor as well as indoor environments. According to experimental results, the proposed sensor fusion scheme has much better detection performance compared to the case without our proposed method.

Testing the implicit processing hypothesis of precognitive dream experience.

PubMed

Valášek, Milan; Watt, Caroline; Hutton, Jenny; Neill, Rebecca; Nuttall, Rachel; Renwick, Grace

2014-08-01

Seemingly precognitive (prophetic) dreams may be a result of one's unconscious processing of environmental cues and having an implicit inference based on these cues manifest itself in one's dreams. We present two studies exploring this implicit processing hypothesis of precognitive dream experience. Study 1 investigated the relationship between implicit learning, transliminality, and precognitive dream belief and experience. Participants completed the Serial Reaction Time task and several questionnaires. We predicted a positive relationship between the variables. With the exception of relationships between transliminality and precognitive dream belief and experience, this prediction was not supported. Study 2 tested the hypothesis that differences in the ability to notice subtle cues explicitly might account for precognitive dream beliefs and experiences. Participants completed a modified version of the flicker paradigm. We predicted a negative relationship between the ability to explicitly detect changes and precognitive dream variables. This relationship was not found. There was also no relationship between precognitive dream belief and experience and implicit change detection. Copyright © 2014 Elsevier Inc. All rights reserved.

Recommendations for the design, optimization, and qualification of cell-based assays used for the detection of neutralizing antibody responses elicited to biological therapeutics.

PubMed

Gupta, Shalini; Indelicato, Stephen R; Jethwa, Vijay; Kawabata, Thomas; Kelley, Marian; Mire-Sluis, Anthony R; Richards, Susan M; Rup, Bonita; Shores, Elizabeth; Swanson, Steven J; Wakshull, Eric

2007-04-10

The administration of biological therapeutics can evoke some level of immune response to the drug product in the receiving subjects. An immune response comprised of neutralizing antibodies can lead to loss of efficacy or potentially more serious clinical sequelae. Therefore, it is important to monitor the immunogenicity of biological therapeutics throughout the drug product development cycle. Immunoassays are typically used to screen for the presence and development of anti-drug product antibodies. However, in-vitro cell-based assays prove extremely useful for the characterization of immunoassay-positive samples to determine if the detected antibodies have neutralizing properties. This document provides scientific recommendations based on the experience of the authors for the development of cell-based assays for the detection of neutralizing antibodies in non-clinical and clinical studies.

Parallel detection experiment of fluorescence confocal microscopy using DMD.

PubMed

Wang, Qingqing; Zheng, Jihong; Wang, Kangni; Gui, Kun; Guo, Hanming; Zhuang, Songlin

2016-05-01

Parallel detection of fluorescence confocal microscopy (PDFCM) system based on Digital Micromirror Device (DMD) is reported in this paper in order to realize simultaneous multi-channel imaging and improve detection speed. DMD is added into PDFCM system, working to take replace of the single traditional pinhole in the confocal system, which divides the laser source into multiple excitation beams. The PDFCM imaging system based on DMD is experimentally set up. The multi-channel image of fluorescence signal of potato cells sample is detected by parallel lateral scanning in order to verify the feasibility of introducing the DMD into fluorescence confocal microscope. In addition, for the purpose of characterizing the microscope, the depth response curve is also acquired. The experimental result shows that in contrast to conventional microscopy, the DMD-based PDFCM system has higher axial resolution and faster detection speed, which may bring some potential benefits in the biology and medicine analysis. SCANNING 38:234-239, 2016. © 2015 Wiley Periodicals, Inc. © Wiley Periodicals, Inc.

Robust Fault Detection for Aircraft Using Mixed Structured Singular Value Theory and Fuzzy Logic

NASA Technical Reports Server (NTRS)

Collins, Emmanuel G.

2000-01-01

The purpose of fault detection is to identify when a fault or failure has occurred in a system such as an aircraft or expendable launch vehicle. The faults may occur in sensors, actuators, structural components, etc. One of the primary approaches to model-based fault detection relies on analytical redundancy. That is the output of a computer-based model (actually a state estimator) is compared with the sensor measurements of the actual system to determine when a fault has occurred. Unfortunately, the state estimator is based on an idealized mathematical description of the underlying plant that is never totally accurate. As a result of these modeling errors, false alarms can occur. This research uses mixed structured singular value theory, a relatively recent and powerful robustness analysis tool, to develop robust estimators and demonstrates the use of these estimators in fault detection. To allow qualitative human experience to be effectively incorporated into the detection process fuzzy logic is used to predict the seriousness of the fault that has occurred.

Complex background suppression using global-local registration strategy for the detection of small-moving target on moving platform

NASA Astrophysics Data System (ADS)

Zou, Tianhao; Zuo, Zhengrong

2018-02-01

Target detection is a very important and basic problem of computer vision and image processing. The most often case we meet in real world is a detection task for a moving-small target on moving platform. The commonly used methods, such as Registration-based suppression, can hardly achieve a desired result. To crack this hard nut, we introduce a Global-local registration based suppression method. Differ from the traditional ones, the proposed Global-local Registration Strategy consider both the global consistency and the local diversity of the background, obtain a better performance than normal background suppression methods. In this paper, we first discussed the features about the small-moving target detection on unstable platform. Then we introduced a new strategy and conducted an experiment to confirm its noisy stability. In the end, we confirmed the background suppression method based on global-local registration strategy has a better perform in moving target detection on moving platform.

Atmospheric modeling of Mars CH4 subsurface clathrates releases mimicking SAM and 2003 Earth-based detections

NASA Astrophysics Data System (ADS)

Pla-García, J.; Rafkin, S. C.

2017-12-01

The aim of this work is to establish the amount of mixing during all martian seasons to test whether CH4 releases inside or outside of Gale crater are consistent with MSL-SAM observations. Several modeling scenarios were configured, including instantaneous and steady releases, both inside and outside the crater. A simulation to mimic the 2003 Earth-based detections (Mumma et al. 2009 or M09) was also performed. In the instantaneous release inside Gale experiments, Ls270 was shown to be the faster mixing season when air within and outside the crater was well mixed: all tracer mass inside the crater is diluted after just 8 hours. The mixing of near surface crater air with the external environment in the rest of the year is potentially rapid but slower than Ls270.In the instantaneous release outside Gale (NW) experiment, in just 12 hours the CH4 that makes it to the MSL landing location is diluted by six orders of magnitude. The timescale of mixing in MRAMS experiments is on the order of 1 sol regardless of season. The duration of the CH4 peak observed by SAM is 100 sols. Therefore there is a steady release inside the crater, or there is a very large magnitude steady release outside the crater. In the steady release Gale experiments, CH4 flux rate from ground is 1.8 kg m-2 s-1 (derived from Gloesener et al. 2017 clathrates fluxes) and it is not predictive. In these experiments, 200 times lower CH4 values detected by SAM are modeled around MSL location. There are CH4 concentration variations of orders of magnitude depending on the hour, so timing of SAM measurements is important. With a larger (but further away) outside crater release area compared to inside, similar CH4 values around MSL are modeled, so distance to source is important. In the steady experiments mimicking M09 detection release area, only 12 times lower CH4 values detected by SAM are modeled around MSL. The highest value in the M09 modeled scenario (0.6 ppbv) is reached in Ls270. This value is the highest of all modeled experiments. With our initial conditions (flux rates, release area size and distance to MSL), SAM should not be able (or very difficult) to detect CH4, but if we multiply flux by 12, increase the release area or move it closer to MSL (or all of above), it may be possible to get CH4 values that SAM could detect regardless where it comes from: inside, outside (close to) or far away from Gale.

[Analysis of Cr in soil by LIBS based on conical spatial confinement of plasma].

PubMed

Lin, Yong-Zeng; Yao, Ming-Yin; Chen, Tian-Bing; Li, Wen-Bing; Zheng, Mei-Lan; Xu, Xue-Hong; Tu, Jian-Ping; Liu, Mu-Hua

2013-11-01

The present study is to improve the sensitivity of detection and reduce the limit of detection in detecting heavy metal of soil by laser induced breakdown spectroscopy (LIBS). The Cr element of national standard soil was regarded as the research object. In the experiment, a conical cavity with small diameter end of 20 mm and large diameter end of 45 mm respectively was installed below the focusing lens near the experiment sample to mainly confine the signal transmitted by plasma and to some extent to confine the plasma itself in the LIBS setup. In detecting Cr I 425.44 nm, the beast delay time gained from experiment is 1.3 micros, and the relative standard deviation is below 10%. Compared with the setup of non-spatial confinement, the spectral intensity of Cr in the soil sample was enhanced more than 7%. Calibration curve was established in the Cr concentration range from 60 to 400 microg x g(-1). Under the condition of spatial confinement, the liner regression coefficient and the limit of detection were 0.997 71 and 18.85 microg x g(-1) respectively, however, the regression coefficient and the limit of detection were 0.991 22 and 36.99 microg x g(-1) without spatial confinement. So, this shows that conical spatial confinement can/improve the sensitivity of detection and enhance the spectral intensity. And it is a good auxiliary function in detecting Cr in the soil by laser induced breakdown spectroscopy.

Evaluation of automated time-lapse microscopy for assessment of in vitro activity of antibiotics.

PubMed

Ungphakorn, Wanchana; Malmberg, Christer; Lagerbäck, Pernilla; Cars, Otto; Nielsen, Elisabet I; Tängdén, Thomas

2017-01-01

This study aimed to evaluate the potential of a new time-lapse microscopy based method (oCelloScope) to efficiently assess the in vitro antibacterial effects of antibiotics. Two E. coli and one P. aeruginosa strain were exposed to ciprofloxacin, colistin, ertapenem and meropenem in 24-h experiments. Background corrected absorption (BCA) derived from the oCelloScope was used to detect bacterial growth. The data obtained with the oCelloScope were compared with those of the automated Bioscreen C method and standard time-kill experiments and a good agreement in results was observed during 6-24h of experiments. Viable counts obtained at 1, 4, 6 and 24h during oCelloScope and Bioscreen C experiments were well correlated with the corresponding BCA and optical density (OD) data. Initial antibacterial effects during the first 6h of experiments were difficult to detect with the automated methods due to their high detection limits (approximately 10 5 CFU/mL for oCelloScope and 10 7 CFU/mL for Bioscreen C), the inability to distinguish between live and dead bacteria and early morphological changes of bacteria during exposure to ciprofloxacin, ertapenem and meropenem. Regrowth was more frequently detected in time-kill experiments, possibly related to the larger working volume with an increased risk of pre-existing or emerging resistance. In comparison with Bioscreen C, the oCelloScope provided additional information on bacterial growth dynamics in the range of 10 5 to 10 7 CFU/mL and morphological features. In conclusion, the oCelloScope would be suitable for detection of in vitro effects of antibiotics, especially when a large number of regimens need to be tested. Copyright © 2016 Elsevier B.V. All rights reserved.

Control-based continuation: Bifurcation and stability analysis for physical experiments

NASA Astrophysics Data System (ADS)

Barton, David A. W.

2017-02-01

Control-based continuation is technique for tracking the solutions and bifurcations of nonlinear experiments. The idea is to apply the method of numerical continuation to a feedback-controlled physical experiment such that the control becomes non-invasive. Since in an experiment it is not (generally) possible to set the state of the system directly, the control target becomes a proxy for the state. Control-based continuation enables the systematic investigation of the bifurcation structure of a physical system, much like if it was numerical model. However, stability information (and hence bifurcation detection and classification) is not readily available due to the presence of stabilising feedback control. This paper uses a periodic auto-regressive model with exogenous inputs (ARX) to approximate the time-varying linearisation of the experiment around a particular periodic orbit, thus providing the missing stability information. This method is demonstrated using a physical nonlinear tuned mass damper.

Adaptive 4d Psi-Based Change Detection

NASA Astrophysics Data System (ADS)

Yang, Chia-Hsiang; Soergel, Uwe

2018-04-01

In a previous work, we proposed a PSI-based 4D change detection to detect disappearing and emerging PS points (3D) along with their occurrence dates (1D). Such change points are usually caused by anthropic events, e.g., building constructions in cities. This method first divides an entire SAR image stack into several subsets by a set of break dates. The PS points, which are selected based on their temporal coherences before or after a break date, are regarded as change candidates. Change points are then extracted from these candidates according to their change indices, which are modelled from their temporal coherences of divided image subsets. Finally, we check the evolution of the change indices for each change point to detect the break date that this change occurred. The experiment validated both feasibility and applicability of our method. However, two questions still remain. First, selection of temporal coherence threshold associates with a trade-off between quality and quantity of PS points. This selection is also crucial for the amount of change points in a more complex way. Second, heuristic selection of change index thresholds brings vulnerability and causes loss of change points. In this study, we adapt our approach to identify change points based on statistical characteristics of change indices rather than thresholding. The experiment validates this adaptive approach and shows increase of change points compared with the old version. In addition, we also explore and discuss optimal selection of temporal coherence threshold.

An integrated microfluidic analysis microsystems with bacterial capture enrichment and in-situ impedance detection

NASA Astrophysics Data System (ADS)

Liu, Hai-Tao; Wen, Zhi-Yu; Xu, Yi; Shang, Zheng-Guo; Peng, Jin-Lan; Tian, Peng

2017-09-01

In this paper, an integrated microfluidic analysis microsystems with bacterial capture enrichment and in-situ impedance detection was purposed based on microfluidic chips dielectrophoresis technique and electrochemical impedance detection principle. The microsystems include microfluidic chip, main control module, and drive and control module, and signal detection and processing modulet and result display unit. The main control module produce the work sequence of impedance detection system parts and achieve data communication functions, the drive and control circuit generate AC signal which amplitude and frequency adjustable, and it was applied on the foodborne pathogens impedance analysis microsystems to realize the capture enrichment and impedance detection. The signal detection and processing circuit translate the current signal into impendence of bacteria, and transfer to computer, the last detection result is displayed on the computer. The experiment sample was prepared by adding Escherichia coli standard sample into chicken sample solution, and the samples were tested on the dielectrophoresis chip capture enrichment and in-situ impedance detection microsystems with micro-array electrode microfluidic chips. The experiments show that the Escherichia coli detection limit of microsystems is 5 × 104 CFU/mL and the detection time is within 6 min in the optimization of voltage detection 10 V and detection frequency 500 KHz operating conditions. The integrated microfluidic analysis microsystems laid the solid foundation for rapid real-time in-situ detection of bacteria.

Supernovae studied with a ground level atmospheric fluorescence

NASA Technical Reports Server (NTRS)

Bertsch, D. L.

1972-01-01

A monitoring experiment was undertaken late 1968 to search for photon bursts of extraterrestrial origin. The experiment and the results of the observations to date are summarized. The method of detection employs ground-based photomultiplier tubes which are sensitive to the secondary fluorescence light that would be produced when the primary pulse is absorbed in the atmosphere.

Thermal effects on nonlinear vibration of a carbon nanotube-based mass sensor using finite element analysis

NASA Astrophysics Data System (ADS)

Kang, Dong-Keun; Kim, Chang-Wan; Yang, Hyun-Ik

2017-01-01

In the present study we carried out a dynamic analysis of a CNT-based mass sensor by using a finite element method (FEM)-based nonlinear analysis model of the CNT resonator to elucidate the combined effects of thermal effects and nonlinear oscillation behavior upon the overall mass detection sensitivity. Mass sensors using carbon nanotube (CNT) resonators provide very high sensing performance. Because CNT-based resonators can have high aspect ratios, they can easily exhibit nonlinear oscillation behavior due to large displacements. Also, CNT-based devices may experience high temperatures during their manufacture and operation. These geometrical nonlinearities and temperature changes affect the sensing performance of CNT-based mass sensors. However, it is very hard to find previous literature addressing the detection sensitivity of CNT-based mass sensors including considerations of both these nonlinear behaviors and thermal effects. We modeled the nonlinear equation of motion by using the von Karman nonlinear strain-displacement relation, taking into account the additional axial force associated with the thermal effect. The FEM was employed to solve the nonlinear equation of motion because it can effortlessly handle the more complex geometries and boundary conditions. A doubly clamped CNT resonator actuated by distributed electrostatic force was the configuration subjected to the numerical experiments. Thermal effects upon the fundamental resonance behavior and the shift of resonance frequency due to attached mass, i.e., the mass detection sensitivity, were examined in environments of both high and low (or room) temperature. The fundamental resonance frequency increased with decreasing temperature in the high temperature environment, and increased with increasing temperature in the low temperature environment. The magnitude of the shift in resonance frequency caused by an attached mass represents the sensing performance of a mass sensor, i.e., its mass detection sensitivity, and it can be seen that this shift is affected by the temperature change and the amount of electrostatic force. The thermal effects on the mass detection sensitivity are intensified in the linear oscillation regime and increase with increasing CNT length; this intensification can either improve or worsen the detection sensitivity.

Measurement of fault latency in a digital avionic miniprocessor

NASA Technical Reports Server (NTRS)

Mcgough, J. G.; Swern, F. L.

1981-01-01

The results of fault injection experiments utilizing a gate-level emulation of the central processor unit of the Bendix BDX-930 digital computer are presented. The failure detection coverage of comparison-monitoring and a typical avionics CPU self-test program was determined. The specific tasks and experiments included: (1) inject randomly selected gate-level and pin-level faults and emulate six software programs using comparison-monitoring to detect the faults; (2) based upon the derived empirical data develop and validate a model of fault latency that will forecast a software program's detecting ability; (3) given a typical avionics self-test program, inject randomly selected faults at both the gate-level and pin-level and determine the proportion of faults detected; (4) determine why faults were undetected; (5) recommend how the emulation can be extended to multiprocessor systems such as SIFT; and (6) determine the proportion of faults detected by a uniprocessor BIT (built-in-test) irrespective of self-test.

Using Activity-Related Behavioural Features towards More Effective Automatic Stress Detection

PubMed Central

Giakoumis, Dimitris; Drosou, Anastasios; Cipresso, Pietro; Tzovaras, Dimitrios; Hassapis, George; Gaggioli, Andrea; Riva, Giuseppe

2012-01-01

This paper introduces activity-related behavioural features that can be automatically extracted from a computer system, with the aim to increase the effectiveness of automatic stress detection. The proposed features are based on processing of appropriate video and accelerometer recordings taken from the monitored subjects. For the purposes of the present study, an experiment was conducted that utilized a stress-induction protocol based on the stroop colour word test. Video, accelerometer and biosignal (Electrocardiogram and Galvanic Skin Response) recordings were collected from nineteen participants. Then, an explorative study was conducted by following a methodology mainly based on spatiotemporal descriptors (Motion History Images) that are extracted from video sequences. A large set of activity-related behavioural features, potentially useful for automatic stress detection, were proposed and examined. Experimental evaluation showed that several of these behavioural features significantly correlate to self-reported stress. Moreover, it was found that the use of the proposed features can significantly enhance the performance of typical automatic stress detection systems, commonly based on biosignal processing. PMID:23028461

Developments in Analytical Chemistry: Acoustically Levitated Drop Reactors for Enzyme Reaction Kinetics and Single-Walled Carbon Nanotube-Based Sensors for Detection of Toxic Organic Phosphonates

ERIC Educational Resources Information Center

Field, Christopher Ryan

2009-01-01

Developments in analytical chemistry were made using acoustically levitated small volumes of liquid to study enzyme reaction kinetics and by detecting volatile organic compounds in the gas phase using single-walled carbon nanotubes. Experience gained in engineering, electronics, automation, and software development from the design and…

Development of an alpha scattering instrument for heavy element detection in surface materials

NASA Technical Reports Server (NTRS)

Turkevich, A. L.; Economou, T.; Blume, E.; Anderson, W.

1974-01-01

The development and characteristics of a portable instrument for detecting and measuring the amounts of lead in painted surfaces are discussed. The instrument is based on the ones used with the alpha scattering experiment on the Surveyor lunar missions. The principles underlying the instrument are described. It is stated that the performance tests of the instrument were satisfactory.

Scalable Wavelet-Based Active Network Stepping Stone Detection

DTIC Science & Technology

2012-03-22

47 4.2.2 Synchronization Frame . . . . . . . . . . . . . . . . . . . . . . . . 49 4.2.3 Frame Size...the vector. Pilot experiments result in the final algorithm shown in Figure 3.4 and the detector in Figure 3.5. Note that the synchronization frame and... synchronization frames divided by the number of total frames. Comparing this statistic to the detection threshold γ determines whether a watermark is

Vision Marker-Based In Situ Examination of Bacterial Growth in Liquid Culture Media.

PubMed

Kim, Kyukwang; Choi, Duckyu; Lim, Hwijoon; Kim, Hyeongkeun; Jeon, Jessie S

2016-12-18

The detection of bacterial growth in liquid media is an essential process in determining antibiotic susceptibility or the level of bacterial presence for clinical or research purposes. We have developed a system, which enables simplified and automated detection using a camera and a striped pattern marker. The quantification of bacterial growth is possible as the bacterial growth in the culturing vessel blurs the marker image, which is placed on the back of the vessel, and the blurring results in a decrease in the high-frequency spectrum region of the marker image. The experiment results show that the FFT (fast Fourier transform)-based growth detection method is robust to the variations in the type of bacterial carrier and vessels ranging from the culture tubes to the microfluidic devices. Moreover, the automated incubator and image acquisition system are developed to be used as a comprehensive in situ detection system. We expect that this result can be applied in the automation of biological experiments, such as the Antibiotics Susceptibility Test or toxicity measurement. Furthermore, the simple framework of the proposed growth measurement method may be further utilized as an effective and convenient method for building point-of-care devices for developing countries.

Ice detection and classification on an aircraft wing with ultrasonic shear horizontal guided waves.

PubMed

Gao, Huidong; Rose, Joseph L

2009-02-01

Ice accumulation on airfoils has been identified as a primary cause of many accidents in commercial and military aircraft. To improve aviation safety as well as reduce cost and environmental threats related to aircraft icing, sensitive, reliable, and aerodynamically compatible ice detection techniques are in great demand. Ultrasonic guided-wave-based techniques have been proved reliable for "go" and "no go" types of ice detection in some systems including the HALO system, in which the second author of this paper is a primary contributor. In this paper, we propose a new model that takes the ice layer into guided-wave modeling. Using this model, the thickness and type of ice formation can be determined from guided-wave signals. Five experimental schemes are also proposed in this paper based on some unique features identified from the guided- wave dispersion curves. A sample experiment is also presented in this paper, where a 1 mm thick glaze ice on a 2 mm aluminum plate is clearly detected. Quantitative match of the experiment data to theoretical prediction serves as a strong support for future implementation of other testing schemes proposed in this paper.

Non-Intrusive Magneto-Optic Detecting System for Investigations of Air Switching Arcs

NASA Astrophysics Data System (ADS)

Zhang, Pengfei; Zhang, Guogang; Dong, Jinlong; Liu, Wanying; Geng, Yingsan

2014-07-01

In current investigations of electric arc plasmas, experiments based on modern testing technology play an important role. To enrich the testing methods and contribute to the understanding and grasping of the inherent mechanism of air switching arcs, in this paper, a non-intrusive detecting system is described that combines the magneto-optic imaging (MOI) technique with the solution to inverse electromagnetic problems. The detecting system works in a sequence of main steps as follows: MOI of the variation of the arc flux density over a plane, magnetic field information extracted from the magneto-optic (MO) images, arc current density distribution and spatial pattern reconstruction by inverting the resulting field data. Correspondingly, in the system, an MOI set-up is designed based on the Faraday effect and the polarization properties of light, and an intelligent inversion algorithm is proposed that involves simulated annealing (SA). Experiments were carried out for high current (2 kA RMS) discharge cases in a typical low-voltage switchgear. The results show that the MO detection system possesses the advantages of visualization, high resolution and response, and electrical insulation, which provides a novel diagnostics tool for further studies of the arc.

A cross-polarization based rotating-frame separated-local-field NMR experiment under ultrafast MAS conditions

NASA Astrophysics Data System (ADS)

Zhang, Rongchun; Damron, Joshua; Vosegaard, Thomas; Ramamoorthy, Ayyalusamy

2015-01-01

Rotating-frame separated-local-field solid-state NMR experiments measure highly resolved heteronuclear dipolar couplings which, in turn, provide valuable interatomic distances for structural and dynamic studies of molecules in the solid-state. Though many different rotating-frame SLF sequences have been put forth, recent advances in ultrafast MAS technology have considerably simplified pulse sequence requirements due to the suppression of proton-proton dipolar interactions. In this study we revisit a simple two-dimensional 1H-13C dipolar coupling/chemical shift correlation experiment using 13C detected cross-polarization with a variable contact time (CPVC) and systematically study the conditions for its optimal performance at 60 kHz MAS. In addition, we demonstrate the feasibility of a proton-detected version of the CPVC experiment. The theoretical analysis of the CPVC pulse sequence under different Hartmann-Hahn matching conditions confirms that it performs optimally under the ZQ (w1H - w1C = ±wr) condition for polarization transfer. The limits of the cross polarization process are explored and precisely defined as a function of offset and Hartmann-Hahn mismatch via spin dynamics simulation and experiments on a powder sample of uniformly 13C-labeled L-isoleucine. Our results show that the performance of the CPVC sequence and subsequent determination of 1H-13C dipolar couplings are insensitive to 1H/13C frequency offset frequency when high RF fields are used on both RF channels. Conversely, the CPVC sequence is quite sensitive to the Hartmann-Hahn mismatch, particularly for systems with weak heteronuclear dipolar couplings. We demonstrate the use of the CPVC based SLF experiment as a tool to identify different carbon groups, and hope to motivate the exploration of more sophisticated 1H detected avenues for ultrafast MAS.

A new 2D segmentation method based on dynamic programming applied to computer aided detection in mammography.

PubMed

Timp, Sheila; Karssemeijer, Nico

2004-05-01

Mass segmentation plays a crucial role in computer-aided diagnosis (CAD) systems for classification of suspicious regions as normal, benign, or malignant. In this article we present a robust and automated segmentation technique--based on dynamic programming--to segment mass lesions from surrounding tissue. In addition, we propose an efficient algorithm to guarantee resulting contours to be closed. The segmentation method based on dynamic programming was quantitatively compared with two other automated segmentation methods (region growing and the discrete contour model) on a dataset of 1210 masses. For each mass an overlap criterion was calculated to determine the similarity with manual segmentation. The mean overlap percentage for dynamic programming was 0.69, for the other two methods 0.60 and 0.59, respectively. The difference in overlap percentage was statistically significant. To study the influence of the segmentation method on the performance of a CAD system two additional experiments were carried out. The first experiment studied the detection performance of the CAD system for the different segmentation methods. Free-response receiver operating characteristics analysis showed that the detection performance was nearly identical for the three segmentation methods. In the second experiment the ability of the classifier to discriminate between malignant and benign lesions was studied. For region based evaluation the area Az under the receiver operating characteristics curve was 0.74 for dynamic programming, 0.72 for the discrete contour model, and 0.67 for region growing. The difference in Az values obtained by the dynamic programming method and region growing was statistically significant. The differences between other methods were not significant.

The combination design for open and endoscopic surgery using fluorescence molecular imaging technology

NASA Astrophysics Data System (ADS)

Mao, Yamin; Jiang, Shixin; Ye, Jinzuo; An, Yu; Yang, Xin; Chi, Chongwei; Tian, Jie

2015-03-01

For clinical surgery, it is still a challenge to objectively determine tumor margins during surgery. With the development of medical imaging technology, fluorescence molecular imaging (FMI) method can provide real-time intraoperative tumor margin information. Furthermore, surgical navigation system based on FMI technology plays an important role for the aid of surgeons' precise tumor margin decision. However, detection depth is the most limitation exists in the FMI technique and the method convenient for either macro superficial detection or micro deep tissue detection is needed. In this study, we combined advantages of both open surgery and endoscopic imaging systems with FMI technology. Indocyanine green (ICG) experiments were performed to confirm the feasibility of fluorescence detection in our system. Then, the ICG signal was photographed in the detection area with our system. When the system connected with endoscope lens, the minimum quantity of ICG detected by our system was 0.195 ug. For aspect of C mount lens, the sensitivity of ICG detection with our system was 0.195ug. Our experiments results proved that it was feasible to detect fluorescence images with this combination method. Our system shows great potential in the clinical applications of precise dissection of various tumors

Secure access control and large scale robust representation for online multimedia event detection.

PubMed

Liu, Changyu; Lu, Bin; Li, Huiling

2014-01-01

We developed an online multimedia event detection (MED) system. However, there are a secure access control issue and a large scale robust representation issue when we want to integrate traditional event detection algorithms into the online environment. For the first issue, we proposed a tree proxy-based and service-oriented access control (TPSAC) model based on the traditional role based access control model. Verification experiments were conducted on the CloudSim simulation platform, and the results showed that the TPSAC model is suitable for the access control of dynamic online environments. For the second issue, inspired by the object-bank scene descriptor, we proposed a 1000-object-bank (1000OBK) event descriptor. Feature vectors of the 1000OBK were extracted from response pyramids of 1000 generic object detectors which were trained on standard annotated image datasets, such as the ImageNet dataset. A spatial bag of words tiling approach was then adopted to encode these feature vectors for bridging the gap between the objects and events. Furthermore, we performed experiments in the context of event classification on the challenging TRECVID MED 2012 dataset, and the results showed that the robust 1000OBK event descriptor outperforms the state-of-the-art approaches.

Testing the TPF Interferometry Approach before Launch

NASA Technical Reports Server (NTRS)

Serabyn, Eugene; Mennesson, Bertrand

2006-01-01

One way to directly detect nearby extra-solar planets is via their thermal infrared emission, and with this goal in mind, both NASA and ESA are investigating cryogenic infrared interferometers. Common to both agencies' approaches to faint off-axis source detection near bright stars is the use of a rotating nulling interferometer, such as the Terrestrial Planet Finder interferometer (TPF-I), or Darwin. In this approach, the central star is nulled, while the emission from off-axis sources is transmitted and modulated by the rotation of the off-axis fringes. Because of the high contrasts involved, and the novelty of the measurement technique, it is essential to gain experience with this technique before launch. Here we describe a simple ground-based experiment that can test the essential aspects of the TPF signal measurement and image reconstruction approaches by generating a rotating interferometric baseline within the pupil of a large singleaperture telescope. This approach can mimic potential space-based interferometric configurations, and allow the extraction of signals from off-axis sources using the same algorithms proposed for the space-based missions. This approach should thus allow for testing of the applicability of proposed signal extraction algorithms for the detection of single and multiple near-neighbor companions...

Detection of Perlger-Huet anomaly based on augmented fast marching method and speeded up robust features.

PubMed

Sun, Minglei; Yang, Shaobao; Jiang, Jinling; Wang, Qiwei

2015-01-01

Pelger-Huet anomaly (PHA) and Pseudo Pelger-Huet anomaly (PPHA) are neutrophil with abnormal morphology. They have the bilobed or unilobed nucleus and excessive clumping chromatin. Currently, detection of this kind of cell mainly depends on the manual microscopic examination by a clinician, thus, the quality of detection is limited by the efficiency and a certain subjective consciousness of the clinician. In this paper, a detection method for PHA and PPHA is proposed based on karyomorphism and chromatin distribution features. Firstly, the skeleton of the nucleus is extracted using an augmented Fast Marching Method (AFMM) and width distribution is obtained through distance transform. Then, caryoplastin in the nucleus is extracted based on Speeded Up Robust Features (SURF) and a K-nearest-neighbor (KNN) classifier is constructed to analyze the features. Experiment shows that the sensitivity and specificity of this method achieved 87.5% and 83.33%, which means that the detection accuracy of PHA is acceptable. Meanwhile, the detection method should be helpful to the automatic morphological classification of blood cells.

Vision Sensor-Based Road Detection for Field Robot Navigation

PubMed Central

Lu, Keyu; Li, Jian; An, Xiangjing; He, Hangen

2015-01-01

Road detection is an essential component of field robot navigation systems. Vision sensors play an important role in road detection for their great potential in environmental perception. In this paper, we propose a hierarchical vision sensor-based method for robust road detection in challenging road scenes. More specifically, for a given road image captured by an on-board vision sensor, we introduce a multiple population genetic algorithm (MPGA)-based approach for efficient road vanishing point detection. Superpixel-level seeds are then selected in an unsupervised way using a clustering strategy. Then, according to the GrowCut framework, the seeds proliferate and iteratively try to occupy their neighbors. After convergence, the initial road segment is obtained. Finally, in order to achieve a globally-consistent road segment, the initial road segment is refined using the conditional random field (CRF) framework, which integrates high-level information into road detection. We perform several experiments to evaluate the common performance, scale sensitivity and noise sensitivity of the proposed method. The experimental results demonstrate that the proposed method exhibits high robustness compared to the state of the art. PMID:26610514

Interference and deception detection technology of satellite navigation based on deep learning

NASA Astrophysics Data System (ADS)

Chen, Weiyi; Deng, Pingke; Qu, Yi; Zhang, Xiaoguang; Li, Yaping

2017-10-01

Satellite navigation system plays an important role in people's daily life and war. The strategic position of satellite navigation system is prominent, so it is very important to ensure that the satellite navigation system is not disturbed or destroyed. It is a critical means to detect the jamming signal to avoid the accident in a navigation system. At present, the detection technology of jamming signal in satellite navigation system is not intelligent , mainly relying on artificial decision and experience. For this issue, the paper proposes a method based on deep learning to monitor the interference source in a satellite navigation. By training the interference signal data, and extracting the features of the interference signal, the detection sys tem model is constructed. The simulation results show that, the detection accuracy of our detection system can reach nearly 70%. The method in our paper provides a new idea for the research on intelligent detection of interference and deception signal in a satellite navigation system.

SAGE II V7

Atmospheric Science Data Center

2017-09-06

... The series of Stratospheric Aerosol and Gas Experiments (SAGE I, II, and III) are satellite-based solar occultation ... significantly more shortwave radiation than previously thought. Clouds in a Clear Sky Scientists have detected a nearly ...

An RFID-Based Smart Nest Box: An Experimental Study of Laying Performance and Behavior of Individual Hens

PubMed Central

Chen, Yu-Xian

2018-01-01

This study designed a radio-frequency identification (RFID)-based Internet of Things (IoT) platform to create the core of a smart nest box. At the sensing level, we have deployed RFID-based sensors and egg detection sensors. A low-frequency RFID reader is installed in the bottom of the nest box and a foot ring RFID tag is worn on the leg of individual hens. The RFID-based sensors detect when a hen enters or exits the nest box. The egg-detection sensors are implemented with a resistance strain gauge pressure sensor, which weights the egg in the egg-collection tube. Thus, the smart nest box makes it possible to analyze the laying performance and behavior of individual hens. An evaluative experiment was performed using an enriched cage, a smart nest box, web camera, and monitoring console. The hens were allowed 14 days to become accustomed to the experimental environment before monitoring began. The proposed IoT platform makes it possible to analyze the egg yield of individual hens in real time, thereby enabling the replacement of hens with egg yield below a pre-defined level in order to meet the overall target egg yield rate. The results of this experiment demonstrate the efficacy of the proposed RFID-based smart nest box in monitoring the egg yield and laying behavior of individual hens. PMID:29538334

An RFID-Based Smart Nest Box: An Experimental Study of Laying Performance and Behavior of Individual Hens.

PubMed

Chien, Ying-Ren; Chen, Yu-Xian

2018-03-14

This study designed a radio-frequency identification (RFID)-based Internet of Things (IoT) platform to create the core of a smart nest box. At the sensing level, we have deployed RFID-based sensors and egg detection sensors. A low-frequency RFID reader is installed in the bottom of the nest box and a foot ring RFID tag is worn on the leg of individual hens. The RFID-based sensors detect when a hen enters or exits the nest box. The egg-detection sensors are implemented with a resistance strain gauge pressure sensor, which weights the egg in the egg-collection tube. Thus, the smart nest box makes it possible to analyze the laying performance and behavior of individual hens. An evaluative experiment was performed using an enriched cage, a smart nest box, web camera, and monitoring console. The hens were allowed 14 days to become accustomed to the experimental environment before monitoring began. The proposed IoT platform makes it possible to analyze the egg yield of individual hens in real time, thereby enabling the replacement of hens with egg yield below a pre-defined level in order to meet the overall target egg yield rate. The results of this experiment demonstrate the efficacy of the proposed RFID-based smart nest box in monitoring the egg yield and laying behavior of individual hens.

Molecular Recognition: Detection of Colorless Compounds Based on Color Change

ERIC Educational Resources Information Center

Khalafi, Lida; Kashani, Samira; Karimi, Javad

2016-01-01

A laboratory experiment is described in which students measure the amount of cetirizine in allergy-treatment tablets based on molecular recognition. The basis of recognition is competition of cetirizine with phenolphthalein to form an inclusion complex with ß-cyclodextrin. Phenolphthalein is pinkish under basic condition, whereas it's complex form…

A new edge detection algorithm based on Canny idea

NASA Astrophysics Data System (ADS)

Feng, Yingke; Zhang, Jinmin; Wang, Siming

2017-10-01

The traditional Canny algorithm has poor self-adaptability threshold, and it is more sensitive to noise. In order to overcome these drawbacks, this paper proposed a new edge detection method based on Canny algorithm. Firstly, the media filtering and filtering based on the method of Euclidean distance are adopted to process it; secondly using the Frei-chen algorithm to calculate gradient amplitude; finally, using the Otsu algorithm to calculate partial gradient amplitude operation to get images of thresholds value, then find the average of all thresholds that had been calculated, half of the average is high threshold value, and the half of the high threshold value is low threshold value. Experiment results show that this new method can effectively suppress noise disturbance, keep the edge information, and also improve the edge detection accuracy.

Research on metallic material defect detection based on bionic sensing of human visual properties

NASA Astrophysics Data System (ADS)

Zhang, Pei Jiang; Cheng, Tao

2018-05-01

Due to the fact that human visual system can quickly lock the areas of interest in complex natural environment and focus on it, this paper proposes an eye-based visual attention mechanism by simulating human visual imaging features based on human visual attention mechanism Bionic Sensing Visual Inspection Model Method to Detect Defects of Metallic Materials in the Mechanical Field. First of all, according to the biologically visually significant low-level features, the mark of defect experience marking is used as the intermediate feature of simulated visual perception. Afterwards, SVM method was used to train the advanced features of visual defects of metal material. According to the weight of each party, the biometrics detection model of metal material defect, which simulates human visual characteristics, is obtained.

Identifying High-Risk Patients without Labeled Training Data: Anomaly Detection Methodologies to Predict Adverse Outcomes

PubMed Central

Syed, Zeeshan; Saeed, Mohammed; Rubinfeld, Ilan

2010-01-01

For many clinical conditions, only a small number of patients experience adverse outcomes. Developing risk stratification algorithms for these conditions typically requires collecting large volumes of data to capture enough positive and negative for training. This process is slow, expensive, and may not be appropriate for new phenomena. In this paper, we explore different anomaly detection approaches to identify high-risk patients as cases that lie in sparse regions of the feature space. We study three broad categories of anomaly detection methods: classification-based, nearest neighbor-based, and clustering-based techniques. When evaluated on data from the National Surgical Quality Improvement Program (NSQIP), these methods were able to successfully identify patients at an elevated risk of mortality and rare morbidities following inpatient surgical procedures. PMID:21347083

Automatic measurement and representation of prosodic features

NASA Astrophysics Data System (ADS)

Ying, Goangshiuan Shawn

Effective measurement and representation of prosodic features of the acoustic signal for use in automatic speech recognition and understanding systems is the goal of this work. Prosodic features-stress, duration, and intonation-are variations of the acoustic signal whose domains are beyond the boundaries of each individual phonetic segment. Listeners perceive prosodic features through a complex combination of acoustic correlates such as intensity, duration, and fundamental frequency (F0). We have developed new tools to measure F0 and intensity features. We apply a probabilistic global error correction routine to an Average Magnitude Difference Function (AMDF) pitch detector. A new short-term frequency-domain Teager energy algorithm is used to measure the energy of a speech signal. We have conducted a series of experiments performing lexical stress detection on words in continuous English speech from two speech corpora. We have experimented with two different approaches, a segment-based approach and a rhythm unit-based approach, in lexical stress detection. The first approach uses pattern recognition with energy- and duration-based measurements as features to build Bayesian classifiers to detect the stress level of a vowel segment. In the second approach we define rhythm unit and use only the F0-based measurement and a scoring system to determine the stressed segment in the rhythm unit. A duration-based segmentation routine was developed to break polysyllabic words into rhythm units. The long-term goal of this work is to develop a system that can effectively detect the stress pattern for each word in continuous speech utterances. Stress information will be integrated as a constraint for pruning the word hypotheses in a word recognition system based on hidden Markov models.

A Robust Method to Detect Zero Velocity for Improved 3D Personal Navigation Using Inertial Sensors

PubMed Central

Xu, Zhengyi; Wei, Jianming; Zhang, Bo; Yang, Weijun

2015-01-01

This paper proposes a robust zero velocity (ZV) detector algorithm to accurately calculate stationary periods in a gait cycle. The proposed algorithm adopts an effective gait cycle segmentation method and introduces a Bayesian network (BN) model based on the measurements of inertial sensors and kinesiology knowledge to infer the ZV period. During the detected ZV period, an Extended Kalman Filter (EKF) is used to estimate the error states and calibrate the position error. The experiments reveal that the removal rate of ZV false detections by the proposed method increases 80% compared with traditional method at high walking speed. Furthermore, based on the detected ZV, the Personal Inertial Navigation System (PINS) algorithm aided by EKF performs better, especially in the altitude aspect. PMID:25831086

Efficient airport detection using region-based fully convolutional neural networks

NASA Astrophysics Data System (ADS)

Xin, Peng; Xu, Yuelei; Zhang, Xulei; Ma, Shiping; Li, Shuai; Lv, Chao

2018-04-01

This paper presents a model for airport detection using region-based fully convolutional neural networks. To achieve fast detection with high accuracy, we shared the conv layers between the region proposal procedure and the airport detection procedure and used graphics processing units (GPUs) to speed up the training and testing time. For lack of labeled data, we transferred the convolutional layers of ZF net pretrained by ImageNet to initialize the shared convolutional layers, then we retrained the model using the alternating optimization training strategy. The proposed model has been tested on an airport dataset consisting of 600 images. Experiments show that the proposed method can distinguish airports in our dataset from similar background scenes almost real-time with high accuracy, which is much better than traditional methods.

Weak photoacoustic signal detection based on the differential duffing oscillator

NASA Astrophysics Data System (ADS)

Li, Chenjing; Xu, Xuemei; Ding, Yipeng; Yin, Linzi; Dou, Beibei

2018-04-01

In view of photoacoustic spectroscopy theory, the relationship between weak photoacoustic signal and gas concentration is described. The studies, on the principle of Duffing oscillator for identifying state transition as well as determining the threshold value, have proven the feasibility of applying the Duffing oscillator in weak signal detection. An improved differential Duffing oscillator is proposed to identify weak signals with any frequency and ameliorate the signal-to-noise ratio. The analytical methods and numerical experiments of the novel model are introduced in detail to confirm its superiority. Then the signal detection system of weak photoacoustic based on differential Duffing oscillator is constructed, it is the first time that the weak signal detection method with differential Duffing oscillator is applied triumphantly in photoacoustic spectroscopy gas monitoring technology.

A novel approach for pilot error detection using Dynamic Bayesian Networks.

PubMed

Saada, Mohamad; Meng, Qinggang; Huang, Tingwen

2014-06-01

In the last decade Dynamic Bayesian Networks (DBNs) have become one type of the most attractive probabilistic modelling framework extensions of Bayesian Networks (BNs) for working under uncertainties from a temporal perspective. Despite this popularity not many researchers have attempted to study the use of these networks in anomaly detection or the implications of data anomalies on the outcome of such models. An abnormal change in the modelled environment's data at a given time, will cause a trailing chain effect on data of all related environment variables in current and consecutive time slices. Albeit this effect fades with time, it still can have an ill effect on the outcome of such models. In this paper we propose an algorithm for pilot error detection, using DBNs as the modelling framework for learning and detecting anomalous data. We base our experiments on the actions of an aircraft pilot, and a flight simulator is created for running the experiments. The proposed anomaly detection algorithm has achieved good results in detecting pilot errors and effects on the whole system.

Preceding Vehicle Detection and Tracking Adaptive to Illumination Variation in Night Traffic Scenes Based on Relevance Analysis

PubMed Central

Guo, Junbin; Wang, Jianqiang; Guo, Xiaosong; Yu, Chuanqiang; Sun, Xiaoyan

2014-01-01

Preceding vehicle detection and tracking at nighttime are challenging problems due to the disturbance of other extraneous illuminant sources coexisting with the vehicle lights. To improve the detection accuracy and robustness of vehicle detection, a novel method for vehicle detection and tracking at nighttime is proposed in this paper. The characteristics of taillights in the gray level are applied to determine the lower boundary of the threshold for taillights segmentation, and the optimal threshold for taillight segmentation is calculated using the OTSU algorithm between the lower boundary and the highest grayscale of the region of interest. The candidate taillight pairs are extracted based on the similarity between left and right taillights, and the non-vehicle taillight pairs are removed based on the relevance analysis of vehicle location between frames. To reduce the false negative rate of vehicle detection, a vehicle tracking method based on taillights estimation is applied. The taillight spot candidate is sought in the region predicted by Kalman filtering, and the disturbed taillight is estimated based on the symmetry and location of the other taillight of the same vehicle. Vehicle tracking is completed after estimating its location according to the two taillight spots. The results of experiments on a vehicle platform indicate that the proposed method could detect vehicles quickly, correctly and robustly in the actual traffic environments with illumination variation. PMID:25195855

Preceding vehicle detection and tracking adaptive to illumination variation in night traffic scenes based on relevance analysis.

PubMed

Guo, Junbin; Wang, Jianqiang; Guo, Xiaosong; Yu, Chuanqiang; Sun, Xiaoyan

2014-08-19

Preceding vehicle detection and tracking at nighttime are challenging problems due to the disturbance of other extraneous illuminant sources coexisting with the vehicle lights. To improve the detection accuracy and robustness of vehicle detection, a novel method for vehicle detection and tracking at nighttime is proposed in this paper. The characteristics of taillights in the gray level are applied to determine the lower boundary of the threshold for taillights segmentation, and the optimal threshold for taillight segmentation is calculated using the OTSU algorithm between the lower boundary and the highest grayscale of the region of interest. The candidate taillight pairs are extracted based on the similarity between left and right taillights, and the non-vehicle taillight pairs are removed based on the relevance analysis of vehicle location between frames. To reduce the false negative rate of vehicle detection, a vehicle tracking method based on taillights estimation is applied. The taillight spot candidate is sought in the region predicted by Kalman filtering, and the disturbed taillight is estimated based on the symmetry and location of the other taillight of the same vehicle. Vehicle tracking is completed after estimating its location according to the two taillight spots. The results of experiments on a vehicle platform indicate that the proposed method could detect vehicles quickly, correctly and robustly in the actual traffic environments with illumination variation.

The difference of detecting water mist and smoke by electromagnetic wave in simulation experiments

NASA Astrophysics Data System (ADS)

Zhang, Jingdi; Cui, Bing; Xiao, Si

2015-10-01

Although mist is similar to smoke in morphology, their compositions are very different. Therefore there is a significant difference between mist and smoke when detected by electromagnetic wave. This paper puts forward a kind of feasible solution based on Ansoft HFSS software about how to determine the forest fire by distinguishing mist and smoke above the forest. The experiments simulate the difference between mist and smoke model when detected by electromagnetic wave in different wavelengths. We find the mist and smoke model cannot absorb or reflect electromagnetic wave efficiently in Megahertz band. While in Gigahertz band mist model began to absorb and reflect electromagnetic wave above 650 Gigahertz band, but no change in smoke model. And the biggest difference appears in Terahertz band.

The Quest for Organic Carbon on Mars

NASA Technical Reports Server (NTRS)

Eigenbrode, Jennifer

2011-01-01

We are entering an era of Mars exploration in which organic carbon detection, characterization, and structural identification will be key to addressing some of the outstanding science objectives of the Mars Exploration Program. Success of these missions will depend on technical, scientific, and strategic elements--all of which are strongly determined based on terrestrial experience and knowledge of organic matter formation, concentration, and preservation. Analog studies including Precambrian sediments, modern endolithic communities, and experiments help us fine-tune these approaches, but we also need to expect the unexpected. This presentation will provide perspective on the challenges of detecting organic carbon on Mars, how we may achieve such detections with the in situ instruments, such as the SAM (Science Analysis at Mars) instrument suite onboard Curiosity, the rover for the 2011 Mars Science Laboratory mission.

Detection of tunnel excavation using fiber optic reflectometry: experimental validation

NASA Astrophysics Data System (ADS)

Linker, Raphael; Klar, Assaf

2013-06-01

Cross-border smuggling tunnels enable unmonitored movement of people and goods, and pose a severe threat to homeland security. In recent years, we have been working on the development of a system based on fiber- optic Brillouin time domain reflectometry (BOTDR) for detecting tunnel excavation. In two previous SPIE publications we have reported the initial development of the system as well as its validation using small-scale experiments. This paper reports, for the first time, results of full-scale experiments and discusses the system performance. The results confirm that distributed measurement of strain profiles in fiber cables buried at shallow depth enable detection of tunnel excavation, and by proper data processing, these measurements enable precise localization of the tunnel, as well as reasonable estimation of its depth.

Learning-dependent plasticity with and without training in the human brain.

PubMed

Zhang, Jiaxiang; Kourtzi, Zoe

2010-07-27

Long-term experience through development and evolution and shorter-term training in adulthood have both been suggested to contribute to the optimization of visual functions that mediate our ability to interpret complex scenes. However, the brain plasticity mechanisms that mediate the detection of objects in cluttered scenes remain largely unknown. Here, we combine behavioral and functional MRI (fMRI) measurements to investigate the human-brain mechanisms that mediate our ability to learn statistical regularities and detect targets in clutter. We show two different routes to visual learning in clutter with discrete brain plasticity signatures. Specifically, opportunistic learning of regularities typical in natural contours (i.e., collinearity) can occur simply through frequent exposure, generalize across untrained stimulus features, and shape processing in occipitotemporal regions implicated in the representation of global forms. In contrast, learning to integrate discontinuities (i.e., elements orthogonal to contour paths) requires task-specific training (bootstrap-based learning), is stimulus-dependent, and enhances processing in intraparietal regions implicated in attention-gated learning. We propose that long-term experience with statistical regularities may facilitate opportunistic learning of collinear contours, whereas learning to integrate discontinuities entails bootstrap-based training for the detection of contours in clutter. These findings provide insights in understanding how long-term experience and short-term training interact to shape the optimization of visual recognition processes.

Surface plasmon resonance label-free monitoring of antibody antigen interactions in real time

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

Kausaite, A.; van Dijk, M.; Castrop, J.

2007-01-01

Detection of biologically active compounds is one of the most important topics in molecular biology and biochemistry. One of the most promising detection methods is based on the application of surface plasmon resonance for label-free detection of biologically active compounds. This method allows one to monitor binding events in real time without labeling. The system can therefore be used to determine both affinity and rate constants for interactions between various types of molecules. Here, we describe the application of a surface plasmon resonance biosensor for label-free investigation of the interaction between an immobilized antigen bovine serum albumin (BSA) and antibodymore » rabbit anti-cow albumin IgG1 (anti-BSA). The formation of a self-assembled monolayer (SAM) over a gold surface is introduced into this laboratory training protocol as an effective immobilization method, which is very promising in biosensing systems based on detection of affinity interactions. In the next step, covalent attachment via artificially formed amide bonds is applied for the immobilization of proteins on the formed SAM surface. These experiments provide suitable experience for postgraduate students to help them understand immobilization of biologically active materials via SAMs, fundamentals of surface plasmon resonance biosensor applications, and determination of non-covalent biomolecular interactions. The experiment is designed for master and/or Ph.D. students. In some particular cases, this protocol might be adoptable for bachelor students that already have completed an extended biochemistry program that included a background in immunology.« less

Numerical study on the sequential Bayesian approach for radioactive materials detection

NASA Astrophysics Data System (ADS)

Qingpei, Xiang; Dongfeng, Tian; Jianyu, Zhu; Fanhua, Hao; Ge, Ding; Jun, Zeng

2013-01-01

A new detection method, based on the sequential Bayesian approach proposed by Candy et al., offers new horizons for the research of radioactive detection. Compared with the commonly adopted detection methods incorporated with statistical theory, the sequential Bayesian approach offers the advantages of shorter verification time during the analysis of spectra that contain low total counts, especially in complex radionuclide components. In this paper, a simulation experiment platform implanted with the methodology of sequential Bayesian approach was developed. Events sequences of γ-rays associating with the true parameters of a LaBr3(Ce) detector were obtained based on an events sequence generator using Monte Carlo sampling theory to study the performance of the sequential Bayesian approach. The numerical experimental results are in accordance with those of Candy. Moreover, the relationship between the detection model and the event generator, respectively represented by the expected detection rate (Am) and the tested detection rate (Gm) parameters, is investigated. To achieve an optimal performance for this processor, the interval of the tested detection rate as a function of the expected detection rate is also presented.

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.

Measuring the Velocity of Cosmic Photons

NASA Astrophysics Data System (ADS)

Vazquez, Gerardo Arturo

2018-01-01

The position of the JWST in space—close to the L2 point at a distance of 1.5 million kilometers from Earth—allows us a unique chance to measure the speed of cosmic photons through a double detection in two different telescopes. The speed of cosmic photons has been considered constant as a matter of principle, but in the same way, the energy lost by these photons could have a contribution due to a different nature such as dark matter. In this work, an experiment to measure the speed of photons is proposed based on the detection on two different telescopes located at a considerable distance. Some of the most important results of this experiment could be variations of the speed of light as it passes through dark matter and, as a consequence, the ability to map dark matter in the universe. Although JWST is not in the direction to measure the difference in time of 5 seconds, the fact that it can move up to a 50 arc degree angle will allow us to measure a difference in detection between 3 to 4.5 seconds. The observations needed to do this experiment should come from the detection of gamma ray bursts and then, the simultaneous detection by the sudden pointing of JWST plus a secondary telescope—on ground or in space—to catch the afterglow of the GRB in longer wavelengths. The new technology in telescopes will allow us to catch a difference in magnitude between both telescopes or even to measure single photon detection in time in order to accomplish the purpose of the experiment.

SAGE II V6.20

Atmospheric Science Data Center

2017-09-06

... The series of Stratospheric Aerosol and Gas Experiments (SAGE I, II, and III) are satellite-based solar occultation ... significantly more shortwave radiation than previously thought. Clouds in a Clear Sky Scientists have detected a nearly ...

Study on Elastic Helical TDR Sensing Cable for Distributed Deformation Detection

PubMed Central

Tong, Renyuan; Li, Ming; Li, Qing

2012-01-01

In order to detect distributed ground surface deformation, an elastic helical structure Time Domain Reflectometry (TDR) sensing cable is shown in this paper. This special sensing cable consists of three parts: a silicone rubber rope in the center; a couple of parallel wires coiling around the rope; a silicone rubber pipe covering the sensing cable. By analyzing the relationship between the impedance and the structure of the sensing cable, the impedance model shows that the sensing cable impedance will increase when the cable is stretched. This specific characteristic is verified in the cable stretching experiment which is the base of TDR sensing technology. The TDR experiment shows that a positive reflected signal is created at the stretching deformation point on the sensing cable. The results show that the deformation section length and the stretching elongation will both affect the amplitude of the reflected signal. Finally, the deformation locating experiments show that the sensing cable can accurately detect the deformation point position on the sensing cable. PMID:23012560

THz QCL-Based Cryogen-Free Spectrometer for in Situ Trace Gas Sensing

PubMed Central

Consolino, Luigi; Bartalini, Saverio; Beere, Harvey E.; Ritchie, David A.; Vitiello, Miriam Serena; De Natale, Paolo

2013-01-01

We report on a set of high-sensitivity terahertz spectroscopy experiments making use of QCLs to detect rotational molecular transitions in the far-infrared. We demonstrate that using a compact and transportable cryogen-free setup, based on a quantum cascade laser in a closed-cycle Stirling cryostat, and pyroelectric detectors, a considerable improvement in sensitivity can be obtained by implementing a wavelength modulation spectroscopy technique. Indeed, we show that the sensitivity of methanol vapour detection can be improved by a factor ≈ 4 with respect to standard direct absorption approaches, offering perspectives for high sensitivity detection of a number of chemical compounds across the far-infrared spectral range. PMID:23478601

THz QCL-based cryogen-free spectrometer for in situ trace gas sensing.

PubMed

Consolino, Luigi; Bartalini, Saverio; Beere, Harvey E; Ritchie, David A; Vitiello, Miriam Serena; De Natale, Paolo

2013-03-11

We report on a set of high-sensitivity terahertz spectroscopy experiments making use of QCLs to detect rotational molecular transitions in the far-infrared. We demonstrate that using a compact and transportable cryogen-free setup, based on a quantum cascade laser in a closed-cycle Stirling cryostat, and pyroelectric detectors, a considerable improvement in sensitivity can be obtained by implementing a wavelength modulation spectroscopy technique. Indeed, we show that the sensitivity of methanol vapour detection can be improved by a factor ≈ 4 with respect to standard direct absorption approaches, offering perspectives for high sensitivity detection of a number of chemical compounds across the far-infrared spectral range.

Using Landsat digital data to detect moisture stress in corn-soybean growing regions

NASA Technical Reports Server (NTRS)

Thompson, D. R.; Wehmanen, O. A.

1980-01-01

As a part of a follow-on study to the moisture stress detection effort conducted in the Large Area Crop Inventory Experiment (LACIE), a technique utilizing transformed Landsat digital data was evaluated for detecting moisture stress in humid growing regions using sample segments from Iowa, Illinois, and Indiana. At known growth stages of corn and soybeans, segments were classified as undergoing moisture stress or not undergoing stress. The remote-sensing-based information was compared to a weekly ground-based index (Crop Moisture Index). This comparison demonstrated that the remote sensing technique could be used to monitor the growing conditions within a region where corn and soybeans are the major crop.

An Improved Vision-based Algorithm for Unmanned Aerial Vehicles Autonomous Landing

NASA Astrophysics Data System (ADS)

Zhao, Yunji; Pei, Hailong

In vision-based autonomous landing system of UAV, the efficiency of target detecting and tracking will directly affect the control system. The improved algorithm of SURF(Speed Up Robust Features) will resolve the problem which is the inefficiency of the SURF algorithm in the autonomous landing system. The improved algorithm is composed of three steps: first, detect the region of the target using the Camshift; second, detect the feature points in the region of the above acquired using the SURF algorithm; third, do the matching between the template target and the region of target in frame. The results of experiment and theoretical analysis testify the efficiency of the algorithm.

Remote laser spectroscopy of oil and gas deposits

NASA Astrophysics Data System (ADS)

Zhevlakov, A. P.; Bespalov, V. G.; Elizarov, V. V.; Grishkanich, A. S.; Kascheev, S. V.; Makarov, E. A.; Bogoslovsky, S. A.; Il'inskiy, A. A.

2014-06-01

We developed a Raman lidar with ultraspectral resolution for automatic airborne monitoring of pipeline leaks and for oil and gas exploration. Test flights indicate that a sensitivity of 6 ppm for methane and 2 ppm for hydrogen sulfide has been reached for leakage detection. The lidar is based on the CARS method with a Ti:Sapphire pump laser and a frequencydoubled YLF:Nd probe beam whose frequency is displaced by a BBO crystal. In ground-based experiments, a detection level of 3 to 10 molecules has been reached.

Person detection, tracking and following using stereo camera

NASA Astrophysics Data System (ADS)

Wang, Xiaofeng; Zhang, Lilian; Wang, Duo; Hu, Xiaoping

2018-04-01

Person detection, tracking and following is a key enabling technology for mobile robots in many human-robot interaction applications. In this article, we present a system which is composed of visual human detection, video tracking and following. The detection is based on YOLO(You only look once), which applies a single convolution neural network(CNN) to the full image, thus can predict bounding boxes and class probabilities directly in one evaluation. Then the bounding box provides initial person position in image to initialize and train the KCF(Kernelized Correlation Filter), which is a video tracker based on discriminative classifier. At last, by using a stereo 3D sparse reconstruction algorithm, not only the position of the person in the scene is determined, but also it can elegantly solve the problem of scale ambiguity in the video tracker. Extensive experiments are conducted to demonstrate the effectiveness and robustness of our human detection and tracking system.

Ultrasound image edge detection based on a novel multiplicative gradient and Canny operator.

PubMed

Zheng, Yinfei; Zhou, Yali; Zhou, Hao; Gong, Xiaohong

2015-07-01

To achieve the fast and accurate segmentation of ultrasound image, a novel edge detection method for speckle noised ultrasound images was proposed, which was based on the traditional Canny and a novel multiplicative gradient operator. The proposed technique combines a new multiplicative gradient operator of non-Newtonian type with the traditional Canny operator to generate the initial edge map, which is subsequently optimized by the following edge tracing step. To verify the proposed method, we compared it with several other edge detection methods that had good robustness to noise, with experiments on the simulated and in vivo medical ultrasound image. Experimental results showed that the proposed algorithm has higher speed for real-time processing, and the edge detection accuracy could be 75% or more. Thus, the proposed method is very suitable for fast and accurate edge detection of medical ultrasound images. © The Author(s) 2014.

Dual Low-Rank Pursuit: Learning Salient Features for Saliency Detection.

PubMed

Lang, Congyan; Feng, Jiashi; Feng, Songhe; Wang, Jingdong; Yan, Shuicheng

2016-06-01

Saliency detection is an important procedure for machines to understand visual world as humans do. In this paper, we consider a specific saliency detection problem of predicting human eye fixations when they freely view natural images, and propose a novel dual low-rank pursuit (DLRP) method. DLRP learns saliency-aware feature transformations by utilizing available supervision information and constructs discriminative bases for effectively detecting human fixation points under the popular low-rank and sparsity-pursuit framework. Benefiting from the embedded high-level information in the supervised learning process, DLRP is able to predict fixations accurately without performing the expensive object segmentation as in the previous works. Comprehensive experiments clearly show the superiority of the proposed DLRP method over the established state-of-the-art methods. We also empirically demonstrate that DLRP provides stronger generalization performance across different data sets and inherits the advantages of both the bottom-up- and top-down-based saliency detection methods.

Sound synthesis and evaluation of interactive footsteps and environmental sounds rendering for virtual reality applications.

PubMed

Nordahl, Rolf; Turchet, Luca; Serafin, Stefania

2011-09-01

We propose a system that affords real-time sound synthesis of footsteps on different materials. The system is based on microphones, which detect real footstep sounds from subjects, from which the ground reaction force (GRF) is estimated. Such GRF is used to control a sound synthesis engine based on physical models. Two experiments were conducted. In the first experiment, the ability of subjects to recognize the surface they were exposed to was assessed. In the second experiment, the sound synthesis engine was enhanced with environmental sounds. Results show that, in some conditions, adding a soundscape significantly improves the recognition of the simulated environment.

Significance of parametric spectral ratio methods in detection and recognition of whispered speech

NASA Astrophysics Data System (ADS)

Mathur, Arpit; Reddy, Shankar M.; Hegde, Rajesh M.

2012-12-01

In this article the significance of a new parametric spectral ratio method that can be used to detect whispered speech segments within normally phonated speech is described. Adaptation methods based on the maximum likelihood linear regression (MLLR) are then used to realize a mismatched train-test style speech recognition system. This proposed parametric spectral ratio method computes a ratio spectrum of the linear prediction (LP) and the minimum variance distortion-less response (MVDR) methods. The smoothed ratio spectrum is then used to detect whispered segments of speech within neutral speech segments effectively. The proposed LP-MVDR ratio method exhibits robustness at different SNRs as indicated by the whisper diarization experiments conducted on the CHAINS and the cell phone whispered speech corpus. The proposed method also performs reasonably better than the conventional methods for whisper detection. In order to integrate the proposed whisper detection method into a conventional speech recognition engine with minimal changes, adaptation methods based on the MLLR are used herein. The hidden Markov models corresponding to neutral mode speech are adapted to the whispered mode speech data in the whispered regions as detected by the proposed ratio method. The performance of this method is first evaluated on whispered speech data from the CHAINS corpus. The second set of experiments are conducted on the cell phone corpus of whispered speech. This corpus is collected using a set up that is used commercially for handling public transactions. The proposed whisper speech recognition system exhibits reasonably better performance when compared to several conventional methods. The results shown indicate the possibility of a whispered speech recognition system for cell phone based transactions.

Computational and human observer image quality evaluation of low dose, knowledge-based CT iterative reconstruction

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

Eck, Brendan L.; Fahmi, Rachid; Miao, Jun

2015-10-15

Purpose: Aims in this study are to (1) develop a computational model observer which reliably tracks the detectability of human observers in low dose computed tomography (CT) images reconstructed with knowledge-based iterative reconstruction (IMR™, Philips Healthcare) and filtered back projection (FBP) across a range of independent variables, (2) use the model to evaluate detectability trends across reconstructions and make predictions of human observer detectability, and (3) perform human observer studies based on model predictions to demonstrate applications of the model in CT imaging. Methods: Detectability (d′) was evaluated in phantom studies across a range of conditions. Images were generated usingmore » a numerical CT simulator. Trained observers performed 4-alternative forced choice (4-AFC) experiments across dose (1.3, 2.7, 4.0 mGy), pin size (4, 6, 8 mm), contrast (0.3%, 0.5%, 1.0%), and reconstruction (FBP, IMR), at fixed display window. A five-channel Laguerre–Gauss channelized Hotelling observer (CHO) was developed with internal noise added to the decision variable and/or to channel outputs, creating six different internal noise models. Semianalytic internal noise computation was tested against Monte Carlo and used to accelerate internal noise parameter optimization. Model parameters were estimated from all experiments at once using maximum likelihood on the probability correct, P{sub C}. Akaike information criterion (AIC) was used to compare models of different orders. The best model was selected according to AIC and used to predict detectability in blended FBP-IMR images, analyze trends in IMR detectability improvements, and predict dose savings with IMR. Predicted dose savings were compared against 4-AFC study results using physical CT phantom images. Results: Detection in IMR was greater than FBP in all tested conditions. The CHO with internal noise proportional to channel output standard deviations, Model-k4, showed the best trade-off between fit and model complexity according to AIC{sub c}. With parameters fixed, the model reasonably predicted detectability of human observers in blended FBP-IMR images. Semianalytic internal noise computation gave results equivalent to Monte Carlo, greatly speeding parameter estimation. Using Model-k4, the authors found an average detectability improvement of 2.7 ± 0.4 times that of FBP. IMR showed greater improvements in detectability with larger signals and relatively consistent improvements across signal contrast and x-ray dose. In the phantom tested, Model-k4 predicted an 82% dose reduction compared to FBP, verified with physical CT scans at 80% reduced dose. Conclusions: IMR improves detectability over FBP and may enable significant dose reductions. A channelized Hotelling observer with internal noise proportional to channel output standard deviation agreed well with human observers across a wide range of variables, even across reconstructions with drastically different image characteristics. Utility of the model observer was demonstrated by predicting the effect of image processing (blending), analyzing detectability improvements with IMR across dose, size, and contrast, and in guiding real CT scan dose reduction experiments. Such a model observer can be applied in optimizing parameters in advanced iterative reconstruction algorithms as well as guiding dose reduction protocols in physical CT experiments.« less

Auditory sensitivity of seals and sea lions in complex listening scenarios.

PubMed

Cunningham, Kane A; Southall, Brandon L; Reichmuth, Colleen

2014-12-01

Standard audiometric data, such as audiograms and critical ratios, are often used to inform marine mammal noise-exposure criteria. However, these measurements are obtained using simple, artificial stimuli-i.e., pure tones and flat-spectrum noise-while natural sounds typically have more complex structure. In this study, detection thresholds for complex signals were measured in (I) quiet and (II) masked conditions for one California sea lion (Zalophus californianus) and one harbor seal (Phoca vitulina). In Experiment I, detection thresholds in quiet conditions were obtained for complex signals designed to isolate three common features of natural sounds: Frequency modulation, amplitude modulation, and harmonic structure. In Experiment II, detection thresholds were obtained for the same complex signals embedded in two types of masking noise: Synthetic flat-spectrum noise and recorded shipping noise. To evaluate how accurately standard hearing data predict detection of complex sounds, the results of Experiments I and II were compared to predictions based on subject audiograms and critical ratios combined with a basic hearing model. Both subjects exhibited greater-than-predicted sensitivity to harmonic signals in quiet and masked conditions, as well as to frequency-modulated signals in masked conditions. These differences indicate that the complex features of naturally occurring sounds enhance detectability relative to simple stimuli.

A portable fluorescence detector for fast ultra trace detection of explosive vapors

NASA Astrophysics Data System (ADS)

Xin, Yunhong; He, Gang; Wang, Qi; Fang, Yu

2011-10-01

This paper developed a portable detector based on a specific material-based fluorescent sensing film for an ultra trace detection of explosives, such as 2,4,6-trinitrotoluene (TNT) or its derivate 2,4-dinitrotoluene (DNT), in ambient air or on objects tainted by explosives. The fluorescent sensing films are based on single-layer chemistry and the signal amplification effect of conjugated polymers, which exhibited higher sensitivity and shorter response time to TNT or DNT at their vapor pressures. Due to application of the light emitting diode and the solid state photomultiplier and the cross-correlation-based circuit design technology, the device has the advantages of low-power, low-cost, small size, and an improved signal to noise ratio. The results of the experiments showed that the detector can real-time detect and identify of explosive vapors at extremely low levels; it is suitable for the identification of suspect luggage, forensic analyses, or battlefields clearing.

Crack image segmentation based on improved DBC method

NASA Astrophysics Data System (ADS)

Cao, Ting; Yang, Nan; Wang, Fengping; Gao, Ting; Wang, Weixing

2017-11-01

With the development of computer vision technology, crack detection based on digital image segmentation method arouses global attentions among researchers and transportation ministries. Since the crack always exhibits the random shape and complex texture, it is still a challenge to accomplish reliable crack detection results. Therefore, a novel crack image segmentation method based on fractal DBC (differential box counting) is introduced in this paper. The proposed method can estimate every pixel fractal feature based on neighborhood information which can consider the contribution from all possible direction in the related block. The block moves just one pixel every time so that it could cover all the pixels in the crack image. Unlike the classic DBC method which only describes fractal feature for the related region, this novel method can effectively achieve crack image segmentation according to the fractal feature of every pixel. The experiment proves the proposed method can achieve satisfactory results in crack detection.

A portable fluorescence detector for fast ultra trace detection of explosive vapors.

PubMed

Xin, Yunhong; He, Gang; Wang, Qi; Fang, Yu

2011-10-01

This paper developed a portable detector based on a specific material-based fluorescent sensing film for an ultra trace detection of explosives, such as 2,4,6-trinitrotoluene (TNT) or its derivate 2,4-dinitrotoluene (DNT), in ambient air or on objects tainted by explosives. The fluorescent sensing films are based on single-layer chemistry and the signal amplification effect of conjugated polymers, which exhibited higher sensitivity and shorter response time to TNT or DNT at their vapor pressures. Due to application of the light emitting diode and the solid state photomultiplier and the cross-correlation-based circuit design technology, the device has the advantages of low-power, low-cost, small size, and an improved signal to noise ratio. The results of the experiments showed that the detector can real-time detect and identify of explosive vapors at extremely low levels; it is suitable for the identification of suspect luggage, forensic analyses, or battlefields clearing.

A method to detect layover and shadow based on distributed spaceborne single-baseline InSAR

NASA Astrophysics Data System (ADS)

Yun, Ren; Huanxin, Zou; Shilin, Zhou; Hao, Sun; Kefeng, Ji

2014-03-01

Layover and Shadow are inevitable phenomenena in InSAR, which seriously destroy the continuity of interferometric phase images and present difficulties in the follow-up phase unwrapping. Thus, it's significant to detect layover and shadow. This paper presents an approach to detect layover and shadow using the auto-correlation matrix and amplitude of the two images. The method can make full use of the spatial information of neighboring pixels and effectively detect layover and shadow regions in the case of low registration accuracy. Experiment result on the simulated data verifies effectiveness of the algorithm.

Three-dimensional nitrogen-doped graphene as an ultrasensitive electrochemical sensor for the detection of dopamine

NASA Astrophysics Data System (ADS)

Feng, Xiaomiao; Zhang, Yu; Zhou, Jinhua; Li, Yi; Chen, Shufen; Zhang, Lei; Ma, Yanwen; Wang, Lianhui; Yan, Xiaohong

2015-01-01

Three-dimensional nitrogen-doped graphene (3D N-doped graphene) was prepared through chemical vapor deposition (CVD) by using porous nickel foam as a substrate. As a model, a dopamine biosensor was constructed based on the 3D N-doped graphene porous foam. Electrochemical experiments exhibited that this biosensor had a remarkable detection ability with a wide linear detection range from 3 × 10-6 M to 1 × 10-4 M and a low detection limit of 1 nM. Moreover, the fabricated biosensor also showed an excellent anti-interference ability, reproducibility, and stability.

Three-dimensional nitrogen-doped graphene as an ultrasensitive electrochemical sensor for the detection of dopamine.

PubMed

Feng, Xiaomiao; Zhang, Yu; Zhou, Jinhua; Li, Yi; Chen, Shufen; Zhang, Lei; Ma, Yanwen; Wang, Lianhui; Yan, Xiaohong

2015-02-14

Three-dimensional nitrogen-doped graphene (3D N-doped graphene) was prepared through chemical vapor deposition (CVD) by using porous nickel foam as a substrate. As a model, a dopamine biosensor was constructed based on the 3D N-doped graphene porous foam. Electrochemical experiments exhibited that this biosensor had a remarkable detection ability with a wide linear detection range from 3 × 10(-6) M to 1 × 10(-4) M and a low detection limit of 1 nM. Moreover, the fabricated biosensor also showed an excellent anti-interference ability, reproducibility, and stability.

[Design and experiment of micro biochemical detector based on micro spectrometer].

PubMed

Yu, Qing-hua; Wen, Zhi-yu; Chen, Gang; Dai, Wei-wei; Liu, Nian-ci; Wu, Xin

2012-03-01

According to the requirements of rapid detection of important life parameters for the sick and wounded, a new micro bio-chemical detection configuration was proposed utilizing continuous spectroscopy analysis, which was founded on MOEMS and embedded technology. The configuration was developed as so much research work was carried out on the detecting objects and methods. Important parameters such as stray light, absorbance linearity, absorbance ratability, stability and temperature accuracy of the instrument were tested, which are all in good agreement with the design requirements. Clinic tests show that it can detect multiple life parameters quickly (Na+, GLU, Hb eg.).

The polarised internal target for the PAX experiment

NASA Astrophysics Data System (ADS)

Ciullo, G.; Barion, L.; Barschel, C.; Grigoriev, K.; Lenisa, P.; Nass, A.; Sarkadi, J.; Statera, M.; Steffens, E.; Tagliente, G.

2011-05-01

The PAX (Polarized Antiproton eXperiment) collaboration aims to polarise antiproton beams stored in ring by means of spin-filtering. The experimental setup is based on a polarised internal gas target, surrounded by a detection system for the measurement of spin observables. In this report, we present results from the commission of the PAX target (atomic beam source, openable cell, and polarimeter).

The Benefit of Surface Uniformity for Encoding Boundary Features in Visual Working Memory

ERIC Educational Resources Information Center

Kim, Sung-Ho; Kim, Jung-Oh

2011-01-01

Using a change detection paradigm, the present study examined an object-based encoding benefit in visual working memory (VWM) for two boundary features (two orientations in Experiments 1-2 and two shapes in Experiments 3-4) assigned to a single object. Participants remembered more boundary features when they were conjoined into a single object of…

Investigating strength and frequency effects in recognition memory using type-2 signal detection theory.

PubMed

Higham, Philip A; Perfect, Timothy J; Bruno, Davide

2009-01-01

Criterion- versus distribution-shift accounts of frequency and strength effects in recognition memory were investigated with Type-2 signal detection receiver operating characteristic (ROC) analysis, which provides a measure of metacognitive monitoring. Experiment 1 demonstrated a frequency-based mirror effect, with a higher hit rate and lower false alarm rate, for low frequency words compared with high frequency words. In Experiment 2, the authors manipulated item strength with repetition, which showed an increased hit rate but no effect on the false alarm rate. Whereas Type-1 indices were ambiguous as to whether these effects were based on a criterion- or distribution-shift model, the two models predict opposite effects on Type-2 distractor monitoring under some assumptions. Hence, Type-2 ROC analysis discriminated between potential models of recognition that could not be discriminated using Type-1 indices alone. In Experiment 3, the authors manipulated Type-1 response bias by varying the number of old versus new response categories to confirm the assumptions made in Experiments 1 and 2. The authors conclude that Type-2 analyses are a useful tool for investigating recognition memory when used in conjunction with more traditional Type-1 analyses.

Adaptive Non-Interventional Heuristics for Covariation Detection in Causal Induction: Model Comparison and Rational Analysis

ERIC Educational Resources Information Center

Hattori, Masasi; Oaksford, Mike

2007-01-01

In this article, 41 models of covariation detection from 2 x 2 contingency tables were evaluated against past data in the literature and against data from new experiments. A new model was also included based on a limiting case of the normative phi-coefficient under an extreme rarity assumption, which has been shown to be an important factor in…

NHPP-Based Software Reliability Models Using Equilibrium Distribution

NASA Astrophysics Data System (ADS)

Xiao, Xiao; Okamura, Hiroyuki; Dohi, Tadashi

Non-homogeneous Poisson processes (NHPPs) have gained much popularity in actual software testing phases to estimate the software reliability, the number of remaining faults in software and the software release timing. In this paper, we propose a new modeling approach for the NHPP-based software reliability models (SRMs) to describe the stochastic behavior of software fault-detection processes. The fundamental idea is to apply the equilibrium distribution to the fault-detection time distribution in NHPP-based modeling. We also develop efficient parameter estimation procedures for the proposed NHPP-based SRMs. Through numerical experiments, it can be concluded that the proposed NHPP-based SRMs outperform the existing ones in many data sets from the perspective of goodness-of-fit and prediction performance.

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.

[Detection of oil spills on water by differential polarization FTIR spectrometry].

PubMed

Yuan, Yue-ming; Xiong, Wei; Fang, Yong-hua; Lan, Tian-ge; Li, Da-cheng

2010-08-01

Detection of oil spills on water, by traditional thermal remote sensing, is based on the radiance contrast between the large area of clean water and the polluted area of water. And the categories of oil spills can not be identified by analysing the thermal infrared image. In order to find out the extent of pollution and identify the oil contaminants, an approach to the passive detection of oil spills on water by differential polarization FTIR spectrometry is proposed. This approach can detect the contaminants by obtaining and analysing the subtracted spectrum of horizontal and vertical polarization intensity spectrum. In the present article, the radiance model of differential polarization FTIR spectrometry is analysed, and an experiment about detection of No. O diesel and SF96 film on water by this method is presented. The results of this experiment indicate that this method can detect the oil contaminants on water without radiance contrast with clean water, and it also can identify oil spills by analysing the spectral characteristic of differential polarization FTIR spectrum. So it well makes up for the shortage of traditional thermal remote sensing on detecting oil spills on water.

Novel Hierarchical Fall Detection Algorithm Using a Multiphase Fall Model.

PubMed

Hsieh, Chia-Yeh; Liu, Kai-Chun; Huang, Chih-Ning; Chu, Woei-Chyn; Chan, Chia-Tai

2017-02-08

Falls are the primary cause of accidents for the elderly in the living environment. Reducing hazards in the living environment and performing exercises for training balance and muscles are the common strategies for fall prevention. However, falls cannot be avoided completely; fall detection provides an alarm that can decrease injuries or death caused by the lack of rescue. The automatic fall detection system has opportunities to provide real-time emergency alarms for improving the safety and quality of home healthcare services. Two common technical challenges are also tackled in order to provide a reliable fall detection algorithm, including variability and ambiguity. We propose a novel hierarchical fall detection algorithm involving threshold-based and knowledge-based approaches to detect a fall event. The threshold-based approach efficiently supports the detection and identification of fall events from continuous sensor data. A multiphase fall model is utilized, including free fall, impact, and rest phases for the knowledge-based approach, which identifies fall events and has the potential to deal with the aforementioned technical challenges of a fall detection system. Seven kinds of falls and seven types of daily activities arranged in an experiment are used to explore the performance of the proposed fall detection algorithm. The overall performances of the sensitivity, specificity, precision, and accuracy using a knowledge-based algorithm are 99.79%, 98.74%, 99.05% and 99.33%, respectively. The results show that the proposed novel hierarchical fall detection algorithm can cope with the variability and ambiguity of the technical challenges and fulfill the reliability, adaptability, and flexibility requirements of an automatic fall detection system with respect to the individual differences.

Novel Hierarchical Fall Detection Algorithm Using a Multiphase Fall Model

PubMed Central

Hsieh, Chia-Yeh; Liu, Kai-Chun; Huang, Chih-Ning; Chu, Woei-Chyn; Chan, Chia-Tai

2017-01-01

Falls are the primary cause of accidents for the elderly in the living environment. Reducing hazards in the living environment and performing exercises for training balance and muscles are the common strategies for fall prevention. However, falls cannot be avoided completely; fall detection provides an alarm that can decrease injuries or death caused by the lack of rescue. The automatic fall detection system has opportunities to provide real-time emergency alarms for improving the safety and quality of home healthcare services. Two common technical challenges are also tackled in order to provide a reliable fall detection algorithm, including variability and ambiguity. We propose a novel hierarchical fall detection algorithm involving threshold-based and knowledge-based approaches to detect a fall event. The threshold-based approach efficiently supports the detection and identification of fall events from continuous sensor data. A multiphase fall model is utilized, including free fall, impact, and rest phases for the knowledge-based approach, which identifies fall events and has the potential to deal with the aforementioned technical challenges of a fall detection system. Seven kinds of falls and seven types of daily activities arranged in an experiment are used to explore the performance of the proposed fall detection algorithm. The overall performances of the sensitivity, specificity, precision, and accuracy using a knowledge-based algorithm are 99.79%, 98.74%, 99.05% and 99.33%, respectively. The results show that the proposed novel hierarchical fall detection algorithm can cope with the variability and ambiguity of the technical challenges and fulfill the reliability, adaptability, and flexibility requirements of an automatic fall detection system with respect to the individual differences. PMID:28208694

Ultramicroelectrode Sensors and Detectors. Considerations of the Stability, Sensitivity, Reproducibility, and Mechanism of Ion Transport in Gas Phase Chromatography and in High Performance Liquid Phase Chromatography

DTIC Science & Technology

1988-07-15

solvents were used. For high performance liquid chromatographic studies, the DNA bases thymine, adenine, cytocine, uracil, and guanine (Aldrich...this experiment. The DNA bases guanine, adenine, cytocine, uracil, and thymine were detected for a gradient elution of a mixture of the bases in a

Non-Contact Laser Based Ultrasound Evaluation of Canned Foods

NASA Astrophysics Data System (ADS)

Shelton, David

2005-03-01

Laser-Based Ultrasound detection was used to measure the velocity of compression waves transmitted through canned foods. Condensed broth, canned pasta, and non-condensed soup were evaluated in these experiments. Homodyne adaptive optics resulted in measurements that were more accurate than the traditional heterodyne method, as well as yielding a 10 dB gain in signal to noise. A-Scans measured the velocity of ultrasound sent through the center of the can and were able to distinguish the quantity of food stuff in its path, as well as distinguish between meat and potato. B-Scans investigated the heterogeneity of the sample’s contents. The evaluation of canned foods was completely non-contact and would be suitable for continuous monitoring in production. These results were verified by conducting the same experiments with a contact piezo transducer. Although the contact method yields a higher signal to noise ratio than the non-contact method, Laser-Based Ultrasound was able to detect surface waves the contact transducer could not.

Multi-Objective Community Detection Based on Memetic Algorithm

PubMed Central

2015-01-01

Community detection has drawn a lot of attention as it can provide invaluable help in understanding the function and visualizing the structure of networks. Since single objective optimization methods have intrinsic drawbacks to identifying multiple significant community structures, some methods formulate the community detection as multi-objective problems and adopt population-based evolutionary algorithms to obtain multiple community structures. Evolutionary algorithms have strong global search ability, but have difficulty in locating local optima efficiently. In this study, in order to identify multiple significant community structures more effectively, a multi-objective memetic algorithm for community detection is proposed by combining multi-objective evolutionary algorithm with a local search procedure. The local search procedure is designed by addressing three issues. Firstly, nondominated solutions generated by evolutionary operations and solutions in dominant population are set as initial individuals for local search procedure. Then, a new direction vector named as pseudonormal vector is proposed to integrate two objective functions together to form a fitness function. Finally, a network specific local search strategy based on label propagation rule is expanded to search the local optimal solutions efficiently. The extensive experiments on both artificial and real-world networks evaluate the proposed method from three aspects. Firstly, experiments on influence of local search procedure demonstrate that the local search procedure can speed up the convergence to better partitions and make the algorithm more stable. Secondly, comparisons with a set of classic community detection methods illustrate the proposed method can find single partitions effectively. Finally, the method is applied to identify hierarchical structures of networks which are beneficial for analyzing networks in multi-resolution levels. PMID:25932646

Multi-objective community detection based on memetic algorithm.

PubMed

Wu, Peng; Pan, Li

2015-01-01

Community detection has drawn a lot of attention as it can provide invaluable help in understanding the function and visualizing the structure of networks. Since single objective optimization methods have intrinsic drawbacks to identifying multiple significant community structures, some methods formulate the community detection as multi-objective problems and adopt population-based evolutionary algorithms to obtain multiple community structures. Evolutionary algorithms have strong global search ability, but have difficulty in locating local optima efficiently. In this study, in order to identify multiple significant community structures more effectively, a multi-objective memetic algorithm for community detection is proposed by combining multi-objective evolutionary algorithm with a local search procedure. The local search procedure is designed by addressing three issues. Firstly, nondominated solutions generated by evolutionary operations and solutions in dominant population are set as initial individuals for local search procedure. Then, a new direction vector named as pseudonormal vector is proposed to integrate two objective functions together to form a fitness function. Finally, a network specific local search strategy based on label propagation rule is expanded to search the local optimal solutions efficiently. The extensive experiments on both artificial and real-world networks evaluate the proposed method from three aspects. Firstly, experiments on influence of local search procedure demonstrate that the local search procedure can speed up the convergence to better partitions and make the algorithm more stable. Secondly, comparisons with a set of classic community detection methods illustrate the proposed method can find single partitions effectively. Finally, the method is applied to identify hierarchical structures of networks which are beneficial for analyzing networks in multi-resolution levels.

New method for analyzing dark matter direct detection data

NASA Astrophysics Data System (ADS)

Davis, Jonathan H.; Enßlin, Torsten; BÅ`hm, Céline

2014-02-01

The experimental situation of dark matter direct detection has reached an exciting crossroads, with potential hints of a discovery of dark matter (DM) from the CDMS, CoGeNT, CRESST-II and DAMA experiments in tension with null results from xenon-based experiments such as XENON100 and LUX. Given the present controversial experimental status, it is important that the analytical method used to search for DM in direct detection experiments is both robust and flexible enough to deal with data for which the distinction between signal and background points is difficult, and hence where the choice between setting a limit or defining a discovery region is debatable. In this article we propose a novel (Bayesian) analytical method, which can be applied to all direct detection experiments and which extracts the maximum amount of information from the data. We apply our method to the XENON100 experiment data as a worked example, and show that firstly our exclusion limit at 90% confidence is in agreement with their own for the 225 live days data, but is several times stronger for the 100 live days data. Secondly we find that, due to the two points at low values of S1 and S2 in the 225 days data set, our analysis points to either weak consistency with low-mass dark matter or the possible presence of an unknown background. Given the null result from LUX, the latter scenario seems the more plausible.

Highly selective luminescent sensing of picric acid based on a water-stable europium metal-organic framework

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

Xia, Tifeng; Zhu, Fengliang; Cui, Yuanjing, E-mail: cuiyj@zju.edu.cn

A water-stable metal-organic framework (MOF) EuNDC has been synthesized for selective detection of the well-known contaminant and toxicant picric acid (PA) in aqueous solution. Due to the photo-induced electron transfer and self-absorption mechanism, EuNDC displayed rapid, selective and sensitive detection of PA with a detection limit of 37.6 ppb. Recyclability experiments revealed that EuNDC retains its initial luminescent intensity and same quenching efficiency in each cycle, suggesting high photostability and reusability for long-term sensing applications. The excellent detection performance of EuNDC makes it a promising PA sensing material for practical applications. - Graphical abstract: A water-stable europium-based metal-organic framework hasmore » been reported for highly selective sensing of picric acid (PA) with a detection limit of 37.6 ppb in aqueous solution. - Highlights: • A water-stable metal-organic framework (MOF) EuNDC was synthesized. • The highly selective detection of picric acid with a detection limit of 37.6 ppb was realized. • The detection mechanism were also presented and discussed.« less

Efficient Mining and Detection of Sequential Intrusion Patterns for Network Intrusion Detection Systems

NASA Astrophysics Data System (ADS)

Shyu, Mei-Ling; Huang, Zifang; Luo, Hongli

In recent years, pervasive computing infrastructures have greatly improved the interaction between human and system. As we put more reliance on these computing infrastructures, we also face threats of network intrusion and/or any new forms of undesirable IT-based activities. Hence, network security has become an extremely important issue, which is closely connected with homeland security, business transactions, and people's daily life. Accurate and efficient intrusion detection technologies are required to safeguard the network systems and the critical information transmitted in the network systems. In this chapter, a novel network intrusion detection framework for mining and detecting sequential intrusion patterns is proposed. The proposed framework consists of a Collateral Representative Subspace Projection Modeling (C-RSPM) component for supervised classification, and an inter-transactional association rule mining method based on Layer Divided Modeling (LDM) for temporal pattern analysis. Experiments on the KDD99 data set and the traffic data set generated by a private LAN testbed show promising results with high detection rates, low processing time, and low false alarm rates in mining and detecting sequential intrusion detections.

Convolutional neural network based deep-learning architecture for prostate cancer detection on multiparametric magnetic resonance images

NASA Astrophysics Data System (ADS)

Tsehay, Yohannes K.; Lay, Nathan S.; Roth, Holger R.; Wang, Xiaosong; Kwak, Jin Tae; Turkbey, Baris I.; Pinto, Peter A.; Wood, Brad J.; Summers, Ronald M.

2017-03-01

Prostate cancer (PCa) is the second most common cause of cancer related deaths in men. Multiparametric MRI (mpMRI) is the most accurate imaging method for PCa detection; however, it requires the expertise of experienced radiologists leading to inconsistency across readers of varying experience. To increase inter-reader agreement and sensitivity, we developed a computer-aided detection (CAD) system that can automatically detect lesions on mpMRI that readers can use as a reference. We investigated a convolutional neural network based deep-learing (DCNN) architecture to find an improved solution for PCa detection on mpMRI. We adopted a network architecture from a state-of-the-art edge detector that takes an image as an input and produces an image probability map. Two-fold cross validation along with a receiver operating characteristic (ROC) analysis and free-response ROC (FROC) were used to determine our deep-learning based prostate-CAD's (CADDL) performance. The efficacy was compared to an existing prostate CAD system that is based on hand-crafted features, which was evaluated on the same test-set. CADDL had an 86% detection rate at 20% false-positive rate while the top-down learning CAD had 80% detection rate at the same false-positive rate, which translated to 94% and 85% detection rate at 10 false-positives per patient on the FROC. A CNN based CAD is able to detect cancerous lesions on mpMRI of the prostate with results comparable to an existing prostate-CAD showing potential for further development.

Wavelet threshold method of resolving noise interference in periodic short-impulse signals chaotic detection

NASA Astrophysics Data System (ADS)

Deng, Ke; Zhang, Lu; Luo, Mao-Kang

2010-03-01

The chaotic oscillator has already been considered as a powerful method to detect weak signals, even weak signals accompanied with noises. However, many examples, analyses and simulations indicate that chaotic oscillator detection system cannot guarantee the immunity to noises (even white noise). In fact the randomness of noises has a serious or even a destructive effect on the detection results in many cases. To solve this problem, we present a new detecting method based on wavelet threshold processing that can detect the chaotic weak signal accompanied with noise. All theoretical analyses and simulation experiments indicate that the new method reduces the noise interferences to detection significantly, thereby making the corresponding chaotic oscillator that detects the weak signals accompanied with noises more stable and reliable.

Eyewitness decisions in simultaneous and sequential lineups: a dual-process signal detection theory analysis.

PubMed

Meissner, Christian A; Tredoux, Colin G; Parker, Janat F; MacLin, Otto H

2005-07-01

Many eyewitness researchers have argued for the application of a sequential alternative to the traditional simultaneous lineup, given its role in decreasing false identifications of innocent suspects (sequential superiority effect). However, Ebbesen and Flowe (2002) have recently noted that sequential lineups may merely bring about a shift in response criterion, having no effect on discrimination accuracy. We explored this claim, using a method that allows signal detection theory measures to be collected from eyewitnesses. In three experiments, lineup type was factorially combined with conditions expected to influence response criterion and/or discrimination accuracy. Results were consistent with signal detection theory predictions, including that of a conservative criterion shift with the sequential presentation of lineups. In a fourth experiment, we explored the phenomenological basis for the criterion shift, using the remember-know-guess procedure. In accord with previous research, the criterion shift in sequential lineups was associated with a reduction in familiarity-based responding. It is proposed that the relative similarity between lineup members may create a context in which fluency-based processing is facilitated to a greater extent when lineup members are presented simultaneously.

A Diagnostic Approach for Electro-Mechanical Actuators in Aerospace Systems

NASA Technical Reports Server (NTRS)

Balaban, Edward; Saxena, Abhinav; Bansal, Prasun; Goebel, Kai Frank; Stoelting, Paul; Curran, Simon

2009-01-01

Electro-mechanical actuators (EMA) are finding increasing use in aerospace applications, especially with the trend towards all all-electric aircraft and spacecraft designs. However, electro-mechanical actuators still lack the knowledge base accumulated for other fielded actuator types, particularly with regard to fault detection and characterization. This paper presents a thorough analysis of some of the critical failure modes documented for EMAs and describes experiments conducted on detecting and isolating a subset of them. The list of failures has been prepared through an extensive Failure Modes and Criticality Analysis (FMECA) reference, literature review, and accessible industry experience. Methods for data acquisition and validation of algorithms on EMA test stands are described. A variety of condition indicators were developed that enabled detection, identification, and isolation among the various fault modes. A diagnostic algorithm based on an artificial neural network is shown to operate successfully using these condition indicators and furthermore, robustness of these diagnostic routines to sensor faults is demonstrated by showing their ability to distinguish between them and component failures. The paper concludes with a roadmap leading from this effort towards developing successful prognostic algorithms for electromechanical actuators.

Solution of the problem of superposing image and digital map for detection of new objects

NASA Astrophysics Data System (ADS)

Rizaev, I. S.; Miftakhutdinov, D. I.; Takhavova, E. G.

2018-01-01

The problem of superposing the map of the terrain with the image of the terrain is considered. The image of the terrain may be represented in different frequency bands. Further analysis of the results of collation the digital map with the image of the appropriate terrain is described. Also the approach to detection of differences between information represented on the digital map and information of the image of the appropriate area is offered. The algorithm for calculating the values of brightness of the converted image area on the original picture is offered. The calculation is based on using information about the navigation parameters and information according to arranged bench marks. For solving the posed problem the experiments were performed. The results of the experiments are shown in this paper. The presented algorithms are applicable to the ground complex of remote sensing data to assess differences between resulting images and accurate geopositional data. They are also suitable for detecting new objects in the image, based on the analysis of the matching the digital map and the image of corresponding locality.

Development of microcontroller-based acquisition and processing unit for fiber optic vibration sensor

NASA Astrophysics Data System (ADS)

Suryadi; Puranto, P.; Adinanta, H.; Waluyo, T. B.; Priambodo, P. S.

2017-04-01

Microcontroller based acquisition and processing unit (MAPU) has been developed to measure vibration signal from fiber optic vibration sensor. The MAPU utilizes a 32-bit ARM microcontroller to perform acquisition and processing of the input signal. The input signal is acquired with 12 bit ADC and processed using FFT method to extract frequency information. Stability of MAPU is characterized by supplying a constant input signal at 500 Hz for 29 hours and shows a stable operation. To characterize the frequency response, input signal is swapped from 20 to 1000 Hz with 20 Hz interval. The characterization result shows that MAPU can detect input signal from 20 to 1000 Hz with minimum signal of 4 mV RMS. The experiment has been set that utilizes the MAPU with singlemode-multimode-singlemode (SMS) fiber optic sensor to detect vibration which is induced by a transducer in a wooden platform. The experimental result indicates that vibration signal from 20 to 600 Hz has been successfully detected. Due to the limitation of the vibration source used in the experiment, vibration signal above 600 Hz is undetected.

Research on fiber Bragg grating heart sound sensing and wavelength demodulation method

NASA Astrophysics Data System (ADS)

Zhang, Cheng; Miao, Chang-Yun; Gao, Hua; Gan, Jing-Meng; Li, Hong-Qiang

2010-11-01

Heart sound includes a lot of physiological and pathological information of heart and blood vessel. Heart sound detecting is an important method to gain the heart status, and has important significance to early diagnoses of cardiopathy. In order to improve sensitivity and reduce noise, a heart sound measurement method based on fiber Bragg grating was researched. By the vibration principle of plane round diaphragm, a heart sound sensor structure of fiber Bragg grating was designed and a heart sound sensing mathematical model was established. A formula of heart sound sensitivity was deduced and the theoretical sensitivity of the designed sensor is 957.11pm/KPa. Based on matched grating method, the experiment system was built, by which the excursion of reflected wavelength of the sensing grating was detected and the information of heart sound was obtained. Experiments show that the designed sensor can detect the heart sound and the reflected wavelength variety range is about 70pm. When the sampling frequency is 1 KHz, the extracted heart sound waveform by using the db4 wavelet has the same characteristics with a standard heart sound sensor.

Detection of low-amplitude in vivo intrinsic signals from an optical imager of retinal function

NASA Astrophysics Data System (ADS)

Barriga, Eduardo S.; T'so, Dan; Pattichis, Marios; Kwon, Young; Kardon, Randy; Abramoff, Michael; Soliz, Peter

2006-02-01

In the early stages of some retinal diseases, such as glaucoma, loss of retinal activity may be difficult to detect with today's clinical instruments. Many of today's instruments focus on detecting changes in anatomical structures, such as the nerve fiber layer. Our device, which is based on a modified fundus camera, seeks to detect changes in optical signals that reflect functional changes in the retina. The functional imager uses a patterned stimulus at wavelength of 535nm. An intrinsic functional signal is collected at a near infrared wavelength. Measured changes in reflectance in response to the visual stimulus are on the order of 0.1% to 1% of the total reflected intensity level, which makes the functional signal difficult to detect by standard methods because it is masked by other physiological signals and by imaging system noise. In this paper, we analyze the video sequences from a set of 60 experiments with different patterned stimuli from cats. Using a set of statistical techniques known as Independent Component Analysis (ICA), we estimate the signals present in the videos. Through controlled simulation experiments, we quantify the limits of signal strength in order to detect the physiological signal of interest. The results of the analysis show that, in principle, signal levels of 0.1% (-30dB) can be detected. The study found that in 86% of the animal experiments the patterned stimuli effects on the retina can be detected and extracted. The analysis of the different responses extracted from the videos can give an insight of the functional processes present during the stimulation of the retina.

An extensive analysis of various texture feature extractors to detect Diabetes Mellitus using facial specific regions.

PubMed

Shu, Ting; Zhang, Bob; Yan Tang, Yuan

2017-04-01

Researchers have recently discovered that Diabetes Mellitus can be detected through non-invasive computerized method. However, the focus has been on facial block color features. In this paper, we extensively study the effects of texture features extracted from facial specific regions at detecting Diabetes Mellitus using eight texture extractors. The eight methods are from four texture feature families: (1) statistical texture feature family: Image Gray-scale Histogram, Gray-level Co-occurance Matrix, and Local Binary Pattern, (2) structural texture feature family: Voronoi Tessellation, (3) signal processing based texture feature family: Gaussian, Steerable, and Gabor filters, and (4) model based texture feature family: Markov Random Field. In order to determine the most appropriate extractor with optimal parameter(s), various parameter(s) of each extractor are experimented. For each extractor, the same dataset (284 Diabetes Mellitus and 231 Healthy samples), classifiers (k-Nearest Neighbors and Support Vector Machines), and validation method (10-fold cross validation) are used. According to the experiments, the first and third families achieved a better outcome at detecting Diabetes Mellitus than the other two. The best texture feature extractor for Diabetes Mellitus detection is the Image Gray-scale Histogram with bin number=256, obtaining an accuracy of 99.02%, a sensitivity of 99.64%, and a specificity of 98.26% by using SVM. Copyright © 2017 Elsevier Ltd. All rights reserved.

GMR-based eddy current probe for weld seam inspection and its non-scanning detection study

NASA Astrophysics Data System (ADS)

Gao, Peng; Wang, Chao; Li, Yang; Wang, Libin; Cong, Zheng; Zhi, Ya

2017-04-01

Eddy current testing is one of the most important non-destructive testing methods for welding defects detection. This paper presents the use of a probe consisting of 4 giant magneto-resistive (GMR) sensors to detect weld defects. Information from four measuring points above and on both sides of the weld seam is collected at the same time. By setting the GMR sensors' sensing axes perpendicular to the direction of the excitation magnetic field, the information collected mainly reflects the change in the eddy current which is caused by defects. Digital demodulation technology is applied to extract the real part and imaginary part of the GMR sensors' output signals. The variables containing directional information of the magnetic field are introduced. Based on the data from the four GMR (4-GMR) sensors' output signals, four values, Ran, Mean, Var and k are selected as the feature quantities for defect recognition. Experiments are carried out on weld seams with and without defects, and the detection outputs are given in this paper. The 4-GMR probe is also employed to investigate non-scanning weld defect detection and the four feature quantities (Ran, Mean, Var and k) are studied to evaluate weld quality. The non-scanning weld defect detection is presented. A support vector machine is used to classify and discriminate welds with and without defects. Experiments carried out show that through the method in this paper, the recognition rate is 92% for welds without defects and 90% for welds with defects, with an overall recognition rate of 90.9%, indicating that this method could effectively detect weld defects.

A unified approach for debugging is-a structure and mappings in networked taxonomies

PubMed Central

2013-01-01

Background With the increased use of ontologies and ontology mappings in semantically-enabled applications such as ontology-based search and data integration, the issue of detecting and repairing defects in ontologies and ontology mappings has become increasingly important. These defects can lead to wrong or incomplete results for the applications. Results We propose a unified framework for debugging the is-a structure of and mappings between taxonomies, the most used kind of ontologies. We present theory and algorithms as well as an implemented system RepOSE, that supports a domain expert in detecting and repairing missing and wrong is-a relations and mappings. We also discuss two experiments performed by domain experts: an experiment on the Anatomy ontologies from the Ontology Alignment Evaluation Initiative, and a debugging session for the Swedish National Food Agency. Conclusions Semantically-enabled applications need high quality ontologies and ontology mappings. One key aspect is the detection and removal of defects in the ontologies and ontology mappings. Our system RepOSE provides an environment that supports domain experts to deal with this issue. We have shown the usefulness of the approach in two experiments by detecting and repairing circa 200 and 30 defects, respectively. PMID:23548155

Object detection from images obtained through underwater turbulence medium

NASA Astrophysics Data System (ADS)

Furhad, Md. Hasan; Tahtali, Murat; Lambert, Andrew

2017-09-01

Imaging through underwater experiences severe distortions due to random fluctuations of temperature and salinity in water, which produces underwater turbulence through diffraction limited blur. Lights reflecting from objects perturb and attenuate contrast, making the recognition of objects of interest difficult. Thus, the information available for detecting underwater objects of interest becomes a challenging task as they have inherent confusion among the background, foreground and other image properties. In this paper, a saliency-based approach is proposed to detect the objects acquired through an underwater turbulent medium. This approach has drawn attention among a wide range of computer vision applications, such as image retrieval, artificial intelligence, neuro-imaging and object detection. The image is first processed through a deblurring filter. Next, a saliency technique is used on the image for object detection. In this step, a saliency map that highlights the target regions is generated and then a graph-based model is proposed to extract these target regions for object detection.

Quantitation of secreted proteins using mCherry fusion constructs and a fluorescent microplate reader.

PubMed

Duellman, Tyler; Burnett, John; Yang, Jay

2015-03-15

Traditional assays for secreted proteins include methods such as Western blot and enzyme-linked immunosorbent assay (ELISA) detection of the protein in the cell culture medium. We describe a method for the detection of a secreted protein based on fluorescent measurement of an mCherry fusion reporter. This microplate reader-based mCherry fluorescence detection method has a wide dynamic range of 4.5 orders of magnitude and a sensitivity that allows detection of 1 to 2fmol fusion protein. Comparison with the Western blot detection method indicated greater linearity, wider dynamic range, and a similar lower detection threshold for the microplate-based fluorescent detection assay of secreted fusion proteins. An mCherry fusion protein of matrix metalloproteinase-9 (MMP-9), a secreted glycoprotein, was created and expressed by transfection of human embryonic kidney (HEK) 293 cells. The cell culture medium was assayed for the presence of the fluorescent signal up to 32 h after transfection. The secreted MMP-9-mCherry fusion protein was detected 6h after transfection with a linear increase in signal intensity over time. Treatment with chloroquine, a drug known to inhibit the secretion of many proteins, abolished the MMP-9-mCherry secretion, demonstrating the utility of this method in a biological experiment. Copyright © 2014 Elsevier Inc. All rights reserved.

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.

The use of Landsat digital data to detect and monitor vegetation water deficiencies

NASA Technical Reports Server (NTRS)

Thompson, D. R.; Wehmanen, O. A.

1977-01-01

In the Large Area Crop Inventory Experiment a technique was devised using a vector transformation of Landsat digital data to indicate when vegetation is undergoing moisture stress. A relation was established between the remote-sensing-based criterion (the Green Index Number) and a ground-based criterion (Crop Moisture Index).

Testing Theories of Recognition Memory by Predicting Performance Across Paradigms

ERIC Educational Resources Information Center

Smith, David G.; Duncan, Matthew J. J.

2004-01-01

Signal-detection theory (SDT) accounts of recognition judgments depend on the assumption that recognition decisions result from a single familiarity-based process. However, fits of a hybrid SDT model, called dual-process theory (DPT), have provided evidence for the existence of a second, recollection-based process. In 2 experiments, the authors…

Proactive Control Processes in Event-Based Prospective Memory: Evidence from Intraindividual Variability and Ex-Gaussian Analyses

ERIC Educational Resources Information Center

Ball, B. Hunter; Brewer, Gene A.

2018-01-01

The present study implemented an individual differences approach in conjunction with response time (RT) variability and distribution modeling techniques to better characterize the cognitive control dynamics underlying ongoing task cost (i.e., slowing) and cue detection in event-based prospective memory (PM). Three experiments assessed the relation…

Detecting Nasal Vowels in Speech Interfaces Based on Surface Electromyography

PubMed Central

Freitas, João; Teixeira, António; Silva, Samuel; Oliveira, Catarina; Dias, Miguel Sales

2015-01-01

Nasality is a very important characteristic of several languages, European Portuguese being one of them. This paper addresses the challenge of nasality detection in surface electromyography (EMG) based speech interfaces. We explore the existence of useful information about the velum movement and also assess if muscles deeper down in the face and neck region can be measured using surface electrodes, and the best electrode location to do so. The procedure we adopted uses Real-Time Magnetic Resonance Imaging (RT-MRI), collected from a set of speakers, providing a method to interpret EMG data. By ensuring compatible data recording conditions, and proper time alignment between the EMG and the RT-MRI data, we are able to accurately estimate the time when the velum moves and the type of movement when a nasal vowel occurs. The combination of these two sources revealed interesting and distinct characteristics in the EMG signal when a nasal vowel is uttered, which motivated a classification experiment. Overall results of this experiment provide evidence that it is possible to detect velum movement using sensors positioned below the ear, between mastoid process and the mandible, in the upper neck region. In a frame-based classification scenario, error rates as low as 32.5% for all speakers and 23.4% for the best speaker have been achieved, for nasal vowel detection. This outcome stands as an encouraging result, fostering the grounds for deeper exploration of the proposed approach as a promising route to the development of an EMG-based speech interface for languages with strong nasal characteristics. PMID:26069968

SERS detection of R6G based on a novel graphene oxide/silver nanoparticles/silicon pyramid arrays structure.

PubMed

Zhang, C; Jiang, S Z; Huo, Y Y; Liu, A H; Xu, S C; Liu, X Y; Sun, Z C; Xu, Y Y; Li, Z; Man, B Y

2015-09-21

We present a novel surface-enhanced Raman scattering (SERS) substrate based on graphene oxide/silver nanoparticles/silicon pyramid arrays structure (GO/Ag/PSi). The SERS behaviors are discussed and compared by the detection of R6G. Based on the contrast experiments with PSi, GO/PSi, Ag/PSi and GO/AgA/PSi as SERS substrate, the perfect bio-compatibility, good homogeneity and chemical stability were confirmed. We also calculated the electric field distributions using Finite-difference time-domain (FDTD) analysis to further understand the GO/Ag/PSi structure as a perfect SERS platform. These experimental and theoretical results imply that the GO/Ag/PSi with regular pyramids array is expected to be an effective substrate for label-free sensitive SERS detections in areas of medicine, food safety and biotechnology.

Deep Constrained Siamese Hash Coding Network and Load-Balanced Locality-Sensitive Hashing for Near Duplicate Image Detection.

PubMed

Hu, Weiming; Fan, Yabo; Xing, Junliang; Sun, Liang; Cai, Zhaoquan; Maybank, Stephen

2018-09-01

We construct a new efficient near duplicate image detection method using a hierarchical hash code learning neural network and load-balanced locality-sensitive hashing (LSH) indexing. We propose a deep constrained siamese hash coding neural network combined with deep feature learning. Our neural network is able to extract effective features for near duplicate image detection. The extracted features are used to construct a LSH-based index. We propose a load-balanced LSH method to produce load-balanced buckets in the hashing process. The load-balanced LSH significantly reduces the query time. Based on the proposed load-balanced LSH, we design an effective and feasible algorithm for near duplicate image detection. Extensive experiments on three benchmark data sets demonstrate the effectiveness of our deep siamese hash encoding network and load-balanced LSH.

Robust skin color-based moving object detection for video surveillance

NASA Astrophysics Data System (ADS)

Kaliraj, Kalirajan; Manimaran, Sudha

2016-07-01

Robust skin color-based moving object detection for video surveillance is proposed. The objective of the proposed algorithm is to detect and track the target under complex situations. The proposed framework comprises four stages, which include preprocessing, skin color-based feature detection, feature classification, and target localization and tracking. In the preprocessing stage, the input image frame is smoothed using averaging filter and transformed into YCrCb color space. In skin color detection, skin color regions are detected using Otsu's method of global thresholding. In the feature classification, histograms of both skin and nonskin regions are constructed and the features are classified into foregrounds and backgrounds based on Bayesian skin color classifier. The foreground skin regions are localized by a connected component labeling process. Finally, the localized foreground skin regions are confirmed as a target by verifying the region properties, and nontarget regions are rejected using the Euler method. At last, the target is tracked by enclosing the bounding box around the target region in all video frames. The experiment was conducted on various publicly available data sets and the performance was evaluated with baseline methods. It evidently shows that the proposed algorithm works well against slowly varying illumination, target rotations, scaling, fast, and abrupt motion changes.

Depth- and range-dependent variation in the performance of aquatic telemetry systems: understanding and predicting the susceptibility of acoustic tag-receiver pairs to close proximity detection interference.

PubMed

Scherrer, Stephen R; Rideout, Brendan P; Giorli, Giacomo; Nosal, Eva-Marie; Weng, Kevin C

2018-01-01

Passive acoustic telemetry using coded transmitter tags and stationary receivers is a popular method for tracking movements of aquatic animals. Understanding the performance of these systems is important in array design and in analysis. Close proximity detection interference (CPDI) is a condition where receivers fail to reliably detect tag transmissions. CPDI generally occurs when the tag and receiver are near one another in acoustically reverberant settings. Here we confirm transmission multipaths reflected off the environment arriving at a receiver with sufficient delay relative to the direct signal cause CPDI. We propose a ray-propagation based model to estimate the arrival of energy via multipaths to predict CPDI occurrence, and we show how deeper deployments are particularly susceptible. A series of experiments were designed to develop and validate our model. Deep (300 m) and shallow (25 m) ranging experiments were conducted using Vemco V13 acoustic tags and VR2-W receivers. Probabilistic modeling of hourly detections was used to estimate the average distance a tag could be detected. A mechanistic model for predicting the arrival time of multipaths was developed using parameters from these experiments to calculate the direct and multipath path lengths. This model was retroactively applied to the previous ranging experiments to validate CPDI observations. Two additional experiments were designed to validate predictions of CPDI with respect to combinations of deployment depth and distance. Playback of recorded tags in a tank environment was used to confirm multipaths arriving after the receiver's blanking interval cause CPDI effects. Analysis of empirical data estimated the average maximum detection radius (AMDR), the farthest distance at which 95% of tag transmissions went undetected by receivers, was between 840 and 846 m for the deep ranging experiment across all factor permutations. From these results, CPDI was estimated within a 276.5 m radius of the receiver. These empirical estimations were consistent with mechanistic model predictions. CPDI affected detection at distances closer than 259-326 m from receivers. AMDR determined from the shallow ranging experiment was between 278 and 290 m with CPDI neither predicted nor observed. Results of validation experiments were consistent with mechanistic model predictions. Finally, we were able to predict detection/nondetection with 95.7% accuracy using the mechanistic model's criterion when simulating transmissions with and without multipaths. Close proximity detection interference results from combinations of depth and distance that produce reflected signals arriving after a receiver's blanking interval has ended. Deployment scenarios resulting in CPDI can be predicted with the proposed mechanistic model. For deeper deployments, sea-surface reflections can produce CPDI conditions, resulting in transmission rejection, regardless of the reflective properties of the seafloor.

Cloud Detection of Optical Satellite Images Using Support Vector Machine

NASA Astrophysics Data System (ADS)

Lee, Kuan-Yi; Lin, Chao-Hung

2016-06-01

Cloud covers are generally present in optical remote-sensing images, which limit the usage of acquired images and increase the difficulty of data analysis, such as image compositing, correction of atmosphere effects, calculations of vegetation induces, land cover classification, and land cover change detection. In previous studies, thresholding is a common and useful method in cloud detection. However, a selected threshold is usually suitable for certain cases or local study areas, and it may be failed in other cases. In other words, thresholding-based methods are data-sensitive. Besides, there are many exceptions to control, and the environment is changed dynamically. Using the same threshold value on various data is not effective. In this study, a threshold-free method based on Support Vector Machine (SVM) is proposed, which can avoid the abovementioned problems. A statistical model is adopted to detect clouds instead of a subjective thresholding-based method, which is the main idea of this study. The features used in a classifier is the key to a successful classification. As a result, Automatic Cloud Cover Assessment (ACCA) algorithm, which is based on physical characteristics of clouds, is used to distinguish the clouds and other objects. In the same way, the algorithm called Fmask (Zhu et al., 2012) uses a lot of thresholds and criteria to screen clouds, cloud shadows, and snow. Therefore, the algorithm of feature extraction is based on the ACCA algorithm and Fmask. Spatial and temporal information are also important for satellite images. Consequently, co-occurrence matrix and temporal variance with uniformity of the major principal axis are used in proposed method. We aim to classify images into three groups: cloud, non-cloud and the others. In experiments, images acquired by the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and images containing the landscapes of agriculture, snow area, and island are tested. Experiment results demonstrate the detection accuracy of the proposed method is better than related methods.

Design of Moisture Content Detection System

NASA Astrophysics Data System (ADS)

Wang, W. C.; Wang, L.

In this paper, a method for measuring the moisture content of grain was presented based on single chip microcomputer and capacitive sensor. The working principle of measuring moisture content is introduced and a concentric cylinder type of capacitive sensor is designed, the signal processing circuits of system are described in details. System is tested in practice and discussions are made on the various factors affecting the capacitive measuring of grain moisture based on the practical experiments, experiment results showed that the system has high measuring accuracy and good controlling capacity.

Change detection for synthetic aperture radar images based on pattern and intensity distinctiveness analysis

NASA Astrophysics Data System (ADS)

Wang, Xiao; Gao, Feng; Dong, Junyu; Qi, Qiang

2018-04-01

Synthetic aperture radar (SAR) image is independent on atmospheric conditions, and it is the ideal image source for change detection. Existing methods directly analysis all the regions in the speckle noise contaminated difference image. The performance of these methods is easily affected by small noisy regions. In this paper, we proposed a novel change detection framework for saliency-guided change detection based on pattern and intensity distinctiveness analysis. The saliency analysis step can remove small noisy regions, and therefore makes the proposed method more robust to the speckle noise. In the proposed method, the log-ratio operator is first utilized to obtain a difference image (DI). Then, the saliency detection method based on pattern and intensity distinctiveness analysis is utilized to obtain the changed region candidates. Finally, principal component analysis and k-means clustering are employed to analysis pixels in the changed region candidates. Thus, the final change map can be obtained by classifying these pixels into changed or unchanged class. The experiment results on two real SAR images datasets have demonstrated the effectiveness of the proposed method.

Development of a Coded Aperture X-Ray Backscatter Imager for Explosive Device Detection

NASA Astrophysics Data System (ADS)

Faust, Anthony A.; Rothschild, Richard E.; Leblanc, Philippe; McFee, John Elton

2009-02-01

Defence R&D Canada has an active research and development program on detection of explosive devices using nuclear methods. One system under development is a coded aperture-based X-ray backscatter imaging detector designed to provide sufficient speed, contrast and spatial resolution to detect antipersonnel landmines and improvised explosive devices. The successful development of a hand-held imaging detector requires, among other things, a light-weight, ruggedized detector with low power requirements, supplying high spatial resolution. The University of California, San Diego-designed HEXIS detector provides a modern, large area, high-temperature CZT imaging surface, robustly packaged in a light-weight housing with sound mechanical properties. Based on the potential for the HEXIS detector to be incorporated as the detection element of a hand-held imaging detector, the authors initiated a collaborative effort to demonstrate the capability of a coded aperture-based X-ray backscatter imaging detector. This paper will discuss the landmine and IED detection problem and review the coded aperture technique. Results from initial proof-of-principle experiments will then be reported.

Effects of Resolution, Range, and Image Contrast on Target Acquisition Performance.

PubMed

Hollands, Justin G; Terhaar, Phil; Pavlovic, Nada J

2018-05-01

We sought to determine the joint influence of resolution, target range, and image contrast on the detection and identification of targets in simulated naturalistic scenes. Resolution requirements for target acquisition have been developed based on threshold values obtained using imaging systems, when target range was fixed, and image characteristics were determined by the system. Subsequent work has examined the influence of factors like target range and image contrast on target acquisition. We varied the resolution and contrast of static images in two experiments. Participants (soldiers) decided whether a human target was located in the scene (detection task) or whether a target was friendly or hostile (identification task). Target range was also varied (50-400 m). In Experiment 1, 30 participants saw color images with a single target exemplar. In Experiment 2, another 30 participants saw monochrome images containing different target exemplars. The effects of target range and image contrast were qualitatively different above and below 6 pixels per meter of target for both tasks in both experiments. Target detection and identification performance were a joint function of image resolution, range, and contrast for both color and monochrome images. The beneficial effects of increasing resolution for target acquisition performance are greater for closer (larger) targets.

A Designed Experiments Approach to Optimizing MALDI-TOF MS Spectrum Processing Parameters Enhances Detection of Antibiotic Resistance in Campylobacter jejuni

PubMed Central

Penny, Christian; Grothendick, Beau; Zhang, Lin; Borror, Connie M.; Barbano, Duane; Cornelius, Angela J.; Gilpin, Brent J.; Fagerquist, Clifton K.; Zaragoza, William J.; Jay-Russell, Michele T.; Lastovica, Albert J.; Ragimbeau, Catherine; Cauchie, Henry-Michel; Sandrin, Todd R.

2016-01-01

MALDI-TOF MS has been utilized as a reliable and rapid tool for microbial fingerprinting at the genus and species levels. Recently, there has been keen interest in using MALDI-TOF MS beyond the genus and species levels to rapidly identify antibiotic resistant strains of bacteria. The purpose of this study was to enhance strain level resolution for Campylobacter jejuni through the optimization of spectrum processing parameters using a series of designed experiments. A collection of 172 strains of C. jejuni were collected from Luxembourg, New Zealand, North America, and South Africa, consisting of four groups of antibiotic resistant isolates. The groups included: (1) 65 strains resistant to cefoperazone (2) 26 resistant to cefoperazone and beta-lactams (3) 5 strains resistant to cefoperazone, beta-lactams, and tetracycline, and (4) 76 strains resistant to cefoperazone, teicoplanin, amphotericin, B and cephalothin. Initially, a model set of 16 strains (three biological replicates and three technical replicates per isolate, yielding a total of 144 spectra) of C. jejuni was subjected to each designed experiment to enhance detection of antibiotic resistance. The most optimal parameters were applied to the larger collection of 172 isolates (two biological replicates and three technical replicates per isolate, yielding a total of 1,031 spectra). We observed an increase in antibiotic resistance detection whenever either a curve based similarity coefficient (Pearson or ranked Pearson) was applied rather than a peak based (Dice) and/or the optimized preprocessing parameters were applied. Increases in antimicrobial resistance detection were scored using the jackknife maximum similarity technique following cluster analysis. From the first four groups of antibiotic resistant isolates, the optimized preprocessing parameters increased detection respective to the aforementioned groups by: (1) 5% (2) 9% (3) 10%, and (4) 2%. An additional second categorization was created from the collection consisting of 31 strains resistant to beta-lactams and 141 strains sensitive to beta-lactams. Applying optimal preprocessing parameters, beta-lactam resistance detection was increased by 34%. These results suggest that spectrum processing parameters, which are rarely optimized or adjusted, affect the performance of MALDI-TOF MS-based detection of antibiotic resistance and can be fine-tuned to enhance screening performance. PMID:27303397

Tracking wakefulness as it fades: Micro-measures of alertness.

PubMed

Jagannathan, Sridhar R; Ezquerro-Nassar, Alejandro; Jachs, Barbara; Pustovaya, Olga V; Bareham, Corinne A; Bekinschtein, Tristan A

2018-08-01

A major problem in psychology and physiology experiments is drowsiness: around a third of participants show decreased wakefulness despite being instructed to stay alert. In some non-visual experiments participants keep their eyes closed throughout the task, thus promoting the occurrence of such periods of varying alertness. These wakefulness changes contribute to systematic noise in data and measures of interest. To account for this omnipresent problem in data acquisition we defined criteria and code to allow researchers to detect and control for varying alertness in electroencephalography (EEG) experiments under eyes-closed settings. We first revise a visual-scoring method developed for detection and characterization of the sleep-onset process, and adapt the same for detection of alertness levels. Furthermore, we show the major issues preventing the practical use of this method, and overcome these issues by developing an automated method (micro-measures algorithm) based on frequency and sleep graphoelements, which are capable of detecting micro variations in alertness. The validity of the micro-measures algorithm was verified by training and testing using a dataset where participants are known to fall asleep. In addition, we tested generalisability by independent validation on another dataset. The methods developed constitute a unique tool to assess micro variations in levels of alertness and control trial-by-trial retrospectively or prospectively in every experiment performed with EEG in cognitive neuroscience under eyes-closed settings. Copyright © 2018. Published by Elsevier Inc.

Composite Sampling of a Bacillus anthracis Surrogate with ...

EPA Pesticide Factsheets

Journal Article A series of experiments were conducted to explore the utility of composite-based collection of surface samples for the detection of a Bacillus anthracis surrogate using cellulose sponge samplers on a stainless steel surface.

Aliasing Signal Separation of Superimposed Abrasive Debris Based on Degenerate Unmixing Estimation Technique.

PubMed

Li, Tongyang; Wang, Shaoping; Zio, Enrico; Shi, Jian; Hong, Wei

2018-03-15

Leakage is the most important failure mode in aircraft hydraulic systems caused by wear and tear between friction pairs of components. The accurate detection of abrasive debris can reveal the wear condition and predict a system's lifespan. The radial magnetic field (RMF)-based debris detection method provides an online solution for monitoring the wear condition intuitively, which potentially enables a more accurate diagnosis and prognosis on the aviation hydraulic system's ongoing failures. To address the serious mixing of pipe abrasive debris, this paper focuses on the superimposed abrasive debris separation of an RMF abrasive sensor based on the degenerate unmixing estimation technique. Through accurately separating and calculating the morphology and amount of the abrasive debris, the RMF-based abrasive sensor can provide the system with wear trend and sizes estimation of the wear particles. A well-designed experiment was conducted and the result shows that the proposed method can effectively separate the mixed debris and give an accurate count of the debris based on RMF abrasive sensor detection.

Subpixel Mapping of Hyperspectral Image Based on Linear Subpixel Feature Detection and Object Optimization

NASA Astrophysics Data System (ADS)

Liu, Zhaoxin; Zhao, Liaoying; Li, Xiaorun; Chen, Shuhan

2018-04-01

Owing to the limitation of spatial resolution of the imaging sensor and the variability of ground surfaces, mixed pixels are widesperead in hyperspectral imagery. The traditional subpixel mapping algorithms treat all mixed pixels as boundary-mixed pixels while ignoring the existence of linear subpixels. To solve this question, this paper proposed a new subpixel mapping method based on linear subpixel feature detection and object optimization. Firstly, the fraction value of each class is obtained by spectral unmixing. Secondly, the linear subpixel features are pre-determined based on the hyperspectral characteristics and the linear subpixel feature; the remaining mixed pixels are detected based on maximum linearization index analysis. The classes of linear subpixels are determined by using template matching method. Finally, the whole subpixel mapping results are iteratively optimized by binary particle swarm optimization algorithm. The performance of the proposed subpixel mapping method is evaluated via experiments based on simulated and real hyperspectral data sets. The experimental results demonstrate that the proposed method can improve the accuracy of subpixel mapping.

Production of radioactive isotopes through cosmic muon spallation in KamLAND

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

Abe, S.; Furuno, K.; Gando, Y.

2010-02-15

Radioactive isotopes produced through cosmic muon spallation are a background for rare-event detection in nu detectors, double-beta-decay experiments, and dark-matter searches. Understanding the nature of cosmogenic backgrounds is particularly important for future experiments aiming to determine the pep and CNO solar neutrino fluxes, for which the background is dominated by the spallation production of {sup 11}C. Data from the Kamioka liquid-scintillator antineutrino detector (KamLAND) provides valuable information for better understanding these backgrounds, especially in liquid scintillators, and for checking estimates from current simulations based upon MUSIC, FLUKA, and GEANT4. Using the time correlation between detected muons and neutron captures, themore » neutron production yield in the KamLAND liquid scintillator is measured to be Y{sub n}=(2.8+-0.3)x10{sup -4} mu{sup -1} g{sup -1} cm{sup 2}. For other isotopes, the production yield is determined from the observed time correlation related to known isotope lifetimes. We find some yields are inconsistent with extrapolations based on an accelerator muon beam experiment.« less

Study of the Production of Radioactive Isotopes through Cosmic Muon Spallation in KamLAND

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

KamLAND Collaboration; Abe, S.; Enomoto, S.

2009-06-30

Radioactive isotopes produced through cosmic muon spallation are a background for rare event detection in {nu} detectors, double-beta-decay experiments, and dark-matter searches. Understanding the nature of cosmogenic backgrounds is particularly important for future experiments aiming to determine the pep and CNO solar neutrino fluxes, for which the background is dominated by the spallation production of {sup 11}C. Data from the Kamioka Liquid scintillator Anti-Neutrino Detector (KamLAND) provides valuable information for better understanding these backgrounds, especially in liquid scintillator, and for checking estimates from current simulations based upon MUSIC, FLUKA, and Geant4. Using the time correlation between detected muons and neutronmore » captures, the neutron production yield in the KamLAND liquid scintillator is measured to be (2.8 {+-} 0.3) x 10{sup -4} n/({mu} {center_dot} (g/cm{sup 2})). For other isotopes, the production yield is determined from the observed time correlation related to known isotope lifetimes. We find some yields are inconsistent with extrapolations based on an accelerator muon beam experiment.« less

Data Driven, Force Based Interaction for Quadrotors

NASA Astrophysics Data System (ADS)

McKinnon, Christopher D.

Quadrotors are small and agile, and are becoming more capable for their compact size. They are expected perform a wide variety of tasks including inspection, physical interaction, and formation flight. In all of these tasks, the quadrotors can come into close proximity with infrastructure or other quadrotors, and may experience significant external forces and torques. Reacting properly in each case is essential to completing the task safely and effectively. In this thesis, we develop an algorithm, based on the Unscented Kalman Filter, to estimate such forces and torques without making assumptions about the source of the forces and torques. We then show in experiment how the proposed estimation algorithm can be used in conjunction with controls and machine learning to choose the appropriate actions in a wide variety of tasks including detecting downwash, tracking the wind induced by a fan, and detecting proximity to the wall.

Robust Foregrounds Removal for 21-cm Experiments

NASA Astrophysics Data System (ADS)

Mertens, F.; Ghosh, A.; Koopmans, L. V. E.

2018-05-01

Direct detection of the Epoch of Reionization via the redshifted 21-cm line will have unprecedented implications on the study of structure formation in the early Universe. To fulfill this promise current and future 21-cm experiments will need to detect the weak 21-cm signal over foregrounds several order of magnitude greater. This requires accurate modeling of the galactic and extragalactic emission and of its contaminants due to instrument chromaticity, ionosphere and imperfect calibration. To solve for this complex modeling, we propose a new method based on Gaussian Process Regression (GPR) which is able to cleanly separate the cosmological signal from most of the foregrounds contaminants. We also propose a new imaging method based on a maximum likelihood framework which solves for the interferometric equation directly on the sphere. Using this method, chromatic effects causing the so-called ``wedge'' are effectively eliminated (i.e. deconvolved) in the cylindrical (k⊥, k∥) power spectrum.

Evolution of the Ultrasonic Inspection Requirements of Heavy Rotor Forgings Over the Past Decades

NASA Astrophysics Data System (ADS)

Vrana, J.; Zimmer, A.; Bailey, K.; Angal, R.; Zombo, P.; Büchner, U.; Buschmann, A.; Shannon, R. E.; Lohmann, H.-P.; Heinrich, W.

2010-02-01

Heavy rotor forgings for land-based power generation turbines and generators are inspected ultrasonically. Several decades ago the first inspections were conducted using manual, straight beam, contact transducers with simple, non-descript reporting requirements. The development of ultrasonic inspection capabilities, the change in design engineer requirements, improvements of fracture mechanics calculations, experience with turbine operation, experience with the inspection technology, and probability of detection drove the changes that have resulted in the current day inspection requirements: sizing technologies were implemented, detection limits were lowered, angle and pitch/catch (dual crystal) scans were introduced, and most recently automated equipment for the inspection was required. Due to all these changes, model based sizing techniques, like DGS, and modern ultrasonic techniques, like phased array, are being introduced globally. This paper describes the evolution of the ultrasonic inspection requirements over the last decades and presents an outlook for tomorrow.

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.

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.

Advances in SAW gas sensors based on the condensate-adsorption effect.

PubMed

Liu, Jiuling; Wang, Wen; Li, Shunzhou; Liu, Minghua; He, Shitang

2011-01-01

A surface-acoustic-wave (SAW) gas sensor with a low detection limit and fast response for volatile organic compounds (VOCs) based on the condensate-adsorption effect detection is developed. In this sensor a gas chromatography (GC) column acts as the separator element and a dual-resonator oscillator acts as the detector element. Regarding the surface effective permittivity method, the response mechanism analysis, which relates the condensate-adsorption effect, is performed, leading to the sensor performance prediction prior to fabrication. New designs of SAW resonators, which act as feedback of the oscillator, are devised in order to decrease the insertion loss and to achieve single-mode control, resulting in superior frequency stability of the oscillator. Based on the new phase modulation approach, excellent short-term frequency stability (±3 Hz/s) is achieved with the SAW oscillator by using the 500 MHz dual-port resonator as feedback element. In a sensor experiment investigating formaldehyde detection, the implemented SAW gas sensor exhibits an excellent threshold detection limit as low as 0.38 pg.

Urban Area Detection in Very High Resolution Remote Sensing Images Using Deep Convolutional Neural Networks.

PubMed

Tian, Tian; Li, Chang; Xu, Jinkang; Ma, Jiayi

2018-03-18

Detecting urban areas from very high resolution (VHR) remote sensing images plays an important role in the field of Earth observation. The recently-developed deep convolutional neural networks (DCNNs), which can extract rich features from training data automatically, have achieved outstanding performance on many image classification databases. Motivated by this fact, we propose a new urban area detection method based on DCNNs in this paper. The proposed method mainly includes three steps: (i) a visual dictionary is obtained based on the deep features extracted by pre-trained DCNNs; (ii) urban words are learned from labeled images; (iii) the urban regions are detected in a new image based on the nearest dictionary word criterion. The qualitative and quantitative experiments on different datasets demonstrate that the proposed method can obtain a remarkable overall accuracy (OA) and kappa coefficient. Moreover, it can also strike a good balance between the true positive rate (TPR) and false positive rate (FPR).

A vision-based fall detection algorithm of human in indoor environment

NASA Astrophysics Data System (ADS)

Liu, Hao; Guo, Yongcai

2017-02-01

Elderly care becomes more and more prominent in China as the population is aging fast and the number of aging population is large. Falls, as one of the biggest challenges in elderly guardianship system, have a serious impact on both physical health and mental health of the aged. Based on feature descriptors, such as aspect ratio of human silhouette, velocity of mass center, moving distance of head and angle of the ultimate posture, a novel vision-based fall detection method was proposed in this paper. A fast median method of background modeling with three frames was also suggested. Compared with the conventional bounding box and ellipse method, the novel fall detection technique is not only applicable for recognizing the fall behaviors end of lying down but also suitable for detecting the fall behaviors end of kneeling down and sitting down. In addition, numerous experiment results showed that the method had a good performance in recognition accuracy on the premise of not adding the cost of time.

Selectivity verification of cardiac troponin monoclonal antibodies for cardiac troponin detection by using conventional ELISA

NASA Astrophysics Data System (ADS)

Fathil, M. F. M.; Arshad, M. K. Md; Gopinath, Subash C. B.; Adzhri, R.; Ruslinda, A. R.; Hashim, U.

2017-03-01

This paper presents preparation and characterization of conventional enzyme-linked immunosorbent assay (ELISA) for cardiac troponin detection to determine the selectivity of the cardiac troponin monoclonal antibodies. Monoclonal antibodies, used to capture and bind the targets in this experiment, are cTnI monoclonal antibody (MAb-cTnI) and cTnT monoclonal antibody (MAb-cTnT), while both cardiac troponin I (cTnI) and T (cTnT) are used as targets. ELISA is performed inside two microtiter plates for MAb-cTnI and MAb-cTnT. For each plate, monoclonal antibodies are tested by various concentrations of cTnI and cTnT ranging from 0-6400 µg/l. The binding selectivity and level of detection between monoclonal antibodies and antigen are determined through visual observation based on the color change inside each well on the plate. ELISA reader is further used to quantitatively measured the optical density of the color changes, thus produced more accurate reading. The results from this experiment are utilized to justify the use of these monoclonal antibodies as bio-receptors for cardiac troponin detection by using field-effect transistor (FET)-based biosensors coupled with substrate-gate in the future.

Development of the MOOSY4 eNose IoT for Sulphur-Based VOC Water Pollution Detection

PubMed Central

Climent, Enric; Pelegri-Sebastia, Jose; Sogorb, Tomas; Talens, J. B.; Chilo, Jose

2017-01-01

In this paper, we describe a new low-cost and portable electronic nose instrument, the Multisensory Odor Olfactory System MOOSY4. This prototype is based on only four metal oxide semiconductor (MOS) gas sensors suitable for IoT technology. The system architecture consists of four stages: data acquisition, data storage, data processing, and user interfacing. The designed eNose was tested with experiment for detection of volatile components in water pollution, as a dimethyl disulphide or dimethyl diselenide or sulphur. Therefore, the results provide evidence that odor information can be recognized with around 86% efficiency, detecting smells unwanted in the water and improving the quality control in bottled water factories. PMID:28825645

Can we estimate the cellular phone RF peak output power with a simple experiment?

NASA Astrophysics Data System (ADS)

Fioreze, Maycon; dos Santos Junior, Sauli; Goncalves Hönnicke, Marcelo

2016-07-01

Cellular phones are becoming increasingly useful tools for students. Since cell phones operate in the microwave bandwidth, they can be used to motivate students to demonstrate and better understand the properties of electromagnetic waves. However, since these waves operate at higher frequencies (L-band, from 800 MHz to 2 GHz) it is not simple to detect them. Usually, expensive real-time high frequency oscilloscopes are required. Indirect measurements are also possible through heat-based and diode-detector-based radio-frequency (RF) power sensors. Another didactic and intuitive way is to explore a simple and inexpensive detection system, based on the interference effect caused in the electronic circuit of TV and PC soundspeakers, and to try to investigate different properties of the cell phones’ RF electromagnetic waves, such as its power and modulated frequency. This manuscript proposes a trial to quantify these measurements, based on a simple Friis equation model and the time constant of the circuit used in the detection system, in order to show it didactically to the students and even allow them also to explore such a simple detection system at home.

Wavefront detection method of a single-sensor based adaptive optics system.

PubMed

Wang, Chongchong; Hu, Lifa; Xu, Huanyu; Wang, Yukun; Li, Dayu; Wang, Shaoxin; Mu, Quanquan; Yang, Chengliang; Cao, Zhaoliang; Lu, Xinghai; Xuan, Li

2015-08-10

In adaptive optics system (AOS) for optical telescopes, the reported wavefront sensing strategy consists of two parts: a specific sensor for tip-tilt (TT) detection and another wavefront sensor for other distortions detection. Thus, a part of incident light has to be used for TT detection, which decreases the light energy used by wavefront sensor and eventually reduces the precision of wavefront correction. In this paper, a single Shack-Hartmann wavefront sensor based wavefront measurement method is presented for both large amplitude TT and other distortions' measurement. Experiments were performed for testing the presented wavefront method and validating the wavefront detection and correction ability of the single-sensor based AOS. With adaptive correction, the root-mean-square of residual TT was less than 0.2 λ, and a clear image was obtained in the lab. Equipped on a 1.23-meter optical telescope, the binary stars with angle distance of 0.6″ were clearly resolved using the AOS. This wavefront measurement method removes the separate TT sensor, which not only simplifies the AOS but also saves light energy for subsequent wavefront sensing and imaging, and eventually improves the detection and imaging capability of the AOS.

Temporal Data-Driven Sleep Scheduling and Spatial Data-Driven Anomaly Detection for Clustered Wireless Sensor Networks

PubMed Central

Li, Gang; He, Bin; Huang, Hongwei; Tang, Limin

2016-01-01

The spatial–temporal correlation is an important feature of sensor data in wireless sensor networks (WSNs). Most of the existing works based on the spatial–temporal correlation can be divided into two parts: redundancy reduction and anomaly detection. These two parts are pursued separately in existing works. In this work, the combination of temporal data-driven sleep scheduling (TDSS) and spatial data-driven anomaly detection is proposed, where TDSS can reduce data redundancy. The TDSS model is inspired by transmission control protocol (TCP) congestion control. Based on long and linear cluster structure in the tunnel monitoring system, cooperative TDSS and spatial data-driven anomaly detection are then proposed. To realize synchronous acquisition in the same ring for analyzing the situation of every ring, TDSS is implemented in a cooperative way in the cluster. To keep the precision of sensor data, spatial data-driven anomaly detection based on the spatial correlation and Kriging method is realized to generate an anomaly indicator. The experiment results show that cooperative TDSS can realize non-uniform sensing effectively to reduce the energy consumption. In addition, spatial data-driven anomaly detection is quite significant for maintaining and improving the precision of sensor data. PMID:27690035

Bats Use Magnetite to Detect the Earth's Magnetic Field

PubMed Central

Holland, Richard A.; Kirschvink, Joseph L.; Doak, Thomas G.; Wikelski, Martin

2008-01-01

While the role of magnetic cues for compass orientation has been confirmed in numerous animals, the mechanism of detection is still debated. Two hypotheses have been proposed, one based on a light dependent mechanism, apparently used by birds and another based on a “compass organelle” containing the iron oxide particles magnetite (Fe3O4). Bats have recently been shown to use magnetic cues for compass orientation but the method by which they detect the Earth's magnetic field remains unknown. Here we use the classic “Kalmijn-Blakemore” pulse re-magnetization experiment, whereby the polarity of cellular magnetite is reversed. The results demonstrate that the big brown bat Eptesicus fuscus uses single domain magnetite to detect the Earths magnetic field and the response indicates a polarity based receptor. Polarity detection is a prerequisite for the use of magnetite as a compass and suggests that big brown bats use magnetite to detect the magnetic field as a compass. Our results indicate the possibility that sensory cells in bats contain freely rotating magnetite particles, which appears not to be the case in birds. It is crucial that the ultrastructure of the magnetite containing magnetoreceptors is described for our understanding of magnetoreception in animals. PMID:18301753

Presentation Attack Detection for Iris Recognition System Using NIR Camera Sensor

PubMed Central

Nguyen, Dat Tien; Baek, Na Rae; Pham, Tuyen Danh; Park, Kang Ryoung

2018-01-01

Among biometric recognition systems such as fingerprint, finger-vein, or face, the iris recognition system has proven to be effective for achieving a high recognition accuracy and security level. However, several recent studies have indicated that an iris recognition system can be fooled by using presentation attack images that are recaptured using high-quality printed images or by contact lenses with printed iris patterns. As a result, this potential threat can reduce the security level of an iris recognition system. In this study, we propose a new presentation attack detection (PAD) method for an iris recognition system (iPAD) using a near infrared light (NIR) camera image. To detect presentation attack images, we first localized the iris region of the input iris image using circular edge detection (CED). Based on the result of iris localization, we extracted the image features using deep learning-based and handcrafted-based methods. The input iris images were then classified into real and presentation attack categories using support vector machines (SVM). Through extensive experiments with two public datasets, we show that our proposed method effectively solves the iris recognition presentation attack detection problem and produces detection accuracy superior to previous studies. PMID:29695113

Automatic event detection in low SNR microseismic signals based on multi-scale permutation entropy and a support vector machine

NASA Astrophysics Data System (ADS)

Jia, Rui-Sheng; Sun, Hong-Mei; Peng, Yan-Jun; Liang, Yong-Quan; Lu, Xin-Ming

2017-07-01

Microseismic monitoring is an effective means for providing early warning of rock or coal dynamical disasters, and its first step is microseismic event detection, although low SNR microseismic signals often cannot effectively be detected by routine methods. To solve this problem, this paper presents permutation entropy and a support vector machine to detect low SNR microseismic events. First, an extraction method of signal features based on multi-scale permutation entropy is proposed by studying the influence of the scale factor on the signal permutation entropy. Second, the detection model of low SNR microseismic events based on the least squares support vector machine is built by performing a multi-scale permutation entropy calculation for the collected vibration signals, constructing a feature vector set of signals. Finally, a comparative analysis of the microseismic events and noise signals in the experiment proves that the different characteristics of the two can be fully expressed by using multi-scale permutation entropy. The detection model of microseismic events combined with the support vector machine, which has the features of high classification accuracy and fast real-time algorithms, can meet the requirements of online, real-time extractions of microseismic events.

Bats use magnetite to detect the earth's magnetic field.

PubMed

Holland, Richard A; Kirschvink, Joseph L; Doak, Thomas G; Wikelski, Martin

2008-02-27

While the role of magnetic cues for compass orientation has been confirmed in numerous animals, the mechanism of detection is still debated. Two hypotheses have been proposed, one based on a light dependent mechanism, apparently used by birds and another based on a "compass organelle" containing the iron oxide particles magnetite (Fe(3)O(4)). Bats have recently been shown to use magnetic cues for compass orientation but the method by which they detect the Earth's magnetic field remains unknown. Here we use the classic "Kalmijn-Blakemore" pulse re-magnetization experiment, whereby the polarity of cellular magnetite is reversed. The results demonstrate that the big brown bat Eptesicus fuscus uses single domain magnetite to detect the Earths magnetic field and the response indicates a polarity based receptor. Polarity detection is a prerequisite for the use of magnetite as a compass and suggests that big brown bats use magnetite to detect the magnetic field as a compass. Our results indicate the possibility that sensory cells in bats contain freely rotating magnetite particles, which appears not to be the case in birds. It is crucial that the ultrastructure of the magnetite containing magnetoreceptors is described for our understanding of magnetoreception in animals.

Presentation Attack Detection for Iris Recognition System Using NIR Camera Sensor.

PubMed

Nguyen, Dat Tien; Baek, Na Rae; Pham, Tuyen Danh; Park, Kang Ryoung

2018-04-24

Among biometric recognition systems such as fingerprint, finger-vein, or face, the iris recognition system has proven to be effective for achieving a high recognition accuracy and security level. However, several recent studies have indicated that an iris recognition system can be fooled by using presentation attack images that are recaptured using high-quality printed images or by contact lenses with printed iris patterns. As a result, this potential threat can reduce the security level of an iris recognition system. In this study, we propose a new presentation attack detection (PAD) method for an iris recognition system (iPAD) using a near infrared light (NIR) camera image. To detect presentation attack images, we first localized the iris region of the input iris image using circular edge detection (CED). Based on the result of iris localization, we extracted the image features using deep learning-based and handcrafted-based methods. The input iris images were then classified into real and presentation attack categories using support vector machines (SVM). Through extensive experiments with two public datasets, we show that our proposed method effectively solves the iris recognition presentation attack detection problem and produces detection accuracy superior to previous studies.

Detecting communities in large networks

NASA Astrophysics Data System (ADS)

Capocci, A.; Servedio, V. D. P.; Caldarelli, G.; Colaiori, F.

2005-07-01

We develop an algorithm to detect community structure in complex networks. The algorithm is based on spectral methods and takes into account weights and link orientation. Since the method detects efficiently clustered nodes in large networks even when these are not sharply partitioned, it turns to be specially suitable for the analysis of social and information networks. We test the algorithm on a large-scale data-set from a psychological experiment of word association. In this case, it proves to be successful both in clustering words, and in uncovering mental association patterns.

Reversed-phase high-performance liquid chromatography of sulfur mustard in water

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

Raghuveeran, C.D.; Malhotra, R.C.; Dangi, R.S.

1993-01-01

A reversed-phase high-performance liquid chromatography method for the detection and quantitation of sulfur mustard (HD) in water is described with detection at 200 nm. The detection based on the solubility of HD in water revealed that extremely low quantities of HD (4 to 5 mg/L) only are soluble. Experience shows that water is still the medium of choice for the analysis of HD in water and aqueous effluents in spite of the minor handicap of its half-life of ca. 4 minutes, which only calls for speedy analysis.

Clone tag detection in distributed RFID systems.

PubMed

Kamaludin, Hazalila; Mahdin, Hairulnizam; Abawajy, Jemal H

2018-01-01

Although Radio Frequency Identification (RFID) is poised to displace barcodes, security vulnerabilities pose serious challenges for global adoption of the RFID technology. Specifically, RFID tags are prone to basic cloning and counterfeiting security attacks. A successful cloning of the RFID tags in many commercial applications can lead to many serious problems such as financial losses, brand damage, safety and health of the public. With many industries such as pharmaceutical and businesses deploying RFID technology with a variety of products, it is important to tackle RFID tag cloning problem and improve the resistance of the RFID systems. To this end, we propose an approach for detecting cloned RFID tags in RFID systems with high detection accuracy and minimal overhead thus overcoming practical challenges in existing approaches. The proposed approach is based on consistency of dual hash collisions and modified count-min sketch vector. We evaluated the proposed approach through extensive experiments and compared it with existing baseline approaches in terms of execution time and detection accuracy under varying RFID tag cloning ratio. The results of the experiments show that the proposed approach outperforms the baseline approaches in cloned RFID tag detection accuracy.

Secure Access Control and Large Scale Robust Representation for Online Multimedia Event Detection

PubMed Central

Liu, Changyu; Li, Huiling

2014-01-01

We developed an online multimedia event detection (MED) system. However, there are a secure access control issue and a large scale robust representation issue when we want to integrate traditional event detection algorithms into the online environment. For the first issue, we proposed a tree proxy-based and service-oriented access control (TPSAC) model based on the traditional role based access control model. Verification experiments were conducted on the CloudSim simulation platform, and the results showed that the TPSAC model is suitable for the access control of dynamic online environments. For the second issue, inspired by the object-bank scene descriptor, we proposed a 1000-object-bank (1000OBK) event descriptor. Feature vectors of the 1000OBK were extracted from response pyramids of 1000 generic object detectors which were trained on standard annotated image datasets, such as the ImageNet dataset. A spatial bag of words tiling approach was then adopted to encode these feature vectors for bridging the gap between the objects and events. Furthermore, we performed experiments in the context of event classification on the challenging TRECVID MED 2012 dataset, and the results showed that the robust 1000OBK event descriptor outperforms the state-of-the-art approaches. PMID:25147840

Evaluation of an Enhanced Bank of Kalman Filters for In-Flight Aircraft Engine Sensor Fault Diagnostics

NASA Technical Reports Server (NTRS)

Kobayashi, Takahisa; Simon, Donald L.

2004-01-01

In this paper, an approach for in-flight fault detection and isolation (FDI) of aircraft engine sensors based on a bank of Kalman filters is developed. This approach utilizes multiple Kalman filters, each of which is designed based on a specific fault hypothesis. When the propulsion system experiences a fault, only one Kalman filter with the correct hypothesis is able to maintain the nominal estimation performance. Based on this knowledge, the isolation of faults is achieved. Since the propulsion system may experience component and actuator faults as well, a sensor FDI system must be robust in terms of avoiding misclassifications of any anomalies. The proposed approach utilizes a bank of (m+1) Kalman filters where m is the number of sensors being monitored. One Kalman filter is used for the detection of component and actuator faults while each of the other m filters detects a fault in a specific sensor. With this setup, the overall robustness of the sensor FDI system to anomalies is enhanced. Moreover, numerous component fault events can be accounted for by the FDI system. The sensor FDI system is applied to a commercial aircraft engine simulation, and its performance is evaluated at multiple power settings at a cruise operating point using various fault scenarios.

Simultaneous detection of P300 and steady-state visually evoked potentials for hybrid brain-computer interface.

PubMed

Combaz, Adrien; Van Hulle, Marc M

2015-01-01

We study the feasibility of a hybrid Brain-Computer Interface (BCI) combining simultaneous visual oddball and Steady-State Visually Evoked Potential (SSVEP) paradigms, where both types of stimuli are superimposed on a computer screen. Potentially, such a combination could result in a system being able to operate faster than a purely P300-based BCI and encode more targets than a purely SSVEP-based BCI. We analyse the interactions between the brain responses of the two paradigms, and assess the possibility to detect simultaneously the brain activity evoked by both paradigms, in a series of 3 experiments where EEG data are analysed offline. Despite differences in the shape of the P300 response between pure oddball and hybrid condition, we observe that the classification accuracy of this P300 response is not affected by the SSVEP stimulation. We do not observe either any effect of the oddball stimulation on the power of the SSVEP response in the frequency of stimulation. Finally results from the last experiment show the possibility of detecting both types of brain responses simultaneously and suggest not only the feasibility of such hybrid BCI but also a gain over pure oddball- and pure SSVEP-based BCIs in terms of communication rate.

Abnormal global and local event detection in compressive sensing domain

NASA Astrophysics Data System (ADS)

Wang, Tian; Qiao, Meina; Chen, Jie; Wang, Chuanyun; Zhang, Wenjia; Snoussi, Hichem

2018-05-01

Abnormal event detection, also known as anomaly detection, is one challenging task in security video surveillance. It is important to develop effective and robust movement representation models for global and local abnormal event detection to fight against factors such as occlusion and illumination change. In this paper, a new algorithm is proposed. It can locate the abnormal events on one frame, and detect the global abnormal frame. The proposed algorithm employs a sparse measurement matrix designed to represent the movement feature based on optical flow efficiently. Then, the abnormal detection mission is constructed as a one-class classification task via merely learning from the training normal samples. Experiments demonstrate that our algorithm performs well on the benchmark abnormal detection datasets against state-of-the-art methods.

Direct detection of light dark matter and solar neutrinos via color center production in crystals

NASA Astrophysics Data System (ADS)

Budnik, Ranny; Cheshnovsky, Ori; Slone, Oren; Volansky, Tomer

2018-07-01

We propose a new low-threshold direct-detection concept for dark matter and for coherent nuclear scattering of solar neutrinos, based on the dissociation of atoms and subsequent creation of color center type defects within a lattice. The novelty in our approach lies in its ability to detect single defects in a macroscopic bulk of material. This class of experiments features ultra-low energy thresholds which allows for the probing of dark matter as light as O (10) MeV through nuclear scattering. Another feature of defect creation in crystals is directional information, which presents as a spectacular signal and a handle on background reduction in the form of daily modulation of the interaction rate. We discuss the envisioned setup and detection technique, as well as background reduction. We further calculate the expected rates for dark matter and solar neutrinos in two example crystals for which available data exists, demonstrating the prospective sensitivity of such experiments.

Study on the influence factors of camouflage target polarization detection

NASA Astrophysics Data System (ADS)

Huang, Yanhua; Chen, Lei; Li, Xia; Wu, Wenyuan

2016-10-01

The degree of linear polarization (DOLP) expressions at any polarizer direction (PD) was deduced based on the Stokes vector and Mueller matrix. The outdoors experiments were carried out to demonstrate the expressions. This paper mainly explored the DOLP-image-Contrast (DOLPC) between the target image and the background image, and the PD and RGB waveband that be considered two important influence factors were studied for camouflage target polarization detection. It was found that the DOLPC of target and background was obviously higher than intensity image. When setting the reference direction that polarizer was perpendicular to the incident face, the DOLP image of interval angle 60 degree between PD and reference direction had relatively high DOLPC, the interval angle 45 degree was the second, and the interval angle 35 degree was the third. The outdoors polarization detection experiment of controlling waveband showed that the DOLPC results was significantly different to use 650nm, 550nm and 450nm waveband, and the polarization detection performance by using 650nm band was an optimization method.

An impedance-based approach for detection and quantification of damage in cracked plates and loose bolts in bridge structures

NASA Astrophysics Data System (ADS)

Rabiei, Masoud; Sheldon, Jeremy; Palmer, Carl

2012-04-01

The applicability of Electro-Mechanical Impedance (EMI) approach to damage detection, localization and quantification in a mobile bridge structure is investigated in this paper. The developments in this paper focus on assessing the health of Armored Vehicle Launched Bridges (AVLBs). Specifically, two key failure mechanisms of the AVLB to be monitored were fatigue crack growth and damaged (loose) rivets (bolts) were identified. It was shown through experiment that bolt damage (defined here as different torque levels applied to bolts) can be detected, quantified and located using a network of lead zirconate titanate (PZT) transducers distributed on the structure. It was also shown that cracks of various sizes can be detected and quantified using the EMI approach. The experiments were performed on smaller laboratory specimens as well as full size bridge-like components that were built as part of this research. The effects of various parameters such as transducer type and size on the performance of the proposed health assessment approach were also investigated.

The Highest-Energy Photons Seen by the Energetic Gamma-Ray Experiment Telescope (EGRET) on the Compton Gamma Ray Observatory

NASA Technical Reports Server (NTRS)

Thompson, D. J.; Bertsch, D. L.; ONeal, R. H., Jr.

2005-01-01

During its nine-year lifetime, the Energetic Gamma Ray Experiment Telescope (EGBET) on the Compton Gamma Ray Observatory (CGRO) detected 1506 cosmic photons with measured energy E>10 GeV. Of this number, 187 are found within a 1 deg of sources that are listed in the Third EGRET Catalog and were included in determining the detection likelihood, flux, and spectra of those sources. In particular, five detected EGRET pulsars are found to have events above 10 GeV, and together they account for 37 events. A pulsar not included in the Third EGRET Catalog has 2 events, both with the same phase and in one peak of the lower-energy gamma-ray light-curve. Most of the remaining 1319 events appear to be diffuse Galactic and extragalactic radiation based on the similarity of the their spatial and energy distributions with the diffuse model and in the E>100, MeV emission. No significant time clustering which would suggest a burst was detected.

The analysis and detection of hypernasality based on a formant extraction algorithm

NASA Astrophysics Data System (ADS)

Qian, Jiahui; Fu, Fanglin; Liu, Xinyi; He, Ling; Yin, Heng; Zhang, Han

2017-08-01

In the clinical practice, the effective assessment of cleft palate speech disorders is important. For hypernasal speech, the resonance between nasal cavity and oral cavity causes an additional nasal formant. Thus, the formant frequency is a crucial cue for the judgment of hypernasality in cleft palate speech. Due to the existence of nasal formant, the peak merger occurs to the spectrum of nasal speech more often. However, the peak merger could not be solved by classical linear prediction coefficient root extraction method. In this paper, a method is proposed to detect the additional nasal formant in low-frequency region and obtain the formant frequency. The experiment results show that the proposed method could locate the nasal formant preferably. Moreover, the formants are regarded as the extraction features to proceed the detection of hypernasality. 436 phonemes, which are collected from Hospital of Stomatology, are used to carry out the experiment. The detection accuracy of hypernasality in cleft palate speech is 95.2%.

Enhancing patient freedom in rehabilitation robotics using gaze-based intention detection.

PubMed

Novak, Domen; Riener, Robert

2013-06-01

Several design strategies for rehabilitation robotics have aimed to improve patients' experiences using motivating and engaging virtual environments. This paper presents a new design strategy: enhancing patient freedom with a complex virtual environment that intelligently detects patients' intentions and supports the intended actions. A 'virtual kitchen' scenario has been developed in which many possible actions can be performed at any time, allowing patients to experiment and giving them more freedom. Remote eye tracking is used to detect the intended action and trigger appropriate support by a rehabilitation robot. This approach requires no additional equipment attached to the patient and has a calibration time of less than a minute. The system was tested on healthy subjects using the ARMin III arm rehabilitation robot. It was found to be technically feasible and usable by healthy subjects. However, the intention detection algorithm should be improved using better sensor fusion, and clinical tests with patients are needed to evaluate the system's usability and potential therapeutic benefits.

How Prevalent Is Object-Based Attention?

PubMed Central

Pilz, Karin S.; Roggeveen, Alexa B.; Creighton, Sarah E.; Bennett, Patrick J.; Sekuler, Allison B.

2012-01-01

Previous research suggests that visual attention can be allocated to locations in space (space-based attention) and to objects (object-based attention). The cueing effects associated with space-based attention tend to be large and are found consistently across experiments. Object-based attention effects, however, are small and found less consistently across experiments. In three experiments we address the possibility that variability in object-based attention effects across studies reflects low incidence of such effects at the level of individual subjects. Experiment 1 measured space-based and object-based cueing effects for horizontal and vertical rectangles in 60 subjects comparing commonly used target detection and discrimination tasks. In Experiment 2 we ran another 120 subjects in a target discrimination task in which rectangle orientation varied between subjects. Using parametric statistical methods, we found object-based effects only for horizontal rectangles. Bootstrapping methods were used to measure effects in individual subjects. Significant space-based cueing effects were found in nearly all subjects in both experiments, across tasks and rectangle orientations. However, only a small number of subjects exhibited significant object-based cueing effects. Experiment 3 measured only object-based attention effects using another common paradigm and again, using bootstrapping, we found only a small number of subjects that exhibited significant object-based cueing effects. Our results show that object-based effects are more prevalent for horizontal rectangles, which is in accordance with the theory that attention may be allocated more easily along the horizontal meridian. The fact that so few individuals exhibit a significant object-based cueing effect presumably is why previous studies of this effect might have yielded inconsistent results. The results from the current study highlight the importance of considering individual subject data in addition to commonly used statistical methods. PMID:22348018

Monocular precrash vehicle detection: features and classifiers.

PubMed

Sun, Zehang; Bebis, George; Miller, Ronald

2006-07-01

Robust and reliable vehicle detection from images acquired by a moving vehicle (i.e., on-road vehicle detection) is an important problem with applications to driver assistance systems and autonomous, self-guided vehicles. The focus of this work is on the issues of feature extraction and classification for rear-view vehicle detection. Specifically, by treating the problem of vehicle detection as a two-class classification problem, we have investigated several different feature extraction methods such as principal component analysis, wavelets, and Gabor filters. To evaluate the extracted features, we have experimented with two popular classifiers, neural networks and support vector machines (SVMs). Based on our evaluation results, we have developed an on-board real-time monocular vehicle detection system that is capable of acquiring grey-scale images, using Ford's proprietary low-light camera, achieving an average detection rate of 10 Hz. Our vehicle detection algorithm consists of two main steps: a multiscale driven hypothesis generation step and an appearance-based hypothesis verification step. During the hypothesis generation step, image locations where vehicles might be present are extracted. This step uses multiscale techniques not only to speed up detection, but also to improve system robustness. The appearance-based hypothesis verification step verifies the hypotheses using Gabor features and SVMs. The system has been tested in Ford's concept vehicle under different traffic conditions (e.g., structured highway, complex urban streets, and varying weather conditions), illustrating good performance.

Rapid Target Detection in High Resolution Remote Sensing Images Using Yolo Model

NASA Astrophysics Data System (ADS)

Wu, Z.; Chen, X.; Gao, Y.; Li, Y.

2018-04-01

Object detection in high resolution remote sensing images is a fundamental and challenging problem in the field of remote sensing imagery analysis for civil and military application due to the complex neighboring environments, which can cause the recognition algorithms to mistake irrelevant ground objects for target objects. Deep Convolution Neural Network(DCNN) is the hotspot in object detection for its powerful ability of feature extraction and has achieved state-of-the-art results in Computer Vision. Common pipeline of object detection based on DCNN consists of region proposal, CNN feature extraction, region classification and post processing. YOLO model frames object detection as a regression problem, using a single CNN predicts bounding boxes and class probabilities in an end-to-end way and make the predict faster. In this paper, a YOLO based model is used for object detection in high resolution sensing images. The experiments on NWPU VHR-10 dataset and our airport/airplane dataset gain from GoogleEarth show that, compare with the common pipeline, the proposed model speeds up the detection process and have good accuracy.

Detecting Spatial Patterns in Biological Array Experiments

PubMed Central

ROOT, DAVID E.; KELLEY, BRIAN P.; STOCKWELL, BRENT R.

2005-01-01

Chemical genetic screening and DNA and protein microarrays are among a number of increasingly important and widely used biological research tools that involve large numbers of parallel experiments arranged in a spatial array. It is often difficult to ensure that uniform experimental conditions are present throughout the entire array, and as a result, one often observes systematic spatially correlated errors, especially when array experiments are performed using robots. Here, the authors apply techniques based on the discrete Fourier transform to identify and quantify spatially correlated errors superimposed on a spatially random background. They demonstrate that these techniques are effective in identifying common spatially systematic errors in high-throughput 384-well microplate assay data. In addition, the authors employ a statistical test to allow for automatic detection of such errors. Software tools for using this approach are provided. PMID:14567791

Auditory sensitivity to spectral modulation phase reversal as a function of modulation depth

PubMed Central

Grose, John

2018-01-01

The present study evaluated auditory sensitivity to spectral modulation by determining the modulation depth required to detect modulation phase reversal. This approach may be preferable to spectral modulation detection with a spectrally flat standard, since listeners appear unable to perform the task based on the detection of temporal modulation. While phase reversal thresholds are often evaluated by holding modulation depth constant and adjusting modulation rate, holding rate constant and adjusting modulation depth supports rate-specific assessment of modulation processing. Stimuli were pink noise samples, filtered into seven octave-wide bands (0.125–8 kHz) and spectrally modulated in dB. Experiment 1 measured performance as a function of modulation depth to determine appropriate units for adaptive threshold estimation. Experiment 2 compared thresholds in dB for modulation detection with a flat standard and modulation phase reversal; results supported the idea that temporal cues were available at high rates for the former but not the latter. Experiment 3 evaluated spectral modulation phase reversal thresholds for modulation that was restricted to either one or two neighboring bands. Flanking bands of unmodulated noise had a larger detrimental effect on one-band than two-band targets. Thresholds for high-rate modulation improved with increasing carrier frequency up to 2 kHz, whereas low-rate modulation appeared more consistent across frequency, particularly in the two-band condition. Experiment 4 measured spectral weights for spectral modulation phase reversal detection and found higher weights for bands in the spectral center of the stimulus than for the lowest (0.125 kHz) or highest (8 kHz) band. Experiment 5 compared performance for highly practiced and relatively naïve listeners, and found weak evidence of a larger practice effect at high than low spectral modulation rates. These results provide preliminary data for a task that may provide a better estimate of sensitivity to spectral modulation than spectral modulation detection with a flat standard. PMID:29621338

Internalizing the threat of risk--a qualitative study about adolescents' experience living with screening-detected celiac disease 5 years after diagnosis.

PubMed

Nordyke, Katrina; Rosén, Anna; Emmelin, Maria; Ivarsson, Anneli

2014-06-11

Mass screening could identify those with unrecognized celiac disease (CD), but the experience of being detected through screening and living with screening-detected CD should be explored before considering this as acceptable intervention. For this study we invited screening-detected adolescents to describe their experience living with screening-detected CD five years after diagnosis with the aim to explore how their perceptions, practices, and beliefs evolved. Adolescents who were diagnosed through a population-based CD screening were invited to write narratives after being diagnosed. Of 153 adolescents who were eventually diagnosed through the screening, 91 wrote narratives one year after diagnosis and 72 five years after diagnosis. A qualitative content analysis resulted in a theme and categories that describe the experience living with screening-detected CD five years after diagnosis. The overall theme--Internalizing the threat of risk--illustrates that being detected through screening and the internalized threat of future health complications have impacted how these adolescents felt about the diagnosis, coped with the gluten-free diet (GFD), and thought about CD screening. This theme is supported by four categories: maintaining an imposed disease identity describes how they continued to define their diagnosis in relation to the screening. They also expressed moving from forced food changes to adapted diet routines by describing habits, routines, coping strategies, and the financial burden of the GFD. They had enduring beliefs of being spared negative consequences, however, even after five years, some doubted they had CD and worried that being detected and eating a GFD might not be beneficial, i.e. continuing to fear it is "all in vain". There was maintenance and evolution in the perceptions, practices, and beliefs of the adolescents after five years. Some have adjusted to the disease and adapted new habits and coping strategies to deal with the GFD, while others still doubt they have CD or that being detected was beneficial. The transition to adapting to the disease and GFD is ongoing, illustrating the importance of providing ongoing support for those with screening-detected CD as they adjust to this chronic disease and the GFD.

Probing Cherenkov and Scintillation Light Separation for Next-Generation Neutrino Detectors

NASA Astrophysics Data System (ADS)

Caravaca, J.; Descamps, F. B.; Land, B. J.; Orebi Gann, G. D.; Wallig, J.; Yeh, M.

2017-09-01

The ability to separate Cherenkov and scintillation signals in liquid scintillator detectors would enable outstanding background rejection for next-generation neutrino experiments. Reconstruction of directional information, ring imaging, and sub-Cherenkov threshold detection all have the potential to substantially improve particle and event identification. The Cherenkov-Scintillation Separation (CHESS) experiment uses an array of small, fast photomultipliers (PMTs) and state-of-the-art electronics to demonstrate the reconstruction of a Cherenkov ring in a scintillation medium based on photon hit times and detected charge. This setup has been used to characterize the ability to detect Cherenkov light in a range of target media. We show results with pure organic scintillator (LAB) and the prospects with scintillators with a secondary fluor (LAB/PPO). There are future plans to deploy the newly developed water-based liquid scintillator, a medium with a higher Cherenkov/Scintillation light yield ratio than conventional pure liquid scintillators, enhancing the visibility of the less abundant Cherenkov light in the presence of scintillation light. These results can inform the development of future large-scale detectors, such as the proposed Theia experiment, or other large detectors at underground laboratories such as the far-site of the new Long Baseline Neutrino Facility at the Sanford Underground Research Facility. CHESS detector calibrations and commissioning will be discussed, and the latest results will be presented.

Data-driven region-of-interest selection without inflating Type I error rate.

PubMed

Brooks, Joseph L; Zoumpoulaki, Alexia; Bowman, Howard

2017-01-01

In ERP and other large multidimensional neuroscience data sets, researchers often select regions of interest (ROIs) for analysis. The method of ROI selection can critically affect the conclusions of a study by causing the researcher to miss effects in the data or to detect spurious effects. In practice, to avoid inflating Type I error rate (i.e., false positives), ROIs are often based on a priori hypotheses or independent information. However, this can be insensitive to experiment-specific variations in effect location (e.g., latency shifts) reducing power to detect effects. Data-driven ROI selection, in contrast, is nonindependent and uses the data under analysis to determine ROI positions. Therefore, it has potential to select ROIs based on experiment-specific information and increase power for detecting effects. However, data-driven methods have been criticized because they can substantially inflate Type I error rate. Here, we demonstrate, using simulations of simple ERP experiments, that data-driven ROI selection can indeed be more powerful than a priori hypotheses or independent information. Furthermore, we show that data-driven ROI selection using the aggregate grand average from trials (AGAT), despite being based on the data at hand, can be safely used for ROI selection under many circumstances. However, when there is a noise difference between conditions, using the AGAT can inflate Type I error and should be avoided. We identify critical assumptions for use of the AGAT and provide a basis for researchers to use, and reviewers to assess, data-driven methods of ROI localization in ERP and other studies. © 2016 Society for Psychophysiological Research.

Insect detection and nitrogen management for irrigated potatoes using remote sensing from small unmanned aircraft systems

NASA Astrophysics Data System (ADS)

Hunt, E. Raymond; Rondon, Silvia I.; Hamm, Philip B.; Turner, Robert W.; Bruce, Alan E.; Brungardt, Josh J.

2016-05-01

Remote sensing with small unmanned aircraft systems (sUAS) has potential applications in agriculture because low flight altitudes allow image acquisition at very high spatial resolution. We set up experiments at the Oregon State University Hermiston Agricultural Research and Extension Center with different platforms and sensors to assess advantages and disadvantages of sUAS for precision farming. In 2013, we conducted an experiment with 4 levels of N fertilizer, and followed the changes in the normalized difference vegetation index (NDVI) over time. In late June, there were no differences in chlorophyll content or leaf area index (LAI) among the 3 higher application rates. Consistent with the field data, only plots with the lowest rate of applied N were distinguished by low NDVI. In early August, N deficiency was determined by NDVI, but it was too late to mitigate losses in potato yield and quality. Populations of the Colorado potato beetle (CPB) may rapidly increase, devouring the shoots, thus early detection and treatment could prevent yield losses. In 2014, we conducted an experiment with 4 levels of CPB infestation. Over one day, damage from CPB in some plots increased from 0 to 19%. A visual ranking of damage was not correlated with the total number of CPB or treatment. Plot-scale vegetation indices were not correlated with damage, although the damaged area determined by object-based feature extraction was highly correlated. Methods based on object-based image analysis of sUAS data have potential for early detection and reduced cost.

Geophysical techniques in detection to river embankments - A case study: To locate sites of potential leaks using surface-wave and electrical methods

USGS Publications Warehouse

Chen, C.; Liu, J.; Xu, S.; Xia, J.; ,

2004-01-01

Geophysical technologies are very effective in environmental, engineering and groundwater applications. Parameters of delineating nature of near-surface materials such as compressional-wave velocity, shear-wave velocity can be obtained using shallow seismic methods. Electric methods are primary approaches for investigating groundwater and detecting leakage. Both of methods are applied to detect embankment in hope of obtaining evidences of the strength and moisture inside the body. A technological experiment has done for detecting and discovering the hidden troubles in the embankment of Yangtze River, Songzi, Hubei, China in 2003. Surface-wave and DC multi-channel array resistivity sounding techniques were used to detect hidden trouble inside and under dike like pipe-seeps. This paper discusses the exploration strategy and the effect of geological characteristics. A practical approach of combining seismic and electric resistivity measurements was applied to locate potential pipe-seeps in embankment in the experiment. The method presents a potential leak factor based on the shear-wave velocity and the resistivity of the medium to evaluate anomalies. An anomaly found in a segment of embankment detected was verified, where occurred a pipe-seep during the 98' flooding.

Study on Miniaturized UHF Antennas for Partial Discharge Detection in High-Voltage Electrical Equipment.

PubMed

Liu, Jingcun; Zhang, Guogang; Dong, Jinlong; Wang, Jianhua

2015-11-20

Detecting partial discharge (PD) is an effective way to evaluate the condition of high-voltage electrical equipment insulation. The UHF detection method has attracted attention due to its high sensitivity, strong interference resistance, and ability to locate PDs. In this paper, a miniaturized equiangular spiral antenna (ESA) for UHF detection that uses a printed circuit board is proposed. I-shaped, L-shaped, and C-shaped microstrip baluns were designed to match the impedance between the ESA and coaxial cable and were verified by a vector network analyzer. For comparison, three other types of UHF antenna were also designed: A microstrip patch antenna, a microstrip slot antenna, and a printed dipole antenna. Their antenna factors were calibrated in a uniform electric field of different frequencies modulated in a gigahertz transverse electromagnetic cell. We performed comparison experiments on PD signal detection using an artificial defect model based on the international IEC 60270 standard. We also conducted time-delay test experiments on the ESA sensor to locate a PD source. It was found that the proposed ESA sensor meets PD signal detection requirements. The sensor's compact size makes it suitable for internal installation in high-voltage electrical equipment.

Study on Miniaturized UHF Antennas for Partial Discharge Detection in High-Voltage Electrical Equipment

PubMed Central

Liu, Jingcun; Zhang, Guogang; Dong, Jinlong; Wang, Jianhua

2015-01-01

Detecting partial discharge (PD) is an effective way to evaluate the condition of high-voltage electrical equipment insulation. The UHF detection method has attracted attention due to its high sensitivity, strong interference resistance, and ability to locate PDs. In this paper, a miniaturized equiangular spiral antenna (ESA) for UHF detection that uses a printed circuit board is proposed. I-shaped, L-shaped, and C-shaped microstrip baluns were designed to match the impedance between the ESA and coaxial cable and were verified by a vector network analyzer. For comparison, three other types of UHF antenna were also designed: A microstrip patch antenna, a microstrip slot antenna, and a printed dipole antenna. Their antenna factors were calibrated in a uniform electric field of different frequencies modulated in a gigahertz transverse electromagnetic cell. We performed comparison experiments on PD signal detection using an artificial defect model based on the international IEC 60270 standard. We also conducted time-delay test experiments on the ESA sensor to locate a PD source. It was found that the proposed ESA sensor meets PD signal detection requirements. The sensor’s compact size makes it suitable for internal installation in high-voltage electrical equipment. PMID:26610506

A novel approach to simulate chest wall micro-motion for bio-radar life detection purpose

NASA Astrophysics Data System (ADS)

An, Qiang; Li, Zhao; Liang, Fulai; Chen, Fuming; Wang, Jianqi

2016-10-01

Volunteers are often recruited to serve as the detection targets during the research process of bio-radar life detection technology, in which the experiment results are highly susceptible to the physical status of different individuals (shape, posture, etc.). In order to objectively evaluate the radar system performance and life detection algorithms, a standard detection target is urgently needed. The paper first proposed a parameter quantitatively controllable system to simulate the chest wall micro-motion caused mainly by breathing and heart beating. Then, the paper continued to analyze the material and size selection of the scattering body mounted on the simulation system from the perspective of back scattering energy. The computational electromagnetic method was employed to determine the exact scattering body. Finally, on-site experiments were carried out to verify the reliability of the simulation platform utilizing an IR UWB bioradar. Experimental result shows that the proposed system can simulate a real human target from three aspects: respiration frequency, amplitude and body surface scattering energy. Thus, it can be utilized as a substitute for a human target in radar based non-contact life detection research in various scenarios.

A bubble detection system for propellant filling pipeline

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

Wen, Wen; Zong, Guanghua; Bi, Shusheng

2014-06-15

This paper proposes a bubble detection system based on the ultrasound transmission method, mainly for probing high-speed bubbles in the satellite propellant filling pipeline. First, three common ultrasonic detection methods are compared and the ultrasound transmission method is used in this paper. Then, the ultrasound beam in a vertical pipe is investigated, suggesting that the width of the beam used for detection is usually smaller than the internal diameter of the pipe, which means that when bubbles move close to the pipe wall, they may escape from being detected. A special device is designed to solve this problem. It canmore » generate the spiral flow to force all the bubbles to ascend along the central line of the pipe. In the end, experiments are implemented to evaluate the performance of this system. Bubbles of five different sizes are generated and detected. Experiment results show that the sizes and quantity of bubbles can be estimated by this system. Also, the bubbles of different radii can be distinguished from each other. The numerical relationship between the ultrasound attenuation and the bubble radius is acquired and it can be utilized for estimating the unknown bubble size and measuring the total bubble volume.« less

Research on aircraft trailing vortex detection based on laser's multiplex information echo

NASA Astrophysics Data System (ADS)

Zhao, Nan-xiang; Wu, Yong-hua; Hu, Yi-hua; Lei, Wu-hu

2010-10-01

Airfoil trailing vortex is an important reason for the crash, and vortex detection is the basic premise for the civil aeronautics boards to make the flight measures and protect civil aviation's security. So a new method of aircraft trailing vortex detection based on laser's multiplex information echo has been proposed in this paper. According to the classical aerodynamics theories, the formation mechanism of the trailing vortex from the airfoil wingtip has been analyzed, and the vortex model of Boeing 737 in the taking-off phase has also been established on the FLUENT software platform. Combining with the unique morphological structure characteristics of trailing vortex, we have discussed the vortex's possible impact on the frequency, amplitude and phase information of laser echo, and expounded the principle of detecting vortex based on fusing this information variation of laser echo. In order to prove the feasibility of this detecting technique, the field experiment of detecting the vortex of civil Boeing 737 by laser has been carried on. The experimental result has shown that the aircraft vortex could be found really in the laser scanning area, and its diffusion characteristic has been very similar to the previous simulation result. Therefore, this vortex detection means based on laser's multiplex information echo was proved to be practicable relatively in this paper. It will provide the detection and identification of aircraft's trailing vortex a new way, and have massive research value and extensive application prospect as well.

An image-based automatic recognition method for the flowering stage of maize

NASA Astrophysics Data System (ADS)

Yu, Zhenghong; Zhou, Huabing; Li, Cuina

2018-03-01

In this paper, we proposed an image-based approach for automatic recognizing the flowering stage of maize. A modified HOG/SVM detection framework is first adopted to detect the ears of maize. Then, we use low-rank matrix recovery technology to precisely extract the ears at pixel level. At last, a new feature called color gradient histogram, as an indicator, is proposed to determine the flowering stage. Comparing experiment has been carried out to testify the validity of our method and the results indicate that our method can meet the demand for practical observation.

Design of the flame detector based on pyroelectric infrared sensor

NASA Astrophysics Data System (ADS)

Liu, Yang; Yu, Benhua; Dong, Lei; Li, Kai

2017-10-01

As a fire detection device, flame detector has the advantages of short reaction time and long distance. Based on pyroelectric infrared sensor working principle, the passive pyroelectric infrared alarm system is designed, which is mainly used for safety of tunnel to detect whether fire occurred or not. Modelling and Simulation of the pyroelectric Detector Using Labview. An attempt was made to obtain a simple test platform of a pyroelectric detector which would make an excellent basis for the analysis of its dynamic behaviour. After many experiments, This system has sensitive response, high anti-interference ability and safe and reliable performance.

A study of malware detection on smart mobile devices

NASA Astrophysics Data System (ADS)

Yu, Wei; Zhang, Hanlin; Xu, Guobin

2013-05-01

The growing in use of smart mobile devices for everyday applications has stimulated the spread of mobile malware, especially on popular mobile platforms. As a consequence, malware detection becomes ever more critical in sustaining the mobile market and providing a better user experience. In this paper, we review the existing malware and detection schemes. Using real-world malware samples with known signatures, we evaluate four popular commercial anti-virus tools and our data shows that these tools can achieve high detection accuracy. To deal with the new malware with unknown signatures, we study the anomaly based detection using decision tree algorithm. We evaluate the effectiveness of our detection scheme using malware and legitimate software samples. Our data shows that the detection scheme using decision tree can achieve a detection rate up to 90% and a false positive rate as low as 10%.

Accuracy comparison among different machine learning techniques for detecting malicious codes

NASA Astrophysics Data System (ADS)

Narang, Komal

2016-03-01

In this paper, a machine learning based model for malware detection is proposed. It can detect newly released malware i.e. zero day attack by analyzing operation codes on Android operating system. The accuracy of Naïve Bayes, Support Vector Machine (SVM) and Neural Network for detecting malicious code has been compared for the proposed model. In the experiment 400 benign files, 100 system files and 500 malicious files have been used to construct the model. The model yields the best accuracy 88.9% when neural network is used as classifier and achieved 95% and 82.8% accuracy for sensitivity and specificity respectively.

Initial experiences in the photoacoustic detection of melanoma metastases in resected lymph nodes

NASA Astrophysics Data System (ADS)

Grootendorst, D.; Jose, J.; Van der Jagt, P.; Van der Weg, W.; Nagel, K.; Wouters, M.; Van Boven, H.; Van Leeuwen, T. G.; Steenbergen, W.; Ruers, T.; Manohar, S.

2011-03-01

Accurate lymph node analysis is essential to determine the prognosis and treatment of patients suffering from melanoma. The initial results of a tomographic photoacoustic modality to detect melanoma metastases in resected lymph nodes are presented based on phantom models and a human lymph node. The results show melanoma metastases detection is feasible and the setup is capable of distinguishing absorbing structures down to 1 mm. In addition, the use of longer laser wavelengths could result in an image containing a higher contrast ratio. Future research shall be focused on using the melanin characteristics to improve contrast and detection possibilities.

Highly selective luminescent sensing of picric acid based on a water-stable europium metal-organic framework

NASA Astrophysics Data System (ADS)

Xia, Tifeng; Zhu, Fengliang; Cui, Yuanjing; Yang, Yu; Wang, Zhiyu; Qian, Guodong

2017-01-01

A water-stable metal-organic framework (MOF) EuNDC has been synthesized for selective detection of the well-known contaminant and toxicant picric acid (PA) in aqueous solution. Due to the photo-induced electron transfer and self-absorption mechanism, EuNDC displayed rapid, selective and sensitive detection of PA with a detection limit of 37.6 ppb. Recyclability experiments revealed that EuNDC retains its initial luminescent intensity and same quenching efficiency in each cycle, suggesting high photostability and reusability for long-term sensing applications. The excellent detection performance of EuNDC makes it a promising PA sensing material for practical applications.

Detecting temporal changes in acoustic scenes: The variable benefit of selective attention.

PubMed

Demany, Laurent; Bayle, Yann; Puginier, Emilie; Semal, Catherine

2017-09-01

Four experiments investigated change detection in acoustic scenes consisting of a sum of five amplitude-modulated pure tones. As the tones were about 0.7 octave apart and were amplitude-modulated with different frequencies (in the range 2-32 Hz), they were perceived as separate streams. Listeners had to detect a change in the frequency (experiments 1 and 2) or the shape (experiments 3 and 4) of the modulation of one of the five tones, in the presence of an informative cue orienting selective attention either before the scene (pre-cue) or after it (post-cue). The changes left intensity unchanged and were not detectable in the spectral (tonotopic) domain. Performance was much better with pre-cues than with post-cues. Thus, change deafness was manifest in the absence of an appropriate focusing of attention when the change occurred, even though the streams and the changes to be detected were acoustically very simple (in contrast to the conditions used in previous demonstrations of change deafness). In one case, the results were consistent with a model based on the assumption that change detection was possible if and only if attention was endogenously focused on a single tone. However, it was also found that changes resulting in a steepening of amplitude rises were to some extent able to draw attention exogenously. Change detection was not markedly facilitated when the change produced a discontinuity in the modulation domain, contrary to what could be expected from the perspective of predictive coding. Copyright © 2017 Elsevier B.V. All rights reserved.

Dynamic SERS nanosensor for neurotransmitter sensing near neurons.

PubMed

Lussier, Félix; Brulé, Thibault; Bourque, Marie-Josée; Ducrot, Charles; Trudeau, Louis-Éric; Masson, Jean-François

2017-12-04

Current electrophysiology and electrochemistry techniques have provided unprecedented understanding of neuronal activity. However, these techniques are suited to a small, albeit important, panel of neurotransmitters such as glutamate, GABA and dopamine, and these constitute only a subset of the broader range of neurotransmitters involved in brain chemistry. Surface-enhanced Raman scattering (SERS) provides a unique opportunity to detect a broader range of neurotransmitters in close proximity to neurons. Dynamic SERS (D-SERS) nanosensors based on patch-clamp-like nanopipettes decorated with gold nanoraspberries can be located accurately under a microscope using techniques analogous to those used in current electrophysiology or electrochemistry experiments. In this manuscript, we demonstrate that D-SERS can measure in a single experiment ATP, glutamate (glu), acetylcholine (ACh), GABA and dopamine (DA), among other neurotransmitters, with the potential for detecting a greater number of neurotransmitters. The SERS spectra of these neurotransmitters were identified with a barcoding data processing method and time series of the neurotransmitter levels were constructed. The D-SERS nanosensor was then located near cultured mouse dopaminergic neurons. The detection of neurotransmitters was performed in response to a series of K + depolarisations, and allowed the detection of elevated levels of both ATP and dopamine. Control experiments were also performed near glial cells, showing only very low basal detection neurotransmitter events. This paper demonstrates the potential of D-SERS to detect neurotransmitter secretion events near living neurons, but also constitutes a strong proof-of-concept for the broad application of SERS to the detection of secretion events by neurons or other cell types in order to study normal or pathological cell functions.

Increasing sensitivity of pulse EPR experiments using echo train detection schemes.

PubMed

Mentink-Vigier, F; Collauto, A; Feintuch, A; Kaminker, I; Tarle, V; Goldfarb, D

2013-11-01

Modern pulse EPR experiments are routinely used to study the structural features of paramagnetic centers. They are usually performed at low temperatures, where relaxation times are long and polarization is high, to achieve a sufficient Signal/Noise Ratio (SNR). However, when working with samples whose amount and/or concentration are limited, sensitivity becomes an issue and therefore measurements may require a significant accumulation time, up to 12h or more. As the detection scheme of practically all pulse EPR sequences is based on the integration of a spin echo--either primary, stimulated or refocused--a considerable increase in SNR can be obtained by replacing the single echo detection scheme by a train of echoes. All these echoes, generated by Carr-Purcell type sequences, are integrated and summed together to improve the SNR. This scheme is commonly used in NMR and here we demonstrate its applicability to a number of frequently used pulse EPR experiments: Echo-Detected EPR, Davies and Mims ENDOR (Electron-Nuclear Double Resonance), DEER (Electron-Electron Double Resonance|) and EDNMR (Electron-Electron Double Resonance (ELDOR)-Detected NMR), which were combined with a Carr-Purcell-Meiboom-Gill (CPMG) type detection scheme at W-band. By collecting the transient signal and integrating a number of refocused echoes, this detection scheme yielded a 1.6-5 folds SNR improvement, depending on the paramagnetic center and the pulse sequence applied. This improvement is achieved while keeping the experimental time constant and it does not introduce signal distortion. Copyright © 2013 Elsevier Inc. All rights reserved.

[superscript 1]H NMR Spectroscopy-Based Configurational Analysis of Mono- and Disaccharides and Detection of ß-Glucosidase Activity: An Undergraduate Biochemistry Laboratory

ERIC Educational Resources Information Center

Periyannan, Gopal R.; Lawrence, Barbara A.; Egan, Annie E.

2015-01-01

A [superscript 1]H NMR spectroscopy-based laboratory experiment explores mono- and disaccharide structural chemistry, and the enzyme-substrate specificity of glycosidic bond cleavage by ß-glucosidase towards cellobiose (ß-linked gluco-disaccharide) and maltose (a-linked gluco-disaccharide). Structural differences between cellobiose, maltose, and…

Image Mosaic Method Based on SIFT Features of Line Segment

PubMed Central

Zhu, Jun; Ren, Mingwu

2014-01-01

This paper proposes a novel image mosaic method based on SIFT (Scale Invariant Feature Transform) feature of line segment, aiming to resolve incident scaling, rotation, changes in lighting condition, and so on between two images in the panoramic image mosaic process. This method firstly uses Harris corner detection operator to detect key points. Secondly, it constructs directed line segments, describes them with SIFT feature, and matches those directed segments to acquire rough point matching. Finally, Ransac method is used to eliminate wrong pairs in order to accomplish image mosaic. The results from experiment based on four pairs of images show that our method has strong robustness for resolution, lighting, rotation, and scaling. PMID:24511326

Research on Dust Concentration Measurement Technique Based on the Theory of Ultrasonic Attenuation

NASA Astrophysics Data System (ADS)

Zhang, Yan; Lou, Wenzhong; Liao, Maohao

2018-03-01

In this paper, a method of characteristics dust concentration is proposed, which based on ultrasonic changes of MEMS piezoelectric ultrasonic transducer. The principle is that the intensity of the ultrasonic will produce attenuation with the propagation medium and propagation distance, the attenuation coefficient is affect by dust concentration. By detecting the changes of ultra acoustic in the dust, the concentration of the dust is calculate by the attenuation-concentration model, and the EACH theory model is based on this principle. The experimental results show that the MEMS piezoelectric ultrasonic transducer can be use for dust concentration of 100-900 g/m3 detection, the deviation between theory and experiments is smaller than 10.4%.

Adaptive Temporal Matched Filtering for Noise Suppression in Fiber Optic Distributed Acoustic Sensing.

PubMed

Ölçer, İbrahim; Öncü, Ahmet

2017-06-05

Distributed vibration sensing based on phase-sensitive optical time domain reflectometry ( ϕ -OTDR) is being widely used in several applications. However, one of the main challenges in coherent detection-based ϕ -OTDR systems is the fading noise, which impacts the detection performance. In addition, typical signal averaging and differentiating techniques are not suitable for detecting high frequency events. This paper presents a new approach for reducing the effect of fading noise in fiber optic distributed acoustic vibration sensing systems without any impact on the frequency response of the detection system. The method is based on temporal adaptive processing of ϕ -OTDR signals. The fundamental theory underlying the algorithm, which is based on signal-to-noise ratio (SNR) maximization, is presented, and the efficacy of our algorithm is demonstrated with laboratory experiments and field tests. With the proposed digital processing technique, the results show that more than 10 dB of SNR values can be achieved without any reduction in the system bandwidth and without using additional optical amplifier stages in the hardware. We believe that our proposed adaptive processing approach can be effectively used to develop fiber optic-based distributed acoustic vibration sensing systems.

Adaptive Temporal Matched Filtering for Noise Suppression in Fiber Optic Distributed Acoustic Sensing

PubMed Central

Ölçer, İbrahim; Öncü, Ahmet

2017-01-01

Distributed vibration sensing based on phase-sensitive optical time domain reflectometry (ϕ-OTDR) is being widely used in several applications. However, one of the main challenges in coherent detection-based ϕ-OTDR systems is the fading noise, which impacts the detection performance. In addition, typical signal averaging and differentiating techniques are not suitable for detecting high frequency events. This paper presents a new approach for reducing the effect of fading noise in fiber optic distributed acoustic vibration sensing systems without any impact on the frequency response of the detection system. The method is based on temporal adaptive processing of ϕ-OTDR signals. The fundamental theory underlying the algorithm, which is based on signal-to-noise ratio (SNR) maximization, is presented, and the efficacy of our algorithm is demonstrated with laboratory experiments and field tests. With the proposed digital processing technique, the results show that more than 10 dB of SNR values can be achieved without any reduction in the system bandwidth and without using additional optical amplifier stages in the hardware. We believe that our proposed adaptive processing approach can be effectively used to develop fiber optic-based distributed acoustic vibration sensing systems. PMID:28587240

Robot learning and error correction

NASA Technical Reports Server (NTRS)

Friedman, L.

1977-01-01

A model of robot learning is described that associates previously unknown perceptions with the sensed known consequences of robot actions. For these actions, both the categories of outcomes and the corresponding sensory patterns are incorporated in a knowledge base by the system designer. Thus the robot is able to predict the outcome of an action and compare the expectation with the experience. New knowledge about what to expect in the world may then be incorporated by the robot in a pre-existing structure whether it detects accordance or discrepancy between a predicted consequence and experience. Errors committed during plan execution are detected by the same type of comparison process and learning may be applied to avoiding the errors.

Dark matter repulsion could thwart direct detection

DOE PAGES

Davoudiasl, Hooman

2017-11-20

We consider a feeble repulsive interaction between ordinary matter and dark matter, with a range similar to or larger than the size of the Earth. Dark matter can thus be repelled from the Earth, leading to null results in direct detection experiments, regardless of the strength of the short-distance interactions of dark matter with atoms. Generically, such a repulsive force would not allow trapping of dark matter inside astronomical bodies. In this scenario, accelerator-based experiments may furnish the only robust signals of asymmetric dark matter models, which typically lack indirect signals from self-annihilation. Finally, some of the variants of ourmore » hypothesis are also briefly discussed.« less

Dark matter repulsion could thwart direct detection

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

Davoudiasl, Hooman

We consider a feeble repulsive interaction between ordinary matter and dark matter, with a range similar to or larger than the size of the Earth. Dark matter can thus be repelled from the Earth, leading to null results in direct detection experiments, regardless of the strength of the short-distance interactions of dark matter with atoms. Generically, such a repulsive force would not allow trapping of dark matter inside astronomical bodies. In this scenario, accelerator-based experiments may furnish the only robust signals of asymmetric dark matter models, which typically lack indirect signals from self-annihilation. Finally, some of the variants of ourmore » hypothesis are also briefly discussed.« less

Immunity-Based Aircraft Fault Detection System

NASA Technical Reports Server (NTRS)

Dasgupta, D.; KrishnaKumar, K.; Wong, D.; Berry, M.

2004-01-01

In the study reported in this paper, we have developed and applied an Artificial Immune System (AIS) algorithm for aircraft fault detection, as an extension to a previous work on intelligent flight control (IFC). Though the prior studies had established the benefits of IFC, one area of weakness that needed to be strengthened was the control dead band induced by commanding a failed surface. Since the IFC approach uses fault accommodation with no detection, the dead band, although it reduces over time due to learning, is present and causes degradation in handling qualities. If the failure can be identified, this dead band can be further A ed to ensure rapid fault accommodation and better handling qualities. The paper describes the application of an immunity-based approach that can detect a broad spectrum of known and unforeseen failures. The approach incorporates the knowledge of the normal operational behavior of the aircraft from sensory data, and probabilistically generates a set of pattern detectors that can detect any abnormalities (including faults) in the behavior pattern indicating unsafe in-flight operation. We developed a tool called MILD (Multi-level Immune Learning Detection) based on a real-valued negative selection algorithm that can generate a small number of specialized detectors (as signatures of known failure conditions) and a larger set of generalized detectors for unknown (or possible) fault conditions. Once the fault is detected and identified, an adaptive control system would use this detection information to stabilize the aircraft by utilizing available resources (control surfaces). We experimented with data sets collected under normal and various simulated failure conditions using a piloted motion-base simulation facility. The reported results are from a collection of test cases that reflect the performance of the proposed immunity-based fault detection algorithm.

PRIMORDIAL GRAVITATIONAL WAVE DETECTABILITY WITH DEEP SMALL-SKY COSMIC MICROWAVE BACKGROUND EXPERIMENTS

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

Farhang, M.; Bond, J. R.; Netterfield, C. B.

2013-07-01

We use the Bayesian estimation on direct T - Q - U cosmic microwave background (CMB) polarization maps to forecast errors on the tensor-to-scalar power ratio r, and hence on primordial gravitational waves, as a function of sky coverage f{sub sky}. This map-based likelihood filters the information in the pixel-pixel space into the optimal combinations needed for r detection for cut skies, providing enhanced information over a first-step linear separation into a combination of E, B, and mixed modes, and ignoring the latter. With current computational power and for typical resolutions appropriate for r detection, the large matrix inversions requiredmore » are accurate and fast. Our simulations explore two classes of experiments, with differing bolometric detector numbers, sensitivities, and observational strategies. One is motivated by a long duration balloon experiment like Spider, with pixel noise {proportional_to}{radical}(f{sub sky}) for a specified observing period. This analysis also applies to ground-based array experiments. We find that, in the absence of systematic effects and foregrounds, an experiment with Spider-like noise concentrating on f{sub sky} {approx} 0.02-0.2 could place a 2{sigma}{sub r} Almost-Equal-To 0.014 boundary ({approx}95% confidence level), which rises to 0.02 with an l-dependent foreground residual left over from an assumed efficient component separation. We contrast this with a Planck-like fixed instrumental noise as f{sub sky} varies, which gives a Galaxy-masked (f{sub sky} = 0.75) 2{sigma}{sub r} Almost-Equal-To 0.015, rising to Almost-Equal-To 0.05 with the foreground residuals. Using as the figure of merit the (marginalized) one-dimensional Shannon entropy of r, taken relative to the first 2003 WMAP CMB-only constraint, gives -2.7 bits from the 2012 WMAP9+ACT+SPT+LSS data, and forecasts of -6 bits from Spider (+ Planck); this compares with up to -11 bits for CMBPol, COrE, and PIXIE post-Planck satellites and -13 bits for a perfectly noiseless cosmic variance limited experiment. We thus confirm the wisdom of the current strategy for r detection of deeply probed patches covering the f{sub sky} minimum-error trough with balloon and ground experiments.« less

Atomic oxygen interaction with spacecraft materials: Relationship between orbital and ground-based testing for materials certification

NASA Technical Reports Server (NTRS)

Cross, Jon B.; Koontz, Steven L.; Lan, Esther H.

1993-01-01

The effects of atomic oxygen on boron nitride (BN), silicon nitride (Si3N4), Intelsat 6 solar cell interconnects, organic polymers, and MoS2 and WS2 dry lubricant, were studied in Low Earth Orbit (LEO) flight experiments and in a ground based simulation facility. Both the inflight and ground based experiments employed in situ electrical resistance measurements to detect penetration of atomic oxygen through materials and Electron Spectroscopy for Chemical Analysis (ESCA) analysis to measure chemical composition changes. Results are given. The ground based results on the materials studied to date show good qualitative correlation with the LEO flight results, thus validating the simulation fidelity of the ground based facility in terms of reproducing LEO flight results. In addition it was demonstrated that ground based simulation is capable of performing more detailed experiments than orbital exposures can presently perform. This allows the development of a fundamental understanding of the mechanisms involved in the LEO environment degradation of materials.

Forest fire autonomous decision system based on fuzzy logic

NASA Astrophysics Data System (ADS)

Lei, Z.; Lu, Jianhua

2010-11-01

The proposed system integrates GPS / pseudolite / IMU and thermal camera in order to autonomously process the graphs by identification, extraction, tracking of forest fire or hot spots. The airborne detection platform, the graph-based algorithms and the signal processing frame are analyzed detailed; especially the rules of the decision function are expressed in terms of fuzzy logic, which is an appropriate method to express imprecise knowledge. The membership function and weights of the rules are fixed through a supervised learning process. The perception system in this paper is based on a network of sensorial stations and central stations. The sensorial stations collect data including infrared and visual images and meteorological information. The central stations exchange data to perform distributed analysis. The experiment results show that working procedure of detection system is reasonable and can accurately output the detection alarm and the computation of infrared oscillations.

Non-contact FBG sensing based steam turbine rotor dynamic balance vibration detection system

NASA Astrophysics Data System (ADS)

Li, Tianliang; Tan, Yuegang; Cai, Lin

2015-10-01

This paper has proposed a non-contact vibration sensor based on fiber Bragg grating sensing, and applied to detect vibration of steam turbine rotor dynamic balance experimental platform. The principle of the sensor has been introduced, as well as the experimental analysis; performance of non-contact FBG vibration sensor has been analyzed in the experiment; in addition, turbine rotor dynamic vibration detection system based on eddy current displacement sensor and non-contact FBG vibration sensor have built; finally, compared with results of signals under analysis of the time domain and frequency domain. The analysis of experimental data contrast shows that: the vibration signal analysis of non-contact FBG vibration sensor is basically the same as the result of eddy current displacement sensor; it verified that the sensor can be used for non-contact measurement of steam turbine rotor dynamic balance vibration.

An Effective Electrical Resonance-Based Method to Detect Delamination in Thermal Barrier Coating

NASA Astrophysics Data System (ADS)

Kim, Jong Min; Park, Jae-Ha; Lee, Ho Girl; Kim, Hak-Joon; Song, Sung-Jin; Seok, Chang-Sung; Lee, Young-Ze

2017-12-01

This research proposes a simple yet highly sensitive method based on electrical resonance of an eddy-current probe to detect delamination of thermal barrier coating (TBC). This method can directly measure the mechanical characteristics of TBC compared to conventional ultrasonic testing and infrared thermography methods. The electrical resonance-based method can detect the delamination of TBC from the metallic bond coat by shifting the electrical impedance of eddy current testing (ECT) probe coupling with degraded TBC, and, due to this shift, the resonant frequencies near the peak impedance of ECT probe revealed high sensitivity to the delamination. In order to verify the performance of the proposed method, a simple experiment is performed with degraded TBC specimens by thermal cyclic exposure. Consequently, the delamination with growth of thermally grown oxide in a TBC system is experimentally identified. Additionally, the results are in good agreement with the results obtained from ultrasonic C-scanning.

An Effective Electrical Resonance-Based Method to Detect Delamination in Thermal Barrier Coating

NASA Astrophysics Data System (ADS)

Kim, Jong Min; Park, Jae-Ha; Lee, Ho Girl; Kim, Hak-Joon; Song, Sung-Jin; Seok, Chang-Sung; Lee, Young-Ze

2018-02-01

This research proposes a simple yet highly sensitive method based on electrical resonance of an eddy-current probe to detect delamination of thermal barrier coating (TBC). This method can directly measure the mechanical characteristics of TBC compared to conventional ultrasonic testing and infrared thermography methods. The electrical resonance-based method can detect the delamination of TBC from the metallic bond coat by shifting the electrical impedance of eddy current testing (ECT) probe coupling with degraded TBC, and, due to this shift, the resonant frequencies near the peak impedance of ECT probe revealed high sensitivity to the delamination. In order to verify the performance of the proposed method, a simple experiment is performed with degraded TBC specimens by thermal cyclic exposure. Consequently, the delamination with growth of thermally grown oxide in a TBC system is experimentally identified. Additionally, the results are in good agreement with the results obtained from ultrasonic C-scanning.

Immunomagnetic separation for MEMS-based biosensor of waterborne pathogens detection

NASA Astrophysics Data System (ADS)

Guo, Jianjiang; Zhang, Rongbiao

2017-07-01

Rapid isolation and detection of special pathogens present in environmental drinking water is critical for water quality monitoring. Numerical analysis and experimental investigations on immunomagnetic capture and isolation of waterborne pathogens with magnetic nanoparticles (MNPs) in microfluidic channel are performed. A finite-element COMSOL-based model is established to demonstrate the novel method of on-chip capturing pathogens using MNPs together with periodic pulse magnetic field. Simulation results determine the optimum magnetic pole current and switching frequency for magnetic separation. With the magnetic isolation experiment platform built up, as a pathogen example of Escherichia coli O157:H7, the performance of the method is experimentally verified. Both numerical and experimental results are found to agree reasonably well. Results of these investigations show that the capture efficiency of the immunomagnetic separation method is more than 92%, which could be encouraging for the design and optimization of MEMS-based biosensor of waterborne pathogen detection.

SWCD: a sliding window and self-regulated learning-based background updating method for change detection in videos

NASA Astrophysics Data System (ADS)

Işık, Şahin; Özkan, Kemal; Günal, Serkan; Gerek, Ömer Nezih

2018-03-01

Change detection with background subtraction process remains to be an unresolved issue and attracts research interest due to challenges encountered on static and dynamic scenes. The key challenge is about how to update dynamically changing backgrounds from frames with an adaptive and self-regulated feedback mechanism. In order to achieve this, we present an effective change detection algorithm for pixelwise changes. A sliding window approach combined with dynamic control of update parameters is introduced for updating background frames, which we called sliding window-based change detection. Comprehensive experiments on related test videos show that the integrated algorithm yields good objective and subjective performance by overcoming illumination variations, camera jitters, and intermittent object motions. It is argued that the obtained method makes a fair alternative in most types of foreground extraction scenarios; unlike case-specific methods, which normally fail for their nonconsidered scenarios.

Computer-aided detection of initial polyp candidates with level set-based adaptive convolution

NASA Astrophysics Data System (ADS)

Zhu, Hongbin; Duan, Chaijie; Liang, Zhengrong

2009-02-01

In order to eliminate or weaken the interference between different topological structures on the colon wall, adaptive and normalized convolution methods were used to compute the first and second order spatial derivatives of computed tomographic colonography images, which is the beginning of various geometric analyses. However, the performance of such methods greatly depends on the single-layer representation of the colon wall, which is called the starting layer (SL) in the following text. In this paper, we introduce a level set-based adaptive convolution (LSAC) method to compute the spatial derivatives, in which the level set method is employed to determine a more reasonable SL. The LSAC was applied to a computer-aided detection (CAD) scheme to detect the initial polyp candidates, and experiments showed that it benefits the CAD scheme in both the detection sensitivity and specificity as compared to our previous work.

MixDroid: A multi-features and multi-classifiers bagging system for Android malware detection

NASA Astrophysics Data System (ADS)

Huang, Weiqing; Hou, Erhang; Zheng, Liang; Feng, Weimiao

2018-05-01

In the past decade, Android platform has rapidly taken over the mobile market for its superior convenience and open source characteristics. However, with the popularity of Android, malwares targeting on Android devices are increasing rapidly, while the conventional rule-based and expert-experienced approaches are no longer able to handle such explosive growth. In this paper, combining with the theory of natural language processing and machine learning, we not only implement the basic feature extraction of permission application features, but also propose two innovative schemes of feature extraction: Dalvik opcode features and malicious code image, and implement an automatic Android malware detection system MixDroid which is based on multi-features and multi-classifiers. According to our experiment results on 20,000 Android applications, detection accuracy of MixDroid is 98.1%, which proves our schemes' effectiveness in Android malware detection.

The inescapable smart impact detection system (ISIS): An ubiquitous and personalized fall detector based on a distributed 'divide and conquer strategy'.

PubMed

Prado-Velasco, Manuel; del Rio-Cidoncha, Maria Gloria; Ortiz-Marin, Rafael

2008-01-01

Despite the intense research in the last decade with the aim of developing a reliable solution for fall detection in the elderly and other risk populations, it can be asserted that the diffusion of fall detectors in the geriatric practice is near null. This scenario is similar to the very scarce use of telemedicine in healthcare. The present work begins analyzing why fall detectors have not achieved to permeate the industry. That road is used to know the drawbacks of current devices and systems, besides to allow studying several important concepts underlying the principles of fall detection. A novel smart detection system based on that survey is finally briefly presented. The design of this device is founded on the experience and results obtained by an earlier device that was designed in the framework of the thesis of one of the authors.

Label propagation algorithm for community detection based on node importance and label influence

NASA Astrophysics Data System (ADS)

Zhang, Xian-Kun; Ren, Jing; Song, Chen; Jia, Jia; Zhang, Qian

2017-09-01

Recently, the detection of high-quality community has become a hot spot in the research of social network. Label propagation algorithm (LPA) has been widely concerned since it has the advantages of linear time complexity and is unnecessary to define objective function and the number of community in advance. However, LPA has the shortcomings of uncertainty and randomness in the label propagation process, which affects the accuracy and stability of the community. For large-scale social network, this paper proposes a novel label propagation algorithm for community detection based on node importance and label influence (LPA_NI). The experiments with comparative algorithms on real-world networks and synthetic networks have shown that LPA_NI can significantly improve the quality of community detection and shorten the iteration period. Also, it has better accuracy and stability in the case of similar complexity.

Small target detection based on difference accumulation and Gaussian curvature under complex conditions

NASA Astrophysics Data System (ADS)

Zhang, He; Niu, Yanxiong; Zhang, Hao

2017-12-01

Small target detection is a significant subject in infrared search and track and other photoelectric imaging systems. The small target is imaged under complex conditions, which contains clouds, horizon and bright part. In this paper, a novel small target detection method is proposed based on difference accumulation, clustering and Gaussian curvature. Difference accumulation varies from regions. Therefore, after obtaining difference accumulations, clustering is applied to determine whether the pixel belongs to the heterogeneous region, and eliminate heterogeneous region. Then Gaussian curvature is used to separate target from the homogeneous region. Experiments are conducted for verification, along with comparisons to several other methods. The experimental results demonstrate that our method has an advantage of 1-2 orders of magnitude on SCRG and BSF than others. Given that the false alarm rate is 1, the detection probability can be approximately 0.9 by using proposed method.

Atomic oxygen effects on boron nitride and silicon nitride: A comparison of ground based and space flight data

NASA Technical Reports Server (NTRS)

Cross, J. B.; Lan, E. H.; Smith, C. A.; Whatley, W. J.

1990-01-01

The effects of atomic oxygen on boron nitride (BN) and silicon nitride (Si3N4) were evaluated in a low Earth orbit (LEO) flight experiment and in a ground based simulation facility. In both the inflight and ground based experiments, these materials were coated on thin (approx. 250A) silver films, and the electrical resistance of the silver was measured in situ to detect any penetration of atomic oxygen through the BN and Si3N4 materials. In the presence of atomic oxygen, silver oxidizes to form silver oxide, which has a much higher electrical resistance than pure silver. Permeation of atomic oxygen through BN, as indicated by an increase in the electrical resistance of the silver underneath, was observed in both the inflight and ground based experiments. In contrast, no permeation of atomic oxygen through Si3N4 was observed in either the inflight or ground based experiments. The ground based results show good qualitative correlation with the LEO flight results, indicating that ground based facilities such as the one at Los Alamos National Lab can reproduce space flight data from LEO.

A comparison of ground-based and space flight data: Atomic oxygen reactions with boron nitride and silicon nitride

NASA Technical Reports Server (NTRS)

Cross, J. B.; Lan, E. H.; Smith, C. A.; Whatley, W. J.; Koontz, S. L.

1990-01-01

The effects of atomic oxygen on boron nitride (BN) and silicon nitride (Si3N4) have been studied in low Earth orbit (LEO) flight experiments and in a ground-based simulation facility at Los Alamos National Laboratory. Both the in-flight and ground-based experiments employed the materials coated over thin (approx 250 Angstrom) silver films whose electrical resistance was measured in situ to detect penetration of atomic oxygen through the BN and Si3N4 materials. In the presence of atomic oxygen, silver oxidizes to form silver oxide, which has a much higher electrical resistance than pure silver. Permeation of atomic oxygen through BN, as indicated by an increase in the electrical resistance of the silver underneath, was observed in both the in-flight and ground-based experiments. In contrast, no permeation of atomic oxygen through Si3N4 was observed in either the in-flight or ground-based experiments. The ground-based results show good qualitative correlation with the LEO flight results, thus validating the simulation fidelity of the ground-based facility in terms of reproducing LEO flight results.

SAR image change detection using watershed and spectral clustering

NASA Astrophysics Data System (ADS)

Niu, Ruican; Jiao, L. C.; Wang, Guiting; Feng, Jie

2011-12-01

A new method of change detection in SAR images based on spectral clustering is presented in this paper. Spectral clustering is employed to extract change information from a pair images acquired on the same geographical area at different time. Watershed transform is applied to initially segment the big image into non-overlapped local regions, leading to reduce the complexity. Experiments results and system analysis confirm the effectiveness of the proposed algorithm.

Label-free detection of circulating melanoma cells by in vivo photoacoustic flow cytometry

NASA Astrophysics Data System (ADS)

Wang, Xiaoling; Yang, Ping; Liu, Rongrong; Niu, Zhenyu; Suo, Yuanzhen; He, Hao; Gao, Wenyuan; Tang, Shuo; Wei, Xunbin

2016-03-01

Melanoma is a malignant tumor of melanocytes. Melanoma cells have high light absorption due to melanin highly contained in melanoma cells. This property is employed for the detection of circulating melanoma cell by in vivo photoacoustic flow cytometry (PAFC), which is based on photoacoustic effect. Compared to in vivo flow cytometry based on fluorescence, PAFC can employ high melanin content of melanoma cells as endogenous biomarkers to detect circulating melanoma cells in vivo. We have developed in vitro experiments to prove the ability of PAFC system of detecting photoacoustic signals from melanoma cells. For in vivo experiments, we have constructed a model of melanoma tumor bearing mice by inoculating highly metastatic murine melanoma cancer cells, B16F10 with subcutaneous injection. PA signals are detected in the blood vessels of mouse ears in vivo. The raw signal detected from target cells often contains some noise caused by electronic devices, such as background noise and thermal noise. We choose the Wavelet denoising method to effectively distinguish the target signal from background noise. Processing in time domain and frequency domain would be combined to analyze the signal after denoising. This algorithm contains time domain filter and frequency transformation. The frequency spectrum image of the signal contains distinctive features that can be used to analyze the property of target cells or particles. The processing methods have a great potential for analyzing signals accurately and rapidly. By counting circulating melanoma cells termly, we obtain the number variation of circulating melanoma cells as melanoma metastasized. Those results show that PAFC is a noninvasive and label-free method to detect melanoma metastases in blood or lymph circulation.

Modulation of Thalamic Somatosensory Neurons by Arousal and Attention

DTIC Science & Technology

1988-08-23

posterior lateral thalamus of the awake , behaving monkey that respond to somatosensory stimuli applied to the body surface. - to detect and quantfy...tested in pilot experiments to determine their feasibility for use in the awake monkey. These are discussed under the appropriate sections below. I I l~i...somatosensory responsiveness. This model is based on focal cortical suppression using MgSO 4 . Our previous experiments in the anesthetized and awake

Detecting primordial B-modes after Planck

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

Creminelli, Paolo; Nacir, Diana López; Simonović, Marko

2015-11-01

We update the forecasts for the measurement of the tensor-to-scalar ratio r for various ground-based experiments (AdvACT, CLASS, Keck/BICEP3, Simons Array, SPT-3G), balloons (EBEX 10k and Spider) and satellites (CMBPol, COrE and LiteBIRD), taking into account the recent Planck data on polarized dust and using a component separation method. The forecasts do not change significantly with respect to previous estimates when at least three frequencies are available, provided foregrounds can be accurately described by few parameters. We argue that a theoretically motivated goal for future experiments is r∼2×10{sup −3}, and that this is achievable if the noise is reduced tomore » ∼1 μK-arcmin and lensing is reduced to 10% in power. We study the constraints experiments will be able to put on the frequency and ℓ-dependence of the tensor signal as a check of its primordial origin. Futuristic ground-based and balloon experiments can have good constraints on these parameters, even for r∼2×10{sup −3}. For the same value of r, satellites will marginally be able to detect the presence of the recombination bump, the most distinctive feature of the primordial signal.« less

Detection and Inspection of Steel Bars in Reinforced Concrete Structures Using Active Infrared Thermography with Microwave Excitation and Eddy Current Sensors

PubMed Central

Szymanik, Barbara; Frankowski, Paweł Karol; Chady, Tomasz; John Chelliah, Cyril Robinson Azariah

2016-01-01

The purpose of this paper is to present a multi-sensor approach to the detection and inspection of steel bars in reinforced concrete structures. In connection with our past experience related to non-destructive testing of different materials, we propose using two potentially effective methods: active infrared thermography with microwave excitation and the eddy current technique. In this article active infrared thermography with microwave excitation is analyzed both by numerical modeling and experiments. This method, based on thermal imaging, due to its characteriatics should be considered as a preliminary method for the assessment of relatively shallowly located steel bar reinforcements. The eddy current technique, on the other hand, allows for more detailed evaluation and detection of deeply located rebars. In this paper a series of measurement results, together with the initial identification of certain features of steel reinforcement bars will be presented. PMID:26891305

Assessment of a simple obstacle detection device for the visually impaired.

PubMed

Lee, Cheng-Lung; Chen, Chih-Yung; Sung, Peng-Cheng; Lu, Shih-Yi

2014-07-01

A simple obstacle detection device, based upon an automobile parking sensor, was assessed as a mobility aid for the visually impaired. A questionnaire survey for mobility needs was performed at the start of this study. After the detector was developed, five blindfolded sighted and 15 visually impaired participants were invited to conduct travel experiments under three test conditions: (1) using a white cane only, (2) using the obstacle detector only and (3) using both devices. A post-experiment interview regarding the usefulness of the obstacle detector for the visually impaired participants was performed. The results showed that the obstacle detector could augment mobility performance with the white cane. The obstacle detection device should be used in conjunction with the white cane to achieve the best mobility speed and body protection. Copyright © 2013 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Detection and Inspection of Steel Bars in Reinforced Concrete Structures Using Active Infrared Thermography with Microwave Excitation and Eddy Current Sensors.

PubMed

Szymanik, Barbara; Frankowski, Paweł Karol; Chady, Tomasz; John Chelliah, Cyril Robinson Azariah

2016-02-16

The purpose of this paper is to present a multi-sensor approach to the detection and inspection of steel bars in reinforced concrete structures. In connection with our past experience related to non-destructive testing of different materials, we propose using two potentially effective methods: active infrared thermography with microwave excitation and the eddy current technique. In this article active infrared thermography with microwave excitation is analyzed both by numerical modeling and experiments. This method, based on thermal imaging, due to its characteriatics should be considered as a preliminary method for the assessment of relatively shallowly located steel bar reinforcements. The eddy current technique, on the other hand, allows for more detailed evaluation and detection of deeply located rebars. In this paper a series of measurement results, together with the initial identification of certain features of steel reinforcement bars will be presented.

Wind shear predictive detector technology study status

NASA Technical Reports Server (NTRS)

Gandolfi, C.

1990-01-01

Among the different elements to be investigated when considering the Wind Shear hazard, the Aeronautical Navigation Technical Service (STNA/3E), whose task is to participate in the development of new technologies and equipments, focused its effort on airborne and ground sensors for the detection of low-level wind shear. The first task, initiated in 1986, consists in the evaluation of three candidate techniques for forward-looking sensors: lidar, sodar, and radar. No development is presently foreseen for an infrared based air turbulence advance warning system although some flight experiments took place in the 70's. A Thomson infrared radiometer was then installed on an Air France Boeing 707 to evaluate its capability of detecting clear air turbulence. The conclusion showed that this technique was apparently able to detect cloud layers but that additional experiments were needed; on the other hand, the rarity of the phenomenon and the difficulty in operating on a commercial aircraft were also mentioned.

Rapid, sensitive, and selective fluorescent DNA detection using iron-based metal-organic framework nanorods: Synergies of the metal center and organic linker.

PubMed

Tian, Jingqi; Liu, Qian; Shi, Jinle; Hu, Jianming; Asiri, Abdullah M; Sun, Xuping; He, Yuquan

2015-09-15

Considerable recent attention has been paid to homogeneous fluorescent DNA detection with the use of nanostructures as a universal "quencher", but it still remains a great challenge to develop such nanosensor with the benefits of low cost, high speed, sensitivity, and selectivity. In this work, we report the use of iron-based metal-organic framework nanorods as a high-efficient sensing platform for fluorescent DNA detection. It only takes about 4 min to complete the whole "mix-and-detect" process with a low detection limit of 10 pM and a strong discrimination of single point mutation. Control experiments reveal the remarkable sensing behavior is a consequence of the synergies of the metal center and organic linker. This work elucidates how composition control of nanostructures can significantly impact their sensing properties, enabling new opportunities for the rational design of functional materials for analytical applications. Copyright © 2015 Elsevier B.V. All rights reserved.

Ship Detection Based on Multiple Features in Random Forest Model for Hyperspectral Images

NASA Astrophysics Data System (ADS)

Li, N.; Ding, L.; Zhao, H.; Shi, J.; Wang, D.; Gong, X.

2018-04-01

A novel method for detecting ships which aim to make full use of both the spatial and spectral information from hyperspectral images is proposed. Firstly, the band which is high signal-noise ratio in the range of near infrared or short-wave infrared spectrum, is used to segment land and sea on Otsu threshold segmentation method. Secondly, multiple features that include spectral and texture features are extracted from hyperspectral images. Principal components analysis (PCA) is used to extract spectral features, the Grey Level Co-occurrence Matrix (GLCM) is used to extract texture features. Finally, Random Forest (RF) model is introduced to detect ships based on the extracted features. To illustrate the effectiveness of the method, we carry out experiments over the EO-1 data by comparing single feature and different multiple features. Compared with the traditional single feature method and Support Vector Machine (SVM) model, the proposed method can stably achieve the target detection of ships under complex background and can effectively improve the detection accuracy of ships.

Analysis of Intrinsic Peptide Detectability via Integrated Label-Free and SRM-Based Absolute Quantitative Proteomics.

PubMed

Jarnuczak, Andrew F; Lee, Dave C H; Lawless, Craig; Holman, Stephen W; Eyers, Claire E; Hubbard, Simon J

2016-09-02

Quantitative mass spectrometry-based proteomics of complex biological samples remains challenging in part due to the variability and charge competition arising during electrospray ionization (ESI) of peptides and the subsequent transfer and detection of ions. These issues preclude direct quantification from signal intensity alone in the absence of a standard. A deeper understanding of the governing principles of peptide ionization and exploitation of the inherent ionization and detection parameters of individual peptides is thus of great value. Here, using the yeast proteome as a model system, we establish the concept of peptide F-factor as a measure of detectability, closely related to ionization efficiency. F-factor is calculated by normalizing peptide precursor ion intensity by absolute abundance of the parent protein. We investigated F-factor characteristics in different shotgun proteomics experiments, including across multiple ESI-based LC-MS platforms. We show that F-factors mirror previously observed physicochemical predictors as peptide detectability but demonstrate a nonlinear relationship between hydrophobicity and peptide detectability. Similarly, we use F-factors to show how peptide ion coelution adversely affects detectability and ionization. We suggest that F-factors have great utility for understanding peptide detectability and gas-phase ion chemistry in complex peptide mixtures, selection of surrogate peptides in targeted MS studies, and for calibration of peptide ion signal in label-free workflows. Data are available via ProteomeXchange with identifier PXD003472.

Studying generalised dark matter interactions with extended halo-independent methods

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

Kahlhoefer, Felix; Wild, Sebastian

2016-10-20

The interpretation of dark matter direct detection experiments is complicated by the fact that neither the astrophysical distribution of dark matter nor the properties of its particle physics interactions with nuclei are known in detail. To address both of these issues in a very general way we develop a new framework that combines the full formalism of non-relativistic effective interactions with state-of-the-art halo-independent methods. This approach makes it possible to analyse direct detection experiments for arbitrary dark matter interactions and quantify the goodness-of-fit independent of astrophysical uncertainties. We employ this method in order to demonstrate that the degeneracy between astrophysicalmore » uncertainties and particle physics unknowns is not complete. Certain models can be distinguished in a halo-independent way using a single ton-scale experiment based on liquid xenon, while other models are indistinguishable with a single experiment but can be separated using combined information from several target elements.« less

New Technologies Being Developed for the Thermophoretic Sampling of Smoke Particulates in Microgravity

NASA Technical Reports Server (NTRS)

Sheredy, William A.

2003-01-01

The Characterization of Smoke Particulate for Spacecraft Fire Detection, or Smoke, microgravity experiment is planned to be performed in the Microgravity Science Glovebox Facility on the International Space Station (ISS). This investigation, which is being developed by the NASA Glenn Research Center, ZIN Technologies, and the National Institute of Standards and Technologies (NIST), is based on the results and experience gained from the successful Comparative Soot Diagnostics experiment, which was flown as part of the USMP-3 (United States Microgravity Payload 3) mission on space shuttle flight STS-75. The Smoke experiment is designed to determine the particle size distributions of the smokes generated from a variety of overheated spacecraft materials and from microgravity fires. The objective is to provide the data that spacecraft designers need to properly design and implement fire detection in spacecraft. This investigation will also evaluate the performance of the smoke detectors currently in use aboard the space shuttle and ISS for the test materials in a microgravity environment.

[Force-based local navigation in robot-assisted implantation bed anlage in the lateral skull base. An experimental study].

PubMed

Plinkert, P K; Federspil, P A; Plinkert, B; Henrich, D

2002-03-01

Excellent precision, miss of retiring, reproducibility are main characteristics of robots in the operating theatre. Because of these facts their use for surgery in the lateral scull base is of great interest. In recent experiments we determined process parameters for robot assisted reaming of a cochlea implant bed and for a mastoidectomy. These results suggested that optimizing parameters for thrilling with the robot is needed. Therefore we implemented a suitable reaming curve from the geometrical data of the implant and a force controlled process control for robot assisted reaming at the lateral scull base. Experiments were performed with an industrial robot on animal and human scull base specimen. Because of online force detection and feedback of sensory data the reaming with the robot was controlled. With increasing force values above a defined limit feed rates were automatically regulated. Furthermore we were able to detect contact of the thrill to dura mater by analyzing the force values. With the new computer program the desired implant bed was exactly prepared. Our examinations showed a successful reaming of an implant bed in the lateral scull base with a robot. Because of a force controlled reaming process locale navigation is possible and enables careful thrilling with a robot.

A portable smart phone-based plasmonic nanosensor readout platform that measures transmitted light intensities of nanosubstrates using an ambient light sensor.

PubMed

Fu, Qiangqiang; Wu, Ze; Xu, Fangxiang; Li, Xiuqing; Yao, Cuize; Xu, Meng; Sheng, Liangrong; Yu, Shiting; Tang, Yong

2016-05-21

Plasmonic nanosensors may be used as tools for diagnostic testing in the field of medicine. However, quantification of plasmonic nanosensors often requires complex and bulky readout instruments. Here, we report the development of a portable smart phone-based plasmonic nanosensor readout platform (PNRP) for accurate quantification of plasmonic nanosensors. This device operates by transmitting excitation light from a LED through a nanosubstrate and measuring the intensity of the transmitted light using the ambient light sensor of a smart phone. The device is a cylinder with a diameter of 14 mm, a length of 38 mm, and a gross weight of 3.5 g. We demonstrated the utility of this smart phone-based PNRP by measuring two well-established plasmonic nanosensors with this system. In the first experiment, the device measured the morphology changes of triangular silver nanoprisms (AgNPRs) in an immunoassay for the detection of carcinoembryonic antigen (CEA). In the second experiment, the device measured the aggregation of gold nanoparticles (AuNPs) in an aptamer-based assay for the detection of adenosine triphosphate (ATP). The results from the smart phone-based PNRP were consistent with those from commercial spectrophotometers, demonstrating that the smart phone-based PNRP enables accurate quantification of plasmonic nanosensors.

Active Semi-Supervised Community Detection Based on Must-Link and Cannot-Link Constraints

PubMed Central

Cheng, Jianjun; Leng, Mingwei; Li, Longjie; Zhou, Hanhai; Chen, Xiaoyun

2014-01-01

Community structure detection is of great importance because it can help in discovering the relationship between the function and the topology structure of a network. Many community detection algorithms have been proposed, but how to incorporate the prior knowledge in the detection process remains a challenging problem. In this paper, we propose a semi-supervised community detection algorithm, which makes full utilization of the must-link and cannot-link constraints to guide the process of community detection and thereby extracts high-quality community structures from networks. To acquire the high-quality must-link and cannot-link constraints, we also propose a semi-supervised component generation algorithm based on active learning, which actively selects nodes with maximum utility for the proposed semi-supervised community detection algorithm step by step, and then generates the must-link and cannot-link constraints by accessing a noiseless oracle. Extensive experiments were carried out, and the experimental results show that the introduction of active learning into the problem of community detection makes a success. Our proposed method can extract high-quality community structures from networks, and significantly outperforms other comparison methods. PMID:25329660

Driver fatigue detection based on eye state.

PubMed

Lin, Lizong; Huang, Chao; Ni, Xiaopeng; Wang, Jiawen; Zhang, Hao; Li, Xiao; Qian, Zhiqin

2015-01-01

Nowadays, more and more traffic accidents occur because of driver fatigue. In order to reduce and prevent it, in this study, a calculation method using PERCLOS (percentage of eye closure time) parameter characteristics based on machine vision was developed. It determined whether a driver's eyes were in a fatigue state according to the PERCLOS value. The overall workflow solutions included face detection and tracking, detection and location of the human eye, human eye tracking, eye state recognition, and driver fatigue testing. The key aspects of the detection system incorporated the detection and location of human eyes and driver fatigue testing. The simplified method of measuring the PERCLOS value of the driver was to calculate the ratio of the eyes being open and closed with the total number of frames for a given period. If the eyes were closed more than the set threshold in the total number of frames, the system would alert the driver. Through many experiments, it was shown that besides the simple detection algorithm, the rapid computing speed, and the high detection and recognition accuracies of the system, the system was demonstrated to be in accord with the real-time requirements of a driver fatigue detection system.

Dangerous gas detection based on infrared video

NASA Astrophysics Data System (ADS)

Ding, Kang; Hong, Hanyu; Huang, Likun

2018-03-01

As the gas leak infrared imaging detection technology has significant advantages of high efficiency and remote imaging detection, in order to enhance the detail perception of observers and equivalently improve the detection limit, we propose a new type of gas leak infrared image detection method, which combines background difference methods and multi-frame interval difference method. Compared to the traditional frame methods, the multi-frame interval difference method we proposed can extract a more complete target image. By fusing the background difference image and the multi-frame interval difference image, we can accumulate the information of infrared target image of the gas leak in many aspect. The experiment demonstrate that the completeness of the gas leakage trace information is enhanced significantly, and the real-time detection effect can be achieved.

[Study of the Detecting System of CH4 and SO2 Based on Spectral Absorption Method and UV Fluorescence Method].

PubMed

Wang, Shu-tao; Wang, Zhi-fang; Liu, Ming-hua; Wei, Meng; Chen, Dong-ying; Wang, Xing-long

2016-01-01

According to the spectral absorption characteristics of polluting gases and fluorescence characteristics, a time-division multiplexing detection system is designed. Through this system we can detect Methane (CH4) and sulfur dioxide (SO2) by using spectral absorption method and the SO2 can be detected by using UV fluorescence method. The system consists of four parts: a combination of a light source which could be switched, the common optical path, the air chamber and the signal processing section. The spectral absorption characteristics and fluorescence characteristics are measured first. Then the experiment of detecting CH4 and SO2 through spectral absorption method and the experiment of detecting SO2 through UV fluorescence method are conducted, respectively. Through measuring characteristics of spectral absorption and fluorescence, we get excitation wavelengths of SO2 and CH4 measured by spectral absorption method at the absorption peak are 280 nm and 1.64 μm, respectively, and the optimal excitation wavelength of SO2 measured by UV fluorescence method is 220 nm. we acquire the linear relation between the concentration of CH4 and relative intensity and the linear relation between the concentration of SO2 and output voltage after conducting the experiment of spectral absorption method, and the linearity are 98.7%, 99.2% respectively. Through the experiment of UV fluorescence method we acquire that the relation between the concentration of SO2 and the voltage is linear, and the linearity is 99.5%. Research shows that the system is able to be applied to detect the polluted gas by absorption spectrum method and UV fluorescence method. Combing these two measurement methods decreases the costing and the volume, and this system can also be used to measure the other gases. Such system has a certain value of application.

Design of a novel noninvasive spectrometer for pesticide residues monitor

NASA Astrophysics Data System (ADS)

Ren, Zhong; Liu, Guodong; Huang, Zhen

2014-11-01

Although the gas or liquid chromatography had been widely used into pesticide residues monitoring, some drawbacks such as time-consuming, complicated operation and especially the destructivity for samples were existed. To overcome the limits of destructive detection methods, the noninvasive detection method based on spectroscopy was used to detect the pesticide residues in this paper. To overcome low resolution and light-efficiency due to the drawbacks of the classical plane and holography concave gratings, a novel noninvasive spectrometer for pesticide residues monitor (PRM) based on volume holography transmission (VHT) grating was designed. Meanwhile, a custom-built splitting light system for PRM based on the VHT grating was developed. In addition, the linear charge coupled device (CCD) with combined data acquisition (DAQ) card and the virtual-PRM based on LabVIEW were respectively used as the spectral acquisition hardware and software-platform. Experimental results showed that the spectral resolution of this spectrometer reached 2nm, and the VHT grating's diffraction efficiency was gotten via the simulation experiment.

Implementation of sobel method to detect the seed rubber plant leaves

NASA Astrophysics Data System (ADS)

Suyanto; Munte, J.

2018-03-01

This research was conducted to develop a system that can identify and recognize the type of rubber tree based on the pattern of leaves of the plant. The steps research are started with the identification of the image data acquisition, image processing, image edge detection and identification method template matching. Edge detection is using Sobel edge detection. Pattern recognition would detect image as input and compared with other images in a database called templates. Experiments carried out in one phase, identification of the leaf edge, using a rubber plant leaf image 14 are superior and 5 for each type of test images (clones) of the plant. From the experimental results obtained by the recognition rate of 91.79%.

Tapered Polymer Fiber Sensors for Reinforced Concrete Beam Vibration Detection.

PubMed

Luo, Dong; Ibrahim, Zainah; Ma, Jianxun; Ismail, Zubaidah; Iseley, David Thomas

2016-12-16

In this study, tapered polymer fiber sensors (TPFSs) have been employed to detect the vibration of a reinforced concrete beam (RC beam). The sensing principle was based on transmission modes theory. The natural frequency of an RC beam was theoretically analyzed. Experiments were carried out with sensors mounted on the surface or embedded in the RC beam. Vibration detection results agreed well with Kistler accelerometers. The experimental results found that both the accelerometer and TPFS detected the natural frequency function of a vibrated RC beam well. The mode shapes of the RC beam were also found by using the TPFSs. The proposed vibration detection method provides a cost-comparable solution for a structural health monitoring (SHM) system in civil engineering.

Tapered Polymer Fiber Sensors for Reinforced Concrete Beam Vibration Detection

PubMed Central

Luo, Dong; Ibrahim, Zainah; Ma, Jianxun; Ismail, Zubaidah; Iseley, David Thomas

2016-01-01

In this study, tapered polymer fiber sensors (TPFSs) have been employed to detect the vibration of a reinforced concrete beam (RC beam). The sensing principle was based on transmission modes theory. The natural frequency of an RC beam was theoretically analyzed. Experiments were carried out with sensors mounted on the surface or embedded in the RC beam. Vibration detection results agreed well with Kistler accelerometers. The experimental results found that both the accelerometer and TPFS detected the natural frequency function of a vibrated RC beam well. The mode shapes of the RC beam were also found by using the TPFSs. The proposed vibration detection method provides a cost-comparable solution for a structural health monitoring (SHM) system in civil engineering. PMID:27999245

Infrared small target detection with kernel Fukunaga Koontz transform

NASA Astrophysics Data System (ADS)

Liu, Rui-ming; Liu, Er-qi; Yang, Jie; Zhang, Tian-hao; Wang, Fang-lin

2007-09-01

The Fukunaga-Koontz transform (FKT) has been proposed for many years. It can be used to solve two-pattern classification problems successfully. However, there are few researchers who have definitely extended FKT to kernel FKT (KFKT). In this paper, we first complete this task. Then a method based on KFKT is developed to detect infrared small targets. KFKT is a supervised learning algorithm. How to construct training sets is very important. For automatically detecting targets, the synthetic target images and real background images are used to train KFKT. Because KFKT can represent the higher order statistical properties of images, we expect better detection performance of KFKT than that of FKT. The well-devised experiments verify that KFKT outperforms FKT in detecting infrared small targets.

Global-Context Based Salient Region Detection in Nature Images

NASA Astrophysics Data System (ADS)

Bao, Hong; Xu, De; Tang, Yingjun

Visually saliency detection provides an alternative methodology to image description in many applications such as adaptive content delivery and image retrieval. One of the main aims of visual attention in computer vision is to detect and segment the salient regions in an image. In this paper, we employ matrix decomposition to detect salient object in nature images. To efficiently eliminate high contrast noise regions in the background, we integrate global context information into saliency detection. Therefore, the most salient region can be easily selected as the one which is globally most isolated. The proposed approach intrinsically provides an alternative methodology to model attention with low implementation complexity. Experiments show that our approach achieves much better performance than that from the existing state-of-art methods.

Application of laser to nondestructive detection of fruit quality

NASA Astrophysics Data System (ADS)

Li, Jing; Xue, Long; Liu, Muhua; Li, Zhanlong; Yang, Yong

2008-12-01

In this study, a hyperspectral imaging system using a laser source was developed and two experiments were carried out. The first experiment was detection of pesticide residue on navel orange surface. We calculated the mean intensity of regions of interest to plot the curves between 629nm to 638nm. The analysis of the mean intensity curves showed that the mean intensity can be described by a characteristic Gaussian curve equation. The coefficients a in characteristic equations of 0%, 0.1% and 0.5% fenvalerate residue images were more than 2400, 1570-2400 and less than 1570, respectively. So we suggest using equation coefficient a to detect pesticide residue on navel orange surface. The second experiment was predicting firmness, sugar content and vitamin C content of kiwi fruit. The optimal wavelength range of the kiwi fruit firmness, sugar content, vitamin C content line regressing prediction model were 680-711nm, 674-708nm, 669-701nm. The correlation coefficients (R) of prediction models for firmness, sugar content and vitamin C content were 0.898, 0.932 and 0.918. The mean errors of validation results were 0.35×105Pa, 0.32%Brix and 7mg/100g. The experimental results indicate that a hyperspectral imaging system based on a laser source can detect fruit quality effectively.

SMOKE: Characterization of Smoke Particulate for Spacecraft Fire Detection

NASA Technical Reports Server (NTRS)

Urban, D. L.; Mulholland, G.; Yuan, Z. G.; Yang, J.; Cleary, T.

2001-01-01

'Smoke' is a flight definition investigation whose purpose is to characterize the smoke particulate from microgravity smoke sources to enable improved design of future space-craft smoke detectors. In the earliest missions (Mercury, Gemini and Apollo), the crew quarters were so cramped that it was considered reasonable that the astronauts would rapidly detect any fire. The Skylab module, however, included approximately 30 UV-sensing fire detectors. The Space Shuttle Orbiter has nine particle-ionization smoke detectors in the mid-deck and flight deck. The detectors for the US segments of the International Space Station (ISS) are laser-diode, forward-scattering, smoke detectors. Current plans for the ISS call for two detectors in the open area of the module, and detectors in racks that have cooling air-flow. Due to the complete absence of microgravity data, all three of these detector systems were designed based upon 1-g test data and experience. As planned mission durations and complexity increase and the volume of spacecraft increases, the need for and importance of effective, crew-independent, fire detection will grow significantly, necessitating more research into microgravity fire phenomena. In 1997 the Comparative Soot Diagnostics Experiment (CSD) flew in the Orbiter Middeck as a Glovebox payload. The CSD experiment was designed to produce small quantities of smoke from several sources to obtain particulate samples and to determine the response of the ISS and Orbiter smoke detectors to these sources. Marked differences in the performance of the detectors compared to their behavior in 1-g were observed. In extreme cases, the detector used in the orbiter was completely blind to easily visible smoke from sources that were readily detected in 1-g. It is hypothesized but as yet unverified that this performance difference was due to enhanced growth of liquid smoke droplets in low-g. These CSD results clearly demonstrate that spacecraft smoke detector design cannot be based on 1-g experience.

Suspicious Behavior Detection System for an Open Space Parking Based on Recognition of Human Elemental Actions

NASA Astrophysics Data System (ADS)

Inomata, Teppei; Kimura, Kouji; Hagiwara, Masafumi

Studies for video surveillance applications for preventing various crimes such as stealing and violence have become a hot topic. This paper proposes a new video surveillance system that can detect suspicious behaviors such as a car break-in and vandalization in an open space parking, and that is based on image processing. The proposed system has the following features: it 1)deals time series data flow, 2)recognizes “human elemental actions” using statistic features, and 3)detects suspicious behavior using Subspace method and AdaBoost. We conducted the experiments to test the performance of the proposed system using open space parking scenes. As a result, we obtained about 10.0% for false positive rate, and about 4.6% for false negative rate.

Protein-based nanobiosensor for direct detection of hydrogen sulfide

NASA Astrophysics Data System (ADS)

Omidi, Meisam; Amoabediny, Ghasem; Yazdian, Fatemeh; Habibi-Rezaei, M.

2015-01-01

The chemically modified cytochrome c from equine heart, EC (232-700-9), was immobilized onto gold nanoparticles in order to develop a specific biosensing system for monitoring hydrogen sulfide down to the micromolar level, by means of a localized surface plasmon resonance spectroscopy. The sensing mechanism is based on the cytochrome-c conformational changes in the presence of H2S which alter the dielectric properties of the gold nanoparticles and the surface plasmon resonance peak undergoes a redshift. According to the experiments, it is revealed that H2S can be detected at a concentration of 4.0 μ \\text{M} (1.3 \\text{ppb}) by the fabricated biosensor. This simple, quantitative and sensitive sensing platform provides a rapid and convenient detection for H2S at concentrations far below the hazardous limit.