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Sample records for accurate change detection

  1. Population variability complicates the accurate detection of climate change responses.

    PubMed

    McCain, Christy; Szewczyk, Tim; Bracy Knight, Kevin

    2016-06-01

    The rush to assess species' responses to anthropogenic climate change (CC) has underestimated the importance of interannual population variability (PV). Researchers assume sampling rigor alone will lead to an accurate detection of response regardless of the underlying population fluctuations of the species under consideration. Using population simulations across a realistic, empirically based gradient in PV, we show that moderate to high PV can lead to opposite and biased conclusions about CC responses. Between pre- and post-CC sampling bouts of modeled populations as in resurvey studies, there is: (i) A 50% probability of erroneously detecting the opposite trend in population abundance change and nearly zero probability of detecting no change. (ii) Across multiple years of sampling, it is nearly impossible to accurately detect any directional shift in population sizes with even moderate PV. (iii) There is up to 50% probability of detecting a population extirpation when the species is present, but in very low natural abundances. (iv) Under scenarios of moderate to high PV across a species' range or at the range edges, there is a bias toward erroneous detection of range shifts or contractions. Essentially, the frequency and magnitude of population peaks and troughs greatly impact the accuracy of our CC response measurements. Species with moderate to high PV (many small vertebrates, invertebrates, and annual plants) may be inaccurate 'canaries in the coal mine' for CC without pertinent demographic analyses and additional repeat sampling. Variation in PV may explain some idiosyncrasies in CC responses detected so far and urgently needs more careful consideration in design and analysis of CC responses.

  2. Flexible and accurate detection of genomic copy-number changes from aCGH.

    PubMed

    Rueda, Oscar M; Díaz-Uriarte, Ramón

    2007-06-01

    Genomic DNA copy-number alterations (CNAs) are associated with complex diseases, including cancer: CNAs are indeed related to tumoral grade, metastasis, and patient survival. CNAs discovered from array-based comparative genomic hybridization (aCGH) data have been instrumental in identifying disease-related genes and potential therapeutic targets. To be immediately useful in both clinical and basic research scenarios, aCGH data analysis requires accurate methods that do not impose unrealistic biological assumptions and that provide direct answers to the key question, "What is the probability that this gene/region has CNAs?" Current approaches fail, however, to meet these requirements. Here, we introduce reversible jump aCGH (RJaCGH), a new method for identifying CNAs from aCGH; we use a nonhomogeneous hidden Markov model fitted via reversible jump Markov chain Monte Carlo; and we incorporate model uncertainty through Bayesian model averaging. RJaCGH provides an estimate of the probability that a gene/region has CNAs while incorporating interprobe distance and the capability to analyze data on a chromosome or genome-wide basis. RJaCGH outperforms alternative methods, and the performance difference is even larger with noisy data and highly variable interprobe distance, both commonly found features in aCGH data. Furthermore, our probabilistic method allows us to identify minimal common regions of CNAs among samples and can be extended to incorporate expression data. In summary, we provide a rigorous statistical framework for locating genes and chromosomal regions with CNAs with potential applications to cancer and other complex human diseases.

  3. Ultrasonic Measurement of Change in Elasticity due to Endothelium Dependent Relaxation Response by Accurate Detection of Artery-Wall Boundary

    NASA Astrophysics Data System (ADS)

    Kaneko, Takuya; Hasegawa, Hideyuki; Kanai, Hiroshi

    2007-07-01

    Ross hypothesized that an endothelial dysfunction is considered to be an initial step in atherosclerosis. Endothelial cells, which release nitric oxide (NO) in response to shear stress from blood flow, have a function of relaxing smooth muscle in the media of the arterial wall. For the assessment of the endothelial function, there is a conventional method in which the change in the diameter of the brachial artery caused by flow-mediated dilation (FMD) is measured with ultrasound. However, despite the fact that the collagen-rich hard adventitia does not respond to NO, the conventional method measures the change in diameter depending on the mechanical property of the entire wall including the adventitia. Therefore, we developed a method of measuring the change in the thickness and the elasticity of the brachial artery during a cardiac cycle using the phased tracking method for the evaluation of the mechanical property of only the intima-media region. In this study, the initial positions of echoes from the lumen-intima and media-adventitia boundaries are determined using complex template matching to accurately estimate the minute change in the thickness and the elasticity of the brachial and radial arteries. The ambiguity in the determination of such boundaries was eliminated using complex template matching, and the change in elasticity measured by the proposed method was larger than the change in inner diameter obtained by the conventional method.

  4. High Frequency QRS ECG Accurately Detects Cardiomyopathy

    NASA Technical Reports Server (NTRS)

    Schlegel, Todd T.; Arenare, Brian; Poulin, Gregory; Moser, Daniel R.; Delgado, Reynolds

    2005-01-01

    High frequency (HF, 150-250 Hz) analysis over the entire QRS interval of the ECG is more sensitive than conventional ECG for detecting myocardial ischemia. However, the accuracy of HF QRS ECG for detecting cardiomyopathy is unknown. We obtained simultaneous resting conventional and HF QRS 12-lead ECGs in 66 patients with cardiomyopathy (EF = 23.2 plus or minus 6.l%, mean plus or minus SD) and in 66 age- and gender-matched healthy controls using PC-based ECG software recently developed at NASA. The single most accurate ECG parameter for detecting cardiomyopathy was an HF QRS morphological score that takes into consideration the total number and severity of reduced amplitude zones (RAZs) present plus the clustering of RAZs together in contiguous leads. This RAZ score had an area under the receiver operator curve (ROC) of 0.91, and was 88% sensitive, 82% specific and 85% accurate for identifying cardiomyopathy at optimum score cut-off of 140 points. Although conventional ECG parameters such as the QRS and QTc intervals were also significantly longer in patients than controls (P less than 0.001, BBBs excluded), these conventional parameters were less accurate (area under the ROC = 0.77 and 0.77, respectively) than HF QRS morphological parameters for identifying underlying cardiomyopathy. The total amplitude of the HF QRS complexes, as measured by summed root mean square voltages (RMSVs), also differed between patients and controls (33.8 plus or minus 11.5 vs. 41.5 plus or minus 13.6 mV, respectively, P less than 0.003), but this parameter was even less accurate in distinguishing the two groups (area under ROC = 0.67) than the HF QRS morphologic and conventional ECG parameters. Diagnostic accuracy was optimal (86%) when the RAZ score from the HF QRS ECG and the QTc interval from the conventional ECG were used simultaneously with cut-offs of greater than or equal to 40 points and greater than or equal to 445 ms, respectively. In conclusion 12-lead HF QRS ECG employing

  5. Detecting Unidentified Changes

    PubMed Central

    Howe, Piers D. L.; Webb, Margaret E.

    2014-01-01

    Does becoming aware of a change to a purely visual stimulus necessarily cause the observer to be able to identify or localise the change or can change detection occur in the absence of identification or localisation? Several theories of visual awareness stress that we are aware of more than just the few objects to which we attend. In particular, it is clear that to some extent we are also aware of the global properties of the scene, such as the mean luminance or the distribution of spatial frequencies. It follows that we may be able to detect a change to a visual scene by detecting a change to one or more of these global properties. However, detecting a change to global property may not supply us with enough information to accurately identify or localise which object in the scene has been changed. Thus, it may be possible to reliably detect the occurrence of changes without being able to identify or localise what has changed. Previous attempts to show that this can occur with natural images have produced mixed results. Here we use a novel analysis technique to provide additional evidence that changes can be detected in natural images without also being identified or localised. It is likely that this occurs by the observers monitoring the global properties of the scene. PMID:24454727

  6. Accurate and Reliable Gait Cycle Detection in Parkinson's Disease.

    PubMed

    Hundza, Sandra R; Hook, William R; Harris, Christopher R; Mahajan, Sunny V; Leslie, Paul A; Spani, Carl A; Spalteholz, Leonhard G; Birch, Benjamin J; Commandeur, Drew T; Livingston, Nigel J

    2014-01-01

    There is a growing interest in the use of Inertial Measurement Unit (IMU)-based systems that employ gyroscopes for gait analysis. We describe an improved IMU-based gait analysis processing method that uses gyroscope angular rate reversal to identify the start of each gait cycle during walking. In validation tests with six subjects with Parkinson disease (PD), including those with severe shuffling gait patterns, and seven controls, the probability of True-Positive event detection and False-Positive event detection was 100% and 0%, respectively. Stride time validation tests using high-speed cameras yielded a standard deviation of 6.6 ms for controls and 11.8 ms for those with PD. These data demonstrate that the use of our angular rate reversal algorithm leads to improvements over previous gyroscope-based gait analysis systems. Highly accurate and reliable stride time measurements enabled us to detect subtle changes in stride time variability following a Parkinson's exercise class. We found unacceptable measurement accuracy for stride length when using the Aminian et al gyro-based biomechanical algorithm, with errors as high as 30% in PD subjects. An alternative method, using synchronized infrared timing gates to measure velocity, combined with accurate mean stride time from our angular rate reversal algorithm, more accurately calculates mean stride length.

  7. How to accurately detect autobiographical events.

    PubMed

    Sartori, Giuseppe; Agosta, Sara; Zogmaister, Cristina; Ferrara, Santo Davide; Castiello, Umberto

    2008-08-01

    We describe a new method, based on indirect measures of implicit autobiographical memory, that allows evaluation of which of two contrasting autobiographical events (e.g., crimes) is true for a given individual. Participants were requested to classify sentences describing possible autobiographical events by pressing one of two response keys. Responses were faster when sentences related to truly autobiographical events shared the same response key with other sentences reporting true events and slower when sentences related to truly autobiographical events shared the same response key with sentences reporting false events. This method has possible application in forensic settings and as a lie-detection technique.

  8. Accurately Detecting Students' Lies regarding Relational Aggression by Correctional Instructions

    ERIC Educational Resources Information Center

    Dickhauser, Oliver; Reinhard, Marc-Andre; Marksteiner, Tamara

    2012-01-01

    This study investigates the effect of correctional instructions when detecting lies about relational aggression. Based on models from the field of social psychology, we predict that correctional instruction will lead to a less pronounced lie bias and to more accurate lie detection. Seventy-five teachers received videotapes of students' true denial…

  9. Accurate mobile malware detection and classification in the cloud.

    PubMed

    Wang, Xiaolei; Yang, Yuexiang; Zeng, Yingzhi

    2015-01-01

    As the dominator of the Smartphone operating system market, consequently android has attracted the attention of s malware authors and researcher alike. The number of types of android malware is increasing rapidly regardless of the considerable number of proposed malware analysis systems. In this paper, by taking advantages of low false-positive rate of misuse detection and the ability of anomaly detection to detect zero-day malware, we propose a novel hybrid detection system based on a new open-source framework CuckooDroid, which enables the use of Cuckoo Sandbox's features to analyze Android malware through dynamic and static analysis. Our proposed system mainly consists of two parts: anomaly detection engine performing abnormal apps detection through dynamic analysis; signature detection engine performing known malware detection and classification with the combination of static and dynamic analysis. We evaluate our system using 5560 malware samples and 6000 benign samples. Experiments show that our anomaly detection engine with dynamic analysis is capable of detecting zero-day malware with a low false negative rate (1.16 %) and acceptable false positive rate (1.30 %); it is worth noting that our signature detection engine with hybrid analysis can accurately classify malware samples with an average positive rate 98.94 %. Considering the intensive computing resources required by the static and dynamic analysis, our proposed detection system should be deployed off-device, such as in the Cloud. The app store markets and the ordinary users can access our detection system for malware detection through cloud service. PMID:26543718

  10. Accurate mobile malware detection and classification in the cloud.

    PubMed

    Wang, Xiaolei; Yang, Yuexiang; Zeng, Yingzhi

    2015-01-01

    As the dominator of the Smartphone operating system market, consequently android has attracted the attention of s malware authors and researcher alike. The number of types of android malware is increasing rapidly regardless of the considerable number of proposed malware analysis systems. In this paper, by taking advantages of low false-positive rate of misuse detection and the ability of anomaly detection to detect zero-day malware, we propose a novel hybrid detection system based on a new open-source framework CuckooDroid, which enables the use of Cuckoo Sandbox's features to analyze Android malware through dynamic and static analysis. Our proposed system mainly consists of two parts: anomaly detection engine performing abnormal apps detection through dynamic analysis; signature detection engine performing known malware detection and classification with the combination of static and dynamic analysis. We evaluate our system using 5560 malware samples and 6000 benign samples. Experiments show that our anomaly detection engine with dynamic analysis is capable of detecting zero-day malware with a low false negative rate (1.16 %) and acceptable false positive rate (1.30 %); it is worth noting that our signature detection engine with hybrid analysis can accurately classify malware samples with an average positive rate 98.94 %. Considering the intensive computing resources required by the static and dynamic analysis, our proposed detection system should be deployed off-device, such as in the Cloud. The app store markets and the ordinary users can access our detection system for malware detection through cloud service.

  11. Accurate hydrogen depth profiling by reflection elastic recoil detection analysis

    SciTech Connect

    Verda, R. D.; Tesmer, Joseph R.; Nastasi, Michael Anthony,; Bower, R. W.

    2001-01-01

    A technique to convert reflection elastic recoil detection analysis spectra to depth profiles, the channel-depth conversion, was introduced by Verda, et al [1]. But the channel-depth conversion does not correct for energy spread, the unwanted broadening in the energy of the spectra, which can lead to errors in depth profiling. A work in progress introduces a technique that corrects for energy spread in elastic recoil detection analysis spectra, the energy spread correction [2]. Together, the energy spread correction and the channel-depth conversion comprise an accurate and convenient hydrogen depth profiling method.

  12. Detection and accurate localization of harmonic chipless tags

    NASA Astrophysics Data System (ADS)

    Dardari, Davide

    2015-12-01

    We investigate the detection and localization properties of harmonic tags working at microwave frequencies. A two-tone interrogation signal and a dedicated signal processing scheme at the receiver are proposed to eliminate phase ambiguities caused by the short signal wavelength and to provide accurate distance/position estimation even in the presence of clutter and multipath. The theoretical limits on tag detection and localization accuracy are investigated starting from a concise characterization of harmonic backscattered signals. Numerical results show that accuracies in the order of centimeters are feasible within an operational range of a few meters in the RFID UHF band.

  13. Automatic and Accurate Shadow Detection Using Near-Infrared Information.

    PubMed

    Rüfenacht, Dominic; Fredembach, Clément; Süsstrunk, Sabine

    2014-08-01

    We present a method to automatically detect shadows in a fast and accurate manner by taking advantage of the inherent sensitivity of digital camera sensors to the near-infrared (NIR) part of the spectrum. Dark objects, which confound many shadow detection algorithms, often have much higher reflectance in the NIR. We can thus build an accurate shadow candidate map based on image pixels that are dark both in the visible and NIR representations. We further refine the shadow map by incorporating ratios of the visible to the NIR image, based on the observation that commonly encountered light sources have very distinct spectra in the NIR band. The results are validated on a new database, which contains visible/NIR images for a large variety of real-world shadow creating illuminant conditions, as well as manually labeled shadow ground truth. Both quantitative and qualitative evaluations show that our method outperforms current state-of-the-art shadow detection algorithms in terms of accuracy and computational efficiency.

  14. Building dynamic population graph for accurate correspondence detection.

    PubMed

    Du, Shaoyi; Guo, Yanrong; Sanroma, Gerard; Ni, Dong; Wu, Guorong; Shen, Dinggang

    2015-12-01

    In medical imaging studies, there is an increasing trend for discovering the intrinsic anatomical difference across individual subjects in a dataset, such as hand images for skeletal bone age estimation. Pair-wise matching is often used to detect correspondences between each individual subject and a pre-selected model image with manually-placed landmarks. However, the large anatomical variability across individual subjects can easily compromise such pair-wise matching step. In this paper, we present a new framework to simultaneously detect correspondences among a population of individual subjects, by propagating all manually-placed landmarks from a small set of model images through a dynamically constructed image graph. Specifically, we first establish graph links between models and individual subjects according to pair-wise shape similarity (called as forward step). Next, we detect correspondences for the individual subjects with direct links to any of model images, which is achieved by a new multi-model correspondence detection approach based on our recently-published sparse point matching method. To correct those inaccurate correspondences, we further apply an error detection mechanism to automatically detect wrong correspondences and then update the image graph accordingly (called as backward step). After that, all subject images with detected correspondences are included into the set of model images, and the above two steps of graph expansion and error correction are repeated until accurate correspondences for all subject images are established. Evaluations on real hand X-ray images demonstrate that our proposed method using a dynamic graph construction approach can achieve much higher accuracy and robustness, when compared with the state-of-the-art pair-wise correspondence detection methods as well as a similar method but using static population graph.

  15. Accurate Detection of Rifampicin-Resistant Mycobacterium Tuberculosis Strains

    PubMed Central

    Song, Keum-Soo; Nimse, Satish Balasaheb; Kim, Hee Jin; Yang, Jeongseong; Kim, Taisun

    2016-01-01

    In 2013 alone, the death rate among the 9.0 million people infected with Mycobacterium tuberculosis (TB) worldwide was around 14%, which is unacceptably high. An empiric treatment of patients infected with TB or drug-resistant Mycobacterium tuberculosis (MDR-TB) strain can also result in the spread of MDR-TB. The diagnostic tools which are rapid, reliable, and have simple experimental protocols can significantly help in decreasing the prevalence rate of MDR-TB strain. We report the evaluation of the 9G technology based 9G DNAChips that allow accurate detection and discrimination of TB and MDR-TB-RIF. One hundred and thirteen known cultured samples were used to evaluate the ability of 9G DNAChip in the detection and discrimination of TB and MDR-TB-RIF strains. Hybridization of immobilized probes with the PCR products of TB and MDR-TB-RIF strains allow their detection and discrimination. The accuracy of 9G DNAChip was determined by comparing its results with sequencing analysis and drug susceptibility testing. Sequencing analysis showed 100% agreement with the results of 9G DNAChip. The 9G DNAChip showed very high sensitivity (95.4%) and specificity (100%). PMID:26999135

  16. Fast and Accurate Detection of Multiple Quantitative Trait Loci

    PubMed Central

    Nettelblad, Carl; Holmgren, Sverker

    2013-01-01

    Abstract We present a new computational scheme that enables efficient and reliable quantitative trait loci (QTL) scans for experimental populations. Using a standard brute-force exhaustive search effectively prohibits accurate QTL scans involving more than two loci to be performed in practice, at least if permutation testing is used to determine significance. Some more elaborate global optimization approaches, for example, DIRECT have been adopted earlier to QTL search problems. Dramatic speedups have been reported for high-dimensional scans. However, since a heuristic termination criterion must be used in these types of algorithms, the accuracy of the optimization process cannot be guaranteed. Indeed, earlier results show that a small bias in the significance thresholds is sometimes introduced. Our new optimization scheme, PruneDIRECT, is based on an analysis leading to a computable (Lipschitz) bound on the slope of a transformed objective function. The bound is derived for both infinite- and finite-size populations. Introducing a Lipschitz bound in DIRECT leads to an algorithm related to classical Lipschitz optimization. Regions in the search space can be permanently excluded (pruned) during the optimization process. Heuristic termination criteria can thus be avoided. Hence, PruneDIRECT has a well-defined error bound and can in practice be guaranteed to be equivalent to a corresponding exhaustive search. We present simulation results that show that for simultaneous mapping of three QTLS using permutation testing, PruneDIRECT is typically more than 50 times faster than exhaustive search. The speedup is higher for stronger QTL. This could be used to quickly detect strong candidate eQTL networks. PMID:23919387

  17. Do Canadian collegiate hockey players accurately perceive body composition changes after unmonitored training and diet?

    PubMed

    Prokop, Neal W; Duncan, Lindsay R; Andersen, Ross E

    2015-10-01

    Collegiate athletes often use nutritional programs and supplements to elicit body composition changes in muscle or fat. It is unknown if athletes can accurately perceive their fluctuations in body composition, yet their understanding may help them make more accurate interpretations regarding the success of potential nutrition or exercise regimens. The purpose of this study was to investigate if collegiate hockey players could accurately perceive a change in body composition during a 3-month period within their regular season, in which no predetermined nutritional or exercise program was provided. Twenty-four male Canadian collegiate hockey players completed preseason and midseason body composition assessments using dual-energy X-ray absorptiometry. Immediately before the midseason scan, players attempted to accurately match their perceived fluctuation in composition, with predetermined categorical ranges of relative body composition and strength. Two-thirds of players and one-half of players accurately perceived changes in arm-lean and arm-fat tissue, respectively. Approximately two-thirds of players did not accurately perceive gains or losses of lean or fat tissue within their leg and overall body. Although some athletes partially detected changes in the lean and fat tissue of particular regions, the vast majority of players cannot detect the type, or amount of tissue gained and lost across the overall body. Body composition assessments, rather than an athlete's perceptions, should be used to help interpret the success of a sport nutrition or exercise program. Athletes should be aware that physiologic adaptations might take place unnoticed, which could affect the acceptance and adherence of nutrition or exercise interventions. PMID:26394260

  18. Accurate feature detection and estimation using nonlinear and multiresolution analysis

    NASA Astrophysics Data System (ADS)

    Rudin, Leonid; Osher, Stanley

    1994-11-01

    A program for feature detection and estimation using nonlinear and multiscale analysis was completed. The state-of-the-art edge detection was combined with multiscale restoration (as suggested by the first author) and robust results in the presence of noise were obtained. Successful applications to numerous images of interest to DOD were made. Also, a new market in the criminal justice field was developed, based in part, on this work.

  19. SAR change detection MTI

    NASA Astrophysics Data System (ADS)

    Scarborough, Steven; Lemanski, Christopher; Nichols, Howard; Owirka, Gregory; Minardi, Michael; Hale, Todd

    2006-05-01

    This paper examines the theory, application, and results of using single-channel synthetic aperture radar (SAR) data with Moving Reference Processing (MRP) to focus and geolocate moving targets. Moving targets within a standard SAR imaging scene are defocused, displaced, or completely missing in the final image. Building on previous research at AFRL, the SAR-MRP method focuses and geolocates moving targets by reprocessing the SAR data to focus the movers rather than the stationary clutter. SAR change detection is used so that target detection and focusing is performed more robustly. In the cases where moving target returns possess the same range versus slow-time histories, a geolocation ambiguity results. This ambiguity can be resolved in a number of ways. This paper concludes by applying the SAR-MRP method to high-frequency radar measurements from persistent continuous-dwell SAR observations of a moving target.

  20. Detecting and predicting changes.

    PubMed

    Brown, Scott D; Steyvers, Mark

    2009-02-01

    When required to predict sequential events, such as random coin tosses or basketball free throws, people reliably use inappropriate strategies, such as inferring temporal structure when none is present. We investigate the ability of observers to predict sequential events in dynamically changing environments, where there is an opportunity to detect true temporal structure. In two experiments we demonstrate that participants often make correct statistical decisions when asked to infer the hidden state of the data generating process. However, when asked to make predictions about future outcomes, accuracy decreased even though normatively correct responses in the two tasks were identical. A particle filter model accounts for all data, describing performance in terms of a plausible psychological process. By varying the number of particles, and the prior belief about the probability of a change occurring in the data generating process, we were able to model most of the observed individual differences.

  1. Novel Cortical Thickness Pattern for Accurate Detection of Alzheimer's Disease.

    PubMed

    Zheng, Weihao; Yao, Zhijun; Hu, Bin; Gao, Xiang; Cai, Hanshu; Moore, Philip

    2015-01-01

    Brain network occupies an important position in representing abnormalities in Alzheimer's disease (AD) and mild cognitive impairment (MCI). Currently, most studies only focused on morphological features of regions of interest without exploring the interregional alterations. In order to investigate the potential discriminative power of a morphological network in AD diagnosis and to provide supportive evidence on the feasibility of an individual structural network study, we propose a novel approach of extracting the correlative features from magnetic resonance imaging, which consists of a two-step approach for constructing an individual thickness network with low computational complexity. Firstly, multi-distance combination is utilized for accurate evaluation of between-region dissimilarity; and then the dissimilarity is transformed to connectivity via calculation of correlation function. An evaluation of the proposed approach has been conducted with 189 normal controls, 198 MCI subjects, and 163 AD patients using machine learning techniques. Results show that the observed correlative feature suggests significant promotion in classification performance compared with cortical thickness, with accuracy of 89.88% and area of 0.9588 under receiver operating characteristic curve. We further improved the performance by integrating both thickness and apolipoprotein E ɛ4 allele information with correlative features. New achieved accuracies are 92.11% and 79.37% in separating AD from normal controls and AD converters from non-converters, respectively. Differences between using diverse distance measurements and various correlation transformation functions are also discussed to explore an optimal way for network establishment. PMID:26444768

  2. Accurate detection of blood vessels improves the detection of exudates in color fundus images.

    PubMed

    Youssef, Doaa; Solouma, Nahed H

    2012-12-01

    Exudates are one of the earliest and most prevalent symptoms of diseases leading to blindness such as diabetic retinopathy and macular degeneration. Certain areas of the retina with such conditions are to be photocoagulated by laser to stop the disease progress and prevent blindness. Outlining these areas is dependent on outlining the lesions and the anatomic structures of the retina. In this paper, we provide a new method for the detection of blood vessels that improves the detection of exudates in fundus photographs. The method starts with an edge detection algorithm which results in a over segmented image. Then the new feature-based algorithm can be used to accurately detect the blood vessels. This algorithm considers the characteristics of a retinal blood vessel such as its width range, intensities and orientations for the purpose of selective segmentation. Because of its bulb shape and its color similarity with exudates, the optic disc can be detected using the common Hough transform technique. The extracted blood vessel tree and optic disc could be subtracted from the over segmented image to get an initial estimate of exudates. The final estimation of exudates can then be obtained by morphological reconstruction based on the appearance of exudates. This method is shown to be promising since it increases the sensitivity and specificity of exudates detection to 80% and 100% respectively.

  3. Instrument accurately measures small temperature changes on test surface

    NASA Technical Reports Server (NTRS)

    Harvey, W. D.; Miller, H. B.

    1966-01-01

    Calorimeter apparatus accurately measures very small temperature rises on a test surface subjected to aerodynamic heating. A continuous thin sheet of a sensing material is attached to a base support plate through which a series of holes of known diameter have been drilled for attaching thermocouples to the material.

  4. Change detection: training and transfer.

    PubMed

    Gaspar, John G; Neider, Mark B; Simons, Daniel J; McCarley, Jason S; Kramer, Arthur F

    2013-01-01

    Observers often fail to notice even dramatic changes to their environment, a phenomenon known as change blindness. If training could enhance change detection performance in general, then it might help to remedy some real-world consequences of change blindness (e.g. failing to detect hazards while driving). We examined whether adaptive training on a simple change detection task could improve the ability to detect changes in untrained tasks for young and older adults. Consistent with an effective training procedure, both young and older adults were better able to detect changes to trained objects following training. However, neither group showed differential improvement on untrained change detection tasks when compared to active control groups. Change detection training led to improvements on the trained task but did not generalize to other change detection tasks.

  5. Change Detection: Training and Transfer

    PubMed Central

    Gaspar, John G.; Neider, Mark B.; Simons, Daniel J.; McCarley, Jason S.; Kramer, Arthur F.

    2013-01-01

    Observers often fail to notice even dramatic changes to their environment, a phenomenon known as change blindness. If training could enhance change detection performance in general, then it might help to remedy some real-world consequences of change blindness (e.g. failing to detect hazards while driving). We examined whether adaptive training on a simple change detection task could improve the ability to detect changes in untrained tasks for young and older adults. Consistent with an effective training procedure, both young and older adults were better able to detect changes to trained objects following training. However, neither group showed differential improvement on untrained change detection tasks when compared to active control groups. Change detection training led to improvements on the trained task but did not generalize to other change detection tasks. PMID:23840775

  6. The Development of Change Detection

    ERIC Educational Resources Information Center

    Shore, David I.; Burack, Jacob A.; Miller, Danny; Joseph, Shari; Enns, James T.

    2006-01-01

    Changes to a scene often go unnoticed if the objects of the change are unattended, making change detection an index of where attention is focused during scene perception. We measured change detection in school-age children and young adults by repeatedly alternating two versions of an image. To provide an age-fair assessment we used a bimanual…

  7. Change in BMI accurately predicted by social exposure to acquaintances.

    PubMed

    Oloritun, Rahman O; Ouarda, Taha B M J; Moturu, Sai; Madan, Anmol; Pentland, Alex Sandy; Khayal, Inas

    2013-01-01

    Research has mostly focused on obesity and not on processes of BMI change more generally, although these may be key factors that lead to obesity. Studies have suggested that obesity is affected by social ties. However these studies used survey based data collection techniques that may be biased toward select only close friends and relatives. In this study, mobile phone sensing techniques were used to routinely capture social interaction data in an undergraduate dorm. By automating the capture of social interaction data, the limitations of self-reported social exposure data are avoided. This study attempts to understand and develop a model that best describes the change in BMI using social interaction data. We evaluated a cohort of 42 college students in a co-located university dorm, automatically captured via mobile phones and survey based health-related information. We determined the most predictive variables for change in BMI using the least absolute shrinkage and selection operator (LASSO) method. The selected variables, with gender, healthy diet category, and ability to manage stress, were used to build multiple linear regression models that estimate the effect of exposure and individual factors on change in BMI. We identified the best model using Akaike Information Criterion (AIC) and R(2). This study found a model that explains 68% (p<0.0001) of the variation in change in BMI. The model combined social interaction data, especially from acquaintances, and personal health-related information to explain change in BMI. This is the first study taking into account both interactions with different levels of social interaction and personal health-related information. Social interactions with acquaintances accounted for more than half the variation in change in BMI. This suggests the importance of not only individual health information but also the significance of social interactions with people we are exposed to, even people we may not consider as close friends.

  8. Multisensor Fusion for Change Detection

    NASA Astrophysics Data System (ADS)

    Schenk, T.; Csatho, B.

    2005-12-01

    Combining sensors that record different properties of a 3-D scene leads to complementary and redundant information. If fused properly, a more robust and complete scene description becomes available. Moreover, fusion facilitates automatic procedures for object reconstruction and modeling. For example, aerial imaging sensors, hyperspectral scanning systems, and airborne laser scanning systems generate complementary data. We describe how data from these sensors can be fused for such diverse applications as mapping surface erosion and landslides, reconstructing urban scenes, monitoring urban land use and urban sprawl, and deriving velocities and surface changes of glaciers and ice sheets. An absolute prerequisite for successful fusion is a rigorous co-registration of the sensors involved. We establish a common 3-D reference frame by using sensor invariant features. Such features are caused by the same object space phenomena and are extracted in multiple steps from the individual sensors. After extracting, segmenting and grouping the features into more abstract entities, we discuss ways on how to automatically establish correspondences. This is followed by a brief description of rigorous mathematical models suitable to deal with linear and area features. In contrast to traditional, point-based registration methods, lineal and areal features lend themselves to a more robust and more accurate registration. More important, the chances to automate the registration process increases significantly. The result of the co-registration of the sensors is a unique transformation between the individual sensors and the object space. This makes spatial reasoning of extracted information more versatile; reasoning can be performed in sensor space or in 3-D space where domain knowledge about features and objects constrains reasoning processes, reduces the search space, and helps to make the problem well-posed. We demonstrate the feasibility of the proposed multisensor fusion approach

  9. Change in body mass accurately and reliably predicts change in body water after endurance exercise.

    PubMed

    Baker, Lindsay B; Lang, James A; Kenney, W Larry

    2009-04-01

    This study tested the hypothesis that the change in body mass (DeltaBM) accurately reflects the change in total body water (DeltaTBW) after prolonged exercise. Subjects (4 men, 4 women; 22-36 year; 66 +/- 10 kg) completed 2 h of interval running (70% VO(2max)) in the heat (30 degrees C), followed by a run to exhaustion (85% VO(2max)), and then sat for a 1 h recovery period. During exercise and recovery, subjects drank fluid or no fluid to maintain their BM, increase BM by 2%, or decrease BM by 2 or 4% in separate trials. Pre- and post-experiment TBW were determined using the deuterium oxide (D(2)O) dilution technique and corrected for D(2)O lost in urine, sweat, breath vapor, and nonaqueous hydrogen exchange. The average difference between DeltaBM and DeltaTBW was 0.07 +/- 1.07 kg (paired t test, P = 0.29). The slope and intercept of the relation between DeltaBM and DeltaTBW were not significantly different from 1 and 0, respectively. The intraclass correlation coefficient between DeltaBM and DeltaTBW was 0.76, which is indicative of excellent reliability between methods. Measuring pre- to post-exercise DeltaBM is an accurate and reliable method to assess the DeltaTBW.

  10. Distributed Pedestrian Detection Alerts Based on Data Fusion with Accurate Localization

    PubMed Central

    García, Fernando; Jiménez, Felipe; Anaya, José Javier; Armingol, José María; Naranjo, José Eugenio; de la Escalera, Arturo

    2013-01-01

    Among Advanced Driver Assistance Systems (ADAS) pedestrian detection is a common issue due to the vulnerability of pedestrians in the event of accidents. In the present work, a novel approach for pedestrian detection based on data fusion is presented. Data fusion helps to overcome the limitations inherent to each detection system (computer vision and laser scanner) and provides accurate and trustable tracking of any pedestrian movement. The application is complemented by an efficient communication protocol, able to alert vehicles in the surroundings by a fast and reliable communication. The combination of a powerful location, based on a GPS with inertial measurement, and accurate obstacle localization based on data fusion has allowed locating the detected pedestrians with high accuracy. Tests proved the viability of the detection system and the efficiency of the communication, even at long distances. By the use of the alert communication, dangerous situations such as occlusions or misdetections can be avoided. PMID:24008284

  11. Distributed pedestrian detection alerts based on data fusion with accurate localization.

    PubMed

    García, Fernando; Jiménez, Felipe; Anaya, José Javier; Armingol, José María; Naranjo, José Eugenio; de la Escalera, Arturo

    2013-01-01

    Among Advanced Driver Assistance Systems (ADAS) pedestrian detection is a common issue due to the vulnerability of pedestrians in the event of accidents. In the present work, a novel approach for pedestrian detection based on data fusion is presented. Data fusion helps to overcome the limitations inherent to each detection system (computer vision and laser scanner) and provides accurate and trustable tracking of any pedestrian movement. The application is complemented by an efficient communication protocol, able to alert vehicles in the surroundings by a fast and reliable communication. The combination of a powerful location, based on a GPS with inertial measurement, and accurate obstacle localization based on data fusion has allowed locating the detected pedestrians with high accuracy. Tests proved the viability of the detection system and the efficiency of the communication, even at long distances. By the use of the alert communication, dangerous situations such as occlusions or misdetections can be avoided.

  12. A simplified hydroethidine method for fast and accurate detection of superoxide production in isolated mitochondria.

    PubMed

    Back, Patricia; Matthijssens, Filip; Vanfleteren, Jacques R; Braeckman, Bart P

    2012-04-01

    Because superoxide is involved in various physiological processes, many efforts have been made to improve its accurate quantification. We optimized and validated a superoxide-specific and -sensitive detection method. The protocol is based on fluorescence detection of the superoxide-specific hydroethidine (HE) oxidation product, 2-hydroxyethidium. We established a method for the quantification of superoxide production in isolated mitochondria without the need for acetone extraction and purification chromatography as described in previous studies.

  13. Breaking Snake Camouflage: Humans Detect Snakes More Accurately than Other Animals under Less Discernible Visual Conditions

    PubMed Central

    He, Hongshen

    2016-01-01

    Humans and non-human primates are extremely sensitive to snakes as exemplified by their ability to detect pictures of snakes more quickly than those of other animals. These findings are consistent with the Snake Detection Theory, which hypothesizes that as predators, snakes were a major source of evolutionary selection that favored expansion of the visual system of primates for rapid snake detection. Many snakes use camouflage to conceal themselves from both prey and their own predators, making it very challenging to detect them. If snakes have acted as a selective pressure on primate visual systems, they should be more easily detected than other animals under difficult visual conditions. Here we tested whether humans discerned images of snakes more accurately than those of non-threatening animals (e.g., birds, cats, or fish) under conditions of less perceptual information by presenting a series of degraded images with the Random Image Structure Evolution technique (interpolation of random noise). We find that participants recognize mosaic images of snakes, which were regarded as functionally equivalent to camouflage, more accurately than those of other animals under dissolved conditions. The present study supports the Snake Detection Theory by showing that humans have a visual system that accurately recognizes snakes under less discernible visual conditions. PMID:27783686

  14. Accurate, noninvasive detection of Helicobacter pylori DNA from stool samples: potential usefulness for monitoring treatment.

    PubMed

    Shuber, Anthony P; Ascaño, Jennifer J; Boynton, Kevin A; Mitchell, Anastasia; Frierson, Henry F; El-Rifai, Wa'el; Powell, Steven M

    2002-01-01

    A novel DNA assay demonstrating sensitive and accurate detection of Helicobacter pylori from stool samples is reported. Moreover, in three individuals tested for therapeutic response, the assay showed the disappearance of H. pylori DNA during treatment. Thus, this noninvasive molecular biology-based assay has the potential to be a powerful diagnostic tool given its ability to specifically identify H. pylori DNA.

  15. Accurate means of detecting and characterizing abnormal patterns of ventricular activation by phase image analysis

    SciTech Connect

    Botvinick, E.H.; Frais, M.A.; Shosa, D.W.; O'Connell, J.W.; Pacheco-Alvarez, J.A.; Scheinman, M.; Hattner, R.S.; Morady, F.; Faulkner, D.B.

    1982-08-01

    The ability of scintigraphic phase image analysis to characterize patterns of abnormal ventricular activation was investigated. The pattern of phase distribution and sequential phase changes over both right and left ventricular regions of interest were evaluated in 16 patients with normal electrical activation and wall motion and compared with those in 8 patients with an artificial pacemaker and 4 patients with sinus rhythm with the Wolff-Parkinson-White syndrome and delta waves. Normally, the site of earliest phase angle was seen at the base of the interventricular septum, with sequential change affecting the body of the septum and the cardiac apex and then spreading laterally to involve the body of both ventricles. The site of earliest phase angle was located at the apex of the right ventricle in seven patients with a right ventricular endocardial pacemaker and on the lateral left ventricular wall in one patient with a left ventricular epicardial pacemaker. In each case the site corresponded exactly to the position of the pacing electrode as seen on posteroanterior and left lateral chest X-ray films, and sequential phase changes spread from the initial focus to affect both ventricles. In each of the patients with the Wolff-Parkinson-White syndrome, the site of earliest ventricular phase angle was located, and it corresponded exactly to the site of the bypass tract as determined by endocardial mapping. In this way, four bypass pathways, two posterior left paraseptal, one left lateral and one right lateral, were correctly localized scintigraphically. On the basis of the sequence of mechanical contraction, phase image analysis provides an accurate noninvasive method of detecting abnormal foci of ventricular activation.

  16. Accurate band-to-band registration of AOTF imaging spectrometer using motion detection technology

    NASA Astrophysics Data System (ADS)

    Zhou, Pengwei; Zhao, Huijie; Jin, Shangzhong; Li, Ningchuan

    2016-05-01

    This paper concerns the problem of platform vibration induced band-to-band misregistration with acousto-optic imaging spectrometer in spaceborne application. Registrating images of different bands formed at different time or different position is difficult, especially for hyperspectral images form acousto-optic tunable filter (AOTF) imaging spectrometer. In this study, a motion detection method is presented using the polychromatic undiffracted beam of AOTF. The factors affecting motion detect accuracy are analyzed theoretically, and calculations show that optical distortion is an easily overlooked factor to achieve accurate band-to-band registration. Hence, a reflective dual-path optical system has been proposed for the first time, with reduction of distortion and chromatic aberration, indicating the potential of higher registration accuracy. Consequently, a spectra restoration experiment using additional motion detect channel is presented for the first time, which shows the accurate spectral image registration capability of this technique.

  17. Robust and accurate anomaly detection in ECG artifacts using time series motif discovery.

    PubMed

    Sivaraks, Haemwaan; Ratanamahatana, Chotirat Ann

    2015-01-01

    Electrocardiogram (ECG) anomaly detection is an important technique for detecting dissimilar heartbeats which helps identify abnormal ECGs before the diagnosis process. Currently available ECG anomaly detection methods, ranging from academic research to commercial ECG machines, still suffer from a high false alarm rate because these methods are not able to differentiate ECG artifacts from real ECG signal, especially, in ECG artifacts that are similar to ECG signals in terms of shape and/or frequency. The problem leads to high vigilance for physicians and misinterpretation risk for nonspecialists. Therefore, this work proposes a novel anomaly detection technique that is highly robust and accurate in the presence of ECG artifacts which can effectively reduce the false alarm rate. Expert knowledge from cardiologists and motif discovery technique is utilized in our design. In addition, every step of the algorithm conforms to the interpretation of cardiologists. Our method can be utilized to both single-lead ECGs and multilead ECGs. Our experiment results on real ECG datasets are interpreted and evaluated by cardiologists. Our proposed algorithm can mostly achieve 100% of accuracy on detection (AoD), sensitivity, specificity, and positive predictive value with 0% false alarm rate. The results demonstrate that our proposed method is highly accurate and robust to artifacts, compared with competitive anomaly detection methods.

  18. An accurate assay for HCV based on real-time fluorescence detection of isothermal RNA amplification.

    PubMed

    Wu, Xuping; Wang, Jianfang; Song, Jinyun; Li, Jiayan; Yang, Yongfeng

    2016-09-01

    Hepatitis C virus (HCV) is one of the common reasons of liver fibrosis and hepatocellular carcinoma (HCC). Early, rapid and accurate HCV RNA detection is important to prevent and control liver disease. A simultaneous amplification and testing (SAT) assay, which is based on isothermal amplification of RNA and real-time fluorescence detection, was designed to optimize routine HCV RNA detection. In this study, HCV RNA and an internal control (IC) were amplified and analyzed simultaneously by SAT assay and detection of fluorescence using routine real-time PCR equipment. The assay detected as few as 10 copies of HCV RNA transcripts. We tested 705 serum samples with SAT, among which 96.4% (680/705) showed consistent results compared with routine real-time PCR. About 92% (23/25) discordant samples were confirmed to be same results as SAT-HCV by using a second real-time PCR. The sensitivity and specificity of SAT-HCV assay were 99.6% (461/463) and 100% (242/242), respectively. In conclusion, the SAT assay is an accurate test with a high specificity and sensitivity which may increase the detection rate of HCV. It is therefore a promising tool to diagnose HCV infection. PMID:27283884

  19. An accurate assay for HCV based on real-time fluorescence detection of isothermal RNA amplification.

    PubMed

    Wu, Xuping; Wang, Jianfang; Song, Jinyun; Li, Jiayan; Yang, Yongfeng

    2016-09-01

    Hepatitis C virus (HCV) is one of the common reasons of liver fibrosis and hepatocellular carcinoma (HCC). Early, rapid and accurate HCV RNA detection is important to prevent and control liver disease. A simultaneous amplification and testing (SAT) assay, which is based on isothermal amplification of RNA and real-time fluorescence detection, was designed to optimize routine HCV RNA detection. In this study, HCV RNA and an internal control (IC) were amplified and analyzed simultaneously by SAT assay and detection of fluorescence using routine real-time PCR equipment. The assay detected as few as 10 copies of HCV RNA transcripts. We tested 705 serum samples with SAT, among which 96.4% (680/705) showed consistent results compared with routine real-time PCR. About 92% (23/25) discordant samples were confirmed to be same results as SAT-HCV by using a second real-time PCR. The sensitivity and specificity of SAT-HCV assay were 99.6% (461/463) and 100% (242/242), respectively. In conclusion, the SAT assay is an accurate test with a high specificity and sensitivity which may increase the detection rate of HCV. It is therefore a promising tool to diagnose HCV infection.

  20. Giant African pouched rats (Cricetomys gambianus) that work on tilled soil accurately detect land mines.

    PubMed

    Edwards, Timothy L; Cox, Christophe; Weetjens, Bart; Tewelde, Tesfazghi; Poling, Alan

    2015-09-01

    Pouched rats were employed as mine-detection animals in a quality-control application where they searched for mines in areas previously processed by a mechanical tiller. The rats located 58 mines and fragments in this 28,050-m(2) area with a false indication rate of 0.4 responses per 100 m(2) . Humans with metal detectors found no mines that were not located by the rats. These findings indicate that pouched rats can accurately detect land mines in disturbed soil and suggest that they can play multiple roles in humanitarian demining. PMID:25962550

  1. Comparison of methods for accurate end-point detection of potentiometric titrations

    NASA Astrophysics Data System (ADS)

    Villela, R. L. A.; Borges, P. P.; Vyskočil, L.

    2015-01-01

    Detection of the end point in potentiometric titrations has wide application on experiments that demand very low measurement uncertainties mainly for certifying reference materials. Simulations of experimental coulometric titration data and consequential error analysis of the end-point values were conducted using a programming code. These simulations revealed that the Levenberg-Marquardt method is in general more accurate than the traditional second derivative technique used currently as end-point detection for potentiometric titrations. Performance of the methods will be compared and presented in this paper.

  2. Giant African pouched rats (Cricetomys gambianus) that work on tilled soil accurately detect land mines.

    PubMed

    Edwards, Timothy L; Cox, Christophe; Weetjens, Bart; Tewelde, Tesfazghi; Poling, Alan

    2015-09-01

    Pouched rats were employed as mine-detection animals in a quality-control application where they searched for mines in areas previously processed by a mechanical tiller. The rats located 58 mines and fragments in this 28,050-m(2) area with a false indication rate of 0.4 responses per 100 m(2) . Humans with metal detectors found no mines that were not located by the rats. These findings indicate that pouched rats can accurately detect land mines in disturbed soil and suggest that they can play multiple roles in humanitarian demining.

  3. Accurate Automatic Detection of Densely Distributed Cell Nuclei in 3D Space

    PubMed Central

    Tokunaga, Terumasa; Kanamori, Manami; Teramoto, Takayuki; Jang, Moon Sun; Kuge, Sayuri; Ishihara, Takeshi; Yoshida, Ryo; Iino, Yuichi

    2016-01-01

    To measure the activity of neurons using whole-brain activity imaging, precise detection of each neuron or its nucleus is required. In the head region of the nematode C. elegans, the neuronal cell bodies are distributed densely in three-dimensional (3D) space. However, no existing computational methods of image analysis can separate them with sufficient accuracy. Here we propose a highly accurate segmentation method based on the curvatures of the iso-intensity surfaces. To obtain accurate positions of nuclei, we also developed a new procedure for least squares fitting with a Gaussian mixture model. Combining these methods enables accurate detection of densely distributed cell nuclei in a 3D space. The proposed method was implemented as a graphical user interface program that allows visualization and correction of the results of automatic detection. Additionally, the proposed method was applied to time-lapse 3D calcium imaging data, and most of the nuclei in the images were successfully tracked and measured. PMID:27271939

  4. Accurate Automatic Detection of Densely Distributed Cell Nuclei in 3D Space.

    PubMed

    Toyoshima, Yu; Tokunaga, Terumasa; Hirose, Osamu; Kanamori, Manami; Teramoto, Takayuki; Jang, Moon Sun; Kuge, Sayuri; Ishihara, Takeshi; Yoshida, Ryo; Iino, Yuichi

    2016-06-01

    To measure the activity of neurons using whole-brain activity imaging, precise detection of each neuron or its nucleus is required. In the head region of the nematode C. elegans, the neuronal cell bodies are distributed densely in three-dimensional (3D) space. However, no existing computational methods of image analysis can separate them with sufficient accuracy. Here we propose a highly accurate segmentation method based on the curvatures of the iso-intensity surfaces. To obtain accurate positions of nuclei, we also developed a new procedure for least squares fitting with a Gaussian mixture model. Combining these methods enables accurate detection of densely distributed cell nuclei in a 3D space. The proposed method was implemented as a graphical user interface program that allows visualization and correction of the results of automatic detection. Additionally, the proposed method was applied to time-lapse 3D calcium imaging data, and most of the nuclei in the images were successfully tracked and measured. PMID:27271939

  5. Accurate Automatic Detection of Densely Distributed Cell Nuclei in 3D Space.

    PubMed

    Toyoshima, Yu; Tokunaga, Terumasa; Hirose, Osamu; Kanamori, Manami; Teramoto, Takayuki; Jang, Moon Sun; Kuge, Sayuri; Ishihara, Takeshi; Yoshida, Ryo; Iino, Yuichi

    2016-06-01

    To measure the activity of neurons using whole-brain activity imaging, precise detection of each neuron or its nucleus is required. In the head region of the nematode C. elegans, the neuronal cell bodies are distributed densely in three-dimensional (3D) space. However, no existing computational methods of image analysis can separate them with sufficient accuracy. Here we propose a highly accurate segmentation method based on the curvatures of the iso-intensity surfaces. To obtain accurate positions of nuclei, we also developed a new procedure for least squares fitting with a Gaussian mixture model. Combining these methods enables accurate detection of densely distributed cell nuclei in a 3D space. The proposed method was implemented as a graphical user interface program that allows visualization and correction of the results of automatic detection. Additionally, the proposed method was applied to time-lapse 3D calcium imaging data, and most of the nuclei in the images were successfully tracked and measured.

  6. Change Detection in Auditory Textures.

    PubMed

    Boubenec, Yves; Lawlor, Jennifer; Shamma, Shihab; Englitz, Bernhard

    2016-01-01

    Many natural sounds have spectrotemporal signatures only on a statistical level, e.g. wind, fire or rain. While their local structure is highly variable, the spectrotemporal statistics of these auditory textures can be used for recognition. This suggests the existence of a neural representation of these statistics. To explore their encoding, we investigated the detectability of changes in the spectral statistics in relation to the properties of the change. To achieve precise parameter control, we designed a minimal sound texture--a modified cloud of tones--which retains the central property of auditory textures: solely statistical predictability. Listeners had to rapidly detect a change in the frequency marginal probability of the tone cloud occurring at a random time.The size of change as well as the time available to sample the original statistics were found to correlate positively with performance and negatively with reaction time, suggesting the accumulation of noisy evidence. In summary we quantified dynamic aspects of change detection in statistically defined contexts, and found evidence of integration of statistical information.

  7. Highly accurate moving object detection in variable bit rate video-based traffic monitoring systems.

    PubMed

    Huang, Shih-Chia; Chen, Bo-Hao

    2013-12-01

    Automated motion detection, which segments moving objects from video streams, is the key technology of intelligent transportation systems for traffic management. Traffic surveillance systems use video communication over real-world networks with limited bandwidth, which frequently suffers because of either network congestion or unstable bandwidth. Evidence supporting these problems abounds in publications about wireless video communication. Thus, to effectively perform the arduous task of motion detection over a network with unstable bandwidth, a process by which bit-rate is allocated to match the available network bandwidth is necessitated. This process is accomplished by the rate control scheme. This paper presents a new motion detection approach that is based on the cerebellar-model-articulation-controller (CMAC) through artificial neural networks to completely and accurately detect moving objects in both high and low bit-rate video streams. The proposed approach is consisted of a probabilistic background generation (PBG) module and a moving object detection (MOD) module. To ensure that the properties of variable bit-rate video streams are accommodated, the proposed PBG module effectively produces a probabilistic background model through an unsupervised learning process over variable bit-rate video streams. Next, the MOD module, which is based on the CMAC network, completely and accurately detects moving objects in both low and high bit-rate video streams by implementing two procedures: 1) a block selection procedure and 2) an object detection procedure. The detection results show that our proposed approach is capable of performing with higher efficacy when compared with the results produced by other state-of-the-art approaches in variable bit-rate video streams over real-world limited bandwidth networks. Both qualitative and quantitative evaluations support this claim; for instance, the proposed approach achieves Similarity and F1 accuracy rates that are 76

  8. Highly accurate moving object detection in variable bit rate video-based traffic monitoring systems.

    PubMed

    Huang, Shih-Chia; Chen, Bo-Hao

    2013-12-01

    Automated motion detection, which segments moving objects from video streams, is the key technology of intelligent transportation systems for traffic management. Traffic surveillance systems use video communication over real-world networks with limited bandwidth, which frequently suffers because of either network congestion or unstable bandwidth. Evidence supporting these problems abounds in publications about wireless video communication. Thus, to effectively perform the arduous task of motion detection over a network with unstable bandwidth, a process by which bit-rate is allocated to match the available network bandwidth is necessitated. This process is accomplished by the rate control scheme. This paper presents a new motion detection approach that is based on the cerebellar-model-articulation-controller (CMAC) through artificial neural networks to completely and accurately detect moving objects in both high and low bit-rate video streams. The proposed approach is consisted of a probabilistic background generation (PBG) module and a moving object detection (MOD) module. To ensure that the properties of variable bit-rate video streams are accommodated, the proposed PBG module effectively produces a probabilistic background model through an unsupervised learning process over variable bit-rate video streams. Next, the MOD module, which is based on the CMAC network, completely and accurately detects moving objects in both low and high bit-rate video streams by implementing two procedures: 1) a block selection procedure and 2) an object detection procedure. The detection results show that our proposed approach is capable of performing with higher efficacy when compared with the results produced by other state-of-the-art approaches in variable bit-rate video streams over real-world limited bandwidth networks. Both qualitative and quantitative evaluations support this claim; for instance, the proposed approach achieves Similarity and F1 accuracy rates that are 76

  9. Land-cover change detection

    USGS Publications Warehouse

    Chen, Xuexia; Giri, Chandra; Vogelmann, James

    2012-01-01

    Land cover is the biophysical material on the surface of the earth. Land-cover types include grass, shrubs, trees, barren, water, and man-made features. Land cover changes continuously.  The rate of change can be either dramatic and abrupt, such as the changes caused by logging, hurricanes and fire, or subtle and gradual, such as regeneration of forests and damage caused by insects (Verbesselt et al., 2001).  Previous studies have shown that land cover has changed dramatically during the past sevearal centuries and that these changes have severely affected our ecosystems (Foody, 2010; Lambin et al., 2001). Lambin and Strahlers (1994b) summarized five types of cause for land-cover changes: (1) long-term natural changes in climate conditions, (2) geomorphological and ecological processes, (3) human-induced alterations of vegetation cover and landscapes, (4) interannual climate variability, and (5) human-induced greenhouse effect.  Tools and techniques are needed to detect, describe, and predict these changes to facilitate sustainable management of natural resources.

  10. Fast and Accurate Large-Scale Detection of β-Lactamase Genes Conferring Antibiotic Resistance.

    PubMed

    Lee, Jae Jin; Lee, Jung Hun; Kwon, Dae Beom; Jeon, Jeong Ho; Park, Kwang Seung; Lee, Chang-Ro; Lee, Sang Hee

    2015-10-01

    Fast detection of β-lactamase (bla) genes allows improved surveillance studies and infection control measures, which can minimize the spread of antibiotic resistance. Although several molecular diagnostic methods have been developed to detect limited bla gene types, these methods have significant limitations, such as their failure to detect almost all clinically available bla genes. We developed a fast and accurate molecular method to overcome these limitations using 62 primer pairs, which were designed through elaborate optimization processes. To verify the ability of this large-scale bla detection method (large-scaleblaFinder), assays were performed on previously reported bacterial control isolates/strains. To confirm the applicability of the large-scaleblaFinder, the assays were performed on unreported clinical isolates. With perfect specificity and sensitivity in 189 control isolates/strains and 403 clinical isolates, the large-scaleblaFinder detected almost all clinically available bla genes. Notably, the large-scaleblaFinder detected 24 additional unreported bla genes in the isolates/strains that were previously studied, suggesting that previous methods detecting only limited types of bla genes can miss unexpected bla genes existing in pathogenic bacteria, and our method has the ability to detect almost all bla genes existing in a clinical isolate. The ability of large-scaleblaFinder to detect bla genes on a large scale enables prompt application to the detection of almost all bla genes present in bacterial pathogens. The widespread use of the large-scaleblaFinder in the future will provide an important aid for monitoring the emergence and dissemination of bla genes and minimizing the spread of resistant bacteria. PMID:26169415

  11. Fast and Accurate Large-Scale Detection of β-Lactamase Genes Conferring Antibiotic Resistance

    PubMed Central

    Lee, Jae Jin; Lee, Jung Hun; Kwon, Dae Beom; Jeon, Jeong Ho; Park, Kwang Seung; Lee, Chang-Ro

    2015-01-01

    Fast detection of β-lactamase (bla) genes allows improved surveillance studies and infection control measures, which can minimize the spread of antibiotic resistance. Although several molecular diagnostic methods have been developed to detect limited bla gene types, these methods have significant limitations, such as their failure to detect almost all clinically available bla genes. We developed a fast and accurate molecular method to overcome these limitations using 62 primer pairs, which were designed through elaborate optimization processes. To verify the ability of this large-scale bla detection method (large-scaleblaFinder), assays were performed on previously reported bacterial control isolates/strains. To confirm the applicability of the large-scaleblaFinder, the assays were performed on unreported clinical isolates. With perfect specificity and sensitivity in 189 control isolates/strains and 403 clinical isolates, the large-scaleblaFinder detected almost all clinically available bla genes. Notably, the large-scaleblaFinder detected 24 additional unreported bla genes in the isolates/strains that were previously studied, suggesting that previous methods detecting only limited types of bla genes can miss unexpected bla genes existing in pathogenic bacteria, and our method has the ability to detect almost all bla genes existing in a clinical isolate. The ability of large-scaleblaFinder to detect bla genes on a large scale enables prompt application to the detection of almost all bla genes present in bacterial pathogens. The widespread use of the large-scaleblaFinder in the future will provide an important aid for monitoring the emergence and dissemination of bla genes and minimizing the spread of resistant bacteria. PMID:26169415

  12. Detecting changes during pregnancy with Raman spectroscopy

    NASA Astrophysics Data System (ADS)

    Vargis, Elizabeth; Robertson, Kesha; Al-Hendy, Ayman; Reese, Jeff; Mahadevan-Jansen, Anita

    2010-02-01

    Preterm labor is the second leading cause of neonatal mortality and leads to a myriad of complications like delayed development and cerebral palsy. Currently, there is no way to accurately predict preterm labor, making its prevention and treatment virtually impossible. While there are some at-risk patients, over half of all preterm births do not fall into any high-risk category. This study seeks to predict and prevent preterm labor by using Raman spectroscopy to detect changes in the cervix during pregnancy. Since Raman spectroscopy has been used to detect cancers in vivo in organs like the cervix and skin, it follows that spectra will change over the course of pregnancy. Previous studies have shown that fluorescence decreased during pregnancy and increased during post-partum exams to pre-pregnancy levels. We believe significant changes will occur in the Raman spectra obtained during the course of pregnancy. In this study, Raman spectra from the cervix of pregnant mice and women will be acquired. Specific changes that occur due to cervical softening or changes in hormonal levels will be observed to understand the likelihood that a female mouse or a woman will enter labor.

  13. Accurate single-trial detection of movement intention made possible using adaptive wavelet transform.

    PubMed

    Chamanzar, Alireza; Malekmohammadi, Alireza; Bahrani, Masih; Shabany, Mahdi

    2015-01-01

    The outlook of brain-computer interfacing (BCI) is very bright. The real-time, accurate detection of a motor movement task is critical in BCI systems. The poor signal-to-noise-ratio (SNR) of EEG signals and the ambiguity of noise generator sources in brain renders this task quite challenging. In this paper, we demonstrate a novel algorithm for precise detection of the onset of a motor movement through identification of event-related-desynchronization (ERD) patterns. Using an adaptive matched filter technique implemented based on an optimized continues Wavelet transform by selecting an appropriate basis, we can detect single-trial ERDs. Moreover, we use a maximum-likelihood (ML), electrooculography (EOG) artifact removal method to remove eye-related artifacts to significantly improve the detection performance. We have applied this technique to our locally recorded Emotiv(®) data set of 6 healthy subjects, where an average detection selectivity of 85 ± 6% and sensitivity of 88 ± 7.7% is achieved with a temporal precision in the range of -1250 to 367 ms in onset detections of single-trials.

  14. Spectroscopic Method for Fast and Accurate Group A Streptococcus Bacteria Detection.

    PubMed

    Schiff, Dillon; Aviv, Hagit; Rosenbaum, Efraim; Tischler, Yaakov R

    2016-02-16

    Rapid and accurate detection of pathogens is paramount to human health. Spectroscopic techniques have been shown to be viable methods for detecting various pathogens. Enhanced methods of Raman spectroscopy can discriminate unique bacterial signatures; however, many of these require precise conditions and do not have in vivo replicability. Common biological detection methods such as rapid antigen detection tests have high specificity but do not have high sensitivity. Here we developed a new method of bacteria detection that is both highly specific and highly sensitive by combining the specificity of antibody staining and the sensitivity of spectroscopic characterization. Bacteria samples, treated with a fluorescent antibody complex specific to Streptococcus pyogenes, were volumetrically normalized according to their Raman bacterial signal intensity and characterized for fluorescence, eliciting a positive result for samples containing Streptococcus pyogenes and a negative result for those without. The normalized fluorescence intensity of the Streptococcus pyogenes gave a signal that is up to 16.4 times higher than that of other bacteria samples for bacteria stained in solution and up to 12.7 times higher in solid state. This method can be very easily replicated for other bacteria species using suitable antibody-dye complexes. In addition, this method shows viability for in vivo detection as it requires minute amounts of bacteria, low laser excitation power, and short integration times in order to achieve high signal.

  15. Spectroscopic Method for Fast and Accurate Group A Streptococcus Bacteria Detection.

    PubMed

    Schiff, Dillon; Aviv, Hagit; Rosenbaum, Efraim; Tischler, Yaakov R

    2016-02-16

    Rapid and accurate detection of pathogens is paramount to human health. Spectroscopic techniques have been shown to be viable methods for detecting various pathogens. Enhanced methods of Raman spectroscopy can discriminate unique bacterial signatures; however, many of these require precise conditions and do not have in vivo replicability. Common biological detection methods such as rapid antigen detection tests have high specificity but do not have high sensitivity. Here we developed a new method of bacteria detection that is both highly specific and highly sensitive by combining the specificity of antibody staining and the sensitivity of spectroscopic characterization. Bacteria samples, treated with a fluorescent antibody complex specific to Streptococcus pyogenes, were volumetrically normalized according to their Raman bacterial signal intensity and characterized for fluorescence, eliciting a positive result for samples containing Streptococcus pyogenes and a negative result for those without. The normalized fluorescence intensity of the Streptococcus pyogenes gave a signal that is up to 16.4 times higher than that of other bacteria samples for bacteria stained in solution and up to 12.7 times higher in solid state. This method can be very easily replicated for other bacteria species using suitable antibody-dye complexes. In addition, this method shows viability for in vivo detection as it requires minute amounts of bacteria, low laser excitation power, and short integration times in order to achieve high signal. PMID:26752013

  16. Accurate Optical Detection of Amphiphiles at Liquid-Crystal-Water Interfaces

    NASA Astrophysics Data System (ADS)

    Popov, Piotr; Mann, Elizabeth K.; Jákli, Antal

    2014-04-01

    Liquid-crystal-based biosensors utilize the high sensitivity of liquid-crystal alignment to the presence of amphiphiles adsorbed to one of the liquid-crystal surfaces from water. They offer inexpensive, easy optical detection of biologically relevant molecules such as lipids, proteins, and cells. Present techniques use linear polarizers to analyze the alignment of the liquid crystal. The resulting images contain information not only about the liquid-crystal tilt with respect to the surface normal, the quantity which is controlled by surface adsorption, but also on the uncontrolled in-plane liquid-crystal alignment, thus making the detection largely qualitative. Here we show that detecting the liquid-crystal alignment between circular polarizers, which are only sensitive to the liquid-crystal tilt with respect to the interface normal, makes possible quantitative detection by measuring the transmitted light intensity with a spectrophotometer. Following a new procedure, not only the concentration dependence of the optical path difference but also the film thickness and the effective birefringence can be determined accurately. We also introduce a new "dynamic" mode of sensing, where (instead of the conventional "steady" mode, which detects the concentration dependence of the steady-state texture) we increase the concentration at a constant rate.

  17. Methodological Guidelines for Accurate Detection of Viruses in Wild Plant Species

    PubMed Central

    Renner, Kurra; Cole, Ellen; Seabloom, Eric W.; Borer, Elizabeth T.; Malmstrom, Carolyn M.

    2016-01-01

    Ecological understanding of disease risk, emergence, and dynamics and of the efficacy of control strategies relies heavily on efficient tools for microorganism identification and characterization. Misdetection, such as the misclassification of infected hosts as healthy, can strongly bias estimates of disease prevalence and lead to inaccurate conclusions. In natural plant ecosystems, interest in assessing microbial dynamics is increasing exponentially, but guidelines for detection of microorganisms in wild plants remain limited, particularly so for plant viruses. To address this gap, we explored issues and solutions associated with virus detection by serological and molecular methods in noncrop plant species as applied to the globally important Barley yellow dwarf virus PAV (Luteoviridae), which infects wild native plants as well as crops. With enzyme-linked immunosorbent assays (ELISA), we demonstrate how virus detection in a perennial wild plant species may be much greater in stems than in leaves, although leaves are most commonly sampled, and may also vary among tillers within an individual, thereby highlighting the importance of designing effective sampling strategies. With reverse transcription-PCR (RT-PCR), we demonstrate how inhibitors in tissues of perennial wild hosts can suppress virus detection but can be overcome with methods and products that improve isolation and amplification of nucleic acids. These examples demonstrate the paramount importance of testing and validating survey designs and virus detection methods for noncrop plant communities to ensure accurate ecological surveys and reliable assumptions about virus dynamics in wild hosts. PMID:26773088

  18. A Highly Accurate Inclusive Cancer Screening Test Using Caenorhabditis elegans Scent Detection

    PubMed Central

    Uozumi, Takayuki; Shinden, Yoshiaki; Mimori, Koshi; Maehara, Yoshihiko; Ueda, Naoko; Hamakawa, Masayuki

    2015-01-01

    Early detection and treatment are of vital importance to the successful eradication of various cancers, and development of economical and non-invasive novel cancer screening systems is critical. Previous reports using canine scent detection demonstrated the existence of cancer-specific odours. However, it is difficult to introduce canine scent recognition into clinical practice because of the need to maintain accuracy. In this study, we developed a Nematode Scent Detection Test (NSDT) using Caenorhabditis elegans to provide a novel highly accurate cancer detection system that is economical, painless, rapid and convenient. We demonstrated wild-type C. elegans displayed attractive chemotaxis towards human cancer cell secretions, cancer tissues and urine from cancer patients but avoided control urine; in parallel, the response of the olfactory neurons of C. elegans to the urine from cancer patients was significantly stronger than to control urine. In contrast, G protein α mutants and olfactory neurons-ablated animals were not attracted to cancer patient urine, suggesting that C. elegans senses odours in urine. We tested 242 samples to measure the performance of the NSDT, and found the sensitivity was 95.8%; this is markedly higher than that of other existing tumour markers. Furthermore, the specificity was 95.0%. Importantly, this test was able to diagnose various cancer types tested at the early stage (stage 0 or 1). To conclude, C. elegans scent-based analyses might provide a new strategy to detect and study disease-associated scents. PMID:25760772

  19. An accurate algorithm to match imperfectly matched images for lung tumor detection without markers.

    PubMed

    Rozario, Timothy; Bereg, Sergey; Yan, Yulong; Chiu, Tsuicheng; Liu, Honghuan; Kearney, Vasant; Jiang, Lan; Mao, Weihua

    2015-05-08

    implanted and used as ground truth for tumor positions. Although other organs and bony structures introduced strong signals superimposed on tumors at some angles, this method accurately located tumors on every projection over 12 gantry angles. The maximum error was less than 2.2 mm, while the total average error was less than 0.9mm. This algorithm was capable of detecting tumors without markers, despite strong background signals.

  20. Effective Echo Detection and Accurate Orbit Estimation Algorithms for Space Debris Radar

    NASA Astrophysics Data System (ADS)

    Isoda, Kentaro; Sakamoto, Takuya; Sato, Toru

    Orbit estimation of space debris, objects of no inherent value orbiting the earth, is a task that is important for avoiding collisions with spacecraft. The Kamisaibara Spaceguard Center radar system was built in 2004 as the first radar facility in Japan devoted to the observation of space debris. In order to detect the smaller debris, coherent integration is effective in improving SNR (Signal-to-Noise Ratio). However, it is difficult to apply coherent integration to real data because the motions of the targets are unknown. An effective algorithm is proposed for echo detection and orbit estimation of the faint echoes from space debris. The characteristics of the evaluation function are utilized by the algorithm. Experiments show the proposed algorithm improves SNR by 8.32dB and enables estimation of orbital parameters accurately to allow for re-tracking with a single radar.

  1. A simplified and accurate detection of the genetically modified wheat MON71800 with one calibrator plasmid.

    PubMed

    Kim, Jae-Hwan; Park, Saet-Byul; Roh, Hyo-Jeong; Park, Sunghoon; Shin, Min-Ki; Moon, Gui Im; Hong, Jin-Hwan; Kim, Hae-Yeong

    2015-06-01

    With the increasing number of genetically modified (GM) events, unauthorized GMO releases into the food market have increased dramatically, and many countries have developed detection tools for them. This study described the qualitative and quantitative detection methods of unauthorized the GM wheat MON71800 with a reference plasmid (pGEM-M71800). The wheat acetyl-CoA carboxylase (acc) gene was used as the endogenous gene. The plasmid pGEM-M71800, which contains both the acc gene and the event-specific target MON71800, was constructed as a positive control for the qualitative and quantitative analyses. The limit of detection in the qualitative PCR assay was approximately 10 copies. In the quantitative PCR assay, the standard deviation and relative standard deviation repeatability values ranged from 0.06 to 0.25 and from 0.23% to 1.12%, respectively. This study supplies a powerful and very simple but accurate detection strategy for unauthorized GM wheat MON71800 that utilizes a single calibrator plasmid.

  2. Fast and accurate border detection in dermoscopy images using statistical region merging

    NASA Astrophysics Data System (ADS)

    Celebi, M. Emre; Kingravi, Hassan A.; Iyatomi, Hitoshi; Lee, JeongKyu; Aslandogan, Y. Alp; Van Stoecker, William; Moss, Randy; Malters, Joseph M.; Marghoob, Ashfaq A.

    2007-03-01

    As a result of advances in skin imaging technology and the development of suitable image processing techniques during the last decade, there has been a significant increase of interest in the computer-aided diagnosis of melanoma. Automated border detection is one of the most important steps in this procedure, since the accuracy of the subsequent steps crucially depends on it. In this paper, a fast and unsupervised approach to border detection in dermoscopy images of pigmented skin lesions based on the Statistical Region Merging algorithm is presented. The method is tested on a set of 90 dermoscopy images. The border detection error is quantified by a metric in which a set of dermatologist-determined borders is used as the ground-truth. The proposed method is compared to six state-of-the-art automated methods (optimized histogram thresholding, orientation-sensitive fuzzy c-means, gradient vector flow snakes, dermatologist-like tumor extraction algorithm, meanshift clustering, and the modified JSEG method) and borders determined by a second dermatologist. The results demonstrate that the presented method achieves both fast and accurate border detection in dermoscopy images.

  3. On Radar Resolution in Coherent Change Detection.

    SciTech Connect

    Bickel, Douglas L.

    2015-11-01

    It is commonly observed that resolution plays a role in coherent change detection. Although this is the case, the relationship of the resolution in coherent change detection is not yet defined . In this document, we present an analytical method of evaluating this relationship using detection theory. Specifically we examine the effect of resolution on receiver operating characteristic curves for coherent change detection.

  4. Land Cover Change Detection Using Saliency Andwavelet Transformation

    NASA Astrophysics Data System (ADS)

    Zhang, Haopeng; Jiang, Zhiguo; Cheng, Yan

    2016-06-01

    How to obtain accurate difference map remains an open challenge in change detection. To tackle this problem, we propose a change detection method based on saliency detection and wavelet transformation. We do frequency-tuned saliency detection in initial difference image (IDI) obtained by logarithm ratio to get a salient difference image (SDI). Then, we calculate local entropy of SDI to obtain an entropic salient difference image (ESDI). The final difference image (FDI) is the wavelet fusion of IDI and ESDI, and Otsu thresholding is used to extract difference map from FDI. Experimental results validate the effectiveness and feasibility.

  5. Novel Accurate and Fast Optic Disc Detection in Retinal Images With Vessel Distribution and Directional Characteristics.

    PubMed

    Zhang, Dongbo; Zhao, Yuanyuan

    2016-01-01

    A novel accurate and fast optic disc (OD) detection method is proposed by using vessel distribution and directional characteristics. A feature combining three vessel distribution characteristics, i.e., local vessel density, compactness, and uniformity, is designed to find possible horizontal coordinate of OD. Then, according to the global vessel direction characteristic, a General Hough Transformation is introduced to identify the vertical coordinate of OD. By confining the possible OD vertical range and by simplifying vessel structure with blocks, we greatly decrease the computational cost of the algorithm. Four public datasets have been tested. The OD localization accuracy lies from 93.8% to 99.7%, when 8-20% vessel detection results are adopted to achieve OD detection. Average computation times for STARE images are about 3.4-11.5 s, which relate to image size. The proposed method shows satisfactory robustness on both normal and diseased images. It is better than many previous methods with respect to accuracy and efficiency.

  6. A Fabry-Perot interferometer for accurate measurement of temporal changes in stellar Doppler shift

    NASA Technical Reports Server (NTRS)

    Mcmillan, R. S.; Smith, P. H.; Frecker, J. E.; Merline, W. J.; Perry, M. L.

    1986-01-01

    The scrambling of incident light by an optical filter, and the stability obtainable through wavelength calibration by means of a tilt-tunable Fabry-Perot etalon, allow the accurate observation of Doppler shift changes in stellar absorption lines. Distinct, widely spaced monochromatic images of the entrance aperture are formed in the focal plane of the camera through a sampling of about 350 points on the profile of the stellar spectrum by successive orders of interferometric transmission through the etalon. Changes in Doppler shift modify the relative intensities of these images, in proportion to the slope of the spectral profile at each point sampled.

  7. Accurate Monitoring and Fault Detection in Wind Measuring Devices through Wireless Sensor Networks

    PubMed Central

    Khan, Komal Saifullah; Tariq, Muhammad

    2014-01-01

    Many wind energy projects report poor performance as low as 60% of the predicted performance. The reason for this is poor resource assessment and the use of new untested technologies and systems in remote locations. Predictions about the potential of an area for wind energy projects (through simulated models) may vary from the actual potential of the area. Hence, introducing accurate site assessment techniques will lead to accurate predictions of energy production from a particular area. We solve this problem by installing a Wireless Sensor Network (WSN) to periodically analyze the data from anemometers installed in that area. After comparative analysis of the acquired data, the anemometers transmit their readings through a WSN to the sink node for analysis. The sink node uses an iterative algorithm which sequentially detects any faulty anemometer and passes the details of the fault to the central system or main station. We apply the proposed technique in simulation as well as in practical implementation and study its accuracy by comparing the simulation results with experimental results to analyze the variation in the results obtained from both simulation model and implemented model. Simulation results show that the algorithm indicates faulty anemometers with high accuracy and low false alarm rate when as many as 25% of the anemometers become faulty. Experimental analysis shows that anemometers incorporating this solution are better assessed and performance level of implemented projects is increased above 86% of the simulated models. PMID:25421739

  8. Joint iris boundary detection and fit: a real-time method for accurate pupil tracking.

    PubMed

    Barbosa, Marconi; James, Andrew C

    2014-08-01

    A range of applications in visual science rely on accurate tracking of the human pupil's movement and contraction in response to light. While the literature for independent contour detection and fitting of the iris-pupil boundary is vast, a joint approach, in which it is assumed that the pupil has a given geometric shape has been largely overlooked. We present here a global method for simultaneously finding and fitting of an elliptic or circular contour against a dark interior, which produces consistently accurate results even under non-ideal recording conditions, such as reflections near and over the boundary, droopy eye lids, or the sudden formation of tears. The specific form of the proposed optimization problem allows us to write down closed analytic formulae for the gradient and the Hessian of the objective function. Moreover, both the objective function and its derivatives can be cast into vectorized form, making the proposed algorithm significantly faster than its closest relative in the literature. We compare methods in multiple ways, both analytically and numerically, using real iris images as well as idealizations of the iris for which the ground truth boundary is precisely known. The method proposed here is illustrated under challenging recording conditions and it is shown to be robust. PMID:25136477

  9. Medical Image Watermarking Technique for Accurate Tamper Detection in ROI and Exact Recovery of ROI.

    PubMed

    Eswaraiah, R; Sreenivasa Reddy, E

    2014-01-01

    In telemedicine while transferring medical images tampers may be introduced. Before making any diagnostic decisions, the integrity of region of interest (ROI) of the received medical image must be verified to avoid misdiagnosis. In this paper, we propose a novel fragile block based medical image watermarking technique to avoid embedding distortion inside ROI, verify integrity of ROI, detect accurately the tampered blocks inside ROI, and recover the original ROI with zero loss. In this proposed method, the medical image is segmented into three sets of pixels: ROI pixels, region of noninterest (RONI) pixels, and border pixels. Then, authentication data and information of ROI are embedded in border pixels. Recovery data of ROI is embedded into RONI. Results of experiments conducted on a number of medical images reveal that the proposed method produces high quality watermarked medical images, identifies the presence of tampers inside ROI with 100% accuracy, and recovers the original ROI without any loss.

  10. Medical Image Watermarking Technique for Accurate Tamper Detection in ROI and Exact Recovery of ROI

    PubMed Central

    Eswaraiah, R.; Sreenivasa Reddy, E.

    2014-01-01

    In telemedicine while transferring medical images tampers may be introduced. Before making any diagnostic decisions, the integrity of region of interest (ROI) of the received medical image must be verified to avoid misdiagnosis. In this paper, we propose a novel fragile block based medical image watermarking technique to avoid embedding distortion inside ROI, verify integrity of ROI, detect accurately the tampered blocks inside ROI, and recover the original ROI with zero loss. In this proposed method, the medical image is segmented into three sets of pixels: ROI pixels, region of noninterest (RONI) pixels, and border pixels. Then, authentication data and information of ROI are embedded in border pixels. Recovery data of ROI is embedded into RONI. Results of experiments conducted on a number of medical images reveal that the proposed method produces high quality watermarked medical images, identifies the presence of tampers inside ROI with 100% accuracy, and recovers the original ROI without any loss. PMID:25328515

  11. ROM Plus(®): accurate point-of-care detection of ruptured fetal membranes.

    PubMed

    McQuivey, Ross W; Block, Jon E

    2016-01-01

    Accurate and timely diagnosis of rupture of fetal membranes is imperative to inform and guide gestational age-specific interventions to optimize perinatal outcomes and reduce the risk of serious complications, including preterm delivery and infections. The ROM Plus is a rapid, point-of-care, qualitative immunochromatographic diagnostic test that uses a unique monoclonal/polyclonal antibody approach to detect two different proteins found in amniotic fluid at high concentrations: alpha-fetoprotein and insulin-like growth factor binding protein-1. Clinical study results have uniformly demonstrated high diagnostic accuracy and performance characteristics with this point-of-care test that exceeds conventional clinical testing with external laboratory evaluation. The description, indications for use, procedural steps, and laboratory and clinical characterization of this assay are presented in this article. PMID:27274316

  12. Tissue resonance interaction accurately detects colon lesions: A double-blind pilot study

    PubMed Central

    Dore, Maria P; Tufano, Marcello O; Pes, Giovanni M; Cuccu, Marianna; Farina, Valentina; Manca, Alessandra; Graham, David Y

    2015-01-01

    AIM: To investigated the performance of the tissue resonance interaction method (TRIM) for the non-invasive detection of colon lesions. METHODS: We performed a prospective single-center blinded pilot study of consecutive adults undergoing colonoscopy at the University Hospital in Sassari, Italy. Before patients underwent colonoscopy, they were examined by the TRIMprobe which detects differences in electromagnetic properties between pathological and normal tissues. All patients had completed the polyethylene glycol-containing bowel prep for the colonoscopy procedure before being screened. During the procedure the subjects remained fully dressed. A hand-held probe was moved over the abdomen and variations in electromagnetic signals were recorded for 3 spectral lines (462-465 MHz, 930 MHz, and 1395 MHz). A single investigator, blind to any clinical information, performed the test using the TRIMprob system. Abnormal signals were identified and recorded as malignant or benign (adenoma or hyperplastic polyps). Findings were compared with those from colonoscopy with histologic confirmation. Statistical analysis was performed by χ2 test. RESULTS: A total of 305 consecutive patients fulfilling the inclusion criteria were enrolled over a period of 12 months. The most frequent indication for colonoscopy was abdominal pain (33%). The TRIMprob was well accepted by all patients; none spontaneously complained about the procedure, and no adverse effects were observed. TRIM proved inaccurate for polyp detection in patients with inflammatory bowel disease (IBD) and they were excluded leaving 281 subjects (mean age 59 ± 13 years; 107 males). The TRIM detected and accurately characterized all 12 adenocarcinomas and 135/137 polyps (98.5%) including 64 adenomatous (100%) found. The method identified cancers and polyps with 98.7% sensitivity, 96.2% specificity, and 97.5% diagnostic accuracy, compared to colonoscopy and histology analyses. The positive predictive value was 96.7% and the

  13. Detection of light transformations and concomitant changes in surface albedo

    PubMed Central

    Gerhard, Holly E.; Maloney, Laurence T.

    2010-01-01

    We report two experiments demonstrating that (1) observers are sensitive to information about changes in the light field not captured by local scene statistics and that (2) they can use this information to enhance detection of changes in surface albedo. Observers viewed scenes consisting of matte surfaces at many orientations illuminated by a collimated light source. All surfaces were achromatic, all lights neutral. In the first experiment, observers attempted to discriminate small changes in direction of the collimated light source (light transformations) from matched changes in the albedos of all surfaces (non-light transformations). Light changes and non-light changes shared the same local scene statistics and edge ratios, but the latter were not consistent with any change in direction to the collimated source. We found that observers could discriminate light changes as small as 5 degrees with sensitivity d′ > 1 and accurately judge the direction of change. In a second experiment, we measured observers' ability to detect a change in the surface albedo of an isolated surface patch during either a light change or a surface change. Observers were more accurate in detecting isolated albedo changes during light changes. Measures of sensitivity d′ were more than twice as great. PMID:20884599

  14. An accurate heart beat detection method in the EKG recorded in fMRI system.

    PubMed

    Oh, Sung Suk; Chung, Jun-Young; Yoon, Hyo Woon; Park, HyunWook

    2007-01-01

    The simultaneous recording of functional magnetic resonance imaging (fMRI) and electroencephalogram (EEG) provides an efficient signal for the high spatiotemporal brain mapping because each modality provides complementary information. The peak detection in the EEG signal measured in the MR scanner is necessary for removal of the ballistocardiac artifact. Especially, it would be affected by the quality of the EKG signal and the variation of the heart beat rate. Therefore, we propose the peak detection method using a K-teager energy operator (K-TEO) as well as further refinement processes in order to detect precise peaks. We applied this technique to the analysis of simulation waves with random noise and abrupt heat beat changes.

  15. COSMOS: accurate detection of somatic structural variations through asymmetric comparison between tumor and normal samples.

    PubMed

    Yamagata, Koichi; Yamanishi, Ayako; Kokubu, Chikara; Takeda, Junji; Sese, Jun

    2016-05-01

    An important challenge in cancer genomics is precise detection of structural variations (SVs) by high-throughput short-read sequencing, which is hampered by the high false discovery rates of existing analysis tools. Here, we propose an accurate SV detection method named COSMOS, which compares the statistics of the mapped read pairs in tumor samples with isogenic normal control samples in a distinct asymmetric manner. COSMOS also prioritizes the candidate SVs using strand-specific read-depth information. Performance tests on modeled tumor genomes revealed that COSMOS outperformed existing methods in terms of F-measure. We also applied COSMOS to an experimental mouse cell-based model, in which SVs were induced by genome engineering and gamma-ray irradiation, followed by polymerase chain reaction-based confirmation. The precision of COSMOS was 84.5%, while the next best existing method was 70.4%. Moreover, the sensitivity of COSMOS was the highest, indicating that COSMOS has great potential for cancer genome analysis.

  16. Detection and accurate identification of new or emerging bacteria in cystic fibrosis patients.

    PubMed

    Bittar, F; Rolain, J-M

    2010-07-01

    Respiratory infections remain a major threat to cystic fibrosis (CF) patients. The detection and correct identification of the bacteria implicated in these infections is critical for the therapeutic management of patients. The traditional methods of culture and phenotypic identification of bacteria lack both sensitivity and specificity because many bacteria can be missed and/or misidentified. Molecular analyses have recently emerged as useful means to resolve these problems, including molecular methods for accurate identification or detection of bacteria and molecular methods for evaluation of microbial diversity. These recent molecular technologies have increased the list of new and/or emerging pathogens and epidemic strains associated with CF patients. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry of intact cells has also emerged recently as a powerful and rapid method for the routine identification of bacteria in clinical microbiology laboratories and will certainly represent the method of choice also for the routine identification of bacteria in the context of CF. Finally, recent data derived from molecular culture-independent analyses indicate the presence of a previously underestimated, complex microbial community in sputa from CF patients. Interestingly, full genome sequencing of some bacteria frequently recovered from CF patients has highlighted the fact that the lungs of CF patients are hotspots for lateral gene transfer and the adaptation of these ecosystems to a specific chronic condition.

  17. COSMOS: accurate detection of somatic structural variations through asymmetric comparison between tumor and normal samples

    PubMed Central

    Yamagata, Koichi; Yamanishi, Ayako; Kokubu, Chikara; Takeda, Junji; Sese, Jun

    2016-01-01

    An important challenge in cancer genomics is precise detection of structural variations (SVs) by high-throughput short-read sequencing, which is hampered by the high false discovery rates of existing analysis tools. Here, we propose an accurate SV detection method named COSMOS, which compares the statistics of the mapped read pairs in tumor samples with isogenic normal control samples in a distinct asymmetric manner. COSMOS also prioritizes the candidate SVs using strand-specific read-depth information. Performance tests on modeled tumor genomes revealed that COSMOS outperformed existing methods in terms of F-measure. We also applied COSMOS to an experimental mouse cell-based model, in which SVs were induced by genome engineering and gamma-ray irradiation, followed by polymerase chain reaction-based confirmation. The precision of COSMOS was 84.5%, while the next best existing method was 70.4%. Moreover, the sensitivity of COSMOS was the highest, indicating that COSMOS has great potential for cancer genome analysis. PMID:26833260

  18. Active change detection by pigeons and humans.

    PubMed

    Hagmann, Carl Erick; Cook, Robert G

    2013-10-01

    Detecting change is vital to both human and nonhuman animals' interactions with the environment. Using the go/no-go dynamic change detection task, we examined the capacity of four pigeons to detect changes in brightness of an area on a computer display. In contrast to our prior research, we reversed the response contingencies so that the animals had to actively inhibit pecking upon detecting change in brightness rather than its constancy. Testing eight rates of change revealed that this direct report change detection contingency produced results equivalent to the earlier indirect procedure. Corresponding tests with humans suggested that the temporal dynamics of detecting change were similar for both species. The results indicate the mechanisms of change detection in both pigeons and humans are organized in similar ways, although limitations in the operations of working memory may prevent pigeons from integrating information over the same time scale as humans.

  19. Change in heat capacity accurately predicts vibrational coupling in enzyme catalyzed reactions.

    PubMed

    Arcus, Vickery L; Pudney, Christopher R

    2015-08-01

    The temperature dependence of kinetic isotope effects (KIEs) have been used to infer the vibrational coupling of the protein and or substrate to the reaction coordinate, particularly in enzyme-catalyzed hydrogen transfer reactions. We find that a new model for the temperature dependence of experimentally determined observed rate constants (macromolecular rate theory, MMRT) is able to accurately predict the occurrence of vibrational coupling, even where the temperature dependence of the KIE fails. This model, that incorporates the change in heat capacity for enzyme catalysis, demonstrates remarkable consistency with both experiment and theory and in many respects is more robust than models used at present.

  20. Can phenological models predict tree phenology accurately under climate change conditions?

    NASA Astrophysics Data System (ADS)

    Chuine, Isabelle; Bonhomme, Marc; Legave, Jean Michel; García de Cortázar-Atauri, Inaki; Charrier, Guillaume; Lacointe, André; Améglio, Thierry

    2014-05-01

    The onset of the growing season of trees has been globally earlier by 2.3 days/decade during the last 50 years because of global warming and this trend is predicted to continue according to climate forecast. The effect of temperature on plant phenology is however not linear because temperature has a dual effect on bud development. On one hand, low temperatures are necessary to break bud dormancy, and on the other hand higher temperatures are necessary to promote bud cells growth afterwards. Increasing phenological changes in temperate woody species have strong impacts on forest trees distribution and productivity, as well as crops cultivation areas. Accurate predictions of trees phenology are therefore a prerequisite to understand and foresee the impacts of climate change on forests and agrosystems. Different process-based models have been developed in the last two decades to predict the date of budburst or flowering of woody species. They are two main families: (1) one-phase models which consider only the ecodormancy phase and make the assumption that endodormancy is always broken before adequate climatic conditions for cell growth occur; and (2) two-phase models which consider both the endodormancy and ecodormancy phases and predict a date of dormancy break which varies from year to year. So far, one-phase models have been able to predict accurately tree bud break and flowering under historical climate. However, because they do not consider what happens prior to ecodormancy, and especially the possible negative effect of winter temperature warming on dormancy break, it seems unlikely that they can provide accurate predictions in future climate conditions. It is indeed well known that a lack of low temperature results in abnormal pattern of bud break and development in temperate fruit trees. An accurate modelling of the dormancy break date has thus become a major issue in phenology modelling. Two-phases phenological models predict that global warming should delay

  1. Fast and Accurate Microplate Method (Biolog MT2) for Detection of Fusarium Fungicides Resistance/Sensitivity

    PubMed Central

    Frąc, Magdalena; Gryta, Agata; Oszust, Karolina; Kotowicz, Natalia

    2016-01-01

    The need for finding fungicides against Fusarium is a key step in the chemical plant protection and using appropriate chemical agents. Existing, conventional methods of evaluation of Fusarium isolates resistance to fungicides are costly, time-consuming and potentially environmentally harmful due to usage of high amounts of potentially toxic chemicals. Therefore, the development of fast, accurate and effective detection methods for Fusarium resistance to fungicides is urgently required. MT2 microplates (BiologTM) method is traditionally used for bacteria identification and the evaluation of their ability to utilize different carbon substrates. However, to the best of our knowledge, there is no reports concerning the use of this technical tool to determine fungicides resistance of the Fusarium isolates. For this reason, the objectives of this study are to develop a fast method for Fusarium resistance to fungicides detection and to validate the effectiveness approach between both traditional hole-plate and MT2 microplates assays. In presented study MT2 microplate-based assay was evaluated for potential use as an alternative resistance detection method. This was carried out using three commercially available fungicides, containing following active substances: triazoles (tebuconazole), benzimidazoles (carbendazim) and strobilurins (azoxystrobin), in six concentrations (0, 0.0005, 0.005, 0.05, 0.1, 0.2%), for nine selected Fusarium isolates. In this study, the particular concentrations of each fungicides was loaded into MT2 microplate wells. The wells were inoculated with the Fusarium mycelium suspended in PM4-IF inoculating fluid. Before inoculation the suspension was standardized for each isolates into 75% of transmittance. Traditional hole-plate method was used as a control assay. The fungicides concentrations in control method were the following: 0, 0.0005, 0.005, 0.05, 0.5, 1, 2, 5, 10, 25, and 50%. Strong relationships between MT2 microplate and traditional hole

  2. Fast and Accurate Microplate Method (Biolog MT2) for Detection of Fusarium Fungicides Resistance/Sensitivity.

    PubMed

    Frąc, Magdalena; Gryta, Agata; Oszust, Karolina; Kotowicz, Natalia

    2016-01-01

    The need for finding fungicides against Fusarium is a key step in the chemical plant protection and using appropriate chemical agents. Existing, conventional methods of evaluation of Fusarium isolates resistance to fungicides are costly, time-consuming and potentially environmentally harmful due to usage of high amounts of potentially toxic chemicals. Therefore, the development of fast, accurate and effective detection methods for Fusarium resistance to fungicides is urgently required. MT2 microplates (Biolog(TM)) method is traditionally used for bacteria identification and the evaluation of their ability to utilize different carbon substrates. However, to the best of our knowledge, there is no reports concerning the use of this technical tool to determine fungicides resistance of the Fusarium isolates. For this reason, the objectives of this study are to develop a fast method for Fusarium resistance to fungicides detection and to validate the effectiveness approach between both traditional hole-plate and MT2 microplates assays. In presented study MT2 microplate-based assay was evaluated for potential use as an alternative resistance detection method. This was carried out using three commercially available fungicides, containing following active substances: triazoles (tebuconazole), benzimidazoles (carbendazim) and strobilurins (azoxystrobin), in six concentrations (0, 0.0005, 0.005, 0.05, 0.1, 0.2%), for nine selected Fusarium isolates. In this study, the particular concentrations of each fungicides was loaded into MT2 microplate wells. The wells were inoculated with the Fusarium mycelium suspended in PM4-IF inoculating fluid. Before inoculation the suspension was standardized for each isolates into 75% of transmittance. Traditional hole-plate method was used as a control assay. The fungicides concentrations in control method were the following: 0, 0.0005, 0.005, 0.05, 0.5, 1, 2, 5, 10, 25, and 50%. Strong relationships between MT2 microplate and traditional hole

  3. Guided resonances on lithium niobate for extremely small electric field detection investigated by accurate sensitivity analysis.

    PubMed

    Qiu, Wentao; Ndao, Abdoulaye; Lu, Huihui; Bernal, Maria-Pilar; Baida, Fadi Issam

    2016-09-01

    We present a theoretical study of guided resonances (GR) on a thin film lithium niobate rectangular lattice photonic crystal by band diagram calculations and 3D Finite Difference Time Domain (FDTD) transmission investigations which cover a broad range of parameters. A photonic crystal with an active zone as small as 13μm×13μm×0.7μm can be easily designed to obtain a resonance Q value in the order of 1000. These resonances are then employed in electric field (E-field) sensing applications exploiting the electro optic (EO) effect of lithium niobate. A local field factor that is calculated locally for each FDTD cell is proposed to accurately estimate the sensitivity of GR based E-field sensor. The local field factor allows well agreement between simulations and reported experimental data therefore providing a valuable method in optimizing the GR structure to obtain high sensitivities. When these resonances are associated with sub-picometer optical spectrum analyzer and high field enhancement antenna design, an E-field probe with a sensitivity of 50 μV/m could be achieved. The results of our simulations could be also exploited in other EO based applications such as EEG (Electroencephalography) or ECG (Electrocardiography) probe and E-field frequency detector with an 'invisible' probe to the field being detected etc. PMID:27607627

  4. Possibility of detecting anisotropic expansion of the universe by very accurate astrometry measurements.

    PubMed

    Quercellini, Claudia; Quartin, Miguel; Amendola, Luca

    2009-04-17

    Refined astrometry measurements allow us to detect large-scale deviations from isotropy through real-time observations of changes in the angular separation between sources at cosmic distances. This "cosmic parallax" effect is a powerful consistency test of the Friedmann-Robertson-Walker metric and may set independent constraints on cosmic anisotropy. We apply this novel general test to Lemaitre-Tolman-Bondi cosmologies with off-center observers and show that future satellite missions such as Gaia might achieve accuracies that would put limits on the off-center distance which are competitive with cosmic microwave background dipole constraints. PMID:19518616

  5. Three-dimensional accurate detection of lung emphysema in rats using ultra-short and zero echo time MRI.

    PubMed

    Bianchi, Andrea; Tibiletti, Marta; Kjørstad, Åsmund; Birk, Gerald; Schad, Lothar R; Stierstorfer, Birgit; Rasche, Volker; Stiller, Detlef

    2015-11-01

    Emphysema is a life-threatening pathology that causes irreversible destruction of alveolar walls. In vivo imaging techniques play a fundamental role in the early non-invasive pre-clinical and clinical detection and longitudinal follow-up of this pathology. In the present study, we aimed to evaluate the feasibility of using high resolution radial three-dimensional (3D) zero echo time (ZTE) and 3D ultra-short echo time (UTE) MRI to accurately detect lung pathomorphological changes in a rodent model of emphysema.Porcine pancreas elastase (PPE) was intratracheally administered to the rats to produce the emphysematous changes. 3D ZTE MRI, low and high definition 3D UTE MRI and micro-computed tomography images were acquired 4 weeks after the PPE challenge. Signal-to-noise ratios (SNRs) were measured in PPE-treated and control rats. T2* values were computed from low definition 3D UTE MRI. Histomorphometric measurements were made after euthanizing the animals. Both ZTE and UTE MR images showed a significant decrease in the SNR measured in PPE-treated lungs compared with controls, due to the pathomorphological changes taking place in the challenged lungs. A significant decrease in T2* values in PPE-challenged animals compared with controls was measured using UTE MRI. Histomorphometric measurements showed a significant increase in the mean linear intercept in PPE-treated lungs. UTE yielded significantly higher SNR compared with ZTE (14% and 30% higher in PPE-treated and non-PPE-treated lungs, respectively).This study showed that optimized 3D radial UTE and ZTE MRI can provide lung images of excellent quality, with high isotropic spatial resolution (400 µm) and SNR in parenchymal tissue (>25) and negligible motion artifacts in freely breathing animals. These techniques were shown to be useful non-invasive instruments to accurately and reliably detect the pathomorphological alterations taking place in emphysematous lungs, without incurring the risks of cumulative radiation

  6. MIDAS robust trend estimator for accurate GPS station velocities without step detection

    NASA Astrophysics Data System (ADS)

    Blewitt, Geoffrey; Kreemer, Corné; Hammond, William C.; Gazeaux, Julien

    2016-03-01

    Automatic estimation of velocities from GPS coordinate time series is becoming required to cope with the exponentially increasing flood of available data, but problems detectable to the human eye are often overlooked. This motivates us to find an automatic and accurate estimator of trend that is resistant to common problems such as step discontinuities, outliers, seasonality, skewness, and heteroscedasticity. Developed here, Median Interannual Difference Adjusted for Skewness (MIDAS) is a variant of the Theil-Sen median trend estimator, for which the ordinary version is the median of slopes vij = (xj-xi)/(tj-ti) computed between all data pairs i > j. For normally distributed data, Theil-Sen and least squares trend estimates are statistically identical, but unlike least squares, Theil-Sen is resistant to undetected data problems. To mitigate both seasonality and step discontinuities, MIDAS selects data pairs separated by 1 year. This condition is relaxed for time series with gaps so that all data are used. Slopes from data pairs spanning a step function produce one-sided outliers that can bias the median. To reduce bias, MIDAS removes outliers and recomputes the median. MIDAS also computes a robust and realistic estimate of trend uncertainty. Statistical tests using GPS data in the rigid North American plate interior show ±0.23 mm/yr root-mean-square (RMS) accuracy in horizontal velocity. In blind tests using synthetic data, MIDAS velocities have an RMS accuracy of ±0.33 mm/yr horizontal, ±1.1 mm/yr up, with a 5th percentile range smaller than all 20 automatic estimators tested. Considering its general nature, MIDAS has the potential for broader application in the geosciences.

  7. MIDAS robust trend estimator for accurate GPS station velocities without step detection

    PubMed Central

    Kreemer, Corné; Hammond, William C.; Gazeaux, Julien

    2016-01-01

    Abstract Automatic estimation of velocities from GPS coordinate time series is becoming required to cope with the exponentially increasing flood of available data, but problems detectable to the human eye are often overlooked. This motivates us to find an automatic and accurate estimator of trend that is resistant to common problems such as step discontinuities, outliers, seasonality, skewness, and heteroscedasticity. Developed here, Median Interannual Difference Adjusted for Skewness (MIDAS) is a variant of the Theil‐Sen median trend estimator, for which the ordinary version is the median of slopes vij = (xj–xi)/(tj–ti) computed between all data pairs i > j. For normally distributed data, Theil‐Sen and least squares trend estimates are statistically identical, but unlike least squares, Theil‐Sen is resistant to undetected data problems. To mitigate both seasonality and step discontinuities, MIDAS selects data pairs separated by 1 year. This condition is relaxed for time series with gaps so that all data are used. Slopes from data pairs spanning a step function produce one‐sided outliers that can bias the median. To reduce bias, MIDAS removes outliers and recomputes the median. MIDAS also computes a robust and realistic estimate of trend uncertainty. Statistical tests using GPS data in the rigid North American plate interior show ±0.23 mm/yr root‐mean‐square (RMS) accuracy in horizontal velocity. In blind tests using synthetic data, MIDAS velocities have an RMS accuracy of ±0.33 mm/yr horizontal, ±1.1 mm/yr up, with a 5th percentile range smaller than all 20 automatic estimators tested. Considering its general nature, MIDAS has the potential for broader application in the geosciences. PMID:27668140

  8. MIDAS robust trend estimator for accurate GPS station velocities without step detection

    PubMed Central

    Kreemer, Corné; Hammond, William C.; Gazeaux, Julien

    2016-01-01

    Abstract Automatic estimation of velocities from GPS coordinate time series is becoming required to cope with the exponentially increasing flood of available data, but problems detectable to the human eye are often overlooked. This motivates us to find an automatic and accurate estimator of trend that is resistant to common problems such as step discontinuities, outliers, seasonality, skewness, and heteroscedasticity. Developed here, Median Interannual Difference Adjusted for Skewness (MIDAS) is a variant of the Theil‐Sen median trend estimator, for which the ordinary version is the median of slopes vij = (xj–xi)/(tj–ti) computed between all data pairs i > j. For normally distributed data, Theil‐Sen and least squares trend estimates are statistically identical, but unlike least squares, Theil‐Sen is resistant to undetected data problems. To mitigate both seasonality and step discontinuities, MIDAS selects data pairs separated by 1 year. This condition is relaxed for time series with gaps so that all data are used. Slopes from data pairs spanning a step function produce one‐sided outliers that can bias the median. To reduce bias, MIDAS removes outliers and recomputes the median. MIDAS also computes a robust and realistic estimate of trend uncertainty. Statistical tests using GPS data in the rigid North American plate interior show ±0.23 mm/yr root‐mean‐square (RMS) accuracy in horizontal velocity. In blind tests using synthetic data, MIDAS velocities have an RMS accuracy of ±0.33 mm/yr horizontal, ±1.1 mm/yr up, with a 5th percentile range smaller than all 20 automatic estimators tested. Considering its general nature, MIDAS has the potential for broader application in the geosciences.

  9. Accurate tracking of tumor volume change during radiotherapy by CT-CBCT registration with intensity correction

    NASA Astrophysics Data System (ADS)

    Park, Seyoun; Robinson, Adam; Quon, Harry; Kiess, Ana P.; Shen, Colette; Wong, John; Plishker, William; Shekhar, Raj; Lee, Junghoon

    2016-03-01

    In this paper, we propose a CT-CBCT registration method to accurately predict the tumor volume change based on daily cone-beam CTs (CBCTs) during radiotherapy. CBCT is commonly used to reduce patient setup error during radiotherapy, but its poor image quality impedes accurate monitoring of anatomical changes. Although physician's contours drawn on the planning CT can be automatically propagated to daily CBCTs by deformable image registration (DIR), artifacts in CBCT often cause undesirable errors. To improve the accuracy of the registration-based segmentation, we developed a DIR method that iteratively corrects CBCT intensities by local histogram matching. Three popular DIR algorithms (B-spline, demons, and optical flow) with the intensity correction were implemented on a graphics processing unit for efficient computation. We evaluated their performances on six head and neck (HN) cancer cases. For each case, four trained scientists manually contoured the nodal gross tumor volume (GTV) on the planning CT and every other fraction CBCTs to which the propagated GTV contours by DIR were compared. The performance was also compared with commercial image registration software based on conventional mutual information (MI), VelocityAI (Varian Medical Systems Inc.). The volume differences (mean±std in cc) between the average of the manual segmentations and automatic segmentations are 3.70+/-2.30 (B-spline), 1.25+/-1.78 (demons), 0.93+/-1.14 (optical flow), and 4.39+/-3.86 (VelocityAI). The proposed method significantly reduced the estimation error by 9% (B-spline), 38% (demons), and 51% (optical flow) over the results using VelocityAI. Although demonstrated only on HN nodal GTVs, the results imply that the proposed method can produce improved segmentation of other critical structures over conventional methods.

  10. Accurate, multi-kb reads resolve complex populations and detect rare microorganisms.

    PubMed

    Sharon, Itai; Kertesz, Michael; Hug, Laura A; Pushkarev, Dmitry; Blauwkamp, Timothy A; Castelle, Cindy J; Amirebrahimi, Mojgan; Thomas, Brian C; Burstein, David; Tringe, Susannah G; Williams, Kenneth H; Banfield, Jillian F

    2015-04-01

    Accurate evaluation of microbial communities is essential for understanding global biogeochemical processes and can guide bioremediation and medical treatments. Metagenomics is most commonly used to analyze microbial diversity and metabolic potential, but assemblies of the short reads generated by current sequencing platforms may fail to recover heterogeneous strain populations and rare organisms. Here we used short (150-bp) and long (multi-kb) synthetic reads to evaluate strain heterogeneity and study microorganisms at low abundance in complex microbial communities from terrestrial sediments. The long-read data revealed multiple (probably dozens of) closely related species and strains from previously undescribed Deltaproteobacteria and Aminicenantes (candidate phylum OP8). Notably, these are the most abundant organisms in the communities, yet short-read assemblies achieved only partial genome coverage, mostly in the form of short scaffolds (N50 = ∼ 2200 bp). Genome architecture and metabolic potential for these lineages were reconstructed using a new synteny-based method. Analysis of long-read data also revealed thousands of species whose abundances were <0.1% in all samples. Most of the organisms in this "long tail" of rare organisms belong to phyla that are also represented by abundant organisms. Genes encoding glycosyl hydrolases are significantly more abundant than expected in rare genomes, suggesting that rare species may augment the capability for carbon turnover and confer resilience to changing environmental conditions. Overall, the study showed that a diversity of closely related strains and rare organisms account for a major portion of the communities. These are probably common features of many microbial communities and can be effectively studied using a combination of long and short reads.

  11. Accurate, multi-kb reads resolve complex populations and detect rare microorganisms

    PubMed Central

    Sharon, Itai; Kertesz, Michael; Hug, Laura A.; Pushkarev, Dmitry; Blauwkamp, Timothy A.; Castelle, Cindy J.; Amirebrahimi, Mojgan; Thomas, Brian C.; Burstein, David; Tringe, Susannah G.; Williams, Kenneth H.

    2015-01-01

    Accurate evaluation of microbial communities is essential for understanding global biogeochemical processes and can guide bioremediation and medical treatments. Metagenomics is most commonly used to analyze microbial diversity and metabolic potential, but assemblies of the short reads generated by current sequencing platforms may fail to recover heterogeneous strain populations and rare organisms. Here we used short (150-bp) and long (multi-kb) synthetic reads to evaluate strain heterogeneity and study microorganisms at low abundance in complex microbial communities from terrestrial sediments. The long-read data revealed multiple (probably dozens of) closely related species and strains from previously undescribed Deltaproteobacteria and Aminicenantes (candidate phylum OP8). Notably, these are the most abundant organisms in the communities, yet short-read assemblies achieved only partial genome coverage, mostly in the form of short scaffolds (N50 = ∼2200 bp). Genome architecture and metabolic potential for these lineages were reconstructed using a new synteny-based method. Analysis of long-read data also revealed thousands of species whose abundances were <0.1% in all samples. Most of the organisms in this “long tail” of rare organisms belong to phyla that are also represented by abundant organisms. Genes encoding glycosyl hydrolases are significantly more abundant than expected in rare genomes, suggesting that rare species may augment the capability for carbon turnover and confer resilience to changing environmental conditions. Overall, the study showed that a diversity of closely related strains and rare organisms account for a major portion of the communities. These are probably common features of many microbial communities and can be effectively studied using a combination of long and short reads. PMID:25665577

  12. Anomalous change detection in imagery

    DOEpatents

    Theiler, James P.; Perkins, Simon J.

    2011-05-31

    A distribution-based anomaly detection platform is described that identifies a non-flat background that is specified in terms of the distribution of the data. A resampling approach is also disclosed employing scrambled resampling of the original data with one class specified by the data and the other by the explicit distribution, and solving using binary classification.

  13. Detecting abrupt dynamic change based on changes in the fractal properties of spatial images

    NASA Astrophysics Data System (ADS)

    Liu, Qunqun; He, Wenping; Gu, Bin; Jiang, Yundi

    2016-08-01

    Many abrupt climate change events often cannot be detected timely by conventional abrupt detection methods until a few years after these events have occurred. The reason for this lag in detection is that abundant and long-term observational data are required for accurate abrupt change detection by these methods, especially for the detection of a regime shift. So, these methods cannot help us understand and forecast the evolution of the climate system in a timely manner. Obviously, spatial images, generated by a coupled spatiotemporal dynamical model, contain more information about a dynamic system than a single time series, and we find that spatial images show the fractal properties. The fractal properties of spatial images can be quantitatively characterized by the Hurst exponent, which can be estimated by two-dimensional detrended fluctuation analysis (TD-DFA). Based on this, TD-DFA is used to detect an abrupt dynamic change of a coupled spatiotemporal model. The results show that the TD-DFA method can effectively detect abrupt parameter changes in the coupled model by monitoring the changing in the fractal properties of spatial images. The present method provides a new way for abrupt dynamic change detection, which can achieve timely and efficient abrupt change detection results.

  14. Image Change Detection via Ensemble Learning

    SciTech Connect

    Martin, Benjamin W; Vatsavai, Raju

    2013-01-01

    The concept of geographic change detection is relevant in many areas. Changes in geography can reveal much information about a particular location. For example, analysis of changes in geography can identify regions of population growth, change in land use, and potential environmental disturbance. A common way to perform change detection is to use a simple method such as differencing to detect regions of change. Though these techniques are simple, often the application of these techniques is very limited. Recently, use of machine learning methods such as neural networks for change detection has been explored with great success. In this work, we explore the use of ensemble learning methodologies for detecting changes in bitemporal synthetic aperture radar (SAR) images. Ensemble learning uses a collection of weak machine learning classifiers to create a stronger classifier which has higher accuracy than the individual classifiers in the ensemble. The strength of the ensemble lies in the fact that the individual classifiers in the ensemble create a mixture of experts in which the final classification made by the ensemble classifier is calculated from the outputs of the individual classifiers. Our methodology leverages this aspect of ensemble learning by training collections of weak decision tree based classifiers to identify regions of change in SAR images collected of a region in the Staten Island, New York area during Hurricane Sandy. Preliminary studies show that the ensemble method has approximately 11.5% higher change detection accuracy than an individual classifier.

  15. Context sensitivity in the detection of changes in facial emotion

    PubMed Central

    Yamashita, Yuichi; Fujimura, Tomomi; Katahira, Kentaro; Honda, Manabu; Okada, Masato; Okanoya, Kazuo

    2016-01-01

    In social contexts, reading subtle changes in others’ facial expressions is a crucial communication skill. To measure this ability, we developed an expression-change detection task, wherein a series of pictures of changes in an individual’s facial expressions within contextual scenes were presented. The results demonstrated that the detection of subtle changes was highly sensitive to contextual stimuli. That is, participants identified the direction of facial-expression changes more accurately and more quickly when they were ‘appropriate’—consistent with the valence of the contextual stimulus change—than when they were ‘inappropriate’. Moreover, individual differences in sensitivity to contextual stimuli were correlated with scores on the Toronto Alexithymia Scale, a commonly used measure of alexithymia tendencies. These results suggest that the current behavioural task might facilitate investigations of the role of context in human social cognition. PMID:27291099

  16. Detecting Children's Lies: Are Parents Accurate Judges of Their Own Children's Lies?

    ERIC Educational Resources Information Center

    Talwar, Victoria; Renaud, Sarah-Jane; Conway, Lauryn

    2015-01-01

    The current study investigated whether parents are accurate judges of their own children's lie-telling behavior. Participants included 250 mother-child dyads. Children were between three and 11 years of age. A temptation resistance paradigm was used to elicit a minor transgressive behavior from the children involving peeking at a forbidden toy and…

  17. Indigenous people's detection of rapid ecological change.

    PubMed

    Aswani, Shankar; Lauer, Matthew

    2014-06-01

    When sudden catastrophic events occur, it becomes critical for coastal communities to detect and respond to environmental transformations because failure to do so may undermine overall ecosystem resilience and threaten people's livelihoods. We therefore asked how capable of detecting rapid ecological change following massive environmental disruptions local, indigenous people are. We assessed the direction and periodicity of experimental learning of people in the Western Solomon Islands after a tsunami in 2007. We compared the results of marine science surveys with local ecological knowledge of the benthos across 3 affected villages and 3 periods before and after the tsunami. We sought to determine how people recognize biophysical changes in the environment before and after catastrophic events such as earthquakes and tsunamis and whether people have the ability to detect ecological changes over short time scales or need longer time scales to recognize changes. Indigenous people were able to detect changes in the benthos over time. Detection levels differed between marine science surveys and local ecological knowledge sources over time, but overall patterns of statistically significant detection of change were evident for various habitats. Our findings have implications for marine conservation, coastal management policies, and disaster-relief efforts because when people are able to detect ecological changes, this, in turn, affects how they exploit and manage their marine resources.

  18. Anger superiority effect for change detection and change blindness.

    PubMed

    Lyyra, Pessi; Hietanen, Jari K; Astikainen, Piia

    2014-11-01

    In visual search, an angry face in a crowd "pops out" unlike a happy or a neutral face. This "anger superiority effect" conflicts with views of visual perception holding that complex stimulus contents cannot be detected without focused top-down attention. Implicit visual processing of threatening changes was studied by recording event-related potentials (ERPs) using facial stimuli using the change blindness paradigm, in which conscious change detection is eliminated by presenting a blank screen before the changes. Already before their conscious detection, angry faces modulated relatively early emotion sensitive ERPs when appearing among happy and neutral faces, but happy faces only among neutral, not angry faces. Conscious change detection was more efficient for angry than happy faces regardless of background. These findings indicate that the brain can implicitly extract complex emotional information from facial stimuli, and the biological relevance of threatening contents can speed up their break up into visual consciousness.

  19. The relationship between change detection and recognition of centrally attended objects in motion pictures.

    PubMed

    Angelone, Bonnie L; Levin, Daniel T; Simons, Daniel J

    2003-01-01

    Observers typically detect changes to central objects more readily than changes to marginal objects, but they sometimes miss changes to central, attended objects as well. However, even if observers do not report such changes, they may be able to recognize the changed object. In three experiments we explored change detection and recognition memory for several types of changes to central objects in motion pictures. Observers who failed to detect a change still performed at above chance levels on a recognition task in almost all conditions. In addition, observers who detected the change were no more accurate in their recognition than those who did not detect the change. Despite large differences in the detectability of changes across conditions, those observers who missed the change did not vary in their ability to recognize the changing object.

  20. Airborne change detection system for the detection of route mines

    NASA Astrophysics Data System (ADS)

    Donzelli, Thomas P.; Jackson, Larry; Yeshnik, Mark; Petty, Thomas E.

    2003-09-01

    The US Army is interested in technologies that will enable it to maintain the free flow of traffic along routes such as Main Supply Routes (MSRs). Mines emplaced in the road by enemy forces under cover of darkness represent a major threat to maintaining a rapid Operational Tempo (OPTEMPO) along such routes. One technique that shows promise for detecting enemy mining activity is Airborne Change Detection, which allows an operator to detect suspicious day-to-day changes in and around the road that may be indicative of enemy mining. This paper presents an Airborne Change Detection that is currently under development at the US Army Night Vision and Electronic Sensors Directorate (NVESD). The system has been tested using a longwave infrared (LWIR) sensor on a vertical take-off and landing unmanned aerial vehicle (VTOL UAV) and a midwave infrared (MWIR) sensor on a fixed wing aircraft. The system is described and results of the various tests conducted to date are presented.

  1. Neural dynamics of change detection in crowded acoustic scenes.

    PubMed

    Sohoglu, Ediz; Chait, Maria

    2016-02-01

    Two key questions concerning change detection in crowded acoustic environments are the extent to which cortical processing is specialized for different forms of acoustic change and when in the time-course of cortical processing neural activity becomes predictive of behavioral outcomes. Here, we address these issues by using magnetoencephalography (MEG) to probe the cortical dynamics of change detection in ongoing acoustic scenes containing as many as ten concurrent sources. Each source was formed of a sequence of tone pips with a unique carrier frequency and temporal modulation pattern, designed to mimic the spectrotemporal structure of natural sounds. Our results show that listeners are more accurate and quicker to detect the appearance (than disappearance) of an auditory source in the ongoing scene. Underpinning this behavioral asymmetry are change-evoked responses differing not only in magnitude and latency, but also in their spatial patterns. We find that even the earliest (~50 ms) cortical response to change is predictive of behavioral outcomes (detection times), consistent with the hypothesized role of local neural transients in supporting change detection.

  2. Change detection and change blindness in pigeons (Columba livia).

    PubMed

    Herbranson, Walter T; Trinh, Yvan T; Xi, Patricia M; Arand, Mark P; Barker, Michael S K; Pratt, Theodore H

    2014-05-01

    Change blindness is a phenomenon in which even obvious details in a visual scene change without being noticed. Although change blindness has been studied extensively in humans, we do not yet know if it is a phenomenon that also occurs in other animals. Thus, investigation of change blindness in a nonhuman species may prove to be valuable by beginning to provide some insight into its ultimate causes. Pigeons learned a change detection task in which pecks to the location of a change in a sequence of stimulus displays were reinforced. They were worse at detecting changes if the stimulus displays were separated by a brief interstimulus interval, during which the display was blank, and this primary result matches the general pattern seen in previous studies of change blindness in humans. A second experiment attempted to identify specific stimulus characteristics that most reliably produced a failure to detect changes. Change detection was more difficult when interstimulus intervals were longer and when the change was iterated fewer times.

  3. Change Detection via Morphological Comparative Filters

    NASA Astrophysics Data System (ADS)

    Vizilter, Y. V.; Rubis, A. Y.; Zheltov, S. Y.; Vygolov, O. V.

    2016-06-01

    In this paper we propose the new change detection technique based on morphological comparative filtering. This technique generalizes the morphological image analysis scheme proposed by Pytiev. A new class of comparative filters based on guided contrasting is developed. Comparative filtering based on diffusion morphology is implemented too. The change detection pipeline contains: comparative filtering on image pyramid, calculation of morphological difference map, binarization, extraction of change proposals and testing change proposals using local morphological correlation coefficient. Experimental results demonstrate the applicability of proposed approach.

  4. Molecular Detection of Foodborne Pathogens: A Rapid and Accurate Answer to Food Safety.

    PubMed

    Mangal, Manisha; Bansal, Sangita; Sharma, Satish K; Gupta, Ram K

    2016-07-01

    Food safety is a global health concern. For the prevention and recognition of problems related to health and safety, detection of foodborne pathogen is of utmost importance at all levels of food production chain. For several decades, a lot of research has been targeted at the development of rapid methodology as reducing the time needed to complete pathogen detection tests has been the primary goal of food microbiologists. With the result, food microbiology laboratories now have a wide array of detection methods and automated technologies such as enzyme immunoassay, polymerase chain reaction, and microarrays, which can cut test times considerably. Nucleic acid amplification strategies and advances in amplicon detection methodologies have been the key factors in the progress of molecular microbiology. A comprehensive literature survey has been carried out to give an overview in the field of foodborne pathogen detection. In this paper, we describe the conventional methods, as well as recent developments in food pathogen detection, identification, and quantification, with a major emphasis on molecular detection methods.

  5. Change Detection Experiments Using Low Cost UAVs

    NASA Technical Reports Server (NTRS)

    Logan, Michael J.; Vranas, Thomas L.; Motter, Mark; Hines, Glenn D.; Rahman, Zia-ur

    2005-01-01

    This paper presents the progress in the development of a low-cost change-detection system. This system is being developed to provide users with the ability to use a low-cost unmanned aerial vehicle (UAV) and image processing system that can detect changes in specific fixed ground locations using video provided by an autonomous UAV. The results of field experiments conducted with the US Army at Ft. A.P.Hill are presented.

  6. Combining CRF and multi-hypothesis detection for accurate lesion segmentation in breast sonograms.

    PubMed

    Hao, Zhihui; Wang, Qiang; Seong, Yeong Kyeong; Lee, Jong-Ha; Ren, Haibing; Kim, Ji-yeun

    2012-01-01

    The implementation of lesion segmentation for breast ultrasound image relies on several diagnostic rules on intensity, texture, etc. In this paper, we propose a novel algorithm to achieve a comprehensive decision upon these rules by incorporating image over-segmentation and lesion detection in a pairwise CRF model, rather than a term-by-term translation. Multiple detection hypotheses are used to propagate object-level cues to segments and a unified classifier is trained based on the concatenated features. The experimental results show that our algorithm can avoid the drawbacks of separate detection or bottom-up segmentation, and can deal with very complicated cases. PMID:23285589

  7. Towards accurate node-based detection of P2P botnets.

    PubMed

    Yin, Chunyong

    2014-01-01

    Botnets are a serious security threat to the current Internet infrastructure. In this paper, we propose a novel direction for P2P botnet detection called node-based detection. This approach focuses on the network characteristics of individual nodes. Based on our model, we examine node's flows and extract the useful features over a given time period. We have tested our approach on real-life data sets and achieved detection rates of 99-100% and low false positives rates of 0-2%. Comparison with other similar approaches on the same data sets shows that our approach outperforms the existing approaches.

  8. Towards Accurate Node-Based Detection of P2P Botnets

    PubMed Central

    2014-01-01

    Botnets are a serious security threat to the current Internet infrastructure. In this paper, we propose a novel direction for P2P botnet detection called node-based detection. This approach focuses on the network characteristics of individual nodes. Based on our model, we examine node's flows and extract the useful features over a given time period. We have tested our approach on real-life data sets and achieved detection rates of 99-100% and low false positives rates of 0–2%. Comparison with other similar approaches on the same data sets shows that our approach outperforms the existing approaches. PMID:25089287

  9. Change Point Detection in Correlation Networks.

    PubMed

    Barnett, Ian; Onnela, Jukka-Pekka

    2016-01-07

    Many systems of interacting elements can be conceptualized as networks, where network nodes represent the elements and network ties represent interactions between the elements. In systems where the underlying network evolves, it is useful to determine the points in time where the network structure changes significantly as these may correspond to functional change points. We propose a method for detecting change points in correlation networks that, unlike previous change point detection methods designed for time series data, requires minimal distributional assumptions. We investigate the difficulty of change point detection near the boundaries of the time series in correlation networks and study the power of our method and competing methods through simulation. We also show the generalizable nature of the method by applying it to stock price data as well as fMRI data.

  10. Comparison of hyperspectral change detection algorithms

    NASA Astrophysics Data System (ADS)

    Pieper, M.; Manolakis, D.; Truslow, E.; Cooley, T.; Brueggeman, M.; Weisner, A.; Jacobson, J.

    2015-09-01

    There are a multitude of civilian and military applications for the detection of anomalous changes in hyper-spectral images. Anomalous changes occur when the material within a pixel is replaced. Environmental factors that change over time, such as illumination, will affect the radiance of all the pixels in a scene, despite the materials within remaining constant. The goal of an anomalous change detection algorithm is to suppress changes caused by the environment, and detect pixels where the materials within have changed. Anomalous change detection is a two step process. Two co-registered images of a scene are first transformed to maximize the overall correlation between the images, then an anomalous change detector (ACD) is applied to the transformed images. The transforms maximize the correlation between the two images to attenuate the environmental differences that distract from the anomalous changes of importance. Several categories of transforms with different optimization parameters are discussed and compared. One of two types of ACDs are then applied to the transformed images. The first ACD uses the difference of the two transformed images. The second concatenates the spectra of two images and uses an aggregated ACD. A comparison of the two ACD methods and their effectiveness with the different transforms is done for the first time.

  11. Change detection in very high resolution multisensor optical images

    NASA Astrophysics Data System (ADS)

    Solano Correa, Yady T.; Bovolo, Francesca; Bruzzone, Lorenzo

    2014-10-01

    This work aims at developing an approach to the detection of changes in multisensor multitemporal VHR optical images. The main steps of the proposed method are: i) multisensor data homogenization; and ii) change detection in multisensor multitemporal VHR optical images. The proposed approach takes advantage of: the conversion to physical quantities suggested by Pacifici et. al.1 , the framework for the design of systems for change detection in VHR images presented by Bruzzone and Bovolo2 and the framework for unsupervised change detection presented by Bovolo and Bruzzone3. Multisensor data homogenization is achieved during pre-processing by taking into account differences in both radiometric and geometric dimensions. Whereas change detection was approached by extracting proper features from multisensor images such that they result to be comparable (at a given level of abstraction) even if extracted from images acquired by different sensors. In order to illustrate the results, a data set made up of a QuickBird and a WorldView-2 images - acquired in 2006 and 2010 respectively - over an area located in the Trentino region of Italy were used. However, the proposed approach is thought to be exportable to multitemporal images coming from passive sensors other than the two mentioned above. The experimental results obtained on the QuickBird and WorlView-2 image pair are accurate. Thus opening to further experiments on multitemporal images acquired by other sensors.

  12. Detecting and Reacting to Change: The Effect of Exposure to Narrow Categorizations

    ERIC Educational Resources Information Center

    Chakravarti, Amitav; Fang, Christina; Shapira, Zur

    2011-01-01

    The ability to detect a change, to accurately assess the magnitude of the change, and to react to that change in a commensurate fashion are of critical importance in many decision domains. Thus, it is important to understand the factors that systematically affect people's reactions to change. In this article we document a novel effect: Decision…

  13. Sensor for detecting changes in magnetic fields

    DOEpatents

    Praeg, W.F.

    1980-02-26

    A sensor is described for detecting changes in the magnetic field of the equilibrium-field coil of a Tokamak plasma device that comprises a pair of bifilar wires disposed circumferentially, one inside and one outside the equilibrium-field coil. Each is shorted at one end. The difference between the voltages detected at the other ends of the bifilar wires provides a measure of changing flux in the equilibrium-field coil. This difference can be used to detect faults in the coil in time to take action to protect the coil.

  14. Sensor for detecting changes in magnetic fields

    DOEpatents

    Praeg, Walter F.

    1981-01-01

    A sensor for detecting changes in the magnetic field of the equilibrium-field coil of a Tokamak plasma device comprises a pair of bifilar wires disposed circumferentially, one inside and one outside the equilibrium-field coil. Each is shorted at one end. The difference between the voltages detected at the other ends of the bifilar wires provides a measure of changing flux in the equilibrium-field coil. This difference can be used to detect faults in the coil in time to take action to protect the coil.

  15. The modified card agglutination test: an accurate tool for detecting anaplasmosis in Columbian black-tailed deer.

    PubMed

    Howarth, A; Hokama, Y; Amerault, T E

    1976-07-01

    Inoculation of susceptible calves confirmed that the modified card agglutination test accurately detected the anaplasmosis infection status of each of 35 Columbian black-tailed deer (Odocoileus hemionus columbianus). Anaplasma marginale, and specific antibodies, were demonstrated only in calves which received blood from deer that were positive by the card test. The modified card agglutination testing of deer serum was performed in the manner recommended for testing cattle serum with bovine-origin antigen and bovine serum factor.

  16. Hydrogen sulfide detection based on reflection: from a poison test approach of ancient China to single-cell accurate localization.

    PubMed

    Kong, Hao; Ma, Zhuoran; Wang, Song; Gong, Xiaoyun; Zhang, Sichun; Zhang, Xinrong

    2014-08-01

    With the inspiration of an ancient Chinese poison test approach, we report a rapid hydrogen sulfide detection strategy in specific areas of live cells using silver needles with good spatial resolution of 2 × 2 μm(2). Besides the accurate-localization ability, this reflection-based strategy also has attractive merits of convenience and robust response when free pretreatment and short detection time are concerned. The success of endogenous H2S level evaluation in cellular cytoplasm and nuclear of human A549 cells promises the application potential of our strategy in scientific research and medical diagnosis.

  17. lidar change detection using building models

    NASA Astrophysics Data System (ADS)

    Kim, Angela M.; Runyon, Scott C.; Jalobeanu, Andre; Esterline, Chelsea H.; Kruse, Fred A.

    2014-06-01

    Terrestrial LiDAR scans of building models collected with a FARO Focus3D and a RIEGL VZ-400 were used to investigate point-to-point and model-to-model LiDAR change detection. LiDAR data were scaled, decimated, and georegistered to mimic real world airborne collects. Two physical building models were used to explore various aspects of the change detection process. The first model was a 1:250-scale representation of the Naval Postgraduate School campus in Monterey, CA, constructed from Lego blocks and scanned in a laboratory setting using both the FARO and RIEGL. The second model at 1:8-scale consisted of large cardboard boxes placed outdoors and scanned from rooftops of adjacent buildings using the RIEGL. A point-to-point change detection scheme was applied directly to the point-cloud datasets. In the model-to-model change detection scheme, changes were detected by comparing Digital Surface Models (DSMs). The use of physical models allowed analysis of effects of changes in scanner and scanning geometry, and performance of the change detection methods on different types of changes, including building collapse or subsistence, construction, and shifts in location. Results indicate that at low false-alarm rates, the point-to-point method slightly outperforms the model-to-model method. The point-to-point method is less sensitive to misregistration errors in the data. Best results are obtained when the baseline and change datasets are collected using the same LiDAR system and collection geometry.

  18. Implicit processing of tactile information: evidence from the tactile change detection paradigm.

    PubMed

    Pritchett, David; Gallace, Alberto; Spence, Charles

    2011-09-01

    People can maintain accurate representations of visual changes without necessarily being aware of them. Here, we investigate whether a similar phenomenon (implicit change detection) also exists in touch. In Experiments 1 and 2, participants detected the presence of a change between two consecutively-presented tactile displays. Tactile change blindness was observed, with participants failing to report the presence of tactile change. Critically, however, when participants had to make a forced choice response regarding the number of stimuli presented in the two displays, their performance was significantly better than chance (i.e., implicit change detection was observed). Experiment 3 demonstrated that tactile change detection does not necessarily involve a shift of spatial attention toward the location of change, regardless of whether the change is explicitly detected. We conclude that tactile change detection likely results from comparing representations of the two displays, rather than by directing spatial attention to the location of the change.

  19. The impact of misregistration on change detection

    NASA Technical Reports Server (NTRS)

    Townshend, John R. G.; Justice, Christopher O.; Gurney, Charlotte; Mcmanus, James

    1992-01-01

    The impact of images misregistration on the detection of changes in land cover was studied using spatially degraded Landsat MSS images. Emphasis is placed on simulated images of the Normalized Difference Vegetation Index (NDVI) at spatial resolutions of 250 and 500 m. It is pointed out that there is the need to achieve high values of registration accuracy. The evidence from simulations suggests that misregistrations can have a marked effect on the ability of remotely sensed data to detect changes in land cover. Even subpixel misregistrations can have a major impact, and the most marked proportional changes will tend to occur at the finest misregistrations.

  20. Line matching for automatic change detection algorithm

    NASA Astrophysics Data System (ADS)

    Dhollande, Jérôme; Monnin, David; Gond, Laetitia; Cudel, Christophe; Kohler, Sophie; Dieterlen, Alain

    2012-06-01

    During foreign operations, Improvised Explosive Devices (IEDs) are one of major threats that soldiers may unfortunately encounter along itineraries. Based on a vehicle-mounted camera, we propose an original approach by image comparison to detect signicant changes on these roads. The classic 2D-image registration techniques do not take into account parallax phenomena. The consequence is that the misregistration errors could be detected as changes. According to stereovision principles, our automatic method compares intensity proles along corresponding epipolar lines by extrema matching. An adaptive space warping compensates scale dierence in 3D-scene. When the signals are matched, the signal dierence highlights changes which are marked in current video.

  1. Simple but accurate GCM-free approach for quantifying anthropogenic climate change

    NASA Astrophysics Data System (ADS)

    Lovejoy, S.

    2014-12-01

    We are so used to analysing the climate with the help of giant computer models (GCM's) that it is easy to get the impression that they are indispensable. Yet anthropogenic warming is so large (roughly 0.9oC) that it turns out that it is straightforward to quantify it with more empirically based methodologies that can be readily understood by the layperson. The key is to use the CO2 forcing as a linear surrogate for all the anthropogenic effects from 1880 to the present (implicitly including all effects due to Greenhouse Gases, aerosols and land use changes). To a good approximation, double the economic activity, double the effects. The relationship between the forcing and global mean temperature is extremely linear as can be seen graphically and understood without fancy statistics, [Lovejoy, 2014a] (see the attached figure and http://www.physics.mcgill.ca/~gang/Lovejoy.htm). To an excellent approximation, the deviations from the linear forcing - temperature relation can be interpreted as the natural variability. For example, this direct - yet accurate approach makes it graphically obvious that the "pause" or "hiatus" in the warming since 1998 is simply a natural cooling event that has roughly offset the anthropogenic warming [Lovejoy, 2014b]. Rather than trying to prove that the warming is anthropogenic, with a little extra work (and some nonlinear geophysics theory and pre-industrial multiproxies) we can disprove the competing theory that it is natural. This approach leads to the estimate that the probability of the industrial scale warming being a giant natural fluctuation is ≈0.1%: it can be dismissed. This destroys the last climate skeptic argument - that the models are wrong and the warming is natural. It finally allows for a closure of the debate. In this talk we argue that this new, direct, simple, intuitive approach provides an indispensable tool for communicating - and convincing - the public of both the reality and the amplitude of anthropogenic warming

  2. Automated change detection for synthetic aperture sonar

    NASA Astrophysics Data System (ADS)

    G-Michael, Tesfaye; Marchand, Bradley; Tucker, J. D.; Sternlicht, Daniel D.; Marston, Timothy M.; Azimi-Sadjadi, Mahmood R.

    2014-05-01

    In this paper, an automated change detection technique is presented that compares new and historical seafloor images created with sidescan synthetic aperture sonar (SAS) for changes occurring over time. The method consists of a four stage process: a coarse navigational alignment; fine-scale co-registration using the scale invariant feature transform (SIFT) algorithm to match features between overlapping images; sub-pixel co-registration to improves phase coherence; and finally, change detection utilizing canonical correlation analysis (CCA). The method was tested using data collected with a high-frequency SAS in a sandy shallow-water environment. By using precise co-registration tools and change detection algorithms, it is shown that the coherent nature of the SAS data can be exploited and utilized in this environment over time scales ranging from hours through several days.

  3. Accurate detection of Campylobacter spp. antigens by immunochromatography and enzyme immunoassay in routine microbiological laboratory.

    PubMed

    Regnath, Thomas; Ignatius, Ralf

    2014-09-01

    Campylobacter spp. are fastidious microorganisms, and their detection by culture depends on the freshness of the stool sample and the skills of the laboratory staff. To improve laboratory diagnosis, assays for the detection of specific antigens have been developed. Here, we evaluated two assays for the detection of Campylobacter spp.-specific antigens, i.e., one immunochromatographic test and one enzyme-linked immunosorbent assay (EIA), in 38 frozen Campylobacter spp.-positive specimens and prospectively in 533 fresh stool samples with a conventional enzyme immunoassay (EIA) and culture. Both assays were positive for 36 samples with Campylobacter jejuni and one with Campylobacter coli among 38 Campylobacter spp.-positive frozen samples. One Campylobacter lari-positive sample was identified by the immunochromatographic assay (ICA) only. In a prospective study performed within the course of routine microbiology, both assays were positive for 24/25 C. jejuni culture-positive samples (positive percent agreement, 96.0% [95% CI: 78.9-100%]). ICA and EIA also were positive for 14 and 10 culture-negative samples, respectively (negative percent agreement: ICA, 97.2% [95% CI: 95.4-98.4%]; EIA, 98.0% [95% CI: 96.4-99.0%]). In conclusion, the high agreement between both antigen-detection assays and culture indicates that both assays may be initially performed followed by culture only upon a positive test result.

  4. How Accurately Can Your Wrist Device Recognize Daily Activities and Detect Falls?

    PubMed

    Gjoreski, Martin; Gjoreski, Hristijan; Luštrek, Mitja; Gams, Matjaž

    2016-01-01

    Although wearable accelerometers can successfully recognize activities and detect falls, their adoption in real life is low because users do not want to wear additional devices. A possible solution is an accelerometer inside a wrist device/smartwatch. However, wrist placement might perform poorly in terms of accuracy due to frequent random movements of the hand. In this paper we perform a thorough, large-scale evaluation of methods for activity recognition and fall detection on four datasets. On the first two we showed that the left wrist performs better compared to the dominant right one, and also better compared to the elbow and the chest, but worse compared to the ankle, knee and belt. On the third (Opportunity) dataset, our method outperformed the related work, indicating that our feature-preprocessing creates better input data. And finally, on a real-life unlabeled dataset the recognized activities captured the subject's daily rhythm and activities. Our fall-detection method detected all of the fast falls and minimized the false positives, achieving 85% accuracy on the first dataset. Because the other datasets did not contain fall events, only false positives were evaluated, resulting in 9 for the second, 1 for the third and 15 for the real-life dataset (57 days data). PMID:27258282

  5. How Accurately Can Your Wrist Device Recognize Daily Activities and Detect Falls?

    PubMed Central

    Gjoreski, Martin; Gjoreski, Hristijan; Luštrek, Mitja; Gams, Matjaž

    2016-01-01

    Although wearable accelerometers can successfully recognize activities and detect falls, their adoption in real life is low because users do not want to wear additional devices. A possible solution is an accelerometer inside a wrist device/smartwatch. However, wrist placement might perform poorly in terms of accuracy due to frequent random movements of the hand. In this paper we perform a thorough, large-scale evaluation of methods for activity recognition and fall detection on four datasets. On the first two we showed that the left wrist performs better compared to the dominant right one, and also better compared to the elbow and the chest, but worse compared to the ankle, knee and belt. On the third (Opportunity) dataset, our method outperformed the related work, indicating that our feature-preprocessing creates better input data. And finally, on a real-life unlabeled dataset the recognized activities captured the subject’s daily rhythm and activities. Our fall-detection method detected all of the fast falls and minimized the false positives, achieving 85% accuracy on the first dataset. Because the other datasets did not contain fall events, only false positives were evaluated, resulting in 9 for the second, 1 for the third and 15 for the real-life dataset (57 days data). PMID:27258282

  6. SU-E-J-23: An Accurate Algorithm to Match Imperfectly Matched Images for Lung Tumor Detection Without Markers

    SciTech Connect

    Rozario, T; Bereg, S; Chiu, T; Liu, H; Kearney, V; Jiang, L; Mao, W

    2014-06-01

    Purpose: In order to locate lung tumors on projection images without internal markers, digitally reconstructed radiograph (DRR) is created and compared with projection images. Since lung tumors always move and their locations change on projection images while they are static on DRRs, a special DRR (background DRR) is generated based on modified anatomy from which lung tumors are removed. In addition, global discrepancies exist between DRRs and projections due to their different image originations, scattering, and noises. This adversely affects comparison accuracy. A simple but efficient comparison algorithm is reported. Methods: This method divides global images into a matrix of small tiles and similarities will be evaluated by calculating normalized cross correlation (NCC) between corresponding tiles on projections and DRRs. The tile configuration (tile locations) will be automatically optimized to keep the tumor within a single tile which has bad matching with the corresponding DRR tile. A pixel based linear transformation will be determined by linear interpolations of tile transformation results obtained during tile matching. The DRR will be transformed to the projection image level and subtracted from it. The resulting subtracted image now contains only the tumor. A DRR of the tumor is registered to the subtracted image to locate the tumor. Results: This method has been successfully applied to kV fluoro images (about 1000 images) acquired on a Vero (Brainlab) for dynamic tumor tracking on phantom studies. Radiation opaque markers are implanted and used as ground truth for tumor positions. Although, other organs and bony structures introduce strong signals superimposed on tumors at some angles, this method accurately locates tumors on every projection over 12 gantry angles. The maximum error is less than 2.6 mm while the total average error is 1.0 mm. Conclusion: This algorithm is capable of detecting tumor without markers despite strong background signals.

  7. Holistic processing improves change detection but impairs change identification.

    PubMed

    Mathis, Katherine M; Kahan, Todd A

    2014-10-01

    It has been just over a century since Gestalt psychologists described the factors that contribute to the holistic processing of visually presented stimuli. Recent research indicates that holistic processing may come at a cost; specifically, the perception of holistic forms may reduce the visibility of constituent parts. In the present experiment, we examined change detection and change identification accuracy with Kanizsa rectangle patterns that were arranged to either form a Gestalt whole or not. Results from an experiment with 62 participants support this trade-off in processing holistic forms. Holistic processing improved the detection of change but obstructed its identification. Results are discussed in terms of both their theoretical significance and their application in areas ranging from baggage screening and the detection of changes in radiological images to the systems that are used to generate composite images of perpetrators on the basis of eyewitness reports.

  8. Accurately measuring sea level change from space: an ESA climate change initiative for MSL closure budget studies

    NASA Astrophysics Data System (ADS)

    Legeais, JeanFrancois; Benveniste, Jérôme

    2016-07-01

    Sea level is a very sensitive index of climate change and variability. Sea level integrates the ocean warming, mountain glaciers and ice sheet melting. Understanding the sea level variability and changes implies an accurate monitoring of the sea level variable at climate scales, in addition to understanding the ocean variability and the exchanges between ocean, land, cryosphere, and atmosphere. That is why Sea Level is one of the Essential Climate Variables (ECV) selected in the frame of the ESA Climate Change Initiative (CCI) program. It aims at providing long-term monitoring of the sea level ECV with regular updates, as required for climate studies. The program is now in its second phase of 3 year (following phase I during 2011-2013). The objectives are firstly to involve the climate research community, to refine their needs and collect their feedbacks on product quality. And secondly to develop, test and select the best algorithms and standards to generate an updated climate time series and to produce and validate the Sea Level ECV product. This will better answer the climate user needs by improving the quality of the Sea Level products and maintain a sustain service for an up-to-date production. This has led to the production of a first version of the Sea Level ECV which has benefited from yearly extensions and now covers the period 1993-2014. Within phase II, new altimeter standards have been developed and tested in order to reprocess the dataset with the best standards for climate studies. The reprocessed ECV will be released in summer 2016. We will present the main achievements of the ESA CCI Sea Level Project. On the one hand, the major steps required to produce the 22 years climate time series are briefly described: collect and refine the user requirements, development of adapted algorithms for climate applications and specification of the production system. On the other hand, the product characteristics are described as well as the results from product

  9. Detecting regional patterns of changing CO2 flux in Alaska

    NASA Astrophysics Data System (ADS)

    Parazoo, Nicholas C.; Commane, Roisin; Wofsy, Steven C.; Koven, Charles D.; Sweeney, Colm; Lawrence, David M.; Lindaas, Jakob; Chang, Rachel Y.-W.; Miller, Charles E.

    2016-07-01

    With rapid changes in climate and the seasonal amplitude of carbon dioxide (CO2) in the Arctic, it is critical that we detect and quantify the underlying processes controlling the changing amplitude of CO2 to better predict carbon cycle feedbacks in the Arctic climate system. We use satellite and airborne observations of atmospheric CO2 with climatically forced CO2 flux simulations to assess the detectability of Alaskan carbon cycle signals as future warming evolves. We find that current satellite remote sensing technologies can detect changing uptake accurately during the growing season but lack sufficient cold season coverage and near-surface sensitivity to constrain annual carbon balance changes at regional scale. Airborne strategies that target regular vertical profile measurements within continental interiors are more sensitive to regional flux deeper into the cold season but currently lack sufficient spatial coverage throughout the entire cold season. Thus, the current CO2 observing network is unlikely to detect potentially large CO2 sources associated with deep permafrost thaw and cold season respiration expected over the next 50 y. Although continuity of current observations is vital, strategies and technologies focused on cold season measurements (active remote sensing, aircraft, and tall towers) and systematic sampling of vertical profiles across continental interiors over the full annual cycle are required to detect the onset of carbon release from thawing permafrost.

  10. Detecting regional patterns of changing CO2 flux in Alaska.

    PubMed

    Parazoo, Nicholas C; Commane, Roisin; Wofsy, Steven C; Koven, Charles D; Sweeney, Colm; Lawrence, David M; Lindaas, Jakob; Chang, Rachel Y-W; Miller, Charles E

    2016-07-12

    With rapid changes in climate and the seasonal amplitude of carbon dioxide (CO2) in the Arctic, it is critical that we detect and quantify the underlying processes controlling the changing amplitude of CO2 to better predict carbon cycle feedbacks in the Arctic climate system. We use satellite and airborne observations of atmospheric CO2 with climatically forced CO2 flux simulations to assess the detectability of Alaskan carbon cycle signals as future warming evolves. We find that current satellite remote sensing technologies can detect changing uptake accurately during the growing season but lack sufficient cold season coverage and near-surface sensitivity to constrain annual carbon balance changes at regional scale. Airborne strategies that target regular vertical profile measurements within continental interiors are more sensitive to regional flux deeper into the cold season but currently lack sufficient spatial coverage throughout the entire cold season. Thus, the current CO2 observing network is unlikely to detect potentially large CO2 sources associated with deep permafrost thaw and cold season respiration expected over the next 50 y. Although continuity of current observations is vital, strategies and technologies focused on cold season measurements (active remote sensing, aircraft, and tall towers) and systematic sampling of vertical profiles across continental interiors over the full annual cycle are required to detect the onset of carbon release from thawing permafrost. PMID:27354511

  11. High Resolution Melting Analysis: A Rapid and Accurate Method to Detect CALR Mutations

    PubMed Central

    Moreno, Melania; Torres, Laura; Santana-Lopez, Gonzalo; Rodriguez-Medina, Carlos; Perera, María; Bellosillo, Beatriz; de la Iglesia, Silvia; Molero, Teresa; Gomez-Casares, Maria Teresa

    2014-01-01

    Background The recent discovery of CALR mutations in essential thrombocythemia (ET) and primary myelofibrosis (PMF) patients without JAK2/MPL mutations has emerged as a relevant finding for the molecular diagnosis of these myeloproliferative neoplasms (MPN). We tested the feasibility of high-resolution melting (HRM) as a screening method for rapid detection of CALR mutations. Methods CALR was studied in wild-type JAK2/MPL patients including 34 ET, 21 persistent thrombocytosis suggestive of MPN and 98 suspected secondary thrombocytosis. CALR mutation analysis was performed through HRM and Sanger sequencing. We compared clinical features of CALR-mutated versus 45 JAK2/MPL-mutated subjects in ET. Results Nineteen samples showed distinct HRM patterns from wild-type. Of them, 18 were mutations and one a polymorphism as confirmed by direct sequencing. CALR mutations were present in 44% of ET (15/34), 14% of persistent thrombocytosis suggestive of MPN (3/21) and none of the secondary thrombocytosis (0/98). Of the 18 mutants, 9 were 52 bp deletions, 8 were 5 bp insertions and other was a complex mutation with insertion/deletion. No mutations were found after sequencing analysis of 45 samples displaying wild-type HRM curves. HRM technique was reproducible, no false positive or negative were detected and the limit of detection was of 3%. Conclusions This study establishes a sensitive, reliable and rapid HRM method to screen for the presence of CALR mutations. PMID:25068507

  12. GUIDANCE2: accurate detection of unreliable alignment regions accounting for the uncertainty of multiple parameters

    PubMed Central

    Sela, Itamar; Ashkenazy, Haim; Katoh, Kazutaka; Pupko, Tal

    2015-01-01

    Inference of multiple sequence alignments (MSAs) is a critical part of phylogenetic and comparative genomics studies. However, from the same set of sequences different MSAs are often inferred, depending on the methodologies used and the assumed parameters. Much effort has recently been devoted to improving the ability to identify unreliable alignment regions. Detecting such unreliable regions was previously shown to be important for downstream analyses relying on MSAs, such as the detection of positive selection. Here we developed GUIDANCE2, a new integrative methodology that accounts for: (i) uncertainty in the process of indel formation, (ii) uncertainty in the assumed guide tree and (iii) co-optimal solutions in the pairwise alignments, used as building blocks in progressive alignment algorithms. We compared GUIDANCE2 with seven methodologies to detect unreliable MSA regions using extensive simulations and empirical benchmarks. We show that GUIDANCE2 outperforms all previously developed methodologies. Furthermore, GUIDANCE2 also provides a set of alternative MSAs which can be useful for downstream analyses. The novel algorithm is implemented as a web-server, available at: http://guidance.tau.ac.il. PMID:25883146

  13. GUIDANCE2: accurate detection of unreliable alignment regions accounting for the uncertainty of multiple parameters.

    PubMed

    Sela, Itamar; Ashkenazy, Haim; Katoh, Kazutaka; Pupko, Tal

    2015-07-01

    Inference of multiple sequence alignments (MSAs) is a critical part of phylogenetic and comparative genomics studies. However, from the same set of sequences different MSAs are often inferred, depending on the methodologies used and the assumed parameters. Much effort has recently been devoted to improving the ability to identify unreliable alignment regions. Detecting such unreliable regions was previously shown to be important for downstream analyses relying on MSAs, such as the detection of positive selection. Here we developed GUIDANCE2, a new integrative methodology that accounts for: (i) uncertainty in the process of indel formation, (ii) uncertainty in the assumed guide tree and (iii) co-optimal solutions in the pairwise alignments, used as building blocks in progressive alignment algorithms. We compared GUIDANCE2 with seven methodologies to detect unreliable MSA regions using extensive simulations and empirical benchmarks. We show that GUIDANCE2 outperforms all previously developed methodologies. Furthermore, GUIDANCE2 also provides a set of alternative MSAs which can be useful for downstream analyses. The novel algorithm is implemented as a web-server, available at: http://guidance.tau.ac.il.

  14. NOVELTY DETECTION UNDER CHANGING ENVIRONMENTAL CONDITIONS

    SciTech Connect

    H. SOHN; K. WORDER; C. R. FARRAR

    2001-04-01

    The primary objective of novelty detection is to examine a system's dynamic response to determine if the system significantly deviates from an initial baseline condition. In reality, the system is often subject to changing environmental and operation conditions that affect its dynamic characteristics. Such variations include changes in loading, boundary conditions, temperature, and moisture. Most damage diagnosis techniques, however, generally neglect the effects of these changing ambient conditions. Here, a novelty detection technique is developed explicitly taking into account these natural variations of the system in order to minimize false positive indications of true system changes. Auto-associative neural networks are employed to discriminate system changes of interest such as structural deterioration and damage from the natural variations of the system.

  15. Avoiding incidental predation by mammalian herbivores: accurate detection and efficient response in aphids

    NASA Astrophysics Data System (ADS)

    Gish, Moshe; Dafni, Amots; Inbar, Moshe

    2011-09-01

    Mammalian herbivores eat plants that may also provide food and shelter for insects. The direct trophic effect of the browsing and grazing of mammalian herbivory on insects, which is probably prevalent in terrestrial ecosystems, has been mostly neglected by ecologists. We examined how the aphid Uroleucon sonchi L. deals with the danger of incidental predation by mammalian herbivores. We found that most (76%) of the aphids in a colony survive the ingestion of the plant by a feeding herbivore. They do so by sensing the combination of heat and humidity in the herbivore's breath and immediately dropping off the plant in large numbers. Their ability to sense the herbivore's breath or their tendency to drop off the plant weakens as ambient temperature rises. This could indicate a limitation of the aphids' sensory system or an adaptation that enables them to avoid the hostile conditions on a hot ground. Once on the ground, U. sonchi is highly mobile and capable of locating a new host plant by advancing in a pattern that differs significantly from random movement. The accurate and efficient defense mechanism of U. sonchi emphasizes the significance of incidental predation as a danger to plant-dwelling invertebrates.

  16. Accurate de novo and transmitted indel detection in exome-capture data using microassembly.

    PubMed

    Narzisi, Giuseppe; O'Rawe, Jason A; Iossifov, Ivan; Fang, Han; Lee, Yoon-Ha; Wang, Zihua; Wu, Yiyang; Lyon, Gholson J; Wigler, Michael; Schatz, Michael C

    2014-10-01

    We present an open-source algorithm, Scalpel (http://scalpel.sourceforge.net/), which combines mapping and assembly for sensitive and specific discovery of insertions and deletions (indels) in exome-capture data. A detailed repeat analysis coupled with a self-tuning k-mer strategy allows Scalpel to outperform other state-of-the-art approaches for indel discovery, particularly in regions containing near-perfect repeats. We analyzed 593 families from the Simons Simplex Collection and demonstrated Scalpel's power to detect long (≥30 bp) transmitted events and enrichment for de novo likely gene-disrupting indels in autistic children. PMID:25128977

  17. Accurate Detection of Interaural Time Differences by a Population of Slowly Integrating Neurons

    NASA Astrophysics Data System (ADS)

    Vasilkov, Viacheslav A.; Tikidji-Hamburyan, Ruben A.

    2012-03-01

    For localization of a sound source, animals and humans process the microsecond interaural time differences of arriving sound waves. How nervous systems, consisting of elements with time constants of about and more than 1 ms, can reach such high precision is still an open question. In this Letter we present a hypothesis and show theoretical and computational evidence that a rather large population of slowly integrating neurons with inhibitory and excitatory inputs (EI neurons) can detect minute temporal disparities in input signals which are significantly less than any time constant in the system.

  18. Is 'Resilience' Maladaptive? Towards an Accurate Lexicon for Climate Change Adaptation.

    PubMed

    Fisichelli, Nicholas A; Schuurman, Gregor W; Hoffman, Cat Hawkins

    2016-04-01

    Climate change adaptation is a rapidly evolving field in conservation biology and includes a range of strategies from resisting to actively directing change on the landscape. The term 'climate change resilience,' frequently used to characterize adaptation strategies, deserves closer scrutiny because it is ambiguous, often misunderstood, and difficult to apply consistently across disciplines and spatial and temporal scales to support conservation efforts. Current definitions of resilience encompass all aspects of adaptation from resisting and absorbing change to reorganizing and transforming in response to climate change. However, many stakeholders are unfamiliar with this spectrum of definitions and assume the more common meaning of returning to a previous state after a disturbance. Climate change, however, is unrelenting and intensifying, characterized by both directional shifts in baseline conditions and increasing variability in extreme events. This ongoing change means that scientific understanding and management responses must develop concurrently, iteratively, and collaboratively, in a science-management partnership. Divergent concepts of climate change resilience impede cross-jurisdictional adaptation efforts and complicate use of adaptive management frameworks. Climate change adaptation practitioners require clear terminology to articulate management strategies and the inherent tradeoffs involved in adaptation. Language that distinguishes among strategies that seek to resist change, accommodate change, and direct change (i.e., persistence, autonomous change, and directed change) is prerequisite to clear communication about climate change adaptation goals and management intentions in conservation areas.

  19. Is 'Resilience' Maladaptive? Towards an Accurate Lexicon for Climate Change Adaptation.

    PubMed

    Fisichelli, Nicholas A; Schuurman, Gregor W; Hoffman, Cat Hawkins

    2016-04-01

    Climate change adaptation is a rapidly evolving field in conservation biology and includes a range of strategies from resisting to actively directing change on the landscape. The term 'climate change resilience,' frequently used to characterize adaptation strategies, deserves closer scrutiny because it is ambiguous, often misunderstood, and difficult to apply consistently across disciplines and spatial and temporal scales to support conservation efforts. Current definitions of resilience encompass all aspects of adaptation from resisting and absorbing change to reorganizing and transforming in response to climate change. However, many stakeholders are unfamiliar with this spectrum of definitions and assume the more common meaning of returning to a previous state after a disturbance. Climate change, however, is unrelenting and intensifying, characterized by both directional shifts in baseline conditions and increasing variability in extreme events. This ongoing change means that scientific understanding and management responses must develop concurrently, iteratively, and collaboratively, in a science-management partnership. Divergent concepts of climate change resilience impede cross-jurisdictional adaptation efforts and complicate use of adaptive management frameworks. Climate change adaptation practitioners require clear terminology to articulate management strategies and the inherent tradeoffs involved in adaptation. Language that distinguishes among strategies that seek to resist change, accommodate change, and direct change (i.e., persistence, autonomous change, and directed change) is prerequisite to clear communication about climate change adaptation goals and management intentions in conservation areas. PMID:26721473

  20. Is `Resilience' Maladaptive? Towards an Accurate Lexicon for Climate Change Adaptation

    NASA Astrophysics Data System (ADS)

    Fisichelli, Nicholas A.; Schuurman, Gregor W.; Hoffman, Cat Hawkins

    2016-04-01

    Climate change adaptation is a rapidly evolving field in conservation biology and includes a range of strategies from resisting to actively directing change on the landscape. The term `climate change resilience,' frequently used to characterize adaptation strategies, deserves closer scrutiny because it is ambiguous, often misunderstood, and difficult to apply consistently across disciplines and spatial and temporal scales to support conservation efforts. Current definitions of resilience encompass all aspects of adaptation from resisting and absorbing change to reorganizing and transforming in response to climate change. However, many stakeholders are unfamiliar with this spectrum of definitions and assume the more common meaning of returning to a previous state after a disturbance. Climate change, however, is unrelenting and intensifying, characterized by both directional shifts in baseline conditions and increasing variability in extreme events. This ongoing change means that scientific understanding and management responses must develop concurrently, iteratively, and collaboratively, in a science-management partnership. Divergent concepts of climate change resilience impede cross-jurisdictional adaptation efforts and complicate use of adaptive management frameworks. Climate change adaptation practitioners require clear terminology to articulate management strategies and the inherent tradeoffs involved in adaptation. Language that distinguishes among strategies that seek to resist change, accommodate change, and direct change (i.e., persistence, autonomous change, and directed change) is prerequisite to clear communication about climate change adaptation goals and management intentions in conservation areas.

  1. Region-Based Convolutional Networks for Accurate Object Detection and Segmentation.

    PubMed

    Girshick, Ross; Donahue, Jeff; Darrell, Trevor; Malik, Jitendra

    2016-01-01

    Object detection performance, as measured on the canonical PASCAL VOC Challenge datasets, plateaued in the final years of the competition. The best-performing methods were complex ensemble systems that typically combined multiple low-level image features with high-level context. In this paper, we propose a simple and scalable detection algorithm that improves mean average precision (mAP) by more than 50 percent relative to the previous best result on VOC 2012-achieving a mAP of 62.4 percent. Our approach combines two ideas: (1) one can apply high-capacity convolutional networks (CNNs) to bottom-up region proposals in order to localize and segment objects and (2) when labeled training data are scarce, supervised pre-training for an auxiliary task, followed by domain-specific fine-tuning, boosts performance significantly. Since we combine region proposals with CNNs, we call the resulting model an R-CNN or Region-based Convolutional Network. Source code for the complete system is available at http://www.cs.berkeley.edu/~rbg/rcnn.

  2. Parametric probability distributions for anomalous change detection

    SciTech Connect

    Theiler, James P; Foy, Bernard R; Wohlberg, Brendt E; Scovel, James C

    2010-01-01

    The problem of anomalous change detection arises when two (or possibly more) images are taken of the same scene, but at different times. The aim is to discount the 'pervasive differences' that occur thoughout the imagery, due to the inevitably different conditions under which the images were taken (caused, for instance, by differences in illumination, atmospheric conditions, sensor calibration, or misregistration), and to focus instead on the 'anomalous changes' that actually take place in the scene. In general, anomalous change detection algorithms attempt to model these normal or pervasive differences, based on data taken directly from the imagery, and then identify as anomalous those pixels for which the model does not hold. For many algorithms, these models are expressed in terms of probability distributions, and there is a class of such algorithms that assume the distributions are Gaussian. By considering a broader class of distributions, however, a new class of anomalous change detection algorithms can be developed. We consider several parametric families of such distributions, derive the associated change detection algorithms, and compare the performance with standard algorithms that are based on Gaussian distributions. We find that it is often possible to significantly outperform these standard algorithms, even using relatively simple non-Gaussian models.

  3. An accurate analytic approximation to the non-linear change in volume of solids with applied pressure

    NASA Technical Reports Server (NTRS)

    Schlosser, Herbert; Ferrante, John

    1989-01-01

    An accurate analytic expression for the nonlinear change of the volume of a solid as a function of applied pressure is of great interest in high-pressure experimentation. It is found that a two-parameter analytic expression, fits the experimental volume-change data to within a few percent over the entire experimentally attainable pressure range. Results are presented for 24 different materials including metals, ceramic semiconductors, polymers, and ionic and rare-gas solids.

  4. Ultrasound thermal change detection based on steerable filters.

    PubMed

    Sahba, Nima; Tavakoli, Vahid; Nambakhsh, MohamadSaleh

    2008-01-01

    Growing tendency toward utilization of Laser and RF knives has opened a new port for thermal control applications in which ultrasound thermal detection is crucial. Ultrasound velocity is dependent on the thermal properties of the environment. In this paper we focus on tissue temperature detection using multiresolution steerable filter-based motion estimation. The proposed technique was evaluated on simulated and real in-vivo cases during surgical occlusion and reopening of renal segmental artery and demonstrated promising results for observation of internal organ temperature changes using only digital ultrasound systems for diagnosis and therapy. It is proved that being oriented in space and time, steerable filters can achieve more accurate results. Performing thermal detection methods on synthetic phantoms demonstrated good correlation between speckle shifts and the ground truth temperature. For the simulated images average thermal error was 0.68 degrees Celsius with a standard deviation of 0.79.

  5. Simple, Sensitive and Accurate Multiplex Detection of Clinically Important Melanoma DNA Mutations in Circulating Tumour DNA with SERS Nanotags

    PubMed Central

    Wee, Eugene J.H.; Wang, Yuling; Tsao, Simon Chang-Hao; Trau, Matt

    2016-01-01

    Sensitive and accurate identification of specific DNA mutations can influence clinical decisions. However accurate diagnosis from limiting samples such as circulating tumour DNA (ctDNA) is challenging. Current approaches based on fluorescence such as quantitative PCR (qPCR) and more recently, droplet digital PCR (ddPCR) have limitations in multiplex detection, sensitivity and the need for expensive specialized equipment. Herein we describe an assay capitalizing on the multiplexing and sensitivity benefits of surface-enhanced Raman spectroscopy (SERS) with the simplicity of standard PCR to address the limitations of current approaches. This proof-of-concept method could reproducibly detect as few as 0.1% (10 copies, CV < 9%) of target sequences thus demonstrating the high sensitivity of the method. The method was then applied to specifically detect three important melanoma mutations in multiplex. Finally, the PCR/SERS assay was used to genotype cell lines and ctDNA from serum samples where results subsequently validated with ddPCR. With ddPCR-like sensitivity and accuracy yet at the convenience of standard PCR, we believe this multiplex PCR/SERS method could find wide applications in both diagnostics and research. PMID:27446486

  6. Detecting Landscape Change: The View from Above

    ERIC Educational Resources Information Center

    Porter, Jess

    2008-01-01

    This article will demonstrate an approach for discovering and assessing local landscape change through the use of remotely sensed images. A brief introduction to remotely sensed imagery is followed by a discussion of relevant ways to introduce this technology into the college science classroom. The Map Detective activity demonstrates the…

  7. Detection of abrupt changes in dynamic systems

    NASA Technical Reports Server (NTRS)

    Willsky, A. S.

    1984-01-01

    Some of the basic ideas associated with the detection of abrupt changes in dynamic systems are presented. Multiple filter-based techniques and residual-based method and the multiple model and generalized likelihood ratio methods are considered. Issues such as the effect of unknown onset time on algorithm complexity and structure and robustness to model uncertainty are discussed.

  8. Automatic change detection using mobile laser scanning

    NASA Astrophysics Data System (ADS)

    Hebel, M.; Hammer, M.; Gordon, M.; Arens, M.

    2014-10-01

    Automatic change detection in 3D environments requires the comparison of multi-temporal data. By comparing current data with past data of the same area, changes can be automatically detected and identified. Volumetric changes in the scene hint at suspicious activities like the movement of military vehicles, the application of camouflage nets, or the placement of IEDs, etc. In contrast to broad research activities in remote sensing with optical cameras, this paper addresses the topic using 3D data acquired by mobile laser scanning (MLS). We present a framework for immediate comparison of current MLS data to given 3D reference data. Our method extends the concept of occupancy grids known from robot mapping, which incorporates the sensor positions in the processing of the 3D point clouds. This allows extracting the information that is included in the data acquisition geometry. For each single range measurement, it becomes apparent that an object reflects laser pulses in the measured range distance, i.e., space is occupied at that 3D position. In addition, it is obvious that space is empty along the line of sight between sensor and the reflecting object. Everywhere else, the occupancy of space remains unknown. This approach handles occlusions and changes implicitly, such that the latter are identifiable by conflicts of empty space and occupied space. The presented concept of change detection has been successfully validated in experiments with recorded MLS data streams. Results are shown for test sites at which MLS data were acquired at different time intervals.

  9. Total least squares for anomalous change detection

    NASA Astrophysics Data System (ADS)

    Theiler, James; Matsekh, Anna M.

    2010-04-01

    A family of subtraction-based anomalous change detection algorithms is derived from a total least squares (TLSQ) framework. This provides an alternative to the well-known chronochrome algorithm, which is derived from ordinary least squares. In both cases, the most anomalous changes are identified with the pixels that exhibit the largest residuals with respect to the regression of the two images against each other. The family of TLSQbased anomalous change detectors is shown to be equivalent to the subspace RX formulation for straight anomaly detection, but applied to the stacked space. However, this family is not invariant to linear coordinate transforms. On the other hand, whitened TLSQ is coordinate invariant, and special cases of it are equivalent to canonical correlation analysis and optimized covariance equalization. What whitened TLSQ offers is a generalization of these algorithms with the potential for better performance.

  10. Narrow-band imaging with magnifying endoscopy is accurate for detecting gastric intestinal metaplasia

    PubMed Central

    Savarino, Edoardo; Corbo, Marina; Dulbecco, Pietro; Gemignani, Lorenzo; Giambruno, Elisa; Mastracci, Luca; Grillo, Federica; Savarino, Vincenzo

    2013-01-01

    AIM: To investigate the predictive value of narrow-band imaging with magnifying endoscopy (NBI-ME) for identifying gastric intestinal metaplasia (GIM) in unselected patients. METHODS: We prospectively evaluated consecutive patients undergoing upper endoscopy for various indications, such as epigastric discomfort/pain, anaemia, gastro-oesophageal reflux disease, suspicion of peptic ulcer disease, or chronic liver diseases. Patients underwent NBI-ME, which was performed by three blinded, experienced endoscopists. In addition, five biopsies (2 antrum, 1 angulus, and 2 corpus) were taken and examined by two pathologists unaware of the endoscopic findings to determine the presence or absence of GIM. The correlation between light blue crest (LBC) appearance and histology was measured. Moreover, we quantified the degree of LBC appearance as less than 20% (+), 20%-80% (++) and more than 80% (+++) of an image field, and the semiquantitative evaluation of LBC appearance was correlated with IM percentage from the histological findings. RESULTS: We enrolled 100 (58 F/42 M) patients who were mainly referred for gastro-esophageal reflux disease/dyspepsia (46%), cancer screening/anaemia (34%), chronic liver disease (9%), and suspected celiac disease (6%); the remaining patients were referred for other indications. The prevalence of Helicobacter pylori (H. pylori) infection detected from the biopsies was 31%, while 67% of the patients used proton pump inhibitors. LBCs were found in the antrum of 33 patients (33%); 20 of the cases were classified as LBC+, 9 as LBC++, and 4 as LBC+++. LBCs were found in the gastric body of 6 patients (6%), with 5 of them also having LBCs in the antrum. The correlation between the appearance of LBCs and histological GIM was good, with a sensitivity of 80% (95%CI: 67-92), a specificity of 96% (95%CI: 93-99), a positive predictive value of 84% (95%CI: 73-96), a negative predictive value of 95% (95%CI: 92-98), and an accuracy of 93% (95%CI: 90-97). The

  11. Graphene fluorescence switch-based cooperative amplification: a sensitive and accurate method to detection microRNA.

    PubMed

    Liu, Haiyun; Li, Lu; Wang, Qian; Duan, Lili; Tang, Bo

    2014-06-01

    MicroRNAs (miRNAs) play significant roles in a diverse range of biological progress and have been regarded as biomarkers and therapeutic targets in cancer treatment. Sensitive and accurate detection of miRNAs is crucial for better understanding their roles in cancer cells and further validating their function in clinical diagnosis. Here, we developed a stable, sensitive, and specific miRNAs detection method on the basis of cooperative amplification combining with the graphene oxide (GO) fluorescence switch-based circular exponential amplification and the multimolecules labeling of SYBR Green I (SG). First, the target miRNA is adsorbed on the surface of GO, which can protect the miRNA from enzyme digest. Next, the miRNA hybridizes with a partial hairpin probe and then acts as a primer to initiate a strand displacement reaction to form a complete duplex. Finally, under the action of nicking enzyme, universal DNA fragments are released and used as triggers to initiate next reaction cycle, constituting a new circular exponential amplification. In the proposed strategy, a small amount of target miRNA can be converted to a large number of stable DNA triggers, leading to a remarkable amplification for the target. Moreover, compared with labeling with a 1:1 stoichiometric ratio, multimolecules binding of intercalating dye SG to double-stranded DNA (dsDNA) can induce significant enhancement of fluorescence signal and further improve the detection sensitivity. The extraordinary fluorescence quenching of GO used here guarantees the high signal-to-noise ratio. Due to the protection for target miRNA by GO, the cooperative amplification, and low fluorescence background, sensitive and accurate detection of miRNAs has been achieved. The strategy proposed here will offer a new approach for reliable quantification of miRNAs in medical research and early clinical diagnostics. PMID:24823448

  12. Development and application of accurate detection and assay techniques for oilfield scale inhibitors in produced water samples

    SciTech Connect

    Graham, G.M.; Sorbie, K.S.; Boak, L.S.; Taylor, K.; Blilie, L.

    1995-11-01

    In the application of chemical inhibitors in field squeeze treatments for the prevention of sulfate and carbonate mineral scale formation, it is very important that the chemical species involved can be accurately assayed. When the inhibitor concentration drops below a predetermined threshold level for scale inhibition (C{sub t}) then the well may need to be resqueezed. The accurate assay of scale inhibitors down to concentration levels of a few ppm in real field brines can be a difficult task. In this paper, the authors examine a number of interferences which often make assay techniques very difficult to apply in field produced brines. The inhibitors examined include phosphonates (PH), polyacrylates (PAA) and phosphinopolycarboxylates (PPCA). The main objective of this work is to develop suitable pre-treatment/purification techniques which allow the standard wet chemical techniques to be applied effectively after appropriate modification. Successful techniques all based on careful modification of existing methods have been developed by which these common inhibitors can be assayed very accurately at ppm and sub-ppm levels in a variety of North Sea field produced waters. This paper examines some of the major problems and interferences associated with poor analysis and introduces modified methods which can be applied in the field without the use of expensive equipment. It is also shown that different detection methods can often be employed in order to avoid more extensive clean-up strategies. Finally, instrumental methods such as ICP analysis (commonly used for phosphonates) are examined and pre-treatment methods are developed which allow phosphino-polycarboxylic acid based inhibitors to be assayed very accurately by this method. The results from an independent assessment by a North Sea operator, using spiked field produced water, are also presented as an independent verification of the accuracy of the techniques which have been developed in this work.

  13. Olfactory processing: detection of rapid changes.

    PubMed

    Croy, Ilona; Krone, Franziska; Walker, Susannah; Hummel, Thomas

    2015-06-01

    Changes in the olfactory environment have a rather poor chance of being detected. Aim of the present study was to determine, whether the same (cued) or different (uncued) odors can generally be detected at short inter stimulus intervals (ISI) below 2.5 s. Furthermore we investigated, whether inhibition of return, an attentional phenomenon facilitating the detection of new stimuli at longer ISI, is present in the domain of olfaction. Thirteen normosmic people (3 men, 10 women; age range 19-27 years; mean age 23 years) participated. Stimulation was performed using air-dilution olfactometry with 2 odors: phenylethylalcohol and hydrogen disulfide. Reaction time to target stimuli was assessed in cued and uncued conditions at ISIs of 1, 1.5, 2, and 2.5 s. There was a significant main effect of ISI, indicating that odors presented only 1 s apart are missed frequently. Uncued presentation facilitated detection at short ISIs, implying that changes of the olfactory environment are detected better than presentation of the same odor again. Effects in relation to "olfactory inhibition of return," on the other hand, are not supported by our results. This suggests that attention works different for the olfactory system compared with the visual and auditory systems.

  14. Is the Posner Reaction Time Test More Accurate Than Clinical Tests in Detecting Left Neglect in Acute and Chronic Stroke?

    PubMed Central

    Rengachary, Jennifer; d'Avossa, Giovanni; Sapir, Ayelet; Shulman, Gordon L.; Corbetta, Maurizio

    2013-01-01

    Objective To compare the accuracy of common clinical tests for left neglect with that of a computerized reaction time Posner test in a stroke population. Design Neglect measures were collected longitudinally in stroke patients at the acute (≈2wk) and chronic (≈9mo) stage. Identical measures were collected in a healthy control group. Setting Inpatient and outpatient rehabilitation. Participants Acute stroke patients (n=59) with left neglect, 30 of whom were tested longitudinally; healthy age-matched controls (n=30). Interventions Not applicable. Main Outcome Measures A receiver operating characteristic analysis, ranking the measures' sensitivity and specificity using a single summary statistic. Results Most clinical tests were adequately accurate at the acute stage, but many were near chance at the chronic stage. The Posner test was the most sensitive test at both stages, the most sensitive variable being the reaction time difference for detecting targets appearing on the left compared to the right side. Conclusions Computerized reaction time tests can be used to screen for subtle but potentially clinically relevant left neglect, which may not be detectable by conventional clinical tests, especially at the chronic stage. Such tests may be useful to assess the severity of the patients' deficits and provide more accurate measures of the degree of recovery in clinical trials than established clinical measures. PMID:19969172

  15. Change point detection in risk adjusted control charts.

    PubMed

    Assareh, Hassan; Smith, Ian; Mengersen, Kerrie

    2015-12-01

    Precise identification of the time when a change in a clinical process has occurred enables experts to identify a potential special cause more effectively. In this article, we develop change point estimation methods for a clinical dichotomous process in the presence of case mix. We apply Bayesian hierarchical models to formulate the change point where there exists a step change in the odds ratio and logit of risk of a Bernoulli process. Markov Chain Monte Carlo is used to obtain posterior distributions of the change point parameters including location and magnitude of changes and also corresponding probabilistic intervals and inferences. The performance of the Bayesian estimator is investigated through simulations and the result shows that precise estimates can be obtained when they are used in conjunction with the risk-adjusted CUSUM and EWMA control charts. In comparison with alternative EWMA and CUSUM estimators, more accurate and precise estimates are obtained by the Bayesian estimator. These superiorities enhance when probability quantification, flexibility and generaliability of the Bayesian change point detection model are also considered. The Deviance Information Criterion, as a model selection criterion in the Bayesian context, is applied to find the best change point model for a given dataset where there is no prior knowledge about the change type in the process.

  16. Total least squares for anomalous change detection

    SciTech Connect

    Theiler, James P; Matsekh, Anna M

    2010-01-01

    A family of difference-based anomalous change detection algorithms is derived from a total least squares (TLSQ) framework. This provides an alternative to the well-known chronochrome algorithm, which is derived from ordinary least squares. In both cases, the most anomalous changes are identified with the pixels that exhibit the largest residuals with respect to the regression of the two images against each other. The family of TLSQ-based anomalous change detectors is shown to be equivalent to the subspace RX formulation for straight anomaly detection, but applied to the stacked space. However, this family is not invariant to linear coordinate transforms. On the other hand, whitened TLSQ is coordinate invariant, and furthermore it is shown to be equivalent to the optimized covariance equalization algorithm. What whitened TLSQ offers, in addition to connecting with a common language the derivations of two of the most popular anomalous change detection algorithms - chronochrome and covariance equalization - is a generalization of these algorithms with the potential for better performance.

  17. Full house of fears: evidence that people high in attachment anxiety are more accurate in detecting deceit.

    PubMed

    Ein-Dor, Tsachi; Perry, Adi

    2014-04-01

    Lying is deep-rooted in our nature, as over 90% of all people lie. Laypeople, however, do only slightly better than chance when detecting lies and deceptions. Recently, attachment anxiety was linked with people's hypervigilance toward threat-related cues. Accordingly, we tested whether attachment anxiety predicts people's ability to detect deceit and to play poker-a game that is based on players' ability to detect cheating. In Study 1, 202 participants watched a series of interpersonal interactions that comprised subtle clues to the honesty or dishonesty of the speakers. In Study 2, 58 participants watched clips in which such cues were absent. Participants were asked to decide whether the main characters were honest or dishonest. In Study 3, we asked 35 semiprofessional poker players to participate in a poker tournament, and then we predicted the amount of money won during the game. Results indicated that attachment anxiety, but not other types of anxiety, predicted more accurate detection of deceitful statements (Studies 1-2) and a greater amount of money won during a game of poker (Study 3). Results are discussed in relation to the possible adaptive functions of certain personality characteristics, such as attachment anxiety, often viewed as undesirable. PMID:23437786

  18. Less accurate but more efficient family of search templates for detection of gravitational waves from inspiraling compact binaries

    NASA Astrophysics Data System (ADS)

    Chronopoulos, Andreas E.; Apostolatos, Theocharis A.

    2001-08-01

    The network of interferometric detectors that is under construction at various locations on Earth is expected to start searching for gravitational waves in a few years. The number of search templates that is needed to be cross correlated with the noisy output of the detectors is a major issue since computing power capabilities are restricted. By choosing higher and higher post-Newtonian order expansions for the family of search templates we make sure that our filters are more accurate copies of the real waves that hit our detectors. However, this is not the only criterion for choosing a family of search templates. To make the process of detection as efficient as possible, one needs a family of templates with a relatively small number of members that manages to pick up any detectable signal with only a tiny reduction in signal-to-noise ratio. Evidently, one family is better than another if it accomplishes its goal with a smaller number of templates. Following the geometric language of Owen, we have studied the performance of the post1.5-Newtonian family of templates on detecting post2-Newtonian signals for binaries. Several technical issues arise from the fact that the two types of waveforms cannot be made to coincide by a suitable choice of parameters. In general, the parameter space of the signals is not identical with the parameter space of the templates, although in our case they are of the same dimension, and one has to take into account all such peculiarities before drawing any conclusion. An interesting result we have obtained is that the post1.5-Newtonian family of templates happens to be more economical for detecting post2-Newtonian signals than the perfectly accurate post2-Newtonian family of templates itself. The number of templates is reduced by 20-30 %, depending on the acceptable level of reduction in signal-to-noise ratio due to discretization of the family of templates. This makes the post1.5-Newtonian family of templates more favorable for detecting

  19. Detecting genetic responses to environmental change.

    PubMed

    Hoffmann, Ary A; Willi, Yvonne

    2008-06-01

    Changes in environmental conditions can rapidly shift allele frequencies in populations of species with relatively short generation times. Frequency shifts might be detectable in neutral genetic markers when stressful conditions cause a population decline. However, frequency shifts that are diagnostic of specific conditions depend on isolating sets of genes that are involved in adaptive responses. Shifts at candidate loci underlying adaptive responses and DNA regions that control their expression have now been linked to evolutionary responses to pollution, global warming and other changes. Conversely, adaptive constraints, particularly in physiological traits, are recognized through DNA decay in candidate genes. These approaches help researchers and conservation managers understand the power and constraints of evolution.

  20. Evaluation of object level change detection techniques

    NASA Astrophysics Data System (ADS)

    Irvine, John M.; Bergeron, Stuart; Hugo, Doug; O'Brien, Michael A.

    2007-04-01

    A variety of change detection (CD) methods have been developed and employed to support imagery analysis for applications including environmental monitoring, mapping, and support to military operations. Evaluation of these methods is necessary to assess technology maturity, identify areas for improvement, and support transition to operations. This paper presents a methodology for conducting this type of evaluation, discusses the challenges, and illustrates the techniques. The evaluation of object-level change detection methods is more complicated than for automated techniques for processing a single image. We explore algorithm performance assessments, emphasizing the definition of the operating conditions (sensor, target, and environmental factors) and the development of measures of performance. Specific challenges include image registration; occlusion due to foliage, cultural clutter and terrain masking; diurnal differences; and differences in viewing geometry. Careful planning, sound experimental design, and access to suitable imagery with image truth and metadata are critical.

  1. Creation of an Accurate Algorithm to Detect Snellen Best Documented Visual Acuity from Ophthalmology Electronic Health Record Notes

    PubMed Central

    French, Dustin D; Gill, Manjot; Mitchell, Christopher; Jackson, Kathryn; Kho, Abel; Bryar, Paul J

    2016-01-01

    Background Visual acuity is the primary measure used in ophthalmology to determine how well a patient can see. Visual acuity for a single eye may be recorded in multiple ways for a single patient visit (eg, Snellen vs. Jäger units vs. font print size), and be recorded for either distance or near vision. Capturing the best documented visual acuity (BDVA) of each eye in an individual patient visit is an important step for making electronic ophthalmology clinical notes useful in research. Objective Currently, there is limited methodology for capturing BDVA in an efficient and accurate manner from electronic health record (EHR) notes. We developed an algorithm to detect BDVA for right and left eyes from defined fields within electronic ophthalmology clinical notes. Methods We designed an algorithm to detect the BDVA from defined fields within 295,218 ophthalmology clinical notes with visual acuity data present. About 5668 unique responses were identified and an algorithm was developed to map all of the unique responses to a structured list of Snellen visual acuities. Results Visual acuity was captured from a total of 295,218 ophthalmology clinical notes during the study dates. The algorithm identified all visual acuities in the defined visual acuity section for each eye and returned a single BDVA for each eye. A clinician chart review of 100 random patient notes showed a 99% accuracy detecting BDVA from these records and 1% observed error. Conclusions Our algorithm successfully captures best documented Snellen distance visual acuity from ophthalmology clinical notes and transforms a variety of inputs into a structured Snellen equivalent list. Our work, to the best of our knowledge, represents the first attempt at capturing visual acuity accurately from large numbers of electronic ophthalmology notes. Use of this algorithm can benefit research groups interested in assessing visual acuity for patient centered outcome. All codes used for this study are currently

  2. Detecting hydrological changes through conceptual model

    NASA Astrophysics Data System (ADS)

    Viola, Francesco; Caracciolo, Domenico; Pumo, Dario; Francipane, Antonio; Valerio Noto, Leonardo

    2015-04-01

    Natural changes and human modifications in hydrological systems coevolve and interact in a coupled and interlinked way. If, on one hand, climatic changes are stochastic, non-steady, and affect the hydrological systems, on the other hand, human-induced changes due to over-exploitation of soils and water resources modifies the natural landscape, water fluxes and its partitioning. Indeed, the traditional assumption of static systems in hydrological analysis, which has been adopted for long time, fails whenever transient climatic conditions and/or land use changes occur. Time series analysis is a way to explore environmental changes together with societal changes; unfortunately, the not distinguishability between causes restrict the scope of this method. In order to overcome this limitation, it is possible to couple time series analysis with an opportune hydrological model, such as a conceptual hydrological model, which offers a schematization of complex dynamics acting within a basin. Assuming that model parameters represent morphological basin characteristics and that calibration is a way to detect hydrological signature at a specific moment, it is possible to argue that calibrating the model over different time windows could be a method for detecting potential hydrological changes. In order to test the capabilities of a conceptual model in detecting hydrological changes, this work presents different "in silico" experiments. A synthetic-basin is forced with an ensemble of possible future scenarios generated with a stochastic weather generator able to simulate steady and non-steady climatic conditions. The experiments refer to Mediterranean climate, which is characterized by marked seasonality, and consider the outcomes of the IPCC 5th report for describing climate evolution in the next century. In particular, in order to generate future climate change scenarios, a stochastic downscaling in space and time is carried out using realizations of an ensemble of General

  3. Ischemia detection from morphological QRS angle changes.

    PubMed

    Romero, Daniel; Martínez, Juan Pablo; Laguna, Pablo; Pueyo, Esther

    2016-07-01

    In this paper, an ischemia detector is presented based on the analysis of QRS-derived angles. The detector has been developed by modeling ischemic effects on the QRS angles as a gradual change with a certain transition time and assuming a Laplacian additive modeling error contaminating the angle series. Both standard and non-standard leads were used for analysis. Non-standard leads were obtained by applying the PCA technique over specific lead subsets to represent different potential locations of the ischemic zone. The performance of the proposed detector was tested over a population of 79 patients undergoing percutaneous coronary intervention in one of the major coronary arteries (LAD (n  =  25), RCA (n  =  16) and LCX (n  =  38)). The best detection performance, obtained for standard ECG leads, was achieved in the LAD group with values of sensitivity and specificity of [Formula: see text], [Formula: see text], followed by the RCA group with [Formula: see text], Sp  =  94.4 and the LCX group with [Formula: see text], [Formula: see text], notably outperforming detection based on the ST series in all cases, with the same detector structure. The timing of the detected ischemic events ranged from 30 s up to 150 s (mean  =  66.8 s) following the start of occlusion. We conclude that changes in the QRS angles can be used to detect acute myocardial ischemia. PMID:27243441

  4. Seabed change detection in challenging environments

    NASA Astrophysics Data System (ADS)

    Matthews, Cameron A.; Sternlicht, Daniel D.

    2011-06-01

    Automatic Change Detection (ACD) compares new and stored terrain images for alerting to changes occurring over time. These techniques, long used in airborne radar, are just beginning to be applied to sidescan sonar. Under the right conditions ACD by image correlation-comparing multi-temporal image data at the pixel or parcel level-can be used to detect new objects on the seafloor. Synthetic aperture sonars (SAS)-coherent sensors that produce fine-scale, range-independent resolution seafloor images-are well suited for this approach; however, dynamic seabed environments can introduce "clutter" to the process. This paper explores an ACD method that uses salience mapping in a global-to-local analysis architecture. In this method, termed Temporally Invariant Saliency (TIS), variance ratios of median-filtered repeat-pass images are used to detect new objects, while deemphasizing modest environmental or radiometric-induced changes in the background. Successful tests with repeat-pass data from two SAS systems mounted on autonomous undersea vehicles (AUV) demonstrate the feasibility of the technique.

  5. Scene change detection based on multimodal integration

    NASA Astrophysics Data System (ADS)

    Zhu, Yingying; Zhou, Dongru

    2003-09-01

    Scene change detection is an essential step to automatic and content-based video indexing, retrieval and browsing. In this paper, a robust scene change detection and classification approach is presented, which analyzes audio, visual and textual sources and accounts for their inter-relations and coincidence to semantically identify and classify video scenes. Audio analysis focuses on the segmentation of audio stream into four types of semantic data such as silence, speech, music and environmental sound. Further processing on speech segments aims at locating speaker changes. Video analysis partitions visual stream into shots. Text analysis can provide a supplemental source of clues for scene classification and indexing information. We integrate the video and audio analysis results to identify video scenes and use the text information detected by the video OCR technology or derived from transcripts available to refine scene classification. Results from single source segmentation are in some cases suboptimal. By combining visual, aural features adn the accessorial text information, the scence extraction accuracy is enhanced, and more semantic segmentations are developed. Experimental results are proven to rather promising.

  6. Accurate detection of on-state quantum dot and biomolecules in a microfluidic flow with single-molecule two-color coincidence detection.

    PubMed

    Zhang, Chun-Yang; Yang, Kun

    2010-05-01

    Due to their unique optical and electronic properties, quantum dots (QDs) have been widely used in a variety of biosensors for sensitive detection of biomarkers and small molecules. However, single QD exhibits dynamic fluctuation of fluorescence intensity (i.e., blinking) with the transition between on and off states, which adversely influences the development of QD-based optical biosensors. Therefore, the methods for efficient evaluation of on-state QD are especially important and highly desirable. In this paper, a novel and unique approach based on single-molecule two-color coincidence detection is developed to simply and accurately evaluate the on-state QDs in a microfluidic flow. Our results demonstrate that improved QDs in the on state are detected in a microfluidic flow in comparison with that in the Brownian motion state, thus paving the way to the development of single QD-based biosensors for sensitive detection of low-abundance biomolecules. This single-molecule two-color coincidence detection has been applied for the homegeneous detection of nucleic acids in a microfluidic flow with the detection sensitivity of 5.0 fM.

  7. Probabilistic Change Detection Framework for Analyzing Settlement Dynamics Using Very High-resolution Satellite Imagery

    SciTech Connect

    Vatsavai, Raju; Graesser, Jordan B

    2012-01-01

    Global human population growth and an increasingly urbanizing world have led to rapid changes in human settlement landscapes and patterns. Timely monitoring and assessment of these changes and dissemination of accurate information is important for policy makers, city planners, and humanitarian relief workers. Satellite imagery provides useful data for the aforementioned applications, and remote sensing can be used to identify and quantify change areas. We explore a probabilistic framework to identify changes in human settlements using very high-resolution satellite imagery. As compared to predominantly pixel-based change detection systems which are highly sensitive to image registration errors, our grid (block) based approach is more robust to registration errors. The presented framework is an automated change detection system applicable to both panchromatic and multi-spectral imagery. The detection system provides comprehensible information about change areas, and minimizes the post-detection thresholding procedure often needed in traditional change detection algorithms.

  8. Liquid Hybridization and Solid Phase Detection: A Highly Sensitive and Accurate Strategy for MicroRNA Detection in Plants and Animals.

    PubMed

    Li, Fosheng; Mei, Lanju; Zhan, Cheng; Mao, Qiang; Yao, Min; Wang, Shenghua; Tang, Lin; Chen, Fang

    2016-01-01

    MicroRNAs (miRNAs) play important roles in nearly every aspect of biology, including physiological, biochemical, developmental and pathological processes. Therefore, a highly sensitive and accurate method of detection of miRNAs has great potential in research on theory and application, such as the clinical approach to medicine, animal and plant production, as well as stress response. Here, we report a strategic method to detect miRNAs from multicellular organisms, which mainly includes liquid hybridization and solid phase detection (LHSPD); it has been verified in various species and is much more sensitive than traditional biotin-labeled Northern blots. By using this strategy and chemiluminescent detection with digoxigenin (DIG)-labeled or biotin-labeled oligonucleotide probes, as low as 0.01-0.25 fmol [for DIG-CDP Star (disodium2-chloro-5-(4-methoxyspiro{1,2-dioxetane-3,2'-(5'-chloro)tricyclo[3.3.1.13,7]decan}-4-yl)phenyl phosphate) system], 0.005-0.1 fmol (for biotin-CDP Star system), or 0.05-0.5 fmol (for biotin-luminol system) of miRNA can be detected and one-base difference can be distinguished between miRNA sequences. Moreover, LHSPD performed very well in the quantitative analysis of miRNAs, and the whole process can be completed within about 9 h. The strategy of LHSPD provides an effective solution for rapid, accurate, and sensitive detection and quantitative analysis of miRNAs in plants and animals. PMID:27598139

  9. Liquid Hybridization and Solid Phase Detection: A Highly Sensitive and Accurate Strategy for MicroRNA Detection in Plants and Animals

    PubMed Central

    Li, Fosheng; Mei, Lanju; Zhan, Cheng; Mao, Qiang; Yao, Min; Wang, Shenghua; Tang, Lin; Chen, Fang

    2016-01-01

    MicroRNAs (miRNAs) play important roles in nearly every aspect of biology, including physiological, biochemical, developmental and pathological processes. Therefore, a highly sensitive and accurate method of detection of miRNAs has great potential in research on theory and application, such as the clinical approach to medicine, animal and plant production, as well as stress response. Here, we report a strategic method to detect miRNAs from multicellular organisms, which mainly includes liquid hybridization and solid phase detection (LHSPD); it has been verified in various species and is much more sensitive than traditional biotin-labeled Northern blots. By using this strategy and chemiluminescent detection with digoxigenin (DIG)-labeled or biotin-labeled oligonucleotide probes, as low as 0.01–0.25 fmol [for DIG-CDP Star (disodium2-chloro-5-(4-methoxyspiro{1,2-dioxetane-3,2′-(5′-chloro)tricyclo[3.3.1.13,7]decan}-4-yl)phenyl phosphate) system], 0.005–0.1 fmol (for biotin-CDP Star system), or 0.05–0.5 fmol (for biotin-luminol system) of miRNA can be detected and one-base difference can be distinguished between miRNA sequences. Moreover, LHSPD performed very well in the quantitative analysis of miRNAs, and the whole process can be completed within about 9 h. The strategy of LHSPD provides an effective solution for rapid, accurate, and sensitive detection and quantitative analysis of miRNAs in plants and animals. PMID:27598139

  10. Accurate Point-of-Care Detection of Ruptured Fetal Membranes: Improved Diagnostic Performance Characteristics with a Monoclonal/Polyclonal Immunoassay

    PubMed Central

    Rogers, Linda C.; Scott, Laurie; Block, Jon E.

    2016-01-01

    OBJECTIVE Accurate and timely diagnosis of rupture of membranes (ROM) is imperative to allow for gestational age-specific interventions. This study compared the diagnostic performance characteristics between two methods used for the detection of ROM as measured in the same patient. METHODS Vaginal secretions were evaluated using the conventional fern test as well as a point-of-care monoclonal/polyclonal immunoassay test (ROM Plus®) in 75 pregnant patients who presented to labor and delivery with complaints of leaking amniotic fluid. Both tests were compared to analytical confirmation of ROM using three external laboratory tests. Diagnostic performance characteristics were calculated including sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy. RESULTS Diagnostic performance characteristics uniformly favored ROM detection using the immunoassay test compared to the fern test: sensitivity (100% vs. 77.8%), specificity (94.8% vs. 79.3%), PPV (75% vs. 36.8%), NPV (100% vs. 95.8%), and accuracy (95.5% vs. 79.1%). CONCLUSIONS The point-of-care immunoassay test provides improved diagnostic accuracy for the detection of ROM compared to fern testing. It has the potential of improving patient management decisions, thereby minimizing serious complications and perinatal morbidity. PMID:27199579

  11. Time series change detection: Algorithms for land cover change

    NASA Astrophysics Data System (ADS)

    Boriah, Shyam

    can be used for decision making and policy planning purposes. In particular, previous change detection studies have primarily relied on examining differences between two or more satellite images acquired on different dates. Thus, a technological solution that detects global land cover change using high temporal resolution time series data will represent a paradigm-shift in the field of land cover change studies. To realize these ambitious goals, a number of computational challenges in spatio-temporal data mining need to be addressed. Specifically, analysis and discovery approaches need to be cognizant of climate and ecosystem data characteristics such as seasonality, non-stationarity/inter-region variability, multi-scale nature, spatio-temporal autocorrelation, high-dimensionality and massive data size. This dissertation, a step in that direction, translates earth science challenges to computer science problems, and provides computational solutions to address these problems. In particular, three key technical capabilities are developed: (1) Algorithms for time series change detection that are effective and can scale up to handle the large size of earth science data; (2) Change detection algorithms that can handle large numbers of missing and noisy values present in satellite data sets; and (3) Spatio-temporal analysis techniques to identify the scale and scope of disturbance events.

  12. Evaluation of change detection techniques for monitoring coastal zone environments

    NASA Technical Reports Server (NTRS)

    Weismiller, R. A. (Principal Investigator); Kristof, S. J.; Scholz, D. K.; Anuta, P. E.; Momin, S. M.

    1977-01-01

    The author has identified the following significant results. Four change detection techniques were designed and implemented for evaluation: (1) post classification comparison change detection, (2) delta data change detection, (3) spectral/temporal change classification, and (4) layered spectral/temporal change classification. The post classification comparison technique reliably identified areas of change and was used as the standard for qualitatively evaluating the other three techniques. The layered spectral/temporal change classification and the delta data change detection results generally agreed with the post classification comparison technique results; however, many small areas of change were not identified. Major discrepancies existed between the post classification comparison and spectral/temporal change detection results.

  13. Children with mixed language disorder do not discriminate accurately facial identity when expressions change.

    PubMed

    Robel, Laurence; Vaivre-Douret, Laurence; Neveu, Xavier; Piana, Hélène; Perier, Antoine; Falissard, Bruno; Golse, Bernard

    2008-12-01

    We investigated the recognition of pairs of faces (same or different facial identities and expressions) in two groups of 14 children aged 6-10 years, with either an expressive language disorder (ELD), or a mixed language disorder (MLD), and two groups of 14 matched healthy controls. When looking at their global performances, children with either expressive (ELD) or MLD have few differences from controls in either face or emotional recognition. At contrary, we found that children with MLD, but not those with ELD, take identical faces to be different if their expressions change. Since children with mixed language disorders are socially more impaired than children with ELD, we think that these features may partly underpin the social difficulties of these children.

  14. Immunohistochemical Detection of Changes in Tumor Hypoxia

    SciTech Connect

    Russell, James Carlin, Sean; Burke, Sean A.; Wen Bixiu; Yang, Kwang Mo; Ling, C. Clifton

    2009-03-15

    Purpose: Although hypoxia is a known prognostic factor, its effect will be modified by the rate of reoxygenation and the extent to which the cells are acutely hypoxic. We tested the ability of exogenous and endogenous markers to detect reoxygenation in a xenograft model. Our technique might be applicable to stored patient samples. Methods and Materials: The human colorectal carcinoma line, HT29, was grown in nude mice. Changes in tumor hypoxia were examined by injection of pimonidazole, followed 24 hours later by EF5. Cryosections were stained for these markers and for carbonic anhydrase IX (CAIX) and hypoxia-inducible factor 1{alpha} (HIF1{alpha}). Tumor hypoxia was artificially manipulated by carbogen exposure. Results: In unstressed tumors, all four markers showed very similar spatial distributions. After carbogen treatment, pimonidazole and EF5 could detect decreased hypoxia. HIF1{alpha} staining was also decreased relative to CAIX, although the effect was less pronounced than for EF5. Control tumors displayed small regions that had undergone spontaneous changes in tumor hypoxia, as judged by pimonidazole relative to EF5; most of these changes were reflected by CAIX and HIF1{alpha}. Conclusion: HIF1{alpha} can be compared with either CAIX or a previously administered nitroimidazole to provide an estimate of reoxygenation.

  15. Nationwide Hybrid Change Detection of Buildings

    NASA Astrophysics Data System (ADS)

    Hron, V.; Halounova, L.

    2016-06-01

    The Fundamental Base of Geographic Data of the Czech Republic (hereinafter FBGD) is a national 2D geodatabase at a 1:10,000 scale with more than 100 geographic objects. This paper describes the design of the permanent updating mechanism of buildings in FBGD. The proposed procedure belongs to the category of hybrid change detection (HCD) techniques which combine pixel-based and object-based evaluation. The main sources of information for HCD are cadastral information and bi-temporal vertical digital aerial photographs. These photographs have great information potential because they contain multispectral, position and also elevation information. Elevation information represents a digital surface model (DSM) which can be obtained using the image matching technique. Pixel-based evaluation of bi-temporal DSMs enables fast localization of places with potential building changes. These coarse results are subsequently classified through the object-based image analysis (OBIA) using spectral, textural and contextual features and GIS tools. The advantage of the two-stage evaluation is the pre-selection of locations where image segmentation (a computationally demanding part of OBIA) is performed. It is not necessary to apply image segmentation to the entire scene, but only to the surroundings of detected changes, which contributes to significantly faster processing and lower hardware requirements. The created technology is based on open-source software solutions that allow easy portability on multiple computers and parallelization of processing. This leads to significant savings of financial resources which can be expended on the further development of FBGD.

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

    PubMed

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

    2016-01-01

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

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-02-22

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

  19. Imaging, object detection, and change detection with a polarized multistatic GPR array

    DOEpatents

    Beer, N. Reginald; Paglieroni, David W.

    2015-07-21

    A polarized detection system performs imaging, object detection, and change detection factoring in the orientation of an object relative to the orientation of transceivers. The polarized detection system may operate on one of several modes of operation based on whether the imaging, object detection, or change detection is performed separately for each transceiver orientation. In combined change mode, the polarized detection system performs imaging, object detection, and change detection separately for each transceiver orientation, and then combines changes across polarizations. In combined object mode, the polarized detection system performs imaging and object detection separately for each transceiver orientation, and then combines objects across polarizations and performs change detection on the result. In combined image mode, the polarized detection system performs imaging separately for each transceiver orientation, and then combines images across polarizations and performs object detection followed by change detection on the result.

  20. Accurate and Rigorous Prediction of the Changes in Protein Free Energies in a Large-Scale Mutation Scan.

    PubMed

    Gapsys, Vytautas; Michielssens, Servaas; Seeliger, Daniel; de Groot, Bert L

    2016-06-20

    The prediction of mutation-induced free-energy changes in protein thermostability or protein-protein binding is of particular interest in the fields of protein design, biotechnology, and bioengineering. Herein, we achieve remarkable accuracy in a scan of 762 mutations estimating changes in protein thermostability based on the first principles of statistical mechanics. The remaining error in the free-energy estimates appears to be due to three sources in approximately equal parts, namely sampling, force-field inaccuracies, and experimental uncertainty. We propose a consensus force-field approach, which, together with an increased sampling time, leads to a free-energy prediction accuracy that matches those reached in experiments. This versatile approach enables accurate free-energy estimates for diverse proteins, including the prediction of changes in the melting temperature of the membrane protein neurotensin receptor 1. PMID:27122231

  1. CLARREO Cornerstone of the Earth Observing System: Measuring Decadal Change Through Accurate Emitted Infrared and Reflected Solar Spectra and Radio Occultation

    NASA Technical Reports Server (NTRS)

    Sandford, Stephen P.

    2010-01-01

    The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is one of four Tier 1 missions recommended by the recent NRC Decadal Survey report on Earth Science and Applications from Space (NRC, 2007). The CLARREO mission addresses the need to provide accurate, broadly acknowledged climate records that are used to enable validated long-term climate projections that become the foundation for informed decisions on mitigation and adaptation policies that address the effects of climate change on society. The CLARREO mission accomplishes this critical objective through rigorous SI traceable decadal change observations that are sensitive to many of the key uncertainties in climate radiative forcings, responses, and feedbacks that in turn drive uncertainty in current climate model projections. These same uncertainties also lead to uncertainty in attribution of climate change to anthropogenic forcing. For the first time CLARREO will make highly accurate, global, SI-traceable decadal change observations sensitive to the most critical, but least understood, climate forcings, responses, and feedbacks. The CLARREO breakthrough is to achieve the required levels of accuracy and traceability to SI standards for a set of observations sensitive to a wide range of key decadal change variables. The required accuracy levels are determined so that climate trend signals can be detected against a background of naturally occurring variability. Climate system natural variability therefore determines what level of accuracy is overkill, and what level is critical to obtain. In this sense, the CLARREO mission requirements are considered optimal from a science value perspective. The accuracy for decadal change traceability to SI standards includes uncertainties associated with instrument calibration, satellite orbit sampling, and analysis methods. Unlike most space missions, the CLARREO requirements are driven not by the instantaneous accuracy of the measurements, but by accuracy in

  2. An accurate and inexpensive color-based assay for detecting severe anemia in a limited-resource setting.

    PubMed

    McGann, Patrick T; Tyburski, Erika A; de Oliveira, Vysolela; Santos, Brigida; Ware, Russell E; Lam, Wilbur A

    2015-12-01

    Severe anemia is an important cause of morbidity and mortality among children in resource-poor settings, but laboratory diagnostics are often limited in these locations. To address this need, we developed a simple, inexpensive, and color-based point-of-care (POC) assay to detect severe anemia. The purpose of this study was to evaluate the accuracy of this novel POC assay to detect moderate and severe anemia in a limited-resource setting. The study was a cross-sectional study conducted on children with sickle cell anemia in Luanda, Angola. The hemoglobin concentrations obtained by the POC assay were compared to reference values measured by a calibrated automated hematology analyzer. A total of 86 samples were analyzed (mean hemoglobin concentration 6.6 g/dL). There was a strong correlation between the hemoglobin concentrations obtained by the POC assay and reference values obtained from an automated hematology analyzer (r=0.88, P<0.0001). The POC assay demonstrated excellent reproducibility (r=0.93, P<0.0001) and the reagents appeared to be durable in a tropical setting (r=0.93, P<0.0001). For the detection of severe anemia that may require blood transfusion (hemoglobin <5 g/dL), the POC assay had sensitivity of 88.9% and specificity of 98.7%. These data demonstrate that an inexpensive (<$0.25 USD) POC assay accurately estimates low hemoglobin concentrations and has the potential to become a transformational diagnostic tool for severe anemia in limited-resource settings.

  3. Detecting past changes of effective population size.

    PubMed

    Nikolic, Natacha; Chevalet, Claude

    2014-06-01

    Understanding and predicting population abundance is a major challenge confronting scientists. Several genetic models have been developed using microsatellite markers to estimate the present and ancestral effective population sizes. However, to get an overview on the evolution of population requires that past fluctuation of population size be traceable. To address the question, we developed a new model estimating the past changes of effective population size from microsatellite by resolving coalescence theory and using approximate likelihoods in a Monte Carlo Markov Chain approach. The efficiency of the model and its sensitivity to gene flow and to assumptions on the mutational process were checked using simulated data and analysis. The model was found especially useful to provide evidence of transient changes of population size in the past. The times at which some past demographic events cannot be detected because they are too ancient and the risk that gene flow may suggest the false detection of a bottleneck are discussed considering the distribution of coalescence times. The method was applied on real data sets from several Atlantic salmon populations. The method called VarEff (Variation of Effective size) was implemented in the R package VarEff and is made available at https://qgsp.jouy.inra.fr and at http://cran.r-project.org/web/packages/VarEff.

  4. Bone Positron Emission Tomography with or without CT Is More Accurate than Bone Scan for Detection of Bone Metastasis

    PubMed Central

    Lee, Soo Jin; Kim, Sang Eun

    2013-01-01

    Objective Na18F bone positron emission tomography (bone PET) is a new imaging modality which is useful for the evaluation of bone diseases. Here, we compared the diagnostic accuracies between bone PET and bone scan for the detection of bone metastasis (BM). Materials and Methods Sixteen cancer patients (M:F = 10:6, mean age = 60 ± 12 years) who underwent both bone PET and bone scan were analyzed. Bone PET was conducted 30 minutes after the injection of 370 MBq Na18F, and a bone scan was performed 3 hours after the injection of 1295 MBq 99mTc-hydroxymethylene diphosphonate. Results In the patient-based analysis (8 patients with BM and 8 without BM), the sensitivities of bone PET (100% = 8/8) and bone scan (87.5% = 7/8) were not significantly different (p > 0.05), whereas the specificity of bone PET (87.5% = 7/8) was significantly greater than that of the bone scan (25% = 2/8) (p < 0.05). In the lesion-based analysis (43 lesions in 14 patients; 31 malignant and 12 benign), the sensitivity of bone PET (100% = 31/31) was significantly greater than that of bone scan (38.7% = 12/31) (p < 0.01), and the specificity of bone PET (75.0% = 9/12) was also significantly higher than that of bone scan (8.3% = 1/12) (p < 0.05). The receiver operating characteristic curve analysis showed that bone PET was significantly more accurate than the bone scan in the patient (p = 0.0306) and lesion (p = 0.0001) based analyses. Conclusion Na18F bone PET is more accurate than bone scan for BM evaluation. PMID:23690722

  5. Point pattern match-based change detection in a constellation of previously detected objects

    DOEpatents

    Paglieroni, David W.

    2016-06-07

    A method and system is provided that applies attribute- and topology-based change detection to objects that were detected on previous scans of a medium. The attributes capture properties or characteristics of the previously detected objects, such as location, time of detection, detection strength, size, elongation, orientation, etc. The locations define a three-dimensional network topology forming a constellation of previously detected objects. The change detection system stores attributes of the previously detected objects in a constellation database. The change detection system detects changes by comparing the attributes and topological consistency of newly detected objects encountered during a new scan of the medium to previously detected objects in the constellation database. The change detection system may receive the attributes of the newly detected objects as the objects are detected by an object detection system in real time.

  6. The time course of configural change detection for novel 3-D objects.

    PubMed

    Favelle, Simone; Palmisano, Stephen

    2010-05-01

    The present study investigated the time course of visual information processing that is responsible for successful object change detection involving the configuration and shape of 3-D novel object parts. Using a one-shot change detection task, we manipulated stimulus and interstimulus mask durations (40-500 msec). Experiments 1A and 1B showed no change detection advantage for configuration at very short (40-msec) stimulus durations, but the configural advantage did emerge with durations between 80 and 160 msec. In Experiment 2, we showed that, at shorter stimulus durations, the number of parts changing was the best predictor of change detection performance. Finally, in Experiment 3, with a stimulus duration of 160 msec, configuration change detection was found to be highly accurate for each of the mask durations tested, suggesting a fast processing speed for this kind of change information. However, switch and shape change detection reached peak levels of accuracy only when mask durations were increased to 160 and 320 msec, respectively. We conclude that, with very short stimulus exposures, successful object change detection depends primarily on quantitative measures of change. However, with longer stimulus exposures, the qualitative nature of the change becomes progressively more important, resulting in the well-known configural advantage for change detection.

  7. Classification, change-detection and accuracy assessment: Toward fuller automation

    NASA Astrophysics Data System (ADS)

    Podger, Nancy E.

    This research aims to automate methods for conducting change detection studies using remotely sensed images. Five major objectives were tested on two study sites, one encompassing Madison, Wisconsin, and the other Fort Hood, Texas. (Objective 1) Enhance accuracy assessments by estimating standard errors using bootstrap analysis. Bootstrap estimates of the standard errors were found to be comparable to parametric statistical estimates. Also, results show that bootstrapping can be used to evaluate the consistency of a classification process. (Objective 2) Automate the guided clustering classifier. This research shows that the guided clustering classification process can be automated while maintaining highly accurate results. Three different evaluation methods were used. (Evaluation 1) Appraised the consistency of 25 classifications produced from the automated system. The classifications differed from one another by only two to four percent. (Evaluation 2) Compared accuracies produced by the automated system to classification accuracies generated following a manual guided clustering protocol. Results: The automated system produced higher overall accuracies in 50 percent of the tests and was comparable for all but one of the remaining tests. (Evaluation 3) Assessed the time and effort required to produce accurate classifications. Results: The automated system produced classifications in less time and with less effort than the manual 'protocol' method. (Objective 3) Built a flexible, interactive software tool to aid in producing binary change masks. (Objective 4) Reduced by automation the amount of training data needed to classify the second image of a two-time-period change detection project. Locations of the training sites in 'unchanged' areas employed to classify the first image were used to identify sites where spectral information was automatically extracted from the second image. Results: The automatically generated training data produces classification accuracies

  8. Study of vegetation index selection and changing detection thresholds in land cover change detection assessment using change vector analysis

    NASA Astrophysics Data System (ADS)

    Nguyen, Duy; Tran, Giang

    2012-07-01

    In recent years, Vietnamese rapidly developing economy has led to speedy changes in land cover. The study of changing detection of land cover plays an important role in making the strategy of the managers. There are two main approaches in changing detection research by using remote sensing and GIS: post- classification change detection analysis approach and pre-classification changing spectral determination approach. Each has their own different advantages and disadvantages. The second one is further divided into: Image Differencing, Multi-date Principal Component Analysis (MPCA); Change Vector Analysis (CVA). In this study, researchers introduce CVA method. This method is based on two important index to show the primary feature of land cover, such as: vegetation index (NDVI-) and barren land index (-BI). Ability to apply methods of CVA has been mentioned in the studies [1, 2, 3, and 4]. However, in these studies did not mention the NDVI index selection and changing detection threshold in changing detection assessment? This paper proposes application to solve these two problems.

  9. Vehicle Localization by LIDAR Point Correlation Improved by Change Detection

    NASA Astrophysics Data System (ADS)

    Schlichting, A.; Brenner, C.

    2016-06-01

    LiDAR sensors are proven sensors for accurate vehicle localization. Instead of detecting and matching features in the LiDAR data, we want to use the entire information provided by the scanners. As dynamic objects, like cars, pedestrians or even construction sites could lead to wrong localization results, we use a change detection algorithm to detect these objects in the reference data. If an object occurs in a certain number of measurements at the same position, we mark it and every containing point as static. In the next step, we merge the data of the single measurement epochs to one reference dataset, whereby we only use static points. Further, we also use a classification algorithm to detect trees. For the online localization of the vehicle, we use simulated data of a vertical aligned automotive LiDAR sensor. As we only want to use static objects in this case as well, we use a random forest classifier to detect dynamic scan points online. Since the automotive data is derived from the LiDAR Mobile Mapping System, we are able to use the labelled objects from the reference data generation step to create the training data and further to detect dynamic objects online. The localization then can be done by a point to image correlation method using only static objects. We achieved a localization standard deviation of about 5 cm (position) and 0.06° (heading), and were able to successfully localize the vehicle in about 93 % of the cases along a trajectory of 13 km in Hannover, Germany.

  10. A Multi-Index Integrated Change detection method for updating the National Land Cover Database

    USGS Publications Warehouse

    Jin, Suming; Yang, Limin; Xian, George Z.; Danielson, Patrick; Homer, Collin G.

    2010-01-01

    Land cover change is typically captured by comparing two or more dates of imagery and associating spectral change with true thematic change. A new change detection method, Multi-Index Integrated Change (MIIC), has been developed to capture a full range of land cover disturbance patterns for updating the National Land Cover Database (NLCD). Specific indices typically specialize in identifying only certain types of disturbances; for example, the Normalized Burn Ratio (NBR) has been widely used for monitoring fire disturbance. Recognizing the potential complementary nature of multiple indices, we integrated four indices into one model to more accurately detect true change between two NLCD time periods. The four indices are NBR, Normalized Difference Vegetation Index (NDVI), Change Vector (CV), and a newly developed index called the Relative Change Vector (RCV). The model is designed to provide both change location and change direction (e.g. biomass increase or biomass decrease). The integrated change model has been tested on five image pairs from different regions exhibiting a variety of disturbance types. Compared with a simple change vector method, MIIC can better capture the desired change without introducing additional commission errors. The model is particularly accurate at detecting forest disturbances, such as forest harvest, forest fire, and forest regeneration. Agreement between the initial change map areas derived from MIIC and the retained final land cover type change areas will be showcased from the pilot test sites.

  11. A Multi-Index Integrated Change Detection Method for Updating the National Land Cover Database

    NASA Astrophysics Data System (ADS)

    Jin, S.; Yang, L.; Xian, G. Z.; Danielson, P.; Homer, C.

    2010-12-01

    Land cover change is typically captured by comparing two or more dates of imagery and associating spectral change with true thematic change. A new change detection method, Multi-Index Integrated Change (MIIC), has been developed to capture a full range of land cover disturbance patterns for updating the National Land Cover Database (NLCD). Specific indices typically specialize in identifying only certain types of disturbances; for example, the Normalized Burn Ratio (NBR) has been widely used for monitoring fire disturbance. Recognizing the potential complementary nature of multiple indices, we integrated four indices into one model to more accurately detect true change between two NLCD time periods. The four indices are NBR, Normalized Difference Vegetation Index (NDVI), Change Vector (CV), and a newly developed index called the Relative Change Vector (RCV). The model is designed to provide both change location and change direction (e.g. biomass increase or biomass decrease). The integrated change model has been tested on five image pairs from different regions exhibiting a variety of disturbance types. Compared with a simple change vector method, MIIC can better capture the desired change without introducing additional commission errors. The model is particularly accurate at detecting forest disturbances, such as forest harvest, forest fire, and forest regeneration. Agreement between the initial change map areas derived from MIIC and the retained final land cover type change areas will be showcased from the pilot test sites.

  12. A finite rate of innovation algorithm for fast and accurate spike detection from two-photon calcium imaging

    NASA Astrophysics Data System (ADS)

    Oñativia, Jon; Schultz, Simon R.; Dragotti, Pier Luigi

    2013-08-01

    Objective. Inferring the times of sequences of action potentials (APs) (spike trains) from neurophysiological data is a key problem in computational neuroscience. The detection of APs from two-photon imaging of calcium signals offers certain advantages over traditional electrophysiological approaches, as up to thousands of spatially and immunohistochemically defined neurons can be recorded simultaneously. However, due to noise, dye buffering and the limited sampling rates in common microscopy configurations, accurate detection of APs from calcium time series has proved to be a difficult problem. Approach. Here we introduce a novel approach to the problem making use of finite rate of innovation (FRI) theory (Vetterli et al 2002 IEEE Trans. Signal Process. 50 1417-28). For calcium transients well fit by a single exponential, the problem is reduced to reconstructing a stream of decaying exponentials. Signals made of a combination of exponentially decaying functions with different onset times are a subclass of FRI signals, for which much theory has recently been developed by the signal processing community. Main results. We demonstrate for the first time the use of FRI theory to retrieve the timing of APs from calcium transient time series. The final algorithm is fast, non-iterative and parallelizable. Spike inference can be performed in real-time for a population of neurons and does not require any training phase or learning to initialize parameters. Significance. The algorithm has been tested with both real data (obtained by simultaneous electrophysiology and multiphoton imaging of calcium signals in cerebellar Purkinje cell dendrites), and surrogate data, and outperforms several recently proposed methods for spike train inference from calcium imaging data.

  13. Stealth surface modification of surface-enhanced Raman scattering substrates for sensitive and accurate detection in protein solutions.

    PubMed

    Sun, Fang; Ella-Menye, Jean-Rene; Galvan, Daniel David; Bai, Tao; Hung, Hsiang-Chieh; Chou, Ying-Nien; Zhang, Peng; Jiang, Shaoyi; Yu, Qiuming

    2015-03-24

    Reliable surface-enhanced Raman scattering (SERS) based biosensing in complex media is impeded by nonspecific protein adsorptions. Because of the near-field effect of SERS, it is challenging to modify SERS-active substrates using conventional nonfouling materials without introducing interference from their SERS signals. Herein, we report a stealth surface modification strategy for sensitive, specific and accurate detection of fructose in protein solutions using SERS by forming a mixed self-assembled monolayer (SAM). The SAM consists of a short zwitterionic thiol, N,N-dimethyl-cysteamine-carboxybetaine (CBT), and a fructose probe 4-mercaptophenylboronic acid (4-MPBA). The specifically designed and synthesized CBT not only resists protein fouling effectively, but also has very weak Raman activity compared to 4-MPBA. Thus, the CBT SAM provides a stealth surface modification to SERS-active substrates. The surface compositions of mixed SAMs were investigated using X-ray photoelectron spectroscopy (XPS) and SERS, and their nonfouling properties were studied with a surface plasmon resonance (SPR) biosensor. The mixed SAM with a surface composition of 94% CBT demonstrated a very low bovine serum albumin (BSA) adsorption (∼3 ng/cm(2)), and moreover, only the 4-MPBA signal appeared in the SERS spectrum. With the use of this surface-modified SERS-active substrate, quantification of fructose over clinically relevant concentrations (0.01-1 mM) was achieved. Partial least-squares regression (PLS) analysis showed that the detection sensitivity and accuracy were maintained for the measurements in 1 mg/mL BSA solutions. This stealth surface modification strategy provides a novel route to introduce nonfouling property to SERS-active substrates for SERS biosensing in complex media.

  14. Accurate detection of Neisseria gonorrhoeae ciprofloxacin susceptibility directly from genital and extragenital clinical samples: towards genotype-guided antimicrobial therapy

    PubMed Central

    Pond, Marcus J.; Hall, Catherine L.; Miari, Victoria F.; Cole, Michelle; Laing, Ken G.; Jagatia, Heena; Harding-Esch, Emma; Monahan, Irene M.; Planche, Timothy; Hinds, Jason; Ison, Catherine A.; Chisholm, Stephanie; Butcher, Philip D.; Sadiq, Syed Tariq

    2016-01-01

    Introduction Increasing use of nucleic acid amplification tests (NAATs) as the primary means of diagnosing gonococcal infection has resulted in diminished availability of Neisseria gonorrhoeae antimicrobial susceptibility data. We conducted a prospective diagnostic assessment of a real-time PCR assay (NGSNP) enabling direct detection of gonococcal ciprofloxacin susceptibility from a range of clinical sample types. Methods NGSNP, designed to discriminate an SNP associated with ciprofloxacin resistance within the N. gonorrhoeae genome, was validated using a characterized panel of geographically diverse isolates (n = 90) and evaluated to predict ciprofloxacin susceptibility directly on N. gonorrhoeae-positive NAAT lysates derived from genital (n = 174) and non-genital (n = 116) samples (n = 290), from 222 culture-confirmed clinical episodes of gonococcal infection. Results NGSNP correctly genotyped all phenotypically susceptible (n = 49) and resistant (n = 41) panel isolates. Ciprofloxacin-resistant N. gonorrhoeae was responsible for infection in 29.7% (n = 66) of clinical episodes evaluated. Compared with phenotypic susceptibility testing, NGSNP demonstrated sensitivity and specificity of 95.8% (95% CI 91.5%–98.3%) and 100% (95% CI 94.7%–100%), respectively, for detecting ciprofloxacin-susceptible N. gonorrhoeae, with a positive predictive value of 100% (95% CI 97.7%–100%). Applied to urogenital (n = 164), rectal (n = 40) and pharyngeal samples alone (n = 30), positive predictive values were 100% (95% CI 96.8%–100%), 100% (95% CI 87.2%–100%) and 100% (95% CI 82.4%–100%), respectively. Conclusions Genotypic prediction of N. gonorrhoeae ciprofloxacin susceptibility directly from clinical samples was highly accurate and, in the absence of culture, will facilitate use of tailored therapy for gonococcal infection, sparing use of current empirical treatment regimens and enhancing acquisition of susceptibility data for

  15. A finite rate of innovation algorithm for fast and accurate spike detection from two-photon calcium imaging

    PubMed Central

    Oñativia, Jon; Schultz, Simon R; Dragotti, Pier Luigi

    2014-01-01

    Objective Inferring the times of sequences of action potentials (APs) (spike trains) from neurophysiological data is a key problem in computational neuroscience. The detection of APs from two-photon imaging of calcium signals offers certain advantages over traditional electrophysiological approaches, as up to thousands of spatially and immunohistochemically defined neurons can be recorded simultaneously. However, due to noise, dye buffering and the limited sampling rates in common microscopy configurations, accurate detection of APs from calcium time series has proved to be a difficult problem. Approach Here we introduce a novel approach to the problem making use of finite rate of innovation (FRI) theory (Vetterli et al 2002 IEEE Trans. Signal Process. 50 1417–28). For calcium transients well fit by a single exponential, the problem is reduced to reconstructing a stream of decaying exponentials. Signals made of a combination of exponentially decaying functions with different onset times are a subclass of FRI signals, for which much theory has recently been developed by the signal processing community. Main results We demonstrate for the first time the use of FRI theory to retrieve the timing of APs from calcium transient time series. The final algorithm is fast, non-iterative and parallelizable. Spike inference can be performed in real-time for a population of neurons and does not require any training phase or learning to initialize parameters. Significance The algorithm has been tested with both real data (obtained by simultaneous electrophysiology and multiphoton imaging of calcium signals in cerebellar Purkinje cell dendrites), and surrogate data, and outperforms several recently proposed methods for spike train inference from calcium imaging data. PMID:23860257

  16. RNA-Based Detection Does not Accurately Enumerate Living Escherichia coli O157:H7 Cells on Plants

    PubMed Central

    Ju, Wenting; Moyne, Anne-Laure; Marco, Maria L.

    2016-01-01

    The capacity to distinguish between living and dead cells is an important, but often unrealized, attribute of rapid detection methods for foodborne pathogens. In this study, the numbers of enterohemorrhagic Escherichia coli O157:H7 after inoculation onto Romaine lettuce plants and on plastic (abiotic) surfaces were measured over time by culturing, and quantitative PCR (qPCR), propidium monoazide (PMA)-qPCR, and reverse transcriptase (RT)-qPCR targeting E. coli O157:H7 gapA, rfbE, eae, and lpfA genes and gene transcripts. On Romaine lettuce plants incubated at low relative humidity, E. coli O157:H7 cell numbers declined 107-fold within 96 h according to culture-based assessments. In contrast, there were no reductions in E. coli levels according to qPCR and only 100- and 1000-fold lower numbers per leaf by RT-qPCR and PMA-qPCR, respectively. Similar results were obtained upon exposure of E. coli O157:H7 to desiccation conditions on a sterile plastic surface. Subsequent investigation of mixtures of living and dead E. coli O157:H7 cells strongly indicated that PMA-qPCR detection was subject to false-positive enumerations of viable targets when in the presence of 100-fold higher numbers of dead cells. RT-qPCR measurements of killed E. coli O157:H7 as well as for RNaseA-treated E. coli RNA confirmed that transcripts from dead cells and highly degraded RNA were also amplified by RT-qPCR. These findings show that neither PMA-qPCR nor RT-qPCR provide accurate estimates of bacterial viability in environments where growth and survival is limited. PMID:26955370

  17. RNA-Based Detection Does not Accurately Enumerate Living Escherichia coli O157:H7 Cells on Plants.

    PubMed

    Ju, Wenting; Moyne, Anne-Laure; Marco, Maria L

    2016-01-01

    The capacity to distinguish between living and dead cells is an important, but often unrealized, attribute of rapid detection methods for foodborne pathogens. In this study, the numbers of enterohemorrhagic Escherichia coli O157:H7 after inoculation onto Romaine lettuce plants and on plastic (abiotic) surfaces were measured over time by culturing, and quantitative PCR (qPCR), propidium monoazide (PMA)-qPCR, and reverse transcriptase (RT)-qPCR targeting E. coli O157:H7 gapA, rfbE, eae, and lpfA genes and gene transcripts. On Romaine lettuce plants incubated at low relative humidity, E. coli O157:H7 cell numbers declined 10(7)-fold within 96 h according to culture-based assessments. In contrast, there were no reductions in E. coli levels according to qPCR and only 100- and 1000-fold lower numbers per leaf by RT-qPCR and PMA-qPCR, respectively. Similar results were obtained upon exposure of E. coli O157:H7 to desiccation conditions on a sterile plastic surface. Subsequent investigation of mixtures of living and dead E. coli O157:H7 cells strongly indicated that PMA-qPCR detection was subject to false-positive enumerations of viable targets when in the presence of 100-fold higher numbers of dead cells. RT-qPCR measurements of killed E. coli O157:H7 as well as for RNaseA-treated E. coli RNA confirmed that transcripts from dead cells and highly degraded RNA were also amplified by RT-qPCR. These findings show that neither PMA-qPCR nor RT-qPCR provide accurate estimates of bacterial viability in environments where growth and survival is limited. PMID:26955370

  18. Census cities experiment in urban change detection

    NASA Technical Reports Server (NTRS)

    Wray, J. R. (Principal Investigator)

    1973-01-01

    The author has identified the following significant results. Work continues on mapping of 1970 urban land use from 1970 census contemporaneous aircraft photography. In addition, change detection analysis from 1972 aircraft photography is underway for several urban test sites. Land use maps, mosaics, and census overlays for the two largest urban test sites are nearing publication readiness. Preliminary examinations of ERTS-1 imagery of San Francisco Bay have been conducted which show that tracts of land of more than 10 acres in size which are undergoing development in an urban setting can be identified. In addition, each spectral band is being evaluated as to its utility for urban analyses. It has been found that MSS infrared band 7 helps to differentiate intra-urban land use details not found in other MSS bands or in the RBV coverage of the same scene. Good quality false CIR composites have been generated from 9 x 9 inch positive MSS bands using the Diazo process.

  19. Aptamer-conjugated live human immune cell based biosensors for the accurate detection of C-reactive protein

    NASA Astrophysics Data System (ADS)

    Hwang, Jangsun; Seo, Youngmin; Jo, Yeonho; Son, Jaewoo; Choi, Jonghoon

    2016-10-01

    C-reactive protein (CRP) is a pentameric protein that is present in the bloodstream during inflammatory events, e.g., liver failure, leukemia, and/or bacterial infection. The level of CRP indicates the progress and prognosis of certain diseases; it is therefore necessary to measure CRP levels in the blood accurately. The normal concentration of CRP is reported to be 1–3 mg/L. Inflammatory events increase the level of CRP by up to 500 times; accordingly, CRP is a biomarker of acute inflammatory disease. In this study, we demonstrated the preparation of DNA aptamer-conjugated peripheral blood mononuclear cells (Apt-PBMCs) that specifically capture human CRP. Live PBMCs functionalized with aptamers could detect different levels of human CRP by producing immune complexes with reporter antibody. The binding behavior of Apt-PBMCs toward highly concentrated CRP sites was also investigated. The immune responses of Apt-PBMCs were evaluated by measuring TNF-alpha secretion after stimulating the PBMCs with lipopolysaccharides. In summary, engineered Apt-PBMCs have potential applications as live cell based biosensors and for in vitro tracing of CRP secretion sites.

  20. Aptamer-conjugated live human immune cell based biosensors for the accurate detection of C-reactive protein

    PubMed Central

    Hwang, Jangsun; Seo, Youngmin; Jo, Yeonho; Son, Jaewoo; Choi, Jonghoon

    2016-01-01

    C-reactive protein (CRP) is a pentameric protein that is present in the bloodstream during inflammatory events, e.g., liver failure, leukemia, and/or bacterial infection. The level of CRP indicates the progress and prognosis of certain diseases; it is therefore necessary to measure CRP levels in the blood accurately. The normal concentration of CRP is reported to be 1–3 mg/L. Inflammatory events increase the level of CRP by up to 500 times; accordingly, CRP is a biomarker of acute inflammatory disease. In this study, we demonstrated the preparation of DNA aptamer-conjugated peripheral blood mononuclear cells (Apt-PBMCs) that specifically capture human CRP. Live PBMCs functionalized with aptamers could detect different levels of human CRP by producing immune complexes with reporter antibody. The binding behavior of Apt-PBMCs toward highly concentrated CRP sites was also investigated. The immune responses of Apt-PBMCs were evaluated by measuring TNF-alpha secretion after stimulating the PBMCs with lipopolysaccharides. In summary, engineered Apt-PBMCs have potential applications as live cell based biosensors and for in vitro tracing of CRP secretion sites. PMID:27708384

  1. Water quality change detection: multivariate algorithms

    NASA Astrophysics Data System (ADS)

    Klise, Katherine A.; McKenna, Sean A.

    2006-05-01

    In light of growing concern over the safety and security of our nation's drinking water, increased attention has been focused on advanced monitoring of water distribution systems. The key to these advanced monitoring systems lies in the combination of real time data and robust statistical analysis. Currently available data streams from sensors provide near real time information on water quality. Combining these data streams with change detection algorithms, this project aims to develop automated monitoring techniques that will classify real time data and denote anomalous water types. Here, water quality data in 1 hour increments over 3000 hours at 4 locations are used to test multivariate algorithms to detect anomalous water quality events. The algorithms use all available water quality sensors to measure deviation from expected water quality. Simulated anomalous water quality events are added to the measured data to test three approaches to measure this deviation. These approaches include multivariate distance measures to 1) the previous observation, 2) the closest observation in multivariate space, and 3) the closest cluster of previous water quality observations. Clusters are established using kmeans classification. Each approach uses a moving window of previous water quality measurements to classify the current measurement as normal or anomalous. Receiver Operating Characteristic (ROC) curves test the ability of each approach to discriminate between normal and anomalous water quality using a variety of thresholds and simulated anomalous events. These analyses result in a better understanding of the deviation from normal water quality that is necessary to sound an alarm.

  2. Detecting Thermohaline Circulation Changes from Ocean properties

    NASA Astrophysics Data System (ADS)

    Hu, A.; Meehl, G. A.; Han, W.

    2003-12-01

    height gradient (SHG) between 30oS and 60oN in Atlantic. In HOS and CON, it shows a higher SSS contrast related to a stronger THC, but opposite in TRC. However, a colder NP (warmer NA) is related to a stronger THC for both forced runs. The SHG in Atlantic gives the most consistent result among these 3 runs, however, the linear regression shows a 17 Sv change in THC vs a change of one cm/deg-lat in SHG for CON and HOS, but a number increased to 29 for TRC. EOF analyses of the global SST indicate that the first EOF in CON, explaining 14% of the total variance, is a ENSO related pattern with a 2.6-year frequency. In the forced runs, this pattern becomes the second EOF with a frequency of 3.3- to 4.5-year, explaining 11% and 3% of the total variance for HOS and TRC, respectively. The first EOFs are a general cooling in Northern Hemisphere and warming in Southern Hemisphere in HOS (explaining 12% of the variance) and a global warming in TRC (explaining 70% of the variance). The general conclusion is that the proposed mechanisms used to detecting the THC strength are held for past and current climate condition, but not perfectly held for the future (at least in NCAR's CCSM2.0). The increase in atmospheric CO2 level seems changed the behavior of the THC, and causes a breakdown of many teleconnections between THC and others.

  3. Accurate Analysis of the Change in Volume, Location, and Shape of Metastatic Cervical Lymph Nodes During Radiotherapy

    SciTech Connect

    Takao, Seishin; Tadano, Shigeru; Taguchi, Hiroshi; Yasuda, Koichi; Onimaru, Rikiya; Ishikawa, Masayori; Bengua, Gerard; Suzuki, Ryusuke; Shirato, Hiroki

    2011-11-01

    Purpose: To establish a method for the accurate acquisition and analysis of the variations in tumor volume, location, and three-dimensional (3D) shape of tumors during radiotherapy in the era of image-guided radiotherapy. Methods and Materials: Finite element models of lymph nodes were developed based on computed tomography (CT) images taken before the start of treatment and every week during the treatment period. A surface geometry map with a volumetric scale was adopted and used for the analysis. Six metastatic cervical lymph nodes, 3.5 to 55.1 cm{sup 3} before treatment, in 6 patients with head and neck carcinomas were analyzed in this study. Three fiducial markers implanted in mouthpieces were used for the fusion of CT images. Changes in the location of the lymph nodes were measured on the basis of these fiducial markers. Results: The surface geometry maps showed convex regions in red and concave regions in blue to ensure that the characteristics of the 3D tumor geometries are simply understood visually. After the irradiation of 66 to 70 Gy in 2 Gy daily doses, the patterns of the colors had not changed significantly, and the maps before and during treatment were strongly correlated (average correlation coefficient was 0.808), suggesting that the tumors shrank uniformly, maintaining the original characteristics of the shapes in all 6 patients. The movement of the gravitational center of the lymph nodes during the treatment period was everywhere less than {+-}5 mm except in 1 patient, in whom the change reached nearly 10 mm. Conclusions: The surface geometry map was useful for an accurate evaluation of the changes in volume and 3D shapes of metastatic lymph nodes. The fusion of the initial and follow-up CT images based on fiducial markers enabled an analysis of changes in the location of the targets. Metastatic cervical lymph nodes in patients were suggested to decrease in size without significant changes in the 3D shape during radiotherapy. The movements of the

  4. Monitoring land-cover changes in the Terminos Lagoon region, Mexico: A comparison of change detection techniques

    SciTech Connect

    Mas, J.F.

    1997-06-01

    Six change detection procedures were tested using Landsat MSS images for detecting areas of changes in the region of the Terminos Lagoon, a coastal zone of the State of Campeche, Mexico. The change detection techniques considered were image differencing, vegetative index differencing, selective principal components analysis, direct multidate unsupervised classification, post-classification change differencing and a combination of image enhancement and post-classification comparison. Accuracy of the results obtained by each technique was evaluated by comparison with aerial photographs through Kappa coefficient calculation. Post-classification comparison was found to be the most accurate procedure and presents the advantage to indicate the nature of the changes. Poor performances obtained by image enhancement procedures were attributed to the spectral variation due to differences of soil moisture and of vegetation phenology between both scenes. Methods based on classification were found less sensitive at these spectral variations.

  5. Attribute and topology based change detection in a constellation of previously detected objects

    DOEpatents

    Paglieroni, David W.; Beer, Reginald N.

    2016-01-19

    A system that applies attribute and topology based change detection to networks of objects that were detected on previous scans of a structure, roadway, or area of interest. The attributes capture properties or characteristics of the previously detected objects, such as location, time of detection, size, elongation, orientation, etc. The topology of the network of previously detected objects is maintained in a constellation database that stores attributes of previously detected objects and implicitly captures the geometrical structure of the network. A change detection system detects change by comparing the attributes and topology of new objects detected on the latest scan to the constellation database of previously detected objects.

  6. Ensembles of detectors for online detection of transient changes

    NASA Astrophysics Data System (ADS)

    Artemov, Alexey; Burnaev, Evgeny

    2015-12-01

    Classical change-point detection procedures assume a change-point model to be known and a change consisting in establishing a new observations regime, i.e. the change lasts infinitely long. These modeling assumptions contradicts applied problems statements. Therefore, even theoretically optimal statistics in practice very often fail when detecting transient changes online. In this work in order to overcome limitations of classical change-point detection procedures we consider approaches to constructing ensembles of change-point detectors, i.e. algorithms that use many detectors to reliably identify a change-point. We propose a learning paradigm and specific implementations of ensembles for change detection of short-term (transient) changes in observed time series. We demonstrate by means of numerical experiments that the performance of an ensemble is superior to that of the conventional change-point detection procedures.

  7. Accurate detection of spatio-temporal variability of plant phenology by using satellite-observed daily green-red vegetation index (GRVI) in Japan

    NASA Astrophysics Data System (ADS)

    Nagai, S.; Saitoh, T. M.; Nasahara, K. N.; Inoue, T.; Suzuki, R.

    2015-12-01

    To evaluate the spatio-temporal variability of biodiversity and ecosystem functioning and service in deciduous forests, accurate detection of the timing of plant phenology such as leaf-flushing, -coloring, and -falling is important from plot to continental scales. Here, (1) we detected the spatio-temporal variability in the timing of start (SGS) and end of growing season (EGS) in Japan from 2001 to 2014 by analyzing Terra and Aqua/MODIS satellite-observed daily green-red vegetation index (GRVI) with a 500-m spatial resolution. (2) We examined the characteristics of timing of SGS and EGS in deciduous forests along vertical (altitude) and horizontal (latitude) gradients and their sensitivity to air temperature. (3) We evaluated the relationship between the spatial distribution of leaf-coloring phenology derived from Landsat-8/OLI satellite-observed GRVI with a 30-m spatial resolution on 23 November 2014 and leaf-coloring information published on web sites in Kanagawa Prefecture, Japan. We found that (1) changes along the vertical and horizontal gradients in the timing of SGS tended to be larger than those of EGS; (2) the sensitivity of the timing of SGS to air temperature was much more than that of EGS; and (3) leaf-coloring information published on web sites covering multiple points was useful for verification of leaf-coloring phenology derived from satellite-observed GRVI in relation to the altitude gradient in mountainous regions.

  8. Color changing photonic crystals detect blast exposure.

    PubMed

    Cullen, D Kacy; Xu, Yongan; Reneer, Dexter V; Browne, Kevin D; Geddes, James W; Yang, Shu; Smith, Douglas H

    2011-01-01

    Blast-induced traumatic brain injury (bTBI) is the "signature wound" of the current wars in Iraq and Afghanistan. However, with no objective information of relative blast exposure, warfighters with bTBI may not receive appropriate medical care and are at risk of being returned to the battlefield. Accordingly, we have created a colorimetric blast injury dosimeter (BID) that exploits material failure of photonic crystals to detect blast exposure. Appearing like a colored sticker, the BID is fabricated in photosensitive polymers via multi-beam interference lithography. Although very stable in the presence of heat, cold or physical impact, sculpted micro- and nano-structures of the BID are physically altered in a precise manner by blast exposure, resulting in color changes that correspond with blast intensity. This approach offers a lightweight, power-free sensor that can be readily interpreted by the naked eye. Importantly, with future refinement this technology may be deployed to identify soldiers exposed to blast at levels suggested to be supra-threshold for non-impact blast-induced mild TBI.

  9. Color changing photonic crystals detect blast exposure

    PubMed Central

    Cullen, D. Kacy; Xu, Yongan; Reneer, Dexter V.; Browne, Kevin D.; Geddes, James W.; Yang, Shu; Smith, Douglas H.

    2010-01-01

    Blast-induced traumatic brain injury (bTBI) is the “signature wound” of the current wars in Iraq and Afghanistan. However, with no objective information of relative blast exposure, warfighters with bTBI may not receive appropriate medical care and are at risk of being returned to the battlefield. Accordingly, we have created a colorimetric blast injury dosimeter (BID) that exploits material failure of photonic crystals to detect blast exposure. Appearing like a colored sticker, the BID is fabricated in photosensitive polymers via multi-beam interference lithography. Although very stable in the presence of heat, cold or physical impact, sculpted micro- and nano-structures of the BID are physically altered in a precise manner by blast exposure, resulting in color changes that correspond with blast intensity. This approach offers a lightweight, power-free sensor that can be readily interpreted by the naked eye. Importantly, with future refinement this technology may be deployed to identify soldiers exposed to blast at levels suggested to be supra-threshold for non-impact blast-induced mild TBI. PMID:21040795

  10. Detecting land-use/land-cover change in rural-urban fringe areas using extended change-vector analysis

    NASA Astrophysics Data System (ADS)

    He, Chunyang; Wei, Anni; Shi, Peijun; Zhang, Qiaofeng; Zhao, Yuanyuan

    2011-08-01

    Detecting land-use/land-cover (LULC) changes in rural-urban fringe areas (RUFAs) timely and accurately using satellite imagery is essential for land-use planning and management in China. Although traditional spectral-based change-vector analysis (CVA) can effectively detect LULC change in many cases, it encounters difficulties in RUFAs because of deficiencies in the spectral information of satellite images. To detect LULC changes in RUFAs effectively, this paper proposes an extended CVA approach that incorporates textural change information into the traditional spectral-based CVA. The extended CVA was applied to three different pilot RUFAs in China with different remotely sensed data, including Landsat Thematic Mapper (TM), China-Brazil Earth Resources Satellite (CBERS) and Advanced Land Observing Satellite (ALOS) images. The results demonstrated the improvement of the extended CVA compared to the traditional spectral-based CVA with the overall accuracy increased between 4.66% and 8.00% and the kappa coefficient increased between 0.10 and 0.15, respectively. The advantage of the extended CVA lies in its integration of both spectral and textural change information to detect LULC changes, allowing for effective discrimination of LULC changes that are spectrally similar but texturally different in RUFAs. The extended CVA has great potential to be widely used for LULC-change detection in RUFAs, which are often heterogeneous and fragmental in nature, with rich textural information.

  11. Functional DNA quantification guides accurate next-generation sequencing mutation detection in formalin-fixed, paraffin-embedded tumor biopsies

    PubMed Central

    2013-01-01

    The formalin-fixed, paraffin-embedded (FFPE) biopsy is a challenging sample for molecular assays such as targeted next-generation sequencing (NGS). We compared three methods for FFPE DNA quantification, including a novel PCR assay (‘QFI-PCR’) that measures the absolute copy number of amplifiable DNA, across 165 residual clinical specimens. The results reveal the limitations of commonly used approaches, and demonstrate the value of an integrated workflow using QFI-PCR to improve the accuracy of NGS mutation detection and guide changes in input that can rescue low quality FFPE DNA. These findings address a growing need for improved quality measures in NGS-based patient testing. PMID:24001039

  12. Land use change detection based on multi-date imagery from different satellite sensor systems

    NASA Technical Reports Server (NTRS)

    Stow, Douglas A.; Collins, Doretta; Mckinsey, David

    1990-01-01

    An empirical study is conducted to assess the accuracy of land use change detection using satellite image data acquired ten years apart by sensors with differing spatial resolutions. The primary goals of the investigation were to (1) compare standard change detection methods applied to image data of varying spatial resolution, (2) assess whether to transform the raster grid of the higher resolution image data to that of the lower resolution raster grid or vice versa in the registration process, (3) determine if Landsat/Thermatic Mapper or SPOT/High Resolution Visible multispectral data provide more accurate detection of land use changes when registered to historical Landsat/MSS data. It is concluded that image ratioing of multisensor, multidate satellite data produced higher change detection accuracies than did principal components analysis, and that it is useful as a land use change enhancement method.

  13. Eye Movements and Display Change Detection during Reading

    ERIC Educational Resources Information Center

    Slattery, Timothy J.; Angele, Bernhard; Rayner, Keith

    2011-01-01

    In the boundary change paradigm (Rayner, 1975), when a reader's eyes cross an invisible boundary location, a preview word is replaced by a target word. Readers are generally unaware of such changes due to saccadic suppression. However, some readers detect changes on a few trials and a small percentage of them detect many changes. Two experiments…

  14. Toward optimizing patient-specific IMRT QA techniques in the accurate detection of dosimetrically acceptable and unacceptable patient plans

    SciTech Connect

    McKenzie, Elizabeth M.; Balter, Peter A.; Stingo, Francesco C.; Jones, Jimmy; Followill, David S.; Kry, Stephen F.

    2014-12-15

    was no significant difference in the performance of any device between gamma criteria of 2%/2 mm, 3%/3 mm, and 5%/3 mm. Finally, optimal cutoffs (e.g., percent of pixels passing gamma) were determined for each device and while clinical practice commonly uses a threshold of 90% of pixels passing for most cases, these results showed variability in the optimal cutoff among devices. Conclusions: IMRT QA devices have differences in their ability to accurately detect dosimetrically acceptable and unacceptable plans. Field-by-field analysis with a MapCheck device and use of the MapCheck with a MapPhan phantom while delivering at planned rotational gantry angles resulted in a significantly poorer ability to accurately sort acceptable and unacceptable plans compared with the other techniques examined. Patient-specific IMRT QA techniques in general should be thoroughly evaluated for their ability to correctly differentiate acceptable and unacceptable plans. Additionally, optimal agreement thresholds should be identified and used as common clinical thresholds typically worked very poorly to identify unacceptable plans.

  15. Evaluation of change detection techniques for monitoring coastal zone environments

    NASA Technical Reports Server (NTRS)

    Weismiller, R. A.; Kristof, S. J.; Scholz, D. K.; Anuta, P. E.; Momin, S. M.

    1977-01-01

    Development of satisfactory techniques for detecting change in coastal zone environments is required before operational monitoring procedures can be established. In an effort to meet this need a study was directed toward developing and evaluating different types of change detection techniques, based upon computer aided analysis of LANDSAT multispectral scanner (MSS) data, to monitor these environments. The Matagorda Bay estuarine system along the Texas coast was selected as the study area. Four change detection techniques were designed and implemented for evaluation: (1) post classification comparison change detection, (2) delta data change detection, (3) spectral/temporal change classification, and (4) layered spectral/temporal change classification. Each of the four techniques was used to analyze a LANDSAT MSS temporal data set to detect areas of change of the Matagorda Bay region.

  16. Eye movements and display change detection during reading.

    PubMed

    Slattery, Timothy J; Angele, Bernhard; Rayner, Keith

    2011-12-01

    In the boundary change paradigm (Rayner, 1975), when a reader's eyes cross an invisible boundary location, a preview word is replaced by a target word. Readers are generally unaware of such changes due to saccadic suppression. However, some readers detect changes on a few trials and a small percentage of them detect many changes. Two experiments are reported in which we combined eye movement data with signal detection analyses to investigate display change detection. On each trial, readers had to indicate if they saw a display change in addition to reading for meaning. On half the trials the display change occurred during the saccade (immediate condition); on the other half, it was slowed by 15-25 ms (delay condition) to increase the likelihood that a change would be detected. Sentences were presented in an alternating case fashion allowing us to investigate the influence of both letter identity and case. In the immediate condition, change detection was higher when letters changed than when case changed corroborating findings that word processing utilizes abstract (case independent) letter identities. However, in the delay condition (where d' was much higher than the immediate condition), detection was equal for letter and case changes. The results of both experiments indicate that sensitivity to display changes was related to how close the eyes were to the invalid preview on the fixation prior to the display change, as well as the timing of the completion of this change relative to the start of the post-change fixation.

  17. Neural network for change detection of remotely sensed imagery

    NASA Astrophysics Data System (ADS)

    Chen, C. F.; Chen, Kun S.; Chang, J. S.

    1995-11-01

    The use of a neural network for determining the change of landcover/land-use with remotely sensed data is proposed. In this study, a single image contains both spectral and temporal information is created from a multidate satellite imagery. The proposed change detection method can be divided into two main steps: training data selection and change detection. At the training step, the training set, basically consists of the classes of no-change and possible change data, is obtained from the composited image. Then the training data is used to input the neural network and obtain the network's weights. At the change detection step, the network's weights is employed to detect the change and no-change classes in the combined image. The proposed method is tested using a multidate SPOT imageries and a satisfied change pattern detection is obtained.

  18. High-precision topography measurement through accurate in-focus plane detection with hybrid digital holographic microscope and white light interferometer module.

    PubMed

    Liżewski, Kamil; Tomczewski, Sławomir; Kozacki, Tomasz; Kostencka, Julianna

    2014-04-10

    High-precision topography measurement of micro-objects using interferometric and holographic techniques can be realized provided that the in-focus plane of an imaging system is very accurately determined. Therefore, in this paper we propose an accurate technique for in-focus plane determination, which is based on coherent and incoherent light. The proposed method consists of two major steps. First, a calibration of the imaging system with an amplitude object is performed with a common autofocusing method using coherent illumination, which allows for accurate localization of the in-focus plane position. In the second step, the position of the detected in-focus plane with respect to the imaging system is measured with white light interferometry. The obtained distance is used to accurately adjust a sample with the precision required for the measurement. The experimental validation of the proposed method is given for measurement of high-numerical-aperture microlenses with subwavelength accuracy.

  19. Detecting holocene changes in thermohaline circulation.

    PubMed

    Keigwin, L D; Boyle, E A

    2000-02-15

    Throughout the last glacial cycle, reorganizations of deep ocean water masses were coincident with rapid millennial-scale changes in climate. Climate changes have been less severe during the present interglacial, but evidence for concurrent deep ocean circulation change is ambiguous. PMID:10677463

  20. Detecting Holocene changes in thermohaline circulation

    PubMed Central

    Keigwin, L. D.; Boyle, E. A.

    2000-01-01

    Throughout the last glacial cycle, reorganizations of deep ocean water masses were coincident with rapid millennial-scale changes in climate. Climate changes have been less severe during the present interglacial, but evidence for concurrent deep ocean circulation change is ambiguous. PMID:10677463

  1. Detecting holocene changes in thermohaline circulation.

    PubMed

    Keigwin, L D; Boyle, E A

    2000-02-15

    Throughout the last glacial cycle, reorganizations of deep ocean water masses were coincident with rapid millennial-scale changes in climate. Climate changes have been less severe during the present interglacial, but evidence for concurrent deep ocean circulation change is ambiguous.

  2. Change Detection in Naturalistic Pictures among Children with Autism

    ERIC Educational Resources Information Center

    Burack, Jacob A.; Joseph, Shari; Russo, Natalie; Shore, David I.; Porporino, Mafalda; Enns, James T.

    2009-01-01

    Persons with autism often show strong reactions to changes in the environment, suggesting that they may detect changes more efficiently than typically developing (TD) persons. However, Fletcher-Watson et al. (Br J Psychol 97:537-554, 2006) reported no differences between adults with autism and TD adults with a change-detection task. In this study,…

  3. Change detection on a hunch: pre-attentive vision allows "sensing" of unique feature changes.

    PubMed

    Ball, Felix; Busch, Niko A

    2015-11-01

    Studies on change detection and change blindness have investigated the nature of visual representations by testing the conditions under which observers are able to detect when an object in a complex scene changes from one moment to the next. Several authors have proposed that change detection can occur without identification of the changing object, but the perceptual processes underlying this phenomenon are currently unknown. We hypothesized that change detection without localization or identification occurs when the change happens outside the focus of attention. Such changes would usually go entirely unnoticed, unless the change brings about a modification of one of the feature maps representing the scene. Thus, the appearance or disappearance of a unique feature might be registered even in the absence of focused attention and without feature binding, allowing for change detection, but not localization or identification. We tested this hypothesis in three experiments, in which changes either involved colors that were already present elsewhere in the display or entirely unique colors. Observers detected whether any change had occurred and then localized or identified the change. Change detection without localization occurred almost exclusively when changes involved a unique color. Moreover, change detection without localization for unique feature changes was independent of the number of objects in the display and independent of change identification. These findings suggest that pre-attentive registration of a change on a feature map can give rise to a conscious experience even when feature binding has failed: that something has changed without knowing what or where. PMID:26353860

  4. Change detection on a hunch: pre-attentive vision allows "sensing" of unique feature changes.

    PubMed

    Ball, Felix; Busch, Niko A

    2015-11-01

    Studies on change detection and change blindness have investigated the nature of visual representations by testing the conditions under which observers are able to detect when an object in a complex scene changes from one moment to the next. Several authors have proposed that change detection can occur without identification of the changing object, but the perceptual processes underlying this phenomenon are currently unknown. We hypothesized that change detection without localization or identification occurs when the change happens outside the focus of attention. Such changes would usually go entirely unnoticed, unless the change brings about a modification of one of the feature maps representing the scene. Thus, the appearance or disappearance of a unique feature might be registered even in the absence of focused attention and without feature binding, allowing for change detection, but not localization or identification. We tested this hypothesis in three experiments, in which changes either involved colors that were already present elsewhere in the display or entirely unique colors. Observers detected whether any change had occurred and then localized or identified the change. Change detection without localization occurred almost exclusively when changes involved a unique color. Moreover, change detection without localization for unique feature changes was independent of the number of objects in the display and independent of change identification. These findings suggest that pre-attentive registration of a change on a feature map can give rise to a conscious experience even when feature binding has failed: that something has changed without knowing what or where.

  5. Is a pre-change object representation weakened under correct detection of a change?

    PubMed

    Yeh, Yei-Yu; Yang, Cheng-Ta

    2009-03-01

    We investigated whether a pre-change representation is inhibited or weakened under correct change detection. Two arrays of six objects were rapidly presented for change detection in three experiments. After detection, the perceptual identification of degraded stimuli was tested in Experiments 1 and 2. The weakening of a pre-change representation was not observed under correct detection. The repetition priming effect was observed for a pre-change object and the magnitude was equivalent to the effect for a post-change object. Under change blindness, repetition priming for a pre-change representation was observed when detection did not require report of location in Experiment 1 and was not observed when location was required to be reported in Experiment 2. The results of Experiment 3 showed that a pre-change representation was recognized at a higher rate under correct detection than under change blindness, reflecting a stronger rather than a weaker pre-change representation in the former context.

  6. Occupancy change detection system and method

    DOEpatents

    Bruemmer, David J [Idaho Falls, ID; Few, Douglas A [Idaho Falls, ID

    2009-09-01

    A robot platform includes perceptors, locomotors, and a system controller. The system controller executes instructions for producing an occupancy grid map of an environment around the robot, scanning the environment to generate a current obstacle map relative to a current robot position, and converting the current obstacle map to a current occupancy grid map. The instructions also include processing each grid cell in the occupancy grid map. Within the processing of each grid cell, the instructions include comparing each grid cell in the occupancy grid map to a corresponding grid cell in the current occupancy grid map. For grid cells with a difference, the instructions include defining a change vector for each changed grid cell, wherein the change vector includes a direction from the robot to the changed grid cell and a range from the robot to the changed grid cell.

  7. Application of multi-sensor images for detecting land cover change and analysis of urban expansion

    NASA Astrophysics Data System (ADS)

    Deng, Jinsong; Wang, Ke; Deng, Yanhua; Li, Jun

    2005-10-01

    Zhejiang province is playing an increasingly vital role in China's overall economic growth. Concomitant with the dramatic economic development, this region has been undergoing tremendous urban growth on an unprecedented scale and rate. Many urbanization-related problems have been identified, including agricultural land and wetland loss, water pollution and soil erosion. There is an urgent need to detect and monitor the land cover change and analyze the magnitude and pattern, accurately and timely for planning and management. Remote sensing is a powerful tool for monitoring rapid change in the landscape resulting from urban development. However, change detection capabilities are intrinsically limited by the spatial resolution of the digital imagery in urban. The application of multi-sensor data provides the potential to more accurately detect land-cover changes through integration of different features of sensor data. Taking Hangzhou city as case study, this paper presents a method that combines principal component analysis (PCA) of multi-sensor data (SPOT-5 XS and ETM Pan data) and a hybrid classification involving unsupervised and supervised classier to detect and analysis land cover change. The study demonstrates that this method provides a very useful way in monitoring rapid land cover change in urban environment.

  8. Detecting Temporal Change in Watershed Nutrient Yields

    NASA Astrophysics Data System (ADS)

    Wickham, James D.; Wade, Timothy G.; Riitters, Kurt H.

    2008-08-01

    Meta-analyses reveal that nutrient yields tend to be higher for watersheds dominated by anthropogenic uses (e.g., urban, agriculture) and lower for watersheds dominated by natural vegetation. One implication of this pattern is that loss of natural vegetation will produce increases in watershed nutrient yields. Yet, the same meta-analyses also reveal that, absent land-cover change, watershed nutrient yields vary from one year to the next due to many exogenous factors. The interacting effects of land cover and exogenous factors suggest nutrient yields should be treated as distributions, and the effect of land-cover change should be examined by looking for significant changes in the distributions. We compiled nutrient yield distributions from published data. The published data included watersheds with homogeneous land cover that typically reported two or more years of annual nutrient yields for the same watershed. These data were used to construct statistical models, and the models were used to estimate changes in the nutrient yield distributions as a result of land-cover change. Land-cover changes were derived from the National Land Cover Database (NLCD). Total nitrogen (TN) yield distributions increased significantly for 35 of 1550 watersheds and decreased significantly for 51. Total phosphorus (TP) yield distributions increased significantly for 142 watersheds and decreased significantly for 17. The amount of land-cover change required to produce significant shifts in nutrient yield distributions was not constant. Small land-cover changes led to significant shifts in nutrient yield distributions when watersheds were dominated by natural vegetation, whereas much larger land-cover changes were needed to produce significant shifts when watersheds were dominated by urban or agriculture. We discuss our results in the context of the Clean Water Act.

  9. Detecting temporal change in watershed nutrient yields.

    PubMed

    Wickham, James D; Wade, Timothy G; Riitters, Kurt H

    2008-08-01

    Meta-analyses reveal that nutrient yields tend to be higher for watersheds dominated by anthropogenic uses (e.g., urban, agriculture) and lower for watersheds dominated by natural vegetation. One implication of this pattern is that loss of natural vegetation will produce increases in watershed nutrient yields. Yet, the same meta-analyses also reveal that, absent land-cover change, watershed nutrient yields vary from one year to the next due to many exogenous factors. The interacting effects of land cover and exogenous factors suggest nutrient yields should be treated as distributions, and the effect of land-cover change should be examined by looking for significant changes in the distributions. We compiled nutrient yield distributions from published data. The published data included watersheds with homogeneous land cover that typically reported two or more years of annual nutrient yields for the same watershed. These data were used to construct statistical models, and the models were used to estimate changes in the nutrient yield distributions as a result of land-cover change. Land-cover changes were derived from the National Land Cover Database (NLCD). Total nitrogen (TN) yield distributions increased significantly for 35 of 1550 watersheds and decreased significantly for 51. Total phosphorus (TP) yield distributions increased significantly for 142 watersheds and decreased significantly for 17. The amount of land-cover change required to produce significant shifts in nutrient yield distributions was not constant. Small land-cover changes led to significant shifts in nutrient yield distributions when watersheds were dominated by natural vegetation, whereas much larger land-cover changes were needed to produce significant shifts when watersheds were dominated by urban or agriculture. We discuss our results in the context of the Clean Water Act. PMID:18446405

  10. Are skinfold-based models accurate and suitable for assessing changes in body composition in highly trained athletes?

    PubMed

    Silva, Analiza M; Fields, David A; Quitério, Ana L; Sardinha, Luís B

    2009-09-01

    This study was designed to assess the usefulness of skinfold (SKF) equations developed by Jackson and Pollock (JP) and by Evans (Ev) in tracking body composition changes (relative fat mass [%FM], absolute fat mass [FM], and fat-free mass [FFM]) of elite male judo athletes before a competition using a 4-compartment (4C) model as the reference method. A total of 18 male, top-level (age: 22.6 +/- 2.9 yr) athletes were evaluated at baseline (weight: 73.4 +/- 7.9 kg; %FM4C: 7.0 +/- 3.3%; FM4C: 5.1 +/- 2.6 kg; and FFM4C: 68.3 +/- 7.3 kg) and before a competition (weight: 72.7 +/- 7.5 kg; %FM4C: 6.5 +/- 3.4%; FM4C: 4.8 +/- 2.6 kg; and FFM4C: 67.9 +/- 7.1 kg). Measures of body density assessed by air displacement plethysmography, bone mineral content by dual energy X-ray absorptiometry, and total-body water by bioelectrical impedance spectroscopy were used to estimate 4C model %FM, FM, and FFM. Seven SKF site models using both JP and Ev were used to estimate %FM, FM, and FFM along with the simplified Ev3SKF site. Changes in %FM, FM, and FFM were not significantly different from the 4C model. The regression model for the SKF in question and the reference method did not differ from the line of identity in estimating changes in %FM, FM, and FFM. The limits of agreement were similar, ranging from -3.4 to 3.6 for %FM, -2.7 to 2.5 kg for FM, and -2.5 to 2.7 kg for FFM. Considering the similar performance of both 7SKF- and 3SKF-based equations compared with the criterion method, these data indicate that either the 7- or 3-site SFK models are not valid to detect %FM, FM, and FFM changes of highly trained athletes. These results highlighted the inaccuracy of anthropometric models in tracking desired changes in body composition of elite male judo athletes before a competition.

  11. Change Detection Module for New Orleans City of USA Using

    NASA Astrophysics Data System (ADS)

    Singh, Dharmendra

    accuracy. The New Orleans city of USA is taken as study area because this is reported that this city is shrinking. RADARSAT SLC (Single look complex) images acquired from January 2002 to March 2007 were obtained for the study area. Image pairs with perpendicular baselines less than 100 km are chosen. Selection of suitable image pairs is crucial since baseline distance between them affects the altitude ambiguity in resultant change detection map. Coherence is computed for the image pairs. If the coherence is greater than 0.25, such image pairs are considered for further analysis. Three pass differential InSAR is used for the analysis of change detection. Images 1 and 2 of the study area with lesser temporal span (minimum of 24 day interval) is chosen to make a digital elevation model and then images 1 and 3 of the same area with one year of temporal span is chosen to make an interferogram. The topographic phase estimated with images 1 and 2 is then subtracted to make a differential interferogram showing change from image 2 to 3. Image pairs with approximately one month temporal span, are considered for generating interferogram. Changes occurred in every one year is measured by subtracting topographic phase of the year corresponding to master image, from interferogram. From the change detection map obtained from both methods show that areas of larger changes are identified near Lake Borgne, and in the boundaries of Mississippi river. Lake Borgne is reported to be identified as an area of major land subsidence as found by other studies also. On comparing our result with this interferometric study, it is found that both are showing some common regions with high changes near water bodies. Surface deformation can be monitored quantitatively in the scale of mm with the help of temporal analysis of D-InSAR.

  12. A Dual-Process Account of Auditory Change Detection

    ERIC Educational Resources Information Center

    McAnally, Ken I.; Martin, Russell L.; Eramudugolla, Ranmalee; Stuart, Geoffrey W.; Irvine, Dexter R. F.; Mattingley, Jason B.

    2010-01-01

    Listeners can be "deaf" to a substantial change in a scene comprising multiple auditory objects unless their attention has been directed to the changed object. It is unclear whether auditory change detection relies on identification of the objects in pre- and post-change scenes. We compared the rates at which listeners correctly identify changed…

  13. Change detection for objects on surfaces slanted in depth.

    PubMed

    Ozkan, Kerem; Braunstein, Myron L

    2010-09-15

    Change detection for objects associated with a surface extended in depth might be more difficult than for a frontal surface if it is easier to shift attention within a frontal surface. On the other hand, previous research has shown that ground surfaces have a special role in organizing the 3-D layout of objects shown against scene backgrounds. In the current study, we examined whether a frontal background or a ground surface background would result in superior change detection performance using a change detection flicker paradigm. In the first experiment, we considered whether background slant affects change detection performance. In Experiment 2, we examined the effect of height in the image on change detection performance. In Experiment 3, we examined change detection performance on slanted ceiling surfaces. The results of these experiments indicate that change detection is more efficient on near-ground planes than on surfaces at intermediate slants or ceiling surfaces. This suggests that any superiority of frontal plane backgrounds in a change detection task may be equivalent to the superiority of a near-ground plane in organizing a scene, with the lowest level of performance occurring for surfaces that are not frontal but further from a ground surface orientation.

  14. Detection of ocean color changes from high altitudes

    NASA Technical Reports Server (NTRS)

    Hovis, W. A.; Forman, M. L.; Blaine, L. R.

    1973-01-01

    The detection of ocean color changes, thought to be due to chlorophyll concentrations and gelbstoffe variations, is attempted from high altitude (11.3km) and low altitude (0.3km). The atmospheric back scattering is shown to reduce contrast, but not sufficiently to obscure color change detection at high altitudes.

  15. An Adaptive-Duration Version of the PVT Accurately Tracks Changes in Psychomotor Vigilance Induced by Sleep Restriction

    PubMed Central

    Basner, Mathias; Dinges, David F.

    2012-01-01

    96.8% (range 91.6%-99.9%). Test duration averaged 6.4 minutes (SD 1.7 min), with a minimum of 27 seconds. Conclusions: We developed and validated a highly accurate, sensitive, and specific adaptive-duration version of the 10-minute PVT. Test duration of the adaptive PVT averaged less than 6.5 minutes, with 60 tests (4.3%) terminating after less than 2 minutes, increasing the practicability of the test in operational and clinical settings. The adaptive-duration strategy may be superior to a simple reduction of PVT duration in which the fixed test duration may be too short to identify subjects with moderate impairment (showing deficits only later during the test) but unnecessarily long for those who are either fully alert or severely impaired. Citation: Basner M; Dinges DF. An adaptive-duration version of the PVT accurately tracks changes in psychomotor vigilance induced by sleep restriction. SLEEP 2012;35(2):193-202. PMID:22294809

  16. Change magnitude does not guide attention in an object change detection task.

    PubMed

    Favelle, Simone K; Palmisano, Stephen

    2015-01-01

    Investigations of change detection consistently reveal an effect of change magnitude: changes involving more object parts are detected more easily than those involving fewer parts. Whether large changes improve detection by providing stronger preattentive signals to the change location is subject to debate. We report a cued object change detection experiment that tested this hypothesis while controlling for stimulus familiarity, semantic knowledge, and change type (addition versus deletion). We found strong magnitude effects regardless of whether trials were validly or invalidly cued. The size of the cueing effects, which were exhibited for all the change magnitudes examined, did not decrease with the number of parts changing. These findings provide little support for a preattentive guidance hypothesis and instead support the thesis that change detection requires attention.

  17. Comparing Several Algorithms for Change Detection of Wetland

    NASA Astrophysics Data System (ADS)

    Yan, F.; Zhang, S.; Chang, L.

    2015-12-01

    As "the kidneys of the landscape" and "ecological supermarkets", wetland plays an important role in ecological equilibrium and environmental protection.Therefore, it is of great significance to understand the dynamic changes of the wetland. Nowadays, many index and many methods have been used in dynamic Monitoring of Wetland. However, there are no single method and no single index are adapted to detect dynamic change of wetland all over the world. In this paper, three digital change detection algorithms are applied to 2005 and 2010 Landsat Thematic Mapper (TM) images of a portion of the Northeast China to detect wetland dynamic between the two dates. The change vector analysis method (CVA) uses 6 bands of TM images to detect wetland dynamic. The tassled cap transformation is used to create three change images (change in brightness, greenness, and wetness). A new method--- Comprehensive Change Detection Method (CCDM) is introduced to detect forest dynamic change. The CCDM integrates spectral-based change detection algorithms including a Multi-Index Integrated Change Analysis (MIICA) model and a novel change model called Zone, which extracts change information from two Landsat image pairs. The MIICA model is the core module of the change detection strategy and uses four spectral indices (differenced Normalized Burn Ratio (dNBR), differenced Normalized Difference Vegetation Index (dNDVI), the Change Vector (CV) and a new index called the Relative Change Vector Maximum (RCVMAX)) to obtain the changes that occurred between two image dates. The CCDM also includes a knowledge-based system, which uses critical information on historical and current land cover conditions and trends and the likelihood of land cover change, to combine the changes from MIICA and Zone. Related test proved that CCDM method is simple, easy to operate, widely applicable, and capable of capturing a variety of natural and anthropogenic disturbances potentially associated with land cover changes on

  18. Synthetic circuit for exact adaptation and fold-change detection.

    PubMed

    Kim, Jongmin; Khetarpal, Ishan; Sen, Shaunak; Murray, Richard M

    2014-05-01

    Biological organisms use their sensory systems to detect changes in their environment. The ability of sensory systems to adapt to static inputs allows wide dynamic range as well as sensitivity to input changes including fold-change detection, a response that depends only on fold changes in input, and not on absolute changes. This input scale invariance underlies an important strategy for search that depends solely on the spatial profile of the input. Synthetic efforts to reproduce the architecture and response of cellular circuits provide an important step to foster understanding at the molecular level. We report the bottom-up assembly of biochemical systems that show exact adaptation and fold-change detection. Using a malachite green aptamer as the output, a synthetic transcriptional circuit with the connectivity of an incoherent feed-forward loop motif exhibits pulse generation and exact adaptation. A simple mathematical model was used to assess the amplitude and duration of pulse response as well as the parameter regimes required for fold-change detection. Upon parameter tuning, this synthetic circuit exhibits fold-change detection for four successive rounds of two-fold input changes. The experimental realization of fold-change detection circuit highlights the programmability of transcriptional switches and the ability to obtain predictive dynamical systems in a cell-free environment for technological applications.

  19. Simulation framework for spatio-spectral anomalous change detection

    SciTech Connect

    Theiler, James P; Harvey, Neal R; Porter, Reid B; Wohlberg, Brendt E

    2009-01-01

    The authors describe the development of a simulation framework for anomalous change detection that considers both the spatial and spectral aspects of the imagery. A purely spectral framework has previously been introduced, but the extension to spatio-spectral requires attention to a variety of new issues, and requires more careful modeling of the anomalous changes. Using this extended framework, they evaluate the utility of spatial image processing operators to enhance change detection sensitivity in (simulated) remote sensing imagery.

  20. A network of superconducting gravimeters detects submicrogal coseismic gravity changes.

    PubMed

    Imanishi, Yuichi; Sato, Tadahiro; Higashi, Toshihiro; Sun, Wenke; Okubo, Shuhei

    2004-10-15

    With high-resolution continuous gravity recordings from a regional network of superconducting gravimeters, we have detected permanent changes in gravity acceleration associated with a recent large earthquake. Detected changes in gravity acceleration are smaller than 10(-8) meters seconds(-2) (1 micro-Galileo, about 10(-9) times the surface gravity acceleration) and agree with theoretical values calculated from a dislocation model. Superconducting gravimetry can contribute to the studies of secular gravity changes associated with tectonic processes.

  1. One new method for road data shape change detection

    NASA Astrophysics Data System (ADS)

    Tang, Luliang; Li, Qingquan; Xu, Feng; Chang, Xiaomeng

    2009-10-01

    Similarity is a psychological cognition; this paper defines the Difference Distance and puts forward the Similarity Measuring Model for linear spatial data (SMM-L) based on the integration of the Distance View and the Feature Set View which are the views for similarity cognition. Based on the study of the relationship between the spatial data change and the similarity, a change detection algorithm for linear spatial data is developed, and a test on road data change detection is realized.

  2. Loop Mediated Isothermal Amplification (LAMP) Accurately Detects Malaria DNA from Filter Paper Blood Samples of Low Density Parasitaemias

    PubMed Central

    González, Iveth J.; Polley, Spencer D.; Bell, David; Shakely, Delér; Msellem, Mwinyi I.; Björkman, Anders; Mårtensson, Andreas

    2014-01-01

    Background Loop mediated isothermal amplification (LAMP) provides an opportunity for improved, field-friendly detection of malaria infections in endemic areas. However data on the diagnostic accuracy of LAMP for active case detection, particularly low-density parasitaemias, are lacking. We therefore evaluated the performance of a new LAMP kit compared with PCR using DNA from filter paper blood spots. Methods and Findings Samples from 865 fever patients and 465 asymptomatic individuals collected in Zanzibar were analysed for Pan (all species) and Pf (P. falciparum) DNA with the Loopamp MALARIA Pan/Pf kit. Samples were amplified at 65°C for 40 minutes in a real-time turbidimeter and results were compared with nested PCR. Samples with discordant results between LAMP and nested PCR were analysed with real-time PCR. The real-time PCR corrected nested PCR result was defined as gold standard. Among the 117 (13.5%) PCR detected P. falciparum infections from fever patients (mean parasite density 7491/µL, range 6–782,400) 115, 115 and 111 were positive by Pan-LAMP, Pf-LAMP and nested PCR, respectively. The sensitivities were 98.3% (95%CI 94–99.8) for both Pan and Pf-LAMP. Among the 54 (11.6%) PCR positive samples from asymptomatic individuals (mean parasite density 10/µL, range 0–4972) Pf-LAMP had a sensitivity of 92.7% (95%CI 80.1–98.5) for detection of the 41 P. falciparum infections. Pan-LAMP had sensitivities of 97% (95%CI 84.2–99.9) and 76.9% (95%CI 46.2–95) for detection of P. falciparum and P. malariae, respectively. The specificities for both Pan and Pf-LAMP were 100% (95%CI 99.1–100) in both study groups. Conclusion Both components of the Loopamp MALARIA Pan/Pf detection kit revealed high diagnostic accuracy for parasite detection among fever patients and importantly also among asymptomatic individuals of low parasite densities from minute blood volumes preserved on filter paper. These data support LAMPs potential role for improved detection of low

  3. Are the Original and Second Edition of the California Verbal Learning Test Equally Accurate in Detecting Malingering?

    ERIC Educational Resources Information Center

    Greve, Kevin W.; Curtis, Kelly L.; Bianchini, Kevin J.; Ord, Jonathan S.

    2009-01-01

    This two-part study sought to determine the equivalence of the California Verbal Learning Tests (CVLT-1 and CVLT-2) in the detection of malingering in traumatic brain injury (TBI) and chronic pain. Part 1 compared a variety of scores from the two versions in carefully matched patient groups. Part 2 used criterion groups (known-groups) methodology…

  4. Change-point detection for recursive Bayesian geoacoustic inversions.

    PubMed

    Tan, Bien Aik; Gerstoft, Peter; Yardim, Caglar; Hodgkiss, William S

    2015-04-01

    In order to carry out geoacoustic inversion in low signal-to-noise ratio (SNR) conditions, extended duration observations coupled with source and/or receiver motion may be necessary. As a result, change in the underlying model parameters due to time or space is anticipated. In this paper, an inversion method is proposed for cases when the model parameters change abruptly or slowly. A model parameter change-point detection method is developed to detect the change in the model parameters using the importance samples and corresponding weights that are already available from the recursive Bayesian inversion. If the model parameters change abruptly, a change-point will be detected and the inversion will restart with the pulse measurement after the change-point. If the model parameters change gradually, the inversion (based on constant model parameters) may proceed until the accumulated model parameter mismatch is significant and triggers the detection of a change-point. These change-point detections form the heuristics for controlling the coherent integration time in recursive Bayesian inversion. The method is demonstrated in simulation with parameters corresponding to the low SNR, 100-900 Hz linear frequency modulation pulses observed in the Shallow Water 2006 experiment [Tan, Gerstoft, Yardim, and Hodgkiss, J. Acoust. Soc. Am. 136, 1187-1198 (2014)].

  5. The Nature of Change Detection and Online Representations of Scenes

    ERIC Educational Resources Information Center

    Ryan,J ennifer D.; Cohen, Neal J.

    2004-01-01

    This article provides evidence for implicit change detection and for the contribution of multiple memory sources to online representations. Multiple eye-movement measures distinguished original from changed scenes, even when college students had no conscious awareness for the change. Patients with amnesia showed a systematic deficit on 1 class of…

  6. Improved change detection with local co-registration adjustments

    SciTech Connect

    Wohlberg, Brendt E; Theiler, James P

    2009-01-01

    We introduce a simple approach for compensating for residual misregistration error on the performance of anomalous change detection algorithms. Using real data with a simulation framework for anomalous change and with a real anomalous change, we illustrate the approach and investigate its effectiveness.

  7. Detecting data and schema changes in scientific documents

    SciTech Connect

    Adiwijaya, I; Critchlow, T; Musick, R

    1999-06-08

    Data stored in a data warehouse must be kept consistent and up-to-date with the underlying information sources. By providing the capability to identify, categorize and detect changes in these sources, only the modified data needs to be transferred and entered into the warehouse. Another alternative, periodically reloading from scratch, is obviously inefficient. When the schema of an information source changes, all components that interact with, or make use of, data originating from that source must be updated to conform to the new schema. In this paper, the authors present an approach to detecting data and schema changes in scientific documents. Scientific data is of particular interest because it is normally stored as semi-structured documents, and it incurs frequent schema updates. They address the change detection problem by detecting data and schema changes between two versions of the same semi-structured document. This paper presents a graph representation of semi-structured documents and their schema before describing their approach to detecting changes while parsing the document. It also discusses how analysis of a collection of schema changes obtained from comparing several individual can be used to detect complex schema changes.

  8. Relative Saliency in Change Signals Affects Perceptual Comparison and Decision Processes in Change Detection

    ERIC Educational Resources Information Center

    Yang, Cheng-Ta

    2011-01-01

    Change detection requires perceptual comparison and decision processes on different features of multiattribute objects. How relative salience between two feature-changes influences the processes has not been addressed. This study used the systems factorial technology to investigate the processes when detecting changes in a Gabor patch with visual…

  9. Accurate method for measurement of pipe wall thickness using a circumferential guided wave generated and detected by a pair of noncontact transducers

    NASA Astrophysics Data System (ADS)

    Nishino, H.; Taniguchi, Y.; Yoshida, K.

    2012-05-01

    A noncontact method of an accurate estimation of a pipe wall thickness using a circumferential (C-) Lamb wave is presented. The C-Lamb waves circling along the circumference of pipes are transmitted and received by the critical angle method using a pair of noncontact air-coupled ultrasonic transducers. For the accurate estimation of a pipe wall thickness, the accurate measurement of the angular wave number that changes minutely owing to the thickness must be achieved. To achieve the accurate measurement, a large number of tone-burst cycles are used so as to superpose the C-Lamb wave on itself along its circumferential orbit. In this setting, the amplitude of the superposed region changes considerably with the angular wave number, from which the wall thickness can be estimated. This paper presents the principle of the method and experimental verifications. As results of the experimental verifications, it was confirmed that the maximum error between the estimates and the theoretical model was less than 10 micrometers.

  10. Questioning the Specificity of ASRS-v1.1 to Accurately Detect ADHD in Substance Abusing Populations

    ERIC Educational Resources Information Center

    Chiasson, Jean-Pierre; Stavro, Katherine; Rizkallah, Elie; Lapierre, Luc; Dussault, Maxime; Legault, Louis; Potvin, Stephane

    2012-01-01

    Objective: To assess the specificity of the Adult ADHD Self-Report Scale (ASRS-v1.1) in detecting ADHD among individuals with substance use disorders (SUDs). Method: A chart review of 183 SUD patients was conducted. Patients were screened for ADHD with the ASRS-v1.1 and were later assessed by a psychiatrist specialized in ADHD. Results: Among SUD…

  11. Comparison of Methodologies to Detect Low Levels of Hemolysis in Serum for Accurate Assessment of Serum microRNAs

    PubMed Central

    Shah, Jaynish S.; Soon, Patsy S.; Marsh, Deborah J.

    2016-01-01

    microRNAs have emerged as powerful regulators of many biological processes, and their expression in many cancer tissues has been shown to correlate with clinical parameters such as cancer type and prognosis. Present in a variety of biological fluids, microRNAs have been described as a ‘gold mine’ of potential noninvasive biomarkers. Release of microRNA content of blood cells upon hemolysis dramatically alters the microRNA profile in blood, potentially affecting levels of a significant number of proposed biomarker microRNAs and, consequently, accuracy of serum or plasma-based tests. Several methods to detect low levels of hemolysis have been proposed; however, a direct comparison assessing their sensitivities is currently lacking. In this study, we evaluated the sensitivities of four methods to detect hemolysis in serum (listed in the order of sensitivity): measurement of hemoglobin using a Coulter® AcT diff™ Analyzer, visual inspection, the absorbance of hemoglobin measured by spectrophotometry at 414 nm and the ratio of red blood cell-enriched miR-451a to the reference microRNA miR-23a-3p. The miR ratio detected hemolysis down to approximately 0.001%, whereas the Coulter® AcT diff™ Analyzer was unable to detect hemolysis lower than 1%. The spectrophotometric method could detect down to 0.004% hemolysis, and correlated with the miR ratio. Analysis of hemolysis in a cohort of 86 serum samples from cancer patients and healthy controls showed that 31 of 86 (36%) were predicted by the miR ratio to be hemolyzed, whereas only 8 of these samples (9%) showed visible pink discoloration. Using receiver operator characteristic (ROC) analyses, we identified absorbance cutoffs of 0.072 and 0.3 that could identify samples with low and high levels of hemolysis, respectively. Overall, this study will assist researchers in the selection of appropriate methodologies to test for hemolysis in serum samples prior to quantifying expression of microRNAs. PMID:27054342

  12. Novel real-time simultaneous amplification and testing method to accurately and rapidly detect Mycobacterium tuberculosis complex.

    PubMed

    Cui, Zhenling; Wang, Yongzhong; Fang, Liang; Zheng, Ruijuan; Huang, Xiaochen; Liu, Xiaoqin; Zhang, Gang; Rui, Dongmei; Ju, Jinliang; Hu, Zhongyi

    2012-03-01

    The aim of this study was to establish and evaluate a simultaneous amplification and testing method for detection of the Mycobacterium tuberculosis complex (SAT-TB assay) in clinical specimens by using isothermal RNA amplification and real-time fluorescence detection. In the SAT-TB assay, a 170-bp M. tuberculosis 16S rRNA fragment is reverse transcribed to DNA by use of Moloney murine leukemia virus (M-MLV) reverse transcriptase, using specific primers incorporating the T7 promoter sequence, and undergoes successive cycles of amplification using T7 RNA polymerase. Using a real-time PCR instrument, hybridization of an internal 6-carboxyfluorescein-4-[4-(dimethylamino)phenylazo] benzoic acid N-succinimidyl ester (FAM-DABCYL)-labeled fluorescent probe can be used to detect RNA amplification. The SAT-TB assay takes less than 1.5 h to perform, and the sensitivity of the assay for detection of M. tuberculosis H37Rv is 100 CFU/ml. The TB probe has no cross-reactivity with nontuberculous mycobacteria or other common respiratory tract pathogens. For 253 pulmonary tuberculosis (PTB) specimens and 134 non-TB specimens, the SAT-TB results correlated with 95.6% (370/387 specimens) of the Bactec MGIT 960 culture assay results. The sensitivity, specificity, and positive and negative predictive values of the SAT-TB test for the diagnosis of PTB were 67.6%, 100%, 100%, and 62.0%, respectively, compared to 61.7%, 100%, 100%, and 58.0% for Bactec MGIT 960 culture. For PTB diagnosis, the sensitivities of the SAT-TB and Bactec MGIT 960 culture methods were 97.6% and 95.9%, respectively, for smear-positive specimens and 39.2% and 30.2%, respectively, for smear-negative specimens. In conclusion, the SAT-TB assay is a novel, simple test with a high specificity which may enhance the detection rate of TB. It is therefore a promising tool for rapid diagnosis of M. tuberculosis infection in clinical microbiology laboratories.

  13. Detection and Attribution of Regional Climate Change

    SciTech Connect

    Bala, G; Mirin, A

    2007-01-19

    We developed a high resolution global coupled modeling capability to perform breakthrough studies of the regional climate change. The atmospheric component in our simulation uses a 1{sup o} latitude x 1.25{sup o} longitude grid which is the finest resolution ever used for the NCAR coupled climate model CCSM3. Substantial testing and slight retuning was required to get an acceptable control simulation. The major accomplishment is the validation of this new high resolution configuration of CCSM3. There are major improvements in our simulation of the surface wind stress and sea ice thickness distribution in the Arctic. Surface wind stress and ocean circulation in the Antarctic Circumpolar Current are also improved. Our results demonstrate that the FV version of the CCSM coupled model is a state of the art climate model whose simulation capabilities are in the class of those used for IPCC assessments. We have also provided 1000 years of model data to Scripps Institution of Oceanography to estimate the natural variability of stream flow in California. In the future, our global model simulations will provide boundary data to high-resolution mesoscale model that will be used at LLNL. The mesoscale model would dynamically downscale the GCM climate to regional scale on climate time scales.

  14. Cortical dynamics of visual change detection based on sensory memory.

    PubMed

    Urakawa, Tomokazu; Inui, Koji; Yamashiro, Koya; Tanaka, Emi; Kakigi, Ryusuke

    2010-08-01

    Detecting a visual change was suggested to relate closely to the visual sensory memory formed by visual stimuli before the occurrence of the change, because change detection involves identifying a difference between ongoing and preceding sensory conditions. Previous neuroimaging studies showed that an abrupt visual change activates the middle occipital gyrus (MOG). However, it still remains to be elucidated whether the MOG is related to visual change detection based on sensory memory. Here we tried to settle this issue using a new method of stimulation with blue and red LEDs to emphasize a memory-based change detection process. There were two stimuli, a standard trial stimulus and a deviant trial stimulus. The former was a red light lasting 500 ms, and the latter was a red light lasting 250 ms immediately followed by a blue light lasting 250 ms. Effects of the trial-trial interval, 250 approximately 2000 ms, were investigated to know how cortical responses to the abrupt change (from red to blue) were affected by preceding conditions. The brain response to the deviant trial stimulus was recorded by magnetoencephalography. Results of a multi-dipole analysis showed that the activity in the MOG, peaking at around 150 ms after the change onset, decreased in amplitude as the interval increased, but the earlier activity in BA 17/18 was not affected by the interval. These results suggested that the MOG is an important cortical area relating to the sensory memory-based visual change-detecting system.

  15. Classification of change detection and change blindness from near-infrared spectroscopy signals.

    PubMed

    Tanaka, Hirokazu; Katura, Takusige

    2011-08-01

    Using a machine-learning classification algorithm applied to near-infrared spectroscopy (NIRS) signals, we classify a success (change detection) or a failure (change blindness) in detecting visual changes for a change-detection task. Five subjects perform a change-detection task, and their brain activities are continuously monitored. A support-vector-machine algorithm is applied to classify the change-detection and change-blindness trials, and correct classification probability of 70-90% is obtained for four subjects. Two types of temporal shapes in classification probabilities are found: one exhibiting a maximum value after the task is completed (postdictive type), and another exhibiting a maximum value during the task (predictive type). As for the postdictive type, the classification probability begins to increase immediately after the task completion and reaches its maximum in about the time scale of neuronal hemodynamic response, reflecting a subjective report of change detection. As for the predictive type, the classification probability shows an increase at the task initiation and is maximal while subjects are performing the task, predicting the task performance in detecting a change. We conclude that decoding change detection and change blindness from NIRS signal is possible and argue some future applications toward brain-machine interfaces.

  16. Classification of change detection and change blindness from near-infrared spectroscopy signals

    NASA Astrophysics Data System (ADS)

    Tanaka, Hirokazu; Katura, Takusige

    2011-08-01

    Using a machine-learning classification algorithm applied to near-infrared spectroscopy (NIRS) signals, we classify a success (change detection) or a failure (change blindness) in detecting visual changes for a change-detection task. Five subjects perform a change-detection task, and their brain activities are continuously monitored. A support-vector-machine algorithm is applied to classify the change-detection and change-blindness trials, and correct classification probability of 70-90% is obtained for four subjects. Two types of temporal shapes in classification probabilities are found: one exhibiting a maximum value after the task is completed (postdictive type), and another exhibiting a maximum value during the task (predictive type). As for the postdictive type, the classification probability begins to increase immediately after the task completion and reaches its maximum in about the time scale of neuronal hemodynamic response, reflecting a subjective report of change detection. As for the predictive type, the classification probability shows an increase at the task initiation and is maximal while subjects are performing the task, predicting the task performance in detecting a change. We conclude that decoding change detection and change blindness from NIRS signal is possible and argue some future applications toward brain-machine interfaces.

  17. Accurate variant detection across non-amplified and whole genome amplified DNA using targeted next generation sequencing

    PubMed Central

    2012-01-01

    Background Many hypothesis-driven genetic studies require the ability to comprehensively and efficiently target specific regions of the genome to detect sequence variations. Often, sample availability is limited requiring the use of whole genome amplification (WGA). We evaluated a high-throughput microdroplet-based PCR approach in combination with next generation sequencing (NGS) to target 384 discrete exons from 373 genes involved in cancer. In our evaluation, we compared the performance of six non-amplified gDNA samples from two HapMap family trios. Three of these samples were also preamplified by WGA and evaluated. We tested sample pooling or multiplexing strategies at different stages of the tested targeted NGS (T-NGS) workflow. Results The results demonstrated comparable sequence performance between non-amplified and preamplified samples and between different indexing strategies [sequence specificity of 66.0% ± 3.4%, uniformity (coverage at 0.2× of the mean) of 85.6% ± 0.6%]. The average genotype concordance maintained across all the samples was 99.5% ± 0.4%, regardless of sample type or pooling strategy. We did not detect any errors in the Mendelian patterns of inheritance of genotypes between the parents and offspring within each trio. We also demonstrated the ability to detect minor allele frequencies within the pooled samples that conform to predicted models. Conclusion Our described PCR-based sample multiplex approach and the ability to use WGA material for NGS may enable researchers to perform deep resequencing studies and explore variants at very low frequencies and cost. PMID:22994565

  18. Full automatic fiducial marker detection on coil arrays for accurate instrumentation placement during MRI guided breast interventions

    NASA Astrophysics Data System (ADS)

    Filippatos, Konstantinos; Boehler, Tobias; Geisler, Benjamin; Zachmann, Harald; Twellmann, Thorsten

    2010-02-01

    With its high sensitivity, dynamic contrast-enhanced MR imaging (DCE-MRI) of the breast is today one of the first-line tools for early detection and diagnosis of breast cancer, particularly in the dense breast of young women. However, many relevant findings are very small or occult on targeted ultrasound images or mammography, so that MRI guided biopsy is the only option for a precise histological work-up [1]. State-of-the-art software tools for computer-aided diagnosis of breast cancer in DCE-MRI data offer also means for image-based planning of biopsy interventions. One step in the MRI guided biopsy workflow is the alignment of the patient position with the preoperative MR images. In these images, the location and orientation of the coil localization unit can be inferred from a number of fiducial markers, which for this purpose have to be manually or semi-automatically detected by the user. In this study, we propose a method for precise, full-automatic localization of fiducial markers, on which basis a virtual localization unit can be subsequently placed in the image volume for the purpose of determining the parameters for needle navigation. The method is based on adaptive thresholding for separating breast tissue from background followed by rigid registration of marker templates. In an evaluation of 25 clinical cases comprising 4 different commercial coil array models and 3 different MR imaging protocols, the method yielded a sensitivity of 0.96 at a false positive rate of 0.44 markers per case. The mean distance deviation between detected fiducial centers and ground truth information that was appointed from a radiologist was 0.94mm.

  19. Detection of Greenhouse-Gas-Induced Climatic Change

    SciTech Connect

    Jones, P.D.; Wigley, T.M.L.

    1998-05-26

    The objective of this report is to assemble and analyze instrumental climate data and to develop and apply climate models as a basis for (1) detecting greenhouse-gas-induced climatic change, and (2) validation of General Circulation Models.

  20. Fast Change Point Detection for Electricity Market Analysis

    SciTech Connect

    Berkeley, UC; Gu, William; Choi, Jaesik; Gu, Ming; Simon, Horst; Wu, Kesheng

    2013-08-25

    Electricity is a vital part of our daily life; therefore it is important to avoid irregularities such as the California Electricity Crisis of 2000 and 2001. In this work, we seek to predict anomalies using advanced machine learning algorithms. These algorithms are effective, but computationally expensive, especially if we plan to apply them on hourly electricity market data covering a number of years. To address this challenge, we significantly accelerate the computation of the Gaussian Process (GP) for time series data. In the context of a Change Point Detection (CPD) algorithm, we reduce its computational complexity from O($n^{5}$) to O($n^{2}$). Our efficient algorithm makes it possible to compute the Change Points using the hourly price data from the California Electricity Crisis. By comparing the detected Change Points with known events, we show that the Change Point Detection algorithm is indeed effective in detecting signals preceding major events.

  1. Accurate detection of male subclinical genital tract infection via cervical culture and DNA hybridization assay of the female partner.

    PubMed

    Trum, J W; Pannekoek, Y; Spanjaard, L; Bleker, O P; Van Der Veen, F

    2000-02-01

    The accuracy of the PACE2 DNA hybridization assay of the cervix and cervical culture in female partners for the diagnosis of male subclinical genital tract infection were assessed in a male infertility population. A total of 184 men were screened for the presence of Chlamydia trachomatis, Ureaplasma urealyticum and Mycoplasma hominis. Seventy-one men were identified with a positive test for one or more of the above mentioned micro-organisms. The overall prevalence of bacterial infection was 39%. Female partners of all men were tested with the PACE2 DNA hybridization assay to detect a C. trachomatis infection. Sensitivity was 100% and specificity was 100%. In 67 female partners (94%) of men who tested positive for U. urealyticum and/or M. hominis, a cervical swab culture was performed. The sensitivity of the cervical swab culture was 100%. In view of the high prevalence of U. urealyticum and M. hominis in the male genital tract and the role these sexually transmitted pathogens may play in infertility, one might question whether all couples should be screened for the presence of these pathogens. Transurethral swab culture after digital prostatic massage is disincentive to men. The cervical culture in their female partner, performed as part of the routine fertility work-up, is a suitable alternative to detect the presence of these micro-organisms in the male genital tract.

  2. Isothermal microcalorimetry accurately detects bacteria, tumorous microtissues, and parasitic worms in a label-free well-plate assay

    PubMed Central

    Braissant, Olivier; Keiser, Jennifer; Meister, Isabel; Bachmann, Alexander; Wirz, Dieter; Göpfert, Beat; Bonkat, Gernot; Wadsö, Ingemar

    2015-01-01

    Isothermal microcalorimetry is a label-free assay that allows monitoring of enzymatic and metabolic activities. The technique has strengths, but most instruments have a low throughput, which has limited their use for bioassays. Here, an isothermal microcalorimeter, equipped with a vessel holder similar to a 48-well plate, was used. The increased throughput of this microcalorimeter makes it valuable for biomedical and pharmaceutical applications. Our results show that the sensitivity of the instrument allows the detection of 3 × 104 bacteria per vial. Growth of P. mirabilis in Luria Broth medium was detected between 2 and 9 h with decreasing inoculum. The culture released 2.1J with a maximum thermal power of 76 μW. The growth rate calculated using calorimetric and spectrophotometric data were 0.60 and 0.57 h–1, respectively. Additional insight on protease activities of P. mirabilis matching the last peak in heat production could be gathered as well. Growth of tumor microtissues releasing a maximum thermal power of 2.1 μW was also monitored and corresponds to a diameter increase of the microtissues from ca. 100 to 428 μm. This opens new research avenues in cancer research, diagnostics, and development of new antitumor drugs. For parasitic worms, the technique allows assessment of parasite survival using motor and metabolic activities even with a single worm. PMID:25511812

  3. An Optimized Method for Accurate Fetal Sex Prediction and Sex Chromosome Aneuploidy Detection in Non-Invasive Prenatal Testing.

    PubMed

    Wang, Ting; He, Quanze; Li, Haibo; Ding, Jie; Wen, Ping; Zhang, Qin; Xiang, Jingjing; Li, Qiong; Xuan, Liming; Kong, Lingyin; Mao, Yan; Zhu, Yijun; Shen, Jingjing; Liang, Bo; Li, Hong

    2016-01-01

    Massively parallel sequencing (MPS) combined with bioinformatic analysis has been widely applied to detect fetal chromosomal aneuploidies such as trisomy 21, 18, 13 and sex chromosome aneuploidies (SCAs) by sequencing cell-free fetal DNA (cffDNA) from maternal plasma, so-called non-invasive prenatal testing (NIPT). However, many technical challenges, such as dependency on correct fetal sex prediction, large variations of chromosome Y measurement and high sensitivity to random reads mapping, may result in higher false negative rate (FNR) and false positive rate (FPR) in fetal sex prediction as well as in SCAs detection. Here, we developed an optimized method to improve the accuracy of the current method by filtering out randomly mapped reads in six specific regions of the Y chromosome. The method reduces the FNR and FPR of fetal sex prediction from nearly 1% to 0.01% and 0.06%, respectively and works robustly under conditions of low fetal DNA concentration (1%) in testing and simulation of 92 samples. The optimized method was further confirmed by large scale testing (1590 samples), suggesting that it is reliable and robust enough for clinical testing.

  4. An Optimized Method for Accurate Fetal Sex Prediction and Sex Chromosome Aneuploidy Detection in Non-Invasive Prenatal Testing.

    PubMed

    Wang, Ting; He, Quanze; Li, Haibo; Ding, Jie; Wen, Ping; Zhang, Qin; Xiang, Jingjing; Li, Qiong; Xuan, Liming; Kong, Lingyin; Mao, Yan; Zhu, Yijun; Shen, Jingjing; Liang, Bo; Li, Hong

    2016-01-01

    Massively parallel sequencing (MPS) combined with bioinformatic analysis has been widely applied to detect fetal chromosomal aneuploidies such as trisomy 21, 18, 13 and sex chromosome aneuploidies (SCAs) by sequencing cell-free fetal DNA (cffDNA) from maternal plasma, so-called non-invasive prenatal testing (NIPT). However, many technical challenges, such as dependency on correct fetal sex prediction, large variations of chromosome Y measurement and high sensitivity to random reads mapping, may result in higher false negative rate (FNR) and false positive rate (FPR) in fetal sex prediction as well as in SCAs detection. Here, we developed an optimized method to improve the accuracy of the current method by filtering out randomly mapped reads in six specific regions of the Y chromosome. The method reduces the FNR and FPR of fetal sex prediction from nearly 1% to 0.01% and 0.06%, respectively and works robustly under conditions of low fetal DNA concentration (1%) in testing and simulation of 92 samples. The optimized method was further confirmed by large scale testing (1590 samples), suggesting that it is reliable and robust enough for clinical testing. PMID:27441628

  5. An Optimized Method for Accurate Fetal Sex Prediction and Sex Chromosome Aneuploidy Detection in Non-Invasive Prenatal Testing

    PubMed Central

    Li, Haibo; Ding, Jie; Wen, Ping; Zhang, Qin; Xiang, Jingjing; Li, Qiong; Xuan, Liming; Kong, Lingyin; Mao, Yan; Zhu, Yijun; Shen, Jingjing; Liang, Bo; Li, Hong

    2016-01-01

    Massively parallel sequencing (MPS) combined with bioinformatic analysis has been widely applied to detect fetal chromosomal aneuploidies such as trisomy 21, 18, 13 and sex chromosome aneuploidies (SCAs) by sequencing cell-free fetal DNA (cffDNA) from maternal plasma, so-called non-invasive prenatal testing (NIPT). However, many technical challenges, such as dependency on correct fetal sex prediction, large variations of chromosome Y measurement and high sensitivity to random reads mapping, may result in higher false negative rate (FNR) and false positive rate (FPR) in fetal sex prediction as well as in SCAs detection. Here, we developed an optimized method to improve the accuracy of the current method by filtering out randomly mapped reads in six specific regions of the Y chromosome. The method reduces the FNR and FPR of fetal sex prediction from nearly 1% to 0.01% and 0.06%, respectively and works robustly under conditions of low fetal DNA concentration (1%) in testing and simulation of 92 samples. The optimized method was further confirmed by large scale testing (1590 samples), suggesting that it is reliable and robust enough for clinical testing. PMID:27441628

  6. Electrophysiological evidence for different types of change detection and change blindness.

    PubMed

    Busch, Niko A; Fründ, Ingo; Herrmann, Christoph S

    2010-08-01

    Numerous studies have demonstrated that observers often fail to notice large changes in visual scenes, a phenomenon known as change blindness. Some experiments have suggested that phenomenological experience in change blindness experiments is more diverse than the common distinction between change detection and change blindness allows to resolve. Recently, it has been debated whether changes in visual scenes can be detected ("sensed") without a corresponding perception of the changing object ("seeing") and whether these phenomena build on fundamentally different perceptual processes. The present study investigated whether phenomenologically different perceptual processes such as sensing and seeing rely on different or similar neural processes. We studied ERP effects of visual change processing (as compared to change blindness) when observers merely detected the presence of a change ("sensing") and when they identified the changing object in addition to detection ("seeing"). Although the visual awareness negativity (VAN)/selection negativity was similar for detection with and without identification, a change-related positivity and the N2pc contralateral to changes were found exclusively when the change was fully identified. This finding indicates that change identification requires perceptual and neural processes that are not involved in mere detection. In a second experiment, we demonstrated that the VAN and N2pc effects are similar to effects of selective attention in a visual search task. By contrast, the change-related positivity was specific for conscious processing of visual changes. The results suggest that changes can be detected ("sensed") without perception of the changing object. Furthermore, sensing and seeing seem to rely on different neural processes and seem to constitute different types of visual perception. These findings bear implications for how different categories of visual awareness are related to different stages in visual processing.

  7. DNA extraction techniques compared for accurate detection of genetically modified organisms (GMOs) in maize food and feed products.

    PubMed

    Turkec, Aydin; Kazan, Hande; Karacanli, Burçin; Lucas, Stuart J

    2015-08-01

    In this paper, DNA extraction methods have been evaluated to detect the presence of genetically modified organisms (GMOs) in maize food and feed products commercialised in Turkey. All the extraction methods tested performed well for the majority of maize foods and feed products analysed. However, the highest DNA content was achieved by the Wizard, Genespin or the CTAB method, all of which produced optimal DNA yield and purity for different maize food and feed products. The samples were then screened for the presence of GM elements, along with certified reference materials. Of the food and feed samples, 8 % tested positive for the presence of one GM element (NOS terminator), of which half (4 % of the total) also contained a second element (the Cauliflower Mosaic Virus 35S promoter). The results obtained herein clearly demonstrate the presence of GM maize in the Turkish market, and that the Foodproof GMO Screening Kit provides reliable screening of maize food and feed products. PMID:26243938

  8. DNA extraction techniques compared for accurate detection of genetically modified organisms (GMOs) in maize food and feed products.

    PubMed

    Turkec, Aydin; Kazan, Hande; Karacanli, Burçin; Lucas, Stuart J

    2015-08-01

    In this paper, DNA extraction methods have been evaluated to detect the presence of genetically modified organisms (GMOs) in maize food and feed products commercialised in Turkey. All the extraction methods tested performed well for the majority of maize foods and feed products analysed. However, the highest DNA content was achieved by the Wizard, Genespin or the CTAB method, all of which produced optimal DNA yield and purity for different maize food and feed products. The samples were then screened for the presence of GM elements, along with certified reference materials. Of the food and feed samples, 8 % tested positive for the presence of one GM element (NOS terminator), of which half (4 % of the total) also contained a second element (the Cauliflower Mosaic Virus 35S promoter). The results obtained herein clearly demonstrate the presence of GM maize in the Turkish market, and that the Foodproof GMO Screening Kit provides reliable screening of maize food and feed products.

  9. 3D change detection at street level using mobile laser scanning point clouds and terrestrial images

    NASA Astrophysics Data System (ADS)

    Qin, Rongjun; Gruen, Armin

    2014-04-01

    Automatic change detection and geo-database updating in the urban environment are difficult tasks. There has been much research on detecting changes with satellite and aerial images, but studies have rarely been performed at the street level, which is complex in its 3D geometry. Contemporary geo-databases include 3D street-level objects, which demand frequent data updating. Terrestrial images provides rich texture information for change detection, but the change detection with terrestrial images from different epochs sometimes faces problems with illumination changes, perspective distortions and unreliable 3D geometry caused by the lack of performance of automatic image matchers, while mobile laser scanning (MLS) data acquired from different epochs provides accurate 3D geometry for change detection, but is very expensive for periodical acquisition. This paper proposes a new method for change detection at street level by using combination of MLS point clouds and terrestrial images: the accurate but expensive MLS data acquired from an early epoch serves as the reference, and terrestrial images or photogrammetric images captured from an image-based mobile mapping system (MMS) at a later epoch are used to detect the geometrical changes between different epochs. The method will automatically mark the possible changes in each view, which provides a cost-efficient method for frequent data updating. The methodology is divided into several steps. In the first step, the point clouds are recorded by the MLS system and processed, with data cleaned and classified by semi-automatic means. In the second step, terrestrial images or mobile mapping images at a later epoch are taken and registered to the point cloud, and then point clouds are projected on each image by a weighted window based z-buffering method for view dependent 2D triangulation. In the next step, stereo pairs of the terrestrial images are rectified and re-projected between each other to check the geometrical

  10. You Seem Certain but You Were Wrong Before: Developmental Change in Preschoolers’ Relative Trust in Accurate versus Confident Speakers

    PubMed Central

    Brosseau-Liard, Patricia; Cassels, Tracy; Birch, Susan

    2014-01-01

    The present study tested how preschoolers weigh two important cues to a person’s credibility, namely prior accuracy and confidence, when deciding what to learn and believe. Four- and 5-year-olds (N = 96) preferred to believe information provided by a confident rather than hesitant individual; however, when confidence conflicted with accuracy, preschoolers increasingly favored information from the previously accurate but hesitant individual as they aged. These findings reveal an important developmental progression in how children use others’ confidence and prior accuracy to shape what they learn and provide a window into children’s developing social cognition, scepticism, and critical thinking. PMID:25254553

  11. Pattern-histogram-based temporal change detection using personal chest radiographs

    NASA Astrophysics Data System (ADS)

    Ugurlu, Yucel; Obi, Takashi; Hasegawa, Akira; Yamaguchi, Masahiro; Ohyama, Nagaaki

    1999-05-01

    An accurate and reliable detection of temporal changes from a pair of images has considerable interest in the medical science. Traditional registration and subtraction techniques can be applied to extract temporal differences when,the object is rigid or corresponding points are obvious. However, in radiological imaging, loss of the depth information, the elasticity of object, the absence of clearly defined landmarks and three-dimensional positioning differences constraint the performance of conventional registration techniques. In this paper, we propose a new method in order to detect interval changes accurately without using an image registration technique. The method is based on construction of so-called pattern histogram and comparison procedure. The pattern histogram is a graphic representation of the frequency counts of all allowable patterns in the multi-dimensional pattern vector space. K-means algorithm is employed to partition pattern vector space successively. Any differences in the pattern histograms imply that different patterns are involved in the scenes. In our experiment, a pair of chest radiographs of pneumoconiosis is employed and the changing histogram bins are visualized on both of the images. We found that the method can be used as an alternative way of temporal change detection, particularly when the precise image registration is not available.

  12. New Method for Accurate Calibration of Micro-Channel Plate based Detection Systems and its use in the Fast Plasma Investigation of NASA's Magnetospheric MultiScale Mission

    NASA Astrophysics Data System (ADS)

    Gliese, U.; Avanov, L. A.; Barrie, A.; Kujawski, J. T.; Mariano, A. J.; Tucker, C. J.; Chornay, D. J.; Cao, N. T.; Zeuch, M.; Pollock, C. J.; Jacques, A. D.

    2013-12-01

    The Fast Plasma Investigation (FPI) of the NASA Magnetospheric MultiScale (MMS) mission employs 16 Dual Electron Spectrometers (DESs) and 16 Dual Ion Spectrometers (DISs) with 4 of each type on each of 4 spacecraft to enable fast (30ms for electrons; 150ms for ions) and spatially differentiated measurements of full the 3D particle velocity distributions. This approach presents a new and challenging aspect to the calibration and operation of these instruments on ground and in flight. The response uniformity and reliability of their calibration and the approach to handling any temporal evolution of these calibrated characteristics all assume enhanced importance in this application, where we attempt to understand the meaning of particle distributions within the ion and electron diffusion regions. Traditionally, the micro-channel plate (MCP) based detection systems for electrostatic particle spectrometers have been calibrated by setting a fixed detection threshold and, subsequently, measuring a detection system count rate plateau curve to determine the MCP voltage that ensures the count rate has reached a constant value independent of further variation in the MCP voltage. This is achieved when most of the MCP pulse height distribution (PHD) is located at higher values (larger pulses) than the detection amplifier threshold. This method is adequate in single-channel detection systems and in multi-channel detection systems with very low crosstalk between channels. However, in dense multi-channel systems, it can be inadequate. Furthermore, it fails to fully and individually characterize each of the fundamental parameters of the detection system. We present a new detection system calibration method that enables accurate and repeatable measurement and calibration of MCP gain, MCP efficiency, signal loss due to variation in gain and efficiency, crosstalk from effects both above and below the MCP, noise margin, and stability margin in one single measurement. The fundamental

  13. An accurate projector gamma correction method for phase-measuring profilometry based on direct optical power detection

    NASA Astrophysics Data System (ADS)

    Liu, Miao; Yin, Shibin; Yang, Shourui; Zhang, Zonghua

    2015-10-01

    Digital projector is frequently applied to generate fringe pattern in phase calculation-based three dimensional (3D) imaging systems. Digital projector often works with camera in this kind of systems so the intensity response of a projector should be linear in order to ensure the measurement precision especially in Phase-Measuring Profilometry (PMP). Some correction methods are often applied to cope with the non-linear intensity response of the digital projector. These methods usually rely on camera and gamma function is often applied to compensate the non-linear response so the correction performance is restricted by the dynamic range of camera. In addition, the gamma function is not suitable to compensate the nonmonotonicity intensity response. This paper propose a gamma correction method by the precisely detecting the optical energy instead of using a plate and camera. A photodiode with high dynamic range and linear response is used to directly capture the light optical from the digital projector. After obtaining the real gamma curve precisely by photodiode, a gray level look-up table (LUT) is generated to correct the image to be projected. Finally, this proposed method is verified experimentally.

  14. Surface Change Detection Using Large Footprint Laser Altimetry

    NASA Technical Reports Server (NTRS)

    Blair, J. Bryan; Hofton, Michelle A.; Smith, David E. (Technical Monitor)

    2000-01-01

    Laser altimeters provide a precise and accurate method for mapping topography at fine horizontal and vertical scales. A laser altimeter provides range by measuring the roundtrip flight time of a short pulse of laser light from the laser altimeter instrument to the target surface. The range is then combined with laser beam pointing knowledge and absolute position knowledge to provide an absolute measurement of the surface topography. Newer generations of laser altimeters measure the range by recording the shape and time of the outgoing and received laser pulses. The shape of the return pulse can also provide unique information about the vertical structure of material such as vegetation within each laser footprint. Distortion of the return pulse is caused by the time-distributed reflections adding together and representing the vertical distribution of surfaces within the footprint. Larger footprints (10 - 100m in diameter) can support numerous target surfaces and thus provide the potential for producing complex return pulses. Interpreting the return pulse from laser altimeters has evolved from simple timing between thresholds, range-walk corrections, constant-fraction discriminators, and multi-stop time interval units to actual recording of the time varying return pulse intensity - the return waveform. Interpreting the waveform can be as simple as digitally thresholding the return pulse, calculating a centroid, to fitting one or more gaussian pulse-shapes to the signal. What we present here is a new technique for using the raw recorded return pulse as a raw observation to detect centimeter-level vertical topographic change using large footprint airborne and spaceborne laser altimetry. We use the correlation of waveforms from coincident footprints as an indication of the similarity in structure of the waveforms from epoch to epoch, and assume that low correlation is an indicator of vertical structure or elevation change. Thus, using vertically and horizontally

  15. Vegetation cover change detection in Chamela-Cuixamala, Mexico

    NASA Astrophysics Data System (ADS)

    De la Barreda Bautista, Betsabé; López-Caloca, Alejandra A.

    2009-09-01

    In Mexico, and everywhere else, the ecosystems are constantly changing either by natural factors or anthropogenic activity. Remote sensing has been a key tool to monitoring these changes throughout history and also to understanding the ecological dynamics. Hence, sustainable development plans have been created in order to improve the decisionmaking process; thus, this paper analyses deforestation impact in a very important natural resourcing area in Mexico, considering land cover changes. The study area is located in the coast of Jalisco, Mexico, where deforestation and fragmentation as well as high speed touristic development have been the causes of enormous biodiversity losses; the Chamela-Cuixamala Biosphere Reserve is located within this area. It has great species richness and vast endemism. The exploitation of this biome is widespread all over the country and it has already had an impact in the reserve. The change detection multi-temporal study uses Landsat satellite imagery during the 1970-2003 time period. Thus, the objective of change detection analysis is to detect and localize environmental changes through time. The change detection method consists in producing an image of change likelihood (by post-classification, multivariate alteration detection) and thresholding it in order to produce the change map. Experimental results confirmed that the patterns of land use and land cover changes have increased significantly over the last decade. This study also analyzes the deforestation impact on biodiversity. The analysis validation was carried out using field and statistic data. Spatial-temporal changing range enables the analysis of the structural and dynamic effects on the ecosystem and it enhances better decision-making and public environmental policies to decrease or eliminate deforestation, the creation of natural protected areas as a biodiversity conservation method, and counteracting the global warming phenomena.

  16. A Hopfield neural network for image change detection.

    PubMed

    Pajares, Gonzalo

    2006-09-01

    This paper outlines an optimization relaxation approach based on the analog Hopfield neural network (HNN) for solving the image change detection problem between two images. A difference image is obtained by subtracting pixel by pixel both images. The network topology is built so that each pixel in the difference image is a node in the network. Each node is characterized by its state, which determines if a pixel has changed. An energy function is derived, so that the network converges to stable states. The analog Hopfield's model allows each node to take on analog state values. Unlike most widely used approaches, where binary labels (changed/unchanged) are assigned to each pixel, the analog property provides the strength of the change. The main contribution of this paper is reflected in the customization of the analog Hopfield neural network to derive an automatic image change detection approach. When a pixel is being processed, some existing image change detection procedures consider only interpixel relations on its neighborhood. The main drawback of such approaches is the labeling of this pixel as changed or unchanged according to the information supplied by its neighbors, where its own information is ignored. The Hopfield model overcomes this drawback and for each pixel allows a tradeoff between the influence of its neighborhood and its own criterion. This is mapped under the energy function to be minimized. The performance of the proposed method is illustrated by comparative analysis against some existing image change detection methods.

  17. A Hopfield neural network for image change detection.

    PubMed

    Pajares, Gonzalo

    2006-09-01

    This paper outlines an optimization relaxation approach based on the analog Hopfield neural network (HNN) for solving the image change detection problem between two images. A difference image is obtained by subtracting pixel by pixel both images. The network topology is built so that each pixel in the difference image is a node in the network. Each node is characterized by its state, which determines if a pixel has changed. An energy function is derived, so that the network converges to stable states. The analog Hopfield's model allows each node to take on analog state values. Unlike most widely used approaches, where binary labels (changed/unchanged) are assigned to each pixel, the analog property provides the strength of the change. The main contribution of this paper is reflected in the customization of the analog Hopfield neural network to derive an automatic image change detection approach. When a pixel is being processed, some existing image change detection procedures consider only interpixel relations on its neighborhood. The main drawback of such approaches is the labeling of this pixel as changed or unchanged according to the information supplied by its neighbors, where its own information is ignored. The Hopfield model overcomes this drawback and for each pixel allows a tradeoff between the influence of its neighborhood and its own criterion. This is mapped under the energy function to be minimized. The performance of the proposed method is illustrated by comparative analysis against some existing image change detection methods. PMID:17001985

  18. Automated baseline change detection phase I. Final report

    SciTech Connect

    1995-12-01

    The Automated Baseline Change Detection (ABCD) project is supported by the DOE Morgantown Energy Technology Center (METC) as part of its ER&WM cross-cutting technology program in robotics. Phase 1 of the Automated Baseline Change Detection project is summarized in this topical report. The primary objective of this project is to apply robotic and optical sensor technology to the operational inspection of mixed toxic and radioactive waste stored in barrels, using Automated Baseline Change Detection (ABCD), based on image subtraction. Absolute change detection is based on detecting any visible physical changes, regardless of cause, between a current inspection image of a barrel and an archived baseline image of the same barrel. Thus, in addition to rust, the ABCD system can also detect corrosion, leaks, dents, and bulges. The ABCD approach and method rely on precise camera positioning and repositioning relative to the barrel and on feature recognition in images. In support of this primary objective, there are secondary objectives to determine DOE operational inspection requirements and DOE system fielding requirements.

  19. Evaluating coverage changes in national parks using a hybrid change detection algorithm and remote sensing

    NASA Astrophysics Data System (ADS)

    Ghofrani, Zahra; Mokhtarzade, Mehdi; Reza Sahebi, Mahmod; Beykikhoshk, Adham

    2014-01-01

    Remote sensing is a useful tool for detecting change over time. We introduce a hybrid change-detection method for forest and protected-area vegetation and demonstrate its use with two satellite images of Golestan National Park in northern Iran (1998 and 2010). We report on the advantages and disadvantages of the hybrid method relative to the standard change-detection method. In the proposed hybrid algorithm, the change vector analysis technique was used to determine changes in vegetation. Following this, we used postclassification comparison to determine the nature of the changes observed and their accuracy and to evaluate the effects of different parameters on the performance of the proposed method. We determined 85% accuracy for the proposed hybrid change-detection method, thus demonstrating a method for discovering and assessing environmental threats to natural treasures.

  20. Detection and Attribution of Anthropogenic Climate Change Impacts

    NASA Technical Reports Server (NTRS)

    Rosenzweig, Cynthia; Neofotis, Peter

    2013-01-01

    Human-influenced climate change is an observed phenomenon affecting physical and biological systems across the globe. The majority of observed impacts are related to temperature changes and are located in the northern high- and midlatitudes. However, new evidence is emerging that demonstrates that impacts are related to precipitation changes as well as temperature, and that climate change is impacting systems and sectors beyond the Northern Hemisphere. In this paper, we highlight some of this new evidence-focusing on regions and sectors that the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4) noted as under-represented-in the context of observed climate change impacts, direct and indirect drivers of change (including carbon dioxide itself), and methods of detection. We also present methods and studies attributing observed impacts to anthropogenic forcing. We argue that the expansion of methods of detection (in terms of a broader array of climate variables and data sources, inclusion of the major modes of climate variability, and incorporation of other drivers of change) is key to discerning the climate sensitivities of sectors and systems in regions where the impacts of climate change currently remain elusive. Attributing such changes to human forcing of the climate system, where possible, is important for development of effective mitigation and adaptation. Current challenges in documenting adaptation and the role of indigenous knowledge in detection and attribution are described.

  1. Statistically normalized coherent change detection for synthetic aperture sonar imagery

    NASA Astrophysics Data System (ADS)

    G-Michael, Tesfaye; Tucker, J. D.; Roberts, Rodney G.

    2016-05-01

    Coherent Change Detection (CCD) is a process of highlighting an area of activity in scenes (seafloor) under survey and generated from pairs of synthetic aperture sonar (SAS) images of approximately the same location observed at two different time instances. The problem of CCD and subsequent anomaly feature extraction/detection is complicated due to several factors such as the presence of random speckle pattern in the images, changing environmental conditions, and platform instabilities. These complications make the detection of weak target activities even more difficult. Typically, the degree of similarity between two images measured at each pixel locations is the coherence between the complex pixel values in the two images. Higher coherence indicates little change in the scene represented by the pixel and lower coherence indicates change activity in the scene. Such coherence estimation scheme based on the pixel intensity correlation is an ad-hoc procedure where the effectiveness of the change detection is determined by the choice of threshold which can lead to high false alarm rates. In this paper, we propose a novel approach for anomalous change pattern detection using the statistical normalized coherence and multi-pass coherent processing. This method may be used to mitigate shadows by reducing the false alarms resulting in the coherent map due to speckles and shadows. Test results of the proposed methods on a data set of SAS images will be presented, illustrating the effectiveness of the normalized coherence in terms statistics from multi-pass survey of the same scene.

  2. A novel video dataset for change detection benchmarking.

    PubMed

    Goyette, Nil; Jodoin, Pierre-Marc; Porikli, Fatih; Konrad, Janusz; Ishwar, Prakash

    2014-11-01

    Change detection is one of the most commonly encountered low-level tasks in computer vision and video processing. A plethora of algorithms have been developed to date, yet no widely accepted, realistic, large-scale video data set exists for benchmarking different methods. Presented here is a unique change detection video data set consisting of nearly 90 000 frames in 31 video sequences representing six categories selected to cover a wide range of challenges in two modalities (color and thermal infrared). A distinguishing characteristic of this benchmark video data set is that each frame is meticulously annotated by hand for ground-truth foreground, background, and shadow area boundaries-an effort that goes much beyond a simple binary label denoting the presence of change. This enables objective and precise quantitative comparison and ranking of video-based change detection algorithms. This paper discusses various aspects of the new data set, quantitative performance metrics used, and comparative results for over two dozen change detection algorithms. It draws important conclusions on solved and remaining issues in change detection, and describes future challenges for the scientific community. The data set, evaluation tools, and algorithm rankings are available to the public on a website and will be updated with feedback from academia and industry in the future.

  3. Unsupervised Change Detection in SAR Images Using Gaussian Mixture Models

    NASA Astrophysics Data System (ADS)

    Kiana, E.; Homayouni, S.; Sharifi, M. A.; Farid-Rohani, M.

    2015-12-01

    In this paper, we propose a method for unsupervised change detection in Remote Sensing Synthetic Aperture Radar (SAR) images. This method is based on the mixture modelling of the histogram of difference image. In this process, the difference image is classified into three classes; negative change class, positive change class and no change class. However the SAR images suffer from speckle noise, the proposed method is able to map the changes without speckle filtering. To evaluate the performance of this method, two dates of SAR data acquired by Uninhabited Aerial Vehicle Synthetic from an agriculture area are used. Change detection results show better efficiency when compared to the state-of-the-art methods.

  4. Accurate classification of 29 objects detected in the 39 month Palermo Swift/BAT hard X-ray catalogue

    NASA Astrophysics Data System (ADS)

    Parisi, P.; Masetti, N.; Jiménez-Bailón, E.; Chavushyan, V.; Palazzi, E.; Landi, R.; Malizia, A.; Bassani, L.; Bazzano, A.; Bird, A. J.; Charles, P. A.; Galaz, G.; Mason, E.; McBride, V. A.; Minniti, D.; Morelli, L.; Schiavone, F.; Ubertini, P.

    2012-09-01

    Through an optical campaign performed at four telescopes located in the northern and the southern hemispheres, plus archival data from two on-line sky surveys, we obtained optical spectroscopy for 29 counterparts of unclassified or poorly studied hard X-ray emitting objects detected with Swift /Burst Alert Telescope (BAT) and listed in the 39 month Palermo catalogue. All these objects also have observations taken with Swift /X-ray Telescope (XRT) or XMM-European Photon Imaging Camera (EPIC) which not only allow us to pinpoint their optical counterpart, but also study their X-ray spectral properties (column density, power law photon index, and F2-10 keV flux). We find that 28 sources in our sample are active galactic nuclei (AGNs); 7 are classified as type 1, while 21 are of type 2; the remaining object is a Galactic cataclysmic variable. Among our type 1 AGNs, we find 5 objects of intermediate Seyfert type (1.2-1.9) and one narrow-line Seyfert 1 galaxy; for 4 out of 7 sources, we are able to estimate the central black hole mass. Three of the type 2 AGNs of our sample display optical features typical of low-ionization nuclear emission-line regions (LINER) and one is a likely Compton thick AGN. All galaxies classified in this work are relatively nearby objects since their redshifts lie in the range 0.008-0.075; the only Galactic object found lies at an estimated distance of 90 pc. We also investigate the optical versus X-ray emission ratio of the galaxies of our sample to test the AGN unified model. For these galaxies, we also compare the X-ray absorption (caused by gas) with the optical reddening (caused by dust): we find that for most of our sources, specifically those of type 1.9-2.0 the former is higher than the latter confirming early results of Maiolino and collaborators; this is possibly due to the properties of dust in the circumnuclear obscuring torus of the AGN. Based on observations obtained from the following observatories: the Astronomical Observatory of

  5. Short-term change detection for UAV video

    NASA Astrophysics Data System (ADS)

    Saur, Günter; Krüger, Wolfgang

    2012-11-01

    In the last years, there has been an increased use of unmanned aerial vehicles (UAV) for video reconnaissance and surveillance. An important application in this context is change detection in UAV video data. Here we address short-term change detection, in which the time between observations ranges from several minutes to a few hours. We distinguish this task from video motion detection (shorter time scale) and from long-term change detection, based on time series of still images taken between several days, weeks, or even years. Examples for relevant changes we are looking for are recently parked or moved vehicles. As a pre-requisite, a precise image-to-image registration is needed. Images are selected on the basis of the geo-coordinates of the sensor's footprint and with respect to a certain minimal overlap. The automatic imagebased fine-registration adjusts the image pair to a common geometry by using a robust matching approach to handle outliers. The change detection algorithm has to distinguish between relevant and non-relevant changes. Examples for non-relevant changes are stereo disparity at 3D structures of the scene, changed length of shadows, and compression or transmission artifacts. To detect changes in image pairs we analyzed image differencing, local image correlation, and a transformation-based approach (multivariate alteration detection). As input we used color and gradient magnitude images. To cope with local misalignment of image structures we extended the approaches by a local neighborhood search. The algorithms are applied to several examples covering both urban and rural scenes. The local neighborhood search in combination with intensity and gradient magnitude differencing clearly improved the results. Extended image differencing performed better than both the correlation based approach and the multivariate alternation detection. The algorithms are adapted to be used in semi-automatic workflows for the ABUL video exploitation system of Fraunhofer

  6. Compact and cost-effective temperature-insensitive bio-sensor based on long-period fiber gratings for accurate detection of E. coli bacteria in water.

    PubMed

    Dandapat, Krishnendu; Tripathi, Saurabh Mani; Chinifooroshan, Yasser; Bock, Wojtek J; Mikulic, Predrag

    2016-09-15

    We propose and demonstrate a novel temperature-insensitive bio-sensor for accurate and quantitative detection of Escherichia coli (E. coli) bacteria in water. Surface sensitivity is maximized by operating the long-period fiber grating (LPFG) closest to its turnaround wavelength, and the temperature insensitivity is achieved by selectively exciting a pair of cladding modes with opposite dispersion characteristics. Our sensor shows a nominal temperature sensitivity of ∼1.25  pm/°C, which can be further reduced by properly adjusting the LPFG lengths, while maintaining a high refractive index sensitivity of 1929 nm/RIU. The overall length of the sensor is ∼3.6  cm, making it ideally suitable for bio-sensing applications. As an example, we also show the sensor's capability for reliable, quantitative detection of E. coli bacteria in water over a temperature fluctuation of room temperature to 40°C. PMID:27628356

  7. Fast, accurate, and robust automatic marker detection for motion correction based on oblique kV or MV projection image pairs

    SciTech Connect

    Slagmolen, Pieter; Hermans, Jeroen; Maes, Frederik; Budiharto, Tom; Haustermans, Karin; Heuvel, Frank van den

    2010-04-15

    Purpose: A robust and accurate method that allows the automatic detection of fiducial markers in MV and kV projection image pairs is proposed. The method allows to automatically correct for inter or intrafraction motion. Methods: Intratreatment MV projection images are acquired during each of five treatment beams of prostate cancer patients with four implanted fiducial markers. The projection images are first preprocessed using a series of marker enhancing filters. 2D candidate marker locations are generated for each of the filtered projection images and 3D candidate marker locations are reconstructed by pairing candidates in subsequent projection images. The correct marker positions are retrieved in 3D by the minimization of a cost function that combines 2D image intensity and 3D geometric or shape information for the entire marker configuration simultaneously. This optimization problem is solved using dynamic programming such that the globally optimal configuration for all markers is always found. Translational interfraction and intrafraction prostate motion and the required patient repositioning is assessed from the position of the centroid of the detected markers in different MV image pairs. The method was validated on a phantom using CT as ground-truth and on clinical data sets of 16 patients using manual marker annotations as ground-truth. Results: The entire setup was confirmed to be accurate to around 1 mm by the phantom measurements. The reproducibility of the manual marker selection was less than 3.5 pixels in the MV images. In patient images, markers were correctly identified in at least 99% of the cases for anterior projection images and 96% of the cases for oblique projection images. The average marker detection accuracy was 1.4{+-}1.8 pixels in the projection images. The centroid of all four reconstructed marker positions in 3D was positioned within 2 mm of the ground-truth position in 99.73% of all cases. Detecting four markers in a pair of MV images

  8. PCA feature extraction for change detection in multidimensional unlabeled data.

    PubMed

    Kuncheva, Ludmila I; Faithfull, William J

    2014-01-01

    When classifiers are deployed in real-world applications, it is assumed that the distribution of the incoming data matches the distribution of the data used to train the classifier. This assumption is often incorrect, which necessitates some form of change detection or adaptive classification. While there has been a lot of work on change detection based on the classification error monitored over the course of the operation of the classifier, finding changes in multidimensional unlabeled data is still a challenge. Here, we propose to apply principal component analysis (PCA) for feature extraction prior to the change detection. Supported by a theoretical example, we argue that the components with the lowest variance should be retained as the extracted features because they are more likely to be affected by a change. We chose a recently proposed semiparametric log-likelihood change detection criterion that is sensitive to changes in both mean and variance of the multidimensional distribution. An experiment with 35 datasets and an illustration with a simple video segmentation demonstrate the advantage of using extracted features compared to raw data. Further analysis shows that feature extraction through PCA is beneficial, specifically for data with multiple balanced classes.

  9. No evidence for an item limit in change detection.

    PubMed

    Keshvari, Shaiyan; van den Berg, Ronald; Ma, Wei Ji

    2013-01-01

    Change detection is a classic paradigm that has been used for decades to argue that working memory can hold no more than a fixed number of items ("item-limit models"). Recent findings force us to consider the alternative view that working memory is limited by the precision in stimulus encoding, with mean precision decreasing with increasing set size ("continuous-resource models"). Most previous studies that used the change detection paradigm have ignored effects of limited encoding precision by using highly discriminable stimuli and only large changes. We conducted two change detection experiments (orientation and color) in which change magnitudes were drawn from a wide range, including small changes. In a rigorous comparison of five models, we found no evidence of an item limit. Instead, human change detection performance was best explained by a continuous-resource model in which encoding precision is variable across items and trials even at a given set size. This model accounts for comparison errors in a principled, probabilistic manner. Our findings sharply challenge the theoretical basis for most neural studies of working memory capacity.

  10. Identifying localized changes in large systems: Change-point detection for biomolecular simulations.

    PubMed

    Fan, Zhou; Dror, Ron O; Mildorf, Thomas J; Piana, Stefano; Shaw, David E

    2015-06-16

    Research on change-point detection, the classical problem of detecting abrupt changes in sequential data, has focused predominantly on datasets with a single observable. A growing number of time series datasets, however, involve many observables, often with the property that a given change typically affects only a few of the observables. We introduce a general statistical method that, given many noisy observables, detects points in time at which various subsets of the observables exhibit simultaneous changes in data distribution and explicitly identifies those subsets. Our work is motivated by the problem of identifying the nature and timing of biologically interesting conformational changes that occur during atomic-level simulations of biomolecules such as proteins. This problem has proved challenging both because each such conformational change might involve only a small region of the molecule and because these changes are often subtle relative to the ever-present background of faster structural fluctuations. We show that our method is effective in detecting biologically interesting conformational changes in molecular dynamics simulations of both folded and unfolded proteins, even in cases where these changes are difficult to detect using alternative techniques. This method may also facilitate the detection of change points in other types of sequential data involving large numbers of observables--a problem likely to become increasingly important as such data continue to proliferate in a variety of application domains.

  11. Can Impacts of Climate Change and Agricultural Adaptation Strategies Be Accurately Quantified if Crop Models Are Annually Re-Initialized?

    PubMed Central

    Basso, Bruno; Hyndman, David W.; Kendall, Anthony D.; Grace, Peter R.; Robertson, G. Philip

    2015-01-01

    Estimates of climate change impacts on global food production are generally based on statistical or process-based models. Process-based models can provide robust predictions of agricultural yield responses to changing climate and management. However, applications of these models often suffer from bias due to the common practice of re-initializing soil conditions to the same state for each year of the forecast period. If simulations neglect to include year-to-year changes in initial soil conditions and water content related to agronomic management, adaptation and mitigation strategies designed to maintain stable yields under climate change cannot be properly evaluated. We apply a process-based crop system model that avoids re-initialization bias to demonstrate the importance of simulating both year-to-year and cumulative changes in pre-season soil carbon, nutrient, and water availability. Results are contrasted with simulations using annual re-initialization, and differences are striking. We then demonstrate the potential for the most likely adaptation strategy to offset climate change impacts on yields using continuous simulations through the end of the 21st century. Simulations that annually re-initialize pre-season soil carbon and water contents introduce an inappropriate yield bias that obscures the potential for agricultural management to ameliorate the deleterious effects of rising temperatures and greater rainfall variability. PMID:26043188

  12. Can Impacts of Climate Change and Agricultural Adaptation Strategies Be Accurately Quantified if Crop Models Are Annually Re-Initialized?

    PubMed

    Basso, Bruno; Hyndman, David W; Kendall, Anthony D; Grace, Peter R; Robertson, G Philip

    2015-01-01

    Estimates of climate change impacts on global food production are generally based on statistical or process-based models. Process-based models can provide robust predictions of agricultural yield responses to changing climate and management. However, applications of these models often suffer from bias due to the common practice of re-initializing soil conditions to the same state for each year of the forecast period. If simulations neglect to include year-to-year changes in initial soil conditions and water content related to agronomic management, adaptation and mitigation strategies designed to maintain stable yields under climate change cannot be properly evaluated. We apply a process-based crop system model that avoids re-initialization bias to demonstrate the importance of simulating both year-to-year and cumulative changes in pre-season soil carbon, nutrient, and water availability. Results are contrasted with simulations using annual re-initialization, and differences are striking. We then demonstrate the potential for the most likely adaptation strategy to offset climate change impacts on yields using continuous simulations through the end of the 21st century. Simulations that annually re-initialize pre-season soil carbon and water contents introduce an inappropriate yield bias that obscures the potential for agricultural management to ameliorate the deleterious effects of rising temperatures and greater rainfall variability.

  13. Online change detection: Monitoring land cover from remotely sensed data

    SciTech Connect

    Fang, Yi; Ganguly, Auroop R; Singh, Nagendra; Vijayaraj, Veeraraghavan; Feierabend, Robert Neal; Potere, David T

    2006-01-01

    We present a fast and statistically principled approach to land cover change detection. A reference statistical distribution is fitted to prior data based on off-line analysis, and an adaptive metric based on the exponentially weighted moving average (EWMA) of normal scores derived from p-values are tracked for new or streaming data, leading to alarms for large or sustained change. Methods which can track the origin of the change are also discussed. The approach is illustrated with a geographic application which involves monitoring remotely sensed data to detect changes in the normalized difference vegetation index (NDVI) in near real-time. We use Wal-Mart store openings as a nontraditional way to monitor and validate known cases of NDVI change. The proposed approach performs well on this validation dataset.

  14. Towards a Framework for Change Detection in Data Sets

    NASA Astrophysics Data System (ADS)

    Böttcher, Mirko; Nauck, Detlef; Ruta, Dymitr; Spott, Martin

    Since the world with its markets, innovations and customers is changing faster than ever before, the key to survival for businesses is the ability to detect, assess and respond to changing conditions rapidly and intelligently. Discovering changes and reacting to or acting upon them before others do has therefore become a strategical issue for many companies. However, existing data analysis techniques are insufflent for this task since they typically assume that the domain under consideration is stable over time. This paper presents a framework that detects changes within a data set at virtually any level of granularity. The underlying idea is to derive a rule-based description of the data set at different points in time and to subsequently analyse how these rules change. Nevertheless, further techniques are required to assist the data analyst in interpreting and assessing their changes. Therefore the framework also contains methods to discard rules that are non-drivers for change and to assess the interestingness of detected changes.

  15. SU-E-J-191: Automated Detection of Anatomic Changes in H'N Patients

    SciTech Connect

    Usynin, A; Ramsey, C

    2014-06-01

    Purpose: To develop a novel statistics-based method for automated detection of anatomical changes using cone-beam CT data. A method was developed that can provide a reliable and automated early warning system that enables a “just-in-time” adaptation of the treatment plan. Methods: Anatomical changes were evaluated by comparing the original treatment planning CT with daily CBCT images taken prior treatment delivery. The external body contour was computed on a given CT slice and compared against the corresponding contour on the daily CBCT. In contrast to threshold-based techniques, a statistical approach was employed to evaluate the difference between the contours using a given confidence level. The detection tool used the two-sample Kolmogorov-Smirnov test, which is a non-parametric technique that compares two samples drawn from arbitrary probability distributions. 11 H'N patients were retrospectively selected from a clinical imaging database with a total of 186 CBCT images. Six patients in the database were confirmed to have anatomic changes during the course of radiotherapy. Five of the H'N patients did not have significant changes. The KS test was applied to the contour data using a sliding window analysis. The confidence level of 0.99 was used to moderate false detection. Results: The algorithm was able to correctly detect anatomical changes in 6 out of 6 patients with an excellent spatial accuracy as early as at the 14th elapsed day. The algorithm provided a consistent and accurate delineation of the detected changes. The output of the anatomical change tool is easy interpretable, and can be shown overlaid on a 3D rendering of the patient's anatomy. Conclusion: The detection method provides the basis for one of the key components of Adaptive Radiation Therapy. The method uses tools that are readily available in the clinic, including daily CBCT imaging, and image co-registration facilities.

  16. An Investigation of Automatic Change Detection for Topographic Map Updating

    NASA Astrophysics Data System (ADS)

    Duncan, P.; Smit, J.

    2012-08-01

    Changes to the landscape are constantly occurring and it is essential for geospatial and mapping organisations that these changes are regularly detected and captured, so that map databases can be updated to reflect the current status of the landscape. The Chief Directorate of National Geospatial Information (CD: NGI), South Africa's national mapping agency, currently relies on manual methods of detecting changes and capturing these changes. These manual methods are time consuming and labour intensive, and rely on the skills and interpretation of the operator. It is therefore necessary to move towards more automated methods in the production process at CD: NGI. The aim of this research is to do an investigation into a methodology for automatic or semi-automatic change detection for the purpose of updating topographic databases. The method investigated for detecting changes is through image classification as well as spatial analysis and is focussed on urban landscapes. The major data input into this study is high resolution aerial imagery and existing topographic vector data. Initial results indicate the traditional pixel-based image classification approaches are unsatisfactory for large scale land-use mapping and that object-orientated approaches hold more promise. Even in the instance of object-oriented image classification generalization of techniques on a broad-scale has provided inconsistent results. A solution may lie with a hybrid approach of pixel and object-oriented techniques.

  17. Extended image differencing for change detection in UAV video mosaics

    NASA Astrophysics Data System (ADS)

    Saur, Günter; Krüger, Wolfgang; Schumann, Arne

    2014-03-01

    Change detection is one of the most important tasks when using unmanned aerial vehicles (UAV) for video reconnaissance and surveillance. We address changes of short time scale, i.e. the observations are taken in time distances from several minutes up to a few hours. Each observation is a short video sequence acquired by the UAV in near-nadir view and the relevant changes are, e.g., recently parked or moved vehicles. In this paper we extend our previous approach of image differencing for single video frames to video mosaics. A precise image-to-image registration combined with a robust matching approach is needed to stitch the video frames to a mosaic. Additionally, this matching algorithm is applied to mosaic pairs in order to align them to a common geometry. The resulting registered video mosaic pairs are the input of the change detection procedure based on extended image differencing. A change mask is generated by an adaptive threshold applied to a linear combination of difference images of intensity and gradient magnitude. The change detection algorithm has to distinguish between relevant and non-relevant changes. Examples for non-relevant changes are stereo disparity at 3D structures of the scene, changed size of shadows, and compression or transmission artifacts. The special effects of video mosaicking such as geometric distortions and artifacts at moving objects have to be considered, too. In our experiments we analyze the influence of these effects on the change detection results by considering several scenes. The results show that for video mosaics this task is more difficult than for single video frames. Therefore, we extended the image registration by estimating an elastic transformation using a thin plate spline approach. The results for mosaics are comparable to that of single video frames and are useful for interactive image exploitation due to a larger scene coverage.

  18. An Unsupervised Change Detection Based on Test Statistic and KI from Multi-Temporal and Full Polarimetric SAR Images

    NASA Astrophysics Data System (ADS)

    Zhao, J. Q.; Yang, J.; Li, P. X.; Liu, M. Y.; Shi, Y. M.

    2016-06-01

    Accurate and timely change detection of Earth's surface features is extremely important for understanding relationships and interactions between people and natural phenomena. Many traditional methods of change detection only use a part of polarization information and the supervised threshold selection. Those methods are insufficiency and time-costing. In this paper, we present a novel unsupervised change-detection method based on quad-polarimetric SAR data and automatic threshold selection to solve the problem of change detection. First, speckle noise is removed for the two registered SAR images. Second, the similarity measure is calculated by the test statistic, and automatic threshold selection of KI is introduced to obtain the change map. The efficiency of the proposed method is demonstrated by the quad-pol SAR images acquired by Radarsat-2 over Wuhan of China.

  19. A new maximum-likelihood change estimator for two-pass SAR coherent change detection

    DOE PAGES

    Wahl, Daniel E.; Yocky, David A.; Jakowatz, Jr., Charles V.; Simonson, Katherine Mary

    2016-01-11

    In past research, two-pass repeat-geometry synthetic aperture radar (SAR) coherent change detection (CCD) predominantly utilized the sample degree of coherence as a measure of the temporal change occurring between two complex-valued image collects. Previous coherence-based CCD approaches tend to show temporal change when there is none in areas of the image that have a low clutter-to-noise power ratio. Instead of employing the sample coherence magnitude as a change metric, in this paper, we derive a new maximum-likelihood (ML) temporal change estimate—the complex reflectance change detection (CRCD) metric to be used for SAR coherent temporal change detection. The new CRCD estimatormore » is a surprisingly simple expression, easy to implement, and optimal in the ML sense. As a result, this new estimate produces improved results in the coherent pair collects that we have tested.« less

  20. Folded Compact Range Development and Coherent Change Detection Measurement Project

    SciTech Connect

    Sorensen, K.W.

    1995-03-01

    A novel, folded compact range configuration has been developed at the Sandia National Laboratories compact range antenna and radar cross section measurement facility, operated by the Radar/Antenna Department 2343, as a means of performing indoor, environmentally-controlled, far-field simulations of synthetic aperture radar (SAR) coherent change detection (CCD) measurements. This report describes the development of the folded compact range configuration, as well as the initial set of coherent change detection measurements made with the system. These measurements have been highly successful, and have demonstrated the viability of the folded compact range concept in simulating SAR CCD measurements. It is felt that follow-on measurements have the potential of contributing significantly to the body of knowledge available to the scientific community involved in CCD image generation and processing, and that this tool will be a significant aid in the research and development of change detection methodologies.

  1. Land Cover Change Detection from MODIS Vegetation Index Time Series Data

    NASA Astrophysics Data System (ADS)

    Mithal, V.; O'Connor, Z.; Steinhaeuser, K.; Boriah, S.; Kumar, V.; Potter, C. S.; Klooster, S. A.

    2012-12-01

    Quantifiable knowledge about changes occurring in land cover and land use at a global scale is key to effective planning for sustainable use of diminishing natural resources such as forest cover and agricultural land. Accurate and timely information about land cover and land use changes is therefore of significant interest to earth and climate scientists as well as policy and decision makers. Recently, global time series data sets, such as Moderate Resolution Imaging Spectroradiometer Enhanced Vegetation Index (EVI), have become publicly available and have been used to identify changes in vegetation cover. In this talk, we will discuss our work that analyzes the MODIS EVI time series data sets for global land cover change detection. Our group has developed a suite of time series change detection methods that are used to identify EVI time series with patterns indicative of land cover disturbance such as abrupt or gradual change, or changes in the recurring annual vegetation pattern. These algorithms can successfully identify different land cover change events such as deforestation, forest fires, agricultural conversions, and degradation due to insect damage at a global scale. In context of land cover monitoring, one of the significant challenges is posed by the differences in inter-annual variability and noise characteristics of different land cover types. These data characteristics can significantly impact change detection performance especially in land cover types such as farms, grasslands and tropical forests. We will discuss our recent work that incorporates a bootstrap-based normalization of change detection scores to account for the natural variability present in vegetation time series data. We studied the strengths and weakness of our proposed normalizing approaches in the context of characteristics of land cover data such as seasonality and noise and showed that relative performance of normalization approaches vary significantly depending on the

  2. High resolution/accurate mass (HRMS) detection of anatoxin-a in lake water using LDTD-APCI coupled to a Q-Exactive mass spectrometer.

    PubMed

    Roy-Lachapelle, Audrey; Solliec, Morgan; Sinotte, Marc; Deblois, Christian; Sauvé, Sébastien

    2015-01-01

    A new innovative analytical method combining ultra-fast analysis time with high resolution/accurate mass detection was developed to eliminate the misidentification of anatoxin-a (ANA-a), a cyanobacterial toxin, from the natural amino acid phenylalanine (PHE). This was achieved by using the laser diode thermal desorption-atmospheric pressure chemical ionization (LDTD-APCI) coupled to the Q-Exactive, a high resolution/accurate mass spectrometer (HRMS). This novel combination, the LDTD-APCI-HRMS, allowed for an ultra-fast analysis time (<15 s/sample). A comparison of two different acquisition modes (full scan and targeted ion fragmentation) was made to determine the most rigorous analytical method using the LDTD-APCI interface. Method development focused toward selectivity and sensitivity improvement to reduce the possibility of false positives and to lower detection limits. The Q-Exactive mass spectrometer operates with resolving powers between 17500 and 140000 FWHM (m/z 200). Nevertheless, a resolution of 17500FWHM is enough to dissociate ANA-a and PHE signals. Mass accuracy was satisfactory with values below 1 ppm reaching precision to the fourth decimal. Internal calibration with standard addition was achieved with the isotopically-labeled (D5) phenylalanine with good linearity (R(2)>0.999). Enhancement of signal to noise ratios relative to a standard triple-quadrupole method was demonstrated with lower detection and quantification limit values of 0.2 and 0.6 μg/L using the Q-Exactive. Accuracy and interday/intraday relative standard deviations were below 15%. The new method was applied to 8 different lake water samples with signs of cyanobacterial blooms. This work demonstrates the possibility of using an ultra-fast LDTD-APCI sample introduction system with an HRMS hybrid instrument for quantitative purposes with high selectivity in complex environmental matrices.

  3. Optical and SAR data integration for automatic change pattern detection

    NASA Astrophysics Data System (ADS)

    Mishra, B.; Susaki, J.

    2014-09-01

    Automatic change pattern mapping in urban and sub-urban area is important but challenging due to the diversity of urban land use pattern. With multi-sensor imagery, it is possible to generate multidimensional unique information of Earth surface features that allow developing a relationship between a response of each feature to synthetic aperture radar (SAR) and optical sensors to track the change automatically. Thus, a SAR and optical data integration framework for change detection and a relationship for automatic change pattern detection were developed. It was carried out in three steps: (i) Computation of indicators from SAR and optical images, namely: normalized difference ratio (NDR) from multi-temporal SAR images and the normalized difference vegetation index difference (NDVI) from multi-temporal optical images, (ii) computing the change magnitude image from NDR and ΔNDVI and delineating the change area and (iii) the development of an empirical relationship, for automatic change pattern detection. The experiment was carried out in an outskirts part of Ho Chi Minh City, one of the fastest growing cities in the world. The empirical relationship between the response of surface feature to optical and SAR imagery has successfully delineated six changed classes in a very complex urban sprawl area that was otherwise impossible with multi-spectral imagery. The improvement of the change detection results by making use of the unique information on both sensors, optical and SAR, is also noticeable with a visual inspection and the kappa index was increased by 0.13 (0.75 to 0.88) in comparison to only optical images.

  4. Real-time change detection for countering improvised explosive devices

    NASA Astrophysics Data System (ADS)

    van de Wouw, Dennis W. J. M.; van Rens, Kris; van Lint, Hugo; Jaspers, Egbert G. T.; de With, Peter H. N.

    2014-03-01

    We explore an automatic real-time change detection system to assist military personnel during transport and surveillance, by detection changes in the environment with respect to a previous operation. Such changes may indicate the presence of Improvised Explosive Devices (IEDs), which can then be bypassed. While driving, images of the scenes are acquired by the camera and stored with their GPS positions. At the same time, the best matching reference image (from a previous patrol) is retrieved and registered to the live image. Next a change mask is generated by differencing the reference and live image, followed by an adaptive thresholding technique. Post-processing steps such as Markov Random Fields, local texture comparisons and change tracking, further improve time- and space-consistency of changes and suppress noise. The resulting changes are visualized as an overlay on the live video content. The system has been extensively tested on 28 videos, containing over 10,000 manually annotated objects. The system is capable of detecting small test objects of 10 cm3 at a range of 40 meters. Although the system shows an acceptable performance in multiple cases, the performance degrades under certain circumstances for which extensions are discussed.

  5. Scene change detection for video retrieval on MPEG streams

    NASA Astrophysics Data System (ADS)

    Kang, Eung-Kwan; Kim, Sung-Joo; Jahng, SurngGabb; Song, Ho-Keun; Choi, Jong S.

    2000-05-01

    IN this paper, we propose a new scene change detection (SCD) algorithm, and also provide a novel video-indexing scheme for fast content-based browsing and retrieval in video databases. We detect scene changes from the MPEG video sequence, and extract key frames to represent contents of a shot. Then, we perform the video indexing by applying the rosette pattern to the extracted key frames, and retrieve them. Our SCD method is better than the conventional ones in terms of the SCD performance. Moreover, by applying the rosette pattern for indexing, we can remarkably reduce the number of pixels required to index and excellently retrieve the video scene.

  6. Landsat change detection can aid in water quality monitoring

    NASA Technical Reports Server (NTRS)

    Macdonald, H. C.; Steele, K. F.; Waite, W. P.; Shinn, M. R.

    1977-01-01

    Comparison between Landsat-1 and -2 imagery of Arkansas provided evidence of significant land use changes during the 1972-75 time period. Analysis of Arkansas historical water quality information has shown conclusively that whereas point source pollution generally can be detected by use of water quality data collected by state and federal agencies, sampling methodologies for nonpoint source contamination attributable to surface runoff are totally inadequate. The expensive undertaking of monitoring all nonpoint sources for numerous watersheds can be lessened by implementing Landsat change detection analyses.

  7. Using adversary text to detect adversary phase changes.

    SciTech Connect

    Speed, Ann Elizabeth; Doser, Adele Beatrice; Warrender, Christina E.

    2009-05-01

    The purpose of this work was to help develop a research roadmap and small proof ofconcept for addressing key problems and gaps from the perspective of using text analysis methods as a primary tool for detecting when a group is undergoing a phase change. Self- rganizing map (SOM) techniques were used to analyze text data obtained from the tworld-wide web. Statistical studies indicate that it may be possible to predict phase changes, as well as detect whether or not an example of writing can be attributed to a group of interest.

  8. Sharper detection of winter temperature changes in the Romanian higher-elevations

    NASA Astrophysics Data System (ADS)

    Croitoru, Adina-Eliza; Drignei, Dorin; Dragotă, Carmen Sofia; Imecs, Zoltan; Burada, Doina Cristina

    2014-11-01

    This paper investigates winter temperature trends in the Romanian higher-altitude areas, for three types of topographies: depression, slope and summit. The main challenge is that some winter temperature trends, by comparison with the other seasons, are milder and harder to detect. We used a change-point regression model with statistically dependent errors and compared it with a standard change-point model with independent errors. Statistical theory ensures that the former model gives a more accurate trend analysis than the latter. The model with statistically dependent errors detects change-points in the mid 70s and statistically significant increasing trends both before and after the change-point. On the other hand, the model with independent errors does not detect statistically significant increasing trends after the change-points for the winter series. These general results occur for all topography types. A separate multiple regression model reveals that the winter temperature trend changes in the Romanian higher-elevations can be described by a linear additive effect of several global atmospheric circulation patterns.

  9. Instantaneous dynamic change detection based on three-line-array stereoscopic images of TH-1 satellite

    NASA Astrophysics Data System (ADS)

    Zheng, Tuanjie; Cheng, Jiasheng; Li, Heyuan

    2014-05-01

    TH-1 satellite loading three-line array stereoscopic camera, can scanning 3 times from different directions on the same region or target within the time for about 1 minute, conducive to regional monitoring or target instantaneous change monitoring. Based on the time difference of forward, nadir and backward images of the three-line-array camera of TH-1 Satellite, this paper gives a method to get regional dynamic change image by processing of geometric and physical consistency under the principle of photogrammetry, and to construct the model of change detection by the quantitative results of change detection under the improvement and optimization of noise filtering algorithm. The experimental results show that, by using the detection results of forward, nadir and backward images of the three-line -array camera of TH-1 Satellite, moving distance and velocity can be accurately calculated, and quantitative monitoring of topography changes can be achieved, which not only has temporal resolution, but also can't be achieved by other environmental monitoring satellites. It's significant for flood, fire, clouds, or motion detectors. TH-1 satellite is China's first generation of transmission photogrammetry satellite. With the more satellites networking operation, and higher spatial and temporal resolution, The TH satellites will play a greater role in the field of Earth observation. This article merely uses the principles of photogrammetry to consider photography deformation from different directions, and thorough study will aim at shadow and sun elevation angle, to fully realize the monitoring of changes in topography and moving targets.

  10. Change-point models to estimate the limit of detection.

    PubMed

    May, Ryan C; Chu, Haitao; Ibrahim, Joseph G; Hudgens, Michael G; Lees, Abigail C; Margolis, David M

    2013-12-10

    In many biological and environmental studies, measured data is subject to a limit of detection. The limit of detection is generally defined as the lowest concentration of analyte that can be differentiated from a blank sample with some certainty. Data falling below the limit of detection is left censored, falling below a level that is easily quantified by a measuring device. A great deal of interest lies in estimating the limit of detection for a particular measurement device. In this paper, we propose a change-point model to estimate the limit of detection by using data from an experiment with known analyte concentrations. Estimation of the limit of detection proceeds by a two-stage maximum likelihood method. Extensions are considered that allow for censored measurements and data from multiple experiments. A simulation study is conducted demonstrating that in some settings the change-point model provides less biased estimates of the limit of detection than conventional methods. The proposed method is then applied to data from an HIV pilot study.

  11. Segmentation of Arteries in Minimally Invasive Surgery Using Change Detection

    NASA Astrophysics Data System (ADS)

    Akbari, Hamed; Kosugi, Yukio; Kojima, Kazuyuki

    In laparoscopic surgery, the lack of tactile sensation and 3D visual feedback make it difficult to identify the position of a blood vessel intraoperatively. An unintentional partial tear or complete rupture of a blood vessel may result in a serious complication; moreover, if the surgeon cannot manage this situation, open surgery will be necessary. Differentiation of arteries from veins and other structures and the ability to independently detect them has a variety of applications in surgical procedures involving the head, neck, lung, heart, abdomen, and extremities. We have used the artery's pulsatile movement to detect and differentiate arteries from veins. The algorithm for change detection in this study uses edge detection for unsupervised image registration. Changed regions are identified by subtracting the systolic and diastolic images. As a post-processing step, region properties, including color average, area, major and minor axis lengths, perimeter, and solidity, are used as inputs of the LVQ (Learning Vector Quantization) network. The output results in two object classes: arteries and non-artery regions. After post-processing, arteries can be detected in the laparoscopic field. The registration method used here is evaluated in comparison with other linear and nonlinear elastic methods. The performance of this method is evaluated for the detection of arteries in several laparoscopic surgeries on an animal model and on eleven human patients. The performance evaluation criteria are based on false negative and false positive rates. This algorithm is able to detect artery regions, even in cases where the arteries are obscured by other tissues.

  12. Detection of cardiac activity changes from human speech

    NASA Astrophysics Data System (ADS)

    Tovarek, Jaromir; Partila, Pavol; Voznak, Miroslav; Mikulec, Martin; Mehic, Miralem

    2015-05-01

    Impact of changes in blood pressure and pulse from human speech is disclosed in this article. The symptoms of increased physical activity are pulse, systolic and diastolic pressure. There are many methods of measuring and indicating these parameters. The measurements must be carried out using devices which are not used in everyday life. In most cases, the measurement of blood pressure and pulse following health problems or other adverse feelings. Nowadays, research teams are trying to design and implement modern methods in ordinary human activities. The main objective of the proposal is to reduce the delay between detecting the adverse pressure and to the mentioned warning signs and feelings. Common and frequent activity of man is speaking, while it is known that the function of the vocal tract can be affected by the change in heart activity. Therefore, it can be a useful parameter for detecting physiological changes. A method for detecting human physiological changes by speech processing and artificial neural network classification is described in this article. The pulse and blood pressure changes was induced by physical exercises in this experiment. The set of measured subjects was formed by ten healthy volunteers of both sexes. None of the subjects was a professional athlete. The process of the experiment was divided into phases before, during and after physical training. Pulse, systolic, diastolic pressure was measured and voice activity was recorded after each of them. The results of this experiment describe a method for detecting increased cardiac activity from human speech using artificial neural network.

  13. Climate Change Detection and Attribution of Infrared Spectrum Measurements

    NASA Technical Reports Server (NTRS)

    Phojanamongkolkij, Nipa; Parker, Peter A.; Mlynczak, Martin G.

    2012-01-01

    Climate change occurs when the Earth's energy budget changes due to natural or possibly anthropogenic forcings. These forcings cause the climate system to adjust resulting in a new climate state that is warmer or cooler than the original. The key question is how to detect and attribute climate change. The inference of infrared spectral signatures of climate change has been discussed in the literature for nearly 30 years. Pioneering work in the 1980s noted that distinct spectral signatures would be evident in changes in the infrared radiance emitted by the Earth and its atmosphere, and that these could be observed from orbiting satellites. Since then, a number of other studies have advanced the concepts of spectral signatures of climate change. Today the concept of using spectral signatures to identify and attribute atmospheric composition change is firmly accepted and is the foundation of the Climate Absolute Radiance and Refractivity Observatory (CLARREO) satellite mission being developed at NASA. In this work, we will present an overview of the current climate change detection concept using climate model calculations as surrogates for climate change. Any future research work improving the methodology to achieve this concept will be valuable to our society.

  14. Exponentially Weighted Moving Average Change Detection Around the Country (and the World)

    NASA Astrophysics Data System (ADS)

    Brooks, E.; Wynne, R. H.; Thomas, V. A.; Blinn, C. E.; Coulston, J.

    2014-12-01

    With continuous, freely available moderate-resolution imagery of the Earth's surface available, and with the promise of more imagery to come, change detection based on continuous process models continues to be a major area of research. One such method, exponentially weighted moving average change detection (EWMACD), is based on a mixture of harmonic regression (HR) and statistical quality control, a branch of statistics commonly used to detect aberrations in industrial and medical processes. By using HR to approximate per-pixel seasonal curves, the resulting residuals characterize information about the pixels which stands outside of the periodic structure imposed by HR. Under stable pixels, these residuals behave as might be expected, but in the presence of changes (growth, stress, removal), the residuals clearly show these changes when they are used as inputs into an EWMA chart. In prior work in Alabama, USA, EWMACD yielded an overall accuracy of 85% on a random sample of known thinned stands, in some cases detecting thinnings as sparse as 25% removal. It was also shown to correctly identify the timing of the thinning activity, typically within a single image date of the change. The net result of the algorithm was to produce date-by-date maps of afforestation and deforestation on a variable scale of severity. In other research, EWMACD has also been applied to detect land use and land cover changes in central Java, Indonesia, despite the heavy incidence of clouds and a monsoonal climate. Preliminary results show that EWMACD accurately identifies land use conversion (agricultural to residential, for example) and also identifies neighborhoods where the building density has increased, removing neighborhood vegetation. In both cases, initial results indicate the potential utility of EWMACD to detect both gross and subtle ecosystem disturbance, but further testing across a range of ecosystems and disturbances is clearly warranted.

  15. Detecting human influence in observed changes in precipitation

    NASA Astrophysics Data System (ADS)

    Polson, Debbie; Hegerl, Gabriele; Bollasina, Massimo; Wilcox, Laura; Zhang, Xuebin; Osborn, Timothy; Balan Sarojini, Beena

    2015-04-01

    Human induced changes to the precipitation could cause some of the most serious impacts of climate change, with potential consequences for water resources, health, agriculture and ecosystems. However, quantifying and understanding the drivers of changes to precipitation is challenging due to its large spatial and temporal variability, the lack of long-term observational records over much of the globe and the counteracting affects of greenhouse gases and aerosols. Nevertheless, detection and attribution studies have shown that human influence has changed both global and regional precipitation over the latter half of the 20th century. Using climates models to derive fingerprints of external forcing, we are able to show that greenhouse gas warming has driven large scale changes in precipitation. Greenhouse gas forcing is detectable in observed changes to zonal mean precipitation over land (Polson et al., 2012a). It has also been shown to have caused the intensification of the water cycle, enhancing existing patterns of the precipitation in the tropics and subtropics, over both land and ocean (Polson et al., 2012b). While at global scales, the influence of greenhouse gases is detectable in observations, separating the response of precipitation to anthropogenic aerosol forcing is more difficult. However, in some regions the influence of aerosols dominate, making it possible to detect aerosol forcing. Observed precipitation in the monsoon regions underwent substantial changes during the second half of the twentieth century, with drying from the 1950s to mid-1980s and increasing precipitation in recent decades. Climate model simulations are used to derive fingerprints of individual climate forcings (i.e., greenhouse gas, anthropogenic aerosol, and natural) and detection and attribution methods applied to determine which, if any, have driven these changes to monsoon precipitation. Even when accounting for internal variability of the climate, a clear signal of anthropogenic

  16. 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.

  17. The fate of object memory traces under change detection and change blindness.

    PubMed

    Busch, Niko A

    2013-07-01

    Observers often fail to detect substantial changes in a visual scene. This so-called change blindness is often taken as evidence that visual representations are sparse and volatile. This notion rests on the assumption that the failure to detect a change implies that representations of the changing objects are lost all together. However, recent evidence suggests that under change blindness, object memory representations may be formed and stored, but not retrieved. This study investigated the fate of object memory representations when changes go unnoticed. Participants were presented with scenes consisting of real world objects, one of which changed on each trial, while recording event-related potentials (ERPs). Participants were first asked to localize where the change had occurred. In an additional recognition task, participants then discriminated old objects, either from the pre-change or the post-change scene, from entirely new objects. Neural traces of object memories were studied by comparing ERPs for old and novel objects. Participants performed poorly in the detection task and often failed to recognize objects from the scene, especially pre-change objects. However, a robust old/novel effect was observed in the ERP, even when participants were change blind and did not recognize the old object. This implicit memory trace was found both for pre-change and post-change objects. These findings suggest that object memories are stored even under change blindness. Thus, visual representations may not be as sparse and volatile as previously thought. Rather, change blindness may point to a failure to retrieve and use these representations for change detection.

  18. Remote sensing of debris-covered glaciers: Change detection and analysis using multiple sensors

    NASA Astrophysics Data System (ADS)

    Ahn, Y.; Huh, K.; Mark, B. G.; La Frenierre, J.; Gulley, J. D.; Park, K.

    2013-12-01

    Debris-cover can insulate glaciers and hinder surface melting, but also challenges accurate assessment of change detection and subsequent risk evaluation of outburst floods from moraine-dammed supra-glacial lakes that endanger downstream inhabitants. These events have been predicted to increase frequency along with the coverage of debris as warming accelerates. Enhanced monitoring capability from optical air and space-borne sensors has improved the detection of changes in surface-derived characteristics such as areal and volumetric fluctuations as well as glacier velocity over debris-covered glaciers, improving the accuracy of geometric and temporal resolutions in hydrological analysis. In this study we present case studies from Nepal, Peru and Ecuador focusing on: 1) time series of debris-coverage and moraine-dammed lakes; and 2) the relationship of remotely sensed observable quantities from different sensors such as aerial photographs, ASTER, Landsat imagery and Airborne/Terrestrial Laser Scanner.

  19. Detecting changes in terrain using unmanned aerial vehicles

    NASA Astrophysics Data System (ADS)

    Rahman, Zia-ur; Hines, Glenn D.; Logan, Michael J.

    2005-05-01

    In recent years, small unmanned aerial vehicles (UAVs) have been used for more than the thrill they bring to model airplane enthusiasts. Their flexibility and low cost have made them a viable option for low-altitude reconnaissance. In a recent effort, we acquired video data from a small UAV during several passes over the same flight path. The objective of the exercise was to determine if objects had been added to the terrain along the flight path between flight passes. Several issues accrue to this simple-sounding problem: (1) lighting variations may cause false detection of objects because of changes in shadow orientation and strength between passes; (2) variations in the flight path due to wind-speed, and heading change may cause misalignment of gross features making the task of detecting changes between the frames very difficult; and (3) changes in the aircraft orientation and altitude lead to a change in size of the features from frame-to-frame making a comparison difficult. In this paper, we discuss our efforts to perform this change detection, and the lessons that we learned from this exercise.

  20. The potential of inductively coupled plasma mass spectrometry detection for high-performance liquid chromatography combined with accurate mass measurement of organic pharmaceutical compounds.

    PubMed

    Axelsson, B O; Jörnten-Karlsson, M; Michelsen, P; Abou-Shakra, F

    2001-01-01

    Quantification of unknown components in pharmaceutical, metabolic and environmental samples is an important but difficult task. Most commonly used detectors (like UV, RI or MS) require standards of each analyte for accurate quantification. Even if the chemical structure or elemental composition is known, the response from these detectors is difficult to predict with any accuracy. In inductively coupled plasma mass spectrometry (ICP-MS) compounds are atomised and ionised irrespective of the chemical structure(s) incorporating the element of interest. Liquid chromatography coupled with inductively coupled plasma mass spectrometry (LC/ICP-MS) has been shown to provide a generic detection for structurally non-correlated compounds with common elements like phosphorus and iodine. Detection of selected elements gives a better quantification of tested 'unknowns' than UV and organic mass spectrometric detection. It was shown that the ultrasonic nebuliser did not introduce any measurable dead volume and preserves the separation efficiency of the system. ICP-MS can be used in combination with many different mobile phases ranging from 0-100% organic modifier. The dynamic range was found to exceed 2.5 orders of magnitude. The application of LC/ICP-MS to pharmaceutical drugs and formulations has shown that impurities can be quantified below the 0.1 mol-% level.

  1. Detection and quantitation of trace phenolphthalein (in pharmaceutical preparations and in forensic exhibits) by liquid chromatography-tandem mass spectrometry, a sensitive and accurate method.

    PubMed

    Sharma, Kakali; Sharma, Shiba P; Lahiri, Sujit C

    2013-01-01

    Phenolphthalein, an acid-base indicator and laxative, is important as a constituent of widely used weight-reducing multicomponent food formulations. Phenolphthalein is an useful reagent in forensic science for the identification of blood stains of suspected victims and for apprehending erring officials accepting bribes in graft or trap cases. The pink-colored alkaline hand washes originating from the phenolphthalein-smeared notes can easily be determined spectrophotometrically. But in many cases, colored solution turns colorless with time, which renders the genuineness of bribe cases doubtful to the judiciary. No method is known till now for the detection and identification of phenolphthalein in colorless forensic exhibits with positive proof. Liquid chromatography-tandem mass spectrometry had been found to be most sensitive, accurate method capable of detection and quantitation of trace phenolphthalein in commercial formulations and colorless forensic exhibits with positive proof. The detection limit of phenolphthalein was found to be 1.66 pg/L or ng/mL, and the calibration curve shows good linearity (r(2) = 0.9974). PMID:23106487

  2. A change detection approach to moving object detection in low frame-rate video

    SciTech Connect

    Porter, Reid B; Harvey, Neal R; Theiler, James P

    2009-01-01

    Moving object detection is of significant interest in temporal image analysis since it is a first step in many object identification and tracking applications. A key component in almost all moving object detection algorithms is a pixel-level classifier, where each pixel is predicted to be either part of a moving object or part of the background. In this paper we investigate a change detection approach to the pixel-level classification problem and evaluate its impact on moving object detection. The change detection approach that we investigate was previously applied to multi-and hyper-spectral datasets, where images were typically taken several days, or months apart. In this paper, we apply the approach to low-frame rate (1-2 frames per second) video datasets.

  3. Helicopter Based Magnetic Detection Of Wells At The Teapot Dome (Naval Petroleum Reserve No. 3 Oilfield: Rapid And Accurate Geophysical Algorithms For Locating Wells

    NASA Astrophysics Data System (ADS)

    Harbert, W.; Hammack, R.; Veloski, G.; Hodge, G.

    2011-12-01

    In this study Airborne magnetic data was collected by Fugro Airborne Surveys from a helicopter platform (Figure 1) using the Midas II system over the 39 km2 NPR3 (Naval Petroleum Reserve No. 3) oilfield in east-central Wyoming. The Midas II system employs two Scintrex CS-2 cesium vapor magnetometers on opposite ends of a transversely mounted, 13.4-m long horizontal boom located amidships (Fig. 1). Each magnetic sensor had an in-flight sensitivity of 0.01 nT. Real time compensation of the magnetic data for magnetic noise induced by maneuvering of the aircraft was accomplished using two fluxgate magnetometers mounted just inboard of the cesium sensors. The total area surveyed was 40.5 km2 (NPR3) near Casper, Wyoming. The purpose of the survey was to accurately locate wells that had been drilled there during more than 90 years of continuous oilfield operation. The survey was conducted at low altitude and with closely spaced flight lines to improve the detection of wells with weak magnetic response and to increase the resolution of closely spaced wells. The survey was in preparation for a planned CO2 flood to enhance oil recovery, which requires a complete well inventory with accurate locations for all existing wells. The magnetic survey was intended to locate wells that are missing from the well database and to provide accurate locations for all wells. The well location method used combined an input dataset (for example, leveled total magnetic field reduced to the pole), combined with first and second horizontal spatial derivatives of this input dataset, which were then analyzed using focal statistics and finally combined using a fuzzy combination operation. Analytic signal and the Shi and Butt (2004) ZS attribute were also analyzed using this algorithm. A parameter could be adjusted to determine sensitivity. Depending on the input dataset 88% to 100% of the wells were located, with typical values being 95% to 99% for the NPR3 field site.

  4. Environmental Change Detection Using Multi-Temporal SAR Imagery

    NASA Astrophysics Data System (ADS)

    Fazel, Mohammad A.; Homayouni, Saeid; Aghakarimi, Armin

    2013-04-01

    Monitoring of environmental phenomena in short-, mid- and long-term periods is the first step of any study or plan for natural resource management. As a result, detection and identification of the environmental changes became a main area of research for different applications. Remotely sensed data and especially Synthetic Aperture Radar (SAR) imagery thanks to its independence to weather conditions and sun illumination, and its spatial and temporal resolution ability is a valuable source of information for change detection analysis and provides reliable data for information extraction for various applications. In general, change detection methods are grouped into supervised and unsupervised methods. Supervised methods work based on multi-temporal land-cover mapping of satellite images. While, unsupervised techniques include the very simple idea of image differencing to more sophisticated statistical modeling of changes in images. Unsupervised methods because of their advantages are more important in many applications. In recent years, the use of kernel based methods in change detection applications became an interesting topic in remote sensing community. Kernel-based methods and machine learning algorithms are the unsupervised paradigms which introduced powerful tools to deal with nonlinear classification. In this paper, we have presented a fully unsupervised framework for detecting the Urmia Lake changes during 2007 to 2010. This method uses the kernel-based clustering technique. The kernel k-means algorithm separates the changes from no-change classes of speckle free images. This method is a non-linear algorithm which considers the contextual information. For this purpose, at first, difference maps are calculated from multi-temporal data. Then these maps are projected into a higher dimensional space by using kernel function. Finally an unsupervised k-means clustering algorithm is used to obtain change and no-change classes. The proposed methodology is applied to

  5. Detection of epigenetic changes using ANOVA with spatially varying coefficients.

    PubMed

    Guanghua, Xiao; Xinlei, Wang; Quincey, LaPlant; Nestler, Eric J; Xie, Yang

    2013-03-13

    Identification of genome-wide epigenetic changes, the stable changes in gene function without a change in DNA sequence, under various conditions plays an important role in biomedical research. High-throughput epigenetic experiments are useful tools to measure genome-wide epigenetic changes, but the measured intensity levels from these high-resolution genome-wide epigenetic profiling data are often spatially correlated with high noise levels. In addition, it is challenging to detect genome-wide epigenetic changes across multiple conditions, so efficient statistical methodology development is needed for this purpose. In this study, we consider ANOVA models with spatially varying coefficients, combined with a hierarchical Bayesian approach, to explicitly model spatial correlation caused by location-dependent biological effects (i.e., epigenetic changes) and borrow strength among neighboring probes to compare epigenetic changes across multiple conditions. Through simulation studies and applications in drug addiction and depression datasets, we find that our approach compares favorably with competing methods; it is more efficient in estimation and more effective in detecting epigenetic changes. In addition, it can provide biologically meaningful results.

  6. Detecting forest canopy change due to insect activity using Landsat MSS

    NASA Technical Reports Server (NTRS)

    Nelson, R. F.

    1983-01-01

    Multitemporal Landsat multispectral scanner data were analyzed to test various computer-aided analysis techniques for detecting significant forest canopy alteration. Three data transformations - differencing, ratioing, and a vegetative index difference - were tested to determine which best delineated gypsy moth defoliation. Response surface analyses were conducted to determine optimal threshold levels for the individual transformed bands and band combinations. Results indicate that, of the three transformations investigated, a vegetative index difference (VID) transformation most accurately delineates forest canopy change. Band 5 (0.6 to 0.7 micron ratioed data did nearly as well. However, other single bands and band combinations did not improve upon the band 5 ratio and VID results.

  7. Climate change and the detection of trends in annual runoff

    USGS Publications Warehouse

    McCabe, G.J., Jr.; Wolock, D.M.

    1997-01-01

    This study examines the statistical likelihood of detecting a trend in annual runoff given an assumed change in mean annual runoff, the underlying year-to-year variability in runoff, and serial correlation of annual runoff. Means, standard deviations, and lag-1 serial correlations of annual runoff were computed for 585 stream gages in the conterminous United States, and these statistics were used to compute the probability of detecting a prescribed trend in annual runoff. Assuming a linear 20% change in mean annual runoff over a 100 yr period and a significance level of 95%, the average probability of detecting a significant trend was 28% among the 585 stream gages. The largest probability of detecting a trend was in the northwestern U.S., the Great Lakes region, the northeastern U.S., the Appalachian Mountains, and parts of the northern Rocky Mountains. The smallest probability of trend detection was in the central and southwestern U.S., and in Florida. Low probabilities of trend detection were associated with low ratios of mean annual runoff to the standard deviation of annual runoff and with high lag-1 serial correlation in the data.

  8. Robust Detection of Examinees with Aberrant Answer Changes

    ERIC Educational Resources Information Center

    Belov, Dmitry I.

    2015-01-01

    The statistical analysis of answer changes (ACs) has uncovered multiple testing irregularities on large-scale assessments and is now routinely performed at testing organizations. However, AC data has an uncertainty caused by technological or human factors. Therefore, existing statistics (e.g., number of wrong-to-right ACs) used to detect examinees…

  9. Improved forest change detection with terrain illumination corrected landsat images

    Technology Transfer Automated Retrieval System (TEKTRAN)

    An illumination correction algorithm has been developed to improve the accuracy of forest change detection from Landsat reflectance data. This algorithm is based on an empirical rotation model and was tested on the Landsat imagery pair over Cherokee National Forest, Tennessee, Uinta-Wasatch-Cache N...

  10. Cryosphere Change Detection With The Autonomous Sciencecraft Experiment

    NASA Astrophysics Data System (ADS)

    Davies, A. G.; Doggett, T. C.

    2006-05-01

    The Autonomous Sciencecraft Experiment (ASE) is operating on-board Earth Observing - 1 (EO-1) with the Hyperion hyper-spectral visible to short-wave infrared spectrometer. ASE science activities include autonomous monitoring of cryospheric changes, triggering the collection of additional data when change is detected and filtering of null data such as no change or cloud cover. A cryosphere classification algorithm, developed with Support Vector Machine (SVM) machine learning techniques [1], replacing a manually derived classifier used in earlier operations [2], has been used in conjunction with on-board autonomous software application to execute over two hundred on-board scenarios in 2005 and early 2006, to detect and autonomously respond to sea ice break-up and formation, lake freeze and thaw, as well as the onset and melting of snow cover on land. This demonstrates an approach which could be applied to the monitoring of cryospheres on Earth and Mars as well as the search for dynamic activity on the icy moons of the outer solar system. [1] Castano et al. (2005) Learning classifiers for event detection in remote sensing imagery, i-SAIRAS, [2] Doggett et al. (2006), Autonomous detection of cryospheric change with Hyperion on-board Earth Observing-1, Rem. Sens. Env. (in press)

  11. Groundwater storage change detection using micro-gravimetric technology

    NASA Astrophysics Data System (ADS)

    El-Diasty, Mohammed

    2016-06-01

    In this paper, new perspectives and developments in applying a ground-based micro-gravimetric method to detect groundwater storage change in Waterloo Moraine are investigated. Four epochs of gravity survey were conducted using absolute gravimeter (FG5), two relative gravity meters (CG5) and two geodetic global positioning systems (GPS) in the Waterloo Moraine in May and August of 2010 and 2011, respectively. Data were processed using the parametric least-squares method and integrated with geological and hydrological studies. The gravity differences between May and August for 2010 and 2011 epochs were inverted to provide the estimated total water storage changes. Changes in soil water content obtained from land surface models of Ecological Assimilation of Land and Climate Observations (EALCO) and the Global Land Data Assimilation System (GLDAS) program were employed to estimate the groundwater storage change. The ratios between the estimated groundwater storage changes and measured water table changes (specific yields) were determined at a local monitoring well located in the survey area. The results showed that the estimates of specific yields between May and August of 2010 and 2011 were consistent at a significant confidence level and are also within the range of the specific yield from geological and hydrological studies. Therefore, the micro-gravimetric (absolute and relative gravity meters) technology has demonstrated the great potential in detecting groundwater storage change and specific yield for local scale aquifers such as Waterloo Moraine.

  12. Silicon chips detect intracellular pressure changes in living cells.

    PubMed

    Gómez-Martínez, Rodrigo; Hernández-Pinto, Alberto M; Duch, Marta; Vázquez, Patricia; Zinoviev, Kirill; de la Rosa, Enrique J; Esteve, Jaume; Suárez, Teresa; Plaza, José A

    2013-07-01

    The ability to measure pressure changes inside different components of a living cell is important, because it offers an alternative way to study fundamental processes that involve cell deformation. Most current techniques such as pipette aspiration, optical interferometry or external pressure probes use either indirect measurement methods or approaches that can damage the cell membrane. Here we show that a silicon chip small enough to be internalized into a living cell can be used to detect pressure changes inside the cell. The chip, which consists of two membranes separated by a vacuum gap to form a Fabry-Pérot resonator, detects pressure changes that can be quantified from the intensity of the reflected light. Using this chip, we show that extracellular hydrostatic pressure is transmitted into HeLa cells and that these cells can endure hypo-osmotic stress without significantly increasing their intracellular hydrostatic pressure.

  13. Silicon chips detect intracellular pressure changes in living cells

    NASA Astrophysics Data System (ADS)

    Gómez-Martínez, Rodrigo; Hernández-Pinto, Alberto M.; Duch, Marta; Vázquez, Patricia; Zinoviev, Kirill; de La Rosa, Enrique J.; Esteve, Jaume; Suárez, Teresa; Plaza, José A.

    2013-07-01

    The ability to measure pressure changes inside different components of a living cell is important, because it offers an alternative way to study fundamental processes that involve cell deformation. Most current techniques such as pipette aspiration, optical interferometry or external pressure probes use either indirect measurement methods or approaches that can damage the cell membrane. Here we show that a silicon chip small enough to be internalized into a living cell can be used to detect pressure changes inside the cell. The chip, which consists of two membranes separated by a vacuum gap to form a Fabry-Pérot resonator, detects pressure changes that can be quantified from the intensity of the reflected light. Using this chip, we show that extracellular hydrostatic pressure is transmitted into HeLa cells and that these cells can endure hypo-osmotic stress without significantly increasing their intracellular hydrostatic pressure.

  14. PNA-based microbial pathogen identification and resistance marker detection: an accurate, isothermal rapid assay based on genome-specific features

    PubMed Central

    Smolina, Irina; Miller, Nancy S.; Frank-Kamenetskii, Maxim

    2010-01-01

    With the rapidly growing availability of the entire genome sequences of microbial pathogens, there is unmet need for increasingly sensitive systems to monitor the gene-specific markers for diagnosis of bacteremia that enables an earlier detection of causative agent and determination of drug resistance. To address these challenges, a novel FISH-type genomic sequence-based molecular technique is proposed that can identify bacteria and simultaneously detect antibiotic resistance markers for rapid and accurate testing of pathogens. The approach is based on a synergistic combination of advanced Peptide Nucleic Acid (PNA)-based technology and signal-enhancing Rolling Circle Amplification (RCA) reaction to achieve a highly specific and sensitive assay. A specific PNA-DNA construct serves as an exceedingly selective and very effective biomarker, while RCA enhances detection sensitivity and provide with a highly multiplexed assay system. Distinct-color fluorescent decorator probes are used to identify about 20-nucleotide-long signature sequences in bacterial genomic DNA and/or key genetic markers of drug resistance in order to identify and characterize various pathogens. The technique's potential and its utility for clinical diagnostics are illustrated by identification of S. aureus with simultaneous discrimination of methicillin-sensitive (MSSA) versus methicillin-resistant (MRSA) strains. Overall these promising results hint to the adoption of PNA-based rapid sensitive detection for diagnosis of other clinically relevant organisms. Thereby, new assay enables significantly earlier administration of appropriate antimicrobial therapy and may, thus have a positive impact on the outcome of the patient. PMID:20953307

  15. Change detection is impaired in children with dyslexia.

    PubMed

    Rutkowski, Jacqueline S; Crewther, David P; Crewther, Sheila G

    2003-01-01

    The severe deficits in rapid automatized naming demonstrated by children with developmental dyslexia has usually been interpreted in terms of a deficit in speed of access to the lexicon rather than as a possible deficit in speed of visual object recognition. Yet fluent reading requires rapid visual recognition and semantic interpretation of new letters and words appearing in successive fixations of the eyes. Thus we wondered whether change detection performance was related to reading ability. We investigated whether children with developmental dyslexia (DD) were less able to detect change in a simple display--gap--display paradigm than normal reading (NR) children of the same age and children with impaired reading and mentation (LD). In a first experimental phase, the DDs required a longer initial exposure of four letter items in order to detect change of a single letter at a level of 71% correct, compared with NRs performing at the same level. Thus the deficit in reading in DD is associated with a deficit in early processes associated with visual recognition. In a second experimental phase (using the individual target display exposures measured in the first phase), cues appeared during the 250 ms gap for a period of either 0 (no cue), 50 or 200 ms immediately prior to the presentation of the second (comparison) display. Children of all groups showed dependence on the presence of the cue to help make a judgement of change (versus no change), with the NRs least affected. When change was detected in the presence of a cue, the NRs were better able to identify the new letter than either of the other groups. However, only about 50% of the correct detections were accompanied by a correct identification. Despite published reports of a mini-neglect for left visual field in dyslexic adults, none of our groups showed such an effect. However, a significant upper visual field (UpVF) advantage in change detection performance was found across groups, which we interpret in terms

  16. Aircraft MSS data registration and vegetation classification of wetland change detection

    USGS Publications Warehouse

    Christensen, E.J.; Jensen, J.R.; Ramsey, Elijah W.; Mackey, H.E.

    1988-01-01

    Portions of the Savannah River floodplain swamp were evaluated for vegetation change using high resolution (5a??6 m) aircraft multispectral scanner (MSS) data. Image distortion from aircraft movement prevented precise image-to-image registration in some areas. However, when small scenes were used (200-250 ha), a first-order linear transformation provided registration accuracies of less than or equal to one pixel. A larger area was registered using a piecewise linear method. Five major wetland classes were identified and evaluated for change. Phenological differences and the variable distribution of vegetation limited wetland type discrimination. Using unsupervised methods and ground-collected vegetation data, overall classification accuracies ranged from 84 per cent to 87 per cent for each scene. Results suggest that high-resolution aircraft MSS data can be precisely registered, if small areas are used, and that wetland vegetation change can be accurately detected and monitored.

  17. A targeted change-detection procedure by combining change vector analysis and post-classification approach

    NASA Astrophysics Data System (ADS)

    Ye, Su; Chen, Dongmei; Yu, Jie

    2016-04-01

    In remote sensing, conventional supervised change-detection methods usually require effective training data for multiple change types. This paper introduces a more flexible and efficient procedure that seeks to identify only the changes that users are interested in, here after referred to as "targeted change detection". Based on a one-class classifier "Support Vector Domain Description (SVDD)", a novel algorithm named "Three-layer SVDD Fusion (TLSF)" is developed specially for targeted change detection. The proposed algorithm combines one-class classification generated from change vector maps, as well as before- and after-change images in order to get a more reliable detecting result. In addition, this paper introduces a detailed workflow for implementing this algorithm. This workflow has been applied to two case studies with different practical monitoring objectives: urban expansion and forest fire assessment. The experiment results of these two case studies show that the overall accuracy of our proposed algorithm is superior (Kappa statistics are 86.3% and 87.8% for Case 1 and 2, respectively), compared to applying SVDD to change vector analysis and post-classification comparison.

  18. Global scene layout modulates contextual learning in change detection.

    PubMed

    Conci, Markus; Müller, Hermann J

    2014-01-01

    Change in the visual scene often goes unnoticed - a phenomenon referred to as "change blindness." This study examined whether the hierarchical structure, i.e., the global-local layout of a scene can influence performance in a one-shot change detection paradigm. To this end, natural scenes of a laid breakfast table were presented, and observers were asked to locate the onset of a new local object. Importantly, the global structure of the scene was manipulated by varying the relations among objects in the scene layouts. The very same items were either presented as global-congruent (typical) layouts or as global-incongruent (random) arrangements. Change blindness was less severe for congruent than for incongruent displays, and this congruency benefit increased with the duration of the experiment. These findings show that global layouts are learned, supporting detection of local changes with enhanced efficiency. However, performance was not affected by scene congruency in a subsequent control experiment that required observers to localize a static discontinuity (i.e., an object that was missing from the repeated layouts). Our results thus show that learning of the global layout is particularly linked to the local objects. Taken together, our results reveal an effect of "global precedence" in natural scenes. We suggest that relational properties within the hierarchy of a natural scene are governed, in particular, by global image analysis, reducing change blindness for local objects through scene learning.

  19. Statistical method for detecting structural change in the growth process.

    PubMed

    Ninomiya, Yoshiyuki; Yoshimoto, Atsushi

    2008-03-01

    Due to competition among individual trees and other exogenous factors that change the growth environment, each tree grows following its own growth trend with some structural changes in growth over time. In the present article, a new method is proposed to detect a structural change in the growth process. We formulate the method as a simple statistical test for signal detection without constructing any specific model for the structural change. To evaluate the p-value of the test, the tube method is developed because the regular distribution theory is insufficient. Using two sets of tree diameter growth data sampled from planted forest stands of Cryptomeria japonica in Japan, we conduct an analysis of identifying the effect of thinning on the growth process as a structural change. Our results demonstrate that the proposed method is useful to identify the structural change caused by thinning. We also provide the properties of the method in terms of the size and power of the test. PMID:17608782

  20. Panel-based Genetic Diagnostic Testing for Inherited Eye Diseases is Highly Accurate and Reproducible and More Sensitive for Variant Detection Than Exome Sequencing

    PubMed Central

    Bujakowska, Kinga M.; Sousa, Maria E.; Fonseca-Kelly, Zoë D.; Taub, Daniel G.; Janessian, Maria; Wang, Dan Yi; Au, Elizabeth D.; Sims, Katherine B.; Sweetser, David A.; Fulton, Anne B.; Liu, Qin; Wiggs, Janey L.; Gai, Xiaowu; Pierce, Eric A.

    2015-01-01

    Purpose Next-generation sequencing (NGS) based methods are being adopted broadly for genetic diagnostic testing, but the performance characteristics of these techniques have not been fully defined with regard to test accuracy and reproducibility. Methods We developed a targeted enrichment and NGS approach for genetic diagnostic testing of patients with inherited eye disorders, including inherited retinal degenerations, optic atrophy and glaucoma. In preparation for providing this Genetic Eye Disease (GEDi) test on a CLIA-certified basis, we performed experiments to measure the sensitivity, specificity, reproducibility as well as the clinical sensitivity of the test. Results The GEDi test is highly reproducible and accurate, with sensitivity and specificity for single nucleotide variant detection of 97.9% and 100%, respectively. The sensitivity for variant detection was notably better than the 88.3% achieved by whole exome sequencing (WES) using the same metrics, due to better coverage of targeted genes in the GEDi test compared to commercially available exome capture sets. Prospective testing of 192 patients with IRDs indicated that the clinical sensitivity of the GEDi test is high, with a diagnostic rate of 51%. Conclusion The data suggest that based on quantified performance metrics, selective targeted enrichment is preferable to WES for genetic diagnostic testing. PMID:25412400

  1. Accurate mass determination, quantification and determination of detection limits in liquid chromatography-high-resolution time-of-flight mass spectrometry: challenges and practical solutions.

    PubMed

    Vergeynst, Leendert; Van Langenhove, Herman; Joos, Pieter; Demeestere, Kristof

    2013-07-30

    Uniform guidelines for the data processing and validation of qualitative and quantitative multi-residue analysis using full-spectrum high-resolution mass spectrometry are scarce. Through systematic research, optimal mass accuracy and sensitivity are obtained after refining the post-processing of the HRMS data. For qualitative analysis, transforming the raw profile spectra to centroid spectra is recommended resulting in a 2.3 fold improved precision on the accurate mass determination of spectrum peaks. However, processing centroid data for quantitative purposes could lead to signal interruption when too narrow mass windows are applied for the construction of extracted ion chromatograms. Therefore, peak integration on the raw profile data is recommended. An optimal width of the mass window of 50 ppm, which is a trade-off between sensitivity and selectivity, was obtained for a TOF instrument providing a resolving power of 20,000 at full width at half maximum (FWHM). For the validation of HRMS analytical methods, widespread concepts such as the signal-to-noise ratios for the determination of decision limits and detection capabilities have shown to be not always applicable because in some cases almost no noise can be detected anymore. A statistical methodology providing a reliable alternative is extended and applied. PMID:23856232

  2. Object-Based Change Detection Using Georeferenced Uav Images

    NASA Astrophysics Data System (ADS)

    Shi, J.; Wang, J.; Xu, Y.

    2011-09-01

    Unmanned aerial vehicles (UAV) have been widely used to capture and down-link real-time videos/images. However, their role as a low-cost airborne platform for capturing high-resolution, geo-referenced still imagery has not been fully utilized. The images obtained from UAV are advantageous over remote sensing images as they can be obtained at a low cost and potentially no risk to human life. However, these images are distorted due to the noise generated by the rotary wings which limits the usefulness of such images. One potential application of such images is to detect changes between the images of the same area which are collected over time. Change detection is of widespread interest due to a large number of applications, including surveillance and civil infrastructure. Although UAVs can provide images with high resolution in a portable and easy way, such images only cover small parts of the entire field of interest and are often with high deformation. Until now, there is not much application of change detection for UAV images. Also the traditional pixel-based change detection method does not give satisfactory results for such images. In this paper, we have proposed a novel object-based method for change detection using UAV images which can overcome the effect of deformation and can fully utilize the high resolution capability of UAV images. The developed method can be divided into five main blocks: pre-processing, image matching, image segmentation and feature extraction, change detection and accuracy evaluation. The pre-processing step is further divided into two sub-steps: the first sub-step is to geometrically correct the bi-temporal image based on the geo-reference information (GPS/INS) installed on the UAV system, and the second sub-step is the radiometric normalization using a histogram method. The image matching block uses the well-known scale-invariant feature transform (SIFT) algorithm to match the same areas in the images and then resample them. The

  3. Automatic analysis of the slight change image for unsupervised change detection

    NASA Astrophysics Data System (ADS)

    Yang, Jilian; Sun, Weidong

    2015-01-01

    We propose an unsupervised method for slight change extraction and detection in multitemporal hyperspectral image sequence. To exploit the spectral signatures in hyperspectral images, autoregressive integrated moving average and fitting models are employed to create a prediction of single-band and multiband time series. Minimum mean absolute error index is then applied to obtain the preliminary change information image (PCII), which contains slight change information. After that, feature vectors are created for each pixel in the PCII using block processing and locally linear embedding. The final change detection (CD) mask is obtained by clustering the extracted feature vectors into changed and unchanged classes using k-means clustering algorithm with k=2. Experimental results demonstrate that the proposed method extracts the slight change information efficiently in the hyperspectral image sequence and outperforms the state-of-the-art CD methods quantitatively and qualitatively.

  4. Detection of perturbed quantization class stego images based on possible change modes

    NASA Astrophysics Data System (ADS)

    Zhang, Yi; Liu, Fenlin; Yang, Chunfang; Luo, Xiangyang; Song, Xiaofeng

    2015-11-01

    To improve the detection performance for perturbed quantization (PQ) class [PQ, energy-adaptive PQ (PQe), and texture-adaptive PQ (PQt)] stego images, a detection method based on possible change modes is proposed. First, by using the relationship between the changeable coefficients used for carrying secret messages and the second quantization steps, the modes having even second quantization steps are identified as possible change modes. Second, by referencing the existing features, the modified features that can accurately capture the embedding changes based on possible change modes are extracted. Next, feature sensitivity analyses based on the modifications performed before and after the embedding are carried out. These analyses show that the modified features are more sensitive to the original features. Experimental results indicate that detection performance of the modified features is better than that of the corresponding original features for three typical feature models [Cartesian calibrated PEVny (ccPEV), Cartesian calibrated co-occurrence matrix features (CF), and JPEG rich model (JRM)], and the integrated feature consisting of enhanced histogram features (EHF) and the modified JRM outperforms two current state-of-the-art feature models, namely, phase aware projection model (PHARM) and Gabor rich model (GRM).

  5. Sensitive, accurate and rapid detection of trace aliphatic amines in environmental samples with ultrasonic-assisted derivatization microextraction using a new fluorescent reagent for high performance liquid chromatography.

    PubMed

    Chen, Guang; Liu, Jianjun; Liu, Mengge; Li, Guoliang; Sun, Zhiwei; Zhang, Shijuan; Song, Cuihua; Wang, Hua; Suo, Yourui; You, Jinmao

    2014-07-25

    A new fluorescent reagent, 1-(1H-imidazol-1-yl)-2-(2-phenyl-1H-phenanthro[9,10-d]imidazol-1-yl)ethanone (IPPIE), is synthesized, and a simple pretreatment based on ultrasonic-assisted derivatization microextraction (UDME) with IPPIE is proposed for the selective derivatization of 12 aliphatic amines (C1: methylamine-C12: dodecylamine) in complex matrix samples (irrigation water, river water, waste water, cultivated soil, riverbank soil and riverbed soil). Under the optimal experimental conditions (solvent: ACN-HCl, catalyst: none, molar ratio: 4.3, time: 8 min and temperature: 80°C), micro amount of sample (40 μL; 5mg) can be pretreated in only 10 min, with no preconcentration, evaporation or other additional manual operations required. The interfering substances (aromatic amines, aliphatic alcohols and phenols) get the derivatization yields of <5%, causing insignificant matrix effects (<4%). IPPIE-analyte derivatives are separated by high performance liquid chromatography (HPLC) and quantified by fluorescence detection (FD). The very low instrumental detection limits (IDL: 0.66-4.02 ng/L) and method detection limits (MDL: 0.04-0.33 ng/g; 5.96-45.61 ng/L) are achieved. Analytes are further identified from adjacent peaks by on-line ion trap mass spectrometry (MS), thereby avoiding additional operations for impurities. With this UDME-HPLC-FD-MS method, the accuracy (-0.73-2.12%), precision (intra-day: 0.87-3.39%; inter-day: 0.16-4.12%), recovery (97.01-104.10%) and sensitivity were significantly improved. Successful applications in environmental samples demonstrate the superiority of this method in the sensitive, accurate and rapid determination of trace aliphatic amines in micro amount of complex samples. PMID:24925451

  6. Detection of Epigenetic Changes Using ANOVA with Spatially Varying Coefficients

    PubMed Central

    Xiao, Guanghua; Wang, Xinlei; LaPlant, Quincey; Nestler, Eric; Xie, Yang

    2016-01-01

    Identification of genome-wide epigenetic changes, the stable changes in gene function without a change in DNA sequence, under various conditions plays an important role in biomedical research. High-throughput epigenetic experiments are useful tools to measure genome-wide epigenetic changes, but the measured intensity levels from these high-resolution genome-wide epigenetic profiling data are often spatially correlated with high noise levels. In addition, no formal statistical method was developed to compare genome-wide epigenetic changes across multiple conditions. In this study, we consider ANOVA models with spatially varying coefficients, combined with a hierarchical Bayes approach, to explicitly model spatial correlation caused by location-dependent biological effects (i.e., epigenetic changes) and borrow strength among neighboring probes to compare epigenetic changes across multiple conditions. Through simulation studies and applications in drug addiction and depression models, we find that our approach compares favorably with competing methods; it is more efficient in estimation and more effective in detecting epigenetic changes. In addition, it can provide biologically meaningful results. PMID:23502341

  7. The failure to detect tactile change: a tactile analogue of visual change blindness.

    PubMed

    Gallace, Alberto; Tan, Hong Z; Spence, Charles

    2006-04-01

    A large body of empirical research now shows that people are surprisingly poor at detecting significant changes in visually presented scenes. This phenomenon is known as change blindness in vision. A similar phenomenon occurs in audition, but to date no such effect has been documented in touch. In the present study, we explored the ability of people to detect changes introduced between two consecutively presented vibrotactile patterns presented over the body surface. The patterns consisted of two or three vibrotactile stimuli presented for 200 msec. The position of one of the vibrotactile stimuli composing the display was repeatedly changed (alternating between two different positions) on 50% of the trials, but the same pattern was presented repeatedly on the remaining trials. Three conditions were investigated: No interval between the patterns, an empty interval between the patterns, and a masked interval between the patterns. Change detection was near perfect in the no-interval block. Performance deteriorated somewhat in the empty-interval block, but by far the worst change detection performance occurred in the masked-interval block. These results demonstrate that "change blindness" can also affect tactile perception. PMID:16892998

  8. When visual transients impair tactile change detection: a novel case of crossmodal change blindness?

    PubMed

    Gallace, Alberto; Auvray, Malika; Tan, Hong Z; Spence, Charles

    2006-05-01

    The inability of people to detect changes between consecutively presented visual displays, when separated by a blank screen or distractor, is known as "change blindness". This phenomenon has recently been reported to occur within the auditory and tactile modalities as well. To date, however, only distractors presented within the same sensory modality as the change have been demonstrated to produce change blindness. In the present experiment, we studied whether tactile change blindness might also be elicited by the presentation of a visual mask. Participants made same versus different judgments regarding two successively presented displays composed of two to three vibrotactile stimuli. While change detection performance was near-perfect when the two displays were presented one directly after the other, participants failed to detect many of the changes between the tactile displays when they were separated by an empty temporal interval. Critically, performance deteriorated still further when the presentation of a local (i.e., a mudsplash) or global visual transient coincided with the onset of the second tactile pattern. Analysis of the results using signal detection theory revealed that this crossmodal effect reflected a genuine perceptual impairment. PMID:16480821

  9. Identification of a 251 Gene Expression Signature That Can Accurately Detect M. tuberculosis in Patients with and without HIV Co-Infection

    PubMed Central

    Dawany, Noor; Showe, Louise C.; Kossenkov, Andrew V.; Chang, Celia; Ive, Prudence; Conradie, Francesca; Stevens, Wendy; Sanne, Ian

    2014-01-01

    Background Co-infection with tuberculosis (TB) is the leading cause of death in HIV-infected individuals. However, diagnosis of TB, especially in the presence of an HIV co-infection, can be limiting due to the high inaccuracy associated with the use of conventional diagnostic methods. Here we report a gene signature that can identify a tuberculosis infection in patients co-infected with HIV as well as in the absence of HIV. Methods We analyzed global gene expression data from peripheral blood mononuclear cell (PBMC) samples of patients that were either mono-infected with HIV or co-infected with HIV/TB and used support vector machines to identify a gene signature that can distinguish between the two classes. We then validated our results using publically available gene expression data from patients mono-infected with TB. Results Our analysis successfully identified a 251-gene signature that accurately distinguishes patients co-infected with HIV/TB from those infected with HIV only, with an overall accuracy of 81.4% (sensitivity = 76.2%, specificity = 86.4%). Furthermore, we show that our 251-gene signature can also accurately distinguish patients with active TB in the absence of an HIV infection from both patients with a latent TB infection and healthy controls (88.9–94.7% accuracy; 69.2–90% sensitivity and 90.3–100% specificity). We also demonstrate that the expression levels of the 251-gene signature diminish as a correlate of the length of TB treatment. Conclusions A 251-gene signature is described to (a) detect TB in the presence or absence of an HIV co-infection, and (b) assess response to treatment following anti-TB therapy. PMID:24587128

  10. A structural framework for anomalous change detection and characterization

    SciTech Connect

    Prasad, Lakshman; Theiler, James P

    2009-01-01

    We present a spatially adaptive scheme for automatically searching a pair of images of a scene for unusual and interesting changes. Our motivation is to bring into play structural aspects of image features alongside the spectral attributes used for anomalous change detection (ACD). We leverage a small but informative subset of pixels, namely edge pixels of the images, as anchor points of a Delaunay triangulation to jointly decompose the images into a set of triangular regions, called trixels, which are spectrally uniform. Such decomposition helps in image regularization by simple-function approximation on a feature-adaptive grid. Applying ACD to this trixel grid instead of pixels offers several advantages. It allows: (1) edge-preserving smoothing of images, (2) speed-up of spatial computations by significantly reducing the representation of the images, and (3) the easy recovery of structure of the detected anomalous changes by associating anomalous trixels with polygonal image features. The latter facility further enables the application of shape-theoretic criteria and algorithms to characterize the changes and recognize them as interesting or not. This incorporation of spatial information has the potential to filter out some spurious changes, such as due to parallax, shadows, and misregistration, by identifying and filtering out those that are structurally similar and spatially pervasive. Our framework supports the joint spatial and spectral analysis of images, potentially enabling the design of more robust ACD algorithms.

  11. Refractive index change detection based on porous silicon microarray

    NASA Astrophysics Data System (ADS)

    Chen, Weirong; Jia, Zhenhong; Li, Peng; Lv, Guodong; Lv, Xiaoyi

    2016-05-01

    By combining photolithography with the electrochemical anodization method, a microarray device of porous silicon (PS) photonic crystal was fabricated on the crystalline silicon substrate. The optical properties of the microarray were analyzed with the transfer matrix method. The relationship between refractive index and reflectivity of each array element of the microarray at 633 nm was also studied, and the array surface reflectivity changes were observed through digital imaging. By means of the reflectivity measurement method, reflectivity changes below 10-3 can be observed based on PS microarray. The results of this study can be applied to the detection of biosensor arrays.

  12. Theory of optimal weighting of data to detect climatic change

    NASA Technical Reports Server (NTRS)

    Bell, T. L.

    1986-01-01

    A search for climatic change predicted by climate models can easily yield unconvincing results because of 'climatic noise,' the inherent, unpredictable variability of time-average atmospheric data. A weighted average of data that maximizes the probability of detecting predicted climatic change is presented. To obtain the optimal weights, an estimate of the covariance matrix of the data from a prior data set is needed. This introduces additional sampling error into the method. This is presently taken into account. A form of the weighted average is found whose probability distribution is independent of the true (but unknown) covariance statistics of the data and of the climate model prediction.

  13. Techniques of UAV system land use changes detection application

    NASA Astrophysics Data System (ADS)

    Zhang, Youying; Cui, Hongxia

    2011-02-01

    The unmanned aerial vehicle( UAV) was able to acquire remote sensing images with low cost, precise and high spatial resolution information needed by management of Land use at desired time. The aim of this paper was to present an overview of the ongoing research on the potential and techniques of low-altitude UAV system for land use applications. The development of crucial subsystems consisting of the UAV platforms, multiple camera system, camera calibration and photogrammetric production, was introduced together. A procedure of images acquisition and photogrammetric processing was proposed. To detect land use changes, methods based on DSMs and DLG were discussed and adopted in this paper. Finally, analysis of land use research based UAVs was realized on real flight experiments of two study areas. The results of this study show that UAVs can be used successfully for land use change detection.

  14. Impact of LANDSAT MSS sensor differences on change detection analysis

    NASA Technical Reports Server (NTRS)

    Likens, W. C.; Wrigley, R. C.

    1983-01-01

    Some 512 by 512 pixel subwindows for simultaneously acquired scene pairs obtained by LANDSAT 2,3 and 4 multispectral band scanners were coregistered using LANDSAT 4 scenes as the base to which the other images were registered. Scattergrams between the coregistered scenes (a form of contingency analysis) were used to radiometrically compare data from the various sensors. Mode values were derived and used to visually fit a linear regression. Root mean square errors of the registration varied between .1 and 1.5 pixels. There appear to be no major problem preventing the use of LANDSAT 4 MSS with previous MSS sensors for change detection, provided the noise interference can be removed or minimized. Data normalizations for change detection should be based on the data rather than solely on calibration information. This allows simultaneous normalization of the atmosphere as well as the radiometry.

  15. Vegetation mapping for change detection on an arid-zone river.

    PubMed

    Nagler, Pamela; Glenn, Edward P; Hursh, Kim; Curtis, Charles; Huete, Alfredo

    2005-10-01

    A vegetation mapping system for change detection was tested at the Havasu National Wildlife Refuge (HNWR) on the Lower Colorado River. A low-cost, aerial photomosaic of the 4200 ha, study area was constructed utilizing an automated digital camera system, supplemented with oblique photographs to aid in determining species composition and plant heights. Ground-truth plots showed high accuracy in distinguishing native cottonwood (Populus fremontii) and willow (Salix gooddingii) trees from other vegetation on aerial photos. Marsh vegetation (mainly cattails, Typha domengensis) was also easily identified. However, shrubby terrestrial vegetation, consisting of saltcedar (Tamarix ramosissima), arrowweed (Pluchea sericea), and mesquite trees (Prosopis spp.), could not be accurately distinguished from each other and were combined into a single shrub layer on the final vegetation map. The final map took the form of a base, shrub and marsh layer, which was displayed as a Normalized Difference Vegetation Index map from a Landsat Enhanced Thematic Mapper (ETM+) image to show vegetation intensity. Native willow and cottonwood trees were digitized manually on the photomosaic and overlain on the shrub layer in a GIS. By contrast to present, qualitative mapping systems used on the Lower Colorado River, this mapping system provides quantitative information that can be used for accurate change detection. However, better methods to distinguish between saltcedar, mesquite, and arrowweed are needed to map the shrub layer. PMID:16240202

  16. [Early detection of cervical cancer in Chile: time for change].

    PubMed

    Léniz Martelli, Javiera; Van De Wyngard, Vanessa; Lagos, Marcela; Barriga, María Isabel; Puschel Illanes, Klaus; Ferreccio Readi, Catterina

    2014-08-01

    Mortality rates for cervical cancer (CC) in Chile are higher than those of developed countries and it has an unequal socioeconomic distribution. The recognition of human papilloma virus (HPV) as the causal agent of cervical cancer in the early 80's changed the prevention paradigms. Current goals are to prevent HPV infection by vaccination before the onset of sexual activity and to detect HPV infection in women older than 30 years. This article reviews CC prevention and early detection methods, discusses relevant evidence to support a change in Chile and presents an innovation proposal. A strategy of primary screening based on HPV detection followed by triage of HPV-positive women by colposcopy in primary care or by cytological or molecular reflex testing is proposed. Due to the existence in Chile of a well-organized nationwide CC prevention program, the replacement of a low-sensitivity screening test such as the Papanicolau test with a highly sensitive one such as HPV detection, could quickly improve the effectiveness of the program. The program also has a network of personnel qualified to conduct naked-eye inspections of the cervix, who could easily be trained to perform triage colposcopy. The incorporation of new prevention strategies could reduce the deaths of Chilean women and correct inequities.

  17. Instantaneous crack detection under changing operational and environmental variations

    NASA Astrophysics Data System (ADS)

    Kim, Seung Bum; Sohn, Hoon

    2007-04-01

    A new methodology of guided wave based nondestructive testing (NDT) is developed to detect crack damage in a thin metal structure without using prior baseline data or a predetermined decision boundary. In conventional guided wave based techniques, damage is often identified by comparing the "current" data obtained from a potentially damaged condition of a structure with the "past" baseline data collected at the pristine condition of the structure. However, it has been reported that this type of pattern comparison with the baseline data can lead to increased false alarms due to its susceptibility to varying operational and environmental conditions of the structure. To develop a more robust damage diagnosis technique, a new concept of NDT is conceived so that cracks can be detected even when the system being monitored is subjected to changing operational and environmental conditions. The proposed NDT technique utilizes the polarization characteristics of the piezoelectric wafers attached on the both sides of the thin metal structure. Crack formation creates Lamb wave mode conversion due to a sudden change in the thickness of the structure. Then, the proposed technique instantly detects the appearance of the crack by extracting this mode conversion from the measured Lamb waves, and the threshold value from damage classification is also obtained only from the current data set. Numerical and experimental results are presented to demonstrate the applicability of the proposed technique to instantaneous crack detection.

  18. Multiscale object-oriented change detection over urban areas

    NASA Astrophysics Data System (ADS)

    Wang, Jianmei; Li, Deren

    2006-10-01

    Urban growth induces urban spatial expansion in many cities in China. There is a great need for up-to-date information for effective urban decision-making and sustainable development. Many researches have demonstrated that satellite images, especial high resolution images, are very suitable for urban growth studies. However, change detection technique is the key to keep current with the rapid urban growth rate, taking advantage of tremendous amounts of satellite data. In this paper, a multi-scale object-oriented change detection approach integrating GIS and remote sensing is introduced. Firstly, a subset of image is cropped based on existing parcel boundaries stored in GIS database, then a multi-scale watershed transform is carried out to obtain the image objects. The image objects are classified into different land cover types by supervised classification based on their spectral, geometry and texture attributes. Finally a rule-based system is set up to judge every parcel one by one whether or not change happened comparing to existing GIS land use types. In order to verify the application validity of the presented methodology, the rural-urban fringe of Shanghai in China with the support of QuickBird date and GIS is tested, the result shown that it is effective to detect illegal land use parcel.

  19. Ice Sheet Change Detection by Satellite Image Differencing

    NASA Technical Reports Server (NTRS)

    Bindschadler, Robert A.; Scambos, Ted A.; Choi, Hyeungu; Haran, Terry M.

    2010-01-01

    Differencing of digital satellite image pairs highlights subtle changes in near-identical scenes of Earth surfaces. Using the mathematical relationships relevant to photoclinometry, we examine the effectiveness of this method for the study of localized ice sheet surface topography changes using numerical experiments. We then test these results by differencing images of several regions in West Antarctica, including some where changes have previously been identified in altimeter profiles. The technique works well with coregistered images having low noise, high radiometric sensitivity, and near-identical solar illumination geometry. Clouds and frosts detract from resolving surface features. The ETM(plus) sensor on Landsat-7, ALI sensor on EO-1, and MODIS sensor on the Aqua and Terra satellite platforms all have potential for detecting localized topographic changes such as shifting dunes, surface inflation and deflation features associated with sub-glacial lake fill-drain events, or grounding line changes. Availability and frequency of MODIS images favor this sensor for wide application, and using it, we demonstrate both qualitative identification of changes in topography and quantitative mapping of slope and elevation changes.

  20. Change Detection Based on Persistent Scatterer Interferometry - a New Method of Monitoring Building Changes

    NASA Astrophysics Data System (ADS)

    Yang, C. H.; Kenduiywo, B. K.; Soergel, U.

    2016-06-01

    Persistent Scatterer Interferometry (PSI) is a technique to detect a network of extracted persistent scatterer (PS) points which feature temporal phase stability and strong radar signal throughout time-series of SAR images. The small surface deformations on such PS points are estimated. PSI particularly works well in monitoring human settlements because regular substructures of man-made objects give rise to large number of PS points. If such structures and/or substructures substantially alter or even vanish due to big change like construction, their PS points are discarded without additional explorations during standard PSI procedure. Such rejected points are called big change (BC) points. On the other hand, incoherent change detection (ICD) relies on local comparison of multi-temporal images (e.g. image difference, image ratio) to highlight scene modifications of larger size rather than detail level. However, image noise inevitably degrades ICD accuracy. We propose a change detection approach based on PSI to synergize benefits of PSI and ICD. PS points are extracted by PSI procedure. A local change index is introduced to quantify probability of a big change for each point. We propose an automatic thresholding method adopting change index to extract BC points along with a clue of the period they emerge. In the end, PS ad BC points are integrated into a change detection image. Our method is tested at a site located around north of Berlin main station where steady, demolished, and erected building substructures are successfully detected. The results are consistent with ground truth derived from time-series of aerial images provided by Google Earth. In addition, we apply our technique for traffic infrastructure, business district, and sports playground monitoring.

  1. Vegetation change detection in the Savannah River swamp

    SciTech Connect

    Jensen, J.R.; Christensen, E.J.; Mackey, H.E. Jr.

    1986-01-01

    Portions of Pen Branch, Four Mile Creek, Steel Creek, and Beaver Dam Creek deltas in the Savannah River swamp were evaluated for wetlands vegetation change using aircraft multispectral scanner (MSS) data acquired at 2440 meters altitude. Areas of 190 hectares on the Pen Branch, Four Mile Creek, and Beaver Dam Creek deltas, and a 240-hectare portion of Steel Creek delta were registered, classified, and wetlands vegetation change detection categories determined. Pen Branch and Four Mile Creek deltas each lost about 12 hectares of swamp forest from 1981 to 1984. Secondary successional forest regrew on portions of the Four Mile Creek delta (2.4 hectares) and the Beaver Dam Creek delta (15.4 hectares). About 5 hectares of swamp forest regrew on the Steel Creek delta. This may be the first study to detect wetlands vegetation change over several years using aircraft MSS data. One reason could be due to difficulties similar to those encountered in this study. Data distortion from aircraft movement in some areas of the swamp made image-to-image registration difficult. Best results were obtained on Beaver Dam Creek and Steel Creek deltas which had average registration accuracies within one data element, or pixel, of 5.6 x 5.6 meters. Phenological differences and shadows caused difficulties in vegetation-type discrimination and classification. As a result, the number of vegetation change classes were sometimes limited.

  2. Symmetrized local co-registration optimization for anomalous change detection

    SciTech Connect

    Wohlberg, Brendt E; Theiler, James P

    2009-01-01

    The goal of anomalous change detection (ACD) is to identify what unusual changes have occurred in a scene, based on two images of the scene taken at different times and under different conditions. The actual anomalous changes need to be distinguished from the incidental differences that occur throughout the imagery, and one of the most common and confounding of these incidental differences is due to the misregistration of the images, due to limitations of the registration pre-processing applied to the image pair. We propose a general method to compensate for residual misregistration in any ACD algorithm which constructs an estimate of the degree of 'anomalousness' for every pixel in the image pair. The method computes a modified misregistration-insensitive anomalousness by making local re-registration adjustments to minimize the local anomalousness. In this paper we describe a symmetrized version of our initial algorithm, and find significant performance improvements in the anomalous change detection ROC curves for a number of real and synthetic data sets.

  3. Topographic Change Detection using Full-waveform Imaging Lidar

    NASA Astrophysics Data System (ADS)

    Blair, B.; Hofton, M. A.

    2001-12-01

    The capability of wide-footprint (i.e. 10 m or greater), full-waveform laser altimeters to penetrate beneath dense vegetation to directly measure the sub-canopy topography provides us with a unique capability for sensing topographic change in the presence of vegetation. We evaluate the feasibility of using a geolocated laser altimeter return waveform instead of individual elevation measurements to measure vertical elevation change within a laser footprint. The method, dubbed the return pulse correlation method, maximizes the shape similarity of near-coincident, vertically-geolocated laser return waveforms from two observation epochs as they are vertically-shifted relative to each other. First, we evaluate the inherent accuracy of the pulse correlation method using models and simulations under "bare-Earth" conditions. We then analyze the effects of vegetation and vegetation growth on the change detection capability. The use of this method, combined with order of magnitude improvements to laser altimeter swath widths (from 1 km to 10 km) and the potential for a future spaceborne imaging lidar, may provide sub-centimeter level relative change detection beneath vegetation to complement IFSAR's ability to make similar measurements in low or vegetation-free conditions.

  4. Topographic Change Detection Using Full-Waveform Imaging Lidar

    NASA Technical Reports Server (NTRS)

    Blair, Bryan; Hofton, Michele A.; Smith, David E. (Technical Monitor)

    2001-01-01

    The capability of wide-footprint (i.e. 10m or greater), full-waveform laser altimeters to penetrate beneath dense vegetation to directly measure the sub-canopy topography provides us with a unique capability for sensing topographic change in the presence of vegetation. We evaluate the feasibility of using a geolocated laser altimeter return waveform instead of individual elevation measurements to measure vertical elevation change within a laser footprint. The method, dubbed the return pulse correlation method, maximizes the shape similarity of nea-coincident, vertically- geolocated laser return waveforms from two observation epochs as they are vertically-shifted relative to each other. First, we evaluate the inherent accuracy of the pulse correlation method using models and simulations under "bare-Earth" conditions. We then analyze the effects of vegetation and vegetation growth on the change detection capability. The use of this method, combined with order of magnitude improvements to laser altimeter swath widths (from 1 km to 10 km) and the potential for a future spaceborne imaging lidar, may provide subcentimeter level relative change detection beneath vegetation to complement IFSAR's ability to make similar measurements in low or vegetation-free conditions.

  5. Object-based rapid change detection for disaster management

    NASA Astrophysics Data System (ADS)

    Thunig, Holger; Michel, Ulrich; Ehlers, Manfred; Reinartz, Peter

    2011-11-01

    Rapid change detection is used in cases of natural hazards and disasters. This analysis lead to quick information about areas of damage. In certain cases the lack of information after catastrophe events is obstructing supporting measures within disaster management. Earthquakes, tsunamis, civil war, volcanic eruption, droughts and floods have much in common: people are directly affected, landscapes and buildings are destroyed. In every case geospatial data is necessary to gain knowledge as basement for decision support. Where to go first? Which infrastructure is usable? How much area is affected? These are essential questions which need to be answered before appropriate, eligible help can be established. This study presents an innovative strategy to retrieve post event information by use of an object-based change detection approach. Within a transferable framework, the developed algorithms can be implemented for a set of remote sensing data among different investigation areas. Several case studies are the base for the retrieved results. Within a coarse dividing into statistical parts and the segmentation in meaningful objects, the framework is able to deal with different types of change. By means of an elaborated normalized temporal change index (NTCI) panchromatic datasets are used to extract areas which are destroyed, areas which were not affected and in addition areas which are developing new for cases where rebuilding has already started. The results of the study are also feasible for monitoring urban growth.

  6. Symmetrized local co-registration optimization for anomalous change detection

    NASA Astrophysics Data System (ADS)

    Wohlberg, Brendt; Theiler, James

    2010-01-01

    The goal of anomalous change detection (ACD) is to identify what unusual changes have occurred in a scene, based on two images of the scene taken at different times and under different conditions. The actual anomalous changes need to be distinguished from the incidental differences that occur throughout the imagery, and one of the most common and confounding of these incidental differences is due to the misregistration of the images, due to limitations of the registration pre-processing applied to the image pair. We propose a general method to compensate for residual misregistration in any ACD algorithm which constructs an estimate of the degree of "anomalousness" for every pixel in the image pair. The method computes a modified misregistration-insensitive anomalousness by making local re-registration adjustments to minimize the local anomalousness. In this paper we describe a symmetrized version of our initial algorithm, and find significant performance improvements in the anomalous change detection ROC curves for a number of real and synthetic data sets.

  7. Detecting Changes of Thermal Environment over the Bohai Coastal Region by Spectral Change Vector Analysis

    NASA Astrophysics Data System (ADS)

    Hu, Y.; Jia, G.

    2009-12-01

    Change vector analysis (CVA) is an effective approach for detecting and characterizing land-cover change by comparing pairs of multi-spectral and multi-temporal datasets over certain area derived from various satellite platforms. NDVI is considered as an effective detector for biophysical changes due to its sensitivity to red and near infrared signals, while land surface temperature (LST) is considered as a valuable indicator for changes of ground thermal conditions. Here we try to apply CVA over satellite derived LST datasets to detect changes of land surface thermal properties parallel to climate change and anthropogenic influence in a city cluster since 2001. In this study, monthly land surface temperature datasets from 2001-2008 derived from MODIS collection 5 were used to examine change pattern of thermal environment over the Bohai coastal region by using spectral change vector analysis. The results from principle component analysis (PCA) for LST show that the PC 1-3 contain over 80% information on monthly variations and these PCA components represent the main processes of land thermal environment change over the study area. Time series of CVA magnitude combined with land cover information show that greatest change occurred in urban and heavily populated area, featured with expansion of urban heat island, while moderate change appeared in grassland area in the north. However few changes were observed over large plain area and forest area. Strong signals also are related to economy level and especially the events of surface cover change, such as emergence of railway and port. Two main processes were also noticed about the changes of thermal environment. First, weak signal was detected in mostly natural area influenced by interannual climate change in temperate broadleaf forest area. Second, land surface temperature changes were controlled by human activities as 1) moderate change of LST happened in grassland influenced by grazing and 2) urban heat island was

  8. Action change detection in video using a bilateral spatial-temporal constraint

    NASA Astrophysics Data System (ADS)

    Tian, Jing; Chen, Li

    2016-08-01

    Action change detection in video aims to detect action discontinuity in video. The silhouettes-based features are desirable for action change detection. This paper studies the problem of silhouette-quality assessment. For that, a non-reference approach without the need for ground truth is proposed in this paper to evaluate the quality of silhouettes, by exploiting both the boundary contrast of the silhouettes in the spatial domain and the consistency of the silhouettes in the temporal domain. This is in contrast to that either only spatial information or only temporal information of silhouettes is exploited in conventional approaches. Experiments are conducted using artificially generated degraded silhouettes to show that the proposed approach outperforms conventional approaches to achieve more accurate quality assessment. Furthermore, experiments are performed to show that the proposed approach is able to improve the accuracy performance of conventional action change approaches in two human action video data-sets. The average runtime of the proposed approach for Weizmann action video data-set is 0.08 second for one frame using Matlab programming language. It is computationally efficient and potential to real-time implementations.

  9. Change detection of polarimetric SAR images based on the KummerU Distribution

    NASA Astrophysics Data System (ADS)

    Chen, Quan; Zou, Pengfei; Li, Zhen; Zhang, Ping

    2014-11-01

    In the society of PolSAR image segmentation, change detection and classification, the classical Wishart distribution has been used for a long time, but it especially suit to low-resolution SAR image, because in traditional sensors, only a small number of scatterers are present in each resolution cell. With the improving of SAR systems these years, the classical statistical models can therefore be reconsidered for high resolution and polarimetric information contained in the images acquired by these advanced systems. In this study, SAR image segmentation algorithm based on level-set method, added with distance regularized level-set evolution (DRLSE) is performed using Envisat/ASAR single-polarization data and Radarsat-2 polarimetric images, respectively. KummerU heterogeneous clutter model is used in the later to overcome the homogeneous hypothesis at high resolution cell. An enhanced distance regularized level-set evolution (DRLSE-E) is also applied in the later, to ensure accurate computation and stable level-set evolution. Finally, change detection based on four polarimetric Radarsat-2 time series images is carried out at Genhe area of Inner Mongolia Autonomous Region, NorthEastern of China, where a heavy flood disaster occurred during the summer of 2013, result shows the recommend segmentation method can detect the change of watershed effectively.

  10. Automated baseline change detection -- Phases 1 and 2. Final report

    SciTech Connect

    Byler, E.

    1997-10-31

    The primary objective of this project is to apply robotic and optical sensor technology to the operational inspection of mixed toxic and radioactive waste stored in barrels, using Automated Baseline Change Detection (ABCD), based on image subtraction. Absolute change detection is based on detecting any visible physical changes, regardless of cause, between a current inspection image of a barrel and an archived baseline image of the same barrel. Thus, in addition to rust, the ABCD system can also detect corrosion, leaks, dents, and bulges. The ABCD approach and method rely on precise camera positioning and repositioning relative to the barrel and on feature recognition in images. The ABCD image processing software was installed on a robotic vehicle developed under a related DOE/FETC contract DE-AC21-92MC29112 Intelligent Mobile Sensor System (IMSS) and integrated with the electronics and software. This vehicle was designed especially to navigate in DOE Waste Storage Facilities. Initial system testing was performed at Fernald in June 1996. After some further development and more extensive integration the prototype integrated system was installed and tested at the Radioactive Waste Management Facility (RWMC) at INEEL beginning in April 1997 through the present (November 1997). The integrated system, composed of ABCD imaging software and IMSS mobility base, is called MISS EVE (Mobile Intelligent Sensor System--Environmental Validation Expert). Evaluation of the integrated system in RWMC Building 628, containing approximately 10,000 drums, demonstrated an easy to use system with the ability to properly navigate through the facility, image all the defined drums, and process the results into a report delivered to the operator on a GUI interface and on hard copy. Further work is needed to make the brassboard system more operationally robust.

  11. A method for detecting changes in long time series

    SciTech Connect

    Downing, D.J.; Lawkins, W.F.; Morris, M.D.; Ostrouchov, G.

    1995-09-01

    Modern scientific activities, both physical and computational, can result in time series of many thousands or even millions of data values. Here the authors describe a statistically motivated algorithm for quick screening of very long time series data for the presence of potentially interesting but arbitrary changes. The basic data model is a stationary Gaussian stochastic process, and the approach to detecting a change is the comparison of two predictions of the series at a time point or contiguous collection of time points. One prediction is a ``forecast``, i.e. based on data from earlier times, while the other a ``backcast``, i.e. based on data from later times. The statistic is the absolute value of the log-likelihood ratio for these two predictions, evaluated at the observed data. A conservative procedure is suggested for specifying critical values for the statistic under the null hypothesis of ``no change``.

  12. Visual detection of body weight change in young women.

    PubMed

    Alley, T R

    1991-12-01

    To assess whether small changes in body weight can be visually detected, college students (58 women and 42 men) were asked to select the less heavy person shown in two photographs for each of 33 young women. All of these women had been photographed twice in a standardized pose and attire, separated by an 8-wk. interval during which most of them lost weight. These pairs were presented in varying orders to control for the order and side of presentation. One photograph was reliably selected as the lighter person for 64% of the pairs, but the picture selected was in fact lighter only 57% of the time. The accuracy of selecting the lighter photograph was not correlated with the percent weight change for the person shown in the pairs of photographs. The results suggest that small changes in women's weight may not have a significant perceptual effect, particularly for male perceivers.

  13. Detecting a trend change in cross-border epidemic transmission

    NASA Astrophysics Data System (ADS)

    Maeno, Yoshiharu

    2016-09-01

    A method for a system of Langevin equations is developed for detecting a trend change in cross-border epidemic transmission. The equations represent a standard epidemiological SIR compartment model and a meta-population network model. The method analyzes a time series of the number of new cases reported in multiple geographical regions. The method is applicable to investigating the efficacy of the implemented public health intervention in managing infectious travelers across borders. It is found that the change point of the probability of travel movements was one week after the WHO worldwide alert on the SARS outbreak in 2003. The alert was effective in managing infectious travelers. On the other hand, it is found that the probability of travel movements did not change at all for the flu pandemic in 2009. The pandemic did not affect potential travelers despite the WHO alert.

  14. Change detection of built-up land: A framework of combining pixel-based detection and object-based recognition

    NASA Astrophysics Data System (ADS)

    Xiao, Pengfeng; Zhang, Xueliang; Wang, Dongguang; Yuan, Min; Feng, Xuezhi; Kelly, Maggi

    2016-09-01

    This study proposed a new framework that combines pixel-level change detection and object-level recognition to detect changes of built-up land from high-spatial resolution remote sensing images. First, an adaptive differencing method was designed to detect changes at the pixel level based on both spectral and textural features. Next, the changed pixels were subjected to a set of morphological operations to improve the completeness and to generate changed objects, achieving the transition of change detection from the pixel level to the object level. The changed objects were further recognised through the difference of morphological building index in two phases to indicate changed objects on built-up land. The transformation from changed pixels to changed objects makes the proposed framework distinct with both the pixel-based and the object-based change detection methods. Compared with the pixel-based methods, the proposed framework can improve the change detection capability through the transformation and successive recognition of objects. Compared with the object-based method, the proposed framework avoids the issue of multitemporal segmentation and can generate changed objects directly from changed pixels. The experimental results show the effectiveness of the transformation from changed pixels to changed objects and the successive object-based recognition on improving the detection accuracy, which justify the application potential of the proposed change detection framework.

  15. Multi-driver attribution of detected hydrological change

    NASA Astrophysics Data System (ADS)

    Harrigan, Shaun; Murphy, Conor; Hall, Julia; Wilby, Robert L.; Sweeney, John

    2014-05-01

    There is growing evidence that significant links between large-scale climate indices and streamflow over decadal time-scales can be established. However identifying the dominant driving mechanism(s) of detected changes in streamflow (i.e. attribution) at the catchment scale is a challenging task due to the confounding influence of human disturbances such as land-use changes, water abstractions, and river engineering. This study addresses this challenge by examining the utility of the multiple working hypotheses framework in moving towards more rigorous attribution of changes using the Boyne catchment in the east of Ireland as a case study. Previous research on this catchment found that a large upward change point in streamflow during the mid-1970s corresponded with a shift in the North Atlantic Oscillation (NAO) index towards a more positive phase, bringing increased precipitation, and hence increased risk of flooding. Here, the single-driver analysis is extended to include multiple factors causing change within the catchment (both climatic and internal) in order to establish relative contributions of hypothesised drivers. Rainfall-runoff models were employed to reconstruct streamflow to isolate the effect of climate taking account of both model structure and parameter uncertainty. The Mann-Kendall test for monotonic trend and Pettitt change point test were applied to explore signatures of change. Results show that the detected increase in annual mean and high flows was not predominantly driven by changes in precipitation as a result of a shift in the NAO index. Rather we assert that the dominant driver of change was arterial drainage and the contemporaneous onset of agricultural field drainage in the 1970s and early 1980s. It is also demonstrated that attribution can be more complex at different time-scales with multiple drivers acting simultaneously. This study emphasises the quantity and range of data types needed for rigorous attribution, especially when

  16. Enhanced climate change and its detection over the Rocky Mountains

    SciTech Connect

    Fyfe, J.C.; Flato, G.M.

    1999-01-01

    Results from an ensemble of climate change experiments with increasing greenhouse gas and aerosols using the Canadian Centre for Climate Modeling and Analysis Coupled Climate Model are presented with a focus on surface quantities over the Rocky Mountains. There is a marked elevation dependency of the simulated surface screen temperature increase over the Rocky Mountains in the winter and spring seasons, with more pronounced changes at higher elevations. The elevation signal is linked to a rise in the snow line in the winter and spring seasons, which amplifies the surface warming via the snow-albedo feedback. Analysis of the winter surface energy budget shows that large changes in the solar component of the radiative input are the direct consequence of surface albedo changes caused by decreasing snow cover. Although the warming signal is enhanced at higher elevations, a two-way analysis of variance reveals that the elevation effect has no potential for early climate change detection. In the early stages of surface warming the elevation effect is masked by relatively large noise, so that the signal-to-noise ratio over the Rocky Mountains is no larger than elsewhere. Only after significant continental-scale warming does the local Rocky Mountain signal begin to dominate the pattern of climate change over western North America (and presumably also the surrounding ecosystems and hydrological networks).

  17. Geomorphic change detection using historic maps and DEM differencing: The temporal dimension of geospatial analysis

    NASA Astrophysics Data System (ADS)

    James, L. Allan; Hodgson, Michael E.; Ghoshal, Subhajit; Latiolais, Mary Megison

    2012-01-01

    The ability to develop spatially distributed models of topographic change is presenting new capabilities in geomorphic research. High resolution maps of elevation change indicate locations, processes, and rates of geomorphic change, and provide a means of calibrating temporal simulation models. Methods of geomorphic change detection (GCD), based on gridded models, may be applied to a wide range of time periods by utilizing cartometric, remote sensing, or ground-based topographic survey data to measure volumetric change. Advantages and limitations of historical DEM reconstruction methods are reviewed with a focus on coupling them with subsequent DEMs to construct DEMs of difference (DoD), which can be created by subtracting one elevation model from another, to map erosion, deposition, and volumetric change. The period of DoD analysis can be extended to several decades if accurate historical DEMs can be generated by extracting topographic data from historical data and selecting areas where geomorphic change has been substantial. The challenge is to recognize and minimize uncertainties in data that are particularly elusive with early topographic data. This paper reviews potential sources of error in digitized topographic maps and DEMs. Although the paper is primarily a review of methods, three brief examples are presented at the end to demonstrate GCD using DoDs constructed from data extending over periods ranging from 70 to 90 years.

  18. Foot-to-foot bioelectrical impedance accurately tracks direction of adiposity change in overweight and obese 7- to 13-year-old children.

    PubMed

    Kasvis, Popi; Cohen, Tamara R; Loiselle, Sarah-Ève; Kim, Nicolas; Hazell, Tom J; Vanstone, Catherine A; Rodd, Celia; Plourde, Hugues; Weiler, Hope A

    2015-03-01

    Body composition measurements are valuable when evaluating pediatric obesity interventions. We hypothesized that foot-to-foot bioelectrical impedance analysis (BIA) will accurately track the direction of adiposity change, but not magnitude, in part due to differences in fat patterning. The purposes of this study were to examine the accuracy of body composition measurements of overweight and obese children over time using dual-energy x-ray absorptiometry (DXA) and BIA and to determine if BIA accuracy was affected by fat patterning. Eighty-nine overweight or obese children (48 girls, 41 boys, age 7-13 years) participating in a randomized controlled trial providing a family-centered, lifestyle intervention, underwent DXA and BIA measurements every 3 months. Bland-Altman plots showed a poor level of agreement between devices for baseline percent body fat (%BF; mean, 0.398%; +2SD, 8.685%; -2SD, -7.889%). There was overall agreement between DXA and BIA in the direction of change over time for %BF (difference between visits 3 and 1: DXA -0.8 ± 0.5%, BIA -0.7 ± 0.5%; P = 1.000) and fat mass (FM; difference between visits 3 and 1: DXA 0.7 ± 0.5 kg, BIA 0.6 ± 0.5 kg; P = 1.000). Bioelectrical impedance analysis measurements of %BF and FM at baseline were significantly different in those with android and gynoid fat (%BF: 35.9% ± 1.4%, 32.2% ± 1.4%, P < .003; FM: 20.1 ± 0.8 kg, 18.4 ± 0.8, P < .013). Bioelectrical impedance analysis accurately reports the direction of change in FM and FFM in overweight and obese children; inaccuracy in the magnitude of BIA measurements may be a result of fat patterning differences.

  19. Foot-to-foot bioelectrical impedance accurately tracks direction of adiposity change in overweight and obese 7- to 13-year-old children.

    PubMed

    Kasvis, Popi; Cohen, Tamara R; Loiselle, Sarah-Ève; Kim, Nicolas; Hazell, Tom J; Vanstone, Catherine A; Rodd, Celia; Plourde, Hugues; Weiler, Hope A

    2015-03-01

    Body composition measurements are valuable when evaluating pediatric obesity interventions. We hypothesized that foot-to-foot bioelectrical impedance analysis (BIA) will accurately track the direction of adiposity change, but not magnitude, in part due to differences in fat patterning. The purposes of this study were to examine the accuracy of body composition measurements of overweight and obese children over time using dual-energy x-ray absorptiometry (DXA) and BIA and to determine if BIA accuracy was affected by fat patterning. Eighty-nine overweight or obese children (48 girls, 41 boys, age 7-13 years) participating in a randomized controlled trial providing a family-centered, lifestyle intervention, underwent DXA and BIA measurements every 3 months. Bland-Altman plots showed a poor level of agreement between devices for baseline percent body fat (%BF; mean, 0.398%; +2SD, 8.685%; -2SD, -7.889%). There was overall agreement between DXA and BIA in the direction of change over time for %BF (difference between visits 3 and 1: DXA -0.8 ± 0.5%, BIA -0.7 ± 0.5%; P = 1.000) and fat mass (FM; difference between visits 3 and 1: DXA 0.7 ± 0.5 kg, BIA 0.6 ± 0.5 kg; P = 1.000). Bioelectrical impedance analysis measurements of %BF and FM at baseline were significantly different in those with android and gynoid fat (%BF: 35.9% ± 1.4%, 32.2% ± 1.4%, P < .003; FM: 20.1 ± 0.8 kg, 18.4 ± 0.8, P < .013). Bioelectrical impedance analysis accurately reports the direction of change in FM and FFM in overweight and obese children; inaccuracy in the magnitude of BIA measurements may be a result of fat patterning differences. PMID:25697463

  20. How minimum detectable displacement in a GNSS Monitoring Network change?

    NASA Astrophysics Data System (ADS)

    Hilmi Erkoç, Muharrem; Doǧan, Uǧur; Aydın, Cüneyt

    2016-04-01

    The minimum detectable displacement in a geodetic monitoring network shows the displacement magnitude which may be just discriminated with known error probabilities. This displacement, which is originally deduced from sensitivity analysis, depends on network design, observation accuracy, datum of the network, direction of the displacement and power of the statistical test used for detecting the displacements. One may investigate how different scenarios on network design and observation accuracies influence the minimum detectable displacements for the specified datum, a-priorly forecasted directions and assumed power of the test and decide which scenario is the best or most optimum. It is sometimes difficult to forecast directions of the displacements. In that case, the minimum detectable displacements in a geodetic monitoring network are derived on the eigen-directions associated with the maximum eigen-values of the network stations. This study investigates how minimum detectable displacements in a GNSS monitoring network change depending on the accuracies of the network stations. For this, CORS-TR network in Turkey with 15 stations (a station fixed) is used. The data with 4h, 6h, 12 h and 24 h observing session duration in three sequential days of 2011, 2012 and 2013 were analyzed with Bernese 5.2 GNSS software. The repeatabilities of the daily solutions belonging to each year were analyzed carefully to scale the Bernese cofactor matrices properly. The root mean square (RMS) values for daily repeatability with respect to the combined 3-day solution are computed (the RMS values are generally less than 2 mm in the horizontal directions (north and east) and < 5 mm in the vertical direction for 24 h observing session duration). With the obtained cofactor matrices for these observing sessions, the minimum detectable displacements along the (maximum) eigen directions are compared each other. According to these comparisons, more session duration less minimum detectable

  1. Street environment change detection from mobile laser scanning point clouds

    NASA Astrophysics Data System (ADS)

    Xiao, Wen; Vallet, Bruno; Brédif, Mathieu; Paparoditis, Nicolas

    2015-09-01

    Mobile laser scanning (MLS) has become a popular technique for road inventory, building modelling, infrastructure management, mobility assessment, etc. Meanwhile, due to the high mobility of MLS systems, it is easy to revisit interested areas. However, change detection using MLS data of street environment has seldom been studied. In this paper, an approach that combines occupancy grids and a distance-based method for change detection from MLS point clouds is proposed. Unlike conventional occupancy grids, our occupancy-based method models space based on scanning rays and local point distributions in 3D without voxelization. A local cylindrical reference frame is presented for the interpolation of occupancy between rays according to the scanning geometry. The Dempster-Shafer theory (DST) is utilized for both intra-data evidence fusion and inter-data consistency assessment. Occupancy of reference point cloud is fused at the location of target points and then the consistency is evaluated directly on the points. A point-to-triangle (PTT) distance-based method is combined to improve the occupancy-based method. Because it is robust to penetrable objects, e.g. vegetation, which cause self-conflicts when modelling occupancy. The combined method tackles irregular point density and occlusion problems, also eliminates false detections on penetrable objects.

  2. Site change detection for RADIUS using thermophysical algebraic invariants

    NASA Astrophysics Data System (ADS)

    Nandhakumar, Nagaraj; Michel, Johnathan D.; Arnold, D. Gregory; Velten, Vincent J.; Tsihrintzis, George A.

    1996-02-01

    Research on the formulation of invariant features for model-based object recognition has mostly been concerned with geometric constructs either of the object or in the imaging process. We describe a new method that identifies invariant features computed from long wave infrared (LWIR) imagery. These features are called thermophysical invariants and depend primarily on the material composition of the object. Features are defined that are functions of only the thermophysical properties of the imaged materials. A physics-based model is derived from the principle of conservation of energy applied at the surface of the imaged regions. A linear form of the model is used to derive features that remain constant despite changes in scene parameters/driving conditions. Simulated and real imagery, as well as ground truth thermo-couple measurements were used to test the behavior of such features. A method of change detection in outdoor scenes is investigated. The invariants are used to detect when a hypothesized material no longer exists at a given location. For example, one can detect when a patch of clay/gravel has been replaced with concrete at a given site. This formulation yields promising results, but it can produce large values outside a normally small range. Therefore, we adopt a new feature classification algorithm based on the theories of symmetric alpha- stable (S(alpha) S) distributions. We show that symmetric, alpha-stable distributions model the thermophysical invariant data much better than the Gaussian model and suggest a classifier with superior performance.

  3. Reference chart for relative weight change to detect hypernatraemic dehydration

    PubMed Central

    van Dommelen, Paula; van Wouwe, Jacobus P; Breuning‐Boers, Jacqueline M; van Buuren, Stef; Verkerk, Paul H

    2007-01-01

    Objective The validity of the rule of thumb that infants may have a weight loss of 10% in the first days after birth is unknown. We assessed the validity of this and other rules to detect breast‐fed infants with hypernatraemic dehydration. Design A reference chart for relative weight change was constructed by the LMS method. The reference group was obtained by a retrospective cohort study. Participants 1544 healthy, exclusively breast‐fed infants with 3075 weight measurements born in the Netherlands and 83 cases of breast‐fed infants with hypernatraemic dehydration obtained from literature. Results The rule of thumb had a sensitivity of 90.4%, a specificity of 98.3% and a positive predictive value of 3.7%. Referring infants if their weight change is below −2.5 SDS (0.6th centile) in the reference chart in the first week of life and using the rule of thumb in the second week had a sensitivity of 85.5%, a specificity of 99.4% and a positive predictive value of 9.2%. Conclusions The rule of thumb is likely to produce too many false positive results, assuming that for screening purposes the specificity needs to be high. A chart for relative weight change can be helpful to detect infants with hypernatraemic dehydration. PMID:16880225

  4. ROLE OF SPATIAL RESOLUTION AND SPECTRAL CONTENT IN CHANGE DETECTION.

    USGS Publications Warehouse

    Milazzo, Valerie A.

    1984-01-01

    Summary form only given, as follows. Advancements in remote sensing technology have brought improvements and sophistication to modern remote sensor systems, especially those aboard earth resources satellites. These improvements have considerbly expanded the capabilities of the newer sensor systems, particularly the capability to achieve greatly increased spatial and spectral resolution levels. The debate still lingers, however, over whether future systems should maximize spatial resolution or spectral information, or both. As yet, the high costs and large volumes of data associated with even modest incremental improvements in spatial and spectral content have precluded the design of a single system that attempts to fully optimize both. Thus, the user is faced with having to choose between those systems providing high spatial resolutions but limited spectral information and those which offer a broad range of spectral data but hold spatial resolution to a less than optimum level. In this study, the contribution of both spatial resolution and spectral content to land cover change detection is examined. Ten-meter SPOT simulation imagery is compared with multispectral images acquired by the Thematic Mapper sensor system for use in the visual interpretation and mapping of changes. Several image processing and enhancement techniques are utilized to maximize the spatial and spectral data content offered by each system. Results indicate that when using visual image interpretation techniques to detect change, higher spatial resolutions are generally preferred over increased spectral content.

  5. Automatic detection of unattended changes in room acoustics.

    PubMed

    Frey, Johannes Daniel; Wendt, Mike; Jacobsen, Thomas

    2015-01-01

    Previous research has shown that the human auditory system continuously monitors its acoustic environment, detecting a variety of irregularities (e.g., deviance from prior stimulation regularity in pitch, loudness, duration, and (perceived) sound source location). Detection of irregularities can be inferred from a component of the event-related brain potential (ERP), referred to as the mismatch negativity (MMN), even in conditions in which participants are instructed to ignore the auditory stimulation. The current study extends previous findings by demonstrating that auditory irregularities brought about by a change in room acoustics elicit a MMN in a passive oddball protocol (acoustic stimuli with differing room acoustics, that were otherwise identical, were employed as standard and deviant stimuli), in which participants watched a fiction movie (silent with subtitles). While the majority of participants reported no awareness for any changes in the auditory stimulation, only one out of 14 participants reported to have become aware of changing room acoustics or sound source location. Together, these findings suggest automatic monitoring of room acoustics.

  6. Visual change detection recruits auditory cortices in early deafness.

    PubMed

    Bottari, Davide; Heimler, Benedetta; Caclin, Anne; Dalmolin, Anna; Giard, Marie-Hélène; Pavani, Francesco

    2014-07-01

    Although cross-modal recruitment of early sensory areas in deafness and blindness is well established, the constraints and limits of these plastic changes remain to be understood. In the case of human deafness, for instance, it is known that visual, tactile or visuo-tactile stimuli can elicit a response within the auditory cortices. Nonetheless, both the timing of these evoked responses and the functional contribution of cross-modally recruited areas remain to be ascertained. In the present study, we examined to what extent auditory cortices of deaf humans participate in high-order visual processes, such as visual change detection. By measuring visual ERPs, in particular the visual MisMatch Negativity (vMMN), and performing source localization, we show that individuals with early deafness (N=12) recruit the auditory cortices when a change in motion direction during shape deformation occurs in a continuous visual motion stream. Remarkably this "auditory" response for visual events emerged with the same timing as the visual MMN in hearing controls (N=12), between 150 and 300 ms after the visual change. Furthermore, the recruitment of auditory cortices for visual change detection in early deaf was paired with a reduction of response within the visual system, indicating a shift from visual to auditory cortices of part of the computational process. The present study suggests that the deafened auditory cortices participate at extracting and storing the visual information and at comparing on-line the upcoming visual events, thus indicating that cross-modally recruited auditory cortices can reach this level of computation.

  7. Spatio-temporal change detection from multidimensional arrays: Detecting deforestation from MODIS time series

    NASA Astrophysics Data System (ADS)

    Lu, Meng; Pebesma, Edzer; Sanchez, Alber; Verbesselt, Jan

    2016-07-01

    Growing availability of long-term satellite imagery enables change modeling with advanced spatio-temporal statistical methods. Multidimensional arrays naturally match the structure of spatio-temporal satellite data and can provide a clean modeling process for complex spatio-temporal analysis over large datasets. Our study case illustrates the detection of breakpoints in MODIS imagery time series for land cover change in the Brazilian Amazon using the BFAST (Breaks For Additive Season and Trend) change detection framework. BFAST includes an Empirical Fluctuation Process (EFP) to alarm the change and a change point time locating process. We extend the EFP to account for the spatial autocorrelation between spatial neighbors and assess the effects of spatial correlation when applying BFAST on satellite image time series. In addition, we evaluate how sensitive EFP is to the assumption that its time series residuals are temporally uncorrelated, by modeling it as an autoregressive process. We use arrays as a unified data structure for the modeling process, R to execute the analysis, and an array database management system to scale computation. Our results point to BFAST as a robust approach against mild temporal and spatial correlation, to the use of arrays to ease the modeling process of spatio-temporal change, and towards communicable and scalable analysis.

  8. Spatiotemporal quantile regression for detecting distributional changes in environmental processes.

    PubMed

    Reich, Brian J

    2012-08-01

    Climate change may lead to changes in several aspects of the distribution of climate variables, including changes in the mean, increased variability, and severity of extreme events. In this paper, we propose using spatiotemporal quantile regression as a flexible and interpretable method for simultaneously detecting changes in several features of the distribution of climate variables. The spatiotemporal quantile regression model assumes that each quantile level changes linearly in time, permitting straight-forward inference on the time trend for each quantile level. Unlike classical quantile regression which uses model-free methods to analyze a single quantile or several quantiles separately, we take a model-based approach which jointly models all quantiles, and thus the entire response distribution. In the spatiotemporal quantile regression model, each spatial location has its own quantile function that evolves over time, and the quantile functions are smoothed spatially using Gaussian process priors. We propose a basis expansion for the quantile function that permits a closed-form for the likelihood, and allows for residual correlation modeling via a Gaussian spatial copula. We illustrate the methods using temperature data for the southeast US from the years 1931-2009. For these data, borrowing information across space identifies more significant time trends than classical non-spatial quantile regression. We find a decreasing time trend for much of the spatial domain for monthly mean and maximum temperatures. For the lower quantiles of monthly minimum temperature, we find a decrease in Georgia and Florida, and an increase in Virginia and the Carolinas.

  9. Memory strength versus memory variability in visual change detection.

    PubMed

    Nosofsky, Robert M; Gold, Jason

    2016-01-01

    Observers made change-detection judgments for colored squares in a paradigm that manipulated the retention interval, the magnitude of change, and objective change probability. The probability of change judgments increased across the retention interval for “same” and “small-change” test items but stayed the same or decreased for “large-change” and “far” test items. A variety of formal models were fitted to the individual-subject data. The modeling results provided evidence that, beyond changes in visual-memory precision, there were decreases in memory strength of individual study items across the retention interval. In addition, the modeling results provided evidence of a zero-information, absence-of-memory state that required guessing. The data were not sufficiently strong to sharply distinguish whether the losses in memory strength across the retention interval were continuous in nature or all-or-none. The authors argue that the construct of memory strength as distinct from memory variability is an important component of the nature of forgetting from visual working memory.

  10. Memory strength versus memory variability in visual change detection.

    PubMed

    Nosofsky, Robert M; Gold, Jason

    2016-01-01

    Observers made change-detection judgments for colored squares in a paradigm that manipulated the retention interval, the magnitude of change, and objective change probability. The probability of change judgments increased across the retention interval for “same” and “small-change” test items but stayed the same or decreased for “large-change” and “far” test items. A variety of formal models were fitted to the individual-subject data. The modeling results provided evidence that, beyond changes in visual-memory precision, there were decreases in memory strength of individual study items across the retention interval. In addition, the modeling results provided evidence of a zero-information, absence-of-memory state that required guessing. The data were not sufficiently strong to sharply distinguish whether the losses in memory strength across the retention interval were continuous in nature or all-or-none. The authors argue that the construct of memory strength as distinct from memory variability is an important component of the nature of forgetting from visual working memory. PMID:26480836

  11. Competitive SWIFT cluster templates enhance detection of aging changes

    PubMed Central

    Rebhahn, Jonathan A.; Roumanes, David R.; Qi, Yilin; Khan, Atif; Thakar, Juilee; Rosenberg, Alex; Lee, F. Eun‐Hyung; Quataert, Sally A.; Sharma, Gaurav

    2015-01-01

    Abstract Clustering‐based algorithms for automated analysis of flow cytometry datasets have achieved more efficient and objective analysis than manual processing. Clustering organizes flow cytometry data into subpopulations with substantially homogenous characteristics but does not directly address the important problem of identifying the salient differences in subpopulations between subjects and groups. Here, we address this problem by augmenting SWIFT—a mixture model based clustering algorithm reported previously. First, we show that SWIFT clustering using a “template” mixture model, in which all subpopulations are represented, identifies small differences in cell numbers per subpopulation between samples. Second, we demonstrate that resolution of inter‐sample differences is increased by “competition” wherein a joint model is formed by combining the mixture model templates obtained from different groups. In the joint model, clusters from individual groups compete for the assignment of cells, sharpening differences between samples, particularly differences representing subpopulation shifts that are masked under clustering with a single template model. The benefit of competition was demonstrated first with a semisynthetic dataset obtained by deliberately shifting a known subpopulation within an actual flow cytometry sample. Single templates correctly identified changes in the number of cells in the subpopulation, but only the competition method detected small changes in median fluorescence. In further validation studies, competition identified a larger number of significantly altered subpopulations between young and elderly subjects. This enrichment was specific, because competition between templates from consensus male and female samples did not improve the detection of age‐related differences. Several changes between the young and elderly identified by SWIFT template competition were consistent with known alterations in the elderly, and additional

  12. A modified approach for change detection using change vector analysis in posterior probability space

    NASA Astrophysics Data System (ADS)

    Azzouzi, S. A.; Vidal, A.; Bentounes, H. A.

    2015-04-01

    The multispectral and multitemporal data coming from satellites allow us to extract valuable spatiotemporal change. Consequently, Earth surface change detection analysis has been used in the past to monitor land cover changes caused by different reasons. Several techniques have been used for that purpose and change vector analysis (CVA) has been frequently employed to carry out automatic spatiotemporal information extraction. This work describes a modified methodology based on Supervised Change Vector Analysis in Posterior probability Space (SCVAPS) with the final aim of obtaining a change detection map in Blida, Algeria. The proposed technique is a Modified version of Supervised Change Vector Analysis Posterior probability Space (MSCVAPS) and it is applied at the same region that the original technique studied in the literature. The classical Maximum Likelihood classifier is the selected method for supervised classification since it provides good properties in the posterior probability map. An improved method for threshold determination based on Double Flexible Pace Search (DFPS) is proposed in this work and it is employed to obtain the most adequate threshold value. Then, the MSCVAPS approach is evaluated by two cases study of the land cover change detection in the region of Blida, Algeria, and in the region of Shunyi District, Beijing, China, using a pair of Landsat Thematic Mapper images and pair of Landsat Enhanced Thematic Mapper images, respectively. The final evaluation is given by the overall accuracy of changed and unchanged pixels and the kappa coefficient. The results show that the modified approach gives excellent results using the same area of study that was selected in the literature.

  13. Object-Based Change Detection Using High-Resolution Remotely Sensed Data and GIS

    NASA Astrophysics Data System (ADS)

    Sofina, N.; Ehlers, M.

    2012-08-01

    High resolution remotely sensed images provide current, detailed, and accurate information for large areas of the earth surface which can be used for change detection analyses. Conventional methods of image processing permit detection of changes by comparing remotely sensed multitemporal images. However, for performing a successful analysis it is desirable to take images from the same sensor which should be acquired at the same time of season, at the same time of a day, and - for electro-optical sensors - in cloudless conditions. Thus, a change detection analysis could be problematic especially for sudden catastrophic events. A promising alternative is the use of vector-based maps containing information about the original urban layout which can be related to a single image obtained after the catastrophe. The paper describes a methodology for an object-based search of destroyed buildings as a consequence of a natural or man-made catastrophe (e.g., earthquakes, flooding, civil war). The analysis is based on remotely sensed and vector GIS data. It includes three main steps: (i) generation of features describing the state of buildings; (ii) classification of building conditions; and (iii) data import into a GIS. One of the proposed features is a newly developed 'Detected Part of Contour' (DPC). Additionally, several features based on the analysis of textural information corresponding to the investigated vector objects are calculated. The method is applied to remotely sensed images of areas that have been subjected to an earthquake. The results show the high reliability of the DPC feature as an indicator for change.

  14. Image change detection systems, methods, and articles of manufacture

    DOEpatents

    Jones, James L.; Lassahn, Gordon D.; Lancaster, Gregory D.

    2010-01-05

    Aspects of the invention relate to image change detection systems, methods, and articles of manufacture. According to one aspect, a method of identifying differences between a plurality of images is described. The method includes loading a source image and a target image into memory of a computer, constructing source and target edge images from the source and target images to enable processing of multiband images, displaying the source and target images on a display device of the computer, aligning the source and target edge images, switching displaying of the source image and the target image on the display device, to enable identification of differences between the source image and the target image.

  15. A New Maximum-Likelihood Change Estimator for Two-Pass SAR Coherent Change Detection.

    SciTech Connect

    Wahl, Daniel E.; Yocky, David A.; Jakowatz, Charles V,

    2014-09-01

    In this paper, we derive a new optimal change metric to be used in synthetic aperture RADAR (SAR) coherent change detection (CCD). Previous CCD methods tend to produce false alarm states (showing change when there is none) in areas of the image that have a low clutter-to-noise power ratio (CNR). The new estimator does not suffer from this shortcoming. It is a surprisingly simple expression, easy to implement, and is optimal in the maximum-likelihood (ML) sense. The estimator produces very impressive results on the CCD collects that we have tested.

  16. Multiplexed detection of molecular biomarkers with phase-change nanoparticles

    PubMed Central

    Su, Ming

    2014-01-01

    This review describes a new biosensing method based on nanoparticles of solid-to-liquid phase-change materials, in which a panel of metallic nanoparticles (metals and eutectic alloys) that have different compositions and melting temperatures are used as thermal reporters. Each type of nanoparticle will be conjugated to a ligand that can specifically bind to one type of molecular biomarker (protein or DNA) and then immobilized onto a substrate that is comodified with multiple ligands by forming sandwiched antibody–antigen complexes or DNA double helices. After removing unbound nanoparticles by washing, the nature and concentration of the biomarkers are determined by detecting the melting temperature and fusion enthalpy of the nanoparticles using differential scanning calorimetry. Furthermore, an even larger panel of thermal barcodes can be formed by encapsulating selected phase-change nanoparticles inside non-melting shells, such as silica, where each microparticle will have a characteristic signature that can be determined from its thermal signatures. PMID:23394155

  17. Street-side vehicle detection, classification and change detection using mobile laser scanning data

    NASA Astrophysics Data System (ADS)

    Xiao, Wen; Vallet, Bruno; Schindler, Konrad; Paparoditis, Nicolas

    2016-04-01

    Statistics on street-side car parks, e.g. occupancy rates, parked vehicle types, parking durations, are of great importance for urban planning and policy making. Related studies, e.g. vehicle detection and classification, mostly focus on static images or video. Whereas mobile laser scanning (MLS) systems are increasingly utilized for urban street environment perception due to their direct 3D information acquisition, high accuracy and movability. In this paper, we design a complete system for car park monitoring, including vehicle recognition, localization, classification and change detection, from laser scanning point clouds. The experimental data are acquired by an MLS system using high frequency laser scanner which scans the streets vertically along the system's moving trajectory. The point clouds are firstly classified as ground, building façade, and street objects which are then segmented using state-of-the-art methods. Each segment is treated as an object hypothesis, and its geometric features are extracted. Moreover, a deformable vehicle model is fitted to each object. By fitting an explicit model to the vehicle points, detailed information, such as precise position and orientation, can be obtained. The model parameters are also treated as vehicle features. Together with the geometric features, they are applied to a supervised learning procedure for vehicle or non-vehicle recognition. The classes of detected vehicles are also investigated. Whether vehicles have changed across two datasets acquired at different times is detected to estimate the durations. Here, vehicles are trained pair-wisely. Two same or different vehicles are paired up as training samples. As a result, the vehicle recognition, classification and change detection accuracies are 95.9%, 86.0% and 98.7%, respectively. Vehicle modelling improves not only the recognition rate, but also the localization precision compared to bounding boxes.

  18. Onboard Data Processor for Change-Detection Radar Imaging

    NASA Technical Reports Server (NTRS)

    Lou, Yunling; Muellerschoen, Ronald J.; Chien, Steve A.; Saatchi, Sasan S.; Clark, Duane

    2008-01-01

    A computer system denoted a change-detection onboard processor (CDOP) is being developed as a means of processing the digitized output of a synthetic-aperture radar (SAR) apparatus aboard an aircraft or spacecraft to generate images showing changes that have occurred in the terrain below between repeat passes of the aircraft or spacecraft over the terrain. When fully developed, the CDOP is intended to be capable of generating SAR images and/or SAR differential interferograms in nearly real time. The CDOP is expected to be especially useful for understanding some large-scale natural phenomena and/or mitigating natural hazards: For example, it could be used for near-real-time observation of surface changes caused by floods, landslides, forest fires, volcanic eruptions, earthquakes, glaciers, and sea ice movements. It could also be used to observe such longer-term surface changes as those associated with growth of vegetation (relevant to estimation of wildfire fuel loads). The CDOP is, essentially, an interferometric SAR processor designed to operate aboard a radar platform.

  19. Detecting inaudible vocal organ changes through glottal inverse filtering.

    PubMed

    Geneid, Ahmed; Rönkkö, Marjo; Voutilainen, Risto; Airaksinen, Liisa; Toskala, Elina; Alku, Paavo; Vilkman, Erkki

    2012-03-01

    The aim of this study was to investigate if there were objective quantities extracted from the speech pressure waveforms that underlay inaudible changes in the symptoms of the vocal organ. This was done through analyzing 180 voice samples obtained from nine subjects (five females and four males) before and after exposure to a placebo substance (lactose) and an organic dust substance. Acoustical analysis of the voice samples was achieved by using glottal inverse filtering. Results showed that the values of primary open quotient and primary speed quotient changed significantly (P<0.05) as did the amplitude quotient (P<0.01). Exposure to lactose resulted in significant changes of secondary open quotient (P<0.05) but opposite to effects found for exposure to organic dust. Modeling of the vocal tract into cross-sectional planes revealed that the immediate plane above the vocal folds correlates inversely with the feeling that voice is tense, or feeling the need to make an effort when speaking in addition having a feeling of shortness of breath or the need to gasp for air. Such results may point to acoustically detected subclinical changes in the vocal organ that the subject him/herself feels while they remain perceptually undetected by others.

  20. An example of fingerprint detection of greenhouse climate changes

    SciTech Connect

    Karoly, D.J.; Cohen, J.A.; Meehl, G.A.

    1994-07-01

    As an example of the technique of fingerprint detection of greenhouse climate change, a multivariate signal or fingerprint of the enhanced greenhouse effect is defined using the zonal mean atmospheric temperature change as a function of height and latitude between equilibrium climate model simulations with control and doubled CO{sub 2} concentrations. This signal is compared with observed atmospheric temperature variations over the period 1963 to 1988 from radiosonde-based global analyses. There is a signiificant increase of this greenhouse signal in the observational data over this period. These results must be treated with caution. Upper air data are available for a short period only, possibly, to be able to resolve any real greenhouse climate change. The greenhouse fingerprint used in this study may not be unique to the enhanced greenhouse effect and may be due to other forcing mechanisms. However, it is shown that the patterns of atmospheric temperature change associated with uniform global increases of sea surface temperature, with El Nino-Southern Oscillation events and with decreases of stratospheric ozone concentrations individually are different from the greenhouse fingerprint used here. 30 refs., 6 figs., 2 tabs.

  1. Accurate Detection of Adenylation Domain Functions in Nonribosomal Peptide Synthetases by an Enzyme-linked Immunosorbent Assay System Using Active Site-directed Probes for Adenylation Domains.

    PubMed

    Ishikawa, Fumihiro; Miyamoto, Kengo; Konno, Sho; Kasai, Shota; Kakeya, Hideaki

    2015-12-18

    A significant gap exists between protein engineering and enzymes used for the biosynthesis of natural products, largely because there is a paucity of strategies that rapidly detect active-site phenotypes of the enzymes with desired activities. Herein, we describe a proof-of-concept study of an enzyme-linked immunosorbent assay (ELISA) system for the adenylation (A) domains in nonribosomal peptide synthetases (NRPSs) using a combination of active site-directed probes coupled to a 5'-O-N-(aminoacyl)sulfamoyladenosine scaffold with a biotin functionality that immobilizes probe molecules onto a streptavidin-coated solid support. The recombinant NRPSs have a C-terminal His-tag motif that is targeted by an anti-6×His mouse antibody as the primary antibody and a horseradish peroxidase-linked goat antimouse antibody as the secondary antibody. These probes can selectively capture the cognate A domains by ligand-directed targeting. In addition, the ELISA technique detected A domains in the crude cell-free homogenates from the Escherichia coli expression systems. When coupled with a chromogenic substrate, the antibody-based ELISA technique can visualize probe-protein binding interactions, which provides accurate readouts of the A-domain functions in NRPS enzymes. To assess the ELISA-based engineering of the A domains of NRPSs, we reprogramed 2,3-dihydroxybenzoic acid (DHB)-activating enzyme EntE toward salicylic acid (Sal)-activating enzymes and investigated a correlation between binding properties for probe molecules and enzyme catalysts. We generated a mutant of EntE that displayed negligible loss in the kcat/Km value with the noncognate substrate Sal and a corresponding 48-fold decrease in the kcat/Km value with the cognate substrate DHB. The resulting 26-fold switch in substrate specificity was achieved by the replacement of a Ser residue in the active site of EntE with a Cys toward the nonribosomal codes of Sal-activating enzymes. Bringing a laboratory ELISA technique

  2. Detecting and isolating abrupt changes in linear switching systems

    NASA Astrophysics Data System (ADS)

    Nazari, Sohail; Zhao, Qing; Huang, Biao

    2015-04-01

    In this paper, a novel fault detection and isolation (FDI) method for switching linear systems is developed. All input and output signals are assumed to be corrupted with measurement noises. In the proposed method, a 'lifted' linear model named as stochastic hybrid decoupling polynomial (SHDP) is introduced. The SHDP model governs the dynamics of the switching linear system with all different modes, and is independent of the switching sequence. The error-in-variable (EIV) representation of SHDP is derived, and is used for the fault residual generation and isolation following the well-adopted local approach. The proposed FDI method can detect and isolate the fault-induced abrupt changes in switching models' parameters without estimating the switching modes. Furthermore, in this paper, the analytical expressions of the gradient vector and Hessian matrix are obtained based on the EIV SHDP formulation, so that they can be used to implement the online fault detection scheme. The performance of the proposed method is then illustrated by simulation examples.

  3. Illumination robust change detection with CMOS imaging sensors

    NASA Astrophysics Data System (ADS)

    Rengarajan, Vijay; Gupta, Sheetal B.; Rajagopalan, A. N.; Seetharaman, Guna

    2015-05-01

    Change detection between two images in the presence of degradations is an important problem in the computer vision community, more so for the aerial scenario which is particularly challenging. Cameras mounted on moving platforms such as aircrafts or drones are subject to general six-dimensional motion as the motion is not restricted to a single plane. With CMOS cameras increasingly in vogue due to their low power consumption, the inevitability of rolling-shutter (RS) effect adds to the challenge. This is caused by sequential exposure of rows in CMOS cameras unlike conventional global shutter cameras where all pixels are exposed simultaneously. The RS effect is particularly pronounced in aerial imaging since each row of the imaging sensor is likely to experience a different motion. For fast-moving platforms, the problem is further compounded since the rows are also affected by motion blur. Moreover, since the two images are shot at different times, illumination differences are common. In this paper, we propose a unified computational framework that elegantly exploits the scarcity constraint to deal with the problem of change detection in images degraded by RS effect, motion blur as well as non-global illumination differences. We formulate an optimization problem where each row of the distorted image is approximated as a weighted sum of the corresponding rows in warped versions of the reference image due to camera motion within the exposure period to account for geometric as well as photometric differences. The method has been validated on both synthetic and real data.

  4. Online scene change detection of multicast (MBone) video

    NASA Astrophysics Data System (ADS)

    Zhou, Wensheng; Shen, Ye; Vellaikal, Asha; Kuo, C.-C. Jay

    1998-10-01

    Many multimedia applications, such as multimedia data management systems and communication systems, require efficient representation of multimedia content. Thus semantic interpretation of video content has been a popular research area. Currently, most content-based video representation involves the segmentation of video based on key frames which are generated using scene change detection techniques as well as camera/object motion. Then, video features can be extracted from key frames. However most of such research performs off-line video processing in which the whole video scope is known as a priori which allows multiple scans of the stored video files during video processing. In comparison, relatively not much research has been done in the area of on-line video processing, which is crucial in video communication applications such as on-line collaboration, news broadcasts and so on. Our research investigates on-line real-time scene change detection of multicast video over the Internet. Our on-line processing system are designed to meet the requirements of real-time video multicasting over the Internet and to utilize the successful video parsing techniques available today. The proposed algorithms extract key frames from video bitstreams sent through the MBone network, and the extracted key frames are multicasted as annotations or metadata over a separate channel to assist in content filtering such as those anticipated to be in use by on-line filtering proxies in the Internet. The performance of the proposed algorithms are demonstrated and discussed in this paper.

  5. Correlation based efficient face recognition and color change detection

    NASA Astrophysics Data System (ADS)

    Elbouz, M.; Alfalou, A.; Brosseau, C.; Alam, M. S.; Qasmi, S.

    2013-01-01

    Identifying the human face via correlation is a topic attracting widespread interest. At the heart of this technique lies the comparison of an unknown target image to a known reference database of images. However, the color information in the target image remains notoriously difficult to interpret. In this paper, we report a new technique which: (i) is robust against illumination change, (ii) offers discrimination ability to detect color change between faces having similar shape, and (iii) is specifically designed to detect red colored stains (i.e. facial bleeding). We adopt the Vanderlugt correlator (VLC) architecture with a segmented phase filter and we decompose the color target image using normalized red, green, and blue (RGB), and hue, saturation, and value (HSV) scales. We propose a new strategy to effectively utilize color information in signatures for further increasing the discrimination ability. The proposed algorithm has been found to be very efficient for discriminating face subjects with different skin colors, and those having color stains in different areas of the facial image.

  6. Volumetric Forest Change Detection Through Vhr Satellite Imagery

    NASA Astrophysics Data System (ADS)

    Akca, Devrim; Stylianidis, Efstratios; Smagas, Konstantinos; Hofer, Martin; Poli, Daniela; Gruen, Armin; Sanchez Martin, Victor; Altan, Orhan; Walli, Andreas; Jimeno, Elisa; Garcia, Alejandro

    2016-06-01

    Quick and economical ways of detecting of planimetric and volumetric changes of forest areas are in high demand. A research platform, called FORSAT (A satellite processing platform for high resolution forest assessment), was developed for the extraction of 3D geometric information from VHR (very-high resolution) imagery from satellite optical sensors and automatic change detection. This 3D forest information solution was developed during a Eurostars project. FORSAT includes two main units. The first one is dedicated to the geometric and radiometric processing of satellite optical imagery and 2D/3D information extraction. This includes: image radiometric pre-processing, image and ground point measurement, improvement of geometric sensor orientation, quasiepipolar image generation for stereo measurements, digital surface model (DSM) extraction by using a precise and robust image matching approach specially designed for VHR satellite imagery, generation of orthoimages, and 3D measurements in single images using mono-plotting and in stereo images as well as triplets. FORSAT supports most of the VHR optically imagery commonly used for civil applications: IKONOS, OrbView - 3, SPOT - 5 HRS, SPOT - 5 HRG, QuickBird, GeoEye-1, WorldView-1/2, Pléiades 1A/1B, SPOT 6/7, and sensors of similar type to be expected in the future. The second unit of FORSAT is dedicated to 3D surface comparison for change detection. It allows users to import digital elevation models (DEMs), align them using an advanced 3D surface matching approach and calculate the 3D differences and volume changes between epochs. To this end our 3D surface matching method LS3D is being used. FORSAT is a single source and flexible forest information solution with a very competitive price/quality ratio, allowing expert and non-expert remote sensing users to monitor forests in three and four dimensions from VHR optical imagery for many forest information needs. The capacity and benefits of FORSAT have been tested in

  7. Uncertainty in Estimation of Bioenergy Induced Lulc Change: Development of a New Change Detection Technique.

    NASA Astrophysics Data System (ADS)

    Singh, N.; Vatsavai, R. R.; Patlolla, D.; Bhaduri, B. L.; Lim, S. J.

    2015-12-01

    Recent estimates of bioenergy induced land use land cover change (LULCC) have large uncertainty due to misclassification errors in the LULC datasets used for analysis. These uncertainties are further compounded when data is modified by merging classes, aggregating pixels and change in classification methods over time. Hence the LULCC computed using these derived datasets is more a reflection of change in classification methods, change in input data and data manipulation rather than reflecting actual changes ion ground. Furthermore results are constrained by geographic extent, update frequency and resolution of the dataset. To overcome this limitation we have developed a change detection system to identify yearly as well as seasonal changes in LULC patterns. Our method uses hierarchical clustering which works by grouping objects into a hierarchy based on phenological similarity of different vegetation types. The algorithm explicitly models vegetation phenology to reduce spurious changes. We apply our technique on globally available Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI data at 250-meter resolution. We analyze 10 years of bi-weekly data to predict changes in the mid-western US as a case study. The results of our analysis are presented and its advantages over existing techniques are discussed.

  8. Early auditory change detection implicitly facilitated by ignored concurrent visual change during a Braille reading task.

    PubMed

    Aoyama, Atsushi; Haruyama, Tomohiro; Kuriki, Shinya

    2013-09-01

    Unconscious monitoring of multimodal stimulus changes enables humans to effectively sense the external environment. Such automatic change detection is thought to be reflected in auditory and visual mismatch negativity (MMN) and mismatch negativity fields (MMFs). These are event-related potentials and magnetic fields, respectively, evoked by deviant stimuli within a sequence of standard stimuli, and both are typically studied during irrelevant visual tasks that cause the stimuli to be ignored. Due to the sensitivity of MMN/MMF to potential effects of explicit attention to vision, however, it is unclear whether multisensory co-occurring changes can purely facilitate early sensory change detection reciprocally across modalities. We adopted a tactile task involving the reading of Braille patterns as a neutral ignore condition, while measuring magnetoencephalographic responses to concurrent audiovisual stimuli that were infrequently deviated either in auditory, visual, or audiovisual dimensions; 1000-Hz standard tones were switched to 1050-Hz deviant tones and/or two-by-two standard check patterns displayed on both sides of visual fields were switched to deviant reversed patterns. The check patterns were set to be faint enough so that the reversals could be easily ignored even during Braille reading. While visual MMFs were virtually undetectable even for visual and audiovisual deviants, significant auditory MMFs were observed for auditory and audiovisual deviants, originating from bilateral supratemporal auditory areas. Notably, auditory MMFs were significantly enhanced for audiovisual deviants from about 100 ms post-stimulus, as compared with the summation responses for auditory and visual deviants or for each of the unisensory deviants recorded in separate sessions. Evidenced by high tactile task performance with unawareness of visual changes, we conclude that Braille reading can successfully suppress explicit attention and that simultaneous multisensory changes can

  9. Glacier Change Detection in the Hindu Kush of Afghanistan

    NASA Astrophysics Data System (ADS)

    Shroder, J. F.; Bishop, M. P.

    2004-12-01

    A half century of intermittently collected cryospheric and hydrologic data in Afghanistan has involved diverse field surveys, aerial photography, and satellite imagery that enable change detection in the war-torn, drought-stricken region. Afghanistan relies heavily upon snow-and ice-melt for vital irrigation and ground-water recharge, yet the past two decades of war have only exacerbated the originally already deficient information collection and analysis of such data. Glacier field studies and base-line inventory work initiated in the pre-war 1960-1970 period are now providing limited change detection information for the vital physical analysis necessary in the reconstruction of the country. Five case study areas were selected for renewed assessment over the intervening half century, from the western-most ice masses of the Koh-i-Foladi region in central Afghanistan, through the Mir Samir and Sakhi regions of the central Hindu Kush, to the Keshnikhan and Pamir areas of the Wakhan Corridor. Certain incompatibilities or ambiguities exist between Soviet-era and Western-derived data sets. In general, however, glaciers of Afghanistan are continuing to downwaste and retreat, with smaller ice masses disappearing altogether, presumably as the climatic snowline continues to rise above the peaks, a trend first noticed in the 1960s. Glacier survival in the lower central areas is now in part determined by topographic shielding from solar radiation high in shadowed cirques, or being preserved beneath increasing debris covers, whereas in the higher regions to the northeast, fewer changes to the larger, higher altitude glaciers are apparent. Renewed assessment of all Afghanistan glaciers is now underway as a part of the USGS- and NASA-supported GLIMS (Global Land-Ice Measurements from Space) project, and is viewed as an important element in the primary geodata collection and hazard assessment necessary for aiding in rebuilding the infrastructure of the beleaguered nation.

  10. Detection of Deforestation and Land Conversion in Rondonia, Brazil Using Change Detection Techniques

    NASA Technical Reports Server (NTRS)

    Guild, Liane S.; Cohen, Warren B,; Kauffman, J. Boone; Peterson, David L. (Technical Monitor)

    2001-01-01

    Fires associated with tropical deforestation, land conversion, and land use greatly contribute to emissions as well as the depletion of carbon and nutrient pools. The objective of this research was to compare change detection techniques for identifying deforestation and cattle pasture formation during a period of early colonization and agricultural expansion in the vicinity of Jamari, Rond6nia. Multi-date Landsat Thematic Mapper (TM) data between 1984 and 1992 was examined in a 94 370-ha area of active deforestation to map land cover change. The Tasseled Cap (TC) transformation was used to enhance the contrast between forest, cleared areas, and regrowth. TC images were stacked into a composite multi-date TC and used in a principal components (PC) transformation to identify change components. In addition, consecutive TC image pairs were differenced and stacked into a composite multi-date differenced image. A maximum likelihood classification of each image composite was compared for identification of land cover change. The multi-date TC composite classification had the best accuracy of 78.1% (kappa). By 1984, only 5% of the study area had been cleared, but by 1992, 11% of the area had been deforested, primarily for pasture and 7% lost due to hydroelectric dam flooding. Finally, discrimination of pasture versus cultivation was improved due to the ability to detect land under sustained clearing opened to land exhibiting regrowth with infrequent clearing.

  11. Geocentric position preliminary detection from the extreme ultraviolet images of Chang'E-3

    NASA Astrophysics Data System (ADS)

    Zheng, Chen; Ping, Jinsong; Wang, Mingyuan; Li, Wenxiao

    2015-08-01

    An Extreme ultraviolet (EUV) Camera was installed onboard the Chinese lunar surface landing mission, the Chang'E-3 lander, as a useful method to observe the Earth plasmasphere. This EUV optical payload obtained more than 600 moon-based Earth plasmasphere images since December 14, 2013. However, due to errors of unknown size and origin in the platform attitude control of the lander and in the EUV telescope pointing control during the mission operating periods, the geocentric coordinates in these EUV images are not fixed in the same position of CCD pixel. Before adequately calibrating, these positioning offsets will introduce extra errors into the analysis of the plasmaspheric structure. With only a little insufficient telemetry information, an effective calibrating method of circle-based differential algorithm is suggested and demonstrated, for automatically and precisely detecting the geocentric position in each EUV image of Chang'E-3 mission. In each EUV image, the tested method uses the outline of a circle as the basic unit to capture the contour for the bright region based on the spectral characteristic. Then, the center of the extracted circle is adopted as the geocentric position for the image. The preliminary analysis shows that this method can effectively detect the geocentric position being always consistent with the recognition result by the basic hand labor method. It is found that the radius of the circles varies from month to month from December, 2013 to May, 2014. The monthly averages of radius show relative notable positive correlation and negative correlation with the changes of both Zenith angle of the Earth at the landing area of Chang'E-3 lander, and the Earth-moon distance, respectively. This method and results here will benefit the Chang'E-3 EUV study.

  12. [Digital subtraction radiography for the detection of periodontal bone changes].

    PubMed

    Mera, T

    1989-03-01

    This study was performed to evaluate the efficacy of digital subtraction radiography in detecting alveolar bone changes. In order to test the sensitivity of quantitative evaluation by subtraction radiography, a copper equivalent thickness obtained from digitized radiographs was compared with the actual mineral content of bone phantoms with 15 different minerals and 25 bone specimens. Results demonstrated that the copper equivalent thickness correlated well with the actual mineral content (bone phantoms: gamma s = 1.0, bone specimens: gamma s = 0.985). In order to test the ability of digitized subtraction radiography in assessing alveolar bone changes in vivo, subtraction images were compared with histological features. The experimental angular bony defects were treated with conservative periodontal therapy in 3 monkeys. The standardized radiographs were taken longitudinally after therapy, and subtraction images were made from the sequentially obtained radiographs. In addition, for fluorescent histomorphometrical evaluations of new bone formations, the animals were dosed with oxytetracycline, calsein solution and arizarin complex solution. Radiographic and histological evaluations were scheduled to provide healing periods of 2, 3, 4, 5, 6 and 9 weeks after periodontal therapy. Subtraction radiography offered an objective method to follow histological changes of alveolar bone, and the copper equivalent thickness obtained from subtraction radiographs correlated with the histometric bone volume (gamma s = 0.9023, p less than 0.01). The results of these studies indicated that subtraction radiography was useful in monitoring alveolar bone changes associated with periodontal disease and treatment and that the quanitative measurement of periodontal bone changes by subtraction radiography was feasible. PMID:2517790

  13. Trend Estimation and Change Point Detection in Climatic Series

    NASA Astrophysics Data System (ADS)

    Bates, B. C.; Chandler, R. E.

    2011-12-01

    The problems of trend estimation and change point detection in climatic series have received substantial attention in recent years. Key issues include the magnitudes and directions of underlying trends, and the existence (or otherwise) of abrupt shifts in the mean background state. There are many procedures in use including: t-tests, Mann-Whitney and Pettit tests, linear and piecewise linear regression; cumulative sum analysis; hierarchical Bayesian change point analysis; Markov chain Monte Carlo methods; and reversible jump Markov chain Monte Carlo. The purpose of our presentation is to motivate wider use of modern regression techniques for trend estimation and change point detection in climatic series. We pay particular attention to the underlying statistical assumptions as their violation can lead to serious errors in data interpretation and study conclusions. In this context we consider two case studies. The first involves the application of local linear regression and a test for discontinuities in the regression function to the winter (December-March) North Atlantic Oscillation (NAO) index series for the period 1864-2010. This series exhibits a reversal from strongly negative values in the late 1960s to strongly positive NAO index values in the mid-1990s. The second involves the analysis of a seasonal (June to October) series of typhoon counts in the vicinity of Taiwan for the period 1970-2006. A previous investigation by other researchers concluded that an abrupt shift in this series occurred between 1999 and 2000. For both case studies, our findings indicate little evidence for abrupt shifts: rather, the decadal to multidecadal changes in the mean levels of both series appear well described by smooth trends. For the winter NAO index series, the trend is non-monotonic; for the typhoon counts, it can be regarded as linear on the square root scale. Our statistical results do not contradict those obtained by other researchers: our interpretation of these results

  14. Effect of projective viewpoint in detecting temporal density changes

    NASA Astrophysics Data System (ADS)

    Raundahl, Jakob; Nielsen, Mads; Olsen, Ole F.; Bagger, Yu Z.

    2004-05-01

    An important question in mammographic image analysis is the importance of the projected view of the breast. Can temporal changes in density be detected equally well using either one of the commonly available views Medio-Lateral (ML) and Cranio-Caudal (CC) or a combination of the two? Two sets of mammograms of 50 patients in a double-blind, placebo controlled hormone replacement therapy (HRT) experiment were used. One set of ML and CC view from 1999 and one from 2001. HRT increases density which means that the degree of separation of the populations (one group receiving HRT and the other placebo) can be used as a measure of how much density change information is carried in a particular view or combination of views. Earlier results have shown a high correlation between CC and ML views leading to the conclusion that only one of them is needed for density assessment purposes. A similar high correlation coefficient was observed in this study (0.85), while the correlation between changes was a bit lower (0.71). Using both views to separate the patients receiving hormones from the ones receiving placebo increased the area under corresponding ROC curves from 0.76 +/- 0.04 to 0.79 +/- 0.04.

  15. Robust real-time change detection in high jitter.

    SciTech Connect

    Simonson, Katherine Mary; Ma, Tian J.

    2009-08-01

    A new method is introduced for real-time detection of transient change in scenes observed by staring sensors that are subject to platform jitter, pixel defects, variable focus, and other real-world challenges. The approach uses flexible statistical models for the scene background and its variability, which are continually updated to track gradual drift in the sensor's performance and the scene under observation. Two separate models represent temporal and spatial variations in pixel intensity. For the temporal model, each new frame is projected into a low-dimensional subspace designed to capture the behavior of the frame data over a recent observation window. Per-pixel temporal standard deviation estimates are based on projection residuals. The second approach employs a simple representation of jitter to generate pixelwise moment estimates from a single frame. These estimates rely on spatial characteristics of the scene, and are used gauge each pixel's susceptibility to jitter. The temporal model handles pixels that are naturally variable due to sensor noise or moving scene elements, along with jitter displacements comparable to those observed in the recent past. The spatial model captures jitter-induced changes that may not have been seen previously. Change is declared in pixels whose current values are inconsistent with both models.

  16. Detection and attribution of streamflow timing changes to climate change in the Western United States

    USGS Publications Warehouse

    Hidalgo, H.G.; Das, T.; Dettinger, M.D.; Cayan, D.R.; Pierce, D.W.; Barnett, T.P.; Bala, G.; Mirin, A.; Wood, A.W.; Bonfils, Celine; Santer, B.D.; Nozawa, T.

    2009-01-01

    This article applies formal detection and attribution techniques to investigate the nature of observed shifts in the timing of streamflow in the western United States. Previous studies have shown that the snow hydrology of the western United States has changed in the second half of the twentieth century. Such changes manifest themselves in the form of more rain and less snow, in reductions in the snow water contents, and in earlier snowmelt and associated advances in streamflow "center" timing (the day in the "water-year" on average when half the water-year flow at a point has passed). However, with one exception over a more limited domain, no other study has attempted to formally attribute these changes to anthropogenic increases of greenhouse gases in the atmosphere. Using the observations together with a set of global climate model simulations and a hydrologic model (applied to three major hydrological regions of the western United States_the California region, the upper Colorado River basin, and the Columbia River basin), it is found that the observed trends toward earlier "center" timing of snowmelt-driven streamflows in the western United States since 1950 are detectably different from natural variability (significant at the p < 0.05 level). Furthermore, the nonnatural parts of these changes can be attributed confidently to climate changes induced by anthropogenic greenhouse gases, aerosols, ozone, and land use. The signal from the Columbia dominates the analysis, and it is the only basin that showed a detectable signal when the analysis was performed on individual basins. It should be noted that although climate change is an important signal, other climatic processes have also contributed to the hydrologic variability of large basins in the western United States. ?? 2009 American Meteorological Society.

  17. Orthorectified High Resolution Multispectral Imagery for Application to Change Detection and Analysis

    NASA Technical Reports Server (NTRS)

    Benkelman, Cody A.

    1997-01-01

    The project team has outlined several technical objectives which will allow the companies to improve on their current capabilities. These include modifications to the imaging system, enabling it to operate more cost effectively and with greater ease of use, automation of the post-processing software to mosaic and orthorectify the image scenes collected, and the addition of radiometric calibration to greatly aid in the ability to perform accurate change detection. Business objectives include fine tuning of the market plan plus specification of future product requirements, expansion of sales activities (including identification of necessary additional resources required to meet stated revenue objectives), development of a product distribution plan, and implementation of a world wide sales effort.

  18. Detection of short-term changes in vegetation cover by use of LANDSAT imagery. [Arizona

    NASA Technical Reports Server (NTRS)

    Turner, R. M. (Principal Investigator); Wiseman, F. M.

    1975-01-01

    The author has identified the following significant results. By using a constant band 6 to band 5 radiance ratio of 1.25, the changing pattern of areas of relatively dense vegetation cover was detected for the semiarid region in the vicinity of Tucson, Arizona. Electronically produced binary thematic masks were used to map areas with dense vegetation. The foliar cover threshold represented by the ratio was not accurately determined but field measurements show that the threshold lies in the range of 10 to 25 percent foliage cover. Montana evergreen forests with constant dense cover were correctly shown to exceed the threshold on all dates. The summer active grassland exceeded the threshold in the summer unless rainfall was insufficient. Desert areas exceeded the threshold during the spring of 1973 following heavy rains; the same areas during the rainless spring of 1974 did not exceed threshold. Irrigated fields, parks, golf courses, and riparian communities were among the habitats most frequently surpassing the threshold.

  19. Spaceborne SAR data for land-cover classification and change detection

    NASA Technical Reports Server (NTRS)

    Brisco, B.; Ulaby, F. T.; Dobson, M. C.

    1983-01-01

    Supervised maximum-likelihood classifications of Seasat, SIR-A, and Landsat pixel data demonstrated that SIR-A data provided the most accurate discrimination (72 percent) between five land-cover categories. Spatial averaging of the SAR data improved classification accuracy significantly due to a reduction in both fading and within-field variability. The best multichannel classification accuracy (97.5 percent) was achieved by combining the SIR-A data with two Seasat images (ascending and descending orbits). In addition, semiquantitative analysis of Seasat-A digital data shows that orbital SAR imagery can be successfully used for multitemporal detection of change related to hydrologic and agronomic conditions by using simple machine processing techniques.

  20. Detecting regional changes in myocardial contraction patterns using MRI

    NASA Astrophysics Data System (ADS)

    Sanchez-Ortiz, Gerardo I.; Chandrashekara, Raghavendra; Rhode, Kawal S.; Razavi, Reza; Hill, Derek L. G.; Rueckert, Daniel

    2004-04-01

    Measuring changes in cardiac motion patterns can assist in diagnosing the onset of arrhythmia and ischaemia and in the follow-up of treatment. This work presents a methodology for measuring such motion changes from MR images. Non-rigid registration is used to track cardiac motion in a sequence of 3D tagged MR images. We use a cylindrical coordinate system to subdivide the myocardium into smaller anatomically meaningful regions and to express motion derived measurements such as displacement and strain for each myocardial region during the cardiac cycle. In the first experiment we have evaluated the proposed methods using synthetic image sequences where the ground truth was available. These images were generated using a cardiac motion simulator for tagged MRI. Normal and abnormal motion fields were produced by modifying parameters in a small region of the myocardium. In the second experiment we have acquired two separate tagged MR image sequences from five healthy volunteers. Both acquisitions have been carried out without moving the volunteer inside the scanner, thus avoiding potential misregistration errors due to subject motion between scans. In addition, one of volunteers was subjected to stress during one of the scans. In the final experiment we acquired tagged MR images from a patient with super-ventricular tachyarrhythmia, before and after radio frequency ablation. The image acquisition and catheter intervention were performed with a combined X-ray and MRI system. Detection results were correct on synthetic data and no region was incorrectly classified as having significant changes in the repetition studies. Significant changes in motion pattern were measured in the stress and ablation studies. Furthermore, results seem to corroborate that the ablation regularised cardiac contraction.

  1. Change Detection of Mobile LIDAR Data Using Cloud Computing

    NASA Astrophysics Data System (ADS)

    Liu, Kun; Boehm, Jan; Alis, Christian

    2016-06-01

    Change detection has long been a challenging problem although a lot of research has been conducted in different fields such as remote sensing and photogrammetry, computer vision, and robotics. In this paper, we blend voxel grid and Apache Spark together to propose an efficient method to address the problem in the context of big data. Voxel grid is a regular geometry representation consisting of the voxels with the same size, which fairly suites parallel computation. Apache Spark is a popular distributed parallel computing platform which allows fault tolerance and memory cache. These features can significantly enhance the performance of Apache Spark and results in an efficient and robust implementation. In our experiments, both synthetic and real point cloud data are employed to demonstrate the quality of our method.

  2. Long-term change detection from historical photography

    NASA Astrophysics Data System (ADS)

    Yoon, T.; Schenk, T.

    2006-12-01

    There is an increasing awareness in the science community about the potential of utilizing old photography and derived products together with new data for change detection and for extending the timeline as far back as possible. For example recent observations have revealed dramatic changes in the behavior of many ice streams and outlet glaciers in Greenland and Antarctica, ranging from complete shutdown of ice streams to manifold increases in velocity. Most observations are typically from the comparatively short time period since the beginning of the civilian satellite imagery (1980s), with most quantitative measurements starting only 10-15 years ago. To evaluate whether ongoing observed changes are climatically significant, changes must be determined over longer time frames. Earlier terrestrial and aerial photography and maps indeed exist and the objective of the project to disseminate these historical data and to develop techniques and tools for combining (fusing) old and new data in order to compile long-term time series of changes in the polar regions, for example in ice extent, velocity and surface elevations. The presentation focuses on new methodologies and interdisciplinary approaches that greatly facilitate the use of old photography for quantitative studies in the polar regions. An absolute prerequisite for the successful use of old photography is a rigorous registration, either with other sensory input data or with respect to 3D reference systems. Recent advances in digital photogrammetry allow registration with linear features, such as lines, curves and free-form lines without the need for identifying identical points. The concept of sensor invariant features was developed to register such disparate data sets as aerial imagery and 3D laser point clouds, originating from satellite laser altimetry or airborne laser scanning systems. Examples illustrating these concepts are shown from the Transantarctic Mountains, including the registration of aerial

  3. Tapping into the Hexagon spy imagery database: A new automated pipeline for geomorphic change detection

    NASA Astrophysics Data System (ADS)

    Maurer, Joshua; Rupper, Summer

    2015-10-01

    Declassified historical imagery from the Hexagon spy satellite database has near-global coverage, yet remains a largely untapped resource for geomorphic change studies. Unavailable satellite ephemeris data make DEM (digital elevation model) extraction difficult in terms of time and accuracy. A new fully-automated pipeline for DEM extraction and image orthorectification is presented which yields accurate results and greatly increases efficiency over traditional photogrammetric methods, making the Hexagon image database much more appealing and accessible. A 1980 Hexagon DEM is extracted and geomorphic change computed for the Thistle Creek Landslide region in the Wasatch Range of North America to demonstrate an application of the new method. Surface elevation changes resulting from the landslide show an average elevation decrease of 14.4 ± 4.3 m in the source area, an increase of 17.6 ± 4.7 m in the deposition area, and a decrease of 30.2 ± 5.1 m resulting from a new roadcut. Two additional applications of the method include volume estimates of material excavated during the Mount St. Helens volcanic eruption and the volume of net ice loss over a 34-year period for glaciers in the Bhutanese Himalayas. These results show the value of Hexagon imagery in detecting and quantifying historical geomorphic change, especially in regions where other data sources are limited.

  4. Analyzing the auditory scene: neurophysiologic evidence of a dissociation between detection of regularity and detection of change.

    PubMed

    Pannese, Alessia; Herrmann, Christoph S; Sussman, Elyse

    2015-05-01

    Detecting regularity and change in the environment is crucial for survival, as it enables making predictions about the world and informing goal-directed behavior. In the auditory modality, the detection of regularity involves segregating incoming sounds into distinct perceptual objects (stream segregation). The detection of change from this within-stream regularity is associated with the mismatch negativity, a component of auditory event-related brain potentials (ERPs). A central unanswered question is how the detection of regularity and the detection of change are interrelated, and whether attention affects the former, the latter, or both. Here we show that the detection of regularity and the detection of change can be empirically dissociated, and that attention modulates the detection of change without precluding the detection of regularity, and the perceptual organization of the auditory background into distinct streams. By applying frequency spectra analysis on the EEG of subjects engaged in a selective listening task, we found distinct peaks of ERP synchronization, corresponding to the rhythm of the frequency streams, independently of whether the stream was attended or ignored. Our results provide direct neurophysiological evidence of regularity detection in the auditory background, and show that it can occur independently of change detection and in the absence of attention.

  5. Detecting Change in Landscape Greenness over Large Areas: An Example for New Mexico, USA

    EPA Science Inventory

    Monitoring and quantifying changes in vegetation cover over large areas using remote sensing can potentially detect large-scale, slow changes (e.g., climate change), as well as more local and rapid changes (e.g., fire, land development). A useful indicator for detecting change i...

  6. Updating National Topographic Data Base Using Change Detection Methods

    NASA Astrophysics Data System (ADS)

    Keinan, E.; Felus, Y. A.; Tal, Y.; Zilberstien, O.; Elihai, Y.

    2016-06-01

    The traditional method for updating a topographic database on a national scale is a complex process that requires human resources, time and the development of specialized procedures. In many National Mapping and Cadaster Agencies (NMCA), the updating cycle takes a few years. Today, the reality is dynamic and the changes occur every day, therefore, the users expect that the existing database will portray the current reality. Global mapping projects which are based on community volunteers, such as OSM, update their database every day based on crowdsourcing. In order to fulfil user's requirements for rapid updating, a new methodology that maps major interest areas while preserving associated decoding information, should be developed. Until recently, automated processes did not yield satisfactory results, and a typically process included comparing images from different periods. The success rates in identifying the objects were low, and most were accompanied by a high percentage of false alarms. As a result, the automatic process required significant editorial work that made it uneconomical. In the recent years, the development of technologies in mapping, advancement in image processing algorithms and computer vision, together with the development of digital aerial cameras with NIR band and Very High Resolution satellites, allow the implementation of a cost effective automated process. The automatic process is based on high-resolution Digital Surface Model analysis, Multi Spectral (MS) classification, MS segmentation, object analysis and shape forming algorithms. This article reviews the results of a novel change detection methodology as a first step for updating NTDB in the Survey of Israel.

  7. Applications of the automatic change detection for disaster monitoring by the knowledge-based framework

    NASA Astrophysics Data System (ADS)

    Tadono, T.; Hashimoto, S.; Onosato, M.; Hori, M.

    2012-11-01

    Change detection is a fundamental approach in utilization of satellite remote sensing image, especially in multi-temporal analysis that involves for example extracting damaged areas by a natural disaster. Recently, the amount of data obtained by Earth observation satellites has increased significantly owing to the increasing number and types of observing sensors, the enhancement of their spatial resolution, and improvements in their data processing systems. In applications for disaster monitoring, in particular, fast and accurate analysis of broad geographical areas is required to facilitate efficient rescue efforts. It is expected that robust automatic image interpretation is necessary. Several algorithms have been proposed in the field of automatic change detection in past, however they are still lack of robustness for multi purposes, an instrument independency, and accuracy better than a manual interpretation. We are trying to develop a framework for automatic image interpretation using ontology-based knowledge representation. This framework permits the description, accumulation, and use of knowledge drawn from image interpretation. Local relationships among certain concepts defined in the ontology are described as knowledge modules and are collected in the knowledge base. The knowledge representation uses a Bayesian network as a tool to describe various types of knowledge in a uniform manner. Knowledge modules are synthesized and used for target-specified inference. The results applied to two types of disasters by the framework without any modification and tuning are shown in this paper.

  8. DSM generation using multiple radar data for relief change detection in North Peloponnese

    NASA Astrophysics Data System (ADS)

    Nikolakopoulos, Konstantinos G.; Kyriou, Aggeliki; Sabatakakis, Nikolaos; Anastassopoulos, Vassilis

    2016-08-01

    Interferometry constitutes a technique of acquisition height information with a range of applications, such as Digital Surface Model (DSM) generation in order to monitoring the Earth's surface. This work is focused on interferometric DSM creation utilizing radar data of Sentinel-1 and TerraSAR-X missions, covering the wider area of Northern Peloponnese. This area is characterized of loose geological formations and intense active tectonics resulting in continuous and intense relief changes. In this context, the accuracy and the update of the DSMs is essential in order to detect and map any terrain change. The selection of Sentinel-1 and TerraSAR-X images was based on the fact that both missions provide timely, with short revisiting period and satisfactory spatial resolution data. In particular, two ranges of radar data from both missions were submitted in interferometric process aimed at DSM creation. The produced DSMs were compared both visually and statistically to a very accurate reference DSM produced from airphotos by the Greek Cadastral. Furthermore, in order to estimate the accuracy of the DSMs and detect variations of terrain's surface, points of known elevation have been used. 2D RMSE, correlation and the percentile value were computed and the results are presented.

  9. Linear and kernel methods for multi- and hypervariate change detection

    NASA Astrophysics Data System (ADS)

    Nielsen, Allan A.; Canty, Morton J.

    2010-10-01

    The iteratively re-weighted multivariate alteration detection (IR-MAD) algorithm may be used both for unsuper- vised change detection in multi- and hyperspectral remote sensing imagery as well as for automatic radiometric normalization of multi- or hypervariate multitemporal image sequences. Principal component analysis (PCA) as well as maximum autocorrelation factor (MAF) and minimum noise fraction (MNF) analyses of IR-MAD images, both linear and kernel-based (which are nonlinear), may further enhance change signals relative to no-change background. The kernel versions are based on a dual formulation, also termed Q-mode analysis, in which the data enter into the analysis via inner products in the Gram matrix only. In the kernel version the inner products of the original data are replaced by inner products between nonlinear mappings into higher dimensional feature space. Via kernel substitution, also known as the kernel trick, these inner products between the mappings are in turn replaced by a kernel function and all quantities needed in the analysis are expressed in terms of the kernel function. This means that we need not know the nonlinear mappings explicitly. Kernel principal component analysis (PCA), kernel MAF and kernel MNF analyses handle nonlinearities by implicitly transforming data into high (even innite) dimensional feature space via the kernel function and then performing a linear analysis in that space. In image analysis the Gram matrix is often prohibitively large (its size is the number of pixels in the image squared). In this case we may sub-sample the image and carry out the kernel eigenvalue analysis on a set of training data samples only. To obtain a transformed version of the entire image we then project all pixels, which we call the test data, mapped nonlinearly onto the primal eigenvectors. IDL (Interactive Data Language) implementations of IR-MAD, automatic radiometric normalization and kernel PCA/MAF/MNF transformations have been written

  10. Automatic detection of surface changes on Mars - a status report

    NASA Astrophysics Data System (ADS)

    Sidiropoulos, Panagiotis; Muller, Jan-Peter

    2016-10-01

    Orbiter missions have acquired approximately 500,000 high-resolution visible images of the Martian surface, covering an area approximately 6 times larger than the overall area of Mars. This data abundance allows the scientific community to examine the Martian surface thoroughly and potentially make exciting new discoveries. However, the increased data volume, as well as its complexity, generate problems at the data processing stages, which are mainly related to a number of unresolved issues that batch-mode planetary data processing presents. As a matter of fact, the scientific community is currently struggling to scale the common ("one-at-a-time" processing of incoming products by expert scientists) paradigm to tackle the large volumes of input data. Moreover, expert scientists are more or less forced to use complex software in order to extract input information for their research from raw data, even though they are not data scientists themselves.Our work within the STFC and EU FP7 i-Mars projects aims at developing automated software that will process all of the acquired data, leaving domain expert planetary scientists to focus on their final analysis and interpretation. Moreover, after completing the development of a fully automated pipeline that processes automatically the co-registration of high-resolution NASA images to ESA/DLR HRSC baseline, our main goal has shifted to the automated detection of surface changes on Mars. In particular, we are developing a pipeline that uses as an input multi-instrument image pairs, which are processed by an automated pipeline, in order to identify changes that are correlated with Mars surface dynamic phenomena. The pipeline has currently been tested in anger on 8,000 co-registered images and by the time of DPS/EPSC we expect to have processed many tens of thousands of image pairs, producing a set of change detection results, a subset of which will be shown in the presentation.The research leading to these results has received

  11. Detection of impervious surface change with multitemporal Landsat images in an urban-rural frontier

    PubMed Central

    Lu, Dengsheng; Moran, Emilio; Hetrick, Scott

    2011-01-01

    Mapping and monitoring impervious surface dynamic change in a complex urban-rural frontier with medium or coarse spatial resolution images is a challenge due to the mixed pixel problem and the spectral confusion between impervious surfaces and other non-vegetation land covers. This research selected Lucas do Rio Verde County in Mato Grosso State, Brazil as a case study to improve impervious surface estimation performance by the integrated use of Landsat and QuickBird images and to monitor impervious surface change by analyzing the normalized multitemporal Landsat-derived fractional impervious surfaces. This research demonstrates the importance of two step calibrations. The first step is to calibrate the Landsat-derived fraction impervious surface values through the established regression model based on the QuickBird-derived impervious surface image in 2008. The second step is to conduct the normalization between the calibrated 2008 impervious surface image with other dates of impervious surface images. This research indicates that the per-pixel based method overestimates the impervious surface area in the urban-rural frontier by 50-60%. In order to accurately estimate impervious surface area, it is necessary to map the fractional impervious surface image and further calibrate the estimates with high spatial resolution images. Also normalization of the multitemporal fractional impervious surface images is needed to reduce the impacts from different environmental conditions, in order to effectively detect the impervious surface dynamic change in a complex urban-rural frontier. The procedure developed in this paper for mapping and monitoring impervious surface area is especially valuable in urban-rural frontiers where multitemporal Landsat images are difficult to be used for accurately extracting impervious surface features based on traditional per-pixel based classification methods as they cannot effectively handle the mixed pixel problem. PMID:21552379

  12. A new statistical approach to climate change detection and attribution

    NASA Astrophysics Data System (ADS)

    Ribes, Aurélien; Zwiers, Francis W.; Azaïs, Jean-Marc; Naveau, Philippe

    2016-04-01

    We propose here a new statistical approach to climate change detection and attribution that is based on additive decomposition and simple hypothesis testing. Most current statistical methods for detection and attribution rely on linear regression models where the observations are regressed onto expected response patterns to different external forcings. These methods do not use physical information provided by climate models regarding the expected response magnitudes to constrain the estimated responses to the forcings. Climate modelling uncertainty is difficult to take into account with regression based methods and is almost never treated explicitly. As an alternative to this approach, our statistical model is only based on the additivity assumption; the proposed method does not regress observations onto expected response patterns. We introduce estimation and testing procedures based on likelihood maximization, and show that climate modelling uncertainty can easily be accounted for. Some discussion is provided on how to practically estimate the climate modelling uncertainty based on an ensemble of opportunity. Our approach is based on the "models are statistically indistinguishable from the truth" paradigm, where the difference between any given model and the truth has the same distribution as the difference between any pair of models, but other choices might also be considered. The properties of this approach are illustrated and discussed based on synthetic data. Lastly, the method is applied to the linear trend in global mean temperature over the period 1951-2010. Consistent with the last IPCC assessment report, we find that most of the observed warming over this period (+0.65 K) is attributable to anthropogenic forcings (+0.67 ± 0.12 K, 90 % confidence range), with a very limited contribution from natural forcings (-0.01± 0.02 K).

  13. Change Detection and Dynamic Analysis Based on Remote Sensing Images

    NASA Astrophysics Data System (ADS)

    Luzi, G.; Crosetto, M.; Devanthéry, N.; Cuevas, M.; Meng, X.

    2013-08-01

    A radar uses the time elapsed between the transmission and reception of an electromagnetic waveform to locate targets present in the illuminated area. Different objects will reflect the radiation with different intensities and phase. The signal provided by standard radar is a profile of the intensity backscattered from the scene as a function of the distance. The resolution, i.e. the capability to distinguish different targets, is related to instrumental parameters and, for conventional radar, is in the range of tens of centimetres. The elementary sampling volume of a radar measurement is usually called radar bin. A radar image can be obtained when an azimuth and a range resolution is available, and this can be attained in different ways: performing a mechanical scanning of the antenna, the most familiar mode used for surveillance, meteorological radar etc, or modifying its spatial features by changing the characteristics of the radiated signal or finally through a specific processing of the acquired data, as in the case of Synthetic Aperture Radar (SAR). In this paper only 1D data without any cross range resolution are used. The vibration of a target corresponds to a small and rapid variation of the radar-target distance to which the phase of the received signal is related. Coherent radar is able to provide measurements of the phase variation along time exploiting the interferometric technique. The received radar signals permits to retrieve distance variations of the observed objects in the order of small fractions of the transmitted wavelength, by comparing the phase of signals acquired at different times. Use a short span bridge as a test-bed this study investigates the actual capability of a Real Aperture Radar (RAR) interferometer to detect the natural vibration caused by wind or pass pedestrians. It is found that RAR can pick up bridge displacements of a few tens of μm and detect a wide range of vibrations.

  14. Researches on the Land-Use Change Detection of Mine Area Based on Tm/etm Images

    NASA Astrophysics Data System (ADS)

    Qin, Y.; Liling, H.; Min, Y.; Yi, L.

    2013-07-01

    With the economic development and population growth, land use status is changing rapidly in Chinese urban. Since the remote sensing technology can analyze and detect the land use information quickly and accurately, it has been widely applied to obtain the land use/land cover change (LUCC) information today. The land surface destroy occurred in mineral resources exploration will result in a lot of environmental problems in coal mine areas. But there are few research in small and medium-sized cities and coal mine areas. So Peixian is used as the study area in the paper. The Landsat TM/ETM images spanning 3 years and thematic map are adopted to detect the land-use change of the area. In order to improve the classification results, we built an optimized classification model adapting classic SVM method, which was defined "a feature weighted SVM classifier using mixed kernel function". Based on geostatistic and multi-scale statistical knowledge, we calculated the transformation matrix and dynamic index of land-use types, from which we conducted quantitative analysis and the driving force on the mine land-use change of Peixian. Then, we can achieve resource dynamic change detection of four years in Peixian area, analyze the effect of the surface land-use change due to mineral exploration and obtain the causes of land-use change.

  15. Testing Distributed Parameter Hypotheses for the Detection of Climate Change.

    NASA Astrophysics Data System (ADS)

    Kheshgi, Haroon S.; White, Benjamin S.

    2001-08-01

    A general statistical methodology, based on testing alternative distributed parameter hypotheses, is proposed as a method for deciding whether or not anthropogenic influences are causing climate change. This methodology provides a framework for including known uncertainties in the definition of the hypotheses by allowing model parameters to be specified by probability distributions and thereby allowing the definition of more realistic hypotheses. The method can be used to derive the unique statistical test that minimizes errors in test conclusions. The method is applied to illustrative detection problems by first defining alternative hypotheses for global mean temperature; second, deriving the most powerful test and calculating its statistics; third, applying the test to observed temperature records; and finally, illustrating the test statistics and results on a receiver or relative operating characteristic curve showing the relation between false positive and false negative test errors. It is demonstrated, with an illustrative example, that proper accounting for the uncertainty in all the parameters can produce very different statistical conclusions than the conclusions that would be obtained by simply fixing some parameters at nominal values.

  16. Radome effects on coherent change detection radar systems

    NASA Astrophysics Data System (ADS)

    Raynal, Ann Marie; Dubbert, Dale F.; Burns, Bryan L.; Hensley, William H.

    2015-05-01

    A radome, or radar dome, protects a radar system from exposure to the elements. Unfortunately, radomes can affect the radiation pattern of the enclosed antenna. The co-design of a platform's radome and radar is ideal to mitigate any deleterious effects of the radome. However, maintaining structural integrity and other platform flight requirements, particularly when integrating a new radar onto an existing platform, often limits radome electrical design choices. Radars that rely heavily on phase measurements such as monopulse, interferometric, or coherent change detection (CCD) systems require particular attention be paid to components, such as the radome, that might introduce loss and phase variations as a function of the antenna scan angle. Material properties, radome wall construction, overall dimensions, and shape characteristics of a radome can impact insertion loss and phase delay, antenna beamwidth and sidelobe level, polarization, and ultimately the impulse response of the radar, among other things, over the desired radar operating parameters. The precision-guided munitions literature has analyzed radome effects on monopulse systems for well over half a century. However, to the best of our knowledge, radome-induced errors on CCD performance have not been described. The impact of radome material and wall construction, shape, dimensions, and antenna characteristics on CCD is examined herein for select radar and radome examples using electromagnetic simulations.

  17. Photogrammetric processing of hexagon stereo data for change detection studies

    NASA Astrophysics Data System (ADS)

    Padmanabha, E. Anantha; Shashivardhan Reddy, P.; Narender, B.; Muralikrishnan, S.; Dadhwal, V. K.

    2014-11-01

    Hexagon satellite data acquired as a part of USA Corona program has been declassified and is accessible to general public. This image data was acquired in high resolution much before the launch of civilian satellites. However the non availability of interior and exterior orientation parameters is the main bottle neck in photogrammetric processing of this data. In the present study, an attempt was made to orient and adjust Hexagon stereo pair through Rigorous Sensor Model (RSM) and Rational Function Models (RFM). The study area is part of Western Ghats in India. For rigorous sensor modelling an arbitrary camera file is generated based on the information available in the literature and few assumptions. A terrain dependent RFM was generated for the stereo data using Cartosat-1 reference data. The model accuracy achieved for both RSM and RFM was better than one pixel. DEM and orthoimage were generated with a spacing of 50 m and Ground Sampling Distance (GSD) of 6 m to carry out the change detection with a special emphasis on water bodies with reference to recent Cartosat-1 data. About 72 new water bodies covering an area of 2300 hectares (23 sq. km) were identified in Cartosat-1 orthoimage that were not present in Hexagon data. The image data from various Corona programs like Hexagon provide a rich source of information for temporal studies. However photogrammetric processing of the data is a bit tedious due to lack of information about internal sensor geometry.

  18. Geomorphological change detection of fluvial processes of lower Siret channel using LIDAR data

    NASA Astrophysics Data System (ADS)

    Niculita, Mihai; Obreja, Florin; Boca, Bogdan

    2015-04-01

    :121-134. Lague D., Brodu N., Leroux J., 2013. Accurate 3D comparison of complex topography with terrestrial laser scanner: application to the Rangitikei canyon (N-Z), ISPRS journal of Photogrammmetry and Remote Sensing, 80:10-26. James L.A., Hodgson M.E., Ghoshal S., Latiolais M.M., 2012. Geomorphic change detection using historic maps and DEM differencing: the temporal dimension of geospatial analysis. Geomorphology, 137:181-198. Nedelcu G., Borcan M., Branescu E., Petre C., Teleanu B., Preda A., Murafa R., 2011. Exceptional floods from the years 2008 and 2010 in Siret river basin, Proceedings of the Annual Scientific Conference of National Romanian Institute of Hydrology and Water Administration, 1-3 November 2011. (in Romanian) Olariu P., Obreja F., Obreja I., 2009. Some aspects regarding the sediment transit from Trotus catchment and lower sector of Siret river during the exceptional floods from 1991 and 2005, Annals of Stefan cel Mare University of Suceava, XVIII:93-104.(in Romanian) Serbu M., Obreja F., Olariu P., 2009. The 2008 floods from upper Siret catchment. Causes, effects, evaluation, Hidrotechnics, 54(12):1-38. (in Romanian) Wheaton J.M., Brasington J., Darby S., Sear D., 2009. Accounting for uncertainty in DEMs from repeat topographic surveys: improved sediment budgets. Earth Surface Processes and Landforms, 35(2):136-156.

  19. Topographic change detection at select archeological sites in Grand Canyon National Park, Arizona, 2007–2010

    USGS Publications Warehouse

    Collins, Brian D.; Corbett, Skye C.; Fairley, Helen C.; Minasian, Diane L.; Kayen, Robert; Dealy, Timothy P.; Bedford, David R.

    2012-01-01

    Human occupation in Grand Canyon, Arizona, dates from at least 11,000 years before present to the modern era. For most of this period, the only evidence of human occupation in this iconic landscape is provided by archeological sites. Because of the dynamic nature of this environment, many archeological sites are subject to relatively rapid topographic change. Quantifying the extent, magnitude, and cause of such change is important for monitoring and managing these archeological sites. Such quantification is necessary to help inform the continuing debate on whether and how controlled releases from Glen Canyon Dam, located immediately upstream of Grand Canyon National Park, are affecting site erosion rates, artifact transport, and archeological resource preservation along the Colorado River in Grand Canyon. Although long-term topographic change resulting from a variety of natural processes is inherent in the Grand Canyon region, continued erosion of archeological sites threatens both the archeological resources and our future ability to study evidence of past cultural habitation. Thus, this subject is of considerable interest to National Park Service managers and other stakeholders in the Glen Canyon Dam Adaptive Management Program. Understanding the causes and effects of archeological site erosion requires a knowledge of several factors, including the location, timing, and magnitude of the changes occurring in relation to archeological resources, the rates of change, and the relative contribution of potential causes. These potential causes include sediment depletion associated with managed flows from Glen Canyon Dam, site-specific weather and overland flow patterns, visitor impacts, and long-term regional climate change. To obtain this information, highly accurate, spatially specific data are needed from sites undergoing change. Using terrestrial lidar techniques, and building upon three previous surveys of archeological sites performed in 2006 and 2007, we

  20. A non-contact method based on multiple signal classification algorithm to reduce the measurement time for accurately heart rate detection

    NASA Astrophysics Data System (ADS)

    Bechet, P.; Mitran, R.; Munteanu, M.

    2013-08-01

    Non-contact methods for the assessment of vital signs are of great interest for specialists due to the benefits obtained in both medical and special applications, such as those for surveillance, monitoring, and search and rescue. This paper investigates the possibility of implementing a digital processing algorithm based on the MUSIC (Multiple Signal Classification) parametric spectral estimation in order to reduce the observation time needed to accurately measure the heart rate. It demonstrates that, by proper dimensioning the signal subspace, the MUSIC algorithm can be optimized in order to accurately assess the heart rate during an 8-28 s time interval. The validation of the processing algorithm performance was achieved by minimizing the mean error of the heart rate after performing simultaneous comparative measurements on several subjects. In order to calculate the error the reference value of heart rate was measured using a classic measurement system through direct contact.

  1. Multiscale Region-Level VHR Image Change Detection via Sparse Change Descriptor and Robust Discriminative Dictionary Learning.

    PubMed

    Xu, Yuan; Ding, Kun; Huo, Chunlei; Zhong, Zisha; Li, Haichang; Pan, Chunhong

    2015-01-01

    Very high resolution (VHR) image change detection is challenging due to the low discriminative ability of change feature and the difficulty of change decision in utilizing the multilevel contextual information. Most change feature extraction techniques put emphasis on the change degree description (i.e., in what degree the changes have happened), while they ignore the change pattern description (i.e., how the changes changed), which is of equal importance in characterizing the change signatures. Moreover, the simultaneous consideration of the classification robust to the registration noise and the multiscale region-consistent fusion is often neglected in change decision. To overcome such drawbacks, in this paper, a novel VHR image change detection method is proposed based on sparse change descriptor and robust discriminative dictionary learning. Sparse change descriptor combines the change degree component and the change pattern component, which are encoded by the sparse representation error and the morphological profile feature, respectively. Robust change decision is conducted by multiscale region-consistent fusion, which is implemented by the superpixel-level cosparse representation with robust discriminative dictionary and the conditional random field model. Experimental results confirm the effectiveness of the proposed change detection technique.

  2. Multiscale Region-Level VHR Image Change Detection via Sparse Change Descriptor and Robust Discriminative Dictionary Learning

    PubMed Central

    Xu, Yuan; Ding, Kun; Huo, Chunlei; Zhong, Zisha; Li, Haichang; Pan, Chunhong

    2015-01-01

    Very high resolution (VHR) image change detection is challenging due to the low discriminative ability of change feature and the difficulty of change decision in utilizing the multilevel contextual information. Most change feature extraction techniques put emphasis on the change degree description (i.e., in what degree the changes have happened), while they ignore the change pattern description (i.e., how the changes changed), which is of equal importance in characterizing the change signatures. Moreover, the simultaneous consideration of the classification robust to the registration noise and the multiscale region-consistent fusion is often neglected in change decision. To overcome such drawbacks, in this paper, a novel VHR image change detection method is proposed based on sparse change descriptor and robust discriminative dictionary learning. Sparse change descriptor combines the change degree component and the change pattern component, which are encoded by the sparse representation error and the morphological profile feature, respectively. Robust change decision is conducted by multiscale region-consistent fusion, which is implemented by the superpixel-level cosparse representation with robust discriminative dictionary and the conditional random field model. Experimental results confirm the effectiveness of the proposed change detection technique. PMID:25918748

  3. Feasibility of a portable morphological scene change detection security system for field programmable gate arrays (FPGA)

    NASA Astrophysics Data System (ADS)

    Tickle, Andrew J.; Smith, Jeremy S.; Wu, Q. Henry

    2008-04-01

    In this paper, there is an investigation into the possibility of executing a Morphological Scene Change Detection (MSCD) system on a Field Programmable Gate Array (FPGA), which would allow its set up in virtually any location, with its purpose to detect intruders and raise an alarm to call security personal, and a signal to initial a lockdown of the local area. This paper will include how the system was scaled down from the full building multi-computer system, to an FPGA without losing any functionality using Altera's DSP Builder development tool. Also included is the analysis of the different situations which the system would encounter in the field, and their respective alarm triggering levels, these include indoors, outdoors, close-up, distance, high-brightness, low-light, bad weather, etc. The triggering mechanism is a pixel counter and threshold system, and its adaptive design will be included. All the results shown in this paper, will also be verified by MATLAB m-files running on a full desktop PC, to show that the results obtained from the FPGA based system are accurate.

  4. Detection of changes in leaf water content using near- and middle-infrared reflectances

    NASA Technical Reports Server (NTRS)

    Hunt, E. Raymond, Jr.; Rock, Barrett N.

    1989-01-01

    A method to detect plant water stress by remote sensing is proposed using indices of near-IR and mid-IR wavelengths. The ability of the Leaf Water Content Index (LWCI) to determine leaf relative water content (RWC) is tested on species with different leaf morphologies. The way in which the Misture Stress Index (MSI) varies with RWC is studied. On test with several species, it is found that LWCI is equal to RWC, although the reflectances at 1.6 microns for two different RWC must be known to accurately predict unknown RWC. A linear correlation is found between MSI and RWC with each species having a different regression equation. Also, MSI is correlated with log sub 10 Equivalent Water Thickness (EWT) with data for all species falling on the same regression line. It is found that the minimum significant change of RWC that could be detected by appying the linear regression equation of MSI to EWT is 52 percent. Because the natural RWC variation from water stress is about 20 percent for most species, it is concluded that the near-IR and mid-IR reflectances cannot be used to remotely sense water stress.

  5. Space-based detection of wetlands' surface water level changes from L-band SAR interferometry

    USGS Publications Warehouse

    Wdowinski, S.; Kim, S.-W.; Amelung, F.; Dixon, T.H.; Miralles-Wilhelm, F.; Sonenshein, R.

    2008-01-01

    Interferometric processing of JERS-1 L-band Synthetic Aperture Radar (SAR) data acquired over south Florida during 1993-1996 reveals detectable surface changes in the Everglades wetlands. Although our study is limited to south Florida it has implication for other large-scale wetlands, because south Florida wetlands have diverse vegetation types and both managed and natural flow environments. Our analysis reveals that interferometric coherence level is sensitive to wetland vegetation type and to the interferogram time span. Interferograms with time spans less than six months maintain phase observations for all wetland types, allowing characterization of water level changes in different wetland environments. The most noticeable changes occur between the managed and the natural flow wetlands. In the managed wetlands, fringes are organized, follow patterns related to some of the managed water control structures and have high fringe-rate. In the natural flow areas, fringes are irregular and have a low fringe-rate. The high fringe rate in managed areas reflects dynamic water topography caused by high flow rate due to gate operation. Although this organized fringe pattern is not characteristic of most large-scale wetlands, the high level of water level change enables accurate estimation of the wetland InSAR technique, which lies in the range of 5-10??cm. The irregular and low rate fringe pattern in the natural flow area reflects uninterrupted flow that diffuses water efficiently and evenly. Most of the interferograms in the natural flow area show an elongated fringe located along the transitional zone between salt- and fresh-water wetlands, reflecting water level changes due to ocean tides. ?? 2007 Elsevier Inc. All rights reserved.

  6. Topographic Change Detection at Select Archeological Sites in Grand Canyon National Park, Arizona, 2006-2007

    USGS Publications Warehouse

    Collins, Brian D.; Minasian, Diane L.; Kayen, Robert

    2009-01-01

    Topographic change of archeological sites within the Colorado River corridor of Grand Canyon National Park (GCNP) is a subject of interest to National Park Service managers and other stakeholders in the Glen Canyon Dam Adaptive Management Program. Although long-term topographic change resulting from a variety of natural processes is typical in the Grand Canyon region, a continuing debate exists on whether and how controlled releases from Glen Canyon Dam, located immediately upstream of GCNP, are impacting rates of site erosion, artifact transport, and the preservation of archeological resources. Continued erosion of archeological sites threatens both the archeological resources and our future ability to study evidence of past cultural habitation. Understanding the causes and effects of archaeological site erosion requires a knowledge of several factors including the location and magnitude of the changes occurring in relation to archeological resources, the rate of the changes, and the relative contribution of several potential causes, including sediment depletion associated with managed flows from Glen Canyon Dam, site-specific weather patterns, visitor impacts, and long-term climate change. To obtain this information, highly accurate, spatially specific data are needed from sites undergoing change. Using terrestrial lidar data collection techniques and novel TIN- and GRID-based change-detection post-processing methods, we analyzed topographic data for nine archeological sites. The data were collected using three separate data collection efforts spanning 16 months (May 2006 to September 2007). Our results documented positive evidence of erosion, deposition, or both at six of the nine sites investigated during this time interval. In addition, we observed possible signs of change at two of the other sites. Erosion was concentrated in established gully drainages and averaged 12 cm to 17 cm in depth with maximum depths of 50 cm. Deposition was concentrated at specific

  7. Nonparametric decomposition of quasi-periodic time series for change-point detection

    NASA Astrophysics Data System (ADS)

    Artemov, Alexey; Burnaev, Evgeny; Lokot, Andrey

    2015-12-01

    The paper is concerned with the sequential online change-point detection problem for a dynamical system driven by a quasiperiodic stochastic process. We propose a multicomponent time series model and an effective online decomposition algorithm to approximate the components of the models. Assuming the stationarity of the obtained components, we approach the change-point detection problem on a per-component basis and propose two online change-point detection schemes corresponding to two real-world scenarios. Experimental results for decomposition and detection algorithms for synthesized and real-world datasets are provided to demonstrate the efficiency of our change-point detection framework.

  8. Electrophysiological Correlates of Automatic Visual Change Detection in School-Age Children

    ERIC Educational Resources Information Center

    Clery, Helen; Roux, Sylvie; Besle, Julien; Giard, Marie-Helene; Bruneau, Nicole; Gomot, Marie

    2012-01-01

    Automatic stimulus-change detection is usually investigated in the auditory modality by studying Mismatch Negativity (MMN). Although the change-detection process occurs in all sensory modalities, little is known about visual deviance detection, particularly regarding the development of this brain function throughout childhood. The aim of the…

  9. Hydrography change detection: the usefulness of surface channels derived From LiDAR DEMs for updating mapped hydrography

    USGS Publications Warehouse

    Poppenga, Sandra K.; Gesch, Dean B.; Worstell, Bruce B.

    2013-01-01

    The 1:24,000-scale high-resolution National Hydrography Dataset (NHD) mapped hydrography flow lines require regular updating because land surface conditions that affect surface channel drainage change over time. Historically, NHD flow lines were created by digitizing surface water information from aerial photography and paper maps. Using these same methods to update nationwide NHD flow lines is costly and inefficient; furthermore, these methods result in hydrography that lacks the horizontal and vertical accuracy needed for fully integrated datasets useful for mapping and scientific investigations. Effective methods for improving mapped hydrography employ change detection analysis of surface channels derived from light detection and ranging (LiDAR) digital elevation models (DEMs) and NHD flow lines. In this article, we describe the usefulness of surface channels derived from LiDAR DEMs for hydrography change detection to derive spatially accurate and time-relevant mapped hydrography. The methods employ analyses of horizontal and vertical differences between LiDAR-derived surface channels and NHD flow lines to define candidate locations of hydrography change. These methods alleviate the need to analyze and update the nationwide NHD for time relevant hydrography, and provide an avenue for updating the dataset where change has occurred.

  10. Two stages of parafoveal processing during reading: Evidence from a display change detection task.

    PubMed

    Angele, Bernhard; Slattery, Timothy J; Rayner, Keith

    2016-08-01

    We used a display change detection paradigm (Slattery, Angele, & Rayner Human Perception and Performance, 37, 1924-1938 2011) to investigate whether display change detection uses orthographic regularity and whether detection is affected by the processing difficulty of the word preceding the boundary that triggers the display change. Subjects were significantly more sensitive to display changes when the change was from a nonwordlike preview than when the change was from a wordlike preview, but the preview benefit effect on the target word was not affected by whether the preview was wordlike or nonwordlike. Additionally, we did not find any influence of preboundary word frequency on display change detection performance. Our results suggest that display change detection and lexical processing do not use the same cognitive mechanisms. We propose that parafoveal processing takes place in two stages: an early, orthography-based, preattentional stage, and a late, attention-dependent lexical access stage.

  11. Comparison of interstimulus intervals on change detection in nondriving and driving scenarios.

    PubMed

    VanWormer, Lisa A; Senkbeil, Sara K; Kass, Steven J

    2014-01-01

    Change detection across disruptions of visual scenes is typically studied using brief durations of the interstimulus interval (ISI) (i.e., up to 300 ms). We investigated change detection across durations that approximate longer, voluntary glances away from a visual scene (i.e., 500-2,000 ms), which are often actualized in driving situations. Experiment 1 found that in nondriving scenarios, change detection performance, as measured by accuracy and response time, decreased as ISI increased. Experiment 2 found that in driving scenarios, change detection for plausible changes also decreased as the ISI increased, but there was no similar decrease in performance for implausible changes. Both Experiments 1 and 2 showed that the necessary number of exposures to the change decreased as ISIs approximated voluntary glances, suggesting that change detection strategies may be modified at longer ISI durations.

  12. Two stages of parafoveal processing during reading: Evidence from a display change detection task.

    PubMed

    Angele, Bernhard; Slattery, Timothy J; Rayner, Keith

    2016-08-01

    We used a display change detection paradigm (Slattery, Angele, & Rayner Human Perception and Performance, 37, 1924-1938 2011) to investigate whether display change detection uses orthographic regularity and whether detection is affected by the processing difficulty of the word preceding the boundary that triggers the display change. Subjects were significantly more sensitive to display changes when the change was from a nonwordlike preview than when the change was from a wordlike preview, but the preview benefit effect on the target word was not affected by whether the preview was wordlike or nonwordlike. Additionally, we did not find any influence of preboundary word frequency on display change detection performance. Our results suggest that display change detection and lexical processing do not use the same cognitive mechanisms. We propose that parafoveal processing takes place in two stages: an early, orthography-based, preattentional stage, and a late, attention-dependent lexical access stage. PMID:26769246

  13. Long-term memory guidance of visuospatial attention in a change-detection paradigm.

    PubMed

    Rosen, Maya L; Stern, Chantal E; Somers, David C

    2014-01-01

    Visual task performance is generally stronger in familiar environments. One reason for this familiarity benefit is that we learn where to direct our visual attention and effective attentional deployment enhances performance. Visual working memory plays a central role in supporting long-term memory guidance of visuospatial attention. We modified a change detection task to create a new paradigm for investigating long-term memory guidance of attention. During the training phase, subjects viewed images in a flicker paradigm and were asked to detect between one and three changes in the images. The test phase required subjects to detect a single change in a one-shot change detection task in which they held all possible locations of changes in visual working memory and deployed attention to those locations to determine if a change occurred. Subjects detected significantly more changes in images for which they had been trained to detect the changes, demonstrating that memory of the images guided subjects in deploying their attention. Moreover, capacity to detect changes was greater for images that had multiple changes during the training phase. In Experiment 2, we observed that capacity to detect changes for the 3-studied change condition increased significantly with more study exposures and capacity was significantly higher than 1, indicating that subjects were able to attend to more than one location. Together, these findings suggest memory and attentional systems interact via working memory such that long-term memory can be used to direct visual spatial attention to multiple locations based on previous experience.

  14. Detection Capability Evaluation on Chang'e-5 Lunar Mineralogical Spectrometer (LMS)

    NASA Astrophysics Data System (ADS)

    Liu, Bin; Ren, Xin; Yan, Wei; Xu, Xuesen; Cai, Tingni; Liu, Dawei; Liu, Jianjun; Li, Chunlai

    2016-04-01

    The Chang'e-5 (CE-5) lunar sample return mission is scheduled to launch in 2017 to bring back lunar regolith and drill samples. The Chang'e-5 Lunar Mineralogical Spectrometer (LMS), as one of the three sets of scientific payload installed on the lander, is used to collect in-situ spectrum and analyze the mineralogical composition of the sampling site. It can also help to select the sampling site , and to compare the measured laboratory spectrum of returned sample with in-situ data. LMS employs acousto-optic tunable filters (AOTFs) and is composed of a VIS/NIR module (0.48μm-1.45μm) and an IR module (1.4μm -3.2μm). It has spectral resolution ranging from 3 to 25 nm, with a field of view (FOV) of 4.24°×4.24°. Unlike Chang'e-3 VIS/NIR Imaging Spectrometer (VNIS), the spectral coverage of LMS is extended from 2.4μm to 3.2μm, which has capability to identify H2O/OH absorption features around 2.7μm. An aluminum plate and an Infragold plate are fixed in the dust cover, being used as calibration targets in the VIS/NIR and IR spectral range respectively when the dust cover is open. Before launch, a ground verification test of LMS needs to be conducted in order to: 1) test and verify the detection capability of LMS through evaluation on the quality of image and spectral data collected for the simulated lunar samples; and 2) evaluate the accuracy of data processing methods by the simulation of instrument working on the moon. The ground verification test will be conducted both in the lab and field. The spectra of simulated lunar regolith/mineral samples will be collected simultaneously by the LMS and two calibrated spectrometers: a FTIR spectrometer (Model 102F) and an ASD FieldSpec 4 Hi-Res spectrometer. In this study, the results of the LMS ground verification test will be reported including the evaluation on the LMS spectral and image data quality, mineral identification and inversion ability, accuracy of calibration and geometric positioning .

  15. A novel asymmetric-loop molecular beacon-based two-phase hybridization assay for accurate and high-throughput detection of multiple drug resistance-conferring point mutations in Mycobacterium tuberculosis.

    PubMed

    Chen, Qinghai; Wu, Nan; Xie, Meng; Zhang, Bo; Chen, Ming; Li, Jianjun; Zhuo, Lisha; Kuang, Hong; Fu, Weiling

    2012-04-01

    The accurate and high-throughput detection of drug resistance-related multiple point mutations remains a challenge. Although the combination of molecular beacons with bio-immobilization technology, such as microarray, is promising, its application is difficult due to the ineffective immobilization of molecular beacons on the chip surface. Here, we propose a novel asymmetric-loop molecular beacon in which the loop consists of 2 parts. One is complementary to a target, while the other is complementary to an oligonucleotide probe immobilized on the chip surface. With this novel probe, a two-phase hybridization assay can be used for simultaneously detecting multiple point mutations. This assay will have advantages, such as easy probe availability, multiplex detection, low background, and high-efficiency hybridization, and may provide a new avenue for the immobilization of molecular beacons and high-throughput detection of point mutations.

  16. Distinct frontal and amygdala correlates of change detection for facial identity and expression

    PubMed Central

    Achaibou, Amal; Loth, Eva

    2016-01-01

    Recruitment of ‘top-down’ frontal attentional mechanisms is held to support detection of changes in task-relevant stimuli. Fluctuations in intrinsic frontal activity have been shown to impact task performance more generally. Meanwhile, the amygdala has been implicated in ‘bottom-up’ attentional capture by threat. Here, 22 adult human participants took part in a functional magnetic resonance change detection study aimed at investigating the correlates of successful (vs failed) detection of changes in facial identity vs expression. For identity changes, we expected prefrontal recruitment to differentiate ‘hit’ from ‘miss’ trials, in line with previous reports. Meanwhile, we postulated that a different mechanism would support detection of emotionally salient changes. Specifically, elevated amygdala activation was predicted to be associated with successful detection of threat-related changes in expression, over-riding the influence of fluctuations in top-down attention. Our findings revealed that fusiform activity tracked change detection across conditions. Ventrolateral prefrontal cortical activity was uniquely linked to detection of changes in identity not expression, and amygdala activity to detection of changes from neutral to fearful expressions. These results are consistent with distinct mechanisms supporting detection of changes in face identity vs expression, the former potentially reflecting top-down attention, the latter bottom-up attentional capture by stimulus emotional salience. PMID:26245835

  17. Distinct frontal and amygdala correlates of change detection for facial identity and expression.

    PubMed

    Achaibou, Amal; Loth, Eva; Bishop, Sonia J

    2016-02-01

    Recruitment of 'top-down' frontal attentional mechanisms is held to support detection of changes in task-relevant stimuli. Fluctuations in intrinsic frontal activity have been shown to impact task performance more generally. Meanwhile, the amygdala has been implicated in 'bottom-up' attentional capture by threat. Here, 22 adult human participants took part in a functional magnetic resonance change detection study aimed at investigating the correlates of successful (vs failed) detection of changes in facial identity vs expression. For identity changes, we expected prefrontal recruitment to differentiate 'hit' from 'miss' trials, in line with previous reports. Meanwhile, we postulated that a different mechanism would support detection of emotionally salient changes. Specifically, elevated amygdala activation was predicted to be associated with successful detection of threat-related changes in expression, over-riding the influence of fluctuations in top-down attention. Our findings revealed that fusiform activity tracked change detection across conditions. Ventrolateral prefrontal cortical activity was uniquely linked to detection of changes in identity not expression, and amygdala activity to detection of changes from neutral to fearful expressions. These results are consistent with distinct mechanisms supporting detection of changes in face identity vs expression, the former potentially reflecting top-down attention, the latter bottom-up attentional capture by stimulus emotional salience.

  18. Visual long-term memory and change blindness: Different effects of pre- and post-change information on one-shot change detection using meaningless geometric objects.

    PubMed

    Nishiyama, Megumi; Kawaguchi, Jun

    2014-11-01

    To clarify the relationship between visual long-term memory (VLTM) and online visual processing, we investigated whether and how VLTM involuntarily affects the performance of a one-shot change detection task using images consisting of six meaningless geometric objects. In the study phase, participants observed pre-change (Experiment 1), post-change (Experiment 2), or both pre- and post-change (Experiment 3) images appearing in the subsequent change detection phase. In the change detection phase, one object always changed between pre- and post-change images and participants reported which object was changed. Results showed that VLTM of pre-change images enhanced the performance of change detection, while that of post-change images decreased accuracy. Prior exposure to both pre- and post-change images did not influence performance. These results indicate that pre-change information plays an important role in change detection, and that information in VLTM related to the current task does not always have a positive effect on performance.

  19. EEG oscillations reflect task effects for the change detection in vocal emotion.

    PubMed

    Chen, Xuhai; Pan, Zhihui; Wang, Ping; Zhang, Lijie; Yuan, Jiajin

    2015-06-01

    How task focus affects recognition of change in vocal emotion remains in debate. In this study, we investigated the role of task focus for change detection in emotional prosody by measuring changes in event-related electroencephalogram (EEG) power. EEG was recorded for prosodies with and without emotion change while subjects performed emotion change detection task (explicit) and visual probe detection task (implicit). We found that vocal emotion change induced theta event-related synchronization during 100-600 ms regardless of task focus. More importantly, vocal emotion change induced significant beta event-related desynchronization during 400-750 ms under explicit instead of implicit task condition. These findings suggest that the detection of emotional changes is independent of task focus, while the task focus effect in neural processing of vocal emotion change is specific to the integration of emotional deviations.

  20. Accurate detection of the tumor clone in peripheral T-cell lymphoma biopsies by flow cytometric analysis of TCR-Vβ repertoire.

    PubMed

    Salameire, Dimitri; Solly, Françoise; Fabre, Blandine; Lefebvre, Christine; Chauvet, Martine; Gressin, Rémy; Corront, Bernadette; Ciapa, Agnès; Pernollet, Martine; Plumas, Joël; Macintyre, Elizabeth; Callanan, Mary B; Leroux, Dominique; Jacob, Marie-Christine

    2012-09-01

    Multiparametric flow cytometry has proven to be a powerful method for detection and immunophenotypic characterization of clonal subsets, particularly in lymphoproliferative disorders of the B-cell lineage. Although in theory promising, this approach has not been comparably fulfilled in mature T-cell malignancies. Specifically, the T-cell receptor-Vβ repertoire analysis in blood can provide strong evidence of clonality, particularly when a single expanded Vß family is detected. The purpose of this study was to determine the relevance of this approach when applied to biopsies, at the site of tumor involvement. To this end, 30 peripheral T-cell lymphoma and 94 control biopsies were prospectively studied. Vβ expansions were commonly detected within CD4+ or CD8+ T cells (97% of peripheral T-cell lymphoma and 54% of non-peripheral T-cell lymphoma cases); thus, not differentiating malignant from reactive processes. Interestingly, we demonstrated that using a standardized evaluation, the detection of a high Vβ expansion was closely associated with diagnosis of peripheral T-cell lymphoma, with remarkable specificity (98%) and sensitivity (90%). This approach also identified eight cases of peripheral T-cell lymphoma that were not detectable by other forms of immunophenotyping. Moreover, focusing Vβ expression analysis to T-cell subsets with aberrant immunophenotypes, we demonstrated that the T-cell clone might be heterogeneous with regard to surface CD7 or CD10 expression (4/11 cases), providing indication on 'phenotypic plasticity'. Finally, among the wide variety of Vβ families, the occurrence of a Vβ17 expansion in five cases was striking. To our knowledge, this is the first report demonstrating the power of T-cell receptor-Vβ repertoire analysis by flow cytometry in biopsies as a basis for peripheral T-cell lymphoma diagnosis and precise T-cell clone identification and characterization.

  1. Techniques for land use change detection using Landsat imagery

    NASA Technical Reports Server (NTRS)

    Angelici, G. L.; Bryant, N. A.; Friedman, S. Z.

    1977-01-01

    A variety of procedures were developed for the delineation of areas of land use change using Landsat Multispectral Scanner data and the generation of statistics revealing the nature of the changes involved (i.e., number of acres changed from rural to urban). Techniques of the Image Based Information System were utilized in all stages of the procedure, from logging the Landsat data and registering two frames of imagery, to extracting the changed areas and printing tabulations of land use change in acres. Two alternative methods of delineating land use change are presented while enumerating the steps of the entire process. The Houston, Texas urban area, and the Orlando, Florida urban area, are used as illustrative examples of various procedures.

  2. Integration of Landsat TM and SPOT HRG Images for Vegetation Change Detection in the Brazilian Amazon.

    PubMed

    Lu, Dengsheng; Batistella, Mateus; Moran, Emilio

    2008-01-01

    Traditional change detection approaches have been proven to be difficult in detecting vegetation changes in the moist tropical regions with multitemporal images. This paper explores the integration of Landsat Thematic Mapper (TM) and SPOT High Resolution Geometric (HRG) instrument data for vegetation change detection in the Brazilian Amazon. A principal component analysis was used to integrate TM and HRG panchromatic data. Vegetation change/non-change was detected with the image differencing approach based on the TM and HRG fused image and the corresponding TM image. A rule-based approach was used to classify the TM and HRG multispectral images into thematic maps with three coarse land-cover classes: forest, non-forest vegetation, and non-vegetation lands. A hybrid approach combining image differencing and post-classification comparison was used to detect vegetation change trajectories. This research indicates promising vegetation change techniques, especially for vegetation gain and loss, even if very limited reference data are available.

  3. Electrophysiological evidence for the hierarchical organization of auditory change detection in the human brain.

    PubMed

    Grimm, Sabine; Escera, Carles; Slabu, Lavinia; Costa-Faidella, Jordi

    2011-03-01

    Auditory change detection has been associated with mismatch negativity (MMN), an event-related potential (ERP) occurring at 100-250 ms after the onset of an acoustic change. Yet, single-unit recordings in animals suggest much faster novelty-specific responses in the auditory system. To investigate change detection in a corresponding early time range in humans, we measured the Middle Latency Response (MLR) and MMN during a controlled frequency oddball paradigm. In addition to MMN, an early effect of change detection was observed at about 40 ms after change onset reflected in an enhancement of the Nb component of the MLR. Both MMN and the Nb effect were shown to be free from confounding influences such as differences in refractoriness. This finding implies that early change detection processes exist in humans upstream of MMN generation, which supports the emerging view of a hierarchical organization of change detection expanding along multiple levels of the auditory pathway.

  4. An ontology-based annotation of cardiac implantable electronic devices to detect therapy changes in a national registry.

    PubMed

    Rosier, Arnaud; Mabo, Philippe; Chauvin, Michel; Burgun, Anita

    2015-05-01

    The patient population benefitting from cardiac implantable electronic devices (CIEDs) is increasing. This study introduces a device annotation method that supports the consistent description of the functional attributes of cardiac devices and evaluates how this method can detect device changes from a CIED registry. We designed the Cardiac Device Ontology, an ontology of CIEDs and device functions. We annotated 146 cardiac devices with this ontology and used it to detect therapy changes with respect to atrioventricular pacing, cardiac resynchronization therapy, and defibrillation capability in a French national registry of patients with implants (STIDEFIX). We then analyzed a set of 6905 device replacements from the STIDEFIX registry. Ontology-based identification of therapy changes (upgraded, downgraded, or similar) was accurate (6905 cases) and performed better than straightforward analysis of the registry codes (F-measure 1.00 versus 0.75 to 0.97). This study demonstrates the feasibility and effectiveness of ontology-based functional annotation of devices in the cardiac domain. Such annotation allowed a better description and in-depth analysis of STIDEFIX. This method was useful for the automatic detection of therapy changes and may be reused for analyzing data from other device registries.

  5. Feasibility of using fluorescence in situ hybridization (FISH) to detect early gene changes in sputum cells from uranium miners

    SciTech Connect

    Neft, R.E.; Rogers, J.L.; Belinsky, S.A.

    1995-12-01

    Epidemiological studies have shown that combined exposure to radon progeny and tobacco smoke produce a greater than additive or synergistic increase in lung cancer risk. Lung cancer results from multiple genetic changes over a long period of time. An early change that occurs in lung cancer is trisomy 7 which is found in 50% of non-small cell lung cancer and in the far margins of resected lung tumors. The 80% mortality associated with lung cancer is in part related to the high proportion of patients who present with an advanced, unresectable tumor. Therefore, early detection of patients at risk for tumor development is critical to improve treatment of this disease. Currently, it is difficult to detect lung cancer early while it is still amendable by surgery. Saccomanno, G. has shown that premalignant cytologic changes in sputum cells collected from uranium miners can be detected by a skilled, highly trained cytopathologist. A more objective alternative for identifying premalignant cells in sputum may be to determine whether an early genetic change such as trisomy 7 is present in these cells. Fluorescence in situ hybridization (FISH) can be used to identify cells with trisomy 7. The results of this investigation indicate that FISH may prove to be an accurate, efficient method to test at-risk individuals for genetic alterations in bronchial epithelial cells from sputum.

  6. Principal modes of Asian summer monsoon variability: Detection and changes

    NASA Astrophysics Data System (ADS)

    Yasutomi, N.; Kimoto, M.

    2009-12-01

    Principal modes of Asian summer monsoon variability are identified. By using vertically integrated moisture flux, principal modes represent better separation than commonly used variables such as rainfall, winds and outgoing longwave radiation. An empirical orthogonal function of vertically integrated moisture flux within the South, Southeast and East Asia during summertime is analysed. Results of various analyses let us convince that the first and second EOFs of the moisture flux are the principal modes of the Asian monsoon variability. In summer, there are two modes dominant in the Asian monsoon region; one consists of low-level circulation over the subtropical western Pacific near Philippines and associated convective dipole centers located over the western Pacific and Indonesia. The other consists of El Nino-Southern Oscillation (ENSO) signal and the Pacific-Japan (PJ) pattern, called ENSO-PJ mixed mode. This pattern is detected as the first EOF mode of a simulation with an atmospheric general circulation model giving the climatological mean sea surface temperature. Furthermore, the pattern is dominant in both present climate simulation and global warming simulation using coupled GCM. A projected change shows increasing of precipitation over South China and Japan. The Pacific-Indo dipole pattern is found out to be excited without external forcing like a specific sea surface temperature anomaly. Moreover, the Pacific-Indo dipole pattern appears as the preferred structure of variability by giving small perturbations to a three-dimensionally varying basic state in summertime by using a linear baroclinic model. Factors of the basic state which help to excite and maintain the Pacific-Indo dipole pattern are examined. Free, stationary Rossby waves can be excited in the region of low-level westerly extending from the Indian Ocean to the South China Sea which blows as a part of the monsoonal flow in summer. Rossby waves at the eastern end of the low-level westerly where

  7. Novelty detection in a changing environment: A negative selection approach

    NASA Astrophysics Data System (ADS)

    Surace, Cecilia; Worden, Keith

    2010-05-01

    In the recent past, there have been a number of engineering studies motivated by analogies with the human immune system. The immune system has provided a rich source of inspiration for pattern recognition, machine learning and data mining analyses. One of the properties of the immune system which proves particularly useful for novelty detection is that of self/non-self discrimination and this forms the basis of the negative selection algorithm which has previously been applied by other researchers to the problem of time-series novelty detection. The object of the current paper is to apply the negative selection algorithm to more general feature sets and also to consider the case of novelty detection where the normal condition set is significantly non-Gaussian or varies with operational or environmental conditions.

  8. Seasonal Change Detection and Attribution of Surface Temperature changes over Interior Peninsular Region of India

    NASA Astrophysics Data System (ADS)

    Pattanayak, Sonali; Nagesh Kumar, Dasika

    2015-04-01

    A good number of studies have investigated recent trends in the observed and simulated hydrometeorological variables across the world. It has been challenging for the research community to address whether the significant change in climate over the course of 2nd half of 20th century is caused either due to natural or manmade effects. Although evidences for an anthropogenic contribution to climatic trends have been accumulated rapidly worldwide, for India these are scarce. Hence the formal efforts have been undertaken to distinguish whether the recent changes in seasonal temperature over India occurred due to natural internal variation of climate system or human influence using rigorous detection and attribution (D&A) procedure. The surface temperature is the most widely cited indicator of climate fluctuation. Hence maximum and minimum temperatures (Tmax & Tmin) which are among the six most commonly used variables for impact assessment studies are analyzed here. Seasonal divisions are based on conventional meteorological seasons: January-February (winter); March-May (pre monsoon); June-September (monsoon); October-December (post monsoon). Time span considered for this study is 1950-2005. Climate Research Unit (Version 3.21) gridded monthly temperature datasets are considered as observed data. Initially TFPW-MK (Trend Free Pre Whitening Mann Kendall) test is used to search the significant trends in the four seasons over all India. Temporal change detection analysis in evapotranspiration (which is one of the key processes in hydrological cycle) is essential for progress in water resources planning and management. Hence along with Tmax and Tmin, potential evapotranspiration (PET) has also been analyzed for the similar conditions. Significant upward trends in Tmax, Tmin and PET are observed over most of the grid points in Interior Peninsula (IP) region over India. Significant correlation was obtained between PET and Tmax compared to PET and Tmin. Trends in Tmin clearly

  9. A Comparison of Techniques for Detecting Abnormal Change in Blogs

    SciTech Connect

    Furuta, Dr. Richard Keith; ShipmanIII, Dr. Frank Major; Bogen, Paul Logasa

    2012-01-01

    Distributed collections are made of metadata entries that contain references to artifacts not controlled by the collection curators. These collections often have limited forms of change; for digital distributed collections, primarily creation and deletion of additional resources. However, there exists a class of digital collection that undergoes additional kinds of change. These collections consist of resources that are distributed across the Internet and brought together via hyperlinking. Resources in these collections can be expected to change as time goes on. Part of the difficulty in maintaining these collections is determining if a changed page is still a valid member of the collection. Others have tried to address this by defining a maximum allowed threshold of change, however, these methods treat change as a potential problem and treat web content as static despite its intrinsic dynamicism. Instead we acknowledge change on the web as a normal part of a web document and determine the difference between what a maintainer expects a page to do and what it actually does. In this work we evaluate options for extractors and analyzers from a suite of techniques against a human-generated ground-truth set of blog changes. The results of this work show a statistically significant improvement over traditional threshold techniques for our collection.

  10. Grasp Preparation Improves Change Detection for Congruent Objects

    ERIC Educational Resources Information Center

    Symes, Ed; Tucker, Mike; Ellis, Rob; Vainio, Lari; Ottoboni, Giovanni

    2008-01-01

    A series of experiments provided converging support for the hypothesis that action preparation biases selective attention to action-congruent object features. When visual transients are masked in so-called "change-blindness scenes," viewers are blind to substantial changes between 2 otherwise identical pictures that flick back and forth. The…

  11. Development of a strand-specific real-time qRT-PCR for the accurate detection and quantitation of West Nile virus RNA.

    PubMed

    Lim, Stephanie M; Koraka, Penelope; Osterhaus, Albert D M E; Martina, Byron E E

    2013-12-01

    Studying the tropism and replication kinetics of West Nile virus (WNV) in different cell types in vitro and in tissues in animal models is important for understanding its pathogenesis. As detection of the negative strand viral RNA is a more reliable indicator of active replication for single-stranded positive-sense RNA viruses, the specificity of qRT-PCR assays currently used for the detection of WNV positive and negative strand RNA was reassessed. It was shown that self- and falsely-primed cDNA was generated during the reverse transcription step in an assay employing unmodified primers and several reverse transcriptases. As a result, a qRT-PCR assay using the thermostable rTth in combination with tagged primers was developed, which greatly improved strand specificity by circumventing the events of self- and false-priming. The reliability of the assay was then addressed in vitro using BV-2 microglia cells as well as in C57/BL6 mice. It was possible to follow the kinetics of positive and negative-strand RNA synthesis both in vitro and in vivo; however, the sensitivity of the assay will need to be optimized in order to detect and quantify negative-strand RNA synthesis in the very early stages of infection. Overall, the strand-specific qRT-PCR assay developed in this study is an effective tool to quantify WNV RNA, reassess viral replication, and study tropism of WNV in the context of WNV pathogenesis.

  12. PRESENTATION ON--LAND-COVER CHANGE DETECTION USING MULTI-TEMPORAL MODIS NDVI DATA

    EPA Science Inventory

    Monitoring the locations and distributions of land-cover changes is important for establishing linkages between policy decisions, regulatory actions and subsequent landuse activities. Past efforts incorporating two-date change detection using moderate resolution data (e.g., Lands...

  13. Mutual Comparative Filtering for Change Detection in Videos with Unstable Illumination Conditions

    NASA Astrophysics Data System (ADS)

    Sidyakin, Sergey V.; Vishnyakov, Boris V.; Vizilter, Yuri V.; Roslov, Nikolay I.

    2016-06-01

    In this paper we propose a new approach for change detection and moving objects detection in videos with unstable, abrupt illumination changes. This approach is based on mutual comparative filters and background normalization. We give the definitions of mutual comparative filters and outline their strong advantage for change detection purposes. Presented approach allows us to deal with changing illumination conditions in a simple and efficient way and does not have drawbacks, which exist in models that assume different color transformation laws. The proposed procedure can be used to improve a number of background modelling methods, which are not specifically designed to work under illumination changes.

  14. Object-Oriented Change Detection Based on Multi-Scale Approach

    NASA Astrophysics Data System (ADS)

    Jia, Yonghong; Zhou, Mingting; Jinshan, Ye

    2016-06-01

    The change detection of remote sensing images means analysing the change information quantitatively and recognizing the change types of the surface coverage data in different time phases. With the appearance of high resolution remote sensing image, object-oriented change detection method arises at this historic moment. In this paper, we research multi-scale approach for high resolution images, which includes multi-scale segmentation, multi-scale feature selection and multi-scale classification. Experimental results show that this method has a stronger advantage than the traditional single-scale method of high resolution remote sensing image change detection.

  15. Bayesian analysis to detect abrupt changes in extreme hydrological processes

    NASA Astrophysics Data System (ADS)

    Jo, Seongil; Kim, Gwangsu; Jeon, Jong-June

    2016-07-01

    In this study, we develop a new method for a Bayesian change point analysis. The proposed method is easy to implement and can be extended to a wide class of distributions. Using a generalized extreme-value distribution, we investigate the annual maximum of precipitations observed at stations in the South Korean Peninsula, and find significant changes in the considered sites. We evaluate the hydrological risk in predictions using the estimated return levels. In addition, we explain that the misspecification of the probability model can lead to a bias in the number of change points and using a simple example, show that this problem is difficult to avoid by technical data transformation.

  16. Wind shear detection using measurement of aircraft total energy change

    NASA Technical Reports Server (NTRS)

    Joppa, R. G.

    1976-01-01

    Encounters with wind shears are of concern and have caused major accidents, particularly during landing approaches. Changes in the longitudinal component of the wind affect the aircraft by changing its kinetic energy with respect to the air. It is shown that an instrument which will measure and display the rate of change of total energy of the aircraft with respect to the air will give a leading indication of wind shear problems. The concept is outlined and some instrumentation and display considerations are discussed.

  17. Adversary phase change detection using SOMs and text data.

    SciTech Connect

    Speed, Ann Elizabeth; Doser, Adele Beatrice; Warrender, Christina E.

    2010-05-01

    In this work, we developed a self-organizing map (SOM) technique for using web-based text analysis to forecast when a group is undergoing a phase change. By 'phase change', we mean that an organization has fundamentally shifted attitudes or behaviors. For instance, when ice melts into water, the characteristics of the substance change. A formerly peaceful group may suddenly adopt violence, or a violent organization may unexpectedly agree to a ceasefire. SOM techniques were used to analyze text obtained from organization postings on the world-wide web. Results suggest it may be possible to forecast phase changes, and determine if an example of writing can be attributed to a group of interest.

  18. Probable detection of climatically significant change of the solar constant

    NASA Technical Reports Server (NTRS)

    Sofia, S.; Endal, A. S.

    1980-01-01

    It is suggested that the decrease in the solar radius inferred from solar eclipse observations made from 1715 to 1979 reflects a variation of the solar constant that may be of considerable climatic significance. A general, time-averaged relationship between changes in the solar constant and changes in the solar radius is derived based on a model of the contraction and expansion of the convective zone. A preliminary numerical calculation of radius changes due to changes in the mixing length of the solar envelope is presented which indicates that a decrease in solar radius of 0.5 arcsec, as observed in the last 264 years, would correspond to a decrease of 0.7% in the solar constant, a value of large climatic significance. Limitations of the observational method and the numerical approach are pointed out, and required additional theoretical and observational efforts are indicated.

  19. Validation of White-Matter Lesion Change Detection Methods on a Novel Publicly Available MRI Image Database.

    PubMed

    Lesjak, Žiga; Pernuš, Franjo; Likar, Boštjan; Špiclin, Žiga

    2016-10-01

    Changes of white-matter lesions (WMLs) are good predictors of the progression of neurodegenerative diseases like multiple sclerosis (MS). Based on longitudinal magnetic resonance (MR) imaging the changes can be monitored, while the need for their accurate and reliable quantification led to the development of several automated MR image analysis methods. However, an objective comparison of the methods is difficult, because publicly unavailable validation datasets with ground truth and different sets of performance metrics were used. In this study, we acquired longitudinal MR datasets of 20 MS patients, in which brain regions were extracted, spatially aligned and intensity normalized. Two expert raters then delineated and jointly revised the WML changes on subtracted baseline and follow-up MR images to obtain ground truth WML segmentations. The main contribution of this paper is an objective, quantitative and systematic evaluation of two unsupervised and one supervised intensity based change detection method on the publicly available datasets with ground truth segmentations, using common pre- and post-processing steps and common evaluation metrics. Besides, different combinations of the two main steps of the studied change detection methods, i.e. dissimilarity map construction and its segmentation, were tested to identify the best performing combination.

  20. Validation of White-Matter Lesion Change Detection Methods on a Novel Publicly Available MRI Image Database.

    PubMed

    Lesjak, Žiga; Pernuš, Franjo; Likar, Boštjan; Špiclin, Žiga

    2016-10-01

    Changes of white-matter lesions (WMLs) are good predictors of the progression of neurodegenerative diseases like multiple sclerosis (MS). Based on longitudinal magnetic resonance (MR) imaging the changes can be monitored, while the need for their accurate and reliable quantification led to the development of several automated MR image analysis methods. However, an objective comparison of the methods is difficult, because public