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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. PMID:26725404

  2. Obtaining Accurate Change Detection Results from High-Resolution Satellite Sensors

    NASA Technical Reports Server (NTRS)

    Bryant, N.; Bunch, W.; Fretz, R.; Kim, P.; Logan, T.; Smyth, M.; Zobrist, A.

    2012-01-01

    Multi-date acquisitions of high-resolution imaging satellites (e.g. GeoEye and WorldView), can display local changes of current economic interest. However, their large data volume precludes effective manual analysis, requiring image co-registration followed by image-to-image change detection, preferably with minimal analyst attention. We have recently developed an automatic change detection procedure that minimizes false-positives. The processing steps include: (a) Conversion of both the pre- and post- images to reflectance values (this step is of critical importance when different sensors are involved); reflectance values can be either top-of-atmosphere units or have full aerosol optical depth calibration applied using bi-directional reflectance knowledge. (b) Panchromatic band image-to-image co-registration, using an orthorectified base reference image (e.g. Digital Orthophoto Quadrangle) and a digital elevation model; this step can be improved if a stereo-pair of images have been acquired on one of the image dates. (c) Pan-sharpening of the multispectral data to assure recognition of change objects at the highest resolution. (d) Characterization of multispectral data in the post-image ( i.e. the background) using unsupervised cluster analysis. (e) Band ratio selection in the post-image to separate surface materials of interest from the background. (f) Preparing a pre-to-post change image. (g) Identifying locations where change has occurred involving materials of interest.

  3. Detecting Cancer Quickly and Accurately

    NASA Astrophysics Data System (ADS)

    Gourley, Paul; McDonald, Anthony; Hendricks, Judy; Copeland, Guild; Hunter, John; Akhil, Ohmar; Capps, Heather; Curry, Marc; Skirboll, Steve

    2000-03-01

    We present a new technique for high throughput screening of tumor cells in a sensitive nanodevice that has the potential to quickly identify a cell population that has begun the rapid protein synthesis and mitosis characteristic of cancer cell proliferation. Currently, pathologists rely on microscopic examination of cell morphology using century-old staining methods that are labor-intensive, time-consuming and frequently in error. New micro-analytical methods for automated, real time screening without chemical modification are critically needed to advance pathology and improve diagnoses. We have teamed scientists with physicians to create a microlaser biochip (based upon our R&D award winning bio-laser concept)1 which evaluates tumor cells by quantifying their growth kinetics. The key new discovery was demonstrating that the lasing spectra are sensitive to the biomolecular mass in the cell, which changes the speed of light in the laser microcavity. Initial results with normal and cancerous human brain cells show that only a few hundred cells -- the equivalent of a billionth of a liter -- are required to detect abnormal growth. The ability to detect cancer in such a minute tissue sample is crucial for resecting a tumor margin or grading highly localized tumor malignancy. 1. P. L. Gourley, NanoLasers, Scientific American, March 1998, pp. 56-61. This work supported under DOE contract DE-AC04-94AL85000 and the Office of Basic Energy Sciences.

  4. Detecting cancer quickly and accurately

    NASA Astrophysics Data System (ADS)

    Gourley, Paul L.; McDonald, Anthony E.; Hendricks, Judy K.; Copeland, G. C.; Hunter, John A.; Akhil, O.; Cheung, D.; Cox, Jimmy D.; Capps, H.; Curry, Mark S.; Skirboll, Steven K.

    2000-03-01

    We present a new technique for high throughput screening of tumor cells in a sensitive nanodevice that has the potential to quickly identify a cell population that has begun the rapid protein synthesis and mitosis characteristic of cancer cell proliferation. Currently, pathologists rely on microscopic examination of cell morphology using century-old staining methods that are labor-intensive, time-consuming and frequently in error. New micro-analytical methods for automated, real time screening without chemical modification are critically needed to advance pathology and improve diagnoses. We have teamed scientists with physicians to create a microlaser biochip (based upon our R&D award winning bio- laser concept) which evaluates tumor cells by quantifying their growth kinetics. The key new discovery was demonstrating that the lasing spectra are sensitive to the biomolecular mass in the cell, which changes the speed of light in the laser microcavity. Initial results with normal and cancerous human brain cells show that only a few hundred cells -- the equivalent of a billionth of a liter -- are required to detect abnormal growth. The ability to detect cancer in such a minute tissue sample is crucial for resecting a tumor margin or grading highly localized tumor malignancy.

  5. 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.

  6. 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

  7. 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

  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. A fast and accurate FPGA based QRS detection system.

    PubMed

    Shukla, Ashish; Macchiarulo, Luca

    2008-01-01

    An accurate Field Programmable Gate Array (FPGA) based ECG Analysis system is described in this paper. The design, based on a popular software based QRS detection algorithm, calculates the threshold value for the next peak detection cycle, from the median of eight previously detected peaks. The hardware design has accuracy in excess of 96% in detecting the beats correctly when tested with a subset of five 30 minute data records obtained from the MIT-BIH Arrhythmia database. The design, implemented using a proprietary design tool (System Generator), is an extension of our previous work and uses 76% resources available in a small-sized FPGA device (Xilinx Spartan xc3s500), has a higher detection accuracy as compared to our previous design and takes almost half the analysis time in comparison to software based approach. PMID:19163797

  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. PMID:26543718

  11. 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.

  12. Accurate Detection of Rifampicin-Resistant Mycobacterium Tuberculosis Strains.

    PubMed

    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

  13. 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

  14. 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

  15. Accurate single-molecule FRET studies using multiparameter fluorescence detection.

    PubMed

    Sisamakis, Evangelos; Valeri, Alessandro; Kalinin, Stanislav; Rothwell, Paul J; Seidel, Claus A M

    2010-01-01

    In the recent decade, single-molecule (sm) spectroscopy has come of age and is providing important insight into how biological molecules function. So far our view of protein function is formed, to a significant extent, by traditional structure determination showing many beautiful static protein structures. Recent experiments by single-molecule and other techniques have questioned the idea that proteins and other biomolecules are static structures. In particular, Förster resonance energy transfer (FRET) studies of single molecules have shown that biomolecules may adopt many conformations as they perform their function. Despite the success of sm-studies, interpretation of smFRET data are challenging since they can be complicated due to many artifacts arising from the complex photophysical behavior of fluorophores, dynamics, and motion of fluorophores, as well as from small amounts of contaminants. We demonstrate that the simultaneous acquisition of a maximum of fluorescence parameters by multiparameter fluorescence detection (MFD) allows for a robust assessment of all possible artifacts arising from smFRET and offers unsurpassed capabilities regarding the identification and analysis of individual species present in a population of molecules. After a short introduction, the data analysis procedure is described in detail together with some experimental considerations. The merits of MFD are highlighted further with the presentation of some applications to proteins and nucleic acids, including accurate structure determination based on FRET. A toolbox is introduced in order to demonstrate how complications originating from orientation, mobility, and position of fluorophores have to be taken into account when determining FRET-related distances with high accuracy. Furthermore, the broad time resolution (picoseconds to hours) of MFD allows for kinetic studies that resolve interconversion events between various subpopulations as a biomolecule of interest explores its

  16. 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.

  17. 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.

  18. 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

  19. 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

  20. Accurate, Automated Detection of Atrial Fibrillation in Ambulatory Recordings.

    PubMed

    Linker, David T

    2016-06-01

    A highly accurate, automated algorithm would facilitate cost-effective screening for asymptomatic atrial fibrillation. This study analyzed a new algorithm and compared it to existing techniques. The incremental benefit of each step in refinement of the algorithm was measured, and the algorithm was compared to other methods using the Physionet atrial fibrillation and normal sinus rhythm databases. When analyzing segments of 21 RR intervals or less, the algorithm had a significantly higher area under the receiver operating characteristic curve (AUC) than the other algorithms tested. At analysis segment sizes of up to 101 RR intervals, the algorithm continued to have a higher AUC than any of the other methods tested, although the difference from the second best other algorithm was no longer significant, with an AUC of 0.9992 with a 95% confidence interval (CI) of 0.9986-0.9998, vs. 0.9986 (CI 0.9978-0.9994). With identical per-subject sensitivity, per-subject specificity of the current algorithm was superior to the other tested algorithms even at 101 RR intervals, with no false positives (CI 0.0-0.8%) vs. 5.3% false positives for the second best algorithm (CI 3.4-7.9%). The described algorithm shows great promise for automated screening for atrial fibrillation by reducing false positives requiring manual review, while maintaining high sensitivity. PMID:26850411

  1. 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.

  2. 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…

  3. Change in BMI Accurately Predicted by Social Exposure to Acquaintances

    PubMed Central

    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 R2. 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. PMID

  4. 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

  5. Detecting and Predicting Changes

    ERIC Educational Resources Information Center

    Brown, Scott D.; Steyvers, Mark

    2009-01-01

    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…

  6. Fast and accurate circle detection using gradient-direction-based segmentation.

    PubMed

    Wu, Jianping; Chen, Ke; Gao, Xiaohui

    2013-06-01

    We present what is to our knowledge the first-ever fitting-based circle detection algorithm, namely, the fast and accurate circle (FACILE) detection algorithm, based on gradient-direction-based edge clustering and direct least square fitting. Edges are segmented into sections based on gradient directions, and each section is validated separately; valid arcs are then fitted and further merged to extract more accurate circle information. We implemented the algorithm with the C++ language and compared it with four other algorithms. Testing on simulated data showed FACILE was far superior to the randomized Hough transform, standard Hough transform, and fast circle detection using gradient pair vectors with regard to processing speed and detection reliability. Testing on publicly available standard datasets showed FACILE outperformed robust and precise circular detection, a state-of-art arc detection method, by 35% with regard to recognition rate and is also a significant improvement over the latter in processing speed. PMID:24323106

  7. 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

  8. 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. PMID:24008284

  9. Accurate LC Peak Boundary Detection for 16O/18O Labeled LC-MS Data

    PubMed Central

    Cui, Jian; Petritis, Konstantinos; Tegeler, Tony; Petritis, Brianne; Ma, Xuepo; Jin, Yufang; Gao, Shou-Jiang (SJ); Zhang, Jianqiu (Michelle)

    2013-01-01

    In liquid chromatography-mass spectrometry (LC-MS), parts of LC peaks are often corrupted by their co-eluting peptides, which results in increased quantification variance. In this paper, we propose to apply accurate LC peak boundary detection to remove the corrupted part of LC peaks. Accurate LC peak boundary detection is achieved by checking the consistency of intensity patterns within peptide elution time ranges. In addition, we remove peptides with erroneous mass assignment through model fitness check, which compares observed intensity patterns to theoretically constructed ones. The proposed algorithm can significantly improve the accuracy and precision of peptide ratio measurements. PMID:24115998

  10. 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.

  11. 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.

  12. SAR change detection based on intensity and texture changes

    NASA Astrophysics Data System (ADS)

    Gong, Maoguo; Li, Yu; Jiao, Licheng; Jia, Meng; Su, Linzhi

    2014-07-01

    In this paper, a novel change detection approach is proposed for multitemporal synthetic aperture radar (SAR) images. The approach is based on two difference images, which are constructed through intensity and texture information, respectively. In the extraction of the texture differences, robust principal component analysis technique is used to separate irrelevant and noisy elements from Gabor responses. Then graph cuts are improved by a novel energy function based on multivariate generalized Gaussian model for more accurately fitting. The effectiveness of the proposed method is proved by the experiment results obtained on several real SAR images data sets.

  13. 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

  14. 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.

  15. Change detection in underwater imagery.

    PubMed

    Seemakurthy, Karthik; Rajagopalan, A N

    2016-03-01

    In this work, we deal with the problem of change detection in an underwater scenario given an unblurred-blurred image pair of a planar scene taken at different times. The blur is primarily due to the dynamic nature of the water surface and its nature is space-invariant in the presence of cyclic water flows. Exploiting the sparsity of the induced blur as well as the occlusions, we propose a distort-difference pipeline that employs an alternating minimization framework to perform change detection in the presence of geometric distortions (skew) as well as photometric degradations (blur and global illumination variations). The method can effectively yield both sharp and blurred occluder maps. Using synthetic as well as real data, we demonstrate how the proposed technique advances the state of the art. PMID:26974899

  16. 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

  17. 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.

  18. 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

  19. 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

  20. 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.

  1. Detecting change as it occurs

    NASA Technical Reports Server (NTRS)

    Radok, Uwe; Brown, Timothy J.

    1992-01-01

    Traditionally climate changes have been detected from long series of observations and long after they have happened. Our 'inverse sequential' procedure, for detecting change as soon as it occurs, describes the existing or most recent data by their frequency distribution. Its parameter(s) are estimated both from the existing set of observations and from the same set augmented by 1,2,....j new observations. Individual-value probability products ('likelihoods') are used to form ratios which yield two probabilities for erroneously accepting the existing parameter(s) as valid for the augmented data set, and vice versa. A genuine parameter change is signaled when these probabilities (or a more stable compound probability) show a progressive decrease. New parameter values can then be estimated from the new observations alone using standard statistical techniques. The inverse sequential procedure will be illustrated for global annual mean temperatures (assumed normally distributed), and for annual numbers of North Atlantic hurricanes (assumed to represent Poisson distributions). The procedure was developed, but not yet tested, for linear or exponential trends, and for chi-squared means or degrees of freedom, a special measure of autocorrelation.

  2. 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

  3. 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

  4. 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

  5. Parente2: a fast and accurate method for detecting identity by descent

    PubMed Central

    Rodriguez, Jesse M.; Bercovici, Sivan; Huang, Lin; Frostig, Roy; Batzoglou, Serafim

    2015-01-01

    Identity-by-descent (IBD) inference is the problem of establishing a genetic connection between two individuals through a genomic segment that is inherited by both individuals from a recent common ancestor. IBD inference is an important preceding step in a variety of population genomic studies, ranging from demographic studies to linking genomic variation with phenotype and disease. The problem of accurate IBD detection has become increasingly challenging with the availability of large collections of human genotypes and genomes: Given a cohort’s size, a quadratic number of pairwise genome comparisons must be performed. Therefore, computation time and the false discovery rate can also scale quadratically. To enable accurate and efficient large-scale IBD detection, we present Parente2, a novel method for detecting IBD segments. Parente2 is based on an embedded log-likelihood ratio and uses a model that accounts for linkage disequilibrium by explicitly modeling haplotype frequencies. Parente2 operates directly on genotype data without the need to phase data prior to IBD inference. We evaluate Parente2’s performance through extensive simulations using real data, and we show that it provides substantially higher accuracy compared to previous state-of-the-art methods while maintaining high computational efficiency. PMID:25273070

  6. 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.

  7. Real-time 3D change detection of IEDs

    NASA Astrophysics Data System (ADS)

    Wathen, Mitch; Link, Norah; Iles, Peter; Jinkerson, John; Mrstik, Paul; Kusevic, Kresimir; Kovats, David

    2012-06-01

    Road-side bombs are a real and continuing threat to soldiers in theater. CAE USA recently developed a prototype Volume based Intelligence Surveillance Reconnaissance (VISR) sensor platform for IED detection. This vehicle-mounted, prototype sensor system uses a high data rate LiDAR (1.33 million range measurements per second) to generate a 3D mapping of roadways. The mapped data is used as a reference to generate real-time change detection on future trips on the same roadways. The prototype VISR system is briefly described. The focus of this paper is the methodology used to process the 3D LiDAR data, in real-time, to detect small changes on and near the roadway ahead of a vehicle traveling at moderate speeds with sufficient warning to stop the vehicle at a safe distance from the threat. The system relies on accurate navigation equipment to geo-reference the reference run and the change-detection run. Since it was recognized early in the project that detection of small changes could not be achieved with accurate navigation solutions alone, a scene alignment algorithm was developed to register the reference run with the change detection run prior to applying the change detection algorithm. Good success was achieved in simultaneous real time processing of scene alignment plus change detection.

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

    PubMed

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

    2016-03-01

    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

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. Accurate moving cast shadow suppression based on local color constancy detection.

    PubMed

    Amato, Ariel; Mozerov, Mikhail G; Bagdanov, Andrew D; Gonzàlez, Jordi

    2011-10-01

    This paper describes a novel framework for detection and suppression of properly shadowed regions for most possible scenarios occurring in real video sequences. Our approach requires no prior knowledge about the scene, nor is it restricted to specific scene structures. Furthermore, the technique can detect both achromatic and chromatic shadows even in the presence of camouflage that occurs when foreground regions are very similar in color to shadowed regions. The method exploits local color constancy properties due to reflectance suppression over shadowed regions. To detect shadowed regions in a scene, the values of the background image are divided by values of the current frame in the RGB color space. We show how this luminance ratio can be used to identify segments with low gradient constancy, which in turn distinguish shadows from foreground. Experimental results on a collection of publicly available datasets illustrate the superior performance of our method compared with the most sophisticated, state-of-the-art shadow detection algorithms. These results show that our approach is robust and accurate over a broad range of shadow types and challenging video conditions. PMID:21435975

  14. 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. PMID:25624198

  15. 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

  16. 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

  17. 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

  18. ROM Plus®: accurate point-of-care detection of ruptured fetal membranes

    PubMed Central

    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

  19. 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

  20. 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

  1. 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

  2. A novel biosensor based on competitive SERS immunoassay and magnetic separation for accurate and sensitive detection of chloramphenicol.

    PubMed

    Yang, Kang; Hu, Yongjun; Dong, Ning

    2016-06-15

    The accurate and sensitive detection of chloramphenicol (CAP) is particularly imperative to public health and safety. Here, we present a novel sensor for residual CAP detection based on competitive surface-enhanced Raman scattering (SERS) immunoassay and magnetic separation. In this nanosensor, functionalized Au nanoparticles (AuNPs) were labeled with the Raman reporter molecule (e.g. 4,4'-dipyridyl). With the addition of free CAP, a competitive immune reaction was initiated between free CAP and above AuNPs for conjugating with CAP antibody-modified magnetic nanoparticles (MNPs). Instead of the solid substrate, the antibody conjugated-magnetic beads were used as supporting materials and separation tools in the present sensor. With the aid of a magnet, the mixture was removed from the supernatant for concentration effects. This caused obvious change of SERS signal intensity obtained from supernatant. The SERS signals were collected from the supernatant directly, which made the SERS measurements more stable, repeatable and reliable. The proposed SERS-based magnetic immunosensor allows us to detect CAP in a fast, selective and sensitive (1.0 pg/mL) manner over a wide concentration range ( 1-1 × 10(4)pg/mL). In addition, these results demonstrate that this immunosensor holds great potential for the detection of antibiotics in real aquatic environment, which is crucial to our life. PMID:26866562

  3. 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

  4. Accurate and reliable high-throughput detection of copy number variation in the human genome

    PubMed Central

    Fiegler, Heike; Redon, Richard; Andrews, Dan; Scott, Carol; Andrews, Robert; Carder, Carol; Clark, Richard; Dovey, Oliver; Ellis, Peter; Feuk, Lars; French, Lisa; Hunt, Paul; Kalaitzopoulos, Dimitrios; Larkin, James; Montgomery, Lyndal; Perry, George H.; Plumb, Bob W.; Porter, Keith; Rigby, Rachel E.; Rigler, Diane; Valsesia, Armand; Langford, Cordelia; Humphray, Sean J.; Scherer, Stephen W.; Lee, Charles; Hurles, Matthew E.; Carter, Nigel P.

    2006-01-01

    This study describes a new tool for accurate and reliable high-throughput detection of copy number variation in the human genome. We have constructed a large-insert clone DNA microarray covering the entire human genome in tiling path resolution that we have used to identify copy number variation in human populations. Crucial to this study has been the development of a robust array platform and analytic process for the automated identification of copy number variants (CNVs). The array consists of 26,574 clones covering 93.7% of euchromatic regions. Clones were selected primarily from the published “Golden Path,” and mapping was confirmed by fingerprinting and BAC-end sequencing. Array performance was extensively tested by a series of validation assays. These included determining the hybridization characteristics of each individual clone on the array by chromosome-specific add-in experiments. Estimation of data reproducibility and false-positive/negative rates was carried out using self–self hybridizations, replicate experiments, and independent validations of CNVs. Based on these studies, we developed a variance-based automatic copy number detection analysis process (CNVfinder) and have demonstrated its robustness by comparison with the SW-ARRAY method. PMID:17122085

  5. 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. PMID:20880410

  6. 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. PMID:26833260

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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

  12. Airborne hyperspectral detection of small changes.

    PubMed

    Eismann, Michael T; Meola, Joseph; Stocker, Alan D; Beaven, Scott G; Schaum, Alan P

    2008-10-01

    Hyperspectral change detection offers a promising approach to detect objects and features of remotely sensed areas that are too difficult to find in single images, such as slight changes in land cover and the insertion, deletion, or movement of small objects, by exploiting subtle differences in the imagery over time. Methods for performing such change detection, however, must effectively maintain invariance to typically larger image-to-image changes in illumination and environmental conditions, as well as misregistration and viewing differences between image observations, while remaining sensitive to small differences in scene content. Previous research has established predictive algorithms to overcome such natural changes between images, and these approaches have recently been extended to deal with space-varying changes. The challenges to effective change detection, however, are often exacerbated in an airborne imaging geometry because of the limitations in control over flight conditions and geometry, and some of the recent change detection algorithms have not been demonstrated in an airborne setting. We describe the airborne implementation and relative performance of such methods. We specifically attempt to characterize the effects of spatial misregistration on change detection performance, the efficacy of class-conditional predictors in an airborne setting, and extensions to the change detection approach, including physically motivated shadow transition classifiers and matched change filtering based on in-scene atmospheric normalization. PMID:18830283

  13. 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.

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

    PubMed

    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

  15. 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.

  16. 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.

  17. 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.

  18. 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

  19. 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

  20. Detecting Concentration Changes with Cooperative Receptors

    NASA Astrophysics Data System (ADS)

    Bo, Stefano; Celani, Antonio

    2016-03-01

    Cells constantly need to monitor the state of the environment to detect changes and timely respond. The detection of concentration changes of a ligand by a set of receptors can be cast as a problem of hypothesis testing, and the cell viewed as a Neyman-Pearson detector. Within this framework, we investigate the role of receptor cooperativity in improving the cell's ability to detect changes. We find that cooperativity decreases the probability of missing an occurred change. This becomes especially beneficial when difficult detections have to be made. Concerning the influence of cooperativity on how fast a desired detection power is achieved, we find in general that there is an optimal value at finite levels of cooperation, even though easy discrimination tasks can be performed more rapidly by noncooperative receptors.

  1. 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. PMID:24528101

  2. A sequential framework for image change detection.

    PubMed

    Lingg, Andrew J; Zelnio, Edmund; Garber, Fred; Rigling, Brian D

    2014-05-01

    We present a sequential framework for change detection. This framework allows us to use multiple images from reference and mission passes of a scene of interest in order to improve detection performance. It includes a change statistic that is easily updated when additional data becomes available. Detection performance using this statistic is predictable when the reference and image data are drawn from known distributions. We verify our performance prediction by simulation. Additionally, we show that detection performance improves with additional measurements on a set of synthetic aperture radar images and a set of visible images with unknown probability distributions. PMID:24818249

  3. 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.

  4. 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. PMID:26631816

  5. Neural dynamics of change detection in crowded acoustic scenes

    PubMed Central

    Sohoglu, Ediz; Chait, Maria

    2016-01-01

    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. PMID:26631816

  6. 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.

  7. 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.

  8. Change Point Detection in Correlation Networks

    PubMed Central

    Barnett, Ian; Onnela, Jukka-Pekka

    2016-01-01

    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. PMID:26739105

  9. 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…

  10. 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.

  11. 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.

  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. 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.

  14. 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.

  15. 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.

  16. Image change detection algorithms: a systematic survey.

    PubMed

    Radke, Richard J; Andra, Srinivas; Al-Kofahi, Omar; Roysam, Badrinath

    2005-03-01

    Detecting regions of change in multiple images of the same scene taken at different times is of widespread interest due to a large number of applications in diverse disciplines, including remote sensing, surveillance, medical diagnosis and treatment, civil infrastructure, and underwater sensing. This paper presents a systematic survey of the common processing steps and core decision rules in modern change detection algorithms, including significance and hypothesis testing, predictive models, the shading model, and background modeling. We also discuss important preprocessing methods, approaches to enforcing the consistency of the change mask, and principles for evaluating and comparing the performance of change detection algorithms. It is hoped that our classification of algorithms into a relatively small number of categories will provide useful guidance to the algorithm designer. PMID:15762326

  17. 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.

  18. Development of a High Throughput Assay for Rapid and Accurate 10-Plex Detection of Citrus Pathogens

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The need to reliably detect and identify multiple plant pathogens simultaneously, especially in woody perennial hosts, has led to development of new molecular diagnostic approaches. In this study, a Luminex-based system was developed that provided a robust and sensitive test for simultaneous detect...

  19. Priming effects under correct change detection and change blindness.

    PubMed

    Caudek, Corrado; Domini, Fulvio

    2013-03-01

    In three experiments, we investigated the priming effects induced by an image change on a successive animate/inanimate decision task. We studied both perceptual (Experiments 1 and 2) and conceptual (Experiment 3) priming effects, under correct change detection and change blindness (CB). Under correct change detection, we found larger positive priming effects on congruent trials for probes representing animate entities than for probes representing artifactual objects. Under CB, we found performance impairment relative to a "no-change" baseline condition. This inhibition effect induced by CB was modulated by the semantic congruency between the changed item and the probe in the case of probe images, but not for probe words. We discuss our results in the context of the literature on the negative priming effect. PMID:22964454

  20. 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. PMID:25830555

  1. 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

  2. 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. PMID:25089287

  3. 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

  4. 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

  5. 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.

  6. An accurate tongue tissue strain synthesis using pseudo-wavelet reconstruction-based tagline detection

    NASA Astrophysics Data System (ADS)

    Yuan, Xiaohui; Ozturk, Cengizhan; Chi-Fishman, Gloria

    2007-03-01

    This paper describe our work on tagline detection and tissue strain synthesis. The tagline detection method extends our previous work 16 using pseudo-wavelet reconstruction. The novelty in tagline detection is that we integrated an active contour model and successfully improved the detection and indexing performance. Using pseudo-wavelet reconstruction-based method, prominent wavelet coefficients were retained while others were eliminated. Taglines were then extracted from the reconstructed images using thresholding. Due to noise and artifacts, a tagline can be broken into segments. We employed an active contour model that tracks the most likely segments and bridges them. Experiments demonstrated that our method extracts taglines automatically with greater robustness. Tissue strain was also reconstructed using extracted taglines.

  7. 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.

  8. Is Commercially Available Point Finder Accurate and Reliable in Detecting Active Auricular Acupuncture Points?

    PubMed Central

    Maranets, Inna; Lin, Eric C.; DeZinno, Peggy

    2012-01-01

    Abstract Objectives This study was done to determine the specificity and sensitivity of a commercial Pointer Plus (Point finder) in detecting a region of low skin resistance on the ear. Design This was a prospective blinded study. Setting/location The study was done at the Yale New Haven Hospital, New Haven, CT. Subjects The subjects were men and women who work at Yale New Haven Hospital. Interventions There were no interventions. Outcome measures Correlations were made between self-reported musculoskeletal pain and the detection of low skin resistance on the ear. Results The positive predictive value for Pointer Plus detecting low skin resistance correlating to the neck region of French auricular map is 0.76 (76%). The positive predictive value for Pointer Plus to detect low skin resistance area correlating to the low back region of French auricular map is 0.25. The positive predictive value for Pointer Plus in detecting any low in skin resistance on the external auricles in patients who complained of more than two musculoskeletal pains is 0.29. Conclusions The specificity and sensitivity of a commercial Pointer Plus (point finder) in detecting a region of low skin resistance on the ear being unreliable, depending on the correlating area based on a published auricular map. Additional assessments are needed to support the clinical practice. PMID:22834870

  9. Enabling accurate photodiode detection of multiple optical traps by spatial filtering

    NASA Astrophysics Data System (ADS)

    Ott, Dino; Reihani, S. Nader S.; Oddershede, Lene B.

    2014-09-01

    Dual and multiple beam optical tweezers allow for advanced trapping geometries beyond single traps, however, these increased manipulation capabilities, usually complicate the detection of position and force. The accuracy of position and force measurements is often compromised by crosstalk between the detected signals, this crosstalk leading to a systematic error on the measured forces and distances. In dual-beam optical trapping setups, the two traps are typically orthogonal polarized and crosstalk can be minimized by inserting polarization optics in front of the detector, however, this method is not perfect because of the de-polarization of the trapping beam introduced by the required high numerical aperture optics. Moreover, the restriction to two orthogonal polarisation states limits the number of detectable traps to two. Here, we present an easy-to-implement simple method to efficiently eliminate cross-talk in dual beam setups.1 The technique is based on spatial filtering and is highly compatible with standard back-focal-plane photodiode based detection. The reported method significantly improves the accuracy of force-distance measurements, e.g., of single molecules, hence providing much more scientific value for the experimental efforts. Furthermore, it opens the possibility for fast and simultaneous photodiode based detection of multiple holographically generated optical traps.

  10. Accurate and reproducible detection of proteins in water using an extended-gate type organic transistor biosensor

    NASA Astrophysics Data System (ADS)

    Minamiki, Tsukuru; Minami, Tsuyoshi; Kurita, Ryoji; Niwa, Osamu; Wakida, Shin-ichi; Fukuda, Kenjiro; Kumaki, Daisuke; Tokito, Shizuo

    2014-06-01

    In this Letter, we describe an accurate antibody detection method using a fabricated extended-gate type organic field-effect-transistor (OFET), which can be operated at below 3 V. The protein-sensing portion of the designed device is the gate electrode functionalized with streptavidin. Streptavidin possesses high molecular recognition ability for biotin, which specifically allows for the detection of biotinylated proteins. Here, we attempted to detect biotinylated immunoglobulin G (IgG) and observed a shift of threshold voltage of the OFET upon the addition of the antibody in an aqueous solution with a competing bovine serum albumin interferent. The detection limit for the biotinylated IgG was 8 nM, which indicates the potential utility of the designed device in healthcare applications.

  11. 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

  12. 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.

  13. 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.

  14. 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

  15. Accurately measuring sea level change from space: an ESA Climate Change Initiative for MSL closure budget studies

    NASA Astrophysics Data System (ADS)

    Legeais, JeanFrancois; Cazenave, Anny; Ablain, Michael; Larnicol, Gilles; Benveniste, Jerome; Johannessen, Johnny; Timms, Gary; Andersen, Ole; Cipollini, Paolo; Roca, Monica; Rudenko, Sergei; Fernandes, Joana; Balmaseda, Magdalena; Quartly, Graham; Fenoglio-Marc, Luciana; Meyssignac, Benoit; Scharffenberg, Martin

    2016-04-01

    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 the Sea Level ECV which has benefited from yearly extensions and now covers the period 1993-2014. We will firstly 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 validation, performed by several groups of the ocean and climate modeling community. At last, new altimeter standards have been developed and the best one have been recently selected in order to produce a full

  16. 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

  17. 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

  18. 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.

  19. 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…

  20. 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

  1. RT-PCR is a more accurate diagnostic tool for detection of BCR-ABL rearrangement

    SciTech Connect

    Zehnbauer, B.A.; Allen, A.P.; McGrath, S.D.

    1994-09-01

    Detection of the Philadelphia chromosome (Ph1) or genomic Southern hybridization for clonal gene rearrangement (GSH-R) has provided very specific identification of BCR-ABL gene rearrangement. Reverse transcriptase-polymerase chain reaction (RT-PCR) is diagnostic for patterns of BCR-ABL expression which are undetected by GSH-R and/or Ph1 and provides increased sensitivity both at diagnosis and in detection of minimal residual leukemia. Fifty-three specimens (of 150 tested from 119 consecutive leukemia patients) were RT-PCR positive for BCR-ABL gene expression confirmed by hybridization of PCR products with b{sub 3}a{sub 2}, b{sub 2}a{sub 2}, or e{sub 1}a{sub 2} junction-specific oligonucleotides. In 6 cases of CML with GSH-R{sup {minus}}at diagnosis, RT-PCR provided specific BCR-ABL identification. Deletion of BCR regions, low mitotic index, or e{sub 1}a{sub 2} expression caused failure to detect GSH-R or Ph1 translocation.

  2. 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.

  3. 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.

  4. A MATLAB-based tool for accurate detection of perfect overlapping and nested inverted repeats in DNA sequences

    PubMed Central

    Sreeskandarajan, Sutharzan; Flowers, Michelle M.; Karro, John E.; Liang, Chun

    2014-01-01

    Summary: Palindromic sequences, or inverted repeats (IRs), in DNA sequences involve important biological processes such as DNA–protein binding, DNA replication and DNA transposition. Development of bioinformatics tools that are capable of accurately detecting perfect IRs can enable genome-wide studies of IR patterns in both prokaryotes and eukaryotes. Different from conventional string-comparison approaches, we propose a novel algorithm that uses a cumulative score system based on a prime number representation of nucleotide bases. We then implemented this algorithm as a MATLAB-based program for perfect IR detection. In comparison with other existing tools, our program demonstrates a high accuracy in detecting nested and overlapping IRs. Availability and implementation: The source code is freely available on (http://bioinfolab.miamioh.edu/bioinfolab/palindrome.php) Contact: liangc@miamioh.edu or karroje@miamioh.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24215021

  5. 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

  6. 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.

  7. Abdominal MRI without Enteral Contrast Accurately Detects Intestinal Fibrostenosis in Patients with Inflammatory Bowel Disease.

    PubMed

    Fisher, Jeremy G; Kalb, Bobby; Martin, Diego; Dhere, Tanvi; Perez, Sebastian D; Srinivasan, Jahnavi K

    2015-11-01

    Patients with inflammatory bowel disease (IBD) presenting for surgical evaluation require thorough small bowel surveillance as it improves accuracy of diagnosis (ulcerative colitis versus Crohn's) and differentiates those who may respond to nonoperative therapy, preserving bowel length. MRI has not been validated conclusively against histopathology in IBD. Most protocols require enteral contrast. This study aimed to 1) evaluate the accuracy of MRI for inflammation, fibrosis, and extraluminal complications and 2) compare MRI without enteral contrast to standard magnetic resonance enterography. Adults with Crohn's disease or ulcerative colitis who underwent abdominal MRI and surgery were retrospectively reviewed. Of 65 patients evaluated, 55 met inclusion criteria. Overall sensitivity and specificity of MRI for disease involvement localized by segment were 93 per cent (95% confidence interval = 89.4-95.0) and 95 per cent (95% confidence interval = 92.3-97.0), respectively (positive predictive value was 86%, negative predictive value was 98%). Sensitivity and specificity between MRI with and without oral and rectal contrast were similar (96% vs 91% and 99% vs 94%, P > 0.10). As were positive predictive value and negative predictive value (85% vs 96%, P = 0.16; 97% vs 99%, P = 0.42). Magnetic resonance is highly sensitive and specific for localized disease involvement and extraluminal abdominal sequelae of IBD. It accurately differentiates patients who have chronic transmural (fibrotic) disease and thus may require an operation from those with acute inflammation, whose symptoms may improve with aggressive medical therapy alone. MRI without contrast had comparable diagnostic yield to standard magnetic resonance enterography. PMID:26672581

  8. High-throughput baggage scanning employing x-ray diffraction for accurate explosives detection

    NASA Astrophysics Data System (ADS)

    Green, Michael C.; Partain, Larry D.

    2003-07-01

    X-ray systems dominate the installed base of airport baggage scanning systems for explosives detection. The majority are conveyer systems with projection line scanners. These systems can achieve a high throughput but exhibit a high false positive rate and require significant operator involvement. Systems employing computed tomography (CT) are currently being installed at a rapid rate. These can provide good discrimination of levels of xray absorption coefficient and can largely circumvent superimposition effects. Nonetheless CT measures only x-ray absorption coefficient per voxel which does not provide a means of specific material identification resulting in many false positives, and it is relatively straightforward to configure explosive materials so that they are undetectable by CT systems. Diffraction-based x-ray systems present a solution to this problem. They detect and measure atomic layer spacings in crystalline and microcrystalline materials with high sensitivity. This provides a means of specific material identification. The majority of explosive compounds are well crystallized solids at room temperature. X-ray diffraction systems using both conventional wavelength-dispersive diffraction and fixed-angle, multi-wavelength diffraction for improved throughput are described. Large-area, flat-panel x-ray detector technology coupled with an extended x-ray source will permit a full 3D volumetric x-ray diffraction scan of a bag in a single pass, (patent pending).

  9. 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. PMID:26656583

  10. 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.

  11. 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. PMID:25911421

  12. 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.

  13. 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

  14. 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. PMID:22025415

  15. Optimizing photon fluence measurements for the accurate determination of detective quantum efficiency

    NASA Astrophysics Data System (ADS)

    Wong, Molly; Zhang, Da; Rong, John; Wu, Xizeng; Liu, Hong

    2009-10-01

    Our goal was to evaluate the error contributed by photon fluence measurements to the detective quantum efficiency (DQE) of an x-ray imaging system. The investigation consisted of separate error analyses for the exposure and spectrum measurements that determine the photon fluence. Methods were developed for each to determine the number of measurements required to achieve an acceptable error. A new method for calculating the magnification factor in the exposure measurements was presented and compared to the existing method. The new method not only produces much lower error at small source-to-image distances (SIDs) such as clinical systems, but is also independent of SID. The exposure and spectra results were combined to determine the photon fluence error contribution to the DQE of 4%. The error in this study is small because the measurements resulted from precisely controlled experimental procedures designed to minimize the error. However, these procedures are difficult to follow in clinical environments, and application of this method on clinical systems could therefore provide important insight into error reduction. This investigation was focused on the error in the photon fluence contribution to the DQE, but the error analysis method can easily be extended to a wide range of applications.

  16. Accurate determination of the diffusion coefficient of proteins by Fourier analysis with whole column imaging detection.

    PubMed

    Zarabadi, Atefeh S; Pawliszyn, Janusz

    2015-02-17

    Analysis in the frequency domain is considered a powerful tool to elicit precise information from spectroscopic signals. In this study, the Fourier transformation technique is employed to determine the diffusion coefficient (D) of a number of proteins in the frequency domain. Analytical approaches are investigated for determination of D from both experimental and data treatment viewpoints. The diffusion process is modeled to calculate diffusion coefficients based on the Fourier transformation solution to Fick's law equation, and its results are compared to time domain results. The simulations characterize optimum spatial and temporal conditions and demonstrate the noise tolerance of the method. The proposed model is validated by its application for the electropherograms from the diffusion path of a set of proteins. Real-time dynamic scanning is conducted to monitor dispersion by employing whole column imaging detection technology in combination with capillary isoelectric focusing (CIEF) and the imaging plug flow (iPF) experiment. These experimental techniques provide different peak shapes, which are utilized to demonstrate the Fourier transformation ability in extracting diffusion coefficients out of irregular shape signals. Experimental results confirmed that the Fourier transformation procedure substantially enhanced the accuracy of the determined values compared to those obtained in the time domain. PMID:25607375

  17. Blood Pressure over Height Ratios: Simple and Accurate Method of Detecting Elevated Blood Pressure in Children.

    PubMed

    Galescu, Ovidiu; George, Minu; Basetty, Sudhakar; Predescu, Iuliana; Mongia, Anil; Ten, Svetlana; Bhangoo, Amrit

    2012-01-01

    Background. Blood pressure (BP) percentiles in childhood are assessed according to age, gender, and height. Objective. To create a simple BP/height ratio for both systolic BP (SBP) and diastolic BP (DBP). To study the relationship between BP/height ratios and corresponding BP percentiles in children. Methods. We analyzed data on height and BP from 2006-2007 NHANES data. BP percentiles were calculated for 3775 children. Receiver-operating characteristic (ROC) curve analyses were performed to calculate sensitivity and specificity of BP/height ratios as diagnostic tests for elevated BP (>90%). Correlation analysis was performed between BP percentiles and BP/height ratios. Results. The average age was 12.54 ± 2.67 years. SBP/height and DBP/height ratios strongly correlated with SBP & DBP percentiles in both boys (P < 0.001, R(2) = 0.85, R(2) = 0.86) and girls (P < 0.001, R(2) = 0.85, R(2) = 0.90). The cutoffs of SBP/height and DBP/height ratios in boys were ≥0.75 and ≥0.46, respectively; in girls the ratios were ≥0.75 and ≥0.48, respectively with sensitivity and specificity in range of 83-100%. Conclusion. BP/height ratios are simple with high sensitivity and specificity to detect elevated BP in children. These ratios can be easily used in routine medical care of children. PMID:22577400

  18. Blood Pressure over Height Ratios: Simple and Accurate Method of Detecting Elevated Blood Pressure in Children

    PubMed Central

    Galescu, Ovidiu; George, Minu; Basetty, Sudhakar; Predescu, Iuliana; Mongia, Anil; Ten, Svetlana; Bhangoo, Amrit

    2012-01-01

    Background. Blood pressure (BP) percentiles in childhood are assessed according to age, gender, and height. Objective. To create a simple BP/height ratio for both systolic BP (SBP) and diastolic BP (DBP). To study the relationship between BP/height ratios and corresponding BP percentiles in children. Methods. We analyzed data on height and BP from 2006-2007 NHANES data. BP percentiles were calculated for 3775 children. Receiver-operating characteristic (ROC) curve analyses were performed to calculate sensitivity and specificity of BP/height ratios as diagnostic tests for elevated BP (>90%). Correlation analysis was performed between BP percentiles and BP/height ratios. Results. The average age was 12.54 ± 2.67 years. SBP/height and DBP/height ratios strongly correlated with SBP & DBP percentiles in both boys (P < 0.001, R2 = 0.85, R2 = 0.86) and girls (P < 0.001, R2 = 0.85, R2 = 0.90). The cutoffs of SBP/height and DBP/height ratios in boys were ≥0.75 and ≥0.46, respectively; in girls the ratios were ≥0.75 and ≥0.48, respectively with sensitivity and specificity in range of 83–100%. Conclusion. BP/height ratios are simple with high sensitivity and specificity to detect elevated BP in children. These ratios can be easily used in routine medical care of children. PMID:22577400

  19. A new hybrid intelligent system for accurate detection of Parkinson's disease.

    PubMed

    Hariharan, M; Polat, Kemal; Sindhu, R

    2014-03-01

    Elderly people are commonly affected by Parkinson's disease (PD) which is one of the most common neurodegenerative disorders due to the loss of dopamine-producing brain cells. People with PD's (PWP) may have difficulty in walking, talking or completing other simple tasks. Variety of medications is available to treat PD. Recently, researchers have found that voice signals recorded from the PWP is becoming a useful tool to differentiate them from healthy controls. Several dysphonia features, feature reduction/selection techniques and classification algorithms were proposed by researchers in the literature to detect PD. In this paper, hybrid intelligent system is proposed which includes feature pre-processing using Model-based clustering (Gaussian mixture model), feature reduction/selection using principal component analysis (PCA), linear discriminant analysis (LDA), sequential forward selection (SFS) and sequential backward selection (SBS), and classification using three supervised classifiers such as least-square support vector machine (LS-SVM), probabilistic neural network (PNN) and general regression neural network (GRNN). PD dataset was used from University of California-Irvine (UCI) machine learning database. The strength of the proposed method has been evaluated through several performance measures. The experimental results show that the combination of feature pre-processing, feature reduction/selection methods and classification gives a maximum classification accuracy of 100% for the Parkinson's dataset. PMID:24485390

  20. Enhancing implicit change detection through action.

    PubMed

    Tseng, Philip; Tuennermann, Jan; Roker-Knight, Nancy; Winter, Dorina; Scharlau, Ingrid; Bridgeman, Bruce

    2010-01-01

    Implicit change detection demonstrates how the visual system can benefit from stored information that is not immediately available to conscious awareness. We investigated the role of motor action in this context. In the first two experiments, using a one-shot implicit change-detection paradigm, participants responded to unperceived changes either with an action (jabbing the screen at the guessed location of a change) or with words (verbal report), and sat either 60 cm or 300 cm (with a laser pointer) away from the display. Our observers guessed the locations of changes at a reachable distance better with an action than with a verbal judgment. At 300 cm, beyond reach, the motor advantage disappeared. In experiment 3, this advantage was also unavailable when participants sat at a reachable distance but responded with hand-held laser pointers near their bodies. We conclude that a motor system specialized for real-time visually guided behavior has access to additional visual information. Importantly, this system is not activated by merely executing an action (experiment 2) or presenting stimuli in one's near space (experiment 3). It is activated only when both conditions are fulfilled, which implies that it is the actual contact that matters to the visual system. PMID:21180353

  1. 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

  2. PLIF: A rapid, accurate method to detect and quantitatively assess protein-lipid interactions.

    PubMed

    Ceccato, Laurie; Chicanne, Gaëtan; Nahoum, Virginie; Pons, Véronique; Payrastre, Bernard; Gaits-Iacovoni, Frédérique; Viaud, Julien

    2016-01-01

    Phosphoinositides are a type of cellular phospholipid that regulate signaling in a wide range of cellular and physiological processes through the interaction between their phosphorylated inositol head group and specific domains in various cytosolic proteins. These lipids also influence the activity of transmembrane proteins. Aberrant phosphoinositide signaling is associated with numerous diseases, including cancer, obesity, and diabetes. Thus, identifying phosphoinositide-binding partners and the aspects that define their specificity can direct drug development. However, current methods are costly, time-consuming, or technically challenging and inaccessible to many laboratories. We developed a method called PLIF (for "protein-lipid interaction by fluorescence") that uses fluorescently labeled liposomes and tethered, tagged proteins or peptides to enable fast and reliable determination of protein domain specificity for given phosphoinositides in a membrane environment. We validated PLIF against previously known phosphoinositide-binding partners for various proteins and obtained relative affinity profiles. Moreover, PLIF analysis of the sorting nexin (SNX) family revealed not only that SNXs bound most strongly to phosphatidylinositol 3-phosphate (PtdIns3P or PI3P), which is known from analysis with other methods, but also that they interacted with other phosphoinositides, which had not previously been detected using other techniques. Different phosphoinositide partners, even those with relatively weak binding affinity, could account for the diverse functions of SNXs in vesicular trafficking and protein sorting. Because PLIF is sensitive, semiquantitative, and performed in a high-throughput manner, it may be used to screen for highly specific protein-lipid interaction inhibitors. PMID:27025878

  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. 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.

  5. 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.

  6. 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.

  7. 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

  8. 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

  9. 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.

  10. 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.

  11. Accurate sensitivity of quantum dots for detection of HER2 expression in breast cancer cells and tissues.

    PubMed

    Tabatabaei-Panah, Akram-Sadat; Jeddi-Tehrani, Mahmood; Ghods, Roya; Akhondi, Mohammad-Mehdi; Mojtabavi, Nazanin; Mahmoudi, Ahmad-Reza; Mirzadegan, Ebrahim; Shojaeian, Sorour; Zarnani, Amir-Hassan

    2013-03-01

    Here we introduce novel optical properties and accurate sensitivity of Quantum dot (QD)-based detection system for tracking the breast cancer marker, HER2. QD525 was used to detect HER2 using home-made HER2-specific monoclonal antibodies in fixed and living HER2(+) SKBR-3 cell line and breast cancer tissues. Additionally, we compared fluorescence intensity (FI), photostability and staining index (SI) of QD525 signals at different exposure times and two excitation wavelengths with those of the conventional organic dye, FITC. Labeling signals of QD525 in both fixed and living breast cancer cells and tissue preparations were found to be significantly higher than those of FITC at 460-495 nm excitation wavelengths. Interestingly, when excited at 330-385 nm, the superiority of QD525 was more highlighted with at least 4-5 fold higher FI and SI compared to FITC. Moreover, QDs exhibited exceptional photostability during continuous illumination of cancerous cells and tissues, while FITC signal faded very quickly. QDs can be used as sensitive reporters for in situ detection of tumor markers which in turn could be viewed as a novel approach for early detection of cancers. To take comprehensive advantage of QDs, it is necessary that their optimal excitation wavelength is employed. PMID:23212129

  12. 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

  13. Age-related changes in multifinger synergies in accurate moment of force production tasks

    PubMed Central

    Olafsdottir, Halla; Zhang, Wei; Zatsiorsky, Vladimir M.; Latash, Mark L.

    2010-01-01

    The purpose of this investigation was to document and quantify age-related differences in the coordination of fingers during a task that required production of an accurate time profile of the total moment of force by the four fingers of a hand. We hypothesized that elderly subjects would show a decreased ability to stabilize a time profile of the total moment of force, leading to larger indexes of moment variability compared with young subjects. The subjects followed a trapezoidal template on a computer screen by producing a time profile of the total moment of force while pressing down on force sensors with the four fingers of the right (dominant) hand. To quantify synergies, we used the framework of the uncontrolled manifold hypothesis. The elderly subjects produced larger total force, larger variance of both total force and total moment of force, and larger involvement of fingers that produced moment of force against the required moment direction (antagonist moment). This was particularly prominent during supination efforts. Young subjects showed covariation of commands to fingers across trials that stabilized the moment of total force (moment-stabilizing synergy), while elderly subjects failed to do so. Both subject groups showed similar indexes of covariation of commands to the fingers that stabilized the time profile of the total force. The lack of moment-stabilizing synergies may be causally related to the documented impairment of hand function with age. PMID:17204576

  14. Lake Chapala change detection using time series

    NASA Astrophysics Data System (ADS)

    López-Caloca, Alejandra; Tapia-Silva, Felipe-Omar; Escalante-Ramírez, Boris

    2008-10-01

    The Lake Chapala is the largest natural lake in Mexico. It presents a hydrological imbalance problem caused by diminishing intakes from the Lerma River, pollution from said volumes, native vegetation and solid waste. This article presents a study that allows us to determine with high precision the extent of the affectation in both extension and volume reduction of the Lake Chapala in the period going from 1990 to 2007. Through satellite images this above-mentioned period was monitored. Image segmentation was achieved through a Markov Random Field model, extending the application towards edge detection. This allows adequately defining the lake's limits as well as determining new zones within the lake, both changes pertaining the Lake Chapala. Detected changes are related to a hydrological balance study based on measuring variables such as storage volumes, evapotranspiration and water balance. Results show that the changes in the Lake Chapala establish frail conditions which pose a future risk situation. Rehabilitation of the lake requires a hydrologic balance in its banks and aquifers.

  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. 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.

  17. Immunohistochemical Detection of Changes in Tumor Hypoxia

    PubMed Central

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

    2009-01-01

    Purpose Although hypoxia is a known prognostic factor, its impact will be modified by the rate of reoxygenation and the extent to which cells are acutely hypoxic. We tested the ability of exogenous and endogenous markers to detect reoxygenation in a xenograft model. Our technique may 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 CAIX and HIF1α. 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. HIF1α staining was also decreased relative to CAIX, though 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 HIF1α Conclusions HIF1α can be compared to either CAIX or a previously administered nitroimidazole to provide an estimate of reoxygenation. PMID:19251089

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

    SciTech Connect

    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.

  19. 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

  20. 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

  1. Detecting past changes of effective population size

    PubMed Central

    Nikolic, Natacha; Chevalet, Claude

    2014-01-01

    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. PMID:25067949

  2. 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.

  3. 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

  4. 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

  5. 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

  6. 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.

  7. 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

    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.

  8. SAR coherent change detection (CCD) for search and rescue

    NASA Astrophysics Data System (ADS)

    Mansfield, Arthur W.; Poehler, Paul L.; Rais, Houra

    1997-06-01

    Recent advances in the areas of phase history processing, interferometry, and radargrammetric adjustment have made possible extremely accurate information extraction from synthetic aperture radar (SAR) image pairs by means of interferometric techniques. The potential gain in accuracy is significant since measurements can theoretically be determined to within a fraction of a wavelength (subcentimeter accuracy) as opposed to a fraction of pixel distance (meter accuracy). One promising application of interferometric SAR (IFSAR) is the use of coherent change detection (CCD) over large areas to locate downed aircraft. This application poses an additional challenge since IFSAR must be processed at longer wavelengths to achieve foliage penetration. In this paper a combination of advanced techniques is described for using airborne SAR imagery to carry out this mission. Performance parameters are derived, and some examples are given from actual data.

  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. 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.

  11. 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. PMID:26317494

  12. 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.

  13. 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.

  14. Highly Accurate Antibody Assays for Early and Rapid Detection of Tuberculosis in African and Asian Elephants ▿

    PubMed Central

    Greenwald, Rena; Lyashchenko, Olena; Esfandiari, Javan; Miller, Michele; Mikota, Susan; Olsen, John H.; Ball, Ray; Dumonceaux, Genevieve; Schmitt, Dennis; Moller, Torsten; Payeur, Janet B.; Harris, Beth; Sofranko, Denise; Waters, W. Ray; Lyashchenko, Konstantin P.

    2009-01-01

    Tuberculosis (TB) in elephants is a reemerging zoonotic disease caused primarily by Mycobacterium tuberculosis. Current methods for screening and diagnosis rely on trunk wash culture, which has serious limitations due to low test sensitivity, slow turnaround time, and variable sample quality. Innovative and more efficient diagnostic tools are urgently needed. We describe three novel serologic techniques, the ElephantTB Stat-Pak kit, multiantigen print immunoassay, and dual-path platform VetTB test, for rapid antibody detection in elephants. The study was performed with serum samples from 236 captive African and Asian elephants from 53 different locations in the United States and Europe. The elephants were divided into three groups based on disease status and history of exposure: (i) 26 animals with culture-confirmed TB due to M. tuberculosis or Mycobacterium bovis, (ii) 63 exposed elephants from known-infected herds that had never produced a culture-positive result from trunk wash samples, and (iii) 147 elephants without clinical symptoms suggestive of TB, with consistently negative trunk wash culture results, and with no history of potential exposure to TB in the past 5 years. Elephants with culture-confirmed TB and a proportion of exposed but trunk wash culture-negative elephants produced robust antibody responses to multiple antigens of M. tuberculosis, with seroconversions detectable years before TB-positive cultures were obtained from trunk wash specimens. ESAT-6 and CFP10 proteins were immunodominant antigens recognized by elephant antibodies during disease. The serologic assays demonstrated 100% sensitivity and 95 to 100% specificity. Rapid and accurate antibody tests to identify infected elephants will likely allow earlier and more efficient treatment, thus limiting transmission of infection to other susceptible animals and to humans. PMID:19261770

  15. 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

  16. 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

  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. Fiber-optic immuno-biosensor for rapid and accurate detection of nerve growth factor in human blood.

    PubMed

    Tang, Liang; Cha, Yong-Mei; Li, Hongmei; Chen, Peng-Sheng; Lin, Shien-Fong

    2006-01-01

    An accurate and rapid assay of cardiac nerve growth factor (NGF) levels in blood can provide physicians with critical information regarding myocardial injury and neural remodeling in cardiac tissues to identify patients at risk of impending heart attack, thereby enabling them to receive appropriate lifesaving treatment more quickly. Currently used assay methods, such as enzyme-linked immunosorbent assay (ELISA), are usually time-consuming (hours to days), expensive and technically complicated. In this paper, we described the development and clinical study of a rapid and sensitive method for detection and quantification of NGF in human blood plasma. This method utilizes a fiber-optic, immuno-biosensing system which performs a fluorophore-mediated sandwich immunoassay on the surface of an optical fiber. Physiological concentrations of NGF could be quantified in both buffer and human blood plasma samples within 5 minutes. The NGF concentrations determined by the fiberoptic sensor were comparable to those by the gold standard, ELISA. Preliminary study of NGF assay in cardiac patient plasma samples showed a great potential of the fiber-optic sensor as a rapid diagnostic and prognostic tool in clinical applications. PMID:17946002

  19. 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.

  20. 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…

  1. 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

  2. Accurate three-dimensional registration of magnetic resonance images for detecting local changes in cartilage thickness

    NASA Astrophysics Data System (ADS)

    Cheng, Yuanzhi; Jin, Quan; Zhao, Jie; Guo, Changyong; Bai, Jing

    2011-04-01

    The purpose of this study is to develop a three-dimensional registration method for monitoring knee joint disease from magnetic resonance (MR) image data sets. A global optimization technique was used for identifying anatomically corresponding points of knee femur surfaces (bone cartilage interfaces). In a first pre-registration step, we used the principal axes transformation to correct for different knee joint positions and orientations in the MR scanner. In a second step, we presented a global search algorithm based on Lipschitz optimization theory. This technique can simultaneously determine the translation and rotation parameters through searching a six-dimensional space of Euclidean motion metrics (translation and rotation) after calculating the point correspondences. The point correspondences were calculated by using the Hungarian algorithm. The accuracy of registration was evaluated using 20 porcine knees. There were 300 corresponding landmark points over the 20 pig knees. We evaluated the registration accuracy by measuring the root-mean-square distance (RMSD) error of corresponding landmark points between two femur surfaces (two time-points). The results show that the average RMSD was 1.22 +/- 0.10 mm (SD) by the iterative closest point (ICP) method, 1.17 +/- 0.10 mm the by expectation-maximization-ICP method, 1.02 +/- 0.06 mm by the genetic method, and 0.93 +/- 0.04 mm by the proposed method. Compared with the other three registration approaches, the proposed method achieved the highest registration accuracy.

  3. 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.

  4. A subsurface structure change associated with the eruptive activity at Sakurajima Volcano, Japan, inferred from an accurately controlled source

    NASA Astrophysics Data System (ADS)

    Maeda, Yuta; Yamaoka, Koshun; Miyamachi, Hiroki; Watanabe, Toshiki; Kunitomo, Takahiro; Ikuta, Ryoya; Yakiwara, Hiroshi; Iguchi, Masato

    2015-07-01

    Temporal variations of Green functions associated with the eruptive activity at Sakurajima Volcano, Japan, were estimated using an accurately controlled routinely operated signal system (ACROSS). We deconvolved 400 s waveforms of the ACROSS signal at nearby stations by a known source time function and stacked the results based on the time relative to individual eruptions and the eruption intervals; the quantities obtained by this procedure are Green functions corresponding to various stages of the eruptive activity. We found an energy decrease in the later phase of the Green functions in active eruptive periods. This energy decrease, localized in the 2-6 s window of the Green functions, is difficult to explain by contamination from volcanic earthquakes and tremors. The decrease could be more reasonably attributed to a subsurface structure change caused by the volcanic activity.

  5. Detection of temporal changes in earthquake rates

    NASA Astrophysics Data System (ADS)

    Touati, S.

    2012-12-01

    Many statistical analyses of earthquake rates and time-dependent forecasting of future rates involve the detection of changes in the basic rate of events, independent of the fluctuations caused by aftershock sequences. We examine some of the statistical techniques for inferring these changes, using both real and synthetic earthquake data to check the statistical significance of these inferences. One common method is to use the Akaike Information Criterion (AIC) to choose between a single model and a double model with a changepoint; this criterion evaluates the strength of the fit and incorporates a penalty for the extra parameters. We test this method on many realisations of the ETAS model, with and without changepoints present, to see how often it chooses the correct model. A more rigorous method is to calculate the Bayesian evidence, or marginal likelihood, for each model and then compare these. The evidence is essentially the likelihood of the model integrated over the whole of the model space, giving a measure of how likely the data is for that model. It does not rely on estimation of best-fit parameters, making it a better comparator than the AIC; Occam's razor also arises naturally in this process due to the fact that more complex models tend to be able to explain a larger range of observations, and therefore the relative likelihood of any particular observations will be smaller than for a simpler model. Evidence can be calculated using Markov Chain Monte Carlo techniques. We compare these two approaches on synthetic data. We also look at the 1997-98 Colfiorito sequence in Umbria-Marche, Italy, using maximum likelihood to fit the ETAS model and then simulating the ETAS model to create synthetic versions of the catalogue for comparison. We simulate using ensembles of parameter values sampled from the posterior for each parameter, with the largest events artificially inserted, to compare the resultant event rates, inter-event time distributions and other

  6. Change-point detection in time-series data by relative density-ratio estimation.

    PubMed

    Liu, Song; Yamada, Makoto; Collier, Nigel; Sugiyama, Masashi

    2013-07-01

    The objective of change-point detection is to discover abrupt property changes lying behind time-series data. In this paper, we present a novel statistical change-point detection algorithm based on non-parametric divergence estimation between time-series samples from two retrospective segments. Our method uses the relative Pearson divergence as a divergence measure, and it is accurately and efficiently estimated by a method of direct density-ratio estimation. Through experiments on artificial and real-world datasets including human-activity sensing, speech, and Twitter messages, we demonstrate the usefulness of the proposed method. PMID:23500502

  7. 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

  8. 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.

  9. 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

  10. Accurate detection for a wide range of mutation and editing sites of microRNAs from small RNA high-throughput sequencing profiles.

    PubMed

    Zheng, Yun; Ji, Bo; Song, Renhua; Wang, Shengpeng; Li, Ting; Zhang, Xiaotuo; Chen, Kun; Li, Tianqing; Li, Jinyan

    2016-08-19

    Various types of mutation and editing (M/E) events in microRNAs (miRNAs) can change the stabilities of pre-miRNAs and/or complementarities between miRNAs and their targets. Small RNA (sRNA) high-throughput sequencing (HTS) profiles can contain many mutated and edited miRNAs. Systematic detection of miRNA mutation and editing sites from the huge volume of sRNA HTS profiles is computationally difficult, as high sensitivity and low false positive rate (FPR) are both required. We propose a novel method (named MiRME) for an accurate and fast detection of miRNA M/E sites using a progressive sequence alignment approach which refines sensitivity and improves FPR step-by-step. From 70 sRNA HTS profiles with over 1.3 billion reads, MiRME has detected thousands of statistically significant M/E sites, including 3'-editing sites, 57 A-to-I editing sites (of which 32 are novel), as well as some putative non-canonical editing sites. We demonstrated that a few non-canonical editing sites were not resulted from mutations in genome by integrating the analysis of genome HTS profiles of two human cell lines, suggesting the existence of new editing types to further diversify the functions of miRNAs. Compared with six existing studies or methods, MiRME has shown much superior performance for the identification and visualization of the M/E sites of miRNAs from the ever-increasing sRNA HTS profiles. PMID:27229138

  11. Occupancy change detection system and method

    SciTech Connect

    Bruemmer, David J; Few, Douglas A

    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.

  12. 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.

  13. 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.

  14. 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

  15. 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.

  16. 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.

  17. Vegetation change detection based on image fusion technique

    NASA Astrophysics Data System (ADS)

    Jia, Yonghong; Liu, Yueyan; Yu, Hui; Li, Deren

    2005-10-01

    The change detection of land use and land cover has always been the focus of remotely sensed study and application. Based on techniques of image fusion, a new approach of detecting vegetation change according to vector of brightness index (BI) and perpendicular vegetation index (PVI) extracted from multi-temporal remotely sensed imagery is proposed. The procedure is introduced. Firstly, the Landsat eTM+ imagery is geometrically corrected and registered. Secondly, band 2,3,4 and panchromatic images of Landsat eTM+ are fused by a trous wavelet fusion, and bands 1,2,3 of SPOT are registered to the fused images. Thirdly, brightness index and perpendicular vegetation index are respectively extracted from SPOT images and fused images. Finally, change vectors are obtained and used to detect vegetation change. The testing results show that the approach of detecting vegetation change is very efficient.

  18. 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

  19. 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…

  20. 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.

  1. 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.

  2. 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.

  3. Change detection using the synchronous impulse reconstruction (SIRE) radar

    NASA Astrophysics Data System (ADS)

    Ranney, Kenneth; Nguyen, Lam; Ressler, Marc; Stanton, Brian; Wong, David; Koenig, Francois; Tran, Chi; Kirose, Getachew; Martone, Anthony; Smith, Greg; Sichina, Jeff; Kappra, Karl

    2008-04-01

    Change detection provides a powerful tool for detecting the introduction of weapons or hazardous materials into an area under surveillance, as demonstrated in past work carried out at the Army Research Laboratory (ARL). This earlier work demonstrated the potential for detecting recently emplaced surface landmines using an X-Band, synthetic aperture radar (SAR) sensor. Recent experiments conducted at ARL have extended these change detection results to imagery collected by the synthetic impulse reconstruction (SIRE) radar - a lower-frequency system developed at ARL. In this paper we describe the algorithms adopted for this change detection experiment and present results obtained by applying these algorithms to the SIRE data set. Results indicate the potential for utilizing systems such as the SIRE as surveillance tools.

  4. Universal scene change detection on MPEG-coded data domain

    NASA Astrophysics Data System (ADS)

    Nakajima, Yasuyuki; Ujihara, Kiyono; Yoneyama, Akio

    1997-01-01

    In this paper, we propose scene decomposition algorithm from MPEG compressed video data. As a preprocessing for scene decomposition, partial reconstruction methods of DC image for P- and B-pictures as well as I-pictures directly from MPEG bitstream are used. As for detection algorithms, we have exploited several methods for detection of abrupt scene change, dissolve and wipe transitions using comparison of DC images between frames and coding information such as motion vectors. It is also proposed the method for exclusion of undesired detection such as flashlight in order to enhance scene change detection accuracy. It is shown that more than 95 percent of decomposition accuracy has been obtained in the experiment using more than one hour TV program. It is also found that in the proposed algorithm scene change detection can be performed more than 5 times faster than normal playback speed using 130MIPS workstation.

  5. 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

  6. Robust Detection of Dynamical Change in Scalp EEG

    SciTech Connect

    Gailey, P.C.; Hively, L.M.; Protopopescu, V.A.

    1999-06-28

    We present a robust, model-independent technique for measuring changes in the dynamics underlying nonlinear time-serial data. We define indicators of dynamical change by comparing distribution functions on the attractor via L{sub 1}-distance and X{sup 2} statistics. We apply the measures to scalp EEG data with the objective of capturing the transition between non-seizure and epileptic brain activity in a timely, accurate, and non-invasive manner. We find a clear superiority of the new metrics in comparison to traditional nonlinear measures as discriminators of dynamical change.

  7. Method to detect environmental change for an arid land

    NASA Astrophysics Data System (ADS)

    Ito, A.; Miyamoto, J.; Tsuchiya, K.; Ishiyama, T.

    A method to detect natural environmental change for an arid land is developed based on 17 bands Visible NIR SWIR and Thermal IR ASTER Advanced SpaceborneThermal Emission and Reflection radiometer aboard Terra and in situ ground truth survey in Taklimakan Desert The method first extracts an area of macroscopic change then detailed or microscopic changes are detected Although the procedure is described in two steps the actual precessing is performed automatically and nearly simultaneously The method is named as ECD Environmental Change Automatic Discrimination model method for the sake of convenience

  8. COPS: a sensitive and accurate tool for detecting somatic Copy Number Alterations using short-read sequence data from paired samples.

    PubMed

    Krishnan, Neeraja M; Gaur, Prakhar; Chaudhary, Rakshit; Rao, Arjun A; Panda, Binay

    2012-01-01

    Copy Number Alterations (CNAs) such as deletions and duplications; compose a larger percentage of genetic variations than single nucleotide polymorphisms or other structural variations in cancer genomes that undergo major chromosomal re-arrangements. It is, therefore, imperative to identify cancer-specific somatic copy number alterations (SCNAs), with respect to matched normal tissue, in order to understand their association with the disease. We have devised an accurate, sensitive, and easy-to-use tool, COPS, COpy number using Paired Samples, for detecting SCNAs. We rigorously tested the performance of COPS using short sequence simulated reads at various sizes and coverage of SCNAs, read depths, read lengths and also with real tumor:normal paired samples. We found COPS to perform better in comparison to other known SCNA detection tools for all evaluated parameters, namely, sensitivity (detection of true positives), specificity (detection of false positives) and size accuracy. COPS performed well for sequencing reads of all lengths when used with most upstream read alignment tools. Additionally, by incorporating a downstream boundary segmentation detection tool, the accuracy of SCNA boundaries was further improved. Here, we report an accurate, sensitive and easy to use tool in detecting cancer-specific SCNAs using short-read sequence data. In addition to cancer, COPS can be used for any disease as long as sequence reads from both disease and normal samples from the same individual are available. An added boundary segmentation detection module makes COPS detected SCNA boundaries more specific for the samples studied. COPS is available at ftp://115.119.160.213 with username "cops" and password "cops". PMID:23110103

  9. 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.

  10. 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.

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

    NASA Technical Reports Server (NTRS)

    Morizumi, N.; Kimura, H.

    1986-01-01

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

  12. A SAR ATR algorithm based on coherent change detection

    SciTech Connect

    Harmony, D.W.

    2000-12-01

    This report discusses an automatic target recognition (ATR) algorithm for synthetic aperture radar (SAR) imagery that is based on coherent change detection techniques. The algorithm relies on templates created from training data to identify targets. Objects are identified or rejected as targets by comparing their SAR signatures with templates using the same complex correlation scheme developed for coherent change detection. Preliminary results are presented in addition to future recommendations.

  13. 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…

  14. Real-time SAR change-detection using neural networks

    NASA Astrophysics Data System (ADS)

    Oliver, Christopher J.; White, Richard G.

    1990-11-01

    This paper describes the techniques evolved at RSRE for the production of undistorted, focused synthetic aperture radar (SAR) images, target detection using a neural network method and the automatic detection of changes between pairs of SAR images. All these processes are achievable in a single pipelined process operating on an input data rate in excess of 10 Mbytes/second.

  15. 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

  16. 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.

  17. Real-Time Cellular Analysis Coupled with a Specimen Enrichment Accurately Detects and Quantifies Clostridium difficile Toxins in Stool

    PubMed Central

    Huang, Bin; Jin, Dazhi; Zhang, Jing; Sun, Janet Y.; Wang, Xiaobo; Stiles, Jeffrey; Xu, Xiao; Kamboj, Mini; Babady, N. Esther

    2014-01-01

    We describe here the use of an immunomagnetic separation enrichment process coupled with a modified real-time cellular analysis (RTCA) system (RTCA version 2) for the detection of C. difficile toxin (CDT) in stool. The limit of CDT detection by RTCA version 2 was 0.12 ng/ml. Among the consecutively collected 401 diarrheal stool specimens, 53 (13.2%) were toxin-producing C. difficile strains by quantitative toxigenic culture (qTC); bacterial loads ranged from 3.00 × 101 to 3.69 × 106 CFU/ml. The RTCA version 2 method detected CDT in 51 samples, resulting in a sensitivity of 96.2%, a specificity of 99.7%, and positive and negative predictive values of 98.1% and 99.4%, respectively. The positive step time ranged from 1.43 to 35.85 h, with <24 h for 80% of the samples. The CDT concentrations in stool samples determined by RTCA version 2 correlated with toxigenic C. difficile bacterial load (R2 = 0.554, P = 0.00002) by qTC as well as the threshold cycle (R2 = 0.343, P = 0.014) by real-time PCR. A statistically significant correlation between the CDT concentrations and the clinical severity of CDI was observed (P = 0.015). The sensitivity of the RTCA version 2 assay for the detection of functional toxins in stool specimens was significantly improved when the immunomagnetic separation enrichment process was incorporated. More than 80% positive results can be obtained within 24 h. The stool specimen CDT concentration derived using the RTCA version 2 assay correlates with clinical severity and may be used as a marker for monitoring the status of CDI. PMID:24452160

  18. Real-time cellular analysis coupled with a specimen enrichment accurately detects and quantifies Clostridium difficile toxins in stool.

    PubMed

    Huang, Bin; Jin, Dazhi; Zhang, Jing; Sun, Janet Y; Wang, Xiaobo; Stiles, Jeffrey; Xu, Xiao; Kamboj, Mini; Babady, N Esther; Tang, Yi-Wei

    2014-04-01

    We describe here the use of an immunomagnetic separation enrichment process coupled with a modified real-time cellular analysis (RTCA) system (RTCA version 2) for the detection of C. difficile toxin (CDT) in stool. The limit of CDT detection by RTCA version 2 was 0.12 ng/ml. Among the consecutively collected 401 diarrheal stool specimens, 53 (13.2%) were toxin-producing C. difficile strains by quantitative toxigenic culture (qTC); bacterial loads ranged from 3.00 × 10(1) to 3.69 × 10(6) CFU/ml. The RTCA version 2 method detected CDT in 51 samples, resulting in a sensitivity of 96.2%, a specificity of 99.7%, and positive and negative predictive values of 98.1% and 99.4%, respectively. The positive step time ranged from 1.43 to 35.85 h, with <24 h for 80% of the samples. The CDT concentrations in stool samples determined by RTCA version 2 correlated with toxigenic C. difficile bacterial load (R(2) = 0.554, P = 0.00002) by qTC as well as the threshold cycle (R(2) = 0.343, P = 0.014) by real-time PCR. A statistically significant correlation between the CDT concentrations and the clinical severity of CDI was observed (P = 0.015). The sensitivity of the RTCA version 2 assay for the detection of functional toxins in stool specimens was significantly improved when the immunomagnetic separation enrichment process was incorporated. More than 80% positive results can be obtained within 24 h. The stool specimen CDT concentration derived using the RTCA version 2 assay correlates with clinical severity and may be used as a marker for monitoring the status of CDI. PMID:24452160

  19. 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…

  20. An N-targeting real-time PCR strategy for the accurate detection of spring viremia of carp virus.

    PubMed

    Shao, Ling; Xiao, Yu; He, Zhengkan; Gao, Longying

    2016-03-01

    Spring viremia of carp virus (SVCV) is a highly pathogenic agent of several economically important Cyprinidae fish species. Currently, there are no effective vaccines or drugs for this virus, and prevention of the disease mostly relies on prompt diagnosis. Previously, nested RT-PCR and RT-qPCR detection methods based on the glycoprotein gene G have been developed. However, the high genetic diversity of the G gene seriously limits the reliability of those methods. Compared with the G gene, phylogenetic analyses indicate that the nucleoprotein gene N is more conserved. Furthermore, studies in other members of the Rhabdoviridae family reveals that their gene transcription level follows the order N>P>M>G>L, indicating that an N gene based RT-PCR should have higher sensitivity. Therefore, two pairs of primers and two corresponding probes targeting the conserved regions of the N gene were designed. RT-qPCR assays demonstrated all primers and probes could detect phylogenetically distant isolates specifically and efficiently. Moreover, in artificially infected fish, the detected copy numbers of the N gene were much higher than those of the G gene in all tissues, and both the N and G gene copy numbers were highest in the kidney and spleen. Testing in 1100 farm-raised fish also showed that the N-targeting strategy was more reliable than the G-targeting methods. The method developed in this study provides a reliable tool for the rapid diagnosis of SVCV. PMID:26717888

  1. Change detection from very high resolution satellite time series with variable off-nadir angle

    NASA Astrophysics Data System (ADS)

    Barazzetti, Luigi; Brumana, Raffaella; Cuca, Branka; Previtali, Mattia

    2015-06-01

    Very high resolution (VHR) satellite images have the potential for revealing changes occurred overtime with a superior level of detail. However, their use for metric purposes requires accurate geo-localization with ancillary DEMs and GCPs to achieve sub-pixel terrain correction, in order to obtain images useful for mapping applications. Change detection with a time series of VHS images is not a simple task because images acquired with different off-nadir angles have a lack of pixel-to-pixel image correspondence, even after accurate geo-correction. This paper presents a procedure for automatic change detection able to deal with variable off-nadir angles. The case study concerns the identification of damaged buildings from pre- and post-event images acquired on the historic center of L'Aquila (Italy), which was struck by an earthquake in April 2009. The developed procedure is a multi-step approach where (i) classes are assigned to both images via object-based classification, (ii) an initial alignment is provided with an automated tile-based rubber sheeting interpolation on the extracted layers, and (iii) change detection is carried out removing residual mis-registration issues resulting in elongated features close to building edges. The method is fully automated except for some thresholds that can be interactively set to improve the visualization of the damaged buildings. The experimental results proved that damages can be automatically found without additional information, such as digital surface models, SAR data, or thematic vector layers.

  2. 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.

  3. 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

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

    PubMed

    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

  5. 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.

  6. 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

  7. 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

  8. 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.

  9. Analytical assays based on detecting conformational changes of single molecules.

    PubMed

    Zocchi, Giovanni

    2006-03-13

    One common strategy for the detection of biomolecules is labeling either the target itself or an antibody that binds to it. Herein, a different approach, based on detecting the conformational change of a probe molecule induced by binding of the target is discussed. That is, what is being detected is not the presence of the target or the probe, but the conformational change of the probe. Recently, a single-molecule sensor has been developed that exploits this mechanism to detect hybridization of a single DNA oligomer to a DNA probe, as well as specific binding of a single protein to a DNA probe. Biomolecular recognition often involves large conformational changes of the molecules involved, and therefore this strategy may be applicable to other assays. PMID:16514690

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. Vegetation change detection for urban areas based on extended change vector analysis

    NASA Astrophysics Data System (ADS)

    Yu, Hui; Jia, Yonghong

    2006-10-01

    This study sought to develop a modified change vector analysis(CVA) using normalized multi-temporal data to detect urban vegetation change. Because of complex change in urban areas, modified CVA application based on NDVI and mask techniques can minify the effect of non-vegetation changes and improve upon efficiency to a great extent. Moreover, drawing from methods in Polar plots, the extended CVA technique measures absolute angular changes and total magnitude of perpendicular vegetation index (PVI) and two of Tasseled Cap indices (greenness and wetness). Polar plots summarized change vectors to quantify and visualize both magnitude and direction of change, and magnitude is applied to determine change pixels through threshold segmentation while direction is applied as pixel's feature to classifying change pixels through supervised classification. Then this application is performed with Landsat ETM+ imageries of Wuhan in 2002 and 2005, and assessed by error matrix, which finds that it could detect change pixels 95.10% correct, and could classify change pixels 91.96% correct in seven change classes through performing supervised classification with direction angles. The technique demonstrates the ability of change vectors in multiple biophysical dimensions to vegetation change detection, and the application can be trended as an efficient alternative to urban vegetation change detection and classification.

  15. 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

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

    PubMed

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

    2015-03-01

    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 × 10(4) 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

  17. 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

  18. 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

  19. 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

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

    PubMed Central

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

    2015-01-01

    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. PMID:26025225

  1. Electrophysiological correlates of auditory change detection and change deafness in complex auditory scenes.

    PubMed

    Puschmann, Sebastian; Sandmann, Pascale; Ahrens, Janina; Thorne, Jeremy; Weerda, Riklef; Klump, Georg; Debener, Stefan; Thiel, Christiane M

    2013-07-15

    Change deafness describes the failure to perceive even intense changes within complex auditory input, if the listener does not attend to the changing sound. Remarkably, previous psychophysical data provide evidence that this effect occurs independently of successful stimulus encoding, indicating that undetected changes are processed to some extent in auditory cortex. Here we investigated cortical representations of detected and undetected auditory changes using electroencephalographic (EEG) recordings and a change deafness paradigm. We applied a one-shot change detection task, in which participants listened successively to three complex auditory scenes, each of them consisting of six simultaneously presented auditory streams. Listeners had to decide whether all scenes were identical or whether the pitch of one stream was changed between the last two presentations. Our data show significantly increased middle-latency Nb responses for both detected and undetected changes as compared to no-change trials. In contrast, only successfully detected changes were associated with a later mismatch response in auditory cortex, followed by increased N2, P3a and P3b responses, originating from hierarchically higher non-sensory brain regions. These results strengthen the view that undetected changes are successfully encoded at sensory level in auditory cortex, but fail to trigger later change-related cortical responses that lead to conscious perception of change. PMID:23466938

  2. 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

  3. A rapid method of accurate detection and differentiation of Newcastle disease virus pathotypes by demonstrating multiple bands in degenerate primer based nested RT-PCR.

    PubMed

    Desingu, P A; Singh, S D; Dhama, K; Kumar, O R Vinodh; Singh, R; Singh, R K

    2015-02-01

    A rapid and accurate method of detection and differentiation of virulent and avirulent Newcastle disease virus (NDV) pathotypes was developed. The NDV detection was carried out for different domestic avian field isolates and pigeon paramyxo virus-1 (25 field isolates and 9 vaccine strains) by using APMV-I "fusion" (F) gene Class II specific external primer A and B (535bp), internal primer C and D (238bp) based reverses transcriptase PCR (RT-PCR). The internal degenerative reverse primer D is specific for F gene cleavage position of virulent strain of NDV. The nested RT-PCR products of avirulent strains showed two bands (535bp and 424bp) while virulent strains showed four bands (535bp, 424bp, 349bp and 238bp) on agar gel electrophoresis. This is the first report regarding development and use of degenerate primer based nested RT-PCR for accurate detection and differentiation of NDV pathotypes by demonstrating multiple PCR band patterns. Being a rapid, simple, and economical test, the developed method could serve as a valuable alternate diagnostic tool for characterizing NDV isolates and carrying out molecular epidemiological surveillance studies for this important pathogen of poultry. PMID:25449112

  4. 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

  5. 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.

  6. 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

  7. (K,Na)NbO3 nanofiber-based self-powered sensors for accurate detection of dynamic strain.

    PubMed

    Wang, Zhao; Zhang, Youdong; Yang, Shulin; Hu, Yongming; Wang, Shengfu; Gu, Haoshuang; Wang, Yu; Chan, H L W; Wang, John

    2015-03-01

    A self-powered active strain sensor based on well-aligned (K,Na)NbO3 piezoelectric nanofibers is successfully fabricated through the electrospinning and polymer packaging process. The device exhibits a fast, active response to dynamic strain by generating impulsive voltage signal that is dependent on the amplitude of the dynamic strains and the vibration frequency. When the frequency is fixed at 1 Hz, the peak to peak value of the voltage increases from ∼1 to ∼40 mV, and the strain changes from 1 to 6%. Furthermore, the output voltage is linearly increased by an order of magnitude with the frequency changing from 0.2 to 5 Hz under the same strain amplitude. The influence of frequency on the output voltage can be further enhanced at higher strain amplitude. This phenomenon is attributed to the increased generating rate of piezoelectric charges under higher strain rate of the nanofibers. By counting the pulse separation of the voltage peaks, the vibration frequency is synchronously measured during the sensing process. The accuracy of the sensing results can be improved by calibration according to the frequency-dependent sensing behavior. PMID:25664376

  8. Change detection of lung cancer using image registration and thin-plate spline warping

    NASA Astrophysics Data System (ADS)

    Almasslawi, Dawood M. S.; Kabir, Ehsanollah

    2011-06-01

    Lung cancer has the lowest survival rate comparing to other types of cancer and determination of the patient's cancer stage is the most vital issue regarding the cancer treatment process. In most cases accurate estimation of the cancer stage is not easy to achieve. The changes in the size of the primary tumor can be detected using image registration techniques. The registration method proposed in this paper uses Normalized Mutual Information metric and Thin-Plate Spline transformation function for the accurate determination of the correspondence between series of the lung cancer Computed Tomography images. The Normalized Mutual Information is used as a metric for the rigid registration of the images to better estimate the global motion of the tissues and the Thin Plate Spline is used to deform the image in a locally supported manner. The Control Points needed for the transformation are extracted semiautomatically. This new approach in change detection of the lung cancer is implemented using the Insight Toolkit. The results from implementing this method on the CT images of 8 patients provided a satisfactory quality for change detection of the lung cancer.

  9. 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.

  10. 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.

  11. 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.

  12. The Complex Trial Protocol (CTP): a new, countermeasure-resistant, accurate, P300-based method for detection of concealed information.

    PubMed

    Rosenfeld, J Peter; Labkovsky, Elena; Winograd, Michael; Lui, Ming A; Vandenboom, Catherine; Chedid, Erica

    2008-11-01

    A new P300-based concealed information test is described. A rare probe or frequent irrelevant stimulus appears in the same trial in which a target or nontarget later appears. One response follows the first stimulus and uses the same button press regardless of stimulus type. A later second stimulus then appears: target or nontarget. The subject presses one button for a target, another for a nontarget. A P300 to the first stimulus indicates probe recognition. One group was tested in 3 weeks for denied recognition of familiar information. Weeks 1 and 3 were guilty conditions; Week 2 was a countermeasure (CM) condition. The probe-irrelevant differences were significant in all weeks, and percent hits were >90%. Attempted CM use was detectable via elevated reaction time to the first stimulus. In a replication, results were similar. False positive rates for both studies varied from 0 to .08, yielding J. B. Grier (1971) A' values from .9 to 1.0. PMID:18823418

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

    DOE PAGESBeta

    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

  14. 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.

  15. Intrusion detection robust to slow and abrupt lighting changes

    NASA Astrophysics Data System (ADS)

    Makarov, Aleksej; Vesin, Jean-Marc; Reymond, Florian

    1996-03-01

    In this communication we present an image based object detection algorithm which is applied to intrusion detection. The algorithm is based on the comparison of input edges and temporally filtered edges of the background. It is characterized by very low computational and memory loads, high sensitivity to the presence of physical intruders and high robustness to slow and abrupt lighting changes. The algorithm is implementable on a cheap digital signal processor. It was tested on a data base of about one thousand gray-level CIF-format frames representing static scenes with various contents (light sources, intruders, lighting changes), and neither false alarm nor detection failure occurred. The number of parameters involved by the algorithm is very low, and their values do not require a fine tuning. The same set of parameters performs equally well in different conditions: different scenes, various lighting changes, various object sizes.

  16. Modelling Visual Change Detection and Identification under Free Viewing Conditions.

    PubMed

    McAnally, Ken; Martin, Russell

    2016-01-01

    We examined whether the abilities of observers to perform an analogue of a real-world monitoring task involving detection and identification of changes to items in a visual display could be explained better by models based on signal detection theory (SDT) or high threshold theory (HTT). Our study differed from most previous studies in that observers were allowed to inspect the initial display for 3s, simulating the long inspection times typical of natural viewing, and their eye movements were not constrained. For the majority of observers, combined change detection and identification performance was best modelled by a SDT-based process that assumed that memory resources were distributed across all eight items in our displays. Some observers required a parameter to allow for sometimes making random guesses at the identities of changes they had missed. However, the performance of a small proportion of observers was best explained by a HTT-based model that allowed for lapses of attention. PMID:26882348

  17. 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.

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. Automatic recognition of landslides based on change detection

    NASA Astrophysics Data System (ADS)

    Li, Song; Hua, Houqiang

    2009-07-01

    After Wenchuan earthquake disaster, landslide disaster becomes a common concern, and remote sensing becomes more and more important in the application of landslide monitoring. Now, the method of interpretation and recognition for landslides using remote sensing is visual interpretation mostly. Automatic recognition of landslide is a new and difficult but significative job. For the purpose of seeking a more effective method to recognize landslide automatically, this project analyzes the current methods for the recognition of landslide disasters, and their applicability to the practice of landslide monitoring. Landslide is a phenomenon and disaster triggered by natural and artificial reasons that a part of slope comprised of rock, soil and other fragmental materials slide alone a certain weak structural surface under the gravitation. Consequently, according to the geo-science principle of landslide, there is an obvious change in the sliding region between the pre-landslide and post-landslide, and it can be described in remote sensing imagery, so we develop the new approach to identify landslides, which uses change detection based on texture analysis in multi-temporal imageries. Preprocessing the remote sensing data including the following aspects of image enhancement and filtering, smoothing and cutting, image mosaics, registration and merge, geometric correction and radiation calibration, this paper does change detection base on texture characteristics in multi-temporal images to recognize landslide automatically. After change detection of multi-temporal remote sensing images based on texture analysis, if there is no change in remote sensing image, the image detected is relatively homogeneous, the image detected shows some clustering characteristics; if there is part change in image, the image detected will show two or more clustering centers; if there is complete change in remote sensing image, the image detected will show disorderly and unsystematic. At last, this

  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. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. 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. PMID:23685191

  11. 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

  12. 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.

  13. Detecting Changes in Terrain Using Unmanned Aerial Vehicles

    NASA Technical Reports Server (NTRS)

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

    2005-01-01

    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.

  14. 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.

  15. A change detection approach to moving object detection in low fame-rate video

    NASA Astrophysics Data System (ADS)

    Porter, Reid; Harvey, Neal; Theiler, James

    2009-05-01

    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 pixellevel 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 lowframe rate (1-2 frames per second) video datasets.

  16. 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.

  17. 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.

  18. 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…

  19. 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...

  20. 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.

  1. Detection of nanoscale structural changes in bone using random lasers

    PubMed Central

    Song, Qinghai; Xu, Zhengbin; Choi, Seung Ho; Sun, Xuanhao; Xiao, Shumin; Akkus, Ozan; Kim, Young L.

    2010-01-01

    We demonstrate that the unique characteristics of random lasing in bone can be used to assess nanoscale structural alterations as a mechanical or structural biosensor, given that bone is a partially disordered biological nanostructure. In this proof-of-concept study, we conduct photoluminescence experiments on cortical bone specimens that are loaded in tension under mechanical testing. The ultra-high sensitivity, the large detection area, and the simple detection scheme of random lasers allow us to detect prefailure damage in bone at very small strains before any microscale damage occurs. Random laser-based biosensors could potentially open a new possibility for highly sensitive detection of nanoscale structural and mechanical alterations prior to overt microscale changes in hard tissue and biomaterials. PMID:21258558

  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. PMID:25476385

  3. 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.

  4. Effects of Disease Detection on Changes in Smoking Behavior

    PubMed Central

    Kwon, Jeoung A; Jeon, Wooman; Park, Eun-Cheol; Kim, Jae-Hyun; Kim, Sun Jung; Yoo, Ki-Bong; Lee, Minjee

    2015-01-01

    Purpose This study was conducted to investigate the effect that detection of chronic disease via health screening programs has on health behaviors, particularly smoking. Materials and Methods We analyzed national health insurance data from 2007 and 2009. Subjects who were 40 years of age in 2007 and eligible for the life cycle-based national health screening program were included. The total study population comprised 153518 individuals who participated in the screening program in 2007 and follow-up screening in 2009. Multiple logistic regression analyses were conducted by sex, with adjustment for health insurance type, socioeconomic status, body mass index, diabetes, hypertension, hyperlipidemia, and family history of cardiovascular and/or neurovascular disease. Results Among men with smoking behavior changes, those newly diagnosed with hyperlipidemia were more likely to show a positive health behavior change, such as smoking cessation, and were less likely to have a negative behavior change (e.g., smoking initiation). Additionally, men newly diagnosed with diabetes showed lower rates of negative health behavior changes compared to those without disease. Body mass index (BMI)≥25, compared to BMI<23, showed higher rates of positive health behavior changes and lower rates of negative health behavior changes. Newly diagnosed chronic disease did not influence smoking behavior in women. Conclusion Smoking behavior changes were only detected in men who participated in health screening programs. In particular, those newly diagnosed with hyperlipidemia were more likely to stop smoking and less likely to start smoking. PMID:26069141

  5. 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.

  6. Detecting Abrupt Changes in a Piecewise Locally Stationary Time Series

    PubMed Central

    Last, Michael; Shumway, Robert

    2007-01-01

    Non-stationary time series arise in many settings, such as seismology, speech-processing, and finance. In many of these settings we are interested in points where a model of local stationarity is violated. We consider the problem of how to detect these change-points, which we identify by finding sharp changes in the time-varying power spectrum. Several different methods are considered, and we find that the symmetrized Kullback-Leibler information discrimination performs best in simulation studies. We derive asymptotic normality of our test statistic, and consistency of estimated change-point locations. We then demonstrate the technique on the problem of detecting arrival phases in earthquakes. PMID:19190715

  7. Use of an Infrared Thermometer with Laser Targeting in Morphological Scene Change Detection for Fire Detection

    NASA Astrophysics Data System (ADS)

    Tickle, Andrew J.; Singh, Harjap; Grindley, Josef E.

    2013-06-01

    Morphological Scene Change Detection (MSCD) is a process typically tasked at detecting relevant changes in a guarded environment for security applications. This can be implemented on a Field Programmable Gate Array (FPGA) by a combination of binary differences based around exclusive-OR (XOR) gates, mathematical morphology and a crucial threshold setting. This is a robust technique and can be applied many areas from leak detection to movement tracking, and further augmented to perform additional functions such as watermarking and facial detection. Fire is a severe problem, and in areas where traditional fire alarm systems are not installed or feasible, it may not be detected until it is too late. Shown here is a way of adapting the traditional Morphological Scene Change Detector (MSCD) with a temperature sensor so if both the temperature sensor and scene change detector are triggered, there is a high likelihood of fire present. Such a system would allow integration into autonomous mobile robots so that not only security patrols could be undertaken, but also fire detection.

  8. 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

  9. 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.

  10. 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

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

    USGS Publications Warehouse

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

    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.

  12. 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.

  13. Accurate blackbodies

    NASA Astrophysics Data System (ADS)

    Latvakoski, Harri M.; Watson, Mike; Topham, Shane; Scott, Deron; Wojcik, Mike; Bingham, Gail

    2010-07-01

    Infrared radiometers and spectrometers generally use blackbodies for calibration, and with the high accuracy needs of upcoming missions, blackbodies capable of meeting strict accuracy requirements are needed. One such mission, the NASA climate science mission Climate Absolute Radiance and Refractivity Observatory (CLARREO), which will measure Earth's emitted spectral radiance from orbit, has an absolute accuracy requirement of 0.1 K (3σ) at 220 K over most of the thermal infrared. Space Dynamics Laboratory (SDL) has a blackbody design capable of meeting strict modern accuracy requirements. This design is relatively simple to build, was developed for use on the ground or onorbit, and is readily scalable for aperture size and required performance. These-high accuracy blackbodies are currently in use as a ground calibration unit and with a high-altitude balloon instrument. SDL is currently building a prototype blackbody to demonstrate the ability to achieve very high accuracy, and we expect it to have emissivity of ~0.9999 from 1.5 to 50 μm, temperature uncertainties of ~25 mK, and radiance uncertainties of ~10 mK due to temperature gradients. The high emissivity and low thermal gradient uncertainties are achieved through cavity design, while the low temperature uncertainty is attained by including phase change materials such as mercury, gallium, and water in the blackbody. Blackbody temperature sensors are calibrated at the melt points of these materials, which are determined by heating through their melt point. This allows absolute temperature calibration traceable to the SI temperature scale.

  14. 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).

  15. 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

  16. 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

  17. A speaker change detection method based on coarse searching

    NASA Astrophysics Data System (ADS)

    Zhang, Xue-yuan; He, Qian-hua; Li, Yan-xiong; He, Jun

    2013-03-01

    The conventional speaker change detection (SCD) method using Bayesian Information Criterion (BIC) has been widely used. However, its performance relies on the choice of penalty factor and suffers from mass calculation. The twostep SCD is less time consuming but generates more detection errors. The limitation of conventional method's performance originates from the two adjacent data windows. We propose a strategy that inserts an interval between the two adjacent fixed-size data windows in each analysis window. The dissimilarity value between the data windows is regarded as the probability of a speaker identity change within the interval area. Then this analysis window is slid along the audio by a large step to locate the areas where speaker change points may appear. Afterwards we only focus on these areas and locate precisely where the change points are. Other areas where a speaker change point unlikely appears are abandoned. The proposed method is computationally efficient and more robust to noise and penalty factor compared with conventional method. Evaluated on the corpus of China Central Television (CCTV) news, the proposed method obtains 74.18% reduction in calculation time and 22.24% improvement in F1-measure compared with the conventional approach.

  18. 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.

  19. 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.

  20. Network for the detection of stratospheric change (NDSC)

    NASA Technical Reports Server (NTRS)

    Kurylo, Michael J.

    1991-01-01

    The notion of a ground-based long-term measuring network specifically designed to provide the earliest possible detection of changes in the composition and structure of the stratosphere and to understand the causes of those changes is examined. The network's short-term goals are: to study the temporal and spatial variability of atmospheric composition and structure; to provide the basis for ground truth and complementary measurements for satellite systems such as the NASA Upper Atmosphere Research Satellite; and to critically test multidimensional stratospheric models and provide the broad data base required for improved model development. Priorities, instrumentation, station considerations, and site requirements are also discussed.

  1. 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.

  2. Visual analysis for live LIDAR battlefield change detection

    NASA Astrophysics Data System (ADS)

    Butkiewicz, Thomas; Chang, Remco; Wartell, Zachary; Ribarsky, William

    2008-04-01

    We present the framework for a battlefield change detection system that allows military analysts to coordinate and utilize live collection of airborne LIDAR range data in a highly interactive visual interface. The system consists of three major components: The adaptive and self-maintaining model of the battlefield selectively incorporates the minority of new data it deems significant, while discarding the redundant majority. The interactive interface presents the analyst with only the minute portion of the data the system deems relevant, provides tools to facilitate the decision making process, and adjusts its behavior to reflect the analyst's objectives. Finally, the cycle is completed by the generation of a goal map for the LIDAR collection hardware that instructs as to which areas should be sampled next in order to best advance the change detection task. All together, the system empowers analysts with the ability to make sense of a deluge of measurements by extracting the salient features and continually refining its definitions of relevancy.

  3. 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.

  4. Stepping inside the niche: microclimate data are critical for accurate assessment of species' vulnerability to climate change.

    PubMed

    Storlie, Collin; Merino-Viteri, Andres; Phillips, Ben; VanDerWal, Jeremy; Welbergen, Justin; Williams, Stephen

    2014-09-01

    To assess a species' vulnerability to climate change, we commonly use mapped environmental data that are coarsely resolved in time and space. Coarsely resolved temperature data are typically inaccurate at predicting temperatures in microhabitats used by an organism and may also exhibit spatial bias in topographically complex areas. One consequence of these inaccuracies is that coarsely resolved layers may predict thermal regimes at a site that exceed species' known thermal limits. In this study, we use statistical downscaling to account for environmental factors and develop high-resolution estimates of daily maximum temperatures for a 36 000 km(2) study area over a 38-year period. We then demonstrate that this statistical downscaling provides temperature estimates that consistently place focal species within their fundamental thermal niche, whereas coarsely resolved layers do not. Our results highlight the need for incorporation of fine-scale weather data into species' vulnerability analyses and demonstrate that a statistical downscaling approach can yield biologically relevant estimates of thermal regimes. PMID:25252835

  5. Stepping inside the niche: microclimate data are critical for accurate assessment of species' vulnerability to climate change

    PubMed Central

    Storlie, Collin; Merino-Viteri, Andres; Phillips, Ben; VanDerWal, Jeremy; Welbergen, Justin; Williams, Stephen

    2014-01-01

    To assess a species' vulnerability to climate change, we commonly use mapped environmental data that are coarsely resolved in time and space. Coarsely resolved temperature data are typically inaccurate at predicting temperatures in microhabitats used by an organism and may also exhibit spatial bias in topographically complex areas. One consequence of these inaccuracies is that coarsely resolved layers may predict thermal regimes at a site that exceed species' known thermal limits. In this study, we use statistical downscaling to account for environmental factors and develop high-resolution estimates of daily maximum temperatures for a 36 000 km2 study area over a 38-year period. We then demonstrate that this statistical downscaling provides temperature estimates that consistently place focal species within their fundamental thermal niche, whereas coarsely resolved layers do not. Our results highlight the need for incorporation of fine-scale weather data into species' vulnerability analyses and demonstrate that a statistical downscaling approach can yield biologically relevant estimates of thermal regimes. PMID:25252835

  6. 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

  7. Neural correlates of auditory sensory memory and automatic change detection.

    PubMed

    Sabri, Merav; Kareken, David A; Dzemidzic, Mario; Lowe, Mark J; Melara, Robert D

    2004-01-01

    An auditory event-related potential component, the mismatch negativity (MMN), reflects automatic change detection and its prerequisite, sensory memory. This study examined the neural correlates of automatic change detection using BOLD fMRI and two rates of presentation previously shown to induce either a large or no MMN. A boxcar block design was employed in two functional scans, each performed twice. A block consisting of 1000-Hz standards (S) alternated with one consisting of 1000-Hz standards and 2000-Hz infrequent deviants (S + D). Presentation rate was either 150 or 2400 ms. Fourteen participants were instructed to ignore all auditory stimulation and concentrate on a film (no audio) by reading subtitles. Data analysis used SPM99 and random effects approach. Cluster statistics (P < 0.05, corrected) were employed at a height threshold of P < 0.001. At the short ISI, there was a significant BOLD response in the right superior temporal gyrus (STG), the left insula, and the left STG (including parts of primary auditory cortex). There were no suprathreshold clusters at the long rate, with S + D blocks inducing no greater activity than S blocks. These results support the hypothesis that the automatic detection of auditory change occurs in the STG bilaterally and relies on the maintenance of sensory memory traces. PMID:14741643

  8. An unsupervised support vector method for change detection

    NASA Astrophysics Data System (ADS)

    Bovolo, F.; Camps-Valls, G.; Bruzzone, L.

    2007-10-01

    This paper formulates the problem of distinguishing changed from unchanged pixels in remote sensing images as a minimum enclosing ball (MEB) problem with changed pixels as target class. The definition of the sphere shaped decision boundary with minimal volume that embraces changed pixels is approached in the context the support vector formalism adopting a support vector domain description (SVDD) one-class classifier. The SVDD maps the data into a high dimensional feature space where the spherical support of the high dimensional distribution of changed pixels is computed. The proposed formulation of the SVDD uses both target and outlier samples for defining the MEB, and is included here in an unsupervised system for change detection. For this purpose, nearly certain examples for the classes of both targets (i.e., changed pixels) and outliers (i.e., unchanged pixels) for training are identified based on thresholding the magnitude of spectral change vectors. Experimental results obtained on two different multitemporal and multispectral remote sensing images pointed out the effectiveness of the proposed method.

  9. 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.

  10. A microcalorimeter used to detect changes in aged energetic materials

    SciTech Connect

    Wiedenheft, C.J.; Rodenburg, W.W.; Shockey, G.C.

    1987-01-01

    To ensure the quality of chemical explosives, analytical tests are performed on the materials. One of the most fundamental measurements is that of heat released during an exothermic reaction. Because only small amounts, less than 20 mg, of explosive material can be removed from most weapons, special techniques and instruments must be used to measure a heat output of a few tens of calories. The calorimeter described in this report consists of a sample side and a reference side placed in a constant temperature bath. The calorimeter and sample are heated by passing the current from a bank of capacitors through a heating wire. In order to measure the temperature change, the resistance of Ni wire is measured. The unit was calibrated and found to be accurate for reactions with greater than 5 calories of heat output. (JDH)

  11. 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

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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``.

  18. 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.

  19. 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. PMID:1792140

  20. 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.

  1. 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.

  2. 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).

  3. Does facial processing prioritize change detection?: change blindness illustrates costs and benefits of holistic processing.

    PubMed

    Wilford, Miko M; Wells, Gary L

    2010-11-01

    There is broad consensus among researchers both that faces are processed more holistically than other objects and that this type of processing is beneficial. We predicted that holistic processing of faces also involves a cost, namely, a diminished ability to localize change. This study (N = 150) utilized a modified change-blindness paradigm in which some trials involved a change in one feature of an image (nose, chin, mouth, hair, or eyes for faces; chimney, porch, window, roof, or door for houses), whereas other trials involved no change. People were better able to detect the occurrence of a change for faces than for houses, but were better able to localize which feature had changed for houses than for faces. Half the trials used inverted images, a manipulation that disrupts holistic processing. With inverted images, the critical interaction between image type (faces vs. houses) and task (change detection vs. change localization) disappeared. The results suggest that holistic processing reduces change-localization abilities. PMID:20935169

  4. 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

  5. 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.

  6. 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

  7. Anomalies in the detection of change: When changes in sample size are mistaken for changes in proportions.

    PubMed

    Fiedler, Klaus; Kareev, Yaakov; Avrahami, Judith; Beier, Susanne; Kutzner, Florian; Hütter, Mandy

    2016-01-01

    Detecting changes, in performance, sales, markets, risks, social relations, or public opinions, constitutes an important adaptive function. In a sequential paradigm devised to investigate detection of change, every trial provides a sample of binary outcomes (e.g., correct vs. incorrect student responses). Participants have to decide whether the proportion of a focal feature (e.g., correct responses) in the population from which the sample is drawn has decreased, remained constant, or increased. Strong and persistent anomalies in change detection arise when changes in proportional quantities vary orthogonally to changes in absolute sample size. Proportional increases are readily detected and nonchanges are erroneously perceived as increases when absolute sample size increases. Conversely, decreasing sample size facilitates the correct detection of proportional decreases and the erroneous perception of nonchanges as decreases. These anomalies are however confined to experienced samples of elementary raw events from which proportions have to be inferred inductively. They disappear when sample proportions are described as percentages in a normalized probability format. To explain these challenging findings, it is essential to understand the inductive-learning constraints imposed on decisions from experience. PMID:26179055

  8. 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. PMID:25301567

  9. 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. PMID:24636881

  10. 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.

  11. Trend Analysis and Detection of Changes in the Stratospheric Circulation

    NASA Technical Reports Server (NTRS)

    Oman, Luke; Douglass, A. R.; Rodriquez, J. M.; Stolarski, R. S.; Waugh, D. W.

    2010-01-01

    Increases in the circulation of the stratosphere appear to be a robust result of climate change in chemistry-climate models over decadal time scales. To date observations have yet to show a significant change in this circulation. It is important for the design of future observational missions to identify suitable atmospheric constituents and to determine the accuracy and length of record needed to identify a significant trend that can be attributed to circulation change. First, we determine what atmospheric variables can be used as proxies for stratospheric circulation changes. A few examples are changes in tropical lower stratospheric ozone, phase lag of the water vapor tape recorder, CO2, and SF6. Then, using both the Goddard Earth Observing System Chemistry-Climate Model (GEOS CCM) and observations from satellites and balloon soundings, we calculate the number of years needed to detect a significant trend, taking into account observational uncertainty. Model simulations will be evaluated to see how well they represent observed variability. In addition, the impacts of autocorrelation among the output or data and gaps in the observational record will be discussed.

  12. Automated Detection of Changes on the Lunar Surface

    NASA Astrophysics Data System (ADS)

    Cook, A.; Gibbens, M.

    2005-08-01

    Although the Moon is considered to be geologically dormant, surface altering events visible to orbiting spacecraft must still occur, albeit infrequently e.g. fresh impact craters detected from Apollo imagery. Given a surface area of 3.8E7 km2 and the 40 year time frame spanning Lunar Orbiter to SMART-1 missions, it is likely that 10's-100's of surface changes measurable in the > 50m scale range may be detected by automatically comparing temporal images of the same areas under similar (< 5 deg difference) incidence and emission angles. Automated tie-pointing and image footprint overlap detection developed from Clementine stereo research can be used to select suitable overlapping temporal image pairs of a given area. These can then be automatically registered/warped together, photometrically calibrated to each other and subtracted to leave a difference image. Differences that exceed 3 standard deviations across the image can then be compared to the most recent mosaics of optical maturity in order to confirm whether a suspected area of change is aligned with fresh non-spaceweathered parts of the surface. Knowledge that could be gained from such a study could include: 1) confirmation of cratering rate assumptions that were made from the Apollo ALSEP seismometers, 2) identification of surface disturbances by ejecta from impacts detected by Apollo seismometer, or Earth based telescopic impact flash observations; these can then be used to help relate estimated impact energy to crater size, 3) the areal extent of dust transport from impact ejecta, landslides, or other suspected mechanisms such as residual outgassing or electrostaic levitation of dust. All three of these have important implications for future surface based exploration in identifying sites of interest that can be either monitored over time to study the progression of space weathering, or for studying freshly excavated underlying geology.

  13. Detection of building changes from aerial images and light detection and ranging (LIDAR) data

    NASA Astrophysics Data System (ADS)

    Chen, Liang-Chien; Lin, Li-Jer

    2010-11-01

    Building models are built to provide three-dimensional (3-D) spatial information, which is needed in a variety of applications including city planning, construction management, location-based services of urban infrastructures, and the like. However, 3-D building models have to be updated on a timely manner to meet the changing demand. Rather than reconstructing building models for the entire area, it would be more convenient and effective to only update parts of the areas where there were changes. This paper aims at developing a new method, namely double-threshold strategy, to find such changes within 3-D building models in the region of interest with the aid of light detection and ranging (LIDAR) data. The proposed modeling scheme comprises three steps, namely, data pre-processing, change detection in building areas, and validation. In the first step for data pre-processing, data registration was carried out based on multi-source data. The second step for data pre-processing requires using the triangulation of an irregular network of data points collected by Light Detection And Ranging (LIDAR), focusing on those locations containing walls or other above-ground objects that were ever removed. Then, change detection in the building models can be made possible for finding differences in height by comparing the LIDAR point measurements and the estimates of the building models. The results may be further refined using spectral and feature information collected from aerial imagery. A double-threshold strategy was applied to cope with the highly sensitive thresholding often encountered when using the rule-based approach. Finally, ground truth data were used for model validation. Research findings clearly indicate that the double-threshold strategy improves the overall accuracy from 93.1% to 95.9%.

  14. 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

  15. 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.

  16. 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.

  17. Urban area change detection procedures with remote sensing data

    NASA Technical Reports Server (NTRS)

    Maxwell, E. L. (Principal Investigator); Riordan, C. J.

    1980-01-01

    The underlying factors affecting the detection and identification of nonurban to urban land cover change using satellite data were studied. Computer programs were developed to create a digital scene and to simulate the effect of the sensor point spread function (PSF) on the transfer of modulation from the scene to an image of the scene. The theory behind the development of a digital filter representing the PSF is given as well as an example of its application. Atmospheric effects on modulation transfer are also discussed. A user's guide and program listings are given.

  18. 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.

  19. 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.

  20. Performance of a Micro-Strip Gas Chamber for event wise, high rate thermal neutron detection with accurate 2D position determination

    NASA Astrophysics Data System (ADS)

    Mindur, B.; Alimov, S.; Fiutowski, T.; Schulz, C.; Wilpert, T.

    2014-12-01

    A two-dimensional (2D) position sensitive detector for neutron scattering applications based on low-pressure gas amplification and micro-strip technology was built and tested with an innovative readout electronics and data acquisition system. This detector contains a thin solid neutron converter and was developed for time- and thus wavelength-resolved neutron detection in single-event counting mode, which improves the image contrast in comparison with integrating detectors. The prototype detector of a Micro-Strip Gas Chamber (MSGC) was built with a solid natGd/CsI thermal neutron converter for spatial resolutions of about 100 μm and counting rates up to 107 neutrons/s. For attaining very high spatial resolutions and counting rates via micro-strip readout with centre-of-gravity evaluation of the signal amplitude distributions, a fast, channel-wise, self-triggering ASIC was developed. The front-end chips (MSGCROCs), which are very first signal processing components, are read out into powerful ADC-FPGA boards for on-line data processing and thereafter via Gigabit Ethernet link into the data receiving PC. The workstation PC is controlled by a modular, high performance dedicated software suite. Such a fast and accurate system is crucial for efficient radiography/tomography, diffraction or imaging applications based on high flux thermal neutron beam. In this paper a brief description of the detector concept with its operation principles, readout electronics requirements and design together with the signals processing stages performed in hardware and software are presented. In more detail the neutron test beam conditions and measurement results are reported. The focus of this paper is on the system integration, two dimensional spatial resolution, the time resolution of the readout system and the imaging capabilities of the overall setup. The detection efficiency of the detector prototype is estimated as well.

  1. Mean Polyp per Patient Is an Accurate and Readily Obtainable Surrogate for Adenoma Detection Rate: Results from an Opportunistic Screening Colonoscopy Program

    PubMed Central

    Delavari, Alireza; Salimzadeh, Hamideh; Bishehsari, Faraz; Sobh Rakhshankhah, Elham; Delavari, Farnaz; Moossavi, Shirin; Khosravi, Pejman; Nasseri-Moghaddam, Siavosh; Merat, Shahin; Ansari, Reza; Vahedi, Homayoon; Shahbazkhani, Bijan; Saberifiroozi, Mehdi; Sotoudeh, Masoud; Malekzadeh, Reza

    2015-01-01

    BACKGROUND The incidence of colorectal cancer is rising in several developing countries. In the absence of integrated endoscopy and pathology databases, adenoma detection rate (ADR), as a validated quality indicator of screening colonoscopy, is generally difficult to obtain in practice. We aimed to measure the correlation of polyp-related indicators with ADR in order to identify the most accurate surrogate(s) of ADR in routine practice. METHODS We retrospectively reviewed the endoscopic and histopathological findings of patients who underwent colonoscopy at a tertiary gastrointestinal clinic. The overall ADR and advanced-ADR were calculated using patient-level data. The Pearson’s correlation coefficient (r) was applied to measure the strength of the correlation between the quality metrics obtained by endoscopists. RESULTS A total of 713 asymptomatic adults aged 50 and older who underwent their first-time screening colonoscopy were included in this study. The ADR and advanced-ADR were 33.00% (95% CI: 29.52-36.54) and 13.18% (95% CI: 10.79-15.90), respectively. We observed good correlations between polyp detection rate (PDR) and ADR (r=0.93), and mean number of polyp per patient (MPP) and ADR (r=0.88) throughout the colon. There was a positive, yet insignificant correlation between advanced ADRs and non-advanced ADRs (r=0.42, p=0.35). CONCLUSION MPP is strongly correlated with ADR, and can be considered as a reliable and readily obtainable proxy for ADR in opportunistic screening colonoscopy programs. PMID:26609349

  2. Detecting abrupt climate changes on different time scales

    NASA Astrophysics Data System (ADS)

    Matyasovszky, István

    2011-10-01

    Two concepts are introduced for detecting abrupt climate changes. In the first case, the sampling frequency of climate data is high as compared to the frequency of climate events examined. The method is based on a separation of trend and noise in the data and is applicable to any dataset that satisfies some mild smoothness and statistical dependence conditions for the trend and the noise, respectively. We say that an abrupt change occurs when the first derivative of the trend function has a discontinuity and the task is to identify such points. The technique is applied to Northern Hemisphere temperature data from 1850 to 2009, Northern Hemisphere temperature data from proxy data, a.d. 200-1995 and Holocene δ18O values going back to 11,700 years BP. Several abrupt changes are detected that are, among other things, beneficial for determining the Medieval Warm Period, Little Ice Age and Holocene Climate Optimum. In the second case, the sampling frequency is low relative to the frequency of climate events studied. A typical example includes Dansgaard-Oeschger events. The methodology used here is based on a refinement of autoregressive conditional heteroscedastic models. The key element of this approach is the volatility that characterises the time-varying variance, and abrupt changes are defined by high volatilities. The technique applied to δ18O values going back to 122,950 years BP is suitable for identifying DO events. These two approaches for the two cases are closely related despite the fact that at first glance, they seem quite different.

  3. Change detection in remote sensing images using modified polynomial regression and spatial multivariate alteration detection

    NASA Astrophysics Data System (ADS)

    Dianat, Rouhollah; Kasaei, Shohreh

    2009-11-01

    A new and efficient method for incorporating the spatiality into difference-based change detection (CD) algorithms is introduced in this paper. It uses the spatial derivatives of image pixels to extract spatial relations among them. Based on this methodology, the performances of two famous difference-based CD methods, conventional polynomial regression (CPR) and multivariate alteration detection (MAD), are improved and called modified polynomial regression (MPR) and spatial multivariate alteration detection (SMAD), respectively. Various quantitative and qualitative evaluations have shown the superiority of MPR over CPR and SMAD over MAD. Also, the superiority of SMAD over all mentioned CD algorithms is shown. Moreover, it has been proved that both proposed methods enjoy the affine invariance property.

  4. 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.

  5. Change in ST segment elevation 60 minutes after thrombolytic initiation predicts clinical outcome as accurately as later electrocardiographic changes

    PubMed Central

    Purcell, I; Newall, N; Farrer, M

    1997-01-01

    Objective—To compare prospectively the prognostic accuracy of a 50% decrease in ST segment elevation on standard 12-lead electrocardiograms (ECGs) recorded at 60, 90, and 180 minutes after thrombolysis initiation in acute myocardial infarction.
Design—Consecutive sample prospective cohort study.
Setting—A single coronary care unit in the north of England.
Patients—190 consecutive patients receiving thrombolysis for first acute myocardial infarction.
Interventions—Thrombolysis at baseline.
Main outcome measures—Cardiac mortality and left ventricular size and function assessed 36 days later.
Results—Failure of ST segment elevation to resolve by 50% in the single lead of maximum ST elevation or the sum ST elevation of all infarct related ECG leads at each of the times studied was associated with a significantly higher mortality, larger left ventricular volume, and lower ejection fraction. There was some variation according to infarct site with only the 60 minute ECG predicting mortality after inferior myocardial infarction and only in anterior myocardial infarction was persistent ST elevation associated with worse left ventricular function. The analysis of the lead of maximum ST elevation at 60 minutes from thrombolysis performed as well as later ECGs in receiver operating characteristic curves for predicting clinical outcome.
Conclusion—The standard 12-lead ECG at 60 minutes predicts clinical outcome as accurately as later ECGs after thrombolysis for first acute myocardial infarction.

 Keywords: myocardial infarction;  thrombolysis;  ST segment elevation PMID:9415005

  6. 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.

  7. 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.

  8. Blind phone segmentation based on spectral change detection using Legendre polynomial approximation.

    PubMed

    Hoang, Dac-Thang; Wang, Hsiao-Chuan

    2015-02-01

    Phone segmentation involves partitioning a continuous speech signal into discrete phone units. In this paper, a method for automatic phone segmentation without prior knowledge of speech content is proposed. The signal spectrum was represented by band-energies. A segment of the band-energy curve was approximated using Legendre polynomial expansion, allowing Legendre polynomial coefficients to describe the properties of the segment. The spectral changes, which imply phone boundaries in the speech signal, were then detected by monitoring the variations of Legendre polynomial coefficients. A two-step algorithm for detecting phone boundaries was derived. The first step was to detect phone boundaries using first-order and second-order coefficients of the Legendre polynomial approximation. The second step was to locate slow spectral changes in the regions of concatenated voiced phones using zero-order coefficients of the Legendre polynomial approximation. This enabled the phone boundaries missed during the first step to be recovered. An evaluation using the TIMIT corpus indicated that the proposed method is comparable to or more accurate than previous methods. PMID:25698014

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. 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.

  14. QuantiSNP: an Objective Bayes Hidden-Markov Model to detect and accurately map copy number variation using SNP genotyping data.

    PubMed

    Colella, Stefano; Yau, Christopher; Taylor, Jennifer M; Mirza, Ghazala; Butler, Helen; Clouston, Penny; Bassett, Anne S; Seller, Anneke; Holmes, Christopher C; Ragoussis, Jiannis

    2007-01-01

    Array-based technologies have been used to detect chromosomal copy number changes (aneuploidies) in the human genome. Recent studies identified numerous copy number variants (CNV) and some are common polymorphisms that may contribute to disease susceptibility. We developed, and experimentally validated, a novel computational framework (QuantiSNP) for detecting regions of copy number variation from BeadArray SNP genotyping data using an Objective Bayes Hidden-Markov Model (OB-HMM). Objective Bayes measures are used to set certain hyperparameters in the priors using a novel re-sampling framework to calibrate the model to a fixed Type I (false positive) error rate. Other parameters are set via maximum marginal likelihood to prior training data of known structure. QuantiSNP provides probabilistic quantification of state classifications and significantly improves the accuracy of segmental aneuploidy identification and mapping, relative to existing analytical tools (Beadstudio, Illumina), as demonstrated by validation of breakpoint boundaries. QuantiSNP identified both novel and validated CNVs. QuantiSNP was developed using BeadArray SNP data but it can be adapted to other platforms and we believe that the OB-HMM framework has widespread applicability in genomic research. In conclusion, QuantiSNP is a novel algorithm for high-resolution CNV/aneuploidy detection with application to clinical genetics, cancer and disease association studies. PMID:17341461

  15. 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.

  16. 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.

  17. [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

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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

  6. 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.

  7. Image animation for theme enhancement and change detection. [LANDSAT 1

    NASA Technical Reports Server (NTRS)

    Evans, W. E.

    1976-01-01

    Animated displays are useful in enhancing subtle temporally related changes in scenes viewed by satellites capable of providing repetitive coverage. The detectability of fixed features is also improved through the help of the powerful visual integration process. To expedite the process of assembling and displaying well-registered, time-lapse sequences and to provide means for making quantitative measurements of radiances, displacements, and areas, an electronic satellite image analysis console was constructed. During the LANDSAT-1 program, this equipment was applied to the needs of a number of earth resource investigators with interests principally related to dynamic hydrology. The measurement of the areal extent of snow cover within defined drainage basins is discussed as a representative applications example.

  8. 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

  9. 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...

  10. 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.

  11. 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.

  12. An ensemble classification approach for improved Land use/cover change detection

    NASA Astrophysics Data System (ADS)

    Chellasamy, M.; Ferré, T. P. A.; Humlekrog Greve, M.; Larsen, R.; Chinnasamy, U.

    2014-11-01

    Change Detection (CD) methods based on post-classification comparison approaches are claimed to provide potentially reliable results. They are considered to be most obvious quantitative method in the analysis of Land Use Land Cover (LULC) changes which provides from - to change information. But, the performance of post-classification comparison approaches highly depends on the accuracy of classification of individual images used for comparison. Hence, we present a classification approach that produce accurate classified results which aids to obtain improved change detection results. Machine learning is a part of broader framework in change detection, where neural networks have drawn much attention. Neural network algorithms adaptively estimate continuous functions from input data without mathematical representation of output dependence on input. A common practice for classification is to use Multi-Layer-Perceptron (MLP) neural network with backpropogation learning algorithm for prediction. To increase the ability of learning and prediction, multiple inputs (spectral, texture, topography, and multi-temporal information) are generally stacked to incorporate diversity of information. On the other hand literatures claims backpropagation algorithm to exhibit weak and unstable learning in use of multiple inputs, while dealing with complex datasets characterized by mixed uncertainty levels. To address the problem of learning complex information, we propose an ensemble classification technique that incorporates multiple inputs for classification unlike traditional stacking of multiple input data. In this paper, we present an Endorsement Theory based ensemble classification that integrates multiple information, in terms of prediction probabilities, to produce final classification results. Three different input datasets are used in this study: spectral, texture and indices, from SPOT-4 multispectral imagery captured on 1998 and 2003. Each SPOT image is classified

  13. 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

  14. 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.

  15. The Effect of Concurrent Music Reading and Performance on the Ability to Detect Tempo Change.

    ERIC Educational Resources Information Center

    Ellis, Mark Carlton

    1989-01-01

    Measures the ability of three groups of musicians to detect tempo change while reading and performing music. Compares this ability with that of the same musicians to detect tempo change while listening only. Found that for all groups the ability to detect tempo changes was inhibited by the playing task, although to different degrees for each…

  16. 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

  17. 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).

  18. Detection of 15NNH+ in L1544: non-LTE modelling of dyazenilium hyperfine line emission and accurate 14N/15N values

    NASA Astrophysics Data System (ADS)

    Bizzocchi, L.; Caselli, P.; Leonardo, E.; Dore, L.

    2013-07-01

    Context. Samples of pristine solar system material found in meteorites and interplanetary dust particles are highly enriched in 15N. Conspicuous nitrogen isotopic anomalies have also been measured in comets, and the 14N/15N abundance ratio of the Earth is itself higher than the recognised presolar value by almost a factor of two. Low-temperature ion/molecule reactions in the proto-solar nebula have been repeatedly indicated as being responsible for these 15N-enhancements. Aims: We have searched for 15N variants of the N2H+ ion in L1544, a prototypical starless cloud core that is one of the best candidate sources for detection owing to its low central core temperature and high CO depletion. The goal is to evaluate accurate and reliable 14N/15N ratio values for this species in the interstellar gas. Methods: A deep integration of the 15NNH+(1-0) line at 90.4 GHz was obtained with the IRAM 30 m telescope. Non-LTE radiative transfer modelling was performed on the J = 1-0 emissions of the parent and 15N-containing dyazenilium ions, using a Bonnor-Ebert sphere as a model for the source. Results: A high-quality fit of the N2H+(1-0) hyperfine spectrum has allowed us to derive a revised value of the N2H+ column density in L1544. Analysis of the observed N15NH+ and 15NNH+ spectra yielded an abundance ratio N(N15NH+)/N(15NNH+) = 1.1 ± 0.3. The obtained 14N/15N isotopic ratio is ~1000 ± 200, suggestive of a sizeable 15N depletion in this molecular ion. Such a result is not consistent with the prediction of the current nitrogen chemical models. Conclusions: Since chemical models predict high 15N fractionation of N2H+, we suggest that 15N14N, or 15N in some other molecular form, tends to deplete onto dust grains. Based on observations carried out with the IRAM 30 m Telescope. IRAM is supported by INSU/CNRS (France), MPG (Germany) and IGN (Spain).Full Tables B.1-B.6 are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http

  19. 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.

  20. Satellite Observations for Detecting and Tracking Changes in Atmospheric Composition

    NASA Technical Reports Server (NTRS)

    Neil, Doreen O.; Kondragunbta, Shobha; Osterman, Gregory; Pickering, Kenneth; Pinder, Robert W.; Prados, Ana I.; Szykman, James

    2009-01-01

    The satellite observations provide constraints on detailed atmospheric modeling, including emissions inventories, indications of transport, harmonized data over vast areas suitable for trends analysis, and a link between spatial scales ranging from local to global, and temporal scales from diurnal to interannual. 1 The National Oceanic and Atmospheric Administration's (NOAA) long-term commitments help provide these observations in cooperation with international meteorological organizations. NASA s long-term commitments will advance scientifically important observations as part of its Earth Science Program, and will assist the transition of the science measurements to applied analyses through the Applied Science Program. Both NASA and NOAA have begun to provide near realtime data and tools to visualize and analyze satellite data,2 while maintaining data quality, validation, and standards. Consequently, decision-makers can expect satellite data services to support air quality decision making now and in the future. The international scientific community's Integrated Global Atmosphere Chemistry Observation System Report3 outlined a plan for ground-based, airborne and satellite measurements and models to integrate the observations into a four-dimensional representation of the atmosphere (space and time) to support assessment and policy information needs. This plan is being carried out under the Global Earth Observation System of Systems (GEOSS). Demonstrations of such an integrated capability4 provide new understanding of the changing atmosphere and link policy decisions to benefits for society. In this article, we highlight the use of satellite data to constrain biomass burning emissions, to assess oxides of nitrogen (NO(x)) emission reductions, and to contribute to state implementation plans, as examples of the use of satellite observations for detecting and tracking changes in atmospheric composition.

  1. 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.

  2. 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.

  3. 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.

  4. 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

  5. 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.

  6. 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.

  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. Detection and attribution of changes in flood probability

    NASA Astrophysics Data System (ADS)

    Merz, Bruno; Delgado, Jose; Hundecha, Yeshewa; Zimmer, Janek

    2010-05-01

    The frequency, magnitude and type of extreme hydrological events are expected to change with climate change. However, other influences, such as construction of reservoirs, river training or land cover change, additionally affect the flood behaviour. Based on flood time series of more than 150 catchments in Germany, we analyse spatial patterns of changes in frequency, magnitude and probabilities of floods across Germany. In particular, we study the changes in the variability (or scale parameter) versus the changes in the mean (or location parameter), and the sensitivity of flood probability to changes in these parameters. In order to differentiate between climate-induced change and land cover change, we investigate if changes at inter-annual, decadal and multidecadal time scales are regionally stable, and if these changes can be linked to climatic variables. For selected catchments, an attempt is made to relate changes in flood behaviour to human-induced interventions in the catchments and to climatic change. Regionally and seasonally coherent results point to the influence of climate on changing flood probabilities in Germany in the last decades.

  10. 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.

  11. 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

  12. A non-contact method based on multiple signal classification algorithm to reduce the measurement time for accurately heart rate detection.

    PubMed

    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. PMID:24007088

  13. 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.

  14. DETECTING LAND COVER CHANGE AT THE JORNADA EXPERIMENTAL RANGE, NEW MEXICO WITH ASTER EMISSIVITIES

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Detecting land cover change over semi-arid rangeland is important for monitoring vegetation responses to drought, population expansion, and changing agricultural practices. Such change can be detected using vegetation indices, but these do not represent non-green vegetation and are dominated by seas...

  15. 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 .

  16. 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. PMID:26245835

  17. 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. PMID:25282403

  18. Integration of Landsat TM and SPOT HRG Images for Vegetation Change Detection in the Brazilian Amazon

    PubMed Central

    Lu, Dengsheng; Batistella, Mateus; Moran, Emilio

    2009-01-01

    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. PMID:19789721

  19. 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.

  20. Detection limits of albedo changes induced by climate engineering

    NASA Astrophysics Data System (ADS)

    Seidel, Dian J.; Feingold, Graham; Jacobson, Andrew R.; Loeb, Norman

    2014-02-01

    A key question surrounding proposals for climate engineering by increasing Earth's reflection of sunlight is the feasibility of detecting engineered albedo increases from short-duration experiments or prolonged implementation of solar-radiation management. We show that satellite observations permit detection of large increases, but interannual variability overwhelms the maximum conceivable albedo increases for some schemes. Detection of an abrupt global average albedo increase <0.002 (comparable to a ~0.7 W m-2 reduction in radiative forcing) would be unlikely within a year, given a five-year prior record. A three-month experiment in the equatorial zone (5° N-5° S), a potential target for stratospheric aerosol injection, would need to cause an ~0.03 albedo increase, three times larger than that due to the Mount Pinatubo eruption, to be detected. Detection limits for three-month experiments in 1° (latitude and longitude) regions of the subtropical Pacific, possible targets for cloud brightening, are ~0.2 larger than might be expected from some model simulations.

  1. 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

  2. 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

  3. 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.

  4. 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…

  5. 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...

  6. 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.

  7. 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.

  8. 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 Central

    Chen, Qinghai; Wu, Nan; Xie, Meng; Zhang, Bo; Chen, Ming; Li, Jianjun; Zhuo, Lisha; Kuang, Hong; Fu, Weiling

    2012-01-01

    Summary 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. PMID:22460100

  9. 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.

  10. 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.

  11. Detection and attribution of global mean thermosteric sea level change

    NASA Astrophysics Data System (ADS)

    Slangen, Aimée. B. A.; Church, John A.; Zhang, Xuebin; Monselesan, Didier

    2014-08-01

    Changes in sea level are driven by a range of natural and anthropogenic forcings. To better understand the response of global mean thermosteric sea level change to these forcings, we compare three observational data sets to experiments of 28 climate models with up to five different forcing scenarios for 1957-2005. We use the preindustrial control runs to determine the internal climate variability. Our analysis shows that anthropogenic greenhouse gas and aerosol forcing are required to explain the magnitude of the observed changes, while natural forcing drives most of the externally forced variability. The experiments that include anthropogenic and natural forcings capture the observed increased trend toward the end of the twentieth century best. The observed changes can be explained by scaling the natural-only experiment by 0.70 ± 0.30 and the anthropogenic-only experiment (including opposing forcing from greenhouse gases and aerosols) by 1.08 ± 0.13(±2σ).

  12. Detection of seagrass distribution changes from 1991 to 2006 in xincun bay, hainan, with satellite remote sensing.

    PubMed

    Yang, Dingtian; Yang, Chaoyu

    2009-01-01

    Seagrass distribution is a very important index for costal management and protection. Seagrass distribution changes can be used as indexes to analyze the reasons for the changes. In this paper, in situ hyperspectral observation and satellite images of QuickBird, CBERS (China Brazil Earth Resources Satellite data) and Landsat data were used to retrieve bio-optical models and seagrass (Enhalus acoroides, Thalassia hemperichii) distribution in Xincun Bay, Hainan province, and seagrass distribution changes from 1991 to 2006 were analyzed. Hyperspectral results showed that the spectral bands at 555, 635, 650 and 675 nm are sensitive to leaf area index (LAI). Seagrass detection with QuickBird was more accurate than that with Landsat TM and CBERS; five classes could be classified clearly and used as correction for seagrass remote sensing data from Landsat TM and CBERS. In order to better describe seagrass distribution changes, the seagrass distribution area was divided as three regions: region A connected with region B in 1991, however it separated in 1999 and was wholly separated in 2001; seagrass in region C shrank gradually and could not be detected in 2006. Analysis of the reasons for seagrass reduction indicated it was mainly affected by aquaculture and typhoons and in recent years, by land use changes. PMID:22399941

  13. Attempt of volcanomagnetic change detection by repeated aeromagnetic survey aeromagnetic survey on Aso and Kuju volcano, central Kyushu Japan -

    NASA Astrophysics Data System (ADS)

    Utsugi, M.; Tanaka, Y.; Kagiyama, T.; Okubo, A.

    2006-12-01

    Recently, geomagnetic field observation is successfully applied to many active volcanos to detect the volcano- magnetic changes. These observations are usually based on the continuous or repeated observation stations setting on the ground near the active area. From these observations, we can obtain high accurate information about the temporal geomagnetic field changes. But we can obtain only limited information about the special distribution of field changes. To interpret the geomagnetic field changes to underground heat transfer, we have to know the special distribution of the geomagnetic changes. To obtain the detailed information about the spatial distribution, aeromagnetic survey is usually used. In our study, we tried to use this method to detect the volcanomagnetic change. The main problem of aeromagnetic repeated observation is the difficulty of the observation point control. In the two flights, it is impossible that quite the same place flies. So that, it is very difficult to separate a change according to the volcanic activity and a spatial change. But, if we know detailed 3-D distribution of geomagnetic field and we can estimate the field intensity on the arbitrary point, we can correct the spatial variation of the repeated aeromagnetic survey data caused by the difference of flight position, and it may be possible to detect the field changes associated with the volcanic activities. For this purpose, we made very high density and low altitude helicopter-borne aeromagnetic survey on Aso and Kuju volcano in July 2002 and Dec. 2004. Each observation was done by a different approach. On Aso volcano, an extremely high density aeromagnetic observation was carried out. The survey area was selected as NS1200 x EW1200 x 300m region above the Nakadake crater which is the most active area on Aso volcano. The flight was made in 8 heights. The total numbers of measurements were about 8200. Based on the equivalent anomaly method, which is usually used to calculate the

  14. Detecting Climate Change due to Increasing Carbon Dioxide.

    PubMed

    Madden, R A; Ramanathan, V

    1980-08-15

    The observed interannual variability of temperature at 60 degrees N has been investigated. The results indicate that the surface warming due to increased carbon dioxide which is predicted by three-dimensional climate models should be detectable now. It is not, possibly because the predicted warming is being delayed more than a decade by ocean thermal inertia, or because there is a compensating cooling due to other factors. Further consideration of the uncertainties in model predictions and of the likely delays introduced by ocean thermal inertia extends the range of time for the detection of warming, if it occurs, to the year 2000. The effects of increasing carbon dioxide should be looked for in several variables simultaneously in order to minimize the ambiguities that could result from unrecognized compensating cooling. PMID:17753291

  15. Deceiving Oneself about Being in Control: Conscious Detection of Changes in Visuomotor Coupling

    ERIC Educational Resources Information Center

    Knoblich, Gunther; Kircher, Tilo T. J.

    2004-01-01

    Previous research has demonstrated that compensatory movements for changes in visuomotor coupling often are not consciously detected. But what factors affect the conscious detection of such changes? This issue was addressed in 4 experiments. Participants carried out a drawing task in which the relative velocity between the actual movement and its…

  16. Shoreline Delineation and Land Reclamation Change Detection Using Landsat Image

    NASA Astrophysics Data System (ADS)

    Rosli, M. I.; Ahmad, M. A.; Kaamin, M.; Izhar, M. F. N.

    2016-07-01

    This study is conducted on the usage of remote sensing images from several different years in order to analyze the changes of shoreline and land cover of the area. Remote sensing images used in this study are the data captured by the Landsat satellite. The images are projecting the land surface in 30 by 30 meter resolution and it is processed by the ENVI software. ENVI is able to change each digital number of the pixels on the images into specific value according to the applied model for classification in which could be used as an approach in calculating the area different classes based from the images itself. Therefore, using this method, the changes on the coastal area are possible to be determined. Analysis of the shoreline and land reclamation around the coastal area is integrated with the land use changes to determine its impact. The study shows that Batu Pahat area might have undergone land reclamation whereas in Pasir Gudang is experiencing substantial amount of erosion. Besides, the changes of land use in both areas were considered to be rapid and due to the results obtained from this study, the issues may be brought about for the local authority awareness action.

  17. Infants detect changes in everyday scenes: the role of scene gist.

    PubMed

    Duh, Shinchieh; Wang, Su-hua

    2014-07-01

    When watching physical events, infants bring to bear prior knowledge about objects and readily detect changes that contradict physical rules. Here we investigate the possibility that scene gist may affect infants, as it affects adults, when detecting changes in everyday scenes. In Experiment 1, 15-month-old infants missed a perceptually salient change that preserved the gist of a generic outdoor scene; the same change was readily detected if infants had insufficient time to process the display and had to rely on perceptual information for change detection. In Experiment 2, 15-month-olds detected a perceptually subtle change that preserved the scene gist but violated the rule of object continuity, suggesting that physical rules may overpower scene gist in infants' change detection. Finally, Experiments 3 and 4 provided converging evidence for the effects of scene gist, showing that 15-month-olds missed a perceptually salient change that preserved the gist and detected a perceptually subtle change that disrupted the gist. Together, these results suggest that prior knowledge, including scene knowledge and physical knowledge, affects the process by which infants maintain their representations of everyday scenes. PMID:24751990

  18. Supervised Change Detection in VHR Images Using Support Vector Machines and Contextual Information

    NASA Astrophysics Data System (ADS)

    Volpi, Michele; Kanevski, Mikhail

    2010-05-01

    One of the recent challenges in environmental studies is how to include and exploit multitemporal information from multispectral very high resolution (VHR) images. This problem is also known as change detection (CD). Nowadays, many approaches, both supervised and unsupervised, are known and the selection of the method depends strongly on the application, the scope of the study and on available time. In the present research an accurate multiclass supervised method based on Support Vector Machines (SVM) for multitemporal remotely sensed image classification is proposed. SVM is a method issued from the statistical learning theory, known for its good generalization abilities and its performance when dealing with high dimensional spaces. Moreover, its sparse solution provides a final model depending only on a few patterns with an associated nonzero weights (support vectors), and resulting in an optimal regularized complexity. The final decision is obtained with a linear separation of data in an induced kernel feature space, corresponding to a nonlinear classification in the input space. When dealing with CD in VHR imagery, misclassified patterns are often caused by the high variance of the information at pixel level, caused by noise and by the influence of the high spatial resolution. Considering a precise coregistration, the variance at object level is high both in space and in time. The usefulness of adding such information is in smoothing, following an object based or a texture based criteria, the interclass variance and increasing the intraclass variance. By adding such information the classifier can better perform when predicting the class of pixels, because of the neighborhood information that was intrinsically extrapolated by the filtering. In the proposed approach, the behavior of mathematical morphology and morphological profiles obtained with different parameters are studied in a CD setting. The series of features are extracted both on the multispectral images

  19. Detecting Changes of a Distant Gas Source with an Array of MOX Gas Sensors

    PubMed Central

    Pashami, Sepideh; Lilienthal, Achim J.; Trincavelli, Marco

    2012-01-01

    We address the problem of detecting changes in the activity of a distant gas source from the response of an array of metal oxide (MOX) gas sensors deployed in an open sampling system. The main challenge is the turbulent nature of gas dispersion and the response dynamics of the sensors. We propose a change point detection approach and evaluate it on individual gas sensors in an experimental setup where a gas source changes in intensity, compound, or mixture ratio. We also introduce an efficient sensor selection algorithm and evaluate the change point detection approach with the selected sensor array subsets. PMID:23443385

  20. Efficient fold-change detection based on protein-protein interactions.

    PubMed

    Buijsman, W; Sheinman, M

    2014-02-01

    Various biological sensory systems exhibit a response to a relative change of the stimulus, often referred to as fold-change detection. In the past few years, fold-change detecting mechanisms, based on transcriptional networks, have been proposed. Here we present a fold-change detecting mechanism, based on protein-protein interactions, consisting of two interacting proteins. This mechanism does not consume chemical energy and is not subject to transcriptional and translational noise, in contrast to previously proposed mechanisms. We show by analytical and numerical calculations that the mechanism is robust and can have a fast, precise, and efficient response for parameters that are relevant to eukaryotic cells. PMID:25353514

  1. Detection and Attribution of Global Mean Thermosteric Sea Level Change

    NASA Astrophysics Data System (ADS)

    Slangen, A.; Church, J. A.; Zhang, X.; Monselesan, D. P.

    2014-12-01

    Changes in sea level are driven by a range of natural and anthropogenic forcings. To better understand the response of global mean thermosteric sea-level change to these forcings, we compare three observational datasets to experiments of 28 climate models with up to five different forcing scenarios for 1957-2005. We use the pre-industrial control runs to determine the internal climate variability. Our analysis shows that anthropogenic greenhouse gas and aerosol forcing is required to explain the magnitude of the observed changes, while natural forcing drives most of the externally-forced decadal variability. The experiments that include anthropogenic and natural forcings capture the observed increased trend towards the end of the 20th century. The observed changes can be best explained by scaling the natural-only experiment by 0.70±0.30 and the anthropogenic-only experiment (including opposing forcing from greenhouse gases and aerosols) by 1.08±0.13 (+/-2σ).

  2. Detecting geomorphic processes and change with high resolution topographic data

    NASA Astrophysics Data System (ADS)

    Mudd, Simon; Hurst, Martin; Grieve, Stuart; Clubb, Fiona; Milodowski, David; Attal, Mikael

    2016-04-01

    The first global topographic dataset was released in 1996, with 1 km grid spacing. It is astonishing that in only 20 years we now have access to tens of thousands of square kilometres of LiDAR data at point densities greater than 5 points per square meter. This data represents a treasure trove of information that our geomorphic predecessors could only dream of. But what are we to do with this data? Here we explore the potential of high resolution topographic data to dig deeper into geomorphic processes across a wider range of landscapes and using much larger spatial coverage than previously possible. We show how this data can be used to constrain sediment flux relationships using relief and hillslope length, and how this data can be used to detect landscape transience. We show how the nonlinear sediment flux law, proposed for upland, soil mantled landscapes by Roering et al. (1999) is consistent with a number of topographic tests. This flux law allows us to predict how landscapes will respond to tectonic forcing, and we show how these predictions can be used to detect erosion rate perturbations across a range of tectonic settings.

  3. Inverse sequential detection of parameter changes in developing time series

    NASA Technical Reports Server (NTRS)

    Radok, Uwe; Brown, Timothy J.

    1992-01-01

    Progressive values of two probabilities are obtained for parameter estimates derived from an existing set of values and from the same set enlarged by one or more new values, respectively. One probability is that of erroneously preferring the second of these estimates for the existing data ('type 1 error'), while the second probability is that of erroneously accepting their estimates for the enlarged test ('type 2 error'). A more stable combined 'no change' probability which always falls between 0.5 and 0 is derived from the (logarithmic) width of the uncertainty region of an equivalent 'inverted' sequential probability ratio test (SPRT, Wald 1945) in which the error probabilities are calculated rather than prescribed. A parameter change is indicated when the compound probability undergoes a progressive decrease. The test is explicitly formulated and exemplified for Gaussian samples.

  4. Protein Binding for Detection of Small Changes on Nanoparticle Surface

    PubMed Central

    Zeng, Shang; Huang, Yu-ming M.; Chang, Chia-en A.; Zhong, Wenwan

    2014-01-01

    Protein adsorption on nanoparticles is closely associated with the physicochemical properties of particles, in particular, their surface property. We synthesized two batches of polyacrylic acid-coated nanoparticles under almost identical conditions except for heating duration and found differences in the head-group structure of the polyacrylic acid. The structure change was confirmed by NMR and MS. The two batches of particles had varied binding affinities to a selected group of proteins. Computational work confirmed that the head group of the polymer on the surface of a nanoparticle could directly interact with a protein, and small structural changes in the head group were sufficient to result in a significant difference in the free energy of binding. Our results demonstrate that protein adsorption is so sensitive to the surface property of particles that it can reveal even small variations in the structure of a nanoparticle surface ligand, and should be useful for quick assessment of nanoparticle properties. PMID:24482794

  5. Influence of storage time on DNA of Chlamydia trachomatis, Ureaplasma urealyticum, and Neisseria gonorrhoeae for accurate detection by quantitative real-time polymerase chain reaction.

    PubMed

    Lu, Y; Rong, C Z; Zhao, J Y; Lao, X J; Xie, L; Li, S; Qin, X

    2016-01-01

    The shipment and storage conditions of clinical samples pose a major challenge to the detection accuracy of Chlamydia trachomatis (CT), Neisseria gonorrhoeae (NG), and Ureaplasma urealyticum (UU) when using quantitative real-time polymerase chain reaction (qRT-PCR). The aim of the present study was to explore the influence of storage time at 4°C on the DNA of these pathogens and its effect on their detection by qRT-PCR. CT, NG, and UU positive genital swabs from 70 patients were collected, and DNA of all samples were extracted and divided into eight aliquots. One aliquot was immediately analyzed with qRT-PCR to assess the initial pathogen load, whereas the remaining samples were stored at 4°C and analyzed after 1, 2, 3, 7, 14, 21, and 28 days. No significant differences in CT, NG, and UU DNA loads were observed between baseline (day 0) and the subsequent time points (days 1, 2, 3, 7, 14, 21, and 28) in any of the 70 samples. Although a slight increase in DNA levels was observed at day 28 compared to day 0, paired sample t-test results revealed no significant differences between the mean DNA levels at different time points following storage at 4°C (all P>0.05). Overall, the CT, UU, and NG DNA loads from all genital swab samples were stable at 4°C over a 28-day period. PMID:27580005

  6. Trimodal color-fluorescence-polarization endoscopy aided by a tumor selective molecular probe accurately detects flat lesions in colitis-associated cancer

    NASA Astrophysics Data System (ADS)

    Charanya, Tauseef; York, Timothy; Bloch, Sharon; Sudlow, Gail; Liang, Kexian; Garcia, Missael; Akers, Walter J.; Rubin, Deborah; Gruev, Viktor; Achilefu, Samuel

    2014-12-01

    Colitis-associated cancer (CAC) arises from premalignant flat lesions of the colon, which are difficult to detect with current endoscopic screening approaches. We have developed a complementary fluorescence and polarization reporting strategy that combines the unique biochemical and physical properties of dysplasia and cancer for real-time detection of these lesions. Using azoxymethane-dextran sodium sulfate (AOM-DSS) treated mice, which recapitulates human CAC and dysplasia, we show that an octapeptide labeled with a near-infrared (NIR) fluorescent dye selectively identified all precancerous and cancerous lesions. A new thermoresponsive sol-gel formulation allowed topical application of the molecular probe during endoscopy. This method yielded high contrast-to-noise ratios (CNR) between adenomatous tumors (20.6±1.65) and flat lesions (12.1±1.03) and surrounding uninvolved colon tissue versus CNR of inflamed tissues (1.62±0.41). Incorporation of nanowire-filtered polarization imaging into NIR fluorescence endoscopy shows a high depolarization contrast in both adenomatous tumors and flat lesions in CAC, reflecting compromised structural integrity of these tissues. Together, the real-time polarization imaging provides real-time validation of suspicious colon tissue highlighted by molecular fluorescence endoscopy.

  7. Influence of storage time on DNA of Chlamydia trachomatis, Ureaplasma urealyticum, and Neisseria gonorrhoeae for accurate detection by quantitative real-time polymerase chain reaction

    PubMed Central

    Lu, Y.; Rong, C.Z.; Zhao, J.Y.; Lao, X.J.; Xie, L.; Li, S.; Qin, X.

    2016-01-01

    The shipment and storage conditions of clinical samples pose a major challenge to the detection accuracy of Chlamydia trachomatis (CT), Neisseria gonorrhoeae (NG), and Ureaplasma urealyticum (UU) when using quantitative real-time polymerase chain reaction (qRT-PCR). The aim of the present study was to explore the influence of storage time at 4°C on the DNA of these pathogens and its effect on their detection by qRT-PCR. CT, NG, and UU positive genital swabs from 70 patients were collected, and DNA of all samples were extracted and divided into eight aliquots. One aliquot was immediately analyzed with qRT-PCR to assess the initial pathogen load, whereas the remaining samples were stored at 4°C and analyzed after 1, 2, 3, 7, 14, 21, and 28 days. No significant differences in CT, NG, and UU DNA loads were observed between baseline (day 0) and the subsequent time points (days 1, 2, 3, 7, 14, 21, and 28) in any of the 70 samples. Although a slight increase in DNA levels was observed at day 28 compared to day 0, paired sample t-test results revealed no significant differences between the mean DNA levels at different time points following storage at 4°C (all P>0.05). Overall, the CT, UU, and NG DNA loads from all genital swab samples were stable at 4°C over a 28-day period. PMID:27580005

  8. Detection of human papillomavirus (HPV) in clinical samples: Evolving methods and strategies for the accurate determination of HPV status of head and neck carcinomas

    PubMed Central

    Westra, William H.

    2015-01-01

    SUMMARY Much recent attention has highlighted a subset of head and neck squamous cell carcinomas (HNSCCs) related to human papillomavirus (HPV) that has an epidemiologic, demographic, molecular and clinical profile which is distinct from non-HPV-related HNSCC. The clinical significance of detecting HPV in a HNSCC has resulted in a growing expectation for HPV testing of HNSCCs. Although the growing demand for routine testing is understandable and appropriate, it has impelled an undisciplined approach that has been largely unsystematic. The current state of the art has now arrived at a point where a better understanding of HPV-related tumorigenesis and a growing experience with HPV testing can now move wide scale, indiscriminant and non-standardized testing towards a more directed, clinically relevant and standardized approach. This review will address the current state of HPV detection; and will focus on why HPV testing is important, when HPV testing is appropriate, and how to test for the presence of HPV in various clinical samples. As no single test has been universally accepted as a best method, this review will consider the strengths and weaknesses of some of the more commonly used assays, and will emphasize some emerging techniques that may improve the efficiency of HPV testing of clinical samples including cytologic specimens. PMID:24932529

  9. Trimodal color-fluorescence-polarization endoscopy aided by a tumor selective molecular probe accurately detects flat lesions in colitis-associated cancer

    PubMed Central

    Charanya, Tauseef; York, Timothy; Bloch, Sharon; Sudlow, Gail; Liang, Kexian; Garcia, Missael; Akers, Walter J.; Rubin, Deborah; Gruev, Viktor; Achilefu, Samuel

    2014-01-01

    Abstract. Colitis-associated cancer (CAC) arises from premalignant flat lesions of the colon, which are difficult to detect with current endoscopic screening approaches. We have developed a complementary fluorescence and polarization reporting strategy that combines the unique biochemical and physical properties of dysplasia and cancer for real-time detection of these lesions. Using azoxymethane-dextran sodium sulfate (AOM-DSS) treated mice, which recapitulates human CAC and dysplasia, we show that an octapeptide labeled with a near-infrared (NIR) fluorescent dye selectively identified all precancerous and cancerous lesions. A new thermoresponsive sol-gel formulation allowed topical application of the molecular probe during endoscopy. This method yielded high contrast-to-noise ratios (CNR) between adenomatous tumors (20.6±1.65) and flat lesions (12.1±1.03) and surrounding uninvolved colon tissue versus CNR of inflamed tissues (1.62±0.41). Incorporation of nanowire-filtered polarization imaging into NIR fluorescence endoscopy shows a high depolarization contrast in both adenomatous tumors and flat lesions in CAC, reflecting compromised structural integrity of these tissues. Together, the real-time polarization imaging provides real-time validation of suspicious colon tissue highlighted by molecular fluorescence endoscopy. PMID:25473883

  10. An epigenetic biomarker combination of PCDH17 and POU4F2 detects bladder cancer accurately by methylation analyses of urine sediment DNA in Han Chinese

    PubMed Central

    Li, Qiaoling; An, Dan; Fang, Lu; Lin, Youcheng; Hou, Yong; Xu, Abai; Fu, Yu; Lu, Wei; Chen, Xin; Chen, Mingwei; Zhang, Meng; Jiang, Huiling; Zhang, Chuanxia; Dong, Pei; Li, Chong; Chen, Jun; Yang, Guosheng; Liu, Chunxiao; Cai, Zhiming; Zhou, Fangjian; Wu, Song

    2016-01-01

    To develop a routine and effectual procedure of detecting bladder cancer (BlCa), an optimized combination of epigenetic biomarkers that work synergistically with high sensitivity and specificity is necessary. In this study, methylation levels of seven biomarkers (EOMES, GDF15, NID2, PCDH17, POU4F2, TCF21, and ZNF154) in 148 individuals—which including 58 urothelial cell carcinoma (UCC) patients, 20 infected urinary calculi (IUC) patients, 20 kidney cancer (KC) patients,20 prostate cancer (PC) patients, and 30 healthy volunteers (HV)—were quantified by qMSP using the urine sediment DNA. Receiver operating characteristic (ROC) curves were generated for each biomarker. The combining predictors of possible combinations were calculated through logistic regression model. Subsequently, ROC curves of the three best performing combinations were constructed. Then, we validated the three best performing combinations and POU4F2 in another 72 UCC, 21 IUC, 26 KC and 22 PC, and 23 HV urine samples. The combination of POU4F2/PCDH17 has yielded the highest sensitivity and specificity of 90.00% and 93.96% in all the 312 individuals, showing the capability of detecting BlCa effectively among pathologically varied sample groups. PMID:26700620

  11. Information Foraging and Change Detection for Automated Science Exploration

    NASA Technical Reports Server (NTRS)

    Furlong, P. Michael; Dille, Michael

    2016-01-01

    This paper presents a new algorithm for autonomous on-line exploration in unknown environments. The objective is to free remote scientists from possibly-infeasible extensive preliminary site investigation prior to sending robotic agents. We simulate a common exploration task for an autonomous robot sampling the environment at various locations and compare performance against simpler control strategies. An extension is proposed and evaluated that further permits operation in the presence of environmental variability in which the robot encounters a change in the distribution underlying sampling targets. Experimental results indicate a strong improvement in performance across varied parameter choices for the scenario.

  12. Change detection for Finnish CORINE land cover classification

    NASA Astrophysics Data System (ADS)

    Törmä, Markus; Härmä, Pekka; Hatunen, Suvi; Teiniranta, Riitta; Kallio, Minna; Järvenpää, Elise

    2011-11-01

    This paper describes the ideas, data and methods to produce Finnish Corine Land Cover 2006 (CLC2006) classification. This version is based on use of existing national GIS data and satellite images and their automated processing, instead of visual interpretation of satellite images. The main idea is that land use information is based on GIS datasets and land cover information interpretation of satellite images. Because Finland participated to CLC2000-project, also changes between years 2000 and 2006 are determined. Finnish approach is good example how national GIS data is used to produce data fulfilling European needs in bottom-up fashion.

  13. Change-Point Detection of Natural Frequency Using Dynamic Model Selection and Clustering

    NASA Astrophysics Data System (ADS)

    Matsuoka, Kodai; Kaito, Kiyoyuki; Sogabe, Masamichi

    In order to apply structural monitoring into practice, it is indispensable to develop a method for change-point detection of bridge vibrational properties. In this study, the authors have developed a methodology using sequential prediction, dynamic model selection, and clustering, with the purpose of evaluating vibrational properties and its change timings. In order to examine the validity, the time series that had the change in frequency was calculated, and proposal method was applied. As a results, it was found that the natural frequency is detected. As for change timings, these were evaluated as change intervals. On the other hand, when the proposed method was applied to the acceleration response of a bridge when a train passes, it was found that bridge frequency can be extracted stably, and it is difficult to detect change timings when the change is small. Based on these results, factors were studied, and some solutions to the problems were proposed.

  14. Fast and accurate metrology of multi-layered ceramic materials by an automated boundary detection algorithm developed for optical coherence tomography data

    PubMed Central

    Ekberg, Peter; Su, Rong; Chang, Ernest W.; Yun, Seok Hyun; Mattsson, Lars

    2014-01-01

    Optical coherence tomography (OCT) is useful for materials defect analysis and inspection with the additional possibility of quantitative dimensional metrology. Here, we present an automated image-processing algorithm for OCT analysis of roll-to-roll multilayers in 3D manufacturing of advanced ceramics. It has the advantage of avoiding filtering and preset modeling, and will, thus, introduce a simplification. The algorithm is validated for its capability of measuring the thickness of ceramic layers, extracting the boundaries of embedded features with irregular shapes, and detecting the geometric deformations. The accuracy of the algorithm is very high, and the reliability is better than 1 µm when evaluating with the OCT images using the same gauge block step height reference. The method may be suitable for industrial applications to the rapid inspection of manufactured samples with high accuracy and robustness. PMID:24562018

  15. Improved Detection System Description and New Method for Accurate Calibration of Micro-Channel Plate Based Instruments and Its Use in the Fast Plasma Investigation on NASA's Magnetospheric MultiScale Mission

    NASA Technical Reports Server (NTRS)

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

    2015-01-01

    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. More precise calibration is highly desirable as the instruments will produce higher quality raw data that will require less post-acquisition data correction using results from in-flight pitch angle distribution measurements and ground calibration measurements. The detection system description and the fundamental concepts of this new calibration method, named threshold scan, will be presented. It will be shown how to derive all the individual detection system parameters and how to choose the optimum detection system operating point. This new method has been successfully applied to achieve a highly accurate calibration of the DESs and DISs of the MMS mission. The practical application of the method will be presented together with the achieved calibration results and their significance. Finally, it will be shown that, with further detailed modeling, this method can be extended for use in flight to achieve and maintain a highly accurate detection system calibration across a large number of instruments during the mission.

  16. Fast SAR Image Change Detection Using Bayesian Approach Based Difference Image and Modified Statistical Region Merging

    PubMed Central

    Ni, Weiping; Yan, Weidong; Bian, Hui; Wu, Junzheng

    2014-01-01

    A novel fast SAR image change detection method is presented in this paper. Based on a Bayesian approach, the prior information that speckles follow the Nakagami distribution is incorporated into the difference image (DI) generation process. The new DI performs much better than the familiar log ratio (LR) DI as well as the cumulant based Kullback-Leibler divergence (CKLD) DI. The statistical region merging (SRM) approach is first introduced to change detection context. A new clustering procedure with the region variance as the statistical inference variable is exhibited to tailor SAR image change detection purposes, with only two classes in the final map, the unchanged and changed classes. The most prominent advantages of the proposed modified SRM (MSRM) method are the ability to cope with noise corruption and the quick implementation. Experimental results show that the proposed method is superior in both the change detection accuracy and the operation efficiency. PMID:25258740

  17. Image change detection using a SWIR active imaging system

    NASA Astrophysics Data System (ADS)

    Schneider, Armin L.; Monnin, David; Laurenzis, Martin; Christnacher, Frank

    2013-10-01

    We are currently developing a system consisting of a GPS receiver, a three-axis magnetic compass as well as a digital video camera in order to visualize changes occuring along a regularily used itinerary. This is done by comparing actual images with images from the same scene, which have been acquired during a previous measurement. The luminosity of images from two different passages however can be quite different (due to different meteorological conditions). Whereas the global luminosity can be adjusted using non-linear luminosity correction, the treatment of shadows is more di cult. Since meteorological conditions cannot be controlled, we are investigating the possibility of using a Laser Gated Viewing system in the SWIR domain to illuminate the scene. Using appropriate filters for the camera, we are completely independent of natural illumination and in addition, the system can also be used at night.

  18. Object-Based Classification and Change Detection of Hokkaido, Japan

    NASA Astrophysics Data System (ADS)

    Park, J. G.; Harada, I.; Kwak, Y.

    2016-06-01

    Topography and geology are factors to characterize the distribution of natural vegetation. Topographic contour is particularly influential on the living conditions of plants such as soil moisture, sunlight, and windiness. Vegetation associations having similar characteristics are present in locations having similar topographic conditions unless natural disturbances such as landslides and forest fires or artificial disturbances such as deforestation and man-made plantation bring about changes in such conditions. We developed a vegetation map of Japan using an object-based segmentation approach with topographic information (elevation, slope, slope direction) that is closely related to the distribution of vegetation. The results found that the object-based classification is more effective to produce a vegetation map than the pixel-based classification.

  19. Accurate, rapid and high-throughput detection of strain-specific polymorphisms in Bacillus anthracis and Yersinia pestis by next-generation sequencing

    PubMed Central

    2010-01-01

    Background In the event of biocrimes or infectious disease outbreaks, high-resolution genetic characterization for identifying the agent and attributing it to a specific source can be crucial for an effective response. Until recently, in-depth genetic characterization required expensive and time-consuming Sanger sequencing of a few strains, followed by genotyping of a small number of marker loci in a panel of isolates at or by gel-based approaches such as pulsed field gel electrophoresis, which by necessity ignores most of the genome. Next-generation, massively parallel sequencing (MPS) technology (specifically the Applied Biosystems sequencing by oligonucleotide ligation and detection (SOLiD™) system) is a powerful investigative tool for rapid, cost-effective and parallel microbial whole-genome characterization. Results To demonstrate the utility of MPS for whole-genome typing of monomorphic pathogens, four Bacillus anthracis and four Yersinia pestis strains were sequenced in parallel. Reads were aligned to complete reference genomes, and genomic variations were identified. Resequencing of the B. anthracis Ames ancestor strain detected no false-positive single-nucleotide polymorphisms (SNPs), and mapping of reads to the Sterne strain correctly identified 98% of the 133 SNPs that are not clustered or associated with repeats. Three geographically distinct B. anthracis strains from the A branch lineage were found to have between 352 and 471 SNPs each, relative to the Ames genome, and one strain harbored a genomic amplification. Sequencing of four Y. pestis strains from the Orientalis lineage identified between 20 and 54 SNPs per strain relative to the CO92 genome, with the single Bolivian isolate having approximately twice as many SNPs as the three more closely related North American strains. Coverage plotting also revealed a common deletion in two strains and an amplification in the Bolivian strain that appear to be due to insertion element-mediated recombination

  20. Detecting changes in maps of gamma spectra with Kolmogorov-Smirnov tests

    NASA Astrophysics Data System (ADS)

    Reinhart, Alex; Ventura, Valérie; Athey, Alex

    2015-12-01

    Various security, regulatory, and consequence management agencies are interested in continuously monitoring wide areas for unexpected changes in radioactivity. Existing detection systems are designed to search for radioactive sources but are not suited to repeat mapping and change detection. Using a set of daily spectral observations collected at the Pickle Research Campus, we improved on the prior Spectral Comparison Ratio Anomaly Mapping (SCRAM) algorithm and developed a new method based on two-sample Kolmogorov-Smirnov tests to detect sudden spectral changes. We also designed simulations and visualizations of statistical power to compare methods and guide deployment scenarios.

  1. Single and Multiple Change Point Detection in Spike Trains: Comparison of Different CUSUM Methods.

    PubMed

    Koepcke, Lena; Ashida, Go; Kretzberg, Jutta

    2016-01-01

    In a natural environment, sensory systems are faced with ever-changing stimuli that can occur, disappear or change their properties at any time. For the animal to react adequately the sensory systems must be able to detect changes in external stimuli based on its neuronal responses. Since the nervous system has no prior knowledge of the stimulus timing, changes in stimulus need to be inferred from the changes in neuronal activity, in particular increase or decrease of the spike rate, its variability, and shifted response latencies. From a mathematical point of view, this problem can be rephrased as detecting changes of statistical properties in a time series. In neuroscience, the CUSUM (cumulative sum) method has been applied to recorded neuronal responses for detecting a single stimulus change. Here, we investigate the applicability of the CUSUM approach for detecting single as well as multiple stimulus changes that induce increases or decreases in neuronal activity. Like the nervous system, our algorithm relies exclusively on previous neuronal population activities, without using knowledge about the timing or number of external stimulus changes. We apply our change point detection methods to experimental data obtained by multi-electrode recordings from turtle retinal ganglion cells, which react to changes in light stimulation with a range of typical neuronal activity patterns. We systematically examine how variations of mathematical assumptions (Poisson, Gaussian, and Gamma distributions) used for the algorithms may affect the detection of an unknown number of stimulus changes in our data and compare these CUSUM methods with the standard Rate Change method. Our results suggest which versions of the CUSUM algorithm could be useful for different types of specific data sets. PMID:27445714

  2. Single and Multiple Change Point Detection in Spike Trains: Comparison of Different CUSUM Methods

    PubMed Central

    Koepcke, Lena; Ashida, Go; Kretzberg, Jutta

    2016-01-01

    In a natural environment, sensory systems are faced with ever-changing stimuli that can occur, disappear or change their properties at any time. For the animal to react adequately the sensory systems must be able to detect changes in external stimuli based on its neuronal responses. Since the nervous system has no prior knowledge of the stimulus timing, changes in stimulus need to be inferred from the changes in neuronal activity, in particular increase or decrease of the spike rate, its variability, and shifted response latencies. From a mathematical point of view, this problem can be rephrased as detecting changes of statistical properties in a time series. In neuroscience, the CUSUM (cumulative sum) method has been applied to recorded neuronal responses for detecting a single stimulus change. Here, we investigate the applicability of the CUSUM approach for detecting single as well as multiple stimulus changes that induce increases or decreases in neuronal activity. Like the nervous system, our algorithm relies exclusively on previous neuronal population activities, without using knowledge about the timing or number of external stimulus changes. We apply our change point detection methods to experimental data obtained by multi-electrode recordings from turtle retinal ganglion cells, which react to changes in light stimulation with a range of typical neuronal activity patterns. We systematically examine how variations of mathematical assumptions (Poisson, Gaussian, and Gamma distributions) used for the algorithms may affect the detection of an unknown number of stimulus changes in our data and compare these CUSUM methods with the standard Rate Change method. Our results suggest which versions of the CUSUM algorithm could be useful for different types of specific data sets. PMID:27445714

  3. Evaluation of the capability of the Lombard test in detecting abrupt changes in variance

    NASA Astrophysics Data System (ADS)

    Nayak, Munir A.; Villarini, Gabriele

    2016-03-01

    Hydrologic time series are often characterized by temporal changes that give rise to non-stationarity. When the distribution describing the data changes over time, it is important to detect these changes so that correct inferences can be drawn from the data. The Lombard test, a non-parametric rank-based test to detect change points in the moments of a time series, has been recently used in the hydrologic literature to detect change points in the mean and variance. Little is known, however, about the performance of this test in detecting changes in variance, despite the potentially large impacts that these changes (shifts) could have when dealing with extremes. Here we address this issue in a Monte Carlo simulation framework. We consider a number of different situations that can manifest themselves in hydrologic time series, including the dependence of the results on the magnitude of the shift, significance level, sample size and location of the change point within the series. Analyses are performed considering abrupt changes in variance occurring with and without shifts in the mean. The results show that the power of the test in detecting change points in variance is small when the changes are small. It is large when the change point occurs close to the middle of the time series, and it increases nonlinearly with increasing sample size. Moreover, the power of the test is greatly reduced by the presence of change points in mean. We propose removing the change in the mean before testing for change points in variance. Simulation results demonstrate that this strategy effectively increases the power of the test. Finally, the Lombard test is applied to annual peak discharge records from 3686 U.S. Geological Survey stream-gaging stations across the conterminous United States, and the results are discussed in light of the insights from the simulations' results.

  4. Building Change Detection by Combining LiDAR Data and Ortho Image

    NASA Astrophysics Data System (ADS)

    Peng, Daifeng; Zhang, Yongjun

    2016-06-01

    The elevation information is not considered in the traditional building change detection methods. This paper presents an algorithm of combining LiDAR data and ortho image for 3D building change detection. The advantages of the proposed approach lie in the fusion of the height and spectral information by thematic segmentation. Furthermore, the proposed method also combines the advantages of pixel-level and object-level change detection by image differencing and object analysis. Firstly, two periods of LiDAR data are filtered and interpolated to generate their corresponding DSMs. Secondly, a binary image of the changed areas is generated by means of differencing and filtering the two DSMs, and then thematic layer is generated and projected onto the DSMs and DOMs. Thirdly, geometric and spectral features of the changed area are calculated, which is followed by decision tree classification for the purpose of extracting the changed building areas. Finally, the statistics of the elevation and area change information as well as the change type of the changed buildings are done for building change analysis. Experimental results show that the completeness and correctness of building change detection are close to 81.8% and 85.7% respectively when the building area is larger than 80 m2, which are increased about 10% when compared with using ortho image alone.

  5. A supervised method for object-based 3D building change detection on aerial stereo images

    NASA Astrophysics Data System (ADS)

    Qin, R.; Gruen, A.

    2014-08-01

    There is a great demand for studying the changes of buildings over time. The current trend for building change detection combines the orthophoto and DSM (Digital Surface Models). The pixel-based change detection methods are very sensitive to the quality of the images and DSMs, while the object-based methods are more robust towards these problems. In this paper, we propose a supervised method for building change detection. After a segment-based SVM (Support Vector Machine) classification with features extracted from the orthophoto and DSM, we focus on the detection of the building changes of different periods by measuring their height and texture differences, as well as their shapes. A decision tree analysis is used to assess the probability of change for each building segment and the traffic lighting system is used to indicate the status "change", "non-change" and "uncertain change" for building segments. The proposed method is applied to scanned aerial photos of the city of Zurich in 2002 and 2007, and the results have demonstrated that our method is able to achieve high detection accuracy.

  6. Object-based automatic change detection in forested areas of Poland between 2000 and 2006 using NDVI times series at moderate resolution.

    NASA Astrophysics Data System (ADS)

    Lamarche, C.; Tomaszewska, M.; Dabrowska-Zielinska, K.; Defourny, P.

    2012-04-01

    In the framework of the Geoland2 project, the Seasonal and Annual Change Monitoring Service (SATChMo) was initiated in order to close the gap between low-resolution global coverage and the high-resolution land cover (LC) and land cover change (LCC) parameters. The SM-14 product aims at developing timely continental and dynamic land cover change indicator maps over Europe and Africa, at moderate resolution. These land cover specific maps indicate where a major land cover change occurs but do not aim to identify the type of change. It can refer to land cover classes as well as to major events affecting temporarily the land surface such as flooding events, volcano, large burnt scarce, etc. In this context, this work applied an automatic and probabilistic change detection algorithm to spot changed objects of the forest of Poland between 2000 and 2006. By the adjustment of the change thresholds, this algorithm allows producing change probability maps rather than binary change/no change according to the needs of end-users. A multispectral segmentation simultaneously using yearly 250m MODIS composites of NDVI of 2000 and 2006 was applied over the coniferous forest defined by the Corine Land Cover 2000 map. This produced spatially homogeneous objects with similar behaviour over time. Under the hypothesis of minor changes in the study area, each object is statistically compared to an unchanged reference using the Mahalanobis distance. All the objects detected as changed by this trimming procedure are then flagged and spatially represented as a change probability map. An assessment of correct detection was performed by confronting the detected changed objects to the Corine Land Cover Change Map 2000-2006. Results show a strong dependency between agreements and the size of changed objects. Both user's and producer's accuracy improve with bigger objects. In the assessment of accurate coverage, taking into account the 250m MODIS pixels and assuming the low reliability of small

  7. Interactive Change Detection Using High Resolution Remote Sensing Images Based on Active Learning with Gaussian Processes

    NASA Astrophysics Data System (ADS)

    Ru, Hui; Yu, Huai; Huang, Pingping; Yang, Wen

    2016-06-01

    Although there have been many studies for change detection, the effective and efficient use of high resolution remote sensing images is still a problem. Conventional supervised methods need lots of annotations to classify the land cover categories and detect their changes. Besides, the training set in supervised methods often has lots of redundant samples without any essential information. In this study, we present a method for interactive change detection using high resolution remote sensing images with active learning to overcome the shortages of existing remote sensing image change detection techniques. In our method, there is no annotation of actual land cover category at the beginning. First, we find a certain number of the most representative objects in unsupervised way. Then, we can detect the change areas from multi-temporal high resolution remote sensing images by active learning with Gaussian processes in an interactive way gradually until the detection results do not change notably. The artificial labelling can be reduced substantially, and a desirable detection result can be obtained in a few iterations. The experiments on Geo-Eye1 and WorldView2 remote sensing images demonstrate the effectiveness and efficiency of our proposed method.

  8. Building Change Detection from LIDAR Point Cloud Data Based on Connected Component Analysis

    NASA Astrophysics Data System (ADS)

    Awrangjeb, M.; Fraser, C. S.; Lu, G.

    2015-08-01

    Building data are one of the important data types in a topographic database. Building change detection after a period of time is necessary for many applications, such as identification of informal settlements. Based on the detected changes, the database has to be updated to ensure its usefulness. This paper proposes an improved building detection technique, which is a prerequisite for many building change detection techniques. The improved technique examines the gap between neighbouring buildings in the building mask in order to avoid under segmentation errors. Then, a new building change detection technique from LIDAR point cloud data is proposed. Buildings which are totally new or demolished are directly added to the change detection output. However, for demolished or extended building parts, a connected component analysis algorithm is applied and for each connected component its area, width and height are estimated in order to ascertain if it can be considered as a demolished or new building part. Finally, a graphical user interface (GUI) has been developed to update detected changes to the existing building map. Experimental results show that the improved building detection technique can offer not only higher performance in terms of completeness and correctness, but also a lower number of undersegmentation errors as compared to its original counterpart. The proposed change detection technique produces no omission errors and thus it can be exploited for enhanced automated building information updating within a topographic database. Using the developed GUI, the user can quickly examine each suggested change and indicate his/her decision with a minimum number of mouse clicks.

  9. Performance evaluation of supervised change detection tool on DubaiSat-2 multispectral and pansharp images

    NASA Astrophysics Data System (ADS)

    Almatroushi, Hessa R.

    2014-10-01

    Supervised Change Detection Tool (SCDT) is an in-house developed tool in Emirates Institution for Advanced Science and Technology (EIAST). The developed tool is based on Algebra Change Detection algorithm and multi-class Support Vector Machine classifier and is capable of highlighting the areas of change, describing them, and discarding any falsedetections that result from shadow. Further, it can collect the analysis results, which include the change of class an area went through and the overall change percentage of each class defined, in a Microsoft Word document automatically. This paper evaluates the performance of the SCDT, which was initially developed for DubaiSat-1 multispectral images, on DubaiSat-2 multispectral and pansharp images. Moreover, it compares its performance opposed to Change Detection Analysis (i.e. Post-Classification) in ENVI.

  10. Change detection based on integration of multi-scale mixed-resolution information

    NASA Astrophysics Data System (ADS)

    Wei, Li; Wang, Cheng; Wen, Chenglu

    2016-03-01

    In this paper, a new method of unsupervised change detection is proposed by modeling multi-scale change detector based on local mixed information and we present a method of automated threshold. A theoretical analysis is presented to demonstrate that more comprehensive information is taken into account by the integration of multi-scale information. The ROC curves show that change detector based on multi-scale mixed information(MSM) is more effective than based on mixed information(MIX). Experiments on artificial and real-world datasets indicate that the multi-scale change detection of mixed information can eliminate the pseudo-change part of the area. Therefore, the proposed algorithm MSM is an effective method for the application of change detection.

  11. Temperature Changes in Brown Adipocytes Detected with a Bimaterial Microcantilever

    PubMed Central

    Sato, Masaaki K.; Toda, Masaya; Inomata, Naoki; Maruyama, Hisataka; Okamatsu-Ogura, Yuko; Arai, Fumihito; Ono, Takahito; Ishijima, Akihiko; Inoue, Yuichi

    2014-01-01

    Mammalian cells must produce heat to maintain body temperature and support other biological activities. Methods to measure a cell’s thermogenic ability by inserting a thermometer into the cell or measuring the rate of oxygen consumption in a closed vessel can disturb its natural state. Here, we developed a noninvasive system for measuring a cell’s heat production with a bimaterial microcantilever. This method is suitable for investigating the heat-generating properties of cells in their native state, because changes in cell temperature can be measured from the bending of the microcantilever, without damaging the cell and restricting its supply of dissolved oxygen. Thus, we were able to measure increases in cell temperature of <1 K in a small number of murine brown adipocytes (n = 4–7 cells) stimulated with norepinephrine, and observed a slow increase in temperature over several hours. This long-term heat production suggests that, in addition to converting fatty acids into heat energy, brown adipocytes may also adjust protein expression to raise their own temperature, to generate more heat. We expect this bimaterial microcantilever system to prove useful for determining a cell’s state by measuring thermal characteristics. PMID:24896125

  12. The experience of land cover change detection by satellite data

    NASA Astrophysics Data System (ADS)

    Spivak, Lev; Vitkovskaya, Irina; Batyrbayeva, Madina; Terekhov, Alexey

    2012-06-01

    Sigificant dependence from climate and anthropogenic influences characterize ecological systems of Kazakhstan. As result of the geographical location of the republic and ecological situation vegetative degradation sites exist throughout the territory of Kazakhstan. The major process of desertification takes place in the arid and semi-arid areas. To allocate spots of stable degradation of vegetation, the transition zone was first identified. Productivity of vegetation in transfer zone is slightly dependent on climate conditions. Multi-year digital maps of vegetation index were generated with NOAA satellite images. According to the result, the territory of the republic was zoned by means of vegetation productivity criterion. All the arable lands in Kazakhstan are in the risky agriculture zone. Estimation of the productivity of agricultural lands is highly important in the context of risky agriculture, where natural factors, such as wind and water erosion, can significantly change land quality in a relatively short time period. We used an integrated vegetation index to indicate land degradation measures to assess the inter-annual features in the response of vegetation to variations in climate conditions from low-resolution satellite data for all of Kazakhstan. This analysis allowed a better understanding of the spatial and temporal variations of land degradation in the country.

  13. Change Detection of Lake Aba Samuel in Ethiopia

    NASA Astrophysics Data System (ADS)

    Kaczynski, R.; Rylko, A.

    2016-06-01

    Old topographic map published in 1975 elaborated from aerial photographs taken in 1972, Landsat TM data acquired in May 1986 and Landsat ETM+ from June 2002 have been used to assess the changes of the lake Aba Samuel in Ethiopia. First map of the lake has been done in the framework of UNDP project running in 1988-90 in the Ethiopian Mapping Authority. The second classification map has been done as M.Sc. thesis in the MUT in 2015. Supervised classification methods with the use of ground truth data have been used for elaboration of the Landsat TM data. From the year 1972 up to 1986 the area of the lake has decreased by 23%. From 1986 up to 2002 the area of the lake has decreased by 20%. Therefore, after 30 years the lake was smaller by 43%. This have had very bad influence on the lives of the local population. From other recent data in the period from 2002-2015 the lake has practically disappeared and now it is only a small part of the river Akaki. ENVI 5.2 and ERDAS IMAGINE 9.2 have been used for Radiometric Calibration, Quick Atmospheric Correction (QUAC) and supervised classification of Landsat ETM+ data. The Optimum Index Factor shows the best combination of Landsat TM and ETM+ bands for color composite as 1,4,5 in the color filters: B, G, R for the signature development. Methodology and final maps are enclosed in the paper.

  14. Detecting climate forcing and feedback signals in surface climate change

    NASA Astrophysics Data System (ADS)

    Davy, Richard; Esau, Igor

    2015-04-01

    The Earth has warmed in the last century and a large component of that warming has been attributed to the build-up of anthropogenic greenhouse gases. There are also numerous feedback processes which can introduce strong, regionalized asymmetries to the overall warming trend. These processes alter the surface energy budget, and thus affect the surface air temperature, which is one of the primary measures of how the climate is changing. However, the degree to which a given forcing or feedback process alters surface temperatures is contingent on the effective heat capacity of the atmosphere which is defined by the depth of the planetary boundary layer. This can vary by an order of magnitude on different temporal and spatial scales, which can lead to a strongly amplified temperature response in shallow boundary layers. Therefore, if a climate forcing or feedback is acting across a wide range of conditions of the boundary layer, then this non-linear response of the surface climate to perturbations in the forcing must be accounted for in order to correctly assess the effect of the forcing on the surface climatology.

  15. Magnetic nanoparticles-cooperated fluorescence sensor for sensitive and accurate detection of DNA methyltransferase activity coupled with exonuclease III-assisted target recycling.

    PubMed

    Xue, Qingwang; Zhang, Youna; Xu, Shuling; Li, Haibo; Wang, Lei; Li, Rui; Zhang, Yuanfu; Yue, Qiaoli; Gu, Xiaohong; Zhang, Shuqiu; Liu, Jifeng; Wang, Huaisheng

    2015-11-21

    A fluorescence magnetic biosensor for the DNA methyltransferase activity was developed based on the cooperative amplification by combining the magnetic nanoparticles synergistic exonuclease III (Exo III)-assisted circular exponential amplification and a supramolecular structure ZnPPIX/G-quadruplex. First, a duplex DNA probe, which was constructed by the hybridization of a quadruplex-forming oligomer with a molecular beacon, was assembled on the magnetic nanoparticles (MNPs) as a reporter. A hairpin probe (HP)-containing sequence of GATC was used as the methylation substrate of DNA adenine methyltransferase (DAM). Once HP was methylated by DAM, it could be recognized and cleaved by Dpn I, which allows the release of a single-stranded DNA. The DNA (tDNA1) then hybridizes to the MNP probe, which then triggers the exonuclease III-mediated target exponential recycling reaction. Simultaneously, numerous quadruplex forming oligomers are liberated and folded into the G-quadruplex-ZnPPIX complexes with the help of zinc(ii)-protoporphyrin IX(ZnPPIX) on the MNP surface to give a remarkable fluorescence response. In the developed sensor, a small amount of target DAM can be converted to a large number of stable DNA triggers, leading to remarkable amplification of the target. Moreover, using MNPs as a vector of the sensor may reduce the interference from the real samples, which increases the anti-interference of the sensing system. Based on this unique amplification strategy, a very low detection limit down to 2.0 × 10(-4) U mL(-1) was obtained. Furthermore, the sensor could be used to evaluate the DAM activity in different growth stages of E. coli cells and screen Dam MTase inhibitors. Therefore, the strategy proposed here provides a promising platform for monitoring the activity and inhibition of DNA MTases and has great potential to be applied further in early clinical diagnostics and medical research. PMID:26421322

  16. Familiarity, expertise, and change detection: change deafness is worse in your native language.

    PubMed

    Neuhoff, John G; Schott, Steven A; Kropf, Adam J; Neuhoff, Emily M

    2014-01-01

    We first replicated the language-familiarity effect for voice discrimination and found better voice discrimination in familiar languages. However, when listeners were not cued to listen for changes, both English and Spanish speakers exhibited greater change deafness in their familiar language. Results suggest that lexical/semantic attention in a familiar language and increased indexical processing in an unfamiliar language can produce greater change deafness in familiar languages. PMID:24919355

  17. Detection and Classification of Changes in Buildings from Airborne Laser Scanning Data

    NASA Astrophysics Data System (ADS)

    Xu, S.; Vosselman, G.; Oude Elberink, S.

    2013-10-01

    Building change detection serves to investigate illegal buildings. Illegal built or removed structures, especially those concealed among gable roofs such as dormers, are difficult to track among potentially millions of buildings. Nevertheless, they can be efficiently located in changed areas. An approach is proposed to automatically detect and classify changes in buildings from two epochs of Airborne Laser Scanning Data. Both datasets are classified into water, ground, building, vegetation and undefined objects in advance. After generalization of a 3D surface separation map, we verify changes by making rules on the separation map. Changes belonging to buildings are then classified into roof, wall, dormers, vehicles, construction above roof and undefined objects. As the ALS data has accuracy in strip difference of lower than 5 cm within the same epoch and from different epochs, changes that are larger than 10 cm were detected. Building changes, which areas are larger than 4 m2, are identified as change. By inspection, nearly all changes are detected and approximately 80% changes are correctly classified.

  18. Automatic detection of vegetation changes in the southwestern United States using remotely sensed images

    SciTech Connect

    Chavez, P.S.; Mackinnon, D.J.

    1994-05-01

    The capability to automatically detect vegetation changes using multitemporal remotely sensed image data is of upmost importance to many global-change research projects. A procedure to automatically map vegetation changes within arid and semi-arid regions of the southwestern United States is presented. Multitemporal Landsat Multispectral Scanner (MSS) images were the primary data source, but some preliminary work was also done using same-date Visible-Infrared Spin-Scan Radiometer (VISSR) data for comparison with the MSS results. The change-detection procedure includes multitemporal image calibration using a hybrid method that we developed for the project; the hybrid calibration allows a radiometric calibration to be applied to historical data by using field-radiance information rather than a modeling procedure. The results indicate that a calibrated visible band is more sensitive than the widely used Normalized Difference Vegetation Index (NDVI) in detecting vegetation changes in the arid and semi-arid environments of the southwestern United States. Changes were detected in the desert environment, where the vegetation density is relatively low, with both Landsat MSS and GOES VISSR images. Some changes detected by the automatic procedure were confirmed in the field during two of the Landsat overpasses. The changes corresponded mostly to the blooming of ephemeral or annual vegetation.

  19. Indigenous Knowledge and Long-term Ecological Change: Detection, Interpretation, and Responses to Changing Ecological Conditions in Pacific Island Communities

    PubMed Central

    Aswani, Shankar

    2010-01-01

    When local resource users detect, understand, and respond to environmental change they can more effectively manage environmental resources. This article assesses these abilities among artisanal fishers in Roviana Lagoon, Solomon Islands. In a comparison of two villages, it documents local resource users’ abilities to monitor long-term ecological change occurring to seagrass meadows near their communities, their understandings of the drivers of change, and their conceptualizations of seagrass ecology. Local observations of ecological change are compared with historical aerial photography and IKONOS satellite images that show 56 years of actual changes in seagrass meadows from 1947 to 2003. Results suggest that villagers detect long-term changes in the spatial cover of rapidly expanding seagrass meadows. However, for seagrass meadows that showed no long-term expansion or contraction in spatial cover over one-third of respondents incorrectly assumed changes had occurred. Examples from a community-based management initiative designed around indigenous ecological knowledge and customary sea tenure governance show how local observations of ecological change shape marine resource use and practices which, in turn, can increase the management adaptability of indigenous or hybrid governance systems. PMID:20336296

  20. Indigenous Knowledge and Long-term Ecological Change: Detection, Interpretation, and Responses to Changing Ecological Conditions in Pacific Island Communities

    NASA Astrophysics Data System (ADS)

    Lauer, Matthew; Aswani, Shankar

    2010-05-01

    When local resource users detect, understand, and respond to environmental change they can more effectively manage environmental resources. This article assesses these abilities among artisanal fishers in Roviana Lagoon, Solomon Islands. In a comparison of two villages, it documents local resource users’ abilities to monitor long-term ecological change occurring to seagrass meadows near their communities, their understandings of the drivers of change, and their conceptualizations of seagrass ecology. Local observations of ecological change are compared with historical aerial photography and IKONOS satellite images that show 56 years of actual changes in seagrass meadows from 1947 to 2003. Results suggest that villagers detect long-term changes in the spatial cover of rapidly expanding seagrass meadows. However, for seagrass meadows that showed no long-term expansion or contraction in spatial cover over one-third of respondents incorrectly assumed changes had occurred. Examples from a community-based management initiative designed around indigenous ecological knowledge and customary sea tenure governance show how local observations of ecological change shape marine resource use and practices which, in turn, can increase the management adaptability of indigenous or hybrid governance systems.

  1. Indigenous knowledge and long-term ecological change: detection, interpretation, and responses to changing ecological conditions in Pacific Island communities.

    PubMed

    Lauer, Matthew; Aswani, Shankar

    2010-05-01

    When local resource users detect, understand, and respond to environmental change they can more effectively manage environmental resources. This article assesses these abilities among artisanal fishers in Roviana Lagoon, Solomon Islands. In a comparison of two villages, it documents local resource users' abilities to monitor long-term ecological change occurring to seagrass meadows near their communities, their understandings of the drivers of change, and their conceptualizations of seagrass ecology. Local observations of ecological change are compared with historical aerial photography and IKONOS satellite images that show 56 years of actual changes in seagrass meadows from 1947 to 2003. Results suggest that villagers detect long-term changes in the spatial cover of rapidly expanding seagrass meadows. However, for seagrass meadows that showed no long-term expansion or contraction in spatial cover over one-third of respondents incorrectly assumed changes had occurred. Examples from a community-based management initiative designed around indigenous ecological knowledge and customary sea tenure governance show how local observations of ecological change shape marine resource use and practices which, in turn, can increase the management adaptability of indigenous or hybrid governance systems. PMID:20336296

  2. The study of target damage assessment system based on image change detection

    NASA Astrophysics Data System (ADS)

    Zhao, Ping; Yang, Fan; Feng, Xinxi

    2009-10-01

    Target Damage Assessment (TDA) system is an important component of the intelligent command and control system. The method of building TDA based on Image Change Detection can greatly improve the system efficiency and accuracy, thus get a fast and precise assessment results. This paper firstly analyzes the structure of TDA system. Then studies the key technology in this system. Finally, gives an evaluation criteria based on image change detection of the target damage assessment system.

  3. Changing Diagnostic Methods and Increased Detection of Verotoxigenic Escherichia coli, Ireland.

    PubMed

    Rice, Thomas; Quinn, Noreen; Sleator, Roy D; Lucey, Brigid

    2016-09-01

    The recent paradigm shift in infectious disease diagnosis from culture-based to molecular-based approaches is exemplified in the findings of a national study assessing the detection of verotoxigenic Escherichia coli infections in Ireland. The methodologic changes have been accompanied by a dramatic increase in detections of non-O157 verotoxigenic E. coli serotypes. PMID:27322897

  4. Changing Diagnostic Methods and Increased Detection of Verotoxigenic Escherichia coli, Ireland

    PubMed Central

    Rice, Thomas; Quinn, Noreen; Lucey, Brigid

    2016-01-01

    The recent paradigm shift in infectious disease diagnosis from culture-based to molecular-based approaches is exemplified in the findings of a national study assessing the detection of verotoxigenic Escherichia coli infections in Ireland. The methodologic changes have been accompanied by a dramatic increase in detections of non-O157 verotoxigenic E. coli serotypes. PMID:27322897

  5. Visual Salience in the Change Detection Paradigm: The Special Role of Object Onset

    ERIC Educational Resources Information Center

    Cole, Geoff G.; Kentridge, Robert W.; Heywood, Charles A.

    2004-01-01

    The relative efficacy with which appearance of a new object orients visual attention was investigated. At issue is whether the visual system treats onset as being of particular importance or only 1 of a number of stimulus events equally likely to summon attention. Using the 1-shot change detection paradigm, the authors compared detectability of…

  6. Fusion of UAV photogrammetry and digital optical granulometry for detection of structural changes in floodplains

    NASA Astrophysics Data System (ADS)

    Langhammer, Jakub; Lendzioch, Theodora; Mirijovsky, Jakub

    2016-04-01

    Granulometric analysis represents a traditional, important and for the description of sedimentary material substantial method with various applications in sedimentology, hydrology and geomorphology. However, the conventional granulometric field survey methods are time consuming, laborious, costly and are invasive to the surface being sampled, which can be limiting factor for their applicability in protected areas.. The optical granulometry has recently emerged as an image analysis technique, enabling non-invasive survey, employing semi-automated identification of clasts from calibrated digital imagery, taken on site by conventional high resolution digital camera and calibrated frame. The image processing allows detection and measurement of mixed size natural grains, their sorting and quantitative analysis using standard granulometric approaches. Despite known limitations, the technique today presents reliable tool, significantly easing and speeding the field survey in fluvial geomorphology. However, the nature of such survey has still limitations in spatial coverage of the sites and applicability in research at multitemporal scale. In our study, we are presenting novel approach, based on fusion of two image analysis techniques - optical granulometry and UAV-based photogrammetry, allowing to bridge the gap between the needs of high resolution structural information for granulometric analysis and spatially accurate and data coverage. We have developed and tested a workflow that, using UAV imaging platform enabling to deliver seamless, high resolution and spatially accurate imagery of the study site from which can be derived the granulometric properties of the sedimentary material. We have set up a workflow modeling chain, providing (i) the optimum flight parameters for UAV imagery to balance the two key divergent requirements - imagery resolution and seamless spatial coverage, (ii) the workflow for the processing of UAV acquired imagery by means of the optical

  7. Toward Robust Climate Baselining: Objective Assessment of Climate Change Using Widely Distributed Miniaturized Sensors for Accurate World-Wide Geophysical Measurements

    DOE R&D Accomplishments Database

    Teller, E.; Leith, C.; Canavan, G.; Marion, J.; Wood, L.

    2001-11-13

    A gap-free, world-wide, ocean-, atmosphere-, and land surface-spanning geophysical data-set of three decades time-duration containing the full set of geophysical parameters characterizing global weather is the scientific perquisite for defining the climate; the generally-accepted definition in the meteorological community is that climate is the 30-year running-average of weather. Until such a tridecadal climate baseline exists, climate change discussions inevitably will have a semi-speculative, vs. a purely scientific, character, as the baseline against which changes are referenced will at least somewhat uncertain.

  8. Accurate 3D point cloud comparison and volumetric change analysis of Terrestrial Laser Scan data in a hard rock coastal cliff environment

    NASA Astrophysics Data System (ADS)

    Earlie, C. S.; Masselink, G.; Russell, P.; Shail, R.; Kingston, K.

    2013-12-01

    Our understanding of the evolution of hard rock coastlines is limited due to the episodic nature and ';slow' rate at which changes occur. High-resolution surveying techniques, such as Terrestrial Laser Scanning (TLS), have just begun to be adopted as a method of obtaining detailed point cloud data to monitor topographical changes over short periods of time (weeks to months). However, the difficulties involved in comparing consecutive point cloud data sets in a complex three-dimensional plane, such as occlusion due to surface roughness and positioning of data capture point as a result of a consistently changing environment (a beach profile), mean that comparing data sets can lead to errors in the region of 10 - 20 cm. Meshing techniques are often used for point cloud data analysis for simple surfaces, but in surfaces such as rocky cliff faces, this technique has been found to be ineffective. Recession rates of hard rock coastlines in the UK are typically determined using aerial photography or airborne LiDAR data, yet the detail of the important changes occurring to the cliff face and toe are missed using such techniques. In this study we apply an algorithm (M3C2 - Multiscale Model to Model Cloud Comparison), initially developed for analysing fluvial morphological change, that directly compares point to point cloud data using surface normals that are consistent with surface roughness and measure the change that occurs along the normal direction (Lague et al., 2013). The surfaces changes are analysed using a set of user defined scales based on surface roughness and registration error. Once the correct parameters are defined, the volumetric cliff face changes are calculated by integrating the mean distance between the point clouds. The analysis has been undertaken at two hard rock sites identified for their active erosion located on the UK's south west peninsular at Porthleven in south west Cornwall and Godrevy in north Cornwall. Alongside TLS point cloud data, in

  9. Detecting Land Cover Change by Trend and Seasonality of Remote Sensing Time Series

    NASA Astrophysics Data System (ADS)

    Oliveira, J. C.; Epiphanio, J. N.; Mello, M. P.

    2013-05-01

    Natural resource managers demand knowledge of information on the spatiotemporal dynamics of land use and land cover change, and detection and characteristics change over time is an initial step for the understanding of the mechanism of change. The propose of this research is the use the approach BFAST (Breaks For Additive Seasonal and Trend) for detects trend and seasonal changes within Normalized Difference Vegetation Index (NDVI) time series. BFAST integrates the decomposition of time series into trend, seasonal, and noise components with methods for detecting change within time series without the need to select a reference period, set a threshold, or define a change trajectory. BFAST iteratively estimates the time and number of changes, and characterizes change by its magnitude and direction. The general model is of the form Yt = Tt + St + et (t= 1,2,3,…, n) where Yt is the observed data at time t, Tt is the trend component, St is the seasonal component, and et is the remainder component. In this study was used MODIS NDVI time series datasets (MOD13Q1) over 11 years (2000 - 2010) on an intensive agricultural area in Mato Grosso - Brazil. At first it was applied a filter for noise reduction (4253H twice) over spectral curve of each MODIS pixel, and subsequently each time series was decomposed into seasonal, trend, and remainder components by BFAST. Were detected one abrupt change from a single pixel of forest and two abrupt changes on trend component to a pixel of the agricultural area. Figure 1 shows the number of phonological change with base in seasonal component for study area. This paper demonstrated the ability of the BFAST to detect long-term phenological change by analyzing time series while accounting for abrupt and gradual changes. The algorithm iteratively estimates the dates and number of changes occurring within seasonal and trend components, and characterizes changes by extracting the magnitude and direction of change. Changes occurring in the

  10. Comparison of Pixel-Based and Object-Oriented Land Cover Change Detection Methods

    NASA Astrophysics Data System (ADS)

    Xie, Zhenlei; Shi, Ruoming; Zhu, Ling; Peng, Shu; Chen, Xu

    2016-06-01

    Change detection method is an efficient way in the aim of land cover product updating on the basis of the existing products, and at the same time saving lots of cost and time. Considering the object-oriented change detection method for 30m resolution Landsat image, analysis of effect of different segmentation scales on the method of the object-oriented is firstly carried out. On the other hand, for analysing the effectiveness and availability of pixel-based change method, the two indices which complement each other are the differenced Normalized Difference Vegetation Index (dNDVI), the Change Vector (CV) were used. To demonstrate the performance of pixel-based and object-oriented, accuracy assessment of these two change detection results will be conducted by four indicators which include overall accuracy, omission error, commission error and Kappa coefficient.

  11. Detecting Evidence of Climate Change in the Forests of the Eastern United States

    USGS Publications Warehouse

    Jones, John W.; Osborne, Jesse D.

    2008-01-01

    Changes in land use or disturbances such as defoliation by insects, disease, or fire all affect the composition and amount of tree canopy in a forest. These changes are easy to detect. Noticing and understanding the complex ways that global or regional-scale climate change combines with these disturbances to affect forest growth patterns and succession is difficult. This is particularly true for regions where changes in climate are not the most extreme, such as the mid-latitude forests of the Eastern United States. If land and water resources are to be managed responsibly, it is important to know how well the impacts of climate change on these forests can be measured in order to provide the best information possible to respond to any future changes. The goal of this study is to test whether climate-induced changes in forests in the Eastern United States can be detected and characterized using satellite imagery.

  12. TREFEX: Trend Estimation and Change Detection in the Response of MOX Gas Sensors

    PubMed Central

    Pashami, Sepideh; Lilienthal, Achim J.; Schaffernicht, Erik; Trincavelli, Marco

    2013-01-01

    Many applications of metal oxide gas sensors can benefit from reliable algorithms to detect significant changes in the sensor response. Significant changes indicate a change in the emission modality of a distant gas source and occur due to a sudden change of concentration or exposure to a different compound. As a consequence of turbulent gas transport and the relatively slow response and recovery times of metal oxide sensors, their response in open sampling configuration exhibits strong fluctuations that interfere with the changes of interest. In this paper we introduce TREFEX, a novel change point detection algorithm, especially designed for metal oxide gas sensors in an open sampling system. TREFEX models the response of MOX sensors as a piecewise exponential signal and considers the junctions between consecutive exponentials as change points. We formulate non-linear trend filtering and change point detection as a parameter-free convex optimization problem for single sensors and sensor arrays. We evaluate the performance of the TREFEX algorithm experimentally for different metal oxide sensors and several gas emission profiles. A comparison with the previously proposed GLR method shows a clearly superior performance of the TREFEX algorithm both in detection performance and in estimating the change time. PMID:23736853

  13. A simple and effective radiometric correction method to improve landscape change detection across sensors and across time

    USGS Publications Warehouse

    Chen, X.; Vierling, Lee; Deering, D.

    2005-01-01

    Satellite data offer unrivaled utility in monitoring and quantifying large scale land cover change over time. Radiometric consistency among collocated multi-temporal imagery is difficult to maintain, however, due to variations in sensor characteristics, atmospheric conditions, solar angle, and sensor view angle that can obscure surface change detection. To detect accurate landscape change using multi-temporal images, we developed a variation of the pseudoinvariant feature (PIF) normalization scheme: the temporally invariant cluster (TIC) method. Image data were acquired on June 9, 1990 (Landsat 4), June 20, 2000 (Landsat 7), and August 26, 2001 (Landsat 7) to analyze boreal forests near the Siberian city of Krasnoyarsk using the normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and reduced simple ratio (RSR). The temporally invariant cluster (TIC) centers were identified via a point density map of collocated pixel VIs from the base image and the target image, and a normalization regression line was created to intersect all TIC centers. Target image VI values were then recalculated using the regression function so that these two images could be compared using the resulting common radiometric scale. We found that EVI was very indicative of vegetation structure because of its sensitivity to shadowing effects and could thus be used to separate conifer forests from deciduous forests and grass/crop lands. Conversely, because NDVI reduced the radiometric influence of shadow, it did not allow for distinctions among these vegetation types. After normalization, correlations of NDVI and EVI with forest leaf area index (LAI) field measurements combined for 2000 and 2001 were significantly improved; the r 2 values in these regressions rose from 0.49 to 0.69 and from 0.46 to 0.61, respectively. An EVI "cancellation effect" where EVI was positively related to understory greenness but negatively related to forest canopy coverage was evident across a

  14. Continuous Change Detection and Classification (CCDC) of Land Cover Using All Available Landsat Data

    NASA Astrophysics Data System (ADS)

    Zhu, Z.; Woodcock, C. E.

    2012-12-01

    A new algorithm for Continuous Change Detection and Classification (CCDC) of land cover using all available Landsat data is developed. This new algorithm is capable of detecting many kinds of land cover change as new images are collected and at the same time provide land cover maps for any given time. To better identify land cover change, a two step cloud, cloud shadow, and snow masking algorithm is used for eliminating "noisy" observations. Next, a time series model that has components of seasonality, trend, and break estimates the surface reflectance and temperature. The time series model is updated continuously with newly acquired observations. Due to the high variability in spectral response for different kinds of land cover change, the CCDC algorithm uses a data-driven threshold derived from all seven Landsat bands. When the difference between observed and predicted exceeds the thresholds three consecutive times, a pixel is identified as land cover change. Land cover classification is done after change detection. Coefficients from the time series models and the Root Mean Square Error (RMSE) from model fitting are used as classification inputs for the Random Forest Classifier (RFC). We applied this new algorithm for one Landsat scene (Path 12 Row 31) that includes all of Rhode Island as well as much of Eastern Massachusetts and parts of Connecticut. A total of 532 Landsat images acquired between 1982 and 2011 were processed. During this period, 619,924 pixels were detected to change once (91% of total changed pixels) and 60,199 pixels were detected to change twice (8% of total changed pixels). The most frequent land cover change category is from mixed forest to low density residential which occupies more than 8% of total land cover change pixels.

  15. Lake sediment multi-taxon DNA from North Greenland records early post-glacial appearance of vascular plants and accurately tracks environmental changes

    NASA Astrophysics Data System (ADS)

    Epp, L. S.; Gussarova, G.; Boessenkool, S.; Olsen, J.; Haile, J.; Schrøder-Nielsen, A.; Ludikova, A.; Hassel, K.; Stenøien, H. K.; Funder, S.; Willerslev, E.; Kjær, K.; Brochmann, C.

    2015-06-01

    High Arctic environments are particularly sensitive to climate changes, but retrieval of paleoecological data is challenging due to low productivity and biomass. At the same time, Arctic soils and sediments have proven exceptional for long-term DNA preservation due to their constantly low temperatures. Lake sediments contain DNA paleorecords of the surrounding ecosystems and can be used to retrieve a variety of organismal groups from a single sample. In this study, we analyzed vascular plant, bryophyte, algal (in particular diatom) and copepod DNA retrieved from a sediment core spanning the Holocene, taken from Bliss Lake on the northernmost coast of Greenland. A previous multi-proxy study including microscopic diatom analyses showed that this lake experienced changes between marine and lacustrine conditions. We inferred the same environmental changes from algal DNA preserved in the sediment core. Our DNA record was stratigraphically coherent, with no indication of leaching between layers, and our cross-taxon comparisons were in accordance with previously inferred local ecosystem changes. Authentic ancient plant DNA was retrieved from nearly all layers, both from the marine and the limnic phases, and distinct temporal changes in plant presence were recovered. The plant DNA was mostly in agreement with expected vegetation history, but very early occurrences of vascular plants, including the woody Empetrum nigrum, document terrestrial vegetation very shortly after glacial retreat. Our study shows that multi-taxon metabarcoding of sedimentary ancient DNA from lake cores is a valuable tool both for terrestrial and aquatic paleoecology, even in low-productivity ecosystems such as the High Arctic.

  16. Object-Oriented Change Detection for Remote Sensing Images Based on Multi-Scale Fusion

    NASA Astrophysics Data System (ADS)

    Feng, Wenqing; Sui, Haigang; Tu, Jihui

    2016-06-01

    In the process of object-oriented change detection, the determination of the optimal segmentation scale is directly related to the subsequent change information extraction and analysis. Aiming at this problem, this paper presents a novel object-level change detection method based on multi-scale segmentation and fusion. First of all, the fine to coarse segmentation is used to obtain initial objects of different sizes; then, according to the features of the objects, Change Vector Analysis is used to obtain the change detection results of various scales. Furthermore, in order to improve the accuracy of change detection, this paper introduces fuzzy fusion and two kinds of decision level fusion methods to get the results of multi-scale fusion. Based on these methods, experiments are done with SPOT5 multi-spectral remote sensing imagery. Compared with pixel-level change detection methods, the overall accuracy of our method has been improved by nearly 10%, and the experimental results prove the feasibility and effectiveness of the fusion strategies.

  17. Detecting Brain State Changes via Fiber-Centered Functional Connectivity Analysis

    PubMed Central

    Li, Xiang; Lim, Chulwoo; Li, Kaiming; Guo, Lei; Liu, Tianming

    2013-01-01

    Diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) have been widely used to study structural and functional brain connectivity in recent years. A common assumption used in many previous functional brain connectivity studies is the temporal stationarity. However, accumulating literature evidence has suggested that functional brain connectivity is under temporal dynamic changes in different time scales. In this paper, a novel and intuitive approach is proposed to model and detect dynamic changes of functional brain states based on multimodal fMRI/DTI data. The basic idea is that functional connectivity patterns of all fiber-connected cortical voxels are concatenated into a descriptive functional feature vector to represent the brain’s state, and the temporal change points of brain states are decided by detecting the abrupt changes of the functional vector patterns via the sliding window approach. Our extensive experimental results have shown that meaningful brain state change points can be detected in task-based fMRI/DTI, resting state fMRI/DTI, and natural stimulus fMRI/DTI data sets. Particularly, the detected change points of functional brain states in task-based fMRI corresponded well to the external stimulus paradigm administered to the participating subjects, thus partially validating the proposed brain state change detection approach. The work in this paper provides novel perspective on the dynamic behaviors of functional brain connectivity and offers a starting point for future elucidation of the complex patterns of functional brain interactions and dynamics. PMID:22941508

  18. A novel approach for change detection from ICESat satellite laser altimetry - spatial and temporal pattern of Greenland Ice Sheet surface changes, 2003-2008

    NASA Astrophysics Data System (ADS)

    Csatho, B.; Schenk, T.; Babonis, G.; Nagarajan, S.; Krabill, W.

    2009-04-01

    The main objective of the ICESat satellite laser altimetry mission is to determine the mass balance of polar ice sheets and their contributions to current sea level changes. By measuring surface topography, ICESat also provides important boundary conditions for ice sheet and atmospheric modeling. To quantify surface elevation changes, to investigate their causes, and to improve predictive ice sheet models, accurate elevation changes on a seasonal, annual and inter-annual basis at scales of drainage basins and outlet glaciers are essential. Determining the spatial and temporal distribution of surface changes from repeat satellite laser altimetry remains a challenging problem, mainly because the footprints of repeat missions do not precisely overlap. We have developed a new method that is based on fitting analytical functions to laser points within repeat tracks or cross-over areas for estimating the ice sheet surface topography. The mathematical model of the change detection algorithm is based on the assumption that for a small surface area, e.g. 1 km by 1 km, only the absolute elevation changes over time but not the shape of the surface patch. Therefore, laser points of all time epochs of a small surface patch contribute to the shape parameters, and the laser points of each time period determine the absolute elevation of the surface patch at that period. The least squares adjustment delivers the surface elevation changes together with statistical information that is extremely helpful in judging how significant the elevation changes and the derived volume changes are. We demonstrate the feasibility of the proposed approach by reconstructing surface and volume changes of the Jakobshavn drainage basin in west Greenland. The accuracy of the surface change estimates derived from repeat ICESat measurements is verified by using NASA's Airborne Topographic Mapper (ATM) airborne laser altimetry. We then combine repeat ICESat and ATM laser altimetry and stereo satellite

  19. An Evaluation of New High-Resolution Image Collection and Processing Techniques for Estimating Shrub Cover and Detecting Landscape Changes

    SciTech Connect

    Hansen, D.J.; Ostler, W.K.

    2001-05-01

    Research funded by the U.S. Department of Defense (DoD), U.S. Department of Energy (DOE), and the U.S. Environmental Protection Agency as part of the Strategic Environmental Research and Development Program (SERDP) evaluated novel techniques for collecting and processing high-resolution images in the Mojave Desert. Several camera types, lens, films, and digital processing techniques were evaluated on the basis of their ability to correctly estimate canopy cover of shrubs. A high degree of accuracy was obtained with photo scales of 1:1000 to 1:4000 and flatbed scanning rates from films or prints of 300 lines per inch or larger. Smaller scale images were of value in detecting retrospective changes in cover of large shrubs, but failed to detect smaller shrubs. New image-processing software, typically used in light microscopy, forensics, and industrial engineering, make it possible to accurately measure areas for total cover of up to four dominant shrub species in minutes compared to hours or days of field work. Canopy cover and individual shrub parameters such as width, length, circumference, and shape factors can be readily measured yielding size distribution histograms and other statistical data on plant community structure. These novel techniques are being evaluated in a four-year study of military training impacts at Fort Irwin, California. Results will be compared among the new and conventional imagery and processing, including 1-meter (m) pixel IKONOS images. The new processes create georectified color-coded contour maps of shrub cover for use with Geographic Information System (GIS) software. The technique is a valuable new emerging tool to accurately assess vegetation structure and landscape changes due to military or other land-use disturbances.

  20. A novel method for detecting abrupt dynamic change based on the changing Hurst exponent of spatial images

    NASA Astrophysics Data System (ADS)

    He, Wen-Ping; Liu, Qun-Qun; Gu, Bin; Zhao, Shan-Shan

    2016-01-01

    The climate system is a classical spatiotemporal evolutionary dynamic system with spatiotemporal correlation characteristics. Based on this, two-dimensional detrended fluctuation analysis (TD-DFA) is used to estimate the Hurst exponent of two-dimensional images. Then, we monitored the change of the Hurst exponent of the images to identify an abrupt dynamic change. We tested the performance of this method with a coupled spatiotemporal dynamic model and found that it works well. The changes in the Hurst exponents of the spatial images are stable when there is no dynamic change in the system, but there will be a clear non-stationary change of the Hurst exponents; for example, the abrupt mean values change if the dynamics of the system change. Thus, the TD-DFA method is suitable for detecting an abrupt dynamic change from natural and artificial images. The spatial images of the NCEP reanalysis of the daily average temperature exhibited fractality. Based on this, we found three non-stationary changes in the Hurst exponents for the NCEP reanalysis of the daily average temperature or for the annual average temperature in the region (60°S-60°N). It can be concluded that the climate system may have incurred three dynamic changes since 1961 on decadal timescales, i.e., in approximately the mid-1970s, the mid-1980s, and between the late 1990s and the early 2000s.

  1. Detectability of change in winter precipitation within mountain landscapes: Spatial patterns and uncertainty

    NASA Astrophysics Data System (ADS)

    Silverman, N. L.; Maneta, M. P.

    2016-06-01

    Detecting long-term change in seasonal precipitation using ground observations is dependent on the representativity of the point measurement to the surrounding landscape. In mountainous regions, representativity can be poor and lead to large uncertainties in precipitation estimates at high elevations or in areas where observations are sparse. If the uncertainty in the estimate is large compared to the long-term shifts in precipitation, then the change will likely go undetected. In this analysis, we examine the minimum detectable change across mountainous terrain in western Montana, USA. We ask the question: What is the minimum amount of change that is necessary to be detected using our best estimates of precipitation in complex terrain? We evaluate the spatial uncertainty in the precipitation estimates by conditioning historic regional climate model simulations to ground observations using Bayesian inference. By using this uncertainty as a null hypothesis, we test for detectability across the study region. To provide context for the detectability calculations, we look at a range of future scenarios from the Coupled Model Intercomparison Project 5 (CMIP5) multimodel ensemble downscaled to 4 km resolution using the MACAv2-METDATA data set. When using the ensemble averages we find that approximately 65% of the significant increases in winter precipitation go undetected at midelevations. At high elevation, approximately 75% of significant increases in winter precipitation are undetectable. Areas where change can be detected are largely controlled by topographic features. Elevation and aspect are key characteristics that determine whether or not changes in winter precipitation can be detected. Furthermore, we find that undetected increases in winter precipitation at high elevation will likely remain as snow under climate change scenarios. Therefore, there is potential for these areas to offset snowpack loss at lower elevations and confound the effects of climate change

  2. Metabolic changes assessed by MRS accurately reflect brain function during drug-induced epilepsy in mice in contrast to fMRI-based hemodynamic readouts.

    PubMed

    Seuwen, Aline; Schroeter, Aileen; Grandjean, Joanes; Rudin, Markus

    2015-10-15

    Functional proton magnetic resonance spectroscopy (1H-MRS) enables the non-invasive assessment of neural activity by measuring signals arising from endogenous metabolites in a time resolved manner. Proof-of-principle of this approach has been demonstrated in humans and rats; yet functional 1H-MRS has not been applied in mice so far, although it would be of considerable interest given the many genetically engineered models of neurological disorders established in this species only. Mouse 1H-MRS is challenging as the high demands on spatial resolution typically result in long data acquisition times not commensurable with functional studies. Here, we propose an approach based on spectroscopic imaging in combination with the acquisition of the free induction decay to maximize signal intensity. Highly resolved metabolite maps have been recorded from mouse brain with 12 min temporal resolution. This enabled monitoring of metabolic changes following the administration of bicuculline, a GABA-A receptor antagonist. Changes in levels of metabolites involved in energy metabolism (lactate and phosphocreatine) and neurotransmitters (glutamate) were investigated in a region-dependent manner and shown to scale with the bicuculline dose. GABAergic inhibition induced spectral changes characteristic for increased neurotransmitter turnover and oxidative stress. In contrast to metabolic readouts, BOLD and CBV fMRI responses did not scale with the bicuculline dose indicative of the failure of neurovascular coupling. Nevertheless fMRI measurements supported the notion of increased oxidative stress revealed by functional MRS. Hence, the combined analysis of metabolic and hemodynamic changes in response to stimulation provides complementary insight into processes associated with neural activity. PMID:26166624

  3. Integrated data processing of remotely sensed and vector data for building change detection

    NASA Astrophysics Data System (ADS)

    Sofina, N.; Ehlers, M.; Michel, U.

    2012-10-01

    In recent years natural disasters have had an increasing impact leading to tremendous economic and human losses. Remote sensing technologies are being used more often for rapid detection and visualization of changes in the affected areas, providing essential information for damage assessment, planning and coordination of recovery activities. This study presents a GIS-based approach for the detection of damaged buildings. The methodology is based on the integrated analysis of vector data containing information about the original urban layout and remotely sensed images obtained after a catastrophic event. For the classification of building integrity a new `Detected Part of Contour' (DPC) feature was developed. The DPC feature defines a part of the building contour that can be detected in the related remotely sensed image. It reaches maximum value (100%) if the investigated building contour is intact. Next, several features based on the analysis of textural information of the remotely sensed image are considered. Finally, a binary classification of building conditions concludes the change detection analysis. The proposed method was applied to the 2010 earthquake in Qinghai (China). The results indicate that a GIS-based analysis can markedly improve the accuracy of change detection analysis. The proposed methodology has been developed solely within the Open Source Software environment (GRASS GIS, Python, Orange). The employment of Open Source Software provides the way for an innovative, flexible and costeffective implementation of change detection operations.