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Sample records for greatly improved detection

  1. Modeling detection probability to improve marsh bird surveys in southern Canada and the Great Lakes states

    Directory of Open Access Journals (Sweden)

    Douglas C. Tozer

    2016-12-01

    Full Text Available Marsh birds are notoriously elusive, with variation in detection probability across species, regions, seasons, and different times of day and weather. Therefore, it is important to develop regional field survey protocols that maximize detections, but that also produce data for estimating and analytically adjusting for remaining differences in detections. We aimed to improve regional field survey protocols by estimating detection probability of eight elusive marsh bird species throughout two regions that have ongoing marsh bird monitoring programs: the southern Canadian Prairies (Prairie region and the southern portion of the Great Lakes basin and parts of southern Québec (Great Lakes-St. Lawrence region. We accomplished our goal using generalized binomial N-mixture models and data from ~22,300 marsh bird surveys conducted between 2008 and 2014 by Bird Studies Canada's Prairie, Great Lakes, and Québec Marsh Monitoring Programs. Across all species, on average, detection probability was highest in the Great Lakes-St. Lawrence region from the beginning of May until mid-June, and then fell throughout the remainder of the season until the end of June; was lowest in the Prairie region in mid-May and then increased throughout the remainder of the season until the end of June; was highest during darkness compared with light; and did not vary significantly according to temperature (range: 0-30°C, cloud cover (0%-100%, or wind (0-20 kph, or during morning versus evening. We used our results to formulate improved marsh bird survey protocols for each region. Our analysis and recommendations are useful and contribute to conservation of wetland birds at various scales from local single-species studies to the continental North American Marsh Bird Monitoring Program.

  2. Improved Motion Estimation Using Early Zero-Block Detection

    Directory of Open Access Journals (Sweden)

    Y. Lin

    2008-07-01

    Full Text Available We incorporate the early zero-block detection technique into the UMHexagonS algorithm, which has already been adopted in H.264/AVC JM reference software, to speed up the motion estimation process. A nearly sufficient condition is derived for early zero-block detection. Although the conventional early zero-block detection method can achieve significant improvement in computation reduction, the PSNR loss, to whatever extent, is not negligible especially for high quantization parameter (QP or low bit-rate coding. This paper modifies the UMHexagonS algorithm with the early zero-block detection technique to improve its coding performance. The experimental results reveal that the improved UMHexagonS algorithm greatly reduces computation while maintaining very high coding efficiency.

  3. The detection of great crested newts year round via environmental DNA analysis.

    Science.gov (United States)

    Rees, Helen C; Baker, Claire A; Gardner, David S; Maddison, Ben C; Gough, Kevin C

    2017-07-26

    Analysis of environmental DNA (eDNA) is a method that has been used for the detection of various species within water bodies. The great crested newt (Triturus cristatus) has a short eDNA survey season (mid-April to June). Here we investigate whether this season could be extended into other months using the current methodology as stipulated by Natural England. Here we present data to show that in monthly water samples taken from two ponds (March 2014-February 2015) we were able to detect great crested newt DNA in all months in at least one of the ponds. Similar levels of great crested newt eDNA (i.e. highly positive identification) were detected through the months of March-August, suggesting it may be possible to extend the current survey window. In order to determine how applicable these observations are for ponds throughout the rest of the UK, further work in multiple other ponds over multiple seasons is suggested. Nevertheless, the current work clearly demonstrates, in two ponds, the efficacy and reproducibility of eDNA detection for determining the presence of great crested newts.

  4. Improved immunocytochemical detection of daunomycin

    DEFF Research Database (Denmark)

    Ohara, Koji; Shin, Masashi; Larsson, Lars-Inge

    2007-01-01

    and mitochondria of heart muscle cells may help to improve our understanding of the cardiac toxicity of DM and related anthracyclin antibiotics. A number of ELISA tests were carried out in order to elucidate the mechanisms of H2O2-assisted antigen retrieval. A possible mechanism is that DM is reduced and converted......Improved immunocytochemical (ICC) detection of the anthracycline anticancer antibiotic daunomycin (DM) has been achieved by used of hydrogen peroxide oxidation prior to ICC staining for DM. The new method greatly enhanced the localization of DM accumulation in cardiac, smooth and skeletal muscle...... to its semiquinone and/or hydroquinone derivative in vivo. Oxidation by hydrogen peroxide acts to convert these derivatives back to the native antigen. The improved ICC methodology using oxidation to recreated native antigens from reduced metabolites may be helpful also with respect to the localization...

  5. Derivatizations for improved detection of alcohols by gas chromatography and photoionization detection (GC-PID)

    International Nuclear Information System (INIS)

    Krull, I.S.; Swartz, M.; Driscoll, J.N.

    1984-01-01

    Pentafluorophenyldimethylsilyl chloride (flophemesyl chloride, Fl) is a well known derivatization reagent for improved electron capture detection (ECD) in gas chromatography (GC)(GC-ECD), but it has never been utilized for improved detectability and sensitivity in GC-photoionization detection (GC-PID). A wide variety of flophemesyl alcohol derivatives have been used in order to show a new approach for realizing greatly reduced minimum detection limits (MDL) of virtually all alcohol derivatives in GC-PID analysis. This particular derivatization approach is inexpensive and easy to apply, leading to quantitative or near 100% conversion of the starting alcohols to the expected flophemesyl ethers (silyl ethers). Detection limits can be lowered by 2-3 orders of magnitude for such derivatives when compared with the starting alcohols, along with calibration plots that are linear over 5-7 orders of magnitude. Specific GC conditions have been developed for many flophemesyl derivatives, in all cases using packed columns. Both ECD and PID relative response factors (RRFs) and normalized RRFs have been determined, and such ratios can now be used for improved analytic identification from complex sample matrices, where appropriate. 28 references, 2 figures, 5 tables

  6. Bayesian image reconstruction for improving detection performance of muon tomography.

    Science.gov (United States)

    Wang, Guobao; Schultz, Larry J; Qi, Jinyi

    2009-05-01

    Muon tomography is a novel technology that is being developed for detecting high-Z materials in vehicles or cargo containers. Maximum likelihood methods have been developed for reconstructing the scattering density image from muon measurements. However, the instability of maximum likelihood estimation often results in noisy images and low detectability of high-Z targets. In this paper, we propose using regularization to improve the image quality of muon tomography. We formulate the muon reconstruction problem in a Bayesian framework by introducing a prior distribution on scattering density images. An iterative shrinkage algorithm is derived to maximize the log posterior distribution. At each iteration, the algorithm obtains the maximum a posteriori update by shrinking an unregularized maximum likelihood update. Inverse quadratic shrinkage functions are derived for generalized Laplacian priors and inverse cubic shrinkage functions are derived for generalized Gaussian priors. Receiver operating characteristic studies using simulated data demonstrate that the Bayesian reconstruction can greatly improve the detection performance of muon tomography.

  7. Quantifying seining detection probability for fishes of Great Plains sand‐bed rivers

    Science.gov (United States)

    Mollenhauer, Robert; Logue, Daniel R.; Brewer, Shannon K.

    2018-01-01

    Species detection error (i.e., imperfect and variable detection probability) is an essential consideration when investigators map distributions and interpret habitat associations. When fish detection error that is due to highly variable instream environments needs to be addressed, sand‐bed streams of the Great Plains represent a unique challenge. We quantified seining detection probability for diminutive Great Plains fishes across a range of sampling conditions in two sand‐bed rivers in Oklahoma. Imperfect detection resulted in underestimates of species occurrence using naïve estimates, particularly for less common fishes. Seining detection probability also varied among fishes and across sampling conditions. We observed a quadratic relationship between water depth and detection probability, in which the exact nature of the relationship was species‐specific and dependent on water clarity. Similarly, the direction of the relationship between water clarity and detection probability was species‐specific and dependent on differences in water depth. The relationship between water temperature and detection probability was also species dependent, where both the magnitude and direction of the relationship varied among fishes. We showed how ignoring detection error confounded an underlying relationship between species occurrence and water depth. Despite imperfect and heterogeneous detection, our results support that determining species absence can be accomplished with two to six spatially replicated seine hauls per 200‐m reach under average sampling conditions; however, required effort would be higher under certain conditions. Detection probability was low for the Arkansas River Shiner Notropis girardi, which is federally listed as threatened, and more than 10 seine hauls per 200‐m reach would be required to assess presence across sampling conditions. Our model allows scientists to estimate sampling effort to confidently assess species occurrence, which

  8. Improving Probe Immobilization for Label-Free Capacitive Detection of DNA Hybridization on Microfabricated Gold Electrodes

    Directory of Open Access Journals (Sweden)

    Sandro Carrara

    2008-02-01

    Full Text Available Alternative approaches to labeled optical detection for DNA arrays are actively investigated for low-cost point-of-care applications. In this domain, label-free capacitive detection is one of the most intensely studied techniques. It is based on the idea to detect the Helmholtz ion layer displacements when molecular recognition occurs at the electrodes/solution interface. The sensing layer is usually prepared by using thiols terminated DNA single-strength oligonucleotide probes on top of the sensor electrodes. However, published data shows evident time drift, which greatly complicates signal conditioning and processing and ultimately increases the uncertainty in DNA recognition sensing. The aim of this work is to show that newly developed ethylene-glycol functionalized alkanethiols greatly reduce time drift, thereby significantly improving capacitance based label-free detection of DNA.

  9. Improving PET spatial resolution and detectability for prostate cancer imaging

    International Nuclear Information System (INIS)

    Bal, H; Guerin, L; Casey, M E; Conti, M; Eriksson, L; Michel, C; Fanti, S; Pettinato, C; Adler, S; Choyke, P

    2014-01-01

    Prostate cancer, one of the most common forms of cancer among men, can benefit from recent improvements in positron emission tomography (PET) technology. In particular, better spatial resolution, lower noise and higher detectability of small lesions could be greatly beneficial for early diagnosis and could provide a strong support for guiding biopsy and surgery. In this article, the impact of improved PET instrumentation with superior spatial resolution and high sensitivity are discussed, together with the latest development in PET technology: resolution recovery and time-of-flight reconstruction. Using simulated cancer lesions, inserted in clinical PET images obtained with conventional protocols, we show that visual identification of the lesions and detectability via numerical observers can already be improved using state of the art PET reconstruction methods. This was achieved using both resolution recovery and time-of-flight reconstruction, and a high resolution image with 2 mm pixel size. Channelized Hotelling numerical observers showed an increase in the area under the LROC curve from 0.52 to 0.58. In addition, a relationship between the simulated input activity and the area under the LROC curve showed that the minimum detectable activity was reduced by more than 23%. (paper)

  10. Nanobarcoding for improved nanoparticle detection in nanomedical biodistribution studies

    Science.gov (United States)

    Eustaquio, Trisha

    Determination of the fate of nanoparticles (NPs) in a biological system, or NP biodistribution, is critical in evaluating a NP formulation for nanomedicine. Unlike small-molecule drugs, NPs impose unique challenges in the design of appropriate biodistribution studies due to their small size and subsequent detection signal. Current methods to determine NP biodistribution are greatly inadequate due to their limited detection thresholds. There is an overwhelming need for a sensitive and efficient imaging-based method that can (1) detect and measure small numbers of NPs of various types, ideally single NPs, (2) associate preferential NP uptake with histological cell type by preserving spatial information in samples, and (3) allow for relatively quick and accurate NP detection in in vitro (and possibly ex vivo) samples for comprehensive NP biodistribution studies. Herein, a novel method for improved NP detection is proposed, coined "nanobarcoding." Nanobarcoding utilizes a non-endogenous oligonucleotide, or "nanobarcode" (NB), conjugated to the NP surface to amplify the detection signal from a single NP via in situ polymerase chain reaction (ISPCR), and this signal amplification will facilitate rapid and precise detection of single NPs inside cells over large areas of sample such that more sophisticated studies can be performed on the NP-positive subpopulation. Moreover, nanobarcoding has the potential to be applied to the detection of more than one NP type to study the effects of physicochemical properties, targeting mechanisms, and route of entry on NP biodistribution. The nanobarcoding method was validated in vitro using NB-functionalized superparamagnetic iron oxide NPs (NB-SPIONs) as the model NP type for improved NP detection inside HeLa human cervical cancer cells, a cell line commonly used for ISPCR-mediated detection of human papilloma virus (HPV). Nanotoxicity effects of NB-SPIONs were also evaluated at the single-cell level using LEAP (Laser-Enabled Analysis

  11. 100 ways to make good photos great tips & techniques for improving your digital photography

    CERN Document Server

    Cope, Peter

    2013-01-01

    A practical, accessible guide to turning your good photographs into great ones whether you are shooting on the latest digital SLR or a camera phone! Discover 100 simple and fun ways to improve your photographs both in-camera and through post-processing image manipulation. Every key photographic genre is covered, from perfect portraits and the great outdoors, to travel photos and shooting at night. Filled with inspirational examples of great photographs compared against the more average images, with easy to follow techniques for how you can achieve the same results.

  12. Imaging of underground karst water channels using an improved multichannel transient Rayleigh wave detecting method.

    Science.gov (United States)

    Zheng, Xuhui; Liu, Lei; Sun, Jinzhong; Li, Gao; Zhou, Fubiao; Xu, Jiemin

    2018-01-01

    Geological and hydrogeological conditions in karst areas are complicated from the viewpoint of engineering. The construction of underground structures in these areas is often disturbed by the gushing of karst water, which may delay the construction schedule, result in economic losses, and even cause heavy casualties. In this paper, an innovative method of multichannel transient Rayleigh wave detecting is proposed by introducing the concept of arrival time difference phase between channels (TDP). Overcoming the restriction of the space-sampling law, the proposed method can extract the phase velocities of different frequency components from only two channels of transient Rayleigh wave recorded on two adjacent detecting points. This feature greatly improves the work efficiency and lateral resolution of transient Rayleigh wave detecting. The improved multichannel transient Rayleigh wave detecting method is applied to the detection of karst caves and fractures in rock mass of the foundation pit of Yan'an Road Station of Guiyang Metro. The imaging of the detecting results clearly reveals the distribution of karst water inflow channels, which provided significant guidance for water plugging and enabled good control over karst water gushing in the foundation pit.

  13. Great cormorants (Phalacrocorax carbo) can detect auditory cues while diving

    DEFF Research Database (Denmark)

    Hansen, Kirstin Anderson; Maxwell, Alyssa; Siebert, Ursula

    2017-01-01

    In-air hearing in birds has been thoroughly investigated. Sound provides birds with auditory information for species and individual recognition from their complex vocalizations, as well as cues while foraging and for avoiding predators. Some 10% of existing species of birds obtain their food under...... the water surface. Whether some of these birds make use of acoustic cues while underwater is unknown. An interesting species in this respect is the great cormorant (Phalacrocorax carbo), being one of the most effective marine predators and relying on the aquatic environment for food year round. Here, its...... underwater hearing abilities were investigated using psychophysics, where the bird learned to detect the presence or absence of a tone while submerged. The greatest sensitivity was found at 2 kHz, with an underwater hearing threshold of 71 dB re 1 μPa rms. The great cormorant is better at hearing underwater...

  14. Improving battery safety by early detection of internal shorting with a bifunctional separator

    Science.gov (United States)

    Wu, Hui; Zhuo, Denys; Kong, Desheng; Cui, Yi

    2014-10-01

    Lithium-based rechargeable batteries have been widely used in portable electronics and show great promise for emerging applications in transportation and wind-solar-grid energy storage, although their safety remains a practical concern. Failures in the form of fire and explosion can be initiated by internal short circuits associated with lithium dendrite formation during cycling. Here we report a new strategy for improving safety by designing a smart battery that allows internal battery health to be monitored in situ. Specifically, we achieve early detection of lithium dendrites inside batteries through a bifunctional separator, which offers a third sensing terminal in addition to the cathode and anode. The sensing terminal provides unique signals in the form of a pronounced voltage change, indicating imminent penetration of dendrites through the separator. This detection mechanism is highly sensitive, accurate and activated well in advance of shorting and can be applied to many types of batteries for improved safety.

  15. Great cormorants ( Phalacrocorax carbo) can detect auditory cues while diving

    Science.gov (United States)

    Hansen, Kirstin Anderson; Maxwell, Alyssa; Siebert, Ursula; Larsen, Ole Næsbye; Wahlberg, Magnus

    2017-06-01

    In-air hearing in birds has been thoroughly investigated. Sound provides birds with auditory information for species and individual recognition from their complex vocalizations, as well as cues while foraging and for avoiding predators. Some 10% of existing species of birds obtain their food under the water surface. Whether some of these birds make use of acoustic cues while underwater is unknown. An interesting species in this respect is the great cormorant ( Phalacrocorax carbo), being one of the most effective marine predators and relying on the aquatic environment for food year round. Here, its underwater hearing abilities were investigated using psychophysics, where the bird learned to detect the presence or absence of a tone while submerged. The greatest sensitivity was found at 2 kHz, with an underwater hearing threshold of 71 dB re 1 μPa rms. The great cormorant is better at hearing underwater than expected, and the hearing thresholds are comparable to seals and toothed whales in the frequency band 1-4 kHz. This opens up the possibility of cormorants and other aquatic birds having special adaptations for underwater hearing and making use of underwater acoustic cues from, e.g., conspecifics, their surroundings, as well as prey and predators.

  16. Optimal Seamline Detection for Orthoimage Mosaicking Based on DSM and Improved JPS Algorithm

    Directory of Open Access Journals (Sweden)

    Gang Chen

    2018-05-01

    Full Text Available Based on the digital surface model (DSM and jump point search (JPS algorithm, this study proposed a novel approach to detect the optimal seamline for orthoimage mosaicking. By threshold segmentation, DSM was first identified as ground regions and obstacle regions (e.g., buildings, trees, and cars. Then, the mathematical morphology method was used to make the edge of obstacles more prominent. Subsequently, the processed DSM was considered as a uniform-cost grid map, and the JPS algorithm was improved and employed to search for key jump points in the map. Meanwhile, the jump points would be evaluated according to an optimized function, finally generating a minimum cost path as the optimal seamline. Furthermore, the search strategy was modified to avoid search failure when the search map was completely blocked by obstacles in the search direction. Comparison of the proposed method and the Dijkstra’s algorithm was carried out based on two groups of image data with different characteristics. Results showed the following: (1 the proposed method could detect better seamlines near the centerlines of the overlap regions, crossing far fewer ground objects; (2 the efficiency and resource consumption were greatly improved since the improved JPS algorithm skips many image pixels without them being explicitly evaluated. In general, based on DSM, the proposed method combining threshold segmentation, mathematical morphology, and improved JPS algorithms was helpful for detecting the optimal seamline for orthoimage mosaicking.

  17. On the possibility of improving the sensitivity of dark-matter detection

    Energy Technology Data Exchange (ETDEWEB)

    Paschos, E.A.; Pilaftsis, A. (Dortmund Univ. (Germany, F.R.). Inst. fuer Physik); Zioutas, K. (Thessaloniki Univ. (Greece). Nuclear and Elementary Particle Physics Section)

    1990-02-22

    First we investigate the detectability of nuclear magnetic transitions produced by dark-matter particles. The M1 transitions are mediated by spin-dependent interactions between dark matter and nuclei. We assume that the dark matter consists mainly of photinos, and show that the expected rate is of the order of 1 event/kg/d for the excitation of nuclear magnetic states accompanied also by a recoiling nucleus. The de-excitation decay that follows, {approx equal} (ms-{mu}s), might later be observed as electromagnetic radiation in the GHz region in future, more sensitive, microwave devices. Secondly, we propose to utilize liquid-xenon detectors for measuring the energy of the recoiling nucleus, either through the Xe odd-isotopes or through other mixed atoms, such as hydrogen, with lowest masses. Furthermore the mass scale of these calorimeters (1-100 t) gives a greatly improved sensitivity for darkmatter detection compared with other conventional systems. (orig.).

  18. Exploiting Habitat and Gear Patterns for Efficient Detection of Rare and Non-native Benthos and Fish in Great Lakes Coastal ecosystems

    Science.gov (United States)

    There is at present no comprehensive early-detection monitoring for exotic species in the Great Lakes, despite their continued arrival and impacts and recognition that early detection is key to effective management. We evaluated strategies for efficient early-detection monitorin...

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

    Science.gov (United States)

    Macy, Marisa; Marks, Kevin; Towle, Alexander

    2014-01-01

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

  20. Improved Detection of Human Respiration Using Data Fusion Basedon a Multistatic UWB Radar

    Directory of Open Access Journals (Sweden)

    Hao Lv

    2016-09-01

    Full Text Available This paper investigated the feasibility for improved detection of human respiration using data fusion based on a multistatic ultra-wideband (UWB radar. UWB-radar-based respiration detection is an emerging technology that has great promise in practice. It can be applied to remotely sense the presence of a human target for through-wall surveillance, post-earthquake search and rescue, etc. In these applications, a human target’s position and posture are not known a priori. Uncertainty of the two factors results in a body orientation issue of UWB radar, namely the human target’s thorax is not always facing the radar. Thus, the radial component of the thorax motion due to respiration decreases and the respiratory motion response contained in UWB radar echoes is too weak to be detected. To cope with the issue, this paper used multisensory information provided by the multistatic UWB radar, which took the form of impulse radios and comprised one transmitting and four separated receiving antennas. An adaptive Kalman filtering algorithm was then designed to fuse the UWB echo data from all the receiving channels to detect the respiratory-motion response contained in those data. In the experiment, a volunteer’s respiration was correctly detected when he curled upon a camp bed behind a brick wall. Under the same scenario, the volunteer’s respiration was detected based on the radar’s single transmitting-receiving channels without data fusion using conventional algorithm, such as adaptive line enhancer and single-channel Kalman filtering. Moreover, performance of the data fusion algorithm was experimentally investigated with different channel combinations and antenna deployments. The experimental results show that the body orientation issue for human respiration detection via UWB radar can be dealt well with the multistatic UWB radar and the Kalman-filter-based data fusion, which can be applied to improve performance of UWB radar in real applications.

  1. Improving Face Detection with TOE Cameras

    DEFF Research Database (Denmark)

    Hansen, Dan Witzner; Larsen, Rasmus; Lauze, F

    2007-01-01

    A face detection method based on a boosted classifier using images from a time-of-flight sensor is presented. We show that the performance of face detection can be improved when using both depth and gray scale images and that the common use of integration of hypotheses for verification can...... be relaxed. Based on the detected face we employ an active contour method on depth images for full head segmentation....

  2. An improved early detection method of type-2 diabetes mellitus using multiple classifier system

    KAUST Repository

    Zhu, Jia

    2015-01-01

    The specific causes of complex diseases such as Type-2 Diabetes Mellitus (T2DM) have not yet been identified. Nevertheless, many medical science researchers believe that complex diseases are caused by a combination of genetic, environmental, and lifestyle factors. Detection of such diseases becomes an issue because it is not free from false presumptions and is accompanied by unpredictable effects. Given the greatly increased amount of data gathered in medical databases, data mining has been used widely in recent years to detect and improve the diagnosis of complex diseases. However, past research showed that no single classifier can be considered optimal for all problems. Therefore, in this paper, we focus on employing multiple classifier systems to improve the accuracy of detection for complex diseases, such as T2DM. We proposed a dynamic weighted voting scheme called multiple factors weighted combination for classifiers\\' decision combination. This method considers not only the local and global accuracy but also the diversity among classifiers and localized generalization error of each classifier. We evaluated our method on two real T2DM data sets and other medical data sets. The favorable results indicated that our proposed method significantly outperforms individual classifiers and other fusion methods.

  3. Apriori-based network intrusion detection system

    International Nuclear Information System (INIS)

    Wang Wenjin; Liu Junrong; Liu Baoxu

    2012-01-01

    With the development of network communication technology, more and more social activities run by Internet. In the meantime, the network information security is getting increasingly serious. Intrusion Detection System (IDS) has greatly improved the general security level of whole network. But there are still many problem exists in current IDS, e.g. high leak rate detection/false alarm rates and feature library need frequently upgrade. This paper presents an association-rule based IDS. This system can detect unknown attack by generate rules from training data. Experiment in last chapter proved the system has great accuracy on unknown attack detection. (authors)

  4. QRS Detection Based on Improved Adaptive Threshold

    Directory of Open Access Journals (Sweden)

    Xuanyu Lu

    2018-01-01

    Full Text Available Cardiovascular disease is the first cause of death around the world. In accomplishing quick and accurate diagnosis, automatic electrocardiogram (ECG analysis algorithm plays an important role, whose first step is QRS detection. The threshold algorithm of QRS complex detection is known for its high-speed computation and minimized memory storage. In this mobile era, threshold algorithm can be easily transported into portable, wearable, and wireless ECG systems. However, the detection rate of the threshold algorithm still calls for improvement. An improved adaptive threshold algorithm for QRS detection is reported in this paper. The main steps of this algorithm are preprocessing, peak finding, and adaptive threshold QRS detecting. The detection rate is 99.41%, the sensitivity (Se is 99.72%, and the specificity (Sp is 99.69% on the MIT-BIH Arrhythmia database. A comparison is also made with two other algorithms, to prove our superiority. The suspicious abnormal area is shown at the end of the algorithm and RR-Lorenz plot drawn for doctors and cardiologists to use as aid for diagnosis.

  5. GREAT: a web portal for Genome Regulatory Architecture Tools.

    Science.gov (United States)

    Bouyioukos, Costas; Bucchini, François; Elati, Mohamed; Képès, François

    2016-07-08

    GREAT (Genome REgulatory Architecture Tools) is a novel web portal for tools designed to generate user-friendly and biologically useful analysis of genome architecture and regulation. The online tools of GREAT are freely accessible and compatible with essentially any operating system which runs a modern browser. GREAT is based on the analysis of genome layout -defined as the respective positioning of co-functional genes- and its relation with chromosome architecture and gene expression. GREAT tools allow users to systematically detect regular patterns along co-functional genomic features in an automatic way consisting of three individual steps and respective interactive visualizations. In addition to the complete analysis of regularities, GREAT tools enable the use of periodicity and position information for improving the prediction of transcription factor binding sites using a multi-view machine learning approach. The outcome of this integrative approach features a multivariate analysis of the interplay between the location of a gene and its regulatory sequence. GREAT results are plotted in web interactive graphs and are available for download either as individual plots, self-contained interactive pages or as machine readable tables for downstream analysis. The GREAT portal can be reached at the following URL https://absynth.issb.genopole.fr/GREAT and each individual GREAT tool is available for downloading. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  6. Multiple strategies to improve sensitivity, speed and robustness of isothermal nucleic acid amplification for rapid pathogen detection

    Directory of Open Access Journals (Sweden)

    Lemieux Bertrand

    2011-05-01

    Full Text Available Abstract Background In the past decades the rapid growth of molecular diagnostics (based on either traditional PCR or isothermal amplification technologies meet the demand for fast and accurate testing. Although isothermal amplification technologies have the advantages of low cost requirements for instruments, the further improvement on sensitivity, speed and robustness is a prerequisite for the applications in rapid pathogen detection, especially at point-of-care diagnostics. Here, we describe and explore several strategies to improve one of the isothermal technologies, helicase-dependent amplification (HDA. Results Multiple strategies were approached to improve the overall performance of the isothermal amplification: the restriction endonuclease-mediated DNA helicase homing, macromolecular crowding agents, and the optimization of reaction enzyme mix. The effect of combing all strategies was compared with that of the individual strategy. With all of above methods, we are able to detect 50 copies of Neisseria gonorrhoeae DNA in just 20 minutes of amplification using a nearly instrument-free detection platform (BESt™ cassette. Conclusions The strategies addressed in this proof-of-concept study are independent of expensive equipments, and are not limited to particular primers, targets or detection format. However, they make a large difference in assay performance. Some of them can be adjusted and applied to other formats of nucleic acid amplification. Furthermore, the strategies to improve the in vitro assays by maximally simulating the nature conditions may be useful in the general field of developing molecular assays. A new fast molecular assay for Neisseria gonorrhoeae has also been developed which has great potential to be used at point-of-care diagnostics.

  7. RASW : a Run-time Adaptive Sliding Window to Improve Viola-Jones object detection.

    NARCIS (Netherlands)

    Comaschi, F.; Stuijk, S.; Basten, T.; Corporaal, H.

    2013-01-01

    Abstract—In recent years accurate algorithms for detecting objects in images have been developed. Among these algorithms, the object detection scheme proposed by Viola and Jones gained great popularity, especially after the release of high-quality face classifiers by the OpenCV group. However, as

  8. The great chemical residue detection debate: dog versus machine

    Science.gov (United States)

    Tripp, Alan C.; Walker, James C.

    2003-09-01

    Many engineering groups desire to construct instrumentation to replace dog-handler teams in identifying and localizing chemical mixtures. This goal requires performance specifications for an "artificial dog-handler team". Progress toward generating such specifications from laboratory tests of dog-handler teams has been made recently at the Sensory Research Institute, and the method employed is amenable to the measurement of tasks representative of the decision-making that must go on when such teams solve problems in actual (and therefore informationally messy) situations. As progressively more quantitative data are obtained on progressively more complex odor tasks, the boundary conditions of dog-handler performance will be understood in great detail. From experiments leading to this knowledge, one ca develop, as we do in this paper, a taxonomy of test conditions that contain various subsets of the variables encountered in "real world settings". These tests provide the basis for the rigorous testing that will provide an improved basis for deciding when biological sensing approaches (e.g. dog-handler teams) are best and when "artificial noses" are most valuable.

  9. Summary of Great East Japan Earthquake response at Onagawa Nuclear Power Station and further safety improvement measures

    International Nuclear Information System (INIS)

    Sato, Toru

    2013-01-01

    A large earthquake occurred on March 11, 2011 and tsunami was generated following it. The East Japan suffered serious damage by the earthquake and tsunami. This is called the Great East Japan Earthquake. Onagawa Nuclear Power Station (NPS) is located closest to the epicenter of Great East Japan Earthquake. We experienced intense shake by the earthquake and some flooding from the tsunami, however, we have succeeded safely cold shutdown of the reactors. In this paper, we introduce summary of Great East Japan Earthquake response a Onagawa NPS and safety improvement measures which are based on both experience of Onagawa NPS and lesson from Fukushima Daiichi NPS accident. (author)

  10. An improved procedure for detection and enumeration of walrus signatures in airborne thermal imagery

    Science.gov (United States)

    Burn, Douglas M.; Udevitz, Mark S.; Speckman, Suzann G.; Benter, R. Bradley

    2009-01-01

    In recent years, application of remote sensing to marine mammal surveys has been a promising area of investigation for wildlife managers and researchers. In April 2006, the United States and Russia conducted an aerial survey of Pacific walrus (Odobenus rosmarus divergens) using thermal infrared sensors to detect groups of animals resting on pack ice in the Bering Sea. The goal of this survey was to estimate the size of the Pacific walrus population. An initial analysis of the U.S. data using previously-established methods resulted in lower detectability of walrus groups in the imagery and higher variability in calibration models than was expected based on pilot studies. This paper describes an improved procedure for detection and enumeration of walrus groups in airborne thermal imagery. Thermal images were first subdivided into smaller 200 x 200 pixel "tiles." We calculated three statistics to represent characteristics of walrus signatures from the temperature histogram for each the. Tiles that exhibited one or more of these characteristics were examined further to determine if walrus signatures were present. We used cluster analysis on tiles that contained walrus signatures to determine which pixels belonged to each group. We then calculated a thermal index value for each walrus group in the imagery and used generalized linear models to estimate detection functions (the probability of a group having a positive index value) and calibration functions (the size of a group as a function of its index value) based on counts from matched digital aerial photographs. The new method described here improved our ability to detect walrus groups at both 2 m and 4 m spatial resolution. In addition, the resulting calibration models have lower variance than the original method. We anticipate that the use of this new procedure will greatly improve the quality of the population estimate derived from these data. This procedure may also have broader applicability to thermal infrared

  11. PROPOSAL FOR IMPROVEMENT OF BUINESS CONTINUITY PLAN (BCP) BASED ON THE LESSONS OF THE GREAT EAST JAPAN EARTHQUAKE

    Science.gov (United States)

    Maruya, Hiroaki

    For most Japanese companies and organizations, the enormous damage of the Great East Japan Earthquake was more than expected. In addition to great tsunami and earthquake motion, the lack of electricity and fuel disturbed to business activities seriously, and they should be considered important constraint factors in future earthquakes. Furthermore, disruption of supply chains also led considerable decline of production in many industries across Japan and foreign countries. Therefore it becomes urgent need for Japanese government and industries to utilize the lessons of the Great Earthquake and execute effective countermeasures, considering great earthquakes such as Tonankai & Nankai earthquakes and Tokyo Inland Earthquakes. Obviously most basic step is improving earthquake-resistant ability of buildings and facilities. In addition the spread of BCP and BCM to enterprises and organizations is indispensable. Based on the lessons, the BCM should include the point of view of the supply chain management more clearly, and emphasize "substitute strategy" more explicitly because a company should survive even if it completely loses its present production base. The central and local governments are requested, in addition to develop their own BCP, to improve related systematic conditions for BCM of the private sectors.

  12. Improved Statistical Fault Detection Technique and Application to Biological Phenomena Modeled by S-Systems.

    Science.gov (United States)

    Mansouri, Majdi; Nounou, Mohamed N; Nounou, Hazem N

    2017-09-01

    In our previous work, we have demonstrated the effectiveness of the linear multiscale principal component analysis (PCA)-based moving window (MW)-generalized likelihood ratio test (GLRT) technique over the classical PCA and multiscale principal component analysis (MSPCA)-based GLRT methods. The developed fault detection algorithm provided optimal properties by maximizing the detection probability for a particular false alarm rate (FAR) with different values of windows, and however, most real systems are nonlinear, which make the linear PCA method not able to tackle the issue of non-linearity to a great extent. Thus, in this paper, first, we apply a nonlinear PCA to obtain an accurate principal component of a set of data and handle a wide range of nonlinearities using the kernel principal component analysis (KPCA) model. The KPCA is among the most popular nonlinear statistical methods. Second, we extend the MW-GLRT technique to one that utilizes exponential weights to residuals in the moving window (instead of equal weightage) as it might be able to further improve fault detection performance by reducing the FAR using exponentially weighed moving average (EWMA). The developed detection method, which is called EWMA-GLRT, provides improved properties, such as smaller missed detection and FARs and smaller average run length. The idea behind the developed EWMA-GLRT is to compute a new GLRT statistic that integrates current and previous data information in a decreasing exponential fashion giving more weight to the more recent data. This provides a more accurate estimation of the GLRT statistic and provides a stronger memory that will enable better decision making with respect to fault detection. Therefore, in this paper, a KPCA-based EWMA-GLRT method is developed and utilized in practice to improve fault detection in biological phenomena modeled by S-systems and to enhance monitoring process mean. The idea behind a KPCA-based EWMA-GLRT fault detection algorithm is to

  13. Integration of biomimicry and nanotechnology for significantly improved detection of circulating tumor cells (CTCs).

    Science.gov (United States)

    Myung, Ja Hye; Park, Sin-Jung; Wang, Andrew Z; Hong, Seungpyo

    2017-12-13

    Circulating tumor cells (CTCs) have received a great deal of scientific and clinical attention as a biomarker for diagnosis and prognosis of many types of cancer. Given their potential significance in clinics, a variety of detection methods, utilizing the recent advances in nanotechnology and microfluidics, have been introduced in an effort of achieving clinically significant detection of CTCs. However, effective detection and isolation of CTCs still remain a tremendous challenge due to their extreme rarity and phenotypic heterogeneity. Among many approaches that are currently under development, this review paper focuses on a unique, promising approach that takes advantages of naturally occurring processes achievable through application of nanotechnology to realize significant improvement in sensitivity and specificity of CTC capture. We provide an overview of successful outcome of this biomimetic CTC capture system in detection of tumor cells from in vitro, in vivo, and clinical pilot studies. We also emphasize the clinical impact of CTCs as biomarkers in cancer diagnosis and predictive prognosis, which provides a cost-effective, minimally invasive method that potentially replaces or supplements existing methods such as imaging technologies and solid tissue biopsy. In addition, their potential prognostic values as treatment guidelines and that ultimately help to realize personalized therapy are discussed. Copyright © 2017. Published by Elsevier B.V.

  14. Improvement of a picking algorithm real-time P-wave detection by kurtosis

    Science.gov (United States)

    Ishida, H.; Yamada, M.

    2016-12-01

    Earthquake early warning (EEW) requires fast and accurate P-wave detection. The current EEW system in Japan uses the STA/LTAalgorithm (Allen, 1978) to detect P-wave arrival.However, some stations did not trigger during the 2011 Great Tohoku Earthquake due to the emergent onset. In addition, accuracy of the P-wave detection is very important: on August 1, 2016, the EEW issued a false alarm with M9 in Tokyo region due to a thunder noise.To solve these problems, we use a P-wave detection method using kurtosis statistics. It detects the change of statistic distribution of the waveform amplitude. This method was recently developed (Saragiotis et al., 2002) and used for off-line analysis such as making seismic catalogs. To apply this method for EEW, we need to remove an acausal calculation and enable a real-time processing. Here, we propose a real-time P-wave detection method using kurtosis statistics with a noise filter.To avoid false triggering by a noise, we incorporated a simple filter to classify seismic signal and noise. Following Kong et al. (2016), we used the interquartilerange and zero cross rate for the classification. The interquartile range is an amplitude measure that is equal to the middle 50% of amplitude in a certain time window. The zero cross rate is a simple frequency measure that counts the number of times that the signal crosses baseline zero. A discriminant function including these measures was constructed by the linear discriminant analysis.To test this kurtosis method, we used strong motion records for 62 earthquakes between April, 2005 and July, 2015, which recorded the seismic intensity greater equal to 6 lower in the JMA intensity scale. The records with hypocentral distance picks. It shows that the median error is 0.13 sec and 0.035 sec for STA/LTA and kurtosis method. The kurtosis method tends to be more sensitive to small changes in amplitude.Our approach will contribute to improve the accuracy of source location determination of

  15. New pediatric vision screener employing polarization-modulated, retinal-birefringence-scanning-based strabismus detection and bull's eye focus detection with an improved target system: opto-mechanical design and operation

    Science.gov (United States)

    Irsch, Kristina; Gramatikov, Boris I.; Wu, Yi-Kai; Guyton, David L.

    2014-06-01

    Amblyopia ("lazy eye") is a major public health problem, caused by misalignment of the eyes (strabismus) or defocus. If detected early in childhood, there is an excellent response to therapy, yet most children are detected too late to be treated effectively. Commercially available vision screening devices that test for amblyopia's primary causes can detect strabismus only indirectly and inaccurately via assessment of the positions of external light reflections from the cornea, but they cannot detect the anatomical feature of the eyes where fixation actually occurs (the fovea). Our laboratory has been developing technology to detect true foveal fixation, by exploiting the birefringence of the uniquely arranged Henle fibers delineating the fovea using retinal birefringence scanning (RBS), and we recently described a polarization-modulated approach to RBS that enables entirely direct and reliable detection of true foveal fixation, with greatly enhanced signal-to-noise ratio and essentially independent of corneal birefringence (a confounding variable with all polarization-sensitive ophthalmic technology). Here, we describe the design and operation of a new pediatric vision screener that employs polarization-modulated, RBS-based strabismus detection and bull's eye focus detection with an improved target system, and demonstrate the feasibility of this new approach.

  16. New pediatric vision screener employing polarization-modulated, retinal-birefringence-scanning-based strabismus detection and bull's eye focus detection with an improved target system: opto-mechanical design and operation.

    Science.gov (United States)

    Irsch, Kristina; Gramatikov, Boris I; Wu, Yi-Kai; Guyton, David L

    2014-06-01

    Amblyopia ("lazy eye") is a major public health problem, caused by misalignment of the eyes (strabismus) or defocus. If detected early in childhood, there is an excellent response to therapy, yet most children are detected too late to be treated effectively. Commercially available vision screening devices that test for amblyopia's primary causes can detect strabismus only indirectly and inaccurately via assessment of the positions of external light reflections from the cornea, but they cannot detect the anatomical feature of the eyes where fixation actually occurs (the fovea). Our laboratory has been developing technology to detect true foveal fixation, by exploiting the birefringence of the uniquely arranged Henle fibers delineating the fovea using retinal birefringence scanning (RBS), and we recently described a polarization-modulated approach to RBS that enables entirely direct and reliable detection of true foveal fixation, with greatly enhanced signal-to-noise ratio and essentially independent of corneal birefringence (a confounding variable with all polarization-sensitive ophthalmic technology). Here, we describe the design and operation of a new pediatric vision screener that employs polarization-modulated, RBS-based strabismus detection and bull's eye focus detection with an improved target system, and demonstrate the feasibility of this new approach.

  17. An Improved Wavelet‐Based Multivariable Fault Detection Scheme

    KAUST Repository

    Harrou, Fouzi

    2017-07-06

    Data observed from environmental and engineering processes are usually noisy and correlated in time, which makes the fault detection more difficult as the presence of noise degrades fault detection quality. Multiscale representation of data using wavelets is a powerful feature extraction tool that is well suited to denoising and decorrelating time series data. In this chapter, we combine the advantages of multiscale partial least squares (MSPLSs) modeling with those of the univariate EWMA (exponentially weighted moving average) monitoring chart, which results in an improved fault detection system, especially for detecting small faults in highly correlated, multivariate data. Toward this end, we applied EWMA chart to the output residuals obtained from MSPLS model. It is shown through simulated distillation column data the significant improvement in fault detection can be obtained by using the proposed methods as compared to the use of the conventional partial least square (PLS)‐based Q and EWMA methods and MSPLS‐based Q method.

  18. Using Information From Prior Satellite Scans to Improve Cloud Detection Near the Day-Night Terminator

    Science.gov (United States)

    Yost, Christopher R.; Minnis, Patrick; Trepte, Qing Z.; Palikonda, Rabindra; Ayers, Jeffrey K.; Spangenberg, Doulas A.

    2012-01-01

    With geostationary satellite data it is possible to have a continuous record of diurnal cycles of cloud properties for a large portion of the globe. Daytime cloud property retrieval algorithms are typically superior to nighttime algorithms because daytime methods utilize measurements of reflected solar radiation. However, reflected solar radiation is difficult to accurately model for high solar zenith angles where the amount of incident radiation is small. Clear and cloudy scenes can exhibit very small differences in reflected radiation and threshold-based cloud detection methods have more difficulty setting the proper thresholds for accurate cloud detection. Because top-of-atmosphere radiances are typically more accurately modeled outside the terminator region, information from previous scans can help guide cloud detection near the terminator. This paper presents an algorithm that uses cloud fraction and clear and cloudy infrared brightness temperatures from previous satellite scan times to improve the performance of a threshold-based cloud mask near the terminator. Comparisons of daytime, nighttime, and terminator cloud fraction derived from Geostationary Operational Environmental Satellite (GOES) radiance measurements show that the algorithm greatly reduces the number of false cloud detections and smoothes the transition from the daytime to the nighttime clod detection algorithm. Comparisons with the Geoscience Laser Altimeter System (GLAS) data show that using this algorithm decreases the number of false detections by approximately 20 percentage points.

  19. Environmental DNA (eDNA metabarcoding assays to detect invasive invertebrate species in the Great Lakes.

    Directory of Open Access Journals (Sweden)

    Katy E Klymus

    Full Text Available Describing and monitoring biodiversity comprise integral parts of ecosystem management. Recent research coupling metabarcoding and environmental DNA (eDNA demonstrate that these methods can serve as important tools for surveying biodiversity, while significantly decreasing the time, expense and resources spent on traditional survey methods. The literature emphasizes the importance of genetic marker development, as the markers dictate the applicability, sensitivity and resolution ability of an eDNA assay. The present study developed two metabarcoding eDNA assays using the mtDNA 16S RNA gene with Illumina MiSeq platform to detect invertebrate fauna in the Laurentian Great Lakes and surrounding waterways, with a focus for use on invasive bivalve and gastropod species monitoring. We employed careful primer design and in vitro testing with mock communities to assess ability of the markers to amplify and sequence targeted species DNA, while retaining rank abundance information. In our mock communities, read abundances reflected the initial input abundance, with regressions having significant slopes (p<0.05 and high coefficients of determination (R2 for all comparisons. Tests on field environmental samples revealed similar ability of our markers to measure relative abundance. Due to the limited reference sequence data available for these invertebrate species, care must be taken when analyzing results and identifying sequence reads to species level. These markers extend eDNA metabarcoding research for molluscs and appear relevant to other invertebrate taxa, such as rotifers and bryozoans. Furthermore, the sphaeriid mussel assay is group-specific, exclusively amplifying bivalves in the Sphaeridae family and providing species-level identification. Our assays provide useful tools for managers and conservation scientists, facilitating early detection of invasive species as well as improving resolution of mollusc diversity.

  20. Improved flaw detection and characterization with difference thermography

    Science.gov (United States)

    Winfree, William P.; Zalameda, Joseph N.; Howell, Patricia A.

    2011-05-01

    Flaw detection and characterization with thermographic techniques in graphite polymer composites is often limited by localized variations in the thermographic response. Variations in properties such as acceptable porosity, variations in fiber volume content and surface polymer thickness result in variations in the thermal response that in general cause significant variations in the initial thermal response. These variations result in a noise floor that increases the difficulty of detecting and characterizing deeper flaws. The paper investigates comparing thermographic responses taken before and after a change in state in a composite to improve the detection of subsurface flaws. A method is presented for registration of the responses before finding the difference. A significant improvement in the detectability is achieved by comparing the differences in response. Examples of changes in state due to application of a load and impact are presented.

  1. Evaluating and Improving Automatic Sleep Spindle Detection by Using Multi-Objective Evolutionary Algorithms

    Directory of Open Access Journals (Sweden)

    Min-Yin Liu

    2017-05-01

    Full Text Available Sleep spindles are brief bursts of brain activity in the sigma frequency range (11–16 Hz measured by electroencephalography (EEG mostly during non-rapid eye movement (NREM stage 2 sleep. These oscillations are of great biological and clinical interests because they potentially play an important role in identifying and characterizing the processes of various neurological disorders. Conventionally, sleep spindles are identified by expert sleep clinicians via visual inspection of EEG signals. The process is laborious and the results are inconsistent among different experts. To resolve the problem, numerous computerized methods have been developed to automate the process of sleep spindle identification. Still, the performance of these automated sleep spindle detection methods varies inconsistently from study to study. There are two reasons: (1 the lack of common benchmark databases, and (2 the lack of commonly accepted evaluation metrics. In this study, we focus on tackling the second problem by proposing to evaluate the performance of a spindle detector in a multi-objective optimization context and hypothesize that using the resultant Pareto fronts for deriving evaluation metrics will improve automatic sleep spindle detection. We use a popular multi-objective evolutionary algorithm (MOEA, the Strength Pareto Evolutionary Algorithm (SPEA2, to optimize six existing frequency-based sleep spindle detection algorithms. They include three Fourier, one continuous wavelet transform (CWT, and two Hilbert-Huang transform (HHT based algorithms. We also explore three hybrid approaches. Trained and tested on open-access DREAMS and MASS databases, two new hybrid methods of combining Fourier with HHT algorithms show significant performance improvement with F1-scores of 0.726–0.737.

  2. Defect Detectability Improvement for Conventional Friction Stir Welds

    Science.gov (United States)

    Hill, Chris

    2013-01-01

    This research was conducted to evaluate the effects of defect detectability via phased array ultrasound technology in conventional friction stir welds by comparing conventionally prepped post weld surfaces to a machined surface finish. A machined surface is hypothesized to improve defect detectability and increase material strength.

  3. Improved QRD-M Detection Algorithm for Generalized Spatial Modulation Scheme

    Directory of Open Access Journals (Sweden)

    Xiaorong Jing

    2017-01-01

    Full Text Available Generalized spatial modulation (GSM is a spectral and energy efficient multiple-input multiple-output (MIMO transmission scheme. It will lead to imperfect detection performance with relatively high computational complexity by directly applying the original QR-decomposition with M algorithm (QRD-M to the GSM scheme. In this paper an improved QRD-M algorithm is proposed for GSM signal detection, which achieves near-optimal performance but with relatively low complexity. Based on the QRD, the improved algorithm firstly transforms the maximum likelihood (ML detection of the GSM signals into searching an inverted tree structure. Then, in the searching process of the M branches, the branches corresponding to the illegitimate transmit antenna combinations (TACs and related to invalid number of active antennas are cut in order to improve the validity of the resultant branches at each level by taking advantage of characteristics of GSM signals. Simulation results show that the improved QRD-M detection algorithm provides similar performance to maximum likelihood (ML with the reduced computational complexity compared to the original QRD-M algorithm, and the optimal value of parameter M of the improved QRD-M algorithm for detection of the GSM scheme is equal to modulation order plus one.

  4. IMPROVING CAUSE DETECTION SYSTEMS WITH ACTIVE LEARNING

    Data.gov (United States)

    National Aeronautics and Space Administration — IMPROVING CAUSE DETECTION SYSTEMS WITH ACTIVE LEARNING ISAAC PERSING AND VINCENT NG Abstract. Active learning has been successfully applied to many natural language...

  5. Improved GLR method to instrument failure detection

    International Nuclear Information System (INIS)

    Jeong, Hak Yeoung; Chang, Soon Heung

    1985-01-01

    The generalized likehood radio(GLR) method performs statistical tests on the innovations sequence of a Kalman-Buchy filter state estimator for system failure detection and its identification. However, the major drawback of the convensional GLR is to hypothesize particular failure type in each case. In this paper, a method to solve this drawback is proposed. The improved GLR method is applied to a PWR pressurizer and gives successful results in detection and identification of any failure. Furthmore, some benefit on the processing time per each cycle of failure detection and its identification can be accompanied. (Author)

  6. Improvement and implementation for Canny edge detection algorithm

    Science.gov (United States)

    Yang, Tao; Qiu, Yue-hong

    2015-07-01

    Edge detection is necessary for image segmentation and pattern recognition. In this paper, an improved Canny edge detection approach is proposed due to the defect of traditional algorithm. A modified bilateral filter with a compensation function based on pixel intensity similarity judgment was used to smooth image instead of Gaussian filter, which could preserve edge feature and remove noise effectively. In order to solve the problems of sensitivity to the noise in gradient calculating, the algorithm used 4 directions gradient templates. Finally, Otsu algorithm adaptively obtain the dual-threshold. All of the algorithm simulated with OpenCV 2.4.0 library in the environments of vs2010, and through the experimental analysis, the improved algorithm has been proved to detect edge details more effectively and with more adaptability.

  7. Improving Accuracy of Dempster-Shafer Theory Based Anomaly Detection Systems

    Directory of Open Access Journals (Sweden)

    Ling Zou

    2014-07-01

    Full Text Available While the Dempster-Shafer theory of evidence has been widely used in anomaly detection, there are some issues with them. Dempster-Shafer theory of evidence trusts evidences equally which does not hold in distributed-sensor ADS. Moreover, evidences are dependent with each other sometimes which will lead to false alert. We propose improving by incorporating two algorithms. Features selection algorithm employs Gaussian Graphical Models to discover correlation between some candidate features. A group of suitable ADS were selected to detect and detection result were send to the fusion engine. Information gain is applied to set weight for every feature on Weights estimated algorithm. A weighted Dempster-Shafer theory of evidence combined the detection results to achieve a better accuracy. We evaluate our detection prototype through a set of experiments that were conducted with standard benchmark Wisconsin Breast Cancer Dataset and real Internet traffic. Evaluations on the Wisconsin Breast Cancer Dataset show that our prototype can find the correlation in nine features and improve the detection rate without affecting the false positive rate. Evaluations on Internet traffic show that Weights estimated algorithm can improve the detection performance significantly.

  8. Prenatal Diagnosis of Transposition of the Great Arteries over a 20-Year Period: Improved but Imperfect

    Science.gov (United States)

    Escobar-Diaz, Maria C; Freud, Lindsay R; Bueno, Alejandra; Brown, David W; Friedman, Kevin; Schidlow, David; Emani, Sitaram; del Nido, Pedro; Tworetzky, Wayne

    2015-01-01

    Objective To evaluate temporal trends in prenatal diagnosis of transposition of the great arteries with intact ventricular septum (TGA/IVS) and its impact on neonatal morbidity and mortality. Methods Newborns with TGA/IVS referred for surgical management to our center over a 20-year period (1992 – 2011) were included. The study time was divided into 5 four-year periods, and the primary outcome was rate of prenatal diagnosis. Secondary outcomes included neonatal pre-operative status and perioperative survival. Results Of the 340 patients, 81 (24%) had a prenatal diagnosis. Prenatal diagnosis increased over the study period from 6% to 41% (p<0.001). Prenatally diagnosed patients underwent a balloon atrial septostomy (BAS) earlier than postnatally diagnosed patients (0 vs. 1 day, p<0.001) and fewer required mechanical ventilation (56% vs. 69%, p=0.03). There were no statistically significant differences in pre-operative acidosis (16% vs. 26%, p=0.1) and need for preoperative ECMO (2% vs. 3%, p=1.0). There was also no significant mortality difference (1 pre-operative and no post-operative deaths among prenatally diagnosed patients, as compared to 4 pre-operative and 6 post-operative deaths among postnatally diagnosed patients). Conclusion The prenatal detection rate of TGA/IVS has improved but still remains below 50%, suggesting the need for strategies to increase detection rates. The mortality rate was not statistically different between pre- and postnatally diagnosed patients; however, there were significant pre-operative differences with regard to earlier BAS and less mechanical ventilation. Ongoing study is required to elucidate whether prenatal diagnosis confers long-term benefit. PMID:25484180

  9. Ammonium Sulfate Improves Detection of Hydrophilic Quaternary Ammonium Compounds through Decreased Ion Suppression in Matrix-Assisted Laser Desorption/Ionization Imaging Mass Spectrometry.

    Science.gov (United States)

    Sugiyama, Eiji; Masaki, Noritaka; Matsushita, Shoko; Setou, Mitsutoshi

    2015-11-17

    Hydrophilic quaternary ammonium compounds (QACs) include derivatives of carnitine (Car) or choline, which are known to have essential bioactivities. Here we developed a technique for improving the detection of hydrophilic QACs using ammonium sulfate (AS) in matrix-assisted laser desorption/ionization-imaging mass spectrometry (MALDI-IMS). In MALDI mass spectrometry for brain homogenates, the addition of AS greatly increased the signal intensities of Car, acetylcarnitine (AcCar), and glycerophosphocholine (GPC) by approximately 300-, 700-, and 2500-fold. The marked improvement required a higher AS concentration than that needed for suppressing the potassium adduction on phosphatidylcholine and 2,5-dihydroxybenzoic acid. Adding AS also increased the signal intensities of Car, AcCar, and GPC by approximately 10-, 20-, and 40-fold in MALDI-IMS. Consequently, the distributions of five hydrophilic QACs (Car, AcCar, GPC, choline, and phosphocholine) were simultaneously visualized by this technique. The distinct mechanism from other techniques such as improved matrix application, derivatization, or postionization suggests the great potential of AS addition to achieve higher sensitivity of MALDI-IMS for various analytes.

  10. Improved peak detection in mass spectrum by incorporating continuous wavelet transform-based pattern matching.

    Science.gov (United States)

    Du, Pan; Kibbe, Warren A; Lin, Simon M

    2006-09-01

    A major problem for current peak detection algorithms is that noise in mass spectrometry (MS) spectra gives rise to a high rate of false positives. The false positive rate is especially problematic in detecting peaks with low amplitudes. Usually, various baseline correction algorithms and smoothing methods are applied before attempting peak detection. This approach is very sensitive to the amount of smoothing and aggressiveness of the baseline correction, which contribute to making peak detection results inconsistent between runs, instrumentation and analysis methods. Most peak detection algorithms simply identify peaks based on amplitude, ignoring the additional information present in the shape of the peaks in a spectrum. In our experience, 'true' peaks have characteristic shapes, and providing a shape-matching function that provides a 'goodness of fit' coefficient should provide a more robust peak identification method. Based on these observations, a continuous wavelet transform (CWT)-based peak detection algorithm has been devised that identifies peaks with different scales and amplitudes. By transforming the spectrum into wavelet space, the pattern-matching problem is simplified and in addition provides a powerful technique for identifying and separating the signal from the spike noise and colored noise. This transformation, with the additional information provided by the 2D CWT coefficients can greatly enhance the effective signal-to-noise ratio. Furthermore, with this technique no baseline removal or peak smoothing preprocessing steps are required before peak detection, and this improves the robustness of peak detection under a variety of conditions. The algorithm was evaluated with SELDI-TOF spectra with known polypeptide positions. Comparisons with two other popular algorithms were performed. The results show the CWT-based algorithm can identify both strong and weak peaks while keeping false positive rate low. The algorithm is implemented in R and will be

  11. High Levels of Antibiotic Resistance but No Antibiotic Production Detected Along a Gypsum Gradient in Great Onyx Cave, KY, USA

    Directory of Open Access Journals (Sweden)

    Kathleen Lavoie

    2017-09-01

    Full Text Available A preliminary study of antibiotic production and antibiotic resistance was conducted in Great Onyx Cave in Mammoth Cave National Park, KY, to determine if gypsum (CaSO4∙2H2O affects these bacterial activities. The cave crosses through the width of Flint Ridge, and passages under the sandstone caprock are dry with different amounts of gypsum. The Great Kentucky Desert hypothesis posits that gypsum limits the distribution of invertebrates in the central areas of Great Onyx Cave. Twenty-four bacterial isolates were cultivated from swabs and soils. Using three methods (soil crumb, soil crumb with indicator bacteria, and the cross-streak method using isolated bacteria we did not detect any production of antibiotics. Antibiotic resistance was widespread, with all 24 isolates resistant to a minimum of two antibiotics of seven tested, with three isolates resistant to all. Antibiotic resistance was high and not correlated with depth into the cave or the amount of gypsum. The Great Kentucky Desert hypothesis of the negative effects of gypsum seems to have no impact on bacterial activity.

  12. Using Land Surface Phenology to Detect Land Use Change in the Northern Great Plains

    Science.gov (United States)

    Nguyen, L. H.; Henebry, G. M.

    2017-12-01

    The Northern Great Plains of the US have been undergoing many types of land cover / land use change over the past two decades, including expansion of irrigation, conversion of grassland to cropland, biofuels production, urbanization, and fossil fuel mining. Much of the literature on these changes has relied on post-classification change detection based on a limited number of observations per year. Here we demonstrate an approach to characterize land dynamics through land surface phenology (LSP) by synergistic use of image time series at two scales. Our study areas include regions of interest (ROIs) across the Northern Great Plains located within Landsat path overlap zones to boost the number of valid observations (free of clouds or snow) each year. We first compute accumulated growing degree-days (AGDD) from MODIS 8-day composites of land surface temperature (MOD11A2 and MYD11A2). Using Landsat Collection 1 surface reflectance-derived vegetation indices (NDVI, EVI), we then fit at each pixel a downward convex quadratic model linking the vegetation index to each year's progression of AGDD. This quadratic equation exhibits linearity in a mathematical sense; thus, the fitted models can be linearly mixed and unmixed using a set of LSP endmembers (defined by the fitted parameter coefficients of the quadratic model) that represent "pure" land cover types with distinct seasonal patterns found within the region, such as winter wheat, spring wheat, maize, soybean, sunflower, hay/pasture/grassland, developed/built-up, among others. Information about land cover corresponding to each endmember are provided by the NLCD (National Land Cover Dataset) and CDL (Cropland Data Layer). We use linear unmixing to estimate the likely proportion of each LSP endmember within particular areas stratified by latitude. By tracking the proportions over the 2001-2011 period, we can quantify various types of land transitions in the Northern Great Plains.

  13. Microchannel electron multiplier: improvement in gain performances and detection dynamics

    International Nuclear Information System (INIS)

    Audier, M.; Delmotte, J.C.; Boutot, J.P.

    1978-01-01

    The performances of an MCP are a function of its geometrical characteristics (diameter d and ratio 1/d of a channel, useful area) and of the applied voltage. Gain and mean output current are limited by saturation phenomena. By using a particular cascaded MCP's configuration, it is possible to simultaneously improve the gain, its associated fluctuations and the detection dynamics (detected level, counting rate). For gains 10 6 7 , the fluctuations, can be kept as low as 20% and an improvement by a factor > 10 can be obtained on the detection dynamics [fr

  14. Application of core–shell-structured CdTe-SiO2 quantum dots synthesized via a facile solution method for improving latent fingerprint detection

    International Nuclear Information System (INIS)

    Gao Feng; Han Jiaxing; Lv Caifeng; Wang Qin; Zhang Jun; Li Qun; Bao Liru; Li Xin

    2012-01-01

    Fingerprint detection is important in criminal investigation. This paper reports a facile powder brushing technique for improving latent fingerprint detection using core–shell-structured CdTe-SiO 2 quantum dots (QDs) as fluorescent labeling marks. Core–shell-structured CdTe-SiO 2 QDs are prepared via a simple solution-based approach using NH 2 NH 2 ·H 2 O as pH adjustor and stabilizer, and their application for improving latent fingerprint detection is explored. The obtained CdTe-SiO 2 QDs show spherical shapes with well-defined core–shell structures encapsulating different amounts of QDs depending on the type of the pH adjustor and stabilizer. Moreover, the fluorescence of CdTe-SiO 2 QDs is largely enhanced by surface modification of the SiO 2 shell. The CdTe-SiO 2 QDs overcome the oxidation problem of pure CdTe QDs in air, thus affording better variability with strong adhesive ability, better resolution, and bright emission colors for practical application in latent fingerprint detection. In comparison with the conventional fluorescence powders, silver powders, and others, the effectiveness of CdTe-SiO 2 QD powders for detection of latent fingerprints present on a large variety of object surfaces is greatly improved. The synthesis method for CdTe-SiO 2 QDs is simple, cheap, and easy for large-scale production, and thus offers many advantages in the practical application of fingerprint detection.

  15. Great improvement in pseudocapacitor properties of nickel hydroxide via simple gold deposition

    Science.gov (United States)

    Kim, Sun-I.; Thiyagarajan, Pradheep; Jang, Ji-Hyun

    2014-09-01

    In this letter, we report a facile approach to improve the capacitor properties of nickel hydroxide (Ni(OH)2) by simply coating gold nanoparticles (Au NPs) on the surface of Ni(OH)2. Au NP-deposited Ni(OH)2 (Au/Ni(OH)2) has been prepared by application of a conventional colloidal coating of Au NPs on the surface of 3D-Ni(OH)2 synthesized via a hydrothermal method. Compared with pristine Ni(OH)2, Au/Ni(OH)2 shows a 41% enhanced capacitance value, excellent rate capacitance behavior at high current density conditions, and greatly improved cycling stability for supercapacitor applications. The specific capacitance of Au/Ni(OH)2 reached 1927 F g-1 at 1 A g-1, which is close to the theoretical capacitance and retained 66% and 80% of the maximum value at a high current density of 20 A g-1 and 5000 cycles while that of pristine Ni(OH)2 was 1363 F g-1 and significantly decreased to 48% and 30%, respectively, under the same conditions. The outstanding performance of Au/Ni(OH)2 as a supercapacitor is attributed to the presence of metal Au NPs on the surface of semiconductor Ni(OH)2; this permits the creation of virtual 3D conducting networks via metal/semiconductor contact, which induces fast electron and ion transport by acting as a bridge between Ni(OH)2 nanostructures, thus eventually leading to significantly improved electrochemical capacitive behaviors, as confirmed by the EIS and I-V characteristic data.In this letter, we report a facile approach to improve the capacitor properties of nickel hydroxide (Ni(OH)2) by simply coating gold nanoparticles (Au NPs) on the surface of Ni(OH)2. Au NP-deposited Ni(OH)2 (Au/Ni(OH)2) has been prepared by application of a conventional colloidal coating of Au NPs on the surface of 3D-Ni(OH)2 synthesized via a hydrothermal method. Compared with pristine Ni(OH)2, Au/Ni(OH)2 shows a 41% enhanced capacitance value, excellent rate capacitance behavior at high current density conditions, and greatly improved cycling stability for

  16. Real-Time Pore Pressure Detection: Indicators and Improved Methods

    Directory of Open Access Journals (Sweden)

    Jincai Zhang

    2017-01-01

    Full Text Available High uncertainties may exist in the predrill pore pressure prediction in new prospects and deepwater subsalt wells; therefore, real-time pore pressure detection is highly needed to reduce drilling risks. The methods for pore pressure detection (the resistivity, sonic, and corrected d-exponent methods are improved using the depth-dependent normal compaction equations to adapt to the requirements of the real-time monitoring. A new method is proposed to calculate pore pressure from the connection gas or elevated background gas, which can be used for real-time pore pressure detection. The pore pressure detection using the logging-while-drilling, measurement-while-drilling, and mud logging data is also implemented and evaluated. Abnormal pore pressure indicators from the well logs, mud logs, and wellbore instability events are identified and analyzed to interpret abnormal pore pressures for guiding real-time drilling decisions. The principles for identifying abnormal pressure indicators are proposed to improve real-time pore pressure monitoring.

  17. An intrusion detection system based on fiber hydrophone

    Science.gov (United States)

    Liu, Junrong; Qiu, Xiufen; Shen, Heping

    2017-10-01

    This paper provides a new intrusion detection system based on fiber hydrophone, focusing beam forming figure positioning according to the near field and high precision sound source location algorithm which can accurately position the intrusion; obtaining its behavior path , obtaining the intrusion events related information such as speed form tracking intrusion trace; And analyze identification the detected intrusion behavior. If the monitor area is larger, the algorithm will take too much time once, and influence the system response time, for reduce the calculating time. This paper provides way that coarse location first, and then scanned for accuracy, so as to realize the intrusion events (such as car, etc.) the remote monitoring of positioning. The system makes up the blank in process capture of the fiber optic intrusion detection technology, and improves the understanding of the invasion. Through the capture of the process of intrusion behavior, and the fusion detection of intrusion behavior itself, thus analysis, judgment, identification of the intrusion information can greatly reduce the rate of false positives, greatly improved the reliability and practicability of the perimeter security system.

  18. Detection algorithm of infrared small target based on improved SUSAN operator

    Science.gov (United States)

    Liu, Xingmiao; Wang, Shicheng; Zhao, Jing

    2010-10-01

    The methods of detecting small moving targets in infrared image sequences that contain moving nuisance objects and background noise is analyzed in this paper. A novel infrared small target detection algorithm based on improved SUSAN operator is put forward. The algorithm selects double templates for the infrared small target detection: one size is greater than the small target point size and another size is equal to the small target point size. First, the algorithm uses the big template to calculate the USAN of each pixel in the image and detect the small target, the edge of the image and isolated noise pixels; Then the algorithm uses the another template to calculate the USAN of pixels detected in the first step and improves the principles of SUSAN algorithm based on the characteristics of the small target so that the algorithm can only detect small targets and don't sensitive to the edge pixels of the image and isolated noise pixels. So the interference of the edge of the image and isolate noise points are removed and the candidate target points can be identified; At last, the target is detected by utilizing the continuity and consistency of target movement. The experimental results indicate that the improved SUSAN detection algorithm can quickly and effectively detect the infrared small targets.

  19. Improved Conflict Detection for Graph Transformation with Attributes

    Directory of Open Access Journals (Sweden)

    Géza Kulcsár

    2015-04-01

    Full Text Available In graph transformation, a conflict describes a situation where two alternative transformations cannot be arbitrarily serialized. When enriching graphs with attributes, existing conflict detection techniques typically report a conflict whenever at least one of two transformations manipulates a shared attribute. In this paper, we propose an improved, less conservative condition for static conflict detection of graph transformation with attributes by explicitly taking the semantics of the attribute operations into account. The proposed technique is based on symbolic graphs, which extend the traditional notion of graphs by logic formulas used for attribute handling. The approach is proven complete, i.e., any potential conflict is guaranteed to be detected.

  20. [Current status and prospects of gene doping detection].

    Science.gov (United States)

    Wang, Wenjun; Zhang, Sichun; Xu, Jingjuan; Xia, Xinghua; Tian, Yaping; Zhang, Xinrong; Chen, Hong-Yuan

    2008-07-01

    The fast development of biotechnology promotes the development of doping. From recombinant protein to gene doping, there is a great challenge to their detection. The improvement of gene therapy and potential to enhance athletic performance open the door for gene doping. After a brief introduction of the concept of gene doping, the current status and prospects of gene doping detection are reviewed.

  1. Improved explosive collection and detection with rationally assembled surface sampling materials

    Energy Technology Data Exchange (ETDEWEB)

    Chouyyok, Wilaiwan; Bays, J. Timothy; Gerasimenko, Aleksandr A.; Cinson, Anthony D.; Ewing, Robert G.; Atkinson, David A.; Addleman, R. Shane

    2016-01-01

    Sampling and detection of trace explosives is a key analytical process in modern transportation safety. In this work we have explored some of the fundamental analytical processes for collection and detection of trace level explosive on surfaces with the most widely utilized system, thermal desorption IMS. The performance of the standard muslin swipe material was compared with chemically modified fiberglass cloth. The fiberglass surface was modified to include phenyl functional groups. When compared to standard muslin, the phenyl functionalized fiberglass sampling material showed better analyte release from the sampling material as well as improved response and repeatability from multiple uses of the same swipe. The improved sample release of the functionalized fiberglass swipes resulted in a significant increase in sensitivity. Various physical and chemical properties were systematically explored to determine optimal performance. The results herein have relevance to improving the detection of other explosive compounds and potentially to a wide range of other chemical sampling and field detection challenges.

  2. Preventive detection of incipient failure and improvement of availability of French PWR using acoustic emission

    International Nuclear Information System (INIS)

    Audenard, B.; Marini, J.

    1982-08-01

    Laboratory tests, on site experience gained on PWR during start up test as well as during nominal functioning have given FRAMATOME very great confidence in A.E. techniques for preventive detection of incidents. Loose part and leakage monitoring are already being used on an industrial basis. Crack growth detection and monitoring are still in the investigation phase and various. Research and Development programs are presently being carried out

  3. Ergonomics for enhancing detection of machine abnormalities.

    Science.gov (United States)

    Illankoon, Prasanna; Abeysekera, John; Singh, Sarbjeet

    2016-10-17

    Detecting abnormal machine conditions is of great importance in an autonomous maintenance environment. Ergonomic aspects can be invaluable when detection of machine abnormalities using human senses is examined. This research outlines the ergonomic issues involved in detecting machine abnormalities and suggests how ergonomics would improve such detections. Cognitive Task Analysis was performed in a plant in Sri Lanka where Total Productive Maintenance is being implemented to identify sensory types that would be used to detect machine abnormalities and relevant Ergonomic characteristics. As the outcome of this research, a methodology comprising of an Ergonomic Gap Analysis Matrix for machine abnormality detection is presented.

  4. Sonar Image Enhancements for Improved Detection of Sea Mines

    DEFF Research Database (Denmark)

    Jespersen, Karl; Sørensen, Helge Bjarup Dissing; Zerr, Benoit

    1999-01-01

    In this paper, five methods for enhancing sonar images prior to automatic detection of sea mines are investigated. Two of the methods have previously been published in connection with detection systems and serve as reference. The three new enhancement approaches are variance stabilizing log...... transform, nonlinear filtering, and pixel averaging for speckle reduction. The effect of the enhancement step is tested by using the full prcessing chain i.e. enhancement, detection and thresholding to determine the number of detections and false alarms. Substituting different enhancement algorithms...... in the processing chain gives a precise measure of the performance of the enhancement stage. The test is performed using a sonar image database with images ranging from very simple to very complex. The result of the comparison indicates that the new enhancement approaches improve the detection performance....

  5. The Time Scale of Recombination Rate Evolution in Great Apes

    Science.gov (United States)

    Stevison, Laurie S.; Woerner, August E.; Kidd, Jeffrey M.; Kelley, Joanna L.; Veeramah, Krishna R.; McManus, Kimberly F.; Bustamante, Carlos D.; Hammer, Michael F.; Wall, Jeffrey D.

    2016-01-01

    Abstract We present three linkage-disequilibrium (LD)-based recombination maps generated using whole-genome sequence data from 10 Nigerian chimpanzees, 13 bonobos, and 15 western gorillas, collected as part of the Great Ape Genome Project (Prado-Martinez J, et al. 2013. Great ape genetic diversity and population history. Nature 499:471–475). We also identified species-specific recombination hotspots in each group using a modified LDhot framework, which greatly improves statistical power to detect hotspots at varying strengths. We show that fewer hotspots are shared among chimpanzee subspecies than within human populations, further narrowing the time scale of complete hotspot turnover. Further, using species-specific PRDM9 sequences to predict potential binding sites (PBS), we show higher predicted PRDM9 binding in recombination hotspots as compared to matched cold spot regions in multiple great ape species, including at least one chimpanzee subspecies. We found that correlations between broad-scale recombination rates decline more rapidly than nucleotide divergence between species. We also compared the skew of recombination rates at centromeres and telomeres between species and show a skew from chromosome means extending as far as 10–15 Mb from chromosome ends. Further, we examined broad-scale recombination rate changes near a translocation in gorillas and found minimal differences as compared to other great ape species perhaps because the coordinates relative to the chromosome ends were unaffected. Finally, on the basis of multiple linear regression analysis, we found that various correlates of recombination rate persist throughout the African great apes including repeats, diversity, and divergence. Our study is the first to analyze within- and between-species genome-wide recombination rate variation in several close relatives. PMID:26671457

  6. Automatic seizure detection: going from sEEG to iEEG

    DEFF Research Database (Denmark)

    Henriksen, Jonas; Remvig, Line Sofie; Madsen, Rasmus Elsborg

    2010-01-01

    Several different algorithms have been proposed for automatic detection of epileptic seizures based on both scalp and intracranial electroencephalography (sEEG and iEEG). Which modality that renders the best result is hard to assess though. From 16 patients with focal epilepsy, at least 24 hours...... of ictal and non-ictal iEEG were obtained. Characteristics of the seizures are represented by use of wavelet transformation (WT) features and classified by a support vector machine. When implementing a method used for sEEG on iEEG data, a great improvement in performance was obtained when the high...... frequency containing lower levels in the WT were included in the analysis. We were able to obtain a sensitivity of 96.4% and a false detection rate (FDR) of 0.20/h. In general, when implementing an automatic seizure detection algorithm made for sEEG on iEEG, great improvement can be obtained if a frequency...

  7. Antibiotic Resistome: Improving Detection and Quantification Accuracy for Comparative Metagenomics.

    Science.gov (United States)

    Elbehery, Ali H A; Aziz, Ramy K; Siam, Rania

    2016-04-01

    The unprecedented rise of life-threatening antibiotic resistance (AR), combined with the unparalleled advances in DNA sequencing of genomes and metagenomes, has pushed the need for in silico detection of the resistance potential of clinical and environmental metagenomic samples through the quantification of AR genes (i.e., genes conferring antibiotic resistance). Therefore, determining an optimal methodology to quantitatively and accurately assess AR genes in a given environment is pivotal. Here, we optimized and improved existing AR detection methodologies from metagenomic datasets to properly consider AR-generating mutations in antibiotic target genes. Through comparative metagenomic analysis of previously published AR gene abundance in three publicly available metagenomes, we illustrate how mutation-generated resistance genes are either falsely assigned or neglected, which alters the detection and quantitation of the antibiotic resistome. In addition, we inspected factors influencing the outcome of AR gene quantification using metagenome simulation experiments, and identified that genome size, AR gene length, total number of metagenomics reads and selected sequencing platforms had pronounced effects on the level of detected AR. In conclusion, our proposed improvements in the current methodologies for accurate AR detection and resistome assessment show reliable results when tested on real and simulated metagenomic datasets.

  8. Improvement to defect detection by ultrasonic data processing: the DTVG method

    International Nuclear Information System (INIS)

    Francois, D.

    1995-10-01

    The cast elbows of the pipes of the principal primary circuit of French PWR, made of austenitic-ferritic stainless steel, pose problems to control. In order to improve the ultrasonic detection of defects in coarse-grained materials, we propose a method (called DTVG) based on the statistic study of the spatial stability of events contained in temporal signals. At the Beginning, the method was developed during a thesis (G. Corneloup, 1998) to improve the detection of cracks in thin thickness austenitic welds. Here, we propose to adapt the DTVG method and estimate its performances in detection of defects in thick materials representative of cast austenitic-ferritic elbows steels. The first objective of the study is adapting the original treatment applied to the thin thickness austenitic welds for the detection of defects in thick thickness austenitic-ferritic cast steels. The second objective consist of improving the algorithm to take in account the difference between thin and thick material and estimating the performances of the DTVG method in detection in specimen block with artificial defects. This work has led to adapt the original DTVG method to control thick cast austenitic-ferritic specimen (80 mm) under normal and oblique incidence. More, the study has allowed to make the the treatment automatic (automatic research of parameters). The results have shown that the DTVG method is fitted to detect artificial defects in thick cast austenitic-ferritic sample steel. All the defects in the specimen block have been detected without revealing false indication. (author). 4 refs., 4 figs

  9. The improvement of the detection power of a U-shaped DC plasma

    Directory of Open Access Journals (Sweden)

    DRAGAN MARKOVIC

    2001-04-01

    Full Text Available Optimization of the operating parameters of U-shpaed DC arc plasma and spectrometer parameters has been undertaken to explore the possibilities of improving its detection power. It is demonstrated, with a U-shaped arc as an example, that the limits of detection, in addition to well-defined parameters as described by Boumans and Winge, depend on the signal integration time. It is shown that with increasing integration time, the limits of detection are decreased within some limits and that the precision and concentration sensitivity are improved as well. A mathematical expression for the dependence of the detection limit on the integration time is presented. To increase the reliability of the measurement of the mentioned parameters, the working conditions were optimized for the following analytes: Ag, Al, Au, Cr, Fe, Mn, Ni, Pb, Pd, Pt, and V. The obtained limits of detection are comparable or better than those obtained by ICP for the elements studied. Itwas estimed that the possibility exists for their further improvement up to 10 times.

  10. Optimizing hyaluronidase dose and plasmid DNA delivery greatly improves gene electrotransfer efficiency in rat skeletal muscle

    DEFF Research Database (Denmark)

    Åkerström, Thorbjörn; Vedel, Kenneth; Needham Andersen, Josefine

    2015-01-01

    Transfection of rat skeletal muscle in vivo is a widely used research model. However, gene electrotransfer protocols have been developed for mice and yield variable results in rats. We investigated whether changes in hyaluronidase pre-treatment and plasmid DNA delivery can improve transfection...... with a homogenous distribution. We also show that transfection was stable over five weeks of regular exercise or inactivity. Our findings show that species-specific plasmid DNA delivery and hyaluronidase pre-treatment greatly improves transfection efficiency in rat skeletal muscle....... efficiency in rat skeletal muscle. We found that pre-treating the muscle with a hyaluronidase dose suitable for rats (0.56. U/g b.w.) prior to plasmid DNA injection increased transfection efficiency by >200% whereas timing of the pre-treatment did not affect efficiency. Uniformly distributing plasmid DNA...

  11. Enhancement of optic cup detection through an improved vessel kink detection framework

    Science.gov (United States)

    Wong, Damon W. K.; Liu, Jiang; Tan, Ngan Meng; Zhang, Zhuo; Lu, Shijian; Lim, Joo Hwee; Li, Huiqi; Wong, Tien Yin

    2010-03-01

    Glaucoma is a leading cause of blindness. The presence and extent of progression of glaucoma can be determined if the optic cup can be accurately segmented from retinal images. In this paper, we present a framework which improves the detection of the optic cup. First, a region of interest is obtained from the retinal fundus image, and a pallor-based preliminary cup contour estimate is determined. Patches are then extracted from the ROI along this contour. To improve the usability of the patches, adaptive methods are introduced to ensure the patches are within the optic disc and to minimize redundant information. The patches are then analyzed for vessels by an edge transform which generates pixel segments of likely vessel candidates. Wavelet, color and gradient information are used as input features for a SVM model to classify the candidates as vessel or non-vessel. Subsequently, a rigourous non-parametric method is adopted in which a bi-stage multi-resolution approach is used to probe and localize the location of kinks along the vessels. Finally, contenxtual information is used to fuse pallor and kink information to obtain an enhanced optic cup segmentation. Using a batch of 21 images obtained from the Singapore Eye Research Institute, the new method results in a 12.64% reduction in the average overlap error against a pallor only cup, indicating viable improvements in the segmentation and supporting the use of kinks for optic cup detection.

  12. Herbicides: A new threat to the Great Barrier Reef

    International Nuclear Information System (INIS)

    Lewis, Stephen E.; Brodie, Jon E.; Bainbridge, Zoe T.; Rohde, Ken W.; Davis, Aaron M.; Masters, Bronwyn L.; Maughan, Mirjam; Devlin, Michelle J.; Mueller, Jochen F.; Schaffelke, Britta

    2009-01-01

    The runoff of pesticides (insecticides, herbicides and fungicides) from agricultural lands is a key concern for the health of the iconic Great Barrier Reef, Australia. Relatively low levels of herbicide residues can reduce the productivity of marine plants and corals. However, the risk of these residues to Great Barrier Reef ecosystems has been poorly quantified due to a lack of large-scale datasets. Here we present results of a study tracing pesticide residues from rivers and creeks in three catchment regions to the adjacent marine environment. Several pesticides (mainly herbicides) were detected in both freshwater and coastal marine waters and were attributed to specific land uses in the catchment. Elevated herbicide concentrations were particularly associated with sugar cane cultivation in the adjacent catchment. We demonstrate that herbicides reach the Great Barrier Reef lagoon and may disturb sensitive marine ecosystems already affected by other pressures such as climate change. - Herbicide residues have been detected in Great Barrier Reef catchment waterways and river water plumes which may affect marine ecosystems.

  13. Improving the Accuracy of Cloud Detection Using Machine Learning

    Science.gov (United States)

    Craddock, M. E.; Alliss, R. J.; Mason, M.

    2017-12-01

    Cloud detection from geostationary satellite imagery has long been accomplished through multi-spectral channel differencing in comparison to the Earth's surface. The distinction of clear/cloud is then determined by comparing these differences to empirical thresholds. Using this methodology, the probability of detecting clouds exceeds 90% but performance varies seasonally, regionally and temporally. The Cloud Mask Generator (CMG) database developed under this effort, consists of 20 years of 4 km, 15minute clear/cloud images based on GOES data over CONUS and Hawaii. The algorithms to determine cloudy pixels in the imagery are based on well-known multi-spectral techniques and defined thresholds. These thresholds were produced by manually studying thousands of images and thousands of man-hours to determine the success and failure of the algorithms to fine tune the thresholds. This study aims to investigate the potential of improving cloud detection by using Random Forest (RF) ensemble classification. RF is the ideal methodology to employ for cloud detection as it runs efficiently on large datasets, is robust to outliers and noise and is able to deal with highly correlated predictors, such as multi-spectral satellite imagery. The RF code was developed using Python in about 4 weeks. The region of focus selected was Hawaii and includes the use of visible and infrared imagery, topography and multi-spectral image products as predictors. The development of the cloud detection technique is realized in three steps. First, tuning of the RF models is completed to identify the optimal values of the number of trees and number of predictors to employ for both day and night scenes. Second, the RF models are trained using the optimal number of trees and a select number of random predictors identified during the tuning phase. Lastly, the model is used to predict clouds for an independent time period than used during training and compared to truth, the CMG cloud mask. Initial results

  14. Improved cancer detection in automated breast ultrasound by radiologists using Computer Aided Detection

    International Nuclear Information System (INIS)

    Zelst, J.C.M. van; Tan, T.; Platel, B.; Jong, M. de; Steenbakkers, A.; Mourits, M.; Grivegnee, A.; Borelli, C.; Karssemeijer, N.; Mann, R.M.

    2017-01-01

    Objective: To investigate the effect of dedicated Computer Aided Detection (CAD) software for automated breast ultrasound (ABUS) on the performance of radiologists screening for breast cancer. Methods: 90 ABUS views of 90 patients were randomly selected from a multi-institutional archive of cases collected between 2010 and 2013. This dataset included normal cases (n = 40) with >1 year of follow up, benign (n = 30) lesions that were either biopsied or remained stable, and malignant lesions (n = 20). Six readers evaluated all cases with and without CAD in two sessions. CAD-software included conventional CAD-marks and an intelligent minimum intensity projection of the breast tissue. Readers reported using a likelihood-of-malignancy scale from 0 to 100. Alternative free-response ROC analysis was used to measure the performance. Results: Without CAD, the average area-under-the-curve (AUC) of the readers was 0.77 and significantly improved with CAD to 0.84 (p = 0.001). Sensitivity of all readers improved (range 5.2–10.6%) by using CAD but specificity decreased in four out of six readers (range 1.4–5.7%). No significant difference was observed in the AUC between experienced radiologists and residents both with and without CAD. Conclusions: Dedicated CAD-software for ABUS has the potential to improve the cancer detection rates of radiologists screening for breast cancer.

  15. Improved cancer detection in automated breast ultrasound by radiologists using Computer Aided Detection

    Energy Technology Data Exchange (ETDEWEB)

    Zelst, J.C.M. van, E-mail: Jan.vanZelst@radboudumc.nl [Radboud University Medical Center, Department of Radiology and Nuclear Medicine, Nijmegen (Netherlands); Tan, T.; Platel, B. [Radboud University Medical Center, Department of Radiology and Nuclear Medicine, Nijmegen (Netherlands); Jong, M. de [Jeroen Bosch Medical Centre, Department of Radiology, ‘s-Hertogenbosch (Netherlands); Steenbakkers, A. [Radboud University Medical Center, Department of Radiology and Nuclear Medicine, Nijmegen (Netherlands); Mourits, M. [Jeroen Bosch Medical Centre, Department of Radiology, ‘s-Hertogenbosch (Netherlands); Grivegnee, A. [Jules Bordet Institute, Department of Radiology, Brussels (Belgium); Borelli, C. [Catholic University of the Sacred Heart, Department of Radiological Sciences, Rome (Italy); Karssemeijer, N.; Mann, R.M. [Radboud University Medical Center, Department of Radiology and Nuclear Medicine, Nijmegen (Netherlands)

    2017-04-15

    Objective: To investigate the effect of dedicated Computer Aided Detection (CAD) software for automated breast ultrasound (ABUS) on the performance of radiologists screening for breast cancer. Methods: 90 ABUS views of 90 patients were randomly selected from a multi-institutional archive of cases collected between 2010 and 2013. This dataset included normal cases (n = 40) with >1 year of follow up, benign (n = 30) lesions that were either biopsied or remained stable, and malignant lesions (n = 20). Six readers evaluated all cases with and without CAD in two sessions. CAD-software included conventional CAD-marks and an intelligent minimum intensity projection of the breast tissue. Readers reported using a likelihood-of-malignancy scale from 0 to 100. Alternative free-response ROC analysis was used to measure the performance. Results: Without CAD, the average area-under-the-curve (AUC) of the readers was 0.77 and significantly improved with CAD to 0.84 (p = 0.001). Sensitivity of all readers improved (range 5.2–10.6%) by using CAD but specificity decreased in four out of six readers (range 1.4–5.7%). No significant difference was observed in the AUC between experienced radiologists and residents both with and without CAD. Conclusions: Dedicated CAD-software for ABUS has the potential to improve the cancer detection rates of radiologists screening for breast cancer.

  16. Great Books. What Works Clearinghouse Intervention Report

    Science.gov (United States)

    What Works Clearinghouse, 2011

    2011-01-01

    "Great Books" is a program that aims to improve the reading, writing, and critical thinking skills of students in kindergarten through high school. The program is implemented as a core or complementary curriculum and is based on the Shared Inquiry[TM] method of learning. The purpose of "Great Books" is to engage students in…

  17. A Decline in Response Variability Improves Neural Signal Detection during Auditory Task Performance.

    Science.gov (United States)

    von Trapp, Gardiner; Buran, Bradley N; Sen, Kamal; Semple, Malcolm N; Sanes, Dan H

    2016-10-26

    The detection of a sensory stimulus arises from a significant change in neural activity, but a sensory neuron's response is rarely identical to successive presentations of the same stimulus. Large trial-to-trial variability would limit the central nervous system's ability to reliably detect a stimulus, presumably affecting perceptual performance. However, if response variability were to decrease while firing rate remained constant, then neural sensitivity could improve. Here, we asked whether engagement in an auditory detection task can modulate response variability, thereby increasing neural sensitivity. We recorded telemetrically from the core auditory cortex of gerbils, both while they engaged in an amplitude-modulation detection task and while they sat quietly listening to the identical stimuli. Using a signal detection theory framework, we found that neural sensitivity was improved during task performance, and this improvement was closely associated with a decrease in response variability. Moreover, units with the greatest change in response variability had absolute neural thresholds most closely aligned with simultaneously measured perceptual thresholds. Our findings suggest that the limitations imposed by response variability diminish during task performance, thereby improving the sensitivity of neural encoding and potentially leading to better perceptual sensitivity. The detection of a sensory stimulus arises from a significant change in neural activity. However, trial-to-trial variability of the neural response may limit perceptual performance. If the neural response to a stimulus is quite variable, then the response on a given trial could be confused with the pattern of neural activity generated when the stimulus is absent. Therefore, a neural mechanism that served to reduce response variability would allow for better stimulus detection. By recording from the cortex of freely moving animals engaged in an auditory detection task, we found that variability

  18. Improving Polyp Detection Algorithms for CT Colonography: Pareto Front Approach.

    Science.gov (United States)

    Huang, Adam; Li, Jiang; Summers, Ronald M; Petrick, Nicholas; Hara, Amy K

    2010-03-21

    We investigated a Pareto front approach to improving polyp detection algorithms for CT colonography (CTC). A dataset of 56 CTC colon surfaces with 87 proven positive detections of 53 polyps sized 4 to 60 mm was used to evaluate the performance of a one-step and a two-step curvature-based region growing algorithm. The algorithmic performance was statistically evaluated and compared based on the Pareto optimal solutions from 20 experiments by evolutionary algorithms. The false positive rate was lower (pPareto optimization process can effectively help in fine-tuning and redesigning polyp detection algorithms.

  19. Great Ellipse Route Planning Based on Space Vector

    Directory of Open Access Journals (Sweden)

    LIU Wenchao

    2015-07-01

    Full Text Available Aiming at the problem of navigation error caused by unified earth model in great circle route planning using sphere model and modern navigation equipment using ellipsoid mode, a method of great ellipse route planning based on space vector is studied. By using space vector algebra method, the vertex of great ellipse is solved directly, and description of great ellipse based on major-axis vector and minor-axis vector is presented. Then calculation formulas of great ellipse azimuth and distance are deduced using two basic vectors. Finally, algorithms of great ellipse route planning are studied, especially equal distance route planning algorithm based on Newton-Raphson(N-R method. Comparative examples show that the difference of route planning between great circle and great ellipse is significant, using algorithms of great ellipse route planning can eliminate the navigation error caused by the great circle route planning, and effectively improve the accuracy of navigation calculation.

  20. Improvement of detection limits of PIXE by substrate signal reduction

    International Nuclear Information System (INIS)

    Beaulieu, S.; Nejedly, Z.; Campbell, J.L.; Edwards, G.C.; Dias, G.M.

    2002-01-01

    Limits of detection (LODs) for aerosol samples collected using PIXE International cascade impactors, were improved approximately 50% after reducing the cross-sectional area of the analytical beam based on results obtained from microscope photographs of aerosol deposits. Improvements in LODs were most noticeable for selected elements collected on the smaller stages of the impactor (stages 1-3)

  1. Detection of termites and other insects consumed by African great apes using molecular fecal analysis.

    Science.gov (United States)

    Hamad, Ibrahim; Delaporte, Eric; Raoult, Didier; Bittar, Fadi

    2014-03-27

    The consumption of insects by apes has previously been reported based on direct observations and/or trail signs in feces. However, DNA-based diet analyses may have the potential to reveal trophic links for these wild species. Herein, we analyzed the insect-diet diversity of 9 feces obtained from three species of African great apes, gorilla (Gorilla gorilla gorilla), chimpanzee (Pan troglodytes) and bonobo (Pan paniscus), using two mitochondrial amplifications for arthropods. A total of 1056 clones were sequenced for Cyt-b and COI gene libraries, which contained 50 and 56 operational taxonomic units (OTUs), respectively. BLAST research revealed that the OTUs belonged to 32 families from 5 orders (Diptera, Isoptera, Lepidoptera, Coleoptera, and Orthoptera). While ants were not detected by this method, the consumption of flies, beetles, moths, mosquitoes and termites was evident in these samples. Our findings indicate that molecular techniques can be used to analyze insect food items in wild animals.

  2. Complete exon sequencing of all known Usher syndrome genes greatly improves molecular diagnosis.

    Science.gov (United States)

    Bonnet, Crystel; Grati, M'hamed; Marlin, Sandrine; Levilliers, Jacqueline; Hardelin, Jean-Pierre; Parodi, Marine; Niasme-Grare, Magali; Zelenika, Diana; Délépine, Marc; Feldmann, Delphine; Jonard, Laurence; El-Amraoui, Aziz; Weil, Dominique; Delobel, Bruno; Vincent, Christophe; Dollfus, Hélène; Eliot, Marie-Madeleine; David, Albert; Calais, Catherine; Vigneron, Jacqueline; Montaut-Verient, Bettina; Bonneau, Dominique; Dubin, Jacques; Thauvin, Christel; Duvillard, Alain; Francannet, Christine; Mom, Thierry; Lacombe, Didier; Duriez, Françoise; Drouin-Garraud, Valérie; Thuillier-Obstoy, Marie-Françoise; Sigaudy, Sabine; Frances, Anne-Marie; Collignon, Patrick; Challe, Georges; Couderc, Rémy; Lathrop, Mark; Sahel, José-Alain; Weissenbach, Jean; Petit, Christine; Denoyelle, Françoise

    2011-05-11

    Usher syndrome (USH) combines sensorineural deafness with blindness. It is inherited in an autosomal recessive mode. Early diagnosis is critical for adapted educational and patient management choices, and for genetic counseling. To date, nine causative genes have been identified for the three clinical subtypes (USH1, USH2 and USH3). Current diagnostic strategies make use of a genotyping microarray that is based on the previously reported mutations. The purpose of this study was to design a more accurate molecular diagnosis tool. We sequenced the 366 coding exons and flanking regions of the nine known USH genes, in 54 USH patients (27 USH1, 21 USH2 and 6 USH3). Biallelic mutations were detected in 39 patients (72%) and monoallelic mutations in an additional 10 patients (18.5%). In addition to biallelic mutations in one of the USH genes, presumably pathogenic mutations in another USH gene were detected in seven patients (13%), and another patient carried monoallelic mutations in three different USH genes. Notably, none of the USH3 patients carried detectable mutations in the only known USH3 gene, whereas they all carried mutations in USH2 genes. Most importantly, the currently used microarray would have detected only 30 of the 81 different mutations that we found, of which 39 (48%) were novel. Based on these results, complete exon sequencing of the currently known USH genes stands as a definite improvement for molecular diagnosis of this disease, which is of utmost importance in the perspective of gene therapy.

  3. Complete exon sequencing of all known Usher syndrome genes greatly improves molecular diagnosis

    Directory of Open Access Journals (Sweden)

    Lacombe Didier

    2011-05-01

    Full Text Available Abstract Background Usher syndrome (USH combines sensorineural deafness with blindness. It is inherited in an autosomal recessive mode. Early diagnosis is critical for adapted educational and patient management choices, and for genetic counseling. To date, nine causative genes have been identified for the three clinical subtypes (USH1, USH2 and USH3. Current diagnostic strategies make use of a genotyping microarray that is based on the previously reported mutations. The purpose of this study was to design a more accurate molecular diagnosis tool. Methods We sequenced the 366 coding exons and flanking regions of the nine known USH genes, in 54 USH patients (27 USH1, 21 USH2 and 6 USH3. Results Biallelic mutations were detected in 39 patients (72% and monoallelic mutations in an additional 10 patients (18.5%. In addition to biallelic mutations in one of the USH genes, presumably pathogenic mutations in another USH gene were detected in seven patients (13%, and another patient carried monoallelic mutations in three different USH genes. Notably, none of the USH3 patients carried detectable mutations in the only known USH3 gene, whereas they all carried mutations in USH2 genes. Most importantly, the currently used microarray would have detected only 30 of the 81 different mutations that we found, of which 39 (48% were novel. Conclusions Based on these results, complete exon sequencing of the currently known USH genes stands as a definite improvement for molecular diagnosis of this disease, which is of utmost importance in the perspective of gene therapy.

  4. Anticoagulant rodenticides in red-tailed hawks, Buteo jamaicensis, and great horned owls, Bubo virginianus, from New Jersey, USA, 2008-2010.

    Science.gov (United States)

    Stansley, William; Cummings, Margaret; Vudathala, Daljit; Murphy, Lisa A

    2014-01-01

    Liver samples from red-tailed hawks (Buteo jamaicensis) and great horned owls (Bubo virginianus) were analyzed for anticoagulant rodenticides. Residues of one or more second generation anticoagulant rodenticides (SGARs) were detected in 81 % of red-tailed hawks and 82 % of great horned owls. The most frequently detected SGAR was brodifacoum, which was detected in 76 % of red-tailed hawks and 73 % of great horned owls. Bromadiolone was detected in 20 % of red-tailed hawks and 27 % of great horned owls. Difenacoum was detected in one great horned owl. No other ARs were detected. There were no significant differences between species in the frequency of detection or concentration of brodifacoum or bromadiolone. There was a marginally significant difference (p = 0.0497) between total SGAR residues in red-tailed hawks (0.117 mg/kg) and great horned owls (0.070 mg/kg). There were no seasonal differences in the frequency of detection or concentration of brodifacoum in red-tailed hawks. The data suggest that SGARs pose a significant risk of poisoning to predatory birds in New Jersey.

  5. Design of improved detection instrumentation for the annulus gas system for wolsong 2

    International Nuclear Information System (INIS)

    Kim, Seog Nam; Koo, Jun Mo; Chang, Ik Ho; Jung, Ho Chang; Han, Sang Joon

    1996-01-01

    The improved and advanced Annulus Gas System (AGS) has been developed for Wolsong 2 to satisfy the requirements of the regulatory body. The Atomic Energy Control Board (AECB) required a shorter detection time following a small leak from a pressure tube and/or calandria tube. This paper describes licensing requirements, functional requirements and detail design description for the AGS. The Wolsong unit No. 1 AGS was designed to operate as a stagnant system normally requiring only pressure regulation and having provisions for purging. The improved AGS involves the adoption of gas recirculation in AGS, duplication of dew point indicators with additional instrumentation and sampling provisions to prompt operator action. The improved system operates in the recirculation mode with continuous dew point measurement for leak detection. An AGS with improved detection instrumentation is provided. 8 refs., 3 figs. (author)

  6. Using an aqueous two-phase polymer-salt system to rapidly concentrate viruses for improving the detection limit of the lateral-flow immunoassay.

    Science.gov (United States)

    Jue, Erik; Yamanishi, Cameron D; Chiu, Ricky Y T; Wu, Benjamin M; Kamei, Daniel T

    2014-12-01

    The development of point-of-need (PON) diagnostics for viruses has the potential to prevent pandemics and protects against biological warfare threats. Here we discuss the approach of using aqueous two-phase systems (ATPSs) to concentrate biomolecules prior to the lateral-flow immunoassay (LFA) for improved viral detection. In this paper, we developed a rapid PON detection assay as an extension to our previous proof-of-concept studies which used a micellar ATPS. We present our investigation of a more rapid polymer-salt ATPS that can drastically improve the assay time, and show that the phase containing the concentrated biomolecule can be extracted prior to macroscopic phase separation equilibrium without affecting the measured biomolecule concentration in that phase. We could therefore significantly decrease the time of the diagnostic assay with an early extraction time of just 30 min. Using this rapid ATPS, the model virus bacteriophage M13 was concentrated between approximately 2 and 10-fold by altering the volume ratio between the two phases. As the extracted virus-rich phase contained a high salt concentration which destabilized the colloidal gold indicator used in LFA, we decorated the gold nanoprobes with polyethylene glycol (PEG) to provide steric stabilization, and used these nanoprobes to demonstrate a 10-fold improvement in the LFA detection limit. Lastly, a MATLAB script was used to quantify the LFA results with and without the pre-concentration step. This approach of combining a rapid ATPS with LFA has great potential for PON applications, especially as greater concentration-fold improvements can be achieved by further varying the volume ratio. Biotechnol. Bioeng. 2014;111: 2499-2507. © 2014 Wiley Periodicals, Inc. © 2014 Wiley Periodicals, Inc.

  7. Factors Associated With Worsened or Improved Mental Health in the Great East Japan Earthquake Survivors.

    Science.gov (United States)

    Yamanouchi, Tomoko; Hiroshima, Mayo; Takeuchi, Yumiko; Sawada, Yumiko; Takahashi, Makiko; Amagai, Manami

    2018-02-01

    The aim of this study was to identify factors contributing to the worsening or improved mental health of long-term evacuees over three years following the Great East Japan Earthquake. The Japanese version of the K6 questionnaire was used as a measure of mental health. The first- and third-year survey results were compared and differences in mental health status calculated. Respondents were then divided into two groups according to worsening or improved mental health status. Differences in stress factors, stress relief methods, and demographics were compared between the two groups. Factors associated with exacerbation of poor mental health were the stress factors "Uncertainty about future" (p=0.048) and "Loss of purpose in life" (p=0.023). Multivariable analysis identified two factors associated with improved mental health, the stress relief methods "Accepting myself" (odds ratio (OR): 2.15, 95% confidence interval (CI): 1.02-4.51) and "Interactions with others" (OR: 3.34, 95% CI: 1.43-7.79). While motivation and hope of livelihood reconstruction have gradually risen in the three years since the disaster, anxieties about an uncertain future, loss of purpose in life, and disruption of social networks continue adversely to affect the mental health of survivors. Copyright © 2017 Elsevier Inc. All rights reserved.

  8. Salient man-made structure detection in infrared images

    Science.gov (United States)

    Li, Dong-jie; Zhou, Fu-gen; Jin, Ting

    2013-09-01

    Target detection, segmentation and recognition is a hot research topic in the field of image processing and pattern recognition nowadays, among which salient area or object detection is one of core technologies of precision guided weapon. Many theories have been raised in this paper; we detect salient objects in a series of input infrared images by using the classical feature integration theory and Itti's visual attention system. In order to find the salient object in an image accurately, we present a new method to solve the edge blur problem by calculating and using the edge mask. We also greatly improve the computing speed by improving the center-surround differences method. Unlike the traditional algorithm, we calculate the center-surround differences through rows and columns separately. Experimental results show that our method is effective in detecting salient object accurately and rapidly.

  9. Research on Abnormal Detection Based on Improved Combination of K - means and SVDD

    Science.gov (United States)

    Hao, Xiaohong; Zhang, Xiaofeng

    2018-01-01

    In order to improve the efficiency of network intrusion detection and reduce the false alarm rate, this paper proposes an anomaly detection algorithm based on improved K-means and SVDD. The algorithm first uses the improved K-means algorithm to cluster the training samples of each class, so that each class is independent and compact in class; Then, according to the training samples, the SVDD algorithm is used to construct the minimum superspheres. The subordinate relationship of the samples is determined by calculating the distance of the minimum superspheres constructed by SVDD. If the test sample is less than the center of the hypersphere, the test sample belongs to this class, otherwise it does not belong to this class, after several comparisons, the final test of the effective detection of the test sample.In this paper, we use KDD CUP99 data set to simulate the proposed anomaly detection algorithm. The results show that the algorithm has high detection rate and low false alarm rate, which is an effective network security protection method.

  10. An improved algorithm of laser spot center detection in strong noise background

    Science.gov (United States)

    Zhang, Le; Wang, Qianqian; Cui, Xutai; Zhao, Yu; Peng, Zhong

    2018-01-01

    Laser spot center detection is demanded in many applications. The common algorithms for laser spot center detection such as centroid and Hough transform method have poor anti-interference ability and low detection accuracy in the condition of strong background noise. In this paper, firstly, the median filtering was used to remove the noise while preserving the edge details of the image. Secondly, the binarization of the laser facula image was carried out to extract target image from background. Then the morphological filtering was performed to eliminate the noise points inside and outside the spot. At last, the edge of pretreated facula image was extracted and the laser spot center was obtained by using the circle fitting method. In the foundation of the circle fitting algorithm, the improved algorithm added median filtering, morphological filtering and other processing methods. This method could effectively filter background noise through theoretical analysis and experimental verification, which enhanced the anti-interference ability of laser spot center detection and also improved the detection accuracy.

  11. Improving Nocturnal Fire Detection with the VIIRS Day-Night Band

    Science.gov (United States)

    Polivka, Thomas N.; Wang, Jun; Ellison, Luke T.; Hyer, Edward J.; Ichoku, Charles M.

    2016-01-01

    Building on existing techniques for satellite remote sensing of fires, this paper takes advantage of the day-night band (DNB) aboard the Visible Infrared Imaging Radiometer Suite (VIIRS) to develop the Firelight Detection Algorithm (FILDA), which characterizes fire pixels based on both visible-light and infrared (IR) signatures at night. By adjusting fire pixel selection criteria to include visible-light signatures, FILDA allows for significantly improved detection of pixels with smaller and/or cooler subpixel hotspots than the operational Interface Data Processing System (IDPS) algorithm. VIIRS scenes with near-coincident Advanced Spaceborne Thermal Emission and Reflection (ASTER) overpasses are examined after applying the operational VIIRS fire product algorithm and including a modified "candidate fire pixel selection" approach from FILDA that lowers the 4-µm brightness temperature (BT) threshold but includes a minimum DNB radiance. FILDA is shown to be effective in detecting gas flares and characterizing fire lines during large forest fires (such as the Rim Fire in California and High Park fire in Colorado). Compared with the operational VIIRS fire algorithm for the study period, FILDA shows a large increase (up to 90%) in the number of detected fire pixels that can be verified with the finer resolution ASTER data (90 m). Part (30%) of this increase is likely due to a combined use of DNB and lower 4-µm BT thresholds for fire detection in FILDA. Although further studies are needed, quantitative use of the DNB to improve fire detection could lead to reduced response times to wildfires and better estimate of fire characteristics (smoldering and flaming) at night.

  12. Adenoma detection rate varies greatly during colonoscopy training

    NARCIS (Netherlands)

    van Doorn, Sascha C.; Klanderman, Robert B.; Hazewinkel, Yark; Fockens, Paul; Dekker, Evelien

    2015-01-01

    The adenoma detection rate (ADR) is considered the most important quality indicator for colonoscopy and varies widely among colonoscopists. It is unknown whether the ADR of gastroenterology consultants can already be predicted during their colonoscopy training. To evaluate the ADR of fellows in

  13. Development of online cable eccentricity detection system based on X-ray CCD

    International Nuclear Information System (INIS)

    Chen Jianzhen; Li Bin; Wei Kaixia; Guo Lanying; Qu Guopu

    2008-01-01

    An improved technology of online cable eccentricity detection, based on X-ray CCD, greatly improves the measuring precision and the responding speed. The theory of eccentricity measuring based on X-ray CCD, and the structure of an apparatus are described. The apparatus is composed of scanning drive subsystem, X-ray generation components, data acquiring subsystem and high performance computer system. The measuring results are also presented. The features of this cable eccentricity detection technology are compared with the features of other technologies. (authors)

  14. Why greatness cannot be planned the myth of the objective

    CERN Document Server

    Stanley, Kenneth O

    2015-01-01

    Why does modern life revolve around objectives? From how science is funded, to improving how children are educated -- and nearly everything in-between -- our society has become obsessed with a seductive illusion: that greatness results from doggedly measuring improvement in the relentless pursuit of an ambitious goal. In Why Greatness Cannot Be Planned, Stanley and Lehman begin with a surprising scientific discovery in artificial intelligence that leads ultimately to the conclusion that the objective obsession has gone too far. They make the case that great achievement can't be bottled up int

  15. Intensive precipitation observation greatly improves hydrological modelling of the poorly gauged high mountain Mabengnong catchment in the Tibetan Plateau

    Science.gov (United States)

    Wang, Li; Zhang, Fan; Zhang, Hongbo; Scott, Christopher A.; Zeng, Chen; Shi, Xiaonan

    2018-01-01

    Precipitation is one of the most critical inputs for models used to improve understanding of hydrological processes. In high mountain areas, it is challenging to generate a reliable precipitation data set capturing the spatial and temporal heterogeneity due to the harsh climate, extreme terrain and the lack of observations. This study conducts intensive observation of precipitation in the Mabengnong catchment in the southeast of the Tibetan Plateau during July to August 2013. Because precipitation is greatly influenced by altitude, the observed data are used to characterize the precipitation gradient (PG) and hourly distribution (HD), showing that the average PG is 0.10, 0.28 and 0.26 mm/d/100 m and the average duration is around 0.1, 0.8 and 5.2 h for trace, light and moderate rain, respectively. A distributed biosphere hydrological model based on water and energy budgets with improved physical process for snow (WEB-DHM-S) is applied to simulate the hydrological processes with gridded precipitation data derived from a lower altitude meteorological station and the PG and HD characterized for the study area. The observed runoff, MODIS/Terra snow cover area (SCA) data, and MODIS/Terra land surface temperature (LST) data are used for model calibration and validation. Runoff, SCA and LST simulations all show reasonable results. Sensitivity analyses illustrate that runoff is largely underestimated without considering PG, indicating that short-term intensive precipitation observation has the potential to greatly improve hydrological modelling of poorly gauged high mountain catchments.

  16. Mobile Anomaly Detection Based on Improved Self-Organizing Maps

    Directory of Open Access Journals (Sweden)

    Chunyong Yin

    2017-01-01

    Full Text Available Anomaly detection has always been the focus of researchers and especially, the developments of mobile devices raise new challenges of anomaly detection. For example, mobile devices can keep connection with Internet and they are rarely turned off even at night. This means mobile devices can attack nodes or be attacked at night without being perceived by users and they have different characteristics from Internet behaviors. The introduction of data mining has made leaps forward in this field. Self-organizing maps, one of famous clustering algorithms, are affected by initial weight vectors and the clustering result is unstable. The optimal method of selecting initial clustering centers is transplanted from K-means to SOM. To evaluate the performance of improved SOM, we utilize diverse datasets and KDD Cup99 dataset to compare it with traditional one. The experimental results show that improved SOM can get higher accuracy rate for universal datasets. As for KDD Cup99 dataset, it achieves higher recall rate and precision rate.

  17. Traffic Light Detection

    DEFF Research Database (Denmark)

    Philipsen, Mark Philip; Jensen, Morten Bornø; Møgelmose, Andreas

    2015-01-01

    Traffic light recognition (TLR) is an integral part of any intelligent vehicle, which must function in the existing infrastructure. Pedestrian and sign detection have recently seen great improvements due to the introduction of learning based detectors using integral channel features. A similar push...... database is collected based on footage from US roads. The database consists of both test and training data, totaling 46,418 frames and 112,971 annotated traffic lights, captured in continuous sequences under a varying light and weather conditions. The learning based detector achieves an AUC of 0.4 and 0...

  18. Synergistic electron transfer effect-based signal amplification strategy for the ultrasensitive detection of dopamine.

    Science.gov (United States)

    Lu, Qiujun; Chen, Xiaogen; Liu, Dan; Wu, Cuiyan; Liu, Meiling; Li, Haitao; Zhang, Youyu; Yao, Shouzhuo

    2018-05-15

    The selective and sensitive detection of dopamine (DA) is of great significance for the identification of schizophrenia, Huntington's disease, and Parkinson's disease from the perspective of molecular diagnostics. So far, most of DA fluorescence sensors are based on the electron transfer from the fluorescence nanomaterials to DA-quinone. However, the limited electron transfer ability of the DA-quinone affects the level of detection sensitivity of these sensors. In this work, based on the DA can reduce Ag + into AgNPs followed by oxidized to DA-quinone, we developed a novel silicon nanoparticles-based electron transfer fluorescent sensor for the detection of DA. As electron transfer acceptor, the AgNPs and DA-quinone can quench the fluorescence of silicon nanoparticles effectively through the synergistic electron transfer effect. Compared with traditional fluorescence DA sensors, the proposed synergistic electron transfer-based sensor improves the detection sensitivity to a great extent (at least 10-fold improvement). The proposed sensor shows a low detection limit of DA, which is as low as 0.1 nM under the optimal conditions. This sensor has potential applicability for the detection of DA in practical sample. This work has been demonstrated to contribute to a substantial improvement in the sensitivity of the sensors. It also gives new insight into design electron transfer-based sensors. Copyright © 2018. Published by Elsevier B.V.

  19. State Government Revenue Recovery from the Great Recession

    OpenAIRE

    James Alm; David L. Sjoquist

    2014-01-01

    The "Great Recession" lasted from December 2007 to June 2009, and it wreaked havoc on the revenues of state (and local) governments. While the U.S. economy has improved since the end of the Great Recession, state government revenues have in most cases still not completely recovered. We use various indicators to measure how different states have -- or have not -- recovered in the aftermath of the Great Recession, and we also attempt to explain why these different patterns of recovery have emer...

  20. Improving HOG with image segmentation: application to human detection

    NARCIS (Netherlands)

    Salas, Y.S.; Bermudez, D.V.; Peña, A.M.L.; Gomez, D.G.; Gevers, T.

    2012-01-01

    In this paper we improve the histogram of oriented gradients (HOG), a core descriptor of state-of-the-art object detection, by the use of higher-level information coming from image segmentation. The idea is to re-weight the descriptor while computing it without increasing its size. The benefits of

  1. Improvement and development of automatic detection techniques

    International Nuclear Information System (INIS)

    Yamada, Kiyomi; Takai, Setsuo; Togashi, Chikako; Itami, Jun

    2000-01-01

    For detection of radiation-induced mutation, establishment of a new sample preparation method and its procedures suitable for its automation is thought to be the key step to improve the detection efficacy and save labor. In this study, an investigation was made on the sensitivity to radiation exposure in respect of the occurrence of chromosomal breakage by high precision chromosome coloring method utilizing FISH. The number of chromosome breakage per cell was determined in chromosome 1, 4, 5, 9, 11 and 13 prepared from an identical sample exposed to three different grays. The breakage number was found to increase linearly as an increase in the amount of chromosomal DNA and hotspots of the radiation-induced breakages tended to concentrate in R band and the position of R band was almost coincident with the sites of chromosomal translocation breakages specific to leukemia, showing a correlation of radiation exposure to leukemia. Chromosome 13, 14 and 15, which were different in band pattern but similar in its length taken from cells exposed to X-ray at 5 Gy were investigated in detail and it was found that the sensitivity of chromosome to radiation was depending on the quantity and the quality of R band in each chromosome. The benefits of this chromosome coloring method for the analysis of chromosome breakage were as follows: when compared with the conventional dicentric method, the kinds of chromosomal abnormalities to be detectable were much more and its detection rate as well as accuracy was higher. In addition, the time required for determination was loess than one tenth of the conventional one. A breakage site was detectable with differences in color tone and thus, any special technique was not necessary. Therefore, the chromosome coloring method by FISH was demonstrated to be much suitable for automatic image analysis by computer. (M.N.)

  2. Sensitivity of the improved Dutch tube diffusion test for detection of ...

    African Journals Online (AJOL)

    The sensitivity of the improved two-tube test for detection of antimicrobial residues in Kenyan milk was investigated by comparison with the commercial Delvo test SP. Suspect positive milk samples (n =244) from five milk collection centers, were analyzed with the improved two-tube and the commercial Delvo SP test as per ...

  3. Improvements in the detection of airborne plutonium

    International Nuclear Information System (INIS)

    Ryden, D.J.

    1981-02-01

    It is shown how it is possible to compensate individually for each of the background components on the filter paper used to collect samples. Experimentally it has been shown that the resulting compensated background count-rate averages zero with a standard deviation very close to the fundamental limit set by random statistical variations. Considerable improvements in the sensitivity of detecting airborne plutonium have been achieved. Two new plutonium-in-air monitors which use the compensation schemes described in this report are now available. Both have operated successfully in high concentrations of radon daughters. (author)

  4. The Great Recession was not so Great

    NARCIS (Netherlands)

    van Ours, J.C.

    2015-01-01

    The Great Recession is characterized by a GDP-decline that was unprecedented in the past decades. This paper discusses the implications of the Great Recession analyzing labor market data from 20 OECD countries. Comparing the Great Recession with the 1980s recession it is concluded that there is a

  5. Development of a heterodyne laser interferometer for very small high frequency displacements detection

    International Nuclear Information System (INIS)

    Baarmann, P.

    1992-10-01

    A heterodyne laser interferometer with detection electronics has been developed for measuring very small amplitude high frequency vibrations. A laser beam from HeNe-laser is focused and reflected in the vibrating surface and the generated phase shifts are after interference with a reference beam detected with a photo detector and evaluated in a demodulation system. The set-up is a prototype and techniques to improve the accuracy and sensitivity of the system are presented. The present system can detect vibration amplitude from around 1 Angstrom and is linear up to 250 Angstrom (±4%). Frequencies from a few tens of kHz up to tens of MHz are covered. The low frequency region can be greatly improved. The minimum detectable displacement may be improved by narrowing the bandwidth of the detection system to the region of interest

  6. Improvements in detection system for pulse radiolysis facility

    CERN Document Server

    Rao, V N; Manimaran, P; Mishra, R K; Mohan, H; Mukherjee, T; Nadkarni, S A; Sapre, A V; Shinde, S J; Toley, M

    2002-01-01

    This report describes the improvements made in the detection system of the pulse radiolysis facility based on a 7 MeV Linear Electron Accelerator (LINAC) located in the Radiation Chemistry and Chemical Dynamics Division of Bhabha Atomic Research Centre. The facility was created in 1986 for kinetic studies of transient species whose absorption lies between 200 and 700 nm. The newly developed detection circuits consist of a silicon (Si) photodiode (PD) detector for the wavelength range 450-1100 nm and a germanium (Ge) photodiode detector for the wavelength range 900-1600 nm. With these photodiode-based detection set-up, kinetic experiments are now routinely carried out in the wavelength range 450-1600 nm. The performance of these circuits has been tested using standard chemical systems. The rise time has been found to be 150 ns. The photo-multiplier tube (PMT) bleeder circuit has been modified. A new DC back-off circuit has been built and installed in order to avoid droop at longer time scales. A steady baselin...

  7. The development of a sub-daily gridded rainfall product to improve hydrological predictions in Great Britain

    Science.gov (United States)

    Quinn, Niall; Freer, Jim; Coxon, Gemma; O'Loughlin, Fiachra; Woods, Ross; Liguori, Sara

    2015-04-01

    In Great Britain and many other regions of the world, flooding resulting from short duration, high intensity rainfall events can lead to significant economic losses and fatalities. At present, such extreme events are often poorly evaluated using hydrological models due, in part, to their rarity and relatively short duration and a lack of appropriate data. Such storm characteristics are not well represented by daily rainfall records currently available using volumetric gauges and/or derived gridded products. This research aims to address this important data gap by developing a sub-daily gridded precipitation product for Great Britain. Our focus is to better understand these storm events and some of the challenges and uncertainties in quantifying such data across catchment scales. Our goal is to both improve such rainfall characterisation and derive an input to drive hydrological model simulations. Our methodology involves the collation, error checking, and spatial interpolation of approximately 2000 rain gauges located across Great Britain, provided by the Scottish Environment Protection Agency (SEPA) and the Environment Agency (EA). Error checking was conducted over the entirety of the TBR data available, utilising a two stage approach. First, rain gauge data at each site were examined independently, with data exceeding reasonable thresholds marked as suspect. Second, potentially erroneous data were marked using a neighbourhood analysis approach whereby measurements at a given gauge were deemed suspect if they did not fall within defined bounds of measurements at neighbouring gauges. A total of eight error checks were conducted. To provide the user with the greatest flexibility possible, the error markers associated with each check have been recorded at every site. This approach aims to enable the user to choose which checks they deem most suitable for a particular application. The quality assured TBR dataset was then spatially interpolated to produce a national

  8. Improving Accuracy of Intrusion Detection Model Using PCA and optimized SVM

    Directory of Open Access Journals (Sweden)

    Sumaiya Thaseen Ikram

    2016-06-01

    Full Text Available Intrusion detection is very essential for providing security to different network domains and is mostly used for locating and tracing the intruders. There are many problems with traditional intrusion detection models (IDS such as low detection capability against unknown network attack, high false alarm rate and insufficient analysis capability. Hence the major scope of the research in this domain is to develop an intrusion detection model with improved accuracy and reduced training time. This paper proposes a hybrid intrusiondetection model by integrating the principal component analysis (PCA and support vector machine (SVM. The novelty of the paper is the optimization of kernel parameters of the SVM classifier using automatic parameter selection technique. This technique optimizes the punishment factor (C and kernel parameter gamma (γ, thereby improving the accuracy of the classifier and reducing the training and testing time. The experimental results obtained on the NSL KDD and gurekddcup dataset show that the proposed technique performs better with higher accuracy, faster convergence speed and better generalization. Minimum resources are consumed as the classifier input requires reduced feature set for optimum classification. A comparative analysis of hybrid models with the proposed model is also performed.

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

    Science.gov (United States)

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

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

  10. Climate variability and Great Plains agriculture

    International Nuclear Information System (INIS)

    Rosenberg, N.J.; Katz, L.A.

    1991-01-01

    The ways in which inhabitants of the Great Plains, including Indians, early settlers, and 20th century farmers, have adapted to climate changes on the Great Plains are explored. The climate of the Great Plains, because of its variability and extremes, can be very stressful to plants, animals and people. It is suggested that agriculture and society on the Great Plains have, during the last century, become less vulnerable to the stresses imposed by climate. Opinions as to the sustainability of agriculture on the Great Plains vary substantially. Lockeretz (1981) suggests that large scale, high cost technologies have stressed farmers by creating surpluses and by requiring large investments. Opie (1989) sees irrigation as a climate substitute, however he stresses that the Ogallala aquifer must inevitably become depleted. Deborah and Frank Popper (1987) believe that farming on the Plains is unsustainable, and destruction of shelterbelts, out-migration of the rural population and environmental problems will lead to total collapse. With global warming, water in the Great Plains is expected to become scarcer, and although improvements in irrigation efficiency may slow depletion of the Ogallala aquifer, ultimately the acreage under irrigation must decrease to levels that can be sustained by natural recharge and reliable surface flows. 23 refs., 2 figs

  11. Quantitative Digital Tomosynthesis Mammography for Improved Breast Cancer Detection and Diagnosis

    National Research Council Canada - National Science Library

    Zhang, Yiheng

    2008-01-01

    .... When fully developed, the DTM can provide radiologists improved quantitative, three-dimensional volumetric information of the breast tissue, and assist in breast cancer detection and diagnosis...

  12. A new approach for monitoring ebolavirus in wild great apes.

    Directory of Open Access Journals (Sweden)

    Patricia E Reed

    2014-09-01

    Full Text Available Central Africa is a "hotspot" for emerging infectious diseases (EIDs of global and local importance, and a current outbreak of ebolavirus is affecting multiple countries simultaneously. Ebolavirus is suspected to have caused recent declines in resident great apes. While ebolavirus vaccines have been proposed as an intervention to protect apes, their effectiveness would be improved if we could diagnostically confirm Ebola virus disease (EVD as the cause of die-offs, establish ebolavirus geographical distribution, identify immunologically naïve populations, and determine whether apes survive virus exposure.Here we report the first successful noninvasive detection of antibodies against Ebola virus (EBOV from wild ape feces. Using this method, we have been able to identify gorillas with antibodies to EBOV with an overall prevalence rate reaching 10% on average, demonstrating that EBOV exposure or infection is not uniformly lethal in this species. Furthermore, evidence of antibodies was identified in gorillas thought previously to be unexposed to EBOV (protected from exposure by rivers as topological barriers of transmission.Our new approach will contribute to a strategy to protect apes from future EBOV infections by early detection of increased incidence of exposure, by identifying immunologically naïve at-risk populations as potential targets for vaccination, and by providing a means to track vaccine efficacy if such intervention is deemed appropriate. Finally, since human EVD is linked to contact with infected wildlife carcasses, efforts aimed at identifying great ape outbreaks could have a profound impact on public health in local communities, where EBOV causes case-fatality rates of up to 88%.

  13. Immunocapture reverse transcription-polymerase chain reaction combined with nested PCR greatly increases the detection of Prunus necrotic ring spot virus in the peach.

    Science.gov (United States)

    Helguera, P R; Taborda, R; Docampo, D M; Ducasse, D A

    2001-06-01

    A detection system based on nested PCR after IC-RT-PCR (IC-RT-PCR-Nested PCR) was developed to improve indexing of Prunus necrotic ringspot virus in peach trees. Inhibitory effects and inconsistencies of the standard IC-RT-PCR were overcome by this approach. IC-RT-PCR-Nested PCR improved detection by three orders of magnitude compared with DAS-ELISA for the detection of PNRSV in leaves. Several different tissues were evaluated and equally consistent results were observed. The main advantages of the method are its consistency, high sensitivity and easy application in quarantine programs.

  14. Great Basin Factsheet Series 2016 - Information and tools to restore and conserve Great Basin ecosystems

    Science.gov (United States)

    Jeanne C. Chambers

    2016-01-01

    Land managers are responsible for developing effective strategies for conserving and restoring Great Basin ecosystems in the face of invasive species, conifer expansion, and altered fire regimes. A warming climate is magnifying the effects of these threats and adding urgency to implementation of management practices that will maintain or improve ecosystem...

  15. Optimization of single photon detection model based on GM-APD

    Science.gov (United States)

    Chen, Yu; Yang, Yi; Hao, Peiyu

    2017-11-01

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

  16. Detection of Babesia annae DNA in lung exudate samples from Red foxes (Vulpes vulpes) in Great Britain.

    Science.gov (United States)

    Bartley, Paul M; Hamilton, Clare; Wilson, Cari; Innes, Elisabeth A; Katzer, Frank

    2016-02-12

    This study aimed to determine the prevalence of Babesia species DNA in lung exudate samples collected from red foxes (Vulpes vulpes) from across Great Britain. Babesia are small piroplasmid parasites which are mainly transmitted through the bite of infected ticks of the family Ixodidae. Babesia can cause potentially fatal disease in a wide-range of mammalian species including humans, dogs and cattle, making them of significant economic importance to both the medical and veterinary fields. DNA was extracted from lung exudate samples of 316 foxes. A semi-nested PCR was used to initially screen samples, using universal Babesia-Theileria primers which target the 18S rRNA gene. A selection of positive PCR amplicons were purified and sequenced. Subsequently specific primers were designed to detect Babesia annae and used to screen all 316 DNA samples. Randomly selected positive samples were purified and sequenced (GenBank accession KT580786). Clones spanning a 1717 bp region of the 18S rRNA gene were generated from 2 positive samples, the resultant consensus sequence was submitted to GenBank (KT580785). Sequence KT580785 was used in the phylogenetic analysis Babesia annae DNA was detected in the fox samples, in total 46/316 (14.6%) of samples tested positive for the presence of Babesia annae DNA. The central region of England had the highest prevalence at 36.7%, while no positive samples were found from Wales, though only 12 samples were tested from this region. Male foxes were found to have a higher prevalence of Babesia annae DNA than females in all regions of Britain. Phylogenetic and sequence analysis of the GenBank submissions (Accession numbers KT580785 and KT580786) showed 100% identity to Babesia sp.-'Spanish Dog' (AY534602, EU583387 and AF188001). This is the first time that Babesia annae DNA has been reported in red foxes in Great Britain with positive samples being found across England and Scotland indicating that this parasite is well established within the

  17. Big Ship Data: Using vessel measurements to improve estimates of temperature and wind speed on the Great Lakes

    Science.gov (United States)

    Fries, Kevin; Kerkez, Branko

    2017-05-01

    The sheer size of many water systems challenges the ability of in situ sensor networks to resolve spatiotemporal variability of hydrologic processes. New sources of vastly distributed and mobile measurements are, however, emerging to potentially fill these observational gaps. This paper poses the question: How can nontraditional measurements, such as those made by volunteer ship captains, be used to improve hydrometeorological estimates across large surface water systems? We answer this question through the analysis of one of the largest such data sets: an unprecedented collection of one million unique measurements made by ships on the North American Great Lakes from 2006 to 2014. We introduce a flexible probabilistic framework, which can be used to integrate ship measurements, or other sets of irregular point measurements, into contiguous data sets. The performance of this framework is validated through the development of a new ship-based spatial data product of water temperature, air temperature, and wind speed across the Great Lakes. An analysis of the final data product suggests that the availability of measurements across the Great Lakes will continue to play a large role in the confidence with which these large surface water systems can be studied and modeled. We discuss how this general and flexible approach can be applied to similar data sets, and how it will be of use to those seeking to merge large collections of measurements with other sources of data, such as physical models or remotely sensed products.

  18. Harmonic detection of magnetic resonance for sensitivity improvement of optical atomic magnetometers

    Energy Technology Data Exchange (ETDEWEB)

    Ranjbaran, M. [Laser and Plasma Research Institute, Shahid Beheshti University, Tehran (Iran, Islamic Republic of); Tehranchi, M.M., E-mail: teranchi@sbu.ac.ir [Laser and Plasma Research Institute, Shahid Beheshti University, Tehran (Iran, Islamic Republic of); Physics Department, Shahid Beheshti University, Tehran (Iran, Islamic Republic of); Hamidi, S.M. [Laser and Plasma Research Institute, Shahid Beheshti University, Tehran (Iran, Islamic Republic of); Khalkhali, S.M.H. [Physics Department, Kharazmi University, Tehran (Iran, Islamic Republic of)

    2017-02-15

    Highly sensitive atomic magnetometers use optically detected magnetic resonance of atomic spins to measure extremely weak magnetic field changes. The magnetometer sensitivity is directly proportional to the ratio of intensity to line-shape of the resonance signal. To obtain narrower resonance signal, we implemented harmonic detection of magnetic resonance method in M{sub x} configuration. The nonlinear spin polarization dynamics in detection of the higher harmonics were employed in phenomenological Bloch equations. The measured and simulated harmonic components of the resonance signals in frequency domain yielded significantly narrower line-width accompanying much improved sensitivity. Our results confirm the sensitivity improvement by a factor of two in optical atomic magnetometer via second harmonic signal which can open a new insight in the weak magnetic field measurement system design. - Highlights: • Highly sensitive atomic magnetometers have been used to measure weak magentic filed. • To obtain narrower resonance signal, we impalnted harmonic detection of magnetic resonance. • The nonlinear spin polarization dynamics in detetion of the higher harmonics were imployed.

  19. Detection of pulmonary nodules. Improvement by new screen-film systems?

    International Nuclear Information System (INIS)

    Lehmann, K.J.; Himmighoefer, U.

    1994-01-01

    In addition to digital radiography and AMBER, the development of asymmetric screen-film systems is another attempt to optimize chest radiography. Due to reduced contrast in the parenchyma, the former asymmetric screen-film systems did not show sufficient image quality. Three new asymmetric systems with completely different composition are available now. In-Sight VHC (Kodak), High Light GUV (3M) and Opthos D (Agfa) were compared to standard chest films using densitometric curves, a chest phantom for high and low contrast detectability, a nodule detection phantom and patient studies. The sensitivity of nodule detection in the mediastinum has been 41-48% for L-films and 58-65% for the asymmetric screen-film systems. No differences could be demonstrated for nodule detection in the lung field. Contrast in the parenchyma is equivalent to L-films. There is no loss of diagnostic information in the lung field. Differences between the asymmetric systems concern speed, dynamic range and granularity. If AMBER and digital radiography are not available, new asymmetric screen-film systems can improve nodule detection without further investment costs. (orig.) [de

  20. Making great leaps forward: Accounting for detectability in herpetological field studies

    Science.gov (United States)

    Mazerolle, Marc J.; Bailey, Larissa L.; Kendall, William L.; Royle, J. Andrew; Converse, Sarah J.; Nichols, James D.

    2007-01-01

    Detecting individuals of amphibian and reptile species can be a daunting task. Detection can be hindered by various factors such as cryptic behavior, color patterns, or observer experience. These factors complicate the estimation of state variables of interest (e.g., abundance, occupancy, species richness) as well as the vital rates that induce changes in these state variables (e.g., survival probabilities for abundance; extinction probabilities for occupancy). Although ad hoc methods (e.g., counts uncorrected for detection, return rates) typically perform poorly in the face of no detection, they continue to be used extensively in various fields, including herpetology. However, formal approaches that estimate and account for the probability of detection, such as capture-mark-recapture (CMR) methods and distance sampling, are available. In this paper, we present classical approaches and recent advances in methods accounting for detectability that are particularly pertinent for herpetological data sets. Through examples, we illustrate the use of several methods, discuss their performance compared to that of ad hoc methods, and we suggest available software to perform these analyses. The methods we discuss control for imperfect detection and reduce bias in estimates of demographic parameters such as population size, survival, or, at other levels of biological organization, species occurrence. Among these methods, recently developed approaches that no longer require marked or resighted individuals should be particularly of interest to field herpetologists. We hope that our effort will encourage practitioners to implement some of the estimation methods presented herein instead of relying on ad hoc methods that make more limiting assumptions.

  1. Great software debates

    CERN Document Server

    Davis, A

    2004-01-01

    The industry’s most outspoken and insightful critic explains how the software industry REALLY works. In Great Software Debates, Al Davis, shares what he has learned about the difference between the theory and the realities of business and encourages you to question and think about software engineering in ways that will help you succeed where others fail. In short, provocative essays, Davis fearlessly reveals the truth about process improvement, productivity, software quality, metrics, agile development, requirements documentation, modeling, software marketing and sales, empiricism, start-up financing, software research, requirements triage, software estimation, and entrepreneurship.

  2. Technical improvement and development of automatic detection method for genomic mutation

    International Nuclear Information System (INIS)

    Yamada, Kiyomi; Takai, Setsuo; Togashi, Chikako; Itami, Jun

    1999-01-01

    Fluorescent in situ hybridization (FISH) method was improved to estimate the dose of radiation exposure. Cleavage of DNA molecules in lymphocyte was used as the detection parameter and the procedures for preparation of samples suitable for atomic force microscopy and laser microscopy were developed. When ordinal primers on the market were used for PCR, the products were generally too small (about 200 b.p.) for detection by FISH method. Therefore, dATP and biotin-labeled dUTP were linked to its 3'-end by treatment with TdT for 2 hours, resulting that the mean length of PCR products was ca. 1.5 Kb. After hybridization using this prove, signal amplification was carried out according to biotin-avidin detection method. Thus, fluorescent signals on chromosomes could be easily detected. When three primers, D6S105, D6S291 and D6S282 were used as primer, fluorescent signal was detectable at 3 sites on chromatin fiber. These results indicate that this method is available for the analysis of cleavage of chromosomes. However, the backgrounds were much varied depending on the way to wash the preparation after incubation with fluorescent particle to form biotin-avidin binding. Therefore, further improvement of this method was necessary to apply in practice. When chromosomes 13, 14 and 15 from lymphocytes exposed to X-ray were used as test samples, it was demonstrated that radio-sensitivity was variable depending on the contents of R band in each chromosome. (M.N.)

  3. Computing Adaptive Feature Weights with PSO to Improve Android Malware Detection

    Directory of Open Access Journals (Sweden)

    Yanping Xu

    2017-01-01

    Full Text Available Android malware detection is a complex and crucial issue. In this paper, we propose a malware detection model using a support vector machine (SVM method based on feature weights that are computed by information gain (IG and particle swarm optimization (PSO algorithms. The IG weights are evaluated based on the relevance between features and class labels, and the PSO weights are adaptively calculated to result in the best fitness (the performance of the SVM classification model. Moreover, to overcome the defects of basic PSO, we propose a new adaptive inertia weight method called fitness-based and chaotic adaptive inertia weight-PSO (FCAIW-PSO that improves on basic PSO and is based on the fitness and a chaotic term. The goal is to assign suitable weights to the features to ensure the best Android malware detection performance. The results of experiments indicate that the IG weights and PSO weights both improve the performance of SVM and that the performance of the PSO weights is better than that of the IG weights.

  4. Improved Genetic Algorithm Optimization for Forward Vehicle Detection Problems

    Directory of Open Access Journals (Sweden)

    Longhui Gang

    2015-07-01

    Full Text Available Automated forward vehicle detection is an integral component of many advanced driver-assistance systems. The method based on multi-visual information fusion, with its exclusive advantages, has become one of the important topics in this research field. During the whole detection process, there are two key points that should to be resolved. One is to find the robust features for identification and the other is to apply an efficient algorithm for training the model designed with multi-information. This paper presents an adaptive SVM (Support Vector Machine model to detect vehicle with range estimation using an on-board camera. Due to the extrinsic factors such as shadows and illumination, we pay more attention to enhancing the system with several robust features extracted from a real driving environment. Then, with the introduction of an improved genetic algorithm, the features are fused efficiently by the proposed SVM model. In order to apply the model in the forward collision warning system, longitudinal distance information is provided simultaneously. The proposed method is successfully implemented on a test car and evaluation experimental results show reliability in terms of both the detection rate and potential effectiveness in a real-driving environment.

  5. A Method for Improving Reliability of Radiation Detection using Deep Learning Framework

    International Nuclear Information System (INIS)

    Chang, Hojong; Kim, Tae-Ho; Han, Byunghun; Kim, Hyunduk; Kim, Ki-duk

    2017-01-01

    Radiation detection is essential technology for overall field of radiation and nuclear engineering. Previously, technology for radiation detection composes of preparation of the table of the input spectrum to output spectrum in advance, which requires simulation of numerous predicted output spectrum with simulation using parameters modeling the spectrum. In this paper, we propose new technique to improve the performance of radiation detector. The software in the radiation detector has been stagnant for a while with possible intrinsic error of simulation. In the proposed method, to predict the input source using output spectrum measured by radiation detector is performed using deep neural network. With highly complex model, we expect that the complex pattern between data and the label can be captured well. Furthermore, the radiation detector should be calibrated regularly and beforehand. We propose a method to calibrate radiation detector using GAN. We hope that the power of deep learning may also reach to radiation detectors and make huge improvement on the field. Using improved radiation detector, the reliability of detection would be confident, and there are many tasks remaining to solve using deep learning in nuclear engineering society.

  6. Predicting Great Lakes fish yields: tools and constraints

    Science.gov (United States)

    Lewis, C.A.; Schupp, D.H.; Taylor, W.W.; Collins, J.J.; Hatch, Richard W.

    1987-01-01

    Prediction of yield is a critical component of fisheries management. The development of sound yield prediction methodology and the application of the results of yield prediction are central to the evolution of strategies to achieve stated goals for Great Lakes fisheries and to the measurement of progress toward those goals. Despite general availability of species yield models, yield prediction for many Great Lakes fisheries has been poor due to the instability of the fish communities and the inadequacy of available data. A host of biological, institutional, and societal factors constrain both the development of sound predictions and their application to management. Improved predictive capability requires increased stability of Great Lakes fisheries through rehabilitation of well-integrated communities, improvement of data collection, data standardization and information-sharing mechanisms, and further development of the methodology for yield prediction. Most important is the creation of a better-informed public that will in turn establish the political will to do what is required.

  7. Great Lake beach-goer behavior during a retrospectively detected bloom of cyanobacteria

    Science.gov (United States)

    Cyanobacteria blooms pose a potential health risk to beachgoers. We conducted a prospective study of weekend beachgoers at a public Great Lake site during July – September 2003. We recorded each person’s health status and activity during their beach visit. We measured...

  8. A Plane Target Detection Algorithm in Remote Sensing Images based on Deep Learning Network Technology

    Science.gov (United States)

    Shuxin, Li; Zhilong, Zhang; Biao, Li

    2018-01-01

    Plane is an important target category in remote sensing targets and it is of great value to detect the plane targets automatically. As remote imaging technology developing continuously, the resolution of the remote sensing image has been very high and we can get more detailed information for detecting the remote sensing targets automatically. Deep learning network technology is the most advanced technology in image target detection and recognition, which provided great performance improvement in the field of target detection and recognition in the everyday scenes. We combined the technology with the application in the remote sensing target detection and proposed an algorithm with end to end deep network, which can learn from the remote sensing images to detect the targets in the new images automatically and robustly. Our experiments shows that the algorithm can capture the feature information of the plane target and has better performance in target detection with the old methods.

  9. Automatic Defect Detection for TFT-LCD Array Process Using Quasiconformal Kernel Support Vector Data Description

    Directory of Open Access Journals (Sweden)

    Yi-Hung Liu

    2011-09-01

    Full Text Available Defect detection has been considered an efficient way to increase the yield rate of panels in thin film transistor liquid crystal display (TFT-LCD manufacturing. In this study we focus on the array process since it is the first and key process in TFT-LCD manufacturing. Various defects occur in the array process, and some of them could cause great damage to the LCD panels. Thus, how to design a method that can robustly detect defects from the images captured from the surface of LCD panels has become crucial. Previously, support vector data description (SVDD has been successfully applied to LCD defect detection. However, its generalization performance is limited. In this paper, we propose a novel one-class machine learning method, called quasiconformal kernel SVDD (QK-SVDD to address this issue. The QK-SVDD can significantly improve generalization performance of the traditional SVDD by introducing the quasiconformal transformation into a predefined kernel. Experimental results, carried out on real LCD images provided by an LCD manufacturer in Taiwan, indicate that the proposed QK-SVDD not only obtains a high defect detection rate of 96%, but also greatly improves generalization performance of SVDD. The improvement has shown to be over 30%. In addition, results also show that the QK-SVDD defect detector is able to accomplish the task of defect detection on an LCD image within 60 ms.

  10. Research on Daily Objects Detection Based on Deep Neural Network

    Science.gov (United States)

    Ding, Sheng; Zhao, Kun

    2018-03-01

    With the rapid development of deep learning, great breakthroughs have been made in the field of object detection. In this article, the deep learning algorithm is applied to the detection of daily objects, and some progress has been made in this direction. Compared with traditional object detection methods, the daily objects detection method based on deep learning is faster and more accurate. The main research work of this article: 1. collect a small data set of daily objects; 2. in the TensorFlow framework to build different models of object detection, and use this data set training model; 3. the training process and effect of the model are improved by fine-tuning the model parameters.

  11. Improving detection probabilities for pests in stored grain.

    Science.gov (United States)

    Elmouttie, David; Kiermeier, Andreas; Hamilton, Grant

    2010-12-01

    The presence of insects in stored grain is a significant problem for grain farmers, bulk grain handlers and distributors worldwide. Inspection of bulk grain commodities is essential to detect pests and thereby to reduce the risk of their presence in exported goods. It has been well documented that insect pests cluster in response to factors such as microclimatic conditions within bulk grain. Statistical sampling methodologies for grain, however, have typically considered pests and pathogens to be homogeneously distributed throughout grain commodities. In this paper, a sampling methodology is demonstrated that accounts for the heterogeneous distribution of insects in bulk grain. It is shown that failure to account for the heterogeneous distribution of pests may lead to overestimates of the capacity for a sampling programme to detect insects in bulk grain. The results indicate the importance of the proportion of grain that is infested in addition to the density of pests within the infested grain. It is also demonstrated that the probability of detecting pests in bulk grain increases as the number of subsamples increases, even when the total volume or mass of grain sampled remains constant. This study underlines the importance of considering an appropriate biological model when developing sampling methodologies for insect pests. Accounting for a heterogeneous distribution of pests leads to a considerable improvement in the detection of pests over traditional sampling models. Copyright © 2010 Society of Chemical Industry.

  12. A comparative study on methods of improving SCR for ship detection in SAR image

    Science.gov (United States)

    Lang, Haitao; Shi, Hongji; Tao, Yunhong; Ma, Li

    2017-10-01

    Knowledge about ship positions plays a critical role in a wide range of maritime applications. To improve the performance of ship detector in SAR image, an effective strategy is improving the signal-to-clutter ratio (SCR) before conducting detection. In this paper, we present a comparative study on methods of improving SCR, including power-law scaling (PLS), max-mean and max-median filter (MMF1 and MMF2), method of wavelet transform (TWT), traditional SPAN detector, reflection symmetric metric (RSM), scattering mechanism metric (SMM). The ability of SCR improvement to SAR image and ship detection performance associated with cell- averaging CFAR (CA-CFAR) of different methods are evaluated on two real SAR data.

  13. Improved detection limits for phthalates by selective solid-phase micro-extraction

    KAUST Repository

    Zia, Asif I.; Afsarimanesh, Nasrin; Xie, Li; Nag, Anindya; Al-Bahadly, I. H.; Yu, P. L.; Kosel, Jü rgen

    2016-01-01

    Presented research reports on an improved method and enhanced limits of detection for phthalates; a hazardous additive used in the production of plastics by solid-phase micro-extraction (SPME) polymer in comparison to molecularly imprinted solid

  14. Detection of Early Ischemic Changes in Noncontrast CT Head Improved with "Stroke Windows".

    Science.gov (United States)

    Mainali, Shraddha; Wahba, Mervat; Elijovich, Lucas

    2014-01-01

    Introduction. Noncontrast head CT (NCCT) is the standard radiologic test for patients presenting with acute stroke. Early ischemic changes (EIC) are often overlooked on initial NCCT. We determine the sensitivity and specificity of improved EIC detection by a standardized method of image evaluation (Stroke Windows). Methods. We performed a retrospective chart review to identify patients with acute ischemic stroke who had NCCT at presentation. EIC was defined by the presence of hyperdense MCA/basilar artery sign; sulcal effacement; basal ganglia/subcortical hypodensity; and loss of cortical gray-white differentiation. NCCT was reviewed with standard window settings and with specialized Stroke Windows. Results. Fifty patients (42% females, 58% males) with a mean NIHSS of 13.4 were identified. EIC was detected in 9 patients with standard windows, while EIC was detected using Stroke Windows in 35 patients (18% versus 70%; P Windows (14% and 36%; P Windows (6% and 46%; P Windows significantly improved detection of EIC.

  15. Bladed wheels damage detection through Non-Harmonic Fourier Analysis improved algorithm

    Science.gov (United States)

    Neri, P.

    2017-05-01

    Recent papers introduced the Non-Harmonic Fourier Analysis for bladed wheels damage detection. This technique showed its potential in estimating the frequency of sinusoidal signals even when the acquisition time is short with respect to the vibration period, provided that some hypothesis are fulfilled. Anyway, previously proposed algorithms showed severe limitations in cracks detection at their early stage. The present paper proposes an improved algorithm which allows to detect a blade vibration frequency shift due to a crack whose size is really small compared to the blade width. Such a technique could be implemented for condition-based maintenance, allowing to use non-contact methods for vibration measurements. A stator-fixed laser sensor could monitor all the blades as they pass in front of the spot, giving precious information about the wheel health. This configuration determines an acquisition time for each blade which become shorter as the machine rotational speed increases. In this situation, traditional Discrete Fourier Transform analysis results in poor frequency resolution, being not suitable for small frequency shift detection. Non-Harmonic Fourier Analysis instead showed high reliability in vibration frequency estimation even with data samples collected in a short time range. A description of the improved algorithm is provided in the paper, along with a comparison with the previous one. Finally, a validation of the method is presented, based on finite element simulations results.

  16. Improving buried threat detection in ground-penetrating radar with transfer learning and metadata analysis

    Science.gov (United States)

    Colwell, Kenneth A.; Torrione, Peter A.; Morton, Kenneth D.; Collins, Leslie M.

    2015-05-01

    Ground-penetrating radar (GPR) technology has proven capable of detecting buried threats. The system relies on a binary classifier that is trained to distinguish between two classes: a target class, encompassing many types of buried threats and their components; and a nontarget class, which includes false alarms from the system prescreener. Typically, the training process involves a simple partition of the data into these two classes, which allows for straightforward application of standard classifiers. However, since training data is generally collected in fully controlled environments, it includes auxiliary information about each example, such as the specific type of threat, its purpose, its components, and its depth. Examples from the same specific or general type may be expected to exhibit similarities in their GPR data, whereas examples from different types may differ greatly. This research aims to leverage this additional information to improve overall classification performance by fusing classifier concepts for multiple groups, and to investigate whether structure in this information can be further utilized for transfer learning, such that the amount of expensive training data necessary to learn a new, previously-unseen target type may be reduced. Methods for accomplishing these goals are presented with results from a dataset containing a variety of target types.

  17. Leakage detection device for weld portion

    International Nuclear Information System (INIS)

    Shinkawa, Toshio; Setokuchi, Sadayuki.

    1994-01-01

    The present invention concerns leakage detection device for weld portions, for example, in a nuclear reactor cavity, which can rapidly detect by remote control. That is, a detection device capable of self running and stopping on a guide rail along a weld line is disposed. The detection device comprises a coating mechanism for automatically coating soap water to the weld portion, a vacuum box capable of evacuating the coated surface and a camera for detecting the presence or absence of the soap bubbles generated under the evacuation. Such a device can conduct, by remote control, self running/stopping along with the weld line, coating of the soap water, settling of the vacuum box and confirmation and recording of foaming by using a television monitor. Accordingly, leakage in the weld portion in the reactor cavity or the like can be inspected. As a result, it greatly contributes to improvement of danger upon worker's operation at high place, detection accuracy and reliability of detection and shortening of operation period. (I.S.)

  18. Improvement in Limit of Detection of Enzymatic Biogas Sensor Utilizing Chromatography Paper for Breath Analysis.

    Science.gov (United States)

    Motooka, Masanobu; Uno, Shigeyasu

    2018-02-02

    Breath analysis is considered to be an effective method for point-of-care diagnosis due to its noninvasiveness, quickness and simplicity. Gas sensors for breath analysis require detection of low-concentration substances. In this paper, we propose that reduction of the background current improves the limit of detection of enzymatic biogas sensors utilizing chromatography paper. After clarifying the cause of the background current, we reduced the background current by improving the fabrication process of the sensors utilizing paper. Finally, we evaluated the limit of detection of the sensor with the sample vapor of ethanol gas. The experiment showed about a 50% reduction of the limit of detection compared to previously-reported sensor. This result presents the possibility of the sensor being applied in diagnosis, such as for diabetes, by further lowering the limit of detection.

  19. Ultrasensitive Detection of Ebola Virus Oligonucleotide Based on Upconversion Nanoprobe/Nanoporous Membrane System.

    Science.gov (United States)

    Tsang, Ming-Kiu; Ye, WeiWei; Wang, Guojing; Li, Jingming; Yang, Mo; Hao, Jianhua

    2016-01-26

    Ebola outbreaks are currently of great concern, and therefore, development of effective diagnosis methods is urgently needed. The key for lethal virus detection is high sensitivity, since early-stage detection of virus may increase the probability of survival. Here, we propose a luminescence scheme of assay consisting of BaGdF5:Yb/Er upconversion nanoparticles (UCNPs) conjugated with oligonucleotide probe and gold nanoparticles (AuNPs) linked with target Ebola virus oligonucleotide. As a proof of concept, a homogeneous assay was fabricated and tested, yielding a detection limit at picomolar level. The luminescence resonance energy transfer is ascribed to the spectral overlapping of upconversion luminescence and the absorption characteristics of AuNPs. Moreover, we anchored the UCNPs and AuNPs on a nanoporous alumina (NAAO) membrane to form a heterogeneous assay. Importantly, the detection limit was greatly improved, exhibiting a remarkable value at the femtomolar level. The enhancement is attributed to the increased light-matter interaction throughout the nanopore walls of the NAAO membrane. The specificity test suggested that the nanoprobes were specific to Ebola virus oligonucleotides. The strategy combining UCNPs, AuNPs, and NAAO membrane provides new insight into low-cost, rapid, and ultrasensitive detection of different diseases. Furthermore, we explored the feasibility of clinical application by using inactivated Ebola virus samples. The detection results showed great potential of our heterogeneous design for practical application.

  20. Improved Data-based Fault Detection Strategy and Application to Distillation Columns

    KAUST Repository

    Madakyaru, Muddu

    2017-01-31

    Chemical and petrochemical processes require continuous monitoring to detect abnormal events and to sustain normal operations. Furthermore, process monitoring enhances productivity, efficiency, and safety in process industries. Here, we propose an innovative statistical approach that exploits the advantages of multiscale partial least squares (MSPLS) models and generalized likelihood ratio (GLR) tests for fault detection in processes. Specifically, we combine an MSPLS algorithm with wavelet analysis to create our modeling framework. Then, we use GLR hypothesis testing based on the uncorrelated residuals obtained from the MSPLS model to improve fault detection. We use simulated distillation column data to evaluate the MSPLS-based GLR chart. Results show that our MSPLS-based GLR method is more powerful than the PLS-based Q and GLR method and MSPLS-based Q method, especially in early detection of small faults with abrupt or incipient behavior.

  1. Improved Data-based Fault Detection Strategy and Application to Distillation Columns

    KAUST Repository

    Madakyaru, Muddu; Harrou, Fouzi; Sun, Ying

    2017-01-01

    Chemical and petrochemical processes require continuous monitoring to detect abnormal events and to sustain normal operations. Furthermore, process monitoring enhances productivity, efficiency, and safety in process industries. Here, we propose an innovative statistical approach that exploits the advantages of multiscale partial least squares (MSPLS) models and generalized likelihood ratio (GLR) tests for fault detection in processes. Specifically, we combine an MSPLS algorithm with wavelet analysis to create our modeling framework. Then, we use GLR hypothesis testing based on the uncorrelated residuals obtained from the MSPLS model to improve fault detection. We use simulated distillation column data to evaluate the MSPLS-based GLR chart. Results show that our MSPLS-based GLR method is more powerful than the PLS-based Q and GLR method and MSPLS-based Q method, especially in early detection of small faults with abrupt or incipient behavior.

  2. Assessing community values for reducing agricultural emissions to improve water quality and protect coral health in the Great Barrier Reef

    Science.gov (United States)

    Rolfe, John; Windle, Jill

    2011-12-01

    Policymakers wanting to increase protection of the Great Barrier Reef from pollutants generated by agriculture need to identify when measures to improve water quality generate benefits to society that outweigh the costs involved. The research reported in this paper makes a contribution in several ways. First, it uses the improved science understanding about the links between management changes and reef health to bring together the analysis of costs and benefits of marginal changes, helping to demonstrate the appropriate way of addressing policy questions relating to reef protection. Second, it uses the scientific relationships to frame a choice experiment to value the benefits of improved reef health, with the results of mixed logit (random parameter) models linking improvements explicitly to changes in "water quality units." Third, the research demonstrates how protection values are consistent across a broader population, with some limited evidence of distance effects. Fourth, the information on marginal costs and benefits that are reported provide policymakers with information to help improve management decisions. The results indicate that while there is potential for water quality improvements to generate net benefits, high cost water quality improvements are generally uneconomic. A major policy implication is that cost thresholds for key pollutants should be set to avoid more expensive water quality proposals being selected.

  3. Improved spectral kurtosis with adaptive redundant multiwavelet packet and its applications for rotating machinery fault detection

    International Nuclear Information System (INIS)

    Chen, Jinglong; Zi, Yanyang; He, Zhengjia; Yuan, Jing

    2012-01-01

    Rotating machinery fault detection is significant to avoid serious accidents and huge economic losses effectively. However, due to the vibration signal with the character of non-stationarity and nonlinearity, the detection and extraction of the fault feature turn into a challenging task. Therefore, a novel method called improved spectral kurtosis (ISK) with adaptive redundant multiwavelet packet (ARMP) is proposed for this task. Spectral kurtosis (SK) has been proved to be a powerful tool to detect and characterize the non-stationary signal. To improve the SK in filter limitation and enhance the resolution of spectral analysis as well as match fault feature optimally, the ARMP is introduced into the SK. Moreover, since kurtosis does not reflect the actual trend of periodic impulses, the SK is improved by incorporating an evaluation index called envelope spectrum entropy as supplement. The proposed method is applied to the rolling element bearing and gear fault detection to validate its reliability and effectiveness. Compared with the conventional frequency spectrum, envelope spectrum, original SK and some single wavelet methods, the results indicate that it could improve the accuracy of frequency-band selection and enhance the ability of rotating machinery fault detection. (paper)

  4. Enhanced change detection performance reveals improved strategy use in avid action video game players.

    Science.gov (United States)

    Clark, Kait; Fleck, Mathias S; Mitroff, Stephen R

    2011-01-01

    Recent research has shown that avid action video game players (VGPs) outperform non-video game players (NVGPs) on a variety of attentional and perceptual tasks. However, it remains unknown exactly why and how such differences arise; while some prior research has demonstrated that VGPs' improvements stem from enhanced basic perceptual processes, other work indicates that they can stem from enhanced attentional control. The current experiment used a change-detection task to explore whether top-down strategies can contribute to VGPs' improved abilities. Participants viewed alternating presentations of an image and a modified version of the image and were tasked with detecting and localizing the changed element. Consistent with prior claims of enhanced perceptual abilities, VGPs were able to detect the changes while requiring less exposure to the change than NVGPs. Further analyses revealed this improved change detection performance may result from altered strategy use; VGPs employed broader search patterns when scanning scenes for potential changes. These results complement prior demonstrations of VGPs' enhanced bottom-up perceptual benefits by providing new evidence of VGPs' potentially enhanced top-down strategic benefits. Copyright © 2010 Elsevier B.V. All rights reserved.

  5. Airplane detection in remote sensing images using convolutional neural networks

    Science.gov (United States)

    Ouyang, Chao; Chen, Zhong; Zhang, Feng; Zhang, Yifei

    2018-03-01

    Airplane detection in remote sensing images remains a challenging problem and has also been taking a great interest to researchers. In this paper we propose an effective method to detect airplanes in remote sensing images using convolutional neural networks. Deep learning methods show greater advantages than the traditional methods with the rise of deep neural networks in target detection, and we give an explanation why this happens. To improve the performance on detection of airplane, we combine a region proposal algorithm with convolutional neural networks. And in the training phase, we divide the background into multi classes rather than one class, which can reduce false alarms. Our experimental results show that the proposed method is effective and robust in detecting airplane.

  6. Evaluation of Advanced Signal Processing Techniques to Improve Detection and Identification of Embedded Defects

    Energy Technology Data Exchange (ETDEWEB)

    Clayton, Dwight A. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Santos-Villalobos, Hector J. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Baba, Justin S. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2016-09-01

    , or an improvement in contrast over conventional SAFT reconstructed images. This report documents our efforts in four fronts: 1) Comparative study between traditional SAFT and FBD SAFT for concrete specimen with and without Alkali-Silica Reaction (ASR) damage, 2) improvement of our Model-Based Iterative Reconstruction (MBIR) for thick reinforced concrete [5], 3) development of a universal framework for sharing, reconstruction, and visualization of ultrasound NDE datasets, and 4) application of machine learning techniques for automated detection of ASR inside concrete. Our comparative study between FBD and traditional SAFT reconstruction images shows a clear difference between images of ASR and non-ASR specimens. In particular, the left first harmonic shows an increased contrast and sensitivity to ASR damage. For MBIR, we show the superiority of model-based techniques over delay and sum techniques such as SAFT. Improvements include elimination of artifacts caused by direct arrival signals, and increased contrast and Signal to Noise Ratio. For the universal framework, we document a format for data storage based on the HDF5 file format, and also propose a modular Graphic User Interface (GUI) for easy customization of data conversion, reconstruction, and visualization routines. Finally, two techniques for ASR automated detection are presented. The first technique is based on an analysis of the frequency content using Hilbert Transform Indicator (HTI) and the second technique employees Artificial Neural Network (ANN) techniques for training and classification of ultrasound data as ASR or non-ASR damaged classes. The ANN technique shows great potential with classification accuracy above 95%. These approaches are extensible to the detection of additional reinforced, thick concrete defects and damage.

  7. Improving Air Force Active Network Defense Systems through an Analysis of Intrusion Detection Techniques

    National Research Council Canada - National Science Library

    Dunklee, David R

    2007-01-01

    .... The research then presents four recommendations to improve DCC operations. These include: Transition or improve the current signature-based IDS systems to include the capability to query and visualize network flows to detect malicious traffic...

  8. Improving Anomaly Detection for Text-Based Protocols by Exploiting Message Structures

    Directory of Open Access Journals (Sweden)

    Christian M. Mueller

    2010-12-01

    Full Text Available Service platforms using text-based protocols need to be protected against attacks. Machine-learning algorithms with pattern matching can be used to detect even previously unknown attacks. In this paper, we present an extension to known Support Vector Machine (SVM based anomaly detection algorithms for the Session Initiation Protocol (SIP. Our contribution is to extend the amount of different features used for classification (feature space by exploiting the structure of SIP messages, which reduces the false positive rate. Additionally, we show how combining our approach with attribute reduction significantly improves throughput.

  9. A pragmatic approach to measuring, monitoring and evaluating interventions for improved tuberculosis case detection

    NARCIS (Netherlands)

    Blok, Lucie; Creswell, Jacob; Stevens, Robert; Brouwer, Miranda; Ramis, Oriol; Weil, Olivier; Klatser, Paul; Sahu, Suvanand; Bakker, Mirjam I.

    2014-01-01

    The inability to detect all individuals with active tuberculosis has led to a growing interest in new approaches to improve case detection. Policy makers and program staff face important challenges measuring effectiveness of newly introduced interventions and reviewing feasibility of scaling-up

  10. A pragmatic approach to measuring, monitoring and evaluating interventions for improved tuberculosis case detection.

    NARCIS (Netherlands)

    Blok, L; Creswell, J; Stevens, R.; Brouwer, M; Ramis, O; Weil, O; Klatser, P.R.; Sahu, S; Bakker, M.I.

    2014-01-01

    The inability to detect all individuals with active tuberculosis has led to a growing interest in new approaches to improve case detection. Policy makers and program staff face important challenges measuring effectiveness of newly introduced interventions and reviewing feasibility of scaling-up

  11. An improved electrochemiluminescence polymerase chain reaction method for highly sensitive detection of plant viruses

    International Nuclear Information System (INIS)

    Tang Yabing; Xing Da; Zhu Debin; Liu Jinfeng

    2007-01-01

    Recently, we have reported an electrochemiluminescence polymerase chain reaction (ECL-PCR) method for detection of genetically modified organisms. The ECL-PCR method was further improved in the current study by introducing a multi-purpose nucleic acid sequence that was specific to the tris(bipyridine) ruthenium (TBR) labeled probe, into the 5' terminal of the primers. The method was applied to detect plant viruses. Conserved sequence of the plant viruses was amplified by PCR. The product was hybridized with a biotin labeled probe and a TBR labeled probe. The hybridization product was separated by streptavidin-coated magnetic beads, and detected by measuring the ECL signals of the TBR labeled. Under the optimized conditions, the experiment results show that the detection limit is 50 fmol of PCR products, and the signal-to-noise ratio is in excess of 14.6. The method was used to detect banana streak virus, banana bunchy top virus, and papaya leaf curl virus. The experiment results show that this method could reliably identity viruses infected plant samples. The improved ECL-PCR approach has higher sensitivity and lower cost than previous approach. It can effectively detect the plant viruses with simplicity, stability, and high sensitivity

  12. Performance improvement of haptic collision detection using subdivision surface and sphere clustering.

    Directory of Open Access Journals (Sweden)

    A Ram Choi

    Full Text Available Haptics applications such as surgery simulations require collision detections that are more precise than others. An efficient collision detection method based on the clustering of bounding spheres was proposed in our prior study. This paper analyzes and compares the applied effects of the five most common subdivision surface methods on some 3D models for haptic collision detection. The five methods are Butterfly, Catmull-Clark, Mid-point, Loop, and LS3 (Least Squares Subdivision Surface. After performing a number of experiments, we have concluded that LS3 method is the most appropriate for haptic simulations. The more we applied surface subdivision, the more the collision detection results became precise. However, it is observed that the performance becomes better until a certain threshold and degrades afterward. In order to reduce the performance degradation, we adopted our prior work, which was the fast and precise collision detection method based on adaptive clustering. As a result, we obtained a notable improvement of the speed of collision detection.

  13. Identification of transcriptional biomarkers by RNA-sequencing for improved detection of β2-agonists abuse in goat skeletal muscle.

    Directory of Open Access Journals (Sweden)

    Luyao Zhao

    Full Text Available In this paper, high-throughput RNA-sequencing (RNA-seq was used to search for transcriptional biomarkers for β2-agonists. In combination with drug mechanisms, a smaller group of genes with higher detection accuracy was screened out. Unknown samples were first predicted by this group of genes, and liquid chromatograph tandem mass spectrometer (LC-MS/MS was applied to positive samples to validate the biomarkers. The results of principal component analysis (PCA, hierarchical cluster analysis (HCA and discriminant analysis (DA indicated that the eight genes screened by high-throughput RNA-seq were able to distinguish samples in the experimental group and control group. Compared with the nine genes selected from an earlier literature, 17 genes including these nine genes were proven to have a more satisfactory effect, which validated the accuracy of gene selection by RNA-seq. Then, six key genes were selected from the 17 genes according to the variable importance in projection (VIP value of greater than 1. The test results using the six genes and 17 genes were similar, revealing that the six genes were critical genes. By using the six genes, three positive samples possibly treated with drugs were screened out from 25 unknown samples through DA and partial least squares discriminant analysis (PLS-DA. Then, the three samples were verified by a standard method, and mapenterol was detected in a sample. Therefore, the six genes can be used as biomarkers to detect β2-agonists. Compared with the previous study, accurate detection of β2-agonists abuse using six key genes is an improvement method, which show great significance in the monitoring of β2-agonists abuse in animal husbandry.

  14. Chemicals of emerging concern in the Great Lakes Basin: an analysis of environmental exposures.

    Science.gov (United States)

    Klecka, Gary; Persoon, Carolyn; Currie, Rebecca

    2010-01-01

    stewardship as well as government risk assessment and risk management programs have been implemented over the past years for many of these compounds. Because risk management strategies for some of these contaminants have been implemented only recently, their impact on environmental concentrations, to date, remains unclear. Current evidence suggests that the concentrations of some brominated flame retardants are trending downward, while the concentrations of others appear to be increasing. Regulatory criteria are not available for many of the chemicals of emerging concern that were detected in the Great Lakes Basin. When criteria do exist, it is important to recognize that they were developed based on the best available science at the time. As the science evolves, regulatory criteria must be reassessed in light of new findings (e.g., consideration of new endpoints and mechanisms of action). Further, there are significant scientific gaps in our ability to interpret environmental monitoring data, including the need for: (a) improving the understanding of the effects of mixtures, (b) information on use of, and the commercial life cycle of chemicals and products that contain them, (c) information on source contributions and exposure pathways, and (d) the need for thoughtful additional regulatory,environmental, and health criteria. Discharges from wastewater treatment plants were identified as an important source of contaminants to surface waters in the Great Lakes Basin. Combined sewer overflows and agricultural operations were also found to be important contributors to concentrations in surface waters. Concentrations of many of the chemicals were generally the highest in the vicinity of these sources, decline with increasing distance from sources, and were generally low or non-detectable in the open waters of the Great Lakes.

  15. Mobile phones improve case detection and management of malaria in rural Bangladesh

    Science.gov (United States)

    2013-01-01

    Background The recent introduction of mobile phones into the rural Bandarban district of Bangladesh provided a resource to improve case detection and treatment of patients with malaria. Methods During studies to define the epidemiology of malaria in villages in south-eastern Bangladesh, an area with hypoendemic malaria, the project recorded 986 mobile phone calls from families because of illness suspected to be malaria between June 2010 and June 2012. Results Based on phone calls, field workers visited the homes with ill persons, and collected blood samples for malaria on 1,046 people. 265 (25%) of the patients tested were positive for malaria. Of the 509 symptomatic malaria cases diagnosed during this study period, 265 (52%) were detected because of an initial mobile phone call. Conclusion Mobile phone technology was found to be an efficient and effective method for rapidly detecting and treating patients with malaria in this remote area. This technology, when combined with local knowledge and field support, may be applicable to other hard-to-reach areas to improve malaria control. PMID:23374585

  16. Precipitation Dynamical Downscaling Over the Great Plains

    Science.gov (United States)

    Hu, Xiao-Ming; Xue, Ming; McPherson, Renee A.; Martin, Elinor; Rosendahl, Derek H.; Qiao, Lei

    2018-02-01

    Detailed, regional climate projections, particularly for precipitation, are critical for many applications. Accurate precipitation downscaling in the United States Great Plains remains a great challenge for most Regional Climate Models, particularly for warm months. Most previous dynamic downscaling simulations significantly underestimate warm-season precipitation in the region. This study aims to achieve a better precipitation downscaling in the Great Plains with the Weather Research and Forecast (WRF) model. To this end, WRF simulations with different physics schemes and nudging strategies are first conducted for a representative warm season. Results show that different cumulus schemes lead to more pronounced difference in simulated precipitation than other tested physics schemes. Simply choosing different physics schemes is not enough to alleviate the dry bias over the southern Great Plains, which is related to an anticyclonic circulation anomaly over the central and western parts of continental U.S. in the simulations. Spectral nudging emerges as an effective solution for alleviating the precipitation bias. Spectral nudging ensures that large and synoptic-scale circulations are faithfully reproduced while still allowing WRF to develop small-scale dynamics, thus effectively suppressing the large-scale circulation anomaly in the downscaling. As a result, a better precipitation downscaling is achieved. With the carefully validated configurations, WRF downscaling is conducted for 1980-2015. The downscaling captures well the spatial distribution of monthly climatology precipitation and the monthly/yearly variability, showing improvement over at least two previously published precipitation downscaling studies. With the improved precipitation downscaling, a better hydrological simulation over the trans-state Oologah watershed is also achieved.

  17. High resolution PET breast imager with improved detection efficiency

    Science.gov (United States)

    Majewski, Stanislaw

    2010-06-08

    A highly efficient PET breast imager for detecting lesions in the entire breast including those located close to the patient's chest wall. The breast imager includes a ring of imaging modules surrounding the imaged breast. Each imaging module includes a slant imaging light guide inserted between a gamma radiation sensor and a photodetector. The slant light guide permits the gamma radiation sensors to be placed in close proximity to the skin of the chest wall thereby extending the sensitive region of the imager to the base of the breast. Several types of photodetectors are proposed for use in the detector modules, with compact silicon photomultipliers as the preferred choice, due to its high compactness. The geometry of the detector heads and the arrangement of the detector ring significantly reduce dead regions thereby improving detection efficiency for lesions located close to the chest wall.

  18. Spatially valid proprioceptive cues improve the detection of a visual stimulus

    DEFF Research Database (Denmark)

    Jackson, Carl P T; Miall, R Chris; Balslev, Daniela

    2010-01-01

    , which has been demonstrated for other modality pairings. The aim of this study was to test whether proprioceptive signals can spatially cue a visual target to improve its detection. Participants were instructed to use a planar manipulandum in a forward reaching action and determine during this movement...

  19. Abnormal Event Detection in Wireless Sensor Networks Based on Multiattribute Correlation

    Directory of Open Access Journals (Sweden)

    Mengdi Wang

    2017-01-01

    Full Text Available Abnormal event detection is one of the vital tasks in wireless sensor networks. However, the faults of nodes and the poor deployment environment have brought great challenges to abnormal event detection. In a typical event detection technique, spatiotemporal correlations are collected to detect an event, which is susceptible to noises and errors. To improve the quality of detection results, we propose a novel approach for abnormal event detection in wireless sensor networks. This approach considers not only spatiotemporal correlations but also the correlations among observed attributes. A dependency model of observed attributes is constructed based on Bayesian network. In this model, the dependency structure of observed attributes is obtained by structure learning, and the conditional probability table of each node is calculated by parameter learning. We propose a new concept named attribute correlation confidence to evaluate the fitting degree between the sensor reading and the abnormal event pattern. On the basis of time correlation detection and space correlation detection, the abnormal events are identified. Experimental results show that the proposed algorithm can reduce the impact of interference factors and the rate of the false alarm effectively; it can also improve the accuracy of event detection.

  20. Spatial distribution and trends of total mercury in waters of the Great Lakes and connecting channels using an improved sampling technique

    International Nuclear Information System (INIS)

    Dove, A.; Hill, B.; Klawunn, P.; Waltho, J.; Backus, S.; McCrea, R.C.

    2012-01-01

    Environment Canada recently developed a clean method suitable for sampling trace levels of metals in surface waters. The results of sampling for total mercury in the Laurentian Great Lakes between 2003 and 2009 give a unique basin-wide perspective of concentrations of this important contaminant and represent improved knowledge of mercury in the region. Results indicate that concentrations of total mercury in the offshore regions of the lakes were within a relatively narrow range from about 0.3 to 0.8 ng/L. The highest concentrations were observed in the western basin of Lake Erie and concentrations then declined towards the east. Compared to the offshore, higher levels were observed at some nearshore locations, particularly in lakes Erie and Ontario. The longer-term temporal record of mercury in Niagara River suspended sediments indicates an approximate 30% decrease in equivalent water concentrations since 1986. - Highlights: ► Basin-wide concentrations of total mercury in Great Lakes surface waters are provided for the first time. ► A clean sampling method is described, stressing isolation of the sample from extraneous sources of contamination. ► Sub-ng/L concentrations of total mercury are observed in most Great Lakes offshore areas. ► Concentrations in the western basin of Lake Erie are consistently the highest observed in the basin. ► The longer-term record of mercury in Niagara River suspended sediments indicates an approximate 30% decrease since 1986. - A new, clean sampling method for metals is described and basin-wide measurements of total mercury are provided for Great Lakes surface waters for the first time.

  1. An Improved Saliency Detection Approach for Flying Apsaras in the Dunhuang Grotto Murals, China

    Directory of Open Access Journals (Sweden)

    Zhong Chen

    2015-01-01

    Full Text Available Saliency can be described as the ability of an item to be detected from its background in any particular scene, and it aims to estimate the probable location of the salient objects. Due to the salient map that computed by local contrast features can extract and highlight the edge parts including painting lines of Flying Apsaras, in this paper, we proposed an improved approach based on a frequency-tuned method for visual saliency detection of Flying Apsaras in the Dunhuang Grotto Murals, China. This improved saliency detection approach comprises three important steps: (1 image color and gray channel decomposition; (2 gray feature value computation and color channel convolution; (3 visual saliency definition based on normalization of previous visual saliency and spatial attention function. Unlike existing approaches that rely on many complex image features, this proposed approach only used local contrast and spatial attention information to simulate human’s visual attention stimuli. This improved approach resulted in a much more efficient salient map in the aspect of computing performance. Furthermore, experimental results on the dataset of Flying Apsaras in the Dunhuang Grotto Murals showed that the proposed visual saliency detection approach is very effective when compared with five other state-of-the-art approaches.

  2. Resolution-improved in situ DNA hybridization detection based on microwave photonic interrogation.

    Science.gov (United States)

    Cao, Yuan; Guo, Tuan; Wang, Xudong; Sun, Dandan; Ran, Yang; Feng, Xinhuan; Guan, Bai-ou

    2015-10-19

    In situ bio-sensing system based on microwave photonics filter (MPF) interrogation method with improved resolution is proposed and experimentally demonstrated. A microfiber Bragg grating (mFBG) is used as sensing probe for DNA hybridization detection. Different from the traditional wavelength monitoring technique, we use the frequency interrogation scheme for resolution-improved bio-sensing detection. Experimental results show that the frequency shift of MPF notch presents a linear response to the surrounding refractive index (SRI) change over the range of 1.33 to 1.38, with a SRI resolution up to 2.6 × 10(-5) RIU, which has been increased for almost two orders of magnitude compared with the traditional fundamental mode monitoring technique (~3.6 × 10(-3) RIU). Due to the high Q value (about 27), the whole process of DNA hybridization can be in situ monitored. The proposed MPF-based bio-sensing system provides a new interrogation method over the frequency domain with improved sensing resolution and rapid interrogation rate for biochemical and environmental measurement.

  3. Improved patient specific seizure detection during pre-surgical evaluation.

    LENUS (Irish Health Repository)

    Chua, Eric C-P

    2011-04-01

    There is considerable interest in improved off-line automated seizure detection methods that will decrease the workload of EEG monitoring units. Subject-specific approaches have been demonstrated to perform better than subject-independent ones. However, for pre-surgical diagnostics, the traditional method of obtaining a priori data to train subject-specific classifiers is not practical. We present an alternative method that works by adapting the threshold of a subject-independent to a specific subject based on feedback from the user.

  4. Guiding principles for the improved governance of port and shipping impacts in the Great Barrier Reef.

    Science.gov (United States)

    Grech, A; Bos, M; Brodie, J; Coles, R; Dale, A; Gilbert, R; Hamann, M; Marsh, H; Neil, K; Pressey, R L; Rasheed, M A; Sheaves, M; Smith, A

    2013-10-15

    The Great Barrier Reef (GBR) region of Queensland, Australia, encompasses a complex and diverse array of tropical marine ecosystems of global significance. The region is also a World Heritage Area and largely within one of the world's best managed marine protected areas. However, a recent World Heritage Committee report drew attention to serious governance problems associated with the management of ports and shipping. We review the impacts of ports and shipping on biodiversity in the GBR, and propose a series of guiding principles to improve the current governance arrangements. Implementing these principles will increase the capacity of decision makers to minimize the impacts of ports and shipping on biodiversity, and will provide certainty and clarity to port operators and developers. A 'business as usual' approach could lead to the GBR's inclusion on the List of World Heritage in Danger in 2014. Copyright © 2013 Elsevier Ltd. All rights reserved.

  5. Improved OAM-Based Radar Targets Detection Using Uniform Concentric Circular Arrays

    Directory of Open Access Journals (Sweden)

    Mingtuan Lin

    2016-01-01

    Full Text Available Without any relative moves or beam scanning, the novel Orbital-Angular-Momentum- (OAM- based radar targets detection technique using uniform concentric circular arrays (UCCAs shows the azimuthal estimation ability, which provides new perspective for radar system design. However, the main estimation method, that is, Fast Fourier Transform (FFT, under this scheme suffers from low resolution. As a solution, this paper rebuilds the OAM-based radar targets detection model and introduces the multiple signal classification (MUSIC algorithm to improve the resolution for detecting targets within the main lobes. The spatial smoothing technique is proposed to tackle the coherent problem brought by the proposed model. Analytical study and simulation demonstrate the superresolution estimation capacity the MUSIC algorithm can achieve for detecting targets within the main lobes. The performance of the MUSIC algorithm to detect targets not illuminated by the main lobes is further evaluated. Despite the fact that MUSIC algorithm loses the resolution advantage under this case, its estimation is more robust than that of the FFT method. Overall, the proposed MUSIC algorithm for the OAM-based radar system demonstrates the superresolution ability for detecting targets within the main lobes and good robustness for targets out of the main lobes.

  6. Implementation. Improving caries detection, assessment, diagnosis and monitoring.

    Science.gov (United States)

    Pitts, N B

    2009-01-01

    This chapter deals with improving the detection, assessment, diagnosis and monitoring of caries to ensure optimal personalized caries management. This can be achieved by delivering what we have (synthesized evidence and international consensus) better and more consistently, as well as driving research and innovation in the areas where we need them. There is a need to better understand the interrelated pieces of the jigsaw that makes up evidence-based dentistry, i.e. the linkages between (a) research and synthesis, (b) dissemination of research results and (c) the implementation of research findings which should ensure that research findings change practice at the clinician-patient level. The current situation is outlined; it is at the implementation step where preventive caries control seems to have failed in some countries but not others. Opportunities for implementation include: capitalizing on the World Health Organization's global policy for improvement of oral health, which sets out an action plan for health promotion and integrated disease prevention; utilizing the developments around the International Caries Detection and Assessment System wardrobe of options and e-learning; building on initiatives from the International Dental Federation and the American Dental Association and linking these to patients' preferences, the wider moves to wellbeing and health maintenance. Challenges for implementation include the slow pace of evolution around dental remuneration systems and some groups of dentists failing to embrace clinical prevention. In the future, implementation of current and developing evidence should be accompanied by research into getting research findings into routine practice, with impacts on the behaviour of patients, professionals and policy makers. Copyright 2009 S. Karger AG, Basel

  7. Enhancing Community Detection By Affinity-based Edge Weighting Scheme

    Energy Technology Data Exchange (ETDEWEB)

    Yoo, Andy [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Sanders, Geoffrey [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Henson, Van [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Vassilevski, Panayot [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2015-10-05

    Community detection refers to an important graph analytics problem of finding a set of densely-connected subgraphs in a graph and has gained a great deal of interest recently. The performance of current community detection algorithms is limited by an inherent constraint of unweighted graphs that offer very little information on their internal community structures. In this paper, we propose a new scheme to address this issue that weights the edges in a given graph based on recently proposed vertex affinity. The vertex affinity quantifies the proximity between two vertices in terms of their clustering strength, and therefore, it is ideal for graph analytics applications such as community detection. We also demonstrate that the affinity-based edge weighting scheme can improve the performance of community detection algorithms significantly.

  8. Knowledge Graphs as Context Models: Improving the Detection of Cross-Language Plagiarism with Paraphrasing

    OpenAIRE

    Franco-Salvador, Marc; Gupta, Parth; Rosso, Paolo

    2013-01-01

    Cross-language plagiarism detection attempts to identify and extract automatically plagiarism among documents in different languages. Plagiarized fragments can be translated verbatim copies or may alter their structure to hide the copying, which is known as paraphrasing and is more difficult to detect. In order to improve the paraphrasing detection, we use a knowledge graph-based approach to obtain and compare context models of document fragments in different languages. Experimental results i...

  9. Improving Focal Depth Estimates: Studies of Depth Phase Detection at Regional Distances

    Science.gov (United States)

    Stroujkova, A.; Reiter, D. T.; Shumway, R. H.

    2006-12-01

    networks of regional stations using a Grid-search, Multiple-Event Location method (GMEL; Rodi and Toksöz, 2000; 2001). 3. Surface-wave dispersion inversion for event depth and focal mechanism (Herrmann and Ammon, 2002). To validate our approach and provide quality control for our solutions, we applied the techniques to moderated- sized events (mb between 4.5 and 6.0) with known focal mechanisms. We illustrate the techniques using events observed at regional distances from the KSAR (Wonju, South Korea) teleseismic array and other nearby broadband three-component stations. Our results indicate that the techniques can produce excellent agreement between the various depth estimates. In addition, combining the techniques into a "unified" estimate greatly reduced location errors and improved robustness of the solution, even if results from the individual methods yielded large standard errors.

  10. Large Area Crop Inventory Experiment (LACIE). Detecting and monitoring agricultural vegetative water stress over large areas using LANDSAT digital data. [Great Plains

    Science.gov (United States)

    Thompson, D. R.; Wehmanen, O. A. (Principal Investigator)

    1978-01-01

    The author has identified the following significant results. The Green Number Index technique which uses LANDSAT digital data from 5X6 nautical mile sampling frames was expanded to evaluate its usefulness in detecting and monitoring vegetative water stress over the Great Plains. At known growth stages for wheat, segments were classified as drought or non drought. Good agreement was found between the 18 day remotely sensed data and a weekly ground-based crop moisture index. Operational monitoring of the 1977 U.S.S.R. and Australian wheat crops indicated drought conditions. Drought isoline maps produced by the Green Number Index technique were in good agreement with conventional sources.

  11. Improved Method of Detection Falsification Results the Digital Image in Conditions of Attacks

    Directory of Open Access Journals (Sweden)

    Kobozeva A.A.

    2016-08-01

    Full Text Available The modern level of information technologies development has led to unheard ease embodiments hitherto unauthorized modifications of digital content. At the moment, very important question is the effective expert examination of authenticity of digital images, video, audio, development of the methods for identification and localization of violations of their integrity using these contents for purposes other than entertainment. Present paper deals with the improvement of the detection method of the cloning results in digital images - one of the most frequently used in the software tools falsification realized in all modern graphics editors. The method is intended for clone detection areas and pre-image in terms of additional disturbing influences in the image after the cloning operation for "masking" of the results, which complicates the search process. The improvement is aimed at reducing the number of "false alarms", when the area of the clone / pre-image detected in the original image or the localization of the identified areas do not correspond to the real clone and pre-image. The proposed improvement, based on analysis of different sizes per-pixel image blocks with the least difference from each other, has made it possible efficient functioning of the method, regardless of the specificity of the analyzed digital image.

  12. Detection of gas molecules on single Mn adatom adsorbed graphyne: a DFT-D study

    Science.gov (United States)

    Lu, Zhansheng; Lv, Peng; Ma, Dongwei; Yang, Xinwei; Li, Shuo; Yang, Zongxian

    2018-02-01

    As one of the prominent applications in intelligent systems, gas sensing technology has attracted great interest in both industry and academia. In the current study, the pristine graphyne (GY) without and with a single Mn atom is investigated to detect the gas molecules (CO, CH4, CO2, NH3, NO and O2). The pristine GY is promising to detect O2 molecules because of its chemical adsorption on GY with large electron transfer. The great stability of the Mn/GY is found, and the Mn atom prefers to anchor at the alkyne ring as a single atom. Upon single Mn atom anchoring, the sensitivity and selectivity of GY based gas sensors is significantly improved for various molecules, except CH4. The recovery time of the Mn/GY after detecting the gas molecules may help to appraise the detection efficiency for the Mn/GY. The current study will help to understand the mechanism of detecting the gas molecules, and extend the potentially fascinating applications of GY-based materials.

  13. Phenomenon detection device

    International Nuclear Information System (INIS)

    Suzuki, Yasuo.

    1994-01-01

    Detection signals for a specific phenomenon outputted from any of detectors are distributed by way of half mirrors and inputted to a logic discrimination circuit by way of a photoelectric convertor. The photoelectric convertor detects the quantity of light corresponding to the optical signals from more than two detectors which detected the phenomenon, and outputs detection signals to the logic discrimination circuit. If the phenomenon is detected, since both inputs turn ON in the logic discrimination circuit in accordance with the predetermined logical sum, the occurrence of a specific phenomenon is detected. Thus, an optical system substantially comprises half mirrors, reflection mirrors and photoelectric convertor in combination provides a logic circuit. Since the circuit which transmits signals of the detectors is constituted with an optical system using the half mirrors, the number of parts constituting the logic circuit can greatly be saved. In addition, since the optical system comprises mirrors or half mirrors which have been used so far, they can be used, once assembled, quasipermanently, and the reliability can be enhanced greatly. (N.H.)

  14. Edge detection of optical subaperture image based on improved differential box-counting method

    Science.gov (United States)

    Li, Yi; Hui, Mei; Liu, Ming; Dong, Liquan; Kong, Lingqin; Zhao, Yuejin

    2018-01-01

    Optical synthetic aperture imaging technology is an effective approach to improve imaging resolution. Compared with monolithic mirror system, the image of optical synthetic aperture system is often more complex at the edge, and as a result of the existence of gap between segments, which makes stitching becomes a difficult problem. So it is necessary to extract the edge of subaperture image for achieving effective stitching. Fractal dimension as a measure feature can describe image surface texture characteristics, which provides a new approach for edge detection. In our research, an improved differential box-counting method is used to calculate fractal dimension of image, then the obtained fractal dimension is mapped to grayscale image to detect edges. Compared with original differential box-counting method, this method has two improvements as follows: by modifying the box-counting mechanism, a box with a fixed height is replaced by a box with adaptive height, which solves the problem of over-counting the number of boxes covering image intensity surface; an image reconstruction method based on super-resolution convolutional neural network is used to enlarge small size image, which can solve the problem that fractal dimension can't be calculated accurately under the small size image, and this method may well maintain scale invariability of fractal dimension. The experimental results show that the proposed algorithm can effectively eliminate noise and has a lower false detection rate compared with the traditional edge detection algorithms. In addition, this algorithm can maintain the integrity and continuity of image edge in the case of retaining important edge information.

  15. Portopulmonary hypertension: Improved detection using CT and echocardiography in combination

    International Nuclear Information System (INIS)

    Devaraj, Anand; Loveridge, Robert; Bernal, William; Willars, Christopher; Wendon, Julia A.; Auzinger, Georg; Bosanac, Diana; Stefanidis, Konstantinos; Desai, Sujal R.

    2014-01-01

    To establish the relationship between CT signs of pulmonary hypertension and mean pulmonary artery pressure (mPAP) in patients with liver disease, and to determine the additive value of CT in the detection of portopulmonary hypertension in combination with transthoracic echocardiography. Forty-nine patients referred for liver transplantation were retrospectively reviewed. Measured CT signs included the main pulmonary artery/ascending aorta diameter ratio (PA/AA meas ) and the mean left and right main PA diameter (RLPA meas ). Enlargement of the pulmonary artery compared to the ascending aorta was also assessed visually (PA/AA vis ). CT measurements were correlated with right-sided heart catheter-derived mPAP. The ability of PA/AA vis combined with echocardiogram-derived right ventricular systolic pressure (RVSP) to detect portopulmonary hypertension was tested with ROC analysis. There were moderate correlations between mPAP and both PA/AA meas and RLPA meas (r s = 0.41 and r s = 0.42, respectively; p vis and transthoracic echocardiography-derived RVSP improved the detection of portopulmonary hypertension (AUC = 0.8, p < 0.0001). CT contributes to the non-invasive detection of portopulmonary hypertension when used in a diagnostic algorithm with transthoracic echocardiography. CT may have a role in the pre-liver transplantation triage of patients with portopulmonary hypertension for right-sided heart catheterisation. (orig.)

  16. Classification with an edge: Improving semantic image segmentation with boundary detection

    Science.gov (United States)

    Marmanis, D.; Schindler, K.; Wegner, J. D.; Galliani, S.; Datcu, M.; Stilla, U.

    2018-01-01

    We present an end-to-end trainable deep convolutional neural network (DCNN) for semantic segmentation with built-in awareness of semantically meaningful boundaries. Semantic segmentation is a fundamental remote sensing task, and most state-of-the-art methods rely on DCNNs as their workhorse. A major reason for their success is that deep networks learn to accumulate contextual information over very large receptive fields. However, this success comes at a cost, since the associated loss of effective spatial resolution washes out high-frequency details and leads to blurry object boundaries. Here, we propose to counter this effect by combining semantic segmentation with semantically informed edge detection, thus making class boundaries explicit in the model. First, we construct a comparatively simple, memory-efficient model by adding boundary detection to the SEGNET encoder-decoder architecture. Second, we also include boundary detection in FCN-type models and set up a high-end classifier ensemble. We show that boundary detection significantly improves semantic segmentation with CNNs in an end-to-end training scheme. Our best model achieves >90% overall accuracy on the ISPRS Vaihingen benchmark.

  17. Railway clearance intrusion detection method with binocular stereo vision

    Science.gov (United States)

    Zhou, Xingfang; Guo, Baoqing; Wei, Wei

    2018-03-01

    In the stage of railway construction and operation, objects intruding railway clearance greatly threaten the safety of railway operation. Real-time intrusion detection is of great importance. For the shortcomings of depth insensitive and shadow interference of single image method, an intrusion detection method with binocular stereo vision is proposed to reconstruct the 3D scene for locating the objects and judging clearance intrusion. The binocular cameras are calibrated with Zhang Zhengyou's method. In order to improve the 3D reconstruction speed, a suspicious region is firstly determined by background difference method of a single camera's image sequences. The image rectification, stereo matching and 3D reconstruction process are only executed when there is a suspicious region. A transformation matrix from Camera Coordinate System(CCS) to Track Coordinate System(TCS) is computed with gauge constant and used to transfer the 3D point clouds into the TCS, then the 3D point clouds are used to calculate the object position and intrusion in TCS. The experiments in railway scene show that the position precision is better than 10mm. It is an effective way for clearance intrusion detection and can satisfy the requirement of railway application.

  18. Multifunctional Dendrimer-templated Antibody Presentation on Biosensor Surfaces for Improved Biomarker Detection.

    Science.gov (United States)

    Han, Hye Jung; Kannan, Rangaramanujam M; Wang, Sunxi; Mao, Guangzhao; Kusanovic, Juan Pedro; Romero, Roberto

    2010-02-08

    Dendrimers, with their well-defined globular shape and a high density of functional groups, are ideal nanoscale materials for templating sensor surfaces. This work exploits dendrimers as a versatile platform for capturing biomarkers with improved sensitivity and specificity. Synthesis, characterization, fabrication, and functional validation of the dendrimer-based assay platform are described. Bifunctional hydroxyl/thiol functionalized G4-polyamidoamine (PAMAM) dendrimer is synthesized and immobilized on to the polyethylene-glycol (PEG)-functionalized assay plate by coupling PEG-maleimide and dendrimer thiol groups. Simultaneously, part of the dendrimer thiol groups are converted to hydrazide functionalities. The resulting dendrimer-modified surface is coupled to the capture antibody in the Fc region of the oxidized antibody. This preserves the orientation flexibility of the antigen binding region (Fv) of the antibody. To validate the approach, the fabricated plates are further used as a solid phase for developing a sandwich type ELISA to detect IL-6 and IL-1β, important biomarkers for early stages of chorioamnionitis. The dendrimer-modified plate provides assays with significantly enhanced sensitivity, lower nonspecific adsorption, and a detection limit of 0.13 pg ml -1 for IL-6 luminol detection and 1.15 pg ml -1 for IL-1β TMB detection, which are significantly better than those for the traditional ELISA. The assays were validated in human serum samples from normal (non-pregnant) woman and pregnant women with pyelonephritis. The specificity and the improved sensitivity of the dendrimer-based capture strategy could have significant implications for the detection of a wide range of cytokines and biomarkers since the capture strategy could be applied to multiplex microbead assays, conductometric immunosensors and field effect biosensors.

  19. Improving staff response to seizures on the epilepsy monitoring unit with online EEG seizure detection algorithms.

    Science.gov (United States)

    Rommens, Nicole; Geertsema, Evelien; Jansen Holleboom, Lisanne; Cox, Fieke; Visser, Gerhard

    2018-05-11

    User safety and the quality of diagnostics on the epilepsy monitoring unit (EMU) depend on reaction to seizures. Online seizure detection might improve this. While good sensitivity and specificity is reported, the added value above staff response is unclear. We ascertained the added value of two electroencephalograph (EEG) seizure detection algorithms in terms of additional detected seizures or faster detection time. EEG-video seizure recordings of people admitted to an EMU over one year were included, with a maximum of two seizures per subject. All recordings were retrospectively analyzed using Encevis EpiScan and BESA Epilepsy. Detection sensitivity and latency of the algorithms were compared to staff responses. False positive rates were estimated on 30 uninterrupted recordings (roughly 24 h per subject) of consecutive subjects admitted to the EMU. EEG-video recordings used included 188 seizures. The response rate of staff was 67%, of Encevis 67%, and of BESA Epilepsy 65%. Of the 62 seizures missed by staff, 66% were recognized by Encevis and 39% by BESA Epilepsy. The median latency was 31 s (staff), 10 s (Encevis), and 14 s (BESA Epilepsy). After correcting for walking time from the observation room to the subject, both algorithms detected faster than staff in 65% of detected seizures. The full recordings included 617 h of EEG. Encevis had a median false positive rate of 4.9 per 24 h and BESA Epilepsy of 2.1 per 24 h. EEG-video seizure detection algorithms may improve reaction to seizures by improving the total number of seizures detected and the speed of detection. The false positive rate is feasible for use in a clinical situation. Implementation of these algorithms might result in faster diagnostic testing and better observation during seizures. Copyright © 2018. Published by Elsevier Inc.

  20. An improved technique for the detection of pilot contamination attacks in TDD wireless communication systems

    Directory of Open Access Journals (Sweden)

    Mihaylova Dimitriya

    2017-01-01

    Full Text Available One of the problems phasing the physical layer security of a wireless system is its vulnerability to pilot contamination attacks and hence schemes for its detection need to be applied. A method proposed in the literature consists of training with two N-PSK pilots. Although the method is effective in most of the cases, it is not able to discover an attack initiated during the transmission of the second pilot from the pair if both the legitimate and non-legitimate pilots coincide. In this current paper, an improvement to this method is proposed which detects an intruder who misses the first pilot transmission. The suggested improvement eliminates the usage of threshold values in the detection – a main drawback of previously existing solution.

  1. Improved anomaly detection using multi-scale PLS and generalized likelihood ratio test

    KAUST Repository

    Madakyaru, Muddu

    2017-02-16

    Process monitoring has a central role in the process industry to enhance productivity, efficiency, and safety, and to avoid expensive maintenance. In this paper, a statistical approach that exploit the advantages of multiscale PLS models (MSPLS) and those of a generalized likelihood ratio (GLR) test to better detect anomalies is proposed. Specifically, to consider the multivariate and multi-scale nature of process dynamics, a MSPLS algorithm combining PLS and wavelet analysis is used as modeling framework. Then, GLR hypothesis testing is applied using the uncorrelated residuals obtained from MSPLS model to improve the anomaly detection abilities of these latent variable based fault detection methods even further. Applications to a simulated distillation column data are used to evaluate the proposed MSPLS-GLR algorithm.

  2. Improved anomaly detection using multi-scale PLS and generalized likelihood ratio test

    KAUST Repository

    Madakyaru, Muddu; Harrou, Fouzi; Sun, Ying

    2017-01-01

    Process monitoring has a central role in the process industry to enhance productivity, efficiency, and safety, and to avoid expensive maintenance. In this paper, a statistical approach that exploit the advantages of multiscale PLS models (MSPLS) and those of a generalized likelihood ratio (GLR) test to better detect anomalies is proposed. Specifically, to consider the multivariate and multi-scale nature of process dynamics, a MSPLS algorithm combining PLS and wavelet analysis is used as modeling framework. Then, GLR hypothesis testing is applied using the uncorrelated residuals obtained from MSPLS model to improve the anomaly detection abilities of these latent variable based fault detection methods even further. Applications to a simulated distillation column data are used to evaluate the proposed MSPLS-GLR algorithm.

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

    Science.gov (United States)

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

    2011-01-01

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

  4. Surface Coatings as Xenon Diffusion Barriers for Improved Detection of Clandestine Nuclear Explosions

    OpenAIRE

    Bläckberg, Lisa

    2014-01-01

    This thesis investigates surface coatings as xenon diffusion barriers on plastic scintillators. The motivation for the work is improved radioxenon detection systems, used within the verification regime of the Comprehensive Nuclear-Test-Ban Treaty (CTBT). One type of radioxenon detection systems used in this context is the Swedish SAUNA system. This system uses a cylindrical plastic scintillator cell to measure the beta decay from radioxenon isotopes. The detector cell also acts as a container...

  5. Vehicle parts detection based on Faster - RCNN with location constraints of vehicle parts feature point

    Science.gov (United States)

    Yang, Liqin; Sang, Nong; Gao, Changxin

    2018-03-01

    Vehicle parts detection plays an important role in public transportation safety and mobility. The detection of vehicle parts is to detect the position of each vehicle part. We propose a new approach by combining Faster RCNN and three level cascaded convolutional neural network (DCNN). The output of Faster RCNN is a series of bounding boxes with coordinate information, from which we can locate vehicle parts. DCNN can precisely predict feature point position, which is the center of vehicle part. We design an output strategy by combining these two results. There are two advantages for this. The quality of the bounding boxes are greatly improved, which means vehicle parts feature point position can be located more precise. Meanwhile we preserve the position relationship between vehicle parts and effectively improve the validity and reliability of the result. By using our algorithm, the performance of the vehicle parts detection improve obviously compared with Faster RCNN.

  6. Improved Ordinary Measure and Image Entropy Theory based intelligent Copy Detection Method

    Directory of Open Access Journals (Sweden)

    Dengpan Ye

    2011-10-01

    Full Text Available Nowadays, more and more multimedia websites appear in social network. It brings some security problems, such as privacy, piracy, disclosure of sensitive contents and so on. Aiming at copyright protection, the copy detection technology of multimedia contents becomes a hot topic. In our previous work, a new computer-based copyright control system used to detect the media has been proposed. Based on this system, this paper proposes an improved media feature matching measure and an entropy based copy detection method. The Levenshtein Distance was used to enhance the matching degree when using for feature matching measure in copy detection. For entropy based copy detection, we make a fusion of the two features of entropy matrix of the entropy feature we extracted. Firstly,we extract the entropy matrix of the image and normalize it. Then, we make a fusion of the eigenvalue feature and the transfer matrix feature of the entropy matrix. The fused features will be used for image copy detection. The experiments show that compared to use these two kinds of features for image detection singly, using feature fusion matching method is apparent robustness and effectiveness. The fused feature has a high detection for copy images which have been received some attacks such as noise, compression, zoom, rotation and so on. Comparing with referred methods, the method proposed is more intelligent and can be achieved good performance.

  7. Incipient failure detection of space shuttle main engine turbopump bearings using vibration envelope detection

    Science.gov (United States)

    Hopson, Charles B.

    1987-01-01

    The results of an analysis performed on seven successive Space Shuttle Main Engine (SSME) static test firings, utilizing envelope detection of external accelerometer data are discussed. The results clearly show the great potential for using envelope detection techniques in SSME incipient failure detection.

  8. Native plant development and restoration program for the Great Basin, USA

    Science.gov (United States)

    N. L. Shaw; M. Pellant; P. Olweli; S. L. Jensen; E. D. McArthur

    2008-01-01

    The Great Basin Native Plant Selection and Increase Project, organized by the USDA Bureau of Land Management, Great Basin Restoration Initiative and the USDA Forest Service, Rocky Mountain Research Station in 2000 as a multi-agency collaborative program (http://www.fs.fed.us/rm/boise/research/shrub/greatbasin.shtml), has the objective of improving the availability of...

  9. Improved detection of canine Angiostrongylus vasorum infection using real-time PCR and indirect ELISA.

    Science.gov (United States)

    Jefferies, Ryan; Morgan, Eric R; Helm, Jenny; Robinson, Matthew; Shaw, Susan E

    2011-12-01

    This study reports the development of a real-time PCR assay and an indirect ELISA to improve on current detection of canine Angiostrongylus vasorum infection. A highly specific fluorescent probe-based, real-time PCR assay was developed to target the A. vasorum second internal transcribed spacer region and detected DNA in EDTA blood, lung tissue, broncho-alveolar larvage fluid, endotracheal mucus, pharyngeal swabs and faecal samples. PCR was fast (∼1 h), highly efficient when using EDTA blood samples, consistently detected a single molecule of parasite DNA and did not amplify DNA from other parasitic nematodes or definitive host species. An indirect ELISA was also developed using the soluble protein fraction from adult A. vasorum worms. Some cross-reactive antigen recognition was observed when tested against sera from dogs infected with Crenosoma vulpis (n = 8), Toxocara canis (n = 5) and Dirofilaria immitis (n = 5). This was largely overcome by setting the cut-off for a positive result at an appropriately high level. Field evaluation of the real-time PCR and ELISA was conducted by testing sera and EDTA blood from dogs with suspected A. vasorum infection (n = 148) and compared with the Baermann's larval migration test in faeces. Thirty-one dogs were positive by at least one test. Of these, 20 (65%) were detected by the Baermann method, 18 (58%) by blood PCR, 24 (77%) by ELISA and 28 (90%) by blood PCR and ELISA together. Combined testing using real-time PCR and ELISA therefore improved the detection rate of A. vasorum infection and holds promise for improved clinical diagnosis and epidemiological investigation.

  10. Great Apes

    Science.gov (United States)

    Sleeman, Jonathan M.; Cerveny, Shannon

    2014-01-01

    Anesthesia of great apes is often necessary to conduct diagnostic analysis, provide therapeutics, facilitate surgical procedures, and enable transport and translocation for conservation purposes. Due to the stress of remote delivery injection of anesthetic agents, recent studies have focused on oral delivery and/or transmucosal absorption of preanesthetic and anesthetic agents. Maintenance of the airway and provision of oxygen is an important aspect of anesthesia in great ape species. The provision of analgesia is an important aspect of the anesthesia protocol for any procedure involving painful stimuli. Opioids and nonsteroidal anti-inflammatory drugs (NSAIDs) are often administered alone, or in combination to provide multi-modal analgesia. There is increasing conservation management of in situ great ape populations, which has resulted in the development of field anesthesia techniques for free-living great apes for the purposes of translocation, reintroduction into the wild, and clinical interventions.

  11. Hybridization chain reaction amplification for highly sensitive fluorescence detection of DNA with dextran coated microarrays.

    Science.gov (United States)

    Chao, Jie; Li, Zhenhua; Li, Jing; Peng, Hongzhen; Su, Shao; Li, Qian; Zhu, Changfeng; Zuo, Xiaolei; Song, Shiping; Wang, Lianhui; Wang, Lihua

    2016-07-15

    Microarrays of biomolecules hold great promise in the fields of genomics, proteomics, and clinical assays on account of their remarkably parallel and high-throughput assay capability. However, the fluorescence detection used in most conventional DNA microarrays is still limited by sensitivity. In this study, we have demonstrated a novel universal and highly sensitive platform for fluorescent detection of sequence specific DNA at the femtomolar level by combining dextran-coated microarrays with hybridization chain reaction (HCR) signal amplification. Three-dimensional dextran matrix was covalently coated on glass surface as the scaffold to immobilize DNA recognition probes to increase the surface binding capacity and accessibility. DNA nanowire tentacles were formed on the matrix surface for efficient signal amplification by capturing multiple fluorescent molecules in a highly ordered way. By quantifying microscopic fluorescent signals, the synergetic effects of dextran and HCR greatly improved sensitivity of DNA microarrays, with a detection limit of 10fM (1×10(5) molecules). This detection assay could recognize one-base mismatch with fluorescence signals dropped down to ~20%. This cost-effective microarray platform also worked well with samples in serum and thus shows great potential for clinical diagnosis. Copyright © 2016 Elsevier B.V. All rights reserved.

  12. Detection of abnormal item based on time intervals for recommender systems.

    Science.gov (United States)

    Gao, Min; Yuan, Quan; Ling, Bin; Xiong, Qingyu

    2014-01-01

    With the rapid development of e-business, personalized recommendation has become core competence for enterprises to gain profits and improve customer satisfaction. Although collaborative filtering is the most successful approach for building a recommender system, it suffers from "shilling" attacks. In recent years, the research on shilling attacks has been greatly improved. However, the approaches suffer from serious problem in attack model dependency and high computational cost. To solve the problem, an approach for the detection of abnormal item is proposed in this paper. In the paper, two common features of all attack models are analyzed at first. A revised bottom-up discretized approach is then proposed based on time intervals and the features for the detection. The distributions of ratings in different time intervals are compared to detect anomaly based on the calculation of chi square distribution (χ(2)). We evaluated our approach on four types of items which are defined according to the life cycles of these items. The experimental results show that the proposed approach achieves a high detection rate with low computational cost when the number of attack profiles is more than 15. It improves the efficiency in shilling attacks detection by narrowing down the suspicious users.

  13. Detection of Abnormal Item Based on Time Intervals for Recommender Systems

    Directory of Open Access Journals (Sweden)

    Min Gao

    2014-01-01

    Full Text Available With the rapid development of e-business, personalized recommendation has become core competence for enterprises to gain profits and improve customer satisfaction. Although collaborative filtering is the most successful approach for building a recommender system, it suffers from “shilling” attacks. In recent years, the research on shilling attacks has been greatly improved. However, the approaches suffer from serious problem in attack model dependency and high computational cost. To solve the problem, an approach for the detection of abnormal item is proposed in this paper. In the paper, two common features of all attack models are analyzed at first. A revised bottom-up discretized approach is then proposed based on time intervals and the features for the detection. The distributions of ratings in different time intervals are compared to detect anomaly based on the calculation of chi square distribution (χ2. We evaluated our approach on four types of items which are defined according to the life cycles of these items. The experimental results show that the proposed approach achieves a high detection rate with low computational cost when the number of attack profiles is more than 15. It improves the efficiency in shilling attacks detection by narrowing down the suspicious users.

  14. Significance of MPEG-7 textural features for improved mass detection in mammography.

    Science.gov (United States)

    Eltonsy, Nevine H; Tourassi, Georgia D; Fadeev, Aleksey; Elmaghraby, Adel S

    2006-01-01

    The purpose of the study is to investigate the significance of MPEG-7 textural features for improving the detection of masses in screening mammograms. The detection scheme was originally based on morphological directional neighborhood features extracted from mammographic regions of interest (ROIs). Receiver Operating Characteristics (ROC) was performed to evaluate the performance of each set of features independently and merged into a back-propagation artificial neural network (BPANN) using the leave-one-out sampling scheme (LOOSS). The study was based on a database of 668 mammographic ROIs (340 depicting cancer regions and 328 depicting normal parenchyma). Overall, the ROC area index of the BPANN using the directional morphological features was Az=0.85+/-0.01. The MPEG-7 edge histogram descriptor-based BPNN showed an ROC area index of Az=0.71+/-0.01 while homogeneous textural descriptors using 30 and 120 channels helped the BPNN achieve similar ROC area indexes of Az=0.882+/-0.02 and Az=0.877+/-0.01 respectively. After merging the MPEG-7 homogeneous textural features with the directional neighborhood features the performance of the BPANN increased providing an ROC area index of Az=0.91+/-0.01. MPEG-7 homogeneous textural descriptor significantly improved the morphology-based detection scheme.

  15. On the theoretical aspects of improved fog detection and prediction in India

    Science.gov (United States)

    Dey, Sagnik

    2018-04-01

    The polluted Indo-Gangetic Basin (IGB) in northern India experiences fog (a condition when visibility degrades below 1 km) every winter (Dec-Jan) causing a massive loss of economy and even loss of life due to accidents. This can be minimized by improved fog detection (especially at night) and forecasting so that activities can be reorganized accordingly. Satellites detect fog at night by a positive brightness temperature difference (BTD). However, fixing the right BTD threshold holds the key to accuracy. Here I demonstrate the sensitivity of BTD in response to changes in fog and surface emissivity and their temperatures and justify a new BTD threshold. Further I quantify the dependence of critical fog droplet number concentration, NF (i.e. minimum fog concentration required to degrade visibility below 1 km) on liquid water content (LWC). NF decreases exponentially with an increase in LWC from 0.01 to 1 g/m3, beyond which it stabilizes. A 10 times low bias in simulated LWC below 1 g/m3 would require 107 times higher aerosol concentration to form the required number of fog droplets. These results provide the theoretical aspects that will help improving the existing fog detection algorithm and fog forecasting by numerical models in India.

  16. Pairing field methods to improve inference in wildlife surveys while accommodating detection covariance.

    Science.gov (United States)

    Clare, John; McKinney, Shawn T; DePue, John E; Loftin, Cynthia S

    2017-10-01

    It is common to use multiple field sampling methods when implementing wildlife surveys to compare method efficacy or cost efficiency, integrate distinct pieces of information provided by separate methods, or evaluate method-specific biases and misclassification error. Existing models that combine information from multiple field methods or sampling devices permit rigorous comparison of method-specific detection parameters, enable estimation of additional parameters such as false-positive detection probability, and improve occurrence or abundance estimates, but with the assumption that the separate sampling methods produce detections independently of one another. This assumption is tenuous if methods are paired or deployed in close proximity simultaneously, a common practice that reduces the additional effort required to implement multiple methods and reduces the risk that differences between method-specific detection parameters are confounded by other environmental factors. We develop occupancy and spatial capture-recapture models that permit covariance between the detections produced by different methods, use simulation to compare estimator performance of the new models to models assuming independence, and provide an empirical application based on American marten (Martes americana) surveys using paired remote cameras, hair catches, and snow tracking. Simulation results indicate existing models that assume that methods independently detect organisms produce biased parameter estimates and substantially understate estimate uncertainty when this assumption is violated, while our reformulated models are robust to either methodological independence or covariance. Empirical results suggested that remote cameras and snow tracking had comparable probability of detecting present martens, but that snow tracking also produced false-positive marten detections that could potentially substantially bias distribution estimates if not corrected for. Remote cameras detected marten

  17. Nanomaterials application in electrochemical detection of heavy metals

    International Nuclear Information System (INIS)

    Aragay, Gemma; Merkoçi, Arben

    2012-01-01

    Highlights: ► We review the recent trends in the application of nanomaterials for electrochemical detection of heavy metals. ► Different types of nanomaterials including metal nanoparticles, different carbon nanomaterials or nanochannels have been applied on the electrochemical analysis of heavy metals in various sensing formats/configurations. ► The great properties of nanomaterials allow the new devices to show advantages in terms of sensing performance (i.e. increase the sensitivity, decrease the detection limits and improve the stability). ► Between the various electrochemical techniques, voltammetric and potentiometric based ones are particularly taking interesting advantages by the incorporation of new nanomaterials due to the improved electrocatalytic properties beside the increase of the sensor's transducing area. - Abstract: Recent trends in the application of nanomaterials for electrochemical detection of heavy metals are shown. Various nanomaterials such as nanoparticles, nanowires, nanotubes, nanochannels, graphene, etc. have been explored either as modifiers of electrodes or as new electrode materials with interest to be applied in electrochemical stripping analysis, ion-selective detection, field-effect transistors or other indirect heavy metals (bio)detection alternatives. The developed devices have shown increased sensitivity and decreased detection limits between other improvements of analytical performance data. The phenomena behind nanomaterials responses are also discussed and some typical responses data of the developed systems either in standard solutions or in real samples are given. The developed nanomaterials based electrochemical systems are giving new inputs to the existing devices or leading to the development of novel heavy metal detection tools with interest for applications in field such as diagnostics, environmental and safety and security controls or other industries.

  18. Direct Detection Electron Energy-Loss Spectroscopy: A Method to Push the Limits of Resolution and Sensitivity.

    Science.gov (United States)

    Hart, James L; Lang, Andrew C; Leff, Asher C; Longo, Paolo; Trevor, Colin; Twesten, Ray D; Taheri, Mitra L

    2017-08-15

    In many cases, electron counting with direct detection sensors offers improved resolution, lower noise, and higher pixel density compared to conventional, indirect detection sensors for electron microscopy applications. Direct detection technology has previously been utilized, with great success, for imaging and diffraction, but potential advantages for spectroscopy remain unexplored. Here we compare the performance of a direct detection sensor operated in counting mode and an indirect detection sensor (scintillator/fiber-optic/CCD) for electron energy-loss spectroscopy. Clear improvements in measured detective quantum efficiency and combined energy resolution/energy field-of-view are offered by counting mode direct detection, showing promise for efficient spectrum imaging, low-dose mapping of beam-sensitive specimens, trace element analysis, and time-resolved spectroscopy. Despite the limited counting rate imposed by the readout electronics, we show that both core-loss and low-loss spectral acquisition are practical. These developments will benefit biologists, chemists, physicists, and materials scientists alike.

  19. Using Enhanced Grace Water Storage Data to Improve Drought Detection by the U.S. and North American Drought Monitors

    Science.gov (United States)

    Houborg, Rasmus; Rodell, Matthew; Lawrimore, Jay; Li, Bailing; Reichle, Rolf; Heim, Richard; Rosencrans, Matthew; Tinker, Rich; Famiglietti, James S.; Svoboda, Mark; hide

    2011-01-01

    NASA's Gravity Recovery and Climate Experiment (GRACE) satellites measure time variations of the Earth's gravity field enabling reliable detection of spatio-temporal variations in total terrestrial water storage (TWS), including groundwater. The U.S. and North American Drought Monitors rely heavily on precipitation indices and do not currently incorporate systematic observations of deep soil moisture and groundwater storage conditions. Thus GRACE has great potential to improve the Drought Monitors by filling this observational gap. GRACE TWS data were assimilating into the Catchment Land Surface Model using an ensemble Kalman smoother enabling spatial and temporal downscaling and vertical decomposition into soil moisture and groundwater components. The Drought Monitors combine several short- and long-term drought indicators expressed in percentiles as a reference to their historical frequency of occurrence. To be consistent, we generated a climatology of estimated soil moisture and ground water based on a 60-year Catchment model simulation, which was used to convert seven years of GRACE assimilated fields into drought indicator percentiles. At this stage we provide a preliminary evaluation of the GRACE assimilated moisture and indicator fields.

  20. Improvement of retinal blood vessel detection by spur removal and Gaussian matched filtering compensation

    Science.gov (United States)

    Xiao, Di; Vignarajan, Janardhan; An, Dong; Tay-Kearney, Mei-Ling; Kanagasingam, Yogi

    2016-03-01

    Retinal photography is a non-invasive and well-accepted clinical diagnosis of ocular diseases. Qualitative and quantitative assessment of retinal images is crucial in ocular diseases related clinical application. In this paper, we proposed approaches for improving the quality of blood vessel detection based on our initial blood vessel detection methods. A blood vessel spur pruning method has been developed for removing the blood vessel spurs both on vessel medial lines and binary vessel masks, which are caused by artifacts and side-effect of Gaussian matched vessel enhancement. A Gaussian matched filtering compensation method has been developed for removing incorrect vessel branches in the areas of low illumination. The proposed approaches were applied and tested on the color fundus images from one publicly available database and our diabetic retinopathy screening dataset. A preliminary result has demonstrated the robustness and good performance of the proposed approaches and their potential application for improving retinal blood vessel detection.

  1. Systems approach to detect and evaluate contaminants of emerging concern in the Great Lakes

    Science.gov (United States)

    The release of chemicals of emerging concern threatens near shore health in the Great Lakes, particularly in regions already suffering from degradation of water and environmental quality due to past and present anthropogenic activities. Critical issues remain in delisting Areas ...

  2. Rapid Detection of Enterobacter Sakazakii in milk Powder using amino modified chitosan immunomagnetic beads.

    Science.gov (United States)

    Zhu, Yinglian; Wang, Dongfeng

    2016-12-01

    Chitosan immunomagnetic beads (CIBs) were first prepared through converting hydroxyl groups of natural polymer material-chitosan into amino groups using epichlorohydrin and ethylenediamine as modification agent and then coupling with polyclonal antibodies of Enterobacter sakazakii using glutaraldehyde as cross-linking agent. The beads before coupling with antibodies were characterized by magnetic property measurement, FTIR, SEM and XRD technologies. In the assay a natural polysaccharide-chitosan, which has good biological and chemical properties such as non-toxicity, biocompatibility and high chemical reactivity was first used for synthesis of immunomagnetic beads. The detection method first established in this paper that combined the beads with chromogenic medium together to rapid detect E. sakazakii in milk powder could greatly improve the detection specificity and working efficiency. The beads exhibited a maximum capturing capacity of 1×10 6 cfu/g with the detection sensitivity of 4cfu/g. The results demonstrate that the assay is a straightforward, specific and sensitive alternative for rapid detection of E.sakazakii in food matrix. The total analysis time was as little as about 25h, which greatly shorten the detection time. The method can provides new ideas not only to preparation technique of immunomagnetic beads but to imunne detection technique in food safety. Copyright © 2016 Elsevier B.V. All rights reserved.

  3. Environmental Conditions Associated with Elevated Vibrio parahaemolyticus Concentrations in Great Bay Estuary, New Hampshire.

    Directory of Open Access Journals (Sweden)

    Erin A Urquhart

    Full Text Available Reports from state health departments and the Centers for Disease Control and Prevention indicate that the annual number of reported human vibriosis cases in New England has increased in the past decade. Concurrently, there has been a shift in both the spatial distribution and seasonal detection of Vibrio spp. throughout the region based on limited monitoring data. To determine environmental factors that may underlie these emerging conditions, this study focuses on a long-term database of Vibrio parahaemolyticus concentrations in oyster samples generated from data collected from the Great Bay Estuary, New Hampshire over a period of seven consecutive years. Oyster samples from two distinct sites were analyzed for V. parahaemolyticus abundance, noting significant relationships with various biotic and abiotic factors measured during the same period of study. We developed a predictive modeling tool capable of estimating the likelihood of V. parahaemolyticus presence in coastal New Hampshire oysters. Results show that the inclusion of chlorophyll a concentration to an empirical model otherwise employing only temperature and salinity variables, offers improved predictive capability for modeling the likelihood of V. parahaemolyticus in the Great Bay Estuary.

  4. Ultrahigh Sensitivity Piezoresistive Pressure Sensors for Detection of Tiny Pressure.

    Science.gov (United States)

    Li, Hongwei; Wu, Kunjie; Xu, Zeyang; Wang, Zhongwu; Meng, Yancheng; Li, Liqiang

    2018-05-31

    High sensitivity pressure sensors are crucial for the ultra-sensitive touch technology and E-skin, especially at the tiny pressure range below 100 Pa. However, it is highly challenging to substantially promote sensitivity beyond the current level at several to two hundred kPa -1 , and to improve the detection limit lower than 0.1 Pa, which is significant for the development of pressure sensors toward ultrasensitive and highly precise detection. Here, we develop an efficient strategy to greatly improve the sensitivity near to 2000 kPa -1 by using short channel coplanar device structure and sharp microstructure, which is systematically proposed for the first time and rationalized by the mathematic calculation and analysis. Significantly, benefiting from the ultrahigh sensitivity, the detection limit is improved to be as small as 0.075 Pa. The sensitivity and detection limit are both superior to the current levels, and far surpass the function of human skin. Furthermore, the sensor shows fast response time (50 μs), excellent reproducibility and stability, and low power consumption. Remarkably, the sensor shows excellent detection capacity in the tiny pressure range including LED switching with a pressure of 7 Pa, ringtone (2-20 Pa) recognition, and ultrasensitive (0.1 Pa) electronic glove. This work represents a performance and strategic progress in the field of pressure sensing.

  5. Addition of Carbon to the Culture Medium Improves the Detection Efficiency of Aflatoxin Synthetic Fungi

    Directory of Open Access Journals (Sweden)

    Tadahiro Suzuki

    2016-11-01

    Full Text Available Aflatoxin (AF is a harmful secondary metabolite that is synthesized by the Aspergillus species. Although AF detection techniques have been developed, techniques for detection of AF synthetic fungi are still required. Techniques such as plate culture methods are continually being modified for this purpose. However, plate culture methods require refinement because they suffer from several issues. In this study, activated charcoal powder (carbon was added to a culture medium containing cyclodextrin (CD to enhance the contrast of fluorescence and improve the detection efficiency for AF synthetic fungi. Two culture media, potato dextrose agar and yeast extract sucrose agar, were investigated using both plate and liquid cultures. The final concentrations of CD and carbon in the media were 3 mg/mL and 0.3 mg/mL, respectively. Addition of carbon improved the visibility of fluorescence by attenuating approximately 30% of light scattering. Several fungi that could not be detected with only CD in the medium were detected with carbon addition. The carbon also facilitated fungal growth in the potato dextrose liquid medium. The results suggest that addition of carbon to media can enhance the observation of AF-derived fluorescence.

  6. Improvements of the sensitivity of burst cartridge detection; Amelioration du seuil de detection des ruptures de gaine

    Energy Technology Data Exchange (ETDEWEB)

    Vasnier, F [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires

    1967-07-01

    I - Special tests for improving the sensitivity of burst cartridge detection equipment in power reactors II - Scintillator purge-flow tests using aged gas in the B.C.D. /E.D.F. 2 Summary. - The first part of this report describes the tests carried out on fission product detectors by a process in which gas is continuously injected in front of the scintillator. Using this system, the background is reduced and perturbations caused by pneumatic switches on the prospecting circuits are eliminated. The quality of the signals thus obtained permits better processing of the data and thus leads to a possible improvement in the sensitivity of burst cartridge detection. The second part gives results of tests carried out with both fresh and aged gases, the economic advantage of the latter being that it permits recycling through the reactor. Reduction of the background is less pronounced but the advantage of the stable signals is conserved. (author) [French] I - Essais speciaux pour ameliorer le seuil de detection des installations de D.R.G. des reacteurs de puissance II- Essais de balayage sous scintillateur avec gaz vieilli a la D.R.G. /E.D.F. 2 Sommaire. - La premiere partie de ce rapport decrit les essais effectues sur les detecteurs de produits de fission par un procede d'injection continue de gaz sous le scintillateur. Grace a ce systeme on obtient une reduction du bruit de fond et l'elimination des perturbations causees par les commutations pneumatiques des circuits de prospection. La qualite des signaux obtenus ainsi permet un meilleur traitement des informations d'ou une amelioration possible du seuil de detection des ruptures de gaines. La seconde partie donne les resultats d'essais effectues avec du gaz propre et vieilli, l'utilisation de ce dernier presentant l'avantage economique d'etre recycle du reacteur. La reduction du bruit de fond est moins importante mais on conserve l'avantage de la stabilisation des signaux. (auteur)

  7. SOFIA/GREAT Discovery of Terahertz Water Masers

    Science.gov (United States)

    Neufeld, David A.; Melnick, Gary J.; Kaufman, Michael J.; Wiesemeyer, Helmut; Güsten, Rolf; Kraus, Alex; Menten, Karl M.; Ricken, Oliver; Faure, Alexandre

    2017-07-01

    We report the discovery of water maser emission at frequencies above 1 THz. Using the GREAT instrument on SOFIA, we have detected emission in the 1.296411 THz {8}27-{7}34 transition of water toward three oxygen-rich evolved stars: W Hya, U Her, and VY CMa. An upper limit on the 1.296 THz line flux was obtained toward R Aql. Near-simultaneous observations of the 22.23508 GHz {6}16-{5}23 water maser transition were carried out toward all four sources using the Effelsberg 100 m telescope. The measured line fluxes imply 22 GHz/1.296 THz photon luminosity ratios of 0.012, 0.12, and 0.83, respectively, for W Hya, U Her, and VY CMa, values that confirm the 22 GHz maser transition to be unsaturated in W Hya and U Her. We also detected the 1.884888 THz {8}45-{7}52 transition toward W Hya and VY CMa, and the 1.278266 THz {7}43-{6}52 transition toward VY CMa. Like the 22 GHz maser transition, all three of the THz emission lines detected here originate from the ortho-H2O spin isomer. Based upon a model for the circumstellar envelope of W Hya, we estimate that stimulated emission is responsible for ˜85% of the observed 1.296 THz line emission, and thus that this transition may be properly described as a terahertz-frequency maser. In the case of the 1.885 THz transition, by contrast, our W Hya model indicates that the observed emission is dominated by spontaneous radiative decay, even though a population inversion exists. GREAT is a development by the MPI für Radioastronomie and the KOSMA/Universität zu Köln, in cooperation with the MPI für Sonnensystemforschung and the DLR Institut für Planetenforschung.

  8. Biomarkers for Early Detection of Malignant Mesothelioma: Diagnostic and Therapeutic Application

    Energy Technology Data Exchange (ETDEWEB)

    Tomasetti, Marco, E-mail: m.tomasetti@univpm.it; Santarelli, Lory [Department of Molecular Pathology and Innovative Therapies, Occupational Medicine, Polytechnic University of Marche, via Tronto 10/A Torrette 60020, Ancona (Italy)

    2010-04-14

    Malignant mesothelioma (MM) is a rare and aggressive tumour of the serosal cavities linked to asbestos exposure. Improved detection methods for diagnosing this type of neoplastic disease are essential for an early and reliable diagnosis and treatment. Thus, focus has been placed on finding tumour markers for the non-invasive detection of MM. Recently, some blood biomarkers have been described as potential indicators of early and advanced MM cancers. The identification of tumour biomarkers alone or in combination could greatly facilitate the surveillance procedure for cohorts of subjects exposed to asbestos, a common phenomenon in several areas of western countries.

  9. Defect Detection of Adhesive Layer of Thermal Insulation Materials Based on Improved Particle Swarm Optimization of ECT.

    Science.gov (United States)

    Wen, Yintang; Jia, Yao; Zhang, Yuyan; Luo, Xiaoyuan; Wang, Hongrui

    2017-10-25

    This paper studies the defect detection problem of adhesive layer of thermal insulation materials. A novel detection method based on an improved particle swarm optimization (PSO) algorithm of Electrical Capacitance Tomography (ECT) is presented. Firstly, a least squares support vector machine is applied for data processing of measured capacitance values. Then, the improved PSO algorithm is proposed and applied for image reconstruction. Finally, some experiments are provided to verify the effectiveness of the proposed method in defect detection for adhesive layer of thermal insulation materials. The performance comparisons demonstrate that the proposed method has higher precision by comparing with traditional ECT algorithms.

  10. Improved efficiency access control equipment and explosive, weapons and drug abuse detection

    International Nuclear Information System (INIS)

    Jenkins, A.; Milford, A.; Woollven, J.

    1985-01-01

    The second generation portal explosives detector has been designed with increased detection capability and convenience in service. The method of detection and performance relative to the first generation is described. A novel method of auto-calibration and self diagnosis is described and results are discussed. Improvements in convenience of operation have been achieved and operating space and costs reduced by combining metal detection capability, together with explosives detection. This allows both alarm signal and diagnostic outputs to be combined on a single remote panel in the guard room, and reduces the number of guards needed to man the access control. This type of access control is entirely a defensive measure against attack but a further additional feature is proposed which will also check the state of mind of all personnel passing through the check point. Any person suffering from the effect of narcotic or alcohol will be detected by their inability to reproduce their normal signature. A new method of signature analysis in five dimensions is described together with proposals for integrating the check without increasing the time in the test area. Some recent results on the effects of alcohol on signature reproduction is given

  11. Great Lakes Restoration Initiative Great Lakes Mussel Watch(2009-2014)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Following the inception of the Great Lakes Restoration Initiative (GLRI) to address the significant environmental issues plaguing the Great Lakes region, the...

  12. Improving Intrusion Detection System Based on Snort Rules for Network Probe Attacks Detection with Association Rules Technique of Data Mining

    Directory of Open Access Journals (Sweden)

    Nattawat Khamphakdee

    2015-07-01

    Full Text Available The intrusion detection system (IDS is an important network security tool for securing computer and network systems. It is able to detect and monitor network traffic data. Snort IDS is an open-source network security tool. It can search and match rules with network traffic data in order to detect attacks, and generate an alert. However, the Snort IDS  can detect only known attacks. Therefore, we have proposed a procedure for improving Snort IDS rules, based on the association rules data mining technique for detection of network probe attacks.  We employed the MIT-DARPA 1999 data set for the experimental evaluation. Since behavior pattern traffic data are both normal and abnormal, the abnormal behavior data is detected by way of the Snort IDS. The experimental results showed that the proposed Snort IDS rules, based on data mining detection of network probe attacks, proved more efficient than the original Snort IDS rules, as well as icmp.rules and icmp-info.rules of Snort IDS.  The suitable parameters for the proposed Snort IDS rules are defined as follows: Min_sup set to 10%, and Min_conf set to 100%, and through the application of eight variable attributes. As more suitable parameters are applied, higher accuracy is achieved.

  13. Detection and recognition of bridge crack based on convolutional neural network

    Directory of Open Access Journals (Sweden)

    Honggong LIU

    2016-10-01

    Full Text Available Aiming at the backward artificial visual detection status of bridge crack in China, which has a great danger coefficient, a digital and intelligent detection method of improving the diagnostic efficiency and reducing the risk coefficient is studied. Combing with machine vision and convolutional neural network technology, Raspberry Pi is used to acquire and pre-process image, and the crack image is analyzed; the processing algorithm which has the best effect in detecting and recognizing is selected; the convolutional neural network(CNN for crack classification is optimized; finally, a new intelligent crack detection method is put forward. The experimental result shows that the system can find all cracks beyond the maximum limit, and effectively identify the type of fracture, and the recognition rate is above 90%. The study provides reference data for engineering detection.

  14. Ion trace detection algorithm to extract pure ion chromatograms to improve untargeted peak detection quality for liquid chromatography/time-of-flight mass spectrometry-based metabolomics data.

    Science.gov (United States)

    Wang, San-Yuan; Kuo, Ching-Hua; Tseng, Yufeng J

    2015-03-03

    Able to detect known and unknown metabolites, untargeted metabolomics has shown great potential in identifying novel biomarkers. However, elucidating all possible liquid chromatography/time-of-flight mass spectrometry (LC/TOF-MS) ion signals in a complex biological sample remains challenging since many ions are not the products of metabolites. Methods of reducing ions not related to metabolites or simply directly detecting metabolite related (pure) ions are important. In this work, we describe PITracer, a novel algorithm that accurately detects the pure ions of a LC/TOF-MS profile to extract pure ion chromatograms and detect chromatographic peaks. PITracer estimates the relative mass difference tolerance of ions and calibrates the mass over charge (m/z) values for peak detection algorithms with an additional option to further mass correction with respect to a user-specified metabolite. PITracer was evaluated using two data sets containing 373 human metabolite standards, including 5 saturated standards considered to be split peaks resultant from huge m/z fluctuation, and 12 urine samples spiked with 50 forensic drugs of varying concentrations. Analysis of these data sets show that PITracer correctly outperformed existing state-of-art algorithm and extracted the pure ion chromatograms of the 5 saturated standards without generating split peaks and detected the forensic drugs with high recall, precision, and F-score and small mass error.

  15. Darkfield illumination improves microscopic detection of metals in Timm's stained tissue

    DEFF Research Database (Denmark)

    Baatrup, E; Frederickson, C J

    1989-01-01

    Deposits of trace or toxic metals can be quickly identified by light microscopical surveys of tissue sections stained for metals by variants of Timm's silver enhancement method. The present work shows that the small, isolated silver grains that label isolated deposits of metal in tissue are undet...... are undetectable in brightfield light microscopy but are easily detected in darkfield microscopy. Darkfield illumination is therefore recommended for improving the detection of trace or toxic metals in tissue. Udgivelsesdato: 1989-Aug......Deposits of trace or toxic metals can be quickly identified by light microscopical surveys of tissue sections stained for metals by variants of Timm's silver enhancement method. The present work shows that the small, isolated silver grains that label isolated deposits of metal in tissue...

  16. Integrated MEMS/NEMS Resonant Cantilevers for Ultrasensitive Biological Detection

    Directory of Open Access Journals (Sweden)

    Xinxin Li

    2009-01-01

    Full Text Available The paper reviews the recent researches implemented in Chinese Academy of Sciences, with achievements on integrated resonant microcantilever sensors. In the resonant cantilevers, the self-sensing elements and resonance exciting elements are both top-down integrated with silicon micromachining techniques. Quite a lot of effort is focused on optimization of the resonance mode and sensing structure for improvement of sensitivity. On the other hand, to enable the micro-cantilevers specifically sensitive to bio/chemical molecules, sensing materials are developed and modified on the cantilever surface with a self-assembled monolayer (SAM based bottom-up construction and surface functionalization. To improve the selectivity of the sensors and depress environmental noise, multiple and localized surface modifications are developed. The achieved volume production capability and satisfactory detecting resolution to trace-level biological antigen of alpha-fetoprotein (AFP give the micro-cantilever sensors a great promise for rapid and high-resoluble detection.

  17. Microfluidic devices for sample preparation and rapid detection of foodborne pathogens

    DEFF Research Database (Denmark)

    Kant, Krishna; Shahbazi, Mohammad-Ali; Dave, Vivek Priy

    2018-01-01

    and improve the limit of detections. Integration of pathogen capturing bio-receptors on microfluidic devices is a crucial step, which can facilitate recognition abilities in harsh chemical and physical conditions, offering a great commercial benefit to the food-manufacturing sector. This article reviews...... diagnosis competences. This has prompted researchers to call the current status of detection approaches into question and leverage new technologies for superior pathogen sensing outcomes. Novel strategies mainly rely on incorporating all the steps from sample preparation to detection in miniaturized devices...... recent advances in current state-of-the-art of sample preparation and concentration from food matrices with focus on bacterial capturing methods and sensing technologies, along with their advantages and limitations when integrated into microfluidic devices for online rapid detection of pathogens in foods...

  18. Portopulmonary hypertension: Improved detection using CT and echocardiography in combination

    Energy Technology Data Exchange (ETDEWEB)

    Devaraj, Anand [Royal Brompton and Harefield NHS Foundation Trust, Department of Radiology, London (United Kingdom); Loveridge, Robert; Bernal, William; Willars, Christopher; Wendon, Julia A.; Auzinger, Georg [King' s College Hospital NHS Foundation Trust, The Institute of Liver Studies, King' s Health Partners, King' s College London, London (United Kingdom); Bosanac, Diana; Stefanidis, Konstantinos; Desai, Sujal R. [King' s College Hospital NHS Foundation Trust, Department of Radiology, King' s Health Partners, King' s College London, London (United Kingdom)

    2014-10-15

    To establish the relationship between CT signs of pulmonary hypertension and mean pulmonary artery pressure (mPAP) in patients with liver disease, and to determine the additive value of CT in the detection of portopulmonary hypertension in combination with transthoracic echocardiography. Forty-nine patients referred for liver transplantation were retrospectively reviewed. Measured CT signs included the main pulmonary artery/ascending aorta diameter ratio (PA/AA{sub meas}) and the mean left and right main PA diameter (RLPA{sub meas}). Enlargement of the pulmonary artery compared to the ascending aorta was also assessed visually (PA/AA{sub vis}). CT measurements were correlated with right-sided heart catheter-derived mPAP. The ability of PA/AA{sub vis} combined with echocardiogram-derived right ventricular systolic pressure (RVSP) to detect portopulmonary hypertension was tested with ROC analysis. There were moderate correlations between mPAP and both PA/AA{sub meas} and RLPA{sub meas} (r{sub s} = 0.41 and r{sub s} = 0.42, respectively; p < 0.005). Compared to transthoracic echocardiography alone (AUC = 0.59, p = 0.23), a diagnostic algorithm incorporating PA/AA{sub vis} and transthoracic echocardiography-derived RVSP improved the detection of portopulmonary hypertension (AUC = 0.8, p < 0.0001). CT contributes to the non-invasive detection of portopulmonary hypertension when used in a diagnostic algorithm with transthoracic echocardiography. CT may have a role in the pre-liver transplantation triage of patients with portopulmonary hypertension for right-sided heart catheterisation. (orig.)

  19. Pipeline Defects Detection Using MFL Signals and Self Quotient Image

    International Nuclear Information System (INIS)

    Kim, Min Ho; Choi, Doo Hyun; Rho, Yong Woo

    2010-01-01

    Defects positioning of underground gas pipelines using MFL(magnetic flux leakage) inspection which is one of non-destructive evaluation techniques is proposed in this paper. MFL signals acquired from MFL PIG(pipeline inspection gauge) have nonlinearity and distortion caused by various extemal disturbances. SQI(self quotient image), a compensation technique for nonlinearity and distortion of MFL signal, is used to correct positioning of pipeline defects. Through the experiments using artificial defects carved in the KOGAS pipeline simulation facility, it is found that the performance of proposed defect detection is greatly improved compared to that of the conventional DCT(discrete cosine transform) coefficients based detection

  20. Detecting text in natural scenes with multi-level MSER and SWT

    Science.gov (United States)

    Lu, Tongwei; Liu, Renjun

    2018-04-01

    The detection of the characters in the natural scene is susceptible to factors such as complex background, variable viewing angle and diverse forms of language, which leads to poor detection results. Aiming at these problems, a new text detection method was proposed, which consisted of two main stages, candidate region extraction and text region detection. At first stage, the method used multiple scale transformations of original image and multiple thresholds of maximally stable extremal regions (MSER) to detect the text regions which could detect character regions comprehensively. At second stage, obtained SWT maps by using the stroke width transform (SWT) algorithm to compute the candidate regions, then using cascaded classifiers to propose non-text regions. The proposed method was evaluated on the standard benchmark datasets of ICDAR2011 and the datasets that we made our own data sets. The experiment results showed that the proposed method have greatly improved that compared to other text detection methods.

  1. Improved biosensor-based detection system

    DEFF Research Database (Denmark)

    2015-01-01

    Described is a new biosensor-based detection system for effector compounds, useful for in vivo applications in e.g. screening and selecting of cells which produce a small molecule effector compound or which take up a small molecule effector compound from its environment. The detection system...... comprises a protein or RNA-based biosensor for the effector compound which indirectly regulates the expression of a reporter gene via two hybrid proteins, providing for fewer false signals or less 'noise', tuning of sensitivity or other advantages over conventional systems where the biosensor directly...

  2. Improving the recommender algorithms with the detected communities in bipartite networks

    Science.gov (United States)

    Zhang, Peng; Wang, Duo; Xiao, Jinghua

    2017-04-01

    Recommender system offers a powerful tool to make information overload problem well solved and thus gains wide concerns of scholars and engineers. A key challenge is how to make recommendations more accurate and personalized. We notice that community structures widely exist in many real networks, which could significantly affect the recommendation results. By incorporating the information of detected communities in the recommendation algorithms, an improved recommendation approach for the networks with communities is proposed. The approach is examined in both artificial and real networks, the results show that the improvement on accuracy and diversity can be 20% and 7%, respectively. This reveals that it is beneficial to classify the nodes based on the inherent properties in recommender systems.

  3. An improved anti-leech mechanism based on session identifier

    Science.gov (United States)

    Zhang, Jianbiao; Zhu, Tong; Zhang, Han; Lin, Li

    2012-01-01

    With the rapid development of information technology and extensive requirement of network resource sharing, plenty of resource hotlinking phenomenons appear on the internet. The hotlinking problem not only harms the interests of legal websites but also leads to a great affection to fair internet environment. The anti-leech technique based on session identifier is highly secure, but the transmission of session identifier in plaintext form causes some security flaws. In this paper, a proxy hotlinking technique based on session identifier is introduced firstly to illustrate these security flaws; next, this paper proposes an improved anti-leech mechanism based on session identifier, the mechanism takes the random factor as the core and detects hotlinking request using a map table that contains random factor, user's information and time stamp; at last the paper analyzes the security of mechanism in theory. The result reveals that the improved mechanism has the merits of simple realization, high security and great flexibility.

  4. Leadership training to improve adenoma detection rate in screening colonoscopy: A randomised trial

    NARCIS (Netherlands)

    M.F. Kaminski (Michal); J. Anderson (John); R.M. Valori (Roland ); E. Kraszewska (Ewa); M. Rupinski (Maciej); J. Pachlewski (Jacek); E. Wronska (Ewa); M. Bretthauer (Michael); S. Thomas-Gibson (Siwan); E.J. Kuipers (Ernst); J. Regula (J.)

    2016-01-01

    textabstractObjective Suboptimal adenoma detection rate (ADR) at colonoscopy is associated with increased risk of interval colorectal cancer. It is uncertain how ADR might be improved. We compared the effect of leadership training versus feedback only on colonoscopy quality in a countrywide

  5. The Viking Great Army and its Legacy: plotting settlement shift using metal-detected finds

    Directory of Open Access Journals (Sweden)

    Dave Haldenby

    2016-09-01

    Full Text Available Investigation of the Anglian and Anglo-Scandinavian settlement at Burrow House Farm, Cottam, East Yorkshire from 1993-95 was a pioneering collaboration between archaeologists and metal-detectorists, and led to the identification of a new form of Anglo-Scandinavian farmstead. It was also one of the first investigations ever undertaken of a 'productive site', so-called because of the large quantities of early medieval metalwork recovered by metal-detecting. The project provided an important demonstration of the effects of the reorganisation of land ownership following the Scandinavian settlement of Northumbria. Excavation demonstrated that the abandonment of an Anglian 'Butterwick-type' enclosure in the late 9th century was closely followed by the construction of the new Anglo-Scandinavian farmstead some 100m to the north, reinforced by the pattern seen in the horizontal stratigraphy of dated metalwork derived from metal-detecting (Richards 1999a; 2001a. Subsequently, metal-detecting has continued at the site, almost doubling the quantity of artefacts. This has led to further breakthroughs in the interpretation of the chronological and spatial development of the settlement, as well as some substantial revisions to the typology and dating of early medieval artefacts, with important implications for the chronology of the period. It allows some significant new conclusions to be drawn about settlement development at Cottam, identifying the changing function of the settlements, as well as their location: There are two phases of Anglian activity, with a transition from an 8th/9th-century estate centre to a 9th-century market, echoing the similar transitions being recorded in Scandinavia at sites such as Tissø. This is the first time such a configuration has been identified in England, and it throws important new light on the nature of 'productive sites'. There are also two phases of Viking activity, with an initial phase of looting, probably linked to

  6. Fault-tolerant control for current sensors of doubly fed induction generators based on an improved fault detection method

    DEFF Research Database (Denmark)

    Li, Hui; Yang, Chao; Hu, Yaogang

    2014-01-01

    Fault-tolerant control of current sensors is studied in this paper to improve the reliability of a doubly fed induction generator (DFIG). A fault-tolerant control system of current sensors is presented for the DFIG, which consists of a new current observer and an improved current sensor fault...... detection algorithm, and fault-tolerant control system are investigated by simulation. The results indicate that the outputs of the observer and the sensor are highly coherent. The fault detection algorithm can efficiently detect both soft and hard faults in current sensors, and the fault-tolerant control...

  7. Improving cyberbullying detection with user context

    NARCIS (Netherlands)

    Dadvar, M.; Trieschnigg, Rudolf Berend; Ordelman, Roeland J.F.; de Jong, Franciska M.G.

    The negative consequences of cyberbullying are becoming more alarming every day and technical solutions that allow for taking appropriate action by means of automated detection are still very limited. Up until now, studies on cyberbullying detection have focused on individual comments only,

  8. Moving object detection in top-view aerial videos improved by image stacking

    Science.gov (United States)

    Teutsch, Michael; Krüger, Wolfgang; Beyerer, Jürgen

    2017-08-01

    Image stacking is a well-known method that is used to improve the quality of images in video data. A set of consecutive images is aligned by applying image registration and warping. In the resulting image stack, each pixel has redundant information about its intensity value. This redundant information can be used to suppress image noise, resharpen blurry images, or even enhance the spatial image resolution as done in super-resolution. Small moving objects in the videos usually get blurred or distorted by image stacking and thus need to be handled explicitly. We use image stacking in an innovative way: image registration is applied to small moving objects only, and image warping blurs the stationary background that surrounds the moving objects. Our video data are coming from a small fixed-wing unmanned aerial vehicle (UAV) that acquires top-view gray-value images of urban scenes. Moving objects are mainly cars but also other vehicles such as motorcycles. The resulting images, after applying our proposed image stacking approach, are used to improve baseline algorithms for vehicle detection and segmentation. We improve precision and recall by up to 0.011, which corresponds to a reduction of the number of false positive and false negative detections by more than 3 per second. Furthermore, we show how our proposed image stacking approach can be implemented efficiently.

  9. A method to test the reproducibility and to improve performance of computer-aided detection schemes for digitized mammograms

    International Nuclear Information System (INIS)

    Zheng Bin; Gur, David; Good, Walter F.; Hardesty, Lara A.

    2004-01-01

    The purpose of this study is to develop a new method for assessment of the reproducibility of computer-aided detection (CAD) schemes for digitized mammograms and to evaluate the possibility of using the implemented approach for improving CAD performance. Two thousand digitized mammograms (representing 500 cases) with 300 depicted verified masses were selected in the study. Series of images were generated for each digitized image by resampling after a series of slight image rotations. A CAD scheme developed in our laboratory was applied to all images to detect suspicious mass regions. We evaluated the reproducibility of the scheme using the detection sensitivity and false-positive rates for the original and resampled images. We also explored the possibility of improving CAD performance using three methods of combining results from the original and resampled images, including simple grouping, averaging output scores, and averaging output scores after grouping. The CAD scheme generated a detection score (from 0 to 1) for each identified suspicious region. A region with a detection score >0.5 was considered as positive. The CAD scheme detected 238 masses (79.3% case-based sensitivity) and identified 1093 false-positive regions (average 0.55 per image) in the original image dataset. In eleven repeated tests using original and ten sets of rotated and resampled images, the scheme detected a maximum of 271 masses and identified as many as 2359 false-positive regions. Two hundred and eighteen masses (80.4%) and 618 false-positive regions (26.2%) were detected in all 11 sets of images. Combining detection results improved reproducibility and the overall CAD performance. In the range of an average false-positive detection rate between 0.5 and 1 per image, the sensitivity of the scheme could be increased approximately 5% after averaging the scores of the regions detected in at least four images. At low false-positive rate (e.g., ≤average 0.3 per image), the grouping method

  10. Improving the detection of illicit substance use in preoperative anesthesiological assessment.

    Science.gov (United States)

    Kleinwächter, R; Kork, F; Weiss-Gerlach, E; Ramme, A; Linnen, H; Radtke, F; Lütz, A; Krampe, H; Spies, C D

    2010-01-01

    Illicit substance use (ISU) is a worldwide burden, and its prevalence in surgical patients has not been well investigated. Co-consumption of legal substances, such as alcohol and tobacco, complicates the perioperative management and is frequently underestimated during routine preoperative assessment. The aim of this study was to compare the anesthesiologists' detection rate of ISU during routine preoperative assessment with a computerized self-assessment questionnaire. In total, 2,938 patients were included in this study. Prior to preoperative assessment, patients were asked to complete a computer-based questionnaire that addressed ISU, alcohol use disorder (AUDIT), nicotine use (Fagerström) and socio-economic variables (education, income, employment, partnership and size of household). Medical records were reviewed, and the anesthesiologists' detection of ISU was compared to the patients' self-reported ISU. Seven point five percent of patients reported ISU within the previous twelve months. ISU was highest in the age group between 18 and 30 years (26.4%; P<0.01). Patients reporting ISU were more often men than women (P<0.01), smokers (P<0.01) and tested positive for alcohol use disorder (P<0.01). Anesthesiologists detected ISU in one in 43 patients, whereas the computerized self-assessment reported it in one in 13 patients. The detection was best in the subgroup self-reporting frequent ISU (P<0.01). Anesthesiologists underestimate the prevalence of ISU. Computer-based self-assessment increases the detection of ISU in preoperative assessment and may decrease perioperative risk. More strategies to improve the detection of ISU as well as brief interventions for ISU are required in preoperative assessment clinics.

  11. Improved Deep Belief Networks (IDBN Dynamic Model-Based Detection and Mitigation for Targeted Attacks on Heavy-Duty Robots

    Directory of Open Access Journals (Sweden)

    Lianpeng Li

    2018-04-01

    Full Text Available In recent years, the robots, especially heavy-duty robots, have become the hardest-hit areas for targeted attacks. These attacks come from both the cyber-domain and the physical-domain. In order to improve the security of heavy-duty robots, this paper proposes a detection and mitigation mechanism which based on improved deep belief networks (IDBN and dynamic model. The detection mechanism consists of two parts: (1 IDBN security checks, which can detect targeted attacks from the cyber-domain; (2 Dynamic model and security detection, used to detect the targeted attacks which can possibly lead to a physical-domain damage. The mitigation mechanism was established on the base of the detection mechanism and could mitigate transient and discontinuous attacks. Moreover, a test platform was established to carry out the performance evaluation test for the proposed mechanism. The results show that, the detection accuracy for the attack of the cyber-domain of IDBN reaches 96.2%, and the detection accuracy for the attack of physical-domain control commands reaches 94%. The performance evaluation test has verified the reliability and high efficiency of the proposed detection and mitigation mechanism for heavy-duty robots.

  12. Does endoscopic ultrasound improve detection of locally recurrent anal squamous-cell cancer?

    Science.gov (United States)

    Peterson, Carrie Y; Weiser, Martin R; Paty, Philip B; Guillem, Jose G; Nash, Garrett M; Garcia-Aguilar, Julio; Patil, Sujata; Temple, Larissa K

    2015-02-01

    Evaluating patients for recurrent anal cancer after primary treatment can be difficult owing to distorted anatomy and scarring. Many institutions incorporate endoscopic ultrasound to improve detection, but the effectiveness is unknown. The aim of this study is to compare the effectiveness of digital rectal examination and endoscopic ultrasound in detecting locally recurrent disease during routine follow-up of patients with anal cancer. This study is a retrospective, single-institution review. This study was conducted at an oncologic tertiary referral center. Included were 175 patients with nonmetastatic anal squamous-cell cancer, without persistent disease after primary chemoradiotherapy, who had at least 1 posttreatment ultrasound and examination by a colorectal surgeon. The primary outcomes measured were the first modality to detect local recurrence, concordance, crude cancer detection rate, sensitivity, specificity, and predictive value. Eight hundred fifty-five endoscopic ultrasounds and 873 digital rectal examinations were performed during 35 months median follow-up. Overall, ultrasound detected 7 (0.8%) mesorectal and 32 (3.7%) anal canal abnormalities; digital examination detected 69 (7.9%) anal canal abnormalities. Locally recurrent disease was found on biopsy in 8 patients, all detected first or only with digital examination. Four patients did not have an ultrasound at the time of diagnosis of recurrence. The concordance of ultrasound and digital examination in detecting recurrent disease was fair at 0.37 (SE, 0.08; 95% CI, 0.21-0.54), and there was no difference in crude cancer detection rate, sensitivity, specificity, and negative or positive predictive values. The heterogeneity of follow-up timing and examinations is not standardized in this study but is reflective of general practice. Endoscopic ultrasound did not provide any advantage over digital rectal examination in identifying locally recurrent anal cancer, and should not be recommended for

  13. Spatio-Temporal Layout of Human Actions for Improved Bag-of-Words Action Detection

    NARCIS (Netherlands)

    Burghouts, G.J.; Schutte, K.

    2013-01-01

    We investigate how human action recognition can be improved by considering spatio-temporal layout of actions. From literature, we adopt a pipeline consisting of STIP features, a random forest to quantize the features into histograms, and an SVM classifier. Our goal is to detect 48 human actions,

  14. Improvement of LOD in Fluorescence Detection with Spectrally Nonuniform Background by Optimization of Emission Filtering.

    Science.gov (United States)

    Galievsky, Victor A; Stasheuski, Alexander S; Krylov, Sergey N

    2017-10-17

    The limit-of-detection (LOD) in analytical instruments with fluorescence detection can be improved by reducing noise of optical background. Efficiently reducing optical background noise in systems with spectrally nonuniform background requires complex optimization of an emission filter-the main element of spectral filtration. Here, we introduce a filter-optimization method, which utilizes an expression for the signal-to-noise ratio (SNR) as a function of (i) all noise components (dark, shot, and flicker), (ii) emission spectrum of the analyte, (iii) emission spectrum of the optical background, and (iv) transmittance spectrum of the emission filter. In essence, the noise components and the emission spectra are determined experimentally and substituted into the expression. This leaves a single variable-the transmittance spectrum of the filter-which is optimized numerically by maximizing SNR. Maximizing SNR provides an accurate way of filter optimization, while a previously used approach based on maximizing a signal-to-background ratio (SBR) is the approximation that can lead to much poorer LOD specifically in detection of fluorescently labeled biomolecules. The proposed filter-optimization method will be an indispensable tool for developing new and improving existing fluorescence-detection systems aiming at ultimately low LOD.

  15. [Progress of cytogenetic detection in myelodysplastic syndromes].

    Science.gov (United States)

    Zhou, Qing-Bing; Hu, Xiao-Mei; Liu, -Feng; Ma, Rou

    2011-12-01

    In recent years, significant progresses have been got in study on pathogenesis, treatment and prognosis of myelodysplastic syndromes (MDS), especially on use of new technology, that has great importance for cytogenetics of MDS. Recently, the progress of cytogenetic detection in MDS is very remarkable. Based on the metaphase cytogenetics (MC) method, prognostic significance of cytogenetics in MDS was clarified gradually. For example, people have known the prognostic significance of 12 p-, 11 q-, +21, t(11(q23)), although these genetic abnormalities are rare in the MDS. In addition, chromosome mutation emerged in the process of MDS may indicate the poor prognosis. On the other hand, with the use of SNP-A and aCGH in the study of genetics, MDS cytogenetic abnormality detection rate has been further improved and can reach to 78%. At the same time, some of MDS patients with the "normal karyotype" detected by MC have new hidden aberrations through the SNP or CGH detection, and these patients have a poorer prognosis. In this review, the advances of study on cytogenetic detection for MDS based on MC and SNP-A or aCGH methods are summarized.

  16. Molecular-Based Identification and Detection of Salmonella in Food Production Systems: Current Perspectives.

    Science.gov (United States)

    Ricke, Steven C; Kim, Sun Ae; Shi, Zhaohao; Park, Si Hong

    2018-04-19

    Salmonella remains a prominent cause of foodborne illnesses and can originate from a wide range of food products. Given the continued presence of pathogenic Salmonella in food production systems, there is a consistent need to improve identification and detection methods that can identify this pathogen at all stages in food systems. Methods for subtyping have evolved over the years, and the introduction of whole genome sequencing and advancements in PCR technologies has greatly improved the resolution for differentiating strains within a particular serovar. This, in turn, has led to the continued improvement in Salmonella detection technologies for utilization in food production systems. In this review, the focus will be on recent advancements in these technologies, as well as potential issues associated with the application of these tools in food production. In addition, the recent and emerging research developments on Salmonella detection and identification methodologies and their potential application in food production systems will be discussed. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

  17. An evaluation of The Great Escape: can an interactive computer game improve young children's fire safety knowledge and behaviors?

    Science.gov (United States)

    Morrongiello, Barbara A; Schwebel, David C; Bell, Melissa; Stewart, Julia; Davis, Aaron L

    2012-07-01

    Fire is a leading cause of unintentional injury and, although young children are at particularly increased risk, there are very few evidence-based resources available to teach them fire safety knowledge and behaviors. Using a pre-post randomized design, the current study evaluated the effectiveness of a computer game (The Great Escape) for teaching fire safety information to young children (3.5-6 years). Using behavioral enactment procedures, children's knowledge and behaviors related to fire safety were compared to a control group of children before and after receiving the intervention. The results indicated significant improvements in knowledge and fire safety behaviors in the intervention group but not the control. Using computer games can be an effective way to promote young children's understanding of safety and how to react in different hazardous situations.

  18. Great Lakes Literacy Principles

    Science.gov (United States)

    Fortner, Rosanne W.; Manzo, Lyndsey

    2011-03-01

    Lakes Superior, Huron, Michigan, Ontario, and Erie together form North America's Great Lakes, a region that contains 20% of the world's fresh surface water and is home to roughly one quarter of the U.S. population (Figure 1). Supporting a $4 billion sport fishing industry, plus $16 billion annually in boating, 1.5 million U.S. jobs, and $62 billion in annual wages directly, the Great Lakes form the backbone of a regional economy that is vital to the United States as a whole (see http://www.miseagrant.umich.edu/downloads/economy/11-708-Great-Lakes-Jobs.pdf). Yet the grandeur and importance of this freshwater resource are little understood, not only by people in the rest of the country but also by many in the region itself. To help address this lack of knowledge, the Centers for Ocean Sciences Education Excellence (COSEE) Great Lakes, supported by the U.S. National Science Foundation and the National Oceanic and Atmospheric Administration, developed literacy principles for the Great Lakes to serve as a guide for education of students and the public. These “Great Lakes Literacy Principles” represent an understanding of the Great Lakes' influences on society and society's influences on the Great Lakes.

  19. Improving dementia care: The role of screening and detection of cognitive impairment

    Science.gov (United States)

    Borson, Soo; Frank, Lori; Bayley, Peter J.; Boustani, Malaz; Dean, Marge; Lin, Pei-Jung; McCarten, J. Riley; Morris, John C.; Salmon, David P.; Schmitt, Frederick A.; Stefanacci, Richard G.; Mendiondo, Marta S.; Peschin, Susan; Hall, Eric J.; Fillit, Howard; Ashford, J. Wesson

    2014-01-01

    The value of screening for cognitive impairment, including dementia and Alzheimer's disease, has been debated for decades. Recent research on causes of and treatments for cognitive impairment has converged to challenge previous thinking about screening for cognitive impairment. Consequently, changes have occurred in health care policies and priorities, including the establishment of the annual wellness visit, which requires detection of any cognitive impairment for Medicare enrollees. In response to these changes, the Alzheimer's Foundation of America and the Alzheimer's Drug Discovery Foundation convened a workgroup to review evidence for screening implementation and to evaluate the implications of routine dementia detection for health care redesign. The primary domains reviewed were consideration of the benefits, harms, and impact of cognitive screening on health care quality. In conference, the workgroup developed 10 recommendations for realizing the national policy goals of early detection as the first step in improving clinical care and ensuring proactive, patient-centered management of dementia. PMID:23375564

  20. SQUID sensor application for small metallic particle detection

    International Nuclear Information System (INIS)

    Tanaka, Saburo; Hatsukade, Yoshimi; Ohtani, Takeyoshi; Suzuki, Shuichi

    2009-01-01

    High-Tc superconducting quantum interference device (SQUID) is an ultra-sensitive magnetic sensor. Since the performance of the SQUID is improved and stabilized, now it is ready for application. One strong candidate for application is a detection system of magnetic foreign matters in industrial products or beverages. There is a possibility that ultra-small metallic foreign matter has been accidentally mixed with industrial products such as lithium ion batteries. If this happens, the manufacturer of the product suffers a great loss recalling products. The outer dimension of metallic particles less than 100 μm cannot be detected by an X-ray imaging, which is commonly used for the inspection. Ionization of the material is also a big issue for beverages in the case of the X-ray imaging. Therefore a highly sensitive and safety detection system for small foreign matters is required. We developed detection systems based on high-Tc SQUID with a high-performance magnetic shield. We could successfully measure small iron particles of 100 μm on a belt conveyer and stainless steel balls of 300 μm in water. These detection levels were hard to be achieved by a conventional X-ray detection or other methods

  1. xMSanalyzer: automated pipeline for improved feature detection and downstream analysis of large-scale, non-targeted metabolomics data

    Directory of Open Access Journals (Sweden)

    Uppal Karan

    2013-01-01

    Full Text Available Abstract Background Detection of low abundance metabolites is important for de novo mapping of metabolic pathways related to diet, microbiome or environmental exposures. Multiple algorithms are available to extract m/z features from liquid chromatography-mass spectral data in a conservative manner, which tends to preclude detection of low abundance chemicals and chemicals found in small subsets of samples. The present study provides software to enhance such algorithms for feature detection, quality assessment, and annotation. Results xMSanalyzer is a set of utilities for automated processing of metabolomics data. The utilites can be classified into four main modules to: 1 improve feature detection for replicate analyses by systematic re-extraction with multiple parameter settings and data merger to optimize the balance between sensitivity and reliability, 2 evaluate sample quality and feature consistency, 3 detect feature overlap between datasets, and 4 characterize high-resolution m/z matches to small molecule metabolites and biological pathways using multiple chemical databases. The package was tested with plasma samples and shown to more than double the number of features extracted while improving quantitative reliability of detection. MS/MS analysis of a random subset of peaks that were exclusively detected using xMSanalyzer confirmed that the optimization scheme improves detection of real metabolites. Conclusions xMSanalyzer is a package of utilities for data extraction, quality control assessment, detection of overlapping and unique metabolites in multiple datasets, and batch annotation of metabolites. The program was designed to integrate with existing packages such as apLCMS and XCMS, but the framework can also be used to enhance data extraction for other LC/MS data software.

  2. Improved detection of multiple environmental antibiotics through an optimized sample extraction strategy in liquid chromatography-mass spectrometry analysis.

    Science.gov (United States)

    Yi, Xinzhu; Bayen, Stéphane; Kelly, Barry C; Li, Xu; Zhou, Zhi

    2015-12-01

    A solid-phase extraction/liquid chromatography/electrospray ionization/multi-stage mass spectrometry (SPE-LC-ESI-MS/MS) method was optimized in this study for sensitive and simultaneous detection of multiple antibiotics in urban surface waters and soils. Among the seven classes of tested antibiotics, extraction efficiencies of macrolides, lincosamide, chloramphenicol, and polyether antibiotics were significantly improved under optimized sample extraction pH. Instead of only using acidic extraction in many existing studies, the results indicated that antibiotics with low pK a values (antibiotics with high pK a values (>7) were extracted more efficiently under neutral conditions. The effects of pH were more obvious on polar compounds than those on non-polar compounds. Optimization of extraction pH resulted in significantly improved sample recovery and better detection limits. Compared with reported values in the literature, the average reduction of minimal detection limits obtained in this study was 87.6% in surface waters (0.06-2.28 ng/L) and 67.1% in soils (0.01-18.16 ng/g dry wt). This method was subsequently applied to detect antibiotics in environmental samples in a heavily populated urban city, and macrolides, sulfonamides, and lincomycin were frequently detected. Antibiotics with highest detected concentrations were sulfamethazine (82.5 ng/L) in surface waters and erythromycin (6.6 ng/g dry wt) in soils. The optimized sample extraction strategy can be used to improve the detection of a variety of antibiotics in environmental surface waters and soils.

  3. Improved multi-stage neonatal seizure detection using a heuristic classifier and a data-driven post-processor.

    Science.gov (United States)

    Ansari, A H; Cherian, P J; Dereymaeker, A; Matic, V; Jansen, K; De Wispelaere, L; Dielman, C; Vervisch, J; Swarte, R M; Govaert, P; Naulaers, G; De Vos, M; Van Huffel, S

    2016-09-01

    After identifying the most seizure-relevant characteristics by a previously developed heuristic classifier, a data-driven post-processor using a novel set of features is applied to improve the performance. The main characteristics of the outputs of the heuristic algorithm are extracted by five sets of features including synchronization, evolution, retention, segment, and signal features. Then, a support vector machine and a decision making layer remove the falsely detected segments. Four datasets including 71 neonates (1023h, 3493 seizures) recorded in two different university hospitals, are used to train and test the algorithm without removing the dubious seizures. The heuristic method resulted in a false alarm rate of 3.81 per hour and good detection rate of 88% on the entire test databases. The post-processor, effectively reduces the false alarm rate by 34% while the good detection rate decreases by 2%. This post-processing technique improves the performance of the heuristic algorithm. The structure of this post-processor is generic, improves our understanding of the core visually determined EEG features of neonatal seizures and is applicable for other neonatal seizure detectors. The post-processor significantly decreases the false alarm rate at the expense of a small reduction of the good detection rate. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  4. Year-round presence of neonicotinoid insecticides in tributaries to the Great Lakes, USA

    Science.gov (United States)

    To better understand the transport of neonicotinoid insecticides to a sensitive freshwater ecosystem, monthly samples (October 2015-September 2016) were collected from 10 major tributaries to the Great Lakes, USA. For the monthly tributary samples, neonicotinoids were detected in...

  5. ASCS online fault detection and isolation based on an improved MPCA

    Science.gov (United States)

    Peng, Jianxin; Liu, Haiou; Hu, Yuhui; Xi, Junqiang; Chen, Huiyan

    2014-09-01

    Multi-way principal component analysis (MPCA) has received considerable attention and been widely used in process monitoring. A traditional MPCA algorithm unfolds multiple batches of historical data into a two-dimensional matrix and cut the matrix along the time axis to form subspaces. However, low efficiency of subspaces and difficult fault isolation are the common disadvantages for the principal component model. This paper presents a new subspace construction method based on kernel density estimation function that can effectively reduce the storage amount of the subspace information. The MPCA model and the knowledge base are built based on the new subspace. Then, fault detection and isolation with the squared prediction error (SPE) statistic and the Hotelling ( T 2) statistic are also realized in process monitoring. When a fault occurs, fault isolation based on the SPE statistic is achieved by residual contribution analysis of different variables. For fault isolation of subspace based on the T 2 statistic, the relationship between the statistic indicator and state variables is constructed, and the constraint conditions are presented to check the validity of fault isolation. Then, to improve the robustness of fault isolation to unexpected disturbances, the statistic method is adopted to set the relation between single subspace and multiple subspaces to increase the corrective rate of fault isolation. Finally fault detection and isolation based on the improved MPCA is used to monitor the automatic shift control system (ASCS) to prove the correctness and effectiveness of the algorithm. The research proposes a new subspace construction method to reduce the required storage capacity and to prove the robustness of the principal component model, and sets the relationship between the state variables and fault detection indicators for fault isolation.

  6. Improved detection of focal pneumonia by chest radiography with bone suppression imaging

    International Nuclear Information System (INIS)

    Li, Feng; Engelmann, Roger; Pesce, Lorenzo; Armato, Samuel G.; MacMahon, Heber

    2012-01-01

    To evaluate radiologists' ability to detect focal pneumonia by use of standard chest radiographs alone compared with standard plus bone-suppressed chest radiographs. Standard chest radiographs in 36 patients with 46 focal airspace opacities due to pneumonia (10 patients had bilateral opacities) and 20 patients without focal opacities were included in an observer study. A bone suppression image processing system was applied to the 56 radiographs to create corresponding bone suppression images. In the observer study, eight observers, including six attending radiologists and two radiology residents, indicated their confidence level regarding the presence of a focal opacity compatible with pneumonia for each lung, first by use of standard images, then with the addition of bone suppression images. Receiver operating characteristic (ROC) analysis was used to evaluate the observers' performance. The mean value of the area under the ROC curve (AUC) for eight observers was significantly improved from 0.844 with use of standard images alone to 0.880 with standard plus bone suppression images (P < 0.001) based on 46 positive lungs and 66 negative lungs. Use of bone suppression images improved radiologists' performance for detection of focal pneumonia on chest radiographs. (orig.)

  7. Improved detection of focal pneumonia by chest radiography with bone suppression imaging

    Energy Technology Data Exchange (ETDEWEB)

    Li, Feng; Engelmann, Roger; Pesce, Lorenzo; Armato, Samuel G.; MacMahon, Heber [University of Chicago, Department of Radiology, MC-2026, Chicago, IL (United States)

    2012-12-15

    To evaluate radiologists' ability to detect focal pneumonia by use of standard chest radiographs alone compared with standard plus bone-suppressed chest radiographs. Standard chest radiographs in 36 patients with 46 focal airspace opacities due to pneumonia (10 patients had bilateral opacities) and 20 patients without focal opacities were included in an observer study. A bone suppression image processing system was applied to the 56 radiographs to create corresponding bone suppression images. In the observer study, eight observers, including six attending radiologists and two radiology residents, indicated their confidence level regarding the presence of a focal opacity compatible with pneumonia for each lung, first by use of standard images, then with the addition of bone suppression images. Receiver operating characteristic (ROC) analysis was used to evaluate the observers' performance. The mean value of the area under the ROC curve (AUC) for eight observers was significantly improved from 0.844 with use of standard images alone to 0.880 with standard plus bone suppression images (P < 0.001) based on 46 positive lungs and 66 negative lungs. Use of bone suppression images improved radiologists' performance for detection of focal pneumonia on chest radiographs. (orig.)

  8. Year-round presence of neonicotinoid insecticides in tributaries to the Great Lakes, USA

    Science.gov (United States)

    Hladik, Michelle; Corsi, Steven; Kolpin, Dana W.; Baldwin, Austin K.; Blackwell, Brett R.; Cavallin, Jenna E.

    2018-01-01

    To better characterize the transport of neonicotinoid insecticides to the world's largest freshwater ecosystem, monthly samples (October 2015–September 2016) were collected from 10 major tributaries to the Great Lakes, USA. For the monthly tributary samples, neonicotinoids were detected in every month sampled and five of the six target neonicotinoids were detected. At least one neonicotinoid was detected in 74% of the monthly samples with up to three neonicotinoids detected in an individual sample (10% of all samples). The most frequently detected neonicotinoid was imidacloprid (53%), followed by clothianidin (44%), thiamethoxam (22%), acetamiprid (2%), and dinotefuran (1%). Thiacloprid was not detected in any samples. The maximum concentration for an individual neonicotinoid was 230 ng L−1 and the maximum total neonicotinoids in an individual sample was 400 ng L−1. The median detected individual neonicotinoid concentrations ranged from non-detect to 10 ng L−1. The detections of clothianidin and thiamethoxam significantly increased as the percent of cultivated crops in the basins increased (ρ = 0.73, P = .01; ρ = 0.66, P = .04, respectively). In contrast, imidacloprid detections significantly increased as the percent of the urbanization in the basins increased (ρ = 0.66, P = .03). Neonicotinoid concentrations generally increased in spring through summer coinciding with the planting of neonicotinoid-treated seeds and broadcast applications of neonicotinoids. More spatially intensive samples were collected in an agriculturally dominated basin (8 sites along the Maumee River, Ohio) twice during the spring, 2016 planting season to provide further information on neonicotinoid inputs to the Great Lakes. Three neonicotinoids were ubiquitously detected (clothianidin, imidacloprid, thiamethoxam) in all water samples collected within this basin. Maximum individual neonicotinoid concentrations was 330 ng L−1

  9. Data requirements of GREAT-ER: Modelling and validation using LAS in four UK catchments

    International Nuclear Information System (INIS)

    Price, Oliver R.; Munday, Dawn K.; Whelan, Mick J.; Holt, Martin S.; Fox, Katharine K.; Morris, Gerard; Young, Andrew R.

    2009-01-01

    Higher-tier environmental risk assessments on 'down-the-drain' chemicals in river networks can be conducted using models such as GREAT-ER (Geography-referenced Regional Exposure Assessment Tool for European Rivers). It is important these models are evaluated and their sensitivities to input variables understood. This study had two primary objectives: evaluate GREAT-ER model performance, comparing simulated modelled predictions for LAS (linear alkylbenzene sulphonate) with measured concentrations, for four rivers in the UK, and investigate model sensitivity to input variables. We demonstrate that the GREAT-ER model is very sensitive to variability in river discharges. However it is insensitive to the form of distributions used to describe chemical usage and removal rate in sewage treatment plants (STPs). It is concluded that more effort should be directed towards improving empirical estimates of effluent load and reducing uncertainty associated with usage and removal rates in STPs. Simulations could be improved by incorporating the effect of river depth on dissipation rates. - Validation of GREAT-ER.

  10. Data requirements of GREAT-ER: Modelling and validation using LAS in four UK catchments

    Energy Technology Data Exchange (ETDEWEB)

    Price, Oliver R., E-mail: oliver.price@unilever.co [Safety and Environmental Assurance Centre, Unilever, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ (United Kingdom); Munday, Dawn K. [Safety and Environmental Assurance Centre, Unilever, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ (United Kingdom); Whelan, Mick J. [Department of Natural Resources, School of Applied Sciences, Cranfield University, College Road, Cranfield, Bedfordshire MK43 0AL (United Kingdom); Holt, Martin S. [ECETOC, Ave van Nieuwenhuyse 4, Box 6, B-1160 Brussels (Belgium); Fox, Katharine K. [85 Park Road West, Birkenhead, Merseyside CH43 8SQ (United Kingdom); Morris, Gerard [Environment Agency, Phoenix House, Global Avenue, Leeds LS11 8PG (United Kingdom); Young, Andrew R. [Wallingford HydroSolutions Ltd, Maclean building, Crowmarsh Gifford, Wallingford, Oxon OX10 8BB (United Kingdom)

    2009-10-15

    Higher-tier environmental risk assessments on 'down-the-drain' chemicals in river networks can be conducted using models such as GREAT-ER (Geography-referenced Regional Exposure Assessment Tool for European Rivers). It is important these models are evaluated and their sensitivities to input variables understood. This study had two primary objectives: evaluate GREAT-ER model performance, comparing simulated modelled predictions for LAS (linear alkylbenzene sulphonate) with measured concentrations, for four rivers in the UK, and investigate model sensitivity to input variables. We demonstrate that the GREAT-ER model is very sensitive to variability in river discharges. However it is insensitive to the form of distributions used to describe chemical usage and removal rate in sewage treatment plants (STPs). It is concluded that more effort should be directed towards improving empirical estimates of effluent load and reducing uncertainty associated with usage and removal rates in STPs. Simulations could be improved by incorporating the effect of river depth on dissipation rates. - Validation of GREAT-ER.

  11. Multi-disciplinary team for early gastric cancer diagnosis improves the detection rate of early gastric cancer.

    Science.gov (United States)

    Di, Lianjun; Wu, Huichao; Zhu, Rong; Li, Youfeng; Wu, Xinglong; Xie, Rui; Li, Hongping; Wang, Haibo; Zhang, Hua; Xiao, Hong; Chen, Hui; Zhen, Hong; Zhao, Kui; Yang, Xuefeng; Xie, Ming; Tuo, Bigung

    2017-12-06

    Gastric cancer is a frequent malignant tumor worldwide and its early detection is crucial for curing the disease and enhancing patients' survival rate. This study aimed to assess whether the multi-disciplinary team (MDT) can improve the detection rate of early gastric cancer (EGC). The detection rate of EGC at the Digestive Endoscopy Center, Affiliated Hospital, Zunyi Medical College, China between September 2013 and September 2015 was analyzed. MDT for the diagnosis of EGC in the hospital was established in September 2014. The study was divided into 2 time periods: September 1, 2013 to August 31, 2014 (period 1) and September 1, 2014 to September 1, 2015 (period 2). A total of 60,800 patients' gastroscopies were performed during the two years. 61 of these patients (0.1%) were diagnosed as EGC, accounting for 16.44% (61/371) of total patients with gastric cancer. The EGC detection rate before MDT (period 1) was 0.05% (16/29403), accounting for 9.09% (16/176) of total patients with gastric cancer during this period. In comparison, the EGC detection rate during MDT (period 2) was 0.15% (45/31397), accounting for 23% (45/195) of total patients with gastric cancer during this period (P cooperation with Department of Pathology (OR = 10.1, 95% CI 2.39-43.3, P < 0.05). MDT could improve the endoscopic detection rate of EGC.

  12. Sensitivity improvement of Cerenkov luminescence endoscope with terbium doped Gd{sub 2}O{sub 2}S nanoparticles

    Energy Technology Data Exchange (ETDEWEB)

    Cao, Xin; Chen, Xueli, E-mail: xlchen@xidian.edu.cn, E-mail: jimleung@mail.xidian.edu.cn; Cao, Xu; Zhan, Yonghua; Liang, Jimin, E-mail: xlchen@xidian.edu.cn, E-mail: jimleung@mail.xidian.edu.cn [Engineering Research Center of Molecular and Neuro Imaging of the Ministry of Education and School of Life Science and Technology, Xidian University, Xi' an, Shaanxi 710071 (China); Kang, Fei; Wang, Jing [Department of Nuclear Medicine, Xijing Hospital, Fourth Military Medical University, Xi' an, Shaanxi 710032 (China); Wu, Kaichun [Department of Digestive Diseases, Xijing Hospital, Fourth Military Medical University, Xi' an, Shaanxi 710032 (China)

    2015-05-25

    Our previous study showed a great attenuation for the Cerenkov luminescence endoscope (CLE), resulting in relatively low detection sensitivity of radiotracers. Here, a kind of radioluminescence nanoparticles (RLNPs), terbium doped Gd{sub 2}O{sub 2}S was mixed with the radionuclide {sup 68}Ga to enhance the intensity of emitted luminescence, which finally improved the detection sensitivity of the CLE by using the radioluminescence imaging technique. With the in vitro and in vivo pseudotumor experiments, we showed that the use of RLNPs mixed with the radionuclide {sup 68}Ga enabled superior sensitivity compared with the radionuclide {sup 68}Ga only, with 50-fold improvement on detection sensitivity, which guaranteed meeting the demands of the clinical diagnosis of gastrointestinal tract tumors.

  13. Use of two detection methods to discriminate ciguatoxins from brevetoxins: application to great barracuda from Florida Keys.

    Science.gov (United States)

    Dechraoui, M-Yasmine Bottein; Tiedeken, Jessica A; Persad, Renuka; Wang, Zhihong; Granade, H Ray; Dickey, Robert W; Ramsdell, John S

    2005-09-01

    In Florida (USA), numerous cases of human ciguatera fish poisoning, as well as neurotoxic shellfish poisoning following consumption of local seafood products, have been reported. By using in parallel, the sodium channel receptor binding assay (RBA), and the ouabain/veratridine-dependent cytotoxicity assay (N2A assay), we established criteria to identify, detect, and quantify ciguatoxins in fish extracts, with a brevetoxin as internal standard. Results showed that the Caribbean ciguatoxin C-CTX-1 exhibited an 8-fold higher potency in the RBA than brevetoxins and, a 440 and 2300-fold higher potency in the N2A assay than PbTx-1 and PbTx-3, respectively. Moreover, a sensitivity comparison between assays revealed that the N2A assay was more sensitive (12-fold) for ciguatoxin analysis, whereas the RBA was more sensitive (3-24-fold) for brevetoxins analysis. Based on the relative potency between toxins and the opposite sensitivity of both assays we have used the RBA and the N2A assay to screen great barracuda (Sphyraena barracuda) collected from the Florida Keys for ciguatoxins and brevetoxins. Fish extract analysis showed a sodium channel-dependent activity consistent with the presence of ciguatoxins, and not brevetoxins. Among 40 barracudas analyzed, 60% contained ciguatoxin levels in their liver measurable by the N2A assay with the most toxic fish containing 2.1ppb C-CTX-1 equivalents.

  14. Improving mass candidate detection in mammograms via feature maxima propagation and local feature selection.

    Science.gov (United States)

    Melendez, Jaime; Sánchez, Clara I; van Ginneken, Bram; Karssemeijer, Nico

    2014-08-01

    Mass candidate detection is a crucial component of multistep computer-aided detection (CAD) systems. It is usually performed by combining several local features by means of a classifier. When these features are processed on a per-image-location basis (e.g., for each pixel), mismatching problems may arise while constructing feature vectors for classification, which is especially true when the behavior expected from the evaluated features is a peaked response due to the presence of a mass. In this study, two of these problems, consisting of maxima misalignment and differences of maxima spread, are identified and two solutions are proposed. The first proposed method, feature maxima propagation, reproduces feature maxima through their neighboring locations. The second method, local feature selection, combines different subsets of features for different feature vectors associated with image locations. Both methods are applied independently and together. The proposed methods are included in a mammogram-based CAD system intended for mass detection in screening. Experiments are carried out with a database of 382 digital cases. Sensitivity is assessed at two sets of operating points. The first one is the interval of 3.5-15 false positives per image (FPs/image), which is typical for mass candidate detection. The second one is 1 FP/image, which allows to estimate the quality of the mass candidate detector's output for use in subsequent steps of the CAD system. The best results are obtained when the proposed methods are applied together. In that case, the mean sensitivity in the interval of 3.5-15 FPs/image significantly increases from 0.926 to 0.958 (p < 0.0002). At the lower rate of 1 FP/image, the mean sensitivity improves from 0.628 to 0.734 (p < 0.0002). Given the improved detection performance, the authors believe that the strategies proposed in this paper can render mass candidate detection approaches based on image location classification more robust to feature

  15. Automatic video shot boundary detection using k-means clustering and improved adaptive dual threshold comparison

    Science.gov (United States)

    Sa, Qila; Wang, Zhihui

    2018-03-01

    At present, content-based video retrieval (CBVR) is the most mainstream video retrieval method, using the video features of its own to perform automatic identification and retrieval. This method involves a key technology, i.e. shot segmentation. In this paper, the method of automatic video shot boundary detection with K-means clustering and improved adaptive dual threshold comparison is proposed. First, extract the visual features of every frame and divide them into two categories using K-means clustering algorithm, namely, one with significant change and one with no significant change. Then, as to the classification results, utilize the improved adaptive dual threshold comparison method to determine the abrupt as well as gradual shot boundaries.Finally, achieve automatic video shot boundary detection system.

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

    Science.gov (United States)

    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

  17. Fast rail corrugation detection based on texture filtering

    Science.gov (United States)

    Xiao, Jie; Lu, Kaixia

    2018-02-01

    The condition detection of rails in high-speed railway is one of the important means to ensure the safety of railway transportation. In order to replace the traditional manual inspection, save manpower and material resources, and improve the detection speed and accuracy, it is of great significance to develop a machine vision system for locating and identifying defects on rails automatically. Rail defects exhibit different properties and are divided into various categories related to the type and position of flaws on the rail. Several kinds of interrelated factors cause rail defects such as type of rail, construction conditions, and speed and/or frequency of trains using the rail. Rail corrugation is a particular kind of defects that produce an undulatory deformation on the rail heads. In high speed train, the corrugation induces harmful vibrations on wheels and its components and reduces the lifetime of rails. This type of defects should be detected to avoid rail fractures. In this paper, a novel method for fast rail corrugation detection based on texture filtering was proposed.

  18. Improved optical ranging for space based gravitational wave detection

    International Nuclear Information System (INIS)

    Sutton, Andrew J; Shaddock, Daniel A; McKenzie, Kirk; Ware, Brent; De Vine, Glenn; Spero, Robert E; Klipstein, W

    2013-01-01

    The operation of 10 6  km scale laser interferometers in space will permit the detection of gravitational waves at previously unaccessible frequency regions. Multi-spacecraft missions, such as the Laser Interferometer Space Antenna (LISA), will use time delay interferometry to suppress the otherwise dominant laser frequency noise from their measurements. This is accomplished by performing sub-sample interpolation of the optical phase measurements recorded at each spacecraft for synchronization and cancellation of the otherwise dominant laser frequency noise. These sub-sample interpolation time shifts are dependent upon the inter-spacecraft range and will be measured using a pseudo-random noise ranging modulation upon the science laser. One limit to the ranging performance is mutual interference between the outgoing and incoming ranging signals upon each spacecraft. This paper reports on the demonstration of a noise cancellation algorithm which is shown to providing a factor of ∼8 suppression of the mutual interference noise. Demonstration of the algorithm in an optical test bed showed an rms ranging error of 0.06 m, improved from 0.19 m in previous results, surpassing the 1 m RMS LISA specification and potentially improving the cancellation of laser frequency noise. (paper)

  19. Detection of neovascularization based on fractal and texture analysis with interaction effects in diabetic retinopathy.

    Science.gov (United States)

    Lee, Jack; Zee, Benny Chung Ying; Li, Qing

    2013-01-01

    Diabetic retinopathy is a major cause of blindness. Proliferative diabetic retinopathy is a result of severe vascular complication and is visible as neovascularization of the retina. Automatic detection of such new vessels would be useful for the severity grading of diabetic retinopathy, and it is an important part of screening process to identify those who may require immediate treatment for their diabetic retinopathy. We proposed a novel new vessels detection method including statistical texture analysis (STA), high order spectrum analysis (HOS), fractal analysis (FA), and most importantly we have shown that by incorporating their associated interactions the accuracy of new vessels detection can be greatly improved. To assess its performance, the sensitivity, specificity and accuracy (AUC) are obtained. They are 96.3%, 99.1% and 98.5% (99.3%), respectively. It is found that the proposed method can improve the accuracy of new vessels detection significantly over previous methods. The algorithm can be automated and is valuable to detect relatively severe cases of diabetic retinopathy among diabetes patients.

  20. Detection of neovascularization based on fractal and texture analysis with interaction effects in diabetic retinopathy.

    Directory of Open Access Journals (Sweden)

    Jack Lee

    Full Text Available Diabetic retinopathy is a major cause of blindness. Proliferative diabetic retinopathy is a result of severe vascular complication and is visible as neovascularization of the retina. Automatic detection of such new vessels would be useful for the severity grading of diabetic retinopathy, and it is an important part of screening process to identify those who may require immediate treatment for their diabetic retinopathy. We proposed a novel new vessels detection method including statistical texture analysis (STA, high order spectrum analysis (HOS, fractal analysis (FA, and most importantly we have shown that by incorporating their associated interactions the accuracy of new vessels detection can be greatly improved. To assess its performance, the sensitivity, specificity and accuracy (AUC are obtained. They are 96.3%, 99.1% and 98.5% (99.3%, respectively. It is found that the proposed method can improve the accuracy of new vessels detection significantly over previous methods. The algorithm can be automated and is valuable to detect relatively severe cases of diabetic retinopathy among diabetes patients.

  1. Improved detection limit for {sup 59}Ni using the technique of accelerator mass spectrometry

    Energy Technology Data Exchange (ETDEWEB)

    Persson, Per; Erlandsson, Bengt; Hellborg, Ragnar; Kiisk, Madis; Larsson, Ragnar; Skog, Goeran; Stenstroem, Kristina [Lund Univ. (Sweden). Dept. of Nuclear Physics

    2002-11-01

    59 Ni is produced by neutron activation in the stainless steel close to the core of a nuclear reactor. To be able to classify the different parts of the reactor with respect to their content of long-lived radionuclides before final storage it is important to measure the 59 Ni level. Accelerator mass spectrometry is an ultra-sensitive method for counting atoms, suitable for 59 Ni measurements. Improvements in the reduction of the background and in the chemical reduction of cobalt, the interfering isobar, have been made. This chemical purification is essential when using small tandem accelerators, <3 MV, combined with the detection of characteristic projectile X-rays. These improvements have lowered the detection limit for 59 Ni by a factor of twenty compared with the first value reported for the Lund AMS facility. Material from the Swedish nuclear industry has been analysed and examples of the results are presented.

  2. Research on Copy-Move Image Forgery Detection Using Features of Discrete Polar Complex Exponential Transform

    Science.gov (United States)

    Gan, Yanfen; Zhong, Junliu

    2015-12-01

    With the aid of sophisticated photo-editing software, such as Photoshop, copy-move image forgery operation has been widely applied and has become a major concern in the field of information security in the modern society. A lot of work on detecting this kind of forgery has gained great achievements, but the detection results of geometrical transformations of copy-move regions are not so satisfactory. In this paper, a new method based on the Polar Complex Exponential Transform is proposed. This method addresses issues in image geometric moment, focusing on constructing rotation invariant moment and extracting features of the rotation invariant moment. In order to reduce rounding errors of the transform from the Polar coordinate system to the Cartesian coordinate system, a new transformation method is presented and discussed in detail at the same time. The new method constructs a 9 × 9 shrunk template to transform the Cartesian coordinate system back to the Polar coordinate system. It can reduce transform errors to a much greater degree. Forgery detection, such as copy-move image forgery detection, is a difficult procedure, but experiments prove our method is a great improvement in detecting and identifying forgery images affected by the rotated transform.

  3. Improved detection probability of low level light and infrared image fusion system

    Science.gov (United States)

    Luo, Yuxiang; Fu, Rongguo; Zhang, Junju; Wang, Wencong; Chang, Benkang

    2018-02-01

    Low level light(LLL) image contains rich information on environment details, but is easily affected by the weather. In the case of smoke, rain, cloud or fog, much target information will lose. Infrared image, which is from the radiation produced by the object itself, can be "active" to obtain the target information in the scene. However, the image contrast and resolution is bad, the ability of the acquisition of target details is very poor, and the imaging mode does not conform to the human visual habit. The fusion of LLL and infrared image can make up for the deficiency of each sensor and give play to the advantages of single sensor. At first, we show the hardware design of fusion circuit. Then, through the recognition probability calculation of the target(one person) and the background image(trees), we find that the trees detection probability of LLL image is higher than that of the infrared image, and the person detection probability of the infrared image is obviously higher than that of LLL image. The detection probability of fusion image for one person and trees is higher than that of single detector. Therefore, image fusion can significantly enlarge recognition probability and improve detection efficiency.

  4. Joint estimation of crown of thorns (Acanthaster planci densities on the Great Barrier Reef

    Directory of Open Access Journals (Sweden)

    M. Aaron MacNeil

    2016-08-01

    Full Text Available Crown-of-thorns starfish (CoTS; Acanthaster spp. are an outbreaking pest among many Indo-Pacific coral reefs that cause substantial ecological and economic damage. Despite ongoing CoTS research, there remain critical gaps in observing CoTS populations and accurately estimating their numbers, greatly limiting understanding of the causes and sources of CoTS outbreaks. Here we address two of these gaps by (1 estimating the detectability of adult CoTS on typical underwater visual count (UVC surveys using covariates and (2 inter-calibrating multiple data sources to estimate CoTS densities within the Cairns sector of the Great Barrier Reef (GBR. We find that, on average, CoTS detectability is high at 0.82 [0.77, 0.87] (median highest posterior density (HPD and [95% uncertainty intervals], with CoTS disc width having the greatest influence on detection. Integrating this information with coincident surveys from alternative sampling programs, we estimate CoTS densities in the Cairns sector of the GBR averaged 44 [41, 48] adults per hectare in 2014.

  5. Artificial reefs and reef restoration in the Laurentian Great Lakes

    Science.gov (United States)

    McLean, Matthew W.; Roseman, Edward; Pritt, Jeremy J.; Kennedy, Gregory W.; Manny, Bruce A.

    2015-01-01

    We reviewed the published literature to provide an inventory of Laurentian Great Lakes artificial reef projects and their purposes. We also sought to characterize physical and biological monitoring for artificial reef projects in the Great Lakes and determine the success of artificial reefs in meeting project objectives. We found records of 6 artificial reefs in Lake Erie, 8 in Lake Michigan, 3 in Lakes Huron and Ontario, and 2 in Lake Superior. We found 9 reefs in Great Lakes connecting channels and 6 reefs in Great Lakes tributaries. Objectives of artificial reef creation have included reducing impacts of currents and waves, providing safe harbors, improving sport-fishing opportunities, and enhancing/restoring fish spawning habitats. Most reefs in the lakes themselves were incidental (not created purposely for fish habitat) or built to improve local sport fishing, whereas reefs in tributaries and connecting channels were more frequently built to benefit fish spawning. Levels of assessment of reef performance varied; but long-term monitoring was uncommon as was assessment of physical attributes. Artificial reefs were often successful at attracting recreational species and spawning fish; however, population-level benefits of artificial reefs are unclear. Stressors such as sedimentation and bio-fouling can limit the effectiveness of artificial reefs as spawning enhancement tools. Our investigation underscores the need to develop standard protocols for monitoring the biological and physical attributes of artificial structures. Further, long-term monitoring is needed to assess the benefits of artificial reefs to fish populations and inform future artificial reef projects.

  6. Enhancement of MS Signal Processing For Improved Cancer Biomarker Discovery

    Science.gov (United States)

    Si, Qian

    Technological advances in proteomics have shown great potential in detecting cancer at the earliest stages. One way is to use the time of flight mass spectroscopy to identify biomarkers, or early disease indicators related to the cancer. Pattern analysis of time of flight mass spectra data from blood and tissue samples gives great hope for the identification of potential biomarkers among the complex mixture of biological and chemical samples for the early cancer detection. One of the keys issues is the pre-processing of raw mass spectra data. A lot of challenges need to be addressed: unknown noise character associated with the large volume of data, high variability in the mass spectroscopy measurements, and poorly understood signal background and so on. This dissertation focuses on developing statistical algorithms and creating data mining tools for computationally improved signal processing for mass spectrometry data. I have introduced an advanced accurate estimate of the noise model and a half-supervised method of mass spectrum data processing which requires little knowledge about the data.

  7. Detection of mRNA by reverse-transcription PCR as an indicator of viability in Phytophthora ramorum

    Science.gov (United States)

    A. Chimento; S.O. Cacciola; M. Garbelotto

    2011-01-01

    In the last few decades, the use of molecular tools has greatly improved the efficiency of plant disease diagnosis. However, one of the major setbacks of most molecular diagnostic approaches is their inability to differentiate between dead and viable pathogens. We propose a new strategy for the detection of plant pathogens, based on the use of mRNA as a viability...

  8. Improved Diffuse Fluorescence Flow Cytometer Prototype for High Sensitivity Detection of Rare Circulating Cells In Vivo

    Science.gov (United States)

    Pestana, Noah Benjamin

    Accurate quantification of circulating cell populations is important in many areas of pre-clinical and clinical biomedical research, for example, in the study of cancer metastasis or the immune response following tissue and organ transplants. Normally this is done "ex-vivo" by drawing and purifying a small volume of blood and then analyzing it with flow cytometry, hemocytometry or microfludic devices, but the sensitivity of these techniques are poor and the process of handling samples has been shown to affect cell viability and behavior. More recently "in vivo flow cytometry" (IVFC) techniques have been developed where fluorescently-labeled cells flowing in a small blood vessel in the ear or retina are analyzed, but the sensitivity is generally poor due to the small sampling volume. To address this, our group recently developed a method known as "Diffuse Fluorescence Flow Cytometry" (DFFC) that allows detection and counting of rare circulating cells with diffuse photons, offering extremely high single cell counting sensitivity. In this thesis, an improved DFFC prototype was designed and validated. The chief improvements were three-fold, i) improved optical collection efficiency, ii) improved detection electronics, and iii) development of a method to mitigate motion artifacts during in vivo measurements. In combination, these improvements yielded an overall instrument detection sensitivity better than 1 cell/mL in vivo, which is the most sensitive IVFC system reported to date. Second, development and validation of a low-cost microfluidic device reader for analysis of ocular fluids is described. We demonstrate that this device has equivalent or better sensitivity and accuracy compared a fluorescence microscope, but at an order-of-magnitude reduced cost with simplified operation. Future improvements to both instruments are also discussed.

  9. Adaptive sampling algorithm for detection of superpoints

    Institute of Scientific and Technical Information of China (English)

    CHENG Guang; GONG Jian; DING Wei; WU Hua; QIANG ShiQiang

    2008-01-01

    The superpoints are the sources (or the destinations) that connect with a great deal of destinations (or sources) during a measurement time interval, so detecting the superpoints in real time is very important to network security and management. Previous algorithms are not able to control the usage of the memory and to deliver the desired accuracy, so it is hard to detect the superpoints on a high speed link in real time. In this paper, we propose an adaptive sampling algorithm to detect the superpoints in real time, which uses a flow sample and hold module to reduce the detection of the non-superpoints and to improve the measurement accuracy of the superpoints. We also design a data stream structure to maintain the flow records, which compensates for the flow Hash collisions statistically. An adaptive process based on different sampling probabilities is used to maintain the recorded IP ad dresses in the limited memory. This algorithm is compared with the other algo rithms by analyzing the real network trace data. Experiment results and mathematic analysis show that this algorithm has the advantages of both the limited memory requirement and high measurement accuracy.

  10. Simplified Metrics Calculation for Soft Bit Detection in DVB-T2

    Directory of Open Access Journals (Sweden)

    D. Perez-Calderon

    2014-04-01

    Full Text Available The constellation rotation and cyclic quadrature component delay (RQD technique has been adopted in the second generation terrestrial digital video broadcasting (DVB-T2 standard. It improves the system performance under severe propagation conditions, but introduces serious complexity problems in the hardware implementation of the detection process. In this paper, we present a simplified scheme that greatly reduces the complexity of the demapper by simplifying the soft bit metrics computation having a negligible overall system performance loss.

  11. Artificial neural network techniques to improve the ability of optical coherence tomography to detect optic neuritis.

    Science.gov (United States)

    Garcia-Martin, Elena; Herrero, Raquel; Bambo, Maria P; Ara, Jose R; Martin, Jesus; Polo, Vicente; Larrosa, Jose M; Garcia-Feijoo, Julian; Pablo, Luis E

    2015-01-01

    To analyze the ability of Spectralis optical coherence tomography (OCT) to detect multiple sclerosis (MS) and to distinguish MS eyes with antecedent optic neuritis (ON). To analyze the capability of artificial neural network (ANN) techniques to improve the diagnostic precision. MS patients and controls were enrolled (n = 217). OCT was used to determine the 768 retinal nerve fiber layer thicknesses. Sensitivity and specificity were evaluated to test the ability of OCT to discriminate between MS and healthy eyes, and between MS with and without antecedent ON using ANN. Using ANN technique multilayer perceptrons, OCT could detect MS with a sensitivity of 89.3%, a specificity of 87.6%, and a diagnostic precision of 88.5%. Compared with the OCT-provided parameters, the ANN had a better sensitivity-specificity balance. ANN technique improves the capability of Spectralis OCT to detect MS disease and to distinguish MS eyes with or without antecedent ON.

  12. Building Shadow Detection from Ghost Imagery

    Science.gov (United States)

    Zhou, G.; Sha, J.; Yue, T.; Wang, Q.; Liu, X.; Huang, S.; Pan, Q.; Wei, J.

    2018-05-01

    Shadow is one of the basic features of remote sensing image, it expresses a lot of information of the object which is loss or interference, and the removal of shadow is always a difficult problem to remote sensing image processing. In this paper, it is mainly analyzes the characteristics and properties of shadows from the ghost image (traditional orthorectification). The DBM and the interior and exterior orientation elements of the image are used to calculate the zenith angle of sun. Then this paper combines the scope of the architectural shadows which has be determined by the zenith angle of sun with the region growing method to make the detection of architectural shadow areas. This method lays a solid foundation for the shadow of the repair from the ghost image later. It will greatly improve the accuracy of shadow detection from buildings and make it more conducive to solve the problem of urban large-scale aerial imagines.

  13. BUILDING SHADOW DETECTION FROM GHOST IMAGERY

    Directory of Open Access Journals (Sweden)

    G. Zhou

    2018-05-01

    Full Text Available Shadow is one of the basic features of remote sensing image, it expresses a lot of information of the object which is loss or interference, and the removal of shadow is always a difficult problem to remote sensing image processing. In this paper, it is mainly analyzes the characteristics and properties of shadows from the ghost image (traditional orthorectification. The DBM and the interior and exterior orientation elements of the image are used to calculate the zenith angle of sun. Then this paper combines the scope of the architectural shadows which has be determined by the zenith angle of sun with the region growing method to make the detection of architectural shadow areas. This method lays a solid foundation for the shadow of the repair from the ghost image later. It will greatly improve the accuracy of shadow detection from buildings and make it more conducive to solve the problem of urban large-scale aerial imagines.

  14. A Review on Fatigue Driving Detection

    Directory of Open Access Journals (Sweden)

    Shi Sheng-Yang

    2017-01-01

    Full Text Available The socialization of automobile development has brought great convenience to people’s travel. However, the rapid increase in the number of vehicles has also caused a series of problems. The increase in traffic accidents has brought great social casualties and economic losses. Fatigue driving, which is an important factor in the traffic accident, has aroused people’s attention. This paper reviews all kinds of fatigue driving detection methods at present; compares various fatigue driving detection methods in terms of accuracy, real-time and cost; analyses the advantages and disadvantages of various methods; introduces the application of fatigue detection system in automobile; summarizes the current deficiencies and future development trends in the field of fatigue driving detection. The future research of this field will be more to the data fusion, computer vision and deep learning.

  15. Hyperspectral Imagery Target Detection Using Improved Anomaly Detection and Signature Matching Methods

    National Research Council Canada - National Science Library

    Smetek, Timothy E

    2007-01-01

    This research extends the field of hyperspectral target detection by developing autonomous anomaly detection and signature matching methodologies that reduce false alarms relative to existing benchmark detectors...

  16. CSI Frequency Domain Fingerprint-Based Passive Indoor Human Detection

    Directory of Open Access Journals (Sweden)

    Chong Han

    2018-04-01

    Full Text Available Passive indoor personnel detection technology is now a hot topic. Existing methods have been greatly influenced by environmental changes, and there are problems with the accuracy and robustness of detection. Passive personnel detection based on Wi-Fi not only solves the above problems, but also has the advantages of being low cost and easy to implement, and can be better applied to elderly care and safety monitoring. In this paper, we propose a passive indoor personnel detection method based on Wi-Fi, which we call FDF-PIHD (Frequency Domain Fingerprint-based Passive Indoor Human Detection. Through this method, fine-grained physical layer Channel State Information (CSI can be extracted to generate feature fingerprints so as to help determine the state in the scene by matching online fingerprints with offline fingerprints. In order to improve accuracy, we combine the detection results of three receiving antennas to obtain the final test result. The experimental results show that the detection rates of our proposed scheme all reach above 90%, no matter whether the scene is human-free, stationary or a moving human presence. In addition, it can not only detect whether there is a target indoors, but also determine the current state of the target.

  17. Isolation and characterization of microsatellite markers from the great hornbill, Buceros bicornis.

    Science.gov (United States)

    Chamutpong, Siriphatr; Saito, Daichi S; Viseshakul, Nareerat; Nishiumi, Isao; Poonswad, Pilai; Ponglikitmongkol, Mathurose

    2009-03-01

    Thirteen polymorphic microsatellite markers were isolated and characterized from the great hornbill, Buceros bicornis. In analyses of 20 individuals, the numbers of alleles per locus varied from two to 11. The expected and observed heterozygosities ranged from 0.22 to 0.88 and from 0.20 to 1.00, respectively. The mean polymorphic information content was 0.62. Among these, three loci deviated from the Hardy-Weinberg equilibrium. However, no significant genotypic disequilibrium was detected between any pair of loci. These microsatellite markers are useful for the population genetic study of the great hornbill. © 2009 The Authors. Journal compilation © 2009 Blackwell Publishing Ltd.

  18. Electrochemical detection of nitrite based on the polythionine/carbon nanotube modified electrode

    International Nuclear Information System (INIS)

    Deng, Chunyan; Chen, Jinzhuo; Nie, Zhou; Yang, Minghui; Si, Shihui

    2012-01-01

    In this paper, thionine was electro-polymerized onto the surface of carbon nanotube (CNT)-modified glassy carbon (GC) to fabricate the polythionine (PTH)/CNT/GC electrode. It was found that the electro-reduction current of nitrite was enhanced greatly at the PTH/CNT/GC electrode. It may be demonstrated that PTH was used as a mediator for electrocatalytic reduction of nitrite, and CNTs as an excellent nanomaterial can improve the electron transfer between the electrode and nitrite. Therefore, based on the synergic effect of PTH and CNTs, the PTH/CNT/GC electrode was employed to detect nitrite, and the high sensitivity of 5.81 μA mM −1 , and the detection limit of 1.4 × 10 −6 M were obtained. Besides, the modified electrode showed an inherent stability, fast response time, and good anti-interference ability. These suggested that the PTH/CNT/GC electrode was favorable and reliable for the detection of nitrite. - Highlights: ► Polythionine (PTH) was used as a mediator for electrocatalytic reduction of nitrite. ► Carbon nanotubes (CNTs) improve electron transfer between the electrode and nitrite. ► The PTH/CNT/glassy carbon electrode showed excellent nitrite detection performance.

  19. Deterministic Approach to Detect Heart Sound Irregularities

    Directory of Open Access Journals (Sweden)

    Richard Mengko

    2017-07-01

    Full Text Available A new method to detect heart sound that does not require machine learning is proposed. The heart sound is a time series event which is generated by the heart mechanical system. From the analysis of heart sound S-transform and the understanding of how heart works, it can be deducted that each heart sound component has unique properties in terms of timing, frequency, and amplitude. Based on these facts, a deterministic method can be designed to identify each heart sound components. The recorded heart sound then can be printed with each component correctly labeled. This greatly help the physician to diagnose the heart problem. The result shows that most known heart sounds were successfully detected. There are some murmur cases where the detection failed. This can be improved by adding more heuristics including setting some initial parameters such as noise threshold accurately, taking into account the recording equipment and also the environmental condition. It is expected that this method can be integrated into an electronic stethoscope biomedical system.

  20. Nickel-base alloy overlay weld with improved ultrasonic flaw detection by magnetic stirring welding

    International Nuclear Information System (INIS)

    Takashi, Hirano; Kenji, Hirano; Masayuki, Watando; Takahiro, Arakawa; Minoru, Maeda

    2001-01-01

    Ultrasonic flaw detection is more difficult in Nickel-base alloy welds containing dendrites owing to the decrease ultrasonic transmissibility they cause. The present paper discusses application of magnetic stirring welding as a means for reducing dendrite growth with consequent improvement in ultrasonic transmissibility. Single pass and multi-pass welding tests were conducted to determine optimal welding conditions. By PT and macro observation subsequent to welding was carried out, optimal operation conditions were clarified. Overlay welding tests and UT clearly indicated ultrasonic beam transmissibility in overlay welds to be improved and detection capacity to be greater through application of magnetic stirring welding. Optimal operation conditions were determined based on examination of temper bead effects in the heat affected zone of low alloy steel by application of magnetic stirring welding to the butt welded joints between low alloy and stainless steel. Hardness in this zone of low alloy steel after the fourth layer was less than 350 HV. (author)

  1. An Improved Fruit Fly Optimization Algorithm and Its Application in Heat Exchange Fouling Ultrasonic Detection

    Directory of Open Access Journals (Sweden)

    Xia Li

    2018-01-01

    Full Text Available Inspired by the basic theory of Fruit Fly Optimization Algorithm, in this paper, cat mapping was added to the original algorithm, and the individual distribution and evolution mechanism of fruit fly population were improved in order to increase the search speed and accuracy. The flowchart of the improved algorithm was drawn to show its procedure. Using classical test functions, simulation optimization results show that the improved algorithm has faster and more reliable optimization ability. The algorithm was then combined with sparse decomposition theory and used in processing fouling detection ultrasonic signals to verify the validity and practicability of the improved algorithm.

  2. Foundations for Improvements to Passive Detection Systems - Final Report

    International Nuclear Information System (INIS)

    Labov, S E; Pleasance, L; Sokkappa, P; Craig, W; Chapline, G; Frank, M; Gronberg, J; Jernigan, J G; Johnson, S; Kammeraad, J; Lange, D; Meyer, A; Nelson, K; Pohl, B; Wright, D; Wurtz, R

    2004-01-01

    This project explores the scientific foundation and approach for improving passive detection systems for plutonium and highly enriched uranium in real applications. Sources of gamma-ray radiation of interest were chosen to represent a range of national security threats, naturally occurring radioactive materials, industrial and medical radiation sources, and natural background radiation. The gamma-ray flux emerging from these sources, which include unclassified criticality experiment configurations as surrogates for nuclear weapons, were modeled in detail. The performance of several types of gamma-ray imaging systems using Compton scattering were modeled and compared. A mechanism was created to model the combine sources and background emissions and have the simulated radiation ''scene'' impinge on a model of a detector. These modeling tools are now being used in various projects to optimize detector performance and model detector sensitivity in complex measuring environments. This study also developed several automated algorithms for isotope identification from gamma-ray spectra and compared these to each other and to algorithms already in use. Verification testing indicates that these alternative isotope identification algorithms produced less false positive and false negative results than the ''GADRAS'' algorithms currently in use. In addition to these algorithms that used binned spectra, a new approach to isotope identification using ''event mode'' analysis was developed. Finally, a technique using muons to detect nuclear material was explored

  3. Potential for DNA-based ID of Great Lakes fauna: Species inventories vs. barcode libraries

    Science.gov (United States)

    DNA-based identification of mixed-organism samples offers the potential to greatly reduce the need for resource-intensive morphological identification, which would be of value both to biotic condition assessment and non-native species early-detection monitoring. However the abil...

  4. Improved Bi film wrapped single walled carbon nanotubes for ultrasensitive electrochemical detection of trace Cr(VI)

    International Nuclear Information System (INIS)

    Ouyang, Ruizhuo; Zhang, Wangyao; Zhou, Shilin; Xue, Zi-Ling; Xu, Lina; Gu, Yingying; Miao, Yuqing

    2013-01-01

    Highlights: • Electrostatic interaction improves the quality of Bi deposition. • The designed Bi/SWNTs/GCE shows many advantages over Bi/GCE toward Cr VI detection. • The Bi/SWNTs/GCE exhibits good analyzing behavior with pretty low detection limit. • The fabricated sensor is better of reproducibility, repeatability and life time. • River samples were successfully analyzed using current sensor for Cr VI detection. -- Abstract: We report here the successful fabrication of an improved Bi film wrapped single walled carbon nanotubes modified glassy carbon electrode (Bi/SWNTs/GCE) as a highly sensitive platform for ultratrace Cr(VI) detection through catalytic adsorptive cathodic stripping voltammetry (AdCSV). The introduction of negatively charged SWNTs extraordinarily decreased the size of Bi particles to nanoscale due to electrostatic interaction which made Bi(III) cations easily attracted onto the surface of SWNTs in good order, leading to higher quality of Bi film deposition. The obtained Bi/SWNTs composite was well characterized with electrochemical impedance spectroscopy (EIS), scanning electron microscopy (SEM), the static water contact angle and the voltammetric measurements. The results demonstrate the improvements in the quality of Bi film deposited on the surface of SWNTs such as faster speed of electron transfer, more uniform and smoother morphology, better hydrophilicity and higher stripping signal. Using diethylene triaminepentaacetic acid (DTPA) as complexing ligand, the fabricated electrode displays a well-defined and highly sensitive peak for the reduction of Cr(III)–DTPA complex at −1.06 V (vs. Ag/AgCl) with a linear concentration range of 0–25 nM and a fairly low detection limit of 0.036 nM. No interference was found in the presence of coexisting ions, and good recoveries were achieved for the analysis of a river sample. In comparison to previous approaches using Bi film modified GCE, the newly designed electrode exhibits better

  5. Sensitive and label-free detection of miRNA-145 by triplex formation.

    Science.gov (United States)

    Aviñó, Anna; Huertas, César S; Lechuga, Laura M; Eritja, Ramon

    2016-01-01

    The development of new strategies for detecting microRNAs (miRNAs) has become a crucial step in the diagnostic field. miRNA profiles depend greatly on the sample and the analytical platform employed, leading sometimes to contradictory results. In this work, we study the use of modified parallel tail-clamps to detect a miRNA sequence involved in tumor suppression by triplex formation. Thermal denaturing curves and circular dichroism (CD) measurements have been performed to confirm that parallel clamps carrying 8-aminoguanine form the most stable triplex structures with their target miRNA. The modified tail-clamps have been tested as bioreceptors in a surface plasmon resonance (SPR) biosensor for the detection of miRNA-145. The detection limit was improved 2.4 times demonstrating that a stable triplex structure is formed between target miRNA and 8-aminoguanine tail-clamp bioreceptor. This new approach is an essential step toward the label-free and reliable detection of miRNA signatures for diagnostic purposes.

  6. Hybrid Video Stabilization for Mobile Vehicle Detection on SURF in Aerial Surveillance

    Directory of Open Access Journals (Sweden)

    Gao Chunxian

    2015-01-01

    Full Text Available Detection of moving vehicles in aerial video sequences is of great importance with many promising applications in surveillance, intelligence transportation, or public service applications such as emergency evacuation and policy security. However, vehicle detection is a challenging task due to global camera motion, low resolution of vehicles, and low contrast between vehicles and background. In this paper, we present a hybrid method to efficiently detect moving vehicle in aerial videos. Firstly, local feature extraction and matching were performed to estimate the global motion. It was demonstrated that the Speeded Up Robust Feature (SURF key points were more suitable for the stabilization task. Then, a list of dynamic pixels was obtained and grouped for different moving vehicles by comparing the different optical flow normal. To enhance the precision of detection, some preprocessing methods were applied to the surveillance system, such as road extraction and other features. A quantitative evaluation on real video sequences indicated that the proposed method improved the detection performance significantly.

  7. Improved target detection and bearing estimation utilizing fast orthogonal search for real-time spectral analysis

    International Nuclear Information System (INIS)

    Osman, Abdalla; El-Sheimy, Naser; Nourledin, Aboelamgd; Theriault, Jim; Campbell, Scott

    2009-01-01

    The problem of target detection and tracking in the ocean environment has attracted considerable attention due to its importance in military and civilian applications. Sonobuoys are one of the capable passive sonar systems used in underwater target detection. Target detection and bearing estimation are mainly obtained through spectral analysis of received signals. The frequency resolution introduced by current techniques is limited which affects the accuracy of target detection and bearing estimation at a relatively low signal-to-noise ratio (SNR). This research investigates the development of a bearing estimation method using fast orthogonal search (FOS) for enhanced spectral estimation. FOS is employed in this research in order to improve both target detection and bearing estimation in the case of low SNR inputs. The proposed methods were tested using simulated data developed for two different scenarios under different underwater environmental conditions. The results show that the proposed method is capable of enhancing the accuracy for target detection as well as bearing estimation especially in cases of a very low SNR

  8. Detection of hepatocarcinoma in rats by integration of the fluorescence spectrum: Experimental model

    Science.gov (United States)

    Marcassa, J. C.; Ferreira, J.; Zucoloto, S.; Castro E Silva, O., Jr.; Marcassa, L. G.; Bagnato, V. S.

    2006-05-01

    The incorporation of spectroscopic techniques into diagnostic procedures may greatly improve the chances for precise diagnostics. One promising technique is fluorescence spectroscopy, which has recently been used to detect many different types of diseases. In this work, we use laser-induced tissue fluorescence to detect hepatocarcinoma in rats using excitation light at wavelengths of 443 and 532 nm. Hepatocarcinoma was induced chemically in Wistar rats. The collected fluorescence spectrum ranges from the excitation wavelength up to 850 nm. A mathematical procedure carried out on the spectrum determines a figure of merit value, which allows the detection of hepatocarcinoma. The figure of merit involves a procedure which evaluates the ratio between the backscattered excitation wavelength and the broad emission fluorescence band. We demonstrate that a normalization allowed by integration of the fluorescence spectra is a simple operation that may allow the detection of hepatocarcinoma.

  9. Improvement of the Xpert Carba-R Kit for the Detection of Carbapenemase-Producing Enterobacteriaceae.

    Science.gov (United States)

    Dortet, Laurent; Fusaro, Mathieu; Naas, Thierry

    2016-06-01

    The Xpert Carba-R kit, version 2 (v2), which has been improved for the efficient detection of blaOXA-181 and blaOXA-232 genes, was tested on a collection of 150 well-characterized enterobacterial isolates that had a reduced susceptibility to carbapenems. The performance of the Xpert Carba-R v2 was high, as it was able to detect the five major carbapenemases (NDM, VIM, IMP, KPC, and OXA-48). Thus, it is now well adapted to the carbapenemase-producing Enterobacteriaceae epidemiology of many countries worldwide. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

  10. Improvement of Detection of Hypoattenuation in Acute Ischemic Stroke in Unenhanced Computed Tomography Using an Adaptive Smoothing Filter

    International Nuclear Information System (INIS)

    Takahashi, N.; Lee, Y.; Tsai, D. Y.; Ishii, K.; Kinoshita, T.; Tamura, H.; K imura, M.

    2008-01-01

    Background: Much attention has been directed toward identifying early signs of cerebral ischemia on computed tomography (CT) images. Hypoattenuation of ischemic brain parenchyma has been found to be the most frequent early sign. Purpose: To evaluate the effect of a previously proposed adaptive smoothing filter for improving detection of parenchymal hypoattenuation of acute ischemic stroke on unenhanced CT images. Material and Methods: Twenty-six patients with parenchymal hypoattenuation and 49 control subjects without hypoattenuation were retrospectively selected in this study. The adaptive partial median filter (APMF) designed for improving detectability of hypoattenuation areas on unenhanced CT images was applied. Seven radiologists, including four certified radiologists and three radiology residents, indicated their confidence level regarding the presence (or absence) of hypoattenuation on CT images, first without and then with the APMF processed images. Their performances without and with the APMF processed images were evaluated by receiver operating characteristic (ROC) analysis. Results: The mean areas under the ROC curves (AUC) for all observers increased from 0.875 to 0.929 (P=0.002) when the radiologists observed with the APMF processed images. The mean sensitivity in the detection of hypoattenuation significantly improved, from 69% (126 of 182 observations) to 89% (151 of 182 observations), when employing the APMF (P=0.012). The specificity, however, was unaffected by the APMF (P=0.41). Conclusion: The APMF has the potential to improve the detection of parenchymal hypoattenuation of acute ischemic stroke on unenhanced CT images

  11. Single-nanoparticle detection with slot-mode photonic crystal cavities

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Cheng; Kita, Shota; Lončar, Marko, E-mail: loncar@seas.harvard.edu [School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138 (United States); Quan, Qimin [Rowland Institute at Harvard University, Cambridge, Massachusetts 02142 (United States); Li, Yihang [School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138 (United States); Department of Electronic Engineering, Tsinghua University, Beijing 100084 (China)

    2015-06-29

    Optical cavities that are capable for detecting single nanoparticles could lead to great progress in early stage disease diagnostics and the study of biological interactions on the single-molecule level. In particular, photonic crystal (PhC) cavities are excellent platforms for label-free single-nanoparticle detection, owing to their high quality (Q) factors and wavelength-scale modal volumes. Here, we demonstrate the design and fabrication of a high-Q (>10{sup 4}) slot-mode PhC nanobeam cavity, which is able to strongly confine light in the slotted regions. The enhanced light-matter interaction results in an order of magnitude improvement in both refractive index sensitivity (439 nm/RIU) and single-nanoparticle sensitivity compared with conventional dielectric-mode PhC cavities. Detection of single polystyrene nanoparticles with radii of 20 nm and 30 nm is demonstrated in aqueous environments (D{sub 2}O), without additional laser and temperature stabilization techniques.

  12. Fluorescence detection using optical waveguide collection device with high efficiency on assembly of nitrogen vacancy centers in diamond

    Science.gov (United States)

    Zhang, Shaowen; Ma, Zongmin; Qin, Li; Fu, Yueping; Shi, Yunbo; Liu, Jun; Li, Yan Jun

    2018-01-01

    In this letter, we propose a fluorescence waveguide excitation and collection (FWEC) method that allows for an excess of 45% collection efficiency of pump photons into optically detected magnetic resonance. The FWEC system used can collect fluorescence 96 times higher than the confocal system under spin manipulation with a microwave. Furthermore, the signal-to-noise ratio (SNR) of the FWEC system is improved 9 times compared with that of the confocal system. In addition, the increase in contrast observed using the FWEC system shows that the integration of the system is much improved with 3D printing technology. Thus, this research has a great potential application in subsequent magnetic detection and quantum optics.

  13. Great Lakes Science Center

    Data.gov (United States)

    Federal Laboratory Consortium — Since 1927, Great Lakes Science Center (GLSC) research has provided critical information for the sound management of Great Lakes fish populations and other important...

  14. Improvement of retinal blood vessel detection using morphological component analysis.

    Science.gov (United States)

    Imani, Elaheh; Javidi, Malihe; Pourreza, Hamid-Reza

    2015-03-01

    Detection and quantitative measurement of variations in the retinal blood vessels can help diagnose several diseases including diabetic retinopathy. Intrinsic characteristics of abnormal retinal images make blood vessel detection difficult. The major problem with traditional vessel segmentation algorithms is producing false positive vessels in the presence of diabetic retinopathy lesions. To overcome this problem, a novel scheme for extracting retinal blood vessels based on morphological component analysis (MCA) algorithm is presented in this paper. MCA was developed based on sparse representation of signals. This algorithm assumes that each signal is a linear combination of several morphologically distinct components. In the proposed method, the MCA algorithm with appropriate transforms is adopted to separate vessels and lesions from each other. Afterwards, the Morlet Wavelet Transform is applied to enhance the retinal vessels. The final vessel map is obtained by adaptive thresholding. The performance of the proposed method is measured on the publicly available DRIVE and STARE datasets and compared with several state-of-the-art methods. An accuracy of 0.9523 and 0.9590 has been respectively achieved on the DRIVE and STARE datasets, which are not only greater than most methods, but are also superior to the second human observer's performance. The results show that the proposed method can achieve improved detection in abnormal retinal images and decrease false positive vessels in pathological regions compared to other methods. Also, the robustness of the method in the presence of noise is shown via experimental result. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  15. Divide and Conquer: Sub-Grouping of ASD Improves ASD Detection Based on Brain Morphometry

    Science.gov (United States)

    Baum, Stefi A.; Cahill, Nathan D.; Michael, Andrew M.

    2016-01-01

    Low success (ASD) classification using brain morphometry from the large multi-site ABIDE dataset and inconsistent findings on brain morphometric abnormalities in ASD can be attributed to the ASD heterogeneity. In this study, we show that ASD brain morphometry is highly heterogeneous, and demonstrate that the heterogeneity can be mitigated and classification improved if autism severity (AS), verbal IQ (VIQ) and age are used with morphometric features. Morphometric features from structural MRIs (sMRIs) of 734 males (ASD: 361, controls: 373) of ABIDE were derived using FreeSurfer. Applying the Random Forest classifier, an AUC of 0.61 was achieved. Adding VIQ and age to morphometric features, AUC improved to 0.68. Sub-grouping the subjects by AS, VIQ and age improved the classification with the highest AUC of 0.8 in the moderate-AS sub-group (AS = 7–8). Matching subjects on age and/or VIQ in each sub-group further improved the classification with the highest AUC of 0.92 in the low AS sub-group (AS = 4–5). AUC decreased with AS and VIQ, and was the lowest in the mid-age sub-group (13–18 years). The important features were mainly from the frontal, temporal, ventricular, right hippocampal and left amygdala regions. However, they highly varied with AS, VIQ and age. The curvature and folding index features from frontal, temporal, lingual and insular regions were dominant in younger subjects suggesting their importance for early detection. When the experiments were repeated using the Gradient Boosting classifier similar results were obtained. Our findings suggest that identifying brain biomarkers in sub-groups of ASD can yield more robust and insightful results than searching across the whole spectrum. Further, it may allow identification of sub-group specific brain biomarkers that are optimized for early detection and monitoring, increasing the utility of sMRI as an important tool for early detection of ASD. PMID:27065101

  16. Development of techniques using DNA analysis method for detection/analysis of radiation-induced mutation. Development of an useful probe/primer and improvement of detection efficacy

    International Nuclear Information System (INIS)

    Maekawa, Hideaki; Tsuchida, Kozo; Hashido, Kazuo; Takada, Naoko; Kameoka, Yosuke; Hirata, Makoto

    1999-01-01

    Previously, it was demonstrated that detection of centromere became easy and reliable through fluorescent staining by FISH method using a probe of the sequence preserved in α-satelite DNA. Since it was, however, found inappropriate to detect dicentrics based on the relative amount of DNA probe on each chromosome. A prove which allows homogeneous detection of α-satelite DNA for each chromosome was constructed. A presumed sequence specific to kinetochore, CENP-B box was amplified by PCR method and the product DNA was used as a probe. However, the variation in amounts of probe DNA among chromosomes was decreased by only about 20%. Then, a program for image processing of the results obtained from FISH using α-satelite DNA was constructed to use as a marker for centromere. When compared with detection of abnormal chromosomes stained by the conventional method, calculation efficacy for only detection of centromere was improved by the use of this program. Calculation to discriminate the normal or not was still complicated and the detection efficacy was little improved. Chromosomal abnormalities in lymphocytes were used to detect the effects of radiation. In this method, it is needed to shift the phase of cells into metaphase. The mutation induced by radiation might be often repaired during shifting. To exclude this possibility, DNA extraction was conducted at a low temperature and immediately after exposure to 137 Cs, and a rapid genome detection method was established using the genome DNA. As the model genomes, the following three were used: 1) long chain repeated sequences widely dispersed over chromosome, 2) cluster genes, 3) single copy genes. The effects of radiation were detectable at 1-2 Gy for the long repeated sequences and at 7 Gy for the cluster genes, respectively, whereas no significant effects were observed at any Gy tested for the single copy genes. Amplification was marked in the cells exposed at 1-10 Gy (peak at 4 Gy), suggesting that these regions had

  17. Chemical vapor detection using a capacitive micromachined ultrasonic transducer.

    Science.gov (United States)

    Lee, Hyunjoo J; Park, Kwan Kyu; Kupnik, Mario; Oralkan, O; Khuri-Yakub, Butrus T

    2011-12-15

    Distributed sensing of gas-phase chemicals using highly sensitive and inexpensive sensors is of great interest for many defense and consumer applications. In this paper we present ppb-level detection of dimethyl methylphosphonate (DMMP), a common simulant for sarin gas, with a ppt-level resolution using an improved capacitive micromachined ultrasonic transducer (CMUT) as a resonant chemical sensor. The improved CMUT operates at a higher resonant frequency of 47.7 MHz and offers an improved mass sensitivity of 48.8 zg/Hz/μm(2) by a factor of 2.7 compared to the previous CMUT sensors developed. A low-noise oscillator using the CMUT resonant sensor as the frequency-selective device was developed for real-time sensing, which exhibits an Allan deviation of 1.65 Hz (3σ) in the presence of a gas flow; this translates into a mass resolution of 80.5 zg/μm(2). The CMUT resonant sensor is functionalized with a 50-nm thick DKAP polymer developed at Sandia National Laboratory for dimethyl methylphosphonate (DMMP) detection. To demonstrate ppb-level detection of the improved chemical sensor system, the sensor performance was tested at a certified lab (MIT Lincoln Laboratory), which is equipped with an experimental chemical setup that reliably and accurately delivers a wide range of low concentrations down to 10 ppb. We report a high volume sensitivity of 34.5 ± 0.79 pptv/Hz to DMMP and a good selectivity of the polymer to DMMP with respect to dodecane and 1-octanol.

  18. Computer-aided detection of pulmonary embolism at CT pulmonary angiography: can it improve performance of inexperienced readers?

    International Nuclear Information System (INIS)

    Blackmon, Kevin N.; McCain, Joshua W.; Koonce, James D.; Costello, Philip; Florin, Charles; Bogoni, Luca; Salganicoff, Marcos; Lee, Heon; Bastarrika, Gorka; Thilo, Christian; Joseph Schoepf, U.

    2011-01-01

    To evaluate the effect of a computer-aided detection (CAD) algorithm on the performance of novice readers for detection of pulmonary embolism (PE) at CT pulmonary angiography (CTPA). We included CTPA examinations of 79 patients (50 female, 52 ± 18 years). Studies were evaluated by two independent inexperienced readers who marked all vessels containing PE. After 3 months all studies were reevaluated by the same two readers, this time aided by CAD prototype. A consensus read by three expert radiologists served as the reference standard. Statistical analysis used χ 2 and McNemar testing. Expert consensus revealed 119 PEs in 32 studies. For PE detection, the sensitivity of CAD alone was 78%. Inexperienced readers' initial interpretations had an average per-PE sensitivity of 50%, which improved to 71% (p < 0.001) with CAD as a second reader. False positives increased from 0.18 to 0.25 per study (p = 0.03). Per-study, the readers initially detected 27/32 positive studies (84%); with CAD this number increased to 29.5 studies (92%; p = 0.125). Our results suggest that CAD significantly improves the sensitivity of PE detection for inexperienced readers with a small but appreciable increase in the rate of false positives. (orig.)

  19. Computer-aided detection of pulmonary embolism at CT pulmonary angiography: can it improve performance of inexperienced readers?

    Energy Technology Data Exchange (ETDEWEB)

    Blackmon, Kevin N.; McCain, Joshua W.; Koonce, James D.; Costello, Philip [Medical University of South Carolina, Department of Radiology and Radiological Science, Charleston, SC (United States); Florin, Charles; Bogoni, Luca; Salganicoff, Marcos [Siemens AG, H IM SYNGO CAD Research and Development, Malvern, PA (United States); Lee, Heon [Medical University of South Carolina, Department of Radiology and Radiological Science, Charleston, SC (United States); Seoul Medical Center, Department of Radiology, Seoul (Korea, Republic of); Bastarrika, Gorka [Medical University of South Carolina, Department of Radiology and Radiological Science, Charleston, SC (United States); University of Navarra, Department of Radiology, Pamplona (Spain); Thilo, Christian; Joseph Schoepf, U. [Medical University of South Carolina, Department of Radiology and Radiological Science, Charleston, SC (United States); Medical University of South Carolina, Division of Cardiology, Department of Medicine, Charleston, SC (United States)

    2011-06-15

    To evaluate the effect of a computer-aided detection (CAD) algorithm on the performance of novice readers for detection of pulmonary embolism (PE) at CT pulmonary angiography (CTPA). We included CTPA examinations of 79 patients (50 female, 52 {+-} 18 years). Studies were evaluated by two independent inexperienced readers who marked all vessels containing PE. After 3 months all studies were reevaluated by the same two readers, this time aided by CAD prototype. A consensus read by three expert radiologists served as the reference standard. Statistical analysis used {chi}{sup 2} and McNemar testing. Expert consensus revealed 119 PEs in 32 studies. For PE detection, the sensitivity of CAD alone was 78%. Inexperienced readers' initial interpretations had an average per-PE sensitivity of 50%, which improved to 71% (p < 0.001) with CAD as a second reader. False positives increased from 0.18 to 0.25 per study (p = 0.03). Per-study, the readers initially detected 27/32 positive studies (84%); with CAD this number increased to 29.5 studies (92%; p = 0.125). Our results suggest that CAD significantly improves the sensitivity of PE detection for inexperienced readers with a small but appreciable increase in the rate of false positives. (orig.)

  20. Performance improvements on passive activated charcoal 222Rn samplers

    International Nuclear Information System (INIS)

    Wei Suxia

    1996-01-01

    Improvements have been made on passive activated charcoal 222 Rn samplers with sintered metal filters. Based on the samplers of good adaptability to temperature and humidity developed before, better charcoal was selected to further improve their performance in radon absorption ability and moisture-resistance. And charcoal quantity in samplers was strictly controlled. The integration time constant of the improved samplers was about 4.3 days. As the sampler was combined with gamma spectrometer to measure radon concentration, the calibration factor was 0.518 min -1 ·Bq -1 ·m 3 for samplers of 7 days exposure time, and the minimum detectable concentration 0.28 Bq·m -3 if counting time for both background and sample is 1000 minutes. The improved samplers are suited to accurately determine the indoor and outdoor average radon concentration under conditions of great variation in temperature and humidity

  1. Item Purification Does Not Always Improve DIF Detection: A Counterexample with Angoff's Delta Plot

    Science.gov (United States)

    Magis, David; Facon, Bruno

    2013-01-01

    Item purification is an iterative process that is often advocated as improving the identification of items affected by differential item functioning (DIF). With test-score-based DIF detection methods, item purification iteratively removes the items currently flagged as DIF from the test scores to get purified sets of items, unaffected by DIF. The…

  2. Improving detection sensitivity for partial discharge monitoring of high voltage equipment

    Science.gov (United States)

    Hao, L.; Lewin, P. L.; Swingler, S. G.

    2008-05-01

    Partial discharge (PD) measurements are an important technique for assessing the health of power apparatus. Previous published research by the authors has shown that an electro-optic system can be used for PD measurement of oil-filled power transformers. A PD signal generated within an oil-filled power transformer may reach a winding and then travel along the winding to the bushing core bar. The bushing, acting like a capacitor, can transfer the high frequency components of the partial discharge signal to its earthed tap point. Therefore, an effective PD current measurement can be implemented at the bushing tap by using a radio frequency current transducer around the bushing-tap earth connection. In addition, the use of an optical transmission technique not only improves the electrical noise immunity and provides the possibility of remote measurement but also realizes electrical isolation and enhances safety for operators. However, the bushing core bar can act as an aerial and in addition noise induced by the electro-optic modulation system may influence overall measurement sensitivity. This paper reports on a machine learning technique, namely the use of a support vector machine (SVM), to improve the detection sensitivity of the system. Comparison between the signal extraction performances of a passive hardware filter and the SVM technique has been assessed. The results obtained from the laboratory-based experiment have been analysed and indicate that the SVM approach provides better performance than the passive hardware filter and it can reliably detect discharge signals with apparent charge greater than 30 pC.

  3. Improving detection sensitivity for partial discharge monitoring of high voltage equipment

    International Nuclear Information System (INIS)

    Hao, L; Lewin, P L; Swingler, S G

    2008-01-01

    Partial discharge (PD) measurements are an important technique for assessing the health of power apparatus. Previous published research by the authors has shown that an electro-optic system can be used for PD measurement of oil-filled power transformers. A PD signal generated within an oil-filled power transformer may reach a winding and then travel along the winding to the bushing core bar. The bushing, acting like a capacitor, can transfer the high frequency components of the partial discharge signal to its earthed tap point. Therefore, an effective PD current measurement can be implemented at the bushing tap by using a radio frequency current transducer around the bushing-tap earth connection. In addition, the use of an optical transmission technique not only improves the electrical noise immunity and provides the possibility of remote measurement but also realizes electrical isolation and enhances safety for operators. However, the bushing core bar can act as an aerial and in addition noise induced by the electro-optic modulation system may influence overall measurement sensitivity. This paper reports on a machine learning technique, namely the use of a support vector machine (SVM), to improve the detection sensitivity of the system. Comparison between the signal extraction performances of a passive hardware filter and the SVM technique has been assessed. The results obtained from the laboratory-based experiment have been analysed and indicate that the SVM approach provides better performance than the passive hardware filter and it can reliably detect discharge signals with apparent charge greater than 30 pC

  4. Resolution improvement of low frequency AC magnetic field detection for modulated MR sensors.

    Science.gov (United States)

    Hu, Jinghua; Pan, Mengchun; Hu, Jiafei; Li, Sizhong; Chen, Dixiang; Tian, Wugang; Sun, Kun; Du, Qingfa; Wang, Yuan; Pan, Long; Zhou, Weihong; Zhang, Qi; Li, Peisen; Peng, Junping; Qiu, Weicheng; Zhou, Jikun

    2017-09-01

    Magnetic modulation methods especially Micro-Electro-Mechanical System (MEMS) modulation can improve the sensitivity of magnetoresistive (MR) sensors dramatically, and pT level detection of Direct Current (DC) magnetic field can be realized. While in a Low Frequency Alternate Current (LFAC) magnetic field measurement situation, frequency measurement is limited by a serious spectrum aliasing problem caused by the remanence in sensors and geomagnetic field, leading to target information loss because frequency indicates the magnetic target characteristics. In this paper, a compensation field produced with integrated coils is applied to the MR sensor to remove DC magnetic field distortion, and a LFAC magnetic field frequency estimation algorithm is proposed based on a search of the database, which is derived from the numerical model revealing the relationship of the LFAC frequency and determination factor [defined by the ratio of Discrete Fourier Transform (DFT) coefficients]. In this algorithm, an inverse modulation of sensor signals is performed to detect jumping-off point of LFAC in the time domain; this step is exploited to determine sampling points to be processed. A determination factor is calculated and taken into database to figure out frequency with a binary search algorithm. Experimental results demonstrate that the frequency measurement resolution of the LFAC magnetic field is improved from 12.2 Hz to 0.8 Hz by the presented method, which, within the signal band of a magnetic anomaly (0.04-2 Hz), indicates that the proposed method may expand the applications of magnetoresistive (MR) sensors to human healthcare and magnetic anomaly detection (MAD).

  5. Improved people detection in nuclear plants by video processing for safety purpose

    Energy Technology Data Exchange (ETDEWEB)

    Jorge, Carlos Alexandre F.; Mol, Antonio Carlos A.; Carvalho, Paulo Victor R., E-mail: calexandre@ien.gov.br, E-mail: mol@ien.gov.br, E-mail: paulov@ien.gov.br [Instituto de Engenharia Nuclear (IEN/CNEN-RJ), Rio de Janeiro, RJ (Brazil); Seixas, Jose M.; Silva, Eduardo Antonio B., E-mail: seixas@lps.ufrj.br, E-mail: eduardo@smt.ufrj.br [Coordenacao dos Programas de Pos-Graduacao em Engenharia (COPPE/UFRJ), RJ (Brazil). Programa de Engenharia Eletrica; Waintraub, Fabio, E-mail: fabiowaintraub@hotmail.com [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil). Escola Politecnica. Departamento de Engenharia Eletronica e de Computacao

    2013-07-01

    This work describes improvements in a surveillance system for safety purposes in nuclear plants. The objective is to track people online in video, in order to estimate the dose received by personnel, during working tasks executed in nuclear plants. The estimation will be based on their tracked positions and on dose rate mapping in a nuclear research reactor, Argonauta. Cameras have been installed within Argonauta room, supplying the data needed. Video processing methods were combined for detecting and tracking people in video. More specifically, segmentation, performed by background subtraction, was combined with a tracking method based on color distribution. The use of both methods improved the overall results. An alternative approach was also evaluated, by means of blind source signal separation. Results are commented, along with perspectives. (author)

  6. Improved people detection in nuclear plants by video processing for safety purpose

    International Nuclear Information System (INIS)

    Jorge, Carlos Alexandre F.; Mol, Antonio Carlos A.; Carvalho, Paulo Victor R.; Seixas, Jose M.; Silva, Eduardo Antonio B.; Waintraub, Fabio

    2013-01-01

    This work describes improvements in a surveillance system for safety purposes in nuclear plants. The objective is to track people online in video, in order to estimate the dose received by personnel, during working tasks executed in nuclear plants. The estimation will be based on their tracked positions and on dose rate mapping in a nuclear research reactor, Argonauta. Cameras have been installed within Argonauta room, supplying the data needed. Video processing methods were combined for detecting and tracking people in video. More specifically, segmentation, performed by background subtraction, was combined with a tracking method based on color distribution. The use of both methods improved the overall results. An alternative approach was also evaluated, by means of blind source signal separation. Results are commented, along with perspectives. (author)

  7. Great Lakes

    Science.gov (United States)

    Edsall, Thomas A.; Mac, Michael J.; Opler, Paul A.; Puckett Haecker, Catherine E.; Doran, Peter D.

    1998-01-01

    The Great Lakes region, as defined here, includes the Great Lakes and their drainage basins in Minnesota, Wisconsin, Illinois, Indiana, Ohio, Pennsylvania, and New York. The region also includes the portions of Minnesota, Wisconsin, and the 21 northernmost counties of Illinois that lie in the Mississippi River drainage basin, outside the floodplain of the river. The region spans about 9º of latitude and 20º of longitude and lies roughly halfway between the equator and the North Pole in a lowland corridor that extends from the Gulf of Mexico to the Arctic Ocean.The Great Lakes are the most prominent natural feature of the region (Fig. 1). They have a combined surface area of about 245,000 square kilometers and are among the largest, deepest lakes in the world. They are the largest single aggregation of fresh water on the planet (excluding the polar ice caps) and are the only glacial feature on Earth visible from the surface of the moon (The Nature Conservancy 1994a).The Great Lakes moderate the region’s climate, which presently ranges from subarctic in the north to humid continental warm in the south (Fig. 2), reflecting the movement of major weather masses from the north and south (U.S. Department of the Interior 1970; Eichenlaub 1979). The lakes act as heat sinks in summer and heat sources in winter and are major reservoirs that help humidify much of the region. They also create local precipitation belts in areas where air masses are pushed across the lakes by prevailing winds, pick up moisture from the lake surface, and then drop that moisture over land on the other side of the lake. The mean annual frost-free period—a general measure of the growing-season length for plants and some cold-blooded animals—varies from 60 days at higher elevations in the north to 160 days in lakeshore areas in the south. The climate influences the general distribution of wild plants and animals in the region and also influences the activities and distribution of the human

  8. CVD diamond for nuclear detection applications

    CERN Document Server

    Bergonzo, P; Tromson, D; Mer, C; Guizard, B; Marshall, R D; Foulon, F

    2002-01-01

    Chemically vapour deposited (CVD) diamond is a remarkable material for the fabrication of radiation detectors. In fact, there exist several applications where other standard semiconductor detectors do not fulfil the specific requirements imposed by corrosive, hot and/or high radiation dose environments. The improvement of the electronic properties of CVD diamond has been under intensive investigations and led to the development of a few applications that are addressing specific industrial needs. Here, we report on CVD diamond-based detector developments and we describe how this material, even though of a polycrystalline nature, is readily of great interest for applications in the nuclear industry as well as for physics experiments. Improvements in the material synthesis as well as on device fabrication especially concern the synthesis of films that do not exhibit space charge build up effects which are often encountered in CVD diamond materials and that are highly detrimental for detection devices. On a pre-i...

  9. Combined detection of AM, CYFRA21-1, NSE and CEA levels in pleural effusion for differentiation of malignant from tuberculous pleural effusion

    International Nuclear Information System (INIS)

    Yu Hua; Zhu Wenru; Sun Shuhong; Xu Shuhua; Yu Hui

    2005-01-01

    The level s of four tumor markers (AM, CYFRA21-1, NSE and CEA) pleural effusion in plearal effusion were determined by RIA in 52 patients with tuberculous pleural effusion and 74 patients with malignant pleural effusion. The results showed that the levels of the four tumor markers in malignant pleural effusion were significantly higher than those in tuberculous pleural effusion. Combined detection of the four tumor markers could improve the diagnostic sensitivity and the accuracy to 90.5% and 92.9%, respectively (P<0.01). Detection of AM, CYFRA21-1, NSE and CEA levels in pleural effusion is very useful for the differentiation of malignant from tuberculous pleural effusion. Combined detection of the four markers may greatly improve the diagnostic accuracy. (authors)

  10. Highly sensitive and rapid bacteria detection using molecular beacon-Au nanoparticles hybrid nanoprobes.

    Science.gov (United States)

    Cao, Jing; Feng, Chao; Liu, Yan; Wang, Shouyu; Liu, Fei

    2014-07-15

    Since many diseases are caused by pathogenic bacterial infections, accurate and rapid detection of pathogenic bacteria is in urgent need to timely apply appropriate treatments and to reduce economic costs. To end this, we designed molecular beacon-Au nanoparticle hybrid nanoprobes to improve the bacterial detection efficiency and sensitivity. Here, we show that the designed molecular beacon modified Au nanoparticles could specifically recognize synthetic DNAs targets and can readily detect targets in clinical samples. Moreover, the hybrid nanoprobes can recognize Escherichia coli within an hour at a concentration of 10(2) cfu/ml, which is 1000-folds sensitive than using molecular beacon directly. Our results show that the molecular beacon-Au nanoparticle hybrid nanoprobes have great potential in medical and biological applications. Copyright © 2014 Elsevier B.V. All rights reserved.

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

    Science.gov (United States)

    Shuai, Chunyan; Yang, Hengcheng; Gong, Zeweiyi

    2018-05-01

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

  12. Anomaly Detection for Aviation Safety Based on an Improved KPCA Algorithm

    Directory of Open Access Journals (Sweden)

    Xiaoyu Zhang

    2017-01-01

    Full Text Available Thousands of flights datasets should be analyzed per day for a moderate sized fleet; therefore, flight datasets are very large. In this paper, an improved kernel principal component analysis (KPCA method is proposed to search for signatures of anomalies in flight datasets through the squared prediction error statistics, in which the number of principal components and the confidence for the confidence limit are automatically determined by OpenMP-based K-fold cross-validation algorithm and the parameter in the radial basis function (RBF is optimized by GPU-based kernel learning method. Performed on Nvidia GeForce GTX 660, the computation of the proposed GPU-based RBF parameter is 112.9 times (average 82.6 times faster than that of sequential CPU task execution. The OpenMP-based K-fold cross-validation process for training KPCA anomaly detection model becomes 2.4 times (average 1.5 times faster than that of sequential CPU task execution. Experiments show that the proposed approach can effectively detect the anomalies with the accuracy of 93.57% and false positive alarm rate of 1.11%.

  13. Improving Visual Threat Detection: Research to Validate the Threat Detection Skills Trainer

    Science.gov (United States)

    2013-08-01

    26 Threat Detection and Mitigation Strategies...quicker when identifying threats in relevant locations. This task utilized the Flicker paradigm (Rensink, O’Regan, & Clark, 1997; Scholl, 2000...the meaning and implication of threats, why cues were relevant, strategies used to detect and mitigate threats, and challenges when attempting to

  14. Improved detection of incipient anomalies via multivariate memory monitoring charts: Application to an air flow heating system

    KAUST Repository

    Harrou, Fouzi

    2016-08-11

    Detecting anomalies is important for reliable operation of several engineering systems. Multivariate statistical monitoring charts are an efficient tool for checking the quality of a process by identifying abnormalities. Principal component analysis (PCA) was shown effective in monitoring processes with highly correlated data. Traditional PCA-based methods, nevertheless, often are relatively inefficient at detecting incipient anomalies. Here, we propose a statistical approach that exploits the advantages of PCA and those of multivariate memory monitoring schemes, like the multivariate cumulative sum (MCUSUM) and multivariate exponentially weighted moving average (MEWMA) monitoring schemes to better detect incipient anomalies. Memory monitoring charts are sensitive to incipient anomalies in process mean, which significantly improve the performance of PCA method and enlarge its profitability, and to utilize these improvements in various applications. The performance of PCA-based MEWMA and MCUSUM control techniques are demonstrated and compared with traditional PCA-based monitoring methods. Using practical data gathered from a heating air-flow system, we demonstrate the greater sensitivity and efficiency of the developed method over the traditional PCA-based methods. Results indicate that the proposed techniques have potential for detecting incipient anomalies in multivariate data. © 2016 Elsevier Ltd

  15. Improving the Lane Reference Detection for Autonomous Road Vehicle Control

    Directory of Open Access Journals (Sweden)

    Felipe Jiménez

    2016-01-01

    Full Text Available Autonomous road vehicles are increasingly becoming more important and there are several techniques and sensors that are being applied for vehicle control. This paper presents an alternative system for maintaining the position of autonomous vehicles without adding additional elements to the standard sensor architecture, by using a 3D laser scanner for continuously detecting a reference element in situations in which the GNSS receiver fails or provides accuracy below the required level. Considering that the guidance variables are more accurately estimated when dealing with reference points in front of and behind the vehicle, an algorithm based on vehicle dynamics mathematical model is proposed to extend the detected points in cases where the sensor is placed at the front of the vehicle. The algorithm has been tested when driving along a lane delimited by New Jersey barriers at both sides and the results show a correct behaviour. The system is capable of estimating the reference element behind the vehicle with sufficient accuracy when the laser scanner is placed at the front of it, so the robustness of the control input variables (lateral and angular errors estimation is improved making it unnecessary to place the sensor on the vehicle roof or to introduce additional sensors.

  16. Detection of glyco-mucin profiles improves specificity of MUC16 and MUC1 biomarkers in ovarian serous tumours

    DEFF Research Database (Denmark)

    Ricardo, Sara; da Silva, Lara Patricia Marcos; Pereira, Daniela

    2015-01-01

    The CA125 assay detects circulating MUC16 and is one of the most widely used cancer biomarkers for the follow-up of ovarian cancer. We previously demonstrated that detection of aberrant cancer-associated glycoforms of MUC16 as well as MUC1 in circulation could improve the yield of these serum ass...

  17. Background Adjusted Alignment-Free Dissimilarity Measures Improve the Detection of Horizontal Gene Transfer

    Directory of Open Access Journals (Sweden)

    Kujin Tang

    2018-04-01

    Full Text Available Horizontal gene transfer (HGT plays an important role in the evolution of microbial organisms including bacteria. Alignment-free methods based on single genome compositional information have been used to detect HGT. Currently, Manhattan and Euclidean distances based on tetranucleotide frequencies are the most commonly used alignment-free dissimilarity measures to detect HGT. By testing on simulated bacterial sequences and real data sets with known horizontal transferred genomic regions, we found that more advanced alignment-free dissimilarity measures such as CVTree and d2* that take into account the background Markov sequences can solve HGT detection problems with significantly improved performance. We also studied the influence of different factors such as evolutionary distance between host and donor sequences, size of sliding window, and host genome composition on the performances of alignment-free methods to detect HGT. Our study showed that alignment-free methods can predict HGT accurately when host and donor genomes are in different order levels. Among all methods, CVTree with word length of 3, d2* with word length 3, Markov order 1 and d2* with word length 4, Markov order 1 outperform others in terms of their highest F1-score and their robustness under the influence of different factors.

  18. An improved data clustering algorithm for outlier detection

    Directory of Open Access Journals (Sweden)

    Anant Agarwal

    2016-12-01

    Full Text Available Data mining is the extraction of hidden predictive information from large databases. This is a technology with potential to study and analyze useful information present in data. Data objects which do not usually fit into the general behavior of the data are termed as outliers. Outlier Detection in databases has numerous applications such as fraud detection, customized marketing, and the search for terrorism. By definition, outliers are rare occurrences and hence represent a small portion of the data. However, the use of Outlier Detection for various purposes is not an easy task. This research proposes a modified PAM for detecting outliers. The proposed technique has been implemented in JAVA. The results produced by the proposed technique are found better than existing technique in terms of outliers detected and time complexity.

  19. Credit spread variability in U.S. business cycles: the Great Moderation versus the Great Recession

    OpenAIRE

    Hylton Hollander; Guangling Liu

    2014-01-01

    This paper establishes the prevailing financial factors that influence credit spread variability, and its impact on the U.S. business cycle over the Great Moderation and Great Recession periods. To do so, we develop a dynamic general equilibrium framework with a central role of financial intermediation and equity assets. Over the Great Moderation and Great Recession periods, we find an important role for bank market power (sticky rate adjustments and loan rate markups) on credit spread variab...

  20. Credit spread variability in U.S. business cycles: The Great Moderation versus the Great Recession

    OpenAIRE

    Hylton Hollander and Guangling Liu

    2014-01-01

    This paper establishes the prevailing financial factors that influence credit spread variability, and its impact on the U.S. business cycle over the Great Moderation and Great Recession periods. To do so, we develop a dynamic general equilibrium framework with a central role of financial intermediation and equity assets. Over the Great Moderation and Great Recession periods, we find an important role for bank market power (sticky rate adjustments and loan rate markups) on credit spread variab...

  1. The role of iconic memory in change-detection tasks.

    Science.gov (United States)

    Becker, M W; Pashler, H; Anstis, S M

    2000-01-01

    In three experiments, subjects attempted to detect the change of a single item in a visually presented array of items. Subjects' ability to detect a change was greatly reduced if a blank interstimulus interval (ISI) was inserted between the original array and an array in which one item had changed ('change blindness'). However, change detection improved when the location of the change was cued during the blank ISI. This suggests that people represent more information of a scene than change blindness might suggest. We test two possible hypotheses why, in the absence of a cue, this representation fails to produce good change detection. The first claims that the intervening events employed to create change blindness result in multiple neural transients which co-occur with the to-be-detected change. Poor detection rates occur because a serial search of all the transient locations is required to detect the change, during which time the representation of the original scene fades. The second claims that the occurrence of the second frame overwrites the representation of the first frame, unless that information is insulated against overwriting by attention. The results support the second hypothesis. We conclude that people may have a fairly rich visual representation of a scene while the scene is present, but fail to detect changes because they lack the ability to simultaneously represent two complete visual representations.

  2. Environmental DNA (eDNA sampling improves occurrence and detection estimates of invasive burmese pythons.

    Directory of Open Access Journals (Sweden)

    Margaret E Hunter

    Full Text Available Environmental DNA (eDNA methods are used to detect DNA that is shed into the aquatic environment by cryptic or low density species. Applied in eDNA studies, occupancy models can be used to estimate occurrence and detection probabilities and thereby account for imperfect detection. However, occupancy terminology has been applied inconsistently in eDNA studies, and many have calculated occurrence probabilities while not considering the effects of imperfect detection. Low detection of invasive giant constrictors using visual surveys and traps has hampered the estimation of occupancy and detection estimates needed for population management in southern Florida, USA. Giant constrictor snakes pose a threat to native species and the ecological restoration of the Florida Everglades. To assist with detection, we developed species-specific eDNA assays using quantitative PCR (qPCR for the Burmese python (Python molurus bivittatus, Northern African python (P. sebae, boa constrictor (Boa constrictor, and the green (Eunectes murinus and yellow anaconda (E. notaeus. Burmese pythons, Northern African pythons, and boa constrictors are established and reproducing, while the green and yellow anaconda have the potential to become established. We validated the python and boa constrictor assays using laboratory trials and tested all species in 21 field locations distributed in eight southern Florida regions. Burmese python eDNA was detected in 37 of 63 field sampling events; however, the other species were not detected. Although eDNA was heterogeneously distributed in the environment, occupancy models were able to provide the first estimates of detection probabilities, which were greater than 91%. Burmese python eDNA was detected along the leading northern edge of the known population boundary. The development of informative detection tools and eDNA occupancy models can improve conservation efforts in southern Florida and support more extensive studies of invasive

  3. Environmental DNA (eDNA) sampling improves occurrence and detection estimates of invasive burmese pythons.

    Science.gov (United States)

    Hunter, Margaret E; Oyler-McCance, Sara J; Dorazio, Robert M; Fike, Jennifer A; Smith, Brian J; Hunter, Charles T; Reed, Robert N; Hart, Kristen M

    2015-01-01

    Environmental DNA (eDNA) methods are used to detect DNA that is shed into the aquatic environment by cryptic or low density species. Applied in eDNA studies, occupancy models can be used to estimate occurrence and detection probabilities and thereby account for imperfect detection. However, occupancy terminology has been applied inconsistently in eDNA studies, and many have calculated occurrence probabilities while not considering the effects of imperfect detection. Low detection of invasive giant constrictors using visual surveys and traps has hampered the estimation of occupancy and detection estimates needed for population management in southern Florida, USA. Giant constrictor snakes pose a threat to native species and the ecological restoration of the Florida Everglades. To assist with detection, we developed species-specific eDNA assays using quantitative PCR (qPCR) for the Burmese python (Python molurus bivittatus), Northern African python (P. sebae), boa constrictor (Boa constrictor), and the green (Eunectes murinus) and yellow anaconda (E. notaeus). Burmese pythons, Northern African pythons, and boa constrictors are established and reproducing, while the green and yellow anaconda have the potential to become established. We validated the python and boa constrictor assays using laboratory trials and tested all species in 21 field locations distributed in eight southern Florida regions. Burmese python eDNA was detected in 37 of 63 field sampling events; however, the other species were not detected. Although eDNA was heterogeneously distributed in the environment, occupancy models were able to provide the first estimates of detection probabilities, which were greater than 91%. Burmese python eDNA was detected along the leading northern edge of the known population boundary. The development of informative detection tools and eDNA occupancy models can improve conservation efforts in southern Florida and support more extensive studies of invasive constrictors

  4. Computed tomography in the detection of pulmonary metastases. Improvement by application of spiral technology

    International Nuclear Information System (INIS)

    Kauczor, H.U.; Hansen, M.; Schweden, F.; Strunk, H.; Mildenberger, P.; Thelen, M.

    1994-01-01

    Computed tomography is the imaging modality of choice for detection or exclusion of pulmonary metastases. In most cases these are spheric, multiple, bilateral, and located in the peripheral areas of the middle and lower fields of the lungs. Differential diagnosis of solitary pulmonary nodules is difficult. Evaluating whether they are malignant or benign is insufficient despite the application of multiple CT criteria. Spiral computed tomography acquiring an imaging volume in a breathhold has led to significant improvement in the sensitivity of detecting pulmonary nodules. Imaging protocols are presented, and the influence of the different parameters is discussed. Although not all pulmonary metastases may be detected with spiral computed tomography, it is the most important examination when considering pulmonary metastasectomy. Computed tomography is the imaging modality of choice when monitoring pulmonary metastases during systemic therapeutic regimens by measuring all nodules or 'indicator lesions'. (orig.) [de

  5. Improving the Detectability of the Catalan Seismic Network for Local Seismic Activity Monitoring

    Science.gov (United States)

    Jara, Jose Antonio; Frontera, Tànit; Batlló, Josep; Goula, Xavier

    2016-04-01

    The seismic survey of the territory of Catalonia is mainly performed by the regional seismic network operated by the Cartographic and Geologic Institute of Catalonia (ICGC). After successive deployments and upgrades, the current network consists of 16 permanent stations equipped with 3 component broadband seismometers (STS2, STS2.5, CMG3ESP and CMG3T), 24 bits digitizers (Nanometrics Trident) and VSAT telemetry. Data are continuously sent in real-time via Hispasat 1D satellite to the ICGC datacenter in Barcelona. Additionally, data from other 10 stations of neighboring areas (Spain, France and Andorra) are continuously received since 2011 via Internet or VSAT, contributing both to detect and to locate events affecting the region. More than 300 local events with Ml ≥ 0.7 have been yearly detected and located in the region. Nevertheless, small magnitude earthquakes, especially those located in the south and south-west of Catalonia may still go undetected by the automatic detection system (DAS), based on Earthworm (USGS). Thus, in order to improve the detection and characterization of these missed events, one or two new stations should be installed. Before making the decision about where to install these new stations, the performance of each existing station is evaluated taking into account the fraction of detected events using the station records, compared to the total number of events in the catalogue, occurred during the station operation time from January 1, 2011 to December 31, 2014. These evaluations allow us to build an Event Detection Probability Map (EDPM), a required tool to simulate EDPMs resulting from different network topology scenarios depending on where these new stations are sited, and becoming essential for the decision-making process to increase and optimize the event detection probability of the seismic network.

  6. Application of Composite Indices for Improving Joint Detection Capabilities of Instrumented Roof Bolt Drills in Underground Mining and Construction

    Science.gov (United States)

    Liu, Wenpeng; Rostami, Jamal; Elsworth, Derek; Ray, Asok

    2018-03-01

    Roof bolts are the dominant method of ground support in mining and tunneling applications, and the concept of using drilling parameters from the bolter for ground characterization has been studied for a few decades. This refers to the use of drilling data to identify geological features in the ground including joints and voids, as well as rock classification. Rock mass properties, including distribution of joints/voids and strengths of rock layers, are critical factors for proper design of ground support to avoid instability. The goal of this research was to improve the capability and sensitivity of joint detection programs based on the updated pattern recognition algorithms in sensing joints with smaller than 3.175 mm (0.125 in.) aperture while reducing the number of false alarms, and discriminating rock layers with different strengths. A set of concrete blocks with different strengths were used to simulate various rock layers, where the gap between the blocks would represent the joints in laboratory tests. Data obtained from drilling through these blocks were analyzed to improve the reliability and precision of joint detection systems. While drilling parameters can be used to detect the gaps, due to low accuracy of the results, new composite indices have been introduced and used in the analysis to improve the detection rates. This paper briefly discusses ongoing research on joint detection by using drilling parameters collected from a roof bolter in a controlled environment. The performances of the new algorithms for joint detection are also examined by comparing their ability to identify existing joints and reducing false alarms.

  7. Network Interactions in the Great Altai Region

    Directory of Open Access Journals (Sweden)

    Lev Aleksandrovich Korshunov

    2017-12-01

    Full Text Available To improve the efficiency and competitiveness of the regional economy, an effective interaction between educational institutions in the Great Altai region is needed. The innovation growth can enhancing this interaction. The article explores the state of network structures in the economy and higher education in the border territories of the countries of Great Altai. The authors propose an updated approach to the three-level classification of network interaction. We analyze growing influence of the countries with emerging economies. We define the factors that impede the more stable and multifaceted regional development of these countries. Further, the authors determine indicators of the higher education systems and cooperation systems at the university level between the Shanghai Cooperation Organization countries (SCO and BRICS countries, showing the international rankings of the universities in these countries. The teaching language is important to overcome the obstacles in the interregional cooperation. The authors specify the problems of the development of the universities of the SCO and BRICS countries as global educational networks. The research applies basic scientific logical methods of analysis and synthesis, induction and deduction, as well as the SWOT analysis method. We have indentified and analyzed the existing economic and educational relations. To promote the economic innovation development of the border territories of the Great Altai, we propose a model of regional network university. Modern universities function in a new economic environment. Thus, in a great extent, they form the technological and social aspects of this environment. Innovative network structures contribute to the formation of a new network institutional environment of the regional economy, which impacts the macro- and microeconomic performance of the region as a whole. The results of the research can help to optimize the regional economies of the border

  8. Harnessing Context for Vandalism Detection in Wikipedia

    Directory of Open Access Journals (Sweden)

    Lakshmish Ramaswamy

    2014-05-01

    Full Text Available The importance of collaborative social media (CSM applications such as Wikipedia to modern free societies can hardly be overemphasized. By allowing end users to freely create and edit content, Wikipedia has greatly facilitated democratization of information. However, over the past several years, Wikipedia has also become susceptible to vandalism, which has adversely affected its information quality. Traditional vandalism detection techniques that rely upon simple textual features such as spammy or abusive words have not been very effective in combating sophisticated vandal attacks that do not contain common vandalism markers. In this paper, we propose a context-based vandalism detection framework for Wikipedia. We first propose a contextenhanced finite state model for representing the context evolution ofWikipedia articles. This paper identifies two distinct types of context that are potentially valuable for vandalism detection, namely content-context and contributor-context. The distinguishing powers of these contexts are discussed by providing empirical results. We design two novel metrics for measuring how well the content-context of an incoming edit fits into the topic and the existing content of a Wikipedia article. We outline machine learning-based vandalism identification schemes that utilize these metrics. Our experiments indicate that utilizing context can substantially improve vandalism detection accuracy.

  9. Improvement of early detection of breast cancer through collaborative multi-country efforts: Medical physics component.

    Science.gov (United States)

    Mora, Patricia; Faulkner, Keith; Mahmoud, Ahmed M; Gershan, Vesna; Kausik, Aruna; Zdesar, Urban; Brandan, María-Ester; Kurt, Serap; Davidović, Jasna; Salama, Dina H; Aribal, Erkin; Odio, Clara; Chaturvedi, Arvind K; Sabih, Zahida; Vujnović, Saša; Paez, Diana; Delis, Harry

    2018-04-01

    The International Atomic Energy Agency (IAEA) through a Coordinated Research Project on "Enhancing Capacity for Early Detection and Diagnosis of Breast Cancer through Imaging", brought together a group of mammography radiologists, medical physicists and radiographers; to investigate current practices and improve procedures for the early detection of breast cancer by strengthening both the clinical and medical physics components. This paper addresses the medical physics component. The countries that participated in the CRP were Bosnia and Herzegovina, Costa Rica, Egypt, India, Kenya, the Frmr. Yug. Rep. of Macedonia, Mexico, Nigeria, Pakistan, Philippines, Slovenia, Turkey, Uganda, United Kingdom and Zambia. Ten institutions participated using IAEA quality control protocols in 9 digital and 3 analogue mammography equipment. A spreadsheet for data collection was generated and distributed. Evaluation of image quality was done using TOR MAX and DMAM2 Gold phantoms. QC results for analogue equipment showed satisfactory results. QC tests performed on digital systems showed that improvements needed to be implemented, especially in thickness accuracy, signal difference to noise ratio (SDNR) values for achievable levels, uniformity and modulation transfer function (MTF). Mean glandular dose (MGD) was below international recommended levels for patient radiation protection. Evaluation of image quality by phantoms also indicated the need for improvement. Common activities facilitated improvement in mammography practice, including training of medical physicists in QC programs and infrastructure was improved and strengthened; networking among medical physicists and radiologists took place and was maintained over time. IAEA QC protocols provided a uniformed approach to QC measurements. Copyright © 2018 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

  10. Iterative image reconstruction algorithms in coronary CT angiography improve the detection of lipid-core plaque - a comparison with histology

    International Nuclear Information System (INIS)

    Puchner, Stefan B.; Ferencik, Maros; Maurovich-Horvat, Pal; Nakano, Masataka; Otsuka, Fumiyuki; Virmani, Renu; Kauczor, Hans-Ulrich; Hoffmann, Udo; Schlett, Christopher L.

    2015-01-01

    To evaluate whether iterative reconstruction algorithms improve the diagnostic accuracy of coronary CT angiography (CCTA) for detection of lipid-core plaque (LCP) compared to histology. CCTA and histological data were acquired from three ex vivo hearts. CCTA images were reconstructed using filtered back projection (FBP), adaptive-statistical (ASIR) and model-based (MBIR) iterative algorithms. Vessel cross-sections were co-registered between FBP/ASIR/MBIR and histology. Plaque area 2 : 5.78 ± 2.29 vs. 3.39 ± 1.68 FBP; 5.92 ± 1.87 vs. 3.43 ± 1.62 ASIR; 6.40 ± 1.55 vs. 3.49 ± 1.50 MBIR; all p < 0.0001). AUC for detecting LCP was 0.803/0.850/0.903 for FBP/ASIR/MBIR and was significantly higher for MBIR compared to FBP (p = 0.01). MBIR increased sensitivity for detection of LCP by CCTA. Plaque area <60 HU in CCTA was associated with LCP in histology regardless of the reconstruction algorithm. However, MBIR demonstrated higher accuracy for detecting LCP, which may improve vulnerable plaque detection by CCTA. (orig.)

  11. Improvement of the Error-detection Mechanism in Adults with Dyslexia Following Reading Acceleration Training.

    Science.gov (United States)

    Horowitz-Kraus, Tzipi

    2016-05-01

    The error-detection mechanism aids in preventing error repetition during a given task. Electroencephalography demonstrates that error detection involves two event-related potential components: error-related and correct-response negativities (ERN and CRN, respectively). Dyslexia is characterized by slow, inaccurate reading. In particular, individuals with dyslexia have a less active error-detection mechanism during reading than typical readers. In the current study, we examined whether a reading training programme could improve the ability to recognize words automatically (lexical representations) in adults with dyslexia, thereby resulting in more efficient error detection during reading. Behavioural and electrophysiological measures were obtained using a lexical decision task before and after participants trained with the reading acceleration programme. ERN amplitudes were smaller in individuals with dyslexia than in typical readers before training but increased following training, as did behavioural reading scores. Differences between the pre-training and post-training ERN and CRN components were larger in individuals with dyslexia than in typical readers. Also, the error-detection mechanism as represented by the ERN/CRN complex might serve as a biomarker for dyslexia and be used to evaluate the effectiveness of reading intervention programmes. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  12. Multi-vehicle detection with identity awareness using cascade Adaboost and Adaptive Kalman filter for driver assistant system.

    Science.gov (United States)

    Wang, Baofeng; Qi, Zhiquan; Chen, Sizhong; Liu, Zhaodu; Ma, Guocheng

    2017-01-01

    Vision-based vehicle detection is an important issue for advanced driver assistance systems. In this paper, we presented an improved multi-vehicle detection and tracking method using cascade Adaboost and Adaptive Kalman filter(AKF) with target identity awareness. A cascade Adaboost classifier using Haar-like features was built for vehicle detection, followed by a more comprehensive verification process which could refine the vehicle hypothesis in terms of both location and dimension. In vehicle tracking, each vehicle was tracked with independent identity by an Adaptive Kalman filter in collaboration with a data association approach. The AKF adaptively adjusted the measurement and process noise covariance through on-line stochastic modelling to compensate the dynamics changes. The data association correctly assigned different detections with tracks using global nearest neighbour(GNN) algorithm while considering the local validation. During tracking, a temporal context based track management was proposed to decide whether to initiate, maintain or terminate the tracks of different objects, thus suppressing the sparse false alarms and compensating the temporary detection failures. Finally, the proposed method was tested on various challenging real roads, and the experimental results showed that the vehicle detection performance was greatly improved with higher accuracy and robustness.

  13. Detecting non-binomial sex allocation when developmental mortality operates.

    Science.gov (United States)

    Wilkinson, Richard D; Kapranas, Apostolos; Hardy, Ian C W

    2016-11-07

    Optimal sex allocation theory is one of the most intricately developed areas of evolutionary ecology. Under a range of conditions, particularly under population sub-division, selection favours sex being allocated to offspring non-randomly, generating non-binomial variances of offspring group sex ratios. Detecting non-binomial sex allocation is complicated by stochastic developmental mortality, as offspring sex can often only be identified on maturity with the sex of non-maturing offspring remaining unknown. We show that current approaches for detecting non-binomiality have limited ability to detect non-binomial sex allocation when developmental mortality has occurred. We present a new procedure using an explicit model of sex allocation and mortality and develop a Bayesian model selection approach (available as an R package). We use the double and multiplicative binomial distributions to model over- and under-dispersed sex allocation and show how to calculate Bayes factors for comparing these alternative models to the null hypothesis of binomial sex allocation. The ability to detect non-binomial sex allocation is greatly increased, particularly in cases where mortality is common. The use of Bayesian methods allows for the quantification of the evidence in favour of each hypothesis, and our modelling approach provides an improved descriptive capability over existing approaches. We use a simulation study to demonstrate substantial improvements in power for detecting non-binomial sex allocation in situations where current methods fail, and we illustrate the approach in real scenarios using empirically obtained datasets on the sexual composition of groups of gregarious parasitoid wasps. Copyright © 2016 Elsevier Ltd. All rights reserved.

  14. Reproductive behavior of the great hornbill (Buceros bicornis).

    Science.gov (United States)

    Kozlowski, Corinne P; Bauman, Karen L; Asa, Cheryl S

    2015-01-01

    Great hornbills (Buceros bicornis) are a long-lived, monogamous species that forms strong pair-bonds, and mate compatibility is thought to be important for successful reproduction. Within AZA, great hornbills are listed as a red SSP. The population consists of a limited number of individuals that do not breed reliably, and improving reproduction is a top priority for the Coraciiformes TAG. To better understand mating behavior and evaluate mate compatibility, this study documented the behavior of pairs of great hornbills during and immediately after courtship. Using live observations, the study followed one female, an experienced and successful breeder, as she was paired with four successive males over 11 breeding seasons. Initially, males frequently vocalized, investigated the nest, and approached the female. As the female spent more time in the nest, these behaviors were replaced by regurgitation and food offering. The female was most often observed plastering and vocalizing. Behavioral differences between successful and unsuccessful pairs, possibly indicative of pair compatibility, included rates of approaching, billing, and biting. Numerous behaviors occurred more frequently during years that a chick hatched, including pseudoregurgitation, regurgitation, offering food items, and nest investigation. Males also spent more time in proximity to both the female and the nest during years that a chick hatched. Together, these results suggest that the amount of time pairs spend in proximity, the amount of time a male spends near the nest, and the frequency of certain behaviors may help evaluate compatibility and the likelihood of successful reproduction for pairs of great hornbills. © 2015 Wiley Periodicals, Inc.

  15. A Hybrid Vehicle Detection Method Based on Viola-Jones and HOG + SVM from UAV Images

    Science.gov (United States)

    Xu, Yongzheng; Yu, Guizhen; Wang, Yunpeng; Wu, Xinkai; Ma, Yalong

    2016-01-01

    A new hybrid vehicle detection scheme which integrates the Viola-Jones (V-J) and linear SVM classifier with HOG feature (HOG + SVM) methods is proposed for vehicle detection from low-altitude unmanned aerial vehicle (UAV) images. As both V-J and HOG + SVM are sensitive to on-road vehicles’ in-plane rotation, the proposed scheme first adopts a roadway orientation adjustment method, which rotates each UAV image to align the roads with the horizontal direction so the original V-J or HOG + SVM method can be directly applied to achieve fast detection and high accuracy. To address the issue of descending detection speed for V-J and HOG + SVM, the proposed scheme further develops an adaptive switching strategy which sophistically integrates V-J and HOG + SVM methods based on their different descending trends of detection speed to improve detection efficiency. A comprehensive evaluation shows that the switching strategy, combined with the road orientation adjustment method, can significantly improve the efficiency and effectiveness of the vehicle detection from UAV images. The results also show that the proposed vehicle detection method is competitive compared with other existing vehicle detection methods. Furthermore, since the proposed vehicle detection method can be performed on videos captured from moving UAV platforms without the need of image registration or additional road database, it has great potentials of field applications. Future research will be focusing on expanding the current method for detecting other transportation modes such as buses, trucks, motors, bicycles, and pedestrians. PMID:27548179

  16. A Hybrid Vehicle Detection Method Based on Viola-Jones and HOG + SVM from UAV Images.

    Science.gov (United States)

    Xu, Yongzheng; Yu, Guizhen; Wang, Yunpeng; Wu, Xinkai; Ma, Yalong

    2016-08-19

    A new hybrid vehicle detection scheme which integrates the Viola-Jones (V-J) and linear SVM classifier with HOG feature (HOG + SVM) methods is proposed for vehicle detection from low-altitude unmanned aerial vehicle (UAV) images. As both V-J and HOG + SVM are sensitive to on-road vehicles' in-plane rotation, the proposed scheme first adopts a roadway orientation adjustment method, which rotates each UAV image to align the roads with the horizontal direction so the original V-J or HOG + SVM method can be directly applied to achieve fast detection and high accuracy. To address the issue of descending detection speed for V-J and HOG + SVM, the proposed scheme further develops an adaptive switching strategy which sophistically integrates V-J and HOG + SVM methods based on their different descending trends of detection speed to improve detection efficiency. A comprehensive evaluation shows that the switching strategy, combined with the road orientation adjustment method, can significantly improve the efficiency and effectiveness of the vehicle detection from UAV images. The results also show that the proposed vehicle detection method is competitive compared with other existing vehicle detection methods. Furthermore, since the proposed vehicle detection method can be performed on videos captured from moving UAV platforms without the need of image registration or additional road database, it has great potentials of field applications. Future research will be focusing on expanding the current method for detecting other transportation modes such as buses, trucks, motors, bicycles, and pedestrians.

  17. On Improving Face Detection Performance by Modelling Contextual Information

    OpenAIRE

    Atanasoaei, Cosmin; McCool, Chris; Marcel, Sébastien

    2010-01-01

    In this paper we present a new method to enhance object detection by removing false alarms and merging multiple detections in a principled way with few parameters. The method models the output of an object classiï¬er which we consider as the context. A hierarchical model is built using the detection distribution around a target sub-window to discriminate between false alarms and true detections. Next the context is used to iteratively reï¬ne the detections. Finally the detections are clustere...

  18. Computer-aided detection of colorectal polyps: can it improve sensitivity of less-experienced readers? Preliminary findings.

    Science.gov (United States)

    Baker, Mark E; Bogoni, Luca; Obuchowski, Nancy A; Dass, Chandra; Kendzierski, Renee M; Remer, Erick M; Einstein, David M; Cathier, Pascal; Jerebko, Anna; Lakare, Sarang; Blum, Andrew; Caroline, Dina F; Macari, Michael

    2007-10-01

    To determine whether computer-aided detection (CAD) applied to computed tomographic (CT) colonography can help improve sensitivity of polyp detection by less-experienced radiologist readers, with colonoscopy or consensus used as the reference standard. The release of the CT colonographic studies was approved by the individual institutional review boards of each institution. Institutions from the United States were HIPAA compliant. Written informed consent was waived at all institutions. The CT colonographic studies in 30 patients from six institutions were collected; 24 images depicted at least one confirmed polyp 6 mm or larger (39 total polyps) and six depicted no polyps. By using an investigational software package, seven less-experienced readers from two institutions evaluated the CT colonographic images and marked or scored polyps by using a five-point scale before and after CAD. The time needed to interpret the CT colonographic findings without CAD and then to re-evaluate them with CAD was recorded. For each reader, the McNemar test, adjusted for clustered data, was used to compare sensitivities for readers without and with CAD; a Wilcoxon signed-rank test was used to analyze the number of false-positive results per patient. The average sensitivity of the seven readers for polyp detection was significantly improved with CAD-from 0.810 to 0.908 (P=.0152). The number of false-positive results per patient without and with CAD increased from 0.70 to 0.96 (95% confidence interval for the increase: -0.39, 0.91). The mean total time for the readings was 17 minutes 54 seconds; for interpretation of CT colonographic findings alone, the mean time was 14 minutes 16 seconds; and for review of CAD findings, the mean time was 3 minutes 38 seconds. Results of this feasibility study suggest that CAD for CT colonography significantly improves per-polyp detection for less-experienced readers. Copyright (c) RSNA, 2007.

  19. Distance Measurement Methods for Improved Insider Threat Detection

    Directory of Open Access Journals (Sweden)

    Owen Lo

    2018-01-01

    Full Text Available Insider threats are a considerable problem within cyber security and it is often difficult to detect these threats using signature detection. Increasing machine learning can provide a solution, but these methods often fail to take into account changes of behaviour of users. This work builds on a published method of detecting insider threats and applies Hidden Markov method on a CERT data set (CERT r4.2 and analyses a number of distance vector methods (Damerau–Levenshtein Distance, Cosine Distance, and Jaccard Distance in order to detect changes of behaviour, which are shown to have success in determining different insider threats.

  20. Improvement of detection of stress corrosion cracks with ultrasonic phased array probes

    International Nuclear Information System (INIS)

    Wustenberg, H.; Mohrle, W.; Wegner, W.; Schenk, G.; Erhard, A.

    1986-01-01

    Probes with linear arrays can be used for the detection of stress corrosion cracks especially if the variability of the sound field is used to change the skewing angle of angle beam probes. The phased array concept can be used to produce a variable skewing angle or a variable angle of incidence depending on the orientation of the linear array on the wedge. This helps to adapt the direction of the ultrasonic beam to probable crack orientations. It has been demonstrated with artificial reflectors as well as with corrosion cracks, that the detection of misoriented cracks can be improved by this approach. The experiences gained during the investigations are encouraging the application of phased array probes for stress corrosion phenomena close to the heat effected zone of welds. Probes with variable skewing angles may find some interesting applications on welds in tubular structures e.g., at off shore constructions and on some difficult geometries within the primary circuit of nuclear power plants

  1. Improvements on coronal hole detection in SDO/AIA images using supervised classification

    Directory of Open Access Journals (Sweden)

    Reiss Martin A.

    2015-01-01

    Full Text Available We demonstrate the use of machine learning algorithms in combination with segmentation techniques in order to distinguish coronal holes and filaments in SDO/AIA EUV images of the Sun. Based on two coronal hole detection techniques (intensity-based thresholding, SPoCA, we prepared datasets of manually labeled coronal hole and filament channel regions present on the Sun during the time range 2011–2013. By mapping the extracted regions from EUV observations onto HMI line-of-sight magnetograms we also include their magnetic characteristics. We computed shape measures from the segmented binary maps as well as first order and second order texture statistics from the segmented regions in the EUV images and magnetograms. These attributes were used for data mining investigations to identify the most performant rule to differentiate between coronal holes and filament channels. We applied several classifiers, namely Support Vector Machine (SVM, Linear Support Vector Machine, Decision Tree, and Random Forest, and found that all classification rules achieve good results in general, with linear SVM providing the best performances (with a true skill statistic of ≈ 0.90. Additional information from magnetic field data systematically improves the performance across all four classifiers for the SPoCA detection. Since the calculation is inexpensive in computing time, this approach is well suited for applications on real-time data. This study demonstrates how a machine learning approach may help improve upon an unsupervised feature extraction method.

  2. Improved nuclear emergency management system reflecting lessons learned from the emergency response at Fukushima Daini Nuclear Power Station after the Great East Japan Earthquake

    International Nuclear Information System (INIS)

    Kawamura, Shinichi; Narabayashi, Tadashi

    2016-01-01

    Three nuclear reactors at Fukushima Daini Nuclear Power Station lost all their ultimate heat sinks owing to damage from the tsunami caused by the Great East Japan Earthquake on March 11, 2011. Water was injected into the reactors by alternate measures, damaged cooling systems were restored with promptly supplied substitute materials, and all the reactors were brought to a cold shutdown state within four days. Lessons learned from this experience were identified to improve emergency management, especially in the areas of strategic response planning, logistics, and functions supporting response activities continuing over a long period. It was found that continuous planning activities reflecting information from plant parameters and response action results were important, and that relevant functions in emergency response organizations should be integrated. Logistics were handled successfully but many difficulties were experienced. Therefore, their functions should be clearly established and improved by emergency response organizations. Supporting emergency responders in the aspects of their physical and mental conditions was important for sustaining continuous response. As a platform for improvement, the concept of the Incident Command System was applied for the first time to a nuclear emergency management system, with specific improvement ideas such as a phased approach in response planning and common operation pictures. (author)

  3. An improved algorithm for small and cool fire detection using MODIS data: A preliminary study in the southeastern United States

    Science.gov (United States)

    Wanting Wang; John J. Qu; Xianjun Hao; Yongqiang Liu; William T. Sommers

    2006-01-01

    Traditional fire detection algorithms mainly rely on hot spot detection using thermal infrared (TIR) channels with fixed or contextual thresholds. Three solar reflectance channels (0.65 μm, 0.86 μm, and 2.1 μm) were recently adopted into the MODIS version 4 contextual algorithm to improve the active fire detection. In the southeastern United...

  4. Detection of Target ssDNA Using a Microfabricated Hall Magnetometer with Correlated Optical Readout

    Directory of Open Access Journals (Sweden)

    Steven M. Hira

    2012-01-01

    Full Text Available Sensing biological agents at the genomic level, while enhancing the response time for biodetection over commonly used, optics-based techniques such as nucleic acid microarrays or enzyme-linked immunosorbent assays (ELISAs, is an important criterion for new biosensors. Here, we describe the successful detection of a 35-base, single-strand nucleic acid target by Hall-based magnetic transduction as a mimic for pathogenic DNA target detection. The detection platform has low background, large signal amplification following target binding and can discriminate a single, 350 nm superparamagnetic bead labeled with DNA. Detection of the target sequence was demonstrated at 364 pM (<2 target DNA strands per bead target DNA in the presence of 36 μM nontarget (noncomplementary DNA (<10 ppm target DNA using optical microscopy detection on a GaAs Hall mimic. The use of Hall magnetometers as magnetic transduction biosensors holds promise for multiplexing applications that can greatly improve point-of-care (POC diagnostics and subsequent medical care.

  5. Improvements of low-level radioxenon detection sensitivity by a state-of-the art coincidence setup.

    Science.gov (United States)

    Cagniant, A; Le Petit, G; Gross, P; Douysset, G; Richard-Bressand, H; Fontaine, J-P

    2014-05-01

    The ability to quantify isotopic ratios of 135, 133 m, 133 and 131 m radioxenon is essential for the verification of the Comprehensive Nuclear-Test Ban Treaty (CTBT). In order to improve detection limits, CEA has developed a new on-site setup using photon/electron coincidence (Le Petit et al., 2013. J. Radioanal. Nucl. Chem., DOI : 10.1007/s 10697-013-2525-8.). Alternatively, the electron detection cell equipped with large silicon chips (PIPS) can be used with HPGe detector for laboratory analysis purpose. This setup allows the measurement of β/γ coincidences for the detection of (133)Xe and (135)Xe; and K-shell Conversion Electrons (K-CE)/X-ray coincidences for the detection of (131m)Xe, (133m)Xe and (133)Xe as well. Good energy resolution of 11 keV at 130 keV and low energy threshold of 29 keV for the electron detection were obtained. This provides direct discrimination between K-CE from (133)Xe, (133m)Xe and (131m)Xe. Estimation of Minimum Detectable Activity (MDA) for (131m)Xe is in the order of 1mBq over a 4 day measurement. An analysis of an environmental radioxenon sample using this method is shown. © 2013 The Authors. Published by Elsevier Ltd All rights reserved.

  6. An Adaptive Cultural Algorithm with Improved Quantum-behaved Particle Swarm Optimization for Sonar Image Detection.

    Science.gov (United States)

    Wang, Xingmei; Hao, Wenqian; Li, Qiming

    2017-12-18

    This paper proposes an adaptive cultural algorithm with improved quantum-behaved particle swarm optimization (ACA-IQPSO) to detect the underwater sonar image. In the population space, to improve searching ability of particles, iterative times and the fitness value of particles are regarded as factors to adaptively adjust the contraction-expansion coefficient of the quantum-behaved particle swarm optimization algorithm (QPSO). The improved quantum-behaved particle swarm optimization algorithm (IQPSO) can make particles adjust their behaviours according to their quality. In the belief space, a new update strategy is adopted to update cultural individuals according to the idea of the update strategy in shuffled frog leaping algorithm (SFLA). Moreover, to enhance the utilization of information in the population space and belief space, accept function and influence function are redesigned in the new communication protocol. The experimental results show that ACA-IQPSO can obtain good clustering centres according to the grey distribution information of underwater sonar images, and accurately complete underwater objects detection. Compared with other algorithms, the proposed ACA-IQPSO has good effectiveness, excellent adaptability, a powerful searching ability and high convergence efficiency. Meanwhile, the experimental results of the benchmark functions can further demonstrate that the proposed ACA-IQPSO has better searching ability, convergence efficiency and stability.

  7. The Detection of Helicobacter hepaticus Using Whispering-Gallery Mode Microcavity Optical Sensors

    Directory of Open Access Journals (Sweden)

    Mark E. Anderson

    2015-08-01

    Full Text Available Current bacterial detection techniques are relatively slow, require bulky instrumentation, and usually require some form of specialized training. The gold standard for bacterial detection is culture testing, which can take several days to receive a viable result. Therefore, simpler detection techniques that are both fast and sensitive could greatly improve bacterial detection and identification. Here, we present a new method for the detection of the bacteria Helicobacter hepaticus using whispering-gallery mode (WGM optical microcavity-based sensors. Due to minimal reflection losses and low material adsorption, WGM-based sensors have ultra-high quality factors, resulting in high-sensitivity sensor devices. In this study, we have shown that bacteria can be non-specifically detected using WGM optical microcavity-based sensors. The minimum detection for the device was 1 × 104 cells/mL, and the minimum time of detection was found to be 750 s. Given that a cell density as low as 1 × 103 cells/mL for Helicobacter hepaticus can cause infection, the limit of detection shown here would be useful for most levels where Helicobacter hepaticus is biologically relevant. This study suggests a new approach for H. hepaticus detection using label-free optical sensors that is faster than, and potentially as sensitive as, standard techniques.

  8. Improving the performance of univariate control charts for abnormal detection and classification

    Science.gov (United States)

    Yiakopoulos, Christos; Koutsoudaki, Maria; Gryllias, Konstantinos; Antoniadis, Ioannis

    2017-03-01

    Bearing failures in rotating machinery can cause machine breakdown and economical loss, if no effective actions are taken on time. Therefore, it is of prime importance to detect accurately the presence of faults, especially at their early stage, to prevent sequent damage and reduce costly downtime. The machinery fault diagnosis follows a roadmap of data acquisition, feature extraction and diagnostic decision making, in which mechanical vibration fault feature extraction is the foundation and the key to obtain an accurate diagnostic result. A challenge in this area is the selection of the most sensitive features for various types of fault, especially when the characteristics of failures are difficult to be extracted. Thus, a plethora of complex data-driven fault diagnosis methods are fed by prominent features, which are extracted and reduced through traditional or modern algorithms. Since most of the available datasets are captured during normal operating conditions, the last decade a number of novelty detection methods, able to work when only normal data are available, have been developed. In this study, a hybrid method combining univariate control charts and a feature extraction scheme is introduced focusing towards an abnormal change detection and classification, under the assumption that measurements under normal operating conditions of the machinery are available. The feature extraction method integrates the morphological operators and the Morlet wavelets. The effectiveness of the proposed methodology is validated on two different experimental cases with bearing faults, demonstrating that the proposed approach can improve the fault detection and classification performance of conventional control charts.

  9. Smartphone-Based Solutions for Fall Detection and Prevention: Challenges and Open Issues

    Directory of Open Access Journals (Sweden)

    Mohammad Ashfak Habib

    2014-04-01

    Full Text Available This paper presents a state-of-the-art survey of smartphone (SP-based solutions for fall detection and prevention. Falls are considered as major health hazards for both the elderly and people with neurodegenerative diseases. To mitigate the adverse consequences of falling, a great deal of research has been conducted, mainly focused on two different approaches, namely, fall detection and fall prevention. Required hardware for both fall detection and prevention are also available in SPs. Consequently, researchers’ interest in finding SP-based solutions has increased dramatically over recent years. To the best of our knowledge, there has been no published review on SP-based fall detection and prevention. Thus in this paper, we present the taxonomy for SP-based fall detection and prevention solutions and systematic comparisons of existing studies. We have also identified three challenges and three open issues for future research, after reviewing the existing articles. Our time series analysis demonstrates a trend towards the integration of external sensing units with SPs for improvement in usability of the systems.

  10. What Makes a Great Journal Great in Economics? The Singer Not the Song.

    NARCIS (Netherlands)

    C-L. Chang (Chia-Lin); M.J. McAleer (Michael); L. Oxley (Les)

    2010-01-01

    textabstractThe paper is concerned with analysing what makes a great journal great in economics, based on quantifiable measures. Alternative Research Assessment Measures (RAM) are discussed, with an emphasis on the Thomson Reuters ISI Web of Science database (hereafter ISI). The various ISI RAM that

  11. Improving Earth/Prediction Models to Improve Network Processing

    Science.gov (United States)

    Wagner, G. S.

    2017-12-01

    The United States Atomic Energy Detection System (USAEDS) primaryseismic network consists of a relatively small number of arrays andthree-component stations. The relatively small number of stationsin the USAEDS primary network make it both necessary and feasibleto optimize both station and network processing.Station processing improvements include detector tuning effortsthat use Receiver Operator Characteristic (ROC) curves to helpjudiciously set acceptable Type 1 (false) vs. Type 2 (miss) errorrates. Other station processing improvements include the use ofempirical/historical observations and continuous background noisemeasurements to compute time-varying, maximum likelihood probabilityof detection thresholds.The USAEDS network processing software makes extensive use of theazimuth and slowness information provided by frequency-wavenumberanalysis at array sites, and polarization analysis at three-componentsites. Most of the improvements in USAEDS network processing aredue to improvements in the models used to predict azimuth, slowness,and probability of detection. Kriged travel-time, azimuth andslowness corrections-and associated uncertainties-are computedusing a ground truth database. Improvements in station processingand the use of improved models for azimuth, slowness, and probabilityof detection have led to significant improvements in USADES networkprocessing.

  12. Cladophora in the Great Lakes: impacts on beach water quality and human health.

    Science.gov (United States)

    Verhougstraete, M P; Byappanahalli, M N; Rose, J B; Whitman, R L

    2010-01-01

    Cladophora in the Great Lakes grows rapidly during the warm summer months, detaches, and becomes free-floating mats as a result of environmental conditions, eventually becoming stranded on recreational beaches. Cladophora provides protection and nutrients, which allow enteric bacteria such as Escherichia coli, enterococci, Shigella, Campylobacter, and Salmonella to persist and potentially regrow in the presence of the algae. As a result of wind and wave action, these microorganisms can detach and be released to surrounding waters and can influence water quality. Enteric bacterial pathogens have been detected in Cladophora mats; E. coli and enterococci may populate to become part of the naturalized microbiota in Cladophora; the high densities of these bacteria may affect water quality, resulting in unnecessary beach closures. The continued use of traditional fecal indicators at beaches with Cladophora presence is inadequate at accurately predicting the presence of fecal contamination. This paper offers a substantial review of available literature to improve the knowledge of Cladophora impacts on water quality, recreational water monitoring, fecal indicator bacteria and microorganisms, and public health and policy.

  13. Great Basin Experimental Range: Annotated bibliography

    Science.gov (United States)

    E. Durant McArthur; Bryce A. Richardson; Stanley G. Kitchen

    2013-01-01

    This annotated bibliography documents the research that has been conducted on the Great Basin Experimental Range (GBER, also known as the Utah Experiment Station, Great Basin Station, the Great Basin Branch Experiment Station, Great Basin Experimental Center, and other similar name variants) over the 102 years of its existence. Entries were drawn from the original...

  14. Detection of extracellular proteases from microorganisms on agar plates

    Directory of Open Access Journals (Sweden)

    Alane Beatriz Vermelho

    1996-12-01

    Full Text Available We present herein an improved assay for detecting the presence of extracellular proteases from microorganisms on agar plates. Using different substrates (gelatin, BSA, hemoglobin incorporated into the agar and varying the culture medium composition, we were able to detect proteolytic activities from Pseudomonas aeruginosa, Micrococcus luteus and Serratia marcescens as well as the influence that these components displayed in the expression of these enzymes. For all microorganisms tested we found that in agar-BHI or yeast extract medium containing gelatin the sensitivity of proteinase detection was considerably greater than in BSA-agar or hemoglobin-agar. However, when BSA or hemoglobin were added to the culture medium, there was an increase in growth along with a marked reduction in the amount of proteinase production. In the case of M. luteus the incorporation of glycerol in BHI or yeast extract gelatin-agar induced protease liberation. Our results indicate that the technique described here is of value for detecting extracellular proteases directly in the culture medium, by means of a qualitative assay, simple, inexpensive, straight forward method to assess the presence of the proteolytic activity of a given microorganism colony with great freedom in substrate selection.

  15. The GREAT3 challenge

    International Nuclear Information System (INIS)

    Miyatake, H; Mandelbaum, R; Rowe, B

    2014-01-01

    The GRavitational lEnsing Accuracy Testing 3 (GREAT3) challenge is an image analysis competition that aims to test algorithms to measure weak gravitational lensing from astronomical images. The challenge started in October 2013 and ends 30 April 2014. The challenge focuses on testing the impact on weak lensing measurements of realistically complex galaxy morphologies, realistic point spread function, and combination of multiple different exposures. It includes simulated ground- and space-based data. The details of the challenge are described in [1], and the challenge website and its leader board can be found at http://great3challenge.info and http://great3.projects.phys.ucl.ac.uk/leaderboard/, respectively

  16. Detecting Precontact Anthropogenic Microtopographic Features in a Forested Landscape with Lidar: A Case Study from the Upper Great Lakes Region, AD 1000-1600.

    Science.gov (United States)

    Howey, Meghan C L; Sullivan, Franklin B; Tallant, Jason; Kopple, Robert Vande; Palace, Michael W

    2016-01-01

    Forested settings present challenges for understanding the full extent of past human landscape modifications. Field-based archaeological reconnaissance in forests is low-efficiency and most remote sensing techniques are of limited utility, and together, this means many past sites and features in forests are unknown. Archaeologists have increasingly used light detection and ranging (lidar), a remote sensing tool that uses pulses of light to measure reflecting surfaces at high spatial resolution, to address these limitations. Archaeology studies using lidar have made significant progress identifying permanent structures built by large-scale complex agriculturalist societies. Largely unaccounted for, however, are numerous small and more practical modifications of landscapes by smaller-scale societies. Here we show these may also be detectable with lidar by identifying remnants of food storage pits (cache pits) created by mobile hunter-gatherers in the upper Great Lakes during Late Precontact (ca. AD 1000-1600) that now only exist as subtle microtopographic features. Years of intensive field survey identified 69 cache pit groups between two inland lakes in northern Michigan, almost all of which were located within ~500 m of a lakeshore. Applying a novel series of image processing techniques and statistical analyses to a high spatial resolution DTM we created from commercial-grade lidar, our detection routine identified 139 high potential cache pit clusters. These included most of the previously known clusters as well as several unknown clusters located >1500 m from either lakeshore, much further from lakeshores than all previously identified cultural sites. Food storage is understood to have emerged regionally as a risk-buffering strategy after AD 1000 but our results indicate the current record of hunter-gatherer cache pit food storage is markedly incomplete and this practice and its associated impact on the landscape may be greater than anticipated. Our study also

  17. Effect of background correction on peak detection and quantification in online comprehensive two-dimensional liquid chromatography using diode array detection.

    Science.gov (United States)

    Allen, Robert C; John, Mallory G; Rutan, Sarah C; Filgueira, Marcelo R; Carr, Peter W

    2012-09-07

    A singular value decomposition-based background correction (SVD-BC) technique is proposed for the reduction of background contributions in online comprehensive two-dimensional liquid chromatography (LC×LC) data. The SVD-BC technique was compared to simply subtracting a blank chromatogram from a sample chromatogram and to a previously reported background correction technique for one dimensional chromatography, which uses an asymmetric weighted least squares (AWLS) approach. AWLS was the only background correction technique to completely remove the background artifacts from the samples as evaluated by visual inspection. However, the SVD-BC technique greatly reduced or eliminated the background artifacts as well and preserved the peak intensity better than AWLS. The loss in peak intensity by AWLS resulted in lower peak counts at the detection thresholds established using standards samples. However, the SVD-BC technique was found to introduce noise which led to detection of false peaks at the lower detection thresholds. As a result, the AWLS technique gave more precise peak counts than the SVD-BC technique, particularly at the lower detection thresholds. While the AWLS technique resulted in more consistent percent residual standard deviation values, a statistical improvement in peak quantification after background correction was not found regardless of the background correction technique used. Copyright © 2012 Elsevier B.V. All rights reserved.

  18. Detection of Termites and Other Insects Consumed by African Great Apes using Molecular Fecal Analysis

    OpenAIRE

    Ibrahim Hamad; Eric Delaporte; Didier Raoult; Fadi Bittar

    2014-01-01

    The consumption of insects by apes has previously been reported based on direct observations and/or trail signs in feces. However, DNA-based diet analyses may have the potential to reveal trophic links for these wild species. Herein, we analyzed the insect-diet diversity of 9 feces obtained from three species of African great apes, gorilla (Gorilla gorilla gorilla), chimpanzee (Pan troglodytes) and bonobo (Pan paniscus), using two mitochondrial amplifications for arthropods. A total of 1056 c...

  19. Oxytocin administration selectively improves olfactory detection thresholds for lyral in patients with schizophrenia.

    Science.gov (United States)

    Woolley, J D; Lam, O; Chuang, B; Ford, J M; Mathalon, D H; Vinogradov, S

    2015-03-01

    Olfaction plays an important role in mammalian social behavior. Olfactory deficits are common in schizophrenia and correlate with negative symptoms and low social drive. Despite their prominence and possible clinical relevance, little is understood about the pathological mechanisms underlying olfactory deficits in schizophrenia and there are currently no effective treatments for these deficits. The prosocial neuropeptide oxytocin may affect the olfactory system when administered intranasally to humans and there is growing interest in its therapeutic potential in schizophrenia. To examine this model, we administered 40IU of oxytocin and placebo intranasally to 31 patients with a schizophrenia spectrum illness and 34 age-matched healthy control participants in a randomized, double-blind, placebo-controlled, cross-over study. On each test day, participants completed an olfactory detection threshold test for two different odors: (1) lyral, a synthetic fragrance compound for which patients with schizophrenia have specific olfactory detection threshold deficits, possibly related to decreased cyclic adenosine 3',5'-monophosphate (cAMP) signaling; and (2) anise, a compound for which olfactory detection thresholds change with menstrual cycle phase in women. On the placebo test day, patients with schizophrenia did not significantly differ from healthy controls in detection of either odor. We found that oxytocin administration significantly and selectively improved olfactory detection thresholds for lyral but not for anise in patients with schizophrenia. In contrast, oxytocin had no effect on detection of either odor in healthy controls. Our data indicate that oxytocin administration may ameliorate olfactory deficits in schizophrenia and suggest the effects of intranasal oxytocin may extend to influencing the olfactory system. Given that oxytocin has been found to increase cAMP signaling in vitro a possible mechanism for these effects is discussed. Published by Elsevier Ltd.

  20. Improved detection of hydrophilic phosphopeptides using graphite powder microcolumns and mass spectrometry: evidence for in vivo doubly phosphorylated dynamin I and dynamin III

    DEFF Research Database (Denmark)

    Larsen, Martin Røssel; Graham, Mark E; Robinson, Phillip J

    2004-01-01

    A common strategy in proteomics to improve the number and quality of peptides detected by mass spectrometry (MS) is to desalt and concentrate proteolytic digests using reversed phase (RP) chromatography prior to analysis. However, this does not allow for detection of small or hydrophilic peptides...... a large improvement in the detection of small amounts of phosphopeptides by MS and the approach has major implications for both small- and large-scale projects in phosphoproteomics.......A common strategy in proteomics to improve the number and quality of peptides detected by mass spectrometry (MS) is to desalt and concentrate proteolytic digests using reversed phase (RP) chromatography prior to analysis. However, this does not allow for detection of small or hydrophilic peptides......, or peptides altered in hydrophilicity such as phosphopeptides. We used microcolumns to compare the ability of RP resin or graphite powder to retain phosphopeptides. A number of standard phosphopeptides and a biologically relevant phosphoprotein, dynamin I, were analyzed. MS revealed that some phosphopeptides...

  1. An unreported type of coronary artery naomaly in congenitally corrected transposition of great arteries

    Energy Technology Data Exchange (ETDEWEB)

    Kwak, Min Kyu; Jeong, Yeon Joo; Lee, Gee Won; Lee, Nam Kyung; Choi, Jung Hyun; Lee, Ji Won [Medical Research Institute, Pusan National University Hospital, Busan (Korea, Republic of)

    2016-07-15

    Coronary artery variations are associated anomalies in 45% of congenitally corrected transposition of the great arteries (ccTGA) cases, and it is important to detect any coronary artery anomalies before cardiac surgery. We report a case of a 51-year-old woman with ccTGA and an unreported type of coronary artery anomaly.

  2. Real-time PCR improves Helicobacter pylori detection in patients with peptic ulcer bleeding.

    Directory of Open Access Journals (Sweden)

    María José Ramírez-Lázaro

    Full Text Available BACKGROUND AND AIMS: Histological and rapid urease tests to detect H. pylori in biopsy specimens obtained during peptic ulcer bleeding episodes (PUB often produce false-negative results. We aimed to examine whether immunohistochemistry and real-time PCR can improve the sensitivity of these biopsies. PATIENTS AND METHODS: We selected 52 histology-negative formalin-fixed paraffin-embedded biopsy specimens obtained during PUB episodes. Additional tests showed 10 were true negatives and 42 were false negatives. We also selected 17 histology-positive biopsy specimens obtained during PUB to use as controls. We performed immunohistochemistry staining and real-time PCR for 16S rRNA, ureA, and 23S rRNA for H. pylori genes on all specimens. RESULTS: All controls were positive for H. pylori on all PCR assays and immunohistochemical staining. Regarding the 52 initially negative biopsies, all PCR tests were significantly more sensitive than immunohistochemical staining (p<0.01. Sensitivity and specificity were 55% and 80% for 16S rRNA PCR, 43% and 90% for ureA PCR, 41% and 80% for 23S rRNA PCR, and 7% and 100% for immunohistochemical staining, respectively. Combined analysis of PCR assays for two genes were significantly more sensitive than ureA or 23S rRNA PCR tests alone (p<0.05 and marginally better than 16S rRNA PCR alone. The best combination was 16S rRNA+ureA, with a sensitivity of 64% and a specificity of 80%. CONCLUSIONS: Real-time PCR improves the detection of H. pylori infection in histology-negative formalin-fixed paraffin-embedded biopsy samples obtained during PUB episodes. The low reported prevalence of H. pylori in PUB may be due to the failure of conventional tests to detect infection.

  3. Using BiSON to detect solar internal g-modes

    Directory of Open Access Journals (Sweden)

    Kuszlewicz J.

    2015-01-01

    Full Text Available The unambiguous detection of individual solar internal g modes continues to elude us. With the aid of new additions to calibration procedures, as well as updated methods to combine multi-site time series more effectively, the noise and signal detection threshold levels in the low-frequency domain (where the g modes are expected to be found have been greatly improved. In the BiSON 23-year dataset these levels now rival those of GOLF, and with much greater frequency resolution available, due to the long time series, there is an opportunity to place more constraints on the upper limits of individual g mode amplitudes. Here we detail recent work dedicated to the challenges of observing low-frequency oscillations using a ground-based network, including the role of the window function as well as the effect of calibration on the low frequency domain.

  4. 75 FR 6354 - NOAA Great Lakes Habitat Restoration Program Project Grants under the Great Lakes Restoration...

    Science.gov (United States)

    2010-02-09

    ...-04] RIN 0648-ZC10 NOAA Great Lakes Habitat Restoration Program Project Grants under the Great Lakes... Atmospheric Administration (NOAA), Department of Commerce. ACTION: Notice of funding availability; Date... on January 19, 2010. That notice announced the NOAA Great Lakes Habitat Restoration Program Project...

  5. The Next Great Generation?

    Science.gov (United States)

    Brownstein, Andrew

    2000-01-01

    Discusses ideas from a new book, "Millennials Rising: The Next Great Generation," (by Neil Howe and William Strauss) suggesting that youth culture is on the cusp of a radical shift with the generation beginning with this year's college freshmen who are typically team oriented, optimistic, and poised for greatness on a global scale. Includes a…

  6. Two-Stage Classification Approach for Human Detection in Camera Video in Bulk Ports

    Directory of Open Access Journals (Sweden)

    Mi Chao

    2015-09-01

    Full Text Available With the development of automation in ports, the video surveillance systems with automated human detection begun to be applied in open-air handling operation areas for safety and security. The accuracy of traditional human detection based on the video camera is not high enough to meet the requirements of operation surveillance. One of the key reasons is that Histograms of Oriented Gradients (HOG features of the human body will show great different between front & back standing (F&B and side standing (Side human body. Therefore, the final training for classifier will only gain a few useful specific features which have contribution to classification and are insufficient to support effective classification, while using the HOG features directly extracted by the samples from different human postures. This paper proposes a two-stage classification method to improve the accuracy of human detection. In the first stage, during preprocessing classification, images is mainly divided into possible F&B human body and not F&B human body, and then they were put into the second-stage classification among side human and non-human recognition. The experimental results in Tianjin port show that the two-stage classifier can improve the classification accuracy of human detection obviously.

  7. An Improved Wavelet‐Based Multivariable Fault Detection Scheme

    KAUST Repository

    Harrou, Fouzi; Sun, Ying; Madakyaru, Muddu

    2017-01-01

    Data observed from environmental and engineering processes are usually noisy and correlated in time, which makes the fault detection more difficult as the presence of noise degrades fault detection quality. Multiscale representation of data using

  8. Targeting safety improvements through identification of incident origination and detection in a near-miss incident learning system

    International Nuclear Information System (INIS)

    Novak, Avrey; Nyflot, Matthew J.; Ermoian, Ralph P.; Jordan, Loucille E.; Sponseller, Patricia A.; Kane, Gabrielle M.; Ford, Eric C.; Zeng, Jing

    2016-01-01

    Purpose: Radiation treatment planning involves a complex workflow that has multiple potential points of vulnerability. This study utilizes an incident reporting system to identify the origination and detection points of near-miss errors, in order to guide their departmental safety improvement efforts. Previous studies have examined where errors arise, but not where they are detected or applied a near-miss risk index (NMRI) to gauge severity. Methods: From 3/2012 to 3/2014, 1897 incidents were analyzed from a departmental incident learning system. All incidents were prospectively reviewed weekly by a multidisciplinary team and assigned a NMRI score ranging from 0 to 4 reflecting potential harm to the patient (no potential harm to potential critical harm). Incidents were classified by point of incident origination and detection based on a 103-step workflow. The individual steps were divided among nine broad workflow categories (patient assessment, imaging for radiation therapy (RT) planning, treatment planning, pretreatment plan review, treatment delivery, on-treatment quality management, post-treatment completion, equipment/software quality management, and other). The average NMRI scores of incidents originating or detected within each broad workflow area were calculated. Additionally, out of 103 individual process steps, 35 were classified as safety barriers, the process steps whose primary function is to catch errors. The safety barriers which most frequently detected incidents were identified and analyzed. Finally, the distance between event origination and detection was explored by grouping events by the number of broad workflow area events passed through before detection, and average NMRI scores were compared. Results: Near-miss incidents most commonly originated within treatment planning (33%). However, the incidents with the highest average NMRI scores originated during imaging for RT planning (NMRI = 2.0, average NMRI of all events = 1.5), specifically

  9. Targeting safety improvements through identification of incident origination and detection in a near-miss incident learning system

    Energy Technology Data Exchange (ETDEWEB)

    Novak, Avrey; Nyflot, Matthew J.; Ermoian, Ralph P.; Jordan, Loucille E.; Sponseller, Patricia A.; Kane, Gabrielle M.; Ford, Eric C.; Zeng, Jing, E-mail: jzeng13@uw.edu [Department of Radiation Oncology, University of Washington Medical Center, 1959 NE Pacific Street, Campus Box 356043, Seattle, Washington 98195 (United States)

    2016-05-15

    Purpose: Radiation treatment planning involves a complex workflow that has multiple potential points of vulnerability. This study utilizes an incident reporting system to identify the origination and detection points of near-miss errors, in order to guide their departmental safety improvement efforts. Previous studies have examined where errors arise, but not where they are detected or applied a near-miss risk index (NMRI) to gauge severity. Methods: From 3/2012 to 3/2014, 1897 incidents were analyzed from a departmental incident learning system. All incidents were prospectively reviewed weekly by a multidisciplinary team and assigned a NMRI score ranging from 0 to 4 reflecting potential harm to the patient (no potential harm to potential critical harm). Incidents were classified by point of incident origination and detection based on a 103-step workflow. The individual steps were divided among nine broad workflow categories (patient assessment, imaging for radiation therapy (RT) planning, treatment planning, pretreatment plan review, treatment delivery, on-treatment quality management, post-treatment completion, equipment/software quality management, and other). The average NMRI scores of incidents originating or detected within each broad workflow area were calculated. Additionally, out of 103 individual process steps, 35 were classified as safety barriers, the process steps whose primary function is to catch errors. The safety barriers which most frequently detected incidents were identified and analyzed. Finally, the distance between event origination and detection was explored by grouping events by the number of broad workflow area events passed through before detection, and average NMRI scores were compared. Results: Near-miss incidents most commonly originated within treatment planning (33%). However, the incidents with the highest average NMRI scores originated during imaging for RT planning (NMRI = 2.0, average NMRI of all events = 1.5), specifically

  10. An improved AE detection method of rail defect based on multi-level ANC with VSS-LMS

    Science.gov (United States)

    Zhang, Xin; Cui, Yiming; Wang, Yan; Sun, Mingjian; Hu, Hengshan

    2018-01-01

    In order to ensure the safety and reliability of railway system, Acoustic Emission (AE) method is employed to investigate rail defect detection. However, little attention has been paid to the defect detection at high speed, especially for noise interference suppression. Based on AE technology, this paper presents an improved rail defect detection method by multi-level ANC with VSS-LMS. Multi-level noise cancellation based on SANC and ANC is utilized to eliminate complex noises at high speed, and tongue-shaped curve with index adjustment factor is proposed to enhance the performance of variable step-size algorithm. Defect signals and reference signals are acquired by the rail-wheel test rig. The features of noise signals and defect signals are analyzed for effective detection. The effectiveness of the proposed method is demonstrated by comparing with the previous study, and different filter lengths are investigated to obtain a better noise suppression performance. Meanwhile, the detection ability of the proposed method is verified at the top speed of the test rig. The results clearly illustrate that the proposed method is effective in detecting rail defects at high speed, especially for noise interference suppression.

  11. Improving detection of first-episode psychosis by mental health-care services using a self-report questionnaire

    NARCIS (Netherlands)

    Boonstra, Nynke; Wunderink, Lex; Sytema, Sjoerd; Wiersma, Durk

    2009-01-01

    Objective: To examine the utility of the Community Assessment of Psychic Experiences (CAPE)-42, a self-report questionnaire, to improve detection of first-episode psychosis in new referrals to mental health services. Method: At first contact with mental health-care services patients were asked to

  12. Acoustic Event Detection in Multichannel Audio Using Gated Recurrent Neural Networks with High‐Resolution Spectral Features

    Directory of Open Access Journals (Sweden)

    Hyoung‐Gook Kim

    2017-12-01

    Full Text Available Recently, deep recurrent neural networks have achieved great success in various machine learning tasks, and have also been applied for sound event detection. The detection of temporally overlapping sound events in realistic environments is much more challenging than in monophonic detection problems. In this paper, we present an approach to improve the accuracy of polyphonic sound event detection in multichannel audio based on gated recurrent neural networks in combination with auditory spectral features. In the proposed method, human hearing perception‐based spatial and spectral‐domain noise‐reduced harmonic features are extracted from multichannel audio and used as high‐resolution spectral inputs to train gated recurrent neural networks. This provides a fast and stable convergence rate compared to long short‐term memory recurrent neural networks. Our evaluation reveals that the proposed method outperforms the conventional approaches.

  13. Camouflaged target detection based on polarized spectral features

    Science.gov (United States)

    Tan, Jian; Zhang, Junping; Zou, Bin

    2016-05-01

    The polarized hyperspectral images (PHSI) include polarization, spectral, spatial and radiant features, which provide more information about objects and scenes than traditional intensity or spectrum ones. And polarization can suppress the background and highlight the object, leading to the high potential to improve camouflaged target detection. So polarized hyperspectral imaging technique has aroused extensive concern in the last few years. Nowadays, the detection methods are still not very mature, most of which are rooted in the detection of hyperspectral image. And before using these algorithms, Stokes vector is used to process the original four-dimensional polarized hyperspectral data firstly. However, when the data is large and complex, the amount of calculation and error will increase. In this paper, tensor is applied to reconstruct the original four-dimensional data into new three-dimensional data, then, the constraint energy minimization (CEM) is used to process the new data, which adds the polarization information to construct the polarized spectral filter operator and takes full advantages of spectral and polarized information. This way deals with the original data without extracting the Stokes vector, so as to reduce the computation and error greatly. The experimental results also show that the proposed method in this paper is more suitable for the target detection of the PHSI.

  14. System for detecting nuclear explosions

    International Nuclear Information System (INIS)

    Rawls, L.E.

    1978-01-01

    Apparatus for detecting underground nuclear explosions is described that is comprised of an antenna located in the dielectric substance of a deep waveguide in the earth and adapted to detect low frequency electromagnetic waves generated by a nuclear explosion, the deep waveguide comprising the high conductivity upper sedimentary layers of the earth, the dielectric basement rock, and a high conductivity layer of basement rock due to the increased temperature thereof at great depths, and means for receiving the electromagnetic waves detected by said antenna means

  15. Object Detection: Current and Future Directions

    Directory of Open Access Journals (Sweden)

    Rodrigo eVerschae

    2015-11-01

    Full Text Available Object detection is a key ability required by most computer and robot vision systems. The latest research on this area has been making great progress in many directions. In the current manuscript we give an overview of past research on object detection, outline the current main research directions, and discuss open problems and possible future directions.

  16. Wind Regimes in Complex Terrain of the Great Valley of Eastern Tennessee

    Energy Technology Data Exchange (ETDEWEB)

    Birdwell, Kevin R. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2011-05-01

    This research was designed to provide an understanding of physical wind mechanisms within the complex terrain of the Great Valley of Eastern Tennessee to assess the impacts of regional air flow with regard to synoptic and mesoscale weather changes, wind direction shifts, and air quality. Meteorological data from 2008 2009 were analyzed from 13 meteorological sites along with associated upper level data. Up to 15 ancillary sites were used for reference. Two-step complete linkage and K-means cluster analyses, synoptic weather studies, and ambient meteorological comparisons were performed to generate hourly wind classifications. These wind regimes revealed seasonal variations of underlying physical wind mechanisms (forced channeled, vertically coupled, pressure-driven, and thermally-driven winds). Synoptic and ambient meteorological analysis (mixing depth, pressure gradient, pressure gradient ratio, atmospheric and surface stability) suggested up to 93% accuracy for the clustered results. Probabilistic prediction schemes of wind flow and wind class change were developed through characterization of flow change data and wind class succession. Data analysis revealed that wind flow in the Great Valley was dominated by forced channeled winds (45 67%) and vertically coupled flow (22 38%). Down-valley pressure-driven and thermally-driven winds also played significant roles (0 17% and 2 20%, respectively), usually accompanied by convergent wind patterns (15 20%) and large wind direction shifts, especially in the Central/Upper Great Valley. The behavior of most wind regimes was associated with detectable pressure differences between the Lower and Upper Great Valley. Mixing depth and synoptic pressure gradients were significant contributors to wind pattern behavior. Up to 15 wind classes and 10 sub-classes were identified in the Central Great Valley with 67 joined classes for the Great Valley at-large. Two-thirds of Great Valley at-large flow was defined by 12 classes. Winds

  17. Improved linear pyroelectric IR detector arrays

    International Nuclear Information System (INIS)

    Twiney, R.C.; Robinson, M.K.; Porter, S.G.

    1987-01-01

    Good agreement has been found between theoretical models and measured performance for a range of array geometries. A 64-element 80 x 140-micron element array with integral MOSFET IC buffer preamplifiers shows improved source voltage uniformity, a J-FET buffered array, and low-frequency specific detectivity (SD) of 1.7 x 10 to the 8th cm sq rt Hz/W at 40 Hz. The MOSFET array shows reduced degradation of SD at high temperatures, retaining an SD of not less than 1 x 10 to the 8th cm sq rt Hz/W at +70 C across much of the band. A 64-element array has been designed using onboard multiplexers, thus greatly reducing the connections needed to run the array

  18. A safer, urea-based in situ hybridization method improves detection of gene expression in diverse animal species.

    Science.gov (United States)

    Sinigaglia, Chiara; Thiel, Daniel; Hejnol, Andreas; Houliston, Evelyn; Leclère, Lucas

    2018-02-01

    In situ hybridization is a widely employed technique allowing spatial visualization of gene expression in fixed specimens. It has greatly advanced our understanding of biological processes, including developmental regulation. In situ protocols are today routinely followed in numerous laboratories, and although details might change, they all include a hybridization step, where specific antisense RNA or DNA probes anneal to the target nucleic acid sequence. This step is generally carried out at high temperatures and in a denaturing solution, called hybridization buffer, commonly containing 50% (v/v) formamide - a hazardous chemical. When applied to the soft-bodied hydrozoan medusa Clytia hemisphaerica, we found that this traditional hybridization approach was not fully satisfactory, causing extensive deterioration of morphology and tissue texture which compromised our observation and interpretation of results. We thus tested alternative solutions for in situ detection of gene expression and, inspired by optimized protocols for Northern and Southern blot analysis, we substituted the 50% formamide with an equal volume of 8M urea solution in the hybridization buffer. Our new protocol not only yielded better morphologies and tissue consistency, but also notably improved the resolution of the signal, allowing more precise localization of gene expression and reducing aspecific staining associated with problematic areas. Given the improved results and reduced manipulation risks, we tested the urea protocol on other metazoans, two brachiopod species (Novocrania anomala and Terebratalia transversa) and the priapulid worm Priapulus caudatus, obtaining a similar reduction of aspecific probe binding. Overall, substitution of formamide by urea during in situ hybridization offers a safer alternative, potentially of widespread use in research, medical and teaching contexts. We encourage other workers to test this approach on their study organisms, and hope that they will also

  19. Discrepancies in the occurrence of Balantidium coli between wild and captive African great apes.

    Science.gov (United States)

    Pomajbíková, Kateřina; Petrželková, Klára J; Profousová, Ilona; Petrášová, Jana; Modrý, David

    2010-12-01

    Balantidium coli is a ciliate reported in many mammalian species, including African great apes. In the former, asymptomatic infections as well as clinical balantidiasis have been reported in captivity. We carried out a cross-sectional study of B. coli in African great apes (chimpanzees, bonobos, and both species of gorillas) and examined 1,161 fecal samples from 28 captive facilities in Europe, plus 2 sanctuaries and 11 wild sites in Africa. Samples were analyzed with the use of Sheather's flotation and merthiolate-iodine-formaldehyde (MIFC) sedimentation. MIFC sedimentation was the more sensitive technique for diagnostics of B. coli in apes. Although not detected in any wild-ape populations, B. coli was diagnosed in 52.6% of captive individuals. Surprisingly, in the apes' feces, trophozoites of B. coli were commonly detected, in contrast with other animals, e.g., Old World monkeys, pigs, etc. Most likely reservoirs for B. coli in captive apes include synantropic rats. High starch diets in captive apes are likely to exacerbate the occurrence of balantidiasis in captive apes.

  20. Street-side vehicle detection, classification and change detection using mobile laser scanning data

    Science.gov (United States)

    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.

  1. A feasibility study of stateful automaton packet inspection for streaming application detection systems

    Science.gov (United States)

    Tseng, Kuo-Kun; Lo, Jiao; Liu, Yiming; Chang, Shih-Hao; Merabti, Madjid; Ng, Felix, C. K.; Wu, C. H.

    2017-10-01

    The rapid development of the internet has brought huge benefits and social impacts; however, internet security has also become a great problem for users, since traditional approaches to packet classification cannot achieve satisfactory detection performance due to their low accuracy and efficiency. In this paper, a new stateful packet inspection method is introduced, which can be embedded in the network gateway and used by a streaming application detection system. This new detection method leverages the inexact automaton approach, using part of the header field and part of the application layer data of a packet. Based on this approach, an advanced detection system is proposed for streaming applications. The workflow of the system involves two stages: the training stage and the detection stage. In the training stage, the system initially captures characteristic patterns from a set of application packet flows. After this training is completed, the detection stage allows the user to detect the target application by capturing new application flows. This new detection approach is also evaluated using experimental analysis; the results of this analysis show that this new approach not only simplifies the management of the state detection system, but also improves the accuracy of data flow detection, making it feasible for real-world network applications.

  2. Combined detection of CEA, CYFRA21-1, NSE and SF levels in chest effusion fluid for differentiation of malignant hydrothorax from tuberculous hydrothorax

    International Nuclear Information System (INIS)

    Wang Jianguo; Zhai Shijun; Liu Ruihua; Quan Min

    2003-01-01

    Objective: To improve the diagnostic accuracy in the differentiation of malignant hydrothorax from tuberculous hydrothorax by combined detection of the levels of the four tumor markers in chest effusion fluid. Methods: The chest fluid levels of the four tumor markers were determined with RIA (for CYFRA21-1 and NSE) and chemiluminescence method (for CEA and SF) in 69 patients with tuberculous hydrothorax and 107 patients with malignant hydrothorax. Results: The positive rate and mean levels of the four tumor markers in malignant chest fluid were significantly higher than those in tuberculous chest fluid (p<0.01). Positive rate of combined detection in malignant chest fluid was 95.33%. Conclusion: Detection of chest fluid CEA, CYFRA21-1, NSE and SF levels is very useful for the differentiation of malignant hydrothorax from tuberculous hydrothorax. Combined detection of the four markers will greatly improve the diagnostic accuracy

  3. Combined diversity and improved energy detection in cooperative spectrum sensing with faded reporting channels

    Directory of Open Access Journals (Sweden)

    Srinivas Nallagonda

    2016-04-01

    Full Text Available In this paper we evaluate the performance of cooperative spectrum sensing (CSS where each cognitive radio (CR employs an improved energy detector (IED with multiple antennas and uses selection combining (SC for detecting the primary user (PU in noisy and faded sensing (S channels. We derive an expression for the probability of false alarm and expressions for probability of missed detection in non-faded (AWGN and Rayleigh faded sensing environments in terms of cumulative distribution function (CDF. Each CR transmits its decision about PU via noisy and faded reporting (R channel to fusion center (FC. In this paper we assume that S-channels are noisy and Rayleigh faded while several cases of fading are considered for R-channels such as: (i Hoyt (or Nakagami-q, (ii Rayleigh, (iii Rician (or Nakagami-n, and (iv Weibull. A Binary Symmetric channel (BSC with a fixed error probability (r in the R-channel is also considered. The impact of fading in R-channel, S-channel and several network parameters such as IED parameter, normalized detection threshold, number of CRs, and number of antennas on missed detection and total error probability is assessed. The effects of Hoyt, Rician, and Weibull fading parameters on overall performance of IED-CSS are also highlighted.

  4. An improved reconstruction algorithm based on multi-user detection for uplink grant-free NOMA

    Directory of Open Access Journals (Sweden)

    Hou Chengyan

    2017-01-01

    Full Text Available For the traditional orthogonal matching pursuit(OMP algorithm in multi-user detection(MUD for uplink grant-free NOMA, here is a poor BER performance, so in this paper we propose an temporal-correlation orthogonal matching pursuit algorithm(TOMP to realize muli-user detection. The core idea of the TOMP is to use the time correlation of the active user sets to achieve user activity and data detection in a number of continuous time slots. We use the estimated active user set in the current time slot as a priori information to estimate the active user sets for the next slot. By maintaining the active user set Tˆl of size K(K is the number of users, but modified in each iteration. Specifically, active user set is believed to be reliable in one iteration but shown error in another iteration, can be added to the set path delay Tˆl or removed from it. Theoretical analysis of the improved algorithm provide a guarantee that the multi-user can be successfully detected with a high probability. The simulation results show that the proposed scheme can achieve better bit error rate (BER performance in the uplink grant-free NOMA system.

  5. The Great Detective, by Zach Dundas; Gender and the modern Sherlock Holmes, edited by Nadine Farghaly; and Sherlock Holmes, edited by Alex Werner [book review

    Directory of Open Access Journals (Sweden)

    Julia Knaus

    2017-03-01

    Full Text Available Review of: Zach Dundas. The Great Detective: The amazing rise and immortal life of Sherlock Holmes. Boston: Houghton Mifflin Harcourt, 2015, hardcover, $26 (336p, ISBN 978-0-544-21404-0, e-book $15.95 (2378 KB, ISBN 978-0-544-22020-1, ASIN B00LZ7GP6U. Nadine Farghaly, ed. Gender and the modern Sherlock Holmes: Essays on film and television adaptations since 2009. Jefferson, NC: McFarland, 2015, paperback, $35 (260p, ISBN 978-0-786-49459-0, e-book $9.99 (3353 KB, ISBN 978-1-4766-2281-1, ASIN B019WQQEY8. Alex Werner, ed. Sherlock Holmes: The man who never lived and will never die. London: Ebury Press, 2014, hardcover, £25 (256p, ISBN 978-0-09-195872-5, e-book £12.99, ISBN 978-1-47-350264-2.

  6. Development of a filter-based method for detecting silver nanoparticles and their heteroaggregation in aqueous environments by surface-enhanced Raman spectroscopy

    International Nuclear Information System (INIS)

    Guo, Huiyuan; Xing, Baoshan; He, Lili

    2016-01-01

    The rising application of silver nanoparticles (AgNPs) and subsequent release into aquatic systems have generated public concerns over their potential risk and harm to aquatic organisms and human health. Effective and practical analytical methods for AgNPs are urgently needed for their risk assessment. In this study we established an innovative approach to detect trace levels of AgNPs in environmental water through integrating a filtration technique into surface-enhanced Raman spectroscopy (SERS) and compared it with previously established centrifuge-based method. The purpose of filtration was to trap and enrich salt-aggregated AgNPs from water samples onto the filter membrane, through which indicator was then passed and complexed with AgNPs. The enhanced SERS signals of indicator could reflect the presence and quantity of AgNPs in the samples. The most favorable benefit of filtration is being able to process large volume samples, which is more practical for water samples, and greatly improves the sensitivity of AgNP detection. In this study, we tested 20 mL AgNPs-containing samples and the filter-based method is able to detect AgNPs as low as 5 μg/L, which is 20 folds lower than the centrifuge-based method. In addition, the speed and precision of the detection were greatly improved. This approach was used to detect trace levels of AgNPs in real environmental water successfully. Meanwhile, the heteroaggregation of AgNPs with minerals in water was reliably monitored by the new method. Overall, a combination of the filtration-SERS approach provides a rapid, simple, and sensitive way to detect AgNPs and analyze their environmental behavior. - Highlights: • We developed a filtration-SERS method for analyzing AgNPs in water. • Detection limit can be improved by increasing sample volume for filtration. • Trace levels of AgNPs in natural water samples can be successfully detected. • Filtration-SERS is more efficient and precise than centrifugation-SERS.

  7. Congenital malalignment of the great toenails: case report and literature review.

    Science.gov (United States)

    Cohen, P R

    1991-03-01

    A 10-year-old black boy had congenital malalignment of the great toenails (CMGTN). It is important to recognize this condition since several nail disorders can occur concurrently with and/or clinically mimic it. Treatment is dependent on the severity of the condition, and includes conservative management and subsequent examination to detect CMGTN-associated complications for patients with mild lateral deviation of the nail plate, or surgical realignment for individuals with either marked nail plate deviation or condition-related disabling sequelae.

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

    Science.gov (United States)

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

    2017-08-01

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

  9. Great Lakes Environmental Database (GLENDA)

    Data.gov (United States)

    U.S. Environmental Protection Agency — The Great Lakes Environmental Database (GLENDA) houses environmental data on a wide variety of constituents in water, biota, sediment, and air in the Great Lakes area.

  10. Great ape gestures: intentional communication with a rich set of innate signals.

    Science.gov (United States)

    Byrne, R W; Cartmill, E; Genty, E; Graham, K E; Hobaiter, C; Tanner, J

    2017-09-08

    Great apes give gestures deliberately and voluntarily, in order to influence particular target audiences, whose direction of attention they take into account when choosing which type of gesture to use. These facts make the study of ape gesture directly relevant to understanding the evolutionary precursors of human language; here we present an assessment of ape gesture from that perspective, focusing on the work of the "St Andrews Group" of researchers. Intended meanings of ape gestures are relatively few and simple. As with human words, ape gestures often have several distinct meanings, which are effectively disambiguated by behavioural context. Compared to the signalling of most other animals, great ape gestural repertoires are large. Because of this, and the relatively small number of intended meanings they achieve, ape gestures are redundant, with extensive overlaps in meaning. The great majority of gestures are innate, in the sense that the species' biological inheritance includes the potential to develop each gestural form and use it for a specific range of purposes. Moreover, the phylogenetic origin of many gestures is relatively old, since gestures are extensively shared between different genera in the great ape family. Acquisition of an adult repertoire is a process of first exploring the innate species potential for many gestures and then gradual restriction to a final (active) repertoire that is much smaller. No evidence of syntactic structure has yet been detected.

  11. Multi-vehicle detection with identity awareness using cascade Adaboost and Adaptive Kalman filter for driver assistant system.

    Directory of Open Access Journals (Sweden)

    Baofeng Wang

    Full Text Available Vision-based vehicle detection is an important issue for advanced driver assistance systems. In this paper, we presented an improved multi-vehicle detection and tracking method using cascade Adaboost and Adaptive Kalman filter(AKF with target identity awareness. A cascade Adaboost classifier using Haar-like features was built for vehicle detection, followed by a more comprehensive verification process which could refine the vehicle hypothesis in terms of both location and dimension. In vehicle tracking, each vehicle was tracked with independent identity by an Adaptive Kalman filter in collaboration with a data association approach. The AKF adaptively adjusted the measurement and process noise covariance through on-line stochastic modelling to compensate the dynamics changes. The data association correctly assigned different detections with tracks using global nearest neighbour(GNN algorithm while considering the local validation. During tracking, a temporal context based track management was proposed to decide whether to initiate, maintain or terminate the tracks of different objects, thus suppressing the sparse false alarms and compensating the temporary detection failures. Finally, the proposed method was tested on various challenging real roads, and the experimental results showed that the vehicle detection performance was greatly improved with higher accuracy and robustness.

  12. Patient identification errors: the detective in the laboratory.

    Science.gov (United States)

    Salinas, Maria; López-Garrigós, Maite; Lillo, Rosa; Gutiérrez, Mercedes; Lugo, Javier; Leiva-Salinas, Carlos

    2013-11-01

    The eradication of errors regarding patients' identification is one of the main goals for safety improvement. As clinical laboratory intervenes in 70% of clinical decisions, laboratory safety is crucial in patient safety. We studied the number of Laboratory Information System (LIS) demographic data errors registered in our laboratory during one year. The laboratory attends a variety of inpatients and outpatients. The demographic data of outpatients is registered in the LIS, when they present to the laboratory front desk. The requests from the primary care centers (PCC) are made electronically by the general practitioner. A manual step is always done at the PCC to conciliate the patient identification number in the electronic request with the one in the LIS. Manual registration is done through hospital information system demographic data capture when patient's medical record number is registered in LIS. Laboratory report is always sent out electronically to the patient's electronic medical record. Daily, every demographic data in LIS is manually compared to the request form to detect potential errors. Fewer errors were committed when electronic order was used. There was great error variability between PCC when using the electronic order. LIS demographic data manual registration errors depended on patient origin and test requesting method. Even when using the electronic approach, errors were detected. There was a great variability between PCC even when using this electronic modality; this suggests that the number of errors is still dependent on the personnel in charge of the technology. © 2013.

  13. Development of early core anomaly detection system by using in-sodium microphone in JOYO. Fundamental characteristics test of in-sodium microphone in water and examination of improvement of detection accuracy

    International Nuclear Information System (INIS)

    Komai, Masafumi

    2001-07-01

    Fast reactor core anomalies can be detected in near real-time with acoustic sensors. An acoustic detection system senses an in-core anomaly immediately from the fast acoustic signals that propagate through the sodium coolant. One example of a detectable anomaly is sodium boiling due to local blockage in a sub-assembly; the slight change in background acoustic signals can be detected. A key advantage of the acoustic detector is that it can be located outside the core. The location of the anomaly in the core can be determined by correlating multiple acoustic signals. This report describes the testing and fundamental characteristics of a microphone suitable for use in the sodium coolant and examines methods to improve the system's S/N ratio. Testing in water confirmed that the in-sodium microphone has good impulse and wide band frequency responses. These tests used impulse and white noise signals that imitate acoustic signals from boiling sodium. Correlation processing of multiple microphone signals to improve S/N ratio is also described. (author)

  14. The use of image morphing to improve the detection of tumors in emission imaging

    International Nuclear Information System (INIS)

    Dykstra, C.; Greer, K.; Jaszczak, R.; Celler, A.

    1999-01-01

    Two of the limitations on the utility of SPECT and planar scintigraphy for the non-invasive detection of carcinoma are the small sizes of many tumors and the possible low contrast between tumor uptake and background. This is particularly true for breast imaging. Use of some form of image processing can improve the visibility of tumors which are at the limit of hardware resolution. Smoothing, by some form of image averaging, either during or post-reconstruction, is widely used to reduce noise and thereby improve the detectability of regions of elevated activity. However, smoothing degrades resolution and, by averaging together closely spaced noise, may make noise look like a valid region of increased uptake. Image morphing by erosion and dilation does not average together image values; it instead selectively removes small features and irregularities from an image without changing the larger features. Application of morphing to emission images has shown that it does not, therefore, degrade resolution and does not always degrade contrast. For these reasons it may be a better method of image processing for noise removal in some images. In this paper the authors present a comparison of the effects of smoothing and morphing using breast and liver studies

  15. Biomolecule-free, selective detection of o-diphenol and its derivatives with WS2/TiO2-based photoelectrochemical platform.

    Science.gov (United States)

    Ma, Weiguang; Wang, Lingnan; Zhang, Nan; Han, Dongxue; Dong, Xiandui; Niu, Li

    2015-01-01

    Herein, a novel photoelectrochemical platform with WS2/TiO2 composites as optoelectronic materials was designed for selective detection of o-diphenol and its derivatives without any biomolecule auxiliary. First, catechol was chosen as a model compound for the discrimination from resorcinol and hydroquinone; then several o-diphenol derivatives such as dopamine, caffeic acid, and catechin were also detected by employing this proposed photoelectrochemical sensor. Finally, the mechanism of such a selective detection has been elaborately explored. The excellent selectivity and high sensitivity should be attributed to two aspects: (i) chelate effect of adjacent double oxygen atoms in the o-diphenol with the Ti(IV) surface site to form a five/six-atom ring structure, which is considered as the key point for distinction and selective detection. (ii) This selected WS2/TiO2 composites with proper band level between WS2 and TiO2, which could make the photogenerated electron and hole easily separated and results in great improvement of sensitivity. By employing such a photoelectrochemical platform, practical samples including commercial clinic drugs and human urine samples have been successfully performed for dopamine detection. This biomolecule-free WS2/TiO2 based photoelectrochemical platform demonstrates excellent stability, reproducibility, remarkably convenient, and cost-effective advantages, as well as low detection limit (e.g., 0.32 μmol L(-1) for dopamine). It holds great promise to be applied for detection of o-diphenol kind species in environment and food fields.

  16. Improved sensitivity and limit-of-detection of lateral flow devices using spatial constrictions of the flow-path.

    Science.gov (United States)

    Katis, Ioannis N; He, Peijun J W; Eason, Robert W; Sones, Collin L

    2018-05-03

    We report on the use of a laser-direct write (LDW) technique that allows the fabrication of lateral flow devices with enhanced sensitivity and limit of detection. This manufacturing technique comprises the dispensing of a liquid photopolymer at specific regions of a nitrocellulose membrane and its subsequent photopolymerisation to create impermeable walls inside the volume of the membrane. These polymerised structures are intentionally designed to create fluidic channels which are constricted over a specific length that spans the test zone within which the sample interacts with pre-deposited reagents. Experiments were conducted to show how these constrictions alter the fluid flow rate and the test zone area within the constricted channel geometries. The slower flow rate and smaller test zone area result in the increased sensitivity and lowered limit of detection for these devices. We have quantified these via the improved performance of a C-Reactive Protein (CRP) sandwich assay on our lateral flow devices with constricted flow paths which demonstrate an improvement in its sensitivity by 62x and in its limit of detection by 30x when compared to a standard lateral flow CRP device. Crown Copyright © 2018. Published by Elsevier B.V. All rights reserved.

  17. 33 CFR 100.124 - Maggie Fischer Memorial Great South Bay Cross Bay Swim, Great South Bay, New York.

    Science.gov (United States)

    2010-07-01

    ... 33 Navigation and Navigable Waters 1 2010-07-01 2010-07-01 false Maggie Fischer Memorial Great South Bay Cross Bay Swim, Great South Bay, New York. 100.124 Section 100.124 Navigation and Navigable... NAVIGABLE WATERS § 100.124 Maggie Fischer Memorial Great South Bay Cross Bay Swim, Great South Bay, New York...

  18. An improved haemolytic plaque assay for the detection of cells secreting antibody to bacterial antigens

    DEFF Research Database (Denmark)

    Barington, T; Heilmann, C

    1992-01-01

    Recent advances in the development of conjugate polysaccharide vaccines for human use have stimulated interest in the use of assays detecting antibody-secreting cells (AbSC) with specificity for bacterial antigens. Here we present improved haemolytic plaque-forming cell (PFC) assays detecting Ab......SC with specificity for tetanus and diphtheria toxoid as well as for Haemophilus influenzae type b and pneumococcal capsular polysaccharides. These assays were found to be less time consuming, more economical and yielded 1.9-3.4-fold higher plaque numbers than traditional Jerne-type PFC assays. In the case of anti......-polysaccharide antibodies aggregation of secreted monomeric antibody (IgG) is critical for plaque formation and increases the avidity of binding to target cells....

  19. SU-E-T-310: Targeting Safety Improvements Through Analysis of Near-Miss Error Detection Points in An Incident Learning Database

    International Nuclear Information System (INIS)

    Novak, A; Nyflot, M; Sponseller, P; Howard, J; Logan, W; Holland, L; Jordan, L; Carlson, J; Ermoian, R; Kane, G; Ford, E; Zeng, J

    2014-01-01

    Purpose: Radiation treatment planning involves a complex workflow that can make safety improvement efforts challenging. This study utilizes an incident reporting system to identify detection points of near-miss errors, in order to guide our departmental safety improvement efforts. Previous studies have examined where errors arise, but not where they are detected or their patterns. Methods: 1377 incidents were analyzed from a departmental nearmiss error reporting system from 3/2012–10/2013. All incidents were prospectively reviewed weekly by a multi-disciplinary team, and assigned a near-miss severity score ranging from 0–4 reflecting potential harm (no harm to critical). A 98-step consensus workflow was used to determine origination and detection points of near-miss errors, categorized into 7 major steps (patient assessment/orders, simulation, contouring/treatment planning, pre-treatment plan checks, therapist/on-treatment review, post-treatment checks, and equipment issues). Categories were compared using ANOVA. Results: In the 7-step workflow, 23% of near-miss errors were detected within the same step in the workflow, while an additional 37% were detected by the next step in the workflow, and 23% were detected two steps downstream. Errors detected further from origination were more severe (p<.001; Figure 1). The most common source of near-miss errors was treatment planning/contouring, with 476 near misses (35%). Of those 476, only 72(15%) were found before leaving treatment planning, 213(45%) were found at physics plan checks, and 191(40%) were caught at the therapist pre-treatment chart review or on portal imaging. Errors that passed through physics plan checks and were detected by therapists were more severe than other errors originating in contouring/treatment planning (1.81 vs 1.33, p<0.001). Conclusion: Errors caught by radiation treatment therapists tend to be more severe than errors caught earlier in the workflow, highlighting the importance of safety

  20. New Trends in Impedimetric Biosensors for the Detection of Foodborne Pathogenic Bacteria

    Science.gov (United States)

    Wang, Yixian; Ye, Zunzhong; Ying, Yibin

    2012-01-01

    The development of a rapid, sensitive, specific method for the foodborne pathogenic bacteria detection is of great importance to ensure food safety and security. In recent years impedimetric biosensors which integrate biological recognition technology and impedance have gained widespread application in the field of bacteria detection. This paper presents an overview on the progress and application of impedimetric biosensors for detection of foodborne pathogenic bacteria, particularly the new trends in the past few years, including the new specific bio-recognition elements such as bacteriophage and lectin, the use of nanomaterials and microfluidics techniques. The applications of these new materials or techniques have provided unprecedented opportunities for the development of high-performance impedance bacteria biosensors. The significant developments of impedimetric biosensors for bacteria detection in the last five years have been reviewed according to the classification of with or without specific bio-recognition element. In addition, some microfluidics systems, which were used in the construction of impedimetric biosensors to improve analytical performance, are introduced in this review. PMID:22737018

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

    Science.gov (United States)

    Zhong, Jiandan; Lei, Tao; Yao, Guangle

    2017-11-24

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

  2. Improved detection of endoparasite DNA in soil sample PCR by the use of anti-inhibitory substances.

    Science.gov (United States)

    Krämer, F; Vollrath, T; Schnieder, T; Epe, C

    2002-09-26

    Although there have been numerous microbial examinations of soil for the presence of human pathogenic developmental parasite stages of Ancylostoma caninum and Toxocara canis, molecular techniques (e.g. DNA extraction, purification and subsequent PCR) have scarcely been applied. Here, DNA preparations of soil samples artificially contaminated with genomic DNA or parasite eggs were examined by PCR. A. caninum and T. canis-specific primers based on the ITS-2 sequence were used for amplification. After the sheer DNA preparation a high content of PCR-interfering substances was still detectable. Subsequently, two different inhibitors of PCR-interfering agents (GeneReleaser, Bioventures Inc. and Maximator, Connex GmbH) were compared in PCR. Both substances increased PCR sensitivity greatly. However, comparison of the increase in sensitivity achieved with the two compounds demonstrated the superiority of Maximator, which enhanced sensitivity to the point of permitting positive detection of a single A. caninum egg and three T. canis eggs in a soil sample. This degree of sensitivity could not be achieved with GeneReleaser for either parasite Furthermore, Maximator not only increased sensitivity; it also cost less, required less time and had a lower risk of contamination. Future applications of molecular methods in epidemiological examinations of soil samples are discussed/elaborated.

  3. Use of rapid-scan EPR to improve detection sensitivity for spin-trapped radicals.

    Science.gov (United States)

    Mitchell, Deborah G; Rosen, Gerald M; Tseitlin, Mark; Symmes, Breanna; Eaton, Sandra S; Eaton, Gareth R

    2013-07-16

    The short lifetime of superoxide and the low rates of formation expected in vivo make detection by standard continuous wave (CW) electron paramagnetic resonance (EPR) challenging. The new rapid-scan EPR method offers improved sensitivity for these types of samples. In rapid-scan EPR, the magnetic field is scanned through resonance in a time that is short relative to electron spin relaxation times, and data are processed to obtain the absorption spectrum. To validate the application of rapid-scan EPR to spin trapping, superoxide was generated by the reaction of xanthine oxidase and hypoxanthine with rates of 0.1-6.0 μM/min and trapped with 5-tert-butoxycarbonyl-5-methyl-1-pyrroline-N-oxide (BMPO). Spin trapping with BMPO to form the BMPO-OOH adduct converts the very short-lived superoxide radical into a more stable spin adduct. There is good agreement between the hyperfine splitting parameters obtained for BMPO-OOH by CW and rapid-scan EPR. For the same signal acquisition time, the signal/noise ratio is >40 times higher for rapid-scan than for CW EPR. Rapid-scan EPR can detect superoxide produced by Enterococcus faecalis at rates that are too low for detection by CW EPR. Copyright © 2013 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  4. The Great Depression: A Textbook Case of Problems with American History Textbooks.

    Science.gov (United States)

    Miller, Steven L.; Rose, Stephen A.

    1983-01-01

    The 16 US history textbooks reviewed failed to incorporate economists' research on the causes of the Great Depression and consistently presented information that the economics profession has rejected. Strategies that social studies educators might adopt to improve the quality of economic analysis in textbooks is suggested. (Author/RM)

  5. Improved prenatal detection of chromosomal anomalies

    DEFF Research Database (Denmark)

    Frøslev-Friis, Christina; Hjort-Pedersen, Karina; Henriques, Carsten U

    2011-01-01

    Prenatal screening for karyotype anomalies takes place in most European countries. In Denmark, the screening method was changed in 2005. The aim of this study was to study the trends in prevalence and prenatal detection rates of chromosome anomalies and Down syndrome (DS) over a 22-year period....

  6. Loop-mediated isothermal amplification (LAMP) as an alternative to PCR: A rapid on-site detection of gene doping.

    Science.gov (United States)

    Salamin, Olivier; Kuuranne, Tiia; Saugy, Martial; Leuenberger, Nicolas

    2017-11-01

    Innovation in medical research has been diverted at multiple occasions to enhance human performance. The predicted great progress in gene therapy has raised some concerns regarding its misuse in the world of sports (gene doping) for several years now. Even though there is no evidence that gene doping has ever been used in sports, the continuous improvement of gene therapy techniques increases the likelihood of abuse. Therefore, since 2004, efforts have been invested by the anti-doping community and WADA for the development of detection methods. Several nested PCR and qPCR-based strategies exploiting the absence of introns in the transgenic DNA have been proposed for the long-term detection of transgene in blood. Despite their great sensitivity, those protocols are hampered by limitations of the techniques that can be cumbersome and costly. The purpose of this perspective is to describe a new approach based on loop-mediated isothermal amplification (LAMP) for the detection of gene doping. This protocol enables a rapid and simple method to amplify nucleic acids with a high sensitivity and specificity and with a simple visual detection of the results. LAMP is already being used in clinical application for the detection of viruses or mutations. Therefore, this technique has the potential to be further developed for the detection of foreign genetic material in elite athletes. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  7. "Cough officer screening" improves detection of pulmonary tuberculosis in hospital in-patients

    Directory of Open Access Journals (Sweden)

    Wen Jen-Ho

    2010-05-01

    Full Text Available Abstract Background Current tuberculosis (TB reporting protocols are insufficient to achieve the goals established by the Stop TB partnership. Some countries have recommended implementation of active case finding program. We assessed the effect of Cough Officer Screening (an active screening system on the rate of TB detection and health care system delays over the course of four years. Methods Patients who were hospitalized at the Changhua Christian Hospital (Changhua, Taiwan were enrolled from September 2004 to July 2006 (Stage I and August 2006 to August 2008 (Stage II. Stage II was implemented after a Plan-Do-Check-Act (PDCA cycle analysis indicated that we should exclude ICU and paediatric patients. Results In Stage I, our COS system alerted physicians to 19,836 patients, and 7,998 were examined. 184 of these 7,998 patients (2.3% had TB. Among these 184 patients, 142 (77.2% were examined for TB before COS alarming and 42 were diagnosed after COS alarming. In Stage II, a total of 11,323 patients were alerted by the COS system. Among them, 6,221 patients were examined by physicians, and 125 of these patients (2.0% had TB. Among these 125 patients, 113 (90.4% were examined for TB before COS alarming and 12 were diagnosed after COS alarming. The median time from COS alarm to clinical action was significantly less (p = 0.041 for Stage I (1 day; range: 0-16 days than for Stage II (2 days; range: 0-10 days. Conclusion Our COS system improves detection of TB by reducing the delay from infection to diagnosis. Modifications of scope may be needed to improve cost-effectiveness.

  8. An Improved Opposition-Based Learning Particle Swarm Optimization for the Detection of SNP-SNP Interactions

    Science.gov (United States)

    Shang, Junliang; Sun, Yan; Li, Shengjun; Liu, Jin-Xing; Zheng, Chun-Hou; Zhang, Junying

    2015-01-01

    SNP-SNP interactions have been receiving increasing attention in understanding the mechanism underlying susceptibility to complex diseases. Though many works have been done for the detection of SNP-SNP interactions, the algorithmic development is still ongoing. In this study, an improved opposition-based learning particle swarm optimization (IOBLPSO) is proposed for the detection of SNP-SNP interactions. Highlights of IOBLPSO are the introduction of three strategies, namely, opposition-based learning, dynamic inertia weight, and a postprocedure. Opposition-based learning not only enhances the global explorative ability, but also avoids premature convergence. Dynamic inertia weight allows particles to cover a wider search space when the considered SNP is likely to be a random one and converges on promising regions of the search space while capturing a highly suspected SNP. The postprocedure is used to carry out a deep search in highly suspected SNP sets. Experiments of IOBLPSO are performed on both simulation data sets and a real data set of age-related macular degeneration, results of which demonstrate that IOBLPSO is promising in detecting SNP-SNP interactions. IOBLPSO might be an alternative to existing methods for detecting SNP-SNP interactions. PMID:26236727

  9. A Time-Domain Structural Damage Detection Method Based on Improved Multiparticle Swarm Coevolution Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Shao-Fei Jiang

    2014-01-01

    Full Text Available Optimization techniques have been applied to structural health monitoring and damage detection of civil infrastructures for two decades. The standard particle swarm optimization (PSO is easy to fall into the local optimum and such deficiency also exists in the multiparticle swarm coevolution optimization (MPSCO. This paper presents an improved MPSCO algorithm (IMPSCO firstly and then integrates it with Newmark’s algorithm to localize and quantify the structural damage by using the damage threshold proposed. To validate the proposed method, a numerical simulation and an experimental study of a seven-story steel frame were employed finally, and a comparison was made between the proposed method and the genetic algorithm (GA. The results show threefold: (1 the proposed method not only is capable of localization and quantification of damage, but also has good noise-tolerance; (2 the damage location can be accurately detected using the damage threshold proposed in this paper; and (3 compared with the GA, the IMPSCO algorithm is more efficient and accurate for damage detection problems in general. This implies that the proposed method is applicable and effective in the community of damage detection and structural health monitoring.

  10. Improved Detection of Vowel Envelope Frequency Following Responses Using Hotelling's T2 Analysis.

    Science.gov (United States)

    Vanheusden, Frederique J; Bell, Steven L; Chesnaye, Michael A; Simpson, David M

    2018-05-11

    Objective detection of brainstem responses to natural speech stimuli is an important tool for the evaluation of hearing aid fitting, especially in people who may not be able to respond reliably in behavioral tests. Of particular interest is the envelope frequency following response (eFFR), which refers to the EEG response at the stimulus' fundamental frequency (and its harmonics), and here in particular to the response to natural spoken vowel sounds. This article introduces the frequency-domain Hotelling's T (HT2) method for eFFR detection. This method was compared, in terms of sensitivity in detecting eFFRs at the fundamental frequency (HT2_F0), to two different single-channel frequency domain methods (F test on Fourier analyzer (FA) amplitude spectra [FA-F-Test] and magnitude-squared coherence [MSC]) in detecting envelope following responses to natural vowel stimuli in simulated data and EEG data from normal-hearing subjects. Sensitivity was assessed based on the number of detections and the time needed to detect a response for a false-positive rate of 5%. The study also explored whether a single-channel, multifrequency HT2 (HT2_3F) and a multichannel, multifrequency HT2 (HT2_MC) could further improve response detection. Four repeated words were presented sequentially at 70 dB SPL LAeq through ER-2 insert earphones. The stimuli consisted of a prolonged vowel in a /hVd/ structure (where V represents different vowel sounds). Each stimulus was presented over 440 sweeps (220 condensation and 220 rarefaction). EEG data were collected from 12 normal-hearing adult participants. After preprocessing and artifact removal, eFFR detection was compared between the algorithms. For the simulation study, simulated EEG signals were generated by adding random noise at multiple signal to noise ratios (SNRs; 0 to -60dB) to the auditory stimuli as well as to a single sinusoid at the fluctuating and flattened fundamental frequency (f0). For each SNR, 1000 sets of 440 simulated epochs

  11. Antifoulant (butyltin and copper) concentrations in sediments from the Great Barrier Reef World Heritage Area, Australia

    International Nuclear Information System (INIS)

    Haynes, David; Loong, Dominica

    2002-01-01

    Antifoulant concentrations are generally low in the Great Barrier Reef, although ship grounding sites present a previously unidentified significant source of antifoulant pollutants in the Great Barrier Reef. - Antifoulant concentrations were determined in marine sediments collected from commercial harbours, marinas, mooring locations on mid-shelf continental islands, and outer reef sites in four regions within the Great Barrier Reef World Heritage Area in 1999. Highest copper concentrations were present in sediments collected from commercial harbour sampling sites (28-233 μg Cu g -1 dry wt.). In contrast, copper concentrations in sediments collected from boat mooring sites on mid-shelf continental islands and outer reef sites were at background concentrations (i.e. -1 dry wt.). Butyltin was only detectable in four of the 42 sediments sampled for analysis, and was only present in sediments collected from commercial harbours (18-1275 ng Sn g -1 dry wt.) and from marinas (4-5 ng Sn g -1 dry wt.). The detection of tributyltin at marina sites implies that this antifoulant may continue to be used illegally on the hulls of smaller recreational vessels. Sediment samples were also collected opportunistically from the site of a 22,000 t cargo ship grounding in May 1999 at Heath Reef, in the far northern Great Barrier Reef. Butyltin concentrations were grossly elevated (660-340,000 ng Sn g -1 dry wt.) at the grounding site. The impact of residual antifoulants at large ship grounding sites should be recognised as a significant, long-term environmental problem unless antfoulant clean-up strategies are undertaken

  12. Balanced detection for self-mixing interferometry to improve signal-to-noise ratio

    Science.gov (United States)

    Zhao, Changming; Norgia, Michele; Li, Kun

    2018-01-01

    We apply balanced detection to self-mixing interferometry for displacement and vibration measurement, using two photodiodes for implementing a differential acquisition. The method is based on the phase opposition of the self-mixing signal measured between the two laser diode facet outputs. The balanced signal obtained by enlarging the self-mixing signal, also by canceling of the common-due noises mainly due to disturbances on laser supply and transimpedance amplifier. Experimental results demonstrate the signal-to-noise ratio significantly improves, with almost twice signals enhancement and more than half noise decreasing. This method allows for more robust, longer-distance measurement systems, especially using fringe-counting.

  13. Great Expectations

    NARCIS (Netherlands)

    Dickens, Charles

    2005-01-01

    One of Dickens's most renowned and enjoyable novels, Great Expectations tells the story of Pip, an orphan boy who wishes to transcend his humble origins and finds himself unexpectedly given the opportunity to live a life of wealth and respectability. Over the course of the tale, in which Pip

  14. Dual-focus Magnification, High-Definition Endoscopy Improves Pathology Detection in Direct-to-Test Diagnostic Upper Gastrointestinal Endoscopy.

    Science.gov (United States)

    Bond, Ashley; Burkitt, Michael D; Cox, Trevor; Smart, Howard L; Probert, Chris; Haslam, Neil; Sarkar, Sanchoy

    2017-03-01

    In the UK, the majority of diagnostic upper gastrointestinal (UGI) endoscopies are a result of direct-to-test referral from the primary care physician. The diagnostic yield of these tests is relatively low, and the burden high on endoscopy services. Dual-focus magnification, high-definition endoscopy is expected to improve detection and classification of UGI mucosal lesions and also help minimize biopsies by allowing better targeting. This is a retrospective study of patients attending for direct-to-test UGI endoscopy from January 2015 to June 2015. The primary outcome of interest was the identification of significant pathology. Detection of significant pathology was modelled using logistic regression. 500 procedures were included. The mean age of patients was 61.5 (±15.6) years; 60.8% of patients were female. Ninety-four gastroscopies were performed using dual-focus magnification high-definition endoscopy. Increasing age, male gender, type of endoscope, and type of operator were all identified as significant factors influencing the odds of detecting significant mucosal pathology. Use of dual-focus magnification, high-definition endoscopy was associated with an odds ratio of 1.87 (95%CI 1.11-3.12) favouring the detection of significant pathology. Subsequent analysis suggested that the increased detection of pathology during dual-focus magnification, high-definition endoscopy also influenced patient follow-up and led to a 3.0 fold (p=0.04) increase in the proportion of patients entered into an UGI endoscopic surveillance program. Dual-focus magnification, high-definition endoscopy improved the diagnostic yield for significant mucosal pathology in patients referred for direct-to-test endoscopy. If this finding is recapitulated elsewhere it will have substantial impact on the provision of UGI endoscopic services.

  15. Camera trap arrays improve detection probability of wildlife: Investigating study design considerations using an empirical dataset.

    Science.gov (United States)

    O'Connor, Kelly M; Nathan, Lucas R; Liberati, Marjorie R; Tingley, Morgan W; Vokoun, Jason C; Rittenhouse, Tracy A G

    2017-01-01

    Camera trapping is a standard tool in ecological research and wildlife conservation. Study designs, particularly for small-bodied or cryptic wildlife species often attempt to boost low detection probabilities by using non-random camera placement or baited cameras, which may bias data, or incorrectly estimate detection and occupancy. We investigated the ability of non-baited, multi-camera arrays to increase detection probabilities of wildlife. Study design components were evaluated for their influence on wildlife detectability by iteratively parsing an empirical dataset (1) by different sizes of camera arrays deployed (1-10 cameras), and (2) by total season length (1-365 days). Four species from our dataset that represented a range of body sizes and differing degrees of presumed detectability based on life history traits were investigated: white-tailed deer (Odocoileus virginianus), bobcat (Lynx rufus), raccoon (Procyon lotor), and Virginia opossum (Didelphis virginiana). For all species, increasing from a single camera to a multi-camera array significantly improved detection probability across the range of season lengths and number of study sites evaluated. The use of a two camera array increased survey detection an average of 80% (range 40-128%) from the detection probability of a single camera across the four species. Species that were detected infrequently benefited most from a multiple-camera array, where the addition of up to eight cameras produced significant increases in detectability. However, for species detected at high frequencies, single cameras produced a season-long (i.e, the length of time over which cameras are deployed and actively monitored) detectability greater than 0.75. These results highlight the need for researchers to be critical about camera trap study designs based on their intended target species, as detectability for each focal species responded differently to array size and season length. We suggest that researchers a priori identify

  16. Camera trap arrays improve detection probability of wildlife: Investigating study design considerations using an empirical dataset.

    Directory of Open Access Journals (Sweden)

    Kelly M O'Connor

    Full Text Available Camera trapping is a standard tool in ecological research and wildlife conservation. Study designs, particularly for small-bodied or cryptic wildlife species often attempt to boost low detection probabilities by using non-random camera placement or baited cameras, which may bias data, or incorrectly estimate detection and occupancy. We investigated the ability of non-baited, multi-camera arrays to increase detection probabilities of wildlife. Study design components were evaluated for their influence on wildlife detectability by iteratively parsing an empirical dataset (1 by different sizes of camera arrays deployed (1-10 cameras, and (2 by total season length (1-365 days. Four species from our dataset that represented a range of body sizes and differing degrees of presumed detectability based on life history traits were investigated: white-tailed deer (Odocoileus virginianus, bobcat (Lynx rufus, raccoon (Procyon lotor, and Virginia opossum (Didelphis virginiana. For all species, increasing from a single camera to a multi-camera array significantly improved detection probability across the range of season lengths and number of study sites evaluated. The use of a two camera array increased survey detection an average of 80% (range 40-128% from the detection probability of a single camera across the four species. Species that were detected infrequently benefited most from a multiple-camera array, where the addition of up to eight cameras produced significant increases in detectability. However, for species detected at high frequencies, single cameras produced a season-long (i.e, the length of time over which cameras are deployed and actively monitored detectability greater than 0.75. These results highlight the need for researchers to be critical about camera trap study designs based on their intended target species, as detectability for each focal species responded differently to array size and season length. We suggest that researchers a priori

  17. A CNN-Based Method of Vehicle Detection from Aerial Images Using Hard Example Mining

    Directory of Open Access Journals (Sweden)

    Yohei Koga

    2018-01-01

    Full Text Available Recently, deep learning techniques have had a practical role in vehicle detection. While much effort has been spent on applying deep learning to vehicle detection, the effective use of training data has not been thoroughly studied, although it has great potential for improving training results, especially in cases where the training data are sparse. In this paper, we proposed using hard example mining (HEM in the training process of a convolutional neural network (CNN for vehicle detection in aerial images. We applied HEM to stochastic gradient descent (SGD to choose the most informative training data by calculating the loss values in each batch and employing the examples with the largest losses. We picked 100 out of both 500 and 1000 examples for training in one iteration, and we tested different ratios of positive to negative examples in the training data to evaluate how the balance of positive and negative examples would affect the performance. In any case, our method always outperformed the plain SGD. The experimental results for images from New York showed improved performance over a CNN trained in plain SGD where the F1 score of our method was 0.02 higher.

  18. Improved detection of breast cancer on FDG-PET cancer screening using breast positioning device

    International Nuclear Information System (INIS)

    Kaida, Hayato; Ishibashi, Masatoshi; Fujii, Teruhiko; Kurata, Seiji; Ogo, Etsuyo; Hayabuchi, Naofumi; Tanaka, Maki

    2008-01-01

    The aim of this study was to investigate the detection rate of breast cancer by positron emission tomography cancer screening using a breast positioning device. Between January 2004 and January 2006, 1,498 healthy asymptomatic individuals underwent cancer screening by fluorine-18 fluorodeoxyglucose positron emission tomography (FDG-PET) at our institution; 660 of 1498 asymptomatic healthy women underwent breast PET imaging in the prone position using the breast positioning device to examine the mammary glands in addition to whole-body PET imaging. All subjects that showed abnormal 18 F-FDG uptake in the mammary glands were referred for further examination or surgery at our institution or a local hospital. Our data were compared with the histopathological findings or findings of other imaging modalities in our institution and replies from the doctors at another hospital. Of the 660 participants, 7 (1.06%) were found to have breast cancers at a curable stage. All the seven cancers were detected by breast PET imaging, but only five of these were detected by whole-body PET imaging; the other two were detected by breast PET imaging using the breast positioning device. In cancer screening, prone breast imaging using a positioning device may help to improve the detection rate of breast cancer. However, overall cancer including mammography and ultrasonography screening should be performed to investigate the false-negative cases and reduce false-positive cases. The effectiveness of prone breast PET imaging in cancer screening should be investigated using a much larger number of cases in the near future. (author)

  19. Selectivity improvement of positive photoionization ion mobility spectrometry for rapid detection of organophosphorus pesticides by switching dopant concentration.

    Science.gov (United States)

    Zhou, Qinghua; Li, Jia; Wang, Bin; Wang, Shuang; Li, Haiyang; Chen, Jinyuan

    2018-01-01

    Ion mobility spectrometry (IMS) opened a potential avenue for the rapid detection of organophosphorus pesticides (OPPs), though an improved selectivity of stand-alone IMS was still in high demand. In this study, a stand-alone positive photoionization ion mobility spectrometry (PP-IMS) apparatus was constructed for the rapid detection of OPPs with acetone as dopant. The photoionization of acetone molecules was induced by the ultraviolet irradiation to produce the reactant ions (Ac) 2 H + , which were employed to ionize the OPPs including fenthion, imidan, phosphamidon, dursban, dimethoate and isocarbophos via the proton transfer reaction. Due to the difference in proton affinity, the tested OPPs exhibited the different dopant-dependent manners. Based on this observation, the switching of dopant concentration was implemented to improve the selectivity of PP-IMS for OPPs detection. For instance, a mixture of fenthion, dursban and dimethoate was tested. By switching the concentration of doped acetone from 0.07 to 2.33 to 19.94mgL -1 , the ion peaks of fenthion and dursban were inhibited in succession, achieving the selective detection of dimethoate at last. In addition, another mixture of imidan and phosphamidon was initially detected by PP-IMS with a dose of 0.07mgL -1 acetone, indicating that their ion peaks were severely overlapped; when the concentration of doped acetone was switched to 19.94mgL -1 , the inhibition of imidan signals promised the accurate identification of phosphamidon in mixture. Finally, the PP-IMS in combination of switching dopant concentration was applied to detect the mixed fenthion, dursban and dimethoate in Chinese cabbage, demonstrating the applicability of proposed method to real samples. Copyright © 2017. Published by Elsevier B.V.

  20. The great intimidators.

    Science.gov (United States)

    Kramer, Roderick M

    2006-02-01

    After Disney's Michael Eisner, Miramax's Harvey Weinstein, and Hewlett-Packard's Carly Fiorina fell from their heights of power, the business media quickly proclaimed thatthe reign of abrasive, intimidating leaders was over. However, it's premature to proclaim their extinction. Many great intimidators have done fine for a long time and continue to thrive. Their modus operandi runs counter to a lot of preconceptions about what it takes to be a good leader. They're rough, loud, and in your face. Their tactics include invading others' personal space, staging tantrums, keeping people guessing, and possessing an indisputable command of facts. But make no mistake--great intimidators are not your typical bullies. They're driven by vision, not by sheer ego or malice. Beneath their tough exteriors and sharp edges are some genuine, deep insights into human motivation and organizational behavior. Indeed, these leaders possess political intelligence, which can make the difference between paralysis and successful--if sometimes wrenching--organizational change. Like socially intelligent leaders, politically intelligent leaders are adept at sizing up others, but they notice different things. Those with social intelligence assess people's strengths and figure out how to leverage them; those with political intelligence exploit people's weaknesses and insecurities. Despite all the obvious drawbacks of working under them, great intimidators often attract the best and brightest. And their appeal goes beyond their ability to inspire high performance. Many accomplished professionals who gravitate toward these leaders want to cultivate a little "inner intimidator" of their own. In the author's research, quite a few individuals reported having positive relationships with intimidating leaders. In fact, some described these relationships as profoundly educational and even transformational. So before we throw out all the great intimidators, the author argues, we should stop to consider what

  1. An integrated leak detection system for the ALMR steam generator

    International Nuclear Information System (INIS)

    Dayal, Y.; Gaubatz, D.C.; Wong, K.K.; Greene, D.A.

    1995-01-01

    The steam generator (SG) of the Advanced Liquid Metal Reactor (ALMR) system serves as a heat exchanger between the shell side secondary loop hot liquid sodium and the tube side water/steam mixture. A leak in the tube will result in the injection of the higher pressure water/steam into the sodium and cause an exothermic sodium-water reaction. An initial small leak (less than 1 gm/sec) can escalate into an intermediate size leak in a relatively short time by self enlargement of the original flaw and by initiating leaks in neighboring tubes. If not stopped, complete rupture of one or more tubes can cause injection rates of thousands of gm/sec and result in the over pressurization of the secondary loop rupture disk and dumping of the sodium to relieve pressure. The down time associated with severe sodium-water reaction damage has great adverse economic consequence. An integrated leak detection system (ILDS) has been developed which utilizes both chemical and acoustic sensors for improved leak detection. The system provides SG leak status to the reactor operator and is reliable enough to trigger automatic control action to protect the SG. The ILDS chemical subsystem uses conventional in-sodium and cover gas hydrogen detectors and incorporates knowledge based effects due to process parameters for improved reliability. The ILDS acoustic subsystem uses an array of acoustic sensors and incorporates acoustic beamforming technology for highly reliable and accurate leak identification and location. The new ILDS combines the small leak detection capability of the chemical system with the reliability and rapid detection/location capability of the acoustic system to provide a significantly improved level of protection for the SG over a wide range of operation conditions. (author)

  2. Comparative Analysis of Tannins in the Rhizomes of Great Burnet (Sanguisorba officinalis L.)

    OpenAIRE

    Mukhametgaliev N.R.; Idrisova G.I.; Gilazieva G.Z.

    2015-01-01

    Quantitative analysis of the content of tannins in the rhizomes of great burnet (Sanguisorba officinalis L.) was performed using Leventhal’s permanganometric method, its Kursanov's modification, and spectrophotometry. Advantages and disadvantages of the methods used were discussed to determine the quantitative content of tannins in the active parts of different plants. New locations of S. officinalis populations in various regions of the Republic of Tatarstan were detected. The discovered pop...

  3. Improvement of a real-time RT-PCR assay for the detection of enterovirus RNA

    Directory of Open Access Journals (Sweden)

    Bruynseels Peggy

    2009-07-01

    Full Text Available Abstract We describe an improvement of an earlier reported real-time RT-PCR assay for the detection of enterovirus RNA, based on the 5' exonuclease digestion of a dual-labeled fluorogenic probe by Taq DNA polymerase. A different extraction method, real-time RT-PCR instrument and primer set were evaluated. Our data show that the optimized assay yields a higher sensitivity and reproducibility and resulted in a significant reduced hands-on time per sample.

  4. Improved Bi Film Wrapped Single Walled Carbon Nanotubes for Ultrasensitive Electrochemical Detection of Trace Cr(VI)

    Science.gov (United States)

    Zhou, Shilin; Xue, Zi-Ling; Xu, Lina; Gu, Yingying; Miao, Yuqing

    2014-01-01

    We report here the successful fabrication of an improved Bi film wrapped single walled carbon nanotubes modified glassy carbon electrode (Bi/SWNTs/GCE) as a highly sensitive platform for ultratrace Cr(VI) detection through catalytic adsorptive cathodic stripping voltammetry (AdCSV). The introduction of negatively charged SWNTs extraordinarily decreased the size of Bi particles to nanoscale due to electrostatic interaction which made Bi(III) cations easily attracted onto the surface of SWNTs in good order, leading to higher quality of Bi film deposition. The obtained Bi/SWNTs composite was well characterized with electrochemical impedance spectroscopy (EIS), scanning electron microscopy (SEM), the static water contact angle and the voltammetric measurements. The results demonstrates the improvements in the quality of Bi film deposited on the surface of SWNTs such as faster speed of electron transfer, more uniform and smoother morphology, better hydrophilicity and higher stripping signal. Using diethylene triaminepentaacetic acid (DTPA) as complexing ligand, the fabricated electrode displays a well-defined and highly sensitive peak for the reduction of Cr(III)-DTPA complex at −1.06 V (vs. Ag/AgCl) with a linear concentration range of 0–25 nM and a fairly low detection limit of 0.036 nM. No interference was found in the presence of coexisting ions, and good recoveries were achieved for the analysis of a river sample. In comparison to previous approaches using Bi film modified GCE, the newly designed electrode exhibits better reproducibility and repeatability towards aqueous detection of trace Cr(VI) and appears to be very promising as the basis of a highly sensitive and selective voltammetric procedure for Cr(VI) detection at trace level in real samples. PMID:24771881

  5. Delayed-Phase Cone-Beam CT Improves Detectability of Intrahepatic Cholangiocarcinoma During Conventional Transarterial Chemoembolization

    International Nuclear Information System (INIS)

    Schernthaner, Ruediger Egbert; Lin, MingDe; Duran, Rafael; Chapiro, Julius; Wang, Zhijun; Geschwind, Jean-François

    2015-01-01

    PurposeTo evaluate the detectability of intrahepatic cholangiocarcinoma (ICC) on dual-phase cone-beam CT (DPCBCT) during conventional transarterial chemoembolization (cTACE) compared to that of digital subtraction angiography (DSA) with respect to pre-procedure contrast-enhanced magnetic resonance imaging (CE-MRI) of the liver.MethodsThis retrospective study included 17 consecutive patients (10 male, mean age 64) with ICC who underwent pre-procedure CE-MRI of the liver, and DSA and DPCBCT (early-arterial phase (EAP) and delayed-arterial phase (DAP)) just before cTACE. The visibility of each ICC lesion was graded by two radiologists on a three-rank scale (complete, partial, and none) on DPCBCT and DSA images, and then compared to pre-procedure CE-MRI.ResultsOf 61 ICC lesions, only 45.9 % were depicted by DSA, whereas EAP- and DAP-CBCT yielded a significantly higher detectability rate of 73.8 % and 93.4 %, respectively (p < 0.01). Out of the 33 lesions missed on DSA, 18 (54.5 %) and 30 (90.9 %) were revealed on EAP- and DAP-CBCT images, respectively. DSA depicted only one lesion that was missed by DPCBCT due to streak artifacts caused by a prosthetic mitral valve. DAP-CBCT identified significantly more lesions than EAP-CBCT (p < 0.01). Conversely, EAP-CBCT did not detect lesions missed by DAP-CBCT. For complete lesion visibility, DAP-CBCT yielded significantly higher detectability (78.7 %) compared to EAP (31.1 %) and DSA (21.3 %) (p < 0.01).ConclusionDPCBCT, and especially the DAP-CBCT, significantly improved the detectability of ICC lesions during cTACE compared to DSA. We recommend the routine use of DAP-CBCT in patients with ICC for per-procedure detectability and treatment planning in the setting of TACE

  6. Delayed-Phase Cone-Beam CT Improves Detectability of Intrahepatic Cholangiocarcinoma During Conventional Transarterial Chemoembolization

    Energy Technology Data Exchange (ETDEWEB)

    Schernthaner, Ruediger Egbert [The Johns Hopkins Hospital, Russell H. Morgan Department of Radiology and Radiological Science, Division of Vascular and Interventional Radiology (United States); Lin, MingDe [Philips Research North America, Ultrasound and Interventions (United States); Duran, Rafael; Chapiro, Julius; Wang, Zhijun; Geschwind, Jean-François, E-mail: jfg@jhmi.edu [The Johns Hopkins Hospital, Russell H. Morgan Department of Radiology and Radiological Science, Division of Vascular and Interventional Radiology (United States)

    2015-08-15

    PurposeTo evaluate the detectability of intrahepatic cholangiocarcinoma (ICC) on dual-phase cone-beam CT (DPCBCT) during conventional transarterial chemoembolization (cTACE) compared to that of digital subtraction angiography (DSA) with respect to pre-procedure contrast-enhanced magnetic resonance imaging (CE-MRI) of the liver.MethodsThis retrospective study included 17 consecutive patients (10 male, mean age 64) with ICC who underwent pre-procedure CE-MRI of the liver, and DSA and DPCBCT (early-arterial phase (EAP) and delayed-arterial phase (DAP)) just before cTACE. The visibility of each ICC lesion was graded by two radiologists on a three-rank scale (complete, partial, and none) on DPCBCT and DSA images, and then compared to pre-procedure CE-MRI.ResultsOf 61 ICC lesions, only 45.9 % were depicted by DSA, whereas EAP- and DAP-CBCT yielded a significantly higher detectability rate of 73.8 % and 93.4 %, respectively (p < 0.01). Out of the 33 lesions missed on DSA, 18 (54.5 %) and 30 (90.9 %) were revealed on EAP- and DAP-CBCT images, respectively. DSA depicted only one lesion that was missed by DPCBCT due to streak artifacts caused by a prosthetic mitral valve. DAP-CBCT identified significantly more lesions than EAP-CBCT (p < 0.01). Conversely, EAP-CBCT did not detect lesions missed by DAP-CBCT. For complete lesion visibility, DAP-CBCT yielded significantly higher detectability (78.7 %) compared to EAP (31.1 %) and DSA (21.3 %) (p < 0.01).ConclusionDPCBCT, and especially the DAP-CBCT, significantly improved the detectability of ICC lesions during cTACE compared to DSA. We recommend the routine use of DAP-CBCT in patients with ICC for per-procedure detectability and treatment planning in the setting of TACE.

  7. Improvement in Detection of Wrong-Patient Errors When Radiologists Include Patient Photographs in Their Interpretation of Portable Chest Radiographs.

    Science.gov (United States)

    Tridandapani, Srini; Olsen, Kevin; Bhatti, Pamela

    2015-12-01

    This study was conducted to determine whether facial photographs obtained simultaneously with radiographs improve radiologists' detection rate of wrong-patient errors, when they are explicitly asked to include the photographs in their evaluation. Radiograph-photograph combinations were obtained from 28 patients at the time of portable chest radiography imaging. From these, pairs of radiographs were generated. Each unique pair consisted of one new and one old (comparison) radiograph. Twelve pairs of mismatched radiographs (i.e., pairs containing radiographs of different patients) were also generated. In phase 1 of the study, 5 blinded radiologist observers were asked to interpret 20 pairs of radiographs without the photographs. In phase 2, each radiologist interpreted another 20 pairs of radiographs with the photographs. Radiologist observers were not instructed about the purpose of the photographs but were asked to include the photographs in their review. The detection rate of mismatched errors was recorded along with the interpretation time for each session for each observer. The two-tailed Fisher exact test was used to evaluate differences in mismatch detection rates between the two phases. A p value of error detection rates without (0/20 = 0%) and with (17/18 = 94.4%) photographs were different (p = 0.0001). The average interpretation times for the set of 20 radiographs were 26.45 (SD 8.69) and 20.55 (SD 3.40) min, for phase 1 and phase 2, respectively (two-tailed Student t test, p = 0.1911). When radiologists include simultaneously obtained photographs in their review of portable chest radiographs, there is a significant improvement in the detection of labeling errors. No statistically significant difference in interpretation time was observed. This may lead to improved patient safety without affecting radiologists' throughput.

  8. Improved detection of calcium-binding proteins in polyacrylamide gels

    International Nuclear Information System (INIS)

    Anthony, F.A.; Babitch, J.A.

    1984-01-01

    The authors refined the method of Schibeci and Martonosi (1980) to enhance detection of calcium-binding proteins in polyacrylamide gels using 45 Ca 2+ . Their efforts have produced a method which is shorter, has 40-fold greater sensitivity over the previous method, and will detect 'EF hand'-containing calcium-binding proteins in polyacrylamide gels below the 0.5 μg level. In addition this method will detect at least one example from every described class of calcium-binding protein, including lectins and γ-carboxyglutamic acid containing calcium-binding proteins. The method should be useful for detecting calcium-binding proteins which may trigger neurotransmitter release. (Auth.)

  9. A Novel Segment-Based Approach for Improving Classification Performance of Transport Mode Detection.

    Science.gov (United States)

    Guvensan, M Amac; Dusun, Burak; Can, Baris; Turkmen, H Irem

    2017-12-30

    Transportation planning and solutions have an enormous impact on city life. To minimize the transport duration, urban planners should understand and elaborate the mobility of a city. Thus, researchers look toward monitoring people's daily activities including transportation types and duration by taking advantage of individual's smartphones. This paper introduces a novel segment-based transport mode detection architecture in order to improve the results of traditional classification algorithms in the literature. The proposed post-processing algorithm, namely the Healing algorithm, aims to correct the misclassification results of machine learning-based solutions. Our real-life test results show that the Healing algorithm could achieve up to 40% improvement of the classification results. As a result, the implemented mobile application could predict eight classes including stationary, walking, car, bus, tram, train, metro and ferry with a success rate of 95% thanks to the proposed multi-tier architecture and Healing algorithm.

  10. Colorimetry and SERS dual-mode detection of telomerase activity: combining rapid screening with high sensitivity.

    Science.gov (United States)

    Zong, Shenfei; Wang, Zhuyuan; Chen, Hui; Hu, Guohua; Liu, Min; Chen, Peng; Cui, Yiping

    2014-01-01

    As an important biomarker and therapeutic target, telomerase has attracted considerable attention concerning its detection and monitoring. Here, we present a colorimetry and surface enhanced Raman scattering (SERS) dual-mode telomerase activity detection method, which has several distinctive advantages. First, colorimetric functionality allows rapid preliminary discrimination of telomerase activity by the naked eye. Second, the employment of SERS technique results in greatly improved detection sensitivity. Third, the combination of colorimetry and SERS into one detection system can ensure highly efficacious and sensitive screening of numerous samples. Besides, the avoidance of polymerase chain reaction (PCR) procedures further guarantees fine reliability and simplicity. Generally, the presented method is realized by an "elongate and capture" procedure. To be specific, gold nanoparticles modified with Raman molecules and telomeric repeat complementary oligonucleotide are employed as the colorimetric-SERS bifunctional reporting nanotag, while magnetic nanoparticles functionalized with telomerase substrate oligonucleotide are used as the capturing substrate. Telomerase can synthesize and elongate telomeric repeats onto the capturing substrate. The elongated telomeric repeats subsequently facilitate capturing of the reporting nanotag via hybridization between telomeric repeat and its complementary strand. The captured nanotags can cause a significant difference in the color and SERS intensity of the magnetically separated sediments. Thus both the color and SERS can be used as indicators of the telomerase activity. With fast screening ability and outstanding sensitivity, we anticipate that this method would greatly promote practical application of telomerase-based early-stage cancer diagnosis.

  11. Improved Margins Detection of Regions Enriched with Gold Nanoparticles inside Biological Phantom

    Directory of Open Access Journals (Sweden)

    Yossef Danan

    2017-02-01

    Full Text Available Utilizing the surface plasmon resonance (SPR effect of gold nanoparticles (GNPs enables their use as contrast agents in a variety of biomedical applications for diagnostics and treatment. These applications use both the very strong scattering and absorption properties of the GNPs due to their SPR effects. Most imaging methods use the light-scattering properties of the GNPs. However, the illumination source is in the same wavelength of the GNPs’ scattering wavelength, leading to background noise caused by light scattering from the tissue. In this paper we present a method to improve border detection of regions enriched with GNPs aiming for the real-time application of complete tumor resection by utilizing the absorption of specially targeted GNPs using photothermal imaging. Phantoms containing different concentrations of GNPs were irradiated with a continuous-wave laser and measured with a thermal imaging camera which detected the temperature field of the irradiated phantoms. By modulating the laser illumination, and use of a simple post processing, the border location was identified at an accuracy of better than 0.5 mm even when the surrounding area got heated. This work is a continuation of our previous research.

  12. A Tumor-Targeted Nanodelivery System to Improve Early MRI Detection of Cancer

    Directory of Open Access Journals (Sweden)

    Kathleen F. Pirollo

    2006-01-01

    Full Text Available The development of improvements in magnetic resonance imaging (MRI that would enhance sensitivity, leading to earlier detection of cancer and visualization of metastatic disease, is an area of intense exploration. We have devised a tumor-targeting, liposomal nanodelivery platform for use in gene medicine. This systemically administered nanocomplex has been shown to specifically and efficiently deliver both genes and oligonucleotides to primary and metastatic tumor cells, resulting in significant tumor growth inhibition and even tumor regression. Here we examine the effect on MRI of incorporating conventional MRI contrast agent Magnevist® into our anti-transferrin receptor single-chain antibody (TfRscFv liposomal complex. Both in vitro and in an in vivo orthotopic mouse model of pancreatic cancer, we show increased resolution and image intensity with the complexed Magnevist®. Using advanced microscopy techniques (scanning electron microscopy and scanning probe microscopy, we also established that the Magnevist® is in fact encapsulated by the liposome in the complex and that the complex still retains its nanodimensional size. These results demonstrate that this TfRscFv-liposome-Magnevist® nanocomplex has the potential to become a useful tool in early cancer detection.

  13. Phylogenetically informed logic relationships improve detection of biological network organization

    Science.gov (United States)

    2011-01-01

    Background A "phylogenetic profile" refers to the presence or absence of a gene across a set of organisms, and it has been proven valuable for understanding gene functional relationships and network organization. Despite this success, few studies have attempted to search beyond just pairwise relationships among genes. Here we search for logic relationships involving three genes, and explore its potential application in gene network analyses. Results Taking advantage of a phylogenetic matrix constructed from the large orthologs database Roundup, we invented a method to create balanced profiles for individual triplets of genes that guarantee equal weight on the different phylogenetic scenarios of coevolution between genes. When we applied this idea to LAPP, the method to search for logic triplets of genes, the balanced profiles resulted in significant performance improvement and the discovery of hundreds of thousands more putative triplets than unadjusted profiles. We found that logic triplets detected biological network organization and identified key proteins and their functions, ranging from neighbouring proteins in local pathways, to well separated proteins in the whole pathway, and to the interactions among different pathways at the system level. Finally, our case study suggested that the directionality in a logic relationship and the profile of a triplet could disclose the connectivity between the triplet and surrounding networks. Conclusion Balanced profiles are superior to the raw profiles employed by traditional methods of phylogenetic profiling in searching for high order gene sets. Gene triplets can provide valuable information in detection of biological network organization and identification of key genes at different levels of cellular interaction. PMID:22172058

  14. Bio-sensing with butterfly wings: naturally occurring nano-structures for SERS-based malaria parasite detection.

    Science.gov (United States)

    Garrett, Natalie L; Sekine, Ryo; Dixon, Matthew W A; Tilley, Leann; Bambery, Keith R; Wood, Bayden R

    2015-09-07

    Surface enhanced Raman scattering (SERS) is a powerful tool with great potential to provide improved bio-sensing capabilities. The current 'gold-standard' method for diagnosis of malaria involves visual inspection of blood smears using light microscopy, which is time consuming and can prevent early diagnosis of the disease. We present a novel surface-enhanced Raman spectroscopy substrate based on gold-coated butterfly wings, which enabled detection of malarial hemozoin pigment within lysed blood samples containing 0.005% and 0.0005% infected red blood cells.

  15. Sensor integration of multiple tripolar concentric ring electrodes improves pentylenetetrazole-induced seizure onset detection in rats.

    Science.gov (United States)

    Makeyev, Oleksandr; Ding, Quan; Kay, Steven M; Besio, Walter G

    2012-01-01

    As epilepsy affects approximately one percent of the world population, electrical stimulation of the brain has recently shown potential for additive seizure control therapy. Previously, we applied noninvasive transcranial focal stimulation via tripolar concentric ring electrodes on the scalp of rats after inducing seizures with pentylenetetrazole. We developed a system to detect seizures and automatically trigger the stimulation and evaluated the system on the electrographic activity from rats. In this preliminary study we propose and validate a novel seizure onset detection algorithm based on exponentially embedded family. Unlike the previously proposed approach it integrates the data from multiple electrodes allowing an improvement of the detector performance.

  16. What great managers do.

    Science.gov (United States)

    Buckingham, Marcus

    2005-03-01

    Much has been written about the qualities that make a great manager, but most of the literature overlooks a fundamental question: What does a great manager actually do? While there are countless management styles, one thing underpins the behavior of all great managers. Above all, an exceptional manager comes to know and value the particular quirks and abilities of her employees. She figures out how to capitalize on her staffers' strengths and tweaks her environment to meet her larger goals. Such a specialized approach may seem like a lot of work. But in fact, capitalizing on each person's uniqueness can save time. Rather than encourage employees to conform to strict job descriptions that may include tasks they don't enjoy and aren't good at, a manager who develops positions for his staff members based on their unique abilities will be rewarded with behaviors that are far more efficient and effective than they would be otherwise. This focus on individuals also makes employees more accountable. Because staffers are evaluated on their particular strengths and weaknesses, they are challenged to take responsibility for their abilities and to hone them. Capitalizing on a person's uniqueness also builds a stronger sense of team. By taking the time to understand what makes each employee tick, a great manager shows that he sees his people for who they are. This personal investment not only motivates individuals but also galvanizes the entire team. Finally, this approach shakes up existing hierarchies, which leads to more creative thinking. To take great managing from theory to practice, the author says, you must know three things about a person: her strengths, the triggers that activate those strengths, and how she learns. By asking the right questions, squeezing the right triggers, and becoming aware of your employees' learning styles, you will discover what motivates each person to excel.

  17. Deep Learning Methods for Quantifying Invasive Benthic Species in the Great Lakes

    Science.gov (United States)

    Billings, G.; Skinner, K.; Johnson-Roberson, M.

    2017-12-01

    In recent decades, invasive species such as the round goby and dreissenid mussels have greatly impacted the Great Lakes ecosystem. It is critical to monitor these species, model their distribution, and quantify the impacts on the native fisheries and surrounding ecosystem in order to develop an effective management response. However, data collection in underwater environments is challenging and expensive. Furthermore, the round goby is typically found in rocky habitats, which are inaccessible to standard survey techniques such as bottom trawling. In this work we propose a robotic system for visual data collection to automatically detect and quantify invasive round gobies and mussels in the Great Lakes. Robotic platforms equipped with cameras can perform efficient, cost-effective, low-bias benthic surveys. This data collection can be further optimized through automatic detection and annotation of the target species. Deep learning methods have shown success in image recognition tasks. However, these methods often rely on a labelled training dataset, with up to millions of labelled images. Hand labeling large numbers of images is expensive and often impracticable. Furthermore, data collected in the field may be sparse when only considering images that contain the objects of interest. It is easier to collect dense, clean data in controlled lab settings, but this data is not a realistic representation of real field environments. In this work, we propose a deep learning approach to generate a large set of labelled training data realistic of underwater environments in the field. To generate these images, first we draw random sample images of individual fish and mussels from a library of images captured in a controlled lab environment. Next, these randomly drawn samples will be automatically merged into natural background images. Finally, we will use a generative adversarial network (GAN) that incorporates constraints of the physical model of underwater light propagation

  18. A simple optimization can improve the performance of single feature polymorphism detection by Affymetrix expression arrays

    Directory of Open Access Journals (Sweden)

    Fujisawa Hironori

    2010-05-01

    Full Text Available Abstract Background High-density oligonucleotide arrays are effective tools for genotyping numerous loci simultaneously. In small genome species (genome size: Results We compared the single feature polymorphism (SFP detection performance of whole-genome and transcript hybridizations using the Affymetrix GeneChip® Rice Genome Array, using the rice cultivars with full genome sequence, japonica cultivar Nipponbare and indica cultivar 93-11. Both genomes were surveyed for all probe target sequences. Only completely matched 25-mer single copy probes of the Nipponbare genome were extracted, and SFPs between them and 93-11 sequences were predicted. We investigated optimum conditions for SFP detection in both whole genome and transcript hybridization using differences between perfect match and mismatch probe intensities of non-polymorphic targets, assuming that these differences are representative of those between mismatch and perfect targets. Several statistical methods of SFP detection by whole-genome hybridization were compared under the optimized conditions. Causes of false positives and negatives in SFP detection in both types of hybridization were investigated. Conclusions The optimizations allowed a more than 20% increase in true SFP detection in whole-genome hybridization and a large improvement of SFP detection performance in transcript hybridization. Significance analysis of the microarray for log-transformed raw intensities of PM probes gave the best performance in whole genome hybridization, and 22,936 true SFPs were detected with 23.58% false positives by whole genome hybridization. For transcript hybridization, stable SFP detection was achieved for highly expressed genes, and about 3,500 SFPs were detected at a high sensitivity (> 50% in both shoot and young panicle transcripts. High SFP detection performances of both genome and transcript hybridizations indicated that microarrays of a complex genome (e.g., of Oryza sativa can be

  19. Geostationary Sensor Based Forest Fire Detection and Monitoring: An Improved Version of the SFIDE Algorithm

    Directory of Open Access Journals (Sweden)

    Valeria Di Biase

    2018-05-01

    Full Text Available The paper aims to present the results obtained in the development of a system allowing for the detection and monitoring of forest fires and the continuous comparison of their intensity when several events occur simultaneously—a common occurrence in European Mediterranean countries during the summer season. The system, called SFIDE (Satellite FIre DEtection, exploits a geostationary satellite sensor (SEVIRI, Spinning Enhanced Visible and InfraRed Imager, on board of MSG, Meteosat Second Generation, satellite series. The algorithm was developed several years ago in the framework of a project (SIGRI funded by the Italian Space Agency (ASI. This algorithm has been completely reviewed in order to enhance its efficiency by reducing false alarms rate preserving a high sensitivity. Due to the very low spatial resolution of SEVIRI images (4 × 4 km2 at Mediterranean latitude the sensitivity of the algorithm should be very high to detect even small fires. The improvement of the algorithm has been obtained by: introducing the sun elevation angle in the computation of the preliminary thresholds to identify potential thermal anomalies (hot spots, introducing a contextual analysis in the detection of clouds and in the detection of night-time fires. The results of the algorithm have been validated in the Sardinia region by using ground true data provided by the regional Corpo Forestale e di Vigilanza Ambientale (CFVA. A significant reduction of the commission error (less than 10% has been obtained with respect to the previous version of the algorithm and also with respect to fire-detection algorithms based on low earth orbit satellites.

  20. Feasibility of shutter-speed DCE-MRI for improved prostate cancer detection.

    Science.gov (United States)

    Li, Xin; Priest, Ryan A; Woodward, William J; Tagge, Ian J; Siddiqui, Faisal; Huang, Wei; Rooney, William D; Beer, Tomasz M; Garzotto, Mark G; Springer, Charles S

    2013-01-01

    The feasibility of shutter-speed model dynamic-contrast-enhanced MRI pharmacokinetic analyses for prostate cancer detection was investigated in a prebiopsy patient cohort. Differences of results from the fast-exchange-regime-allowed (FXR-a) shutter-speed model version and the fast-exchange-limit-constrained (FXL-c) standard model are demonstrated. Although the spatial information is more limited, postdynamic-contrast-enhanced MRI biopsy specimens were also examined. The MRI results were correlated with the biopsy pathology findings. Of all the model parameters, region-of-interest-averaged K(trans) difference [ΔK(trans) ≡ K(trans)(FXR-a) - K(trans)(FXL-c)] or two-dimensional K(trans)(FXR-a) vs. k(ep)(FXR-a) values were found to provide the most useful biomarkers for malignant/benign prostate tissue discrimination (at 100% sensitivity for a population of 13, the specificity is 88%) and disease burden determination. (The best specificity for the fast-exchange-limit-constrained analysis is 63%, with the two-dimensional plot.) K(trans) and k(ep) are each measures of passive transcapillary contrast reagent transfer rate constants. Parameter value increases with shutter-speed model (relative to standard model) analysis are larger in malignant foci than in normal-appearing glandular tissue. Pathology analyses verify the shutter-speed model (FXR-a) promise for prostate cancer detection. Parametric mapping may further improve pharmacokinetic biomarker performance. Copyright © 2012 Wiley Periodicals, Inc.

  1. The natural history of congenitally corrected transposition of the great arteries.

    Science.gov (United States)

    Huhta, James

    2011-01-01

    The natural history of congenitally corrected transposition of the great arteries is of clinical/surgical importance once the fetus is born without heart block or signs of heart failure. Without significant tricuspid valve malformation, associated defects such as ventricular septal defect and left ventricular outflow obstruction can be repaired surgically. The mortality and long-term outcome appear to be linked strongly with the severity of tricuspid valve regurgitation. Some patients with an intact ventricular septum and no right ventricular dysfunction will live long lives without detection, and some women will successfully complete pregnancy.

  2. Simple system for isothermal DNA amplification coupled to lateral flow detection.

    Directory of Open Access Journals (Sweden)

    Kristina Roskos

    Full Text Available Infectious disease diagnosis in point-of-care settings can be greatly improved through integrated, automated nucleic acid testing devices. We have developed an early prototype for a low-cost system which executes isothermal DNA amplification coupled to nucleic acid lateral flow (NALF detection in a mesofluidic cartridge attached to a portable instrument. Fluid handling inside the cartridge is facilitated through one-way passive valves, flexible pouches, and electrolysis-driven pumps, which promotes a compact and inexpensive instrument design. The closed-system disposable prevents workspace amplicon contamination. The cartridge design is based on standard scalable manufacturing techniques such as injection molding. Nucleic acid amplification occurs in a two-layer pouch that enables efficient heat transfer. We have demonstrated as proof of principle the amplification and detection of Mycobacterium tuberculosis (M.tb genomic DNA in the cartridge, using either Loop Mediated Amplification (LAMP or the Exponential Amplification Reaction (EXPAR, both coupled to NALF detection. We envision that a refined version of this cartridge, including upstream sample preparation coupled to amplification and detection, will enable fully-automated sample-in to answer-out infectious disease diagnosis in primary care settings of low-resource countries with high disease burden.

  3. Using trend templates in a neonatal seizure algorithm improves detection of short seizures in a foetal ovine model.

    Science.gov (United States)

    Zwanenburg, Alex; Andriessen, Peter; Jellema, Reint K; Niemarkt, Hendrik J; Wolfs, Tim G A M; Kramer, Boris W; Delhaas, Tammo

    2015-03-01

    Seizures below one minute in duration are difficult to assess correctly using seizure detection algorithms. We aimed to improve neonatal detection algorithm performance for short seizures through the use of trend templates for seizure onset and end. Bipolar EEG were recorded within a transiently asphyxiated ovine model at 0.7 gestational age, a common experimental model for studying brain development in humans of 30-34 weeks of gestation. Transient asphyxia led to electrographic seizures within 6-8 h. A total of 3159 seizures, 2386 shorter than one minute, were annotated in 1976 h-long EEG recordings from 17 foetal lambs. To capture EEG characteristics, five features, sensitive to seizures, were calculated and used to derive trend information. Feature values and trend information were used as input for support vector machine classification and subsequently post-processed. Performance metrics, calculated after post-processing, were compared between analyses with and without employing trend information. Detector performance was assessed after five-fold cross-validation conducted ten times with random splits. The use of trend templates for seizure onset and end in a neonatal seizure detection algorithm significantly improves the correct detection of short seizures using two-channel EEG recordings from 54.3% (52.6-56.1) to 59.5% (58.5-59.9) at FDR 2.0 (median (range); p seizures by EEG monitoring at the NICU.

  4. Alternative Chemical Amplification Methods for Peroxy Radical Detection

    Science.gov (United States)

    Wood, E. C. D.

    2014-12-01

    Peroxy radicals (HO2, CH3O2, etc.) are commonly detected by the chemical amplification technique, in which ambient air is mixed with high concentrations of CO and NO, initiating a chain reaction that produces 30 - 200 NO2 molecules per sampled peroxy radical. The NO2 is then measured by one of several techniques. With the exception of CIMS-based techniques, the chemical amplification method has undergone only incremental improvements since it was first introduced in 1982. The disadvantages of the technique include the need to use high concentrations of CO and the greatly reduced sensitivity of the amplification chain length in the presence of water vapor. We present a new chemical amplification scheme in which either ethane or acetaldehyde is used in place of CO, with the NO2 product detected using Cavity Attenuated Phase Shift spectroscopy (CAPS). Under dry conditions, the amplification factor of the alternative amplifiers are approximately six times lower than the CO-based amplifier. The relative humidity "penalty" is not as severe, however, such that at typical ambient relative humidity (RH) values the amplification factor is within a factor of three of the CO-based amplifier. Combined with the NO2 sensitivity of CAPS and a dual-channel design, the detection limit of the ethane amplifier is less than 2 ppt (1 minute average, signal-to-noise ratio 2). The advantages of these alternative chemical amplification schemes are improved safety, a reduced RH correction, and increased sensitivity to organic peroxy radicals relative to HO2.

  5. Large-area NbN superconducting nanowire avalanche photon detectors with saturated detection efficiency

    Science.gov (United States)

    Murphy, Ryan P.; Grein, Matthew E.; Gudmundsen, Theodore J.; McCaughan, Adam; Najafi, Faraz; Berggren, Karl K.; Marsili, Francesco; Dauler, Eric A.

    2015-05-01

    Superconducting circuits comprising SNSPDs placed in parallel—superconducting nanowire avalanche photodetectors, or SNAPs—have previously been demonstrated to improve the output signal-to-noise ratio (SNR) by increasing the critical current. In this work, we employ a 2-SNAP superconducting circuit with narrow (40 nm) niobium nitride (NbN) nanowires to improve the system detection efficiency to near-IR photons while maintaining high SNR. Additionally, while previous 2-SNAP demonstrations have added external choke inductance to stabilize the avalanching photocurrent, we show that the external inductance can be entirely folded into the active area by cascading 2-SNAP devices in series to produce a greatly increased active area. We fabricated series-2-SNAP (s2-SNAP) circuits with a nanowire length of 20 μm with cascades of 2-SNAPs providing the choke inductance necessary for SNAP operation. We observed that (1) the detection efficiency saturated at high bias currents, and (2) the 40 nm 2-SNAP circuit critical current was approximately twice that for a 40 nm non-SNAP configuration.

  6. Improving Fraudster Detection in Online Auctions by Using Neighbor-Driven Attributes

    Directory of Open Access Journals (Sweden)

    Jun-Lin Lin

    2015-12-01

    Full Text Available Online auction websites use a simple reputation system to help their users to evaluate the trustworthiness of sellers and buyers. However, to improve their reputation in the reputation system, fraudulent users can easily deceive the reputation system by creating fake transactions. This inflated-reputation fraud poses a major problem for online auction websites because it can lead legitimate users into scams. Numerous approaches have been proposed in the literature to address this problem, most of which involve using social network analysis (SNA to derive critical features (e.g., k-core, center weight, and neighbor diversity for distinguishing fraudsters from legitimate users. This paper discusses the limitations of these SNA features and proposes a class of SNA features referred to as neighbor-driven attributes (NDAs. The NDAs of users are calculated from the features of their neighbors. Because fraudsters require collusive neighbors to provide them with positive ratings in the reputation system, using NDAs can be helpful for detecting fraudsters. Although the idea of NDAs is not entirely new, experimental results on a real-world dataset showed that using NDAs improves classification accuracy compared with state-of-the-art methods that use the k-core, center weight, and neighbor diversity.

  7. Suitability of two-dimensional electrophoretic protein separations for quantitative detection of mutations

    International Nuclear Information System (INIS)

    Taylor, J.; Anderson, N.L.; Anderson, N.G.; Gemmell, A.; Giometti, C.S.; Nance, S.L.; Tollaksen, S.L.

    1986-01-01

    Separation of proteins by two-dimensional electrophoresis (2DE) provides a powerful method for mutagenesis studies, since hundreds of proteins can be monitored simultaneously. In previous mutation studies in which 2DE has been used, only qualitative protein differences were monitored; quantitative protein variations were not evaluated. Although significant differences in protein abundance can be detected by eye, the large number of protein spots present in 2DE patterns together with the large number of individual patterns required for a mutagenesis study would necessitate the use of a computerized analysis system to detect the rare quantitative protein changes indicative of gene deletions or inactivation of genes by point mutations in regulatory genes. A pilot study to search for heritable mutations induced by treatment of mice with either ethylnitrosourea or gamma radiation is underway. Samples are being monitored for quantitative changes that reduce the amount of protein by about 50%. The results of this study indicate that the key methods to improve the application of 2DE to mutation screening are to increase the number of measurable spots (i.e., improve stain sensitivity) and to decrease the spread of values for the volume measurements. Even small improvements in these areas could greatly increase the number of monitorable spots. 9 refs., 4 figs

  8. An improved algorithm for automatic detection of saccades in eye movement data and for calculating saccade parameters.

    Science.gov (United States)

    Behrens, F; Mackeben, M; Schröder-Preikschat, W

    2010-08-01

    This analysis of time series of eye movements is a saccade-detection algorithm that is based on an earlier algorithm. It achieves substantial improvements by using an adaptive-threshold model instead of fixed thresholds and using the eye-movement acceleration signal. This has four advantages: (1) Adaptive thresholds are calculated automatically from the preceding acceleration data for detecting the beginning of a saccade, and thresholds are modified during the saccade. (2) The monotonicity of the position signal during the saccade, together with the acceleration with respect to the thresholds, is used to reliably determine the end of the saccade. (3) This allows differentiation between saccades following the main-sequence and non-main-sequence saccades. (4) Artifacts of various kinds can be detected and eliminated. The algorithm is demonstrated by applying it to human eye movement data (obtained by EOG) recorded during driving a car. A second demonstration of the algorithm detects microsleep episodes in eye movement data.

  9. Bacterial pathogen gene abundance and relation to recreational water quality at seven Great Lakes beaches.

    Science.gov (United States)

    Oster, Ryan J; Wijesinghe, Rasanthi U; Haack, Sheridan K; Fogarty, Lisa R; Tucker, Taaja R; Riley, Stephen C

    2014-12-16

    Quantitative assessment of bacterial pathogens, their geographic variability, and distribution in various matrices at Great Lakes beaches are limited. Quantitative PCR (qPCR) was used to test for genes from E. coli O157:H7 (eaeO157), shiga-toxin producing E. coli (stx2), Campylobacter jejuni (mapA), Shigella spp. (ipaH), and a Salmonella enterica-specific (SE) DNA sequence at seven Great Lakes beaches, in algae, water, and sediment. Overall, detection frequencies were mapA>stx2>ipaH>SE>eaeO157. Results were highly variable among beaches and matrices; some correlations with environmental conditions were observed for mapA, stx2, and ipaH detections. Beach seasonal mean mapA abundance in water was correlated with beach seasonal mean log10 E. coli concentration. At one beach, stx2 gene abundance was positively correlated with concurrent daily E. coli concentrations. Concentration distributions for stx2, ipaH, and mapA within algae, sediment, and water were statistically different (Non-Detect and Data Analysis in R). Assuming 10, 50, or 100% of gene copies represented viable and presumably infective cells, a quantitative microbial risk assessment tool developed by Michigan State University indicated a moderate probability of illness for Campylobacter jejuni at the study beaches, especially where recreational water quality criteria were exceeded. Pathogen gene quantification may be useful for beach water quality management.

  10. Improved security detection strategy in quantum secure direct communication protocol based on four-particle Green-Horne-Zeilinger state

    Energy Technology Data Exchange (ETDEWEB)

    Li, Jian; Nie, Jin-Rui; Li, Rui-Fan [Beijing Univ. of Posts and Telecommunications, Beijing (China). School of Computer; Jing, Bo [Beijing Univ. of Posts and Telecommunications, Beijing (China). School of Computer; Beijing Institute of Applied Meteorology, Beijing (China). Dept. of Computer Science

    2012-06-15

    To enhance the efficiency of eavesdropping detection in the quantum secure direct communication protocol, an improved quantum secure direct communication protocol based on a four-particle Green-Horne-Zeilinger (GHZ) state is presented. In the protocol, the four-particle GHZ state is used to detect eavesdroppers, and quantum dense coding is used to encode the message. In the security analysis, the method of entropy theory is introduced, and two detection strategies are compared quantitatively by using the constraint between the information that the eavesdroppers can obtain and the interference that has been introduced. If the eavesdropper wants to obtain all the information, the detection rate of the quantum secure direct communication using an Einstein-Podolsky-Rosen (EPR) pair block will be 50% and the detection rate of the presented protocol will be 87%. At last, the security of the proposed protocol is discussed. The analysis results indicate that the protocol proposed is more secure than the others. (orig.)

  11. Accelerometer and Camera-Based Strategy for Improved Human Fall Detection

    KAUST Repository

    Zerrouki, Nabil; Harrou, Fouzi; Sun, Ying; Houacine, Amrane

    2016-01-01

    In this paper, we address the problem of detecting human falls using anomaly detection. Detection and classification of falls are based on accelerometric data and variations in human silhouette shape. First, we use the exponentially weighted moving average (EWMA) monitoring scheme to detect a potential fall in the accelerometric data. We used an EWMA to identify features that correspond with a particular type of fall allowing us to classify falls. Only features corresponding with detected falls were used in the classification phase. A benefit of using a subset of the original data to design classification models minimizes training time and simplifies models. Based on features corresponding to detected falls, we used the support vector machine (SVM) algorithm to distinguish between true falls and fall-like events. We apply this strategy to the publicly available fall detection databases from the university of Rzeszow’s. Results indicated that our strategy accurately detected and classified fall events, suggesting its potential application to early alert mechanisms in the event of fall situations and its capability for classification of detected falls. Comparison of the classification results using the EWMA-based SVM classifier method with those achieved using three commonly used machine learning classifiers, neural network, K-nearest neighbor and naïve Bayes, proved our model superior.

  12. Accelerometer and Camera-Based Strategy for Improved Human Fall Detection

    KAUST Repository

    Zerrouki, Nabil

    2016-10-29

    In this paper, we address the problem of detecting human falls using anomaly detection. Detection and classification of falls are based on accelerometric data and variations in human silhouette shape. First, we use the exponentially weighted moving average (EWMA) monitoring scheme to detect a potential fall in the accelerometric data. We used an EWMA to identify features that correspond with a particular type of fall allowing us to classify falls. Only features corresponding with detected falls were used in the classification phase. A benefit of using a subset of the original data to design classification models minimizes training time and simplifies models. Based on features corresponding to detected falls, we used the support vector machine (SVM) algorithm to distinguish between true falls and fall-like events. We apply this strategy to the publicly available fall detection databases from the university of Rzeszow’s. Results indicated that our strategy accurately detected and classified fall events, suggesting its potential application to early alert mechanisms in the event of fall situations and its capability for classification of detected falls. Comparison of the classification results using the EWMA-based SVM classifier method with those achieved using three commonly used machine learning classifiers, neural network, K-nearest neighbor and naïve Bayes, proved our model superior.

  13. Change Detection with Polarimetric SAR Imagery for Nuclear Verification

    International Nuclear Information System (INIS)

    Canty, M.

    2015-01-01

    This paper investigates the application of multivariate statistical change detection with high-resolution polarimetric SAR imagery acquired from commercial satellite platforms for observation and verification of nuclear activities. A prototype software tool comprising a processing chain starting from single look complex (SLC) multitemporal data through to change detection maps is presented. Multivariate change detection algorithms applied to polarimetric SAR data are not common. This is because, up until recently, not many researchers or practitioners have had access to polarimetric data. However with the advent of several spaceborne polarimetric SAR instruments such as the Japanese ALOS, the Canadian Radarsat-2, the German TerraSAR-X, the Italian COSMO-SkyMed missions and the European Sentinal SAR platform, the situation has greatly improved. There is now a rich source of weather-independent satellite radar data which can be exploited for Nuclear Safeguards purposes. The method will also work for univariate data, that is, it is also applicable to scalar or single polarimetric SAR data. The change detection procedure investigated here exploits the complex Wishart distribution of dual and quad polarimetric imagery in look-averaged covariance matrix format in order to define a per-pixel change/no-change hypothesis test. It includes approximations for the probability distribution of the test statistic, and so permits quantitative significance levels to be quoted for change pixels. The method has been demonstrated previously with polarimetric images from the airborne EMISAR sensor, but is applied here for the first time to satellite platforms. In addition, an improved multivariate method is used to estimate the so-called equivalent number of looks (ENL), which is a critical parameter of the hypothesis test. (author)

  14. Harnessing Aptamers to Overcome Challenges in Gluten Detection

    Directory of Open Access Journals (Sweden)

    Rebeca Miranda-Castro

    2016-04-01

    Full Text Available Celiac disease is a lifelong autoimmune disorder triggered by foods containing gluten, the storage protein in wheat, rye, and barley. The rapidly escalating number of patients diagnosed with this disease poses a great challenge to both food industry and authorities to guarantee food safety for all. Therefore, intensive efforts are being made to establish minimal disease-eliciting doses of gluten and consequently to improve gluten-free labeling. These efforts depend to a high degree on the availability of methods capable of detecting the protein in food samples at levels as low as possible. Current analytical approaches rely on the use of antibodies as selective recognition elements. With limited sensitivity, these methods exhibit some deficiencies that compromise the accuracy of the obtained results. Aptamers provide an ideal alternative for designing biosensors for fast and selective measurement of gluten in foods. This article highlights the challenges in gluten detection, the current status of the use of aptamers for solving this problem, and what remains to be done to move these systems into commercial applications.

  15. An improved UPLC method for the detection of undeclared horse meat addition by using myoglobin as molecular marker.

    Science.gov (United States)

    Di Giuseppe, Antonella M A; Giarretta, Nicola; Lippert, Martina; Severino, Valeria; Di Maro, Antimo

    2015-02-15

    In 2013, following the scandal of the presence of undeclared horse meat in various processed beef products across the Europe, several researches have been undertaken for the safety of consumer health. In this framework, an improved UPLC separation method has been developed to detect the presence of horse myoglobin in raw meat samples. The separation of both horse and beef myoglobins was achieved in only seven minutes. The methodology was improved by preparing mixtures with different composition percentages of horse and beef meat. By using myoglobin as marker, low amounts (0.50mg/0.50g, w/w; ∼0.1%) of horse meat can be detected and quantified in minced raw meat samples with high reproducibility and sensitivity, thus offering a valid alternative to conventional PCR techniques. Copyright © 2014 Elsevier Ltd. All rights reserved.

  16. Applied biotechnology for improving fertility of herds in Argentina

    International Nuclear Information System (INIS)

    Mongiardino, M.E.; Dick, A.R.; Murray, R.; Ramos, G.; Balbiani, G.; Maciel, M.

    1990-01-01

    In an attempt to find methods to shorten the calving to conception interval of dairy cattle in Argentina, three research projects were carried out: (1) use of hormonal treatments in the early post-partum period to increase fertility in non-cycling cows; (2) treatments to increase the fertility of cycling cows; and (3) management systems to improve the efficiency of oestrus detection. In non-cycling cows, fewer services per conception and earlier pregnancies were obtained when a progesterone suppository was placed intravaginally (PRID treatment) 24-31 days post-partum. No statistical reduction in days open was observed, however, because of the great variability in response within groups. GnRH injection given 24 and 25 days post-partum did not improve reproductive indices. In cycling cows, clitoral massage after AI did not enhance fertility, while GnRH 14 days post-service resulted in pregnancy rates of 68.4% compared with 25% in the control group. In an attempt to improve the efficiency of oestrus detection successive periods of either 10 or 14 days of 'heat' observation followed by similar periods of no observation, combined with the systematic use of an oestrus synchronizer (cloprostenol), resulted in the same reproductive performance as in control cows observed continuously but with a saving of 50% in time spent in oestrus detection. In a seasonally bred herd, a reduction of 12 days in interval to conception and subsequent improvement in milk produced in the following season were obtained by synchronizing oestrus at the start of the breeding season with a norgestomet implant followed by a prostaglandin injection one day before implant removal. In repeat breeders, a second implant 9 days and 21 days later was found to be effective. (author). 24 refs, 2 figs, 4 tabs

  17. Improvement of Breast Cancer Detection Using Non-subsampled Contourlet Transform and Super-Resolution Technique in Mammographic Images

    Directory of Open Access Journals (Sweden)

    Fatemeh Pak

    2015-05-01

    Full Text Available Introduction Breast cancer is one of the most life-threatening conditions among women. Early detection of this disease is the only way to reduce the associated mortality rate. Mammography is a standard method for the early detection of breast cancer. Today, considering the importance of breast cancer detection, computer-aided detection techniques have been employed to increase the quality of mammographic images and help physicians reduce false positive rate (FPR. Materials and Methods In this study, a method was proposed for improving the quality of mammographic images to help radiologists establish a prompt and accurate diagnosis. The proposed approach included three major parts including pre-processing, feature extraction, and classification. In the pre-processing stage, the region of interest was determined and the image quality was improved by non-subsampled contourlet transform and super-resolution algorithm. In the feature extraction stage, some features of image components were extracted and skewness of each feature was calculated. Finally, a support vector machine was utilized to classify the features and determine the probability of benignity or malignancy of the disease. Results Based on the obtained results using Mammographic Image Analysis Society (MIAS database, the mean accuracy was estimated at 87.26% and maximum accuracy was 96.29%. Also, the mean and minimum FPRs were estimated at 9.55% and 2.87%, respectively.     Conclusion The results obtained using MIAS database indicated the superiority of the proposed method to other techniques. The reduced FPR in the proposed method was a significant finding in the present article.

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

    Directory of Open Access Journals (Sweden)

    Linda C. Rogers

    2016-01-01

    Full Text Available 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.

  19. Improved detection of electrical activity with a voltage probe based on a voltage-sensing phosphatase.

    Science.gov (United States)

    Tsutsui, Hidekazu; Jinno, Yuka; Tomita, Akiko; Niino, Yusuke; Yamada, Yoshiyuki; Mikoshiba, Katsuhiko; Miyawaki, Atsushi; Okamura, Yasushi

    2013-09-15

      One of the most awaited techniques in modern physiology is the sensitive detection of spatiotemporal electrical activity in a complex network of excitable cells. The use of genetically encoded voltage probes has been expected to enable such analysis. However, in spite of recent progress, existing probes still suffer from low signal amplitude and/or kinetics too slow to detect fast electrical activity. Here, we have developed an improved voltage probe named Mermaid2, which is based on the voltage-sensor domain of the voltage-sensing phosphatase from Ciona intestinalis and Förster energy transfer between a pair of fluorescent proteins. In mammalian cells, Mermaid2 permits ratiometric readouts of fractional changes of more than 50% over a physiologically relevant voltage range with fast kinetics, and it was used to follow a train of action potentials at frequencies of up to 150 Hz. Mermaid2 was also able to detect single action potentials and subthreshold voltage responses in hippocampal neurons in vitro, in addition to cortical electrical activity evoked by sound stimuli in single trials in living mice.

  20. Many faces of rationality: Implications of the great rationality debate for clinical decision-making

    OpenAIRE

    Djulbegovic, B.; Elqayam, Shira

    2017-01-01

    open access article Given that more than 30% of healthcare costs are wasted on inappropriate care, suboptimal care is increasingly connected to the quality of medical decisions. It has been argued that personal decisions are the leading cause of death, and 80% of healthcare expenditures result from physicians' decisions. Therefore, improving healthcare necessitates improving medical decisions, ie, making decisions (more) rational. Drawing on writings fromThe Great Rationality Debate from t...

  1. Nothing Great Is Easy

    OpenAIRE

    Stansbie, Lisa

    2014-01-01

    A solo exhibition of 13 pieces of art work.\\ud \\ud Nothing Great is Easy is an exhibition of sculpture, film, drawing and photography that proposes reconstructed narratives using the sport of swimming and in particular the collective interaction and identity of the channel swimmer. The work utilises the processes, rituals/rules, language and the apparatus of sport.\\ud \\ud “Nothing great is easy” are the words on the memorial to Captain Matthew Webb who was the first man to swim the English ch...

  2. An improved EMD method for modal identification and a combined static-dynamic method for damage detection

    Science.gov (United States)

    Yang, Jinping; Li, Peizhen; Yang, Youfa; Xu, Dian

    2018-04-01

    Empirical mode decomposition (EMD) is a highly adaptable signal processing method. However, the EMD approach has certain drawbacks, including distortions from end effects and mode mixing. In the present study, these two problems are addressed using an end extension method based on the support vector regression machine (SVRM) and a modal decomposition method based on the characteristics of the Hilbert transform. The algorithm includes two steps: using the SVRM, the time series data are extended at both endpoints to reduce the end effects, and then, a modified EMD method using the characteristics of the Hilbert transform is performed on the resulting signal to reduce mode mixing. A new combined static-dynamic method for identifying structural damage is presented. This method combines the static and dynamic information in an equilibrium equation that can be solved using the Moore-Penrose generalized matrix inverse. The combination method uses the differences in displacements of the structure with and without damage and variations in the modal force vector. Tests on a four-story, steel-frame structure were conducted to obtain static and dynamic responses of the structure. The modal parameters are identified using data from the dynamic tests and improved EMD method. The new method is shown to be more accurate and effective than the traditional EMD method. Through tests with a shear-type test frame, the higher performance of the proposed static-dynamic damage detection approach, which can detect both single and multiple damage locations and the degree of the damage, is demonstrated. For structures with multiple damage, the combined approach is more effective than either the static or dynamic method. The proposed EMD method and static-dynamic damage detection method offer improved modal identification and damage detection, respectively, in structures.

  3. Detecting plague-host abundance from space: Using a spectral vegetation index to identify occupancy of great gerbil burrows

    NARCIS (Netherlands)

    Wilschut, Liesbeth I.; Heesterbeek, Johan A.P.; Begon, Mike; de Jong, Steven M.; Ageyev, Vladimir; Laudisoit, Anne; Addink, Elisabeth A.

    2018-01-01

    In Kazakhstan, plague outbreaks occur when its main host, the great gerbil, exceeds an abundance threshold. These live in family groups in burrows, which can be mapped using remote sensing. Occupancy (percentage of burrows occupied) is a good proxy for abundance and hence the possibility of an

  4. [Advances of NIR spectroscopy technology applied in seed quality detection].

    Science.gov (United States)

    Zhu, Li-wei; Ma, Wen-guang; Hu, Jin; Zheng, Yun-ye; Tian, Yi-xin; Guan, Ya-jing; Hu, Wei-min

    2015-02-01

    Near infrared spectroscopy (NIRS) technology developed fast in recent years, due to its rapid speed, less pollution, high-efficiency and other advantages. It has been widely used in many fields such as food, chemical industry, pharmacy, agriculture and so on. The seed is the most basic and important agricultural capital goods, and seed quality is important for agricultural production. Most methods presently used for seed quality detecting were destructive, slow and needed pretreatment, therefore, developing one kind of method that is simple and rapid has great significance for seed quality testing. This article reviewed the application and trends of NIRS technology in testing of seed constituents, vigor, disease and insect pests etc. For moisture, starch, protein, fatty acid and carotene content, the model identification rates were high as their relative contents were high; for trace organic, the identification rates were low as their relative content were low. The heat-damaged seeds with low vigor were discriminated by NIRS, the seeds stored for different time could also been identified. The discrimination of frost-damaged seeds was impossible. The NIRS could be used to identify health and infected disease seeds, and did the classification for the health degree; it could identify parts of the fungal pathogens. The NIRS could identify worm-eaten and health seeds, and further distinguished the insect species, however the identification effects for small larval and low injury level of insect pests was not good enough. Finally, in present paper existing problems and development trends for NIRS in seed quality detection was discussed, especially the single seed detecting technology which was characteristic of the seed industry, the standardization of its spectral acquisition accessories will greatly improve its applicability.

  5. Pressure optimization of an EC-QCL based cavity ring-down spectroscopy instrument for exhaled NO detection

    Science.gov (United States)

    Zhou, Sheng; Han, Yanling; Li, Bincheng

    2018-02-01

    Nitric oxide (NO) in exhaled breath has gained increasing interest in recent years mainly driven by the clinical need to monitor inflammatory status in respiratory disorders, such as asthma and other pulmonary conditions. Mid-infrared cavity ring-down spectroscopy (CRDS) using an external cavity, widely tunable continuous-wave quantum cascade laser operating at 5.3 µm was employed for NO detection. The detection pressure was reduced in steps to improve the sensitivity, and the optimal pressure was determined to be 15 kPa based on the fitting residual analysis of measured absorption spectra. A detection limit (1σ, or one time of standard deviation) of 0.41 ppb was experimentally achieved for NO detection in human breath under the optimized condition in a total of 60 s acquisition time (2 s per data point). Diurnal measurement session was conducted for exhaled NO. The experimental results indicated that mid-infrared CRDS technique has great potential for various applications in health diagnosis.

  6. Developments on positron scattering experiments including beam production and detection

    International Nuclear Information System (INIS)

    Selim, F.A.; Golovchenko, J.A.

    2001-01-01

    Positron scattering and channeling experiments require high quality (low emittance) beams. A new electrostatic optics system for extracting positrons from a moderator is presented. The system features improved efficiency of focusing and beam transport of moderated positrons emitted with angular spreads up to ± 30 , with good phase space characteristics. The presented optics also provides a high degree of freedom in controlling exit beam trajectories. The system has been installed in the LLNL Pelletron accelerator and showed great enhancement on the beam quality. On the detection side, image plates were used to measure the angular distributions of positrons transmitted through the gold crystals. The measurements demonstrate the advantages of image plates as quantitative position sensitive detectors for positrons. (orig.)

  7. Transfer Rate Edited experiment for the selective detection of Chemical Exchange via Saturation Transfer (TRE-CEST).

    Science.gov (United States)

    Friedman, Joshua I; Xia, Ding; Regatte, Ravinder R; Jerschow, Alexej

    2015-07-01

    Chemical Exchange Saturation Transfer (CEST) magnetic resonance experiments have become valuable tools in magnetic resonance for the detection of low concentration solutes with far greater sensitivity than direct detection methods. Accurate measures of rates of chemical exchange provided by CEST are of particular interest to biomedical imaging communities where variations in chemical exchange can be related to subtle variations in biomarker concentration, temperature and pH within tissues using MRI. Despite their name, however, traditional CEST methods are not truly selective for chemical exchange and instead detect all forms of magnetization transfer including through-space NOE. This ambiguity crowds CEST spectra and greatly complicates subsequent data analysis. We have developed a Transfer Rate Edited CEST experiment (TRE-CEST) that uses two different types of solute labeling in order to selectively amplify signals of rapidly exchanging proton species while simultaneously suppressing 'slower' NOE-dominated magnetization transfer processes. This approach is demonstrated in the context of both NMR and MRI, where it is used to detect the labile amide protons of proteins undergoing chemical exchange (at rates⩾30s(-1)) while simultaneously eliminating signals originating from slower (∼5s(-1)) NOE-mediated magnetization transfer processes. TRE-CEST greatly expands the utility of CEST experiments in complex systems, and in-vivo, in particular, where it is expected to improve the quantification of chemical exchange and magnetization transfer rates while enabling new forms of imaging contrast. Copyright © 2015 Elsevier Inc. All rights reserved.

  8. Transfer Rate Edited experiment for the selective detection of Chemical Exchange via Saturation Transfer (TRE-CEST)

    Science.gov (United States)

    Friedman, Joshua I.; Xia, Ding; Regatte, Ravinder R.; Jerschow, Alexej

    2015-07-01

    Chemical Exchange Saturation Transfer (CEST) magnetic resonance experiments have become valuable tools in magnetic resonance for the detection of low concentration solutes with far greater sensitivity than direct detection methods. Accurate measures of rates of chemical exchange provided by CEST are of particular interest to biomedical imaging communities where variations in chemical exchange can be related to subtle variations in biomarker concentration, temperature and pH within tissues using MRI. Despite their name, however, traditional CEST methods are not truly selective for chemical exchange and instead detect all forms of magnetization transfer including through-space NOE. This ambiguity crowds CEST spectra and greatly complicates subsequent data analysis. We have developed a Transfer Rate Edited CEST experiment (TRE-CEST) that uses two different types of solute labeling in order to selectively amplify signals of rapidly exchanging proton species while simultaneously suppressing 'slower' NOE-dominated magnetization transfer processes. This approach is demonstrated in the context of both NMR and MRI, where it is used to detect the labile amide protons of proteins undergoing chemical exchange (at rates ⩾ 30 s-1) while simultaneously eliminating signals originating from slower (∼5 s-1) NOE-mediated magnetization transfer processes. TRE-CEST greatly expands the utility of CEST experiments in complex systems, and in-vivo, in particular, where it is expected to improve the quantification of chemical exchange and magnetization transfer rates while enabling new forms of imaging contrast.

  9. Leak detection by vibrational diagnostic methods

    International Nuclear Information System (INIS)

    Siklossy, P.

    1983-01-01

    The possibilities and methods of leak detection due to mechanical failures in nuclear power plants are reviewed on the basis of the literature. Great importance is attributed to vibrational diagnostic methods for their adventageous characteristics which enable them to become final leak detecting methods. The problems of noise analysis, e.g. leak detection by impact sound measurements, probe characteristics, gain problems, probe selection, off-line analysis and correlation functions, types of leak noises etc. are summarized. Leak detection based on noise analysis can be installed additionally to power plants. Its maintenance and testing is simple. On the other hand, it requires special training and measuring methods. (Sz.J.)

  10. Factors influencing variation in physician adenoma detection rates: a theory-based approach for performance improvement.

    Science.gov (United States)

    Atkins, Louise; Hunkeler, Enid M; Jensen, Christopher D; Michie, Susan; Lee, Jeffrey K; Doubeni, Chyke A; Zauber, Ann G; Levin, Theodore R; Quinn, Virginia P; Corley, Douglas A

    2016-03-01

    Interventions to improve physician adenoma detection rates for colonoscopy have generally not been successful, and there are little data on the factors contributing to variation that may be appropriate targets for intervention. We sought to identify factors that may influence variation in detection rates by using theory-based tools for understanding behavior. We separately studied gastroenterologists and endoscopy nurses at 3 Kaiser Permanente Northern California medical centers to identify potentially modifiable factors relevant to physician adenoma detection rate variability by using structured group interviews (focus groups) and theory-based tools for understanding behavior and eliciting behavior change: the Capability, Opportunity, and Motivation behavior model; the Theoretical Domains Framework; and the Behavior Change Wheel. Nine factors potentially associated with adenoma detection rate variability were identified, including 6 related to capability (uncertainty about which types of polyps to remove, style of endoscopy team leadership, compromised ability to focus during an examination due to distractions, examination technique during withdrawal, difficulty detecting certain types of adenomas, and examiner fatigue and pain), 2 related to opportunity (perceived pressure due to the number of examinations expected per shift and social pressure to finish examinations before scheduled breaks or the end of a shift), and 1 related to motivation (valuing a meticulous examination as the top priority). Examples of potential intervention strategies are provided. By using theory-based tools, this study identified several novel and potentially modifiable factors relating to capability, opportunity, and motivation that may contribute to adenoma detection rate variability and be appropriate targets for future intervention trials. Copyright © 2016 American Society for Gastrointestinal Endoscopy. Published by Elsevier Inc. All rights reserved.

  11. Robust Nucleus/Cell Detection and Segmentation in Digital Pathology and Microscopy Images: A Comprehensive Review.

    Science.gov (United States)

    Xing, Fuyong; Yang, Lin

    2016-01-01

    Digital pathology and microscopy image analysis is widely used for comprehensive studies of cell morphology or tissue structure. Manual assessment is labor intensive and prone to interobserver variations. Computer-aided methods, which can significantly improve the objectivity and reproducibility, have attracted a great deal of interest in recent literature. Among the pipeline of building a computer-aided diagnosis system, nucleus or cell detection and segmentation play a very important role to describe the molecular morphological information. In the past few decades, many efforts have been devoted to automated nucleus/cell detection and segmentation. In this review, we provide a comprehensive summary of the recent state-of-the-art nucleus/cell segmentation approaches on different types of microscopy images including bright-field, phase-contrast, differential interference contrast, fluorescence, and electron microscopies. In addition, we discuss the challenges for the current methods and the potential future work of nucleus/cell detection and segmentation.

  12. The Great Recession, genetic sensitivity, and maternal harsh parenting.

    Science.gov (United States)

    Lee, Dohoon; Brooks-Gunn, Jeanne; McLanahan, Sara S; Notterman, Daniel; Garfinkel, Irwin

    2013-08-20

    Using data from the Fragile Families and Child Wellbeing Study, this study examined the effects of the Great Recession on maternal harsh parenting. We found that changes in macroeconomic conditions, rather than current conditions, affected harsh parenting, that declines in macroeconomic conditions had a stronger impact on harsh parenting than improvements in conditions, and that mothers' responses to adverse economic conditions were moderated by the DRD2 Taq1A genotype. We found no evidence of a moderating effect for two other, less well-studied SNPs from the DRD4 and DAT1 genes.

  13. Echo-Planar Imaging-Based, J-Resolved Spectroscopic Imaging for Improved Metabolite Detection in Prostate Cancer

    Science.gov (United States)

    2016-12-01

    post-process the multi-dimensional MRS data from different prostate pathologies . Scope: Improved cancer detection (specificity) in differentiating...MATERIALS AND METHODS Patients Between March 2012 and May 2013, twenty-two patients with PCa with a mean age of 63.8 years (range, 46–79 years), who...tumor voxels, which was confirmed by the pathology report. After reconstruction, the EP-JRESI data were overlaid onto MRI images. MRI and MRSI A body

  14. Theory, phenomenology, and prospects for detection of supersymmetric dark matter

    International Nuclear Information System (INIS)

    Diehl, E.; Kane, G.L.; Kolda, C.; Wells, J.D.

    1995-01-01

    One of the great attractions of minimal superunified supersymmetric models is the prediction of a massive, stable, weakly interacting particle [the lightest supersymmetric partner (LSP)] which can have the right relic abundance to be a cold dark matter candidate. In this paper we investigate the identity, mass, and properties of the LSP after requiring gauge coupling unification, proper electroweak symmetry breaking, and numerous phenomenological constraints. We then discuss the prospects for detecting the LSP. The experiments which we investigate are (1) space annihilations into positrons, antiprotons, and γ rays, (2) large underground arrays to detect upward-going muons arising from LSP capture and annihilation in the sun and earth, (3) elastic collisions on matter in a table top apparatus, and (4) production of LSP's or decays into LSP's at high energy colliders. Our conclusions are that space annihilation experiments and large underground detectors are of limited help in initially detecting the LSP although perhaps they could provide confirmation of a signal seen in other experiments, while table top detectors have considerable discovery potential. Colliders such as the CERN LEP II, an upgraded Fermilab, and the CERN LHC might be the best dark matter detectors of all. This paper improves on most previous analyses in the literature by (a) only considering parameters not already excluded by several physics constraints listed above, (b) presenting results that are independent of (usually untenable) parameter choices, (c) comparing opportunities to study the same cold dark matter, and (d) including minor technical improvements

  15. Change detection of medical images using dictionary learning techniques and principal component analysis.

    Science.gov (United States)

    Nika, Varvara; Babyn, Paul; Zhu, Hongmei

    2014-07-01

    Automatic change detection methods for identifying the changes of serial MR images taken at different times are of great interest to radiologists. The majority of existing change detection methods in medical imaging, and those of brain images in particular, include many preprocessing steps and rely mostly on statistical analysis of magnetic resonance imaging (MRI) scans. Although most methods utilize registration software, tissue classification remains a difficult and overwhelming task. Recently, dictionary learning techniques are being used in many areas of image processing, such as image surveillance, face recognition, remote sensing, and medical imaging. We present an improved version of the EigenBlockCD algorithm, named the EigenBlockCD-2. The EigenBlockCD-2 algorithm performs an initial global registration and identifies the changes between serial MR images of the brain. Blocks of pixels from a baseline scan are used to train local dictionaries to detect changes in the follow-up scan. We use PCA to reduce the dimensionality of the local dictionaries and the redundancy of data. Choosing the appropriate distance measure significantly affects the performance of our algorithm. We examine the differences between [Formula: see text] and [Formula: see text] norms as two possible similarity measures in the improved EigenBlockCD-2 algorithm. We show the advantages of the [Formula: see text] norm over the [Formula: see text] norm both theoretically and numerically. We also demonstrate the performance of the new EigenBlockCD-2 algorithm for detecting changes of MR images and compare our results with those provided in the recent literature. Experimental results with both simulated and real MRI scans show that our improved EigenBlockCD-2 algorithm outperforms the previous methods. It detects clinical changes while ignoring the changes due to the patient's position and other acquisition artifacts.

  16. Improved assessment of multiple sclerosis lesion segmentation agreement via detection and outline error estimates

    Directory of Open Access Journals (Sweden)

    Wack David S

    2012-07-01

    Full Text Available Abstract Background Presented is the method “Detection and Outline Error Estimates” (DOEE for assessing rater agreement in the delineation of multiple sclerosis (MS lesions. The DOEE method divides operator or rater assessment into two parts: 1 Detection Error (DE -- rater agreement in detecting the same regions to mark, and 2 Outline Error (OE -- agreement of the raters in outlining of the same lesion. Methods DE, OE and Similarity Index (SI values were calculated for two raters tested on a set of 17 fluid-attenuated inversion-recovery (FLAIR images of patients with MS. DE, OE, and SI values were tested for dependence with mean total area (MTA of the raters' Region of Interests (ROIs. Results When correlated with MTA, neither DE (ρ = .056, p=.83 nor the ratio of OE to MTA (ρ = .23, p=.37, referred to as Outline Error Rate (OER, exhibited significant correlation. In contrast, SI is found to be strongly correlated with MTA (ρ = .75, p  Conclusions The DE and OER indices are proposed as a better method than SI for comparing rater agreement of ROIs, which also provide specific information for raters to improve their agreement.

  17. Three-dimensional black-blood contrast-enhanced MRI improves detection of intraluminal thrombi in patients with acute ischaemic stroke.

    Science.gov (United States)

    Jang, Won; Kwak, Hyo Sung; Chung, Gyung Ho; Hwang, Seung Bae

    2018-03-19

    This study evaluated the utility of three-dimensional (3D), black-blood (BB), contrast-enhanced, magnetic resonance imaging (MRI) for the detection of intraluminal thrombi in acute stroke patients. Forty-seven patients with acute stroke involving the anterior circulation underwent MRI examination within 6 h of clinical onset. Cerebral angiography was used as the reference standard. In a blinded manner, two neuroradiologists interpreted the following three data sets: (1) diffusion-weighted imaging (DWI) + 3D BB contrast-enhanced MRI; (2) DWI + susceptibility weighted imaging (SWI); (3) DWI + 3D BB contrast-enhanced MRI + SWI. Of these patients, 47 had clots in the middle cerebral artery and four had clots in the anterior cerebral artery. For both observers, the area under the curve (Az) for data sets 1 and 3, which included 3D BB contrast-enhanced MRI, was significantly greater than it was for data set 2, which did not include 3D BB contrast-enhanced MR imaging (observer 1, 0.988 vs 0.904, p = 0.001; observer 2, 0.988 vs 0.894, p = 0.000). Three-dimensional BB contrast-enhanced MRI improves detection of intraluminal thrombi compared to conventional MRI methods in patients with acute ischaemic stroke. • BB contrast-enhanced MRI helps clinicians to assess the intraluminal clot • BB contrast-enhanced MRI improves detection of intraluminal thrombi • BB contrast-enhanced MRI for clot detection has a higher sensitivity.

  18. BMVC test, an improved fluorescence assay for detection of malignant pleural effusions

    International Nuclear Information System (INIS)

    Lin, I-Ting; Tsai, Yu-Lin; Kang, Chi-Chih; Huang, Wei-Chun; Wang, Chiung-Lin; Lin, Mei-Ying; Lou, Pei-Jen; Shih, Jin-Yuan; Wang, Hao-Chien; Wu, Huey-Dong; Tsai, Tzu-Hsiu; Jan, I-Shiow; Chang, Ta-Chau

    2014-01-01

    The diagnosis of malignant pleural effusions is an important issue in the management of malignancy patients. Generally, cytologic examination is a routine diagnostic technique. However, morphological interpretation of cytology is sometimes inconclusive. Here an ancillary method named BMVC test is developed for rapid detection of malignant pleural effusion to improve the diagnostic accuracy at low cost. A simple assay kit is designed to collect living cells from clinical pleural effusion and a fluorescence probe, 3,6-Bis(1-methyl-4-vinylpyridinium) carbazole diiodide (BMVC), is used to illuminate malignant cells. The fluorescence intensity is quantitatively analyzed by ImageJ program. This method yields digital numbers for the test results without any grey zone or ambiguities in the current cytology tests due to intra-observer and inter-observer variability. Comparing with results from double-blind cytologic examination, this simple test gives a good discrimination between malignant and benign specimens with sensitivity of 89.4% (42/47) and specificity of 93.3% (56/60) for diagnosis of malignant pleural effusion. BMVC test provides accurate results in a short time period, and the digital output could assist cytologic examination to become more objective and clear-cut. This is a convenient ancillary tool for detection of malignant pleural effusions

  19. Der Einfluss von personeller Einkommensverteilung auf die „Great Depression“ und die „Great Recession“

    Directory of Open Access Journals (Sweden)

    Stefan Trappl

    2015-12-01

    Full Text Available Der Einfluss gestiegener Einkommensungleichheit auf die „Great Depression“ und die „Great Recession“ wurde mehrfach postuliert (Galbraith 1954/2009; Eccles 1951; Rajan 2010; Stiglitz 2012; Piketty 2014. Konkrete empirische Arbeiten zum Zusammenhang zwischen Einkommensverteilung und dem Entstehen von Wirtschaftskrisen gibt es aber bislang wenige. Kumhof/Ranciere (2010 überprüften die von Rajan (2010 aufgestellte Hypothese, die einen entsprechenden Zusammenhang postuliert, mittels Modellrechnung. Bordo/Meissner (2012 und darauf aufbauend Gu/Huang (2014 verwendeten unterschiedliche Regressionsmodelle in Bezug auf einen entsprechenden Zusammenhang, ohne jedoch eindeutige Ergebnisse zu liefern. Die vorliegende Arbeit schließt an diese Arbeiten an, beschränkt die Untersuchung allerdings auf Staaten, für die Daten für die letzten hundert Jahre verfügbar sind, und untersucht zudem explizit die Zeiträume um die beiden größten Krisen der letzten hundert Jahre, die „Great Depression“ und die „Great Recession“. Die Auswertungen zeigen, dass die personelle Einkommensverteilung ein guter Prädiktor für die Kriseneintrittswahrscheinlichkeit ist.

  20. Leveraging Big Data to Improve Health Awareness Campaigns: A Novel Evaluation of the Great American Smokeout.

    Science.gov (United States)

    Ayers, John W; Westmaas, J Lee; Leas, Eric C; Benton, Adrian; Chen, Yunqi; Dredze, Mark; Althouse, Benjamin M

    2016-01-01

    Awareness campaigns are ubiquitous, but little is known about their potential effectiveness because traditional evaluations are often unfeasible. For 40 years, the "Great American Smokeout" (GASO) has encouraged media coverage and popular engagement with smoking cessation on the third Thursday of November as the nation's longest running awareness campaign. We proposed a novel evaluation framework for assessing awareness campaigns using the GASO as a case study by observing cessation-related news reports and Twitter postings, and cessation-related help seeking via Google, Wikipedia, and government-sponsored quitlines. Time trends (2009-2014) were analyzed using a quasi-experimental design to isolate spikes during the GASO by comparing observed outcomes on the GASO day with the simulated counterfactual had the GASO not occurred. Cessation-related news typically increased by 61% (95% CI 35-87) and tweets by 13% (95% CI -21 to 48) during the GASO compared with what was expected had the GASO not occurred. Cessation-related Google searches increased by 25% (95% CI 10-40), Wikipedia page visits by 22% (95% CI -26 to 67), and quitline calls by 42% (95% CI 19-64). Cessation-related news media positively coincided with cessation tweets, Internet searches, and Wikipedia visits; for example, a 50% increase in news for any year predicted a 28% (95% CI -2 to 59) increase in tweets for the same year. Increases on the day of the GASO rivaled about two-thirds of a typical New Year's Day-the day that is assumed to see the greatest increases in cessation-related activity. In practical terms, there were about 61,000 more instances of help seeking on Google, Wikipedia, or quitlines on GASO each year than would normally be expected. These findings provide actionable intelligence to improve the GASO and model how to rapidly, cost-effectively, and efficiently evaluate hundreds of awareness campaigns, nearly all for the first time.

  1. Improved detection and mapping of deepwater hydrocarbon seeps: optimizing multibeam echosounder seafloor backscatter acquisition and processing techniques

    Science.gov (United States)

    Mitchell, Garrett A.; Orange, Daniel L.; Gharib, Jamshid J.; Kennedy, Paul

    2018-02-01

    Marine seep hunting surveys are a current focus of hydrocarbon exploration surveys due to recent advances in offshore geophysical surveying, geochemical sampling, and analytical technologies. Hydrocarbon seeps are ephemeral, small, discrete, and therefore difficult to sample on the deep seafloor. Multibeam echosounders are an efficient seafloor exploration tool to remotely locate and map seep features. Geophysical signatures from hydrocarbon seeps are acoustically-evident in bathymetric, seafloor backscatter, midwater backscatter datasets. Interpretation of these signatures in backscatter datasets is a fundamental component of commercial seep hunting campaigns. Degradation of backscatter datasets resulting from environmental, geometric, and system noise can interfere with the detection and delineation of seeps. We present a relative backscatter intensity normalization method and an oversampling acquisition technique that can improve the geological resolvability of hydrocarbon seeps. We use Green Canyon (GC) Block 600 in the Northern Gulf of Mexico as a seep calibration site for a Kongsberg EM302 30 kHz MBES prior to the start of the Gigante seep hunting program to analyze these techniques. At GC600, we evaluate the results of a backscatter intensity normalization, assess the effectiveness of 2X seafloor coverage in resolving seep-related features in backscatter data, and determine the off-nadir detection limits of bubble plumes using the EM302. Incorporating these techniques into seep hunting surveys can improve the detectability and sampling of seafloor seeps.

  2. Improved detection and mapping of deepwater hydrocarbon seeps: optimizing multibeam echosounder seafloor backscatter acquisition and processing techniques

    Science.gov (United States)

    Mitchell, Garrett A.; Orange, Daniel L.; Gharib, Jamshid J.; Kennedy, Paul

    2018-06-01

    Marine seep hunting surveys are a current focus of hydrocarbon exploration surveys due to recent advances in offshore geophysical surveying, geochemical sampling, and analytical technologies. Hydrocarbon seeps are ephemeral, small, discrete, and therefore difficult to sample on the deep seafloor. Multibeam echosounders are an efficient seafloor exploration tool to remotely locate and map seep features. Geophysical signatures from hydrocarbon seeps are acoustically-evident in bathymetric, seafloor backscatter, midwater backscatter datasets. Interpretation of these signatures in backscatter datasets is a fundamental component of commercial seep hunting campaigns. Degradation of backscatter datasets resulting from environmental, geometric, and system noise can interfere with the detection and delineation of seeps. We present a relative backscatter intensity normalization method and an oversampling acquisition technique that can improve the geological resolvability of hydrocarbon seeps. We use Green Canyon (GC) Block 600 in the Northern Gulf of Mexico as a seep calibration site for a Kongsberg EM302 30 kHz MBES prior to the start of the Gigante seep hunting program to analyze these techniques. At GC600, we evaluate the results of a backscatter intensity normalization, assess the effectiveness of 2X seafloor coverage in resolving seep-related features in backscatter data, and determine the off-nadir detection limits of bubble plumes using the EM302. Incorporating these techniques into seep hunting surveys can improve the detectability and sampling of seafloor seeps.

  3. Improving Abnormality Detection on Chest Radiography Using Game-Like Reinforcement Mechanics.

    Science.gov (United States)

    Chen, Po-Hao; Roth, Howard; Galperin-Aizenberg, Maya; Ruutiainen, Alexander T; Gefter, Warren; Cook, Tessa S

    2017-11-01

    Despite their increasing prevalence, online textbooks, question banks, and digital references focus primarily on explicit knowledge. Implicit skills such as abnormality detection require repeated practice on clinical service and have few digital substitutes. Using mechanics traditionally deployed in video games such as clearly defined goals, rapid-fire levels, and narrow time constraints may be an effective way to teach implicit skills. We created a freely available, online module to evaluate the ability of individuals to differentiate between normal and abnormal chest radiographs by implementing mechanics, including instantaneous feedback, rapid-fire cases, and 15-second timers. Volunteer subjects completed the modules and were separated based on formal experience with chest radiography. Performance between training and testing sets were measured for each group, and a survey was administered after each session. The module contained 74 cases and took approximately 20 minutes to complete. Thirty-two cases were normal radiographs and 56 cases were abnormal. Of the 60 volunteers recruited, 25 were "never trained" and 35 were "previously trained." "Never trained" users scored 21.9 out of 37 during training and 24.0 out of 37 during testing (59.1% vs 64.9%, P value online module may improve the abnormality detection rates of novice interpreters of chest radiography, although experienced interpreters are less likely to derive similar benefits. Users reviewed the educational module favorably. Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

  4. Great Lakes Bathymetry

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetry of Lakes Michigan, Erie, Saint Clair, Ontario and Huron has been compiled as a component of a NOAA project to rescue Great Lakes lake floor geological and...

  5. Assessment of biomass cogeneration in the Great Lakes region

    International Nuclear Information System (INIS)

    Burnham, M.; Easterly, J.L.

    1994-01-01

    Many biomass cogeneration facilities have successfully entered into power sales agreements with utilities across the country, often after overcoming various difficulties or barriers. Under a project sponsored by the Great Lakes Regional Biomass Energy Program of the U.S. Department of Energy, DynCorp sm-bullet Meridian has conducted a survey of biomass facilities in the seven Great Lakes states, selecting 10 facilities for case studies with at least one facility in each of the seven states. The purpose of the case studies was to address obstacles that biomass processors face in adding power production to their process heat systems, and to provide examples of successful strategies for entering into power sales agreements with utilities. The case studies showed that the primary incentives for investing in cogeneration and power sales are to reduce operating costs through improved biomass waste management and lower energy expenditures. Common barriers to cogeneration and power sales were high utility stand-by charges