Statistical algorithms improve accuracy of gene fusion detection

PubMed Central

Hsieh, Gillian; Bierman, Rob; Szabo, Linda; Lee, Alex Gia; Freeman, Donald E.; Watson, Nathaniel; Sweet-Cordero, E. Alejandro

2017-01-01

Abstract Gene fusions are known to play critical roles in tumor pathogenesis. Yet, sensitive and specific algorithms to detect gene fusions in cancer do not currently exist. In this paper, we present a new statistical algorithm, MACHETE (Mismatched Alignment CHimEra Tracking Engine), which achieves highly sensitive and specific detection of gene fusions from RNA-Seq data, including the highest Positive Predictive Value (PPV) compared to the current state-of-the-art, as assessed in simulated data. We show that the best performing published algorithms either find large numbers of fusions in negative control data or suffer from low sensitivity detecting known driving fusions in gold standard settings, such as EWSR1-FLI1. As proof of principle that MACHETE discovers novel gene fusions with high accuracy in vivo, we mined public data to discover and subsequently PCR validate novel gene fusions missed by other algorithms in the ovarian cancer cell line OVCAR3. These results highlight the gains in accuracy achieved by introducing statistical models into fusion detection, and pave the way for unbiased discovery of potentially driving and druggable gene fusions in primary tumors. PMID:28541529

FusionAnalyser: a new graphical, event-driven tool for fusion rearrangements discovery

PubMed Central

Piazza, Rocco; Pirola, Alessandra; Spinelli, Roberta; Valletta, Simona; Redaelli, Sara; Magistroni, Vera; Gambacorti-Passerini, Carlo

2012-01-01

Gene fusions are common driver events in leukaemias and solid tumours; here we present FusionAnalyser, a tool dedicated to the identification of driver fusion rearrangements in human cancer through the analysis of paired-end high-throughput transcriptome sequencing data. We initially tested FusionAnalyser by using a set of in silico randomly generated sequencing data from 20 known human translocations occurring in cancer and subsequently using transcriptome data from three chronic and three acute myeloid leukaemia samples. in all the cases our tool was invariably able to detect the presence of the correct driver fusion event(s) with high specificity. In one of the acute myeloid leukaemia samples, FusionAnalyser identified a novel, cryptic, in-frame ETS2–ERG fusion. A fully event-driven graphical interface and a flexible filtering system allow complex analyses to be run in the absence of any a priori programming or scripting knowledge. Therefore, we propose FusionAnalyser as an efficient and robust graphical tool for the identification of functional rearrangements in the context of high-throughput transcriptome sequencing data. PMID:22570408

FusionAnalyser: a new graphical, event-driven tool for fusion rearrangements discovery.

PubMed

Piazza, Rocco; Pirola, Alessandra; Spinelli, Roberta; Valletta, Simona; Redaelli, Sara; Magistroni, Vera; Gambacorti-Passerini, Carlo

2012-09-01

Gene fusions are common driver events in leukaemias and solid tumours; here we present FusionAnalyser, a tool dedicated to the identification of driver fusion rearrangements in human cancer through the analysis of paired-end high-throughput transcriptome sequencing data. We initially tested FusionAnalyser by using a set of in silico randomly generated sequencing data from 20 known human translocations occurring in cancer and subsequently using transcriptome data from three chronic and three acute myeloid leukaemia samples. in all the cases our tool was invariably able to detect the presence of the correct driver fusion event(s) with high specificity. In one of the acute myeloid leukaemia samples, FusionAnalyser identified a novel, cryptic, in-frame ETS2-ERG fusion. A fully event-driven graphical interface and a flexible filtering system allow complex analyses to be run in the absence of any a priori programming or scripting knowledge. Therefore, we propose FusionAnalyser as an efficient and robust graphical tool for the identification of functional rearrangements in the context of high-throughput transcriptome sequencing data.

Gene Fusion Markup Language: a prototype for exchanging gene fusion data.

PubMed

Kalyana-Sundaram, Shanker; Shanmugam, Achiraman; Chinnaiyan, Arul M

2012-10-16

An avalanche of next generation sequencing (NGS) studies has generated an unprecedented amount of genomic structural variation data. These studies have also identified many novel gene fusion candidates with more detailed resolution than previously achieved. However, in the excitement and necessity of publishing the observations from this recently developed cutting-edge technology, no community standardization approach has arisen to organize and represent the data with the essential attributes in an interchangeable manner. As transcriptome studies have been widely used for gene fusion discoveries, the current non-standard mode of data representation could potentially impede data accessibility, critical analyses, and further discoveries in the near future. Here we propose a prototype, Gene Fusion Markup Language (GFML) as an initiative to provide a standard format for organizing and representing the significant features of gene fusion data. GFML will offer the advantage of representing the data in a machine-readable format to enable data exchange, automated analysis interpretation, and independent verification. As this database-independent exchange initiative evolves it will further facilitate the formation of related databases, repositories, and analysis tools. The GFML prototype is made available at http://code.google.com/p/gfml-prototype/. The Gene Fusion Markup Language (GFML) presented here could facilitate the development of a standard format for organizing, integrating and representing the significant features of gene fusion data in an inter-operable and query-able fashion that will enable biologically intuitive access to gene fusion findings and expedite functional characterization. A similar model is envisaged for other NGS data analyses.

Landcover classification in MRF context using Dempster-Shafer fusion for multisensor imagery.

PubMed

Sarkar, Anjan; Banerjee, Anjan; Banerjee, Nilanjan; Brahma, Siddhartha; Kartikeyan, B; Chakraborty, Manab; Majumder, K L

2005-05-01

This work deals with multisensor data fusion to obtain landcover classification. The role of feature-level fusion using the Dempster-Shafer rule and that of data-level fusion in the MRF context is studied in this paper to obtain an optimally segmented image. Subsequently, segments are validated and classification accuracy for the test data is evaluated. Two examples of data fusion of optical images and a synthetic aperture radar image are presented, each set having been acquired on different dates. Classification accuracies of the technique proposed are compared with those of some recent techniques in literature for the same image data.

a Comparative Analysis of Spatiotemporal Data Fusion Models for Landsat and Modis Data

NASA Astrophysics Data System (ADS)

Hazaymeh, K.; Almagbile, A.

2018-04-01

In this study, three documented spatiotemporal data fusion models were applied to Landsat-7 and MODIS surface reflectance, and NDVI. The algorithms included the spatial and temporal adaptive reflectance fusion model (STARFM), sparse representation based on a spatiotemporal reflectance fusion model (SPSTFM), and spatiotemporal image-fusion model (STI-FM). The objectives of this study were to (i) compare the performance of these three fusion models using a one Landsat-MODIS spectral reflectance image pairs using time-series datasets from the Coleambally irrigation area in Australia, and (ii) quantitatively evaluate the accuracy of the synthetic images generated from each fusion model using statistical measurements. Results showed that the three fusion models predicted the synthetic Landsat-7 image with adequate agreements. The STI-FM produced more accurate reconstructions of both Landsat-7 spectral bands and NDVI. Furthermore, it produced surface reflectance images having the highest correlation with the actual Landsat-7 images. This study indicated that STI-FM would be more suitable for spatiotemporal data fusion applications such as vegetation monitoring, drought monitoring, and evapotranspiration.

Gene Fusion Markup Language: a prototype for exchanging gene fusion data

PubMed Central

2012-01-01

Background An avalanche of next generation sequencing (NGS) studies has generated an unprecedented amount of genomic structural variation data. These studies have also identified many novel gene fusion candidates with more detailed resolution than previously achieved. However, in the excitement and necessity of publishing the observations from this recently developed cutting-edge technology, no community standardization approach has arisen to organize and represent the data with the essential attributes in an interchangeable manner. As transcriptome studies have been widely used for gene fusion discoveries, the current non-standard mode of data representation could potentially impede data accessibility, critical analyses, and further discoveries in the near future. Results Here we propose a prototype, Gene Fusion Markup Language (GFML) as an initiative to provide a standard format for organizing and representing the significant features of gene fusion data. GFML will offer the advantage of representing the data in a machine-readable format to enable data exchange, automated analysis interpretation, and independent verification. As this database-independent exchange initiative evolves it will further facilitate the formation of related databases, repositories, and analysis tools. The GFML prototype is made available at http://code.google.com/p/gfml-prototype/. Conclusion The Gene Fusion Markup Language (GFML) presented here could facilitate the development of a standard format for organizing, integrating and representing the significant features of gene fusion data in an inter-operable and query-able fashion that will enable biologically intuitive access to gene fusion findings and expedite functional characterization. A similar model is envisaged for other NGS data analyses. PMID:23072312

The Terra Data Fusion Project: An Update

NASA Astrophysics Data System (ADS)

Di Girolamo, L.; Bansal, S.; Butler, M.; Fu, D.; Gao, Y.; Lee, H. J.; Liu, Y.; Lo, Y. L.; Raila, D.; Turner, K.; Towns, J.; Wang, S. W.; Yang, K.; Zhao, G.

2017-12-01

Terra is the flagship of NASA's Earth Observing System. Launched in 1999, Terra's five instruments continue to gather data that enable scientists to address fundamental Earth science questions. By design, the strength of the Terra mission has always been rooted in its five instruments and the ability to fuse the instrument data together for obtaining greater quality of information for Earth Science compared to individual instruments alone. As the data volume grows and the central Earth Science questions move towards problems requiring decadal-scale data records, the need for data fusion and the ability for scientists to perform large-scale analytics with long records have never been greater. The challenge is particularly acute for Terra, given its growing volume of data (> 1 petabyte), the storage of different instrument data at different archive centers, the different file formats and projection systems employed for different instrument data, and the inadequate cyberinfrastructure for scientists to access and process whole-mission fusion data (including Level 1 data). Sharing newly derived Terra products with the rest of the world also poses challenges. As such, the Terra Data Fusion Project aims to resolve two long-standing problems: 1) How do we efficiently generate and deliver Terra data fusion products? 2) How do we facilitate the use of Terra data fusion products by the community in generating new products and knowledge through national computing facilities, and disseminate these new products and knowledge through national data sharing services? Here, we will provide an update on significant progress made in addressing these problems by working with NASA and leveraging national facilities managed by the National Center for Supercomputing Applications (NCSA). The problems that we faced in deriving and delivering Terra L1B2 basic, reprojected and cloud-element fusion products, such as data transfer, data fusion, processing on different computer architectures, science, and sharing, will be presented with quantitative specifics. Results from several science-specific drivers for Terra fusion products will also be presented. We demonstrate that the Terra Data Fusion Project itself provides an excellent use-case for the community addressing Big Data and cyberinfrastructure problems.

A Data Fusion Method in Wireless Sensor Networks

PubMed Central

Izadi, Davood; Abawajy, Jemal H.; Ghanavati, Sara; Herawan, Tutut

2015-01-01

The success of a Wireless Sensor Network (WSN) deployment strongly depends on the quality of service (QoS) it provides regarding issues such as data accuracy, data aggregation delays and network lifetime maximisation. This is especially challenging in data fusion mechanisms, where a small fraction of low quality data in the fusion input may negatively impact the overall fusion result. In this paper, we present a fuzzy-based data fusion approach for WSN with the aim of increasing the QoS whilst reducing the energy consumption of the sensor network. The proposed approach is able to distinguish and aggregate only true values of the collected data as such, thus reducing the burden of processing the entire data at the base station (BS). It is also able to eliminate redundant data and consequently reduce energy consumption thus increasing the network lifetime. We studied the effectiveness of the proposed data fusion approach experimentally and compared it with two baseline approaches in terms of data collection, number of transferred data packets and energy consumption. The results of the experiments show that the proposed approach achieves better results than the baseline approaches. PMID:25635417

Reliability of Measured Data for pH Sensor Arrays with Fault Diagnosis and Data Fusion Based on LabVIEW

PubMed Central

Liao, Yi-Hung; Chou, Jung-Chuan; Lin, Chin-Yi

2013-01-01

Fault diagnosis (FD) and data fusion (DF) technologies implemented in the LabVIEW program were used for a ruthenium dioxide pH sensor array. The purpose of the fault diagnosis and data fusion technologies is to increase the reliability of measured data. Data fusion is a very useful statistical method used for sensor arrays in many fields. Fault diagnosis is used to avoid sensor faults and to measure errors in the electrochemical measurement system, therefore, in this study, we use fault diagnosis to remove any faulty sensors in advance, and then proceed with data fusion in the sensor array. The average, self-adaptive and coefficient of variance data fusion methods are used in this study. The pH electrode is fabricated with ruthenium dioxide (RuO2) sensing membrane using a sputtering system to deposit it onto a silicon substrate, and eight RuO2 pH electrodes are fabricated to form a sensor array for this study. PMID:24351636

Reliability of measured data for pH sensor arrays with fault diagnosis and data fusion based on LabVIEW.

PubMed

Liao, Yi-Hung; Chou, Jung-Chuan; Lin, Chin-Yi

2013-12-13

Fault diagnosis (FD) and data fusion (DF) technologies implemented in the LabVIEW program were used for a ruthenium dioxide pH sensor array. The purpose of the fault diagnosis and data fusion technologies is to increase the reliability of measured data. Data fusion is a very useful statistical method used for sensor arrays in many fields. Fault diagnosis is used to avoid sensor faults and to measure errors in the electrochemical measurement system, therefore, in this study, we use fault diagnosis to remove any faulty sensors in advance, and then proceed with data fusion in the sensor array. The average, self-adaptive and coefficient of variance data fusion methods are used in this study. The pH electrode is fabricated with ruthenium dioxide (RuO2) sensing membrane using a sputtering system to deposit it onto a silicon substrate, and eight RuO2 pH electrodes are fabricated to form a sensor array for this study.

Pairwise diversity ranking of polychotomous features for ensemble physiological signal classifiers.

PubMed

Gupta, Lalit; Kota, Srinivas; Molfese, Dennis L; Vaidyanathan, Ravi

2013-06-01

It is well known that fusion classifiers for physiological signal classification with diverse components (classifiers or data sets) outperform those with less diverse components. Determining component diversity, therefore, is of the utmost importance in the design of fusion classifiers that are often employed in clinical diagnostic and numerous other pattern recognition problems. In this article, a new pairwise diversity-based ranking strategy is introduced to select a subset of ensemble components, which when combined will be more diverse than any other component subset of the same size. The strategy is unified in the sense that the components can be classifiers or data sets. Moreover, the classifiers and data sets can be polychotomous. Classifier-fusion and data-fusion systems are formulated based on the diversity-based selection strategy, and the application of the two fusion strategies are demonstrated through the classification of multichannel event-related potentials. It is observed that for both classifier and data fusion, the classification accuracy tends to increase/decrease when the diversity of the component ensemble increases/decreases. For the four sets of 14-channel event-related potentials considered, it is shown that data fusion outperforms classifier fusion. Furthermore, it is demonstrated that the combination of data components that yield the best performance, in a relative sense, can be determined through the diversity-based selection strategy.

Spatial Statistical Data Fusion for Remote Sensing Applications

NASA Technical Reports Server (NTRS)

Nguyen, Hai

2010-01-01

Data fusion is the process of combining information from heterogeneous sources into a single composite picture of the relevant process, such that the composite picture is generally more accurate and complete than that derived from any single source alone. Data collection is often incomplete, sparse, and yields incompatible information. Fusion techniques can make optimal use of such data. When investment in data collection is high, fusion gives the best return. Our study uses data from two satellites: (1) Multiangle Imaging SpectroRadiometer (MISR), (2) Moderate Resolution Imaging Spectroradiometer (MODIS).

Blob-level active-passive data fusion for Benthic classification

NASA Astrophysics Data System (ADS)

Park, Joong Yong; Kalluri, Hemanth; Mathur, Abhinav; Ramnath, Vinod; Kim, Minsu; Aitken, Jennifer; Tuell, Grady

2012-06-01

We extend the data fusion pixel level to the more semantically meaningful blob level, using the mean-shift algorithm to form labeled blobs having high similarity in the feature domain, and connectivity in the spatial domain. We have also developed Bhattacharyya Distance (BD) and rule-based classifiers, and have implemented these higher-level data fusion algorithms into the CZMIL Data Processing System. Applying these new algorithms to recent SHOALS and CASI data at Plymouth Harbor, Massachusetts, we achieved improved benthic classification accuracies over those produced with either single sensor, or pixel-level fusion strategies. These results appear to validate the hypothesis that classification accuracy may be generally improved by adopting higher spatial and semantic levels of fusion.

Data fusion algorithm for rapid multi-mode dust concentration measurement system based on MEMS

NASA Astrophysics Data System (ADS)

Liao, Maohao; Lou, Wenzhong; Wang, Jinkui; Zhang, Yan

2018-03-01

As single measurement method cannot fully meet the technical requirements of dust concentration measurement, the multi-mode detection method is put forward, as well as the new requirements for data processing. This paper presents a new dust concentration measurement system which contains MEMS ultrasonic sensor and MEMS capacitance sensor, and presents a new data fusion algorithm for this multi-mode dust concentration measurement system. After analyzing the relation between the data of the composite measurement method, the data fusion algorithm based on Kalman filtering is established, which effectively improve the measurement accuracy, and ultimately forms a rapid data fusion model of dust concentration measurement. Test results show that the data fusion algorithm is able to realize the rapid and exact concentration detection.

ChimerDB 3.0: an enhanced database for fusion genes from cancer transcriptome and literature data mining.

PubMed

Lee, Myunggyo; Lee, Kyubum; Yu, Namhee; Jang, Insu; Choi, Ikjung; Kim, Pora; Jang, Ye Eun; Kim, Byounggun; Kim, Sunkyu; Lee, Byungwook; Kang, Jaewoo; Lee, Sanghyuk

2017-01-04

Fusion gene is an important class of therapeutic targets and prognostic markers in cancer. ChimerDB is a comprehensive database of fusion genes encompassing analysis of deep sequencing data and manual curations. In this update, the database coverage was enhanced considerably by adding two new modules of The Cancer Genome Atlas (TCGA) RNA-Seq analysis and PubMed abstract mining. ChimerDB 3.0 is composed of three modules of ChimerKB, ChimerPub and ChimerSeq. ChimerKB represents a knowledgebase including 1066 fusion genes with manual curation that were compiled from public resources of fusion genes with experimental evidences. ChimerPub includes 2767 fusion genes obtained from text mining of PubMed abstracts. ChimerSeq module is designed to archive the fusion candidates from deep sequencing data. Importantly, we have analyzed RNA-Seq data of the TCGA project covering 4569 patients in 23 cancer types using two reliable programs of FusionScan and TopHat-Fusion. The new user interface supports diverse search options and graphic representation of fusion gene structure. ChimerDB 3.0 is available at http://ercsb.ewha.ac.kr/fusiongene/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Real-time sensor validation and fusion for distributed autonomous sensors

NASA Astrophysics Data System (ADS)

Yuan, Xiaojing; Li, Xiangshang; Buckles, Bill P.

2004-04-01

Multi-sensor data fusion has found widespread applications in industrial and research sectors. The purpose of real time multi-sensor data fusion is to dynamically estimate an improved system model from a set of different data sources, i.e., sensors. This paper presented a systematic and unified real time sensor validation and fusion framework (RTSVFF) based on distributed autonomous sensors. The RTSVFF is an open architecture which consists of four layers - the transaction layer, the process fusion layer, the control layer, and the planning layer. This paradigm facilitates distribution of intelligence to the sensor level and sharing of information among sensors, controllers, and other devices in the system. The openness of the architecture also provides a platform to test different sensor validation and fusion algorithms and thus facilitates the selection of near optimal algorithms for specific sensor fusion application. In the version of the model presented in this paper, confidence weighted averaging is employed to address the dynamic system state issue noted above. The state is computed using an adaptive estimator and dynamic validation curve for numeric data fusion and a robust diagnostic map for decision level qualitative fusion. The framework is then applied to automatic monitoring of a gas-turbine engine, including a performance comparison of the proposed real-time sensor fusion algorithms and a traditional numerical weighted average.

Radiation and Electromagnetic Induction Data Fusion for Detection of Buried Radioactive Metal Waste - 12282

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

Long, Zhiling; Wei, Wei; Turlapaty, Anish

2012-07-01

At the United States Army's test sites, fired penetrators made of Depleted Uranium (DU) have been buried under ground and become hazardous waste. Previously, we developed techniques for detecting buried radioactive targets. We also developed approaches for locating buried paramagnetic metal objects by utilizing the electromagnetic induction (EMI) sensor data. In this paper, we apply data fusion techniques to combine results from both the radiation detection and the EMI detection, so that we can further distinguish among DU penetrators, DU oxide, and non- DU metal debris. We develop a two-step fusion approach for the task, and test it with surveymore » data collected on simulation targets. In this work, we explored radiation and EMI data fusion for detecting DU, oxides, and non-DU metals. We developed a two-step fusion approach based on majority voting and a set of decision rules. With this approach, we fuse results from radiation detection based on the RX algorithm and EMI detection based on a 3-step analysis. Our fusion approach has been tested successfully with data collected on simulation targets. In the future, we will need to further verify the effectiveness of this fusion approach with field data. (authors)« less

FuzzyFusion: an application architecture for multisource information fusion

NASA Astrophysics Data System (ADS)

Fox, Kevin L.; Henning, Ronda R.

2009-04-01

The correlation of information from disparate sources has long been an issue in data fusion research. Traditional data fusion addresses the correlation of information from sources as diverse as single-purpose sensors to all-source multi-media information. Information system vulnerability information is similar in its diversity of sources and content, and in the desire to draw a meaningful conclusion, namely, the security posture of the system under inspection. FuzzyFusionTM, A data fusion model that is being applied to the computer network operations domain is presented. This model has been successfully prototyped in an applied research environment and represents a next generation assurance tool for system and network security.

Graph-based Data Modeling and Analysis for Data Fusion in Remote Sensing

NASA Astrophysics Data System (ADS)

Fan, Lei

Hyperspectral imaging provides the capability of increased sensitivity and discrimination over traditional imaging methods by combining standard digital imaging with spectroscopic methods. For each individual pixel in a hyperspectral image (HSI), a continuous spectrum is sampled as the spectral reflectance/radiance signature to facilitate identification of ground cover and surface material. The abundant spectrum knowledge allows all available information from the data to be mined. The superior qualities within hyperspectral imaging allow wide applications such as mineral exploration, agriculture monitoring, and ecological surveillance, etc. The processing of massive high-dimensional HSI datasets is a challenge since many data processing techniques have a computational complexity that grows exponentially with the dimension. Besides, a HSI dataset may contain a limited number of degrees of freedom due to the high correlations between data points and among the spectra. On the other hand, merely taking advantage of the sampled spectrum of individual HSI data point may produce inaccurate results due to the mixed nature of raw HSI data, such as mixed pixels, optical interferences and etc. Fusion strategies are widely adopted in data processing to achieve better performance, especially in the field of classification and clustering. There are mainly three types of fusion strategies, namely low-level data fusion, intermediate-level feature fusion, and high-level decision fusion. Low-level data fusion combines multi-source data that is expected to be complementary or cooperative. Intermediate-level feature fusion aims at selection and combination of features to remove redundant information. Decision level fusion exploits a set of classifiers to provide more accurate results. The fusion strategies have wide applications including HSI data processing. With the fast development of multiple remote sensing modalities, e.g. Very High Resolution (VHR) optical sensors, LiDAR, etc., fusion of multi-source data can in principal produce more detailed information than each single source. On the other hand, besides the abundant spectral information contained in HSI data, features such as texture and shape may be employed to represent data points from a spatial perspective. Furthermore, feature fusion also includes the strategy of removing redundant and noisy features in the dataset. One of the major problems in machine learning and pattern recognition is to develop appropriate representations for complex nonlinear data. In HSI processing, a particular data point is usually described as a vector with coordinates corresponding to the intensities measured in the spectral bands. This vector representation permits the application of linear and nonlinear transformations with linear algebra to find an alternative representation of the data. More generally, HSI is multi-dimensional in nature and the vector representation may lose the contextual correlations. Tensor representation provides a more sophisticated modeling technique and a higher-order generalization to linear subspace analysis. In graph theory, data points can be generalized as nodes with connectivities measured from the proximity of a local neighborhood. The graph-based framework efficiently characterizes the relationships among the data and allows for convenient mathematical manipulation in many applications, such as data clustering, feature extraction, feature selection and data alignment. In this thesis, graph-based approaches applied in the field of multi-source feature and data fusion in remote sensing area are explored. We will mainly investigate the fusion of spatial, spectral and LiDAR information with linear and multilinear algebra under graph-based framework for data clustering and classification problems.

Multi-Sensor Optimal Data Fusion Based on the Adaptive Fading Unscented Kalman Filter

PubMed Central

Gao, Bingbing; Hu, Gaoge; Gao, Shesheng; Gu, Chengfan

2018-01-01

This paper presents a new optimal data fusion methodology based on the adaptive fading unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has a two-level fusion structure: at the bottom level, an adaptive fading unscented Kalman filter based on the Mahalanobis distance is developed and serves as local filters to improve the adaptability and robustness of local state estimations against process-modeling error; at the top level, an unscented transformation-based multi-sensor optimal data fusion for the case of N local filters is established according to the principle of linear minimum variance to calculate globally optimal state estimation by fusion of local estimations. The proposed methodology effectively refrains from the influence of process-modeling error on the fusion solution, leading to improved adaptability and robustness of data fusion for multi-sensor nonlinear stochastic systems. It also achieves globally optimal fusion results based on the principle of linear minimum variance. Simulation and experimental results demonstrate the efficacy of the proposed methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite system/celestial navigation system) integrated navigation. PMID:29415509

Multi-Sensor Optimal Data Fusion Based on the Adaptive Fading Unscented Kalman Filter.

PubMed

Gao, Bingbing; Hu, Gaoge; Gao, Shesheng; Zhong, Yongmin; Gu, Chengfan

2018-02-06

This paper presents a new optimal data fusion methodology based on the adaptive fading unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has a two-level fusion structure: at the bottom level, an adaptive fading unscented Kalman filter based on the Mahalanobis distance is developed and serves as local filters to improve the adaptability and robustness of local state estimations against process-modeling error; at the top level, an unscented transformation-based multi-sensor optimal data fusion for the case of N local filters is established according to the principle of linear minimum variance to calculate globally optimal state estimation by fusion of local estimations. The proposed methodology effectively refrains from the influence of process-modeling error on the fusion solution, leading to improved adaptability and robustness of data fusion for multi-sensor nonlinear stochastic systems. It also achieves globally optimal fusion results based on the principle of linear minimum variance. Simulation and experimental results demonstrate the efficacy of the proposed methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite system/celestial navigation system) integrated navigation.

Forecasting Chronic Diseases Using Data Fusion.

PubMed

Acar, Evrim; Gürdeniz, Gözde; Savorani, Francesco; Hansen, Louise; Olsen, Anja; Tjønneland, Anne; Dragsted, Lars Ove; Bro, Rasmus

2017-07-07

Data fusion, that is, extracting information through the fusion of complementary data sets, is a topic of great interest in metabolomics because analytical platforms such as liquid chromatography-mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR) spectroscopy commonly used for chemical profiling of biofluids provide complementary information. In this study, with a goal of forecasting acute coronary syndrome (ACS), breast cancer, and colon cancer, we jointly analyzed LC-MS, NMR measurements of plasma samples, and the metadata corresponding to the lifestyle of participants. We used supervised data fusion based on multiple kernel learning and exploited the linearity of the models to identify significant metabolites/features for the separation of healthy referents and the cases developing a disease. We demonstrated that (i) fusing LC-MS, NMR, and metadata provided better separation of ACS cases and referents compared with individual data sets, (ii) NMR data performed the best in terms of forecasting breast cancer, while fusion degraded the performance, and (iii) neither the individual data sets nor their fusion performed well for colon cancer. Furthermore, we showed the strengths and limitations of the fusion models by discussing their performance in terms of capturing known biomarkers for smoking and coffee. While fusion may improve performance in terms of separating certain conditions by jointly analyzing metabolomics and metadata sets, it is not necessarily always the best approach as in the case of breast cancer.

Condorcet and borda count fusion method for ligand-based virtual screening.

PubMed

Ahmed, Ali; Saeed, Faisal; Salim, Naomie; Abdo, Ammar

2014-01-01

It is known that any individual similarity measure will not always give the best recall of active molecule structure for all types of activity classes. Recently, the effectiveness of ligand-based virtual screening approaches can be enhanced by using data fusion. Data fusion can be implemented using two different approaches: group fusion and similarity fusion. Similarity fusion involves searching using multiple similarity measures. The similarity scores, or ranking, for each similarity measure are combined to obtain the final ranking of the compounds in the database. The Condorcet fusion method was examined. This approach combines the outputs of similarity searches from eleven association and distance similarity coefficients, and then the winner measure for each class of molecules, based on Condorcet fusion, was chosen to be the best method of searching. The recall of retrieved active molecules at top 5% and significant test are used to evaluate our proposed method. The MDL drug data report (MDDR), maximum unbiased validation (MUV) and Directory of Useful Decoys (DUD) data sets were used for experiments and were represented by 2D fingerprints. Simulated virtual screening experiments with the standard two data sets show that the use of Condorcet fusion provides a very simple way of improving the ligand-based virtual screening, especially when the active molecules being sought have a lowest degree of structural heterogeneity. However, the effectiveness of the Condorcet fusion was increased slightly when structural sets of high diversity activities were being sought.

Condorcet and borda count fusion method for ligand-based virtual screening

PubMed Central

2014-01-01

Background It is known that any individual similarity measure will not always give the best recall of active molecule structure for all types of activity classes. Recently, the effectiveness of ligand-based virtual screening approaches can be enhanced by using data fusion. Data fusion can be implemented using two different approaches: group fusion and similarity fusion. Similarity fusion involves searching using multiple similarity measures. The similarity scores, or ranking, for each similarity measure are combined to obtain the final ranking of the compounds in the database. Results The Condorcet fusion method was examined. This approach combines the outputs of similarity searches from eleven association and distance similarity coefficients, and then the winner measure for each class of molecules, based on Condorcet fusion, was chosen to be the best method of searching. The recall of retrieved active molecules at top 5% and significant test are used to evaluate our proposed method. The MDL drug data report (MDDR), maximum unbiased validation (MUV) and Directory of Useful Decoys (DUD) data sets were used for experiments and were represented by 2D fingerprints. Conclusions Simulated virtual screening experiments with the standard two data sets show that the use of Condorcet fusion provides a very simple way of improving the ligand-based virtual screening, especially when the active molecules being sought have a lowest degree of structural heterogeneity. However, the effectiveness of the Condorcet fusion was increased slightly when structural sets of high diversity activities were being sought. PMID:24883114

Distributed Multisensor Data Fusion under Unknown Correlation and Data Inconsistency

PubMed Central

Abu Bakr, Muhammad; Lee, Sukhan

2017-01-01

The paradigm of multisensor data fusion has been evolved from a centralized architecture to a decentralized or distributed architecture along with the advancement in sensor and communication technologies. These days, distributed state estimation and data fusion has been widely explored in diverse fields of engineering and control due to its superior performance over the centralized one in terms of flexibility, robustness to failure and cost effectiveness in infrastructure and communication. However, distributed multisensor data fusion is not without technical challenges to overcome: namely, dealing with cross-correlation and inconsistency among state estimates and sensor data. In this paper, we review the key theories and methodologies of distributed multisensor data fusion available to date with a specific focus on handling unknown correlation and data inconsistency. We aim at providing readers with a unifying view out of individual theories and methodologies by presenting a formal analysis of their implications. Finally, several directions of future research are highlighted. PMID:29077035

Regional distribution of forest height and biomass from multisensor data fusion

Treesearch

Yifan Yu; Sassan Saatch; Linda S. Heath; Elizabeth LaPoint; Ranga Myneni; Yuri Knyazikhin

2010-01-01

Elevation data acquired from radar interferometry at C-band from SRTM are used in data fusion techniques to estimate regional scale forest height and aboveground live biomass (AGLB) over the state of Maine. Two fusion techniques have been developed to perform post-processing and parameter estimations from four data sets: 1 arc sec National Elevation Data (NED), SRTM...

Tools and Methods for the Registration and Fusion of Remotely Sensed Data

NASA Technical Reports Server (NTRS)

Goshtasby, Arthur Ardeshir; LeMoigne, Jacqueline

2010-01-01

Tools and methods for image registration were reviewed. Methods for the registration of remotely sensed data at NASA were discussed. Image fusion techniques were reviewed. Challenges in registration of remotely sensed data were discussed. Examples of image registration and image fusion were given.

Information Fusion - Methods and Aggregation Operators

NASA Astrophysics Data System (ADS)

Torra, Vicenç

Information fusion techniques are commonly applied in Data Mining and Knowledge Discovery. In this chapter, we will give an overview of such applications considering their three main uses. This is, we consider fusion methods for data preprocessing, model building and information extraction. Some aggregation operators (i.e. particular fusion methods) and their properties are briefly described as well.

Enhanced chemical weapon warning via sensor fusion

NASA Astrophysics Data System (ADS)

Flaherty, Michael; Pritchett, Daniel; Cothren, Brian; Schwaiger, James

2011-05-01

Torch Technologies Inc., is actively involved in chemical sensor networking and data fusion via multi-year efforts with Dugway Proving Ground (DPG) and the Defense Threat Reduction Agency (DTRA). The objective of these efforts is to develop innovative concepts and advanced algorithms that enhance our national Chemical Warfare (CW) test and warning capabilities via the fusion of traditional and non-traditional CW sensor data. Under Phase I, II, and III Small Business Innovative Research (SBIR) contracts with DPG, Torch developed the Advanced Chemical Release Evaluation System (ACRES) software to support non real-time CW sensor data fusion. Under Phase I and II SBIRs with DTRA in conjunction with the Edgewood Chemical Biological Center (ECBC), Torch is using the DPG ACRES CW sensor data fuser as a framework from which to develop the Cloud state Estimation in a Networked Sensor Environment (CENSE) data fusion system. Torch is currently developing CENSE to implement and test innovative real-time sensor network based data fusion concepts using CW and non-CW ancillary sensor data to improve CW warning and detection in tactical scenarios.

The national ignition facility and atomic data

NASA Astrophysics Data System (ADS)

Crandall, David H.

1998-07-01

The National Ignition Facility (NIF) is under construction, capping over 25 years of development of the inertial confinement fusion concept by providing the facility to obtain fusion ignition in the laboratory for the first time. The NIF is a 192 beam glass laser to provide energy controlled in space and time so that a millimeter-scale capsule containing deuterium and tritium can be compressed to fusion conditions. Light transport, conversion of light in frequency, interaction of light with matter in solid and plasma forms, and diagnostics of extreme material conditions on small scale all use atomic data in preparing for use of the NIF. The NIF will provide opportunity to make measurements of atomic data in extreme physical environments related to fusion energy, nuclear weapon detonation, and astrophysics. The first laser beams of NIF should be operational in 2001 and the full facility completed at the end of 2003. NIF is to provide 1.8 megajoule of blue light on fusion targets and is intended to achieve fusion ignition by about the end of 2007. Today's inertial fusion development activities use atomic data to design and predict fusion capsule performance and in non-fusion applications to analyze radiation transport and radiation effects on matter. Conditions investigated involve radiation temperature of hundreds of eV, pressures up to gigabars and time scales of femptoseconds.

[Time consumption and quality of an automated fusion tool for SPECT and MRI images of the brain].

PubMed

Fiedler, E; Platsch, G; Schwarz, A; Schmiedehausen, K; Tomandl, B; Huk, W; Rupprecht, Th; Rahn, N; Kuwert, T

2003-10-01

Although the fusion of images from different modalities may improve diagnostic accuracy, it is rarely used in clinical routine work due to logistic problems. Therefore we evaluated performance and time needed for fusing MRI and SPECT images using a semiautomated dedicated software. PATIENTS, MATERIAL AND METHOD: In 32 patients regional cerebral blood flow was measured using (99m)Tc ethylcystein dimer (ECD) and the three-headed SPECT camera MultiSPECT 3. MRI scans of the brain were performed using either a 0,2 T Open or a 1,5 T Sonata. Twelve of the MRI data sets were acquired using a 3D-T1w MPRAGE sequence, 20 with a 2D acquisition technique and different echo sequences. Image fusion was performed on a Syngo workstation using an entropy minimizing algorithm by an experienced user of the software. The fusion results were classified. We measured the time needed for the automated fusion procedure and in case of need that for manual realignment after automated, but insufficient fusion. The mean time of the automated fusion procedure was 123 s. It was for the 2D significantly shorter than for the 3D MRI datasets. For four of the 2D data sets and two of the 3D data sets an optimal fit was reached using the automated approach. The remaining 26 data sets required manual correction. The sum of the time required for automated fusion and that needed for manual correction averaged 320 s (50-886 s). The fusion of 3D MRI data sets lasted significantly longer than that of the 2D MRI data. The automated fusion tool delivered in 20% an optimal fit, in 80% manual correction was necessary. Nevertheless, each of the 32 SPECT data sets could be merged in less than 15 min with the corresponding MRI data, which seems acceptable for clinical routine use.

Operational data fusion framework for building frequent Landsat-like imagery in a cloudy region

USDA-ARS?s Scientific Manuscript database

An operational data fusion framework is built to generate dense time-series Landsat-like images for a cloudy region by fusing Moderate Resolution Imaging Spectroradiometer (MODIS) data products and Landsat imagery. The Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) is integrated in ...

Flight data results of estimate fusion for spacecraft rendezvous navigation from shuttle mission STS-69

NASA Technical Reports Server (NTRS)

Carpenter, J. Russell; Bishop, Robert H.

1996-01-01

A recently developed rendezvous navigation fusion filter that optimally exploits existing distributed filters for rendezvous and GPS navigation to achieve the relative and inertial state accuracies of both in a global solution is utilized here to process actual flight data. Space Shuttle Mission STS-69 was the first mission to date which gathered data from both the rendezvous and Global Positioning System filters allowing, for the first time, a test of the fusion algorithm with real flight data. Furthermore, a precise best estimate of trajectory is available for portions of STS-69, making possible a check on the performance of the fusion filter. In order to successfully carry out this experiment with flight data, two extensions to the existing scheme were necessary: a fusion edit test based on differences between the filter state vectors, and an underweighting scheme to accommodate the suboptimal perfect target assumption made by the Shuttle rendezvous filter. With these innovations, the flight data was successfully fused from playbacks of downlinked and/or recorded measurement data through ground analysis versions of the Shuttle rendezvous filter and a GPS filter developed for another experiment. The fusion results agree with the best estimate of trajectory at approximately the levels of uncertainty expected from the fusion filter's covariance matrix.

chimeraviz: a tool for visualizing chimeric RNA.

PubMed

Lågstad, Stian; Zhao, Sen; Hoff, Andreas M; Johannessen, Bjarne; Lingjærde, Ole Christian; Skotheim, Rolf I

2017-09-15

Advances in high-throughput RNA sequencing have enabled more efficient detection of fusion transcripts, but the technology and associated software used for fusion detection from sequencing data often yield a high false discovery rate. Good prioritization of the results is important, and this can be helped by a visualization framework that automatically integrates RNA data with known genomic features. Here we present chimeraviz , a Bioconductor package that automates the creation of chimeric RNA visualizations. The package supports input from nine different fusion-finder tools: deFuse, EricScript, InFusion, JAFFA, FusionCatcher, FusionMap, PRADA, SOAPfuse and STAR-FUSION. chimeraviz is an R package available via Bioconductor ( https://bioconductor.org/packages/release/bioc/html/chimeraviz.html ) under Artistic-2.0. Source code and support is available at GitHub ( https://github.com/stianlagstad/chimeraviz ). rolf.i.skotheim@rr-research.no. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Discovering and understanding oncogenic gene fusions through data intensive computational approaches

PubMed Central

Latysheva, Natasha S.; Babu, M. Madan

2016-01-01

Abstract Although gene fusions have been recognized as important drivers of cancer for decades, our understanding of the prevalence and function of gene fusions has been revolutionized by the rise of next-generation sequencing, advances in bioinformatics theory and an increasing capacity for large-scale computational biology. The computational work on gene fusions has been vastly diverse, and the present state of the literature is fragmented. It will be fruitful to merge three camps of gene fusion bioinformatics that appear to rarely cross over: (i) data-intensive computational work characterizing the molecular biology of gene fusions; (ii) development research on fusion detection tools, candidate fusion prioritization algorithms and dedicated fusion databases and (iii) clinical research that seeks to either therapeutically target fusion transcripts and proteins or leverages advances in detection tools to perform large-scale surveys of gene fusion landscapes in specific cancer types. In this review, we unify these different—yet highly complementary and symbiotic—approaches with the view that increased synergy will catalyze advancements in gene fusion identification, characterization and significance evaluation. PMID:27105842

Data fusion for CD metrology: heterogeneous hybridization of scatterometry, CDSEM, and AFM data

NASA Astrophysics Data System (ADS)

Hazart, J.; Chesneau, N.; Evin, G.; Largent, A.; Derville, A.; Thérèse, R.; Bos, S.; Bouyssou, R.; Dezauzier, C.; Foucher, J.

2014-04-01

The manufacturing of next generation semiconductor devices forces metrology tool providers for an exceptional effort in order to meet the requirements for precision, accuracy and throughput stated in the ITRS. In the past years hybrid metrology (based on data fusion theories) has been investigated as a new methodology for advanced metrology [1][2][3]. This paper provides a new point of view of data fusion for metrology through some experiments and simulations. The techniques are presented concretely in terms of equations to be solved. The first point of view is High Level Fusion which is the use of simple numbers with their associated uncertainty postprocessed by tools. In this paper, it is divided into two stages: one for calibration to reach accuracy, the second to reach precision thanks to Bayesian Fusion. From our perspective, the first stage is mandatory before applying the second stage which is commonly presented [1]. However a reference metrology system is necessary for this fusion. So, precision can be improved if and only if the tools to be fused are perfectly matched at least for some parameters. We provide a methodology similar to a multidimensional TMU able to perform this matching exercise. It is demonstrated on a 28 nm node backend lithography case. The second point of view is Deep Level Fusion which works on the contrary with raw data and their combination. In the approach presented here, the analysis of each raw data is based on a parametric model and connections between the parameters of each tool. In order to allow OCD/SEM Deep Level Fusion, a SEM Compact Model derived from [4] has been developed and compared to AFM. As far as we know, this is the first time such techniques have been coupled at Deep Level. A numerical study on the case of a simple stack for lithography is performed. We show strict equivalence of Deep Level Fusion and High Level Fusion when tools are sensitive and models are perfect. When one of the tools can be considered as a reference and the second is biased, High Level Fusion is far superior to standard Deep Level Fusion. Otherwise, only the second stage of High Level Fusion is possible (Bayesian Fusion) and do not provide substantial advantage. Finally, when OCD is equipped with methods for bias detection [5], Deep Level Fusion outclasses the two-stage High Level Fusion and will benefit to the industry for most advanced nodes production.

Deep learning decision fusion for the classification of urban remote sensing data

NASA Astrophysics Data System (ADS)

Abdi, Ghasem; Samadzadegan, Farhad; Reinartz, Peter

2018-01-01

Multisensor data fusion is one of the most common and popular remote sensing data classification topics by considering a robust and complete description about the objects of interest. Furthermore, deep feature extraction has recently attracted significant interest and has become a hot research topic in the geoscience and remote sensing research community. A deep learning decision fusion approach is presented to perform multisensor urban remote sensing data classification. After deep features are extracted by utilizing joint spectral-spatial information, a soft-decision made classifier is applied to train high-level feature representations and to fine-tune the deep learning framework. Next, a decision-level fusion classifies objects of interest by the joint use of sensors. Finally, a context-aware object-based postprocessing is used to enhance the classification results. A series of comparative experiments are conducted on the widely used dataset of 2014 IEEE GRSS data fusion contest. The obtained results illustrate the considerable advantages of the proposed deep learning decision fusion over the traditional classifiers.

Sensor fusion III: 3-D perception and recognition; Proceedings of the Meeting, Boston, MA, Nov. 5-8, 1990

NASA Technical Reports Server (NTRS)

Schenker, Paul S. (Editor)

1991-01-01

The volume on data fusion from multiple sources discusses fusing multiple views, temporal analysis and 3D motion interpretation, sensor fusion and eye-to-hand coordination, and integration in human shape perception. Attention is given to surface reconstruction, statistical methods in sensor fusion, fusing sensor data with environmental knowledge, computational models for sensor fusion, and evaluation and selection of sensor fusion techniques. Topics addressed include the structure of a scene from two and three projections, optical flow techniques for moving target detection, tactical sensor-based exploration in a robotic environment, and the fusion of human and machine skills for remote robotic operations. Also discussed are K-nearest-neighbor concepts for sensor fusion, surface reconstruction with discontinuities, a sensor-knowledge-command fusion paradigm for man-machine systems, coordinating sensing and local navigation, and terrain map matching using multisensing techniques for applications to autonomous vehicle navigation.

A Bio-Inspired Herbal Tea Flavour Assessment Technique

PubMed Central

Zakaria, Nur Zawatil Isqi; Masnan, Maz Jamilah; Zakaria, Ammar; Shakaff, Ali Yeon Md

2014-01-01

Herbal-based products are becoming a widespread production trend among manufacturers for the domestic and international markets. As the production increases to meet the market demand, it is very crucial for the manufacturer to ensure that their products have met specific criteria and fulfil the intended quality determined by the quality controller. One famous herbal-based product is herbal tea. This paper investigates bio-inspired flavour assessments in a data fusion framework involving an e-nose and e-tongue. The objectives are to attain good classification of different types and brands of herbal tea, classification of different flavour masking effects and finally classification of different concentrations of herbal tea. Two data fusion levels were employed in this research, low level data fusion and intermediate level data fusion. Four classification approaches; LDA, SVM, KNN and PNN were examined in search of the best classifier to achieve the research objectives. In order to evaluate the classifiers' performance, an error estimator based on k-fold cross validation and leave-one-out were applied. Classification based on GC-MS TIC data was also included as a comparison to the classification performance using fusion approaches. Generally, KNN outperformed the other classification techniques for the three flavour assessments in the low level data fusion and intermediate level data fusion. However, the classification results based on GC-MS TIC data are varied. PMID:25010697

The "grep" command but not FusionMap, FusionFinder or ChimeraScan captures the CIC-DUX4 fusion gene from whole transcriptome sequencing data on a small round cell tumor with t(4;19)(q35;q13).

PubMed

Panagopoulos, Ioannis; Gorunova, Ludmila; Bjerkehagen, Bodil; Heim, Sverre

2014-01-01

Whole transcriptome sequencing was used to study a small round cell tumor in which a t(4;19)(q35;q13) was part of the complex karyotype but where the initial reverse transcriptase PCR (RT-PCR) examination did not detect a CIC-DUX4 fusion transcript previously described as the crucial gene-level outcome of this specific translocation. The RNA sequencing data were analysed using the FusionMap, FusionFinder, and ChimeraScan programs which are specifically designed to identify fusion genes. FusionMap, FusionFinder, and ChimeraScan identified 1017, 102, and 101 fusion transcripts, respectively, but CIC-DUX4 was not among them. Since the RNA sequencing data are in the fastq text-based format, we searched the files using the "grep" command-line utility. The "grep" command searches the text for specific expressions and displays, by default, the lines where matches occur. The "specific expression" was a sequence of 20 nucleotides from the coding part of the last exon 20 of CIC (Reference Sequence: NM_015125.3) chosen since all the so far reported CIC breakpoints have occurred here. Fifteen chimeric CIC-DUX4 cDNA sequences were captured and the fusion between the CIC and DUX4 genes was mapped precisely. New primer combinations were constructed based on these findings and were used together with a polymerase suitable for amplification of GC-rich DNA templates to amplify CIC-DUX4 cDNA fragments which had the same fusion point found with "grep". In conclusion, FusionMap, FusionFinder, and ChimeraScan generated a plethora of fusion transcripts but did not detect the biologically important CIC-DUX4 chimeric transcript; they are generally useful but evidently suffer from imperfect both sensitivity and specificity. The "grep" command is an excellent tool to capture chimeric transcripts from RNA sequencing data when the pathological and/or cytogenetic information strongly indicates the presence of a specific fusion gene.

Chimera: a Bioconductor package for secondary analysis of fusion products.

PubMed

Beccuti, Marco; Carrara, Matteo; Cordero, Francesca; Lazzarato, Fulvio; Donatelli, Susanna; Nadalin, Francesca; Policriti, Alberto; Calogero, Raffaele A

2014-12-15

Chimera is a Bioconductor package that organizes, annotates, analyses and validates fusions reported by different fusion detection tools; current implementation can deal with output from bellerophontes, chimeraScan, deFuse, fusionCatcher, FusionFinder, FusionHunter, FusionMap, mapSplice, Rsubread, tophat-fusion and STAR. The core of Chimera is a fusion data structure that can store fusion events detected with any of the aforementioned tools. Fusions are then easily manipulated with standard R functions or through the set of functionalities specifically developed in Chimera with the aim of supporting the user in managing fusions and discriminating false-positive results. © The Author 2014. Published by Oxford University Press.

From Data Acquisition to Data Fusion: A Comprehensive Review and a Roadmap for the Identification of Activities of Daily Living Using Mobile Devices

PubMed Central

Pires, Ivan Miguel; Garcia, Nuno M.; Pombo, Nuno; Flórez-Revuelta, Francisco

2016-01-01

This paper focuses on the research on the state of the art for sensor fusion techniques, applied to the sensors embedded in mobile devices, as a means to help identify the mobile device user’s daily activities. Sensor data fusion techniques are used to consolidate the data collected from several sensors, increasing the reliability of the algorithms for the identification of the different activities. However, mobile devices have several constraints, e.g., low memory, low battery life and low processing power, and some data fusion techniques are not suited to this scenario. The main purpose of this paper is to present an overview of the state of the art to identify examples of sensor data fusion techniques that can be applied to the sensors available in mobile devices aiming to identify activities of daily living (ADLs). PMID:26848664

Enhancement of Tropical Land Cover Mapping with Wavelet-Based Fusion and Unsupervised Clustering of SAR and Landsat Image Data

NASA Technical Reports Server (NTRS)

LeMoigne, Jacqueline; Laporte, Nadine; Netanyahuy, Nathan S.; Zukor, Dorothy (Technical Monitor)

2001-01-01

The characterization and the mapping of land cover/land use of forest areas, such as the Central African rainforest, is a very complex task. This complexity is mainly due to the extent of such areas and, as a consequence, to the lack of full and continuous cloud-free coverage of those large regions by one single remote sensing instrument, In order to provide improved vegetation maps of Central Africa and to develop forest monitoring techniques for applications at the local and regional scales, we propose to utilize multi-sensor remote sensing observations coupled with in-situ data. Fusion and clustering of multi-sensor data are the first steps towards the development of such a forest monitoring system. In this paper, we will describe some preliminary experiments involving the fusion of SAR and Landsat image data of the Lope Reserve in Gabon. Similarly to previous fusion studies, our fusion method is wavelet-based. The fusion provides a new image data set which contains more detailed texture features and preserves the large homogeneous regions that are observed by the Thematic Mapper sensor. The fusion step is followed by unsupervised clustering and provides a vegetation map of the area.

Technologies for Army Knowledge Fusion

DTIC Science & Technology

2004-09-01

interpret it in context and understand the implications (Alberts et al., 2002). Note that the knowledge / information fusion issue arises immediately here...Army Knowledge Fusion Richard Scherl Department of Computer Science Monmouth University Dana L. Ulery Computational and Information Sciences...civilian and military sources. Knowledge fusion, also called information fusion and multisensor data fusion, names the body of techniques needed to

Sensor fusion IV: Control paradigms and data structures; Proceedings of the Meeting, Boston, MA, Nov. 12-15, 1991

NASA Technical Reports Server (NTRS)

Schenker, Paul S. (Editor)

1992-01-01

Various papers on control paradigms and data structures in sensor fusion are presented. The general topics addressed include: decision models and computational methods, sensor modeling and data representation, active sensing strategies, geometric planning and visualization, task-driven sensing, motion analysis, models motivated biology and psychology, decentralized detection and distributed decision, data fusion architectures, robust estimation of shapes and features, application and implementation. Some of the individual subjects considered are: the Firefly experiment on neural networks for distributed sensor data fusion, manifold traversing as a model for learning control of autonomous robots, choice of coordinate systems for multiple sensor fusion, continuous motion using task-directed stereo vision, interactive and cooperative sensing and control for advanced teleoperation, knowledge-based imaging for terrain analysis, physical and digital simulations for IVA robotics.

Information Fusion of Conflicting Input Data.

PubMed

Mönks, Uwe; Dörksen, Helene; Lohweg, Volker; Hübner, Michael

2016-10-29

Sensors, and also actuators or external sources such as databases, serve as data sources in order to realise condition monitoring of industrial applications or the acquisition of characteristic parameters like production speed or reject rate. Modern facilities create such a large amount of complex data that a machine operator is unable to comprehend and process the information contained in the data. Thus, information fusion mechanisms gain increasing importance. Besides the management of large amounts of data, further challenges towards the fusion algorithms arise from epistemic uncertainties (incomplete knowledge) in the input signals as well as conflicts between them. These aspects must be considered during information processing to obtain reliable results, which are in accordance with the real world. The analysis of the scientific state of the art shows that current solutions fulfil said requirements at most only partly. This article proposes the multilayered information fusion system MACRO (multilayer attribute-based conflict-reducing observation) employing the μ BalTLCS (fuzzified balanced two-layer conflict solving) fusion algorithm to reduce the impact of conflicts on the fusion result. The performance of the contribution is shown by its evaluation in the scope of a machine condition monitoring application under laboratory conditions. Here, the MACRO system yields the best results compared to state-of-the-art fusion mechanisms. The utilised data is published and freely accessible.

Information Fusion of Conflicting Input Data

PubMed Central

Mönks, Uwe; Dörksen, Helene; Lohweg, Volker; Hübner, Michael

2016-01-01

Sensors, and also actuators or external sources such as databases, serve as data sources in order to realise condition monitoring of industrial applications or the acquisition of characteristic parameters like production speed or reject rate. Modern facilities create such a large amount of complex data that a machine operator is unable to comprehend and process the information contained in the data. Thus, information fusion mechanisms gain increasing importance. Besides the management of large amounts of data, further challenges towards the fusion algorithms arise from epistemic uncertainties (incomplete knowledge) in the input signals as well as conflicts between them. These aspects must be considered during information processing to obtain reliable results, which are in accordance with the real world. The analysis of the scientific state of the art shows that current solutions fulfil said requirements at most only partly. This article proposes the multilayered information fusion system MACRO (multilayer attribute-based conflict-reducing observation) employing the μBalTLCS (fuzzified balanced two-layer conflict solving) fusion algorithm to reduce the impact of conflicts on the fusion result. The performance of the contribution is shown by its evaluation in the scope of a machine condition monitoring application under laboratory conditions. Here, the MACRO system yields the best results compared to state-of-the-art fusion mechanisms. The utilised data is published and freely accessible. PMID:27801874

An Adaptive Multi-Sensor Data Fusion Method Based on Deep Convolutional Neural Networks for Fault Diagnosis of Planetary Gearbox

PubMed Central

Jing, Luyang; Wang, Taiyong; Zhao, Ming; Wang, Peng

2017-01-01

A fault diagnosis approach based on multi-sensor data fusion is a promising tool to deal with complicated damage detection problems of mechanical systems. Nevertheless, this approach suffers from two challenges, which are (1) the feature extraction from various types of sensory data and (2) the selection of a suitable fusion level. It is usually difficult to choose an optimal feature or fusion level for a specific fault diagnosis task, and extensive domain expertise and human labor are also highly required during these selections. To address these two challenges, we propose an adaptive multi-sensor data fusion method based on deep convolutional neural networks (DCNN) for fault diagnosis. The proposed method can learn features from raw data and optimize a combination of different fusion levels adaptively to satisfy the requirements of any fault diagnosis task. The proposed method is tested through a planetary gearbox test rig. Handcraft features, manual-selected fusion levels, single sensory data, and two traditional intelligent models, back-propagation neural networks (BPNN) and a support vector machine (SVM), are used as comparisons in the experiment. The results demonstrate that the proposed method is able to detect the conditions of the planetary gearbox effectively with the best diagnosis accuracy among all comparative methods in the experiment. PMID:28230767

Funding for the 2ND IAEA technical meeting on fusion data processing, validation and analysis

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

Greenwald, Martin

The International Atomic Energy Agency (IAEA) will organize the second Technical Meeting on Fusion Da Processing, Validation and Analysis from 30 May to 02 June, 2017, in Cambridge, MA USA. The meeting w be hosted by the MIT Plasma Science and Fusion Center (PSFC). The objective of the meeting is to provide a platform where a set of topics relevant to fusion data processing, validation and analysis are discussed with the view of extrapolation needs to next step fusion devices such as ITER. The validation and analysis of experimental data obtained from diagnostics used to characterize fusion plasmas are crucialmore » for a knowledge based understanding of the physical processes governing the dynamics of these plasmas. The meeting will aim at fostering, in particular, discussions of research and development results that set out or underline trends observed in the current major fusion confinement devices. General information on the IAEA, including its mission and organization, can be found at the IAEA websit Uncertainty quantification (UQ) Model selection, validation, and verification (V&V) Probability theory and statistical analysis Inverse problems & equilibrium reconstru ction Integrated data analysis Real time data analysis Machine learning Signal/image proc essing & pattern recognition Experimental design and synthetic diagnostics Data management« less

Fusion of imaging and nonimaging data for surveillance aircraft

NASA Astrophysics Data System (ADS)

Shahbazian, Elisa; Gagnon, Langis; Duquet, Jean Remi; Macieszczak, Maciej; Valin, Pierre

1997-06-01

This paper describes a phased incremental integration approach for application of image analysis and data fusion technologies to provide automated intelligent target tracking and identification for airborne surveillance on board an Aurora Maritime Patrol Aircraft. The sensor suite of the Aurora consists of a radar, an identification friend or foe (IFF) system, an electronic support measures (ESM) system, a spotlight synthetic aperture radar (SSAR), a forward looking infra-red (FLIR) sensor and a link-11 tactical datalink system. Lockheed Martin Canada (LMCan) is developing a testbed, which will be used to analyze and evaluate approaches for combining the data provided by the existing sensors, which were initially not designed to feed a fusion system. Three concurrent research proof-of-concept activities provide techniques, algorithms and methodology into three sequential phases of integration of this testbed. These activities are: (1) analysis of the fusion architecture (track/contact/hybrid) most appropriate for the type of data available, (2) extraction and fusion of simple features from the imaging data into the fusion system performing automatic target identification, and (3) development of a unique software architecture which will permit integration and independent evolution, enhancement and optimization of various decision aid capabilities, such as multi-sensor data fusion (MSDF), situation and threat assessment (STA) and resource management (RM).

Fusion of laser and image sensory data for 3-D modeling of the free navigation space

NASA Technical Reports Server (NTRS)

Mass, M.; Moghaddamzadeh, A.; Bourbakis, N.

1994-01-01

A fusion technique which combines two different types of sensory data for 3-D modeling of a navigation space is presented. The sensory data is generated by a vision camera and a laser scanner. The problem of different resolutions for these sensory data was solved by reduced image resolution, fusion of different data, and use of a fuzzy image segmentation technique.

Matrix factorization-based data fusion for gene function prediction in baker's yeast and slime mold.

PubMed

Zitnik, Marinka; Zupan, Blaž

2014-01-01

The development of effective methods for the characterization of gene functions that are able to combine diverse data sources in a sound and easily-extendible way is an important goal in computational biology. We have previously developed a general matrix factorization-based data fusion approach for gene function prediction. In this manuscript, we show that this data fusion approach can be applied to gene function prediction and that it can fuse various heterogeneous data sources, such as gene expression profiles, known protein annotations, interaction and literature data. The fusion is achieved by simultaneous matrix tri-factorization that shares matrix factors between sources. We demonstrate the effectiveness of the approach by evaluating its performance on predicting ontological annotations in slime mold D. discoideum and on recognizing proteins of baker's yeast S. cerevisiae that participate in the ribosome or are located in the cell membrane. Our approach achieves predictive performance comparable to that of the state-of-the-art kernel-based data fusion, but requires fewer data preprocessing steps.

Novel kinase fusion transcripts found in endometrial cancer

PubMed Central

Tamura, Ryo; Yoshihara, Kosuke; Yamawaki, Kaoru; Suda, Kazuaki; Ishiguro, Tatsuya; Adachi, Sosuke; Okuda, Shujiro; Inoue, Ituro; Verhaak, Roel G. W.; Enomoto, Takayuki

2015-01-01

Recent advances in RNA-sequencing technology have enabled the discovery of gene fusion transcripts in the transcriptome of cancer cells. However, it remains difficult to differentiate the therapeutically targetable fusions from passenger events. We have analyzed RNA-sequencing data and DNA copy number data from 25 endometrial cancer cell lines to identify potential therapeutically targetable fusion transcripts, and have identified 124 high-confidence fusion transcripts, of which 69% are associated with gene amplifications. As targetable fusion candidates, we focused on three in-frame kinase fusion transcripts that retain a kinase domain (CPQ-PRKDC, CAPZA2-MET, and VGLL4-PRKG1). We detected only CPQ-PRKDC fusion transcript in three of 122 primary endometrial cancer tissues. Cell proliferation of the fusion-positive cell line was inhibited by knocking down the expression of wild-type PRKDC but not by blocking the CPQ-PRKDC fusion transcript expression. Quantitative real-time RT-PCR demonstrated that the expression of the CPQ-PRKDC fusion transcript was significantly lower than that of wild-type PRKDC, corresponding to a low transcript allele fraction of this fusion, based on RNA-sequencing read counts. In endometrial cancers, the CPQ-PRKDC fusion transcript may be a passenger aberration related to gene amplification. Our findings suggest that transcript allele fraction is a useful predictor to find bona-fide therapeutic-targetable fusion transcripts. PMID:26689674

Novel kinase fusion transcripts found in endometrial cancer.

PubMed

Tamura, Ryo; Yoshihara, Kosuke; Yamawaki, Kaoru; Suda, Kazuaki; Ishiguro, Tatsuya; Adachi, Sosuke; Okuda, Shujiro; Inoue, Ituro; Verhaak, Roel G W; Enomoto, Takayuki

2015-12-22

Recent advances in RNA-sequencing technology have enabled the discovery of gene fusion transcripts in the transcriptome of cancer cells. However, it remains difficult to differentiate the therapeutically targetable fusions from passenger events. We have analyzed RNA-sequencing data and DNA copy number data from 25 endometrial cancer cell lines to identify potential therapeutically targetable fusion transcripts, and have identified 124 high-confidence fusion transcripts, of which 69% are associated with gene amplifications. As targetable fusion candidates, we focused on three in-frame kinase fusion transcripts that retain a kinase domain (CPQ-PRKDC, CAPZA2-MET, and VGLL4-PRKG1). We detected only CPQ-PRKDC fusion transcript in three of 122 primary endometrial cancer tissues. Cell proliferation of the fusion-positive cell line was inhibited by knocking down the expression of wild-type PRKDC but not by blocking the CPQ-PRKDC fusion transcript expression. Quantitative real-time RT-PCR demonstrated that the expression of the CPQ-PRKDC fusion transcript was significantly lower than that of wild-type PRKDC, corresponding to a low transcript allele fraction of this fusion, based on RNA-sequencing read counts. In endometrial cancers, the CPQ-PRKDC fusion transcript may be a passenger aberration related to gene amplification. Our findings suggest that transcript allele fraction is a useful predictor to find bona-fide therapeutic-targetable fusion transcripts.

Proton Spectra from He 3 + T and He 3 + He 3 Fusion at Low Center-of-Mass Energy, with Potential Implications for Solar Fusion Cross Sections

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

Zylstra, A. B.; Frenje, J. A.; Gatu Johnson, M.

Few-body nuclear physics often relies upon phenomenological models, with new efforts at the ab initio theory reported recently; both need high-quality benchmark data, particularly at low center-of-mass energies. We use high-energy-density plasmas to measure the proton spectra from 3He + T and 3He + 3He fusion. The data disagree with R -matrix predictions constrained by neutron spectra from T + T fusion. Here, we present a new analysis of the 3He + 3He proton spectrum; these benchmarked spectral shapes should be used for interpreting low-resolution data, such as solar fusion cross-section measurements.

Proton Spectra from 3He + T and 3He + 3He Fusion at Low Center-of-Mass Energy, with Potential Implications for Solar Fusion Cross Sections

NASA Astrophysics Data System (ADS)

Zylstra, A. B.; Frenje, J. A.; Gatu Johnson, M.; Hale, G. M.; Brune, C. R.; Bacher, A.; Casey, D. T.; Li, C. K.; McNabb, D.; Paris, M.; Petrasso, R. D.; Sangster, T. C.; Sayre, D. B.; Séguin, F. H.

2017-12-01

Few-body nuclear physics often relies upon phenomenological models, with new efforts at the ab initio theory reported recently; both need high-quality benchmark data, particularly at low center-of-mass energies. We use high-energy-density plasmas to measure the proton spectra from 3He +T and 3He + 3He fusion. The data disagree with R -matrix predictions constrained by neutron spectra from T +T fusion. We present a new analysis of the 3He + 3He 3 proton spectrum; these benchmarked spectral shapes should be used for interpreting low-resolution data, such as solar fusion cross-section measurements.

Proton Spectra from He 3 + T and He 3 + He 3 Fusion at Low Center-of-Mass Energy, with Potential Implications for Solar Fusion Cross Sections

DOE PAGES

Zylstra, A. B.; Frenje, J. A.; Gatu Johnson, M.; ...

2017-11-29

Few-body nuclear physics often relies upon phenomenological models, with new efforts at the ab initio theory reported recently; both need high-quality benchmark data, particularly at low center-of-mass energies. We use high-energy-density plasmas to measure the proton spectra from 3He + T and 3He + 3He fusion. The data disagree with R -matrix predictions constrained by neutron spectra from T + T fusion. Here, we present a new analysis of the 3He + 3He proton spectrum; these benchmarked spectral shapes should be used for interpreting low-resolution data, such as solar fusion cross-section measurements.

Analysis of decision fusion algorithms in handling uncertainties for integrated health monitoring systems

NASA Astrophysics Data System (ADS)

Zein-Sabatto, Saleh; Mikhail, Maged; Bodruzzaman, Mohammad; DeSimio, Martin; Derriso, Mark; Behbahani, Alireza

2012-06-01

It has been widely accepted that data fusion and information fusion methods can improve the accuracy and robustness of decision-making in structural health monitoring systems. It is arguably true nonetheless, that decision-level is equally beneficial when applied to integrated health monitoring systems. Several decisions at low-levels of abstraction may be produced by different decision-makers; however, decision-level fusion is required at the final stage of the process to provide accurate assessment about the health of the monitored system as a whole. An example of such integrated systems with complex decision-making scenarios is the integrated health monitoring of aircraft. Thorough understanding of the characteristics of the decision-fusion methodologies is a crucial step for successful implementation of such decision-fusion systems. In this paper, we have presented the major information fusion methodologies reported in the literature, i.e., probabilistic, evidential, and artificial intelligent based methods. The theoretical basis and characteristics of these methodologies are explained and their performances are analyzed. Second, candidate methods from the above fusion methodologies, i.e., Bayesian, Dempster-Shafer, and fuzzy logic algorithms are selected and their applications are extended to decisions fusion. Finally, fusion algorithms are developed based on the selected fusion methods and their performance are tested on decisions generated from synthetic data and from experimental data. Also in this paper, a modeling methodology, i.e. cloud model, for generating synthetic decisions is presented and used. Using the cloud model, both types of uncertainties; randomness and fuzziness, involved in real decision-making are modeled. Synthetic decisions are generated with an unbiased process and varying interaction complexities among decisions to provide for fair performance comparison of the selected decision-fusion algorithms. For verification purposes, implementation results of the developed fusion algorithms on structural health monitoring data collected from experimental tests are reported in this paper.

Pansharpening via coupled triple factorization dictionary learning

DOE PAGES

Skau, Erik; Wohlberg, Brendt; Krim, Hamid; ...

2016-03-01

Data fusion is the operation of integrating data from different modalities to construct a single consistent representation. Here, this paper proposes variations of coupled dictionary learning through an additional factorization. One variation of this model is applicable to the pansharpening data fusion problem. Real world pansharpening data was applied to train and test our proposed formulation. The results demonstrate that the data fusion model can successfully be applied to the pan-sharpening problem.

Unmanned Aerial System (UAS)-based phenotyping of soybean using multi-sensor data fusion and extreme learning machine

NASA Astrophysics Data System (ADS)

Maimaitijiang, Maitiniyazi; Ghulam, Abduwasit; Sidike, Paheding; Hartling, Sean; Maimaitiyiming, Matthew; Peterson, Kyle; Shavers, Ethan; Fishman, Jack; Peterson, Jim; Kadam, Suhas; Burken, Joel; Fritschi, Felix

2017-12-01

Estimating crop biophysical and biochemical parameters with high accuracy at low-cost is imperative for high-throughput phenotyping in precision agriculture. Although fusion of data from multiple sensors is a common application in remote sensing, less is known on the contribution of low-cost RGB, multispectral and thermal sensors to rapid crop phenotyping. This is due to the fact that (1) simultaneous collection of multi-sensor data using satellites are rare and (2) multi-sensor data collected during a single flight have not been accessible until recent developments in Unmanned Aerial Systems (UASs) and UAS-friendly sensors that allow efficient information fusion. The objective of this study was to evaluate the power of high spatial resolution RGB, multispectral and thermal data fusion to estimate soybean (Glycine max) biochemical parameters including chlorophyll content and nitrogen concentration, and biophysical parameters including Leaf Area Index (LAI), above ground fresh and dry biomass. Multiple low-cost sensors integrated on UASs were used to collect RGB, multispectral, and thermal images throughout the growing season at a site established near Columbia, Missouri, USA. From these images, vegetation indices were extracted, a Crop Surface Model (CSM) was advanced, and a model to extract the vegetation fraction was developed. Then, spectral indices/features were combined to model and predict crop biophysical and biochemical parameters using Partial Least Squares Regression (PLSR), Support Vector Regression (SVR), and Extreme Learning Machine based Regression (ELR) techniques. Results showed that: (1) For biochemical variable estimation, multispectral and thermal data fusion provided the best estimate for nitrogen concentration and chlorophyll (Chl) a content (RMSE of 9.9% and 17.1%, respectively) and RGB color information based indices and multispectral data fusion exhibited the largest RMSE 22.6%; the highest accuracy for Chl a + b content estimation was obtained by fusion of information from all three sensors with an RMSE of 11.6%. (2) Among the plant biophysical variables, LAI was best predicted by RGB and thermal data fusion while multispectral and thermal data fusion was found to be best for biomass estimation. (3) For estimation of the above mentioned plant traits of soybean from multi-sensor data fusion, ELR yields promising results compared to PLSR and SVR in this study. This research indicates that fusion of low-cost multiple sensor data within a machine learning framework can provide relatively accurate estimation of plant traits and provide valuable insight for high spatial precision in agriculture and plant stress assessment.

Energy Logic (EL): a novel fusion engine of multi-modality multi-agent data/information fusion for intelligent surveillance systems

NASA Astrophysics Data System (ADS)

Rababaah, Haroun; Shirkhodaie, Amir

2009-04-01

The rapidly advancing hardware technology, smart sensors and sensor networks are advancing environment sensing. One major potential of this technology is Large-Scale Surveillance Systems (LS3) especially for, homeland security, battlefield intelligence, facility guarding and other civilian applications. The efficient and effective deployment of LS3 requires addressing number of aspects impacting the scalability of such systems. The scalability factors are related to: computation and memory utilization efficiency, communication bandwidth utilization, network topology (e.g., centralized, ad-hoc, hierarchical or hybrid), network communication protocol and data routing schemes; and local and global data/information fusion scheme for situational awareness. Although, many models have been proposed to address one aspect or another of these issues but, few have addressed the need for a multi-modality multi-agent data/information fusion that has characteristics satisfying the requirements of current and future intelligent sensors and sensor networks. In this paper, we have presented a novel scalable fusion engine for multi-modality multi-agent information fusion for LS3. The new fusion engine is based on a concept we call: Energy Logic. Experimental results of this work as compared to a Fuzzy logic model strongly supported the validity of the new model and inspired future directions for different levels of fusion and different applications.

Fusion cross sections for reactions involving medium and heavy nucleus-nucleus systems

NASA Astrophysics Data System (ADS)

Atta, Debasis; Basu, D. N.

2014-12-01

Existing data on near-barrier fusion excitation functions of medium and heavy nucleus-nucleus systems have been analyzed by using a simple diffused-barrier formula derived assuming the Gaussian shape of the barrier-height distributions. The fusion cross section is obtained by folding the Gaussian barrier distribution with the classical expression for the fusion cross section for a fixed barrier. The energy dependence of the fusion cross section, thus obtained, provides good description to the existing data on near-barrier fusion and capture excitation functions for medium and heavy nucleus-nucleus systems. The theoretical values for the parameters of the barrier distribution are estimated which can be used for fusion or capture cross-section predictions that are especially important for planning experiments for synthesizing new superheavy elements.

Recent Advances in Registration, Integration and Fusion of Remotely Sensed Data: Redundant Representations and Frames

NASA Technical Reports Server (NTRS)

Czaja, Wojciech; Le Moigne-Stewart, Jacqueline

2014-01-01

In recent years, sophisticated mathematical techniques have been successfully applied to the field of remote sensing to produce significant advances in applications such as registration, integration and fusion of remotely sensed data. Registration, integration and fusion of multiple source imagery are the most important issues when dealing with Earth Science remote sensing data where information from multiple sensors, exhibiting various resolutions, must be integrated. Issues ranging from different sensor geometries, different spectral responses, differing illumination conditions, different seasons, and various amounts of noise need to be dealt with when designing an image registration, integration or fusion method. This tutorial will first define the problems and challenges associated with these applications and then will review some mathematical techniques that have been successfully utilized to solve them. In particular, we will cover topics on geometric multiscale representations, redundant representations and fusion frames, graph operators, diffusion wavelets, as well as spatial-spectral and operator-based data fusion. All the algorithms will be illustrated using remotely sensed data, with an emphasis on current and operational instruments.

Reanalysis of RNA-Sequencing Data Reveals Several Additional Fusion Genes with Multiple Isoforms

PubMed Central

Kangaspeska, Sara; Hultsch, Susanne; Edgren, Henrik; Nicorici, Daniel; Murumägi, Astrid; Kallioniemi, Olli

2012-01-01

RNA-sequencing and tailored bioinformatic methodologies have paved the way for identification of expressed fusion genes from the chaotic genomes of solid tumors. We have recently successfully exploited RNA-sequencing for the discovery of 24 novel fusion genes in breast cancer. Here, we demonstrate the importance of continuous optimization of the bioinformatic methodology for this purpose, and report the discovery and experimental validation of 13 additional fusion genes from the same samples. Integration of copy number profiling with the RNA-sequencing results revealed that the majority of the gene fusions were promoter-donating events that occurred at copy number transition points or involved high-level DNA-amplifications. Sequencing of genomic fusion break points confirmed that DNA-level rearrangements underlie selected fusion transcripts. Furthermore, a significant portion (>60%) of the fusion genes were alternatively spliced. This illustrates the importance of reanalyzing sequencing data as gene definitions change and bioinformatic methods improve, and highlights the previously unforeseen isoform diversity among fusion transcripts. PMID:23119097

Reanalysis of RNA-sequencing data reveals several additional fusion genes with multiple isoforms.

PubMed

Kangaspeska, Sara; Hultsch, Susanne; Edgren, Henrik; Nicorici, Daniel; Murumägi, Astrid; Kallioniemi, Olli

2012-01-01

RNA-sequencing and tailored bioinformatic methodologies have paved the way for identification of expressed fusion genes from the chaotic genomes of solid tumors. We have recently successfully exploited RNA-sequencing for the discovery of 24 novel fusion genes in breast cancer. Here, we demonstrate the importance of continuous optimization of the bioinformatic methodology for this purpose, and report the discovery and experimental validation of 13 additional fusion genes from the same samples. Integration of copy number profiling with the RNA-sequencing results revealed that the majority of the gene fusions were promoter-donating events that occurred at copy number transition points or involved high-level DNA-amplifications. Sequencing of genomic fusion break points confirmed that DNA-level rearrangements underlie selected fusion transcripts. Furthermore, a significant portion (>60%) of the fusion genes were alternatively spliced. This illustrates the importance of reanalyzing sequencing data as gene definitions change and bioinformatic methods improve, and highlights the previously unforeseen isoform diversity among fusion transcripts.

Sensor Fusion Techniques for Phased-Array Eddy Current and Phased-Array Ultrasound Data

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

Arrowood, Lloyd F.

Sensor (or Data) fusion is the process of integrating multiple data sources to produce more consistent, accurate and comprehensive information than is provided by a single data source. Sensor fusion may also be used to combine multiple signals from a single modality to improve the performance of a particular inspection technique. Industrial nondestructive testing may utilize multiple sensors to acquire inspection data depending upon the object under inspection and the anticipated types of defects that can be identified. Sensor fusion can be performed at various levels of signal abstraction with each having its strengths and weaknesses. A multimodal data fusionmore » strategy first proposed by Heideklang and Shokouhi that combines spatially scattered detection locations to improve detection performance of surface-breaking and near-surface cracks in ferromagnetic metals is shown using a surface inspection example and is then extended for volumetric inspections. Utilizing data acquired from an Olympus Omniscan MX2 from both phased array eddy current and ultrasound probes on test phantoms, single and multilevel fusion techniques are employed to integrate signals from the two modalities. Preliminary results demonstrate how confidence in defect identification and interpretation benefit from sensor fusion techniques. Lastly, techniques for integrating data into radiographic and volumetric imagery from computed tomography are described and results are presented.« less

Data fusion strategies for hazard detection and safe site selection for planetary and small body landings

NASA Astrophysics Data System (ADS)

Câmara, F.; Oliveira, J.; Hormigo, T.; Araújo, J.; Ribeiro, R.; Falcão, A.; Gomes, M.; Dubois-Matra, O.; Vijendran, S.

2015-06-01

This paper discusses the design and evaluation of data fusion strategies to perform tiered fusion of several heterogeneous sensors and a priori data. The aim is to increase robustness and performance of hazard detection and avoidance systems, while enabling safe planetary and small body landings anytime, anywhere. The focus is on Mars and asteroid landing mission scenarios and three distinct data fusion algorithms are introduced and compared. The first algorithm consists of a hybrid camera-LIDAR hazard detection and avoidance system, the H2DAS, in which data fusion is performed at both sensor-level data (reconstruction of the point cloud obtained with a scanning LIDAR using the navigation motion states and correcting the image for motion compensation using IMU data), feature-level data (concatenation of multiple digital elevation maps, obtained from consecutive LIDAR images, to achieve higher accuracy and resolution maps while enabling relative positioning) as well as decision-level data (fusing hazard maps from multiple sensors onto a single image space, with a single grid orientation and spacing). The second method presented is a hybrid reasoning fusion, the HRF, in which innovative algorithms replace the decision-level functions of the previous method, by combining three different reasoning engines—a fuzzy reasoning engine, a probabilistic reasoning engine and an evidential reasoning engine—to produce safety maps. Finally, the third method presented is called Intelligent Planetary Site Selection, the IPSIS, an innovative multi-criteria, dynamic decision-level data fusion algorithm that takes into account historical information for the selection of landing sites and a piloting function with a non-exhaustive landing site search capability, i.e., capable of finding local optima by searching a reduced set of global maps. All the discussed data fusion strategies and algorithms have been integrated, verified and validated in a closed-loop simulation environment. Monte Carlo simulation campaigns were performed for the algorithms performance assessment and benchmarking. The simulations results comprise the landing phases of Mars and Phobos landing mission scenarios.

Remote Sensing Data Fusion to Detect Illicit Crops and Unauthorized Airstrips

NASA Astrophysics Data System (ADS)

Pena, J. A.; Yumin, T.; Liu, H.; Zhao, B.; Garcia, J. A.; Pinto, J.

2018-04-01

Remote sensing data fusion has been playing a more and more important role in crop planting area monitoring, especially for crop area information acquisition. Multi-temporal data and multi-spectral time series are two major aspects for improving crop identification accuracy. Remote sensing fusion provides high quality multi-spectral and panchromatic images in terms of spectral and spatial information, respectively. In this paper, we take one step further and prove the application of remote sensing data fusion in detecting illicit crop through LSMM, GOBIA, and MCE analyzing of strategic information. This methodology emerges as a complementary and effective strategy to control and eradicate illicit crops.

Design and Analysis of a Data Fusion Scheme in Mobile Wireless Sensor Networks Based on Multi-Protocol Mobile Agents

PubMed Central

Wu, Chunxue; Wu, Wenliang; Wan, Caihua

2017-01-01

Sensors are increasingly used in mobile environments with wireless network connections. Multiple sensor types measure distinct aspects of the same event. Their measurements are then combined to produce integrated, reliable results. As the number of sensors in networks increases, low energy requirements and changing network connections complicate event detection and measurement. We present a data fusion scheme for use in mobile wireless sensor networks with high energy efficiency and low network delays, that still produces reliable results. In the first phase, we used a network simulation where mobile agents dynamically select the next hop migration node based on the stability parameter of the link, and perform the data fusion at the migration node. Agents use the fusion results to decide if it should return the fusion results to the processing center or continue to collect more data. In the second phase. The feasibility of data fusion at the node level is confirmed by an experimental design where fused data from color sensors show near-identical results to actual physical temperatures. These results are potentially important for new large-scale sensor network applications. PMID:29099793

Geographic identification of Boletus mushrooms by data fusion of FT-IR and UV spectroscopies combined with multivariate statistical analysis

NASA Astrophysics Data System (ADS)

Yao, Sen; Li, Tao; Li, JieQing; Liu, HongGao; Wang, YuanZhong

2018-06-01

Boletus griseus and Boletus edulis are two well-known wild-grown edible mushrooms which have high nutrition, delicious flavor and high economic value distributing in Yunnan Province. In this study, a rapid method using Fourier transform infrared (FT-IR) and ultraviolet (UV) spectroscopies coupled with data fusion was established for the discrimination of Boletus mushrooms from seven different geographical origins with pattern recognition method. Initially, the spectra of 332 mushroom samples obtained from the two spectroscopic techniques were analyzed individually and then the classification performance based on data fusion strategy was investigated. Meanwhile, the latent variables (LVs) of FT-IR and UV spectra were extracted by partial least square discriminant analysis (PLS-DA) and two datasets were concatenated into a new matrix for data fusion. Then, the fusion matrix was further analyzed by support vector machine (SVM). Compared with single spectroscopic technique, data fusion strategy can improve the classification performance effectively. In particular, the accuracy of correct classification of SVM model in training and test sets were 99.10% and 100.00%, respectively. The results demonstrated that data fusion of FT-IR and UV spectra can provide higher synergic effect for the discrimination of different geographical origins of Boletus mushrooms, which may be benefit for further authentication and quality assessment of edible mushrooms.

Geographic identification of Boletus mushrooms by data fusion of FT-IR and UV spectroscopies combined with multivariate statistical analysis.

PubMed

Yao, Sen; Li, Tao; Li, JieQing; Liu, HongGao; Wang, YuanZhong

2018-06-05

Boletus griseus and Boletus edulis are two well-known wild-grown edible mushrooms which have high nutrition, delicious flavor and high economic value distributing in Yunnan Province. In this study, a rapid method using Fourier transform infrared (FT-IR) and ultraviolet (UV) spectroscopies coupled with data fusion was established for the discrimination of Boletus mushrooms from seven different geographical origins with pattern recognition method. Initially, the spectra of 332 mushroom samples obtained from the two spectroscopic techniques were analyzed individually and then the classification performance based on data fusion strategy was investigated. Meanwhile, the latent variables (LVs) of FT-IR and UV spectra were extracted by partial least square discriminant analysis (PLS-DA) and two datasets were concatenated into a new matrix for data fusion. Then, the fusion matrix was further analyzed by support vector machine (SVM). Compared with single spectroscopic technique, data fusion strategy can improve the classification performance effectively. In particular, the accuracy of correct classification of SVM model in training and test sets were 99.10% and 100.00%, respectively. The results demonstrated that data fusion of FT-IR and UV spectra can provide higher synergic effect for the discrimination of different geographical origins of Boletus mushrooms, which may be benefit for further authentication and quality assessment of edible mushrooms. Copyright © 2018 Elsevier B.V. All rights reserved.

Visualization of multi-INT fusion data using Java Viewer (JVIEW)

NASA Astrophysics Data System (ADS)

Blasch, Erik; Aved, Alex; Nagy, James; Scott, Stephen

2014-05-01

Visualization is important for multi-intelligence fusion and we demonstrate issues for presenting physics-derived (i.e., hard) and human-derived (i.e., soft) fusion results. Physics-derived solutions (e.g., imagery) typically involve sensor measurements that are objective, while human-derived (e.g., text) typically involve language processing. Both results can be geographically displayed for user-machine fusion. Attributes of an effective and efficient display are not well understood, so we demonstrate issues and results for filtering, correlation, and association of data for users - be they operators or analysts. Operators require near-real time solutions while analysts have the opportunities of non-real time solutions for forensic analysis. In a use case, we demonstrate examples using the JVIEW concept that has been applied to piloting, space situation awareness, and cyber analysis. Using the open-source JVIEW software, we showcase a big data solution for multi-intelligence fusion application for context-enhanced information fusion.

Robotics and local fusion

NASA Astrophysics Data System (ADS)

Emmerman, Philip J.

2005-05-01

Teams of robots or mixed teams of warfighters and robots on reconnaissance and other missions can benefit greatly from a local fusion station. A local fusion station is defined here as a small mobile processor with interfaces to enable the ingestion of multiple heterogeneous sensor data and information streams, including blue force tracking data. These data streams are fused and integrated with contextual information (terrain features, weather, maps, dynamic background features, etc.), and displayed or processed to provide real time situational awareness to the robot controller or to the robots themselves. These blue and red force fusion applications remove redundancies, lessen ambiguities, correlate, aggregate, and integrate sensor information with context such as high resolution terrain. Applications such as safety, team behavior, asset control, training, pattern analysis, etc. can be generated or enhanced by these fusion stations. This local fusion station should also enable the interaction between these local units and a global information world.

Distributed service-based approach for sensor data fusion in IoT environments.

PubMed

Rodríguez-Valenzuela, Sandra; Holgado-Terriza, Juan A; Gutiérrez-Guerrero, José M; Muros-Cobos, Jesús L

2014-10-15

The Internet of Things (IoT) enables the communication among smart objects promoting the pervasive presence around us of a variety of things or objects that are able to interact and cooperate jointly to reach common goals. IoT objects can obtain data from their context, such as the home, office, industry or body. These data can be combined to obtain new and more complex information applying data fusion processes. However, to apply data fusion algorithms in IoT environments, the full system must deal with distributed nodes, decentralized communication and support scalability and nodes dynamicity, among others restrictions. In this paper, a novel method to manage data acquisition and fusion based on a distributed service composition model is presented, improving the data treatment in IoT pervasive environments.

Distributed Service-Based Approach for Sensor Data Fusion in IoT Environments

PubMed Central

Rodríguez-Valenzuela, Sandra; Holgado-Terriza, Juan A.; Gutiérrez-Guerrero, José M.; Muros-Cobos, Jesús L.

2014-01-01

The Internet of Things (IoT) enables the communication among smart objects promoting the pervasive presence around us of a variety of things or objects that are able to interact and cooperate jointly to reach common goals. IoT objects can obtain data from their context, such as the home, office, industry or body. These data can be combined to obtain new and more complex information applying data fusion processes. However, to apply data fusion algorithms in IoT environments, the full system must deal with distributed nodes, decentralized communication and support scalability and nodes dynamicity, among others restrictions. In this paper, a novel method to manage data acquisition and fusion based on a distributed service composition model is presented, improving the data treatment in IoT pervasive environments. PMID:25320907

A flexible data fusion architecture for persistent surveillance using ultra-low-power wireless sensor networks

NASA Astrophysics Data System (ADS)

Hanson, Jeffrey A.; McLaughlin, Keith L.; Sereno, Thomas J.

2011-06-01

We have developed a flexible, target-driven, multi-modal, physics-based fusion architecture that efficiently searches sensor detections for targets and rejects clutter while controlling the combinatoric problems that commonly arise in datadriven fusion systems. The informational constraints imposed by long lifetime requirements make systems vulnerable to false alarms. We demonstrate that our data fusion system significantly reduces false alarms while maintaining high sensitivity to threats. In addition, mission goals can vary substantially in terms of targets-of-interest, required characterization, acceptable latency, and false alarm rates. Our fusion architecture provides the flexibility to match these trade-offs with mission requirements unlike many conventional systems that require significant modifications for each new mission. We illustrate our data fusion performance with case studies that span many of the potential mission scenarios including border surveillance, base security, and infrastructure protection. In these studies, we deployed multi-modal sensor nodes - including geophones, magnetometers, accelerometers and PIR sensors - with low-power processing algorithms and low-bandwidth wireless mesh networking to create networks capable of multi-year operation. The results show our data fusion architecture maintains high sensitivities while suppressing most false alarms for a variety of environments and targets.

Multisensor Parallel Largest Ellipsoid Distributed Data Fusion with Unknown Cross-Covariances

PubMed Central

Liu, Baoyu; Zhan, Xingqun; Zhu, Zheng H.

2017-01-01

As the largest ellipsoid (LE) data fusion algorithm can only be applied to two-sensor system, in this contribution, parallel fusion structure is proposed to introduce the LE algorithm into a multisensor system with unknown cross-covariances, and three parallel fusion structures based on different estimate pairing methods are presented and analyzed. In order to assess the influence of fusion structure on fusion performance, two fusion performance assessment parameters are defined as Fusion Distance and Fusion Index. Moreover, the formula for calculating the upper bounds of actual fused error covariances of the presented multisensor LE fusers is also provided. Demonstrated with simulation examples, the Fusion Index indicates fuser’s actual fused accuracy and its sensitivity to the sensor orders, as well as its robustness to the accuracy of newly added sensors. Compared to the LE fuser with sequential structure, the LE fusers with proposed parallel structures not only significantly improve their properties in these aspects, but also embrace better performances in consistency and computation efficiency. The presented multisensor LE fusers generally have better accuracies than covariance intersection (CI) fusion algorithm and are consistent when the local estimates are weakly correlated. PMID:28661442

Ontology-aided Data Fusion (Invited)

NASA Astrophysics Data System (ADS)

Raskin, R.

2009-12-01

An ontology provides semantic descriptions that are analogous to those in a dictionary, but are readable by both computers and humans. A data or service is semantically annotated when it is formally associated with elements of an ontology. The ESIP Federation Semantic Web Cluster has developed a set of ontologies to describe datatypes and data services that can be used to support automated data fusion. The service ontology includes descriptors of the service function, its inputs/outputs, and its invocation method. The datatype descriptors resemble typical metadata fields (data format, data model, data structure, originator, etc.) augmented with descriptions of the meaning of the data. These ontologies, in combination with the SWEET science ontology, enable a registered data fusion service to be chained together and implemented that is scientifically meaningful based on machine understanding of the associated data and services. This presentation describes initial results and experiences in automated data fusion.

Olive oil sensory defects classification with data fusion of instrumental techniques and multivariate analysis (PLS-DA).

PubMed

Borràs, Eva; Ferré, Joan; Boqué, Ricard; Mestres, Montserrat; Aceña, Laura; Calvo, Angels; Busto, Olga

2016-07-15

Three instrumental techniques, headspace-mass spectrometry (HS-MS), mid-infrared spectroscopy (MIR) and UV-visible spectrophotometry (UV-vis), have been combined to classify virgin olive oil samples based on the presence or absence of sensory defects. The reference sensory values were provided by an official taste panel. Different data fusion strategies were studied to improve the discrimination capability compared to using each instrumental technique individually. A general model was applied to discriminate high-quality non-defective olive oils (extra-virgin) and the lowest-quality olive oils considered non-edible (lampante). A specific identification of key off-flavours, such as musty, winey, fusty and rancid, was also studied. The data fusion of the three techniques improved the classification results in most of the cases. Low-level data fusion was the best strategy to discriminate musty, winey and fusty defects, using HS-MS, MIR and UV-vis, and the rancid defect using only HS-MS and MIR. The mid-level data fusion approach using partial least squares-discriminant analysis (PLS-DA) scores was found to be the best strategy for defective vs non-defective and edible vs non-edible oil discrimination. However, the data fusion did not sufficiently improve the results obtained by a single technique (HS-MS) to classify non-defective classes. These results indicate that instrumental data fusion can be useful for the identification of sensory defects in virgin olive oils. Copyright © 2016 Elsevier Ltd. All rights reserved.

MATRIX FACTORIZATION-BASED DATA FUSION FOR GENE FUNCTION PREDICTION IN BAKER’S YEAST AND SLIME MOLD

PubMed Central

ŽITNIK, MARINKA; ZUPAN, BLAŽ

2014-01-01

The development of effective methods for the characterization of gene functions that are able to combine diverse data sources in a sound and easily-extendible way is an important goal in computational biology. We have previously developed a general matrix factorization-based data fusion approach for gene function prediction. In this manuscript, we show that this data fusion approach can be applied to gene function prediction and that it can fuse various heterogeneous data sources, such as gene expression profiles, known protein annotations, interaction and literature data. The fusion is achieved by simultaneous matrix tri-factorization that shares matrix factors between sources. We demonstrate the effectiveness of the approach by evaluating its performance on predicting ontological annotations in slime mold D. discoideum and on recognizing proteins of baker’s yeast S. cerevisiae that participate in the ribosome or are located in the cell membrane. Our approach achieves predictive performance comparable to that of the state-of-the-art kernel-based data fusion, but requires fewer data preprocessing steps. PMID:24297565

Fusion Analytics: A Data Integration System for Public Health and Medical Disaster Response Decision Support

PubMed Central

Passman, Dina B.

2013-01-01

Objective The objective of this demonstration is to show conference attendees how they can integrate, analyze, and visualize diverse data type data from across a variety of systems by leveraging an off-the-shelf enterprise business intelligence (EBI) solution to support decision-making in disasters. Introduction Fusion Analytics is the data integration system developed by the Fusion Cell at the U.S. Department of Health and Human Services (HHS), Office of the Assistant Secretary for Preparedness and Response (ASPR). Fusion Analytics meaningfully augments traditional public and population health surveillance reporting by providing web-based data analysis and visualization tools. Methods Fusion Analytics serves as a one-stop-shop for the web-based data visualizations of multiple real-time data sources within ASPR. The 24-7 web availability makes it an ideal analytic tool for situational awareness and response allowing stakeholders to access the portal from any internet-enabled device without installing any software. The Fusion Analytics data integration system was built using off-the-shelf EBI software. Fusion Analytics leverages the full power of statistical analysis software and delivers reports to users in a secure web-based environment. Fusion Analytics provides an example of how public health staff can develop and deploy a robust public health informatics solution using an off-the shelf product and with limited development funding. It also provides the unique example of a public health information system that combines patient data for traditional disease surveillance with manpower and resource data to provide overall decision support for federal public health and medical disaster response operations. Conclusions We are currently in a unique position within public health. One the one hand, we have been gaining greater and greater access to electronic data of all kinds over the last few years. On the other, we are working in a time of reduced government spending to support leveraging this data for decision support with robust analytics and visualizations. Fusion Analytics provides an opportunity for attendees to see how various types of data are integrated into a single application for population health decision support. It also can provide them with ideas of how they can use their own staff to create analyses and reports that support their public health activities.

Stereotactic radiation treatment planning and follow-up studies involving fused multimodality imaging.

PubMed

Hamm, Klaus D; Surber, Gunnar; Schmücking, Michael; Wurm, Reinhard E; Aschenbach, Rene; Kleinert, Gabriele; Niesen, A; Baum, Richard P

2004-11-01

Innovative new software solutions may enable image fusion to produce the desired data superposition for precise target definition and follow-up studies in radiosurgery/stereotactic radiotherapy in patients with intracranial lesions. The aim is to integrate the anatomical and functional information completely into the radiation treatment planning and to achieve an exact comparison for follow-up examinations. Special conditions and advantages of BrainLAB's fully automatic image fusion system are evaluated and described for this purpose. In 458 patients, the radiation treatment planning and some follow-up studies were performed using an automatic image fusion technique involving the use of different imaging modalities. Each fusion was visually checked and corrected as necessary. The computerized tomography (CT) scans for radiation treatment planning (slice thickness 1.25 mm), as well as stereotactic angiography for arteriovenous malformations, were acquired using head fixation with stereotactic arc or, in the case of stereotactic radiotherapy, with a relocatable stereotactic mask. Different magnetic resonance (MR) imaging sequences (T1, T2, and fluid-attenuated inversion-recovery images) and positron emission tomography (PET) scans were obtained without head fixation. Fusion results and the effects on radiation treatment planning and follow-up studies were analyzed. The precision level of the results of the automatic fusion depended primarily on the image quality, especially the slice thickness and the field homogeneity when using MR images, as well as on patient movement during data acquisition. Fully automated image fusion of different MR, CT, and PET studies was performed for each patient. Only in a few cases was it necessary to correct the fusion manually after visual evaluation. These corrections were minor and did not materially affect treatment planning. High-quality fusion of thin slices of a region of interest with a complete head data set could be performed easily. The target volume for radiation treatment planning could be accurately delineated using multimodal information provided by CT, MR, angiography, and PET studies. The fusion of follow-up image data sets yielded results that could be successfully compared and quantitatively evaluated. Depending on the quality of the originally acquired image, automated image fusion can be a very valuable tool, allowing for fast (approximately 1-2 minute) and precise fusion of all relevant data sets. Fused multimodality imaging improves the target volume definition for radiation treatment planning. High-quality follow-up image data sets should be acquired for image fusion to provide exactly comparable slices and volumetric results that will contribute to quality contol.

Advances in Multi-Sensor Information Fusion: Theory and Applications 2017.

PubMed

Jin, Xue-Bo; Sun, Shuli; Wei, Hong; Yang, Feng-Bao

2018-04-11

The information fusion technique can integrate a large amount of data and knowledge representing the same real-world object and obtain a consistent, accurate, and useful representation of that object. The data may be independent or redundant, and can be obtained by different sensors at the same time or at different times. A suitable combination of investigative methods can substantially increase the profit of information in comparison with that from a single sensor. Multi-sensor information fusion has been a key issue in sensor research since the 1970s, and it has been applied in many fields. For example, manufacturing and process control industries can generate a lot of data, which have real, actionable business value. The fusion of these data can greatly improve productivity through digitization. The goal of this special issue is to report innovative ideas and solutions for multi-sensor information fusion in the emerging applications era, focusing on development, adoption, and applications.

Integrated Data Analysis for Fusion: A Bayesian Tutorial for Fusion Diagnosticians

NASA Astrophysics Data System (ADS)

Dinklage, Andreas; Dreier, Heiko; Fischer, Rainer; Gori, Silvio; Preuss, Roland; Toussaint, Udo von

2008-03-01

Integrated Data Analysis (IDA) offers a unified way of combining information relevant to fusion experiments. Thereby, IDA meets with typical issues arising in fusion data analysis. In IDA, all information is consistently formulated as probability density functions quantifying uncertainties in the analysis within the Bayesian probability theory. For a single diagnostic, IDA allows the identification of faulty measurements and improvements in the setup. For a set of diagnostics, IDA gives joint error distributions allowing the comparison and integration of different diagnostics results. Validation of physics models can be performed by model comparison techniques. Typical data analysis applications benefit from IDA capabilities of nonlinear error propagation, the inclusion of systematic effects and the comparison of different physics models. Applications range from outlier detection, background discrimination, model assessment and design of diagnostics. In order to cope with next step fusion device requirements, appropriate techniques are explored for fast analysis applications.

An epidemic model for biological data fusion in ad hoc sensor networks

NASA Astrophysics Data System (ADS)

Chang, K. C.; Kotari, Vikas

2009-05-01

Bio terrorism can be a very refined and a catastrophic approach of attacking a nation. This requires the development of a complete architecture dedicatedly designed for this purpose which includes but is not limited to Sensing/Detection, Tracking and Fusion, Communication, and others. In this paper we focus on one such architecture and evaluate its performance. Various sensors for this specific purpose have been studied. The accent has been on use of Distributed systems such as ad-hoc networks and on application of epidemic data fusion algorithms to better manage the bio threat data. The emphasis has been on understanding the performance characteristics of these algorithms under diversified real time scenarios which are implemented through extensive JAVA based simulations. Through comparative studies on communication and fusion the performance of channel filter algorithm for the purpose of biological sensor data fusion are validated.

Influence of incomplete fusion on complete fusion at energies above the Coulomb barrier

NASA Astrophysics Data System (ADS)

Shuaib, Mohd; Sharma, Vijay R.; Yadav, Abhishek; Sharma, Manoj Kumar; Singh, Pushpendra P.; Singh, Devendra P.; Kumar, R.; Singh, R. P.; Muralithar, S.; Singh, B. P.; Prasad, R.

2017-10-01

In the present work, excitation functions of several reaction residues in the system 19F+169Tm, populated via the complete and incomplete fusion processes, have been measured using off-line γ-ray spectroscopy. The analysis of excitation functions has been done within the framework of statistical model code pace4. The excitation functions of residues populated via xn and pxn channels are found to be in good agreement with those estimated by the theoretical model code, which confirms the production of these residues solely via complete fusion process. However, a significant enhancement has been observed in the cross-sections of residues involving α-emitting channels as compared to the theoretical predictions. The observed enhancement in the cross-sections has been attributed to the incomplete fusion processes. In order to have a better insight into the onset and strength of incomplete fusion, the incomplete fusion strength function has been deduced. At present, there is no theoretical model available which can satisfactorily explain the incomplete fusion reaction data at energies ≈4-6 MeV/nucleon. In the present work, the influence of incomplete fusion on complete fusion in the 19F+169Tm system has also been studied. The measured cross-section data may be important for the development of reactor technology as well. It has been found that the incomplete fusion strength function strongly depends on the α-Q value of the projectile, which is found to be in good agreement with the existing literature data. The analysis strongly supports the projectile-dependent mass-asymmetry systematics. In order to study the influence of Coulomb effect ({Z}{{P}}{Z}{{T}}) on incomplete fusion, the deduced strength function for the present work is compared with the nearby projectile-target combinations. The incomplete fusion strength function is found to increase linearly with {Z}{{P}}{Z}{{T}}, indicating a strong influence of Coulomb effect in the incomplete fusion reactions.

Semiotic foundation for multisensor-multilook fusion

NASA Astrophysics Data System (ADS)

Myler, Harley R.

1998-07-01

This paper explores the concept of an application of semiotic principles to the design of a multisensor-multilook fusion system. Semiotics is an approach to analysis that attempts to process media in a united way using qualitative methods as opposed to quantitative. The term semiotic refers to signs, or signatory data that encapsulates information. Semiotic analysis involves the extraction of signs from information sources and the subsequent processing of the signs into meaningful interpretations of the information content of the source. The multisensor fusion problem predicated on a semiotic system structure and incorporating semiotic analysis techniques is explored and the design for a multisensor system as an information fusion system is explored. Semiotic analysis opens the possibility of using non-traditional sensor sources and modalities in the fusion process, such as verbal and textual intelligence derived from human observers. Examples of how multisensor/multimodality data might be analyzed semiotically is shown and discussion on how a semiotic system for multisensor fusion could be realized is outlined. The architecture of a semiotic multisensor fusion processor that can accept situational awareness data is described, although an implementation has not as yet been constructed.

[Accuracy improvement of spectral classification of crop using microwave backscatter data].

PubMed

Jia, Kun; Li, Qiang-Zi; Tian, Yi-Chen; Wu, Bing-Fang; Zhang, Fei-Fei; Meng, Ji-Hua

2011-02-01

In the present study, VV polarization microwave backscatter data used for improving accuracies of spectral classification of crop is investigated. Classification accuracy using different classifiers based on the fusion data of HJ satellite multi-spectral and Envisat ASAR VV backscatter data are compared. The results indicate that fusion data can take full advantage of spectral information of HJ multi-spectral data and the structure sensitivity feature of ASAR VV polarization data. The fusion data enlarges the spectral difference among different classifications and improves crop classification accuracy. The classification accuracy using fusion data can be increased by 5 percent compared to the single HJ data. Furthermore, ASAR VV polarization data is sensitive to non-agrarian area of planted field, and VV polarization data joined classification can effectively distinguish the field border. VV polarization data associating with multi-spectral data used in crop classification enlarges the application of satellite data and has the potential of spread in the domain of agriculture.

Effects of Conflicts of Interest on Practice Patterns and Complication Rates in Spine Surgery.

PubMed

Cook, Ralph W; Weiner, Joseph A; Schallmo, Michael S; Chun, Danielle S; Barth, Kathryn A; Singh, Sameer K; Hsu, Wellington K

2017-09-01

Retrospective cohort study. We sought to determine whether financial relationships with industry had any impact on operative and/or complication rates of spine surgeons performing fusion surgeries. Recent actions from Congress and the Institute of Medicine have highlighted the importance of conflicts of interest among physicians. Orthopedic surgeons and neurosurgeons have been identified as receiving the highest amount of industry payments among all specialties. No study has yet investigated the potential effects of disclosed industry payments with quality and choices of patient care. A comprehensive database of spine surgeons in the United States with compiled data of industry payments, operative fusion rates, and complication rates was created. Practice pattern data were derived from a publicly available Medicare-based database generated from selected CPT codes from 2011 to 2012. Complication rate data from 2009 to 2013 were extracted from the ProPublica-Surgeon-Scorecard database, which utilizes postoperative inhospital mortality and 30-day-readmission for designated conditions as complications of surgery. Data regarding industry payments from 2013 to 2014 were derived from the Open Payments website. Surgeons performing <10 fusions, those without complication data, and those whose identity could not be verified through public records were excluded. Pearson correlation coefficients and multivariate regression analyses were used to determine the relationship between industry payments, operative fusion rate, and/or complication rate. A total of 2110 surgeons met the inclusion criteria for our database. The average operative fusion rate was 8.8% (SD 4.8%), whereas the average complication rate for lumbar and cervical fusion was 4.1% and 1.9%, respectively. Pearson correlation analysis revealed a statistically significant but negligible relationship between disclosed payments/transactions and both operative fusion and complication rates. Our findings do not support a strong correlation between the payments a surgeon receives from industry and their decisions to perform spine fusion or associated complication rates. Large variability in the rate of fusions performed suggests a poor consensus for indications for spine fusion surgery. 3.

Hierarchical adaptation scheme for multiagent data fusion and resource management in situation analysis

NASA Astrophysics Data System (ADS)

Benaskeur, Abder R.; Roy, Jean

2001-08-01

Sensor Management (SM) has to do with how to best manage, coordinate and organize the use of sensing resources in a manner that synergistically improves the process of data fusion. Based on the contextual information, SM develops options for collecting further information, allocates and directs the sensors towards the achievement of the mission goals and/or tunes the parameters for the realtime improvement of the effectiveness of the sensing process. Conscious of the important role that SM has to play in modern data fusion systems, we are currently studying advanced SM Concepts that would help increase the survivability of the current Halifax and Iroquois Class ships, as well as their possible future upgrades. For this purpose, a hierarchical scheme has been proposed for data fusion and resource management adaptation, based on the control theory and within the process refinement paradigm of the JDL data fusion model, and taking into account the multi-agent model put forward by the SASS Group for the situation analysis process. The novelty of this work lies in the unified framework that has been defined for tackling the adaptation of both the fusion process and the sensor/weapon management.

UAV hyperspectral and lidar data and their fusion for arid and semi-arid land vegetation monitoring

USDA-ARS?s Scientific Manuscript database

We demonstrate a unique fusion of unmanned aerial vehicle (UAV) lidar and hyperspectral imagery for individual plant species identification and 3D characterization of the earth surface at sub-meter scales in southeastern Arizona, USA. We hypothesized that the fusion of the two different data sources...

An Overview of INEL Fusion Safety R&D Facilities

NASA Astrophysics Data System (ADS)

McCarthy, K. A.; Smolik, G. R.; Anderl, R. A.; Carmack, W. J.; Longhurst, G. R.

1997-06-01

The Fusion Safety Program at the Idaho National Engineering Laboratory has the lead for fusion safety work in the United States. Over the years, we have developed several experimental facilities to provide data for fusion reactor safety analyses. We now have four major experimental facilities that provide data for use in safety assessments. The Steam-Reactivity Measurement System measures hydrogen generation rates and tritium mobilization rates in high-temperature (up to 1200°C) fusion relevant materials exposed to steam. The Volatilization of Activation Product Oxides Reactor Facility provides information on mobilization and transport and chemical reactivity of fusion relevant materials at high temperature (up to 1200°C) in an oxidizing environment (air or steam). The Fusion Aerosol Source Test Facility is a scaled-up version of VAPOR. The ion-implanta-tion/thermal-desorption system is dedicated to research into processes and phenomena associated with the interaction of hydrogen isotopes with fusion materials. In this paper we describe the capabilities of these facilities.

Exploration of the gene fusion landscape of glioblastoma using transcriptome sequencing and copy number data.

PubMed

Shah, Nameeta; Lankerovich, Michael; Lee, Hwahyung; Yoon, Jae-Geun; Schroeder, Brett; Foltz, Greg

2013-11-22

RNA-seq has spurred important gene fusion discoveries in a number of different cancers, including lung, prostate, breast, brain, thyroid and bladder carcinomas. Gene fusion discovery can potentially lead to the development of novel treatments that target the underlying genetic abnormalities. In this study, we provide comprehensive view of gene fusion landscape in 185 glioblastoma multiforme patients from two independent cohorts. Fusions occur in approximately 30-50% of GBM patient samples. In the Ivy Center cohort of 24 patients, 33% of samples harbored fusions that were validated by qPCR and Sanger sequencing. We were able to identify high-confidence gene fusions from RNA-seq data in 53% of the samples in a TCGA cohort of 161 patients. We identified 13 cases (8%) with fusions retaining a tyrosine kinase domain in the TCGA cohort and one case in the Ivy Center cohort. Ours is the first study to describe recurrent fusions involving non-coding genes. Genomic locations 7p11 and 12q14-15 harbor majority of the fusions. Fusions on 7p11 are formed in focally amplified EGFR locus whereas 12q14-15 fusions are formed by complex genomic rearrangements. All the fusions detected in this study can be further visualized and analyzed using our website: http://ivygap.swedish.org/fusions. Our study highlights the prevalence of gene fusions as one of the major genomic abnormalities in GBM. The majority of the fusions are private fusions, and a minority of these recur with low frequency. A small subset of patients with fusions of receptor tyrosine kinases can benefit from existing FDA approved drugs and drugs available in various clinical trials. Due to the low frequency and rarity of clinically relevant fusions, RNA-seq of GBM patient samples will be a vital tool for the identification of patient-specific fusions that can drive personalized therapy.

Advances in multi-sensor data fusion: algorithms and applications.

PubMed

Dong, Jiang; Zhuang, Dafang; Huang, Yaohuan; Fu, Jingying

2009-01-01

With the development of satellite and remote sensing techniques, more and more image data from airborne/satellite sensors have become available. Multi-sensor image fusion seeks to combine information from different images to obtain more inferences than can be derived from a single sensor. In image-based application fields, image fusion has emerged as a promising research area since the end of the last century. The paper presents an overview of recent advances in multi-sensor satellite image fusion. Firstly, the most popular existing fusion algorithms are introduced, with emphasis on their recent improvements. Advances in main applications fields in remote sensing, including object identification, classification, change detection and maneuvering targets tracking, are described. Both advantages and limitations of those applications are then discussed. Recommendations are addressed, including: (1) Improvements of fusion algorithms; (2) Development of "algorithm fusion" methods; (3) Establishment of an automatic quality assessment scheme.

Multiple-source spatial data fusion and integration research in the region unified planning management information system

NASA Astrophysics Data System (ADS)

Liu, Zhijun; Zhang, Liangpei; Liu, Zhenmin; Jiao, Hongbo; Chen, Liqun

2008-12-01

In order to manage the internal resources of Gulf of Tonkin and integrate multiple-source spatial data, the establishment of region unified plan management system is needed. The data fusion and the integrated research should be carried on because there are some difficulties in the course of the system's establishment. For example, kinds of planning and the project data format are different, and data criterion is not unified. Besides, the time state property is strong, and spatial reference is inconsistent, etc. In this article the ARCGIS ENGINE is introduced as the developing platform, key technologies are researched, such as multiple-source data transformation and fusion, remote sensing data and DEM fusion and integrated, plan and project data integration, and so on. Practice shows that the system improves the working efficiency of Guangxi Gulf of Tonkin Economic Zone Management Committee significantly and promotes planning construction work of the economic zone remarkably.

FT-Raman and NIR spectroscopy data fusion strategy for multivariate qualitative analysis of food fraud.

PubMed

Márquez, Cristina; López, M Isabel; Ruisánchez, Itziar; Callao, M Pilar

2016-12-01

Two data fusion strategies (high- and mid-level) combined with a multivariate classification approach (Soft Independent Modelling of Class Analogy, SIMCA) have been applied to take advantage of the synergistic effect of the information obtained from two spectroscopic techniques: FT-Raman and NIR. Mid-level data fusion consists of merging some of the previous selected variables from the spectra obtained from each spectroscopic technique and then applying the classification technique. High-level data fusion combines the SIMCA classification results obtained individually from each spectroscopic technique. Of the possible ways to make the necessary combinations, we decided to use fuzzy aggregation connective operators. As a case study, we considered the possible adulteration of hazelnut paste with almond. Using the two-class SIMCA approach, class 1 consisted of unadulterated hazelnut samples and class 2 of samples adulterated with almond. Models performance was also studied with samples adulterated with chickpea. The results show that data fusion is an effective strategy since the performance parameters are better than the individual ones: sensitivity and specificity values between 75% and 100% for the individual techniques and between 96-100% and 88-100% for the mid- and high-level data fusion strategies, respectively. Copyright © 2016 Elsevier B.V. All rights reserved.

Physiological sensor signals classification for healthcare using sensor data fusion and case-based reasoning.

PubMed

Begum, Shahina; Barua, Shaibal; Ahmed, Mobyen Uddin

2014-07-03

Today, clinicians often do diagnosis and classification of diseases based on information collected from several physiological sensor signals. However, sensor signal could easily be vulnerable to uncertain noises or interferences and due to large individual variations sensitivity to different physiological sensors could also vary. Therefore, multiple sensor signal fusion is valuable to provide more robust and reliable decision. This paper demonstrates a physiological sensor signal classification approach using sensor signal fusion and case-based reasoning. The proposed approach has been evaluated to classify Stressed or Relaxed individuals using sensor data fusion. Physiological sensor signals i.e., Heart Rate (HR), Finger Temperature (FT), Respiration Rate (RR), Carbon dioxide (CO2) and Oxygen Saturation (SpO2) are collected during the data collection phase. Here, sensor fusion has been done in two different ways: (i) decision-level fusion using features extracted through traditional approaches; and (ii) data-level fusion using features extracted by means of Multivariate Multiscale Entropy (MMSE). Case-Based Reasoning (CBR) is applied for the classification of the signals. The experimental result shows that the proposed system could classify Stressed or Relaxed individual 87.5% accurately compare to an expert in the domain. So, it shows promising result in the psychophysiological domain and could be possible to adapt this approach to other relevant healthcare systems.

A Markov game theoretic data fusion approach for cyber situational awareness

NASA Astrophysics Data System (ADS)

Shen, Dan; Chen, Genshe; Cruz, Jose B., Jr.; Haynes, Leonard; Kruger, Martin; Blasch, Erik

2007-04-01

This paper proposes an innovative data-fusion/ data-mining game theoretic situation awareness and impact assessment approach for cyber network defense. Alerts generated by Intrusion Detection Sensors (IDSs) or Intrusion Prevention Sensors (IPSs) are fed into the data refinement (Level 0) and object assessment (L1) data fusion components. High-level situation/threat assessment (L2/L3) data fusion based on Markov game model and Hierarchical Entity Aggregation (HEA) are proposed to refine the primitive prediction generated by adaptive feature/pattern recognition and capture new unknown features. A Markov (Stochastic) game method is used to estimate the belief of each possible cyber attack pattern. Game theory captures the nature of cyber conflicts: determination of the attacking-force strategies is tightly coupled to determination of the defense-force strategies and vice versa. Also, Markov game theory deals with uncertainty and incompleteness of available information. A software tool is developed to demonstrate the performance of the high level information fusion for cyber network defense situation and a simulation example shows the enhanced understating of cyber-network defense.

The optimal algorithm for Multi-source RS image fusion.

PubMed

Fu, Wei; Huang, Shui-Guang; Li, Zeng-Shun; Shen, Hao; Li, Jun-Shuai; Wang, Peng-Yuan

2016-01-01

In order to solve the issue which the fusion rules cannot be self-adaptively adjusted by using available fusion methods according to the subsequent processing requirements of Remote Sensing (RS) image, this paper puts forward GSDA (genetic-iterative self-organizing data analysis algorithm) by integrating the merit of genetic arithmetic together with the advantage of iterative self-organizing data analysis algorithm for multi-source RS image fusion. The proposed algorithm considers the wavelet transform of the translation invariance as the model operator, also regards the contrast pyramid conversion as the observed operator. The algorithm then designs the objective function by taking use of the weighted sum of evaluation indices, and optimizes the objective function by employing GSDA so as to get a higher resolution of RS image. As discussed above, the bullet points of the text are summarized as follows.•The contribution proposes the iterative self-organizing data analysis algorithm for multi-source RS image fusion.•This article presents GSDA algorithm for the self-adaptively adjustment of the fusion rules.•This text comes up with the model operator and the observed operator as the fusion scheme of RS image based on GSDA. The proposed algorithm opens up a novel algorithmic pathway for multi-source RS image fusion by means of GSDA.

Uncertainty Assessment and Weight Map Generation for Efficient Fusion of Tandem-X and CARTOSAT-1 Dems

NASA Astrophysics Data System (ADS)

Bagheri, H.; Schmitt, M.; Zhu, X. X.

2017-05-01

Recently, with InSAR data provided by the German TanDEM-X mission, a new global, high-resolution Digital Elevation Model (DEM) has been produced by the German Aerospace Center (DLR) with unprecedented height accuracy. However, due to SAR-inherent sensor specifics, its quality decreases over urban areas, making additional improvement necessary. On the other hand, DEMs derived from optical remote sensing imagery, such as Cartosat-1 data, have an apparently greater resolution in urban areas, making their fusion with TanDEM-X elevation data a promising perspective. The objective of this paper is two-fold: First, the height accuracies of TanDEM-X and Cartosat-1 elevation data over different land types are empirically evaluated in order to analyze the potential of TanDEM-XCartosat- 1 DEM data fusion. After the quality assessment, urban DEM fusion using weighted averaging is investigated. In this experiment, both weight maps derived from the height error maps delivered with the DEM data, as well as more sophisticated weight maps predicted by a procedure based on artificial neural networks (ANNs) are compared. The ANN framework employs several features that can describe the height residual performance to predict the weights used in the subsequent fusion step. The results demonstrate that especially the ANN-based framework is able to improve the quality of the final DEM through data fusion.

General software design for multisensor data fusion

NASA Astrophysics Data System (ADS)

Zhang, Junliang; Zhao, Yuming

1999-03-01

In this paper a general method of software design for multisensor data fusion is discussed in detail, which adopts object-oriented technology under UNIX operation system. The software for multisensor data fusion is divided into six functional modules: data collection, database management, GIS, target display and alarming data simulation etc. Furthermore, the primary function, the components and some realization methods of each modular is given. The interfaces among these functional modular relations are discussed. The data exchange among each functional modular is performed by interprocess communication IPC, including message queue, semaphore and shared memory. Thus, each functional modular is executed independently, which reduces the dependence among functional modules and helps software programing and testing. This software for multisensor data fusion is designed as hierarchical structure by the inheritance character of classes. Each functional modular is abstracted and encapsulated through class structure, which avoids software redundancy and enhances readability.

Data fusion of Landsat TM and IRS images in forest classification

Treesearch

Guangxing Wang; Markus Holopainen; Eero Lukkarinen

2000-01-01

Data fusion of Landsat TM images and Indian Remote Sensing satellite panchromatic image (IRS-1C PAN) was studied and compared to the use of TM or IRS image only. The aim was to combine the high spatial resolution of IRS-1C PAN to the high spectral resolution of Landsat TM images using a data fusion algorithm. The ground truth of the study was based on a sample of 1,020...

Physics-based and human-derived information fusion for analysts

NASA Astrophysics Data System (ADS)

Blasch, Erik; Nagy, James; Scott, Steve; Okoth, Joshua; Hinman, Michael

2017-05-01

Recent trends in physics-based and human-derived information fusion (PHIF) have amplified the capabilities of analysts; however with the big data opportunities there is a need for open architecture designs, methods of distributed team collaboration, and visualizations. In this paper, we explore recent trends in the information fusion to support user interaction and machine analytics. Challenging scenarios requiring PHIF include combing physics-based video data with human-derived text data for enhanced simultaneous tracking and identification. A driving effort would be to provide analysts with applications, tools, and interfaces that afford effective and affordable solutions for timely decision making. Fusion at scale should be developed to allow analysts to access data, call analytics routines, enter solutions, update models, and store results for distributed decision making.

Structured Multi-level Data Fusion and Modelling of Heterogeneous Environmental Data for Future Internet Applications

NASA Astrophysics Data System (ADS)

Sabeur, Zoheir; Chakravarthy, Ajay; Bashevoy, Maxim; Modafferi, Stefano

2013-04-01

The rapid increase in environmental observations which are conducted by Small to Medium Enterprise communities and volunteers using affordable in situ sensors at various scales, in addition to the more established observatories set up by environmental and space agencies using airborne and space-borne sensing technologies is generating serious amounts of BIG data at ever increasing speeds. Furthermore, the emergence of Future Internet technologies and the urgent requirements for the deployment of specific enablers for the delivery of processed environmental knowledge in real-time with advanced situation awareness to citizens has reached paramount importance. Specifically, it has become highly critical now to build and provide services which automate the aggregation of data from various sources, while surmounting the semantic gaps, conflicts and heterogeneity in data sources. The early stage aggregation of data will enable the pre-processing of data from multiple sources while reconciling the temporal gaps in measurement time series, and aligning their respective a-synchronicities. This low level type of data fusion process needs to be automated and chained to more advanced level of data fusion services specialising in observation forecasts at spaces where sensing is not deployed; or at time slices where sensing has not taken place yet. As a result, multi-level fusion services are required among the families of specific enablers for monitoring environments and spaces in the Future Internet. These have been intially deployed and piloted in the ongoing ENVIROFI project of the FI-PPP programme [1]. Automated fusion and modelling of in situ and remote sensing data has been set up and the experimentation successfully conducted using RBF networks for the spatial fusion of water quality parameters measurements from satellite and stationary buoys in the Irish Sea. The RBF networks method scales for the spatial data fusion of multiple types of observation sources. This important approach provides a strong basis for the delivery of environmental observations at desired spatial and temporal scales to multiple users with various needs of spatial and temporal resolutions. It has also led to building robust future internet specific enablers on data fusion, which can indeed be used for multiple usage areas above and beyond the environmental domains of the Future Internet. In this paper, data and processing workflow scenarios shall be described. The fucntionalities of the multi-level fusion services shall be demonstrated and made accessible to the wider communities of the Fututre Internet. [1] The Environmental Observation Web and its Service Applications within the Future Internet. ENVIROFI IP. FP7-2011-ICT-IF Pr.No: 284898 http://www.envirofi.eu/

Towards a Unified Approach to Information Integration - A review paper on data/information fusion

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

Whitney, Paul D.; Posse, Christian; Lei, Xingye C.

2005-10-14

Information or data fusion of data from different sources are ubiquitous in many applications, from epidemiology, medical, biological, political, and intelligence to military applications. Data fusion involves integration of spectral, imaging, text, and many other sensor data. For example, in epidemiology, information is often obtained based on many studies conducted by different researchers at different regions with different protocols. In the medical field, the diagnosis of a disease is often based on imaging (MRI, X-Ray, CT), clinical examination, and lab results. In the biological field, information is obtained based on studies conducted on many different species. In military field, informationmore » is obtained based on data from radar sensors, text messages, chemical biological sensor, acoustic sensor, optical warning and many other sources. Many methodologies are used in the data integration process, from classical, Bayesian, to evidence based expert systems. The implementation of the data integration ranges from pure software design to a mixture of software and hardware. In this review we summarize the methodologies and implementations of data fusion process, and illustrate in more detail the methodologies involved in three examples. We propose a unified multi-stage and multi-path mapping approach to the data fusion process, and point out future prospects and challenges.« less

Multi-scale pixel-based image fusion using multivariate empirical mode decomposition.

PubMed

Rehman, Naveed ur; Ehsan, Shoaib; Abdullah, Syed Muhammad Umer; Akhtar, Muhammad Jehanzaib; Mandic, Danilo P; McDonald-Maier, Klaus D

2015-05-08

A novel scheme to perform the fusion of multiple images using the multivariate empirical mode decomposition (MEMD) algorithm is proposed. Standard multi-scale fusion techniques make a priori assumptions regarding input data, whereas standard univariate empirical mode decomposition (EMD)-based fusion techniques suffer from inherent mode mixing and mode misalignment issues, characterized respectively by either a single intrinsic mode function (IMF) containing multiple scales or the same indexed IMFs corresponding to multiple input images carrying different frequency information. We show that MEMD overcomes these problems by being fully data adaptive and by aligning common frequency scales from multiple channels, thus enabling their comparison at a pixel level and subsequent fusion at multiple data scales. We then demonstrate the potential of the proposed scheme on a large dataset of real-world multi-exposure and multi-focus images and compare the results against those obtained from standard fusion algorithms, including the principal component analysis (PCA), discrete wavelet transform (DWT) and non-subsampled contourlet transform (NCT). A variety of image fusion quality measures are employed for the objective evaluation of the proposed method. We also report the results of a hypothesis testing approach on our large image dataset to identify statistically-significant performance differences.

Multi-Scale Pixel-Based Image Fusion Using Multivariate Empirical Mode Decomposition

PubMed Central

Rehman, Naveed ur; Ehsan, Shoaib; Abdullah, Syed Muhammad Umer; Akhtar, Muhammad Jehanzaib; Mandic, Danilo P.; McDonald-Maier, Klaus D.

2015-01-01

A novel scheme to perform the fusion of multiple images using the multivariate empirical mode decomposition (MEMD) algorithm is proposed. Standard multi-scale fusion techniques make a priori assumptions regarding input data, whereas standard univariate empirical mode decomposition (EMD)-based fusion techniques suffer from inherent mode mixing and mode misalignment issues, characterized respectively by either a single intrinsic mode function (IMF) containing multiple scales or the same indexed IMFs corresponding to multiple input images carrying different frequency information. We show that MEMD overcomes these problems by being fully data adaptive and by aligning common frequency scales from multiple channels, thus enabling their comparison at a pixel level and subsequent fusion at multiple data scales. We then demonstrate the potential of the proposed scheme on a large dataset of real-world multi-exposure and multi-focus images and compare the results against those obtained from standard fusion algorithms, including the principal component analysis (PCA), discrete wavelet transform (DWT) and non-subsampled contourlet transform (NCT). A variety of image fusion quality measures are employed for the objective evaluation of the proposed method. We also report the results of a hypothesis testing approach on our large image dataset to identify statistically-significant performance differences. PMID:26007714

Heterogeneous classifier fusion for ligand-based virtual screening: or, how decision making by committee can be a good thing.

PubMed

Riniker, Sereina; Fechner, Nikolas; Landrum, Gregory A

2013-11-25

The concept of data fusion - the combination of information from different sources describing the same object with the expectation to generate a more accurate representation - has found application in a very broad range of disciplines. In the context of ligand-based virtual screening (VS), data fusion has been applied to combine knowledge from either different active molecules or different fingerprints to improve similarity search performance. Machine-learning (ML) methods based on fusion of multiple homogeneous classifiers, in particular random forests, have also been widely applied in the ML literature. The heterogeneous version of classifier fusion - fusing the predictions from different model types - has been less explored. Here, we investigate heterogeneous classifier fusion for ligand-based VS using three different ML methods, RF, naïve Bayes (NB), and logistic regression (LR), with four 2D fingerprints, atom pairs, topological torsions, RDKit fingerprint, and circular fingerprint. The methods are compared using a previously developed benchmarking platform for 2D fingerprints which is extended to ML methods in this article. The original data sets are filtered for difficulty, and a new set of challenging data sets from ChEMBL is added. Data sets were also generated for a second use case: starting from a small set of related actives instead of diverse actives. The final fused model consistently outperforms the other approaches across the broad variety of targets studied, indicating that heterogeneous classifier fusion is a very promising approach for ligand-based VS. The new data sets together with the adapted source code for ML methods are provided in the Supporting Information .

An optimized data fusion method and its application to improve lateral boundary conditions in winter for Pearl River Delta regional PM2.5 modeling, China

NASA Astrophysics Data System (ADS)

Huang, Zhijiong; Hu, Yongtao; Zheng, Junyu; Zhai, Xinxin; Huang, Ran

2018-05-01

Lateral boundary conditions (LBCs) are essential for chemical transport models to simulate regional transport; however they often contain large uncertainties. This study proposes an optimized data fusion approach to reduce the bias of LBCs by fusing gridded model outputs, from which the daughter domain's LBCs are derived, with ground-level measurements. The optimized data fusion approach follows the framework of a previous interpolation-based fusion method but improves it by using a bias kriging method to correct the spatial bias in gridded model outputs. Cross-validation shows that the optimized approach better estimates fused fields in areas with a large number of observations compared to the previous interpolation-based method. The optimized approach was applied to correct LBCs of PM2.5 concentrations for simulations in the Pearl River Delta (PRD) region as a case study. Evaluations show that the LBCs corrected by data fusion improve in-domain PM2.5 simulations in terms of the magnitude and temporal variance. Correlation increases by 0.13-0.18 and fractional bias (FB) decreases by approximately 3%-15%. This study demonstrates the feasibility of applying data fusion to improve regional air quality modeling.

Y fuse? Sex chromosome fusions in fishes and reptiles.

PubMed

Pennell, Matthew W; Kirkpatrick, Mark; Otto, Sarah P; Vamosi, Jana C; Peichel, Catherine L; Valenzuela, Nicole; Kitano, Jun

2015-05-01

Chromosomal fusion plays a recurring role in the evolution of adaptations and reproductive isolation among species, yet little is known of the evolutionary drivers of chromosomal fusions. Because sex chromosomes (X and Y in male heterogametic systems, Z and W in female heterogametic systems) differ in their selective, mutational, and demographic environments, those differences provide a unique opportunity to dissect the evolutionary forces that drive chromosomal fusions. We estimate the rate at which fusions between sex chromosomes and autosomes become established across the phylogenies of both fishes and squamate reptiles. Both the incidence among extant species and the establishment rate of Y-autosome fusions is much higher than for X-autosome, Z-autosome, or W-autosome fusions. Using population genetic models, we show that this pattern cannot be reconciled with many standard explanations for the spread of fusions. In particular, direct selection acting on fusions or sexually antagonistic selection cannot, on their own, account for the predominance of Y-autosome fusions. The most plausible explanation for the observed data seems to be (a) that fusions are slightly deleterious, and (b) that the mutation rate is male-biased or the reproductive sex ratio is female-biased. We identify other combinations of evolutionary forces that might in principle account for the data although they appear less likely. Our results shed light on the processes that drive structural changes throughout the genome.

Y Fuse? Sex Chromosome Fusions in Fishes and Reptiles

PubMed Central

Vamosi, Jana C.; Peichel, Catherine L.; Valenzuela, Nicole; Kitano, Jun

2015-01-01

Chromosomal fusion plays a recurring role in the evolution of adaptations and reproductive isolation among species, yet little is known of the evolutionary drivers of chromosomal fusions. Because sex chromosomes (X and Y in male heterogametic systems, Z and W in female heterogametic systems) differ in their selective, mutational, and demographic environments, those differences provide a unique opportunity to dissect the evolutionary forces that drive chromosomal fusions. We estimate the rate at which fusions between sex chromosomes and autosomes become established across the phylogenies of both fishes and squamate reptiles. Both the incidence among extant species and the establishment rate of Y-autosome fusions is much higher than for X-autosome, Z-autosome, or W-autosome fusions. Using population genetic models, we show that this pattern cannot be reconciled with many standard explanations for the spread of fusions. In particular, direct selection acting on fusions or sexually antagonistic selection cannot, on their own, account for the predominance of Y-autosome fusions. The most plausible explanation for the observed data seems to be (a) that fusions are slightly deleterious, and (b) that the mutation rate is male-biased or the reproductive sex ratio is female-biased. We identify other combinations of evolutionary forces that might in principle account for the data although they appear less likely. Our results shed light on the processes that drive structural changes throughout the genome. PMID:25993542

Quality dependent fusion of intramodal and multimodal biometric experts

NASA Astrophysics Data System (ADS)

Kittler, J.; Poh, N.; Fatukasi, O.; Messer, K.; Kryszczuk, K.; Richiardi, J.; Drygajlo, A.

2007-04-01

We address the problem of score level fusion of intramodal and multimodal experts in the context of biometric identity verification. We investigate the merits of confidence based weighting of component experts. In contrast to the conventional approach where confidence values are derived from scores, we use instead raw measures of biometric data quality to control the influence of each expert on the final fused score. We show that quality based fusion gives better performance than quality free fusion. The use of quality weighted scores as features in the definition of the fusion functions leads to further improvements. We demonstrate that the achievable performance gain is also affected by the choice of fusion architecture. The evaluation of the proposed methodology involves 6 face and one speech verification experts. It is carried out on the XM2VTS data base.

A Decision Fusion Framework for Treatment Recommendation Systems.

PubMed

Mei, Jing; Liu, Haifeng; Li, Xiang; Xie, Guotong; Yu, Yiqin

2015-01-01

Treatment recommendation is a nontrivial task--it requires not only domain knowledge from evidence-based medicine, but also data insights from descriptive, predictive and prescriptive analysis. A single treatment recommendation system is usually trained or modeled with a limited (size or quality) source. This paper proposes a decision fusion framework, combining both knowledge-driven and data-driven decision engines for treatment recommendation. End users (e.g. using the clinician workstation or mobile apps) could have a comprehensive view of various engines' opinions, as well as the final decision after fusion. For implementation, we leverage several well-known fusion algorithms, such as decision templates and meta classifiers (of logistic and SVM, etc.). Using an outcome-driven evaluation metric, we compare the fusion engine with base engines, and our experimental results show that decision fusion is a promising way towards a more valuable treatment recommendation.

Comparison of the resulting error in data fusion techniques when used with remote sensing, earth observation, and in-situ data sets for water quality applications

NASA Astrophysics Data System (ADS)

Ziemba, Alexander; El Serafy, Ghada

2016-04-01

Ecological modeling and water quality investigations are complex processes which can require a high level of parameterization and a multitude of varying data sets in order to properly execute the model in question. Since models are generally complex, their calibration and validation can benefit from the application of data and information fusion techniques. The data applied to ecological models comes from a wide range of sources such as remote sensing, earth observation, and in-situ measurements, resulting in a high variability in the temporal and spatial resolution of the various data sets available to water quality investigators. It is proposed that effective fusion into a comprehensive singular set will provide a more complete and robust data resource with which models can be calibrated, validated, and driven by. Each individual product contains a unique valuation of error resulting from the method of measurement and application of pre-processing techniques. The uncertainty and error is further compounded when the data being fused is of varying temporal and spatial resolution. In order to have a reliable fusion based model and data set, the uncertainty of the results and confidence interval of the data being reported must be effectively communicated to those who would utilize the data product or model outputs in a decision making process[2]. Here we review an array of data fusion techniques applied to various remote sensing, earth observation, and in-situ data sets whose domains' are varied in spatial and temporal resolution. The data sets examined are combined in a manner so that the various classifications, complementary, redundant, and cooperative, of data are all assessed to determine classification's impact on the propagation and compounding of error. In order to assess the error of the fused data products, a comparison is conducted with data sets containing a known confidence interval and quality rating. We conclude with a quantification of the performance of the data fusion techniques and a recommendation on the feasibility of applying of the fused products in operating forecast systems and modeling scenarios. The error bands and confidence intervals derived can be used in order to clarify the error and confidence of water quality variables produced by prediction and forecasting models. References [1] F. Castanedo, "A Review of Data Fusion Techniques", The Scientific World Journal, vol. 2013, pp. 1-19, 2013. [2] T. Keenan, M. Carbone, M. Reichstein and A. Richardson, "The model-data fusion pitfall: assuming certainty in an uncertain world", Oecologia, vol. 167, no. 3, pp. 587-597, 2011.

Propagation of nuclear data uncertainties for fusion power measurements

NASA Astrophysics Data System (ADS)

Sjöstrand, Henrik; Conroy, Sean; Helgesson, Petter; Hernandez, Solis Augusto; Koning, Arjan; Pomp, Stephan; Rochman, Dimitri

2017-09-01

Neutron measurements using neutron activation systems are an essential part of the diagnostic system at large fusion machines such as JET and ITER. Nuclear data is used to infer the neutron yield. Consequently, high-quality nuclear data is essential for the proper determination of the neutron yield and fusion power. However, uncertainties due to nuclear data are not fully taken into account in uncertainty analysis for neutron yield calibrations using activation foils. This paper investigates the neutron yield uncertainty due to nuclear data using the so-called Total Monte Carlo Method. The work is performed using a detailed MCNP model of the JET fusion machine; the uncertainties due to the cross-sections and angular distributions in JET structural materials, as well as the activation cross-sections in the activation foils, are analysed. It is found that a significant contribution to the neutron yield uncertainty can come from uncertainties in the nuclear data.

Sensor fusion of monocular cameras and laser rangefinders for line-based Simultaneous Localization and Mapping (SLAM) tasks in autonomous mobile robots.

PubMed

Zhang, Xinzheng; Rad, Ahmad B; Wong, Yiu-Kwong

2012-01-01

This paper presents a sensor fusion strategy applied for Simultaneous Localization and Mapping (SLAM) in dynamic environments. The designed approach consists of two features: (i) the first one is a fusion module which synthesizes line segments obtained from laser rangefinder and line features extracted from monocular camera. This policy eliminates any pseudo segments that appear from any momentary pause of dynamic objects in laser data. (ii) The second characteristic is a modified multi-sensor point estimation fusion SLAM (MPEF-SLAM) that incorporates two individual Extended Kalman Filter (EKF) based SLAM algorithms: monocular and laser SLAM. The error of the localization in fused SLAM is reduced compared with those of individual SLAM. Additionally, a new data association technique based on the homography transformation matrix is developed for monocular SLAM. This data association method relaxes the pleonastic computation. The experimental results validate the performance of the proposed sensor fusion and data association method.

Molecular and cellular aspects of rhabdovirus entry.

PubMed

Albertini, Aurélie A V; Baquero, Eduard; Ferlin, Anna; Gaudin, Yves

2012-01-01

Rhabdoviruses enter the cell via the endocytic pathway and subsequently fuse with a cellular membrane within the acidic environment of the endosome. Both receptor recognition and membrane fusion are mediated by a single transmembrane viral glycoprotein (G). Fusion is triggered via a low-pH induced structural rearrangement. G is an atypical fusion protein as there is a pH-dependent equilibrium between its pre- and post-fusion conformations. The elucidation of the atomic structures of these two conformations for the vesicular stomatitis virus (VSV) G has revealed that it is different from the previously characterized class I and class II fusion proteins. In this review, the pre- and post-fusion VSV G structures are presented in detail demonstrating that G combines the features of the class I and class II fusion proteins. In addition to these similarities, these G structures also reveal some particularities that expand our understanding of the working of fusion machineries. Combined with data from recent studies that revealed the cellular aspects of the initial stages of rhabdovirus infection, all these data give an integrated view of the entry pathway of rhabdoviruses into their host cell.

Molecular and Cellular Aspects of Rhabdovirus Entry

PubMed Central

Albertini, Aurélie A. V.; Baquero, Eduard; Ferlin, Anna; Gaudin, Yves

2012-01-01

Rhabdoviruses enter the cell via the endocytic pathway and subsequently fuse with a cellular membrane within the acidic environment of the endosome. Both receptor recognition and membrane fusion are mediated by a single transmembrane viral glycoprotein (G). Fusion is triggered via a low-pH induced structural rearrangement. G is an atypical fusion protein as there is a pH-dependent equilibrium between its pre- and post-fusion conformations. The elucidation of the atomic structures of these two conformations for the vesicular stomatitis virus (VSV) G has revealed that it is different from the previously characterized class I and class II fusion proteins. In this review, the pre- and post-fusion VSV G structures are presented in detail demonstrating that G combines the features of the class I and class II fusion proteins. In addition to these similarities, these G structures also reveal some particularities that expand our understanding of the working of fusion machineries. Combined with data from recent studies that revealed the cellular aspects of the initial stages of rhabdovirus infection, all these data give an integrated view of the entry pathway of rhabdoviruses into their host cell. PMID:22355455

A measurement fusion method for nonlinear system identification using a cooperative learning algorithm.

PubMed

Xia, Youshen; Kamel, Mohamed S

2007-06-01

Identification of a general nonlinear noisy system viewed as an estimation of a predictor function is studied in this article. A measurement fusion method for the predictor function estimate is proposed. In the proposed scheme, observed data are first fused by using an optimal fusion technique, and then the optimal fused data are incorporated in a nonlinear function estimator based on a robust least squares support vector machine (LS-SVM). A cooperative learning algorithm is proposed to implement the proposed measurement fusion method. Compared with related identification methods, the proposed method can minimize both the approximation error and the noise error. The performance analysis shows that the proposed optimal measurement fusion function estimate has a smaller mean square error than the LS-SVM function estimate. Moreover, the proposed cooperative learning algorithm can converge globally to the optimal measurement fusion function estimate. Finally, the proposed measurement fusion method is applied to ARMA signal and spatial temporal signal modeling. Experimental results show that the proposed measurement fusion method can provide a more accurate model.

Data Fusion Analysis for Range Test Validation System

DTIC Science & Technology

2010-07-14

simulants were released during the RTVS ’08 test series: triethyl phosphate (TEP), methyl salicylate (MeS), and acetic acid (AA). A total of 29 release...the combination of a grid of point sensors at ground level and a standoff FTIR system monitoring above ground areas proved effective in detecting the...presence of simulants over the test grid. A Dempster-Shafer approach for data fusion was selected as the most effective strategy for RTVS data fusion

Discrimination of Medicine Radix Astragali from Different Geographic Origins Using Multiple Spectroscopies Combined with Data Fusion Methods

NASA Astrophysics Data System (ADS)

Wang, Hai-Yan; Song, Chao; Sha, Min; Liu, Jun; Li, Li-Ping; Zhang, Zheng-Yong

2018-05-01

Raman spectra and ultraviolet-visible absorption spectra of four different geographic origins of Radix Astragali were collected. These data were analyzed using kernel principal component analysis combined with sparse representation classification. The results showed that the recognition rate reached 70.44% using Raman spectra for data input and 90.34% using ultraviolet-visible absorption spectra for data input. A new fusion method based on Raman combined with ultraviolet-visible data was investigated and the recognition rate was increased to 96.43%. The experimental results suggested that the proposed data fusion method effectively improved the utilization rate of the original data.

Average Throughput Performance of Myopic Policy in Energy Harvesting Wireless Sensor Networks.

PubMed

Gul, Omer Melih; Demirekler, Mubeccel

2017-09-26

This paper considers a single-hop wireless sensor network where a fusion center collects data from M energy harvesting wireless sensors. The harvested energy is stored losslessly in an infinite-capacity battery at each sensor. In each time slot, the fusion center schedules K sensors for data transmission over K orthogonal channels. The fusion center does not have direct knowledge on the battery states of sensors, or the statistics of their energy harvesting processes. The fusion center only has information of the outcomes of previous transmission attempts. It is assumed that the sensors are data backlogged, there is no battery leakage and the communication is error-free. An energy harvesting sensor can transmit data to the fusion center whenever being scheduled only if it has enough energy for data transmission. We investigate average throughput of Round-Robin type myopic policy both analytically and numerically under an average reward (throughput) criterion. We show that Round-Robin type myopic policy achieves optimality for some class of energy harvesting processes although it is suboptimal for a broad class of energy harvesting processes.

Average Throughput Performance of Myopic Policy in Energy Harvesting Wireless Sensor Networks

PubMed Central

Demirekler, Mubeccel

2017-01-01

This paper considers a single-hop wireless sensor network where a fusion center collects data from M energy harvesting wireless sensors. The harvested energy is stored losslessly in an infinite-capacity battery at each sensor. In each time slot, the fusion center schedules K sensors for data transmission over K orthogonal channels. The fusion center does not have direct knowledge on the battery states of sensors, or the statistics of their energy harvesting processes. The fusion center only has information of the outcomes of previous transmission attempts. It is assumed that the sensors are data backlogged, there is no battery leakage and the communication is error-free. An energy harvesting sensor can transmit data to the fusion center whenever being scheduled only if it has enough energy for data transmission. We investigate average throughput of Round-Robin type myopic policy both analytically and numerically under an average reward (throughput) criterion. We show that Round-Robin type myopic policy achieves optimality for some class of energy harvesting processes although it is suboptimal for a broad class of energy harvesting processes. PMID:28954420

Data fusion: principles and applications in air defense

NASA Astrophysics Data System (ADS)

Maltese, Dominique; Lucas, Andre

1998-07-01

Within a Surveillance and Reconnaissance System, the Fusion Process is an essential part of the software package since the different sensors measurements are combined by this process; each sensor sends its data to a fusion center whose task is to elaborate the best tactical situation. In this paper, a practical algorithm of data fusion applied to a military application context is presented; the case studied here is a medium-range surveillance situation featuring a dual-sensor platform which combines a surveillance Radar and an IRST; both sensors are collocated. The presented performances were obtained on validation scenarios via simulations performed by SAGEM with the ESSOR ('Environnement de Simulation de Senseurs Optroniques et Radar') multisensor simulation test bench.

Multisensor data fusion for integrated maritime surveillance

NASA Astrophysics Data System (ADS)

Premji, A.; Ponsford, A. M.

1995-01-01

A prototype Integrated Coastal Surveillance system has been developed on Canada's East Coast to provide effective surveillance out to and beyond the 200 nautical mile Exclusive Economic Zone. The system has been designed to protect Canada's natural resources, and to monitor and control the coastline for smuggling, drug trafficking, and similar illegal activity. This paper describes the Multiple Sensor - Multiple Target data fusion system that has been developed. The fusion processor has been developed around the celebrated Multiple Hypothesis Tracking algorithm which accommodates multiple targets, new targets, false alarms, and missed detections. This processor performs four major functions: plot-to-track association to form individual radar tracks; fusion of radar tracks with secondary sensor reports; track identification and tagging using secondary reports; and track level fusion to form common tracks. Radar data from coherent and non-coherent radars has been used to evaluate the performance of the processor. This paper presents preliminary results.

Issues in Data Fusion for Satellite Aerosol Measurements for Applications with GIOVANNI System at NASA GES DISC

NASA Technical Reports Server (NTRS)

Gopalan, Arun; Zubko, Viktor; Leptoukh, Gregory G.

2008-01-01

We look at issues, barriers and approaches for Data Fusion of satellite aerosol data as available from the GES DISC GIOVANNI Web Service. Daily Global Maps of AOT from a single satellite sensor alone contain gaps that arise due to various sources (sun glint regions, clouds, orbital swath gaps at low latitudes, bright underlying surfaces etc.). The goal is to develop a fast, accurate and efficient method to improve the spatial coverage of the Daily AOT data to facilitate comparisons with Global Models. Data Fusion may be supplemented by Optimal Interpolation (OI) as needed.

New results in low-energy fusion of 40Ca+Zr,9290

NASA Astrophysics Data System (ADS)

Stefanini, A. M.; Montagnoli, G.; Esbensen, H.; Čolović, P.; Corradi, L.; Fioretto, E.; Galtarossa, F.; Goasduff, A.; Grebosz, J.; Haas, F.; Mazzocco, M.; Soić, N.; Strano, E.; Szilner, S.

2017-07-01

Background: Near- and sub-barrier fusion of various Ca + Zr isotopic combinations have been widely investigated. A recent analysis of 40Ca+96Zr data has highlighted the importance of couplings to multiphonon excitations and to both neutron and proton transfer channels. Analogous studies of 40Ca+90Zr tend to exclude any role of transfer couplings. However, the lowest measured cross section for this system is rather high (840 μ b ). A rather complete data set is available for 40Ca+94Zr , while no measurement of 40Ca+92Zr fusion has been performed in the past. Purpose: Our aim is to measure the full excitation function of 40Ca+92Zr near the barrier and to extend downward the existing data on 40Ca+90Zr , in order to estimate the transfer couplings that should be used in coupled-channels calculations of the fusion of these two systems and of 40Ca+94Zr . Methods: 40Ca beams from the XTU Tandem accelerator of INFN-Laboratori Nazionali di Legnaro were used, bombarding thin metallic 90Zr (50 μ g /cm2 ) and 92ZrO2 targets (same thickness) enriched to 99.36 % and 98.06 % in masses 90 and 92, respectively. An electrostatic beam deflector allowed the detection of fusion evaporation residues (ER) at very forward angles, and angular distributions of ER were measured. Results: The excitation function of 40Ca+92Zr has been measured down to the level of ≃60 μ b . Coupled-channels (CC) calculations using a standard Woods-Saxon (WS) potential and following the line of a previous analysis of 40Ca+96Zr fusion data give a good account of the new data, as well as of the existing data for 40Ca+94Zr . The previous excitation function of 40Ca+90Zr has been extended down to 40 μ b . Conclusions: Transfer couplings play an important role in explaining the fusion data for 40Ca+92Zr and 40Ca+94Zr . The strength of the pair-transfer coupling is deduced by applying a simple recipe based on the value obtained for 40Ca+96Zr . The logarithmic slopes and the S factors for fusion are reproduced fairly well for all three systems by the CC calculations, and there are no indications of a fusion hindrance at the lowest energies. In contrast, the new data for 40Ca+90Zr indicate the onset of a fusion hindrance at the lowest energies.

A data fusion framework for meta-evaluation of intelligent transportation system effectiveness

DOT National Transportation Integrated Search

This study presents a framework for the meta-evaluation of Intelligent Transportation System effectiveness. The framework is based on data fusion approaches that adjust for data biases and violations of other standard statistical assumptions. Operati...

The Research on Dryland Crop Classification Based on the Fusion of SENTINEL-1A SAR and Optical Images

NASA Astrophysics Data System (ADS)

Liu, F.; Chen, T.; He, J.; Wen, Q.; Yu, F.; Gu, X.; Wang, Z.

2018-04-01

In recent years, the quick upgrading and improvement of SAR sensors provide beneficial complements for the traditional optical remote sensing in the aspects of theory, technology and data. In this paper, Sentinel-1A SAR data and GF-1 optical data were selected for image fusion, and more emphases were put on the dryland crop classification under a complex crop planting structure, regarding corn and cotton as the research objects. Considering the differences among various data fusion methods, the principal component analysis (PCA), Gram-Schmidt (GS), Brovey and wavelet transform (WT) methods were compared with each other, and the GS and Brovey methods were proved to be more applicable in the study area. Then, the classification was conducted based on the object-oriented technique process. And for the GS, Brovey fusion images and GF-1 optical image, the nearest neighbour algorithm was adopted to realize the supervised classification with the same training samples. Based on the sample plots in the study area, the accuracy assessment was conducted subsequently. The values of overall accuracy and kappa coefficient of fusion images were all higher than those of GF-1 optical image, and GS method performed better than Brovey method. In particular, the overall accuracy of GS fusion image was 79.8 %, and the Kappa coefficient was 0.644. Thus, the results showed that GS and Brovey fusion images were superior to optical images for dryland crop classification. This study suggests that the fusion of SAR and optical images is reliable for dryland crop classification under a complex crop planting structure.

Sensor data fusion of radar, ESM, IFF, and data LINK of the Canadian Patrol Frigate and the data alignment issues

NASA Astrophysics Data System (ADS)

Couture, Jean; Boily, Edouard; Simard, Marc-Alain

1996-05-01

The research and development group at Loral Canada is now at the second phase of the development of a data fusion demonstration model (DFDM) for a naval anti-air warfare to be used as a workbench tool to perform exploratory research. This project has emphatically addressed how the concepts related to fusion could be implemented within the Canadian Patrol Frigate (CPF) software environment. The project has been designed to read data passively on the CPF bus without any modification to the CPF software. This has brought to light important time alignment issues since the CPF sensors and the CPF command and control system were not important time alignment issues since the CPF sensors and the CPF command and control system were not originally designed to support a track management function which fuses information. The fusion of data from non-organic sensors with the tactical Link-11 data has produced stimulating spatial alignment problems which have been overcome by the use of a geodetic referencing coordinate system. Some benchmark scenarios have been selected to quantitatively demonstrate the capabilities of this fusion implementation. This paper describes the implementation design of DFDM (version 2), and summarizes the results obtained so far when fusing the scenarios simulated data.

Guideline update for the performance of fusion procedures for degenerative disease of the lumbar spine. Part 3: assessment of economic outcome.

PubMed

Ghogawala, Zoher; Whitmore, Robert G; Watters, William C; Sharan, Alok; Mummaneni, Praveen V; Dailey, Andrew T; Choudhri, Tanvir F; Eck, Jason C; Groff, Michael W; Wang, Jeffrey C; Resnick, Daniel K; Dhall, Sanjay S; Kaiser, Michael G

2014-07-01

A comprehensive economic analysis generally involves the calculation of indirect and direct health costs from a societal perspective as opposed to simply reporting costs from a hospital or payer perspective. Hospital charges for a surgical procedure must be converted to cost data when performing a cost-effectiveness analysis. Once cost data has been calculated, quality-adjusted life year data from a surgical treatment are calculated by using a preference-based health-related quality-of-life instrument such as the EQ-5D. A recent cost-utility analysis from a single study has demonstrated the long-term (over an 8-year time period) benefits of circumferential fusions over stand-alone posterolateral fusions. In addition, economic analysis from a single study has found that lumbar fusion for selected patients with low-back pain can be recommended from an economic perspective. Recent economic analysis, from a single study, finds that femoral ring allograft might be more cost-effective compared with a specific titanium cage when performing an anterior lumbar interbody fusion plus posterolateral fusion.

Predicting individual fusional range from optometric data

NASA Astrophysics Data System (ADS)

Endrikhovski, Serguei; Jin, Elaine; Miller, Michael E.; Ford, Robert W.

2005-03-01

A model was developed to predict the range of disparities that can be fused by an individual user from optometric measurements. This model uses parameters, such as dissociated phoria and fusional reserves, to calculate an individual user"s fusional range (i.e., the disparities that can be fused on stereoscopic displays) when the user views a stereoscopic stimulus from various distances. This model is validated by comparing its output with data from a study in which the individual fusional range of a group of users was quantified while they viewed a stereoscopic display from distances of 0.5, 1.0, and 2.0 meters. Overall, the model provides good data predictions for the majority of the subjects and can be generalized for other viewing conditions. The model may, therefore, be used within a customized stereoscopic system, which would render stereoscopic information in a way that accounts for the individual differences in fusional range. Because the comfort of an individual user also depends on the user"s ability to fuse stereo images, such a system may, consequently, improve the comfort level and viewing experience for people with different stereoscopic fusional capabilities.

Tensor functors between Morita duals of fusion categories

NASA Astrophysics Data System (ADS)

Galindo, César; Plavnik, Julia Yael

2017-03-01

Given a fusion category C and an indecomposable C -module category M , the fusion category C^*_{_{M}} of C-module endofunctors of M is called the (Morita) dual fusion category of C with respect to M . We describe tensor functors between two arbitrary duals C^*_{_{M}} and D^*_N in terms of data associated to C and D . We apply the results to G-equivariantizations of fusion categories and group-theoretical fusion categories. We describe the orbits of the action of the Brauer-Picard group on the set of module categories and we propose a categorification of the Rosenberg-Zelinsky sequence for fusion categories.

FusionHub: A unified web platform for annotation and visualization of gene fusion events in human cancer.

PubMed

Panigrahi, Priyabrata; Jere, Abhay; Anamika, Krishanpal

2018-01-01

Gene fusion is a chromosomal rearrangement event which plays a significant role in cancer due to the oncogenic potential of the chimeric protein generated through fusions. At present many databases are available in public domain which provides detailed information about known gene fusion events and their functional role. Existing gene fusion detection tools, based on analysis of transcriptomics data usually report a large number of fusion genes as potential candidates, which could be either known or novel or false positives. Manual annotation of these putative genes is indeed time-consuming. We have developed a web platform FusionHub, which acts as integrated search engine interfacing various fusion gene databases and simplifies large scale annotation of fusion genes in a seamless way. In addition, FusionHub provides three ways of visualizing fusion events: circular view, domain architecture view and network view. Design of potential siRNA molecules through ensemble method is another utility integrated in FusionHub that could aid in siRNA-based targeted therapy. FusionHub is freely available at https://fusionhub.persistent.co.in.

Raman/LIBS Data Fusion via Two-Way Variational Autoencoders

NASA Astrophysics Data System (ADS)

Parente, M.; Gemp, I.

2018-04-01

We propose an original solution to extracting mineral abundances from Raman spectra by combining Raman data with LIBS using a novel deep learning model based on variational autoencoders and data fusion, which outperforms the current state of the art.

Prediction of adverse outcomes of acute coronary syndrome using intelligent fusion of triage information with HUMINT

NASA Astrophysics Data System (ADS)

McCullough, Claire L.; Novobilski, Andrew J.; Fesmire, Francis M.

2006-04-01

Faculty from the University of Tennessee at Chattanooga and the University of Tennessee College of Medicine, Chattanooga Unit, have used data mining techniques and neural networks to examine a set of fourteen features, data items, and HUMINT assessments for 2,148 emergency room patients with symptoms possibly indicative of Acute Coronary Syndrome. Specifically, the authors have generated Bayesian networks describing linkages and causality in the data, and have compared them with neural networks. The data includes objective information routinely collected during triage and the physician's initial case assessment, a HUMINT appraisal. Both the neural network and the Bayesian network were used to fuse the disparate types of information with the goal of forecasting thirty-day adverse patient outcome. This paper presents details of the methods of data fusion including both the data mining techniques and the neural network. Results are compared using Receiver Operating Characteristic curves describing the outcomes of both methods, both using only objective features and including the subjective physician's assessment. While preliminary, the results of this continuing study are significant both from the perspective of potential use of the intelligent fusion of biomedical informatics to aid the physician in prescribing treatment necessary to prevent serious adverse outcome from ACS and as a model of fusion of objective data with subjective HUMINT assessment. Possible future work includes extension of successfully demonstrated intelligent fusion methods to other medical applications, and use of decision level fusion to combine results from data mining and neural net approaches for even more accurate outcome prediction.

The actin cytoskeleton inhibits pore expansion during PIV5 fusion protein-promoted cell-cell fusion

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

Wurth, Mark A.; Schowalter, Rachel M.; Smith, Everett Clinton

2010-08-15

Paramyxovirus fusion (F) proteins promote both virus-cell fusion, required for viral entry, and cell-cell fusion, resulting in syncytia formation. We used the F-actin stabilizing drug, jasplakinolide, and the G-actin sequestrant, latrunculin A, to examine the role of actin dynamics in cell-cell fusion mediated by the parainfluenza virus 5 (PIV5) F protein. Jasplakinolide treatment caused a dose-dependent increase in cell-cell fusion as measured by both syncytia and reporter gene assays, and latrunculin A treatment also resulted in fusion stimulation. Treatment with jasplakinolide or latrunculin A partially rescued a fusion pore opening defect caused by deletion of the PIV5 F protein cytoplasmicmore » tail, but these drugs had no effect on fusion inhibited at earlier stages by either temperature arrest or by a PIV5 heptad repeat peptide. These data suggest that the cortical actin cytoskeleton is an important regulator of fusion pore enlargement, an energetically costly stage of viral fusion protein-mediated membrane merger.« less

Driver Fusions and Their Implications in the Development and Treatment of Human Cancers.

PubMed

Gao, Qingsong; Liang, Wen-Wei; Foltz, Steven M; Mutharasu, Gnanavel; Jayasinghe, Reyka G; Cao, Song; Liao, Wen-Wei; Reynolds, Sheila M; Wyczalkowski, Matthew A; Yao, Lijun; Yu, Lihua; Sun, Sam Q; Chen, Ken; Lazar, Alexander J; Fields, Ryan C; Wendl, Michael C; Van Tine, Brian A; Vij, Ravi; Chen, Feng; Nykter, Matti; Shmulevich, Ilya; Ding, Li

2018-04-03

Gene fusions represent an important class of somatic alterations in cancer. We systematically investigated fusions in 9,624 tumors across 33 cancer types using multiple fusion calling tools. We identified a total of 25,664 fusions, with a 63% validation rate. Integration of gene expression, copy number, and fusion annotation data revealed that fusions involving oncogenes tend to exhibit increased expression, whereas fusions involving tumor suppressors have the opposite effect. For fusions involving kinases, we found 1,275 with an intact kinase domain, the proportion of which varied significantly across cancer types. Our study suggests that fusions drive the development of 16.5% of cancer cases and function as the sole driver in more than 1% of them. Finally, we identified druggable fusions involving genes such as TMPRSS2, RET, FGFR3, ALK, and ESR1 in 6.0% of cases, and we predicted immunogenic peptides, suggesting that fusions may provide leads for targeted drug and immune therapy. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

The actin cytoskeleton inhibits pore expansion during PIV5 fusion protein-promoted cell-cell fusion

PubMed Central

Wurth, Mark A.; Schowalter, Rachel M.; Smith, Everett Clinton; Moncman, Carole L.; Dutch, Rebecca Ellis; McCann, Richard O.

2010-01-01

Paramyxovirus fusion (F) proteins promote both virus-cell fusion, required for viral entry, and cell-cell fusion, resulting in syncytia formation. We used the F-actin stabilizing drug, jasplakinolide, and the G-actin sequestrant, latrunculin A, to examine the role of actin dynamics in cell-cell fusion mediated by the parainfluenza virus 5 (PIV5) F protein. Jasplakinolide treatment caused a dose-dependent increase in cell-cell fusion as measured by both syncytia and reporter gene assays, and latrunculin A treatment also resulted in fusion stimulation. Treatment with jasplakinolide or latrunculin A partially rescued a fusion pore opening defect caused by deletion of the PIV5 F protein cytoplasmic tail, but these drugs had no effect on fusion inhibited at earlier stages by either temperature arrest or by a PIV5 heptad repeat peptide. These data suggest that the cortical actin cytoskeleton is an important regulator of fusion pore enlargement, an energetically costly stage of viral fusion protein-mediated membrane merger. PMID:20537366

Multimodal fusion of brain imaging data: A key to finding the missing link(s) in complex mental illness

PubMed Central

Calhoun, Vince D; Sui, Jing

2016-01-01

It is becoming increasingly clear that combining multi-modal brain imaging data is able to provide more information for individual subjects by exploiting the rich multimodal information that exists. However, the number of studies that do true multimodal fusion (i.e. capitalizing on joint information among modalities) is still remarkably small given the known benefits. In part, this is because multi-modal studies require broader expertise in collecting, analyzing, and interpreting the results than do unimodal studies. In this paper, we start by introducing the basic reasons why multimodal data fusion is important and what it can do, and importantly how it can help us avoid wrong conclusions and help compensate for imperfect brain imaging studies. We also discuss the challenges that need to be confronted for such approaches to be more widely applied by the community. We then provide a review of the diverse studies that have used multimodal data fusion (primarily focused on psychosis) as well as provide an introduction to some of the existing analytic approaches. Finally, we discuss some up-and-coming approaches to multi-modal fusion including deep learning and multimodal classification which show considerable promise. Our conclusion is that multimodal data fusion is rapidly growing, but it is still underutilized. The complexity of the human brain coupled with the incomplete measurement provided by existing imaging technology makes multimodal fusion essential in order to mitigate against misdirection and hopefully provide a key to finding the missing link(s) in complex mental illness. PMID:27347565

Multimodal fusion of brain imaging data: A key to finding the missing link(s) in complex mental illness.

PubMed

Calhoun, Vince D; Sui, Jing

2016-05-01

It is becoming increasingly clear that combining multi-modal brain imaging data is able to provide more information for individual subjects by exploiting the rich multimodal information that exists. However, the number of studies that do true multimodal fusion (i.e. capitalizing on joint information among modalities) is still remarkably small given the known benefits. In part, this is because multi-modal studies require broader expertise in collecting, analyzing, and interpreting the results than do unimodal studies. In this paper, we start by introducing the basic reasons why multimodal data fusion is important and what it can do, and importantly how it can help us avoid wrong conclusions and help compensate for imperfect brain imaging studies. We also discuss the challenges that need to be confronted for such approaches to be more widely applied by the community. We then provide a review of the diverse studies that have used multimodal data fusion (primarily focused on psychosis) as well as provide an introduction to some of the existing analytic approaches. Finally, we discuss some up-and-coming approaches to multi-modal fusion including deep learning and multimodal classification which show considerable promise. Our conclusion is that multimodal data fusion is rapidly growing, but it is still underutilized. The complexity of the human brain coupled with the incomplete measurement provided by existing imaging technology makes multimodal fusion essential in order to mitigate against misdirection and hopefully provide a key to finding the missing link(s) in complex mental illness.

Inferences on the evolutionary history of the Drosophila americana polymorphic X/4 fusion from patterns of polymorphism at the X-linked paralytic and elav genes.

PubMed Central

Vieira, Cristina P; Coelho, Paula A; Vieira, Jorge

2003-01-01

In Drosophila there is limited evidence on the nature of evolutionary forces affecting chromosomal arrangements other than inversions. The study of the X/4 fusion polymorphism of Drosophila americana is thus of interest. Polymorphism patterns at the paralytic (para) gene, located at the base of the X chromosome, suggest that there is suppressed crossing over in this region between fusion and nonfusion chromosomes but not within fusion and nonfusion chromosomes. These data are thus compatible with previous claims that within fusion chromosomes the amino acid clines found at fused1 (also located at the base of the X chromosome) are likely maintained by local selection. The para data set also suggests a young age of the X/4 fusion. Polymorphism data on para and elav (located at the middle region of the X chromosome) suggest that there is no population structure other than that caused by the X/4 fusion itself. These findings are therefore compatible with previous claims that selection maintains the strong association observed between the methionine/threonine variants at fused1 and the status of the X chromosome as fused or unfused to the fourth chromosome. PMID:12930752

Remote Sensing Data Visualization, Fusion and Analysis via Giovanni

NASA Technical Reports Server (NTRS)

Leptoukh, G.; Zubko, V.; Gopalan, A.; Khayat, M.

2007-01-01

We describe Giovanni, the NASA Goddard developed online visualization and analysis tool that allows users explore various phenomena without learning remote sensing data formats and downloading voluminous data. Using MODIS aerosol data as an example, we formulate an approach to the data fusion for Giovanni to further enrich online multi-sensor remote sensing data comparison and analysis.

Detection of buried objects by fusing dual-band infrared images

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

Clark, G.A.; Sengupta, S.K.; Sherwood, R.J.

1993-11-01

We have conducted experiments to demonstrate the enhanced detectability of buried land mines using sensor fusion techniques. Multiple sensors, including visible imagery, infrared imagery, and ground penetrating radar (GPR), have been used to acquire data on a number of buried mines and mine surrogates. Because the visible wavelength and GPR data are currently incomplete. This paper focuses on the fusion of two-band infrared images. We use feature-level fusion and supervised learning with the probabilistic neural network (PNN) to evaluate detection performance. The novelty of the work lies in the application of advanced target recognition algorithms, the fusion of dual-band infraredmore » images and evaluation of the techniques using two real data sets.« less

Statistically significant performance results of a mine detector and fusion algorithm from an x-band high-resolution SAR

NASA Astrophysics Data System (ADS)

Williams, Arnold C.; Pachowicz, Peter W.

2004-09-01

Current mine detection research indicates that no single sensor or single look from a sensor will detect mines/minefields in a real-time manner at a performance level suitable for a forward maneuver unit. Hence, the integrated development of detectors and fusion algorithms are of primary importance. A problem in this development process has been the evaluation of these algorithms with relatively small data sets, leading to anecdotal and frequently over trained results. These anecdotal results are often unreliable and conflicting among various sensors and algorithms. Consequently, the physical phenomena that ought to be exploited and the performance benefits of this exploitation are often ambiguous. The Army RDECOM CERDEC Night Vision Laboratory and Electron Sensors Directorate has collected large amounts of multisensor data such that statistically significant evaluations of detection and fusion algorithms can be obtained. Even with these large data sets care must be taken in algorithm design and data processing to achieve statistically significant performance results for combined detectors and fusion algorithms. This paper discusses statistically significant detection and combined multilook fusion results for the Ellipse Detector (ED) and the Piecewise Level Fusion Algorithm (PLFA). These statistically significant performance results are characterized by ROC curves that have been obtained through processing this multilook data for the high resolution SAR data of the Veridian X-Band radar. We discuss the implications of these results on mine detection and the importance of statistical significance, sample size, ground truth, and algorithm design in performance evaluation.

Regular Deployment of Wireless Sensors to Achieve Connectivity and Information Coverage

PubMed Central

Cheng, Wei; Li, Yong; Jiang, Yi; Yin, Xipeng

2016-01-01

Coverage and connectivity are two of the most critical research subjects in WSNs, while regular deterministic deployment is an important deployment strategy and results in some pattern-based lattice WSNs. Some studies of optimal regular deployment for generic values of rc/rs were shown recently. However, most of these deployments are subject to a disk sensing model, and cannot take advantage of data fusion. Meanwhile some other studies adapt detection techniques and data fusion to sensing coverage to enhance the deployment scheme. In this paper, we provide some results on optimal regular deployment patterns to achieve information coverage and connectivity as a variety of rc/rs, which are all based on data fusion by sensor collaboration, and propose a novel data fusion strategy for deployment patterns. At first the relation between variety of rc/rs and density of sensors needed to achieve information coverage and connectivity is derived in closed form for regular pattern-based lattice WSNs. Then a dual triangular pattern deployment based on our novel data fusion strategy is proposed, which can utilize collaborative data fusion more efficiently. The strip-based deployment is also extended to a new pattern to achieve information coverage and connectivity, and its characteristics are deduced in closed form. Some discussions and simulations are given to show the efficiency of all deployment patterns, including previous patterns and the proposed patterns, to help developers make more impactful WSN deployment decisions. PMID:27529246

Data Strategies to Support Automated Multi-Sensor Data Fusion in a Service Oriented Architecture

DTIC Science & Technology

2008-06-01

and employ vast quantities of content. This dissertation provides two software architectural patterns and an auto-fusion process that guide the...UDDI), Simple Order Access Protocol (SOAP), Java, Maritime Domain Awareness (MDA), Business Process Execution Language for Web Service (BPEL4WS) 16...content. This dissertation provides two software architectural patterns and an auto-fusion process that guide the development of a distributed

Integrated Multi-Aperture Sensor and Navigation Fusion

DTIC Science & Technology

2010-02-01

Visio, Springer-Verlag Inc., New York, 2004. [3] R. G. Brown and P. Y. C. Hwang , Introduction to Random Signals and Applied Kalman Filtering, Third...formulate Kalman filter vision/inertial measurement observables for other images without the need to know (or measure) their feature ranges. As compared...Internal Data Fusion Multi-aperture/INS data fusion is formulated in the feature domain using the complementary Kalman filter methodology [3]. In this

Strong expression of the neuronal transcription factor FOXP2 is linked to an increased risk of early PSA recurrence in ERG fusion-negative cancers.

PubMed

Stumm, Laura; Burkhardt, Lia; Steurer, Stefan; Simon, Ronald; Adam, Meike; Becker, Andreas; Sauter, Guido; Minner, Sarah; Schlomm, Thorsten; Sirma, Hüseyin; Michl, Uwe

2013-07-01

Transcription factors of the forkhead box P (FOXP1-4) family have been implicated in various human cancer types before. The relevance and role of neuronal transcription factor FOXP2 in prostate cancer is unknown. A tissue microarray containing samples from more than 11 000 prostate cancers from radical prostatectomy specimens with clinical follow-up data was analysed for FOXP2 expression by immunohistochemistry. FOXP2 data were also compared with pre-existing ERG fusion (by fluorescence in situ hybridisation and immunohistochemistry) and cell proliferation (Ki67 labelling index) data. There was a moderate to strong FOXP2 protein expression in basal and secretory cells of normal prostatic glands. As compared with normal cells, FOXP2 expression was lost or reduced in 25% of cancers. Strong FOXP2 expression was linked to advanced tumour stage, high Gleason score, presence of lymph node metastases and early tumour recurrence (p<0.0001; each) in ERG fusion-negative, but not in ERG fusion-positive cancers. High FOXP2 expression was linked to high Ki67 labelling index (p<0.0001) in all cancers irrespective of ERG fusion status. These data demonstrate that similar high FOXP2 protein levels as in normal prostate epithelium exert a 'paradoxical' oncogenic role in 'non fusion-type' prostate cancer. It may be speculated that interaction of FOXP2 with members of pathways that are specifically activated in 'non fusion-type' cancers may be responsible for this phenomenon.

The role of data fusion in predictive maintenance using digital twin

NASA Astrophysics Data System (ADS)

Liu, Zheng; Meyendorf, Norbert; Mrad, Nezih

2018-04-01

Modern aerospace industry is migrating from reactive to proactive and predictive maintenance to increase platform operational availability and efficiency, extend its useful life cycle and reduce its life cycle cost. Multiphysics modeling together with data-driven analytics generate a new paradigm called "Digital Twin." The digital twin is actually a living model of the physical asset or system, which continually adapts to operational changes based on the collected online data and information, and can forecast the future of the corresponding physical counterpart. This paper reviews the overall framework to develop a digital twin coupled with the industrial Internet of Things technology to advance aerospace platforms autonomy. Data fusion techniques particularly play a significant role in the digital twin framework. The flow of information from raw data to high-level decision making is propelled by sensor-to-sensor, sensor-to-model, and model-to-model fusion. This paper further discusses and identifies the role of data fusion in the digital twin framework for aircraft predictive maintenance.

Data Summarization in the Node by Parameters (DSNP): Local Data Fusion in an IoT Environment.

PubMed

Maschi, Luis F C; Pinto, Alex S R; Meneguette, Rodolfo I; Baldassin, Alexandro

2018-03-07

With the advent of the Internet of Things, billions of objects or devices are inserted into the global computer network, generating and processing data at a volume never imagined before. This paper proposes a way to collect and process local data through a data fusion technology called summarization. The main feature of the proposal is the local data fusion, through parameters provided by the application, ensuring the quality of data collected by the sensor node. In the evaluation, the sensor node was compared when performing the data summary with another that performed a continuous recording of the collected data. Two sets of nodes were created, one with a sensor node that analyzed the luminosity of the room, which in this case obtained a reduction of 97% in the volume of data generated, and another set that analyzed the temperature of the room, obtaining a reduction of 80% in the data volume. Through these tests, it has been proven that the local data fusion at the node can be used to reduce the volume of data generated, consequently decreasing the volume of messages generated by IoT environments.

ITS Data Fusion, Final Report

DOT National Transportation Integrated Search

1996-09-01

THIS PROJECT HAS ACCOMPLISHED THREE SIGNIFICANT TASKS. FIRST, A STATE-OF-THE-ART LITERATURE REVIEW HAS PROVIDED AN ORGANIZATIONAL FRAMEWORK FOR CATEGORIZING THE VARIOUS DATA FUSION PROJECTS THAT HAVE BEEN CONDUCTED TO DATE. A POPULAR TYPOLOGY WAS DIS...

Data fusion for delivering advanced traveler information services

DOT National Transportation Integrated Search

2003-05-01

Many transportation professionals have suggested that improved ATIS data fusion techniques and processing will improve the overall quality, timeliness, and usefulness of traveler information. The purpose of this study was four fold. First, conduct a ...

Leaf area index uncertainty estimates for model-data fusion applications

Treesearch

Andrew D. Richardson; D. Bryan Dail; D.Y. Hollinger

2011-01-01

Estimates of data uncertainties are required to integrate different observational data streams as model constraints using model-data fusion. We describe an approach with which random and systematic uncertainties in optical measurements of leaf area index [LAI] can be quantified. We use data from a measurement campaign at the spruce-dominated Howland Forest AmeriFlux...

The Use of Analytic Decision Game (ADG) Methods for Test and Evaluation of Hard and Soft Data Fusion Systems and Education of a New Generation of Data Fusion Analysts

DTIC Science & Technology

2012-10-01

education of a new generation of data fusion analysts Jacob L. Graham College of Information Sciences & Technology Pennsylvania State University...University Park, PA, U.S.A. jgraham@ist.psu.edu David L. Hall College of Information Sciences & Technology Pennsylvania State University...ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) College

Spatial resolution enhancement of satellite image data using fusion approach

NASA Astrophysics Data System (ADS)

Lestiana, H.; Sukristiyanti

2018-02-01

Object identification using remote sensing data has a problem when the spatial resolution is not in accordance with the object. The fusion approach is one of methods to solve the problem, to improve the object recognition and to increase the objects information by combining data from multiple sensors. The application of fusion image can be used to estimate the environmental component that is needed to monitor in multiple views, such as evapotranspiration estimation, 3D ground-based characterisation, smart city application, urban environments, terrestrial mapping, and water vegetation. Based on fusion application method, the visible object in land area has been easily recognized using the method. The variety of object information in land area has increased the variation of environmental component estimation. The difficulties in recognizing the invisible object like Submarine Groundwater Discharge (SGD), especially in tropical area, might be decreased by the fusion method. The less variation of the object in the sea surface temperature is a challenge to be solved.

The fusion of satellite and UAV data: simulation of high spatial resolution band

NASA Astrophysics Data System (ADS)

Jenerowicz, Agnieszka; Siok, Katarzyna; Woroszkiewicz, Malgorzata; Orych, Agata

2017-10-01

Remote sensing techniques used in the precision agriculture and farming that apply imagery data obtained with sensors mounted on UAV platforms became more popular in the last few years due to the availability of low- cost UAV platforms and low- cost sensors. Data obtained from low altitudes with low- cost sensors can be characterised by high spatial and radiometric resolution but quite low spectral resolution, therefore the application of imagery data obtained with such technology is quite limited and can be used only for the basic land cover classification. To enrich the spectral resolution of imagery data acquired with low- cost sensors from low altitudes, the authors proposed the fusion of RGB data obtained with UAV platform with multispectral satellite imagery. The fusion is based on the pansharpening process, that aims to integrate the spatial details of the high-resolution panchromatic image with the spectral information of lower resolution multispectral or hyperspectral imagery to obtain multispectral or hyperspectral images with high spatial resolution. The key of pansharpening is to properly estimate the missing spatial details of multispectral images while preserving their spectral properties. In the research, the authors presented the fusion of RGB images (with high spatial resolution) obtained with sensors mounted on low- cost UAV platforms and multispectral satellite imagery with satellite sensors, i.e. Landsat 8 OLI. To perform the fusion of UAV data with satellite imagery, the simulation of the panchromatic bands from RGB data based on the spectral channels linear combination, was conducted. Next, for simulated bands and multispectral satellite images, the Gram-Schmidt pansharpening method was applied. As a result of the fusion, the authors obtained several multispectral images with very high spatial resolution and then analysed the spatial and spectral accuracies of processed images.

Assessing the Performance of Sensor Fusion Methods: Application to Magnetic-Inertial-Based Human Body Tracking

PubMed Central

Ligorio, Gabriele; Bergamini, Elena; Pasciuto, Ilaria; Vannozzi, Giuseppe; Cappozzo, Aurelio; Sabatini, Angelo Maria

2016-01-01

Information from complementary and redundant sensors are often combined within sensor fusion algorithms to obtain a single accurate observation of the system at hand. However, measurements from each sensor are characterized by uncertainties. When multiple data are fused, it is often unclear how all these uncertainties interact and influence the overall performance of the sensor fusion algorithm. To address this issue, a benchmarking procedure is presented, where simulated and real data are combined in different scenarios in order to quantify how each sensor’s uncertainties influence the accuracy of the final result. The proposed procedure was applied to the estimation of the pelvis orientation using a waist-worn magnetic-inertial measurement unit. Ground-truth data were obtained from a stereophotogrammetric system and used to obtain simulated data. Two Kalman-based sensor fusion algorithms were submitted to the proposed benchmarking procedure. For the considered application, gyroscope uncertainties proved to be the main error source in orientation estimation accuracy for both tested algorithms. Moreover, although different performances were obtained using simulated data, these differences became negligible when real data were considered. The outcome of this evaluation may be useful both to improve the design of new sensor fusion methods and to drive the algorithm tuning process. PMID:26821027

Assessing the Performance of Sensor Fusion Methods: Application to Magnetic-Inertial-Based Human Body Tracking.

PubMed

Ligorio, Gabriele; Bergamini, Elena; Pasciuto, Ilaria; Vannozzi, Giuseppe; Cappozzo, Aurelio; Sabatini, Angelo Maria

2016-01-26

Information from complementary and redundant sensors are often combined within sensor fusion algorithms to obtain a single accurate observation of the system at hand. However, measurements from each sensor are characterized by uncertainties. When multiple data are fused, it is often unclear how all these uncertainties interact and influence the overall performance of the sensor fusion algorithm. To address this issue, a benchmarking procedure is presented, where simulated and real data are combined in different scenarios in order to quantify how each sensor's uncertainties influence the accuracy of the final result. The proposed procedure was applied to the estimation of the pelvis orientation using a waist-worn magnetic-inertial measurement unit. Ground-truth data were obtained from a stereophotogrammetric system and used to obtain simulated data. Two Kalman-based sensor fusion algorithms were submitted to the proposed benchmarking procedure. For the considered application, gyroscope uncertainties proved to be the main error source in orientation estimation accuracy for both tested algorithms. Moreover, although different performances were obtained using simulated data, these differences became negligible when real data were considered. The outcome of this evaluation may be useful both to improve the design of new sensor fusion methods and to drive the algorithm tuning process.

Heterogeneous Vision Data Fusion for Independently Moving Cameras

DTIC Science & Technology

2010-03-01

target detection , tracking , and identification over a large terrain. The goal of the project is to investigate and evaluate the existing image...fusion algorithms, develop new real-time algorithms for Category-II image fusion, and apply these algorithms in moving target detection and tracking . The...moving target detection and classification. 15. SUBJECT TERMS Image Fusion, Target Detection , Moving Cameras, IR Camera, EO Camera 16. SECURITY

Implication of Culture: User Roles in Information Fusion for Enhanced Situational Understanding

DTIC Science & Technology

2009-07-01

situational understanding through assessment of the environment to determine a coherent state of affairs. The information is integrated with knowledge to...Implication of Culture: User Roles in Information Fusion for Enhanced Situational Understanding Erik Blasch Air Force Research Lab 2241...enhanced tacit knowledge understanding by (1) display fusion for data presentation (e.g. cultural segmentation), (2) interactive fusion to allow the

A pharmacological study of Arabidopsis cell fusion between the persistent synergid and endosperm.

PubMed

Motomura, Kazuki; Kawashima, Tomokazu; Berger, Frédéric; Kinoshita, Tetsu; Higashiyama, Tetsuya; Maruyama, Daisuke

2018-01-29

Cell fusion is a pivotal process in fertilization and multinucleate cell formation. A plant cell is ubiquitously surrounded by a hard cell wall, and very few cell fusions have been observed except for gamete fusions. We recently reported that the fertilized central cell (the endosperm) absorbs the persistent synergid, a highly differentiated cell necessary for pollen tube attraction. The synergid-endosperm fusion (SE fusion) appears to eliminate the persistent synergid from fertilized ovule in Arabidopsis thaliana Here, we analyzed the effects of various inhibitors on SE fusion in an in vitro culture system. Different from other cell fusions, neither disruption of actin polymerization nor protein secretion impaired SE fusion. However, transcriptional and translational inhibitors decreased the SE fusion success rate and also inhibited endosperm division. Failures of SE fusion and endosperm nuclear proliferation were also induced by roscovitine, an inhibitor of cyclin-dependent kinases (CDK). These data indicate unique aspects of SE fusion such as independence of filamentous actin support and the importance of CDK-mediated mitotic control. © 2018. Published by The Company of Biologists Ltd.

Deep data fusion method for missile-borne inertial/celestial system

NASA Astrophysics Data System (ADS)

Zhang, Chunxi; Chen, Xiaofei; Lu, Jiazhen; Zhang, Hao

2018-05-01

Strap-down inertial-celestial integrated navigation system has the advantages of autonomy and high precision and is very useful for ballistic missiles. The star sensor installation error and inertial measurement error have a great influence for the system performance. Based on deep data fusion, this paper establishes measurement equations including star sensor installation error and proposes the deep fusion filter method. Simulations including misalignment error, star sensor installation error, IMU error are analyzed. Simulation results indicate that the deep fusion method can estimate the star sensor installation error and IMU error. Meanwhile, the method can restrain the misalignment errors caused by instrument errors.

[Three-dimensional data fusion method for tooth crown and root based on curvature continuity algorithm].

PubMed

Zhao, Y J; Liu, Y; Sun, Y C; Wang, Y

2017-08-18

To explore a three-dimensional (3D) data fusion and integration method of optical scanning tooth crowns and cone beam CT (CBCT) reconstructing tooth roots for their natural transition in the 3D profile. One mild dental crowding case was chosen from orthodontics clinics with full denture. The CBCT data were acquired to reconstruct the dental model with tooth roots by Mimics 17.0 medical imaging software, and the optical impression was taken to obtain the dentition model with high precision physiological contour of crowns by Smart Optics dental scanner. The two models were doing 3D registration based on their common part of the crowns' shape in Geomagic Studio 2012 reverse engineering software. The model coordinate system was established by defining the occlusal plane. crown-gingiva boundary was extracted from optical scanning model manually, then crown-root boundary was generated by offsetting and projecting crown-gingiva boundary to the root model. After trimming the crown and root models, the 3D fusion model with physiological contour crown and nature root was formed by curvature continuity filling algorithm finally. In the study, 10 patients with dentition mild crowded from the oral clinics were followed up with this method to obtain 3D crown and root fusion models, and 10 high qualification doctors were invited to do subjective evaluation of these fusion models. This study based on commercial software platform, preliminarily realized the 3D data fusion and integration method of optical scanning tooth crowns and CBCT tooth roots with a curvature continuous shape transition. The 10 patients' 3D crown and root fusion models were constructed successfully by the method, and the average score of the doctors' subjective evaluation for these 10 models was 8.6 points (0-10 points). which meant that all the fusion models could basically meet the need of the oral clinics, and also showed the method in our study was feasible and efficient in orthodontics study and clinics. The method of this study for 3D crown and root data fusion could obtain an integrate tooth or dental model more close to the nature shape. CBCT model calibration may probably improve the precision of the fusion model. The adaptation of this method for severe dentition crowding and micromaxillary deformity needs further research.

Massive NGS Data Analysis Reveals Hundreds Of Potential Novel Gene Fusions in Human Cell Lines.

PubMed

Gioiosa, Silvia; Bolis, Marco; Flati, Tiziano; Massini, Annalisa; Garattini, Enrico; Chillemi, Giovanni; Fratelli, Maddalena; Castrignanò, Tiziana

2018-06-01

Gene fusions derive from chromosomal rearrangements and the resulting chimeric transcripts are often endowed with oncogenic potential. Furthermore, they serve as diagnostic tools for the clinical classification of cancer subgroups with different prognosis and, in some cases, they can provide specific drug targets. So far, many efforts have been carried out to study gene fusion events occurring in tumor samples. In recent years, the availability of a comprehensive Next Generation Sequencing dataset for all the existing human tumor cell lines has provided the opportunity to further investigate these data in order to identify novel and still uncharacterized gene fusion events. In our work, we have extensively reanalyzed 935 paired-end RNA-seq experiments downloaded from "The Cancer Cell Line Encyclopedia" repository, aiming at addressing novel putative cell-line specific gene fusion events in human malignancies. The bioinformatics analysis has been performed by the execution of four different gene fusion detection algorithms. The results have been further prioritized by running a bayesian classifier which makes an in silico validation. The collection of fusion events supported by all of the predictive softwares results in a robust set of ∼ 1,700 in-silico predicted novel candidates suitable for downstream analyses. Given the huge amount of data and information produced, computational results have been systematized in a database named LiGeA. The database can be browsed through a dynamical and interactive web portal, further integrated with validated data from other well known repositories. Taking advantage of the intuitive query forms, the users can easily access, navigate, filter and select the putative gene fusions for further validations and studies. They can also find suitable experimental models for a given fusion of interest. We believe that the LiGeA resource can represent not only the first compendium of both known and putative novel gene fusion events in the catalog of all of the human malignant cell lines, but it can also become a handy starting point for wet-lab biologists who wish to investigate novel cancer biomarkers and specific drug targets.

MRI Volume Fusion Based on 3D Shearlet Decompositions.

PubMed

Duan, Chang; Wang, Shuai; Wang, Xue Gang; Huang, Qi Hong

2014-01-01

Nowadays many MRI scans can give 3D volume data with different contrasts, but the observers may want to view various contrasts in the same 3D volume. The conventional 2D medical fusion methods can only fuse the 3D volume data layer by layer, which may lead to the loss of interframe correlative information. In this paper, a novel 3D medical volume fusion method based on 3D band limited shearlet transform (3D BLST) is proposed. And this method is evaluated upon MRI T2* and quantitative susceptibility mapping data of 4 human brains. Both the perspective impression and the quality indices indicate that the proposed method has a better performance than conventional 2D wavelet, DT CWT, and 3D wavelet, DT CWT based fusion methods.

Benchmarking of data fusion algorithms in support of earth observation based Antarctic wildlife monitoring

NASA Astrophysics Data System (ADS)

Witharana, Chandi; LaRue, Michelle A.; Lynch, Heather J.

2016-03-01

Remote sensing is a rapidly developing tool for mapping the abundance and distribution of Antarctic wildlife. While both panchromatic and multispectral imagery have been used in this context, image fusion techniques have received little attention. We tasked seven widely-used fusion algorithms: Ehlers fusion, hyperspherical color space fusion, high-pass fusion, principal component analysis (PCA) fusion, University of New Brunswick fusion, and wavelet-PCA fusion to resolution enhance a series of single-date QuickBird-2 and Worldview-2 image scenes comprising penguin guano, seals, and vegetation. Fused images were assessed for spectral and spatial fidelity using a variety of quantitative quality indicators and visual inspection methods. Our visual evaluation elected the high-pass fusion algorithm and the University of New Brunswick fusion algorithm as best for manual wildlife detection while the quantitative assessment suggested the Gram-Schmidt fusion algorithm and the University of New Brunswick fusion algorithm as best for automated classification. The hyperspherical color space fusion algorithm exhibited mediocre results in terms of spectral and spatial fidelities. The PCA fusion algorithm showed spatial superiority at the expense of spectral inconsistencies. The Ehlers fusion algorithm and the wavelet-PCA algorithm showed the weakest performances. As remote sensing becomes a more routine method of surveying Antarctic wildlife, these benchmarks will provide guidance for image fusion and pave the way for more standardized products for specific types of wildlife surveys.

Effects of a Commercial Insurance Policy Restriction on Lumbar Fusion in North Carolina and the Implications for National Adoption

PubMed Central

Deyo, Richard A.; Lurie, Jon D.; Carey, Timothy S.; Tosteson, Anna N.A.; Mirza, Sohail K.

2015-01-01

Study design Analysis of the State Inpatient Database of North Carolina, 2005–2012, and the Nationwide Inpatient Sample, including all inpatient lumbar fusion admissions from non-federal hospitals. Objective To examine the influence of a major commercial policy change that restricted lumbar fusion for certain indications, and to forecast the potential impact if the policy were adopted nationally. Summary of Background Data Few studies have examined the effects of recent changes in commercial coverage policies that restrict the use of lumbar fusion. Methods We included adults undergoing elective lumbar fusion or re-fusion operations in North Carolina. We aggregated data into a monthly time series to report changes in the rates and volume of lumbar fusion operations for disc herniation or degeneration, spinal stenosis, spondylolisthesis, or revision fusions. Time series regression models were used to test for significant changes in the use of fusion operation following a major commercial coverage policy change initiated on January 1st, 2011. Results There was a substantial decline in the use of lumbar fusion for disc herniation or degeneration following the policy change on January 1st, 2011. Overall rates of elective lumbar fusion operations in North Carolina (per 100,000 residents) increased from 103.2 in 2005 to 120.4 in 2009, before declining to 101.9 by 2012. The population rate (per 100,000 residents) of fusion among those under age 65 increased from 89.5 in 2005 to 101.2 in 2009, followed by a sharp decline to 76.8 by 2012. There was no acceleration in the already increasing rate of fusion for spinal stenosis, spondylolisthesis or revision procedures, but there was a coincident increase in decompression without fusion. Conclusions This commercial insurance policy change had its intended effect of reducing fusion operations for indications with less evidence of effectiveness without changing rates for other indications or resulting in an overall reduction in spine surgery. Nevertheless, broader adoption of the policy could significantly reduce the national rates of fusion operations and associated costs. PMID:26679877

Runtime Simulation for Post-Disaster Data Fusion Visualization

DTIC Science & Technology

2006-10-01

Center for Multisource Information Fusion ( CMIF ) The State University of New York at Buffalo Buffalo, NY 14260 USA kesh@eng.buffalo.edu ABSTRACT...Fusion ( CMIF ) The State University of New York at Buffalo Buffalo, NY 14260 USA 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING/MONITORING

Investigation of complete and incomplete fusion in the 7Li+124Sn reaction near Coulomb barrier energies

NASA Astrophysics Data System (ADS)

Parkar, V. V.; Sharma, Sushil K.; Palit, R.; Upadhyaya, S.; Shrivastava, A.; Pandit, S. K.; Mahata, K.; Jha, V.; Santra, S.; Ramachandran, K.; Nag, T. N.; Rath, P. K.; Kanagalekar, Bhushan; Trivedi, T.

2018-01-01

The complete and incomplete fusion cross sections for the 7Li+124Sn reaction were measured using online and offline characteristic γ -ray detection techniques. The complete fusion (CF) cross sections at energies above the Coulomb barrier were found to be suppressed by ˜26 % compared to the coupled channel calculations. This suppression observed in complete fusion cross sections is found to be commensurate with the measured total incomplete fusion (ICF) cross sections. There is a distinct feature observed in the ICF cross sections, i.e., t capture is found to be dominant compared to α capture at all the measured energies. A simultaneous explanation of complete, incomplete, and total fusion (TF) data was also obtained from the calculations based on the continuum discretized coupled channel method with short range imaginary potentials. The cross section ratios of CF/TF and ICF/TF obtained from the data as well as the calculations showed the dominance of ICF at below-barrier energies and CF at above-barrier energies.

Evaluation of a data fusion approach to estimate daily PM2.5 levels in North China

PubMed Central

Liang, Fengchao; Gao, Meng; Xiao, Qingyang; Carmichael, Gregory R.

2017-01-01

PM2.5 air pollution has been a growing concern worldwide. Previous studies have conducted several techniques to estimate PM2.5 exposure spatiotemporally in China, but all these have limitations. This study was to develop a data fusion approach and compare it with kriging and Chemistry Module. Two techniques were applied to create daily spatial cover of PM2.5 in grid cells with a resolution of 10 km in North China in 2013, respectively, which was kriging with an external drift (KED) and Weather Research and Forecast Model with Chemistry Module (WRF-Chem). A data fusion technique was developed by fusing PM2.5 concentration predicted by KED and WRF-Chem, accounting for the distance from the central of grid cell to the nearest ground observations and daily spatial correlations between WRF-Chem and observations. Model performances were evaluated by comparing them with ground observations and the spatial prediction errors. KED and data fusion performed better at monitoring sites with a daily model R2 of 0.95 and 0.94, respectively and PM2.5 was overestimated by WRF-Chem (R2=0.51). KED and data fusion performed better around the ground monitors, WRF-Chem performed relative worse with high prediction errors in the central of study domain. In our study, both KED and data fusion technique provided highly accurate PM2.5. Current monitoring network in North China was dense enough to provide a reliable PM2.5 prediction by interpolation technique. PMID:28599195

Evaluation of a data fusion approach to estimate daily PM2.5 levels in North China.

PubMed

Liang, Fengchao; Gao, Meng; Xiao, Qingyang; Carmichael, Gregory R; Pan, Xiaochuan; Liu, Yang

2017-10-01

PM 2.5 air pollution has been a growing concern worldwide. Previous studies have conducted several techniques to estimate PM 2.5 exposure spatiotemporally in China, but all these have limitations. This study was to develop a data fusion approach and compare it with kriging and Chemistry Module. Two techniques were applied to create daily spatial cover of PM 2.5 in grid cells with a resolution of 10km in North China in 2013, respectively, which was kriging with an external drift (KED) and Weather Research and Forecast Model with Chemistry Module (WRF-Chem). A data fusion technique was developed by fusing PM 2.5 concentration predicted by KED and WRF-Chem, accounting for the distance from the central of grid cell to the nearest ground observations and daily spatial correlations between WRF-Chem and observations. Model performances were evaluated by comparing them with ground observations and the spatial prediction errors. KED and data fusion performed better at monitoring sites with a daily model R 2 of 0.95 and 0.94, respectively and PM 2.5 was overestimated by WRF-Chem (R 2 =0.51). KED and data fusion performed better around the ground monitors, WRF-Chem performed relative worse with high prediction errors in the central of study domain. In our study, both KED and data fusion technique provided highly accurate PM 2.5 . Current monitoring network in North China was dense enough to provide a reliable PM 2.5 prediction by interpolation technique. Copyright © 2017. Published by Elsevier Inc.

Distributed multimodal data fusion for large scale wireless sensor networks

NASA Astrophysics Data System (ADS)

Ertin, Emre

2006-05-01

Sensor network technology has enabled new surveillance systems where sensor nodes equipped with processing and communication capabilities can collaboratively detect, classify and track targets of interest over a large surveillance area. In this paper we study distributed fusion of multimodal sensor data for extracting target information from a large scale sensor network. Optimal tracking, classification, and reporting of threat events require joint consideration of multiple sensor modalities. Multiple sensor modalities improve tracking by reducing the uncertainty in the track estimates as well as resolving track-sensor data association problems. Our approach to solving the fusion problem with large number of multimodal sensors is construction of likelihood maps. The likelihood maps provide a summary data for the solution of the detection, tracking and classification problem. The likelihood map presents the sensory information in an easy format for the decision makers to interpret and is suitable with fusion of spatial prior information such as maps, imaging data from stand-off imaging sensors. We follow a statistical approach to combine sensor data at different levels of uncertainty and resolution. The likelihood map transforms each sensor data stream to a spatio-temporal likelihood map ideally suitable for fusion with imaging sensor outputs and prior geographic information about the scene. We also discuss distributed computation of the likelihood map using a gossip based algorithm and present simulation results.

Instrumental intelligent test of food sensory quality as mimic of human panel test combining multiple cross-perception sensors and data fusion.

PubMed

Ouyang, Qin; Zhao, Jiewen; Chen, Quansheng

2014-09-02

Instrumental test of food quality using perception sensors instead of human panel test is attracting massive attention recently. A novel cross-perception multi-sensors data fusion imitating multiple mammal perception was proposed for the instrumental test in this work. First, three mimic sensors of electronic eye, electronic nose and electronic tongue were used in sequence for data acquisition of rice wine samples. Then all data from the three different sensors were preprocessed and merged. Next, three cross-perception variables i.e., color, aroma and taste, were constructed using principal components analysis (PCA) and multiple linear regression (MLR) which were used as the input of models. MLR, back-propagation artificial neural network (BPANN) and support vector machine (SVM) were comparatively used for modeling, and the instrumental test was achieved for the comprehensive quality of samples. Results showed the proposed cross-perception multi-sensors data fusion presented obvious superiority to the traditional data fusion methodologies, also achieved a high correlation coefficient (>90%) with the human panel test results. This work demonstrated that the instrumental test based on the cross-perception multi-sensors data fusion can actually mimic the human test behavior, therefore is of great significance to ensure the quality of products and decrease the loss of the manufacturers. Copyright © 2014 Elsevier B.V. All rights reserved.

Three-dimensional fusion of spaceborne and ground radar reflectivity data using a neural network-based approach

NASA Astrophysics Data System (ADS)

Kou, Leilei; Wang, Zhuihui; Xu, Fen

2018-03-01

The spaceborne precipitation radar onboard the Tropical Rainfall Measuring Mission satellite (TRMM PR) can provide good measurement of the vertical structure of reflectivity, while ground radar (GR) has a relatively high horizontal resolution and greater sensitivity. Fusion of TRMM PR and GR reflectivity data may maximize the advantages from both instruments. In this paper, TRMM PR and GR reflectivity data are fused using a neural network (NN)-based approach. The main steps included are: quality control of TRMM PR and GR reflectivity data; spatiotemporal matchup; GR calibration bias correction; conversion of TRMM PR data from Ku to S band; fusion of TRMM PR and GR reflectivity data with an NN method; interpolation of reflectivity data that are below PR's sensitivity; blind areas compensation with a distance weighting-based merging approach; combination of three types of data: data with the NN method, data below PR's sensitivity and data within compensated blind areas. During the NN fusion step, the TRMM PR data are taken as targets of the training NNs, and gridded GR data after horizontal downsampling at different heights are used as the input. The trained NNs are then used to obtain 3D high-resolution reflectivity from the original GR gridded data. After 3D fusion of the TRMM PR and GR reflectivity data, a more complete and finer-scale 3D radar reflectivity dataset incorporating characteristics from both the TRMM PR and GR observations can be obtained. The fused reflectivity data are evaluated based on a convective precipitation event through comparison with the high resolution TRMM PR and GR data with an interpolation algorithm.

Crystal Structure of the Pre-fusion Nipah Virus Fusion Glycoprotein Reveals a Novel Hexamer-of-Trimers Assembly.

PubMed

Xu, Kai; Chan, Yee-Peng; Bradel-Tretheway, Birgit; Akyol-Ataman, Zeynep; Zhu, Yongqun; Dutta, Somnath; Yan, Lianying; Feng, YanRu; Wang, Lin-Fa; Skiniotis, Georgios; Lee, Benhur; Zhou, Z Hong; Broder, Christopher C; Aguilar, Hector C; Nikolov, Dimitar B

2015-12-01

Nipah virus (NiV) is a paramyxovirus that infects host cells through the coordinated efforts of two envelope glycoproteins. The G glycoprotein attaches to cell receptors, triggering the fusion (F) glycoprotein to execute membrane fusion. Here we report the first crystal structure of the pre-fusion form of the NiV-F glycoprotein ectodomain. Interestingly this structure also revealed a hexamer-of-trimers encircling a central axis. Electron tomography of Nipah virus-like particles supported the hexameric pre-fusion model, and biochemical analyses supported the hexamer-of-trimers F assembly in solution. Importantly, structure-assisted site-directed mutagenesis of the interfaces between F trimers highlighted the functional relevance of the hexameric assembly. Shown here, in both cell-cell fusion and virus-cell fusion systems, our results suggested that this hexamer-of-trimers assembly was important during fusion pore formation. We propose that this assembly would stabilize the pre-fusion F conformation prior to cell attachment and facilitate the coordinated transition to a post-fusion conformation of all six F trimers upon triggering of a single trimer. Together, our data reveal a novel and functional pre-fusion architecture of a paramyxoviral fusion glycoprotein.

A fusion approach for coarse-to-fine target recognition

NASA Astrophysics Data System (ADS)

Folkesson, Martin; Grönwall, Christina; Jungert, Erland

2006-04-01

A fusion approach in a query based information system is presented. The system is designed for querying multimedia data bases, and here applied to target recognition using heterogeneous data sources. The recognition process is coarse-to-fine, with an initial attribute estimation step and a following matching step. Several sensor types and algorithms are involved in each of these two steps. An independence of the matching results, on the origin of the estimation results, is observed. It allows for distribution of data between algorithms in an intermediate fusion step, without risk of data incest. This increases the overall chance of recognising the target. An implementation of the system is described.

Real-time threat assessment for critical infrastructure protection: data incest and conflict in evidential reasoning

NASA Astrophysics Data System (ADS)

Brandon, R.; Page, S.; Varndell, J.

2012-06-01

This paper presents a novel application of Evidential Reasoning to Threat Assessment for critical infrastructure protection. A fusion algorithm based on the PCR5 Dezert-Smarandache fusion rule is proposed which fuses alerts generated by a vision-based behaviour analysis algorithm and a-priori watch-list intelligence data. The fusion algorithm produces a prioritised event list according to a user-defined set of event-type severity or priority weightings. Results generated from application of the algorithm to real data and Behaviour Analysis alerts captured at London's Heathrow Airport under the EU FP7 SAMURAI programme are presented. A web-based demonstrator system is also described which implements the fusion process in real-time. It is shown that this system significantly reduces the data deluge problem, and directs the user's attention to the most pertinent alerts, enhancing their Situational Awareness (SA). The end-user is also able to alter the perceived importance of different event types in real-time, allowing the system to adapt rapidly to changes in priorities as the situation evolves. One of the key challenges associated with fusing information deriving from intelligence data is the issue of Data Incest. Techniques for handling Data Incest within Evidential Reasoning frameworks are proposed, and comparisons are drawn with respect to Data Incest management techniques that are commonly employed within Bayesian fusion frameworks (e.g. Covariance Intersection). The challenges associated with simultaneously dealing with conflicting information and Data Incest in Evidential Reasoning frameworks are also discussed.

SCAR/WAVE and Arp2/3 are critical for cytoskeletal remodeling at the site of myoblast fusion

PubMed Central

Richardson, Brian E.; Beckett, Karen; Nowak, Scott J.; Baylies, Mary K.

2010-01-01

Summary Myoblast fusion is critical for formation and repair of skeletal muscle. Here we show that active remodeling of the actin cytoskeleton is essential for fusion in Drosophila. Using live imaging, we have identified a dynamic F-actin accumulation (actin focus) at the site of fusion. Dissolution of the actin focus directly precedes a fusion event. Whereas several known fusion components regulate these actin foci, others target additional behaviors required for fusion. Mutations in kette/Nap1, an actin polymerization regulator, lead to enlarged foci that do not dissolve, consistent with the observed block in fusion. Kette is required to positively regulate SCAR/WAVE, which in turn activates the Arp2/3 complex. Mutants in SCAR and Arp2/3 have a fusion block and foci phenotype, suggesting that Kette-SCAR-Arp2/3 participate in an actin polymerization event required for focus dissolution. Our data identify a new paradigm for understanding the mechanisms underlying fusion in myoblasts and other tissues. PMID:18003739

Belief Function Based Decision Fusion for Decentralized Target Classification in Wireless Sensor Networks

PubMed Central

Zhang, Wenyu; Zhang, Zhenjiang

2015-01-01

Decision fusion in sensor networks enables sensors to improve classification accuracy while reducing the energy consumption and bandwidth demand for data transmission. In this paper, we focus on the decentralized multi-class classification fusion problem in wireless sensor networks (WSNs) and a new simple but effective decision fusion rule based on belief function theory is proposed. Unlike existing belief function based decision fusion schemes, the proposed approach is compatible with any type of classifier because the basic belief assignments (BBAs) of each sensor are constructed on the basis of the classifier’s training output confusion matrix and real-time observations. We also derive explicit global BBA in the fusion center under Dempster’s combinational rule, making the decision making operation in the fusion center greatly simplified. Also, sending the whole BBA structure to the fusion center is avoided. Experimental results demonstrate that the proposed fusion rule has better performance in fusion accuracy compared with the naïve Bayes rule and weighted majority voting rule. PMID:26295399

Fusion method of SAR and optical images for urban object extraction

NASA Astrophysics Data System (ADS)

Jia, Yonghong; Blum, Rick S.; Li, Fangfang

2007-11-01

A new image fusion method of SAR, Panchromatic (Pan) and multispectral (MS) data is proposed. First of all, SAR texture is extracted by ratioing the despeckled SAR image to its low pass approximation, and is used to modulate high pass details extracted from the available Pan image by means of the á trous wavelet decomposition. Then, high pass details modulated with the texture is applied to obtain the fusion product by HPFM (High pass Filter-based Modulation) fusion method. A set of image data including co-registered Landsat TM, ENVISAT SAR and SPOT Pan is used for the experiment. The results demonstrate accurate spectral preservation on vegetated regions, bare soil, and also on textured areas (buildings and road network) where SAR texture information enhances the fusion product, and the proposed approach is effective for image interpret and classification.

Modeling the evolution space of breakage fusion bridge cycles with a stochastic folding process.

PubMed

Greenman, C D; Cooke, S L; Marshall, J; Stratton, M R; Campbell, P J

2016-01-01

Breakage-fusion-bridge cycles in cancer arise when a broken segment of DNA is duplicated and an end from each copy joined together. This structure then 'unfolds' into a new piece of palindromic DNA. This is one mechanism responsible for the localised amplicons observed in cancer genome data. Here we study the evolution space of breakage-fusion-bridge structures in detail. We firstly consider discrete representations of this space with 2-d trees to demonstrate that there are [Formula: see text] qualitatively distinct evolutions involving [Formula: see text] breakage-fusion-bridge cycles. Secondly we consider the stochastic nature of the process to show these evolutions are not equally likely, and also describe how amplicons become localized. Finally we highlight these methods by inferring the evolution of breakage-fusion-bridge cycles with data from primary tissue cancer samples.

Geographic information system for fusion and analysis of high-resolution remote sensing and ground truth data

NASA Technical Reports Server (NTRS)

Freeman, Anthony; Dubois, Pascale; Leberl, Franz; Norikane, L.; Way, Jobea

1991-01-01

Viewgraphs on Geographic Information System for fusion and analysis of high-resolution remote sensing and ground truth data are presented. Topics covered include: scientific objectives; schedule; and Geographic Information System.

Sensor fusion for synthetic vision

NASA Technical Reports Server (NTRS)

Pavel, M.; Larimer, J.; Ahumada, A.

1991-01-01

Display methodologies are explored for fusing images gathered by millimeter wave sensors with images rendered from an on-board terrain data base to facilitate visually guided flight and ground operations in low visibility conditions. An approach to fusion based on multiresolution image representation and processing is described which facilitates fusion of images differing in resolution within and between images. To investigate possible fusion methods, a workstation-based simulation environment is being developed.

Modeling Cyber Situational Awareness Through Data Fusion

DTIC Science & Technology

2013-03-01

following table: Table 3.10: Example Vulnerable Hosts for Criticality Assessment Experiment Example Id OS Applications/Services Version 1 Mac OS X VLC ...linux.org/. [4] Blasch, E., I. Kadar, J. Salerno, M. Kokar, S. Das, G. Powell, D. Corkill, and E. Ruspini. “Issues and challenges of knowledge representation...Holsopple. “Issues and challenges in higher level fusion: Threat/impact assessment and intent modeling (a panel summary)”. Information Fusion (FUSION

An Extension to Deng's Entropy in the Open World Assumption with an Application in Sensor Data Fusion.

PubMed

Tang, Yongchuan; Zhou, Deyun; Chan, Felix T S

2018-06-11

Quantification of uncertain degree in the Dempster-Shafer evidence theory (DST) framework with belief entropy is still an open issue, even a blank field for the open world assumption. Currently, the existed uncertainty measures in the DST framework are limited to the closed world where the frame of discernment (FOD) is assumed to be complete. To address this issue, this paper focuses on extending a belief entropy to the open world by considering the uncertain information represented as the FOD and the nonzero mass function of the empty set simultaneously. An extension to Deng’s entropy in the open world assumption (EDEOW) is proposed as a generalization of the Deng’s entropy and it can be degenerated to the Deng entropy in the closed world wherever necessary. In order to test the reasonability and effectiveness of the extended belief entropy, an EDEOW-based information fusion approach is proposed and applied to sensor data fusion under uncertainty circumstance. The experimental results verify the usefulness and applicability of the extended measure as well as the modified sensor data fusion method. In addition, a few open issues still exist in the current work: the necessary properties for a belief entropy in the open world assumption, whether there exists a belief entropy that satisfies all the existed properties, and what is the most proper fusion frame for sensor data fusion under uncertainty.

Comparison Between CT and MR Images as More Favorable Reference Data Sets for Fusion Imaging-Guided Radiofrequency Ablation or Biopsy of Hepatic Lesions: A Prospective Study with Focus on Patient's Respiration.

PubMed

Cha, Dong Ik; Lee, Min Woo; Kang, Tae Wook; Oh, Young-Taek; Jeong, Ja-Yeon; Chang, Jung-Woo; Ryu, Jiwon; Lee, Kyong Joon; Kim, Jaeil; Bang, Won-Chul; Shin, Dong Kuk; Choi, Sung Jin; Koh, Dalkwon; Kim, Kyunga

2017-10-01

To identify the more accurate reference data sets for fusion imaging-guided radiofrequency ablation or biopsy of hepatic lesions between computed tomography (CT) and magnetic resonance (MR) images. This study was approved by the institutional review board, and written informed consent was received from all patients. Twelve consecutive patients who were referred to assess the feasibility of radiofrequency ablation or biopsy were enrolled. Automatic registration using CT and MR images was performed in each patient. Registration errors during optimal and opposite respiratory phases, time required for image fusion and number of point locks used were compared using the Wilcoxon signed-rank test. The registration errors during optimal respiratory phase were not significantly different between image fusion using CT and MR images as reference data sets (p = 0.969). During opposite respiratory phase, the registration error was smaller with MR images than CT (p = 0.028). The time and the number of points locks needed for complete image fusion were not significantly different between CT and MR images (p = 0.328 and p = 0.317, respectively). MR images would be more suitable as the reference data set for fusion imaging-guided procedures of focal hepatic lesions than CT images.

Present status and trends of image fusion

NASA Astrophysics Data System (ADS)

Xiang, Dachao; Fu, Sheng; Cai, Yiheng

2009-10-01

Image fusion information extracted from multiple images which is more accurate and reliable than that from just a single image. Since various images contain different information aspects of the measured parts, and comprehensive information can be obtained by integrating them together. Image fusion is a main branch of the application of data fusion technology. At present, it was widely used in computer vision technology, remote sensing, robot vision, medical image processing and military field. This paper mainly presents image fusion's contents, research methods, and the status quo at home and abroad, and analyzes the development trend.

Quad-polarized synthetic aperture radar and multispectral data classification using classification and regression tree and support vector machine-based data fusion system

NASA Astrophysics Data System (ADS)

Bigdeli, Behnaz; Pahlavani, Parham

2017-01-01

Interpretation of synthetic aperture radar (SAR) data processing is difficult because the geometry and spectral range of SAR are different from optical imagery. Consequently, SAR imaging can be a complementary data to multispectral (MS) optical remote sensing techniques because it does not depend on solar illumination and weather conditions. This study presents a multisensor fusion of SAR and MS data based on the use of classification and regression tree (CART) and support vector machine (SVM) through a decision fusion system. First, different feature extraction strategies were applied on SAR and MS data to produce more spectral and textural information. To overcome the redundancy and correlation between features, an intrinsic dimension estimation method based on noise-whitened Harsanyi, Farrand, and Chang determines the proper dimension of the features. Then, principal component analysis and independent component analysis were utilized on stacked feature space of two data. Afterward, SVM and CART classified each reduced feature space. Finally, a fusion strategy was utilized to fuse the classification results. To show the effectiveness of the proposed methodology, single classification on each data was compared to the obtained results. A coregistered Radarsat-2 and WorldView-2 data set from San Francisco, USA, was available to examine the effectiveness of the proposed method. The results show that combinations of SAR data with optical sensor based on the proposed methodology improve the classification results for most of the classes. The proposed fusion method provided approximately 93.24% and 95.44% for two different areas of the data.

Rho GTPase activity modulates paramyxovirus fusion protein-mediated cell-cell fusion

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

Schowalter, Rachel M.; Wurth, Mark A.; Aguilar, Hector C.

2006-07-05

The paramyxovirus fusion protein (F) promotes fusion of the viral envelope with the plasma membrane of target cells as well as cell-cell fusion. The plasma membrane is closely associated with the actin cytoskeleton, but the role of actin dynamics in paramyxovirus F-mediated membrane fusion is unclear. We examined cell-cell fusion promoted by two different paramyxovirus F proteins in three cell types in the presence of constitutively active Rho family GTPases, major cellular coordinators of actin dynamics. Reporter gene and syncytia assays demonstrated that expression of either Rac1{sup V12} or Cdc42{sup V12} could increase cell-cell fusion promoted by the Hendra ormore » SV5 glycoproteins, though the effect was dependent on the cell type expressing the viral glycoproteins. In contrast, RhoA{sup L63} decreased cell-cell fusion promoted by Hendra glycoproteins but had little affect on SV5 F-mediated fusion. Also, data suggested that GTPase activation in the viral glycoprotein-containing cell was primarily responsible for changes in fusion. Additionally, we found that activated Cdc42 promoted nuclear rearrangement in syncytia.« less

State-of-the-Art Fusion-Finder Algorithms Sensitivity and Specificity

PubMed Central

Carrara, Matteo; Beccuti, Marco; Lazzarato, Fulvio; Cavallo, Federica; Cordero, Francesca; Donatelli, Susanna; Calogero, Raffaele A.

2013-01-01

Background. Gene fusions arising from chromosomal translocations have been implicated in cancer. RNA-seq has the potential to discover such rearrangements generating functional proteins (chimera/fusion). Recently, many methods for chimeras detection have been published. However, specificity and sensitivity of those tools were not extensively investigated in a comparative way. Results. We tested eight fusion-detection tools (FusionHunter, FusionMap, FusionFinder, MapSplice, deFuse, Bellerophontes, ChimeraScan, and TopHat-fusion) to detect fusion events using synthetic and real datasets encompassing chimeras. The comparison analysis run only on synthetic data could generate misleading results since we found no counterpart on real dataset. Furthermore, most tools report a very high number of false positive chimeras. In particular, the most sensitive tool, ChimeraScan, reports a large number of false positives that we were able to significantly reduce by devising and applying two filters to remove fusions not supported by fusion junction-spanning reads or encompassing large intronic regions. Conclusions. The discordant results obtained using synthetic and real datasets suggest that synthetic datasets encompassing fusion events may not fully catch the complexity of RNA-seq experiment. Moreover, fusion detection tools are still limited in sensitivity or specificity; thus, there is space for further improvement in the fusion-finder algorithms. PMID:23555082

A Foreign Object Damage Event Detector Data Fusion System for Turbofan Engines

NASA Technical Reports Server (NTRS)

Turso, James A.; Litt, Jonathan S.

2004-01-01

A Data Fusion System designed to provide a reliable assessment of the occurrence of Foreign Object Damage (FOD) in a turbofan engine is presented. The FOD-event feature level fusion scheme combines knowledge of shifts in engine gas path performance obtained using a Kalman filter, with bearing accelerometer signal features extracted via wavelet analysis, to positively identify a FOD event. A fuzzy inference system provides basic probability assignments (bpa) based on features extracted from the gas path analysis and bearing accelerometers to a fusion algorithm based on the Dempster-Shafer-Yager Theory of Evidence. Details are provided on the wavelet transforms used to extract the foreign object strike features from the noisy data and on the Kalman filter-based gas path analysis. The system is demonstrated using a turbofan engine combined-effects model (CEM), providing both gas path and rotor dynamic structural response, and is suitable for rapid-prototyping of control and diagnostic systems. The fusion of the disparate data can provide significantly more reliable detection of a FOD event than the use of either method alone. The use of fuzzy inference techniques combined with Dempster-Shafer-Yager Theory of Evidence provides a theoretical justification for drawing conclusions based on imprecise or incomplete data.

Traceability of Boletaceae mushrooms using data fusion of UV-visible and FTIR combined with chemometrics methods.

PubMed

Yao, Sen; Li, Tao; Liu, HongGao; Li, JieQing; Wang, YuanZhong

2018-04-01

Boletaceae mushrooms are wild-grown edible mushrooms that have high nutrition, delicious flavor and large economic value distributing in Yunnan Province, China. Traceability is important for the authentication and quality assessment of Boletaceae mushrooms. In this study, UV-visible and Fourier transform infrared (FTIR) spectroscopies were applied for traceability of 247 Boletaceae mushroom samples in combination with chemometrics. Compared with a single spectroscopy technique, data fusion strategy can obviously improve the classification performance in partial least square discriminant analysis (PLS-DA) and grid-search support vector machine (GS-SVM) models, for both species and geographical origin traceability. In addition, PLS-DA and GS-SVM models can provide 100.00% accuracy for species traceability and have reliable evaluation parameters. For geographical origin traceability, the accuracy of prediction in the PLS-DA model by data fusion was just 64.63%, but the GS-SVM model based on data fusion was 100.00%. The results demonstrated that the data fusion strategy of UV-visible and FTIR combined with GS-SVM could provide a higher synergic effect for traceability of Boletaceae mushrooms and have a good generalization ability for the comprehensive quality control and evaluation of similar foods. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Seismic data fusion anomaly detection

NASA Astrophysics Data System (ADS)

Harrity, Kyle; Blasch, Erik; Alford, Mark; Ezekiel, Soundararajan; Ferris, David

2014-06-01

Detecting anomalies in non-stationary signals has valuable applications in many fields including medicine and meteorology. These include uses such as identifying possible heart conditions from an Electrocardiography (ECG) signals or predicting earthquakes via seismographic data. Over the many choices of anomaly detection algorithms, it is important to compare possible methods. In this paper, we examine and compare two approaches to anomaly detection and see how data fusion methods may improve performance. The first approach involves using an artificial neural network (ANN) to detect anomalies in a wavelet de-noised signal. The other method uses a perspective neural network (PNN) to analyze an arbitrary number of "perspectives" or transformations of the observed signal for anomalies. Possible perspectives may include wavelet de-noising, Fourier transform, peak-filtering, etc.. In order to evaluate these techniques via signal fusion metrics, we must apply signal preprocessing techniques such as de-noising methods to the original signal and then use a neural network to find anomalies in the generated signal. From this secondary result it is possible to use data fusion techniques that can be evaluated via existing data fusion metrics for single and multiple perspectives. The result will show which anomaly detection method, according to the metrics, is better suited overall for anomaly detection applications. The method used in this study could be applied to compare other signal processing algorithms.

Data fusion approach to threat assessment for radar resources management

NASA Astrophysics Data System (ADS)

Komorniczak, Wojciech; Pietrasinski, Jerzy; Solaiman, Basel

2002-03-01

The paper deals with the problem of the multifunction radar resources management. The problem consists of target/tasks ranking and tasks scheduling. The paper is focused on the target ranking, with the data fusion approach. The data from the radar (object's velocity, range, altitude, direction etc.), IFF system (Identification Friend or Foe) and ESM system (Electronic Support Measures - information concerning threat's electro - magnetic activities) is used to decide of the importance assignment for each detected target. The main problem consists of the multiplicity of various types of the input information. The information from the radar is of the probabilistic or ambiguous imperfection type and the IFF information is of evidential type. To take the advantage of these information sources the advanced data fusion system is necessary. The system should deal with the following situations: fusion of the evidential and fuzzy information, fusion of the evidential information and a'priori information. The paper describes the system which fuses the fuzzy and the evidential information without previous change to the same type of information. It is also described the proposal of using of the dynamic fuzzy qualifiers. The paper shows the results of the preliminary system's tests.

Co-fuse: a new class discovery analysis tool to identify and prioritize recurrent fusion genes from RNA-sequencing data.

PubMed

Paisitkriangkrai, Sakrapee; Quek, Kelly; Nievergall, Eva; Jabbour, Anissa; Zannettino, Andrew; Kok, Chung Hoow

2018-06-07

Recurrent oncogenic fusion genes play a critical role in the development of various cancers and diseases and provide, in some cases, excellent therapeutic targets. To date, analysis tools that can identify and compare recurrent fusion genes across multiple samples have not been available to researchers. To address this deficiency, we developed Co-occurrence Fusion (Co-fuse), a new and easy to use software tool that enables biologists to merge RNA-seq information, allowing them to identify recurrent fusion genes, without the need for exhaustive data processing. Notably, Co-fuse is based on pattern mining and statistical analysis which enables the identification of hidden patterns of recurrent fusion genes. In this report, we show that Co-fuse can be used to identify 2 distinct groups within a set of 49 leukemic cell lines based on their recurrent fusion genes: a multiple myeloma (MM) samples-enriched cluster and an acute myeloid leukemia (AML) samples-enriched cluster. Our experimental results further demonstrate that Co-fuse can identify known driver fusion genes (e.g., IGH-MYC, IGH-WHSC1) in MM, when compared to AML samples, indicating the potential of Co-fuse to aid the discovery of yet unknown driver fusion genes through cohort comparisons. Additionally, using a 272 primary glioma sample RNA-seq dataset, Co-fuse was able to validate recurrent fusion genes, further demonstrating the power of this analysis tool to identify recurrent fusion genes. Taken together, Co-fuse is a powerful new analysis tool that can be readily applied to large RNA-seq datasets, and may lead to the discovery of new disease subgroups and potentially new driver genes, for which, targeted therapies could be developed. The Co-fuse R source code is publicly available at https://github.com/sakrapee/co-fuse .

Multimodal Neuroimaging: Basic Concepts and Classification of Neuropsychiatric Diseases.

PubMed

Tulay, Emine Elif; Metin, Barış; Tarhan, Nevzat; Arıkan, Mehmet Kemal

2018-06-01

Neuroimaging techniques are widely used in neuroscience to visualize neural activity, to improve our understanding of brain mechanisms, and to identify biomarkers-especially for psychiatric diseases; however, each neuroimaging technique has several limitations. These limitations led to the development of multimodal neuroimaging (MN), which combines data obtained from multiple neuroimaging techniques, such as electroencephalography, functional magnetic resonance imaging, and yields more detailed information about brain dynamics. There are several types of MN, including visual inspection, data integration, and data fusion. This literature review aimed to provide a brief summary and basic information about MN techniques (data fusion approaches in particular) and classification approaches. Data fusion approaches are generally categorized as asymmetric and symmetric. The present review focused exclusively on studies based on symmetric data fusion methods (data-driven methods), such as independent component analysis and principal component analysis. Machine learning techniques have recently been introduced for use in identifying diseases and biomarkers of disease. The machine learning technique most widely used by neuroscientists is classification-especially support vector machine classification. Several studies differentiated patients with psychiatric diseases and healthy controls with using combined datasets. The common conclusion among these studies is that the prediction of diseases increases when combining data via MN techniques; however, there remain a few challenges associated with MN, such as sample size. Perhaps in the future N-way fusion can be used to combine multiple neuroimaging techniques or nonimaging predictors (eg, cognitive ability) to overcome the limitations of MN.

Application of data fusion technology based on D-S evidence theory in fire detection

NASA Astrophysics Data System (ADS)

Cai, Zhishan; Chen, Musheng

2015-12-01

Judgment and identification based on single fire characteristic parameter information in fire detection is subject to environmental disturbances, and accordingly its detection performance is limited with the increase of false positive rate and false negative rate. The compound fire detector employs information fusion technology to judge and identify multiple fire characteristic parameters in order to improve the reliability and accuracy of fire detection. The D-S evidence theory is applied to the multi-sensor data-fusion: first normalize the data from all sensors to obtain the normalized basic probability function of the fire occurrence; then conduct the fusion processing using the D-S evidence theory; finally give the judgment results. The results show that the method meets the goal of accurate fire signal identification and increases the accuracy of fire alarm, and therefore is simple and effective.

Outcomes of Posterolateral Fusion with and without Instrumentation and of Interbody Fusion for Isthmic Spondylolisthesis: A Prospective Study.

PubMed

Endler, Peter; Ekman, Per; Möller, Hans; Gerdhem, Paul

2017-05-03

Various methods for the treatment of isthmic spondylolisthesis are available. The aim of this study was to compare outcomes after posterolateral fusion without instrumentation, posterolateral fusion with instrumentation, and interbody fusion. The Swedish Spine Register was used to identify 765 patients who had been operated on for isthmic spondylolisthesis and had at least preoperative and 2-year outcome data; 586 of them had longer follow-up (a mean of 6.9 years). The outcome measures were a global assessment of leg and back pain, the Oswestry Disability Index (ODI), the EuroQol-5 Dimensions (EQ-5D) Questionnaire, the Short Form-36 (SF-36), a visual analog scale (VAS) for back and leg pain, and satisfaction with treatment. Data on additional lumbar spine surgery was searched for in the register, with the mean duration of follow-up for this variable being 10.6 years after the index procedure. Statistical analyses were performed with analysis of covariance or competing-risks proportional hazards regression, adjusted for baseline differences in the studied variables, smoking, employment status, and level of fusion. Posterolateral fusion without instrumentation was performed in 102 patients; posterolateral fusion with instrumentation, in 452; and interbody fusion, in 211. At 1 year, improvement was reported in the global assessment for back pain by 54% of the patients who had posterolateral fusion without instrumentation, 68% of those treated with posterolateral fusion with instrumentation, and 70% of those treated with interbody fusion (p = 0.009). The VAS for back pain and reported satisfaction with treatment showed similar patterns (p = 0.003 and p = 0.017, respectively), whereas other outcomes did not differ among the treatment groups at 1 year. At 2 years, the global assessment for back pain indicated improvement in 57% of the patients who had undergone posterolateral fusion without instrumentation, 70% of those who had posterolateral fusion with instrumentation, and 71% of those treated with interbody fusion (p = 0.022). There were no significant outcome differences at the mean 6.9-year follow-up interval. There was an increased hazard ratio for additional lumbar spine surgery after interbody fusion (4.34; 95% confidence interval [CI] = 1.71 to 11.03) and posterolateral fusion with instrumentation (2.56; 95% CI = 1.02 to 6.42) compared with after posterolateral fusion without instrumentation (1.00; reference). Fusion with instrumentation, with or without interbody fusion, was associated with more improvement in back pain scores and higher satisfaction with treatment compared with fusion without instrumentation at 1 year, but the difference was attenuated with longer follow-up. Fusion with instrumentation was associated with a significantly higher risk of additional spine surgery. Therapeutic Level III. See Instructions for Authors for a complete description of levels of evidence.

Ultrahigh field magnetic resonance and colour Doppler real-time fusion imaging of the orbit--a hybrid tool for assessment of choroidal melanoma.

PubMed

Walter, Uwe; Niendorf, Thoralf; Graessl, Andreas; Rieger, Jan; Krüger, Paul-Christian; Langner, Sönke; Guthoff, Rudolf F; Stachs, Oliver

2014-05-01

A combination of magnetic resonance images with real-time high-resolution ultrasound known as fusion imaging may improve ophthalmologic examination. This study was undertaken to evaluate the feasibility of orbital high-field magnetic resonance and real-time colour Doppler ultrasound image fusion and navigation. This case study, performed between April and June 2013, included one healthy man (age, 47 years) and two patients (one woman, 57 years; one man, 67 years) with choroidal melanomas. All cases underwent 7.0-T magnetic resonance imaging using a custom-made ocular imaging surface coil. The Digital Imaging and Communications in Medicine volume data set was then loaded into the ultrasound system for manual registration of the live ultrasound image and fusion imaging examination. Data registration, matching and then volume navigation were feasible in all cases. Fusion imaging provided real-time imaging capabilities and high tissue contrast of choroidal tumour and optic nerve. It also allowed adding a real-time colour Doppler signal on magnetic resonance images for assessment of vasculature of tumour and retrobulbar structures. The combination of orbital high-field magnetic resonance and colour Doppler ultrasound image fusion and navigation is feasible. Multimodal fusion imaging promises to foster assessment and monitoring of choroidal melanoma and optic nerve disorders. • Orbital magnetic resonance and colour Doppler ultrasound real-time fusion imaging is feasible • Fusion imaging combines the spatial and temporal resolution advantages of each modality • Magnetic resonance and ultrasound fusion imaging improves assessment of choroidal melanoma vascularisation.

Research on the Automatic Fusion Strategy of Fixed Value Boundary Based on the Weak Coupling Condition of Grid Partition

NASA Astrophysics Data System (ADS)

Wang, X. Y.; Dou, J. M.; Shen, H.; Li, J.; Yang, G. S.; Fan, R. Q.; Shen, Q.

2018-03-01

With the continuous strengthening of power grids, the network structure is becoming more and more complicated. An open and regional data modeling is used to complete the calculation of the protection fixed value based on the local region. At the same time, a high precision, quasi real-time boundary fusion technique is needed to seamlessly integrate the various regions so as to constitute an integrated fault computing platform which can conduct transient stability analysis of covering the whole network with high accuracy and multiple modes, deal with the impact results of non-single fault, interlocking fault and build “the first line of defense” of the power grid. The boundary fusion algorithm in this paper is an automatic fusion algorithm based on the boundary accurate coupling of the networking power grid partition, which takes the actual operation mode for qualification, complete the boundary coupling algorithm of various weak coupling partition based on open-loop mode, improving the fusion efficiency, truly reflecting its transient stability level, and effectively solving the problems of too much data, too many difficulties of partition fusion, and no effective fusion due to mutually exclusive conditions. In this paper, the basic principle of fusion process is introduced firstly, and then the method of boundary fusion customization is introduced by scene description. Finally, an example is given to illustrate the specific algorithm on how it effectively implements the boundary fusion after grid partition and to verify the accuracy and efficiency of the algorithm.

Estimating rice yield from MODIS-Landsat fusion data in Taiwan

NASA Astrophysics Data System (ADS)

Chen, C. R.; Chen, C. F.; Nguyen, S. T.

2017-12-01

Rice production monitoring with remote sensing is an important activity in Taiwan due to official initiatives. Yield estimation is a challenge in Taiwan because rice fields are small and fragmental. High spatiotemporal satellite data providing phenological information of rice crops is thus required for this monitoring purpose. This research aims to develop data fusion approaches to integrate daily Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat data for rice yield estimation in Taiwan. In this study, the low-resolution MODIS LST and emissivity data are used as reference data sources to obtain the high-resolution LST from Landsat data using the mixed-pixel analysis technique, and the time-series EVI data were derived the fusion of MODIS and Landsat spectral band data using STARFM method. The LST and EVI simulated results showed the close agreement between the LST and EVI obtained by the proposed methods with the reference data. The rice-yield model was established using EVI and LST data based on information of rice crop phenology collected from 371 ground survey sites across the country in 2014. The results achieved from the fusion datasets compared with the reference data indicated the close relationship between the two datasets with the correlation coefficient (R2) of 0.75 and root mean square error (RMSE) of 338.7 kgs, which were more accurate than those using the coarse-resolution MODIS LST data (R2 = 0.71 and RMSE = 623.82 kgs). For the comparison of total production, 64 towns located in the west part of Taiwan were used. The results also confirmed that the model using fusion datasets produced more accurate results (R2 = 0.95 and RMSE = 1,243 tons) than that using the course-resolution MODIS data (R2 = 0.91 and RMSE = 1,749 tons). This study demonstrates the application of MODIS-Landsat fusion data for rice yield estimation at the township level in Taiwan. The results obtained from the methods used in this study could be useful to policymakers; and thus, the methods can be transferable to other regions in the world for rice yield estimation.

Interactive Plasma Physics Education Using Data from Fusion Experiments

NASA Astrophysics Data System (ADS)

Calderon, Brisa; Davis, Bill; Zwicker, Andrew

2010-11-01

The Internet Plasma Physics Education Experience (IPPEX) website was created in 1996 to give users access to data from plasma and fusion experiments. Interactive material on electricity, magnetism, matter, and energy was presented to generate interest and prepare users to understand data from a fusion experiment. Initially, users were allowed to analyze real-time and archival data from the Tokamak Fusion Test Reactor (TFTR) experiment. IPPEX won numerous awards for its novel approach of allowing users to participate in ongoing research. However, the latest revisions of IPPEX were in 2001 and the interactive material is no longer functional on modern browsers. Also, access to real-time data was lost when TFTR was shut down. The interactive material on IPPEX is being rewritten in ActionScript3.0, and real-time and archival data from the National Spherical Tokamak Experiment (NSTX) will be made available to users. New tools like EFIT animations, fast cameras, and plots of important plasma parameters will be included along with an existing Java-based ``virtual tokamak.'' Screenshots from the upgraded website and future directions will be presented.

Optimally Distributed Kalman Filtering with Data-Driven Communication †

PubMed Central

Dormann, Katharina

2018-01-01

For multisensor data fusion, distributed state estimation techniques that enable a local processing of sensor data are the means of choice in order to minimize storage and communication costs. In particular, a distributed implementation of the optimal Kalman filter has recently been developed. A significant disadvantage of this algorithm is that the fusion center needs access to each node so as to compute a consistent state estimate, which requires full communication each time an estimate is requested. In this article, different extensions of the optimally distributed Kalman filter are proposed that employ data-driven transmission schemes in order to reduce communication expenses. As a first relaxation of the full-rate communication scheme, it can be shown that each node only has to transmit every second time step without endangering consistency of the fusion result. Also, two data-driven algorithms are introduced that even allow for lower transmission rates, and bounds are derived to guarantee consistent fusion results. Simulations demonstrate that the data-driven distributed filtering schemes can outperform a centralized Kalman filter that requires each measurement to be sent to the center node. PMID:29596392

NASA Mars rover: a testbed for evaluating applications of covariance intersection

NASA Astrophysics Data System (ADS)

Uhlmann, Jeffrey K.; Julier, Simon J.; Kamgar-Parsi, Behzad; Lanzagorta, Marco O.; Shyu, Haw-Jye S.

1999-07-01

The Naval Research Laboratory (NRL) has spearheaded the development and application of Covariance Intersection (CI) for a variety of decentralized data fusion problems. Such problems include distributed control, onboard sensor fusion, and dynamic map building and localization. In this paper we describe NRL's development of a CI-based navigation system for the NASA Mars rover that stresses almost all aspects of decentralized data fusion. We also describe how this project relates to NRL's augmented reality, advanced visualization, and REBOT projects.

Overview of Fusion Tags for Recombinant Proteins.

PubMed

Kosobokova, E N; Skrypnik, K A; Kosorukov, V S

2016-03-01

Virtually all recombinant proteins are now prepared using fusion domains also known as "tags". The use of tags helps to solve some serious problems: to simplify procedures of protein isolation, to increase expression and solubility of the desired protein, to simplify protein refolding and increase its efficiency, and to prevent proteolysis. In this review, advantages and disadvantages of such fusion tags are analyzed and data on both well-known and new tags are generalized. The authors own data are also presented.

Product development using process monitoring and NDE data fusion

NASA Astrophysics Data System (ADS)

Peterson, Todd; Bossi, Richard H.

1998-03-01

Composite process/product development relies on both process monitoring information and nondestructive evaluation measurements for determining application suitability. In the past these activities have been performed and analyzed independently. Our present approach is to present the process monitoring and NDE data together in a data fusion workstation. This methodology leads to final product acceptance based on a combined process monitoring and NDE criteria. The data fusion work station combines process parameter and NDE data in a single workspace enabling all the data to be used in the acceptance/rejection decision process. An example application is the induction welding process, a unique joining method for assembling primary composite structure, that offers significant cost and weight advantages over traditional fasted structure. The determination of the required time, temperature and pressure conditions used in the process to achieve a complete weld is being aided by the use of ultrasonic inspection techniques. Full waveform ultrasonic inspection data is employed to evaluate the quality of spar cap to skin fit, an essential element of the welding process, and is processed to find a parameter that can be used for weld acceptance. Certification of the completed weld incorporates the data fusion methodology.

One decade of the Data Fusion Information Group (DFIG) model

NASA Astrophysics Data System (ADS)

Blasch, Erik

2015-05-01

The revision of the Joint Directors of the Laboratories (JDL) Information Fusion model in 2004 discussed information processing, incorporated the analyst, and was coined the Data Fusion Information Group (DFIG) model. Since that time, developments in information technology (e.g., cloud computing, applications, and multimedia) have altered the role of the analyst. Data production has outpaced the analyst; however the analyst still has the role of data refinement and information reporting. In this paper, we highlight three examples being addressed by the DFIG model. One example is the role of the analyst to provide semantic queries (through an ontology) so that vast amount of data available can be indexed, accessed, retrieved, and processed. The second idea is reporting which requires the analyst to collect the data into a condensed and meaningful form through information management. The last example is the interpretation of the resolved information from data that must include contextual information not inherent in the data itself. Through a literature review, the DFIG developments in the last decade demonstrate the usability of the DFIG model to bring together the user (analyst or operator) and the machine (information fusion or manager) in a systems design.

[Two-nuclear neurons: sincitial fusion or amitotic division].

PubMed

Sotnikov, O S; Frumkina, L E; Lactionova, A A; Paramonova, N M; Novakovskaia, S A

2011-01-01

In the review the history of research two-nuclear neurons is stated and two hypotheses about mechanisms of their formation are analysed: by sincitial fusion or amytotic divisions. The facts of discrepancy of the former orthodox cellular theory categorically denying possibility sincitial of communications in nervous system and of sincitial fusion neurons are mentioned. As an example results of ultrastructural researches of occurrence sincitium in a cortex of the big brain of rats, in autonomic ganglions, in hypocampus and a cerebellum of adult animals are presented. The video data of the sincitial fusion of live neurons and the mechanism of formation multinuclear neurons in tissue culture are analyzed. Existing data about amytotic a way of formation two-nuclear neurons are critically considered. The conclusion becomes, that the mechanism of formation two-nuclear neurons is cellular fusion. Simultaneously the review confirms our representations about existence in nervous system sincitial interneural communications.

The emissivities of liquid metals at their fusion temperatures

NASA Technical Reports Server (NTRS)

Bonnell, D. W.; Treverton, J. A.; Valerga, A. J.; Margrave, J. L.

1972-01-01

A survey of the literature through 1969 shows an almost total lack of experimental emissivity data for metals in the liquid state. The emissivities for several transition metals and various other metals and compounds in the liquid state at their fusion temperatures have been determined. The technique used involves electromagnetic levitation-induction heating of the materials in an inert atmosphere. The brightness temperature of the liquid phase of the material is measured as the material is heated through fusion. Given a reliable value of the fusion temperature, which is available for most pure substances, one may readily calculate an emissivity for the liquid phase at the fusion temperatures. Even in cases where melting points are poorly known, the brightness temperatures are unique parameters, independent of the temperature scale and measured for a chemically defined system at a fixed point. Better emissivities may be recalculated as better melting point data become available.

Treating Traumatic Lumbosacral Spondylolisthesis Using Posterior Lumbar Interbody Fusion with three years follow up

PubMed Central

Tang, Shujie

2014-01-01

Objective: To analyze the surgical outcome of traumatic lumbosacral spondylolisthesis treated using posterior lumbar interbody fusion, and help spine surgeons to determine the treatment strategy. Methods: We reviewed retrospectively five cases of traumatic lumbosacral spondylolisthesis treated in our hospital from May 2005 to May 2010. There were four male and one female patient, treated surgically using posterior lumbar interbody fusion. The patients’ data including age, neurological status, operation time, blood loss, follow-up periods, X- radiographs and fusion status were collected. Results: All the cases were treated using posterior lumbar interbody fusion to realize decompression, reduction and fusion. Solid arthrodesis was found at the 12-month follow-up. No shift or breakage of the instrumentation was found, and all the patients were symptom-free at the last follow-up. Conclusion: Traumatic lumbosacral spondylolisthesis can be treated using posterior lumbar interbody fusion to realize the perfect reduction, decompression, fixation and fusion. PMID:25225542

Near-real-time data fusion, phase 2

DOT National Transportation Integrated Search

1999-10-01

Report developed under SBIR contract for topic N93-084. In Phase I of this project, we explored several different approaches to Near-Real-Time Data Fusion (NRTDF), and in Phase II we developed the most promising architecture into a prototype NRTDF sy...

Estimating orientation using magnetic and inertial sensors and different sensor fusion approaches: accuracy assessment in manual and locomotion tasks.

PubMed

Bergamini, Elena; Ligorio, Gabriele; Summa, Aurora; Vannozzi, Giuseppe; Cappozzo, Aurelio; Sabatini, Angelo Maria

2014-10-09

Magnetic and inertial measurement units are an emerging technology to obtain 3D orientation of body segments in human movement analysis. In this respect, sensor fusion is used to limit the drift errors resulting from the gyroscope data integration by exploiting accelerometer and magnetic aiding sensors. The present study aims at investigating the effectiveness of sensor fusion methods under different experimental conditions. Manual and locomotion tasks, differing in time duration, measurement volume, presence/absence of static phases, and out-of-plane movements, were performed by six subjects, and recorded by one unit located on the forearm or the lower trunk, respectively. Two sensor fusion methods, representative of the stochastic (Extended Kalman Filter) and complementary (Non-linear observer) filtering, were selected, and their accuracy was assessed in terms of attitude (pitch and roll angles) and heading (yaw angle) errors using stereophotogrammetric data as a reference. The sensor fusion approaches provided significantly more accurate results than gyroscope data integration. Accuracy improved mostly for heading and when the movement exhibited stationary phases, evenly distributed 3D rotations, it occurred in a small volume, and its duration was greater than approximately 20 s. These results were independent from the specific sensor fusion method used. Practice guidelines for improving the outcome accuracy are provided.

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

Hagen, E. C.; Lowe, D. R.; O'Brien, R.

Dense Plasma Focus (DPF) machines are in use worldwide or a wide variety of applications; one of these is to produce intense, short bursts of fusion via r-Z pinch heating and compression of a working gas. We have designed and constructed a series of these, ranging from portable to a maximum energy storage capacity of 2 MJ. Fusion rates from 5 DPF pulsed fusion generators have been measured in a single laboratory using calibrated activation detectors. Measured rates range from ~ 1015 to more than 1019 fusions per second have been measured. Fusion rates from the intense short (20 –more » 50 ns) periods of production were inferred from measurement of neutron production using both calibrated activation detectors and scintillator-PMT neutron time of flight (NTOF) detectors. The NTOF detectors are arranged to measure neutrons versus time over flight paths of 30 Meters. Fusion rate scaling versus energy and current will be discussed. Data showing observed fusion cutoff at D-D fusion yield levels of approximately 1*1012, and corresponding tube currents of ~ 3 MA will be shown. Energy asymmetry of product neutrons will also be discussed. Data from the NTOF lines of sight have been used to measure energy asymmetries of the fusion neutrons. From this, center of mass energies for the D(d,n)3He reaction are inferred. A novel re-entrant chamber that allows extremely high single pulse neutron doses (> 109 neutrons/cm2 in 50 ns) to be supplied to samples will be described. Machine characteristics and detector types will be discussed.« less

Identification of Alternative Splicing and Fusion Transcripts in Non-Small Cell Lung Cancer by RNA Sequencing.

PubMed

Hong, Yoonki; Kim, Woo Jin; Bang, Chi Young; Lee, Jae Cheol; Oh, Yeon-Mok

2016-04-01

Lung cancer is the most common cause of cancer related death. Alterations in gene sequence, structure, and expression have an important role in the pathogenesis of lung cancer. Fusion genes and alternative splicing of cancer-related genes have the potential to be oncogenic. In the current study, we performed RNA-sequencing (RNA-seq) to investigate potential fusion genes and alternative splicing in non-small cell lung cancer. RNA was isolated from lung tissues obtained from 86 subjects with lung cancer. The RNA samples from lung cancer and normal tissues were processed with RNA-seq using the HiSeq 2000 system. Fusion genes were evaluated using Defuse and ChimeraScan. Candidate fusion transcripts were validated by Sanger sequencing. Alternative splicing was analyzed using multivariate analysis of transcript sequencing and validated using quantitative real time polymerase chain reaction. RNA-seq data identified oncogenic fusion genes EML4-ALK and SLC34A2-ROS1 in three of 86 normal-cancer paired samples. Nine distinct fusion transcripts were selected using DeFuse and ChimeraScan; of which, four fusion transcripts were validated by Sanger sequencing. In 33 squamous cell carcinoma, 29 tumor specific skipped exon events and six mutually exclusive exon events were identified. ITGB4 and PYCR1 were top genes that showed significant tumor specific splice variants. In conclusion, RNA-seq data identified novel potential fusion transcripts and splice variants. Further evaluation of their functional significance in the pathogenesis of lung cancer is required.

Vibrio effector protein VopQ inhibits fusion of V-ATPase–containing membranes

PubMed Central

Sreelatha, Anju; Bennett, Terry L.; Carpinone, Emily M.; O’Brien, Kevin M.; Jordan, Kamyron D.; Burdette, Dara L.; Orth, Kim; Starai, Vincent J.

2015-01-01

Vesicle fusion governs many important biological processes, and imbalances in the regulation of membrane fusion can lead to a variety of diseases such as diabetes and neurological disorders. Here we show that the Vibrio parahaemolyticus effector protein VopQ is a potent inhibitor of membrane fusion based on an in vitro yeast vacuole fusion model. Previously, we demonstrated that VopQ binds to the Vo domain of the conserved V-type H+-ATPase (V-ATPase) found on acidic compartments such as the yeast vacuole. VopQ forms a nonspecific, voltage-gated membrane channel of 18 Å resulting in neutralization of these compartments. We now present data showing that VopQ inhibits yeast vacuole fusion. Furthermore, we identified a unique mutation in VopQ that delineates its two functions, deacidification and inhibition of membrane fusion. The use of VopQ as a membrane fusion inhibitor in this manner now provides convincing evidence that vacuole fusion occurs independently of luminal acidification in vitro. PMID:25453092

Vibrio effector protein VopQ inhibits fusion of V-ATPase-containing membranes.

PubMed

Sreelatha, Anju; Bennett, Terry L; Carpinone, Emily M; O'Brien, Kevin M; Jordan, Kamyron D; Burdette, Dara L; Orth, Kim; Starai, Vincent J

2015-01-06

Vesicle fusion governs many important biological processes, and imbalances in the regulation of membrane fusion can lead to a variety of diseases such as diabetes and neurological disorders. Here we show that the Vibrio parahaemolyticus effector protein VopQ is a potent inhibitor of membrane fusion based on an in vitro yeast vacuole fusion model. Previously, we demonstrated that VopQ binds to the V(o) domain of the conserved V-type H(+)-ATPase (V-ATPase) found on acidic compartments such as the yeast vacuole. VopQ forms a nonspecific, voltage-gated membrane channel of 18 Å resulting in neutralization of these compartments. We now present data showing that VopQ inhibits yeast vacuole fusion. Furthermore, we identified a unique mutation in VopQ that delineates its two functions, deacidification and inhibition of membrane fusion. The use of VopQ as a membrane fusion inhibitor in this manner now provides convincing evidence that vacuole fusion occurs independently of luminal acidification in vitro.

Development of variable pathlength UV-vis spectroscopy combined with partial-least-squares regression for wastewater chemical oxygen demand (COD) monitoring.

PubMed

Chen, Baisheng; Wu, Huanan; Li, Sam Fong Yau

2014-03-01

To overcome the challenging task to select an appropriate pathlength for wastewater chemical oxygen demand (COD) monitoring with high accuracy by UV-vis spectroscopy in wastewater treatment process, a variable pathlength approach combined with partial-least squares regression (PLSR) was developed in this study. Two new strategies were proposed to extract relevant information of UV-vis spectral data from variable pathlength measurements. The first strategy was by data fusion with two data fusion levels: low-level data fusion (LLDF) and mid-level data fusion (MLDF). Predictive accuracy was found to improve, indicated by the lower root-mean-square errors of prediction (RMSEP) compared with those obtained for single pathlength measurements. Both fusion levels were found to deliver very robust PLSR models with residual predictive deviations (RPD) greater than 3 (i.e. 3.22 and 3.29, respectively). The second strategy involved calculating the slopes of absorbance against pathlength at each wavelength to generate slope-derived spectra. Without the requirement to select the optimal pathlength, the predictive accuracy (RMSEP) was improved by 20-43% as compared to single pathlength spectroscopy. Comparing to nine-factor models from fusion strategy, the PLSR model from slope-derived spectroscopy was found to be more parsimonious with only five factors and more robust with residual predictive deviation (RPD) of 3.72. It also offered excellent correlation of predicted and measured COD values with R(2) of 0.936. In sum, variable pathlength spectroscopy with the two proposed data analysis strategies proved to be successful in enhancing prediction performance of COD in wastewater and showed high potential to be applied in on-line water quality monitoring. Copyright © 2013 Elsevier B.V. All rights reserved.

Fusion and direct reactions around the barrier for the systems {sup 7,9}Be,{sup 7}Li+{sup 238}U

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

Raabe, R.; Angulo, C.; Charvet, J. L.

2006-10-15

We present new cross section data for the complete fusion of the weakly bound systems {sup 7,9}Be and {sup 7}Li on {sup 238}U at energies around the Coulomb barrier. In the same measurement, yields for direct processes and incomplete fusion are detected. For all systems, a suppression of the complete fusion cross section around and above the barrier is observed. At energies below the barrier, the fusion of the {sup 7}Be+{sup 238}U system shows no enhancement with respect to simple model predictions.

Data Fusion for Enhanced Aircraft Engine Prognostics and Health Management

NASA Technical Reports Server (NTRS)

Volponi, Al

2005-01-01

Aircraft gas-turbine engine data is available from a variety of sources, including on-board sensor measurements, maintenance histories, and component models. An ultimate goal of Propulsion Health Management (PHM) is to maximize the amount of meaningful information that can be extracted from disparate data sources to obtain comprehensive diagnostic and prognostic knowledge regarding the health of the engine. Data fusion is the integration of data or information from multiple sources for the achievement of improved accuracy and more specific inferences than can be obtained from the use of a single sensor alone. The basic tenet underlying the data/ information fusion concept is to leverage all available information to enhance diagnostic visibility, increase diagnostic reliability and reduce the number of diagnostic false alarms. This report describes a basic PHM data fusion architecture being developed in alignment with the NASA C-17 PHM Flight Test program. The challenge of how to maximize the meaningful information extracted from disparate data sources to obtain enhanced diagnostic and prognostic information regarding the health and condition of the engine is the primary goal of this endeavor. To address this challenge, NASA Glenn Research Center, NASA Dryden Flight Research Center, and Pratt & Whitney have formed a team with several small innovative technology companies to plan and conduct a research project in the area of data fusion, as it applies to PHM. Methodologies being developed and evaluated have been drawn from a wide range of areas including artificial intelligence, pattern recognition, statistical estimation, and fuzzy logic. This report will provide a chronology and summary of the work accomplished under this research contract.

Coupled-channel analyses on 16O + 147,148,150,152,154Sm heavy-ion fusion reactions

NASA Astrophysics Data System (ADS)

Erol, Burcu; Yılmaz, Ahmet Hakan

2018-02-01

Heavy-ion collisons are typically characterized by the presence of many open reaction channels. In the energies around the Coulomb barrier, the main processes are elastic scattering, inelastic excitations of low-lying modes and fusion operations of one or two nuclei. The fusion process is generally defined as the effect of one-dimensional barrier penetration model, taking scattering potential as the sum of Coulomb and proximity potential. We have performed heay-ion fusion reactions with coupled-channel (CC) calculations. Coupled-channel formalism is carried out under barrier energy in heavy-ion fusion reactions. In this work fusion cross sections have been calculated and analyzed in detail for the five systems 16O + 147,148,150,152,154sm in the framework of coupled-channel approach (using the codes CCFUS and CCDEF) and Wong Formula. Calculated results are compared with experimental data, CC calculations using code CCFULL and with the cross section datas taken from `nrv'. CCDEF, CCFULL and Wong Formula explains the fusion reactions of heavy-ions very well, while using the scattering potential as WOODS-SAXON volume potential with Akyuz-Winther parameters. It was observed that AW potential parameters are able to reproduce the experimentally observed fusion cross sections reasonably well for these systems. There is a good agreement between the calculated results with the experimental and nrv[8] results.

The Relationship between Serum Vitamin D Levels and Spinal Fusion Success: A Quantitative Analysis

PubMed Central

Metzger, Melodie F.; Kanim, Linda E.; Zhao, Li; Robinson, Samuel T.; Delamarter, Rick B.

2015-01-01

Study Design An in vivo dosing study of vitamin D in a rat posterolateral spinal fusion model with autogenous bone grafting. Rats randomized to four levels of Vitamin D adjusted rat chow, longitudinal serum validation, surgeons/observers blinded to dietary conditions, and rats followed prospectively for fusion endpoint. Objective To assess the impact of dietary and serum levels of Vitamin D on fusion success, consolidation of fusion mass, and biomechanical stiffness after posterolateral spinal fusion procedure. Summary of Background Data Metabolic risk factors, including vitamin D insufficiency, are often overlooked by spine surgeons. Currently there are no published data on the causal effect of insufficient or deficient vitamin D levels on the success of establishing solid bony union after a spinal fusion procedure. Methods 50 rats were randomized to four experimentally controlled rat chow diets: normal control, vitamin D-deficient, vitamin-D insufficient, and a non-toxic high dose of vitamin D, four weeks prior to surgery and maintained post-surgery until sacrifice. Serum levels of 25(OH)D were determined at surgery and sacrifice using radioimmunoassay. Posterolateral fusion surgery with tail autograft was performed. Rats were sacrificed 12 weeks post-operatively and fusion was evaluated via manual palpation, high resolution radiographs, μCT, and biomechanical testing. Results Serum 25(OH)D and calcium levels were significantly correlated with vitamin-D adjusted chow (p<0.001). There was a dose dependent relationship between vitamin D adjusted chow and manual palpation fusion with greatest differences found in measures of radiographic density between high and deficient vitamin D (p<0.05). Adequate levels of vitamin D (high and normal control) yielded stiffer fusion than inadequate levels (insufficient and deficient) (p<0.05). Conclusions Manual palpation fusion rates increased with supplementation of dietary vitamin D. Biomechanical stiffness, bone volume and density were also positively-related to vitamin D, and calcium. PMID:25627287

Chemotropism and Cell Fusion in Neurospora crassa Relies on the Formation of Distinct Protein Complexes by HAM-5 and a Novel Protein HAM-14

PubMed Central

Jonkers, Wilfried; Fischer, Monika S.; Do, Hung P.; Starr, Trevor L.; Glass, N. Louise

2016-01-01

In filamentous fungi, communication is essential for the formation of an interconnected, multinucleate, syncytial network, which is constructed via hyphal fusion or fusion of germinated asexual spores (germlings). Anastomosis in filamentous fungi is comparable to other somatic cell fusion events resulting in syncytia, including myoblast fusion during muscle differentiation, macrophage fusion, and fusion of trophoblasts during placental development. In Neurospora crassa, fusion of genetically identical germlings is a highly dynamic and regulated process that requires components of a MAP kinase signal transduction pathway. The kinase pathway components (NRC-1, MEK-2 and MAK-2) and the scaffold protein HAM-5 are recruited to hyphae and germling tips undergoing chemotropic interactions. The MAK-2/HAM-5 protein complex shows dynamic oscillation to hyphae/germling tips during chemotropic interactions, and which is out-of-phase to the dynamic localization of SOFT, which is a scaffold protein for components of the cell wall integrity MAP kinase pathway. In this study, we functionally characterize HAM-5 by generating ham-5 truncation constructs and show that the N-terminal half of HAM-5 was essential for function. This region is required for MAK-2 and MEK-2 interaction and for correct cellular localization of HAM-5 to “fusion puncta.” The localization of HAM-5 to puncta was not perturbed in 21 different fusion mutants, nor did these puncta colocalize with components of the secretory pathway. We also identified HAM-14 as a novel member of the HAM-5/MAK-2 pathway by mining MAK-2 phosphoproteomics data. HAM-14 was essential for germling fusion, but not for hyphal fusion. Colocalization and coimmunoprecipitation data indicate that HAM-14 interacts with MAK-2 and MEK-2 and may be involved in recruiting MAK-2 (and MEK-2) to complexes containing HAM-5. PMID:27029735

Chemotropism and Cell Fusion in Neurospora crassa Relies on the Formation of Distinct Protein Complexes by HAM-5 and a Novel Protein HAM-14.

PubMed

Jonkers, Wilfried; Fischer, Monika S; Do, Hung P; Starr, Trevor L; Glass, N Louise

2016-05-01

In filamentous fungi, communication is essential for the formation of an interconnected, multinucleate, syncytial network, which is constructed via hyphal fusion or fusion of germinated asexual spores (germlings). Anastomosis in filamentous fungi is comparable to other somatic cell fusion events resulting in syncytia, including myoblast fusion during muscle differentiation, macrophage fusion, and fusion of trophoblasts during placental development. In Neurospora crassa, fusion of genetically identical germlings is a highly dynamic and regulated process that requires components of a MAP kinase signal transduction pathway. The kinase pathway components (NRC-1, MEK-2 and MAK-2) and the scaffold protein HAM-5 are recruited to hyphae and germling tips undergoing chemotropic interactions. The MAK-2/HAM-5 protein complex shows dynamic oscillation to hyphae/germling tips during chemotropic interactions, and which is out-of-phase to the dynamic localization of SOFT, which is a scaffold protein for components of the cell wall integrity MAP kinase pathway. In this study, we functionally characterize HAM-5 by generating ham-5 truncation constructs and show that the N-terminal half of HAM-5 was essential for function. This region is required for MAK-2 and MEK-2 interaction and for correct cellular localization of HAM-5 to "fusion puncta." The localization of HAM-5 to puncta was not perturbed in 21 different fusion mutants, nor did these puncta colocalize with components of the secretory pathway. We also identified HAM-14 as a novel member of the HAM-5/MAK-2 pathway by mining MAK-2 phosphoproteomics data. HAM-14 was essential for germling fusion, but not for hyphal fusion. Colocalization and coimmunoprecipitation data indicate that HAM-14 interacts with MAK-2 and MEK-2 and may be involved in recruiting MAK-2 (and MEK-2) to complexes containing HAM-5. Copyright © 2016 by the Genetics Society of America.

Multi-model data fusion to improve an early warning system for hypo-/hyperglycemic events.

PubMed

Botwey, Ransford Henry; Daskalaki, Elena; Diem, Peter; Mougiakakou, Stavroula G

2014-01-01

Correct predictions of future blood glucose levels in individuals with Type 1 Diabetes (T1D) can be used to provide early warning of upcoming hypo-/hyperglycemic events and thus to improve the patient's safety. To increase prediction accuracy and efficiency, various approaches have been proposed which combine multiple predictors to produce superior results compared to single predictors. Three methods for model fusion are presented and comparatively assessed. Data from 23 T1D subjects under sensor-augmented pump (SAP) therapy were used in two adaptive data-driven models (an autoregressive model with output correction - cARX, and a recurrent neural network - RNN). Data fusion techniques based on i) Dempster-Shafer Evidential Theory (DST), ii) Genetic Algorithms (GA), and iii) Genetic Programming (GP) were used to merge the complimentary performances of the prediction models. The fused output is used in a warning algorithm to issue alarms of upcoming hypo-/hyperglycemic events. The fusion schemes showed improved performance with lower root mean square errors, lower time lags, and higher correlation. In the warning algorithm, median daily false alarms (DFA) of 0.25%, and 100% correct alarms (CA) were obtained for both event types. The detection times (DT) before occurrence of events were 13.0 and 12.1 min respectively for hypo-/hyperglycemic events. Compared to the cARX and RNN models, and a linear fusion of the two, the proposed fusion schemes represents a significant improvement.

A hybrid sensing approach for pure and adulterated honey classification.

PubMed

Subari, Norazian; Mohamad Saleh, Junita; Md Shakaff, Ali Yeon; Zakaria, Ammar

2012-10-17

This paper presents a comparison between data from single modality and fusion methods to classify Tualang honey as pure or adulterated using Linear Discriminant Analysis (LDA) and Principal Component Analysis (PCA) statistical classification approaches. Ten different brands of certified pure Tualang honey were obtained throughout peninsular Malaysia and Sumatera, Indonesia. Various concentrations of two types of sugar solution (beet and cane sugar) were used in this investigation to create honey samples of 20%, 40%, 60% and 80% adulteration concentrations. Honey data extracted from an electronic nose (e-nose) and Fourier Transform Infrared Spectroscopy (FTIR) were gathered, analyzed and compared based on fusion methods. Visual observation of classification plots revealed that the PCA approach able to distinct pure and adulterated honey samples better than the LDA technique. Overall, the validated classification results based on FTIR data (88.0%) gave higher classification accuracy than e-nose data (76.5%) using the LDA technique. Honey classification based on normalized low-level and intermediate-level FTIR and e-nose fusion data scored classification accuracies of 92.2% and 88.7%, respectively using the Stepwise LDA method. The results suggested that pure and adulterated honey samples were better classified using FTIR and e-nose fusion data than single modality data.

Fusion activity of HIV gp41 fusion domain is related to its secondary structure and depth of membrane insertion in a cholesterol-dependent fashion.

PubMed

Lai, Alex L; Moorthy, Anna Eswara; Li, Yinling; Tamm, Lukas K

2012-04-20

The human immunodeficiency virus (HIV) gp41 fusion domain plays a critical role in membrane fusion during viral entry. A thorough understanding of the relationship between the structure and the activity of the fusion domain in different lipid environments helps to formulate mechanistic models on how it might function in mediating membrane fusion. The secondary structure of the fusion domain in small liposomes composed of different lipid mixtures was investigated by circular dichroism spectroscopy.  The fusion domain formed an α-helix in membranes containing less than 30 mol% cholesterol and  formed β-sheet secondary structure in membranes containing ≥30 mol% cholesterol. EPR spectra of spin-labeled fusion domains also indicated different conformations in membranes with and without cholesterol. Power saturation EPR data were further used to determine the orientation and depth of α-helical fusion domains in lipid bilayers. Fusion and membrane perturbation activities of the gp41 fusion domain were measured by lipid mixing and contents leakage. The fusion domain fused membranes in both its helical form and its β-sheet form. High cholesterol, which induced β-sheets, promoted fusion; however, acidic lipids, which promoted relatively deep membrane insertion as an α-helix, also induced fusion. The results indicate that the structure of the HIV gp41 fusion domain is plastic and depends critically on the lipid environment. Provided that their membrane insertion is deep, α-helical and β-sheet conformations contribute to membrane fusion. Copyright © 2012 Elsevier Ltd. All rights reserved.

Decision-Level Fusion of Spatially Scattered Multi-Modal Data for Nondestructive Inspection of Surface Defects

PubMed Central

Heideklang, René; Shokouhi, Parisa

2016-01-01

This article focuses on the fusion of flaw indications from multi-sensor nondestructive materials testing. Because each testing method makes use of a different physical principle, a multi-method approach has the potential of effectively differentiating actual defect indications from the many false alarms, thus enhancing detection reliability. In this study, we propose a new technique for aggregating scattered two- or three-dimensional sensory data. Using a density-based approach, the proposed method explicitly addresses localization uncertainties such as registration errors. This feature marks one of the major of advantages of this approach over pixel-based image fusion techniques. We provide guidelines on how to set all the key parameters and demonstrate the technique’s robustness. Finally, we apply our fusion approach to experimental data and demonstrate its capability to locate small defects by substantially reducing false alarms under conditions where no single-sensor method is adequate. PMID:26784200

Fusion and Gaussian mixture based classifiers for SONAR data

NASA Astrophysics Data System (ADS)

Kotari, Vikas; Chang, KC

2011-06-01

Underwater mines are inexpensive and highly effective weapons. They are difficult to detect and classify. Hence detection and classification of underwater mines is essential for the safety of naval vessels. This necessitates a formulation of highly efficient classifiers and detection techniques. Current techniques primarily focus on signals from one source. Data fusion is known to increase the accuracy of detection and classification. In this paper, we formulated a fusion-based classifier and a Gaussian mixture model (GMM) based classifier for classification of underwater mines. The emphasis has been on sound navigation and ranging (SONAR) signals due to their extensive use in current naval operations. The classifiers have been tested on real SONAR data obtained from University of California Irvine (UCI) repository. The performance of both GMM based classifier and fusion based classifier clearly demonstrate their superior classification accuracy over conventional single source cases and validate our approach.

SNAREs support atlastin-mediated homotypic ER fusion in Saccharomyces cerevisiae

PubMed Central

Lee, Miriam; Ko, Young-Joon; Moon, Yeojin; Han, Minsoo; Kim, Hyung-Wook; Lee, Sung Haeng; Kang, KyeongJin

2015-01-01

Dynamin-like GTPases of the atlastin family are thought to mediate homotypic endoplasmic reticulum (ER) membrane fusion; however, the underlying mechanism remains largely unclear. Here, we developed a simple and quantitative in vitro assay using isolated yeast microsomes for measuring yeast atlastin Sey1p-dependent ER fusion. Using this assay, we found that the ER SNAREs Sec22p and Sec20p were required for Sey1p-mediated ER fusion. Consistently, ER fusion was significantly reduced by inhibition of Sec18p and Sec17p, which regulate SNARE-mediated membrane fusion. The involvement of SNAREs in Sey1p-dependent ER fusion was further supported by the physical interaction of Sey1p with Sec22p and Ufe1p, another ER SNARE. Furthermore, our estimation of the concentration of Sey1p on isolated microsomes, together with the lack of fusion between Sey1p proteoliposomes even with a 25-fold excess of the physiological concentration of Sey1p, suggests that Sey1p requires additional factors to support ER fusion in vivo. Collectively, our data strongly suggest that SNARE-mediated membrane fusion is involved in atlastin-initiated homotypic ER fusion. PMID:26216899

The Activities of the European Consortium on Nuclear Data Development and Analysis for Fusion

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

Fischer, U., E-mail: ulrich.fischer@kit.edu; Avrigeanu, M.; Avrigeanu, V.

This paper presents an overview of the activities of the European Consortium on Nuclear Data Development and Analysis for Fusion. The Consortium combines available European expertise to provide services for the generation, maintenance, and validation of nuclear data evaluations and data files relevant for ITER, IFMIF and DEMO, as well as codes and software tools required for related nuclear calculations.

Weighted fusion of depth and inertial data to improve view invariance for real-time human action recognition

NASA Astrophysics Data System (ADS)

Chen, Chen; Hao, Huiyan; Jafari, Roozbeh; Kehtarnavaz, Nasser

2017-05-01

This paper presents an extension to our previously developed fusion framework [10] involving a depth camera and an inertial sensor in order to improve its view invariance aspect for real-time human action recognition applications. A computationally efficient view estimation based on skeleton joints is considered in order to select the most relevant depth training data when recognizing test samples. Two collaborative representation classifiers, one for depth features and one for inertial features, are appropriately weighted to generate a decision making probability. The experimental results applied to a multi-view human action dataset show that this weighted extension improves the recognition performance by about 5% over equally weighted fusion deployed in our previous fusion framework.

Decision Fusion with Channel Errors in Distributed Decode-Then-Fuse Sensor Networks

PubMed Central

Yan, Yongsheng; Wang, Haiyan; Shen, Xiaohong; Zhong, Xionghu

2015-01-01

Decision fusion for distributed detection in sensor networks under non-ideal channels is investigated in this paper. Usually, the local decisions are transmitted to the fusion center (FC) and decoded, and a fusion rule is then applied to achieve a global decision. We propose an optimal likelihood ratio test (LRT)-based fusion rule to take the uncertainty of the decoded binary data due to modulation, reception mode and communication channel into account. The average bit error rate (BER) is employed to characterize such an uncertainty. Further, the detection performance is analyzed under both non-identical and identical local detection performance indices. In addition, the performance of the proposed method is compared with the existing optimal and suboptimal LRT fusion rules. The results show that the proposed fusion rule is more robust compared to these existing ones. PMID:26251908

A Smartphone-Based Driver Safety Monitoring System Using Data Fusion

PubMed Central

Lee, Boon-Giin; Chung, Wan-Young

2012-01-01

This paper proposes a method for monitoring driver safety levels using a data fusion approach based on several discrete data types: eye features, bio-signal variation, in-vehicle temperature, and vehicle speed. The driver safety monitoring system was developed in practice in the form of an application for an Android-based smartphone device, where measuring safety-related data requires no extra monetary expenditure or equipment. Moreover, the system provides high resolution and flexibility. The safety monitoring process involves the fusion of attributes gathered from different sensors, including video, electrocardiography, photoplethysmography, temperature, and a three-axis accelerometer, that are assigned as input variables to an inference analysis framework. A Fuzzy Bayesian framework is designed to indicate the driver’s capability level and is updated continuously in real-time. The sensory data are transmitted via Bluetooth communication to the smartphone device. A fake incoming call warning service alerts the driver if his or her safety level is suspiciously compromised. Realistic testing of the system demonstrates the practical benefits of multiple features and their fusion in providing a more authentic and effective driver safety monitoring. PMID:23247416

ER-associated SNAREs and Sey1p mediate nuclear fusion at two distinct steps during yeast mating.

PubMed

Rogers, Jason V; Arlow, Tim; Inkellis, Elizabeth R; Koo, Timothy S; Rose, Mark D

2013-12-01

During yeast mating, two haploid nuclei fuse membranes to form a single diploid nucleus. However, the known proteins required for nuclear fusion are unlikely to function as direct fusogens (i.e., they are unlikely to directly catalyze lipid bilayer fusion) based on their predicted structure and localization. Therefore we screened known fusogens from vesicle trafficking (soluble N-ethylmaleimide-sensitive factor attachment protein receptors [SNAREs]) and homotypic endoplasmic reticulum (ER) fusion (Sey1p) for additional roles in nuclear fusion. Here we demonstrate that the ER-localized SNAREs Sec20p, Ufe1p, Use1p, and Bos1p are required for efficient nuclear fusion. In contrast, Sey1p is required indirectly for nuclear fusion; sey1Δ zygotes accumulate ER at the zone of cell fusion, causing a block in nuclear congression. However, double mutants of Sey1p and Sec20p, Ufe1p, or Use1p, but not Bos1p, display extreme ER morphology defects, worse than either single mutant, suggesting that retrograde SNAREs fuse ER in the absence of Sey1p. Together these data demonstrate that SNAREs mediate nuclear fusion, ER fusion after cell fusion is necessary to complete nuclear congression, and there exists a SNARE-mediated, Sey1p-independent ER fusion pathway.

Exploiting the synergistic effect of concurrent data signals: Low-level fusion of liquid chromatographic with dual detection data.

PubMed

Teglia, Carla M; Azcarate, Silvana M; Alcaráz, Mirta R; Goicoechea, Héctor C; Culzoni, María J

2018-08-15

A low-level data fusion strategy was developed and implemented for data processing of second-order liquid chromatographic data with dual detection, i.e. absorbance and fluorescence monitoring. The synergistic effect of coupling individual information provided by two different detectors was evaluated by analyzing the results gathered after the application of a series of data preprocessing steps and chemometric resolution. The chemometric modeling involved data analysis by MCR-ALS, PARAFAC and N-PLS. Their ability to handle the new data block was assessed through the estimation of the analytical figures of merits achieved in the prediction of a validation set containing fifteen fluorescent and non-fluorescent veterinary active ingredients that can be found in poultry litter. Eventually, the feasibility of the application of the fusion strategy to real poultry litter samples containing the studied compounds was verified. Copyright © 2018 Elsevier B.V. All rights reserved.

A Fusion Architecture for Tracking a Group of People Using a Distributed Sensor Network

DTIC Science & Technology

2013-07-01

Determining the composition of the group is done using several classifiers. The fusion is done at the UGS level to fuse information from all the modalities to...to classification and counting of the targets. Section III also presents the algorithms for fusion of distributed sensor data at the UGS level and...ultrasonic sensors. Determining the composition of the group is done using several classifiers. The fusion is done at the UGS level to fuse

Range and Panoramic Image Fusion Into a Textured Range Image for Culture Heritage Documentation

NASA Astrophysics Data System (ADS)

Bila, Z.; Reznicek, J.; Pavelka, K.

2013-07-01

This paper deals with a fusion of range and panoramic images, where the range image is acquired by a 3D laser scanner and the panoramic image is acquired with a digital still camera mounted on a panoramic head and tripod. The fused resulting dataset, called "textured range image", provides more reliable information about the investigated object for conservators and historians, than using both datasets separately. A simple example of fusion of a range and panoramic images, both obtained in St. Francis Xavier Church in town Opařany, is given here. Firstly, we describe the process of data acquisition, then the processing of both datasets into a proper format for following fusion and the process of fusion. The process of fusion can be divided into a two main parts: transformation and remapping. In the first, transformation, part, both images are related by matching similar features detected on both images with a proper detector, which results in transformation matrix enabling transformation of the range image onto a panoramic image. Then, the range data are remapped from the range image space into a panoramic image space and stored as an additional "range" channel. The process of image fusion is validated by comparing similar features extracted on both datasets.

Spatiotemporal dynamics of membrane remodeling and fusion proteins during endocytic transport

PubMed Central

Arlt, Henning; Auffarth, Kathrin; Kurre, Rainer; Lisse, Dominik; Piehler, Jacob; Ungermann, Christian

2015-01-01

Organelles of the endolysosomal system undergo multiple fission and fusion events to combine sorting of selected proteins to the vacuole with endosomal recycling. This sorting requires a consecutive remodeling of the organelle surface in the course of endosomal maturation. Here we dissect the remodeling and fusion machinery on endosomes during the process of endocytosis. We traced selected GFP-tagged endosomal proteins relative to exogenously added fluorescently labeled α-factor on its way from the plasma membrane to the vacuole. Our data reveal that the machinery of endosomal fusion and ESCRT proteins has similar temporal localization on endosomes, whereas they precede the retromer cargo recognition complex. Neither deletion of retromer nor the fusion machinery with the vacuole affects this maturation process, although the kinetics seems to be delayed due to ESCRT deletion. Of importance, in strains lacking the active Rab7-like Ypt7 or the vacuolar SNARE fusion machinery, α-factor still proceeds to late endosomes with the same kinetics. This indicates that endosomal maturation is mainly controlled by the early endosomal fusion and remodeling machinery but not the downstream Rab Ypt7 or the SNARE machinery. Our data thus provide important further understanding of endosomal biogenesis in the context of cargo sorting. PMID:25657322

Complications Related to the Recombinant Human Bone Morphogenetic Protein 2 Use in Posterior Cervical Fusion.

PubMed

Takahashi, Shinji; Buser, Zorica; Cohen, Jeremiah R; Roe, Allison; Myhre, Sue L; Meisel, Hans-Joerg; Brodke, Darrel S; Yoon, S Tim; Park, Jong-Beom; Wang, Jeffrey C; Youssef, Jim A

2017-11-01

A retrospective cohort study. To compare the complications between posterior cervical fusions with and without recombinant human bone morphogenetic protein 2 (rhBMP2). Use of rhBMP2 in anterior cervical spinal fusion procedures can lead to potential complications such as neck edema, resulting in airway complications or neurological compression. However, there are no data on the complications associated with the "off-label" use of rhBMP2 in upper and lower posterior cervical fusion approaches. Patients from the PearlDiver database who had a posterior cervical fusion between 2005 and 2011 were identified. We evaluated complications within 90 days after fusion and data was divided in 2 groups: (1) posterior cervical fusion including upper cervical spine O-C2 (upper group) and (2) posterior cervical fusion including lower cervical spine C3-C7 (lower group). Complications were divided into: any complication, neck-related complications, wound-related complications, and other complications. Of the 352 patients in the upper group, 73 patients (20.7%) received rhBMP2, and 279 patients (79.3%) did not. Likewise, in the lower group of 2372 patients, 378 patients (15.9%) had surgery with rhBMP2 and 1994 patients (84.1%) without. In the upper group, complications were observed in 7 patients (9.6%) with and 34 patients (12%) without rhBMP2. In the lower group, complications were observed in 42 patients (11%) with and 276 patients (14%) without rhBMP2. Furthermore, in the lower group the wound-related complications were significantly higher in the rhBMP2 group (23 patients, 6.1%) compared with the non-rhBMP2 group (75 patients, 3.8%). Our data showed that the use of rhBMP2 does not increase the risk of complications in upper cervical spine fusion procedures. However, in the lower cervical spine, rhBMP2 may elevate the risk of wound-related complications. Overall, there were no major complications associated with the use of rhBMP2 for posterior cervical fusion approaches. Level III.

Perception-oriented fusion of multi-sensor imagery: visible, IR, and SAR

NASA Astrophysics Data System (ADS)

Sidorchuk, D.; Volkov, V.; Gladilin, S.

2018-04-01

This paper addresses the problem of image fusion of optical (visible and thermal domain) data and radar data for the purpose of visualization. These types of images typically contain a lot of complimentary information, and their joint visualization can be useful and more convenient for human user than a set of individual images. To solve the image fusion problem we propose a novel algorithm that utilizes some peculiarities of human color perception and based on the grey-scale structural visualization. Benefits of presented algorithm are exemplified by satellite imagery.

A Proposed Data Fusion Architecture for Micro-Zone Analysis and Data Mining

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

Kevin McCarthy; Milos Manic

Data Fusion requires the ability to combine or “fuse” date from multiple data sources. Time Series Analysis is a data mining technique used to predict future values from a data set based upon past values. Unlike other data mining techniques, however, Time Series places special emphasis on periodicity and how seasonal and other time-based factors tend to affect trends over time. One of the difficulties encountered in developing generic time series techniques is the wide variability of the data sets available for analysis. This presents challenges all the way from the data gathering stage to results presentation. This paper presentsmore » an architecture designed and used to facilitate the collection of disparate data sets well suited to Time Series analysis as well as other predictive data mining techniques. Results show this architecture provides a flexible, dynamic framework for the capture and storage of a myriad of dissimilar data sets and can serve as a foundation from which to build a complete data fusion architecture.« less

Unsupervised Metric Fusion Over Multiview Data by Graph Random Walk-Based Cross-View Diffusion.

PubMed

Wang, Yang; Zhang, Wenjie; Wu, Lin; Lin, Xuemin; Zhao, Xiang

2017-01-01

Learning an ideal metric is crucial to many tasks in computer vision. Diverse feature representations may combat this problem from different aspects; as visual data objects described by multiple features can be decomposed into multiple views, thus often provide complementary information. In this paper, we propose a cross-view fusion algorithm that leads to a similarity metric for multiview data by systematically fusing multiple similarity measures. Unlike existing paradigms, we focus on learning distance measure by exploiting a graph structure of data samples, where an input similarity matrix can be improved through a propagation of graph random walk. In particular, we construct multiple graphs with each one corresponding to an individual view, and a cross-view fusion approach based on graph random walk is presented to derive an optimal distance measure by fusing multiple metrics. Our method is scalable to a large amount of data by enforcing sparsity through an anchor graph representation. To adaptively control the effects of different views, we dynamically learn view-specific coefficients, which are leveraged into graph random walk to balance multiviews. However, such a strategy may lead to an over-smooth similarity metric where affinities between dissimilar samples may be enlarged by excessively conducting cross-view fusion. Thus, we figure out a heuristic approach to controlling the iteration number in the fusion process in order to avoid over smoothness. Extensive experiments conducted on real-world data sets validate the effectiveness and efficiency of our approach.

Beyond RGB: Very high resolution urban remote sensing with multimodal deep networks

NASA Astrophysics Data System (ADS)

Audebert, Nicolas; Le Saux, Bertrand; Lefèvre, Sébastien

2018-06-01

In this work, we investigate various methods to deal with semantic labeling of very high resolution multi-modal remote sensing data. Especially, we study how deep fully convolutional networks can be adapted to deal with multi-modal and multi-scale remote sensing data for semantic labeling. Our contributions are threefold: (a) we present an efficient multi-scale approach to leverage both a large spatial context and the high resolution data, (b) we investigate early and late fusion of Lidar and multispectral data, (c) we validate our methods on two public datasets with state-of-the-art results. Our results indicate that late fusion make it possible to recover errors steaming from ambiguous data, while early fusion allows for better joint-feature learning but at the cost of higher sensitivity to missing data.

Metadata Creation Tool Content Template For Data Stewards

EPA Science Inventory

A space-time Bayesian fusion model (McMillan, Holland, Morara, and Feng, 2009) is used to provide daily, gridded predictive PM_2.5 (daily average) and O₃ (daily 8-hr maximum) surfaces for 2001-2005. The fusion model uses both air quality monitoring data from ...

Fusion Partner Toolchest for the Stabilization and Crystallization of G Protein-Coupled Receptors

PubMed Central

Chun, Eugene; Thompson, Aaron A.; Liu, Wei; Roth, Christopher B.; Griffith, Mark T.; Katritch, Vsevolod; Kunken, Joshua; Xu, Fei; Cherezov, Vadim; Hanson, Michael A.; Stevens, Raymond C.

2012-01-01

SUMMARY Structural studies of human G protein-coupled receptors (GPCRs) have recently been accelerated through the use of the T4 lysozyme fusion partner that was inserted into the third intracellular loop. Using chimeras of the human β2-adrenergic and human A2A adenosine receptors, we present the methodology and data for the selection of five new fusion partners for crystallizing GPCRs. In particular, the use of the thermostabilized apocytochrome b562RIL as a fusion partner displays certain advantages over the previously utilized T4 lysozyme, resulting in a significant improvement in stability and structure in GPCR-fusion constructs. PMID:22681902

Improved Maturity and Ripeness Classifications of Magnifera Indica cv. Harumanis Mangoes through Sensor Fusion of an Electronic Nose and Acoustic Sensor

PubMed Central

Zakaria, Ammar; Shakaff, Ali Yeon Md; Masnan, Maz Jamilah; Saad, Fathinul Syahir Ahmad; Adom, Abdul Hamid; Ahmad, Mohd Noor; Jaafar, Mahmad Nor; Abdullah, Abu Hassan; Kamarudin, Latifah Munirah

2012-01-01

In recent years, there have been a number of reported studies on the use of non-destructive techniques to evaluate and determine mango maturity and ripeness levels. However, most of these reported works were conducted using single-modality sensing systems, either using an electronic nose, acoustics or other non-destructive measurements. This paper presents the work on the classification of mangoes (Magnifera Indica cv. Harumanis) maturity and ripeness levels using fusion of the data of an electronic nose and an acoustic sensor. Three groups of samples each from two different harvesting times (week 7 and week 8) were evaluated by the e-nose and then followed by the acoustic sensor. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) were able to discriminate the mango harvested at week 7 and week 8 based solely on the aroma and volatile gases released from the mangoes. However, when six different groups of different maturity and ripeness levels were combined in one classification analysis, both PCA and LDA were unable to discriminate the age difference of the Harumanis mangoes. Instead of six different groups, only four were observed using the LDA, while PCA showed only two distinct groups. By applying a low level data fusion technique on the e-nose and acoustic data, the classification for maturity and ripeness levels using LDA was improved. However, no significant improvement was observed using PCA with data fusion technique. Further work using a hybrid LDA-Competitive Learning Neural Network was performed to validate the fusion technique and classify the samples. It was found that the LDA-CLNN was also improved significantly when data fusion was applied. PMID:22778629

Improved maturity and ripeness classifications of Magnifera Indica cv. Harumanis mangoes through sensor fusion of an electronic nose and acoustic sensor.

PubMed

Zakaria, Ammar; Shakaff, Ali Yeon Md; Masnan, Maz Jamilah; Saad, Fathinul Syahir Ahmad; Adom, Abdul Hamid; Ahmad, Mohd Noor; Jaafar, Mahmad Nor; Abdullah, Abu Hassan; Kamarudin, Latifah Munirah

2012-01-01

In recent years, there have been a number of reported studies on the use of non-destructive techniques to evaluate and determine mango maturity and ripeness levels. However, most of these reported works were conducted using single-modality sensing systems, either using an electronic nose, acoustics or other non-destructive measurements. This paper presents the work on the classification of mangoes (Magnifera Indica cv. Harumanis) maturity and ripeness levels using fusion of the data of an electronic nose and an acoustic sensor. Three groups of samples each from two different harvesting times (week 7 and week 8) were evaluated by the e-nose and then followed by the acoustic sensor. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) were able to discriminate the mango harvested at week 7 and week 8 based solely on the aroma and volatile gases released from the mangoes. However, when six different groups of different maturity and ripeness levels were combined in one classification analysis, both PCA and LDA were unable to discriminate the age difference of the Harumanis mangoes. Instead of six different groups, only four were observed using the LDA, while PCA showed only two distinct groups. By applying a low level data fusion technique on the e-nose and acoustic data, the classification for maturity and ripeness levels using LDA was improved. However, no significant improvement was observed using PCA with data fusion technique. Further work using a hybrid LDA-Competitive Learning Neural Network was performed to validate the fusion technique and classify the samples. It was found that the LDA-CLNN was also improved significantly when data fusion was applied.

Energy-resolved neutron imaging for inertial confinement fusion

NASA Astrophysics Data System (ADS)

Moran, M. J.; Haan, S. W.; Hatchett, S. P.; Izumi, N.; Koch, J. A.; Lerche, R. A.; Phillips, T. W.

2003-03-01

The success of the National Ignition Facility program will depend on diagnostic measurements which study the performance of inertial confinement fusion (ICF) experiments. Neutron yield, fusion-burn time history, and images are examples of important diagnostics. Neutron and x-ray images will record the geometries of compressed targets during the fusion-burn process. Such images provide a critical test of the accuracy of numerical modeling of ICF experiments. They also can provide valuable information in cases where experiments produce unexpected results. Although x-ray and neutron images provide similar data, they do have significant differences. X-ray images represent the distribution of high-temperature regions where fusion occurs, while neutron images directly reveal the spatial distribution of fusion-neutron emission. X-ray imaging has the advantage of a relatively straightforward path to the imaging system design. Neutron imaging, by using energy-resolved detection, offers the intriguing advantage of being able to provide independent images of burning and nonburning regions of the nuclear fuel. The usefulness of energy-resolved neutron imaging depends on both the information content of the data and on the quality of the data that can be recorded. The information content will relate to the characteristic neutron spectra that are associated with emission from different regions of the source. Numerical modeling of ICF fusion burn will be required to interpret the corresponding energy-dependent images. The exercise will be useful only if the images can be recorded with sufficient definition to reveal the spatial and energy-dependent features of interest. Several options are being evaluated with respect to the feasibility of providing the desired simultaneous spatial and energy resolution.

A novel framework for command and control of networked sensor systems

NASA Astrophysics Data System (ADS)

Chen, Genshe; Tian, Zhi; Shen, Dan; Blasch, Erik; Pham, Khanh

2007-04-01

In this paper, we have proposed a highly innovative advanced command and control framework for sensor networks used for future Integrated Fire Control (IFC). The primary goal is to enable and enhance target detection, validation, and mitigation for future military operations by graphical game theory and advanced knowledge information fusion infrastructures. The problem is approached by representing distributed sensor and weapon systems as generic warfare resources which must be optimized in order to achieve the operational benefits afforded by enabling a system of systems. This paper addresses the importance of achieving a Network Centric Warfare (NCW) foundation of information superiority-shared, accurate, and timely situational awareness upon which advanced automated management aids for IFC can be built. The approach uses the Data Fusion Information Group (DFIG) Fusion hierarchy of Level 0 through Level 4 to fuse the input data into assessments for the enemy target system threats in a battlespace to which military force is being applied. Compact graph models are employed across all levels of the fusion hierarchy to accomplish integrative data fusion and information flow control, as well as cross-layer sensor management. The functional block at each fusion level will have a set of innovative algorithms that not only exploit the corresponding graph model in a computationally efficient manner, but also permit combined functional experiments across levels by virtue of the unifying graphical model approach.

Facility Monitoring: A Qualitative Theory for Sensor Fusion

NASA Technical Reports Server (NTRS)

Figueroa, Fernando

2001-01-01

Data fusion and sensor management approaches have largely been implemented with centralized and hierarchical architectures. Numerical and statistical methods are the most common data fusion methods found in these systems. Given the proliferation and low cost of processing power, there is now an emphasis on designing distributed and decentralized systems. These systems use analytical/quantitative techniques or qualitative reasoning methods for date fusion.Based on other work by the author, a sensor may be treated as a highly autonomous (decentralized) unit. Each highly autonomous sensor (HAS) is capable of extracting qualitative behaviours from its data. For example, it detects spikes, disturbances, noise levels, off-limit excursions, step changes, drift, and other typical measured trends. In this context, this paper describes a distributed sensor fusion paradigm and theory where each sensor in the system is a HAS. Hence, given the reach qualitative information from each HAS, a paradigm and formal definitions are given so that sensors and processes can reason and make decisions at the qualitative level. This approach to sensor fusion makes it possible the implementation of intuitive (effective) methods to monitor, diagnose, and compensate processes/systems and their sensors. This paradigm facilitates a balanced distribution of intelligence (code and/or hardware) to the sensor level, the process/system level, and a higher controller level. The primary application of interest is in intelligent health management of rocket engine test stands.

SAFE Software and FED Database to Uncover Protein-Protein Interactions using Gene Fusion Analysis.

PubMed

Tsagrasoulis, Dimosthenis; Danos, Vasilis; Kissa, Maria; Trimpalis, Philip; Koumandou, V Lila; Karagouni, Amalia D; Tsakalidis, Athanasios; Kossida, Sophia

2012-01-01

Domain Fusion Analysis takes advantage of the fact that certain proteins in a given proteome A, are found to have statistically significant similarity with two separate proteins in another proteome B. In other words, the result of a fusion event between two separate proteins in proteome B is a specific full-length protein in proteome A. In such a case, it can be safely concluded that the protein pair has a common biological function or even interacts physically. In this paper, we present the Fusion Events Database (FED), a database for the maintenance and retrieval of fusion data both in prokaryotic and eukaryotic organisms and the Software for the Analysis of Fusion Events (SAFE), a computational platform implemented for the automated detection, filtering and visualization of fusion events (both available at: http://www.bioacademy.gr/bioinformatics/projects/ProteinFusion/index.htm). Finally, we analyze the proteomes of three microorganisms using these tools in order to demonstrate their functionality.

SAFE Software and FED Database to Uncover Protein-Protein Interactions using Gene Fusion Analysis

PubMed Central

Tsagrasoulis, Dimosthenis; Danos, Vasilis; Kissa, Maria; Trimpalis, Philip; Koumandou, V. Lila; Karagouni, Amalia D.; Tsakalidis, Athanasios; Kossida, Sophia

2012-01-01

Domain Fusion Analysis takes advantage of the fact that certain proteins in a given proteome A, are found to have statistically significant similarity with two separate proteins in another proteome B. In other words, the result of a fusion event between two separate proteins in proteome B is a specific full-length protein in proteome A. In such a case, it can be safely concluded that the protein pair has a common biological function or even interacts physically. In this paper, we present the Fusion Events Database (FED), a database for the maintenance and retrieval of fusion data both in prokaryotic and eukaryotic organisms and the Software for the Analysis of Fusion Events (SAFE), a computational platform implemented for the automated detection, filtering and visualization of fusion events (both available at: http://www.bioacademy.gr/bioinformatics/projects/ProteinFusion/index.htm). Finally, we analyze the proteomes of three microorganisms using these tools in order to demonstrate their functionality. PMID:22267904

Fusion Safety Program annual report, fiscal year 1994

NASA Astrophysics Data System (ADS)

Longhurst, Glen R.; Cadwallader, Lee C.; Dolan, Thomas J.; Herring, J. Stephen; McCarthy, Kathryn A.; Merrill, Brad J.; Motloch, Chester C.; Petti, David A.

1995-03-01

This report summarizes the major activities of the Fusion Safety Program in fiscal year 1994. The Idaho National Engineering Laboratory (INEL) is the designated lead laboratory and Lockheed Idaho Technologies Company is the prime contractor for this program. The Fusion Safety Program was initiated in 1979. Activities are conducted at the INEL, at other DOE laboratories, and at other institutions, including the University of Wisconsin. The technical areas covered in this report include tritium safety, beryllium safety, chemical reactions and activation product release, safety aspects of fusion magnet systems, plasma disruptions, risk assessment failure rate data base development, and thermalhydraulics code development and their application to fusion safety issues. Much of this work has been done in support of the International Thermonuclear Experimental Reactor (ITER). Also included in the report are summaries of the safety and environmental studies performed by the Fusion Safety Program for the Tokamak Physics Experiment and the Tokamak Fusion Test Reactor and of the technical support for commercial fusion facility conceptual design studies. A major activity this year has been work to develop a DOE Technical Standard for the safety of fusion test facilities.

Role of partial linear momentum transfer on incomplete fusion reaction

NASA Astrophysics Data System (ADS)

Ali, Sabir; Ahmad, Tauseef; Kumar, Kamal; Gull, Muntazir; Rizvi, I. A.; Agarwal, Avinash; Ghugre, S. S.; Sinha, A. K.; Chaubey, A. K.

2018-04-01

Measurements of forward recoil range distributions (FRRDs) of the evaporation residues, populated in the 20Ne+51V reaction at E_{lab}≈ 145 MeV, have been carried out using the offline characteristic γ-ray detection method. The observation does corroborate the presence of complete fusion (CF) process in the population of p xn channel residues and both complete as well as incomplete fusion (ICF) processes in the population of α emitting channel residues. The FRRDs of p xn channel residues comprise single peak only, whereas α emitting channel residues have multiple peaks in their FRRDs. CF cross section data were used to extract the fusion functions. Extracted fusion functions were found to be suppressed with respect to the universal fusion function which is used as a uniform standard reference. The observed contribution arising from the ICF process in the population of α emitting channel residues is explained in terms of breakup fusion model.

Spin distribution of evaporation residues formed in complete and incomplete fusion in 16O+154Sm system

NASA Astrophysics Data System (ADS)

Singh, D.; Linda, Sneha B.; Giri, Pankaj K.; Mahato, Amritraj; Tripathi, R.; Kumar, Harish; Afzal Ansari, M.; Sathik, N. P. M.; Ali, Rahbar; Kumar, Rakesh; Muralithar, S.; Singh, R. P.

2017-11-01

Spin distributions for several evaporation residues populated in the 16O+154Sm system have been measured at projectile energy ≈ 6.2 MeV/A by using the charged particle-γ-coincidence technique. The measured spin distributions of the evaporation residues populated through incomplete fusion associated with 'fast' α and 2α-emission channels are found to be entirely different from fusion-evaporation channels. It is observed that the mean input angular momentum for the evaporation residues formed in incomplete fusion channel is relatively higher than that observed for evaporation residues in complete fusion channels. The feeding intensity profile of evaporation residues populated through complete fusion and incomplete fusion have also been studied. The incomplete fusion channels are found to have narrow range feeding only for high spin states, while complete fusion channels are strongly fed over a broad spin range and widely populated. Comparison of present results with earlier data suggests that the mean input angular momentum values are relatively smaller for spherical target than that of deformed target using the same projectile and incident energy highlighting the role of target deformation in incomplete fusion dynamics.

Membrane fusion activity of vesicular stomatitis virus glycoprotein G is induced by low pH but not by heat or denaturant.

PubMed

Yao, Yi; Ghosh, Kakoli; Epand, Raquel F; Epand, Richard M; Ghosh, Hara P

2003-06-05

The fusogenic envelope glycoprotein G of the rhabdovirus vesicular stomatitis virus (VSV) induces membrane fusion at acidic pH. At acidic pH the G protein undergoes a major structural reorganization leading to the fusogenic conformation. However, unlike other viral fusion proteins, the low-pH-induced conformational change of VSV G is completely reversible. As well, the presence of an alpha-helical coiled-coil motif required for fusion by a number of viral and cellular fusion proteins was not predicted in VSV G protein by using a number of algorithms. Results of pH dependence of the thermal stability of G protein as determined by intrinsic Trp fluorescence and circular dichroism (CD) spectroscopy show that the G protein is equally stable at neutral or acidic pH. Destabilization of G structure at neutral pH with either heat or urea did not induce membrane fusion or conformational change(s) leading to membrane fusion. Taken together, these data suggest that the mechanism of VSV G-induced fusion is distinct from the fusion mechanism of fusion proteins that involve a coiled-coil motif.

Cognitive Load Measurement in a Virtual Reality-based Driving System for Autism Intervention.

PubMed

Zhang, Lian; Wade, Joshua; Bian, Dayi; Fan, Jing; Swanson, Amy; Weitlauf, Amy; Warren, Zachary; Sarkar, Nilanjan

2017-01-01

Autism Spectrum Disorder (ASD) is a highly prevalent neurodevelopmental disorder with enormous individual and social cost. In this paper, a novel virtual reality (VR)-based driving system was introduced to teach driving skills to adolescents with ASD. This driving system is capable of gathering eye gaze, electroencephalography, and peripheral physiology data in addition to driving performance data. The objective of this paper is to fuse multimodal information to measure cognitive load during driving such that driving tasks can be individualized for optimal skill learning. Individualization of ASD intervention is an important criterion due to the spectrum nature of the disorder. Twenty adolescents with ASD participated in our study and the data collected were used for systematic feature extraction and classification of cognitive loads based on five well-known machine learning methods. Subsequently, three information fusion schemes-feature level fusion, decision level fusion and hybrid level fusion-were explored. Results indicate that multimodal information fusion can be used to measure cognitive load with high accuracy. Such a mechanism is essential since it will allow individualization of driving skill training based on cognitive load, which will facilitate acceptance of this driving system for clinical use and eventual commercialization.

Compressive hyperspectral and multispectral imaging fusion

NASA Astrophysics Data System (ADS)

Espitia, Óscar; Castillo, Sergio; Arguello, Henry

2016-05-01

Image fusion is a valuable framework which combines two or more images of the same scene from one or multiple sensors, allowing to improve the resolution of the images and increase the interpretable content. In remote sensing a common fusion problem consists of merging hyperspectral (HS) and multispectral (MS) images that involve large amount of redundant data, which ignores the highly correlated structure of the datacube along the spatial and spectral dimensions. Compressive HS and MS systems compress the spectral data in the acquisition step allowing to reduce the data redundancy by using different sampling patterns. This work presents a compressed HS and MS image fusion approach, which uses a high dimensional joint sparse model. The joint sparse model is formulated by combining HS and MS compressive acquisition models. The high spectral and spatial resolution image is reconstructed by using sparse optimization algorithms. Different fusion spectral image scenarios are used to explore the performance of the proposed scheme. Several simulations with synthetic and real datacubes show promising results as the reliable reconstruction of a high spectral and spatial resolution image can be achieved by using as few as just the 50% of the datacube.

The cost-effectiveness of interbody fusions versus posterolateral fusions in 137 patients with lumbar spondylolisthesis.

PubMed

Bydon, Mohamad; Macki, Mohamed; Abt, Nicholas B; Witham, Timothy F; Wolinsky, Jean-Paul; Gokaslan, Ziya L; Bydon, Ali; Sciubba, Daniel M

2015-03-01

Reimbursements for interbody fusions have declined recently because of their questionable cost-effectiveness. A Markov model was adopted to compare the cost-effectiveness of posterior lumbar interbody fusion (PLIF) or transforaminal lumbar interbody fusion (/TLIF) versus noninterbody fusion and posterolateral fusion (PLF) in patients with lumbar spondylolisthesis. Decision model analysis based on retrospective data from a single institutional series. One hundred thirty-seven patients underwent first-time instrumented lumbar fusions for degenerative or isthmic spondylolisthesis. Quality of life adjustments and expenditures were assigned to each short-term complication (durotomy, surgical site infection, and medical complication) and long-term outcome (bowel/bladder dysfunction and paraplegia, neurologic deficit, and chronic back pain). Patients were divided into a PLF cohort and a PLF plus PLIF/TLIF cohort. Anterior techniques and multilevel interbody fusions were excluded. Each short-term complication and long-term outcome was assigned a numerical quality-adjusted life-year (QALY), based on time trade-off values in the Beaver Dam Health Outcomes Study. The cost data for short-term complications were calculated from charges accrued by the institution's finance sector, and the cost data for long-term outcomes were estimated from the literature. The difference in cost of PLF plus PLIF/TLIF from the cost of PLF alone divided by the difference in QALY equals the cost-effectiveness ratio (CER). We do not report any study funding sources or any study-specific appraisal of potential conflict of interest-associated biases in this article. Of 137 first-time lumbar fusions for spondylolisthesis, 83 patients underwent PLF and 54 underwent PLIF/TLIF. The average time to reoperation was 3.5 years. The mean QALY over 3.5 years was 2.81 in the PLF cohort versus 2.66 in the PLIFo/TLIF cohort (p=.110). The mean 3.5-year costs of $54,827.05 after index interbody fusion were statistically higher than that of the $48,822.76 after PLF (p=.042). The CER of interbody fusion to PLF after the first operation was -$46,699.40 per QALY; however, of the 27 patients requiring reoperation, the incident (reoperation) rate ratio was 7.89 times higher after PLF (2.91, 26.67). The CER after the first reoperation was -$24,429.04 per QALY (relative to PLF). Two patients in the PLF cohort required a second reoperation, whereas none required a second reoperation in the PLIF/TLIF cohort. Taken collectively, the total CER for the interbody fusion is $9,883.97 per QALY. The reoperation rate was statistically higher for PLF, whereas the negative CER for the initial operation and first reoperation favors PLF. However, when second reoperations were included, the CER for the interbody fusion became $9,883.97 per QALY, suggesting moderate long-term cost savings and better functional outcomes with the interbody fusion. Copyright © 2015 Elsevier Inc. All rights reserved.

Double differential light charged particle emission cross sections for some structural fusion materials

NASA Astrophysics Data System (ADS)

Sarpün, Ismail Hakki; n, Abdullah Aydı; Tel, Eyyup

2017-09-01

In fusion reactors, neutron induced radioactivity strongly depends on the irradiated material. So, a proper selection of structural materials will have been limited the radioactive inventory in a fusion reactor. First-wall and blanket components have high radioactivity concentration due to being the most flux-exposed structures. The main objective of fusion structural material research is the development and selection of materials for reactor components with good thermo-mechanical and physical properties, coupled with low-activation characteristics. Double differential light charged particle emission cross section, which is a fundamental data to determine nuclear heating and material damages in structural fusion material research, for some elements target nuclei have been calculated by the TALYS 1.8 nuclear reaction code at 14-15 MeV neutron incident energy and compared with available experimental data in EXFOR library. Direct, compound and pre-equilibrium reaction contribution have been theoretically calculated and dominant contribution have been determined for each emission of proton, deuteron and alpha particle.

Multisensor data fusion for physical activity assessment.

PubMed

Liu, Shaopeng; Gao, Robert X; John, Dinesh; Staudenmayer, John W; Freedson, Patty S

2012-03-01

This paper presents a sensor fusion method for assessing physical activity (PA) of human subjects, based on support vector machines (SVMs). Specifically, acceleration and ventilation measured by a wearable multisensor device on 50 test subjects performing 13 types of activities of varying intensities are analyzed, from which activity type and energy expenditure are derived. The results show that the method correctly recognized the 13 activity types 88.1% of the time, which is 12.3% higher than using a hip accelerometer alone. Also, the method predicted energy expenditure with a root mean square error of 0.42 METs, 22.2% lower than using a hip accelerometer alone. Furthermore, the fusion method was effective in reducing the subject-to-subject variability (standard deviation of recognition accuracies across subjects) in activity recognition, especially when data from the ventilation sensor were added to the fusion model. These results demonstrate that the multisensor fusion technique presented is more effective in identifying activity type and energy expenditure than the traditional accelerometer-alone-based methods.

MEG-EEG Information Fusion and Electromagnetic Source Imaging: From Theory to Clinical Application in Epilepsy.

PubMed

Chowdhury, Rasheda Arman; Zerouali, Younes; Hedrich, Tanguy; Heers, Marcel; Kobayashi, Eliane; Lina, Jean-Marc; Grova, Christophe

2015-11-01

The purpose of this study is to develop and quantitatively assess whether fusion of EEG and MEG (MEEG) data within the maximum entropy on the mean (MEM) framework increases the spatial accuracy of source localization, by yielding better recovery of the spatial extent and propagation pathway of the underlying generators of inter-ictal epileptic discharges (IEDs). The key element in this study is the integration of the complementary information from EEG and MEG data within the MEM framework. MEEG was compared with EEG and MEG when localizing single transient IEDs. The fusion approach was evaluated using realistic simulation models involving one or two spatially extended sources mimicking propagation patterns of IEDs. We also assessed the impact of the number of EEG electrodes required for an efficient EEG-MEG fusion. MEM was compared with minimum norm estimate, dynamic statistical parametric mapping, and standardized low-resolution electromagnetic tomography. The fusion approach was finally assessed on real epileptic data recorded from two patients showing IEDs simultaneously in EEG and MEG. Overall the localization of MEEG data using MEM provided better recovery of the source spatial extent, more sensitivity to the source depth and more accurate detection of the onset and propagation of IEDs than EEG or MEG alone. MEM was more accurate than the other methods. MEEG proved more robust than EEG and MEG for single IED localization in low signal-to-noise ratio conditions. We also showed that only few EEG electrodes are required to bring additional relevant information to MEG during MEM fusion.

An Investigation for Ground State Features of Some Structural Fusion Materials

NASA Astrophysics Data System (ADS)

Aytekin, H.; Tel, E.; Baldik, R.; Aydin, A.

2011-02-01

Environmental concerns associated with fossil fuels are creating increased interest in alternative non-fossil energy sources. Nuclear fusion can be one of the most attractive sources of energy from the viewpoint of safety and minimal environmental impact. When considered in all energy systems, the requirements for performance of structural materials in a fusion reactor first wall, blanket or diverter, are arguably more demanding or difficult than for other energy system. The development of fusion materials for the safety of fusion power systems and understanding nuclear properties is important. In this paper, ground state properties for some structural fusion materials as 27Al, 51V, 52Cr, 55Mn, and 56Fe are investigated using Skyrme-Hartree-Fock method. The obtained results have been discussed and compared with the available experimental data.

Regulation of Herpes Simplex Virus Glycoprotein-Induced Cascade of Events Governing Cell-Cell Fusion

PubMed Central

Saw, Wan Ting; Eisenberg, Roselyn J.; Cohen, Gary H.

2016-01-01

ABSTRACT Receptor-dependent herpes simplex virus (HSV)-induced cell-cell fusion requires glycoproteins gD, gH/gL, and gB. Our current model posits that during fusion, receptor-activated conformational changes in gD activate gH/gL, which subsequently triggers the transformation of the prefusion form of gB into a fusogenic state. To examine the role of each glycoprotein in receptor-dependent cell-cell fusion, we took advantage of our discovery that fusion by wild-type herpes simplex virus 2 (HSV-2) glycoproteins occurs twice as fast as that achieved by HSV-1 glycoproteins. By sequentially swapping each glycoprotein between the two serotypes, we established that fusion speed was governed by gH/gL, with gH being the main contributor. While the mutant forms of gB fuse at distinct rates that are dictated by their molecular structure, these restrictions can be overcome by gH/gL of HSV-2 (gH2/gL2), thereby enhancing their activity. We also found that deregulated forms of gD of HSV-1 (gD1) and gH2/gL2 can alter the fusogenic potential of gB, promoting cell fusion in the absence of a cellular receptor, and that deregulated forms of gB can drive the fusion machinery to even higher levels. Low pH enhanced fusion by affecting the structure of both gB and gH/gL mutants. Together, our data highlight the complexity of the fusion machinery, the impact of the activation state of each glycoprotein on the fusion process, and the critical role of gH/gL in regulating HSV-induced fusion. IMPORTANCE Cell-cell fusion mediated by HSV glycoproteins requires gD, gH/gL, gB, and a gD receptor. Here, we show that fusion by wild-type HSV-2 glycoproteins occurs twice as fast as that achieved by HSV-1 glycoproteins. By sequentially swapping each glycoprotein between the two serotypes, we found that the fusion process was controlled by gH/gL. Restrictions imposed on the gB structure by mutations could be overcome by gH2/gL2, enhancing the activity of the mutants. Under low-pH conditions or when using deregulated forms of gD1 and gH2/gL2, the fusogenic potential of gB could only be increased in the absence of receptor, underlining the exquisite regulation that occurs in the presence of receptor. Our data highlight the complexity of the fusion machinery, the impact of the activation state of each glycoprotein on the fusion process, and the critical role of gH/gL in regulating HSV-induced fusion. PMID:27630245

Comparison of LSS-IV and LISS-III+LISS-IV merged data for classification of crops

NASA Astrophysics Data System (ADS)

Hebbar, R.; Sesha Sai, M. V. R.

2014-11-01

Resourcesat-1 satellite with its unique capability of simultaneous acquisition of multispectral images at different spatial resolutions (AWiFS, LISS-III and LISS-IV MX / Mono) has immense potential for crop inventory. The present study was carried for selection of suitable LISS-IV MX band for data fusion and its evaluation for delineation different crops in a multi-cropped area. Image fusion techniques namely intensity hue saturation (IHS), principal component analysis (PCA), brovey, high pass filter (HPF) and wavelet methods were used for merging LISS-III and LISS-IV Mono data. The merged products were evaluated visually and through universal image quality index, ERGAS and classification accuracy. The study revealed that red band of LISS-IV MX data was found to be optimal band for merging with LISS-III data in terms of maintaining both spectral and spatial information and thus, closely matching with multispectral LISS-IVMX data. Among the five data fusion techniques, wavelet method was found to be superior in retaining image quality and higher classification accuracy compared to commonly used methods of IHS, PCA and Brovey. The study indicated that LISS-IV data in mono mode with wider swath of 70 km could be exploited in place of 24km LISS-IVMX data by selection of appropriate fusion techniques by acquiring monochromatic data in the red band.

Systematic investigations of deep sub-barrier fusion reactions using an adiabatic approach

NASA Astrophysics Data System (ADS)

Ichikawa, Takatoshi

2015-12-01

Background: At extremely low incident energies, unexpected decreases in fusion cross sections, compared to the standard coupled-channels (CC) calculations, have been observed in a wide range of fusion reactions. These significant reductions of the fusion cross sections are often referred to as the fusion hindrance. However, the physical origin of the fusion hindrance is still unclear. Purpose: To describe the fusion hindrance based on an adiabatic approach, I propose a novel extension of the standard CC model by introducing a damping factor that describes a smooth transition from sudden to adiabatic processes, that is, the transition from the separated two-body to the united dinuclear system. I demonstrate the performance of this model by systematically investigating various deep sub-barrier fusion reactions. Method: I extend the standard CC model by introducing a damping factor into the coupling matrix elements in the standard CC model. This avoids double counting of the CC effects, when two colliding nuclei overlap one another. I adopt the Yukawa-plus-exponential (YPE) model as a basic heavy ion-ion potential, which is advantageous for a unified description of the one- and two-body potentials. For the purpose of these systematic investigations, I approximate the one-body potential with a third-order polynomial function based on the YPE model. Results: Calculated fusion cross sections for the medium-heavy mass systems of 64Ni+64Ni , 58Ni+58Ni , and 58Ni+54Fe , the medium-light mass systems of 40Ca+40Ca , 48Ca+48Ca , and 24Mg+30Si , and the mass-asymmetric systems of 48Ca+96Zr and 16O+208Pb are consistent with the experimental data. The astrophysical S factor and logarithmic derivative representations of these are also in good agreement with the experimental data. The values obtained for the individual radius and diffuseness parameters in the damping factor, which reproduce the fusion cross sections well, are nearly equal to the average value for all the systems. Conclusions: Since the results calculated with the damping factor are in excellent agreement with the experimental data in all systems, I conclude that a coordinate-dependent coupling strength is responsible for the fusion hindrance. In all systems, the potential energies at the touching point VTouch strongly correlate with the incident threshold energies for which the fusion hindrance starts to emerge, except for the medium-light mass systems.

ER-associated SNAREs and Sey1p mediate nuclear fusion at two distinct steps during yeast mating

PubMed Central

Rogers, Jason V.; Arlow, Tim; Inkellis, Elizabeth R.; Koo, Timothy S.; Rose, Mark D.

2013-01-01

During yeast mating, two haploid nuclei fuse membranes to form a single diploid nucleus. However, the known proteins required for nuclear fusion are unlikely to function as direct fusogens (i.e., they are unlikely to directly catalyze lipid bilayer fusion) based on their predicted structure and localization. Therefore we screened known fusogens from vesicle trafficking (soluble N-ethylmaleimide–sensitive factor attachment protein receptors [SNAREs]) and homotypic endoplasmic reticulum (ER) fusion (Sey1p) for additional roles in nuclear fusion. Here we demonstrate that the ER-localized SNAREs Sec20p, Ufe1p, Use1p, and Bos1p are required for efficient nuclear fusion. In contrast, Sey1p is required indirectly for nuclear fusion; sey1Δ zygotes accumulate ER at the zone of cell fusion, causing a block in nuclear congression. However, double mutants of Sey1p and Sec20p, Ufe1p, or Use1p, but not Bos1p, display extreme ER morphology defects, worse than either single mutant, suggesting that retrograde SNAREs fuse ER in the absence of Sey1p. Together these data demonstrate that SNAREs mediate nuclear fusion, ER fusion after cell fusion is necessary to complete nuclear congression, and there exists a SNARE-mediated, Sey1p-independent ER fusion pathway. PMID:24152736

Quantitative image fusion in infrared radiometry

NASA Astrophysics Data System (ADS)

Romm, Iliya; Cukurel, Beni

2018-05-01

Towards high-accuracy infrared radiance estimates, measurement practices and processing techniques aimed to achieve quantitative image fusion using a set of multi-exposure images of a static scene are reviewed. The conventional non-uniformity correction technique is extended, as the original is incompatible with quantitative fusion. Recognizing the inherent limitations of even the extended non-uniformity correction, an alternative measurement methodology, which relies on estimates of the detector bias using self-calibration, is developed. Combining data from multi-exposure images, two novel image fusion techniques that ultimately provide high tonal fidelity of a photoquantity are considered: ‘subtract-then-fuse’, which conducts image subtraction in the camera output domain and partially negates the bias frame contribution common to both the dark and scene frames; and ‘fuse-then-subtract’, which reconstructs the bias frame explicitly and conducts image fusion independently for the dark and the scene frames, followed by subtraction in the photoquantity domain. The performances of the different techniques are evaluated for various synthetic and experimental data, identifying the factors contributing to potential degradation of the image quality. The findings reflect the superiority of the ‘fuse-then-subtract’ approach, conducting image fusion via per-pixel nonlinear weighted least squares optimization.

Radar image and data fusion for natural hazards characterisation

USGS Publications Warehouse

Lu, Zhong; Dzurisin, Daniel; Jung, Hyung-Sup; Zhang, Jixian; Zhang, Yonghong

2010-01-01

Fusion of synthetic aperture radar (SAR) images through interferometric, polarimetric and tomographic processing provides an all - weather imaging capability to characterise and monitor various natural hazards. This article outlines interferometric synthetic aperture radar (InSAR) processing and products and their utility for natural hazards characterisation, provides an overview of the techniques and applications related to fusion of SAR/InSAR images with optical and other images and highlights the emerging SAR fusion technologies. In addition to providing precise land - surface digital elevation maps, SAR - derived imaging products can map millimetre - scale elevation changes driven by volcanic, seismic and hydrogeologic processes, by landslides and wildfires and other natural hazards. With products derived from the fusion of SAR and other images, scientists can monitor the progress of flooding, estimate water storage changes in wetlands for improved hydrological modelling predictions and assessments of future flood impacts and map vegetation structure on a global scale and monitor its changes due to such processes as fire, volcanic eruption and deforestation. With the availability of SAR images in near real - time from multiple satellites in the near future, the fusion of SAR images with other images and data is playing an increasingly important role in understanding and forecasting natural hazards.

Combined NMR and EPR Spectroscopy to Determine Structures of Viral Fusion Domains in Membranes

PubMed Central

Tamm, Lukas K.; Lai, Alex L.; Li, Yinling

2008-01-01

Methods are described to determine the structures of viral membrane fusion domains in detergent micelles by NMR and in lipid bilayers by site-directed spin labeling and EPR spectroscopy. Since in favorable cases, the lower-resolution spin label data obtained in lipid bilayers fully support the higher-resolution structures obtained by solution NMR, it is possible to graft the NMR structural coordinates into membranes using the EPR-derived distance restraints to the lipid bilayer. Electron paramagnetic dynamics and distance measurements in bilayers support conclusions drawn from NMR in detergent micelles. When these methods are applied to a structure determination of the influenza virus fusion domain and four point mutations with different functional phenotypes, it is evident that a fixed-angle boomerang structure with a glycine edge on the outside of the N-terminal arm is both necessary and sufficient to support membrane fusion. The human immunodeficiency virus fusion domain forms a straight helix with a flexible C-terminus. While EPR data for this fusion domain are not yet available, it is tentatively speculated that, because of its higher hydrophobicity, a critically tilted insertion may occur even in the absence of a kinked boomerang structure in this case. PMID:17963720

Object-based land cover classification based on fusion of multifrequency SAR data and THAICHOTE optical imagery

NASA Astrophysics Data System (ADS)

Sukawattanavijit, Chanika; Srestasathiern, Panu

2017-10-01

Land Use and Land Cover (LULC) information are significant to observe and evaluate environmental change. LULC classification applying remotely sensed data is a technique popularly employed on a global and local dimension particularly, in urban areas which have diverse land cover types. These are essential components of the urban terrain and ecosystem. In the present, object-based image analysis (OBIA) is becoming widely popular for land cover classification using the high-resolution image. COSMO-SkyMed SAR data was fused with THAICHOTE (namely, THEOS: Thailand Earth Observation Satellite) optical data for land cover classification using object-based. This paper indicates a comparison between object-based and pixel-based approaches in image fusion. The per-pixel method, support vector machines (SVM) was implemented to the fused image based on Principal Component Analysis (PCA). For the objectbased classification was applied to the fused images to separate land cover classes by using nearest neighbor (NN) classifier. Finally, the accuracy assessment was employed by comparing with the classification of land cover mapping generated from fused image dataset and THAICHOTE image. The object-based data fused COSMO-SkyMed with THAICHOTE images demonstrated the best classification accuracies, well over 85%. As the results, an object-based data fusion provides higher land cover classification accuracy than per-pixel data fusion.

A Hybrid Sensing Approach for Pure and Adulterated Honey Classification

PubMed Central

Subari, Norazian; Saleh, Junita Mohamad; Shakaff, Ali Yeon Md; Zakaria, Ammar

2012-01-01

This paper presents a comparison between data from single modality and fusion methods to classify Tualang honey as pure or adulterated using Linear Discriminant Analysis (LDA) and Principal Component Analysis (PCA) statistical classification approaches. Ten different brands of certified pure Tualang honey were obtained throughout peninsular Malaysia and Sumatera, Indonesia. Various concentrations of two types of sugar solution (beet and cane sugar) were used in this investigation to create honey samples of 20%, 40%, 60% and 80% adulteration concentrations. Honey data extracted from an electronic nose (e-nose) and Fourier Transform Infrared Spectroscopy (FTIR) were gathered, analyzed and compared based on fusion methods. Visual observation of classification plots revealed that the PCA approach able to distinct pure and adulterated honey samples better than the LDA technique. Overall, the validated classification results based on FTIR data (88.0%) gave higher classification accuracy than e-nose data (76.5%) using the LDA technique. Honey classification based on normalized low-level and intermediate-level FTIR and e-nose fusion data scored classification accuracies of 92.2% and 88.7%, respectively using the Stepwise LDA method. The results suggested that pure and adulterated honey samples were better classified using FTIR and e-nose fusion data than single modality data. PMID:23202033

Sensor data fusion for textured reconstruction and virtual representation of alpine scenes

NASA Astrophysics Data System (ADS)

Häufel, Gisela; Bulatov, Dimitri; Solbrig, Peter

2017-10-01

The concept of remote sensing is to provide information about a wide-range area without making physical contact with this area. If, additionally to satellite imagery, images and videos taken by drones provide a more up-to-date data at a higher resolution, or accurate vector data is downloadable from the Internet, one speaks of sensor data fusion. The concept of sensor data fusion is relevant for many applications, such as virtual tourism, automatic navigation, hazard assessment, etc. In this work, we describe sensor data fusion aiming to create a semantic 3D model of an extremely interesting yet challenging dataset: An alpine region in Southern Germany. A particular challenge of this work is that rock faces including overhangs are present in the input airborne laser point cloud. The proposed procedure for identification and reconstruction of overhangs from point clouds comprises four steps: Point cloud preparation, filtering out vegetation, mesh generation and texturing. Further object types are extracted in several interesting subsections of the dataset: Building models with textures from UAV (Unmanned Aerial Vehicle) videos, hills reconstructed as generic surfaces and textured by the orthophoto, individual trees detected by the watershed algorithm, as well as the vector data for roads retrieved from openly available shapefiles and GPS-device tracks. We pursue geo-specific reconstruction by assigning texture and width to roads of several pre-determined types and modeling isolated trees and rocks using commercial software. For visualization and simulation of the area, we have chosen the simulation system Virtual Battlespace 3 (VBS3). It becomes clear that the proposed concept of sensor data fusion allows a coarse reconstruction of a large scene and, at the same time, an accurate and up-to-date representation of its relevant subsections, in which simulation can take place.

Development of an Information Fusion System for Engine Diagnostics and Health Management

NASA Technical Reports Server (NTRS)

Volponi, Allan J.; Brotherton, Tom; Luppold, Robert; Simon, Donald L.

2004-01-01

Aircraft gas-turbine engine data are available from a variety of sources including on-board sensor measurements, maintenance histories, and component models. An ultimate goal of Propulsion Health Management (PHM) is to maximize the amount of meaningful information that can be extracted from disparate data sources to obtain comprehensive diagnostic and prognostic knowledge regarding the health of the engine. Data Fusion is the integration of data or information from multiple sources, to achieve improved accuracy and more specific inferences than can be obtained from the use of a single sensor alone. The basic tenet underlying the data/information fusion concept is to leverage all available information to enhance diagnostic visibility, increase diagnostic reliability and reduce the number of diagnostic false alarms. This paper describes a basic PHM Data Fusion architecture being developed in alignment with the NASA C17 Propulsion Health Management (PHM) Flight Test program. The challenge of how to maximize the meaningful information extracted from disparate data sources to obtain enhanced diagnostic and prognostic information regarding the health and condition of the engine is the primary goal of this endeavor. To address this challenge, NASA Glenn Research Center (GRC), NASA Dryden Flight Research Center (DFRC) and Pratt & Whitney (P&W) have formed a team with several small innovative technology companies to plan and conduct a research project in the area of data fusion as applied to PHM. Methodologies being developed and evaluated have been drawn from a wide range of areas including artificial intelligence, pattern recognition, statistical estimation, and fuzzy logic. This paper will provide a broad overview of this work, discuss some of the methodologies employed and give some illustrative examples.

Regional Distribution of Forest Height and Biomass from Multisensor Data Fusion

NASA Technical Reports Server (NTRS)

Yu, Yifan; Saatchi, Sassan; Heath, Linda S.; LaPoint, Elizabeth; Myneni, Ranga; Knyazikhin, Yuri

2010-01-01

Elevation data acquired from radar interferometry at C-band from SRTM are used in data fusion techniques to estimate regional scale forest height and aboveground live biomass (AGLB) over the state of Maine. Two fusion techniques have been developed to perform post-processing and parameter estimations from four data sets: 1 arc sec National Elevation Data (NED), SRTM derived elevation (30 m), Landsat Enhanced Thematic Mapper (ETM) bands (30 m), derived vegetation index (VI) and NLCD2001 land cover map. The first fusion algorithm corrects for missing or erroneous NED data using an iterative interpolation approach and produces distribution of scattering phase centers from SRTM-NED in three dominant forest types of evergreen conifers, deciduous, and mixed stands. The second fusion technique integrates the USDA Forest Service, Forest Inventory and Analysis (FIA) ground-based plot data to develop an algorithm to transform the scattering phase centers into mean forest height and aboveground biomass. Height estimates over evergreen (R2 = 0.86, P < 0.001; RMSE = 1.1 m) and mixed forests (R2 = 0.93, P < 0.001, RMSE = 0.8 m) produced the best results. Estimates over deciduous forests were less accurate because of the winter acquisition of SRTM data and loss of scattering phase center from tree ]surface interaction. We used two methods to estimate AGLB; algorithms based on direct estimation from the scattering phase center produced higher precision (R2 = 0.79, RMSE = 25 Mg/ha) than those estimated from forest height (R2 = 0.25, RMSE = 66 Mg/ha). We discuss sources of uncertainty and implications of the results in the context of mapping regional and continental scale forest biomass distribution.

Enhancing radiological volumes with symbolic anatomy using image fusion and collaborative virtual reality.

PubMed

Silverstein, Jonathan C; Dech, Fred; Kouchoukos, Philip L

2004-01-01

Radiological volumes are typically reviewed by surgeons using cross-sections and iso-surface reconstructions. Applications that combine collaborative stereo volume visualization with symbolic anatomic information and data fusions would expand surgeons' capabilities in interpretation of data and in planning treatment. Such an application has not been seen clinically. We are developing methods to systematically combine symbolic anatomy (term hierarchies and iso-surface atlases) with patient data using data fusion. We describe our progress toward integrating these methods into our collaborative virtual reality application. The fully combined application will be a feature-rich stereo collaborative volume visualization environment for use by surgeons in which DICOM datasets will self-report underlying anatomy with visual feedback. Using hierarchical navigation of SNOMED-CT anatomic terms integrated with our existing Tele-immersive DICOM-based volumetric rendering application, we will display polygonal representations of anatomic systems on the fly from menus that query a database. The methods and tools involved in this application development are SNOMED-CT, DICOM, VISIBLE HUMAN, volumetric fusion and C++ on a Tele-immersive platform. This application will allow us to identify structures and display polygonal representations from atlas data overlaid with the volume rendering. First, atlas data is automatically translated, rotated, and scaled to the patient data during loading using a public domain volumetric fusion algorithm. This generates a modified symbolic representation of the underlying canonical anatomy. Then, through the use of collision detection or intersection testing of various transparent polygonal representations, the polygonal structures are highlighted into the volumetric representation while the SNOMED names are displayed. Thus, structural names and polygonal models are associated with the visualized DICOM data. This novel juxtaposition of information promises to expand surgeons' abilities to interpret images and plan treatment.

Microwave and video sensor fusion for the shape extraction of 3D space objects

NASA Technical Reports Server (NTRS)

Shaw, Scott W.; Defigueiredo, Rui J. P.; Krishen, Kumar

1987-01-01

A new system for the fusion of optical image data and polarized radar scattering cross-sections is presented. By considering the scattering data in conjunction with image data, the problem of ambiguity can be reduced. Only a small part of the surface needs to be reconstructed from the radar cross-sections; the remaining portion is constrained by the optical image.

Radiological Source Localisation

DTIC Science & Technology

2007-07-01

activity. This algorithm was able to provide reasonable source estimates based on real data collected using the Low Cost Advanced Airborne...courses in Australia, Europe and the US. He is lecturing a post-graduate subject at Adelaide University (subject ”Multi-Sensor Data Fusion ”). He served on...technical committees of several international conferences, and is the Chair of the Fourth Australian Data Fusion Sym- posium (IDC-07). Dr Ristic won

Statistical Relational Learning (SRL) as an Enabling Technology for Data Acquisition and Data Fusion in Video

DTIC Science & Technology

2013-05-02

REPORT Statistical Relational Learning ( SRL ) as an Enabling Technology for Data Acquisition and Data Fusion in Video 14. ABSTRACT 16. SECURITY...particular, it is important to reason about which portions of video require expensive analysis and storage. This project aims to make these...inferences using new and existing tools from Statistical Relational Learning ( SRL ). SRL is a recently emerging technology that enables the effective 1

A flexible spatiotemporal method for fusing satellite images with different resolutions

Treesearch

Xiaolin Zhu; Eileen H. Helmer; Feng Gao; Desheng Liu; Jin Chen; Michael A. Lefsky

2016-01-01

Studies of land surface dynamics in heterogeneous landscapes often require remote sensing datawith high acquisition frequency and high spatial resolution. However, no single sensor meets this requirement. This study presents a new spatiotemporal data fusion method, the Flexible Spatiotemporal DAta Fusion (FSDAF) method, to generate synthesized frequent high spatial...

Construction and Resource Utilization Explorer (CRUX): Implementing Instrument Suite Data Fusion to Characterize Regolith Hydrogen Resources

NASA Technical Reports Server (NTRS)

Haldemann, Albert F. C.; Johnson, Jerome B.; Elphic, Richard C.; Boynton, William V.; Wetzel, John

2006-01-01

CRUX is a modular suite of geophysical and borehole instruments combined with display and decision support system (MapperDSS) tools to characterize regolith resources, surface conditions, and geotechnical properties. CRUX is a NASA-funded Technology Maturation Program effort to provide enabling technology for Lunar and Planetary Surface Operations (LPSO). The MapperDSS uses data fusion methods with CRUX instruments, and other available data and models, to provide regolith properties information needed for LPSO that cannot be determined otherwise. We demonstrate the data fusion method by showing how it might be applied to characterize the distribution and form of hydrogen using a selection of CRUX instruments: Borehole Neutron Probe and Thermal Evolved Gas Analyzer data as a function of depth help interpret Surface Neutron Probe data to generate 3D information. Secondary information from other instruments along with physical models improves the hydrogen distribution characterization, enabling information products for operational decision-making.

Developmental validation of the PowerPlex(®) Fusion 6C System.

PubMed

Ensenberger, Martin G; Lenz, Kristy A; Matthies, Learden K; Hadinoto, Gregory M; Schienman, John E; Przech, Angela J; Morganti, Michael W; Renstrom, Daniel T; Baker, Victoria M; Gawrys, Kori M; Hoogendoorn, Marlijn; Steffen, Carolyn R; Martín, Pablo; Alonso, Antonio; Olson, Hope R; Sprecher, Cynthia J; Storts, Douglas R

2016-03-01

The PowerPlex(®) Fusion 6C System is a 27-locus, six-dye, multiplex that includes all markers in the expanded CODIS core loci and increases overlap with STR database standards throughout the world. Additionally, it contains two, rapidly mutating, Y-STRs and is capable of both casework and database workflows, including direct amplification. A multi-laboratory developmental validation study was performed on the PowerPlex(®) Fusion 6C System. Here, we report the results of that study which followed SWGDAM guidelines and includes data for: species specificity, sensitivity, stability, precision, reproducibility and repeatability, case-type samples, concordance, stutter, DNA mixtures, and PCR-based procedures. Where appropriate we report data from both extracted DNA samples and direct amplification samples from various substrates and collection devices. Samples from all studies were separated on both Applied Biosystems 3500 series and 6-dye capable 3130 series Genetic Analyzers and data is reported for each. Together, the data validate the design and demonstrate the performance of the PowerPlex(®) Fusion 6C System. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Failure analysis of knee arthrodesis with the WichitaFusion Nail.

PubMed

Parcel, Ted W; Levering, Melissa; Polikandriotis, John A; Gustke, Kenneth A; Bernasek, Thomas L

2013-11-01

Arthrodesis is a salvage procedure for failed total knee arthroplasty with the intent to create a stable, pain-free limb on which to ambulate or transfer. For many patients, the alternative to arthrodesis may be an above-knee amputation. Available techniques for knee arthrodesis include compression plating, external fixators, and intramedullary fixation. The purpose of this study was to report the knee fusion rate of consecutive patients at 1 institution using an intramedullary fusion nail and to identify patient risk factors for fusion failure. Between November 1998 and November 2008, twenty-eight patients undergoing knee arthrodesis with an average follow-up of 18 months (range, 3-64 months) were retrospectively studied. Demographic information, presence of fusion, clinical function, pain level, and bone defect data were collected and analyzed. Eighty-two percent (23/28) of patients had radiographic evidence of successful fusion with an average time to fusion of 21 weeks (range, 10-58 weeks). When examining patient variables that could correlate with fusion rates, patients with an Anderson Orthopaedic Research Institute type 3 femoral or type 3 tibial defect had a statistically significant lower fusion rate. The intramedullary fusion nail is an effective device for knee arthrodesis that offers ease of insertion through the knee wound with the advantages of initial bone compression and rigid fixation. Although the use of intramedullary fusion nails leads to a high fusion rate, significant bone deficiency limits successful fusion. Copyright 2013, SLACK Incorporated.

Flexibility of the Head-Stalk Linker Domain of Paramyxovirus HN Glycoprotein Is Essential for Triggering Virus Fusion.

PubMed

Adu-Gyamfi, Emmanuel; Kim, Lori S; Jardetzky, Theodore S; Lamb, Robert A

2016-10-15

The Paramyxoviridae comprise a large family of enveloped, negative-sense, single-stranded RNA viruses with significant economic and public health implications. For nearly all paramyxoviruses, infection is initiated by fusion of the viral and host cell plasma membranes in a pH-independent fashion. Fusion is orchestrated by the receptor binding protein hemagglutinin-neuraminidase (HN; also called H or G depending on the virus type) protein and a fusion (F) protein, the latter undergoing a major refolding process to merge the two membranes. Mechanistic details regarding the coupling of receptor binding to F activation are not fully understood. Here, we have identified the flexible loop region connecting the bulky enzymatically active head and the four-helix bundle stalk to be essential for fusion promotion. Proline substitution in this region of HN of parainfluenza virus 5 (PIV5) and Newcastle disease virus HN abolishes cell-cell fusion, whereas HN retains receptor binding and neuraminidase activity. By using reverse genetics, we engineered recombinant PIV5-EGFP viruses with mutations in the head-stalk linker region of HN. Mutations in this region abolished virus recovery and infectivity. In sum, our data suggest that the loop region acts as a "hinge" around which the bulky head of HN swings to-and-fro to facilitate timely HN-mediate F-triggering, a notion consistent with the stalk-mediated activation model of paramyxovirus fusion. Paramyxovirus fusion with the host cell plasma membrane is essential for virus infection. Membrane fusion is orchestrated via interaction of the receptor binding protein (HN, H, or G) with the viral fusion glycoprotein (F). Two distinct models have been suggested to describe the mechanism of fusion: these include "the clamp" and the "provocateur" model of activation. By using biochemical and reverse genetics tools, we have obtained strong evidence in favor of the HN stalk-mediated activation of paramyxovirus fusion. Specifically, our data strongly support the notion that the short linker between the head and stalk plays a role in "conformational switching" of the head group to facilitate F-HN interaction and triggering. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Flexibility of the Head-Stalk Linker Domain of Paramyxovirus HN Glycoprotein Is Essential for Triggering Virus Fusion

PubMed Central

Adu-Gyamfi, Emmanuel; Kim, Lori S.; Jardetzky, Theodore S.

2016-01-01

ABSTRACT The Paramyxoviridae comprise a large family of enveloped, negative-sense, single-stranded RNA viruses with significant economic and public health implications. For nearly all paramyxoviruses, infection is initiated by fusion of the viral and host cell plasma membranes in a pH-independent fashion. Fusion is orchestrated by the receptor binding protein hemagglutinin-neuraminidase (HN; also called H or G depending on the virus type) protein and a fusion (F) protein, the latter undergoing a major refolding process to merge the two membranes. Mechanistic details regarding the coupling of receptor binding to F activation are not fully understood. Here, we have identified the flexible loop region connecting the bulky enzymatically active head and the four-helix bundle stalk to be essential for fusion promotion. Proline substitution in this region of HN of parainfluenza virus 5 (PIV5) and Newcastle disease virus HN abolishes cell-cell fusion, whereas HN retains receptor binding and neuraminidase activity. By using reverse genetics, we engineered recombinant PIV5-EGFP viruses with mutations in the head-stalk linker region of HN. Mutations in this region abolished virus recovery and infectivity. In sum, our data suggest that the loop region acts as a “hinge” around which the bulky head of HN swings to-and-fro to facilitate timely HN-mediate F-triggering, a notion consistent with the stalk-mediated activation model of paramyxovirus fusion. IMPORTANCE Paramyxovirus fusion with the host cell plasma membrane is essential for virus infection. Membrane fusion is orchestrated via interaction of the receptor binding protein (HN, H, or G) with the viral fusion glycoprotein (F). Two distinct models have been suggested to describe the mechanism of fusion: these include “the clamp” and the “provocateur” model of activation. By using biochemical and reverse genetics tools, we have obtained strong evidence in favor of the HN stalk-mediated activation of paramyxovirus fusion. Specifically, our data strongly support the notion that the short linker between the head and stalk plays a role in “conformational switching” of the head group to facilitate F-HN interaction and triggering. PMID:27489276

Quality evaluation of different fusion techniques applied on Worldview-2 data

NASA Astrophysics Data System (ADS)

Vaiopoulos, Aristides; Nikolakopoulos, Konstantinos G.

2015-10-01

In the current study a Worldview-2 image was used for fusion quality assessment. The bundle image was collected on July 2014 over Araxos area in Western Peloponnese. Worldview-2 is the first satellite that collects at the same time a panchromatic (Pan) image and 8 band multispectral (MS) image. The Pan data have a spatial resolution of 0.46m while the MS data have a spatial resolution of 1.84m. In contrary to the respective Pan band of Ikonos and Quickbird that range between 0.45 and 0.90 micrometers the Worldview Pan band is narrower and ranges between 0.45 and 0.8 micrometers. The MS bands include four conventional visible and near-infrared bands common to multispectral satellites like Ikonos Quickbird, Geoeye Landsat-7 etc., and four new bands. Thus, it is quite interesting to investigate the assessment of commonly used fusion algorithms with Worldview-2 data. Twelve fusion techniques and more especially the Ehlers, Gram-Schmidt, Color Normalized, High Pass Filter, Hyperspherical Color Space, Local Mean Matching (LMM), Local Mean and Variance Matching (LMVM), Modified IHS (ModIHS), Pansharp, Pansharp2, PCA and Wavelet were used for the fusion of Worldview-2 panchromatic and multispectral data. The optical result, the statistical parameters and different quality indexes such as ERGAS, Q and entropy difference were examined and the results are presented. The quality control was evaluated both in spectral and spatial domain.

confFuse: High-Confidence Fusion Gene Detection across Tumor Entities.

PubMed

Huang, Zhiqin; Jones, David T W; Wu, Yonghe; Lichter, Peter; Zapatka, Marc

2017-01-01

Background: Fusion genes play an important role in the tumorigenesis of many cancers. Next-generation sequencing (NGS) technologies have been successfully applied in fusion gene detection for the last several years, and a number of NGS-based tools have been developed for identifying fusion genes during this period. Most fusion gene detection tools based on RNA-seq data report a large number of candidates (mostly false positives), making it hard to prioritize candidates for experimental validation and further analysis. Selection of reliable fusion genes for downstream analysis becomes very important in cancer research. We therefore developed confFuse, a scoring algorithm to reliably select high-confidence fusion genes which are likely to be biologically relevant. Results: confFuse takes multiple parameters into account in order to assign each fusion candidate a confidence score, of which score ≥8 indicates high-confidence fusion gene predictions. These parameters were manually curated based on our experience and on certain structural motifs of fusion genes. Compared with alternative tools, based on 96 published RNA-seq samples from different tumor entities, our method can significantly reduce the number of fusion candidates (301 high-confidence from 8,083 total predicted fusion genes) and keep high detection accuracy (recovery rate 85.7%). Validation of 18 novel, high-confidence fusions detected in three breast tumor samples resulted in a 100% validation rate. Conclusions: confFuse is a novel downstream filtering method that allows selection of highly reliable fusion gene candidates for further downstream analysis and experimental validations. confFuse is available at https://github.com/Zhiqin-HUANG/confFuse.

Temperature characteristics of fusion splicing Hollow Core Photonic Crystal Fiber by sinusoidal modulation CO2 laser

NASA Astrophysics Data System (ADS)

Fu, Guangwei; Li, Kuixing; Fu, Xinghu; Bi, Weihong

2013-07-01

During the fusion splicing Hollow Core Photonic Crystal Fiber (HC-PCF), the air-holes collapse easily due to the improper fusion duration time and optical power. To analyze the temperature characteristics of fusion splicing HC-PCF, a heating method by sinusoidal modulation CO2 laser has been proposed. In the sinusoidal modulation, the variation relationships among laser power, temperature difference and angular frequency are analyzed. The results show that the theoretical simulation is basically in accordance with the experimental data. Therefore, a low-loss fusion splicing can be achieved by modulating the CO2 laser frequency to avoid the air-holes collapse of HC-PCF. Further, the errors are also given.

New results in low-energy fusion of Ca 40 + Zr 90 , 92

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

Stefanini, A. M.; Montagnoli, G.; Esbensen, H.

Near- and sub-barrier fusion of various Ca + Zr isotopic combinations have been widely investigated. A recent analysis of 40Ca + 96Zr data has highlighted the importance of couplings to multiphonon excitations and to both neutron and proton transfer channels. Analogous studies of 40Ca + 90Zr tend to exclude any role of transfer couplings. However, the lowest measured cross section for this system is rather high (840μb). Here, a rather complete data set is available for 40Ca + 94Zr, while no measurement of 40Ca + 92Zr fusion has been performed in the past.

New results in low-energy fusion of Ca 40 + Zr 90 , 92

DOE PAGES

Stefanini, A. M.; Montagnoli, G.; Esbensen, H.; ...

2017-07-07

Near- and sub-barrier fusion of various Ca + Zr isotopic combinations have been widely investigated. A recent analysis of 40Ca + 96Zr data has highlighted the importance of couplings to multiphonon excitations and to both neutron and proton transfer channels. Analogous studies of 40Ca + 90Zr tend to exclude any role of transfer couplings. However, the lowest measured cross section for this system is rather high (840μb). Here, a rather complete data set is available for 40Ca + 94Zr, while no measurement of 40Ca + 92Zr fusion has been performed in the past.

Concordance of preclinical and clinical pharmacology and toxicology of therapeutic monoclonal antibodies and fusion proteins: cell surface targets

PubMed Central

Bugelski, Peter J; Martin, Pauline L

2012-01-01

Monoclonal antibodies (mAbs) and fusion proteins directed towards cell surface targets make an important contribution to the treatment of disease. The purpose of this review was to correlate the clinical and preclinical data on the 15 currently approved mAbs and fusion proteins targeted to the cell surface. The principal sources used to gather data were: the peer reviewed Literature; European Medicines Agency ‘Scientific Discussions’; and the US Food and Drug Administration ‘Pharmacology/Toxicology Reviews’ and package inserts (United States Prescribing Information). Data on the 15 approved biopharmaceuticals were included: abatacept; abciximab; alefacept; alemtuzumab; basiliximab; cetuximab; daclizumab; efalizumab; ipilimumab; muromonab; natalizumab; panitumumab; rituximab; tocilizumab; and trastuzumab. For statistical analysis of concordance, data from these 15 were combined with data on the approved mAbs and fusion proteins directed towards soluble targets. Good concordance with human pharmacodynamics was found for mice receiving surrogates or non-human primates (NHPs) receiving the human pharmaceutical. In contrast, there was poor concordance for human pharmacodynamics in genetically deficient mice and for human adverse effects in all three test systems. No evidence that NHPs have superior predictive value was found. PMID:22168282

[Fusion of MRI, fMRI and intraoperative MRI data. Methods and clinical significance exemplified by neurosurgical interventions].

PubMed

Moche, M; Busse, H; Dannenberg, C; Schulz, T; Schmitgen, A; Trantakis, C; Winkler, D; Schmidt, F; Kahn, T

2001-11-01

The aim of this work was to realize and clinically evaluate an image fusion platform for the integration of preoperative MRI and fMRI data into the intraoperative images of an interventional MRI system with a focus on neurosurgical procedures. A vertically open 0.5 T MRI scanner was equipped with a dedicated navigation system enabling the registration of additional imaging modalities (MRI, fMRI, CT) with the intraoperatively acquired data sets. These merged image data served as the basis for interventional planning and multimodal navigation. So far, the system has been used in 70 neurosurgical interventions (13 of which involved image data fusion--requiring 15 minutes extra time). The augmented navigation system is characterized by a higher frame rate and a higher image quality as compared to the system-integrated navigation based on continuously acquired (near) real time images. Patient movement and tissue shifts can be immediately detected by monitoring the morphological differences between both navigation scenes. The multimodal image fusion allowed a refined navigation planning especially for the resection of deeply seated brain lesions or pathologies close to eloquent areas. Augmented intraoperative orientation and instrument guidance improve the safety and accuracy of neurosurgical interventions.

Wide diversity of PAX5 alterations in B-ALL: a Groupe Francophone de Cytogenetique Hematologique study.

PubMed

Coyaud, Etienne; Struski, Stephanie; Prade, Nais; Familiades, Julien; Eichner, Ruth; Quelen, Cathy; Bousquet, Marina; Mugneret, Francine; Talmant, Pascaline; Pages, Marie-Pierre; Lefebvre, Christine; Penther, Dominique; Lippert, Eric; Nadal, Nathalie; Taviaux, Sylvie; Poppe, Bruce; Luquet, Isabelle; Baranger, Laurence; Eclache, Virginie; Radford, Isabelle; Barin, Carole; Mozziconacci, Marie-Joëlle; Lafage-Pochitaloff, Marina; Antoine-Poirel, Hélène; Charrin, Christiane; Perot, Christine; Terre, Christine; Brousset, Pierre; Dastugue, Nicole; Broccardo, Cyril

2010-04-15

PAX5 is the main target of somatic mutations in acute B lymphoblastic leukemia (B-ALL). We analyzed 153 adult and child B-ALL harboring karyotypic abnormalities at chromosome 9p, to determine the frequency and the nature of PAX5 alterations. We found PAX5 internal rearrangements in 21% of the cases. To isolate fusion partners, we used classic and innovative techniques (rolling circle amplification-rapid amplification of cDNA ends) and single nucleotide polymorphism-comparative genomic hybridization arrays. Recurrent and novel fusion partners were identified, including NCoR1, DACH2, GOLGA6, and TAOK1 genes showing the high variability of the partners. We noted that half the fusion genes can give rise to truncated PAX5 proteins. Furthermore, malignant cells carrying PAX5 fusion genes displayed a simple karyotype. These data strongly suggest that PAX5 fusion genes are early players in leukemogenesis. In addition, PAX5 deletion was observed in 60% of B-ALL with 9p alterations. Contrary to cases with PAX5 fusions, deletions were associated with complex karyotypes and common recurrent translocations. This supports the hypothesis of the secondary nature of the deletion. Our data shed more light on the high variability of PAX5 alterations in B-ALL. Therefore, it is probable that gene fusions occur early, whereas deletions should be regarded as a late/secondary event.

A joint FED watermarking system using spatial fusion for verifying the security issues of teleradiology.

PubMed

Viswanathan, P; Krishna, P Venkata

2014-05-01

Teleradiology allows transmission of medical images for clinical data interpretation to provide improved e-health care access, delivery, and standards. The remote transmission raises various ethical and legal issues like image retention, fraud, privacy, malpractice liability, etc. A joint FED watermarking system means a joint fingerprint/encryption/dual watermarking system is proposed for addressing these issues. The system combines a region based substitution dual watermarking algorithm using spatial fusion, stream cipher algorithm using symmetric key, and fingerprint verification algorithm using invariants. This paper aims to give access to the outcomes of medical images with confidentiality, availability, integrity, and its origin. The watermarking, encryption, and fingerprint enrollment are conducted jointly in protection stage such that the extraction, decryption, and verification can be applied independently. The dual watermarking system, introducing two different embedding schemes, one used for patient data and other for fingerprint features, reduces the difficulty in maintenance of multiple documents like authentication data, personnel and diagnosis data, and medical images. The spatial fusion algorithm, which determines the region of embedding using threshold from the image to embed the encrypted patient data, follows the exact rules of fusion resulting in better quality than other fusion techniques. The four step stream cipher algorithm using symmetric key for encrypting the patient data with fingerprint verification system using algebraic invariants improves the robustness of the medical information. The experiment result of proposed scheme is evaluated for security and quality analysis in DICOM medical images resulted well in terms of attacks, quality index, and imperceptibility.

Registration and Fusion of Multiple Source Remotely Sensed Image Data

NASA Technical Reports Server (NTRS)

LeMoigne, Jacqueline

2004-01-01

Earth and Space Science often involve the comparison, fusion, and integration of multiple types of remotely sensed data at various temporal, radiometric, and spatial resolutions. Results of this integration may be utilized for global change analysis, global coverage of an area at multiple resolutions, map updating or validation of new instruments, as well as integration of data provided by multiple instruments carried on multiple platforms, e.g. in spacecraft constellations or fleets of planetary rovers. Our focus is on developing methods to perform fast, accurate and automatic image registration and fusion. General methods for automatic image registration are being reviewed and evaluated. Various choices for feature extraction, feature matching and similarity measurements are being compared, including wavelet-based algorithms, mutual information and statistically robust techniques. Our work also involves studies related to image fusion and investigates dimension reduction and co-kriging for application-dependent fusion. All methods are being tested using several multi-sensor datasets, acquired at EOS Core Sites, and including multiple sensors such as IKONOS, Landsat-7/ETM+, EO1/ALI and Hyperion, MODIS, and SeaWIFS instruments. Issues related to the coregistration of data from the same platform (i.e., AIRS and MODIS from Aqua) or from several platforms of the A-train (i.e., MLS, HIRDLS, OMI from Aura with AIRS and MODIS from Terra and Aqua) will also be considered.

Histology, Fusion Status, and Outcome in Alveolar Rhabdomyosarcoma With Low-Risk Clinical Features: A Report From the Children's Oncology Group.

PubMed

Arnold, Michael A; Anderson, James R; Gastier-Foster, Julie M; Barr, Frederic G; Skapek, Stephen X; Hawkins, Douglas S; Raney, R Beverly; Parham, David M; Teot, Lisa A; Rudzinski, Erin R; Walterhouse, David O

2016-04-01

Distinguishing alveolar rhabdomyosarcoma (ARMS) from embryonal rhabdomyosarcoma (ERMS) is of prognostic and therapeutic importance. Criteria for classifying these entities evolved significantly from 1995 to 2013. ARMS is associated with inferior outcome; therefore, patients with alveolar histology have generally been excluded from low-risk therapy. However, patients with ARMS and low-risk stage and group (Stage 1, Group I/II/orbit III; or Stage 2/3, Group I/II) were eligible for the Children's Oncology Group (COG) low-risk rhabdomyosarcoma (RMS) study D9602 from 1997 to 1999. The characteristics and outcomes of these patients have not been previously reported, and the histology of these cases has not been reviewed using current criteria. We re-reviewed cases that were classified as ARMS on D9602 using current histologic criteria, determined PAX3/PAX7-FOXO1 fusion status, and compared these data with outcome for this unique group of patients. Thirty-eight patients with ARMS were enrolled onto D9602. Only one-third of cases with slides available for re-review (11/33) remained classified as ARMS by current histologic criteria. Most cases were reclassified as ERMS (17/33, 51.5%). Cases that remained classified as ARMS were typically fusion-positive (8/11, 73%), therefore current classification results in a similar rate of fusion-positive ARMS for all clinical risk groups. In conjunction with data from COG intermediate-risk treatment protocol D9803, our data demonstrate excellent outcomes for fusion-negative ARMS with otherwise low-risk clinical features. Patients with fusion-positive RMS with low-risk clinical features should be classified and treated as intermediate risk, while patients with fusion-negative ARMS could be appropriately treated with reduced intensity therapy. © 2016 Wiley Periodicals, Inc.

Epidemiologic and Economic Burden Attributable to First Spinal Fusion Surgery: Analysis From an Italian Administrative Database.

PubMed

Cortesi, Paolo A; Assietti, Roberto; Cuzzocrea, Fabrizio; Prestamburgo, Domenico; Pluderi, Mauro; Cozzolino, Paolo; Tito, Patrizia; Vanelli, Roberto; Cecconi, Davide; Borsa, Stefano; Cesana, Giancarlo; Mantovani, Lorenzo G

2017-09-15

Retrospective large population based-study. Assessment of the epidemiologic trends and economic burden of first spinal fusions. No adequate data are available regarding the epidemiology of spinal fusion surgery and its economic impact in Europe. The study population was identified through a data warehouse (DENALI), which matches clinical and economic data of different Healthcare Administrative databases of the Italian Lombardy Region. The study population consisted of all subjects, resident in Lombardy, who, during the period January 2001 to December 2010, underwent spinal fusion surgery (ICD-9-CM codes: 81.04, 81.05, 81.06, 81.07, and 81.08). The first procedure was used as the index event. We estimated the incidence of first spinal fusion surgery, the population and surgery characteristics and the healthcare costs from the National Health Service's perspective. The analysis was performed for the entire population and divided into the main groups of diagnosis. The analysis identified 17,772 [mean age (SD): 54.6 (14.5) years, 55.3% females] spinal fusion surgeries. Almost 67% of the patients suffered from a lumbar degenerative disease. The incidence rate of interventions increased from 11.5 to 18.5 per 100,000 person-year between 2001 and 2006, and was above 20.0 per 100,000 person-year in the last 4 years. The patients' mean age increased during the observational time period from 48.1 to 55.9 years; whereas the median hospital length of stay reported for the index event decreased. The average cost of the spinal fusion surgery increased during the observational period, from &OV0556; 4726 up to &OV0556; 9388. The study showed an increasing incidence of spinal fusion surgery and costs from 2001 to 2010. These results can be used to better understand the epidemiological and economic burden of these interventions, and help to optimize the resources available considering the different clinical approaches accessible today. 4.

Sensor fusion for antipersonnel landmine detection: a case study

NASA Astrophysics Data System (ADS)

den Breejen, Eric; Schutte, Klamer; Cremer, Frank

1999-08-01

In this paper the multi sensor fusion results obtained within the European research project GEODE are presented. The layout of the test lane and the individual sensors used are described. The implementation of the SCOOP algorithm improves the ROC curves, as the false alarm surface and the number of false alarms both are taken into account. The confidence grids, as produced by the sensor manufacturers, of the sensors are used as input for the different sensor fusion methods implemented. The multisensor fusion methods implemented are Bayes, Dempster-Shafer, fuzzy probabilities and rules. The mapping of the confidence grids to the input parameters for fusion methods is an important step. Due to limited amount of the available data the entire test lane is used for training and evaluation. All four sensor fusion methods provide better detection results than the individual sensors.

Exploring incomplete fusion fraction in 6,7Li induced nuclear reactions

NASA Astrophysics Data System (ADS)

Parkar, V. V.; Jha, V.; Kailas, S.

2017-11-01

We have included breakup effects explicitly to simultaneously calculate the measured cross-sections of the complete fusion, incomplete fusion, and total fusion for 6,7Li projectiles on various targets using the Continuum Discretized Coupled Channels method. The breakup absorption cross-sections obtained with different choices of short range imaginary potentials are utilized to evaluate the individual α-capture and d/t-capture cross-sections and compare with the measured data. It is interesting to note, while in case of 7Li projectile the cross-sections for triton-ICF/triton-capture is far more dominant than α-ICF/α-capture at all energies, similar behavior is not observed in case of 6Li projectile for the deuteron-ICF/deuteron-capture and α-ICF/α-capture. Both these observations are also corroborated by the experimental data for all the systems studied.

Practical considerations in Bayesian fusion of point sensors

NASA Astrophysics Data System (ADS)

Johnson, Kevin; Minor, Christian

2012-06-01

Sensor data fusion is and has been a topic of considerable research, but rigorous and quantitative understanding of the benefits of fusing specific types of sensor data remains elusive. Often, sensor fusion is performed on an ad hoc basis with the assumption that overall detection capabilities will improve, only to discover later, after expensive and time consuming laboratory and/or field testing that little advantage was gained. The work presented here will discuss these issues with theoretical and practical considerations in the context of fusing chemical sensors with binary outputs. Results are given for the potential performance gains one could expect with such systems, as well as the practical difficulties involved in implementing an optimal Bayesian fusion strategy with realistic scenarios. Finally, a discussion of the biases that inaccurate statistical estimates introduce into the results and their consequences is presented.

A practical approach for active camera coordination based on a fusion-driven multi-agent system

NASA Astrophysics Data System (ADS)

Bustamante, Alvaro Luis; Molina, José M.; Patricio, Miguel A.

2014-04-01

In this paper, we propose a multi-agent system architecture to manage spatially distributed active (or pan-tilt-zoom) cameras. Traditional video surveillance algorithms are of no use for active cameras, and we have to look at different approaches. Such multi-sensor surveillance systems have to be designed to solve two related problems: data fusion and coordinated sensor-task management. Generally, architectures proposed for the coordinated operation of multiple cameras are based on the centralisation of management decisions at the fusion centre. However, the existence of intelligent sensors capable of decision making brings with it the possibility of conceiving alternative decentralised architectures. This problem is approached by means of a MAS, integrating data fusion as an integral part of the architecture for distributed coordination purposes. This paper presents the MAS architecture and system agents.

Screening effects on 12C+12C fusion reaction

NASA Astrophysics Data System (ADS)

Koyuncu, F.; Soylu, A.

2018-05-01

One of the important reactions for nucleosynthesis in the carbon burning phase in high-mass stars is the 12C+12C fusion reaction. In this study, we investigate the influences of the nuclear potentials and screening effect on astrophysically interesting 12C+12C fusion reaction observables at sub-barrier energies by using the microscopic α–α double folding cluster (DFC) potential and the proximity potential. In order to model the screening effects on the experimental data, a more general exponential cosine screened Coulomb (MGECSC) potential including Debye and quantum plasma cases has been considered in the calculations for the 12C+12C fusion reaction. In the calculations of the reaction observables, the semi-classical Wentzel-Kramers-Brillouin (WKB) approach and coupled channel (CC) formalism have been used. Moreover, in order to investigate how the potentials between 12C nuclei produce molecular cluster states of 24Mg, the normalized resonant energy states of 24Mg cluster bands have been calculated for the DFC potential. By analyzing the results produced from the fusion of 12C+12C, it is found that taking into account the screening effects in terms of MGECSC is important for explaining the 12C+12C fusion data, and the microscopic DFC potential is better than the proximity potential in explaining the experimental data, also considering that clustering is dominant for the structure of the 24Mg nucleus. Supported by the Turkish Science and Research Council (TÜBİTAK) with (117R015)

Statistical rice yield modeling using blended MODIS-Landsat based crop phenology metrics in Taiwan

NASA Astrophysics Data System (ADS)

Chen, C. R.; Chen, C. F.; Nguyen, S. T.; Lau, K. V.

2015-12-01

Taiwan is a populated island with a majority of residents settled in the western plains where soils are suitable for rice cultivation. Rice is not only the most important commodity, but also plays a critical role for agricultural and food marketing. Information of rice production is thus important for policymakers to devise timely plans for ensuring sustainably socioeconomic development. Because rice fields in Taiwan are generally small and yet crop monitoring requires information of crop phenology associating with the spatiotemporal resolution of satellite data, this study used Landsat-MODIS fusion data for rice yield modeling in Taiwan. We processed the data for the first crop (Feb-Mar to Jun-Jul) and the second (Aug-Sep to Nov-Dec) in 2014 through five main steps: (1) data pre-processing to account for geometric and radiometric errors of Landsat data, (2) Landsat-MODIS data fusion using using the spatial-temporal adaptive reflectance fusion model, (3) construction of the smooth time-series enhanced vegetation index 2 (EVI2), (4) rice yield modeling using EVI2-based crop phenology metrics, and (5) error verification. The fusion results by a comparison bewteen EVI2 derived from the fusion image and that from the reference Landsat image indicated close agreement between the two datasets (R2 > 0.8). We analysed smooth EVI2 curves to extract phenology metrics or phenological variables for establishment of rice yield models. The results indicated that the established yield models significantly explained more than 70% variability in the data (p-value < 0.001). The comparison results between the estimated yields and the government's yield statistics for the first and second crops indicated a close significant relationship between the two datasets (R2 > 0.8), in both cases. The root mean square error (RMSE) and mean absolute error (MAE) used to measure the model accuracy revealed the consistency between the estimated yields and the government's yield statistics. This study demonstrates advantages of using EVI2-based phenology metrics (derived from Landsat-MODIS fusion data) for rice yield estimation in Taiwan prior to the harvest period.

Myogenin, AP2β, NOS-1, and HMGA2 are surrogate markers of fusion status in rhabdomyosarcoma: a report from the soft tissue sarcoma committee of the children's oncology group.

PubMed

Rudzinski, Erin R; Anderson, James R; Lyden, Elizabeth R; Bridge, Julia A; Barr, Frederic G; Gastier-Foster, Julie M; Bachmeyer, Karen; Skapek, Stephen X; Hawkins, Douglas S; Teot, Lisa A; Parham, David M

2014-05-01

Pediatric rhabdomyosarcoma (RMS) is traditionally classified on the basis of the histologic appearance into alveolar (ARMS) and embryonal (ERMS) subtypes. The majority of ARMS contain a PAX3-FOXO1 or PAX7-FOXO1 gene fusion, but about 20% do not. Intergroup Rhabdomyosarcoma Study stage-matched and group-matched ARMS typically behaves more aggressively than ERMS, but recent studies have shown that it is, in fact, the fusion status that drives the outcome for RMS. Gene expression microarray data indicate that several genes discriminate between fusion-positive and fusion-negative RMS with high specificity. Using tissue microarrays containing a series of both ARMS and ERMS, we identified a panel of 4 immunohistochemical markers-myogenin, AP2β, NOS-1, and HMGA2-which can be used as surrogate markers of fusion status in RMS. These antibodies provide an alternative to molecular methods for identification of fusion-positive RMS, particularly in cases in which there is scant or poor-quality material. In addition, these antibodies may be useful in fusion-negative ARMS as an indicator that a variant gene fusion may be present.

Cell fusion in the liver, revisited

PubMed Central

Lizier, Michela; Castelli, Alessandra; Montagna, Cristina; Lucchini, Franco; Vezzoni, Paolo; Faggioli, Francesca

2018-01-01

There is wide agreement that cell fusion is a physiological process in cells in mammalian bone, muscle and placenta. In other organs, such as the cerebellum, cell fusion is controversial. The liver contains a considerable number of polyploid cells: They are commonly believed to originate by genome endoreplication, although the contribution of cell fusion to polyploidization has not been excluded. Here, we address the topic of cell fusion in the liver from a historical point of view. We discuss experimental evidence clearly supporting the hypothesis that cell fusion occurs in the liver, specifically when bone marrow cells were injected into mice and shown to rescue genetic hepatic degenerative defects. Those experiments-carried out in the latter half of the last century-were initially interpreted to show “transdifferentiation”, but are now believed to demonstrate fusion between donor macrophages and host hepatocytes, raising the possibility that physiologically polyploid cells, such as hepatocytes, could originate, at least partially, through homotypic cell fusion. In support of the homotypic cell fusion hypothesis, we present new data generated using a chimera-based model, a much simpler model than those previously used. Cell fusion as a road to polyploidization in the liver has not been extensively investigated, and its contribution to a variety of conditions, such as viral infections, carcinogenesis and aging, remains unclear. PMID:29527257

Sensor Data Fusion with Z-Numbers and Its Application in Fault Diagnosis

PubMed Central

Jiang, Wen; Xie, Chunhe; Zhuang, Miaoyan; Shou, Yehang; Tang, Yongchuan

2016-01-01

Sensor data fusion technology is widely employed in fault diagnosis. The information in a sensor data fusion system is characterized by not only fuzziness, but also partial reliability. Uncertain information of sensors, including randomness, fuzziness, etc., has been extensively studied recently. However, the reliability of a sensor is often overlooked or cannot be analyzed adequately. A Z-number, Z = (A, B), can represent the fuzziness and the reliability of information simultaneously, where the first component A represents a fuzzy restriction on the values of uncertain variables and the second component B is a measure of the reliability of A. In order to model and process the uncertainties in a sensor data fusion system reasonably, in this paper, a novel method combining the Z-number and Dempster–Shafer (D-S) evidence theory is proposed, where the Z-number is used to model the fuzziness and reliability of the sensor data and the D-S evidence theory is used to fuse the uncertain information of Z-numbers. The main advantages of the proposed method are that it provides a more robust measure of reliability to the sensor data, and the complementary information of multi-sensors reduces the uncertainty of the fault recognition, thus enhancing the reliability of fault detection. PMID:27649193

Assessing tropical rainforest growth traits: Data - Model fusion in the Congo basin and beyond

NASA Astrophysics Data System (ADS)

Pietsch, Stephan

2017-04-01

Virgin forest ecosystems resemble the key reference level for natural tree growth dynamics. The mosaic cycle concept describes such dynamics as local disequilibria driven by patch level succession cycles of breakdown, regeneration, juvenescence and old growth. These cycles, however, may involve different traits of light demanding and shade tolerant species assemblies. In this work a data model fusion concept will be introduced to assess the differences in growth dynamics of the mosaic cycle of the Western Congolian Lowland Rainforest ecosystem. Field data from 34 forest patches located in an ice age forest refuge, recently pinpointed to the ground and still devoid of direct human impact up to today - resemble the data base. A 3D error assessment procedure versus BGC model simulations for the 34 patches revealed two different growth dynamics, consistent with observed growth traits of pioneer and late succession species assemblies of the Western Congolian Lowland rainforest. An application of the same procedure to Central American Pacific rainforests confirms the strength of the 3D error field data model fusion concept to Central American Pacific rainforests confirms the strength of the 3D error field data model fusion concept to assess different growth traits of the mosaic cycle of natural forest dynamics.

A trainable decisions-in decision-out (DEI-DEO) fusion system

NASA Astrophysics Data System (ADS)

Dasarathy, Belur V.

1998-03-01

Most of the decision fusion systems proposed hitherto in the literature for multiple data source (sensor) environments operate on the basis of pre-defined fusion logic, be they crisp (deterministic), probabilistic, or fuzzy in nature, with no specific learning phase. The fusion systems that are trainable, i.e., ones that have a learning phase, mostly operate in the features-in-decision-out mode, which essentially reduces the fusion process functionally to a pattern classification task in the joint feature space. In this study, a trainable decisions-in-decision-out fusion system is described which estimates a fuzzy membership distribution spread across the different decision choices based on the performance of the different decision processors (sensors) corresponding to each training sample (object) which is associated with a specific ground truth (true decision). Based on a multi-decision space histogram analysis of the performance of the different processors over the entire training data set, a look-up table associating each cell of the histogram with a specific true decision is generated which forms the basis for the operational phase. In the operational phase, for each set of decision inputs, a pointer to the look-up table learnt previously is generated from which a fused decision is derived. This methodology, although primarily designed for fusing crisp decisions from the multiple decision sources, can be adapted for fusion of fuzzy decisions as well if such are the inputs from these sources. Examples, which illustrate the benefits and limitations of the crisp and fuzzy versions of the trainable fusion systems, are also included.

Simulated Radioscapholunate Fusion Alters Carpal Kinematics While Preserving Dart-Thrower's Motion

PubMed Central

Calfee, Ryan P.; Leventhal, Evan L.; Wilkerson, Jim; Moore, Douglas C.; Akelman, Edward; Crisco, Joseph J.

2014-01-01

Purpose Midcarpal degeneration is well documented after radioscapholunate fusion. This study tested the hypothesis that radioscapholunate fusion alters the kinematic behavior of the remaining lunotriquetral and midcarpal joints, with specific focus on the dart-thrower's motion. Methods Simulated radioscapholunate fusions were performed on 6 cadaveric wrists in an anatomically neutral posture. Two 0.060-in. carbon fiber pins were placed from proximal to distal across the radiolunate and radioscaphoid joints, respectively. The wrists were passively positioned in a custom jig toward a full range of motion along the orthogonal axes as well as oblique motions, with additional intermediate positions along the dart-thrower's path. Using a computed tomography– based markerless bone registration technique, each carpal bone's three-dimensional rotation was defined as a function of wrist flexion/extension from the pinned neutral position. Kinematic data was analyzed against data collected on the same wrist prior to fixation using hierarchical linear regression analysis and paired Student's t-tests. Results After simulated fusion, wrist motion was restricted to an average flexion-extension arc of 48°, reduced from 77°, and radial-ulnar deviation arc of 19°, reduced from 33°. The remaining motion was maximally preserved along the dart-thrower's path from radial-extension toward ulnar-flexion. The simulated fusion significantly increased rotation through the scaphotrapezial joint, scaphocapitate joint, triquetrohamate joint, and lunotriquetral joint. For example, in the pinned wrist, the rotation of the hamate relative to the triquetrum increased 85%. Therefore, during every 10° of total wrist motion, the hamate rotated an average of nearly 8° relative to the triquetrum after pinning versus 4° in the normal state. Conclusions Simulated radioscapholunate fusion altered midcarpal and lunotriquetral kinematics. The increased rotations across these remaining joints provide one potential explanation for midcarpal degeneration after radioscapholunate fusion. Additionally, this fusion model confirms the dart-thrower's hypothesis, as wrist motion after simulated radioscapholunate fusion was primarily preserved from radial-extension toward ulnar-flexion. PMID:18406953

Prostate cancer risk regions at 8q24 and 17q24 are differentially associated with somatic TMPRSS2:ERG fusion status

PubMed Central

Luedeke, Manuel; Rinckleb, Antje E.; FitzGerald, Liesel M.; Geybels, Milan S.; Schleutker, Johanna; Eeles, Rosalind A.; Teixeira, Manuel R.; Cannon-Albright, Lisa; Ostrander, Elaine A.; Weikert, Steffen; Herkommer, Kathleen; Wahlfors, Tiina; Visakorpi, Tapio; Leinonen, Katri A.; Tammela, Teuvo L.J.; Cooper, Colin S.; Kote-Jarai, Zsofia; Edwards, Sandra; Goh, Chee L.; McCarthy, Frank; Parker, Chris; Flohr, Penny; Paulo, Paula; Jerónimo, Carmen; Henrique, Rui; Krause, Hans; Wach, Sven; Lieb, Verena; Rau, Tilman T.; Vogel, Walther; Kuefer, Rainer; Hofer, Matthias D.; Perner, Sven; Rubin, Mark A.; Agarwal, Archana M.; Easton, Doug F.; Al Olama, Ali Amin; Benlloch, Sara; Hoegel, Josef; Stanford, Janet L.

2016-01-01

Abstract Molecular and epidemiological differences have been described between TMPRSS2:ERG fusion-positive and fusion-negative prostate cancer (PrCa). Assuming two molecularly distinct subtypes, we have examined 27 common PrCa risk variants, previously identified in genome-wide association studies, for subtype specific associations in a total of 1221 TMPRSS2:ERG phenotyped PrCa cases. In meta-analyses of a discovery set of 552 cases with TMPRSS2:ERG data and 7650 unaffected men from five centers we have found support for the hypothesis that several common risk variants are associated with one particular subtype rather than with PrCa in general. Risk variants were analyzed in case-case comparisons (296 TMPRSS2:ERG fusion-positive versus 256 fusion-negative cases) and an independent set of 669 cases with TMPRSS2:ERG data was established to replicate the top five candidates. Significant differences (P < 0.00185) between the two subtypes were observed for rs16901979 (8q24) and rs1859962 (17q24), which were enriched in TMPRSS2:ERG fusion-negative (OR = 0.53, P = 0.0007) and TMPRSS2:ERG fusion-positive PrCa (OR = 1.30, P = 0.0016), respectively. Expression quantitative trait locus analysis was performed to investigate mechanistic links between risk variants, fusion status and target gene mRNA levels. For rs1859962 at 17q24, genotype dependent expression was observed for the candidate target gene SOX9 in TMPRSS2:ERG fusion-positive PrCa, which was not evident in TMPRSS2:ERG negative tumors. The present study established evidence for the first two common PrCa risk variants differentially associated with TMPRSS2:ERG fusion status. TMPRSS2:ERG phenotyping of larger studies is required to determine comprehensive sets of variants with subtype-specific roles in PrCa. PMID:27798103

The biomechanics of a multilevel lumbar spine hybrid using nucleus replacement in conjunction with fusion.

PubMed

Dahl, Michael C; Ellingson, Arin M; Mehta, Hitesh P; Huelman, Justin H; Nuckley, David J

2013-02-01

Degenerative disc disease is commonly a multilevel pathology with varying deterioration severity. The use of fusion on multiple levels can significantly affect functionality and has been linked to persistent adjacent disc degeneration. A hybrid approach of fusion and nucleus replacement (NR) has been suggested as a solution for mildly degenerated yet painful levels adjacent to fusion. To compare the biomechanical metrics of different hybrid implant constructs, hypothesizing that an NR+fusion hybrid would be similar to a single-level fusion and perform more naturally compared with a two-level fusion. A cadaveric in vitro repeated-measures study was performed to evaluate a multilevel lumbar NR+fusion hybrid. Eight cadaveric spines (L3-S1) were tested in a Spine Kinetic Simulator (Instron, Norwood, MA, USA). Pure moments of 8 Nm were applied in flexion/extension, lateral bending, and axial rotation as well as compression loading. Specimens were tested intact; fused (using transforaminal lumbar interbody fusion instrumentation with posterior rods) at L5-S1; with a nuclectomy at L4-L5 including fusion at L5-S1; with NR at L4-L5 including fusion at L5-S1; and finally with a two-level fusion spanning L4-S1. Repeated-measures analysis of variance and corrected t tests were used to statistically compare outcomes. The NR+fusion hybrid and single-level fusion exhibited no statistical differences for range of motion (ROM), stiffness, neutral zone, and intradiscal pressure in all loading directions. Compared with two-level fusion, the hybrid affords the construct 41.9% more ROM on average. Two-level fusion stiffness was statistically higher than all other constructs and resulted in significantly lower ROM in flexion, extension, and lateral bending. The hybrid construct produced approximately half of the L3-L4 adjacent-level pressures as the two-level fusion case while generating similar pressures to the single-level fusion case. These data portend more natural functional outcomes and fewer adjacent disc complications for a multilevel NR+fusion hybrid compared with the classical two-level fusion. Copyright © 2013 Elsevier Inc. All rights reserved.

Performance evaluation of an asynchronous multisensor track fusion filter

NASA Astrophysics Data System (ADS)

Alouani, Ali T.; Gray, John E.; McCabe, D. H.

2003-08-01

Recently the authors developed a new filter that uses data generated by asynchronous sensors to produce a state estimate that is optimal in the minimum mean square sense. The solution accounts for communications delay between sensors platform and fusion center. It also deals with out of sequence data as well as latent data by processing the information in a batch-like manner. This paper compares, using simulated targets and Monte Carlo simulations, the performance of the filter to the optimal sequential processing approach. It was found that the new asynchronous Multisensor track fusion filter (AMSTFF) performance is identical to that of the extended sequential Kalman filter (SEKF), while the new filter updates its track at a much lower rate than the SEKF.

Population data of 24 STRs in Mexican-Mestizo population from Monterrey, Nuevo Leon (Northeast, Mexico) based on Powerplex(®) Fusion and GlobalFiler(®) kits.

PubMed

Ramos-González, Benito; Aguilar-Velázquez, José Alonso; Chávez-Briones, María de Lourdes; Delgado-Chavarría, Juan Ramón; Alfaro-Lopez, Elizabeth; Rangel-Villalobos, Héctor

2016-03-01

The STR loci included into new commercial human identification kits compels geneticists estimating forensic parameters for interpretation purposes in forensic casework. Therefore, we studied for the first time in Mexico the GlobalFiler(®) and Powerplex(®) Fusion systems in 326 and 682 unrelated individuals, respectively. These individuals are resident of the Monterrey City of the Nuevo Leon state (Northeast, Mexico). Population data from 23 autosomal STRs and the Y-STR locus DYS391 are reported and compared against available STR data from American ethnic groups and the unique Mexican population studied with Powerplex(®) Fusion. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Data Fusion for a Vision-Radiological System: a Statistical Calibration Algorithm

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

Enqvist, Andreas; Koppal, Sanjeev; Riley, Phillip

2015-07-01

Presented here is a fusion system based on simple, low-cost computer vision and radiological sensors for tracking of multiple objects and identifying potential radiological materials being transported or shipped. The main focus of this work is the development of calibration algorithms for characterizing the fused sensor system as a single entity. There is an apparent need for correcting for a scene deviation from the basic inverse distance-squared law governing the detection rates even when evaluating system calibration algorithms. In particular, the computer vision system enables a map of distance-dependence of the sources being tracked, to which the time-dependent radiological datamore » can be incorporated by means of data fusion of the two sensors' output data. (authors)« less

Pedicle screw fixation for isthmic spondylolisthesis: does posterior lumbar interbody fusion improve outcome over posterolateral fusion?

PubMed

La Rosa, Giovanni; Conti, Alfredo; Cacciola, Fabio; Cardali, Salvatore; La Torre, Domenico; Gambadauro, Nicola Maria; Tomasello, Francesco

2003-09-01

Posterolateral fusion involving instrumentation-assisted segmental fixation represents a valid procedure in the treatment of lumbar instability. In cases of anterior column failure, such as in isthmic spondylolisthesis, supplemental posterior lumbar interbody fusion (PLIF) may improve the fusion rate and endurance of the construct. Posterior lumbar interbody fusion is, however, a more demanding procedure and increases costs and risks of the intervention. The advantages of this technique must, therefore, be weighed against those of a simple posterior lumbar fusion. Thirty-five consecutive patients underwent pedicle screw fixation for isthmic spondylolisthesis. In 18 patients posterior lumbar fusion was performed, and in 17 patients PLIF was added. Clinical, economic, functional, and radiographic data were assessed to determine differences in clinical and functional results and biomechanical properties. At 2-year follow-up examination, the correction of subluxation, disc height, and foraminal area were maintained in the group in which a PLIF procedure was performed, but not in the posterolateral fusion-only group (p < 0.05). Nevertheless, no statistical intergroup differences were demonstrated in terms of neurological improvement (p = 1), economic (p = 0.43), or functional (p = 0.95) outcome, nor in terms of fusion rate (p = 0.49). The authors' findings support the view that an interbody fusion confers superior mechanical strength to the spinal construct; when posterolateral fusion is the sole intervention, progressive loss of the extreme correction can be expected. Such mechanical insufficiency, however, did not influence clinical outcome.

The exocytotic fusion pore modeled as a lipidic pore.

PubMed Central

Nanavati, C; Markin, V S; Oberhauser, A F; Fernandez, J M

1992-01-01

Freeze-fracture electron micrographs from degranulating cells show that the lumen of the secretory granule is connected to the extracellular compartment via large (20 to 150 nm diameter) aqueous pores. These exocytotic fusion pores appear to be made up of a highly curved bilayer that spans the plasma and granule membranes. Conductance measurements, using the patch-clamp technique, have been used to study the fusion pore from the instant it conducts ions. These measurements reveal the presence of early fusion pores that are much smaller than those observed in electron micrographs. Early fusion pores open abruptly, fluctuate, and then either expand irreversibly or close. The molecular structure of these early fusion pores is unknown. In the simplest extremes, these early fusion pores could be either ion channel like protein pores or lipidic pores. Here, we explored the latter possibility, namely that of the early exocytotic fusion pore modeled as a lipid-lined pore whose free energy was composed of curvature elastic energy and work done by tension. Like early exocytotic fusion pores, we found that these lipidic pores could open abruptly, fluctuate, and expand irreversibly. Closure of these lipidic pores could be caused by slight changes in lipid composition. Conductance distributions for stable lipidic pores matched those of exocytotic fusion pores. These findings demonstrate that lipidic pores can exhibit the properties of exocytotic fusion pores, thus providing an alternate framework with which to understand and interpret exocytotic fusion pore data. PMID:1420930

Multimodal Fusion with Reference: Searching for Joint Neuromarkers of Working Memory Deficits in Schizophrenia

PubMed Central

Qi, Shile; Calhoun, Vince D.; van Erp, Theo G. M.; Bustillo, Juan; Damaraju, Eswar; Turner, Jessica A.; Du, Yuhui; Chen, Jiayu; Yu, Qingbao; Mathalon, Daniel H.; Ford, Judith M.; Voyvodic, James; Mueller, Bryon A.; Belger, Aysenil; Ewen, Sarah Mc; Potkin, Steven G.; Preda, Adrian; Jiang, Tianzi

2017-01-01

Multimodal fusion is an effective approach to take advantage of cross-information among multiple imaging data to better understand brain diseases. However, most current fusion approaches are blind, without adopting any prior information. To date, there is increasing interest to uncover the neurocognitive mapping of specific behavioral measurement on enriched brain imaging data; hence, a supervised, goal-directed model that enables a priori information as a reference to guide multimodal data fusion is in need and a natural option. Here we proposed a fusion with reference model, called “multi-site canonical correlation analysis with reference plus joint independent component analysis” (MCCAR+jICA), which can precisely identify co-varying multimodal imaging patterns closely related to reference information, such as cognitive scores. In a 3-way fusion simulation, the proposed method was compared with its alternatives on estimation accuracy of both target component decomposition and modality linkage detection. MCCAR+jICA outperforms others with higher precision. In human imaging data, working memory performance was utilized as a reference to investigate the covarying functional and structural brain patterns among 3 modalities and how they are impaired in schizophrenia. Two independent cohorts (294 and 83 subjects respectively) were used. Interestingly, similar brain maps were identified between the two cohorts, with substantial overlap in the executive control networks in fMRI, salience network in sMRI, and major white matter tracts in dMRI. These regions have been linked with working memory deficits in schizophrenia in multiple reports, while MCCAR+jICA further verified them in a repeatable, joint manner, demonstrating the potential of such results to identify potential neuromarkers for mental disorders. PMID:28708547

Joint FACET: the Canada-Netherlands initiative to study multisensor data fusion systems

NASA Astrophysics Data System (ADS)

Bosse, Eloi; Theil, Arne; Roy, Jean; Huizing, Albert G.; van Aartsen, Simon

1998-09-01

This paper presents the progress of a collaborative effort between Canada and The Netherlands in analyzing multi-sensor data fusion systems, e.g. for potential application to their respective frigates. In view of the overlapping interest in studying and comparing applicability and performance and advanced state-of-the-art Multi-Sensor Data FUsion (MSDF) techniques, the two research establishments involved have decided to join their efforts in the development of MSDF testbeds. This resulted in the so-called Joint-FACET, a highly modular and flexible series of applications that is capable of processing both real and synthetic input data. Joint-FACET allows the user to create and edit test scenarios with multiple ships, sensor and targets, generate realistic sensor outputs, and to process these outputs with a variety of MSDF algorithms. These MSDF algorithms can also be tested using typical experimental data collected during live military exercises.

Neutron diffraction studies of viral fusion peptides

NASA Astrophysics Data System (ADS)

Bradshaw, Jeremy P.; J. M. Darkes, Malcolm; Katsaras, John; Epand, Richard M.

2000-03-01

Membrane fusion plays a vital role in a large and diverse number of essential biological processes. Despite this fact, the precise molecular events that occur during fusion are still not known. We are currently engaged on a study of membrane fusion as mediated by viral fusion peptides. These peptides are the N-terminal regions of certain viral envelope proteins that mediate the process of fusion between the viral envelope and the membranes of the host cell during the infection process. As part of this study, we have carried out neutron diffraction measurements at the ILL, BeNSC and Chalk River, on a range of viral fusion peptides. The peptides, from simian immunodeficiency virus (SIV), influenza A and feline leukaemia virus (FeLV), were incorporated into stacked phospholipid bilayers. Some of the peptides had been specifically deuterated at key amino acids. Lamellar diffraction data were collected and analysed to yield information on the peptide conformation, location and orientation relative to the bilayer.

The fusion of large scale classified side-scan sonar image mosaics.

PubMed

Reed, Scott; Tena, Ruiz Ioseba; Capus, Chris; Petillot, Yvan

2006-07-01

This paper presents a unified framework for the creation of classified maps of the seafloor from sonar imagery. Significant challenges in photometric correction, classification, navigation and registration, and image fusion are addressed. The techniques described are directly applicable to a range of remote sensing problems. Recent advances in side-scan data correction are incorporated to compensate for the sonar beam pattern and motion of the acquisition platform. The corrected images are segmented using pixel-based textural features and standard classifiers. In parallel, the navigation of the sonar device is processed using Kalman filtering techniques. A simultaneous localization and mapping framework is adopted to improve the navigation accuracy and produce georeferenced mosaics of the segmented side-scan data. These are fused within a Markovian framework and two fusion models are presented. The first uses a voting scheme regularized by an isotropic Markov random field and is applicable when the reliability of each information source is unknown. The Markov model is also used to inpaint regions where no final classification decision can be reached using pixel level fusion. The second model formally introduces the reliability of each information source into a probabilistic model. Evaluation of the two models using both synthetic images and real data from a large scale survey shows significant quantitative and qualitative improvement using the fusion approach.

Comparative assessment of methods for the fusion transcripts detection from RNA-Seq data

PubMed Central

Kumar, Shailesh; Vo, Angie Duy; Qin, Fujun; Li, Hui

2016-01-01

RNA-Seq made possible the global identification of fusion transcripts, i.e. “chimeric RNAs”. Even though various software packages have been developed to serve this purpose, they behave differently in different datasets provided by different developers. It is important for both users, and developers to have an unbiased assessment of the performance of existing fusion detection tools. Toward this goal, we compared the performance of 12 well-known fusion detection software packages. We evaluated the sensitivity, false discovery rate, computing time, and memory usage of these tools in four different datasets (positive, negative, mixed, and test). We conclude that some tools are better than others in terms of sensitivity, positive prediction value, time consumption and memory usage. We also observed small overlaps of the fusions detected by different tools in the real dataset (test dataset). This could be due to false discoveries by various tools, but could also be due to the reason that none of the tools are inclusive. We have found that the performance of the tools depends on the quality, read length, and number of reads of the RNA-Seq data. We recommend that users choose the proper tools for their purpose based on the properties of their RNA-Seq data. PMID:26862001

Sensor data fusion for spectroscopy-based detection of explosives

NASA Astrophysics Data System (ADS)

Shah, Pratik V.; Singh, Abhijeet; Agarwal, Sanjeev; Sedigh, Sahra; Ford, Alan; Waterbury, Robert

2009-05-01

In-situ trace detection of explosive compounds such as RDX, TNT, and ammonium nitrate, is an important problem for the detection of IEDs and IED precursors. Spectroscopic techniques such as LIBS and Raman have shown promise for the detection of residues of explosive compounds on surfaces from standoff distances. Individually, both LIBS and Raman techniques suffer from various limitations, e.g., their robustness and reliability suffers due to variations in peak strengths and locations. However, the orthogonal nature of the spectral and compositional information provided by these techniques makes them suitable candidates for the use of sensor fusion to improve the overall detection performance. In this paper, we utilize peak energies in a region by fitting Lorentzian or Gaussian peaks around the location of interest. The ratios of peak energies are used for discrimination, in order to normalize the effect of changes in overall signal strength. Two data fusion techniques are discussed in this paper. Multi-spot fusion is performed on a set of independent samples from the same region based on the maximum likelihood formulation. Furthermore, the results from LIBS and Raman sensors are fused using linear discriminators. Improved detection performance with significantly reduced false alarm rates is reported using fusion techniques on data collected for sponsor demonstration at Fort Leonard Wood.

A synthetic dataset for evaluating soft and hard fusion algorithms

NASA Astrophysics Data System (ADS)

Graham, Jacob L.; Hall, David L.; Rimland, Jeffrey

2011-06-01

There is an emerging demand for the development of data fusion techniques and algorithms that are capable of combining conventional "hard" sensor inputs such as video, radar, and multispectral sensor data with "soft" data including textual situation reports, open-source web information, and "hard/soft" data such as image or video data that includes human-generated annotations. New techniques that assist in sense-making over a wide range of vastly heterogeneous sources are critical to improving tactical situational awareness in counterinsurgency (COIN) and other asymmetric warfare situations. A major challenge in this area is the lack of realistic datasets available for test and evaluation of such algorithms. While "soft" message sets exist, they tend to be of limited use for data fusion applications due to the lack of critical message pedigree and other metadata. They also lack corresponding hard sensor data that presents reasonable "fusion opportunities" to evaluate the ability to make connections and inferences that span the soft and hard data sets. This paper outlines the design methodologies, content, and some potential use cases of a COIN-based synthetic soft and hard dataset created under a United States Multi-disciplinary University Research Initiative (MURI) program funded by the U.S. Army Research Office (ARO). The dataset includes realistic synthetic reports from a variety of sources, corresponding synthetic hard data, and an extensive supporting database that maintains "ground truth" through logical grouping of related data into "vignettes." The supporting database also maintains the pedigree of messages and other critical metadata.

Hendra virus fusion protein transmembrane domain contributes to pre-fusion protein stability

PubMed Central

Webb, Stacy; Nagy, Tamas; Moseley, Hunter; Fried, Michael; Dutch, Rebecca

2017-01-01

Enveloped viruses utilize fusion (F) proteins studding the surface of the virus to facilitate membrane fusion with a target cell membrane. Fusion of the viral envelope with a cellular membrane is required for release of viral genomic material, so the virus can ultimately reproduce and spread. To drive fusion, the F protein undergoes an irreversible conformational change, transitioning from a metastable pre-fusion conformation to a more thermodynamically stable post-fusion structure. Understanding the elements that control stability of the pre-fusion state and triggering to the post-fusion conformation is important for understanding F protein function. Mutations in F protein transmembrane (TM) domains implicated the TM domain in the fusion process, but the structural and molecular details in fusion remain unclear. Previously, analytical ultracentrifugation was utilized to demonstrate that isolated TM domains of Hendra virus F protein associate in a monomer-trimer equilibrium (Smith, E. C., Smith, S. E., Carter, J. R., Webb, S. R., Gibson, K. M., Hellman, L. M., Fried, M. G., and Dutch, R. E. (2013) J. Biol. Chem. 288, 35726–35735). To determine factors driving this association, 140 paramyxovirus F protein TM domain sequences were analyzed. A heptad repeat of β-branched residues was found, and analysis of the Hendra virus F TM domain revealed a heptad repeat leucine-isoleucine zipper motif (LIZ). Replacement of the LIZ with alanine resulted in dramatically reduced TM-TM association. Mutation of the LIZ in the whole protein resulted in decreased protein stability, including pre-fusion conformation stability. Together, our data suggest that the heptad repeat LIZ contributed to TM-TM association and is important for F protein function and pre-fusion stability. PMID:28213515

Hendra virus fusion protein transmembrane domain contributes to pre-fusion protein stability.

PubMed

Webb, Stacy; Nagy, Tamas; Moseley, Hunter; Fried, Michael; Dutch, Rebecca

2017-04-07

Enveloped viruses utilize fusion (F) proteins studding the surface of the virus to facilitate membrane fusion with a target cell membrane. Fusion of the viral envelope with a cellular membrane is required for release of viral genomic material, so the virus can ultimately reproduce and spread. To drive fusion, the F protein undergoes an irreversible conformational change, transitioning from a metastable pre-fusion conformation to a more thermodynamically stable post-fusion structure. Understanding the elements that control stability of the pre-fusion state and triggering to the post-fusion conformation is important for understanding F protein function. Mutations in F protein transmembrane (TM) domains implicated the TM domain in the fusion process, but the structural and molecular details in fusion remain unclear. Previously, analytical ultracentrifugation was utilized to demonstrate that isolated TM domains of Hendra virus F protein associate in a monomer-trimer equilibrium (Smith, E. C., Smith, S. E., Carter, J. R., Webb, S. R., Gibson, K. M., Hellman, L. M., Fried, M. G., and Dutch, R. E. (2013) J. Biol. Chem. 288, 35726-35735). To determine factors driving this association, 140 paramyxovirus F protein TM domain sequences were analyzed. A heptad repeat of β-branched residues was found, and analysis of the Hendra virus F TM domain revealed a heptad repeat leucine-isoleucine zipper motif (LIZ). Replacement of the LIZ with alanine resulted in dramatically reduced TM-TM association. Mutation of the LIZ in the whole protein resulted in decreased protein stability, including pre-fusion conformation stability. Together, our data suggest that the heptad repeat LIZ contributed to TM-TM association and is important for F protein function and pre-fusion stability. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Design and implementation of PAVEMON: A GIS web-based pavement monitoring system based on large amounts of heterogeneous sensors data

NASA Astrophysics Data System (ADS)

Shahini Shamsabadi, Salar

A web-based PAVEment MONitoring system, PAVEMON, is a GIS oriented platform for accommodating, representing, and leveraging data from a multi-modal mobile sensor system. Stated sensor system consists of acoustic, optical, electromagnetic, and GPS sensors and is capable of producing as much as 1 Terabyte of data per day. Multi-channel raw sensor data (microphone, accelerometer, tire pressure sensor, video) and processed results (road profile, crack density, international roughness index, micro texture depth, etc.) are outputs of this sensor system. By correlating the sensor measurements and positioning data collected in tight time synchronization, PAVEMON attaches a spatial component to all the datasets. These spatially indexed outputs are placed into an Oracle database which integrates seamlessly with PAVEMON's web-based system. The web-based system of PAVEMON consists of two major modules: 1) a GIS module for visualizing and spatial analysis of pavement condition information layers, and 2) a decision-support module for managing maintenance and repair (Mℝ) activities and predicting future budget needs. PAVEMON weaves together sensor data with third-party climate and traffic information from the National Oceanic and Atmospheric Administration (NOAA) and Long Term Pavement Performance (LTPP) databases for an organized data driven approach to conduct pavement management activities. PAVEMON deals with heterogeneous and redundant observations by fusing them for jointly-derived higher-confidence results. A prominent example of the fusion algorithms developed within PAVEMON is a data fusion algorithm used for estimating the overall pavement conditions in terms of ASTM's Pavement Condition Index (PCI). PAVEMON predicts PCI by undertaking a statistical fusion approach and selecting a subset of all the sensor measurements. Other fusion algorithms include noise-removal algorithms to remove false negatives in the sensor data in addition to fusion algorithms developed for identifying features on the road. PAVEMON offers an ideal research and monitoring platform for rapid, intelligent and comprehensive evaluation of tomorrow's transportation infrastructure based on up-to-date data from heterogeneous sensor systems.

Mapping Forest Height in Gabon Using UAVSAR Multi-Baseline Polarimetric SAR Interferometry and Lidar Fusion

NASA Astrophysics Data System (ADS)

Simard, M.; Denbina, M. W.

2017-12-01

Using data collected by NASA's Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) and Land, Vegetation, and Ice Sensor (LVIS) lidar, we have estimated forest canopy height for a number of study areas in the country of Gabon using a new machine learning data fusion approach. Using multi-baseline polarimetric synthetic aperture radar interferometry (PolInSAR) data collected by UAVSAR, forest heights can be estimated using the random volume over ground model. In the case of multi-baseline UAVSAR data consisting of many repeat passes with spatially separated flight tracks, we can estimate different forest height values for each different image pair, or baseline. In order to choose the best forest height estimate for each pixel, the baselines must be selected or ranked, taking care to avoid baselines with unsuitable spatial separation, or severe temporal decorrelation effects. The current baseline selection algorithms in the literature use basic quality metrics derived from the PolInSAR data which are not necessarily indicative of the true height accuracy in all cases. We have developed a new data fusion technique which treats PolInSAR baseline selection as a supervised classification problem, where the classifier is trained using a sparse sampling of lidar data within the PolInSAR coverage area. The classifier uses a large variety of PolInSAR-derived features as input, including radar backscatter as well as features based on the PolInSAR coherence region shape and the PolInSAR complex coherences. The resulting data fusion method produces forest height estimates which are more accurate than a purely radar-based approach, while having a larger coverage area than the input lidar training data, combining some of the strengths of each sensor. The technique demonstrates the strong potential for forest canopy height and above-ground biomass mapping using fusion of PolInSAR with data from future spaceborne lidar missions such as the upcoming Global Ecosystems Dynamics Investigation (GEDI) lidar.

Dynamic image fusion and general observer preference

NASA Astrophysics Data System (ADS)

Burks, Stephen D.; Doe, Joshua M.

2010-04-01

Recent developments in image fusion give the user community many options for ways of presenting the imagery to an end-user. Individuals at the US Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate have developed an electronic system that allows users to quickly and efficiently determine optimal image fusion algorithms and color parameters based upon collected imagery and videos from environments that are typical to observers in a military environment. After performing multiple multi-band data collections in a variety of military-like scenarios, different waveband, fusion algorithm, image post-processing, and color choices are presented to observers as an output of the fusion system. The observer preferences can give guidelines as to how specific scenarios should affect the presentation of fused imagery.

Pixel-level multisensor image fusion based on matrix completion and robust principal component analysis

NASA Astrophysics Data System (ADS)

Wang, Zhuozheng; Deller, J. R.; Fleet, Blair D.

2016-01-01

Acquired digital images are often corrupted by a lack of camera focus, faulty illumination, or missing data. An algorithm is presented for fusion of multiple corrupted images of a scene using the lifting wavelet transform. The method employs adaptive fusion arithmetic based on matrix completion and self-adaptive regional variance estimation. Characteristics of the wavelet coefficients are used to adaptively select fusion rules. Robust principal component analysis is applied to low-frequency image components, and regional variance estimation is applied to high-frequency components. Experiments reveal that the method is effective for multifocus, visible-light, and infrared image fusion. Compared with traditional algorithms, the new algorithm not only increases the amount of preserved information and clarity but also improves robustness.

Soft x-ray streak camera for laser fusion applications

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

Stradling, G.L.

This thesis reviews the development and significance of the soft x-ray streak camera (SXRSC) in the context of inertial confinement fusion energy development. A brief introduction of laser fusion and laser fusion diagnostics is presented. The need for a soft x-ray streak camera as a laser fusion diagnostic is shown. Basic x-ray streak camera characteristics, design, and operation are reviewed. The SXRSC design criteria, the requirement for a subkilovolt x-ray transmitting window, and the resulting camera design are explained. Theory and design of reflector-filter pair combinations for three subkilovolt channels centered at 220 eV, 460 eV, and 620 eV aremore » also presented. Calibration experiments are explained and data showing a dynamic range of 1000 and a sweep speed of 134 psec/mm are presented. Sensitivity modifications to the soft x-ray streak camera for a high-power target shot are described. A preliminary investigation, using a stepped cathode, of the thickness dependence of the gold photocathode response is discussed. Data from a typical Argus laser gold-disk target experiment are shown.« less

Advanced algorithms for distributed fusion

NASA Astrophysics Data System (ADS)

Gelfand, A.; Smith, C.; Colony, M.; Bowman, C.; Pei, R.; Huynh, T.; Brown, C.

2008-03-01

The US Military has been undergoing a radical transition from a traditional "platform-centric" force to one capable of performing in a "Network-Centric" environment. This transformation will place all of the data needed to efficiently meet tactical and strategic goals at the warfighter's fingertips. With access to this information, the challenge of fusing data from across the batttlespace into an operational picture for real-time Situational Awareness emerges. In such an environment, centralized fusion approaches will have limited application due to the constraints of real-time communications networks and computational resources. To overcome these limitations, we are developing a formalized architecture for fusion and track adjudication that allows the distribution of fusion processes over a dynamically created and managed information network. This network will support the incorporation and utilization of low level tracking information within the Army Distributed Common Ground System (DCGS-A) or Future Combat System (FCS). The framework is based on Bowman's Dual Node Network (DNN) architecture that utilizes a distributed network of interlaced fusion and track adjudication nodes to build and maintain a globally consistent picture across all assets.

Analysis of membrane fusion as a two-state sequential process: evaluation of the stalk model.

PubMed

Weinreb, Gabriel; Lentz, Barry R

2007-06-01

We propose a model that accounts for the time courses of PEG-induced fusion of membrane vesicles of varying lipid compositions and sizes. The model assumes that fusion proceeds from an initial, aggregated vesicle state ((A) membrane contact) through two sequential intermediate states (I(1) and I(2)) and then on to a fusion pore state (FP). Using this model, we interpreted data on the fusion of seven different vesicle systems. We found that the initial aggregated state involved no lipid or content mixing but did produce leakage. The final state (FP) was not leaky. Lipid mixing normally dominated the first intermediate state (I(1)), but content mixing signal was also observed in this state for most systems. The second intermediate state (I(2)) exhibited both lipid and content mixing signals and leakage, and was sometimes the only leaky state. In some systems, the first and second intermediates were indistinguishable and converted directly to the FP state. Having also tested a parallel, two-intermediate model subject to different assumptions about the nature of the intermediates, we conclude that a sequential, two-intermediate model is the simplest model sufficient to describe PEG-mediated fusion in all vesicle systems studied. We conclude as well that a fusion intermediate "state" should not be thought of as a fixed structure (e.g., "stalk" or "transmembrane contact") of uniform properties. Rather, a fusion "state" describes an ensemble of similar structures that can have different mechanical properties. Thus, a "state" can have varying probabilities of having a given functional property such as content mixing, lipid mixing, or leakage. Our data show that the content mixing signal may occur through two processes, one correlated and one not correlated with leakage. Finally, we consider the implications of our results in terms of the "modified stalk" hypothesis for the mechanism of lipid pore formation. We conclude that our results not only support this hypothesis but also provide a means of analyzing fusion time courses so as to test it and gauge the mechanism of action of fusion proteins in the context of the lipidic hypothesis of fusion.

Kernel-Based Sensor Fusion With Application to Audio-Visual Voice Activity Detection

NASA Astrophysics Data System (ADS)

Dov, David; Talmon, Ronen; Cohen, Israel

2016-12-01

In this paper, we address the problem of multiple view data fusion in the presence of noise and interferences. Recent studies have approached this problem using kernel methods, by relying particularly on a product of kernels constructed separately for each view. From a graph theory point of view, we analyze this fusion approach in a discrete setting. More specifically, based on a statistical model for the connectivity between data points, we propose an algorithm for the selection of the kernel bandwidth, a parameter, which, as we show, has important implications on the robustness of this fusion approach to interferences. Then, we consider the fusion of audio-visual speech signals measured by a single microphone and by a video camera pointed to the face of the speaker. Specifically, we address the task of voice activity detection, i.e., the detection of speech and non-speech segments, in the presence of structured interferences such as keyboard taps and office noise. We propose an algorithm for voice activity detection based on the audio-visual signal. Simulation results show that the proposed algorithm outperforms competing fusion and voice activity detection approaches. In addition, we demonstrate that a proper selection of the kernel bandwidth indeed leads to improved performance.

Recurrent R-spondin fusions in colon cancer.

PubMed

Seshagiri, Somasekar; Stawiski, Eric W; Durinck, Steffen; Modrusan, Zora; Storm, Elaine E; Conboy, Caitlin B; Chaudhuri, Subhra; Guan, Yinghui; Janakiraman, Vasantharajan; Jaiswal, Bijay S; Guillory, Joseph; Ha, Connie; Dijkgraaf, Gerrit J P; Stinson, Jeremy; Gnad, Florian; Huntley, Melanie A; Degenhardt, Jeremiah D; Haverty, Peter M; Bourgon, Richard; Wang, Weiru; Koeppen, Hartmut; Gentleman, Robert; Starr, Timothy K; Zhang, Zemin; Largaespada, David A; Wu, Thomas D; de Sauvage, Frederic J

2012-08-30

Identifying and understanding changes in cancer genomes is essential for the development of targeted therapeutics. Here we analyse systematically more than 70 pairs of primary human colon tumours by applying next-generation sequencing to characterize their exomes, transcriptomes and copy-number alterations. We have identified 36,303 protein-altering somatic changes that include several new recurrent mutations in the Wnt pathway gene TCF7L2, chromatin-remodelling genes such as TET2 and TET3 and receptor tyrosine kinases including ERBB3. Our analysis for significantly mutated cancer genes identified 23 candidates, including the cell cycle checkpoint kinase ATM. Copy-number and RNA-seq data analysis identified amplifications and corresponding overexpression of IGF2 in a subset of colon tumours. Furthermore, using RNA-seq data we identified multiple fusion transcripts including recurrent gene fusions involving R-spondin family members RSPO2 and RSPO3 that together occur in 10% of colon tumours. The RSPO fusions were mutually exclusive with APC mutations, indicating that they probably have a role in the activation of Wnt signalling and tumorigenesis. Consistent with this we show that the RSPO fusion proteins were capable of potentiating Wnt signalling. The R-spondin gene fusions and several other gene mutations identified in this study provide new potential opportunities for therapeutic intervention in colon cancer.

Recurrent R-spondin fusions in colon cancer

PubMed Central

Seshagiri, Somasekar; Stawiski, Eric W.; Durinck, Steffen; Modrusan, Zora; Storm, Elaine E.; Conboy, Caitlin B.; Chaudhuri, Subhra; Guan, Yinghui; Janakiraman, Vasantharajan; Jaiswal, Bijay S.; Guillory, Joseph; Ha, Connie; Dijkgraaf, Gerrit J. P.; Stinson, Jeremy; Gnad, Florian; Huntley, Melanie A.; Degenhardt, Jeremiah D.; Haverty, Peter M.; Bourgon, Richard; Wang, Weiru; Koeppen, Hartmut; Gentleman, Robert; Starr, Timothy K.; Zhang, Zemin; Largaespada, David A.; Wu, Thomas D.; de Sauvage, Frederic J

2013-01-01

Identifying and understanding changes in cancer genomes is essential for the development of targeted therapeutics1. Here we analyse systematically more than 70 pairs of primary human colon tumours by applying next-generation sequencing to characterize their exomes, transcriptomes and copy-number alterations. We have identified 36,303 protein-altering somatic changes that include several new recurrent mutations in the Wnt pathway gene TCF7L2, chromatin-remodelling genes such as TET2 and TET3 and receptor tyrosine kinases including ERBB3. Our analysis for significantly mutated cancer genes identified 23 candidates, including the cell cycle checkpoint kinase ATM. Copy-number and RNA-seq data analysis identified amplifications and corresponding overexpression of IGF2 in a subset of colon tumours. Furthermore, using RNA-seq data we identified multiple fusion transcripts including recurrent gene fusions involving R-spondin family members RSPO2 and RSPO3 that together occur in 10% of colon tumours. The RSPO fusions were mutually exclusive with APC mutations, indicating that they probably have a role in the activation of Wnt signalling and tumorigenesis. Consistent with this we show that the RSPO fusion proteins were capable of potentiating Wnt signalling. The R-spondin gene fusions and several other gene mutations identified in this study provide new potential opportunities for therapeutic intervention in colon cancer. PMID:22895193

Multimodal biometric system using rank-level fusion approach.

PubMed

Monwar, Md Maruf; Gavrilova, Marina L

2009-08-01

In many real-world applications, unimodal biometric systems often face significant limitations due to sensitivity to noise, intraclass variability, data quality, nonuniversality, and other factors. Attempting to improve the performance of individual matchers in such situations may not prove to be highly effective. Multibiometric systems seek to alleviate some of these problems by providing multiple pieces of evidence of the same identity. These systems help achieve an increase in performance that may not be possible using a single-biometric indicator. This paper presents an effective fusion scheme that combines information presented by multiple domain experts based on the rank-level fusion integration method. The developed multimodal biometric system possesses a number of unique qualities, starting from utilizing principal component analysis and Fisher's linear discriminant methods for individual matchers (face, ear, and signature) identity authentication and utilizing the novel rank-level fusion method in order to consolidate the results obtained from different biometric matchers. The ranks of individual matchers are combined using the highest rank, Borda count, and logistic regression approaches. The results indicate that fusion of individual modalities can improve the overall performance of the biometric system, even in the presence of low quality data. Insights on multibiometric design using rank-level fusion and its performance on a variety of biometric databases are discussed in the concluding section.

A Combined Approach of Sensor Data Fusion and Multivariate Geostatistics for Delineation of Homogeneous Zones in an Agricultural Field

PubMed Central

Castrignanò, Annamaria; Quarto, Ruggiero; Vitti, Carolina; Langella, Giuliano; Terribile, Fabio

2017-01-01

To assess spatial variability at the very fine scale required by Precision Agriculture, different proximal and remote sensors have been used. They provide large amounts and different types of data which need to be combined. An integrated approach, using multivariate geostatistical data-fusion techniques and multi-source geophysical sensor data to determine simple summary scale-dependent indices, is described here. These indices can be used to delineate management zones to be submitted to differential management. Such a data fusion approach with geophysical sensors was applied in a soil of an agronomic field cropped with tomato. The synthetic regionalized factors determined, contributed to split the 3D edaphic environment into two main horizontal structures with different hydraulic properties and to disclose two main horizons in the 0–1.0-m depth with a discontinuity probably occurring between 0.40 m and 0.70 m. Comparing this partition with the soil properties measured with a shallow sampling, it was possible to verify the coherence in the topsoil between the dielectric properties and other properties more directly related to agronomic management. These results confirm the advantages of using proximal sensing as a preliminary step in the application of site-specific management. Combining disparate spatial data (data fusion) is not at all a naive problem and novel and powerful methods need to be developed. PMID:29207510

A Combined Approach of Sensor Data Fusion and Multivariate Geostatistics for Delineation of Homogeneous Zones in an Agricultural Field.

PubMed

Castrignanò, Annamaria; Buttafuoco, Gabriele; Quarto, Ruggiero; Vitti, Carolina; Langella, Giuliano; Terribile, Fabio; Venezia, Accursio

2017-12-03

To assess spatial variability at the very fine scale required by Precision Agriculture, different proximal and remote sensors have been used. They provide large amounts and different types of data which need to be combined. An integrated approach, using multivariate geostatistical data-fusion techniques and multi-source geophysical sensor data to determine simple summary scale-dependent indices, is described here. These indices can be used to delineate management zones to be submitted to differential management. Such a data fusion approach with geophysical sensors was applied in a soil of an agronomic field cropped with tomato. The synthetic regionalized factors determined, contributed to split the 3D edaphic environment into two main horizontal structures with different hydraulic properties and to disclose two main horizons in the 0-1.0-m depth with a discontinuity probably occurring between 0.40 m and 0.70 m. Comparing this partition with the soil properties measured with a shallow sampling, it was possible to verify the coherence in the topsoil between the dielectric properties and other properties more directly related to agronomic management. These results confirm the advantages of using proximal sensing as a preliminary step in the application of site-specific management. Combining disparate spatial data (data fusion) is not at all a naive problem and novel and powerful methods need to be developed.

Consumer-oriented social data fusion: controlled learning in social environments, social advertising, and more

NASA Astrophysics Data System (ADS)

Grewe, L.

2013-05-01

This paper explores the current practices in social data fusion and analysis as it applies to consumer-oriented applications in a slew of areas including business, economics, politics, sciences, medicine, education and more. A categorization of these systems is proposed and contributions to each area are explored preceded by a discussion of some special issues related to social data and networks. From this work, future paths of consumer-based social data analysis research and current outstanding problems are discovered.

Evolution of an Intelligent Information Fusion System

NASA Technical Reports Server (NTRS)

Campbell, William J.; Cromp, Robert F.

1990-01-01

Consideration is given to the hardware and software needed to manage the enormous amount and complexity of data that the next generation of space-borne sensors will provide. An anthology is presented illustrating the evolution of artificial intelligence, science data processing, and management from the 1960s to the near future. Problems and limitations of technologies, data structures, data standards, and conceptual thinking are addressed. The development of an end-to-end Intelligent Information Fusion System that embodies knowledge of the user's domain-specific goals is proposed.

Fusion hindrance at deep sub-barrier energies for the 11B+197Au system

NASA Astrophysics Data System (ADS)

Shrivastava, A.; Mahata, K.; Nanal, V.; Pandit, S. K.; Parkar, V. V.; Rout, P. C.; Dokania, N.; Ramachandran, K.; Kumar, A.; Chatterjee, A.; Kailas, S.

2017-09-01

Fusion cross sections for the 11B+197Au system have been measured at energies around and deep below the Coulomb barrier, to probe the occurrence of fusion hindrance in case of asymmetric systems. A deviation with respect to the standard coupled channels calculations has been observed at the lowest energy. The results have been compared with an adiabatic model calculation that considers a damping of the coupling strength for a gradual transition from sudden to adiabatic regime at very low energies. The data could be explained without inclusion of the damping factor. This implies that the influence of fusion hindrance is not significant within the measured energy range for this system. The present result is consistent with the observed trend between the degree of fusion hindrance and the charge product that reveals a weaker influence of hindrance on fusion involving lighter projectiles on heavy targets.

Complexin and Ca2+ stimulate SNARE-mediated membrane fusion

PubMed Central

Yoon, Tae-Young; Lu, Xiaobind; Diao, Jiajie; Lee, Soo-Min; Ha, Taekjip; Shin, Yeon-Kyun

2008-01-01

Ca2+-triggered, synchronized synaptic vesicle fusion underlies interneuronal communication. Complexin is a major binding partner of the SNARE complex, the core fusion machinery at the presynapse. The physiological data on complexin, however, have been at odds with each other, making delineation of its molecular function difficult. Here we report direct observation of two-faceted functions of complexin using the single-vesicle fluorescence fusion assay and EPR. We show that complexin I has two opposing effects on trans-SNARE assembly: inhibition of SNARE complex formation and stabilization of assembled SNARE complexes. Of note, SNARE-mediated fusion is markedly stimulated by complexin, and it is further accelerated by two orders of magnitude in response to an externally applied Ca2+ wave. We suggest that SNARE complexes, complexins and phospholipids collectively form a complex substrate for Ca2+ and Ca2+-sensing fusion effectors in neurotransmitter release. PMID:18552825

Visualizing Uncertainty for Data Fusion Graphics: Review of Selected Literature and Industry Approaches

DTIC Science & Technology

2015-06-09

anomaly detection , which is generally considered part of high level information fusion (HLIF) involving temporal-geospatial data as well as meta-data... Anomaly detection in the Maritime defence and security domain typically focusses on trying to identify vessels that are behaving in an unusual...manner compared with lawful vessels operating in the area – an applied case of target detection among distractors. Anomaly detection is a complex problem

Trust and Independence Aware Decision Fusion in Distributed Networks

DTIC Science & Technology

2013-01-01

evidence in order to derive a unified belief where conflicting evidence exists. However, neither DST nor TBM deals with misbehaving data sources and...about the target. The problem is compounded by the misbehaving nodes who supply false data in the network. This work aims at enhancing the accuracy of...derive a unified belief where conflicting evidence exists. However, neither DST nor TBM deals with misbehaving data sources and dependence of fusion

A social science data-fusion tool and the Data Management through e-Social Science (DAMES) infrastructure.

PubMed

Warner, Guy C; Blum, Jesse M; Jones, Simon B; Lambert, Paul S; Turner, Kenneth J; Tan, Larry; Dawson, Alison S F; Bell, David N F

2010-08-28

The last two decades have seen substantially increased potential for quantitative social science research. This has been made possible by the significant expansion of publicly available social science datasets, the development of new analytical methodologies, such as microsimulation, and increases in computing power. These rich resources do, however, bring with them substantial challenges associated with organizing and using data. These processes are often referred to as 'data management'. The Data Management through e-Social Science (DAMES) project is working to support activities of data management for social science research. This paper describes the DAMES infrastructure, focusing on the data-fusion process that is central to the project approach. It covers: the background and requirements for provision of resources by DAMES; the use of grid technologies to provide easy-to-use tools and user front-ends for several common social science data-management tasks such as data fusion; the approach taken to solve problems related to data resources and metadata relevant to social science applications; and the implementation of the architecture that has been designed to achieve this infrastructure.

Data fusion with artificial neural networks (ANN) for classification of earth surface from microwave satellite measurements

NASA Technical Reports Server (NTRS)

Lure, Y. M. Fleming; Grody, Norman C.; Chiou, Y. S. Peter; Yeh, H. Y. Michael

1993-01-01

A data fusion system with artificial neural networks (ANN) is used for fast and accurate classification of five earth surface conditions and surface changes, based on seven SSMI multichannel microwave satellite measurements. The measurements include brightness temperatures at 19, 22, 37, and 85 GHz at both H and V polarizations (only V at 22 GHz). The seven channel measurements are processed through a convolution computation such that all measurements are located at same grid. Five surface classes including non-scattering surface, precipitation over land, over ocean, snow, and desert are identified from ground-truth observations. The system processes sensory data in three consecutive phases: (1) pre-processing to extract feature vectors and enhance separability among detected classes; (2) preliminary classification of Earth surface patterns using two separate and parallely acting classifiers: back-propagation neural network and binary decision tree classifiers; and (3) data fusion of results from preliminary classifiers to obtain the optimal performance in overall classification. Both the binary decision tree classifier and the fusion processing centers are implemented by neural network architectures. The fusion system configuration is a hierarchical neural network architecture, in which each functional neural net will handle different processing phases in a pipelined fashion. There is a total of around 13,500 samples for this analysis, of which 4 percent are used as the training set and 96 percent as the testing set. After training, this classification system is able to bring up the detection accuracy to 94 percent compared with 88 percent for back-propagation artificial neural networks and 80 percent for binary decision tree classifiers. The neural network data fusion classification is currently under progress to be integrated in an image processing system at NOAA and to be implemented in a prototype of a massively parallel and dynamically reconfigurable Modular Neural Ring (MNR).

Context Representation and Fusion: Advancements and Opportunities

PubMed Central

Khattak, Asad Masood; Akbar, Noman; Aazam, Mohammad; Ali, Taqdir; Khan, Adil Mehmood; Jeon, Seokhee; Hwang, Myunggwon; Lee, Sungyoung

2014-01-01

The acceptance and usability of context-aware systems have given them the edge of wide use in various domains and has also attracted the attention of researchers in the area of context-aware computing. Making user context information available to such systems is the center of attention. However, there is very little emphasis given to the process of context representation and context fusion which are integral parts of context-aware systems. Context representation and fusion facilitate in recognizing the dependency/relationship of one data source on another to extract a better understanding of user context. The problem is more critical when data is emerging from heterogeneous sources of diverse nature like sensors, user profiles, and social interactions and also at different timestamps. Both the processes of context representation and fusion are followed in one way or another; however, they are not discussed explicitly for the realization of context-aware systems. In other words most of the context-aware systems underestimate the importance context representation and fusion. This research has explicitly focused on the importance of both the processes of context representation and fusion and has streamlined their existence in the overall architecture of context-aware systems’ design and development. Various applications of context representation and fusion in context-aware systems are also highlighted in this research. A detailed review on both the processes is provided in this research with their applications. Future research directions (challenges) are also highlighted which needs proper attention for the purpose of achieving the goal of realizing context-aware systems. PMID:24887042

Soft X-ray streak camera for laser fusion applications

NASA Astrophysics Data System (ADS)

Stradling, G. L.

1981-04-01

The development and significance of the soft x-ray streak camera (SXRSC) in the context of inertial confinement fusion energy development is reviewed as well as laser fusion and laser fusion diagnostics. The SXRSC design criteria, the requirement for a subkilovolt x-ray transmitting window, and the resulting camera design are explained. Theory and design of reflector-filter pair combinations for three subkilovolt channels centered at 220 eV, 460 eV, and 620 eV are also presented. Calibration experiments are explained and data showing a dynamic range of 1000 and a sweep speed of 134 psec/mm are presented. Sensitivity modifications to the soft x-ray streak camera for a high-power target shot are described. A preliminary investigation, using a stepped cathode, of the thickness dependence of the gold photocathode response is discussed. Data from a typical Argus laser gold-disk target experiment are shown.

Advances in data representation for hard/soft information fusion

NASA Astrophysics Data System (ADS)

Rimland, Jeffrey C.; Coughlin, Dan; Hall, David L.; Graham, Jacob L.

2012-06-01

Information fusion is becoming increasingly human-centric. While past systems typically relegated humans to the role of analyzing a finished fusion product, current systems are exploring the role of humans as integral elements in a modular and extensible distributed framework where many tasks can be accomplished by either human or machine performers. For example, "participatory sensing" campaigns give humans the role of "soft sensors" by uploading their direct observations or as "soft sensor platforms" by using mobile devices to record human-annotated, GPS-encoded high quality photographs, video, or audio. Additionally, the role of "human-in-the-loop", in which individuals or teams using advanced human computer interface (HCI) tools such as stereoscopic 3D visualization, haptic interfaces, or aural "sonification" interfaces can help to effectively engage the innate human capability to perform pattern matching, anomaly identification, and semantic-based contextual reasoning to interpret an evolving situation. The Pennsylvania State University is participating in a Multi-disciplinary University Research Initiative (MURI) program funded by the U.S. Army Research Office to investigate fusion of hard and soft data in counterinsurgency (COIN) situations. In addition to the importance of this research for Intelligence Preparation of the Battlefield (IPB), many of the same challenges and techniques apply to health and medical informatics, crisis management, crowd-sourced "citizen science", and monitoring environmental concerns. One of the key challenges that we have encountered is the development of data formats, protocols, and methodologies to establish an information architecture and framework for the effective capture, representation, transmission, and storage of the vastly heterogeneous data and accompanying metadata -- including capabilities and characteristics of human observers, uncertainty of human observations, "soft" contextual data, and information pedigree. This paper describes our findings and offers insights into the role of data representation in hard/soft fusion.

Fusion of spectra and texture data of hyperspectral imaging for the prediction of the water-holding capacity of fresh chicken breast filets

USDA-ARS?s Scientific Manuscript database

This study investigated the fusion of spectra and texture data of hyperspectral imaging (HSI, 1000–2500 nm) for predicting the water-holding capacity (WHC) of intact, fresh chicken breast filets. Three physical and chemical indicators drip loss, expressible fluid, and salt-induced water gain were me...

A DNA-based semantic fusion model for remote sensing data.

PubMed

Sun, Heng; Weng, Jian; Yu, Guangchuang; Massawe, Richard H

2013-01-01

Semantic technology plays a key role in various domains, from conversation understanding to algorithm analysis. As the most efficient semantic tool, ontology can represent, process and manage the widespread knowledge. Nowadays, many researchers use ontology to collect and organize data's semantic information in order to maximize research productivity. In this paper, we firstly describe our work on the development of a remote sensing data ontology, with a primary focus on semantic fusion-driven research for big data. Our ontology is made up of 1,264 concepts and 2,030 semantic relationships. However, the growth of big data is straining the capacities of current semantic fusion and reasoning practices. Considering the massive parallelism of DNA strands, we propose a novel DNA-based semantic fusion model. In this model, a parallel strategy is developed to encode the semantic information in DNA for a large volume of remote sensing data. The semantic information is read in a parallel and bit-wise manner and an individual bit is converted to a base. By doing so, a considerable amount of conversion time can be saved, i.e., the cluster-based multi-processes program can reduce the conversion time from 81,536 seconds to 4,937 seconds for 4.34 GB source data files. Moreover, the size of result file recording DNA sequences is 54.51 GB for parallel C program compared with 57.89 GB for sequential Perl. This shows that our parallel method can also reduce the DNA synthesis cost. In addition, data types are encoded in our model, which is a basis for building type system in our future DNA computer. Finally, we describe theoretically an algorithm for DNA-based semantic fusion. This algorithm enables the process of integration of the knowledge from disparate remote sensing data sources into a consistent, accurate, and complete representation. This process depends solely on ligation reaction and screening operations instead of the ontology.

A DNA-Based Semantic Fusion Model for Remote Sensing Data

PubMed Central

Sun, Heng; Weng, Jian; Yu, Guangchuang; Massawe, Richard H.

2013-01-01

Semantic technology plays a key role in various domains, from conversation understanding to algorithm analysis. As the most efficient semantic tool, ontology can represent, process and manage the widespread knowledge. Nowadays, many researchers use ontology to collect and organize data's semantic information in order to maximize research productivity. In this paper, we firstly describe our work on the development of a remote sensing data ontology, with a primary focus on semantic fusion-driven research for big data. Our ontology is made up of 1,264 concepts and 2,030 semantic relationships. However, the growth of big data is straining the capacities of current semantic fusion and reasoning practices. Considering the massive parallelism of DNA strands, we propose a novel DNA-based semantic fusion model. In this model, a parallel strategy is developed to encode the semantic information in DNA for a large volume of remote sensing data. The semantic information is read in a parallel and bit-wise manner and an individual bit is converted to a base. By doing so, a considerable amount of conversion time can be saved, i.e., the cluster-based multi-processes program can reduce the conversion time from 81,536 seconds to 4,937 seconds for 4.34 GB source data files. Moreover, the size of result file recording DNA sequences is 54.51 GB for parallel C program compared with 57.89 GB for sequential Perl. This shows that our parallel method can also reduce the DNA synthesis cost. In addition, data types are encoded in our model, which is a basis for building type system in our future DNA computer. Finally, we describe theoretically an algorithm for DNA-based semantic fusion. This algorithm enables the process of integration of the knowledge from disparate remote sensing data sources into a consistent, accurate, and complete representation. This process depends solely on ligation reaction and screening operations instead of the ontology. PMID:24116207

Fusion of pan-tropical biomass maps using weighted averaging and regional calibration data

NASA Astrophysics Data System (ADS)

Ge, Yong; Avitabile, Valerio; Heuvelink, Gerard B. M.; Wang, Jianghao; Herold, Martin

2014-09-01

Biomass is a key environmental variable that influences many biosphere-atmosphere interactions. Recently, a number of biomass maps at national, regional and global scales have been produced using different approaches with a variety of input data, such as from field observations, remotely sensed imagery and other spatial datasets. However, the accuracy of these maps varies regionally and is largely unknown. This research proposes a fusion method to increase the accuracy of regional biomass estimates by using higher-quality calibration data. In this fusion method, the biases in the source maps were first adjusted to correct for over- and underestimation by comparison with the calibration data. Next, the biomass maps were combined linearly using weights derived from the variance-covariance matrix associated with the accuracies of the source maps. Because each map may have different biases and accuracies for different land use types, the biases and fusion weights were computed for each of the main land cover types separately. The conceptual arguments are substantiated by a case study conducted in East Africa. Evaluation analysis shows that fusing multiple source biomass maps may produce a more accurate map than when only one biomass map or unweighted averaging is used.

Flexible ureterorenoscopy in position or fusion anomaly: Is it feasible?

PubMed

Astolfi, Rafael Haddad; Freschi, Gustavo; Berti, Fernando Figueiredo; Gattas, Nelson; Molina, Wilson Rica; Meller, Alex

2017-08-01

To analyze the results of flexible ureterorenoscopy (F-URS) with holmium laser in the treatment of kidney stones with ectopic and fusion anomalies (horseshoe kidney and rotation anomalies). We reviewed data from 13 patients with fusion and ectopic renal anomalies that underwent F-URS from April 2011 to April 2017. We analyzed demographic and clinical data (age, gender, BMI, anatomical abnormality, location and dimension of the renal calculi) and perioperative data (method of treatment, stone-free rate, number of days with DJ catheter and perioperative complications). The mean stone size was 12.23 +/- 5.43 mm (range 6-22mm), located in the inferior (58.33%) and middle (16.76%) calyceal units, renal pelvis (16.67%) and multiple locations (8.33%). All 13 patients were treated with Ho-Yag laser, using dusting technique (25%), fragmentation and extraction of the calculi (58.33%) and mixed technique (16.67%). We did not have any severe perioperative complication. After 90 days, nine patients (75%) were considered stone free. Our data suggest that F-URS is a safe and feasible choice for the treatment of kidney stones in patients with renal ectopic and fusion anomalies.

Kinetic analysis of thermal stability of human low density lipoproteins: a model for LDL fusion in atherogenesis[S

PubMed Central

Lu, Mengxiao; Gantz, Donald L.; Herscovitz, Haya; Gursky, Olga

2012-01-01

Fusion of modified LDL in the arterial wall promotes atherogenesis. Earlier we showed that thermal denaturation mimics LDL remodeling and fusion, and revealed kinetic origin of LDL stability. Here we report the first quantitative analysis of LDL thermal stability. Turbidity data show sigmoidal kinetics of LDL heat denaturation, which is unique among lipoproteins, suggesting that fusion is preceded by other structural changes. High activation energy of denaturation, Ea = 100 ± 8 kcal/mol, indicates disruption of extensive packing interactions in LDL. Size-exclusion chromatography, nondenaturing gel electrophoresis, and negative-stain electron microscopy suggest that LDL dimerization is an early step in thermally induced fusion. Monoclonal antibody binding suggests possible involvement of apoB N-terminal domain in early stages of LDL fusion. LDL fusion accelerates at pH < 7, which may contribute to LDL retention in acidic atherosclerotic lesions. Fusion also accelerates upon increasing LDL concentration in near-physiologic range, which likely contributes to atherogenesis. Thermal stability of LDL decreases with increasing particle size, indicating that the pro-atherogenic properties of small dense LDL do not result from their enhanced fusion. Our work provides the first kinetic approach to measuring LDL stability and suggests that lipid-lowering therapies that reduce LDL concentration but increase the particle size may have opposite effects on LDL fusion. PMID:22855737

Kinetic analysis of thermal stability of human low density lipoproteins: a model for LDL fusion in atherogenesis.

PubMed

Lu, Mengxiao; Gantz, Donald L; Herscovitz, Haya; Gursky, Olga

2012-10-01

Fusion of modified LDL in the arterial wall promotes atherogenesis. Earlier we showed that thermal denaturation mimics LDL remodeling and fusion, and revealed kinetic origin of LDL stability. Here we report the first quantitative analysis of LDL thermal stability. Turbidity data show sigmoidal kinetics of LDL heat denaturation, which is unique among lipoproteins, suggesting that fusion is preceded by other structural changes. High activation energy of denaturation, E(a) = 100 ± 8 kcal/mol, indicates disruption of extensive packing interactions in LDL. Size-exclusion chromatography, nondenaturing gel electrophoresis, and negative-stain electron microscopy suggest that LDL dimerization is an early step in thermally induced fusion. Monoclonal antibody binding suggests possible involvement of apoB N-terminal domain in early stages of LDL fusion. LDL fusion accelerates at pH < 7, which may contribute to LDL retention in acidic atherosclerotic lesions. Fusion also accelerates upon increasing LDL concentration in near-physiologic range, which likely contributes to atherogenesis. Thermal stability of LDL decreases with increasing particle size, indicating that the pro-atherogenic properties of small dense LDL do not result from their enhanced fusion. Our work provides the first kinetic approach to measuring LDL stability and suggests that lipid-lowering therapies that reduce LDL concentration but increase the particle size may have opposite effects on LDL fusion.

A testbed for architecture and fidelity trade studies in the Bayesian decision-level fusion of ATR products

NASA Astrophysics Data System (ADS)

Erickson, Kyle J.; Ross, Timothy D.

2007-04-01

Decision-level fusion is an appealing extension to automatic/assisted target recognition (ATR) as it is a low-bandwidth technique bolstered by a strong theoretical foundation that requires no modification of the source algorithms. Despite the relative simplicity of decision-level fusion, there are many options for fusion application and fusion algorithm specifications. This paper describes a tool that allows trade studies and optimizations across these many options, by feeding an actual fusion algorithm via models of the system environment. Models and fusion algorithms can be specified and then exercised many times, with accumulated results used to compute performance metrics such as probability of correct identification. Performance differences between the best of the contributing sources and the fused result constitute examples of "gain." The tool, constructed as part of the Fusion for Identifying Targets Experiment (FITE) within the Air Force Research Laboratory (AFRL) Sensors Directorate ATR Thrust, finds its main use in examining the relationships among conditions affecting the target, prior information, fusion algorithm complexity, and fusion gain. ATR as an unsolved problem provides the main challenges to fusion in its high cost and relative scarcity of training data, its variability in application, the inability to produce truly random samples, and its sensitivity to context. This paper summarizes the mathematics underlying decision-level fusion in the ATR domain and describes a MATLAB-based architecture for exploring the trade space thus defined. Specific dimensions within this trade space are delineated, providing the raw material necessary to define experiments suitable for multi-look and multi-sensor ATR systems.

Improving the reliability of automated non-destructive inspection

NASA Astrophysics Data System (ADS)

Brierley, N.; Tippetts, T.; Cawley, P.

2014-02-01

In automated NDE a region of an inspected component is often interrogated several times, be it within a single data channel, across multiple channels or over the course of repeated inspections. The systematic combination of these diverse readings is recognized to provide a means to improve the reliability of the inspection, for example by enabling noise suppression. Specifically, such data fusion makes it possible to declare regions of the component defect-free to a very high probability whilst readily identifying indications. Registration, aligning input datasets to a common coordinate system, is a critical pre-computation before meaningful data fusion takes place. A novel scheme based on a multiobjective optimization is described. The developed data fusion framework, that is able to identify and rate possible indications in the dataset probabilistically, based on local data statistics, is outlined. The process is demonstrated on large data sets from the industrial ultrasonic testing of aerospace turbine disks, with major improvements in the probability of detection and probability of false call being obtained.

Enterotoxigenic Escherichia coli heat-stable toxin and heat-labile toxin toxoid fusion 3xSTaN12S-dmLT induces neutralizing anti-STa antibodies in subcutaneously immunized mice.

PubMed

Nandre, Rahul; Ruan, Xiaosai; Duan, Qiangde; Zhang, Weiping

2016-11-02

Enterotoxigenic Escherichia coli (ETEC) bacteria producing heat-stable toxin (STa) and/or heat-labile toxin (LT) are among top causes of children's diarrhea and travelers' diarrhea. Currently no vaccines are available for ETEC associated diarrhea. A major challenge in developing ETEC vaccines is the inability to stimulate protective antibodies against the key STa toxin which is potently toxic and also poorly immunogenic. A recent study suggested toxoid fusion 3xSTa N12S -dmLT, which consists of a monomer LT toxoid (LT R192G/L211A ) and three copies of STa toxoid STa N12S , may represent an optimal immunogen inducing neutralizing antibodies against STa toxin [IAI 2014, 82(5):1823-32]. In this study, we immunized mice with this fusion protein following a different parenteral route and using different adjuvants to further characterize immunogenicity of this toxoid fusion. Data from this study showed that 3xSTa N12S -dmLT toxoid fusion induced neutralizing anti-STa antibodies in the mice following subcutaneous immunization, as effectively as in the mice under intraperitoneal route. Data also indicated that double mutant LT (dmLT) can be an effective adjuvant for this toxoid fusion in mice subcutaneous immunization. Results from this study affirmed that toxoid fusion 3xSTa N12S -dmLT induces neutralizing antibodies against STa toxin, suggesting this toxoid fusion is potentially a promising immunogen for ETEC vaccine development. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Extended optical model analyses of elastic scattering and fusion cross sections for heavy-ion collisions with loosely bound projectiles at near-Coulomb-barrier energies

NASA Astrophysics Data System (ADS)

So, W. Y.; Hong, S. W.; Kim, B. T.; Udagawa, T.

2004-06-01

Within the framework of an extended optical model, simultaneous χ2 analyses are performed for elastic scattering and fusion cross-section data for 9Be + 209 Bi and 6Li + 208 Pb systems, both involving loosely bound projectiles, at near-Coulomb-barrier energies to determine the polarization potential as decomposed into direct reaction (DR) and fusion parts. We show that both DR and fusion potentials extracted from χ2 analyses separately satisfy the dispersion relation, and that the expected threshold anomaly appears in the fusion part. The DR potential turns out to be a rather smooth function of the incident energy, and has a magnitude at the strong absorption radius much larger than the fusion potential, explaining why a threshold anomaly has not been seen in optical potentials deduced from fits to the elastic-scattering data without such a decomposition. Using the extracted DR potential, we examine the effects of projectile breakup on fusion cross sections σF . The observed suppression of σF in the above-barrier region can be explained in terms of the flux loss due to breakup. However, the observed enhancement of σF in the subbarrier region cannot be understood in terms of the breakup effect. Rather, the enhancement can be related to the Q value of the neutron transfer within the systems, supporting the ideas of

Revised analysis of Ca 40 + Zr 96 fusion reactions

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

Esbensen, H.; Montagnoli, G.; Stefanini, A. M.

2016-03-10

Fusion data for 40Ca + 96Zr are analyzed by coupled-channels calculations that are based on a standard Woods-Saxon potential and include couplings to multiphonon excitations and transfer channels. The couplings to multiphonon excitations are the same as those used in a previous work. The transfer couplings are calibrated to reproduce the measured neutron transfer data. This type of calculation gives a poor fit to the fusion data. However, by multiplying the transfer couplings with a √2 one obtains an excellent fit. Finally, the scaling of the transfer strengths is supposed to simulate the combined effect of neutron and proton transfer,more » and the calculated one- and two-nucleon transfer cross sections are indeed in reasonable agreement with the measured cross sections.« less

ATG14 controls SNARE-mediated autophagosome fusion with a lysosome.

PubMed

Liu, Rong; Zhi, Xiaoyong; Zhong, Qing

2015-01-01

Autophagosome fusion with a lysosome constitutes the last barrier for autophagic degradation. It is speculated that this fusion process is precisely and tightly regulated. Recent genetic evidence suggests that a set of SNARE proteins, including STX17, SNAP29, and VAMP8, are essential for the fusion between autophagosomes and lysosomes. However, it remains unclear whether these SNAREs are fusion competent and how their fusogenic activity is specifically regulated during autophagy. Using a combination of biochemical, cell biology, and genetic approaches, we demonstrated that fusogenic activity of the autophagic SNARE complex is temporally and spatially controlled by ATG14/Barkor/Atg14L, an essential autophagy-specific regulator of the class III phosphatidylinositol 3-kinase complex (PtdIns3K). ATG14 directly binds to the STX17-SNAP29 binary complex on autophagosomes and promotes STX17-SNAP29-VAMP8-mediated autophagosome fusion with lysosomes. ATG14 homo-oligomerization is required for SNARE binding and fusion promotion, but is dispensable for PtdIns3K stimulation and autophagosome biogenesis. Consequently, ATG14 homo-oligomerization is required for autophagosome fusion with a lysosome, but is dispensable for autophagosome biogenesis. These data support a key role of ATG14 in controlling autophagosome fusion with a lysosome.

Materials handbook for fusion energy systems

NASA Astrophysics Data System (ADS)

Davis, J. W.; Marchbanks, M. F.

A materials data book for use in the design and analysis of components and systems in near term experimental and commercial reactor concepts has been created by the Office of Fusion Energy. The handbook is known as the Materials Handbook for Fusion Energy Systems (MHFES) and is available to all organizations actively involved in fusion related research or system designs. Distribution of the MHFES and its data pages is handled by the Hanford Engineering Development Laboratory (HEDL), while its direction and content is handled by McDonnell Douglas Astronautics Company — St. Louis (MDAC-STL). The MHFES differs from other handbooks in that its format is geared more to the designer and structural analyst than to the materials scientist or materials engineer. The format that is used organizes the handbook by subsystems or components rather than material. Within each subsystem is information pertaining to material selection, specific material properties, and comments or recommendations on treatment of data. Since its inception a little more than a year ago, over 80 copies have been distributed to over 28 organizations consisting of national laboratories, universities, and private industries.

Multi-sensor fusion of Landsat 8 thermal infrared (TIR) and panchromatic (PAN) images.

PubMed

Jung, Hyung-Sup; Park, Sung-Whan

2014-12-18

Data fusion is defined as the combination of data from multiple sensors such that the resulting information is better than would be possible when the sensors are used individually. The multi-sensor fusion of panchromatic (PAN) and thermal infrared (TIR) images is a good example of this data fusion. While a PAN image has higher spatial resolution, a TIR one has lower spatial resolution. In this study, we have proposed an efficient method to fuse Landsat 8 PAN and TIR images using an optimal scaling factor in order to control the trade-off between the spatial details and the thermal information. We have compared the fused images created from different scaling factors and then tested the performance of the proposed method at urban and rural test areas. The test results show that the proposed method merges the spatial resolution of PAN image and the temperature information of TIR image efficiently. The proposed method may be applied to detect lava flows of volcanic activity, radioactive exposure of nuclear power plants, and surface temperature change with respect to land-use change.

[Data fusion and multi-components quantitative analysis for identification and quality evaluation of Gentiana rigescens from different geographical origins].

PubMed

Wang, Qin-Qin; Shen, Tao; Zuo, Zhi-Tian; Huang, Heng-Yu; Wang, Yuan-Zhong

2018-03-01

The accumulation of secondary metabolites of traditional Chinese medicine (TCM) is closely related to its origins. The identification of origins and multi-components quantitative evaluation are of great significance to ensure the quality of medicinal materials. In this study, the identification of Gentiana rigescens from different geographical origins was conducted by data fusion of Fourier transform infrared (FTIR) spectroscopy and high performance liquid chromatography (HPLC) in combination of partial least squares discriminant analysis; meanwhile quantitative analysis of index components was conducted to provide an accurate and comprehensive identification and quality evaluation strategy for selecting the best production areas of G. rigescens. In this study, the FTIR and HPLC information of 169 G. rigescens samples from Yunnan, Sichuan, Guangxi and Guizhou Provinces were collected. The raw infrared spectra were pre-treated by multiplicative scatter correction, standard normal variate (SNV) and Savitzky-Golay (SG) derivative. Then the performances of FTIR, HPLC, and low-level data fusion and mid-level data fusion for identification were compared, and the contents of gentiopicroside, swertiamarin, loganic acid and sweroside were determined by HPLC. The results showed that the FTIR spectra of G. rigescens from different geographical origins were different, and the best pre-treatment method was SNV+SG-derivative (second derivative, 15 as the window parameter, and 2 as the polynomial order). The results showed that the accuracy rate of low- and mid-level data fusion (96.43%) in prediction set was higher than that of FTIR and HPLC (94.64%) in prediction set. In addition, the accuracy of low-level data fusion (100%) in the training set was higher than that of mid-level data fusion (99.12%) in training set. The contents of the iridoid glycosides in Yunnan were the highest among different provinces. The average content of gentiopicroside, as a bioactive marker in Chinese pharmacopoeia, was 47.40 mg·g⁻¹, and the maximum was 79.83 mg·g⁻¹. The contents of loganic acid, sweroside and gentiopicroside in Yunnan were significantly different from other provinces ( P <0.05). In comparison of total content of iridoid glycosides in G. rigescens with different geographical origins in Yunnan, it was found that the amount of iridoid glycosides was higher in Eryuan Dali (68.59 mg·g⁻¹) and Yulong Lijiang (66.68 mg·g⁻¹), significantly higher than that in Wuding Chuxiong (52.99 mg·g⁻¹), Chengjiang Yuxi (52.29 mg·g⁻¹) and Xundian Kunming (46.71 mg·g⁻¹) ( P <0.05), so these two places can be used as a reference region for screening cultivation and excellent germplasm resources of G. rigescens. A comprehensive and accurate method was established by data fusion of HPLC-FTIR and quantitative analysis of HPLC for identification and quality evaluation of G. rigescens, which could provide a support for the development and utilization of G. rigescens. Copyright© by the Chinese Pharmaceutical Association.

Fusion Rates of Different Anterior Grafts in Thoracolumbar Fractures.

PubMed

Antoni, Maxime; Charles, Yann Philippe; Walter, Axel; Schuller, Sébastien; Steib, Jean-Paul

2015-11-01

Retrospective CT analysis of anterior fusion in thoracolumbar trauma. The aim of this study was to compare fusion rates of different bone grafts and to analyze risk factors for pseudarthrosis. Interbody fusion is indicated in anterior column defects. Different grafts are used: autologous iliac crest, titanium mesh cages filled with cancellous bone, and autologous ribs. It is not clear which graft offers the most reliable fusion. Radiologic data of 116 patients (71 men, 45 women) operated for type A2, A3, B, or C fractures were analyzed. The average age was 44.6 years (range, 16-75 y) and follow-up was 2.7 years (range, 1-9 y). All patients were treated by posterior instrumentation followed by an anterior graft: 53 cases with iliac crest, 43 cases with mesh cages, and 20 with rib grafts. Fusion was evaluated on CT and classified into complete fusion, partial fusion, unipolar pseudarthrosis, and bipolar pseudarthrosis. Iliac crest fused in 66%, cages in 98%, and rib grafts in 90%. The fusion rate of cages filled with bone was significantly higher as the iliac graft fusion rate (P=0.002). The same was applied to rib grafts compared with iliac crest (P=0.041). Additional bone formation around the main graft, bridging both vertebral bodies, was observed in 31 of the 53 iliac crests grafts. Pseudarthrosis occurred more often in smokers (P=0.042). A relationship between fracture or instrumentation types, sex, age, BMI, and fusion could not be determined. Tricortical iliac crest grafts showed an unexpected high pseudarthrosis rate in thoracolumbar injuries. Their cortical bone is dense and their fusion surface is small. Rib grafts led to a better fusion when used in combination with the cancellous bone from the fractured vertebral body. Titanium mesh cages filled with cancellous bone led to the highest fusion rate and built a complete bony bridge between vertebral bodies. Smoking seemed to influence fusion. Case control study, Level III.

Effects of magnetization on fusion product trapping and secondary neutron spectraa)

NASA Astrophysics Data System (ADS)

Knapp, P. F.; Schmit, P. F.; Hansen, S. B.; Gomez, M. R.; Hahn, K. D.; Sinars, D. B.; Peterson, K. J.; Slutz, S. A.; Sefkow, A. B.; Awe, T. J.; Harding, E.; Jennings, C. A.; Desjarlais, M. P.; Chandler, G. A.; Cooper, G. W.; Cuneo, M. E.; Geissel, M.; Harvey-Thompson, A. J.; Porter, J. L.; Rochau, G. A.; Rovang, D. C.; Ruiz, C. L.; Savage, M. E.; Smith, I. C.; Stygar, W. A.; Herrmann, M. C.

2015-05-01

By magnetizing the fusion fuel in inertial confinement fusion (ICF) systems, the required stagnation pressure and density can be relaxed dramatically. This happens because the magnetic field insulates the hot fuel from the cold pusher and traps the charged fusion burn products. This trapping allows the burn products to deposit their energy in the fuel, facilitating plasma self-heating. Here, we report on a comprehensive theory of this trapping in a cylindrical DD plasma magnetized with a purely axial magnetic field. Using this theory, we are able to show that the secondary fusion reactions can be used to infer the magnetic field-radius product, BR, during fusion burn. This parameter, not ρR, is the primary confinement parameter in magnetized ICF. Using this method, we analyze data from recent Magnetized Liner Inertial Fusion experiments conducted on the Z machine at Sandia National Laboratories. We show that in these experiments BR ≈ 0.34(+0.14/-0.06) MG . cm, a ˜ 14× increase in BR from the initial value, and confirming that the DD-fusion tritons are magnetized at stagnation. This is the first experimental verification of charged burn product magnetization facilitated by compression of an initial seed magnetic flux.

Evidence that the lung Adenocarcinoma EML4-ALK fusion gene is not caused by exposure to secondhand tobacco smoke during childhood.

PubMed

Ryan, Bríd M; Wang, Yi; Jen, Jin; Yi, Eunhee S; Olivo-Marston, Susan; Yang, Ping; Harris, Curtis C

2014-07-01

The EML4-ALK fusion gene is more frequently found in younger, never smoking patients with lung cancer. Meanwhile, never smokers exposed to secondhand tobacco smoke (SHS) during childhood are diagnosed at a younger age compared with never smoking patients with lung cancer who are not exposed. We, therefore, hypothesized that SHS, which can induce DNA damage, is associated with the EML4-ALK fusion gene. We compared the frequency of the EML4-ALK fusion gene among 197 never smoker patients with lung cancer with and without a history of exposure to SHS during childhood at Mayo Clinic. The EML4-ALK fusion gene was detected in 33% of cases from never smokers with a history of SHS exposure during childhood, whereas 47% of never smoking lung cancer cases without a history of childhood SHS exposure tested positive for the fusion gene. The EML4-ALK fusion gene is not enriched in tumors from individuals exposed to SHS during childhood. These data suggest that childhood exposure to SHS is not a significant etiologic cause of the EML4-ALK fusion gene in lung cancer. ©2014 American Association for Cancer Research.

SARS-CoV fusion peptides induce membrane surface ordering and curvature.

PubMed

Basso, Luis G M; Vicente, Eduardo F; Crusca, Edson; Cilli, Eduardo M; Costa-Filho, Antonio J

2016-11-28

Viral membrane fusion is an orchestrated process triggered by membrane-anchored viral fusion glycoproteins. The S2 subunit of the spike glycoprotein from severe acute respiratory syndrome (SARS) coronavirus (CoV) contains internal domains called fusion peptides (FP) that play essential roles in virus entry. Although membrane fusion has been broadly studied, there are still major gaps in the molecular details of lipid rearrangements in the bilayer during fusion peptide-membrane interactions. Here we employed differential scanning calorimetry (DSC) and electron spin resonance (ESR) to gather information on the membrane fusion mechanism promoted by two putative SARS FPs. DSC data showed the peptides strongly perturb the structural integrity of anionic vesicles and support the hypothesis that the peptides generate opposing curvature stresses on phosphatidylethanolamine membranes. ESR showed that both FPs increase lipid packing and head group ordering as well as reduce the intramembrane water content for anionic membranes. Therefore, bending moment in the bilayer could be generated, promoting negative curvature. The significance of the ordering effect, membrane dehydration, changes in the curvature properties and the possible role of negatively charged phospholipids in helping to overcome the high kinetic barrier involved in the different stages of the SARS-CoV-mediated membrane fusion are discussed.

Improved Classification of Orthosiphon stamineus by Data Fusion of Electronic Nose and Tongue Sensors

PubMed Central

Zakaria, Ammar; Shakaff, Ali Yeon Md.; Adom, Abdul Hamid; Ahmad, Mohd Noor; Masnan, Maz Jamilah; Aziz, Abdul Hallis Abdul; Fikri, Nazifah Ahmad; Abdullah, Abu Hassan; Kamarudin, Latifah Munirah

2010-01-01

An improved classification of Orthosiphon stamineus using a data fusion technique is presented. Five different commercial sources along with freshly prepared samples were discriminated using an electronic nose (e-nose) and an electronic tongue (e-tongue). Samples from the different commercial brands were evaluated by the e-tongue and then followed by the e-nose. Applying Principal Component Analysis (PCA) separately on the respective e-tongue and e-nose data, only five distinct groups were projected. However, by employing a low level data fusion technique, six distinct groupings were achieved. Hence, this technique can enhance the ability of PCA to analyze the complex samples of Orthosiphon stamineus. Linear Discriminant Analysis (LDA) was then used to further validate and classify the samples. It was found that the LDA performance was also improved when the responses from the e-nose and e-tongue were fused together. PMID:22163381

Improved classification of Orthosiphon stamineus by data fusion of electronic nose and tongue sensors.

PubMed

Zakaria, Ammar; Shakaff, Ali Yeon Md; Adom, Abdul Hamid; Ahmad, Mohd Noor; Masnan, Maz Jamilah; Aziz, Abdul Hallis Abdul; Fikri, Nazifah Ahmad; Abdullah, Abu Hassan; Kamarudin, Latifah Munirah

2010-01-01

An improved classification of Orthosiphon stamineus using a data fusion technique is presented. Five different commercial sources along with freshly prepared samples were discriminated using an electronic nose (e-nose) and an electronic tongue (e-tongue). Samples from the different commercial brands were evaluated by the e-tongue and then followed by the e-nose. Applying Principal Component Analysis (PCA) separately on the respective e-tongue and e-nose data, only five distinct groups were projected. However, by employing a low level data fusion technique, six distinct groupings were achieved. Hence, this technique can enhance the ability of PCA to analyze the complex samples of Orthosiphon stamineus. Linear Discriminant Analysis (LDA) was then used to further validate and classify the samples. It was found that the LDA performance was also improved when the responses from the e-nose and e-tongue were fused together.

An Analytical Framework for Soft and Hard Data Fusion: A Dempster-Shafer Belief Theoretic Approach

DTIC Science & Technology

2012-08-01

fusion. Therefore, we provide a detailed discussion on uncertain data types, their origins and three uncertainty pro- cessing formalisms that are popular...suitable membership functions corresponding to the fuzzy sets. 3.2.3 DS Theory The DS belief theory, originally proposed by Dempster, can be thought of as... originated and various imperfections of the source. Uncertainty handling formalisms provide techniques for modeling and working with these uncertain data types

Characterizing the astrophysical S factor for 12C+12C fusion with wave-packet dynamics

NASA Astrophysics Data System (ADS)

Diaz-Torres, Alexis; Wiescher, Michael

2018-05-01

A quantitative study of the astrophysically important subbarrier fusion of 12C+12C is presented. Low-energy collisions are described in the body-fixed reference frame using wave-packet dynamics within a nuclear molecular picture. A collective Hamiltonian drives the time propagation of the wave packet through the collective potential-energy landscape. The fusion imaginary potential for specific dinuclear configurations is crucial for understanding the appearance of resonances in the fusion cross section. The theoretical subbarrier fusion cross sections explain some observed resonant structures in the astrophysical S factor. These cross sections monotonically decline towards stellar energies. The structures in the data that are not explained are possibly due to cluster effects in the nuclear molecule, which need to be included in the present approach.

Recurrent hyperactive ESR1 fusion proteins in endocrine therapy-resistant breast cancer.

PubMed

Hartmaier, R J; Trabucco, S E; Priedigkeit, N; Chung, J H; Parachoniak, C A; Vanden Borre, P; Morley, S; Rosenzweig, M; Gay, L M; Goldberg, M E; Suh, J; Ali, S M; Ross, J; Leyland-Jones, B; Young, B; Williams, C; Park, B; Tsai, M; Haley, B; Peguero, J; Callahan, R D; Sachelarie, I; Cho, J; Atkinson, J M; Bahreini, A; Nagle, A M; Puhalla, S L; Watters, R J; Erdogan-Yildirim, Z; Cao, L; Oesterreich, S; Mathew, A; Lucas, P C; Davidson, N E; Brufsky, A M; Frampton, G M; Stephens, P J; Chmielecki, J; Lee, A V

2018-04-01

Estrogen receptor-positive (ER-positive) metastatic breast cancer is often intractable due to endocrine therapy resistance. Although ESR1 promoter switching events have been associated with endocrine-therapy resistance, recurrent ESR1 fusion proteins have yet to be identified in advanced breast cancer. To identify genomic structural rearrangements (REs) including gene fusions in acquired resistance, we undertook a multimodal sequencing effort in three breast cancer patient cohorts: (i) mate-pair and/or RNAseq in 6 patient-matched primary-metastatic tumors and 51 metastases, (ii) high coverage (>500×) comprehensive genomic profiling of 287-395 cancer-related genes across 9542 solid tumors (5216 from metastatic disease), and (iii) ultra-high coverage (>5000×) genomic profiling of 62 cancer-related genes in 254 ctDNA samples. In addition to traditional gene fusion detection methods (i.e. discordant reads, split reads), ESR1 REs were detected from targeted sequencing data by applying a novel algorithm (copyshift) that identifies major copy number shifts at rearrangement hotspots. We identify 88 ESR1 REs across 83 unique patients with direct confirmation of 9 ESR1 fusion proteins (including 2 via immunoblot). ESR1 REs are highly enriched in ER-positive, metastatic disease and co-occur with known ESR1 missense alterations, suggestive of polyclonal resistance. Importantly, all fusions result from a breakpoint in or near ESR1 intron 6 and therefore lack an intact ligand binding domain (LBD). In vitro characterization of three fusions reveals ligand-independence and hyperactivity dependent upon the 3' partner gene. Our lower-bound estimate of ESR1 fusions is at least 1% of metastatic solid breast cancers, the prevalence in ctDNA is at least 10× enriched. We postulate this enrichment may represent secondary resistance to more aggressive endocrine therapies applied to patients with ESR1 LBD missense alterations. Collectively, these data indicate that N-terminal ESR1 fusions involving exons 6-7 are a recurrent driver of endocrine therapy resistance and are impervious to ER-targeted therapies.

Oral cancer/endothelial cell fusion experiences nuclear fusion and acquisition of enhanced survival potential

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

Song, Kai; The State Key Laboratory Breeding Base of Basic Science of Stomatology; Song, Yong

Most previous studies have linked cancer–macrophage fusion with tumor progression and metastasis. However, the characteristics of hybrid cells derived from oral cancer and endothelial cells and their involvement in cancer remained unknown. Double-immunofluorescent staining and fluorescent in situ hybridization (FISH) were performed to confirm spontaneous cell fusion between eGFP-labeled human umbilical vein endothelial cells (HUVECs) and RFP-labeled SCC9, and to detect the expression of vementin and cytokeratin 18 in the hybrids. The property of chemo-resistance of such hybrids was examined by TUNEL assay. The hybrid cells in xenografted tumor were identified by FISH and GFP/RFP dual-immunofluoresence staining. We showed thatmore » SCC9 cells spontaneously fused with cocultured endothelial cells, and the resultant hybrid cells maintained the division and proliferation activity after re-plating and thawing. Such hybrids expressed markers of both parental cells and became more resistant to chemotherapeutic drug cisplatin as compared to the parental SCC9 cells. Our in vivo data indicated that the hybrid cells contributed to tumor composition by using of immunostaining and FISH analysis, even though the hybrid cells and SCC9 cells were mixed with 1:10,000, according to the FACS data. Our study suggested that the fusion events between oral cancer and endothelial cells undergo nuclear fusion and acquire a new property of drug resistance and consequently enhanced survival potential. These experimental findings provide further supportive evidence for the theory that cell fusion is involved in cancer progression. - Highlights: • The fusion events between oral cancer and endothelial cells undergo nuclear fusion. • The resulting hybrid cells acquire a new property of drug resistance. • The resulting hybrid cells express the markers of both parental cells (i.e. vimentin and cytokeratin 18). • The hybrid cells contribute to tumor repopulation in vivo.« less

Evaluating the potential of image fusion of multispectral and radar remote sensing data for the assessment of water body structure

NASA Astrophysics Data System (ADS)

Hunger, Sebastian; Karrasch, Pierre; Wessollek, Christine

2016-10-01

The European Water Framework Directive (Directive 2000/60/EC) is a mandatory agreement that guides the member states of the European Union in the field of water policy to fulfill the requirements for reaching the aim of the good ecological status of water bodies. In the last years several workflows and methods were developed to determine and evaluate the characteristics and the status of the water bodies. Due to their area measurements remote sensing methods are a promising approach to constitute a substantial additional value. With increasing availability of optical and radar remote sensing data the development of new methods to extract information from both types of remote sensing data is still in progress. Since most limitations of these data sets do not agree the fusion of both data sets to gain data with higher spectral resolution features the potential to obtain additional information in contrast to the separate processing of the data. Based thereupon this study shall research the potential of multispectral and radar remote sensing data and the potential of their fusion for the assessment of the parameters of water body structure. Due to the medium spatial resolution of the freely available multispectral Sentinel-2 data sets especially the surroundings of the water bodies and their land use are part of this study. SAR data is provided by the Sentinel-1 satellite. Different image fusion methods are tested and the combined products of both data sets are evaluated afterwards. The evaluation of the single data sets and the fused data sets is performed by means of a maximum-likelihood classification and several statistical measurements. The results indicate that the combined use of different remote sensing data sets can have an added value.

SENTINEL-1 and SENTINEL-2 Data Fusion for Wetlands Mapping: Balikdami, Turkey

NASA Astrophysics Data System (ADS)

Kaplan, G.; Avdan, U.

2018-04-01

Wetlands provide a number of environmental and socio-economic benefits such as their ability to store floodwaters and improve water quality, providing habitats for wildlife and supporting biodiversity, as well as aesthetic values. Remote sensing technology has proven to be a useful and frequent application in monitoring and mapping wetlands. Combining optical and microwave satellite data can help with mapping and monitoring the biophysical characteristics of wetlands and wetlands` vegetation. Also, fusing radar and optical remote sensing data can increase the wetland classification accuracy. In this paper, data from the fine spatial resolution optical satellite, Sentinel-2 and the Synthetic Aperture Radar Satellite, Sentinel-1, were fused for mapping wetlands. Both Sentinel-1 and Sentinel-2 images were pre-processed. After the pre-processing, vegetation indices were calculated using the Sentinel-2 bands and the results were included in the fusion data set. For the classification of the fused data, three different classification approaches were used and compared. The results showed significant improvement in the wetland classification using both multispectral and microwave data. Also, the presence of the red edge bands and the vegetation indices used in the data set showed significant improvement in the discrimination between wetlands and other vegetated areas. The statistical results of the fusion of the optical and radar data showed high wetland mapping accuracy, showing an overall classification accuracy of approximately 90 % in the object-based classification method. For future research, we recommend multi-temporal image use, terrain data collection, as well as a comparison of the used method with the traditional image fusion techniques.

Three-Dimensional Road Network by Fusion of Polarimetric and Interferometric SAR Data

NASA Technical Reports Server (NTRS)

Gamba, P.; Houshmand, B.

1998-01-01

In this paper a fuzzy classification procedure is applied to polarimetric radar measurements, and street pixels are detected. These data are successively grouped into consistent roads by means of a dynamic programming approach based on the fuzzy membership function values. Further fusion of the 2D road network extracted and 3D TOPSAR measurements provides a powerful way to analyze urban infrastructures.

Joint Data Management for MOVINT Data-to-Decision Making

DTIC Science & Technology

2011-07-01

flux tensor , aligned motion history images, and related approaches have been shown to be versatile approaches [12, 16, 17, 18]. Scaling these...methods include voting , neural networks, fuzzy logic, neuro-dynamic programming, support vector machines, Bayesian and Dempster-Shafer methods. One way...Information Fusion, 2010. [16] F. Bunyak, K. Palaniappan, S. K. Nath, G. Seetharaman, “Flux tensor constrained geodesic active contours with sensor fusion

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

L. Zakharov, J. Li and Y. Wu

The project of ASIPP (with PPPL participation), called FFRF, (R/a=4/1 m/m, Ipl=5 MA, Btor=4-6 T, PDT=50-100 MW, Pfission=80-4000 MW, 1 m thick blanket) is outlined. FFRF stands for the Fusion-Fission Research Facility with a unique fusion mission and a pioneering mission of merging fusion and fission for accumulation of design, experimental, and operational data for future hybrid applications. The design of FFRF will use as much as possible the EAST and ITER design experience. On the other hand, FFRF strongly relies on new, Lithium Wall Fusion plasma regimes, the development of which has already started in the US and China.

Low-energy nuclear reaction of the 14N+169Tm system: Incomplete fusion

NASA Astrophysics Data System (ADS)

Kumar, R.; Sharma, Vijay R.; Yadav, Abhishek; Singh, Pushpendra P.; Agarwal, Avinash; Appannababu, S.; Mukherjee, S.; Singh, B. P.; Ali, R.; Bhowmik, R. K.

2017-11-01

Excitation functions of reaction residues produced in the 14N+169Tm system have been measured to high precision at energies above the fusion barrier, ranging from 1.04 VB to 1.30 VB , and analyzed in the framework of the statistical model code pace4. Analysis of α -emitting channels points toward the onset of incomplete fusion even at slightly above-barrier energies where complete fusion is supposed to be one of the dominant processes. The onset and strength of incomplete fusion have been deduced and studied in terms of various entrance channel parameters. Present results together with the reanalysis of existing data for various projectile-target combinations conclusively suggest strong influence of projectile structure on the onset of incomplete fusion. Also, a strong dependence on the Coulomb effect (ZPZT) has been observed for the present system along with different projectile-target combinations available in the literature. It is concluded that the fraction of incomplete fusion linearly increases with ZPZT and is found to be more for larger ZPZT values, indicating significantly important linear systematics.

Structure-function analysis of myomaker domains required for myoblast fusion.

PubMed

Millay, Douglas P; Gamage, Dilani G; Quinn, Malgorzata E; Min, Yi-Li; Mitani, Yasuyuki; Bassel-Duby, Rhonda; Olson, Eric N

2016-02-23

During skeletal muscle development, myoblasts fuse to form multinucleated myofibers. Myomaker [Transmembrane protein 8c (TMEM8c)] is a muscle-specific protein that is essential for myoblast fusion and sufficient to promote fusion of fibroblasts with muscle cells; however, the structure and biochemical properties of this membrane protein have not been explored. Here, we used CRISPR/Cas9 mutagenesis to disrupt myomaker expression in the C2C12 muscle cell line, which resulted in complete blockade to fusion. To define the functional domains of myomaker required to direct fusion, we established a heterologous cell-cell fusion system, in which fibroblasts expressing mutant versions of myomaker were mixed with WT myoblasts. Our data indicate that the majority of myomaker is embedded in the plasma membrane with seven membrane-spanning regions and a required intracellular C-terminal tail. We show that myomaker function is conserved in other mammalian orthologs; however, related family members (TMEM8a and TMEM8b) do not exhibit fusogenic activity. These findings represent an important step toward deciphering the cellular components and mechanisms that control myoblast fusion and muscle formation.

Experiment and Theory for Nuclear Reactions in Nano-Materials Show e14 - e16 Solid-State Fusion Reactions

NASA Astrophysics Data System (ADS)

George, Russ

2005-03-01

Nano-lattices of deuterium loving metals exhibit coherent behavior by populations of deuterons (d's) occupying a Bloch state. Therein, coherent d-overlap occurs wherein the Bloch condition reduces the Coulomb barrier.Overlap of dd pairs provides a high probability fusion will/must occur. SEM photo evidence showing fusion events is now revealed by laboratories that load or flux d into metal nano-domains. Solid-state dd fusion creates an excited ^4He nucleus entangled in the large coherent population of d's.This contrasts with plasma dd fusion in collision space where an isolated excited ^4He nucleus seeks the ground state via fast particle emission. In momentum limited solid state fusion,fast particle emission is effectively forbidden.Photographed nano-explosive events are beyond the scope of chemistry. Corroboration of the nuclear nature derives from photographic observation of similar events on spontaneous fission, e.g. Cf. We present predictive theory, heat production, and helium isotope data showing reproducible e14 to e16 solid-state fusion reactions.

Fusion of Modis and Palsar Principal Component Images Through Curvelet Transform for Land Cover Classification

NASA Astrophysics Data System (ADS)

Singh, Dharmendra; Kumar, Harish

Earth observation satellites provide data that covers different portions of the electromagnetic spectrum at different spatial and spectral resolutions. The increasing availability of information products generated from satellite images are extending the ability to understand the patterns and dynamics of the earth resource systems at all scales of inquiry. In which one of the most important application is the generation of land cover classification from satellite images for understanding the actual status of various land cover classes. The prospect for the use of satel-lite images in land cover classification is an extremely promising one. The quality of satellite images available for land-use mapping is improving rapidly by development of advanced sensor technology. Particularly noteworthy in this regard is the improved spatial and spectral reso-lution of the images captured by new satellite sensors like MODIS, ASTER, Landsat 7, and SPOT 5. For the full exploitation of increasingly sophisticated multisource data, fusion tech-niques are being developed. Fused images may enhance the interpretation capabilities. The images used for fusion have different temporal, and spatial resolution. Therefore, the fused image provides a more complete view of the observed objects. It is one of the main aim of image fusion to integrate different data in order to obtain more information that can be de-rived from each of the single sensor data alone. A good example of this is the fusion of images acquired by different sensors having a different spatial resolution and of different spectral res-olution. Researchers are applying the fusion technique since from three decades and propose various useful methods and techniques. The importance of high-quality synthesis of spectral information is well suited and implemented for land cover classification. More recently, an underlying multiresolution analysis employing the discrete wavelet transform has been used in image fusion. It was found that multisensor image fusion is a tradeoff between the spectral information from a low resolution multi-spectral images and the spatial information from a high resolution multi-spectral images. With the wavelet transform based fusion method, it is easy to control this tradeoff. A new transform, the curvelet transform was used in recent years by Starck. A ridgelet transform is applied to square blocks of detail frames of undecimated wavelet decomposition, consequently the curvelet transform is obtained. Since the ridgelet transform possesses basis functions matching directional straight lines therefore, the curvelet transform is capable of representing piecewise linear contours on multiple scales through few significant coefficients. This property leads to a better separation between geometric details and background noise, which may be easily reduced by thresholding curvelet coefficients before they are used for fusion. The Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) instrument provides high radiometric sensitivity (12 bit) in 36 spectral bands ranging in wavelength from 0.4 m to 14.4 m and also it is freely available. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km. In this paper, the band 1 of spatial resolution 250 m and bandwidth 620-670 nm, and band 2, of spatial resolution of 250m and bandwidth 842-876 nm is considered as these bands has special features to identify the agriculture and other land covers. In January 2006, the Advanced Land Observing Satellite (ALOS) was successfully launched by the Japan Aerospace Exploration Agency (JAXA). The Phased Arraytype L-band SAR (PALSAR) sensor onboard the satellite acquires SAR imagery at a wavelength of 23.5 cm (frequency 1.27 GHz) with capabilities of multimode and multipolarization observation. PALSAR can operate in several modes: the fine-beam single (FBS) polarization mode (HH), fine-beam dual (FBD) polariza-tion mode (HH/HV or VV/VH), polarimetric (PLR) mode (HH/HV/VH/VV), and ScanSAR (WB) mode (HH/VV) [15]. These makes PALSAR imagery very attractive for spatially and temporally consistent monitoring system. The Overview of Principal Component Analysis is that the most of the information within all the bands can be compressed into a much smaller number of bands with little loss of information. It allows us to extract the low-dimensional subspaces that capture the main linear correlation among the high-dimensional image data. This facilitates viewing the explained variance or signal in the available imagery, allowing both gross and more subtle features in the imagery to be seen. In this paper we have explored the fusion technique for enhancing the land cover classification of low resolution satellite data espe-cially freely available satellite data. For this purpose, we have considered to fuse the PALSAR principal component data with MODIS principal component data. Initially, the MODIS band 1 and band 2 is considered, its principal component is computed. Similarly the PALSAR HH, HV and VV polarized data are considered, and there principal component is also computed. con-sequently, the PALSAR principal component image is fused with MODIS principal component image. The aim of this paper is to analyze the effect of classification accuracy on major type of land cover types like agriculture, water and urban bodies with fusion of PALSAR data to MODIS data. Curvelet transformation has been applied for fusion of these two satellite images and Minimum Distance classification technique has been applied for the resultant fused image. It is qualitatively and visually observed that the overall classification accuracy of MODIS image after fusion is enhanced. This type of fusion technique may be quite helpful in near future to use freely available satellite data to develop monitoring system for different land cover classes on the earth.

Improving Quantitative Precipitation Estimation via Data Fusion of High-Resolution Ground-based Radar Network and CMORPH Satellite-based Product

NASA Astrophysics Data System (ADS)

Cifelli, R.; Chen, H.; Chandrasekar, V.; Xie, P.

2015-12-01

A large number of precipitation products at multi-scales have been developed based upon satellite, radar, and/or rain gauge observations. However, how to produce optimal rainfall estimation for a given region is still challenging due to the spatial and temporal sampling difference of different sensors. In this study, we develop a data fusion mechanism to improve regional quantitative precipitation estimation (QPE) by utilizing satellite-based CMORPH product, ground radar measurements, as well as numerical model simulations. The CMORPH global precipitation product is essentially derived based on retrievals from passive microwave measurements and infrared observations onboard satellites (Joyce et al. 2004). The fine spatial-temporal resolution of 0.05o Lat/Lon and 30-min is appropriate for regional hydrologic and climate studies. However, it is inadequate for localized hydrometeorological applications such as urban flash flood forecasting. Via fusion of the Regional CMORPH product and local precipitation sensors, the high-resolution QPE performance can be improved. The area of interest is the Dallas-Fort Worth (DFW) Metroplex, which is the largest land-locked metropolitan area in the U.S. In addition to an NWS dual-polarization S-band WSR-88DP radar (i.e., KFWS radar), DFW hosts the high-resolution dual-polarization X-band radar network developed by the center for Collaborative Adaptive Sensing of the Atmosphere (CASA). This talk will present a general framework of precipitation data fusion based on satellite and ground observations. The detailed prototype architecture of using regional rainfall instruments to improve regional CMORPH precipitation product via multi-scale fusion techniques will also be discussed. Particularly, the temporal and spatial fusion algorithms developed for the DFW Metroplex will be described, which utilizes CMORPH product, S-band WSR-88DP, and X-band CASA radar measurements. In order to investigate the uncertainties associated with each individual product and demonstrate the precipitation data fusion performance, both individual and fused QPE products are evaluated using rainfall measurements from a disdrometer and gauge network.

Evaluation of efficacy of a new hybrid fusion device: a randomized, two-centre controlled trial.

PubMed

Siewe, Jan; Bredow, Jan; Oppermann, Johannes; Koy, Timmo; Delank, Stefan; Knoell, Peter; Eysel, Peer; Sobottke, Rolf; Zarghooni, Kourosh; Röllinghoff, Marc

2014-09-05

The 360° fusion of lumbar segments is a common and well-researched therapy to treat various diseases of the spine. But it changes the biomechanics of the spine and may cause adjacent segment disease (ASD). Among the many techniques developed to avoid this complication, one appears promising. It combines a rigid fusion with a flexible pedicle screw system (hybrid instrumentation, "topping off"). However, its clinical significance is still uncertain due to the lack of conclusive data. The study is a randomized, therapy-controlled, two-centre trial conducted in a clinical setting at two university hospitals. If they meet the criteria, outpatients presenting with degenerative disc disease, facet joint arthrosis or spondylolisthesis will be included in the study and randomized into two groups: a control group undergoing conventional fusion surgery (PLIF - posterior lumbar intervertebral fusion), and an intervention group undergoing fusion surgery using a new flexible pedicle screw system (PLIF + "topping off"), which was brought on the market in 2013. Follow-up examination will take place immediately after surgery, after 6 weeks and after 6, 12, 24 and 36 months. An ongoing assessment will be performed every year.Outcome measurements will include quality of life and pain assessments using validated questionnaires (ODI - Ostwestry Disability Index, SF-36™ - Short Form Health Survey 36, COMI - Core Outcome Measure Index). In addition, clinical and radiologic ASD, sagittal balance parameters and duration of work disability will be assessed. Inpatient and 6-month mortality, surgery-related data (e.g., intraoperative complications, blood loss, length of incision, surgical duration), postoperative complications (e.g. implant failure), adverse events, and serious adverse events will be monitored and documented throughout the study. New hybrid "topping off" systems might improve the outcome of lumbar spine fusion. But to date, there is a serious lack of and a great need of convincing data on safety or efficacy, including benefits and harms to the patients, of these systems. Health care providers are particularly interested in such data as these implants are much more expensive than conventional implants. In such a case, randomized clinical trials are the best way to evaluate benefits and risks. NCT01852526.

Cost-utility analysis of posterior minimally invasive fusion compared with conventional open fusion for lumbar spondylolisthesis

PubMed Central

Rampersaud, Y. Raja; Gray, Randolph; Lewis, Steven J.; Massicotte, Eric M.; Fehlings, Michael G.

2011-01-01

Background The utility and cost of minimally invasive surgical (MIS) fusion remain controversial. The primary objective of this study was to compare the direct economic impact of 1- and 2-level fusion for grade I or II degenerative or isthmic spondylolisthesis via an MIS technique compared with conventional open posterior decompression and fusion. Methods A retrospective cohort study was performed by use of prospective data from 78 consecutive patients (37 with MIS technique by 1 surgeon and 41 with open technique by 3 surgeons). Independent review of demographic, intraoperative, and acute postoperative data was performed. Oswestry disability index (ODI) and Short Form 36 (SF-36) values were prospectively collected preoperatively and at 1 year postoperatively. Cost-utility analysis was performed by use of in-hospital micro-costing data (operating room, nursing, imaging, laboratories, pharmacy, and allied health cost) and change in health utility index (SF-6D) at 1 year. Results The groups were comparable in terms of age, sex, preoperative hemoglobin, comorbidities, and body mass index. Groups significantly differed (P < .01) regarding baseline ODI and SF-6D scores, as well as number of 2-level fusions (MIS, 12; open, 20) and number of interbody cages (MIS, 45; open, 14). Blood loss (200 mL vs 798 mL), transfusions (0% vs 17%), and length of stay (LOS) (6.1 days vs 8.4 days) were significantly (P < .01) lower in the MIS group. Complications were also fewer in the MIS group (4 vs 12, P < .02). The mean cost of an open fusion was 1.28 times greater than that of an MIS fusion (P = .001). Both groups had significant improvement in 1-year outcome. The changes in ODI and SF-6D scores were not statistically different between groups. Multivariate regression analysis showed that LOS and number of levels fused were independent predictors of cost. Age and MIS were the only predictors of LOS. Baseline outcomes and MIS were predictors of 1-year outcome. Conclusion MIS posterior fusion for spondylolisthesis does reduce blood loss, transfusion requirements, and LOS. Both techniques provided substantial clinical improvements at 1 year. The cost utility of the MIS technique was considered comparable to that of the open technique. Level of Evidence Level III. PMID:25802665

Sensor and information fusion for improved hostile fire situational awareness

NASA Astrophysics Data System (ADS)

Scanlon, Michael V.; Ludwig, William D.

2010-04-01

A research-oriented Army Technology Objective (ATO) named Sensor and Information Fusion for Improved Hostile Fire Situational Awareness uniquely focuses on the underpinning technologies to detect and defeat any hostile threat; before, during, and after its occurrence. This is a joint effort led by the Army Research Laboratory, with the Armaments and the Communications and Electronics Research, Development, and Engineering Centers (CERDEC and ARDEC) partners. It addresses distributed sensor fusion and collaborative situational awareness enhancements, focusing on the underpinning technologies to detect/identify potential hostile shooters prior to firing a shot and to detect/classify/locate the firing point of hostile small arms, mortars, rockets, RPGs, and missiles after the first shot. A field experiment conducted addressed not only diverse modality sensor performance and sensor fusion benefits, but gathered useful data to develop and demonstrate the ad hoc networking and dissemination of relevant data and actionable intelligence. Represented at this field experiment were various sensor platforms such as UGS, soldier-worn, manned ground vehicles, UGVs, UAVs, and helicopters. This ATO continues to evaluate applicable technologies to include retro-reflection, UV, IR, visible, glint, LADAR, radar, acoustic, seismic, E-field, narrow-band emission and image processing techniques to detect the threats with very high confidence. Networked fusion of multi-modal data will reduce false alarms and improve actionable intelligence by distributing grid coordinates, detection report features, and imagery of threats.

Dynamics of complete and incomplete fusion in heavy ion collisions

NASA Astrophysics Data System (ADS)

Bao, Xiao Jun; Guo, Shu Qing; Zhang, Hong Fei; Li, Jun Qing

2018-02-01

In order to study the influence of the strong Coulomb and nuclear interactions on the dynamics of complete and incomplete fusion, we construct a new four-variable master equation (ME) so that the deformations as well as the nucleon transfer are viewed as consistently governed by MEs in the potential energy surface of the system. The calculated yields of quasifission fragments and evaporation residue cross section (ERCS) are in agreement with experimental data of hot fusion reactions. Comparing cross sections by theoretical results and experimental data, we find the improved dinuclear sysytem model also describes the transfer cross sections reasonably. The production cross sections of new neutron-rich isotopes are estimated by the multinucleon transfer reactions.

Dynamic Creation of Social Networks for Syndromic Surveillance Using Information Fusion

NASA Astrophysics Data System (ADS)

Holsopple, Jared; Yang, Shanchieh; Sudit, Moises; Stotz, Adam

To enhance the effectiveness of health care, many medical institutions have started transitioning to electronic health and medical records and sharing these records between institutions. The large amount of complex and diverse data makes it difficult to identify and track relationships and trends, such as disease outbreaks, from the data points. INFERD: Information Fusion Engine for Real-Time Decision-Making is an information fusion tool that dynamically correlates and tracks event progressions. This paper presents a methodology that utilizes the efficient and flexible structure of INFERD to create social networks representing progressions of disease outbreaks. Individual symptoms are treated as features allowing multiple hypothesis being tracked and analyzed for effective and comprehensive syndromic surveillance.

Parallel Molecular Distributed Detection With Brownian Motion.

PubMed

Rogers, Uri; Koh, Min-Sung

2016-12-01

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

Frequency domain surface EMG sensor fusion for estimating finger forces.

PubMed

Potluri, Chandrasekhar; Kumar, Parmod; Anugolu, Madhavi; Urfer, Alex; Chiu, Steve; Naidu, D; Schoen, Marco P

2010-01-01

Extracting or estimating skeletal hand/finger forces using surface electro myographic (sEMG) signals poses many challenges due to cross-talk, noise, and a temporal and spatially modulated signal characteristics. Normal sEMG measurements are based on single sensor data. In this paper, array sensors are used along with a proposed sensor fusion scheme that result in a simple Multi-Input-Single-Output (MISO) transfer function. Experimental data is used along with system identification to find this MISO system. A Genetic Algorithm (GA) approach is employed to optimize the characteristics of the MISO system. The proposed fusion-based approach is tested experimentally and indicates improvement in finger/hand force estimation.

Sensitivity of the fusion cross section to the density dependence of the symmetry energy

NASA Astrophysics Data System (ADS)

Reinhard, P.-G.; Umar, A. S.; Stevenson, P. D.; Piekarewicz, J.; Oberacker, V. E.; Maruhn, J. A.

2016-04-01

Background: The study of the nuclear equation of state (EOS) and the behavior of nuclear matter under extreme conditions is crucial to our understanding of many nuclear and astrophysical phenomena. Nuclear reactions serve as one of the means for studying the EOS. Purpose: It is the aim of this paper to discuss the impact of nuclear fusion on the EOS. This is a timely subject given the expected availability of increasingly exotic beams at rare isotope facilities [A. B. Balantekin et al., Mod. Phys. Lett. A 29, 1430010 (2014), 10.1142/S0217732314300109]. In practice, we focus on 48Ca+48Ca fusion. Method: We employ three different approaches to calculate fusion cross sections for a set of energy density functionals with systematically varying nuclear matter properties. Fusion calculations are performed using frozen densities, using a dynamic microscopic method based on density-constrained time-dependent Hartree-Fock (DC-TDHF) approach, as well as direct TDHF study of above barrier cross sections. For these studies, we employ a family of Skyrme parametrizations with systematically varied nuclear matter properties. Results: The folding-potential model provides a reasonable first estimate of cross sections. DC-TDHF, which includes dynamical polarization, reduces the fusion barriers and delivers much better cross sections. Full TDHF near the barrier agrees nicely with DC-TDHF. Most of the Skyrme forces which we used deliver, on the average, fusion cross sections in good agreement with the data. Trying to read off a trend in the results, we find a slight preference for forces which deliver a slope of symmetry energy of L ≈50 MeV that corresponds to a neutron-skin thickness of 48Ca of Rskin=(0.180 -0.210 ) fm. Conclusions: Fusion reactions in the barrier and sub-barrier region can be a tool to study the EOS and the neutron skin of nuclei. The success of the approach will depend on reduced experimental uncertainties of fusion data as well as the development of fusion theories that closely couple to the microscopic structure and dynamics.

Mitigating Information Overload: The Impact of Context-Based Approach to the Design of Tools for Intelligence Analysts

DTIC Science & Technology

2008-03-01

amount of arriving data, extract actionable information, and integrate it with prior knowledge. Add to that the pressures of today’s fusion center...information, and integrate it with prior knowledge. Add to that the pressures of today’s fusion center climate and it becomes clear that analysts, police... fusion centers, including specifics about how these problems manifest at the Illinois State Police (ISP) Statewide Terrorism and Intelligence Center

A comparative study of multi-focus image fusion validation metrics

NASA Astrophysics Data System (ADS)

Giansiracusa, Michael; Lutz, Adam; Messer, Neal; Ezekiel, Soundararajan; Alford, Mark; Blasch, Erik; Bubalo, Adnan; Manno, Michael

2016-05-01

Fusion of visual information from multiple sources is relevant for applications security, transportation, and safety applications. One way that image fusion can be particularly useful is when fusing imagery data from multiple levels of focus. Different focus levels can create different visual qualities for different regions in the imagery, which can provide much more visual information to analysts when fused. Multi-focus image fusion would benefit a user through automation, which requires the evaluation of the fused images to determine whether they have properly fused the focused regions of each image. Many no-reference metrics, such as information theory based, image feature based and structural similarity-based have been developed to accomplish comparisons. However, it is hard to scale an accurate assessment of visual quality which requires the validation of these metrics for different types of applications. In order to do this, human perception based validation methods have been developed, particularly dealing with the use of receiver operating characteristics (ROC) curves and the area under them (AUC). Our study uses these to analyze the effectiveness of no-reference image fusion metrics applied to multi-resolution fusion methods in order to determine which should be used when dealing with multi-focus data. Preliminary results show that the Tsallis, SF, and spatial frequency metrics are consistent with the image quality and peak signal to noise ratio (PSNR).

Nonsubsampled rotated complex wavelet transform (NSRCxWT) for medical image fusion related to clinical aspects in neurocysticercosis.

PubMed

Chavan, Satishkumar S; Mahajan, Abhishek; Talbar, Sanjay N; Desai, Subhash; Thakur, Meenakshi; D'cruz, Anil

2017-02-01

Neurocysticercosis (NCC) is a parasite infection caused by the tapeworm Taenia solium in its larvae stage which affects the central nervous system of the human body (a definite host). It results in the formation of multiple lesions in the brain at different locations during its various stages. During diagnosis of such symptomatic patients, these lesions can be better visualized using a feature based fusion of Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). This paper presents a novel approach to Multimodality Medical Image Fusion (MMIF) used for the analysis of the lesions for the diagnostic purpose and post treatment review of NCC. The MMIF presented here is a technique of combining CT and MRI data of the same patient into a new slice using a Nonsubsampled Rotated Complex Wavelet Transform (NSRCxWT). The forward NSRCxWT is applied on both the source modalities separately to extract the complementary and the edge related features. These features are then combined to form a composite spectral plane using average and maximum value selection fusion rules. The inverse transformation on this composite plane results into a new, visually better, and enriched fused image. The proposed technique is tested on the pilot study data sets of patients infected with NCC. The quality of these fused images is measured using objective and subjective evaluation metrics. Objective evaluation is performed by estimating the fusion parameters like entropy, fusion factor, image quality index, edge quality measure, mean structural similarity index measure, etc. The fused images are also evaluated for their visual quality using subjective analysis with the help of three expert radiologists. The experimental results on 43 image data sets of 17 patients are promising and superior when compared with the state of the art wavelet based fusion algorithms. The proposed algorithm can be a part of computer-aided detection and diagnosis (CADD) system which assists the radiologists in clinical practices. Copyright © 2016 Elsevier Ltd. All rights reserved.

Can Surgeon Demographic Factors Predict Postoperative Complication Rates After Elective Spinal Fusion?

PubMed

Chun, Danielle S; Cook, Ralph W; Weiner, Joseph A; Schallmo, Michael S; Barth, Kathryn A; Singh, Sameer K; Freshman, Ryan D; Patel, Alpesh A; Hsu, Wellington K

2018-03-01

Retrospective cohort. Determine whether surgeon demographic factors influence postoperative complication rates after elective spine fusion procedures. Surgeon demographic factors have been shown to impact decision making in the management of degenerative disease of the lumbar spine. Complication rates are frequently reported outcome measurements used to evaluate surgical treatments, quality-of-care, and determine health care reimbursements. However, there are few studies investigating the association between surgeon demographic factors and complication outcomes after elective spine fusions. A database of US spine surgeons with corresponding postoperative complications data after elective spine fusions was compiled utilizing public data provided by the Centers for Medicare and Medicaid Services (2011-2013) and ProPublica Surgeon Scorecard (2009-2013). Demographic data for each surgeon was collected and consisted of: surgical specialty (orthopedic vs. neurosurgery), years in practice, practice setting (private vs. academic), type of medical degree (MD vs. DO), medical school location (United States vs. foreign), sex, and geographic region of practice. General linear mixed models using a Beta distribution with a logit link and pairwise comparison with post hoc Tukey-Kramer were used to assess the relationship between surgeon demographics and complication rates. 2110 US-practicing spine surgeons who performed spine fusions on 125,787 Medicare patients from 2011 to 2013 met inclusion criteria for this study. None of the surgeon demographic factors analyzed were found to significantly affect overall complication rates in lumbar (posterior approach) or cervical spine fusion. Publicly available complication rates for individual spine surgeons are being utilized by hospital systems and patients to assess aptitude and gauge expectations. The increasing demand for transparency will likely lead to emphasis of these statistics to improve outcomes. We conclude that none of the surgeon demographic factors analyzed in this study are associated with differences in overall complications rates in patients undergoing elective spine fusion as published by the ProPublica Surgeon Scorecard. Level 3.

Does partial coating with titanium improve the radiographic fusion rate of empty PEEK cages in cervical spine surgery? A comparative analysis of clinical data.

PubMed

Kotsias, Andreas; Mularski, Sven; Kühn, Björn; Hanna, Michael; Suess, Olaf

2017-01-01

Anterior cervical diskectomy and fusion (ACDF) is a well-established surgical treatment. Several types of intervertebral spacers can be used, but there is increasing evidence that PEEK cages yield insufficient fusion and thus less clinical improvement. The study aim was to assess the outcomes of single-level ACDF with an empty PEEK cage partially coated with titanium. This prospective multicenter single-arm clinical study collected follow-up data at 6, 12, and 18 months. A post hoc comparison was made to closely matched patients from another similar trial treated with identically designed, empty, uncoated PEEK cages. There were 49 of 50 patients (98%) who met the MCID of 3+ points of improvement on VAS pain or had an 18-month VAS ≤ 1. Yet even by 18 months post-op, only 40 of 50 (80%) PEEK + Ti patients achieved complete bony fusion. The PEEK + Ti group ( n  = 49) seemed to have somewhat better fusion scores and significantly better pain relief at 6 M than the matched controls ( n  = 49), but these differences did not persist at 12 M or 18 M. Patients (with either implant) who achieved complete bony fusion had significantly better improvement of pain at 6 M and disability at 6 M and 12 M than patients that remained unfused. ACDF is effective treatment for cervical myelopathy and radiculopathy. Although this and other studies show that titanium fuses better, partial coating of a PEEK cage does not improve the fusion rate sufficiently or confer other lasting clinical benefit. PEEK cages fully coated with titanium should be tested in prospective randomized comparative trials. Prospective, multicenter, single-arm clinical observational study without an individual Trial registration number. Study design and post hoc data analysis according to the "PIERCE-PEEK study", ISRCTN42774128, retrospectively registered 14 April 2009.

Joint sparsity based heterogeneous data-level fusion for target detection and estimation

NASA Astrophysics Data System (ADS)

Niu, Ruixin; Zulch, Peter; Distasio, Marcello; Blasch, Erik; Shen, Dan; Chen, Genshe

2017-05-01

Typical surveillance systems employ decision- or feature-level fusion approaches to integrate heterogeneous sensor data, which are sub-optimal and incur information loss. In this paper, we investigate data-level heterogeneous sensor fusion. Since the sensors monitor the common targets of interest, whose states can be determined by only a few parameters, it is reasonable to assume that the measurement domain has a low intrinsic dimensionality. For heterogeneous sensor data, we develop a joint-sparse data-level fusion (JSDLF) approach based on the emerging joint sparse signal recovery techniques by discretizing the target state space. This approach is applied to fuse signals from multiple distributed radio frequency (RF) signal sensors and a video camera for joint target detection and state estimation. The JSDLF approach is data-driven and requires minimum prior information, since there is no need to know the time-varying RF signal amplitudes, or the image intensity of the targets. It can handle non-linearity in the sensor data due to state space discretization and the use of frequency/pixel selection matrices. Furthermore, for a multi-target case with J targets, the JSDLF approach only requires discretization in a single-target state space, instead of discretization in a J-target state space, as in the case of the generalized likelihood ratio test (GLRT) or the maximum likelihood estimator (MLE). Numerical examples are provided to demonstrate that the proposed JSDLF approach achieves excellent performance with near real-time accurate target position and velocity estimates.

Multisource data fusion for documenting archaeological sites

NASA Astrophysics Data System (ADS)

Knyaz, Vladimir; Chibunichev, Alexander; Zhuravlev, Denis

2017-10-01

The quality of archaeological sites documenting is of great importance for cultural heritage preserving and investigating. The progress in developing new techniques and systems for data acquisition and processing creates an excellent basis for achieving a new quality of archaeological sites documenting and visualization. archaeological data has some specific features which have to be taken into account when acquiring, processing and managing. First of all, it is a needed to gather as full as possible information about findings providing no loss of information and no damage to artifacts. Remote sensing technologies are the most adequate and powerful means which satisfy this requirement. An approach to archaeological data acquiring and fusion based on remote sensing is proposed. It combines a set of photogrammetric techniques for obtaining geometrical and visual information at different scales and detailing and a pipeline for archaeological data documenting, structuring, fusion, and analysis. The proposed approach is applied for documenting of Bosporus archaeological expedition of Russian State Historical Museum.

Benchmarking comparison and validation of MCNP photon interaction data

NASA Astrophysics Data System (ADS)

Colling, Bethany; Kodeli, I.; Lilley, S.; Packer, L. W.

2017-09-01

The objective of the research was to test available photoatomic data libraries for fusion relevant applications, comparing against experimental and computational neutronics benchmarks. Photon flux and heating was compared using the photon interaction data libraries (mcplib 04p, 05t, 84p and 12p). Suitable benchmark experiments (iron and water) were selected from the SINBAD database and analysed to compare experimental values with MCNP calculations using mcplib 04p, 84p and 12p. In both the computational and experimental comparisons, the majority of results with the 04p, 84p and 12p photon data libraries were within 1σ of the mean MCNP statistical uncertainty. Larger differences were observed when comparing computational results with the 05t test photon library. The Doppler broadening sampling bug in MCNP-5 is shown to be corrected for fusion relevant problems through use of the 84p photon data library. The recommended libraries for fusion neutronics are 84p (or 04p) with MCNP6 and 84p if using MCNP-5.

A comparison of data interoperability approaches of fusion codes with application to synthetic diagnostics

NASA Astrophysics Data System (ADS)

Kruger, Scott; Shasharina, S.; Vadlamani, S.; McCune, D.; Holland, C.; Jenkins, T. G.; Candy, J.; Cary, J. R.; Hakim, A.; Miah, M.; Pletzer, A.

2010-11-01

As various efforts to integrate fusion codes proceed worldwide, standards for sharing data have emerged. In the U.S., the SWIM project has pioneered the development of the Plasma State, which has a flat-hierarchy and is dominated by its use within 1.5D transport codes. The European Integrated Tokamak Modeling effort has developed a more ambitious data interoperability effort organized around the concept of Consistent Physical Objects (CPOs). CPOs have deep hierarchies as needed by an effort that seeks to encompass all of fusion computing. Here, we discuss ideas for implementing data interoperability that is complementary to both the Plasma State and CPOs. By making use of attributes within the netcdf and HDF5 binary file formats, the goals of data interoperability can be achieved with a more informal approach. In addition, a file can be simultaneously interoperable to several standards at once. As an illustration of this approach, we discuss its application to the development of synthetic diagnostics that can be used for multiple codes.

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

Henderson, Ian M.; Collins, Aaron M.; Quintana, Hope A.

In this study, we develop a quantitative dye dequenching technique for the measurement of polymersome fusion, using it to characterize the salt mediated, mechanically-induced fusion of polymersomes with polymer, lipid, and so-called stealth lipid vesicles. While dye dequenching has been used to quantitatively explore liposome fusion in the past, this is the first use of dye dequenching to measure polymersome fusion of which we are aware. In addition to providing quantitative results, dye dequenching is ideal for detecting fusion in instances where DLS results would be ambiguous, such as low yield levels and size ranges outside the capabilities of DLS.more » The dye chosen for this study was a cyanine derivative, 1,1'-dioctadecyl-3,3,3',3'-tetramethylindotricarbocyanine iodide (DiR), which proved to provide excellent data on the extent of polymersome fusion. Using this technique, we have shown the limited fusion capabilities of polymersome/liposome heterofusion, notably DOPC vesicles fusing with polymersomes at half the efficiency of polymersome homofusion and DPPC vesicles showing virtually no fusion. In addition to these key heterofusion experiments, we determined the broad applicability of dye dequenching in measuring kinetic rates of polymersome fusion; and showed that even at elevated temperatures or over multiple weeks' time, no polymersome fusion occurred without agitation. Stealth liposomes formed from DPPC and PEO-functionalized lipid, however, fused with polymersomes and stealth liposomes with relatively high efficiency, lending support to our hypothesis that the response of the PEO corona to salt is a key factor in the fusion process. This last finding suggests that although the conjugation of PEO to lipids increases vesicle biocompatibility and enables their longer circulation times, it also renders the vesicles subject to destabilization under high salt and shear (e.g. in the circulatory system) that may lead to, in this case, fusion.« less

The Formin Diaphanous Regulates Myoblast Fusion through Actin Polymerization and Arp2/3 Regulation

PubMed Central

Deng, Su; Bothe, Ingo; Baylies, Mary K.

2015-01-01

The formation of multinucleated muscle cells through cell-cell fusion is a conserved process from fruit flies to humans. Numerous studies have shown the importance of Arp2/3, its regulators, and branched actin for the formation of an actin structure, the F-actin focus, at the fusion site. This F-actin focus forms the core of an invasive podosome-like structure that is required for myoblast fusion. In this study, we find that the formin Diaphanous (Dia), which nucleates and facilitates the elongation of actin filaments, is essential for Drosophila myoblast fusion. Following cell recognition and adhesion, Dia is enriched at the myoblast fusion site, concomitant with, and having the same dynamics as, the F-actin focus. Through analysis of Dia loss-of-function conditions using mutant alleles but particularly a dominant negative Dia transgene, we demonstrate that reduction in Dia activity in myoblasts leads to a fusion block. Significantly, no actin focus is detected, and neither branched actin regulators, SCAR or WASp, accumulate at the fusion site when Dia levels are reduced. Expression of constitutively active Dia also causes a fusion block that is associated with an increase in highly dynamic filopodia, altered actin turnover rates and F-actin distribution, and mislocalization of SCAR and WASp at the fusion site. Together our data indicate that Dia plays two roles during invasive podosome formation at the fusion site: it dictates the level of linear F-actin polymerization, and it is required for appropriate branched actin polymerization via localization of SCAR and WASp. These studies provide new insight to the mechanisms of cell-cell fusion, the relationship between different regulators of actin polymerization, and invasive podosome formation that occurs in normal development and in disease. PMID:26295716

Oral cancer/endothelial cell fusion experiences nuclear fusion and acquisition of enhanced survival potential.

PubMed

Song, Kai; Song, Yong; Zhao, Xiao-Ping; Shen, Hui; Wang, Meng; Yan, Ting-Lin; Liu, Ke; Shang, Zheng-Jun

2014-10-15

Most previous studies have linked cancer-macrophage fusion with tumor progression and metastasis. However, the characteristics of hybrid cells derived from oral cancer and endothelial cells and their involvement in cancer remained unknown. Double-immunofluorescent staining and fluorescent in situ hybridization (FISH) were performed to confirm spontaneous cell fusion between eGFP-labeled human umbilical vein endothelial cells (HUVECs) and RFP-labeled SCC9, and to detect the expression of vementin and cytokeratin 18 in the hybrids. The property of chemo-resistance of such hybrids was examined by TUNEL assay. The hybrid cells in xenografted tumor were identified by FISH and GFP/RFP dual-immunofluoresence staining. We showed that SCC9 cells spontaneously fused with cocultured endothelial cells, and the resultant hybrid cells maintained the division and proliferation activity after re-plating and thawing. Such hybrids expressed markers of both parental cells and became more resistant to chemotherapeutic drug cisplatin as compared to the parental SCC9 cells. Our in vivo data indicated that the hybrid cells contributed to tumor composition by using of immunostaining and FISH analysis, even though the hybrid cells and SCC9 cells were mixed with 1:10,000, according to the FACS data. Our study suggested that the fusion events between oral cancer and endothelial cells undergo nuclear fusion and acquire a new property of drug resistance and consequently enhanced survival potential. These experimental findings provide further supportive evidence for the theory that cell fusion is involved in cancer progression. Copyright © 2014 Elsevier Inc. All rights reserved.

Multisource image fusion method using support value transform.

PubMed

Zheng, Sheng; Shi, Wen-Zhong; Liu, Jian; Zhu, Guang-Xi; Tian, Jin-Wen

2007-07-01

With the development of numerous imaging sensors, many images can be simultaneously pictured by various sensors. However, there are many scenarios where no one sensor can give the complete picture. Image fusion is an important approach to solve this problem and produces a single image which preserves all relevant information from a set of different sensors. In this paper, we proposed a new image fusion method using the support value transform, which uses the support value to represent the salient features of image. This is based on the fact that, in support vector machines (SVMs), the data with larger support values have a physical meaning in the sense that they reveal relative more importance of the data points for contributing to the SVM model. The mapped least squares SVM (mapped LS-SVM) is used to efficiently compute the support values of image. The support value analysis is developed by using a series of multiscale support value filters, which are obtained by filling zeros in the basic support value filter deduced from the mapped LS-SVM to match the resolution of the desired level. Compared with the widely used image fusion methods, such as the Laplacian pyramid, discrete wavelet transform methods, the proposed method is an undecimated transform-based approach. The fusion experiments are undertaken on multisource images. The results demonstrate that the proposed approach is effective and is superior to the conventional image fusion methods in terms of the pertained quantitative fusion evaluation indexes, such as quality of visual information (Q(AB/F)), the mutual information, etc.

Macrophage Fusion Is Controlled by the Cytoplasmic Protein Tyrosine Phosphatase PTP-PEST/PTPN12

PubMed Central

Rhee, Inmoo; Davidson, Dominique; Souza, Cleiton Martins; Vacher, Jean

2013-01-01

Macrophages can undergo cell-cell fusion, leading to the formation of multinucleated giant cells and osteoclasts. This process is believed to promote the proteolytic activity of macrophages toward pathogens, foreign bodies, and extracellular matrices. Here, we examined the role of PTP-PEST (PTPN12), a cytoplasmic protein tyrosine phosphatase, in macrophage fusion. Using a macrophage-targeted PTP-PEST-deficient mouse, we determined that PTP-PEST was not needed for macrophage differentiation or cytokine production. However, it was necessary for interleukin-4-induced macrophage fusion into multinucleated giant cells in vitro. It was also needed for macrophage fusion following implantation of a foreign body in vivo. Moreover, in the RAW264.7 macrophage cell line, PTP-PEST was required for receptor activator of nuclear factor kappa-B ligand (RANKL)-triggered macrophage fusion into osteoclasts. PTP-PEST had no impact on expression of fusion mediators such as β-integrins, E-cadherin, and CD47, which enable macrophages to become fusion competent. However, it was needed for polarization of macrophages, migration induced by the chemokine CC chemokine ligand 2 (CCL2), and integrin-induced spreading, three key events in the fusion process. PTP-PEST deficiency resulted in specific hyperphosphorylation of the protein tyrosine kinase Pyk2 and the adaptor paxillin. Moreover, a fusion defect was induced upon treatment of normal macrophages with a Pyk2 inhibitor. Together, these data argue that macrophage fusion is critically dependent on PTP-PEST. This function is seemingly due to the ability of PTP-PEST to control phosphorylation of Pyk2 and paxillin, thereby regulating cell polarization, migration, and spreading. PMID:23589331

Macrophage fusion is controlled by the cytoplasmic protein tyrosine phosphatase PTP-PEST/PTPN12.

PubMed

Rhee, Inmoo; Davidson, Dominique; Souza, Cleiton Martins; Vacher, Jean; Veillette, André

2013-06-01

Macrophages can undergo cell-cell fusion, leading to the formation of multinucleated giant cells and osteoclasts. This process is believed to promote the proteolytic activity of macrophages toward pathogens, foreign bodies, and extracellular matrices. Here, we examined the role of PTP-PEST (PTPN12), a cytoplasmic protein tyrosine phosphatase, in macrophage fusion. Using a macrophage-targeted PTP-PEST-deficient mouse, we determined that PTP-PEST was not needed for macrophage differentiation or cytokine production. However, it was necessary for interleukin-4-induced macrophage fusion into multinucleated giant cells in vitro. It was also needed for macrophage fusion following implantation of a foreign body in vivo. Moreover, in the RAW264.7 macrophage cell line, PTP-PEST was required for receptor activator of nuclear factor kappa-B ligand (RANKL)-triggered macrophage fusion into osteoclasts. PTP-PEST had no impact on expression of fusion mediators such as β-integrins, E-cadherin, and CD47, which enable macrophages to become fusion competent. However, it was needed for polarization of macrophages, migration induced by the chemokine CC chemokine ligand 2 (CCL2), and integrin-induced spreading, three key events in the fusion process. PTP-PEST deficiency resulted in specific hyperphosphorylation of the protein tyrosine kinase Pyk2 and the adaptor paxillin. Moreover, a fusion defect was induced upon treatment of normal macrophages with a Pyk2 inhibitor. Together, these data argue that macrophage fusion is critically dependent on PTP-PEST. This function is seemingly due to the ability of PTP-PEST to control phosphorylation of Pyk2 and paxillin, thereby regulating cell polarization, migration, and spreading.

Study on ( n,t) Reactions of Zr, Nb and Ta Nuclei

NASA Astrophysics Data System (ADS)

Tel, E.; Yiğit, M.; Tanır, G.

2012-04-01

The world faces serious energy shortages in the near future. To meet the world energy demand, the nuclear fusion with safety, environmentally acceptability and economic is the best suited. Fusion is attractive as an energy source because of the virtually inexhaustible supply of fuel, the promise of minimal adverse environmental impact, and its inherent safety. Fusion will not produce CO2 or SO2 and thus will not contribute to global warming or acid rain. Furthermore, there are not radioactive nuclear waste problems in the fusion reactors. Although there have been significant research and development studies on the inertial and magnetic fusion reactor technology, there is still a long way to go to penetrate commercial fusion reactors to the energy market. Because, tritium self-sufficiency must be maintained for a commercial power plant. For self-sustaining (D-T) fusion driver tritium breeding ratio should be greater than 1.05. And also, the success of fusion power system is dependent on performance of the first wall, blanket or divertor systems. So, the performance of structural materials for fusion power systems, understanding nuclear properties systematic and working out of ( n,t) reaction cross sections are very important. Zirconium (Zr), Niobium (Nb) and Tantal (Ta) containing alloys are important structural materials for fusion reactors, accelerator-driven systems, and many other fields. In this study, ( n,t) reactions for some structural fusion materials such as 88,90,92,94,96Zr, 93,94,95Nb and 179,181Ta have been investigated. The calculated results are discussed andcompared with the experimental data taken from the literature.

Comparison of interbody fusion approaches for disabling low back pain.

PubMed

Hacker, R J

1997-03-15

This is a study comparing two groups of patients surgically treated for disabling low back pain. One group was treated with lumbar anteroposterior fusion (360 degrees fusion), the other with posterior lumbar interbody fusion and an interbody fixation device. To determine which approach provided the best and most cost-effective outcome using similar patient selection criteria. Others have shown that certain patients with disabling low back pain benefit from lumbar fusion. Although rarely reported, the costs of different surgical treatments appear to vary significantly, whereas the patient outcome may vary little. Since 1991, 75 patients have been treated Starting in 1993, posterior lumbar interbody fusion BAK was offered to patients as an alternative to 360 degrees fusion. The treating surgeon reviewed the cases. The interbody fixation device used (BAK; Spine-Tech, Inc., Minneapolis, MN) was part of a Food and Drug Administration study. Patient selection criteria included examination, response to conservative therapy, imaging, psychological profile, and discography. North American Spine Society outcome questionnaires, BAK investigation data radiographs, chart entries, billing records and patient interviews were the basis for assessment. Age, sex compensable injury history and history of previous surgery were similar. Operative time; blood loss, hospitalization time, and total costs were significantly different. There was a quicker return to work and closure of workers compensation claims for the posterior lumbar interbody fusion-BAK group. Patient satisfaction was comparable at last follow-up. Posterior lumbar interbody fusion-BAK achieves equal patient satisfaction but fiscally surpasses the 360 degrees fusion approach. Today's environment of regulated medical practice requires the surgeon to consider cost effectiveness when performing fusion for low back pain.

Epidural Abscess: A Propensity Analysis of Surgical Treatment Strategies.

PubMed

Chaker, Anisse N; Bhimani, Abhiraj D; Esfahani, Darian R; Rosinski, Clayton L; Geever, Brett W; Patel, Akash S; Hobbs, Jonathan G; Burch, Taylor G; Patel, Saavan; Mehta, Ankit I

2018-06-18

Observational analysis of retrospectively collected data. A retrospective study was performed in order to compare the surgical profile of risk factors and perioperative complications for laminectomy and laminectomy with fusion procedures in the treatment of SEA. Spinal epidural abscess (SEA) is a highly morbid condition typically presenting with back pain, fever, and neurologic deficits. Posterior fusion has been used to supplement traditional laminectomy of SEA to improve spinal stability. At present, the ideal surgical strategy - laminectomy with or without fusion - remains elusive. 30-day outcomes such as reoperation and readmission following laminectomy and laminectomy with fusion in patients with SEA were investigated utilizing the American College of Surgeons National Quality Improvement Program database. Demographics and clinical risk factors were collected, and propensity matching was performed to account for differences in risk profiles between the groups. 738 patients were studied (608 laminectomy alone, 130 fusion). The fusion population was in worse health. The fusion population experienced significantly greater rate of return to the operating room (odds ratio (OR) 1.892), with the difference primarily accounted for by cervical spine operations. Additionally, fusion patients had significantly greater rates of blood transfusion. Infection was the most common reason for reoperation in both populations. Both laminectomy and laminectomy with fusion effectively treat SEA, but addition of fusion is associated with significantly higher rates of transfusion and perioperative return to the operating room. In operative situations where either procedure is reasonable, surgeons should consider that fusion nearly doubles the odds of reoperation in the short-term, and weigh this risk against the benefit of added stability. 3.

Development of motor fusion in patients with a history of strabismic amblyopia who are treated part-time with Bangerter foils.

PubMed

Abrams, Michael S; Duncan, Candace L; McMurtrey, Ryan

2011-04-01

To document the development of motor fusion when patients with a history of strabismic amblyopia are treated part-time with Bangerter foils. This was a prospective interventional outcome study of consecutive patients with a history of strabismic amblyopia, horizontal strabismus (only) ≤20(∆), visual acuity of 20/60 or better in the nonfixating eye, and no motor fusion (as indicated by the absence of prism vergence) for 1 year before entry into the study. Subjects wore a 0.1 density Bangerter foil for 3-4 hours daily. Data on visual acuity, alignment, and motor fusion status were collected for a minimum of 2 years. Patients with motor fusion were then followed for a minimum of 18 months to assess the stability of their motor fusion status after the Bangerter foil was discontinued. Of the 46 patients meeting entry criteria (mean age, 5.3 ± 1.7 years) who completed follow-up, 28 (61%) developed motor fusion. Motor fusion was retained in all 17 patients who were followed after their foils were discontinued for a mean of 13.3 months. A child's motor fusion status is generally believed to be established during an early formative period of visual development. The development of motor fusion in many of our patients during the course of part-time Bangerter foil treatment suggests that improvements in motor fusion status can occur at a later age than previously believed. Copyright © 2011 American Association for Pediatric Ophthalmology and Strabismus. Published by Mosby, Inc. All rights reserved.

Productivity benefits of minimally invasive surgery in patients with chronic sacroiliac joint dysfunction.

PubMed

Saavoss, Josh D; Koenig, Lane; Cher, Daniel J

2016-01-01

Sacroiliac joint (SIJ) dysfunction is associated with a marked decrease in quality of life. Increasing evidence supports minimally invasive SIJ fusion as a safe and effective procedure for the treatment of chronic SIJ dysfunction. The impact of SIJ fusion on worker productivity is not known. Regression modeling using data from the National Health Interview Survey was applied to determine the relationship between responses to selected interview questions related to function and economic outcomes. Regression coefficients were then applied to prospectively collected, individual patient data in a randomized trial of SIJ fusion (INSITE, NCT01681004) to estimate expected differences in economic outcomes across treatments. Patients who receive SIJ fusion using iFuse Implant System(®) have an expected increase in the probability of working of 16% (95% confidence interval [CI] 11%-21%) relative to nonsurgical patients. The expected change in earnings across groups was US $3,128 (not statistically significant). Combining the two metrics, the annual increase in worker productivity given surgical vs nonsurgical care was $6,924 (95% CI $1,890-$11,945). For employees with chronic, severe SIJ dysfunction, minimally invasive SIJ fusion may improve worker productivity compared to nonsurgical treatment.

Scale Estimation and Correction of the Monocular Simultaneous Localization and Mapping (SLAM) Based on Fusion of 1D Laser Range Finder and Vision Data.

PubMed

Zhang, Zhuang; Zhao, Rujin; Liu, Enhai; Yan, Kun; Ma, Yuebo

2018-06-15

This article presents a new sensor fusion method for visual simultaneous localization and mapping (SLAM) through integration of a monocular camera and a 1D-laser range finder. Such as a fusion method provides the scale estimation and drift correction and it is not limited by volume, e.g., the stereo camera is constrained by the baseline and overcomes the limited depth range problem associated with SLAM for RGBD cameras. We first present the analytical feasibility for estimating the absolute scale through the fusion of 1D distance information and image information. Next, the analytical derivation of the laser-vision fusion is described in detail based on the local dense reconstruction of the image sequences. We also correct the scale drift of the monocular SLAM using the laser distance information which is independent of the drift error. Finally, application of this approach to both indoor and outdoor scenes is verified by the Technical University of Munich dataset of RGBD and self-collected data. We compare the effects of the scale estimation and drift correction of the proposed method with the SLAM for a monocular camera and a RGBD camera.

In Situ 3D Monitoring of Geometric Signatures in the Powder-Bed-Fusion Additive Manufacturing Process via Vision Sensing Methods

PubMed Central

Li, Zhongwei; Liu, Xingjian; Wen, Shifeng; He, Piyao; Zhong, Kai; Wei, Qingsong; Shi, Yusheng; Liu, Sheng

2018-01-01

Lack of monitoring of the in situ process signatures is one of the challenges that has been restricting the improvement of Powder-Bed-Fusion Additive Manufacturing (PBF AM). Among various process signatures, the monitoring of the geometric signatures is of high importance. This paper presents the use of vision sensing methods as a non-destructive in situ 3D measurement technique to monitor two main categories of geometric signatures: 3D surface topography and 3D contour data of the fusion area. To increase the efficiency and accuracy, an enhanced phase measuring profilometry (EPMP) is proposed to monitor the 3D surface topography of the powder bed and the fusion area reliably and rapidly. A slice model assisted contour detection method is developed to extract the contours of fusion area. The performance of the techniques is demonstrated with some selected measurements. Experimental results indicate that the proposed method can reveal irregularities caused by various defects and inspect the contour accuracy and surface quality. It holds the potential to be a powerful in situ 3D monitoring tool for manufacturing process optimization, close-loop control, and data visualization. PMID:29649171

Research Needs for Artificial Intelligence Applications in Support of C3 (Command, Control, and Communication).

DTIC Science & Technology

1984-12-01

system. The reconstruction process is Simply data fusion after allA data are in. After reconstruction, artifcial intelligence (Al) techniques may be...14. CATE OF fhPM~TVW MWtvt Ogv It PAWE COMN Interim __100 -_ TO December 1984 24 MILD ON" s-o Artificial intelligence Command control Data fusion...RD-Ai5O 867 RESEARCH NEEDS FOR ARTIFICIAL INTELLIGENCE APPLICATIONS i/i IN SUPPORT OF C3 (..(U) NAVAL OCEAN SVSTEIIS CENTER SAN DIEGO CA R R DILLARD

Spatial Aspects of Multi-Sensor Data Fusion: Aerosol Optical Thickness

NASA Technical Reports Server (NTRS)

Leptoukh, Gregory; Zubko, V.; Gopalan, A.

2007-01-01

The Goddard Earth Sciences Data and Information Services Center (GES DISC) investigated the applicability and limitations of combining multi-sensor data through data fusion, to increase the usefulness of the multitude of NASA remote sensing data sets, and as part of a larger effort to integrate this capability in the GES-DISC Interactive Online Visualization and Analysis Infrastructure (Giovanni). This initial study focused on merging daily mean Aerosol Optical Thickness (AOT), as measured by the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites, to increase spatial coverage and produce complete fields to facilitate comparison with models and station data. The fusion algorithm used the maximum likelihood technique to merge the pixel values where available. The algorithm was applied to two regional AOT subsets (with mostly regular and irregular gaps, respectively) and a set of AOT fields that differed only in the size and location of artificially created gaps. The Cumulative Semivariogram (CSV) was found to be sensitive to the spatial distribution of gap areas and, thus, useful for assessing the sensitivity of the fused data to spatial gaps.

Rubella virus: first calcium-requiring viral fusion protein.

PubMed

Dubé, Mathieu; Rey, Felix A; Kielian, Margaret

2014-12-01

Rubella virus (RuV) infection of pregnant women can cause fetal death, miscarriage, or severe fetal malformations, and remains a significant health problem in much of the underdeveloped world. RuV is a small enveloped RNA virus that infects target cells by receptor-mediated endocytosis and low pH-dependent membrane fusion. The structure of the RuV E1 fusion protein was recently solved in its postfusion conformation. RuV E1 is a member of the class II fusion proteins and is structurally related to the alphavirus and flavivirus fusion proteins. Unlike the other known class II fusion proteins, however, RuV E1 contains two fusion loops, with a metal ion complexed between them by the polar residues N88 and D136. Here we demonstrated that RuV infection specifically requires Ca(2+) during virus entry. Other tested cations did not substitute. Ca(2+) was not required for virus binding to cell surface receptors, endocytic uptake, or formation of the low pH-dependent E1 homotrimer. However, Ca(2+) was required for low pH-triggered E1 liposome insertion, virus fusion and infection. Alanine substitution of N88 or D136 was lethal. While the mutant viruses were efficiently assembled and endocytosed by host cells, E1-membrane insertion and fusion were specifically blocked. Together our data indicate that RuV E1 is the first example of a Ca(2+)-dependent viral fusion protein and has a unique membrane interaction mechanism.

Research on the use of data fusion technology to evaluate the state of electromechanical equipment

NASA Astrophysics Data System (ADS)

Lin, Lin

2018-04-01

Aiming at the problems of different testing information modes and the coexistence of quantitative and qualitative information in the state evaluation of electromechanical equipment, the paper proposes the use of data fusion technology to evaluate the state of electromechanical equipment. This paper introduces the state evaluation process of mechanical and electrical equipment in detail, uses the D-S evidence theory to fuse the decision-making layers of mechanical and electrical equipment state evaluation and carries out simulation tests. The simulation results show that it is feasible and effective to apply the data fusion technology to the state evaluation of the mechatronic equipment. After the multiple decision-making information provided by different evaluation methods are fused repeatedly and the useful information is extracted repeatedly, the fuzziness of judgment can be reduced and the state evaluation Credibility.

Health-Enabled Smart Sensor Fusion Technology

NASA Technical Reports Server (NTRS)

Wang, Ray

2012-01-01

A process was designed to fuse data from multiple sensors in order to make a more accurate estimation of the environment and overall health in an intelligent rocket test facility (IRTF), to provide reliable, high-confidence measurements for a variety of propulsion test articles. The object of the technology is to provide sensor fusion based on a distributed architecture. Specifically, the fusion technology is intended to succeed in providing health condition monitoring capability at the intelligent transceiver, such as RF signal strength, battery reading, computing resource monitoring, and sensor data reading. The technology also provides analytic and diagnostic intelligence at the intelligent transceiver, enhancing the IEEE 1451.x-based standard for sensor data management and distributions, as well as providing appropriate communications protocols to enable complex interactions to support timely and high-quality flow of information among the system elements.

Effective World Modeling: Multisensor Data Fusion Methodology for Automated Driving

PubMed Central

Elfring, Jos; Appeldoorn, Rein; van den Dries, Sjoerd; Kwakkernaat, Maurice

2016-01-01

The number of perception sensors on automated vehicles increases due to the increasing number of advanced driver assistance system functions and their increasing complexity. Furthermore, fail-safe systems require redundancy, thereby increasing the number of sensors even further. A one-size-fits-all multisensor data fusion architecture is not realistic due to the enormous diversity in vehicles, sensors and applications. As an alternative, this work presents a methodology that can be used to effectively come up with an implementation to build a consistent model of a vehicle’s surroundings. The methodology is accompanied by a software architecture. This combination minimizes the effort required to update the multisensor data fusion system whenever sensors or applications are added or replaced. A series of real-world experiments involving different sensors and algorithms demonstrates the methodology and the software architecture. PMID:27727171

Thermal-hydraulic analysis of low activity fusion blanket designs

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

Fillo, J A; Powell, J; Yu, W S

1977-01-01

The heat transfer aspects of fusion blankets are considered where: (a) conduction and (b) boiling and condensation are the dominant heat transfer mechanisms. In some cases, unique heat transfer problems arise and additional heat transfer data and analyses may be required.

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

Garcia, Natalie K.; Guttman, Miklos; Ebner, Jamie L.

Influenza hemagglutinin (HA) mediates virus attachment to host cells and fusion of the viral and endosomal membranes during entry. While high-resolution structures are available for the pre-fusion HA ectodomain and the post-fusion HA2 subunit, the sequence of conformational changes during HA activation has eluded structural characterization. In this paper, we apply hydrogen-deuterium exchange with mass spectrometry to examine changes in structural dynamics of the HA ectodomain at various stages of activation, and compare the soluble ectodomain with intact HA on virions. At pH conditions approaching activation (pH 6.0–5.5) HA exhibits increased dynamics at the fusion peptide and neighboring regions, whilemore » the interface between receptor binding subunits (HA1) becomes stabilized. In contrast to many activation models, these data suggest that HA responds to endosomal acidification by releasing the fusion peptide prior to HA1 uncaging and the spring-loaded refolding of HA2. Finally, this staged process may facilitate efficient HA-mediated fusion.« less

A Model for Membrane Fusion

NASA Astrophysics Data System (ADS)

Ngatchou, Annita

2010-01-01

Pheochromocytoma is a tumor of the adrenal gland which originates from chromaffin cells and is characterized by the secretion of excessive amounts of neurotransmitter which lead to high blood pressure and palpitations. Pheochromocytoma contain membrane bound granules that store neurotransmitter. The release of these stored molecules into the extracellular space occurs by fusion of the granule membrane with the cell plasma membrane, a process called exocytosis. The molecular mechanism of this membrane fusion is not well understood. It is proposed that the so called SNARE proteins [1] are the pillar of vesicle fusion as their cleavage by clostridial toxin notably, Botulinum neurotoxin and Tetanus toxin abrogate the secretion of neurotransmitter [2]. Here, I describe how physical principles are applied to a biological cell to explore the role of the vesicle SNARE protein synaptobrevin-2 in easing granule fusion. The data presented here suggest a paradigm according to which the movement of the C-terminal of synaptobrevin-2 disrupts the lipid bilayer to form a fusion pore through which molecules can exit.

Dynamic changes during acid-induced activation of influenza hemagglutinin

DOE PAGES

Garcia, Natalie K.; Guttman, Miklos; Ebner, Jamie L.; ...

2015-03-12

Influenza hemagglutinin (HA) mediates virus attachment to host cells and fusion of the viral and endosomal membranes during entry. While high-resolution structures are available for the pre-fusion HA ectodomain and the post-fusion HA2 subunit, the sequence of conformational changes during HA activation has eluded structural characterization. In this paper, we apply hydrogen-deuterium exchange with mass spectrometry to examine changes in structural dynamics of the HA ectodomain at various stages of activation, and compare the soluble ectodomain with intact HA on virions. At pH conditions approaching activation (pH 6.0–5.5) HA exhibits increased dynamics at the fusion peptide and neighboring regions, whilemore » the interface between receptor binding subunits (HA1) becomes stabilized. In contrast to many activation models, these data suggest that HA responds to endosomal acidification by releasing the fusion peptide prior to HA1 uncaging and the spring-loaded refolding of HA2. Finally, this staged process may facilitate efficient HA-mediated fusion.« less

The Fusion Model of Intelligent Transportation Systems Based on the Urban Traffic Ontology

NASA Astrophysics Data System (ADS)

Yang, Wang-Dong; Wang, Tao

On these issues unified representation of urban transport information using urban transport ontology, it defines the statute and the algebraic operations of semantic fusion in ontology level in order to achieve the fusion of urban traffic information in the semantic completeness and consistency. Thus this paper takes advantage of the semantic completeness of the ontology to build urban traffic ontology model with which we resolve the problems as ontology mergence and equivalence verification in semantic fusion of traffic information integration. Information integration in urban transport can increase the function of semantic fusion, and reduce the amount of data integration of urban traffic information as well enhance the efficiency and integrity of traffic information query for the help, through the practical application of intelligent traffic information integration platform of Changde city, the paper has practically proved that the semantic fusion based on ontology increases the effect and efficiency of the urban traffic information integration, reduces the storage quantity, and improve query efficiency and information completeness.

Ectocranial suture fusion in primates: pattern and phylogeny.

PubMed

Cray, James; Cooper, Gregory M; Mooney, Mark P; Siegel, Michael I

2014-03-01

Patterns of ectocranial suture fusion among Primates are subject to species-specific variation. In this study, we used Guttman Scaling to compare modal progression of ectocranial suture fusion among Hominidae (Homo, Pan, Gorilla, and Pongo), Hylobates, and Cercopithecidae (Macaca and Papio) groups. Our hypothesis is that suture fusion patterns should reflect their evolutionary relationship. For the lateral-anterior suture sites there appear to be three major patterns of fusion, one shared by Homo-Pan-Gorilla, anterior to posterior; one shared by Pongo and Hylobates, superior to inferior; and one shared by Cercopithecidae, posterior to anterior. For the vault suture pattern, the Hominidae groups reflect the known phylogeny. The data for Hylobates and Cercopithecidae groups is less clear. The vault suture site termination pattern of Papio is similar to that reported for Gorilla and Pongo. Thus, it may be that some suture sites are under larger genetic influence for patterns of fusion, while others are influenced by environmental/biomechanic influences. Copyright © 2013 Wiley Periodicals, Inc.

TFE3-Fusion Variant Analysis Defines Specific Clinicopathologic Associations Among Xp11 Translocation Cancers

PubMed Central

Argani, Pedram; Zhong, Minghao; Reuter, Victor E.; Fallon, John T.; Epstein, Jonathan I.; Netto, George J.; Antonescu, Cristina R.

2016-01-01

Xp11 translocation cancers include Xp11 translocation renal cell carcinoma (RCC), Xp11 translocation perivascular epithelioid cell tumor (PEComa), and melanotic Xp11 translocation renal cancer. In Xp11 translocation cancers, oncogenic activation of TFE3 is driven by the fusion of TFE3 with a number of different gene partners, however, the impact of individual fusion variant on specific clinicopathologic features of Xp11 translocation cancers has not been well defined. In this study, we analyze 60 Xp11 translocation cancers by fluorescence in situ hybridization (FISH) using custom BAC probes to establish their TFE3 fusion gene partner. In 5 cases RNA sequencing (RNA-seq) was also used to further characterize the fusion transcripts. The 60 Xp11 translocation cancers included 47 Xp11 translocation RCC, 8 Xp11 translocation PEComas, and 5 melanotic Xp11 translocation renal cancers. A fusion partner was identified in 53/60 (88%) cases, including 18 SFPQ (PSF), 16 PRCC, 12 ASPSCR1 (ASPL), 6 NONO, and 1 DVL2. We provide the first morphologic description of the NONO-TFE3 RCC, which frequently demonstrates sub-nuclear vacuoles leading to distinctive suprabasal nuclear palisading. Similar sub-nuclear vacuolization was also characteristic of SFPQ-TFE3 RCC, creating overlapping features with clear cell papillary RCC. We also describe the first RCC with a DVL2-TFE3 gene fusion, in addition to an extrarenal pigmented PEComa with a NONO-TFE3 gene fusion. Furthermore, among neoplasms with the SFPQ-TFE3, NONO-TFE3, DVL2-TFE3 and ASPL-TFE3 gene fusions, the RCC are almost always PAX8-positive, cathepsin K-negative by immunohistochemistry, whereas the mesenchymal counterparts (Xp11 translocation PEComas, melanotic Xp11 translocation renal cancers, and alveolar soft part sarcoma) are PAX8-negative, cathepsin K-positive. These findings support the concept that despite an identical gene fusion, the RCCs are distinct from the corresponding mesenchymal neoplasms, perhaps due to the cellular context in which the translocation occurs. We corroborate prior data showing that the PRCC-TFE3 RCC are the only known Xp11 translocation RCC molecular subtype which is consistently cathepsin K positive. In summary, our data expand further the clinicopathologic features of cancers with specific TFE3 gene fusions, and should allow for more meaningful clinicopathologic associations to be drawn. PMID:26975036

Hrs regulates early endosome fusion by inhibiting formation of an endosomal SNARE complex

PubMed Central

Sun, Wei; Yan, Qing; Vida, Thomas A.; Bean, Andrew J.

2003-01-01

Movement through the endocytic pathway occurs principally via a series of membrane fusion and fission reactions that allow sorting of molecules to be recycled from those to be degraded. Endosome fusion is dependent on SNARE proteins, although the nature of the proteins involved and their regulation has not been fully elucidated. We found that the endosome-associated hepatocyte responsive serum phosphoprotein (Hrs) inhibited the homotypic fusion of early endosomes. A region of Hrs predicted to form a coiled coil required for binding the Q-SNARE, SNAP-25, mimicked the inhibition of endosome fusion produced by full-length Hrs, and was sufficient for endosome binding. SNAP-25, syntaxin 13, and VAMP2 were bound from rat brain membranes to the Hrs coiled-coil domain. Syntaxin 13 inhibited early endosomal fusion and botulinum toxin/E inhibition of early endosomal fusion was reversed by addition of SNAP-25(150–206), confirming a role for syntaxin 13, and establishing a role for SNAP-25 in endosomal fusion. Hrs inhibited formation of the syntaxin 13–SNAP-25–VAMP2 complex by displacing VAMP2 from the complex. These data suggest that SNAP-25 is a receptor for Hrs on early endosomal membranes and that the binding of Hrs to SNAP-25 on endosomal membranes inhibits formation of a SNARE complex required for homotypic endosome fusion. PMID:12847087

Kinetics of Cell Fusion Induced by a Syncytia-Producing Mutant of Herpes Simplex Virus Type I

PubMed Central

Person, Stanley; Knowles, Robert W.; Read, G. Sullivan; Warner, Susan C.; Bond, Vincent C.

1976-01-01

We have isolated a number of plaque-morphology mutants from a strain of herpes simplex virus type I which, unlike the wild type, cause extensive cell fusion during a productive viral infection. After the onset of fusion, there is an exponential decrease in the number of single cells as a function of time after infection. At a multiplicity of infection (MOI) of 3.8 plaque-forming units per cell, fusion begins 5.3 h after infection with the number of single cells decreasing to 10% of the original number 10.2 h after infection. As the MOI is gradually increased from 0.4 to 8, the onset of fusion occurs earlier during infection. However, when the MOI is increased from 8 to 86, the onset of fusion does not occur any earlier. The rate of fusion is independent of the MOI for an MOI greater than 1. The rate of fusion varies linearly with initial cell density up to 3.5 × 104 cells/cm2 and is independent of initial cell density at higher cell concentrations. To assay cell fusion we have developed a simple quantitative assay using a Coulter counter to measure the number of single cells as a function of time after infection. Data obtained using a Coulter counter are similar to those obtained with a microscope assay. PMID:173881

Genetic studies of cell fusion induced by herpes simplex virus type 1

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

Read, G.S.; Person, S.; Keller, P.M.

1980-07-01

Eight cell fusion-causing syn mutants were isolated from the KOS strain of herpes simplex virus type 1. Unlike the wild-type virus, the mutants produced plaques containing multinucleated cells, or syncytia. Fusion kinetics curves were established with a Coulter Counter assay for the mutants and wild-type virus in single infections of human embryonic lung (HEL) cells, for the mutants and wild-type virus in mixed infections (dominance test), and for pairs of mutants in mixed infection and proceeded with an exponential decrease in the number of small single cells. At some later time that was characteristic of the mutant, there was amore » significant reduction in the rate of fusion for all but possibly one of the mutants. Although the wild-type virus did not produce syncytial plaques, it did induce a small amount of fusion that stopped abruptly about 2 h after it started. These data are consistent with the hypothesis that both mutants and wild type induce an active fusion inducer and that the activity of this inducer is subsequently inhibited. The extent of fusion is apparently determined by the length of the interval during which the fusion inducer is active. That fusion is actively inhibited in wild-type infections is indicated by the observation that syn mutant-infected cells fused more readily with uninfected cells than with wild type-infected cells.« less

Semiclassical treatment of fusion and breakup processes of ^{6,8}He halo nuclei

NASA Astrophysics Data System (ADS)

Majeed, Fouad A.; Abdul-Hussien, Yousif A.

2016-06-01

A semiclassical approach has been used to study the effect of channel coupling on the calculations of the total fusion reaction cross section σ _{fus}, and the fusion barrier distribution D_{fus} for the systems 6He +^{238}U and 8He +^{197}Au. Since these systems invloves light exotic nuclei, breakup states channel play an important role that should be considered in the calculations. In semiclassical treatment, the relative motion between the projectile and target nuclei is approximated by a classical trajectory while the intrinsic dynamics is handled by time-dependent quantum mechanics. The calculations of the total fusion cross section σ _{fus}, and the fusion barrier distribution D_{fus} are compared with the full quantum mechanical calculations using the coupled-channels calculations with all order coupling using the computer code and with the available experimental data.

Disassembly time of deuterium-cluster-fusion plasma irradiated by an intense laser pulse.

PubMed

Bang, W

2015-07-01

Energetic deuterium ions from large deuterium clusters (>10nm diameter) irradiated by an intense laser pulse (>10(16)W/cm(2)) produce DD fusion neutrons for a time interval determined by the geometry of the resulting fusion plasma. We present an analytical solution of this time interval, the plasma disassembly time, for deuterium plasmas that are cylindrical in shape. Assuming a symmetrically expanding deuterium plasma, we calculate the expected fusion neutron yield and compare with an independent calculation of the yield using the concept of a finite confinement time at a fixed plasma density. The calculated neutron yields agree quantitatively with the available experimental data. Our one-dimensional simulations indicate that one could expect a tenfold increase in total neutron yield by magnetically confining a 10-keV deuterium fusion plasma for 10ns.

Model-independent determination of the astrophysical S factor in laser-induced fusion plasmas

NASA Astrophysics Data System (ADS)

Lattuada, D.; Barbarino, M.; Bonasera, A.; Bang, W.; Quevedo, H. J.; Warren, M.; Consoli, F.; De Angelis, R.; Andreoli, P.; Kimura, S.; Dyer, G.; Bernstein, A. C.; Hagel, K.; Barbui, M.; Schmidt, K.; Gaul, E.; Donovan, M. E.; Natowitz, J. B.; Ditmire, T.

2016-04-01

In this work, we present a new and general method for measuring the astrophysical S factor of nuclear reactions in laser-induced plasmas and we apply it to :mmultiscripts>(d ,n )3He . The experiment was performed with the Texas Petawatt Laser, which delivered 150-270 fs pulses of energy ranging from 90 to 180 J to D2 or CD4 molecular clusters (where D denotes 2H ) . After removing the background noise, we used the measured time-of-flight data of energetic deuterium ions to obtain their energy distribution. We derive the S factor using the measured energy distribution of the ions, the measured volume of the fusion plasma, and the measured fusion yields. This method is model independent in the sense that no assumption on the state of the system is required, but it requires an accurate measurement of the ion energy distribution, especially at high energies, and of the relevant fusion yields. In the :mmultiscripts>(d ,n )3He and 3He(d ,p )4He cases discussed here, it is very important to apply the background subtraction for the energetic ions and to measure the fusion yields with high precision. While the available data on both ion distribution and fusion yields allow us to determine with good precision the S factor in the d +d case (lower Gamow energies), for the d +3He case the data are not precise enough to obtain the S factor using this method. Our results agree with other experiments within the experimental error, even though smaller values of the S factor were obtained. This might be due to the plasma environment differing from the beam target conditions in a conventional accelerator experiment.

Model-independent determination of the astrophysical S factor in laser-induced fusion plasmas

DOE PAGES

Lattuada, D.; Barbarino, M.; Bonasera, A.; ...

2016-04-19

In this paper, we present a new and general method for measuring the astrophysical S factor of nuclear reactions in laser-induced plasmas and we apply it to 2H(d,n) 3He. The experiment was performed with the Texas Petawatt Laser, which delivered 150–270 fs pulses of energy ranging from 90 to 180 J to D 2 or CD 4 molecular clusters (where D denotes 2H). After removing the background noise, we used the measured time-of-flight data of energetic deuterium ions to obtain their energy distribution. We derive the S factor using the measured energy distribution of the ions, the measured volume ofmore » the fusion plasma, and the measured fusion yields. This method is model independent in the sense that no assumption on the state of the system is required, but it requires an accurate measurement of the ion energy distribution, especially at high energies, and of the relevant fusion yields. In the 2H(d,n) 3He and 3He(d,p) 4He cases discussed here, it is very important to apply the background subtraction for the energetic ions and to measure the fusion yields with high precision. While the available data on both ion distribution and fusion yields allow us to determine with good precision the S factor in the d+d case (lower Gamow energies), for the d+ 3He case the data are not precise enough to obtain the S factor using this method. Our results agree with other experiments within the experimental error, even though smaller values of the S factor were obtained. This might be due to the plasma environment differing from the beam target conditions in a conventional accelerator experiment.« less

Human-computer interface for the study of information fusion concepts in situation analysis and command decision support systems

NASA Astrophysics Data System (ADS)

Roy, Jean; Breton, Richard; Paradis, Stephane

2001-08-01

Situation Awareness (SAW) is essential for commanders to conduct decision-making (DM) activities. Situation Analysis (SA) is defined as a process, the examination of a situation, its elements, and their relations, to provide and maintain a product, i.e., a state of SAW for the decision maker. Operational trends in warfare put the situation analysis process under pressure. This emphasizes the need for a real-time computer-based Situation analysis Support System (SASS) to aid commanders in achieving the appropriate situation awareness, thereby supporting their response to actual or anticipated threats. Data fusion is clearly a key enabler for SA and a SASS. Since data fusion is used for SA in support of dynamic human decision-making, the exploration of the SA concepts and the design of data fusion techniques must take into account human factor aspects in order to ensure a cognitive fit of the fusion system with the decision-maker. Indeed, the tight human factor aspects in order to ensure a cognitive fit of the fusion system with the decision-maker. Indeed, the tight integration of the human element with the SA technology is essential. Regarding these issues, this paper provides a description of CODSI (Command Decision Support Interface), and operational- like human machine interface prototype for investigations in computer-based SA and command decision support. With CODSI, one objective was to apply recent developments in SA theory and information display technology to the problem of enhancing SAW quality. It thus provides a capability to adequately convey tactical information to command decision makers. It also supports the study of human-computer interactions for SA, and methodologies for SAW measurement.

Learning to Classify with Possible Sensor Failures

DTIC Science & Technology

2014-05-04

SVMs), have demonstrated good classification performance when the training data is representative of the test data [1, 2, 3]. However, in many real...Detection of people and animals using non- imaging sensors,” Information Fusion (FUSION), 2011 Proceedings of the 14th International Conference on, pp...classification methods in terms of both classification accuracy and anomaly detection rate using 1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND SUBTITLE 13

Computation Methods for NASA Data-streams for Agricultural Efficiency Applications

NASA Astrophysics Data System (ADS)

Shrestha, B.; O'Hara, C. G.; Mali, P.

2007-12-01

Temporal Map Algebra (TMA) is a novel technique for analyzing time-series of satellite imageries using simple algebraic operators that treats time-series imageries as a three-dimensional dataset, where two dimensions encode planimetric position on earth surface and the third dimension encodes time. Spatio-temporal analytical processing methods such as TMA that utilize moderate spatial resolution satellite imagery having high temporal resolution to create multi-temporal composites are data intensive as well as computationally intensive. TMA analysis for multi-temporal composites provides dramatically enhanced usefulness that will yield previously unavailable capabilities to user communities, if deployment is coupled with significant High Performance Computing (HPC) capabilities; and interfaces are designed to deliver the full potential for these new technological developments. In this research, cross-platform data fusion and adaptive filtering using TMA was employed to create highly useful daily datasets and cloud-free high-temporal resolution vegetation index (VI) composites with enhanced information content for vegetation and bio-productivity monitoring, surveillance, and modeling. Fusion of Normalized Difference Vegetation Index (NDVI) data created from Aqua and Terra Moderate Resolution Imaging Spectroradiometer (MODIS) surface-reflectance data (MOD09) enables the creation of daily composites which are of immense value to a broad spectrum of global and national applications. Additionally these products are highly desired by many natural resources agencies like USDA/FAS/PECAD. Utilizing data streams collected by similar sensors on different platforms that transit the same areas at slightly different times of the day offers the opportunity to develop fused data products that have enhanced cloud-free and reduced noise characteristics. Establishing a Fusion Quality Confidence Code (FQCC) provides a metadata product that quantifies the method of fusion for a given pixel and enables a relative quality and confidence factor to be established for a given daily pixel value. When coupled with metadata that quantify the source sensor, day and time of acquisition, and the fusion method of each pixel to create the daily product; a wealth of information is available to assist in deriving new data and information products. These newly developed abilities to create highly useful daily data sets imply that temporal composites for a geographic area of interest may be created for user-defined temporal intervals that emphasize a user designated day of interest. At GeoResources Institute, Mississippi State University, solutions have been developed to create custom composites and cross-platform satellite data fusion using TMA which are useful for National Aeronautics and Space Administration (NASA) Rapid Prototyping Capability (RPC) and Integrated System Solutions (ISS) experiments for agricultural applications.

An Accurate GPS-IMU/DR Data Fusion Method for Driverless Car Based on a Set of Predictive Models and Grid Constraints

PubMed Central

Wang, Shiyao; Deng, Zhidong; Yin, Gang

2016-01-01

A high-performance differential global positioning system (GPS)  receiver with real time kinematics provides absolute localization for driverless cars. However, it is not only susceptible to multipath effect but also unable to effectively fulfill precise error correction in a wide range of driving areas. This paper proposes an accurate GPS–inertial measurement unit (IMU)/dead reckoning (DR) data fusion method based on a set of predictive models and occupancy grid constraints. First, we employ a set of autoregressive and moving average (ARMA) equations that have different structural parameters to build maximum likelihood models of raw navigation. Second, both grid constraints and spatial consensus checks on all predictive results and current measurements are required to have removal of outliers. Navigation data that satisfy stationary stochastic process are further fused to achieve accurate localization results. Third, the standard deviation of multimodal data fusion can be pre-specified by grid size. Finally, we perform a lot of field tests on a diversity of real urban scenarios. The experimental results demonstrate that the method can significantly smooth small jumps in bias and considerably reduce accumulated position errors due to DR. With low computational complexity, the position accuracy of our method surpasses existing state-of-the-arts on the same dataset and the new data fusion method is practically applied in our driverless car. PMID:26927108

An Accurate GPS-IMU/DR Data Fusion Method for Driverless Car Based on a Set of Predictive Models and Grid Constraints.

PubMed

Wang, Shiyao; Deng, Zhidong; Yin, Gang

2016-02-24

A high-performance differential global positioning system (GPS)  receiver with real time kinematics provides absolute localization for driverless cars. However, it is not only susceptible to multipath effect but also unable to effectively fulfill precise error correction in a wide range of driving areas. This paper proposes an accurate GPS-inertial measurement unit (IMU)/dead reckoning (DR) data fusion method based on a set of predictive models and occupancy grid constraints. First, we employ a set of autoregressive and moving average (ARMA) equations that have different structural parameters to build maximum likelihood models of raw navigation. Second, both grid constraints and spatial consensus checks on all predictive results and current measurements are required to have removal of outliers. Navigation data that satisfy stationary stochastic process are further fused to achieve accurate localization results. Third, the standard deviation of multimodal data fusion can be pre-specified by grid size. Finally, we perform a lot of field tests on a diversity of real urban scenarios. The experimental results demonstrate that the method can significantly smooth small jumps in bias and considerably reduce accumulated position errors due to DR. With low computational complexity, the position accuracy of our method surpasses existing state-of-the-arts on the same dataset and the new data fusion method is practically applied in our driverless car.

Lesion classification using clinical and visual data fusion by multiple kernel learning

NASA Astrophysics Data System (ADS)

Kisilev, Pavel; Hashoul, Sharbell; Walach, Eugene; Tzadok, Asaf

2014-03-01

To overcome operator dependency and to increase diagnosis accuracy in breast ultrasound (US), a lot of effort has been devoted to developing computer-aided diagnosis (CAD) systems for breast cancer detection and classification. Unfortunately, the efficacy of such CAD systems is limited since they rely on correct automatic lesions detection and localization, and on robustness of features computed based on the detected areas. In this paper we propose a new approach to boost the performance of a Machine Learning based CAD system, by combining visual and clinical data from patient files. We compute a set of visual features from breast ultrasound images, and construct the textual descriptor of patients by extracting relevant keywords from patients' clinical data files. We then use the Multiple Kernel Learning (MKL) framework to train SVM based classifier to discriminate between benign and malignant cases. We investigate different types of data fusion methods, namely, early, late, and intermediate (MKL-based) fusion. Our database consists of 408 patient cases, each containing US images, textual description of complaints and symptoms filled by physicians, and confirmed diagnoses. We show experimentally that the proposed MKL-based approach is superior to other classification methods. Even though the clinical data is very sparse and noisy, its MKL-based fusion with visual features yields significant improvement of the classification accuracy, as compared to the image features only based classifier.

Remote sensing based detection of forested wetlands: An evaluation of LiDAR, aerial imagery, and their data fusion

NASA Astrophysics Data System (ADS)

Suiter, Ashley Elizabeth

Multi-spectral imagery provides a robust and low-cost dataset for assessing wetland extent and quality over broad regions and is frequently used for wetland inventories. However in forested wetlands, hydrology is obscured by tree canopy making it difficult to detect with multi-spectral imagery alone. Because of this, classification of forested wetlands often includes greater errors than that of other wetlands types. Elevation and terrain derivatives have been shown to be useful for modelling wetland hydrology. But, few studies have addressed the use of LiDAR intensity data detecting hydrology in forested wetlands. Due the tendency of LiDAR signal to be attenuated by water, this research proposed the fusion of LiDAR intensity data with LiDAR elevation, terrain data, and aerial imagery, for the detection of forested wetland hydrology. We examined the utility of LiDAR intensity data and determined whether the fusion of Lidar derived data with multispectral imagery increased the accuracy of forested wetland classification compared with a classification performed with only multi-spectral image. Four classifications were performed: Classification A -- All Imagery, Classification B -- All LiDAR, Classification C -- LiDAR without Intensity, and Classification D -- Fusion of All Data. These classifications were performed using random forest and each resulted in a 3-foot resolution thematic raster of forested upland and forested wetland locations in Vermilion County, Illinois. The accuracies of these classifications were compared using Kappa Coefficient of Agreement. Importance statistics produced within the random forest classifier were evaluated in order to understand the contribution of individual datasets. Classification D, which used the fusion of LiDAR and multi-spectral imagery as input variables, had moderate to strong agreement between reference data and classification results. It was found that Classification A performed using all the LiDAR data and its derivatives (intensity, elevation, slope, aspect, curvatures, and Topographic Wetness Index) was the most accurate classification with Kappa: 78.04%, indicating moderate to strong agreement. However, Classification C, performed with LiDAR derivative without intensity data had less agreement than would be expected by chance, indicating that LiDAR contributed significantly to the accuracy of Classification B.

Immunological Approach to the Identification and Development of Vaccines to Various Toxins

DTIC Science & Technology

1991-03-30

discussed. 4 II. RESULTS A. SAXITOXIN Within the last year, fusions of spleen cells from mice immu- nized with SXT conjugated to keyhole limpet hemocyanin...as described in previous reports (also see reference 1). A total of approximately 1200 hybrids have been screened from two fusions of spleen cells ...from mice immunized with SXT-formaldeh1yd- KLH and three fusions of spleen cells from mice immunized with SXT-SPDP-KLH (data not shown). Up to date

SARS-CoV fusion peptides induce membrane surface ordering and curvature

PubMed Central

Basso, Luis G. M.; Vicente, Eduardo F.; Crusca Jr., Edson; Cilli, Eduardo M.; Costa-Filho, Antonio J.

2016-01-01

Viral membrane fusion is an orchestrated process triggered by membrane-anchored viral fusion glycoproteins. The S2 subunit of the spike glycoprotein from severe acute respiratory syndrome (SARS) coronavirus (CoV) contains internal domains called fusion peptides (FP) that play essential roles in virus entry. Although membrane fusion has been broadly studied, there are still major gaps in the molecular details of lipid rearrangements in the bilayer during fusion peptide-membrane interactions. Here we employed differential scanning calorimetry (DSC) and electron spin resonance (ESR) to gather information on the membrane fusion mechanism promoted by two putative SARS FPs. DSC data showed the peptides strongly perturb the structural integrity of anionic vesicles and support the hypothesis that the peptides generate opposing curvature stresses on phosphatidylethanolamine membranes. ESR showed that both FPs increase lipid packing and head group ordering as well as reduce the intramembrane water content for anionic membranes. Therefore, bending moment in the bilayer could be generated, promoting negative curvature. The significance of the ordering effect, membrane dehydration, changes in the curvature properties and the possible role of negatively charged phospholipids in helping to overcome the high kinetic barrier involved in the different stages of the SARS-CoV-mediated membrane fusion are discussed. PMID:27892522

The p14 fusion-associated small transmembrane (FAST) protein effects membrane fusion from a subset of membrane microdomains.

PubMed

Corcoran, Jennifer A; Salsman, Jayme; de Antueno, Roberto; Touhami, Ahmed; Jericho, Manfred H; Clancy, Eileen K; Duncan, Roy

2006-10-20

The reovirus fusion-associated small transmembrane (FAST) proteins are a unique family of viral membrane fusion proteins. These nonstructural viral proteins induce efficient cell-cell rather than virus-cell membrane fusion. We analyzed the lipid environment in which the reptilian reovirus p14 FAST protein resides to determine the influence of the cell membrane on the fusion activity of the FAST proteins. Topographical mapping of the surface of fusogenic p14-containing liposomes by atomic force microscopy under aqueous conditions revealed that p14 resides almost exclusively in thickened membrane microdomains. In transfected cells, p14 was found in both Lubrol WX- and Triton X-100-resistant membrane complexes. Cholesterol depletion of donor cell membranes led to preferential disruption of p14 association with Lubrol WX (but not Triton X-100)-resistant membranes and decreased cell-cell fusion activity, both of which were reversed upon subsequent cholesterol repletion. Furthermore, co-patching analysis by fluorescence microscopy indicated that p14 did not co-localize with classical lipid-anchored raft markers. These data suggest that the p14 FAST protein associates with heterogeneous membrane microdomains, a distinct subset of which is defined by cholesterol-dependent Lubrol WX resistance and which may be more relevant to the membrane fusion process.

Inner membrane fusion mediates spatial distribution of axonal mitochondria

PubMed Central

Yu, Yiyi; Lee, Hao-Chih; Chen, Kuan-Chieh; Suhan, Joseph; Qiu, Minhua; Ba, Qinle; Yang, Ge

2016-01-01

In eukaryotic cells, mitochondria form a dynamic interconnected network to respond to changing needs at different subcellular locations. A fundamental yet unanswered question regarding this network is whether, and if so how, local fusion and fission of individual mitochondria affect their global distribution. To address this question, we developed high-resolution computational image analysis techniques to examine the relations between mitochondrial fusion/fission and spatial distribution within the axon of Drosophila larval neurons. We found that stationary and moving mitochondria underwent fusion and fission regularly but followed different spatial distribution patterns and exhibited different morphology. Disruption of inner membrane fusion by knockdown of dOpa1, Drosophila Optic Atrophy 1, not only increased the spatial density of stationary and moving mitochondria but also changed their spatial distributions and morphology differentially. Knockdown of dOpa1 also impaired axonal transport of mitochondria. But the changed spatial distributions of mitochondria resulted primarily from disruption of inner membrane fusion because knockdown of Milton, a mitochondrial kinesin-1 adapter, caused similar transport velocity impairment but different spatial distributions. Together, our data reveals that stationary mitochondria within the axon interconnect with moving mitochondria through fusion and fission and that local inner membrane fusion between individual mitochondria mediates their global distribution. PMID:26742817

Impact of monaural frequency compression on binaural fusion at the brainstem level.

PubMed

Klauke, Isabelle; Kohl, Manuel C; Hannemann, Ronny; Kornagel, Ulrich; Strauss, Daniel J; Corona-Strauss, Farah I

2015-08-01

A classical objective measure for binaural fusion at the brainstem level is the so-called β-wave of the binaural interaction component (BIC) in the auditory brainstem response (ABR). However, in some cases it appeared that a reliable detection of this component still remains a challenge. In this study, we investigate the wavelet phase synchronization stability (WPSS) of ABR data for the analysis of binaural fusion and compare it to the BIC. In particular, we examine the impact of monaural nonlinear frequency compression on binaural fusion. As the auditory system is tonotopically organized, an interaural frequency mismatch caused by monaural frequency compression could negatively effect binaural fusion. In this study, only few subjects showed a detectable β-wave and in most cases only for low ITDs. However, we present a novel objective measure for binaural fusion that outperforms the current state-of-the-art technique (BIC): the WPSS analysis showed a significant difference between the phase stability of the sum of the monaurally evoked responses and the phase stability of the binaurally evoked ABR. This difference could be an indicator for binaural fusion in the brainstem. Furthermore, we observed that monaural frequency compression could indeed effect binaural fusion, as the WPSS results for this condition vary strongly from the results obtained without frequency compression.

Multi-intelligence critical rating assessment of fusion techniques (MiCRAFT)

NASA Astrophysics Data System (ADS)

Blasch, Erik

2015-06-01

Assessment of multi-intelligence fusion techniques includes credibility of algorithm performance, quality of results against mission needs, and usability in a work-domain context. Situation awareness (SAW) brings together low-level information fusion (tracking and identification), high-level information fusion (threat and scenario-based assessment), and information fusion level 5 user refinement (physical, cognitive, and information tasks). To measure SAW, we discuss the SAGAT (Situational Awareness Global Assessment Technique) technique for a multi-intelligence fusion (MIF) system assessment that focuses on the advantages of MIF against single intelligence sources. Building on the NASA TLX (Task Load Index), SAGAT probes, SART (Situational Awareness Rating Technique) questionnaires, and CDM (Critical Decision Method) decision points; we highlight these tools for use in a Multi-Intelligence Critical Rating Assessment of Fusion Techniques (MiCRAFT). The focus is to measure user refinement of a situation over the information fusion quality of service (QoS) metrics: timeliness, accuracy, confidence, workload (cost), and attention (throughput). A key component of any user analysis includes correlation, association, and summarization of data; so we also seek measures of product quality and QuEST of information. Building a notion of product quality from multi-intelligence tools is typically subjective which needs to be aligned with objective machine metrics.

Statistical label fusion with hierarchical performance models

PubMed Central

Asman, Andrew J.; Dagley, Alexander S.; Landman, Bennett A.

2014-01-01

Label fusion is a critical step in many image segmentation frameworks (e.g., multi-atlas segmentation) as it provides a mechanism for generalizing a collection of labeled examples into a single estimate of the underlying segmentation. In the multi-label case, typical label fusion algorithms treat all labels equally – fully neglecting the known, yet complex, anatomical relationships exhibited in the data. To address this problem, we propose a generalized statistical fusion framework using hierarchical models of rater performance. Building on the seminal work in statistical fusion, we reformulate the traditional rater performance model from a multi-tiered hierarchical perspective. This new approach provides a natural framework for leveraging known anatomical relationships and accurately modeling the types of errors that raters (or atlases) make within a hierarchically consistent formulation. Herein, we describe several contributions. First, we derive a theoretical advancement to the statistical fusion framework that enables the simultaneous estimation of multiple (hierarchical) performance models within the statistical fusion context. Second, we demonstrate that the proposed hierarchical formulation is highly amenable to the state-of-the-art advancements that have been made to the statistical fusion framework. Lastly, in an empirical whole-brain segmentation task we demonstrate substantial qualitative and significant quantitative improvement in overall segmentation accuracy. PMID:24817809

Effects of magnetization on fusion product trapping and secondary neutron spectra

DOE PAGES

Knapp, Patrick F.; Schmit, Paul F.; Hansen, Stephanie B.; ...

2015-05-14

In magnetizing the fusion fuel in inertial confinement fusion (ICF) systems, we found that the required stagnation pressure and density can be relaxed dramatically. This happens because the magnetic field insulates the hot fuel from the cold pusher and traps the charged fusion burn products. This trapping allows the burn products to deposit their energy in the fuel, facilitating plasma self-heating. Here, we report on a comprehensive theory of this trapping in a cylindrical DD plasma magnetized with a purely axial magnetic field. Using this theory, we are able to show that the secondary fusion reactions can be used tomore » infer the magnetic field-radius product, BR, during fusion burn. This parameter, not ρR, is the primary confinement parameter in magnetized ICF. Using this method, we analyze data from recent Magnetized Liner InertialFusion experiments conducted on the Z machine at Sandia National Laboratories. Furthermore, we show that in these experiments BR ≈ 0.34(+0.14/-0.06) MG · cm, a ~ 14× increase in BR from the initial value, and confirming that the DD-fusion tritons are magnetized at stagnation. Lastly, this is the first experimental verification of charged burn product magnetization facilitated by compression of an initial seed magnetic flux.« less

[An improved low spectral distortion PCA fusion method].

PubMed

Peng, Shi; Zhang, Ai-Wu; Li, Han-Lun; Hu, Shao-Xing; Meng, Xian-Gang; Sun, Wei-Dong

2013-10-01

Aiming at the spectral distortion produced in PCA fusion process, the present paper proposes an improved low spectral distortion PCA fusion method. This method uses NCUT (normalized cut) image segmentation algorithm to make a complex hyperspectral remote sensing image into multiple sub-images for increasing the separability of samples, which can weaken the spectral distortions of traditional PCA fusion; Pixels similarity weighting matrix and masks were produced by using graph theory and clustering theory. These masks are used to cut the hyperspectral image and high-resolution image into some sub-region objects. All corresponding sub-region objects between the hyperspectral image and high-resolution image are fused by using PCA method, and all sub-regional integration results are spliced together to produce a new image. In the experiment, Hyperion hyperspectral data and Rapid Eye data were used. And the experiment result shows that the proposed method has the same ability to enhance spatial resolution and greater ability to improve spectral fidelity performance.

Towards real-time detection and tracking of spatio-temporal features: Blob-filaments in fusion plasma

DOE PAGES

Wu, Lingfei; Wu, Kesheng; Sim, Alex; ...

2016-06-01

A novel algorithm and implementation of real-time identification and tracking of blob-filaments in fusion reactor data is presented. Similar spatio-temporal features are important in many other applications, for example, ignition kernels in combustion and tumor cells in a medical image. This work presents an approach for extracting these features by dividing the overall task into three steps: local identification of feature cells, grouping feature cells into extended feature, and tracking movement of feature through overlapping in space. Through our extensive work in parallelization, we demonstrate that this approach can effectively make use of a large number of compute nodes tomore » detect and track blob-filaments in real time in fusion plasma. Here, on a set of 30GB fusion simulation data, we observed linear speedup on 1024 processes and completed blob detection in less than three milliseconds using Edison, a Cray XC30 system at NERSC.« less

Iterative Bayesian Estimation of Travel Times on Urban Arterials: Fusing Loop Detector and Probe Vehicle Data.

PubMed

Liu, Kai; Cui, Meng-Ying; Cao, Peng; Wang, Jiang-Bo

2016-01-01

On urban arterials, travel time estimation is challenging especially from various data sources. Typically, fusing loop detector data and probe vehicle data to estimate travel time is a troublesome issue while considering the data issue of uncertain, imprecise and even conflicting. In this paper, we propose an improved data fusing methodology for link travel time estimation. Link travel times are simultaneously pre-estimated using loop detector data and probe vehicle data, based on which Bayesian fusion is then applied to fuse the estimated travel times. Next, Iterative Bayesian estimation is proposed to improve Bayesian fusion by incorporating two strategies: 1) substitution strategy which replaces the lower accurate travel time estimation from one sensor with the current fused travel time; and 2) specially-designed conditions for convergence which restrict the estimated travel time in a reasonable range. The estimation results show that, the proposed method outperforms probe vehicle data based method, loop detector based method and single Bayesian fusion, and the mean absolute percentage error is reduced to 4.8%. Additionally, iterative Bayesian estimation performs better for lighter traffic flows when the variability of travel time is practically higher than other periods.

Iterative Bayesian Estimation of Travel Times on Urban Arterials: Fusing Loop Detector and Probe Vehicle Data

PubMed Central

Cui, Meng-Ying; Cao, Peng; Wang, Jiang-Bo

2016-01-01

On urban arterials, travel time estimation is challenging especially from various data sources. Typically, fusing loop detector data and probe vehicle data to estimate travel time is a troublesome issue while considering the data issue of uncertain, imprecise and even conflicting. In this paper, we propose an improved data fusing methodology for link travel time estimation. Link travel times are simultaneously pre-estimated using loop detector data and probe vehicle data, based on which Bayesian fusion is then applied to fuse the estimated travel times. Next, Iterative Bayesian estimation is proposed to improve Bayesian fusion by incorporating two strategies: 1) substitution strategy which replaces the lower accurate travel time estimation from one sensor with the current fused travel time; and 2) specially-designed conditions for convergence which restrict the estimated travel time in a reasonable range. The estimation results show that, the proposed method outperforms probe vehicle data based method, loop detector based method and single Bayesian fusion, and the mean absolute percentage error is reduced to 4.8%. Additionally, iterative Bayesian estimation performs better for lighter traffic flows when the variability of travel time is practically higher than other periods. PMID:27362654

Binaural fusion and the representation of virtual pitch in the human auditory cortex.

PubMed

Pantev, C; Elbert, T; Ross, B; Eulitz, C; Terhardt, E

1996-10-01

The auditory system derives the pitch of complex tones from the tone's harmonics. Research in psychoacoustics predicted that binaural fusion was an important feature of pitch processing. Based on neuromagnetic human data, the first neurophysiological confirmation of binaural fusion in hearing is presented. The centre of activation within the cortical tonotopic map corresponds to the location of the perceived pitch and not to the locations that are activated when the single frequency constituents are presented. This is also true when the different harmonics of a complex tone are presented dichotically. We conclude that the pitch processor includes binaural fusion to determine the particular pitch location which is activated in the auditory cortex.

Comparing fusion techniques for the ImageCLEF 2013 medical case retrieval task.

PubMed

G Seco de Herrera, Alba; Schaer, Roger; Markonis, Dimitrios; Müller, Henning

2015-01-01

Retrieval systems can supply similar cases with a proven diagnosis to a new example case under observation to help clinicians during their work. The ImageCLEFmed evaluation campaign proposes a framework where research groups can compare case-based retrieval approaches. This paper focuses on the case-based task and adds results of the compound figure separation and modality classification tasks. Several fusion approaches are compared to identify the approaches best adapted to the heterogeneous data of the task. Fusion of visual and textual features is analyzed, demonstrating that the selection of the fusion strategy can improve the best performance on the case-based retrieval task. Copyright © 2014 Elsevier Ltd. All rights reserved.

Phylogenetic ecology at world scale, a new fusion between ecology and evolution.

PubMed

Westoby, Mark

2006-07-01

One fusion between ecology and evolution is well established, under the title of population biology. The years 2006-2020 will see a new fusion, likely to prove equally creative. Inputs from ecology to this second fusion will be worldwide data sets for ecological traits across many species. Inputs from evolution will be phylogenetic trees with well-resolved topology and with increasingly tight geological dates for each branch point. There will be unification of two aims: first to explain the spread of different ways of making a living, across the range of present-day species; and second, to narrate the evolutionary history that has led up to present-day ecology.

The pan-sharpening of satellite and UAV imagery for agricultural applications

NASA Astrophysics Data System (ADS)

Jenerowicz, Agnieszka; Woroszkiewicz, Malgorzata

2016-10-01

Remote sensing techniques are widely used in many different areas of interest, i.e. urban studies, environmental studies, agriculture, etc., due to fact that they provide rapid, accurate and information over large areas with optimal time, spatial and spectral resolutions. Agricultural management is one of the most common application of remote sensing methods nowadays. Monitoring of agricultural sites and creating information regarding spatial distribution and characteristics of crops are important tasks to provide data for precision agriculture, crop management and registries of agricultural lands. For monitoring of cultivated areas many different types of remote sensing data can be used- most popular are multispectral satellites imagery. Such data allow for generating land use and land cover maps, based on various methods of image processing and remote sensing methods. This paper presents fusion of satellite and unnamed aerial vehicle (UAV) imagery for agricultural applications, especially for distinguishing crop types. Authors in their article presented chosen data fusion methods for satellite images and data obtained from low altitudes. Moreover the authors described pan- sharpening approaches and applied chosen pan- sharpening methods for multiresolution image fusion of satellite and UAV imagery. For such purpose, satellite images from Landsat- 8 OLI sensor and data collected within various UAV flights (with mounted RGB camera) were used. In this article, the authors not only had shown the potential of fusion of satellite and UAV images, but also presented the application of pan- sharpening in crop identification and management.

Model-theoretic framework for sensor data fusion

NASA Astrophysics Data System (ADS)

Zavoleas, Kyriakos P.; Kokar, Mieczyslaw M.

1993-09-01

The main goal of our research in sensory data fusion (SDF) is the development of a systematic approach (a methodology) to designing systems for interpreting sensory information and for reasoning about the situation based upon this information and upon available data bases and knowledge bases. To achieve such a goal, two kinds of subgoals have been set: (1) develop a theoretical framework in which rational design/implementation decisions can be made, and (2) design a prototype SDF system along the lines of the framework. Our initial design of the framework has been described in our previous papers. In this paper we concentrate on the model-theoretic aspects of this framework. We postulate that data are embedded in data models, and information processing mechanisms are embedded in model operators. The paper is devoted to analyzing the classes of model operators and their significance in SDF. We investigate transformation abstraction and fusion operators. A prototype SDF system, fusing data from range and intensity sensors, is presented, exemplifying the structures introduced. Our framework is justified by the fact that it provides modularity, traceability of information flow, and a basis for a specification language for SDF.

Medical decision-making inspired from aerospace multisensor data fusion concepts.

PubMed

Pombo, Nuno; Bousson, Kouamana; Araújo, Pedro; Viana, Joaquim

2015-01-01

In recent years, Internet-delivered treatments have been largely used for pain monitoring, offering healthcare professionals and patients the ability to interact anywhere and at any time. Electronic diaries have been increasingly adopted as the preferred methodology to collect data related to pain intensity and symptoms, replacing traditional pen-and-paper diaries. This article presents a multisensor data fusion methodology based on the capabilities provided by aerospace systems to evaluate the effects of electronic and pen-and-paper diaries on pain. We examined English-language studies of randomized controlled trials that use computerized systems and the Internet to collect data about chronic pain complaints. These studies were obtained from three data sources: BioMed Central, PubMed Central and ScienceDirect from the year 2000 until 30 June 2012. Based on comparisons of the reported pain intensity collected during pre- and post-treatment in both the control and intervention groups, the proposed multisensor data fusion model revealed that the benefits of technology and pen-and-paper are qualitatively equivalent [Formula: see text]. We conclude that the proposed model is suitable, intelligible, easy to implement, time efficient and resource efficient.

Lights on: Dye dequenching reveals polymersome fusion with polymer, lipid and stealth lipid vesicles

DOE PAGES

Henderson, Ian M.; Collins, Aaron M.; Quintana, Hope A.; ...

2015-12-13

In this study, we develop a quantitative dye dequenching technique for the measurement of polymersome fusion, using it to characterize the salt mediated, mechanically-induced fusion of polymersomes with polymer, lipid, and so-called stealth lipid vesicles. While dye dequenching has been used to quantitatively explore liposome fusion in the past, this is the first use of dye dequenching to measure polymersome fusion of which we are aware. In addition to providing quantitative results, dye dequenching is ideal for detecting fusion in instances where DLS results would be ambiguous, such as low yield levels and size ranges outside the capabilities of DLS.more » The dye chosen for this study was a cyanine derivative, 1,1'-dioctadecyl-3,3,3',3'-tetramethylindotricarbocyanine iodide (DiR), which proved to provide excellent data on the extent of polymersome fusion. Using this technique, we have shown the limited fusion capabilities of polymersome/liposome heterofusion, notably DOPC vesicles fusing with polymersomes at half the efficiency of polymersome homofusion and DPPC vesicles showing virtually no fusion. In addition to these key heterofusion experiments, we determined the broad applicability of dye dequenching in measuring kinetic rates of polymersome fusion; and showed that even at elevated temperatures or over multiple weeks' time, no polymersome fusion occurred without agitation. Stealth liposomes formed from DPPC and PEO-functionalized lipid, however, fused with polymersomes and stealth liposomes with relatively high efficiency, lending support to our hypothesis that the response of the PEO corona to salt is a key factor in the fusion process. This last finding suggests that although the conjugation of PEO to lipids increases vesicle biocompatibility and enables their longer circulation times, it also renders the vesicles subject to destabilization under high salt and shear (e.g. in the circulatory system) that may lead to, in this case, fusion.« less

Cognitive Load Measurement in a Virtual Reality-based Driving System for Autism Intervention

PubMed Central

Zhang, Lian; Wade, Joshua; Bian, Dayi; Fan, Jing; Swanson, Amy; Weitlauf, Amy; Warren, Zachary; Sarkar, Nilanjan

2016-01-01

Autism Spectrum Disorder (ASD) is a highly prevalent neurodevelopmental disorder with enormous individual and social cost. In this paper, a novel virtual reality (VR)-based driving system was introduced to teach driving skills to adolescents with ASD. This driving system is capable of gathering eye gaze, electroencephalography, and peripheral physiology data in addition to driving performance data. The objective of this paper is to fuse multimodal information to measure cognitive load during driving such that driving tasks can be individualized for optimal skill learning. Individualization of ASD intervention is an important criterion due to the spectrum nature of the disorder. Twenty adolescents with ASD participated in our study and the data collected were used for systematic feature extraction and classification of cognitive loads based on five well-known machine learning methods. Subsequently, three information fusion schemes—feature level fusion, decision level fusion and hybrid level fusion—were explored. Results indicate that multimodal information fusion can be used to measure cognitive load with high accuracy. Such a mechanism is essential since it will allow individualization of driving skill training based on cognitive load, which will facilitate acceptance of this driving system for clinical use and eventual commercialization. PMID:28966730

Quantitative multi-modal NDT data analysis

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

Heideklang, René; Shokouhi, Parisa

2014-02-18

A single NDT technique is often not adequate to provide assessments about the integrity of test objects with the required coverage or accuracy. In such situations, it is often resorted to multi-modal testing, where complementary and overlapping information from different NDT techniques are combined for a more comprehensive evaluation. Multi-modal material and defect characterization is an interesting task which involves several diverse fields of research, including signal and image processing, statistics and data mining. The fusion of different modalities may improve quantitative nondestructive evaluation by effectively exploiting the augmented set of multi-sensor information about the material. It is the redundantmore » information in particular, whose quantification is expected to lead to increased reliability and robustness of the inspection results. There are different systematic approaches to data fusion, each with its specific advantages and drawbacks. In our contribution, these will be discussed in the context of nondestructive materials testing. A practical study adopting a high-level scheme for the fusion of Eddy Current, GMR and Thermography measurements on a reference metallic specimen with built-in grooves will be presented. Results show that fusion is able to outperform the best single sensor regarding detection specificity, while retaining the same level of sensitivity.« less

Mixed H2/H∞-Based Fusion Estimation for Energy-Limited Multi-Sensors in Wearable Body Networks

PubMed Central

Li, Chao; Zhang, Zhenjiang; Chao, Han-Chieh

2017-01-01

In wireless sensor networks, sensor nodes collect plenty of data for each time period. If all of data are transmitted to a Fusion Center (FC), the power of sensor node would run out rapidly. On the other hand, the data also needs a filter to remove the noise. Therefore, an efficient fusion estimation model, which can save the energy of the sensor nodes while maintaining higher accuracy, is needed. This paper proposes a novel mixed H2/H∞-based energy-efficient fusion estimation model (MHEEFE) for energy-limited Wearable Body Networks. In the proposed model, the communication cost is firstly reduced efficiently while keeping the estimation accuracy. Then, the parameters in quantization method are discussed, and we confirm them by an optimization method with some prior knowledge. Besides, some calculation methods of important parameters are researched which make the final estimates more stable. Finally, an iteration-based weight calculation algorithm is presented, which can improve the fault tolerance of the final estimate. In the simulation, the impacts of some pivotal parameters are discussed. Meanwhile, compared with the other related models, the MHEEFE shows a better performance in accuracy, energy-efficiency and fault tolerance. PMID:29280950

Non-ad-hoc decision rule for the Dempster-Shafer method of evidential reasoning

NASA Astrophysics Data System (ADS)

Cheaito, Ali; Lecours, Michael; Bosse, Eloi

1998-03-01

This paper is concerned with the fusion of identity information through the use of statistical analysis rooted in Dempster-Shafer theory of evidence to provide automatic identification aboard a platform. An identity information process for a baseline Multi-Source Data Fusion (MSDF) system is defined. The MSDF system is applied to information sources which include a number of radars, IFF systems, an ESM system, and a remote track source. We use a comprehensive Platform Data Base (PDB) containing all the possible identity values that the potential target may take, and we use the fuzzy logic strategies which enable the fusion of subjective attribute information from sensor and the PDB to make the derivation of target identity more quickly, more precisely, and with statistically quantifiable measures of confidence. The conventional Dempster-Shafer lacks a formal basis upon which decision can be made in the face of ambiguity. We define a non-ad hoc decision rule based on the expected utility interval for pruning the `unessential' propositions which would otherwise overload the real-time data fusion systems. An example has been selected to demonstrate the implementation of our modified Dempster-Shafer method of evidential reasoning.

Systematic study of the fusion barriers using different proximity-type potentials for N=Z colliding nuclei: New extensions

NASA Astrophysics Data System (ADS)

Dutt, Ishwar; Puri, Rajeev K.

2010-04-01

By using 14 different versions and parametrizations of a proximity potential and two new versions of the potential proposed in this paper, we perform a comparative study of fusion barriers by studying 26 symmetric reactions. The mass asymmetry ηA=((A2-A1)/(A2+A1)), however, is very large. Our detailed investigation reveals that most of the proximity potentials reproduce experimental data within ±8% on average. A comparison of fusion cross sections indicates that Bass 80, AW 95, and Denisov DP potentials have a better edge than other potentials. We also propose new versions of the proximity potential as well as Denisov parametrized potential. These new versions improve agreement with the data.

Effects of Local Administration of Boric Acid on Posterolateral Spinal Fusion with Autogenous Bone Grafting in a Rodent Model.

PubMed

Kömürcü, Erkam; Özyalvaçlı, Gülzade; Kaymaz, Burak; Gölge, Umut Hatay; Göksel, Ferdi; Cevizci, Sibel; Adam, Gürhan; Ozden, Raif

2015-09-01

Spinal fusion is among the most frequently applied spinal surgical procedures. The goal of the present study was to evaluate whether the local administration of boric acid (BA) improves spinal fusion in an experimental spinal fusion model in rats. Currently, there is no published data that evaluates the possible positive effects if the local administration of BA on posterolateral spinal fusion. Thirty-two rats were randomly divided into four independent groups: no material was added at the fusion area for group 1; an autogenous morselized corticocancellous bone graft was used for group 2; an autogenous morselized corticocancellous bone graft with boric acid (8.7 mg/kg) for group 3; and only boric acid was placed into the fusion area for group 4. The L4-L6 spinal segments were collected at week 6, and the assessments included radiography, manual palpation, and histomorphometry. A statistically significant difference was determined between the groups with regard to the mean histopathological scores (p = 0.002), and a paired comparison was made with the Mann-Whitney U test to detect the group/groups from which the difference originated. It was determined that only the graft + BA practice increased the histopathological score significantly with regard to the control group (p = 0.002). Whereas, there was no statistically significant difference between the groups in terms of the manual assessment of fusion and radiographic analysis (respectively p = 0.328 and p = 0.196). This preliminary study suggests that BA may clearly be useful as a therapeutic agent in spinal fusion. However, further research is required to show the most effective dosage of BA on spinal fusion, and should indicate whether BA effects spinal fusion in the human body.

3D SPECT/CT fusion using image data projection of bone SPECT onto 3D volume-rendered CT images: feasibility and clinical impact in the diagnosis of bone metastasis.

PubMed

Ogata, Yuji; Nakahara, Tadaki; Ode, Kenichi; Matsusaka, Yohji; Katagiri, Mari; Iwabuchi, Yu; Itoh, Kazunari; Ichimura, Akira; Jinzaki, Masahiro

2017-05-01

We developed a method of image data projection of bone SPECT into 3D volume-rendered CT images for 3D SPECT/CT fusion. The aims of our study were to evaluate its feasibility and clinical usefulness. Whole-body bone scintigraphy (WB) and SPECT/CT scans were performed in 318 cancer patients using a dedicated SPECT/CT systems. Volume data of bone SPECT and CT were fused to obtain 2D SPECT/CT images. To generate our 3D SPECT/CT images, colored voxel data of bone SPECT were projected onto the corresponding location of the volume-rendered CT data after a semi-automatic bone extraction. Then, the resultant 3D images were blended with conventional volume-rendered CT images, allowing to grasp the three-dimensional relationship between bone metabolism and anatomy. WB and SPECT (WB + SPECT), 2D SPECT/CT fusion, and 3D SPECT/CT fusion were evaluated by two independent reviewers in the diagnosis of bone metastasis. The inter-observer variability and diagnostic accuracy in these three image sets were investigated using a four-point diagnostic scale. Increased bone metabolism was found in 744 metastatic sites and 1002 benign changes. On a per-lesion basis, inter-observer agreements in the diagnosis of bone metastasis were 0.72 for WB + SPECT, 0.90 for 2D SPECT/CT, and 0.89 for 3D SPECT/CT. Receiver operating characteristic analyses for the diagnostic accuracy of bone metastasis showed that WB + SPECT, 2D SPECT/CT, and 3D SPECT/CT had an area under the curve of 0.800, 0.983, and 0.983 for reader 1, 0.865, 0.992, and 0.993 for reader 2, respectively (WB + SPECT vs. 2D or 3D SPECT/CT, p < 0.001; 2D vs. 3D SPECT/CT, n.s.). The durations of interpretation of WB + SPECT, 2D SPECT/CT, and 3D SPECT/CT images were 241 ± 75, 225 ± 73, and 182 ± 71 s for reader 1 and 207 ± 72, 190 ± 73, and 179 ± 73 s for reader 2, respectively. As a result, it took shorter time to read 3D SPECT/CT images than 2D SPECT/CT (p < 0.0001) or WB + SPECT images (p < 0.0001). 3D SPECT/CT fusion offers comparable diagnostic accuracy to 2D SPECT/CT fusion. The visual effect of 3D SPECT/CT fusion facilitates reduction of reading time compared to 2D SPECT/CT fusion.

[Contrast-enhanced ultrasound (CEUS) and image fusion for procedures of liver interventions].

PubMed

Jung, E M; Clevert, D A

2018-06-01

Contrast-enhanced ultrasound (CEUS) is becoming increasingly important for the detection and characterization of malignant liver lesions and allows percutaneous treatment when surgery is not possible. Contrast-enhanced ultrasound image fusion with computed tomography (CT) and magnetic resonance imaging (MRI) opens up further options for the targeted investigation of a modified tumor treatment. Ultrasound image fusion offers the potential for real-time imaging and can be combined with other cross-sectional imaging techniques as well as CEUS. With the implementation of ultrasound contrast agents and image fusion, ultrasound has been improved in the detection and characterization of liver lesions in comparison to other cross-sectional imaging techniques. In addition, this method can also be used for intervention procedures. The success rate of fusion-guided biopsies or CEUS-guided tumor ablation lies between 80 and 100% in the literature. Ultrasound-guided image fusion using CT or MRI data, in combination with CEUS, can facilitate diagnosis and therapy follow-up after liver interventions. In addition to the primary applications of image fusion in the diagnosis and treatment of liver lesions, further useful indications can be integrated into daily work. These include, for example, intraoperative and vascular applications as well applications in other organ systems.

Study on polarization image methods in turbid medium

NASA Astrophysics Data System (ADS)

Fu, Qiang; Mo, Chunhe; Liu, Boyu; Duan, Jin; Zhang, Su; Zhu, Yong

2014-11-01

Polarization imaging detection technology in addition to the traditional imaging information, also can get polarization multi-dimensional information, thus improve the probability of target detection and recognition.Image fusion in turbid medium target polarization image research, is helpful to obtain high quality images. Based on visible light wavelength of light wavelength of laser polarization imaging, through the rotation Angle of polaroid get corresponding linear polarized light intensity, respectively to obtain the concentration range from 5% to 10% of turbid medium target stocks of polarization parameters, introduces the processing of image fusion technology, main research on access to the polarization of the image by using different polarization image fusion methods for image processing, discusses several kinds of turbid medium has superior performance of polarization image fusion method, and gives the treatment effect and analysis of data tables. Then use pixel level, feature level and decision level fusion algorithm on three levels of information fusion, DOLP polarization image fusion, the results show that: with the increase of the polarization Angle, polarization image will be more and more fuzzy, quality worse and worse. Than a single fused image contrast of the image be improved obviously, the finally analysis on reasons of the increase the image contrast and polarized light.

Hairpin Folding of HIV gp41 Abrogates Lipid Mixing Function at Physiologic pH and Inhibits Lipid Mixing by Exposed gp41 Constructs†

PubMed Central

Sackett, Kelly; Nethercott, Matthew J.; Shai, Yechiel; Weliky, David P.

2009-01-01

Conformational changes in the HIV gp41 protein are directly correlated with fusion between the HIV and target cell plasma membranes which is the initial step of infection. Key gp41 fusion conformations include an early extended conformation termed pre-hairpin which contains exposed regions and a final low energy conformation termed hairpin which has compact six-helix bundle structure. Current fusion models debate the roles of hairpin and pre-hairpin conformations in the process of membrane merger. In the present work, gp41 constructs have been engineered which correspond to fusion relevant parts of both pre-hairpin and hairpin conformations, and have been analyzed for their ability to induce lipid mixing between membrane vesicles. The data correlate membrane fusion function with the pre-hairpin conformation and suggest that one of the roles of the final hairpin conformation is sequestration of membrane perturbing gp41 regions with consequent loss of the membrane disruption induced earlier by the pre-hairpin structure. To our knowledge, this is the first biophysical study to delineate the membrane fusion potential of gp41 constructs modeling key fusion conformations. PMID:19222185

Loose fusion based on SLAM and IMU for indoor environment

NASA Astrophysics Data System (ADS)

Zhu, Haijiang; Wang, Zhicheng; Zhou, Jinglin; Wang, Xuejing

2018-04-01

The simultaneous localization and mapping (SLAM) method based on the RGB-D sensor is widely researched in recent years. However, the accuracy of the RGB-D SLAM relies heavily on correspondence feature points, and the position would be lost in case of scenes with sparse textures. Therefore, plenty of fusion methods using the RGB-D information and inertial measurement unit (IMU) data have investigated to improve the accuracy of SLAM system. However, these fusion methods usually do not take into account the size of matched feature points. The pose estimation calculated by RGB-D information may not be accurate while the number of correct matches is too few. Thus, considering the impact of matches in SLAM system and the problem of missing position in scenes with few textures, a loose fusion method combining RGB-D with IMU is proposed in this paper. In the proposed method, we design a loose fusion strategy based on the RGB-D camera information and IMU data, which is to utilize the IMU data for position estimation when the corresponding point matches are quite few. While there are a lot of matches, the RGB-D information is still used to estimate position. The final pose would be optimized by General Graph Optimization (g2o) framework to reduce error. The experimental results show that the proposed method is better than the RGB-D camera's method. And this method can continue working stably for indoor environment with sparse textures in the SLAM system.

A methodology for hard/soft information fusion in the condition monitoring of aircraft

NASA Astrophysics Data System (ADS)

Bernardo, Joseph T.

2013-05-01

Condition-based maintenance (CBM) refers to the philosophy of performing maintenance when the need arises, based upon indicators of deterioration in the condition of the machinery. Traditionally, CBM involves equipping machinery with electronic sensors that continuously monitor components and collect data for analysis. The addition of the multisensory capability of human cognitive functions (i.e., sensemaking, problem detection, planning, adaptation, coordination, naturalistic decision making) to traditional CBM may create a fuller picture of machinery condition. Cognitive systems engineering techniques provide an opportunity to utilize a dynamic resource—people acting as soft sensors. The literature is extensive on techniques to fuse data from electronic sensors, but little work exists on fusing data from humans with that from electronic sensors (i.e., hard/soft fusion). The purpose of my research is to explore, observe, investigate, analyze, and evaluate the fusion of pilot and maintainer knowledge, experiences, and sensory perceptions with digital maintenance resources. Hard/soft information fusion has the potential to increase problem detection capability, improve flight safety, and increase mission readiness. This proposed project consists the creation of a methodology that is based upon the Living Laboratories framework, a research methodology that is built upon cognitive engineering principles1. This study performs a critical assessment of concept, which will support development of activities to demonstrate hard/soft information fusion in operationally relevant scenarios of aircraft maintenance. It consists of fieldwork, knowledge elicitation to inform a simulation and a prototype.

Trust Model of Wireless Sensor Networks and Its Application in Data Fusion

PubMed Central

Chen, Zhenguo; Tian, Liqin; Lin, Chuang

2017-01-01

In order to ensure the reliability and credibility of the data in wireless sensor networks (WSNs), this paper proposes a trust evaluation model and data fusion mechanism based on trust. First of all, it gives the model structure. Then, the calculation rules of trust are given. In the trust evaluation model, comprehensive trust consists of three parts: behavior trust, data trust, and historical trust. Data trust can be calculated by processing the sensor data. Based on the behavior of nodes in sensing and forwarding, the behavior trust is obtained. The initial value of historical trust is set to the maximum and updated with comprehensive trust. Comprehensive trust can be obtained by weighted calculation, and then the model is used to construct the trust list and guide the process of data fusion. Using the trust model, simulation results indicate that energy consumption can be reduced by an average of 15%. The detection rate of abnormal nodes is at least 10% higher than that of the lightweight and dependable trust system (LDTS) model. Therefore, this model has good performance in ensuring the reliability and credibility of the data. Moreover, the energy consumption of transmitting was greatly reduced. PMID:28350347

A Framework of Covariance Projection on Constraint Manifold for Data Fusion.

PubMed

Bakr, Muhammad Abu; Lee, Sukhan

2018-05-17

A general framework of data fusion is presented based on projecting the probability distribution of true states and measurements around the predicted states and actual measurements onto the constraint manifold. The constraint manifold represents the constraints to be satisfied among true states and measurements, which is defined in the extended space with all the redundant sources of data such as state predictions and measurements considered as independent variables. By the general framework, we mean that it is able to fuse any correlated data sources while directly incorporating constraints and identifying inconsistent data without any prior information. The proposed method, referred to here as the Covariance Projection (CP) method, provides an unbiased and optimal solution in the sense of minimum mean square error (MMSE), if the projection is based on the minimum weighted distance on the constraint manifold. The proposed method not only offers a generalization of the conventional formula for handling constraints and data inconsistency, but also provides a new insight into data fusion in terms of a geometric-algebraic point of view. Simulation results are provided to show the effectiveness of the proposed method in handling constraints and data inconsistency.

Urban Classification Techniques Using the Fusion of LiDAR and Spectral Data

DTIC Science & Technology

2012-09-01

Photogrammetry and Remote Sensing, 62, 43–63. Stein, D., Beaven, S., Hoff, L., Winter, E., Schaum, A., & Stocker, A. (2002). Anomaly detection from...TECHNIQUES USING THE FUSION OF LIDAR AND SPECTRAL DATA by Justin E. Mesina September 2012 Thesis Advisor: Richard C . Olsen Second...from shadow anomalies . The fused results however, were not as accurate in differentiating trees from grasses as using only spectral results. Overall the

Biomagnetic effects: a consideration in fusion reactor development.

PubMed Central

Mahlum, D D

1977-01-01

Fusion reactors will utilize powerful magnetic fields for the confinement and heating of plasma and for the diversion of impurities. Large dipole fields generated by the plasma current and the divertor and transformer coils will radiate outward for several hundred meters, resulting in magnetic fields up to 450 gauss in working areas. Since occupational personnel could be exposed to substantial magnetic fields in a fusion power plant, an attempt has been made to assess the possible biological and health consequences of such exposure, using the existing literature. The available data indicate that magnetic fields can interact with biological material to produce effects, although the reported effects are usually small in magnitude and often unconfirmed. The existing data base is judged to be totally inadequate for assessment of potential health and environmental consequences of magnetic fields and for the establishment of appropriate standards. Requisite studies to provide an adequate data base are outlined. PMID:598345

Multi-look fusion identification: a paradigm shift from quality to quantity in data samples

NASA Astrophysics Data System (ADS)

Wong, S.

2009-05-01

A multi-look identification method known as score-level fusion is found to be capable of achieving very high identification accuracy, even when low quality target signatures are used. Analysis using measured ground vehicle radar signatures has shown that a 97% correct identification rate can be achieved using this multi-look fusion method; in contrast, only a 37% accuracy rate is obtained when single target signature input is used. The results suggest that quantity can be used to replace quality of the target data in improving identification accuracy. With the advent of sensor technology, a large amount of target signatures of marginal quality can be captured routinely. This quantity over quality approach allows maximum exploitation of the available data to improve the target identification performance and this could have the potential of being developed into a disruptive technology.