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Sample records for feature fusion applied

  1. Model based feature fusion approach

    NARCIS (Netherlands)

    Schwering, P.B.W.

    2001-01-01

    In recent years different sensor data fusion approaches have been analyzed and evaluated in the field of mine detection. In various studies comparisons have been made between different techniques. Although claims can be made for advantages for using certain techniques, until now there has been no si

  2. Multimodal Biometrics using Feature Fusion

    Directory of Open Access Journals (Sweden)

    K. Krishneswari

    2012-01-01

    Full Text Available Problem statement: Biometrics is a unique, measurable physiological or behavioural characteristic of a person and finds extensive applications in authentication and authorization. Fingerprint, palm print, iris, voice, are some of the most widely used biometrics for personal identification. To reduce the error rates and enhance the usability of biometric system, multimodal biometric systems are used where more than one biometric characteristics are used. Approach: In this study it is proposed to investigate the performance of multimodal biometrics using palm print and fingerprint. Features are extracted using Discrete Cosine Transform (DCT and attributes selected using Information Gain (IG. Results and Conclusion: The proposed technique shows an average improvement of 8.52% compared to using palmprint technique alone. The processing time does not increase for verification compared to palm print techniques.

  3. Multifinger Feature Level Fusion Based Fingerprint Identification

    Directory of Open Access Journals (Sweden)

    Praveen N

    2012-12-01

    Full Text Available Fingerprint based authentication systems are one of the cost-effective biometric authentication techniques employed for personal identification. As the data base population increases, fast identification/recognition algorithms are required with high accuracy. Accuracy can be increased using multimodal evidences collected by multiple biometric traits. In this work, consecutive fingerprint images are taken, global singularities are located using directional field strength and their local orientation vector is formulated with respect to the base line of the finger. Featurelevel fusion is carried out and a 32 element feature template is obtained. A matching score is formulated for the identification and 100% accuracy was obtained for a database of 300 persons. The polygonal feature vector helps to reduce the size of the feature database from the present 70-100 minutiae features to just 32 features and also a lower matching threshold can be fixed compared to single finger based identification

  4. Multispectral image fusion based on fractal features

    Science.gov (United States)

    Tian, Jie; Chen, Jie; Zhang, Chunhua

    2004-01-01

    Imagery sensors have been one indispensable part of the detection and recognition systems. They are widely used to the field of surveillance, navigation, control and guide, et. However, different imagery sensors depend on diverse imaging mechanisms, and work within diverse range of spectrum. They also perform diverse functions and have diverse circumstance requires. So it is unpractical to accomplish the task of detection or recognition with a single imagery sensor under the conditions of different circumstances, different backgrounds and different targets. Fortunately, the multi-sensor image fusion technique emerged as important route to solve this problem. So image fusion has been one of the main technical routines used to detect and recognize objects from images. While, loss of information is unavoidable during fusion process, so it is always a very important content of image fusion how to preserve the useful information to the utmost. That is to say, it should be taken into account before designing the fusion schemes how to avoid the loss of useful information or how to preserve the features helpful to the detection. In consideration of these issues and the fact that most detection problems are actually to distinguish man-made objects from natural background, a fractal-based multi-spectral fusion algorithm has been proposed in this paper aiming at the recognition of battlefield targets in the complicated backgrounds. According to this algorithm, source images are firstly orthogonally decomposed according to wavelet transform theories, and then fractal-based detection is held to each decomposed image. At this step, natural background and man-made targets are distinguished by use of fractal models that can well imitate natural objects. Special fusion operators are employed during the fusion of area that contains man-made targets so that useful information could be preserved and features of targets could be extruded. The final fused image is reconstructed from the

  5. Image fusion using sparse overcomplete feature dictionaries

    Energy Technology Data Exchange (ETDEWEB)

    Brumby, Steven P.; Bettencourt, Luis; Kenyon, Garrett T.; Chartrand, Rick; Wohlberg, Brendt

    2015-10-06

    Approaches for deciding what individuals in a population of visual system "neurons" are looking for using sparse overcomplete feature dictionaries are provided. A sparse overcomplete feature dictionary may be learned for an image dataset and a local sparse representation of the image dataset may be built using the learned feature dictionary. A local maximum pooling operation may be applied on the local sparse representation to produce a translation-tolerant representation of the image dataset. An object may then be classified and/or clustered within the translation-tolerant representation of the image dataset using a supervised classification algorithm and/or an unsupervised clustering algorithm.

  6. An investigation of face and fingerprint feature-fusion guidelines

    CSIR Research Space (South Africa)

    Brown, Dane

    2016-05-01

    Full Text Available and application of the face and fingerprint feature-fusion guidelines, respectively. The experimental analyses and results are discussed in Section 8. Section 9 concludes the paper and discusses future work. 2 Quality Enhancement Quality enhancement is used... and discussed as follows. An Investigation of Face and Fingerprint Feature-Fusion Guidelines 9 Table 1: Feature-Fusion Guidelines Stage Name Advantage Disadvantage Suggested Use Quality Enhancement Pixel Normalization Reduces in- consistent lighting. Not very...

  7. A NOVEL REGION FEATURE USED IN MULTISENSOR IMAGE FUSION

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    A new region feature which emphasized the salience of target region and its neighbors is proposed.In region segmentation-based multisensor image fusion scheme, the presented feature can be extracted from each segmented region to determine the fusion weight. Experimental results demonstrate that the proposed feature has extensive application scope and it provides much more information for each region. It can not only be used in image fusion but also be used in other image processing applications.

  8. Weighted feature fusion for content-based image retrieval

    Science.gov (United States)

    Soysal, Omurhan A.; Sumer, Emre

    2016-07-01

    The feature descriptors such as SIFT (Scale Invariant Feature Transform), SURF (Speeded-up Robust Features) and ORB (Oriented FAST and Rotated BRIEF) are known as the most commonly used solutions for the content-based image retrieval problems. In this paper, a novel approach called "Weighted Feature Fusion" is proposed as a generic solution instead of applying problem-specific descriptors alone. Experiments were performed on two basic data sets of the Inria in order to improve the precision of retrieval results. It was found that in cases where the descriptors were used alone the proposed approach yielded 10-30% more accurate results than the ORB alone. Besides, it yielded 9-22% and 12-29% less False Positives compared to the SIFT alone and SURF alone, respectively.

  9. Fusion programs in applied plasma physics

    Energy Technology Data Exchange (ETDEWEB)

    1992-02-01

    The objectives of the theoretical science program are: To support the interpretation of present experiments and predict the outcome of future planned experiments; to improve on existing models and codes and validate against experimental results; and to conduct theoretical physics development of advanced concepts with applications for DIII-D and future devices. Major accomplishments in FY91 include the corroboration between theory and experiment on MHD behavior in the second stable regime of operation on DIII-D, and the frequency and mode structure of toroidal Alfven eigenmodes in high beta, shaped plasmas. We have made significant advances in the development of the gyro-Landau fluid approach to turbulence simulation which more accurately models kinetic drive and damping mechanisms. Several theoretical models to explain the bifurcation phenomenon in L- to H-mode transition were proposed providing the theoretical basis for future experimental verification. The capabilities of new rf codes have been upgraded in response to the expanding needs of the rf experiments. Codes are being employed to plan for a fully non-inductive current drive experiment in a high beta, enhanced confinement regime. GA's experimental effort in Applied Physics encompasses two advanced diagnostics essential for the operation of future fusion experiments: Alpha particle diagnostic, and current and density profile diagnostics. This paper discusses research in all these topics.

  10. Feature Level Fusion of Face and Fingerprint Biometrics

    CERN Document Server

    Rattani, Ajita; Bicego, Manuele; Tistarelli, Massimo

    2010-01-01

    The aim of this paper is to study the fusion at feature extraction level for face and fingerprint biometrics. The proposed approach is based on the fusion of the two traits by extracting independent feature pointsets from the two modalities, and making the two pointsets compatible for concatenation. Moreover, to handle the problem of curse of dimensionality, the feature pointsets are properly reduced in dimension. Different feature reduction techniques are implemented, prior and after the feature pointsets fusion, and the results are duly recorded. The fused feature pointset for the database and the query face and fingerprint images are matched using techniques based on either the point pattern matching, or the Delaunay triangulation. Comparative experiments are conducted on chimeric and real databases, to assess the actual advantage of the fusion performed at the feature extraction level, in comparison to the matching score level.

  11. Multiresolution image fusion scheme based on fuzzy region feature

    Institute of Scientific and Technical Information of China (English)

    LIU Gang; JING Zhong-liang; SUN Shao-yuan

    2006-01-01

    This paper proposes a novel region based image fusion scheme based on multiresolution analysis. The low frequency band of the image multiresolution representation is segmented into important regions, sub-important regions and background regions. Each feature of the regions is used to determine the region's degree of membership in the multiresolution representation,and then to achieve multiresolution representation of the fusion result. The final image fusion result can be obtained by using the inverse multiresolution transform. Experiments showed that the proposed image fusion method can have better performance than existing image fusion methods.

  12. Sparse Representation Fusion of Fingerprint, Iris and Palmprint Biometric Features

    Directory of Open Access Journals (Sweden)

    S.Anu H Nair

    2014-03-01

    Full Text Available Multimodal Biometric System using multiple sources of information for establishing the identity has been widely recognized. But the computational models for multimodal biometrics recognition have only recently received attention. In this paper multimodal biometric image such as fingerprint, palmprint, and iris are extracted individually and are fused together using a sparse fusion mechanism. A multimodal sparse representation method is proposed, which interprets the test data by a sparse linear combination of training data, while constraining the observations from different modalities of the test subject to share their sparse representations. The images are pre-processed for feature extraction. In this process Sobel, canny, Prewitt edge detection methods were applied. The image quality was measured using PSNR, NAE, and NCC metrics. Based on the results obtained, Sobel edge detection was used for feature extraction. Extracted features were subjected to sparse representation for the fusion of different modalities. The fused template can be used for watermarking and person identification application. CASIA database is chosen for the biometric images.

  13. Ear Identification by Fusion of Segmented Slice Regions using Invariant Features: An Experimental Manifold with Dual Fusion Approach

    CERN Document Server

    Kisku, Dakshina Ranjan; Sing, Jamuna Kanta

    2010-01-01

    This paper proposes a robust ear identification system which is developed by fusing SIFT features of color segmented slice regions of an ear. The proposed ear identification method makes use of Gaussian mixture model (GMM) to build ear model with mixture of Gaussian using vector quantization algorithm and K-L divergence is applied to the GMM framework for recording the color similarity in the specified ranges by comparing color similarity between a pair of reference ear and probe ear. SIFT features are then detected and extracted from each color slice region as a part of invariant feature extraction. The extracted keypoints are then fused separately by the two fusion approaches, namely concatenation and the Dempster-Shafer theory. Finally, the fusion approaches generate two independent augmented feature vectors which are used for identification of individuals separately. The proposed identification technique is tested on IIT Kanpur ear database of 400 individuals and is found to achieve 98.25% accuracy for id...

  14. Fusion of polarimetric infrared features and GPR features for landmine detection

    NARCIS (Netherlands)

    Cremer, F.; Jong, W. de; Schutte, K.

    2003-01-01

    Currently no single sensor reaches the performance requirements for humanitarian landmine detection, Using sensor-fusion methods, multiple sensors can be combined for improved detection performance. This paper focuses on the feature-level fusion procedure for a sensor combination consisting of a pol

  15. Feature Fusion Approach on Keystroke Dynamics Efficiency Enhancement

    Directory of Open Access Journals (Sweden)

    Pin Shen Teh

    2015-05-01

    Full Text Available In this paper we study the performance and effect of diverse keystroke feature combinations on keystroke dynamics authentication system by using fusion approach. First of all, four types of keystroke features are acquired from our collected dataset, later then transformed into similarity scores by using Gaussian Probability Density Function (GPD and Direction Similarity Measure (DSM. Next, three fusion approaches are introduced to merge the scores pairing with different combinations of fusion rules. Result shows that the finest performance is obtained by the combination of both dwell time and flight time collectively. Finally, this experiment also investigates the effect of using larger dataset on recognition performance, which turns out to be rather consistent.

  16. Synthetic Aperture Radar Target Recognition with Feature Fusion Based on a Stacked Autoencoder.

    Science.gov (United States)

    Kang, Miao; Ji, Kefeng; Leng, Xiangguang; Xing, Xiangwei; Zou, Huanxin

    2017-01-20

    Feature extraction is a crucial step for any automatic target recognition process, especially in the interpretation of synthetic aperture radar (SAR) imagery. In order to obtain distinctive features, this paper proposes a feature fusion algorithm for SAR target recognition based on a stacked autoencoder (SAE). The detailed procedure presented in this paper can be summarized as follows: firstly, 23 baseline features and Three-Patch Local Binary Pattern (TPLBP) features are extracted. These features can describe the global and local aspects of the image with less redundancy and more complementarity, providing richer information for feature fusion. Secondly, an effective feature fusion network is designed. Baseline and TPLBP features are cascaded and fed into a SAE. Then, with an unsupervised learning algorithm, the SAE is pre-trained by greedy layer-wise training method. Capable of feature expression, SAE makes the fused features more distinguishable. Finally, the model is fine-tuned by a softmax classifier and applied to the classification of targets. 10-class SAR targets based on Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset got a classification accuracy up to 95.43%, which verifies the effectiveness of the presented algorithm.

  17. Synthetic Aperture Radar Target Recognition with Feature Fusion Based on a Stacked Autoencoder

    Directory of Open Access Journals (Sweden)

    Miao Kang

    2017-01-01

    Full Text Available Feature extraction is a crucial step for any automatic target recognition process, especially in the interpretation of synthetic aperture radar (SAR imagery. In order to obtain distinctive features, this paper proposes a feature fusion algorithm for SAR target recognition based on a stacked autoencoder (SAE. The detailed procedure presented in this paper can be summarized as follows: firstly, 23 baseline features and Three-Patch Local Binary Pattern (TPLBP features are extracted. These features can describe the global and local aspects of the image with less redundancy and more complementarity, providing richer information for feature fusion. Secondly, an effective feature fusion network is designed. Baseline and TPLBP features are cascaded and fed into a SAE. Then, with an unsupervised learning algorithm, the SAE is pre-trained by greedy layer-wise training method. Capable of feature expression, SAE makes the fused features more distinguishable. Finally, the model is fine-tuned by a softmax classifier and applied to the classification of targets. 10-class SAR targets based on Moving and Stationary Target Acquisition and Recognition (MSTAR dataset got a classification accuracy up to 95.43%, which verifies the effectiveness of the presented algorithm.

  18. Feature and Score Fusion Based Multiple Classifier Selection for Iris Recognition

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    Md. Rabiul Islam

    2014-01-01

    Full Text Available The aim of this work is to propose a new feature and score fusion based iris recognition approach where voting method on Multiple Classifier Selection technique has been applied. Four Discrete Hidden Markov Model classifiers output, that is, left iris based unimodal system, right iris based unimodal system, left-right iris feature fusion based multimodal system, and left-right iris likelihood ratio score fusion based multimodal system, is combined using voting method to achieve the final recognition result. CASIA-IrisV4 database has been used to measure the performance of the proposed system with various dimensions. Experimental results show the versatility of the proposed system of four different classifiers with various dimensions. Finally, recognition accuracy of the proposed system has been compared with existing N hamming distance score fusion approach proposed by Ma et al., log-likelihood ratio score fusion approach proposed by Schmid et al., and single level feature fusion approach proposed by Hollingsworth et al.

  19. Content Based Image Recognition by Information Fusion with Multiview Features

    Directory of Open Access Journals (Sweden)

    Rik Das

    2015-09-01

    Full Text Available Substantial research interest has been observed in the field of object recognition as a vital component for modern intelligent systems. Content based image classification and retrieval have been considered as two popular techniques for identifying the object of interest. Feature extraction has played the pivotal role towards successful implementation of the aforesaid techniques. The paper has presented two novel techniques of feature extraction from diverse image categories both in spatial domain and in frequency domain. The multi view features from the image categories were evaluated for classification and retrieval performances by means of a fusion based recognition architecture. The experimentation was carried out with four different popular public datasets. The proposed fusion framework has exhibited an average increase of 24.71% and 20.78% in precision rates for classification and retrieval respectively, when compared to state-of-the art techniques. The experimental findings were validated with a paired t test for statistical significance.

  20. Multi-feature fusion for thermal face recognition

    Science.gov (United States)

    Bi, Yin; Lv, Mingsong; Wei, Yangjie; Guan, Nan; Yi, Wang

    2016-07-01

    Human face recognition has been researched for the last three decades. Face recognition with thermal images now attracts significant attention since they can be used in low/none illuminated environment. However, thermal face recognition performance is still insufficient for practical applications. One main reason is that most existing work leverage only single feature to characterize a face in a thermal image. To solve the problem, we propose multi-feature fusion, a technique that combines multiple features in thermal face characterization and recognition. In this work, we designed a systematical way to combine four features, including Local binary pattern, Gabor jet descriptor, Weber local descriptor and Down-sampling feature. Experimental results show that our approach outperforms methods that leverage only a single feature and is robust to noise, occlusion, expression, low resolution and different l1 -minimization methods.

  1. Iris Recognition System Based on Feature Level Fusion

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    Dr. S. R. Ganorkar

    2013-11-01

    Full Text Available Multibiometric systems utilize the evidence presented by multiple biometric sources (e.g., face and fingerprint, multiple fingers of a single user, multiple matchers, etc. in order to determine or verify the identity of an individual. Information from multiple sources can be consolidated in several distinct levels. But fusion of two different biometric traits are difficult due to (i the feature sets of multiple modalities may be incompatible (e.g., minutiae set of fingerprints and eigen-coefficients of face; (ii the relationship between the feature spaces of different biometric systems may not be known; (iii concatenating two feature vectors may result in a feature vector with very large dimensionality leading to the `curse of dimensionality problem, huge storage space and different processing algorithm. Also if we are use multiple images of single biometric trait, then it doesn’t show much variations. So in this paper, we present a efficient technique of feature-based fusion in a multimodal system where left eye and right eye are used as input. Iris recognition basically contains iris location, feature extraction, and identification. This algorithm uses canny edge detection to identify inner and outer boundary of iris. Then this image is feed to Gabor wavelet transform to extract the feature and finally matching is done by using indexing algorithm. The results from the analysis of works indicate that the proposed technique can lead to substantial improvement in performance.

  2. Feature-based fusion of infrared and visible dynamic images using target detection

    Institute of Scientific and Technical Information of China (English)

    Congyi Liu; Zhongliang Jing; Gang Xiao; Bo Yang

    2007-01-01

    We employ the target detection to improve the performance of the feature-based fusion of infrared and visible dynamic images, which forms a novel fusion scheme. First, the target detection is used to segment the source image sequences into target and background regions. Then, the dual-tree complex wavelet transform (DT-CWT) is proposed to decompose all the source image sequences. Different fusion rules are applied respectively in target and background regions to preserve the target information as much as possible. Real world infrared and visible image sequences are used to validate the performance of the proposed novel scheme. Compared with the previous fusion approaches of image sequences, the improvements of shift invariance, temporal stability and consistency, and computation cost are all ensured.

  3. SAR Data Fusion Imaging Method Oriented to Target Feature Extraction

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    Yang Wei

    2015-02-01

    Full Text Available To deal with the difficulty for target outlines extracting precisely due to neglect of target scattering characteristic variation during the processing of high-resolution space-borne SAR data, a novel fusion imaging method is proposed oriented to target feature extraction. Firstly, several important aspects that affect target feature extraction and SAR image quality are analyzed, including curved orbit, stop-and-go approximation, atmospheric delay, and high-order residual phase error. Furthermore, the corresponding compensation methods are addressed as well. Based on the analysis, the mathematical model of SAR echo combined with target space-time spectrum is established for explaining the space-time-frequency change rule of target scattering characteristic. Moreover, a fusion imaging strategy and method under high-resolution and ultra-large observation angle range conditions are put forward to improve SAR quality by fusion processing in range-doppler and image domain. Finally, simulations based on typical military targets are used to verify the effectiveness of the fusion imaging method.

  4. Hyperspectral Image Classification Based on the Weighted Probabilistic Fusion of Multiple Spectral-spatial Features

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    ZHANG Chunsen

    2015-08-01

    Full Text Available A hyperspectral images classification method based on the weighted probabilistic fusion of multiple spectral-spatial features was proposed in this paper. First, the minimum noise fraction (MNF approach was employed to reduce the dimension of hyperspectral image and extract the spectral feature from the image, then combined the spectral feature with the texture feature extracted based on gray level co-occurrence matrix (GLCM, the multi-scale morphological feature extracted based on OFC operator and the end member feature extracted based on sequential maximum angle convex cone (SMACC method to form three spectral-spatial features. Afterwards, support vector machine (SVM classifier was used for the classification of each spectral-spatial feature separately. Finally, we established the weighted probabilistic fusion model and applied the model to fuse the SVM outputs for the final classification result. In order to verify the proposed method, the ROSIS and AVIRIS image were used in our experiment and the overall accuracy reached 97.65% and 96.62% separately. The results indicate that the proposed method can not only overcome the limitations of traditional single-feature based hyperspectral image classification, but also be superior to conventional VS-SVM method and probabilistic fusion method. The classification accuracy of hyperspectral images was improved effectively.

  5. Fusion Framework for Emotional Electrocardiogram and Galvanic Skin Response Recognition: Applying Wavelet Transform

    Directory of Open Access Journals (Sweden)

    Atefeh Goshvarpour

    2016-09-01

    Full Text Available Introduction To extract and combine information from different modalities, fusion techniques are commonly applied to promote system performance. In this study, we aimed to examine the effectiveness of fusion techniques in emotion recognition. Materials and Methods Electrocardiogram (ECG and galvanic skin responses (GSR of 11 healthy female students (mean age: 22.73±1.68 years were collected while the subjects were listening to emotional music clips. For multi-resolution analysis of signals, wavelet transform (Coiflets 5 at level 14 was used. Moreover, a novel feature-level fusion method was employed, in which low-frequency sub-band coefficients of GSR signals and high-frequency sub-band coefficients of ECG signals were fused to reconstruct a new feature. To reduce the dimensionality of the feature vector, the absolute value of some statistical indices was calculated and considered as input of PNN classifier. To describe emotions, two-dimensional models (four quadrants of valence and arousal dimensions, valence-based emotional states, and emotional arousal were applied. Results The highest recognition rates were obtained from sigma=0.01. Mean classification rate of 100% was achieved through applying the proposed fusion methodology. However, the accuracy rates of 97.90% and 97.20% were attained for GSR and ECG signals, respectively. Conclusion Compared to the previously published articles in the field of emotion recognition using musical stimuli, promising results were obtained through application of the proposed methodology.

  6. Person re-identification across aerial and ground-based cameras by deep feature fusion

    Science.gov (United States)

    Schumann, Arne; Metzler, Jürgen

    2017-05-01

    Person re-identification is the task of correctly matching visual appearances of the same person in image or video data while distinguishing appearances of different persons. The traditional setup for re-identification is a network of fixed cameras. However, in recent years mobile aerial cameras mounted on unmanned aerial vehicles (UAV) have become increasingly useful for security and surveillance tasks. Aerial data has many characteristics different from typical camera network data. Thus, re-identification approaches designed for a camera network scenario can be expected to suffer a drop in accuracy when applied to aerial data. In this work, we investigate the suitability of features, which were shown to give robust results for re- identification in camera networks, for the task of re-identifying persons between a camera network and a mobile aerial camera. Specifically, we apply hand-crafted region covariance features and features extracted by convolu- tional neural networks which were learned on separate data. We evaluate their suitability for this new and as yet unexplored scenario. We investigate common fusion methods to combine the hand-crafted and learned features and propose our own deep fusion approach which is already applied during training of the deep network. We evaluate features and fusion methods on our own dataset. The dataset consists of fourteen people moving through a scene recorded by four fixed ground-based cameras and one mobile camera mounted on a small UAV. We discuss strengths and weaknesses of the features in the new scenario and show that our fusion approach successfully leverages the strengths of each feature and outperforms all single features significantly.

  7. Feature Fusion Based SVM Classifier for Protein Subcellular Localization Prediction.

    Science.gov (United States)

    Rahman, Julia; Mondal, Md Nazrul Islam; Islam, Md Khaled Ben; Hasan, Md Al Mehedi

    2016-12-18

    For the importance of protein subcellular localization in different branches of life science and drug discovery, researchers have focused their attentions on protein subcellular localization prediction. Effective representation of features from protein sequences plays a most vital role in protein subcellular localization prediction specially in case of machine learning techniques. Single feature representation-like pseudo amino acid composition (PseAAC), physiochemical property models (PPM), and amino acid index distribution (AAID) contains insufficient information from protein sequences. To deal with such problems, we have proposed two feature fusion representations, AAIDPAAC and PPMPAAC, to work with Support Vector Machine classifiers, which fused PseAAC with PPM and AAID accordingly. We have evaluated the performance for both single and fused feature representation of a Gram-negative bacterial dataset. We have got at least 3% more actual accuracy by AAIDPAAC and 2% more locative accuracy by PPMPAAC than single feature representation.

  8. Real-Time Visual Tracking through Fusion Features.

    Science.gov (United States)

    Ruan, Yang; Wei, Zhenzhong

    2016-06-23

    Due to their high-speed, correlation filters for object tracking have begun to receive increasing attention. Traditional object trackers based on correlation filters typically use a single type of feature. In this paper, we attempt to integrate multiple feature types to improve the performance, and we propose a new DD-HOG fusion feature that consists of discriminative descriptors (DDs) and histograms of oriented gradients (HOG). However, fusion features as multi-vector descriptors cannot be directly used in prior correlation filters. To overcome this difficulty, we propose a multi-vector correlation filter (MVCF) that can directly convolve with a multi-vector descriptor to obtain a single-channel response that indicates the location of an object. Experiments on the CVPR2013 tracking benchmark with the evaluation of state-of-the-art trackers show the effectiveness and speed of the proposed method. Moreover, we show that our MVCF tracker, which uses the DD-HOG descriptor, outperforms the structure-preserving object tracker (SPOT) in multi-object tracking because of its high-speed and ability to address heavy occlusion.

  9. Fast multi-scale feature fusion for ECG heartbeat classification

    Science.gov (United States)

    Ai, Danni; Yang, Jian; Wang, Zeyu; Fan, Jingfan; Ai, Changbin; Wang, Yongtian

    2015-12-01

    Electrocardiogram (ECG) is conducted to monitor the electrical activity of the heart by presenting small amplitude and duration signals; as a result, hidden information present in ECG data is difficult to determine. However, this concealed information can be used to detect abnormalities. In our study, a fast feature-fusion method of ECG heartbeat classification based on multi-linear subspace learning is proposed. The method consists of four stages. First, baseline and high frequencies are removed to segment heartbeat. Second, as an extension of wavelets, wavelet-packet decomposition is conducted to extract features. With wavelet-packet decomposition, good time and frequency resolutions can be provided simultaneously. Third, decomposed confidences are arranged as a two-way tensor, in which feature fusion is directly implemented with generalized N dimensional ICA (GND-ICA). In this method, co-relationship among different data information is considered, and disadvantages of dimensionality are prevented; this method can also be used to reduce computing compared with linear subspace-learning methods (PCA). Finally, support vector machine (SVM) is considered as a classifier in heartbeat classification. In this study, ECG records are obtained from the MIT-BIT arrhythmia database. Four main heartbeat classes are used to examine the proposed algorithm. Based on the results of five measurements, sensitivity, positive predictivity, accuracy, average accuracy, and t-test, our conclusion is that a GND-ICA-based strategy can be used to provide enhanced ECG heartbeat classification. Furthermore, large redundant features are eliminated, and classification time is reduced.

  10. Helicobacter Pylori infection detection from gastric X-ray images based on feature fusion and decision fusion.

    Science.gov (United States)

    Ishihara, Kenta; Ogawa, Takahiro; Haseyama, Miki

    2017-05-01

    In this paper, a fully automatic method for detection of Helicobacter pylori (H. pylori) infection is presented with the aim of constructing a computer-aided diagnosis (CAD) system. In order to realize a CAD system with good performance for detection of H. pylori infection, we focus on the following characteristic of stomach X-ray examination. The accuracy of X-ray examination differs depending on the symptom of H. pylori infection that is focused on and the position from which X-ray images are taken. Therefore, doctors have to comprehensively assess the symptoms and positions. In order to introduce the idea of doctors' assessment into the CAD system, we newly propose a method for detection of H. pylori infection based on the combined use of feature fusion and decision fusion. As a feature fusion scheme, we adopt Multiple Kernel Learning (MKL). Since MKL can combine several features with determination of their weights, it can represent the differences in symptoms. By constructing an MKL classifier for each position, we can obtain several detection results. Furthermore, we introduce confidence-based decision fusion, which can consider the relationship between the classifier's performance and the detection results. Consequently, accurate detection of H. pylori infection becomes possible by the proposed method. Experimental results obtained by applying the proposed method to real X-ray images show that our method has good performance, close to the results of detection by specialists, and indicate that the realization of a CAD system for determining the risk of H. pylori infection is possible. Copyright © 2017 Elsevier Ltd. All rights reserved.

  11. Infrared and visible image fusion scheme based on NSCT and low-level visual features

    Science.gov (United States)

    Li, Huafeng; Qiu, Hongmei; Yu, Zhengtao; Zhang, Yafei

    2016-05-01

    Multi-scale transform (MST) is an efficient tool for image fusion. Recently, many fusion methods have been developed based on different MSTs, and they have shown potential application in many fields. In this paper, we propose an effective infrared and visible image fusion scheme in nonsubsampled contourlet transform (NSCT) domain, in which the NSCT is firstly employed to decompose each of the source images into a series of high frequency subbands and one low frequency subband. To improve the fusion performance we designed two new activity measures for fusion of the lowpass subbands and the highpass subbands. These measures are developed based on the fact that the human visual system (HVS) percept the image quality mainly according to its some low-level features. Then, the selection principles of different subbands are presented based on the corresponding activity measures. Finally, the merged subbands are constructed according to the selection principles, and the final fused image is produced by applying the inverse NSCT on these merged subbands. Experimental results demonstrate the effectiveness and superiority of the proposed method over the state-of-the-art fusion methods in terms of both visual effect and objective evaluation results.

  12. COLOR IMAGE RETRIEVAL BASED ON FEATURE FUSION THROUGH MULTIPLE LINEAR REGRESSION ANALYSIS

    Directory of Open Access Journals (Sweden)

    K. Seetharaman

    2015-08-01

    Full Text Available This paper proposes a novel technique based on feature fusion using multiple linear regression analysis, and the least-square estimation method is employed to estimate the parameters. The given input query image is segmented into various regions according to the structure of the image. The color and texture features are extracted on each region of the query image, and the features are fused together using the multiple linear regression model. The estimated parameters of the model, which is modeled based on the features, are formed as a vector called a feature vector. The Canberra distance measure is adopted to compare the feature vectors of the query and target images. The F-measure is applied to evaluate the performance of the proposed technique. The obtained results expose that the proposed technique is comparable to the other existing techniques.

  13. Remote sensing image classification based on block feature point density analysis and multiple-feature fusion

    Science.gov (United States)

    Li, Shijin; Jiang, Yaping; Zhang, Yang; Feng, Jun

    2015-10-01

    With the development of remote sensing (RS) and the related technologies, the resolution of RS images is enhancing. Compared with moderate or low resolution images, high-resolution ones can provide more detailed ground information. However, a variety of terrain has complex spatial distribution. The different objectives of high-resolution images have a variety of features. The effectiveness of these features is not the same, but some of them are complementary. Considering the above information and characteristics, a new method is proposed to classify RS images based on hierarchical fusion of multi-features. Firstly, RS images are pre-classified into two categories in terms of whether feature points are uniformly or non-uniformly distributed. Then, the color histogram and Gabor texture feature are extracted from the uniformly-distributed categories, and the linear spatial pyramid matching using sparse coding (ScSPM) feature is obtained from the non-uniformly-distributed categories. Finally, the classification is performed by two support vector machine classifiers. The experimental results on a large RS image database with 2100 images show that the overall classification accuracy is boosted by 10.1% in comparison with the highest accuracy of single feature classification method. Compared with other multiple-feature fusion methods, the proposed method has achieved the highest classification accuracy on this dataset which has reached 90.1%, and the time complexity of the algorithm is also greatly reduced.

  14. Feature-based MRI data fusion for cardiac arrhythmia studies.

    Science.gov (United States)

    Magtibay, Karl; Beheshti, Mohammadali; Foomany, Farbod Hosseyndoust; Massé, Stéphane; Lai, Patrick F H; Zamiri, Nima; Asta, John; Nanthakumar, Kumaraswamy; Jaffray, David; Krishnan, Sridhar; Umapathy, Karthikeyan

    2016-05-01

    Current practices in studying cardiac arrhythmias primarily use electrical or optical surface recordings of a heart, spatially limited transmural recordings, and mathematical models. However, given that such arrhythmias occur on a 3D myocardial tissue, information obtained from such practices lack in dimension, completeness, and are sometimes prone to oversimplification. The combination of complementary Magnetic-Resonance Imaging (MRI)-based techniques such as Current Density Imaging (CDI) and Diffusion Tensor Imaging (DTI) could provide more depth to current practices in assessing the cardiac arrhythmia dynamics in entire cross sections of myocardium. In this work, we present an approach utilizing feature-based data fusion methods to demonstrate that complimentary information obtained from electrical current distribution and structural properties within a heart could be quantified and enhanced. Twelve (12) pairs of CDI and DTI image data sets were gathered from porcine hearts perfused through a Langendorff setup. Images were fused together using feature-based data fusion techniques such as Joint Independent Component Analysis (jICA), Canonical Correlation Analysis (CCA), and their combination (CCA+jICA). The results suggest that the complimentary information of cardiac states from CDI and DTI are enhanced and are better classified with the use of data fusion methods. For each data set, an increase in mean correlations of fused images were observed with 38% increase from CCA+jICA compared to the original images while mean mutual information of the fused images from jICA and CCA+jICA increased by approximately three-fold. We conclude that MRI-based techniques present potential viable tools in furthering studies for cardiac arrhythmias especially Ventricular Fibrillation. Copyright © 2016 Elsevier Ltd. All rights reserved.

  15. Robust Tomato Recognition for Robotic Harvesting Using Feature Images Fusion

    Directory of Open Access Journals (Sweden)

    Yuanshen Zhao

    2016-01-01

    Full Text Available Automatic recognition of mature fruits in a complex agricultural environment is still a challenge for an autonomous harvesting robot due to various disturbances existing in the background of the image. The bottleneck to robust fruit recognition is reducing influence from two main disturbances: illumination and overlapping. In order to recognize the tomato in the tree canopy using a low-cost camera, a robust tomato recognition algorithm based on multiple feature images and image fusion was studied in this paper. Firstly, two novel feature images, the  a*-component image and the I-component image, were extracted from the L*a*b* color space and luminance, in-phase, quadrature-phase (YIQ color space, respectively. Secondly, wavelet transformation was adopted to fuse the two feature images at the pixel level, which combined the feature information of the two source images. Thirdly, in order to segment the target tomato from the background, an adaptive threshold algorithm was used to get the optimal threshold. The final segmentation result was processed by morphology operation to reduce a small amount of noise. In the detection tests, 93% target tomatoes were recognized out of 200 overall samples. It indicates that the proposed tomato recognition method is available for robotic tomato harvesting in the uncontrolled environment with low cost.

  16. Robust Ground Target Detection by SAR and IR Sensor Fusion Using Adaboost-Based Feature Selection.

    Science.gov (United States)

    Kim, Sungho; Song, Woo-Jin; Kim, So-Hyun

    2016-07-19

    Long-range ground targets are difficult to detect in a noisy cluttered environment using either synthetic aperture radar (SAR) images or infrared (IR) images. SAR-based detectors can provide a high detection rate with a high false alarm rate to background scatter noise. IR-based approaches can detect hot targets but are affected strongly by the weather conditions. This paper proposes a novel target detection method by decision-level SAR and IR fusion using an Adaboost-based machine learning scheme to achieve a high detection rate and low false alarm rate. The proposed method consists of individual detection, registration, and fusion architecture. This paper presents a single framework of a SAR and IR target detection method using modified Boolean map visual theory (modBMVT) and feature-selection based fusion. Previous methods applied different algorithms to detect SAR and IR targets because of the different physical image characteristics. One method that is optimized for IR target detection produces unsuccessful results in SAR target detection. This study examined the image characteristics and proposed a unified SAR and IR target detection method by inserting a median local average filter (MLAF, pre-filter) and an asymmetric morphological closing filter (AMCF, post-filter) into the BMVT. The original BMVT was optimized to detect small infrared targets. The proposed modBMVT can remove the thermal and scatter noise by the MLAF and detect extended targets by attaching the AMCF after the BMVT. Heterogeneous SAR and IR images were registered automatically using the proposed RANdom SAmple Region Consensus (RANSARC)-based homography optimization after a brute-force correspondence search using the detected target centers and regions. The final targets were detected by feature-selection based sensor fusion using Adaboost. The proposed method showed good SAR and IR target detection performance through feature selection-based decision fusion on a synthetic database generated

  17. Robust Ground Target Detection by SAR and IR Sensor Fusion Using Adaboost-Based Feature Selection

    Directory of Open Access Journals (Sweden)

    Sungho Kim

    2016-07-01

    Full Text Available Long-range ground targets are difficult to detect in a noisy cluttered environment using either synthetic aperture radar (SAR images or infrared (IR images. SAR-based detectors can provide a high detection rate with a high false alarm rate to background scatter noise. IR-based approaches can detect hot targets but are affected strongly by the weather conditions. This paper proposes a novel target detection method by decision-level SAR and IR fusion using an Adaboost-based machine learning scheme to achieve a high detection rate and low false alarm rate. The proposed method consists of individual detection, registration, and fusion architecture. This paper presents a single framework of a SAR and IR target detection method using modified Boolean map visual theory (modBMVT and feature-selection based fusion. Previous methods applied different algorithms to detect SAR and IR targets because of the different physical image characteristics. One method that is optimized for IR target detection produces unsuccessful results in SAR target detection. This study examined the image characteristics and proposed a unified SAR and IR target detection method by inserting a median local average filter (MLAF, pre-filter and an asymmetric morphological closing filter (AMCF, post-filter into the BMVT. The original BMVT was optimized to detect small infrared targets. The proposed modBMVT can remove the thermal and scatter noise by the MLAF and detect extended targets by attaching the AMCF after the BMVT. Heterogeneous SAR and IR images were registered automatically using the proposed RANdom SAmple Region Consensus (RANSARC-based homography optimization after a brute-force correspondence search using the detected target centers and regions. The final targets were detected by feature-selection based sensor fusion using Adaboost. The proposed method showed good SAR and IR target detection performance through feature selection-based decision fusion on a synthetic

  18. Features fusion based approach for handwritten Gujarati character recognition

    Directory of Open Access Journals (Sweden)

    Ankit Sharma

    2017-02-01

    Full Text Available Handwritten character recognition is a challenging area of research. Lots of research activities in the area of character recognition are already done for Indian languages such as Hindi, Bangla, Kannada, Tamil and Telugu. Literature review on handwritten character recognition indicates that in comparison with other Indian scripts research activities on Gujarati handwritten character recognition are very less.  This paper aims to bring Gujarati character recognition in attention. Recognition of isolated Gujarati handwritten characters is proposed using three different kinds of features and their fusion. Chain code based, zone based and projection profiles based features are utilized as individual features. One of the significant contribution of proposed work is towards the generation of large and representative dataset of 88,000 handwritten Gujarati characters. Experiments are carried out on this developed dataset. Artificial Neural Network (ANN, Support Vector Machine (SVM and Naive Bayes (NB classifier based methods are implemented for handwritten Gujarati character recognition. Experimental results show substantial enhancement over state-of-the-art and authenticate our proposals.

  19. Bimodal Log-linear Regression for Fusion of Audio and Visual Features

    NARCIS (Netherlands)

    Rudovic, Ognjen; Petridis, Stavros; Pantic, Maja

    2013-01-01

    One of the most commonly used audiovisual fusion approaches is feature-level fusion where the audio and visual features are concatenated. Although this approach has been successfully used in several applications, it does not take into account interactions between the features, which can be a problem

  20. Feature level fusion of polarimetric infrared and GPR data for landmine detection

    NARCIS (Netherlands)

    Cremer, F.; Jong, W. de; Schutte, K.; Yarovoy, A.G.; Kovalenko, V.; Bloemenkamp, R.F.

    2003-01-01

    Feature-level sensor fusion is the process where specific information (i.e. features) from objects detected by different sensors are combined and classified. This paper focuses on the feature-level fusion procedure for a sensor combination consisting of a polarimetric infrared (IR) imaging sensor an

  1. Machinery running state identification based on discriminant semi-supervised local tangent space alignment for feature fusion and extraction

    Science.gov (United States)

    Su, Zuqiang; Xiao, Hong; Zhang, Yi; Tang, Baoping; Jiang, Yonghua

    2017-04-01

    Extraction of sensitive features is a challenging but key task in data-driven machinery running state identification. Aimed at solving this problem, a method for machinery running state identification that applies discriminant semi-supervised local tangent space alignment (DSS-LTSA) for feature fusion and extraction is proposed. Firstly, in order to extract more distinct features, the vibration signals are decomposed by wavelet packet decomposition WPD, and a mixed-domain feature set consisted of statistical features, autoregressive (AR) model coefficients, instantaneous amplitude Shannon entropy and WPD energy spectrum is extracted to comprehensively characterize the properties of machinery running state(s). Then, the mixed-dimension feature set is inputted into DSS-LTSA for feature fusion and extraction to eliminate redundant information and interference noise. The proposed DSS-LTSA can extract intrinsic structure information of both labeled and unlabeled state samples, and as a result the over-fitting problem of supervised manifold learning and blindness problem of unsupervised manifold learning are overcome. Simultaneously, class discrimination information is integrated within the dimension reduction process in a semi-supervised manner to improve sensitivity of the extracted fusion features. Lastly, the extracted fusion features are inputted into a pattern recognition algorithm to achieve the running state identification. The effectiveness of the proposed method is verified by a running state identification case in a gearbox, and the results confirm the improved accuracy of the running state identification.

  2. Medical Image Fusion Based on Feature Extraction and Sparse Representation.

    Science.gov (United States)

    Fei, Yin; Wei, Gao; Zongxi, Song

    2017-01-01

    As a novel multiscale geometric analysis tool, sparse representation has shown many advantages over the conventional image representation methods. However, the standard sparse representation does not take intrinsic structure and its time complexity into consideration. In this paper, a new fusion mechanism for multimodal medical images based on sparse representation and decision map is proposed to deal with these problems simultaneously. Three decision maps are designed including structure information map (SM) and energy information map (EM) as well as structure and energy map (SEM) to make the results reserve more energy and edge information. SM contains the local structure feature captured by the Laplacian of a Gaussian (LOG) and EM contains the energy and energy distribution feature detected by the mean square deviation. The decision map is added to the normal sparse representation based method to improve the speed of the algorithm. Proposed approach also improves the quality of the fused results by enhancing the contrast and reserving more structure and energy information from the source images. The experiment results of 36 groups of CT/MR, MR-T1/MR-T2, and CT/PET images demonstrate that the method based on SR and SEM outperforms five state-of-the-art methods.

  3. Impulse feature extraction method for machinery fault detection using fusion sparse coding and online dictionary learning

    Directory of Open Access Journals (Sweden)

    Deng Sen

    2015-04-01

    Full Text Available Impulse components in vibration signals are important fault features of complex machines. Sparse coding (SC algorithm has been introduced as an impulse feature extraction method, but it could not guarantee a satisfactory performance in processing vibration signals with heavy background noises. In this paper, a method based on fusion sparse coding (FSC and online dictionary learning is proposed to extract impulses efficiently. Firstly, fusion scheme of different sparse coding algorithms is presented to ensure higher reconstruction accuracy. Then, an improved online dictionary learning method using FSC scheme is established to obtain redundant dictionary and it can capture specific features of training samples and reconstruct the sparse approximation of vibration signals. Simulation shows that this method has a good performance in solving sparse coefficients and training redundant dictionary compared with other methods. Lastly, the proposed method is further applied to processing aircraft engine rotor vibration signals. Compared with other feature extraction approaches, our method can extract impulse features accurately and efficiently from heavy noisy vibration signal, which has significant supports for machinery fault detection and diagnosis.

  4. Applying Feature Extraction for Classification Problems

    Directory of Open Access Journals (Sweden)

    Foon Chi

    2009-03-01

    Full Text Available With the wealth of image data that is now becoming increasingly accessible through the advent of the world wide web and the proliferation of cheap, high quality digital cameras it isbecoming ever more desirable to be able to automatically classify images into appropriate categories such that intelligent agents and other such intelligent software might make better informed decisions regarding them without a need for excessive human intervention.However, as with most Artificial Intelligence (A.I. methods it is seen as necessary to take small steps towards your goal. With this in mind a method is proposed here to represent localised features using disjoint sub-images taken from several datasets of retinal images for their eventual use in an incremental learning system. A tile-based localised adaptive threshold selection method was taken for vessel segmentation based on separate colour components. Arteriole-venous differentiation was made possible by using the composite of these components and high quality fundal images. Performance was evaluated on the DRIVE and STARE datasets achieving average specificity of 0.9379 and sensitivity of 0.5924.

  5. A feature fusion based forecasting model for financial time series.

    Science.gov (United States)

    Guo, Zhiqiang; Wang, Huaiqing; Liu, Quan; Yang, Jie

    2014-01-01

    Predicting the stock market has become an increasingly interesting research area for both researchers and investors, and many prediction models have been proposed. In these models, feature selection techniques are used to pre-process the raw data and remove noise. In this paper, a prediction model is constructed to forecast stock market behavior with the aid of independent component analysis, canonical correlation analysis, and a support vector machine. First, two types of features are extracted from the historical closing prices and 39 technical variables obtained by independent component analysis. Second, a canonical correlation analysis method is utilized to combine the two types of features and extract intrinsic features to improve the performance of the prediction model. Finally, a support vector machine is applied to forecast the next day's closing price. The proposed model is applied to the Shanghai stock market index and the Dow Jones index, and experimental results show that the proposed model performs better in the area of prediction than other two similar models.

  6. A feature fusion based forecasting model for financial time series.

    Directory of Open Access Journals (Sweden)

    Zhiqiang Guo

    Full Text Available Predicting the stock market has become an increasingly interesting research area for both researchers and investors, and many prediction models have been proposed. In these models, feature selection techniques are used to pre-process the raw data and remove noise. In this paper, a prediction model is constructed to forecast stock market behavior with the aid of independent component analysis, canonical correlation analysis, and a support vector machine. First, two types of features are extracted from the historical closing prices and 39 technical variables obtained by independent component analysis. Second, a canonical correlation analysis method is utilized to combine the two types of features and extract intrinsic features to improve the performance of the prediction model. Finally, a support vector machine is applied to forecast the next day's closing price. The proposed model is applied to the Shanghai stock market index and the Dow Jones index, and experimental results show that the proposed model performs better in the area of prediction than other two similar models.

  7. Automatic feature extraction in large fusion databases by using deep learning approach

    Energy Technology Data Exchange (ETDEWEB)

    Farias, Gonzalo, E-mail: gonzalo.farias@ucv.cl [Pontificia Universidad Católica de Valparaíso, Valparaíso (Chile); Dormido-Canto, Sebastián [Departamento de Informática y Automática, UNED, Madrid (Spain); Vega, Jesús; Rattá, Giuseppe [Asociación EURATOM/CIEMAT Para Fusión, CIEMAT, Madrid (Spain); Vargas, Héctor; Hermosilla, Gabriel; Alfaro, Luis; Valencia, Agustín [Pontificia Universidad Católica de Valparaíso, Valparaíso (Chile)

    2016-11-15

    Highlights: • Feature extraction is a very critical stage in any machine learning algorithm. • The problem dimensionality can be reduced enormously when selecting suitable attributes. • Despite the importance of feature extraction, the process is commonly done manually by trial and error. • Fortunately, recent advances in deep learning approach have proposed an encouraging way to find a good feature representation automatically. • In this article, deep learning is applied to the TJ-II fusion database to get more robust and accurate classifiers in comparison to previous work. - Abstract: Feature extraction is one of the most important machine learning issues. Finding suitable attributes of datasets can enormously reduce the dimensionality of the input space, and from a computational point of view can help all of the following steps of pattern recognition problems, such as classification or information retrieval. However, the feature extraction step is usually performed manually. Moreover, depending on the type of data, we can face a wide range of methods to extract features. In this sense, the process to select appropriate techniques normally takes a long time. This work describes the use of recent advances in deep learning approach in order to find a good feature representation automatically. The implementation of a special neural network called sparse autoencoder and its application to two classification problems of the TJ-II fusion database is shown in detail. Results have shown that it is possible to get robust classifiers with a high successful rate, in spite of the fact that the feature space is reduced to less than 0.02% from the original one.

  8. Application of next generation sequencing to human gene fusion detection: computational tools, features and perspectives.

    Science.gov (United States)

    Wang, Qingguo; Xia, Junfeng; Jia, Peilin; Pao, William; Zhao, Zhongming

    2013-07-01

    Gene fusions are important genomic events in human cancer because their fusion gene products can drive the development of cancer and thus are potential prognostic tools or therapeutic targets in anti-cancer treatment. Major advancements have been made in computational approaches for fusion gene discovery over the past 3 years due to improvements and widespread applications of high-throughput next generation sequencing (NGS) technologies. To identify fusions from NGS data, existing methods typically leverage the strengths of both sequencing technologies and computational strategies. In this article, we review the NGS and computational features of existing methods for fusion gene detection and suggest directions for future development.

  9. A Novel DBN Feature Fusion Model for Cross-Corpus Speech Emotion Recognition

    Directory of Open Access Journals (Sweden)

    Zou Cairong

    2016-01-01

    Full Text Available The feature fusion from separate source is the current technical difficulties of cross-corpus speech emotion recognition. The purpose of this paper is to, based on Deep Belief Nets (DBN in Deep Learning, use the emotional information hiding in speech spectrum diagram (spectrogram as image features and then implement feature fusion with the traditional emotion features. First, based on the spectrogram analysis by STB/Itti model, the new spectrogram features are extracted from the color, the brightness, and the orientation, respectively; then using two alternative DBN models they fuse the traditional and the spectrogram features, which increase the scale of the feature subset and the characterization ability of emotion. Through the experiment on ABC database and Chinese corpora, the new feature subset compared with traditional speech emotion features, the recognition result on cross-corpus, distinctly advances by 8.8%. The method proposed provides a new idea for feature fusion of emotion recognition.

  10. FEATURE FUSION TECHNIQUE FOR COLOUR TEXTURE CLASSIFICATION SYSTEM BASED ON GRAY LEVEL CO-OCCURRENCE MATRIX

    Directory of Open Access Journals (Sweden)

    K. L. Shunmuganathan

    2012-01-01

    Full Text Available In this study, an efficient feature fusion based technique for the classification of colour texture images in VisTex album is presented. Gray Level Co-occurrence Matrix (GLCM and its associated texture features contrast, correlation, energy and homogeneity are used in the proposed approach. The proposed GLCM texture features are obtained from the original colour texture as well as the first non singleton dimension of the same image. These features are fused at feature level to classify the colour texture image using nearest neighbor classifier. The results demonstrate that the proposed fusion of difference image GLCM features is much more efficient than the original GLCM features.

  11. Discovery and fusion of salient multimodal features toward news story segmentation

    Science.gov (United States)

    Hsu, Winston; Chang, Shih-Fu; Huang, Chih-Wei; Kennedy, Lyndon; Lin, Ching-Yung; Iyengar, Giridharan

    2003-12-01

    In this paper, we present our new results in news video story segmentation and classification in the context of TRECVID video retrieval benchmarking event 2003. We applied and extended the Maximum Entropy statistical model to effectively fuse diverse features from multiple levels and modalities, including visual, audio, and text. We have included various features such as motion, face, music/speech types, prosody, and high-level text segmentation information. The statistical fusion model is used to automatically discover relevant features contributing to the detection of story boundaries. One novel aspect of our method is the use of a feature wrapper to address different types of features -- asynchronous, discrete, continuous and delta ones. We also developed several novel features related to prosody. Using the large news video set from the TRECVID 2003 benchmark, we demonstrate satisfactory performance (F1 measures up to 0.76 in ABC news and 0.73 in CNN news), present how these multi-level multi-modal features construct the probabilistic framework, and more importantly observe an interesting opportunity for further improvement.

  12. Decision and feature fusion over the fractal inference network using camera and range sensors

    Science.gov (United States)

    Erkmen, Ismet; Erkmen, Aydan M.; Ucar, Ekin

    1998-10-01

    The objective of the ongoing work is to fuse information from uncertain environmental data taken by cameras, short range sensors including infrared and ultrasound sensors for strategic target recognition and task specific action in Mobile Robot applications. Our present goal in this paper is to demonstrate target recognition for service robot in a simple office environment. It is proposed to fuse all sensory signals obtained from multiple sensors over a fully layer-connected sensor network system that provides an equal opportunity competitive environment for sensory data where those bearing less uncertainty, less complexity and less inconsistencies with the overall goal survive, while others fade out. In our work, this task is achieved as a decision fusion using the Fractal Inference Network (FIN), where information patterns or units--modeled as textured belief functions bearing a fractal dimension due to uncertainty-- propagate while being processed at the nodes of the network. Each local process of a node generates a multiresolutional feature fusion. In this model, the environment is observed by multisensors of different type, different resolution and different spatial location without a prescheduled sensing scenario in data gathering. Node activation and flow control of information over the FIN is performed by a neuro- controller, a concept that has been developed recently as an improvement over the classical Fractal Inference Network. In this paper, the mathematical closed form representation for decision fusion over the FIN is developed in a way suitable for analysis and is applied to a NOMAD mobile robot servicing an office environment.

  13. Classification of brain disease in magnetic resonance images using two-stage local feature fusion

    Science.gov (United States)

    Li, Tao; Li, Wu; Yang, Yehui

    2017-01-01

    Background Many classification methods have been proposed based on magnetic resonance images. Most methods rely on measures such as volume, the cerebral cortical thickness and grey matter density. These measures are susceptible to the performance of registration and limited in representation of anatomical structure. This paper proposes a two-stage local feature fusion method, in which deformable registration is not desired and anatomical information is represented from moderate scale. Methods Keypoints are firstly extracted from scale-space to represent anatomical structure. Then, two kinds of local features are calculated around the keypoints, one for correspondence and the other for representation. Scores are assigned for keypoints to quantify their effect in classification. The sum of scores for all effective keypoints is used to determine which group the test subject belongs to. Results We apply this method to magnetic resonance images of Alzheimer's disease and Parkinson's disease. The advantage of local feature in correspondence and representation contributes to the final classification. With the help of local feature (Scale Invariant Feature Transform, SIFT) in correspondence, the performance becomes better. Local feature (Histogram of Oriented Gradient, HOG) extracted from 16×16 cell block obtains better results compared with 4×4 and 8×8 cell block. Discussion This paper presents a method which combines the effect of SIFT descriptor in correspondence and the representation ability of HOG descriptor in anatomical structure. This method has the potential in distinguishing patients with brain disease from controls. PMID:28207873

  14. A feature matching and fusion-based positive obstacle detection algorithm for field autonomous land vehicles

    Directory of Open Access Journals (Sweden)

    Tao Wu

    2017-03-01

    Full Text Available Positive obstacles will cause damage to field robotics during traveling in field. Field autonomous land vehicle is a typical field robotic. This article presents a feature matching and fusion-based algorithm to detect obstacles using LiDARs for field autonomous land vehicles. There are three main contributions: (1 A novel setup method of compact LiDAR is introduced. This method improved the LiDAR data density and reduced the blind region of the LiDAR sensor. (2 A mathematical model is deduced under this new setup method. The ideal scan line is generated by using the deduced mathematical model. (3 Based on the proposed mathematical model, a feature matching and fusion (FMAF-based algorithm is presented in this article, which is employed to detect obstacles. Experimental results show that the performance of the proposed algorithm is robust and stable, and the computing time is reduced by an order of two magnitudes by comparing with other exited algorithms. This algorithm has been perfectly applied to our autonomous land vehicle, which has won the champion in the challenge of Chinese “Overcome Danger 2014” ground unmanned vehicle.

  15. Feature-Based Image Fusion with a Uniform Discrete Curvelet Transform

    Directory of Open Access Journals (Sweden)

    Liang Xu

    2013-05-01

    Full Text Available The uniform discrete curvelet transform (UDCT is a novel tool for multiscale representations with several desirable properties compared to previous representation methods. A novel algorithm based on UDCT is proposed for the fusion of multi‐source images. A novel fusion rule for different subband coefficients obtained by UDCT decomposition is discussed in detail. Low‐pass subband coefficients are merged to develop a fusion rule based on a feature similarity (FSIM index. High‐pass directional subband coefficients are merged for a fusion rule based on a complex coefficients feature similarity (CCFSIM index. Experimental results demonstrate that the proposed algorithm fuses all of the useful information from source images without introducing artefacts. Compared with several state‐of‐the‐art fusion methods, it yields a better performance and achieves higher efficiency.

  16. FEATURE FUSION TECHNIQUE FOR COLOUR TEXTURE CLASSIFICATION SYSTEM BASED ON GRAY LEVEL CO-OCCURRENCE MATRIX

    OpenAIRE

    Shunmuganathan, K. L.; A. Suresh

    2012-01-01

    In this study, an efficient feature fusion based technique for the classification of colour texture images in VisTex album is presented. Gray Level Co-occurrence Matrix (GLCM) and its associated texture features contrast, correlation, energy and homogeneity are used in the proposed approach. The proposed GLCM texture features are obtained from the original colour texture as well as the first non singleton dimension of the same image. These features are fused at feature level to classify the c...

  17. Automatic generation of Chinese character using features fusion from calligraphy and font

    Science.gov (United States)

    Shi, Cao; Xiao, Jianguo; Xu, Canhui; Jia, Wenhua

    2014-02-01

    A spatial statistic based contour feature representation is proposed to achieve extraction of local contour feature from Chinese calligraphy character, and a features fusion strategy is designed to automatically generate new hybrid character, making well use of contour feature of calligraphy and structural feature of font. The features fusion strategy employs dilation and erosion operations iteratively to inject the extracted contour feature from Chinese calligraphy into font, which are similar to "pad" and "cut" in a sculpture progress. Experimental results demonstrate that the generated new hybrid character hold both contour feature of calligraphy and structural feature of font. Especially, two kinds of Chinese calligraphy skills called "Fei Bai" and "Zhang Mo" are imitated in the hybrid character. "Fei Bai" depicts a phenomenon that part of a stroke fade out due to the fast movement of hair brush or the lack of ink, and "Zhang Mo" describes a condition that hair brush holds so much ink that strokes overlap.

  18. Fault Diagnosis of Rotating Machinery Based on Multisensor Information Fusion Using SVM and Time-Domain Features

    Directory of Open Access Journals (Sweden)

    Ling-li Jiang

    2014-01-01

    Full Text Available Multisensor information fusion, when applied to fault diagnosis, the time-space scope, and the quantity of information are expanded compared to what could be acquired by a single sensor, so the diagnostic object can be described more comprehensively. This paper presents a methodology of fault diagnosis in rotating machinery using multisensor information fusion that all the features are calculated using vibration data in time domain to constitute fusional vector and the support vector machine (SVM is used for classification. The effectiveness of the presented methodology is tested by three case studies: diagnostic of faulty gear, rolling bearing, and identification of rotor crack. For each case study, the sensibilities of the features are analyzed. The results indicate that the peak factor is the most sensitive feature in the twelve time-domain features for identifying gear defect, and the mean, amplitude square, root mean square, root amplitude, and standard deviation are all sensitive for identifying gear, rolling bearing, and rotor crack defect comparatively.

  19. Feature importance for machine learning redshifts applied to SDSS galaxies

    CERN Document Server

    Hoyle, Ben; Zitlau, Roman; Steiz, Stella; Weller, Jochen

    2014-01-01

    We present an analysis of importance feature selection applied to photometric redshift estimation using the machine learning architecture Random Decision Forests (RDF) with the ensemble learning routine Adaboost. We select a list of 85 easily measured (or derived) photometric quantities (or 'features') and spectroscopic redshifts for almost two million galaxies from the Sloan Digital Sky Survey Data Release 10. After identifying which features have the most predictive power, we use standard artificial Neural Networks (aNN) to show that the addition of these features, in combination with the standard magnitudes and colours, improves the machine learning redshift estimate by 18% and decreases the catastrophic outlier rate by 32%. We further compare the redshift estimate from RDF using the ensemble learning routine Adaboost with those from two different aNNs, and with photometric redshifts available from the SDSS. We find that the RDF requires orders of magnitude less computation time than the aNNs to obtain a m...

  20. Comparative Study on Feature Selection and Fusion Schemes for Emotion Recognition from Speech

    Directory of Open Access Journals (Sweden)

    Santiago Planet

    2012-09-01

    Full Text Available The automatic analysis of speech to detect affective states may improve the way users interact with electronic devices. However, the analysis only at the acoustic level could be not enough to determine the emotion of a user in a realistic scenario. In this paper we analyzed the spontaneous speech recordings of the FAU Aibo Corpus at the acoustic and linguistic levels to extract two sets of features. The acoustic set was reduced by a greedy procedure selecting the most relevant features to optimize the learning stage. We compared two versions of this greedy selection algorithm by performing the search of the relevant features forwards and backwards. We experimented with three classification approaches: Naïve-Bayes, a support vector machine and a logistic model tree, and two fusion schemes: decision-level fusion, merging the hard-decisions of the acoustic and linguistic classifiers by means of a decision tree; and feature-level fusion, concatenating both sets of features before the learning stage. Despite the low performance achieved by the linguistic data, a dramatic improvement was achieved after its combination with the acoustic information, improving the results achieved by this second modality on its own. The results achieved by the classifiers using the parameters merged at feature level outperformed the classification results of the decision-level fusion scheme, despite the simplicity of the scheme. Moreover, the extremely reduced set of acoustic features obtained by the greedy forward search selection algorithm improved the results provided by the full set.

  1. Feature Fusion Algorithm for Multimodal Emotion Recognition from Speech and Facial Expression Signal

    Directory of Open Access Journals (Sweden)

    Han Zhiyan

    2016-01-01

    Full Text Available In order to overcome the limitation of single mode emotion recognition. This paper describes a novel multimodal emotion recognition algorithm, and takes speech signal and facial expression signal as the research subjects. First, fuse the speech signal feature and facial expression signal feature, get sample sets by putting back sampling, and then get classifiers by BP neural network (BPNN. Second, measure the difference between two classifiers by double error difference selection strategy. Finally, get the final recognition result by the majority voting rule. Experiments show the method improves the accuracy of emotion recognition by giving full play to the advantages of decision level fusion and feature level fusion, and makes the whole fusion process close to human emotion recognition more, with a recognition rate 90.4%.

  2. Medical Image Fusion Algorithm Based on Nonlinear Approximation of Contourlet Transform and Regional Features

    Directory of Open Access Journals (Sweden)

    Hui Huang

    2017-01-01

    Full Text Available According to the pros and cons of contourlet transform and multimodality medical imaging, here we propose a novel image fusion algorithm that combines nonlinear approximation of contourlet transform with image regional features. The most important coefficient bands of the contourlet sparse matrix are retained by nonlinear approximation. Low-frequency and high-frequency regional features are also elaborated to fuse medical images. The results strongly suggested that the proposed algorithm could improve the visual effects of medical image fusion and image quality, image denoising, and enhancement.

  3. Music genre classification via likelihood fusion from multiple feature models

    Science.gov (United States)

    Shiu, Yu; Kuo, C.-C. J.

    2005-01-01

    Music genre provides an efficient way to index songs in a music database, and can be used as an effective means to retrieval music of a similar type, i.e. content-based music retrieval. A new two-stage scheme for music genre classification is proposed in this work. At the first stage, we examine a couple of different features, construct their corresponding parametric models (e.g. GMM and HMM) and compute their likelihood functions to yield soft classification results. In particular, the timbre, rhythm and temporal variation features are considered. Then, at the second stage, these soft classification results are integrated to result in a hard decision for final music genre classification. Experimental results are given to demonstrate the performance of the proposed scheme.

  4. Tool Wear Monitoring in Drilling Using Multiple Feature Fusion of the Cutting Force

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    This paper presents a tool wear monitoring method in drilling process using cutting force signal. The kurtosis coefficient and the energy of a special frequency band of cutting force signals were taken as the signal features of tool wear as well as the mean value and the standard deviation from the time and frequency domain. The relationships between the signal feature andtool wear were discussed, then the vectors constituted of the signal features were input to the artificial neural network for fusion in order to realize intelligent identification of tool wear. The experimental results show that the artificial neural network can realize fusion of multiple features effectively, but the identification precision and the extending ability are not ideal owing to the relationship between the features and the tool wear being fuzzy and not certain. ``

  5. Finger-vein and fingerprint recognition based on a feature-level fusion method

    Science.gov (United States)

    Yang, Jinfeng; Hong, Bofeng

    2013-07-01

    Multimodal biometrics based on the finger identification is a hot topic in recent years. In this paper, a novel fingerprint-vein based biometric method is proposed to improve the reliability and accuracy of the finger recognition system. First, the second order steerable filters are used here to enhance and extract the minutiae features of the fingerprint (FP) and finger-vein (FV). Second, the texture features of fingerprint and finger-vein are extracted by a bank of Gabor filter. Third, a new triangle-region fusion method is proposed to integrate all the fingerprint and finger-vein features in feature-level. Thus, the fusion features contain both the finger texture-information and the minutiae triangular geometry structure. Finally, experimental results performed on the self-constructed finger-vein and fingerprint databases are shown that the proposed method is reliable and precise in personal identification.

  6. Multispectral image feature fusion for detecting land mines

    Energy Technology Data Exchange (ETDEWEB)

    Clark, G.A.; Fields, D.J.; Sherwood, R.J. [Lawrence Livermore National Lab., CA (United States)] [and others

    1994-11-15

    Our system fuses information contained in registered images from multiple sensors to reduce the effect of clutter and improve the the ability to detect surface and buried land mines. The sensor suite currently consists if a camera that acquires images in sixible wavelength bands, du, dual-band infrared (5 micron and 10 micron) and ground penetrating radar. Past research has shown that it is extremely difficult to distinguish land mines from background clutter in images obtained from a single sensor. It is hypothesized, however, that information fused from a suite of various sensors is likely to provide better detection reliability, because the suite of sensors detects a variety of physical properties that are more separate in feature space. The materials surrounding the mines can include natural materials (soil, rocks, foliage, water, holes made by animals and natural processes, etc.) and some artifacts.

  7. Pro duct Image Classification Based on Fusion Features

    Institute of Scientific and Technical Information of China (English)

    YANG Xiao-hui; LIU Jing-jing; YANG Li-jun

    2015-01-01

    Two key challenges raised by a product images classification system are classi-fication precision and classification time. In some categories, classification precision of the latest techniques, in the product images classification system, is still low. In this paper, we propose a local texture descriptor termed fan refined local binary pattern, which captures more detailed information by integrating the spatial distribution into the local binary pattern feature. We compare our approach with different methods on a subset of product images on Amazon/eBay and parts of PI100 and experimental results have demonstrated that our proposed approach is superior to the current existing methods. The highest classification precision is increased by 21%and the average classification time is reduced by 2/3.

  8. Multi-sensor fusion system using wavelet-based detection algorithm applied to physiological monitoring under high-G environment

    Science.gov (United States)

    Ryoo, Han Chool

    2000-06-01

    A significant problem in physiological state monitoring systems with single data channels is high rates of false alarm. In order to reduce false alarm probability, several data channels can be integrated to enhance system performance. In this work, we have investigated a sensor fusion methodology applicable to physiological state monitoring, which combines local decisions made from dispersed detectors. Difficulties in biophysical signal processing are associated with nonstationary signal patterns and individual characteristics of human physiology resulting in nonidentical observation statistics. Thus a two compartment design, a modified version of well established fusion theory in communication systems, is presented and applied to biological signal processing where we combine discrete wavelet transforms (DWT) with sensor fusion theory. The signals were decomposed in time-frequency domain by discrete wavelet transform (DWT) to capture localized transient features. Local decisions by wavelet power analysis are followed by global decisions at the data fusion center operating under an optimization criterion, i.e., minimum error criterion (MEC). We used three signals acquired from human volunteers exposed to high-G forces at the human centrifuge/dynamic flight simulator facility in Warminster, PA. The subjects performed anti-G straining maneuvers to protect them from the adverse effects of high-G forces. These maneuvers require muscular tensing and altered breathing patterns. We attempted to determine the subject's state by detecting the presence or absence of the voluntary anti-G straining maneuvers (AGSM). During the exposure to high G force the respiratory patterns, blood pressure and electroencephalogram (EEG) were measured to determine changes in the subject's state. Experimental results show that the probability of false alarm under MEC can be significantly reduced by applying the same rule found at local thresholds to all subjects, and MEC can be employed as a

  9. A SCHEME FOR TEMPLATE SECURITY AT FEATURE FUSION LEVEL IN MULTIMODAL BIOMETRIC SYSTEM

    Directory of Open Access Journals (Sweden)

    Arvind Selwal

    2016-09-01

    Full Text Available Biometric is the science of human recognition based upon using their biological, chemical or behavioural traits. These systems are used in many real life applications simply from biometric based attendance system to providing security at very sophisticated level. A biometric system deals with raw data captured using a sensor and feature template extracted from raw image. One of the challenges being faced by designers of these systems is to secure template data extracted from the biometric modalities of the user and protect the raw images. To minimize spoof attacks on biometric systems by unauthorised users one of the solutions is to use multi-biometric systems. Multi-modal biometric system works by using fusion technique to merge feature templates generated from different modalities of the human. In this work a new scheme is proposed to secure template during feature fusion level. Scheme is based on union operation of fuzzy relations of templates of modalities during fusion process of multimodal biometric systems. This approach serves dual purpose of feature fusion as well as transformation of templates into a single secured non invertible template. The proposed technique is cancelable and experimentally tested on a bimodal biometric system comprising of fingerprint and hand geometry. Developed scheme removes the problem of an attacker learning the original minutia position in fingerprint and various measurements of hand geometry. Given scheme provides improved performance of the system with reduction in false accept rate and improvement in genuine accept rate.

  10. MRI and PET image fusion using fuzzy logic and image local features.

    Science.gov (United States)

    Javed, Umer; Riaz, Muhammad Mohsin; Ghafoor, Abdul; Ali, Syed Sohaib; Cheema, Tanveer Ahmed

    2014-01-01

    An image fusion technique for magnetic resonance imaging (MRI) and positron emission tomography (PET) using local features and fuzzy logic is presented. The aim of proposed technique is to maximally combine useful information present in MRI and PET images. Image local features are extracted and combined with fuzzy logic to compute weights for each pixel. Simulation results show that the proposed scheme produces significantly better results compared to state-of-art schemes.

  11. Feature Extraction using Sparse SVD for Biometric Fusion in Multimodal Authentication

    Directory of Open Access Journals (Sweden)

    M. V. Ramakrishna

    2013-07-01

    Full Text Available Token based security (ID Cards have been used to restrictaccess to the Securedsystems.The purpose ofBiometricsistoidentify / verifythe correctness of an individualby using certain physiological orbehaviouraltraits associated with the person.Current biometric systems make use of face, fingerprints,iris,hand geometry,retina, signature, palm print, voiceprint and so on to establish a person’s identity.Biometrics isone of the primary key concepts of realapplicationdomains such asaadhar card, passport,pancard, etc.In this paper, we consider face andfingerprint patternsforidentification/verification.Usingthis data weproposed a novel model for authentication in multimodal biometricsoften called Context-SensitiveExponentAssociative Memory Model (CSEAM.It provides different stagesof securityforbiometricsfusionpatterns.Instage1,fusion offace and finger patternsusingPrincipal ComponentAnalysis (PCA,in stage 2by applyingSparseSVD decomposition toextract the feature patternsfrom thefusion data and face pattern and thenin stage 3,using CSEAM model,theextracted feature vectorscan beencoded.Thefinal key will be stored in the smart cardsas Associative Memory (M, which is often calledContext-Sensitive Associative Memory (CSAM. In CSEAM model,theCSEAMwill be computed usingexponential kronecker productforencodingand verificationofthe chosen samplesfrom the users.Theexponentialof matrixcan be computed in various ways such as Taylor Series, Pade Approximation andalso using OrdinaryDifferential Equations (O.D.E.. Among these approaches we considered first twomethods for computing exponential of a feature space.The result analysis of SVD and Sparse SVD forfeature extraction process and also authentication/verification process of the proposed systemin terms ofperformance measuresasMean square error rateswill be presented

  12. A Novel Feature-Level Data Fusion Method for Indoor Autonomous Localization

    Directory of Open Access Journals (Sweden)

    Minxiang Liu

    2013-01-01

    Full Text Available We present a novel feature-level data fusion method for autonomous localization in an inactive multiple reference unknown indoor environment. Since monocular sensors cannot provide the depth information directly, the proposed method incorporates the edge information of images from a camera with homologous depth information received from an infrared sensor. Real-time experimental results demonstrate that the accuracies of position and orientation are greatly improved by using the proposed fusion method in an unknown complex indoor environment. Compared to monocular localization, the proposed method is found to have up to 70 percent improvement in accuracy.

  13. Applying Data Clustering Feature to Speed Up Ant Colony Optimization

    Directory of Open Access Journals (Sweden)

    Chao-Yang Pang

    2014-01-01

    Full Text Available Ant colony optimization (ACO is often used to solve optimization problems, such as traveling salesman problem (TSP. When it is applied to TSP, its runtime is proportional to the squared size of problem N so as to look less efficient. The following statistical feature is observed during the authors’ long-term gene data analysis using ACO: when the data size N becomes big, local clustering appears frequently. That is, some data cluster tightly in a small area and form a class, and the correlation between different classes is weak. And this feature makes the idea of divide and rule feasible for the estimate of solution of TSP. In this paper an improved ACO algorithm is presented, which firstly divided all data into local clusters and calculated small TSP routes and then assembled a big TSP route with them. Simulation shows that the presented method improves the running speed of ACO by 200 factors under the condition that data set holds feature of local clustering.

  14. Facial Age Estimation based on Decision Level Fusion of AAM, LBP and Gabor Features

    Directory of Open Access Journals (Sweden)

    Asuman Günay

    2015-08-01

    Full Text Available In this paper a new hierarchical age estimation method based on decision level fusion of global and local features is proposed. The shape and appearance information of human faces which are extracted with active appearance models (AAM are used as global facial features. The local facial features are the wrinkle features extracted with Gabor filters and skin features extracted with local binary patterns (LBP. Then feature classification is performed using a hierarchical classifier which is the combination of an age group classification and detailed age estimation. In the age group classification phase, three distinct support vector machines (SVM classifiers are trained using each feature vector. Then decision level fusion is performed to combine the results of these classifiers. The detailed age of the classified image is then estimated in that age group, using the aging functions modeled with global and local features, separately. Aging functions are modeled with multiple linear regression. To make a final decision, the results of these aging functions are also fused in decision level. Experimental results on the FG-NET and PAL aging databases have shown that the age estimation accuracy of the proposed method is better than the previous methods.

  15. Joint Facial Action Unit Detection and Feature Fusion: A Multi-conditional Learning Approach.

    Science.gov (United States)

    Eleftheriadis, Stefanos; Rudovic, Ognjen; Pantic, Maja

    2016-10-05

    Automated analysis of facial expressions can benefit many domains, from marketing to clinical diagnosis of neurodevelopmental disorders. Facial expressions are typically encoded as a combination of facial muscle activations, i.e., action units. Depending on context, these action units co-occur in specific patterns, and rarely in isolation. Yet, most existing methods for automatic action unit detection fail to exploit dependencies among them, and the corresponding facial features. To address this, we propose a novel multi-conditional latent variable model for simultaneous fusion of facial features and joint action unit detection. Specifically, the proposed model performs feature fusion in a generative fashion via a low-dimensional shared subspace, while simultaneously performing action unit detection using a discriminative classification approach. We show that by combining the merits of both approaches, the proposed methodology outperforms existing purely discriminative/generative methods for the target task. To reduce the number of parameters, and avoid overfitting, a novel Bayesian learning approach based on Monte Carlo sampling is proposed, to integrate out the shared subspace. We validate the proposed method on posed and spontaneous data from three publicly available datasets (CK+, DISFA and Shoulder-pain), and show that both feature fusion and joint learning of action units leads to improved performance compared to the state-of-the-art methods for the task.

  16. Wood defect detection method with PCA feature fusion and compressed sensing

    Institute of Scientific and Technical Information of China (English)

    Yizhuo Zhang; Chao Xu; Chao Li; Huiling Yu; Jun Cao

    2015-01-01

    We used principal component analysis (PCA) and compressed sensing to detect wood defects from wood plate images. PCA makes it possible to reduce data redundancy and feature dimensions and compressed sensing, used as a clas-sifier, improves identification accuracy. We extracted 25 features, including geometry and regional features, gray-scale texture features, and invariant moment features, from wood board images and then integrated them using PCA, and se-lected eight principal components to express defects. After the fusion process, we used the features to construct a data dic-tionary, and realized the classification of defects by computing the optimal solution of the data dictionary in l1 norm using the least square method. We tested 50 Xylosma samples of live knots, dead knots, and cracks. The average detection time with PCA feature fusion and without were 0.2015 and 0.7125 ms, respectively. The original detection accuracy by SOM neural network was 87%, but after compressed sensing, it was 92%.

  17. Fusion

    CERN Document Server

    Mahaffey, James A

    2012-01-01

    As energy problems of the world grow, work toward fusion power continues at a greater pace than ever before. The topic of fusion is one that is often met with the most recognition and interest in the nuclear power arena. Written in clear and jargon-free prose, Fusion explores the big bang of creation to the blackout death of worn-out stars. A brief history of fusion research, beginning with the first tentative theories in the early 20th century, is also discussed, as well as the race for fusion power. This brand-new, full-color resource examines the various programs currently being funded or p

  18. Fast Image Retrieval of Textile Industrial Accessory Based on Multi-Feature Fusion

    Institute of Scientific and Technical Information of China (English)

    沈文忠; 杨杰

    2004-01-01

    A hierarchical retrieval scheme of the accessory image database is proposed based on textile industrial accessory contour feature and region feature. At first smallest enclosed rectangle[1] feature (degree of accessory coordination) is used to filter the image database to decouple the image search scope. After the accessory contour information and region information are extracted, the fusion multi-feature of the centroid distance Fourier descriptor and distance distribution histogram is adopted to finish image retrieval accurately. All the features above are invariable under translation, scaling and rotation. Results from the test on the image database including 1,000 accessory images demonstrate that the method is effective and practical with high accuracy and fast speed.

  19. Soft sensor design by multivariate fusion of image features and process measurements

    DEFF Research Database (Denmark)

    Lin, Bao; Jørgensen, Sten Bay

    2011-01-01

    This paper presents a multivariate data fusion procedure for design of dynamic soft sensors where suitably selected image features are combined with traditional process measurements to enhance the performance of data-driven soft sensors. A key issue of fusing multiple sensor data, i.e. to determine...... oxides (NOx) emission of cement kilns. On-site tests demonstrate improved performance over soft sensors based on conventional process measurements only....

  20. Self-organizing feature map neural network classification of the ASTER data based on wavelet fusion

    Institute of Scientific and Technical Information of China (English)

    HASI Bagan; MA Jianwen; LI Qiqing; HAN Xiuzhen; LIU Zhili

    2004-01-01

    Most methods for classification of remote sensing data are based on the statistical parameter evaluation with the assumption that the samples obey the normal distribution. However, more accurate classification results can be obtained with the neural network method through getting knowledge from environments and adjusting the parameter (or weight) step by step by a specific measurement. This paper focuses on the double-layer structured Kohonen self-organizing feature map (SOFM), for which all neurons within the two layers are linked one another and those of the competition layers are linked as well along the sides. Therefore, the self-adapting learning ability is improved due to the effective competition and suppression in this method. The SOFM has become a hot topic in the research area of remote sensing data classification. The Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) is a new satellite-borne remote sensing instrument with three 15-m resolution bands and three 30-m resolution bands at the near infrared. The ASTER data of Dagang district, Tianjin Municipality is used as the test data in this study. At first, the wavelet fusion is carried out to make the spatial resolutions of the ASTER data identical; then, the SOFM method is applied to classifying the land cover types. The classification results are compared with those of the maximum likelihood method (MLH). As a consequence, the classification accuracy of SOFM increases about by 7% in general and, in particular, it is almost as twice as that of the MLH method in the town.

  1. A method of recognition based on the feature layer fusion of palmprint and hand vein

    Science.gov (United States)

    Ma, Hua; Yang, Xiaoping; Shi, Guangyuan

    2013-12-01

    In this paper, a method of recognition of multi-modal biometrics for palmprint and hand vein based on the feature layer fusion is proposed, combined with the characteristics of an improved canonical correlation analysis (CCA) and two dimensional principal component analysis (2DPCA). After pretreatment respectively, feature vectors of palmprint and hand vein images are extracted using two dimensional principal component analysis (2DPCA),then fused in the feature level using the improved canonical correlation analysis(CCA), so identification can be done by a adjacent classifier finally. Using this method, two biometric information can be fused and the redundancy of information between features can effectively eliminated, the problem of the high-dimensional and small sample size can be overcome too. Simulation experimental results show that the proposed method in this paper can effectively improve the recognition rate of identification.

  2. Applying the data fusion method to evaluation of the performance of two control signals in monitoring polarization mode dispersion effects in fiber optic links

    Science.gov (United States)

    Dashtbani Moghari, M.; Rezaei, P.; Habibalahi, A.

    2015-02-01

    With increasing distance and bit rate in fiber optic links the effects of polarization mode dispersion (PMD) have been highlighted. Since PMD has a statistical nature, using a control signal that can provide accurate information to dynamically tune a PMD compensator is of great importance. In this paper, we apply the data fusion method with the aim of introducing a method that can be used to evaluate more accurately the performance of control signals before applying them in a PMD compensation system. Firstly, the minimum and average degree of polarization (DOP_min and DOP_ave respectively) as control signals in monitoring differential group delay (DGD) for a system including all-order PMD are calculated. Then, features including the amounts of sensitivity and ambiguity in DGD monitoring are calculated for NRZ data format as DGD to bit time (DGD/T) varies. It is shown that each of the control signals mentioned has both positive and negative features for efficient DGD monitoring. Therefore, in order to evaluate features concurrently and increase reliability, we employ data fusion to fuse features of each control signal, which makes evaluating and predicting the performance of control signals possible, before applying them in a real PMD compensation system. Finally, the reliability of the results obtained from data fusion is tested in a typical PMD compensator.

  3. Confidence level fusion of edge histogram descriptor, hidden Markov model, spectral correlation feature, and NUKEv6

    Science.gov (United States)

    Ho, K. C.; Gader, P. D.; Frigui, H.; Wilson, J. N.

    2007-04-01

    This paper examines the confidence level fusion of several promising algorithms for the vehiclemounted ground penetrating radar landmine detection system. The detection algorithms considered here include Edge Histogram Descriptor (EHD), Hidden Markov Model (HMM), Spectral Correlation Feature (SCF) and NUKEv6. We first form a confidence vector by collecting the confidence values from the four individual detectors. The fused confidence is assigned to be the difference in the square of the Mahalanobis distance to the non-mine class and the square of the Mahalanobis distance to the mine class. Experimental results on a data collection that contains over 1500 mine encounters indicate that the proposed fusion technique can reduce the false alarm rate by a factor of two at 90% probability of detection when compared to the best individual detector.

  4. Biometric hashing for handwriting: entropy-based feature selection and semantic fusion

    Science.gov (United States)

    Scheidat, Tobias; Vielhauer, Claus

    2008-02-01

    Some biometric algorithms lack of the problem of using a great number of features, which were extracted from the raw data. This often results in feature vectors of high dimensionality and thus high computational complexity. However, in many cases subsets of features do not contribute or with only little impact to the correct classification of biometric algorithms. The process of choosing more discriminative features from a given set is commonly referred to as feature selection. In this paper we present a study on feature selection for an existing biometric hash generation algorithm for the handwriting modality, which is based on the strategy of entropy analysis of single components of biometric hash vectors, in order to identify and suppress elements carrying little information. To evaluate the impact of our feature selection scheme to the authentication performance of our biometric algorithm, we present an experimental study based on data of 86 users. Besides discussing common biometric error rates such as Equal Error Rates, we suggest a novel measurement to determine the reproduction rate probability for biometric hashes. Our experiments show that, while the feature set size may be significantly reduced by 45% using our scheme, there are marginal changes both in the results of a verification process as well as in the reproducibility of biometric hashes. Since multi-biometrics is a recent topic, we additionally carry out a first study on a pair wise multi-semantic fusion based on reduced hashes and analyze it by the introduced reproducibility measure.

  5. IMAGING SPECTROSCOPY AND LIGHT DETECTION AND RANGING DATA FUSION FOR URBAN FEATURES EXTRACTION

    Directory of Open Access Journals (Sweden)

    Mohammed Idrees

    2013-01-01

    Full Text Available This study presents our findings on the fusion of Imaging Spectroscopy (IS and LiDAR data for urban feature extraction. We carried out necessary preprocessing of the hyperspectral image. Minimum Noise Fraction (MNF transforms was used for ordering hyperspectral bands according to their noise. Thereafter, we employed Optimum Index Factor (OIF to statistically select the three most appropriate bands combination from MNF result. The composite image was classified using unsupervised classification (k-mean algorithm and the accuracy of the classification assessed. Digital Surface Model (DSM and LiDAR intensity were generated from the LiDAR point cloud. The LiDAR intensity was filtered to remove the noise. Hue Saturation Intensity (HSI fusion algorithm was used to fuse the imaging spectroscopy and DSM as well as imaging spectroscopy and filtered intensity. The fusion of imaging spectroscopy and DSM was found to be better than that of imaging spectroscopy and LiDAR intensity quantitatively. The three datasets (imaging spectrocopy, DSM and Lidar intensity fused data were classified into four classes: building, pavement, trees and grass using unsupervised classification and the accuracy of the classification assessed. The result of the study shows that fusion of imaging spectroscopy and LiDAR data improved the visual identification of surface features. Also, the classification accuracy improved from an overall accuracy of 84.6% for the imaging spectroscopy data to 90.2% for the DSM fused data. Similarly, the Kappa Coefficient increased from 0.71 to 0.82. on the other hand, classification of the fused LiDAR intensity and imaging spectroscopy data perform poorly quantitatively with overall accuracy of 27.8% and kappa coefficient of 0.0988.

  6. Comparative studies for different proximity potentials applied to sub-barrier fusion reactions

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, G.L. [Beihang University, School of Physics and Nuclear Energy Engineering, Beijing (China); Beihang University, Key Laboratory of Micro-Nano Measurement-Manipulation and Physics (Ministry of Education), Beijing (China); Qu, W.W. [Medical College of Soochow University, School of Radiation Medicine and Protection, Soochow (China); Guo, M.F.; Qian, J.Q. [Beihang University, School of Physics and Nuclear Energy Engineering, Beijing (China); Zhang, H.Q. [China Institute of Atomic Energy, Beijing (China); Wolski, R. [Henryk Niewodniczanski Institute of Nuclear Physics PAS, Cracow (Poland)

    2016-02-15

    Coulomb barrier heights calculated by using 14 different versions of proximity potentials are studied and applied for experimental data of fusion in terms of a recently proposed energy scaling approach. The results show that the descriptions of proximity potentials 77 and 88 for the barrier heights seem to be closest to the values required by the systematics. On the basis of proximity potential 77, the parameterized formulas of the barrier height and radius are obtained. These formulas can calculate the barrier positions and barrier heights reasonably well within the error, respectively. Thus it provides a simple and direct way to calculate the barrier positions and barrier heights for heavy-ion fusion reactions. (orig.)

  7. Speech recognition using Kohonen neural networks, dynamic programming, and multi-feature fusion

    Science.gov (United States)

    Stowe, Francis S.

    1990-12-01

    The purpose of this thesis was to develop and evaluate the performance of a three-feature speech recognition system. The three features used were LPC spectrum, formants (F1/F2), and cepstrum. The system uses Kohonen neural networks, dynamic programming, and a rule-based, feature-fusion process which integrates the three input features into one output result. The first half of this research involved evaluating the system in a speaker-dependent atmosphere. For this, the 70 word F-16 cockpit command vocabulary was used and both isolated and connected speech was tested. Results obtained are compared to a two-feature system with the same system configuration. Isolated-speech testing yielded 98.7 percent accuracy. Connected-speech testing yielded 75/0 percent accuracy. The three-feature system performed an average of 1.7 percent better than the two-feature system for isolated-speech. The second half of this research was concerned with the speaker-independent performance of the system. First, cross-speaker testing was performed using an updated 86 word library. In general, this testing yielded less than 50 percent accuracy. Then, testing was performed using averaged templates. This testing yielded an overall average in-template recognition rate of approximately 90 percent and an out-of-template recognition rate of approximately 75 percent.

  8. Multi-modal face parts fusion based on Gabor feature for face recognition

    Institute of Scientific and Technical Information of China (English)

    Xiang Yan; Su Guangda; Shang Yan; Li Congcong

    2009-01-01

    A novel face recognition method, which is a fusion of multi-modal face parts based on Gabor feature (MMP-GF), is proposed in this paper. Firstly, the bare face image detached from the normalized image was convolved with a family of Gabor kernels, and then according to the face structure and the key-points locations, the calculated Gabor images were divided into five parts: Gabor face, Gabor eyebrow, Gabor eye, Gabor nose and Gabor mouth. After that multi-modal Gabor features were spatially partitioned into non-overlapping regions and the averages of regions were concatenated to be a low dimension feature vector, whose dimension was further reduced by principal component analysis (PCA). In the decision level fusion, match results respectively calculated based on the five parts were combined according to linear discriminant analysis (LDA) and a normalized matching algorithm was used to improve the performance. Experiments on FERET database show that the proposed MMP-GF method achieves good robustness to the expression and age variations.

  9. Fusion of local and global features for classification of abnormality in mammograms

    Indian Academy of Sciences (India)

    ANURADHA C PHADKE; PRITI P REGE

    2016-04-01

    Mammography is the most widely used tool for the early detection of breast cancer. Computer based algorithms can be developed to improve diagnostic information in mammograms and assist the radiologist to improve diagnostic accuracy. In this paper, we propose a novel computer aided technique to classifyabnormalities in mammograms using fusion of local and global features. The objective of this work is to test the effectiveness of combined use of local and global features in detecting abnormalities in mammograms. Local features used in the system are Chebyshev moments and Haralick’s gray level co-occurrence matrix based texture features. Global features used are Laws texture energy measures, Gabor based texture energy measures and fractal dimension. All types of abnormalities namely clusters of microcalcifications, circumscribed masses, spiculated masses, architectural distortions and ill-defined masses are considered. A support vector machine classifier is designed to classify the samples into abnormal and normal classes. It is observed that combined useof local and global features has improved classification accuracy from 88.75% to 93.17%

  10. Fusion

    Science.gov (United States)

    Herman, Robin

    1990-10-01

    The book abounds with fascinating anecdotes about fusion's rocky path: the spurious claim by Argentine dictator Juan Peron in 1951 that his country had built a working fusion reactor, the rush by the United States to drop secrecy and publicize its fusion work as a propaganda offensive after the Russian success with Sputnik; the fortune Penthouse magazine publisher Bob Guccione sank into an unconventional fusion device, the skepticism that met an assertion by two University of Utah chemists in 1989 that they had created "cold fusion" in a bottle. Aimed at a general audience, the book describes the scientific basis of controlled fusion--the fusing of atomic nuclei, under conditions hotter than the sun, to release energy. Using personal recollections of scientists involved, it traces the history of this little-known international race that began during the Cold War in secret laboratories in the United States, Great Britain and the Soviet Union, and evolved into an astonishingly open collaboration between East and West.

  11. Bayesian Information Criterion Based Feature Filtering for the Fusion of Multiple Features in High-Spatial-Resolution Satellite Scene Classification

    Directory of Open Access Journals (Sweden)

    Da Lin

    2015-01-01

    Full Text Available This paper presents a novel classification method for high-spatial-resolution satellite scene classification introducing Bayesian information criterion (BIC-based feature filtering process to further eliminate opaque and redundant information between multiple features. Firstly, two diverse and complementary feature descriptors are extracted to characterize the satellite scene. Then, sparse canonical correlation analysis (SCCA with penalty function is employed to fuse the extracted feature descriptors and remove the ambiguities and redundancies between them simultaneously. After that, a two-phase Bayesian information criterion (BIC-based feature filtering process is designed to further filter out redundant information. In the first phase, we gradually impose a constraint via an iterative process to set a constraint on the loadings for averting sparse correlation descending below to a lower confidence limit of the approximated canonical correlation. In the second phase, Bayesian information criterion (BIC is utilized to conduct the feature filtering which sets the smallest loading in absolute value to zero in each iteration for all features. Lastly, a support vector machine with pyramid match kernel is applied to obtain the final result. Experimental results on high-spatial-resolution satellite scenes demonstrate that the suggested approach achieves satisfactory performance in classification accuracy.

  12. Image mining for investigative pathology using optimized feature extraction and data fusion.

    Science.gov (United States)

    Chen, Wenjin; Meer, Peter; Georgescu, Bogdan; He, Wei; Goodell, Lauri A; Foran, David J

    2005-07-01

    In many subspecialties of pathology, the intrinsic complexity of rendering accurate diagnostic decisions is compounded by a lack of definitive criteria for detecting and characterizing diseases and their corresponding histological features. In some cases, there exists a striking disparity between the diagnoses rendered by recognized authorities and those provided by non-experts. We previously reported the development of an Image Guided Decision Support (IGDS) system, which was shown to reliably discriminate among malignant lymphomas and leukemia that are sometimes confused with one another during routine microscopic evaluation. As an extension of those efforts, we report here a web-based intelligent archiving subsystem that can automatically detect, image, and index new cells into distributed ground-truth databases. Systematic experiments showed that through the use of robust texture descriptors and density estimation based fusion the reliability and performance of the governing classifications of the system were improved significantly while simultaneously reducing the dimensionality of the feature space.

  13. Automatic Fusion of Hyperspectral Images and Laser Scans Using Feature Points

    Directory of Open Access Journals (Sweden)

    Xiao Zhang

    2015-01-01

    Full Text Available Automatic fusion of different kinds of image datasets is so intractable with diverse imaging principle. This paper presents a novel method for automatic fusion of two different images: 2D hyperspectral images acquired with a hyperspectral camera and 3D laser scans obtained with a laser scanner, without any other sensor. Only a few corresponding feature points are used, which are automatically extracted from a scene viewed by the two sensors. Extraction method of feature points relies on SURF algorithm and camera model, which can convert a 3D laser scan into a 2D laser image with the intensity of the pixels defined by the attributes in the laser scan. Moreover, Collinearity Equation and Direct Linear Transformation are used to create the initial corresponding relationship of the two images. Adjustment is also used to create corrected values to eliminate errors. The experimental result shows that this method is successfully validated with images collected by a hyperspectral camera and a laser scanner.

  14. Data Field Modeling and Spectral-Spatial Feature Fusion for Hyperspectral Data Classification

    Science.gov (United States)

    Liu, Da; Li, Jianxun

    2016-01-01

    Classification is a significant subject in hyperspectral remote sensing image processing. This study proposes a spectral-spatial feature fusion algorithm for the classification of hyperspectral images (HSI). Unlike existing spectral-spatial classification methods, the influences and interactions of the surroundings on each measured pixel were taken into consideration in this paper. Data field theory was employed as the mathematical realization of the field theory concept in physics, and both the spectral and spatial domains of HSI were considered as data fields. Therefore, the inherent dependency of interacting pixels was modeled. Using data field modeling, spatial and spectral features were transformed into a unified radiation form and further fused into a new feature by using a linear model. In contrast to the current spectral-spatial classification methods, which usually simply stack spectral and spatial features together, the proposed method builds the inner connection between the spectral and spatial features, and explores the hidden information that contributed to classification. Therefore, new information is included for classification. The final classification result was obtained using a random forest (RF) classifier. The proposed method was tested with the University of Pavia and Indian Pines, two well-known standard hyperspectral datasets. The experimental results demonstrate that the proposed method has higher classification accuracies than those obtained by the traditional approaches. PMID:27999259

  15. Data Field Modeling and Spectral-Spatial Feature Fusion for Hyperspectral Data Classification.

    Science.gov (United States)

    Liu, Da; Li, Jianxun

    2016-12-16

    Classification is a significant subject in hyperspectral remote sensing image processing. This study proposes a spectral-spatial feature fusion algorithm for the classification of hyperspectral images (HSI). Unlike existing spectral-spatial classification methods, the influences and interactions of the surroundings on each measured pixel were taken into consideration in this paper. Data field theory was employed as the mathematical realization of the field theory concept in physics, and both the spectral and spatial domains of HSI were considered as data fields. Therefore, the inherent dependency of interacting pixels was modeled. Using data field modeling, spatial and spectral features were transformed into a unified radiation form and further fused into a new feature by using a linear model. In contrast to the current spectral-spatial classification methods, which usually simply stack spectral and spatial features together, the proposed method builds the inner connection between the spectral and spatial features, and explores the hidden information that contributed to classification. Therefore, new information is included for classification. The final classification result was obtained using a random forest (RF) classifier. The proposed method was tested with the University of Pavia and Indian Pines, two well-known standard hyperspectral datasets. The experimental results demonstrate that the proposed method has higher classification accuracies than those obtained by the traditional approaches.

  16. Filling-Based Techniques Applied to Object Projection Feature Estimation

    CERN Document Server

    Quesada, Luis

    2012-01-01

    3D motion tracking is a critical task in many computer vision applications. Unsupervised markerless 3D motion tracking systems determine the most relevant object in the screen and then track it by continuously estimating its projection features (center and area) from the edge image and a point inside the relevant object projection (namely, inner point), until the tracking fails. Existing object projection feature estimation techniques are based on ray-casting from the inner point. These techniques present three main drawbacks: when the inner point is surrounded by edges, rays may not reach other relevant areas; as a consequence of that issue, the estimated features may greatly vary depending on the position of the inner point relative to the object projection; and finally, increasing the number of rays being casted and the ray-casting iterations (which would make the results more accurate and stable) increases the processing time to the point the tracking cannot be performed on the fly. In this paper, we anal...

  17. Automated Offline Arabic Signature Verification System using Multiple Features Fusion for Forensic Applications

    Directory of Open Access Journals (Sweden)

    Saad M. Darwish

    2016-12-01

    Full Text Available The signature of a person is one of the most popular and legally accepted behavioral biometrics that provides a secure means for verification and personal identification in many applications such as financial, commercial and legal transactions. The objective of the signature verification system is to classify between genuine and forged signatures that are often associated with intrapersonal and interpersonal variability. Unlike other languages, Arabic has unique features; it contains diacritics, ligatures, and overlapping. Because of lacking any form of dynamic information during the Arabic signature’s writing process, it will be more difficult to obtain higher verification accuracy. This paper addresses the above difficulty by introducing a novel offline Arabic signature verification algorithm. The key point is using multiple feature fusion with fuzzy modeling to capture different aspects of a signature individually in order to improve the verification accuracy. State-of-the-art techniques adopt the fuzzy set to describe the properties of the extracted features to handle a signature’s uncertainty; this work also employs the fuzzy variables to describe the degree of similarity of the signature’s features to deal with the ambiguity of questioned document examiner judgment of signature similarity. It is concluded from the experimental results that the verification system performs well and has the ability to reduce both False Acceptance Rate (FAR and False Rejection Rate (FRR.

  18. Definition of fine cutting features for laser fusion cutting of stainless steel

    Science.gov (United States)

    Seebach, J.; Norman, S.; Harrison, P.

    2015-07-01

    Laser fusion cutting of stainless steel is often considered in a material range from 0,3mm up to 4mm and laser powers up to 2kW. For a given material thickness, different optimum beam and process parameters can be determined empirically, leading to a dross-free cut for high tool travel speeds. Realising sharp 90-degree corners, dross formation is observed and leads to a deteriorated cutting quality. With reorientation at small radii, the speed-dependent change in the cutting process is superimposed by the existing beam to nozzle misalignment and contributes to the stability of a cut. The feature radius R on the stability of the cutting process is being determined by reducing feature radius R. In this paper, cutting of different radii for different sized conventional nozzles is considered and analysed. Based on cutting quality evaluation, fine feature cutting is defined by discussing thickness-dependent finest cutting feature for a given gas dynamic input.

  19. Feature selection applied to ultrasound carotid images segmentation.

    Science.gov (United States)

    Rosati, Samanta; Molinari, Filippo; Balestra, Gabriella

    2011-01-01

    The automated tracing of the carotid layers on ultrasound images is complicated by noise, different morphology and pathology of the carotid artery. In this study we benchmarked four methods for feature selection on a set of variables extracted from ultrasound carotid images. The main goal was to select those parameters containing the highest amount of information useful to classify the pixels in the carotid regions they belong to. Six different classes of pixels were identified: lumen, lumen-intima interface, intima-media complex, media-adventitia interface, adventitia and adventitia far boundary. The performances of QuickReduct Algorithm (QRA), Entropy-Based Algorithm (EBR), Improved QuickReduct Algorithm (IQRA) and Genetic Algorithm (GA) were compared using Artificial Neural Networks (ANNs). All methods returned subsets with a high dependency degree, even if the average classification accuracy was about 50%. Among all classes, the best results were obtained for the lumen. Overall, the four methods for feature selection assessed in this study return comparable results. Despite the need for accuracy improvement, this study could be useful to build a pre-classifier stage for the optimization of segmentation performance in ultrasound automated carotid segmentation.

  20. Local shape feature fusion for improved matching, pose estimation and 3D object recognition

    DEFF Research Database (Denmark)

    Buch, Anders Glent; Petersen, Henrik Gordon; Krüger, Norbert

    2016-01-01

    We provide new insights to the problem of shape feature description and matching, techniques that are often applied within 3D object recognition pipelines. We subject several state of the art features to systematic evaluations based on multiple datasets from different sources in a uniform manner...... feature matches with a limited processing overhead. Our fused feature matches provide a significant increase in matching accuracy, which is consistent over all tested datasets. Finally, we benchmark all features in a 3D object recognition setting, providing further evidence of the advantage of fused....... We have carefully prepared and performed a neutral test on the datasets for which the descriptors have shown good recognition performance. Our results expose an important fallacy of previous results, namely that the performance of the recognition system does not correlate well with the performance...

  1. A deep feature fusion methodology for breast cancer diagnosis demonstrated on three imaging modality datasets.

    Science.gov (United States)

    Antropova, Natalia; Huynh, Benjamin Q; Giger, Maryellen L

    2017-07-06

    Deep learning methods for radiomics/computer-aided diagnosis (CADx) are often prohibited by small datasets, long computation time, and the need for extensive image preprocessing. We aim to develop a breast CADx methodology that addresses the aforementioned issues by exploiting the efficiency of pre-trained convolutional neural networks (CNNs) and using pre-existing handcrafted CADx features. We present a methodology that extracts and pools low- to mid-level features using a pretrained CNN and fuses them with handcrafted radiomic features computed using conventional CADx methods. Our methodology is tested on three different clinical imaging modalities (dynamic contrast enhanced-MRI [690 cases], full-field digital mammography [245 cases], and ultrasound [1125 cases]). From ROC analysis, our fusion-based method demonstrates, on all three imaging modalities, statistically significant improvements in terms of AUC as compared to previous breast cancer CADx methods in the task of distinguishing between malignant and benign lesions. (DCE-MRI [AUC = 0.89 (se = 0.01)], FFDM [AUC = 0.86 (se = 0.01)], and ultrasound [AUC = 0.90 (se = 0.01)]). We proposed a novel breast CADx methodology that can be used to more effectively characterize breast lesions in comparison to existing methods. Furthermore, our proposed methodology is computationally efficient and circumvents the need for image preprocessing. © 2017 American Association of Physicists in Medicine.

  2. Robust and fast license plate detection based on the fusion of color and edge feature

    Science.gov (United States)

    Cai, De; Shi, Zhonghan; Liu, Jin; Hu, Chuanping; Mei, Lin; Qi, Li

    2014-11-01

    Extracting a license plate is an important stage in automatic vehicle identification. The degradation of images and the computation intense make this task difficult. In this paper, a robust and fast license plate detection based on the fusion of color and edge feature is proposed. Based on the dichromatic reflection model, two new color ratios computed from the RGB color model are introduced and proved to be two color invariants. The global color feature extracted by the new color invariants improves the method's robustness. The local Sobel edge feature guarantees the method's accuracy. In the experiment, the detection performance is good. The detection results show that this paper's method is robust to the illumination, object geometry and the disturbance around the license plates. The method can also detect license plates when the color of the car body is the same as the color of the plates. The processing time for image size of 1000x1000 by pixels is nearly 0.2s. Based on the comparison, the performance of the new ratios is comparable to the common used HSI color model.

  3. Pulmonary Nodule Detection Model Based on SVM and CT Image Feature-Level Fusion with Rough Sets

    Science.gov (United States)

    Lu, Huiling; Zhang, Junjie; Shi, Hongbin

    2016-01-01

    In order to improve the detection accuracy of pulmonary nodules in CT image, considering two problems of pulmonary nodules detection model, including unreasonable feature structure and nontightness of feature representation, a pulmonary nodules detection algorithm is proposed based on SVM and CT image feature-level fusion with rough sets. Firstly, CT images of pulmonary nodule are analyzed, and 42-dimensional feature components are extracted, including six new 3-dimensional features proposed by this paper and others 2-dimensional and 3-dimensional features. Secondly, these features are reduced for five times with rough set based on feature-level fusion. Thirdly, a grid optimization model is used to optimize the kernel function of support vector machine (SVM), which is used as a classifier to identify pulmonary nodules. Finally, lung CT images of 70 patients with pulmonary nodules are collected as the original samples, which are used to verify the effectiveness and stability of the proposed model by four groups' comparative experiments. The experimental results show that the effectiveness and stability of the proposed model based on rough set feature-level fusion are improved in some degrees.

  4. Low-Resolution Tactile Image Recognition for Automated Robotic Assembly Using Kernel PCA-Based Feature Fusion and Multiple Kernel Learning-Based Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Yi-Hung Liu

    2014-01-01

    Full Text Available In this paper, we propose a robust tactile sensing image recognition scheme for automatic robotic assembly. First, an image reprocessing procedure is designed to enhance the contrast of the tactile image. In the second layer, geometric features and Fourier descriptors are extracted from the image. Then, kernel principal component analysis (kernel PCA is applied to transform the features into ones with better discriminating ability, which is the kernel PCA-based feature fusion. The transformed features are fed into the third layer for classification. In this paper, we design a classifier by combining the multiple kernel learning (MKL algorithm and support vector machine (SVM. We also design and implement a tactile sensing array consisting of 10-by-10 sensing elements. Experimental results, carried out on real tactile images acquired by the designed tactile sensing array, show that the kernel PCA-based feature fusion can significantly improve the discriminating performance of the geometric features and Fourier descriptors. Also, the designed MKL-SVM outperforms the regular SVM in terms of recognition accuracy. The proposed recognition scheme is able to achieve a high recognition rate of over 85% for the classification of 12 commonly used metal parts in industrial applications.

  5. RGB-D Hand-Held Ob ject Recognition Based on Heterogeneous Feature Fusion

    Institute of Scientific and Technical Information of China (English)

    吕雄; 蒋树强; 王双

    2015-01-01

    Ob ject recognition has many applications in human-machine interaction and multimedia retrieval. However, due to large intra-class variability and inter-class similarity, accurate recognition relying only on RGB data is still a big challenge. Recently, with the emergence of inexpensive RGB-D devices, this challenge can be better addressed by leveraging additional depth information. A very special yet important case of object recognition is hand-held object recognition, as manipulating objects with hands is common and intuitive in human-human and human-machine interactions. In this paper, we study this problem and introduce an effective framework to address it. This framework first detects and segments the hand-held ob ject by exploiting skeleton information combined with depth information. In the ob ject recognition stage, this work exploits heterogeneous features extracted from different modalities and fuses them to improve the recognition accuracy. In particular, we incorporate handcrafted and deep learned features and study several multi-step fusion variants. Experimental evaluations validate the effectiveness of the proposed method.

  6. Features of a Spatially Constrained Cystine Loop in the p10 FAST Protein Ectodomain Define a New Class of Viral Fusion Peptides*

    OpenAIRE

    Barry, Christopher; Key, Tim; Haddad, Rami; Duncan, Roy

    2010-01-01

    The reovirus fusion-associated small transmembrane (FAST) proteins are the smallest known viral membrane fusion proteins. With ectodomains of only ∼20–40 residues, it is unclear how such diminutive fusion proteins can mediate cell-cell fusion and syncytium formation. Contained within the 40-residue ectodomain of the p10 FAST protein resides an 11-residue sequence of moderately apolar residues, termed the hydrophobic patch (HP). Previous studies indicate the p10 HP shares operational features ...

  7. Influence of Familiar Features on Diagnosis: Instantiated Features in an Applied Setting

    Science.gov (United States)

    Dore, Kelly L.; Brooks, Lee R.; Weaver, Bruce; Norman, Geoffrey R.

    2012-01-01

    Medical diagnosis can be viewed as a categorization task. There are two mechanisms whereby humans make categorical judgments: "analytical reasoning," based on explicit consideration of features and "nonanalytical reasoning," an unconscious holistic process of matching against prior exemplars. However, there is evidence that prior experience can…

  8. Influence of Familiar Features on Diagnosis: Instantiated Features in an Applied Setting

    Science.gov (United States)

    Dore, Kelly L.; Brooks, Lee R.; Weaver, Bruce; Norman, Geoffrey R.

    2012-01-01

    Medical diagnosis can be viewed as a categorization task. There are two mechanisms whereby humans make categorical judgments: "analytical reasoning," based on explicit consideration of features and "nonanalytical reasoning," an unconscious holistic process of matching against prior exemplars. However, there is evidence that prior experience can…

  9. Dorsal hand vein recognition based on Gabor multi-orientation fusion and multi-scale HOG features

    Science.gov (United States)

    Han, Tuo; Wang, Zhiyong; Yang, Xiaoping

    2016-10-01

    Kinds of factors such as illumination and hand gestures would reduce the accuracy of dorsal hand vein recognition. Aiming at single hand vein image with low contrast and simple structure, an algorithm combining Gabor multi-orientation features fusion with Multi-scale Histogram of Oriented Gradient (MS-HOG) is proposed in this paper. With this method, more features will be extracted to improve the recognition accuracy. Firstly, diagrams of multi-scale and multi-orientation are acquired using Gabor transformation, then the Gabor features of the same scale and multi-orientation will be fused, and the features of the correspondent fusion diagrams will be extracted with a HOG operator of a certain scale. Finally the multi-scale cascaded histograms will be obtained for hand vein recognition. The experimental results show that our method not only improve the recognition accuracy but has good robustness in dorsal hand vein recognition.

  10. Feature Level Fusion of Face and Palmprint Biometrics by Isomorphic Graph-based Improved K-Medoids Partitioning

    CERN Document Server

    Kisku, Dakshina Ranjan; Sing, Jamuna Kanta

    2010-01-01

    This paper presents a feature level fusion approach which uses the improved K-medoids clustering algorithm and isomorphic graph for face and palmprint biometrics. Partitioning around medoids (PAM) algorithm is used to partition the set of n invariant feature points of the face and palmprint images into k clusters. By partitioning the face and palmprint images with scale invariant features SIFT points, a number of clusters is formed on both the images. Then on each cluster, an isomorphic graph is drawn. In the next step, the most probable pair of graphs is searched using iterative relaxation algorithm from all possible isomorphic graphs for a pair of corresponding face and palmprint images. Finally, graphs are fused by pairing the isomorphic graphs into augmented groups in terms of addition of invariant SIFT points and in terms of combining pair of keypoint descriptors by concatenation rule. Experimental results obtained from the extensive evaluation show that the proposed feature level fusion with the improve...

  11. Validate and update of 3D urban features using multi-source fusion

    Science.gov (United States)

    Arrington, Marcus; Edwards, Dan; Sengers, Arjan

    2012-06-01

    As forecast by the United Nations in May 2007, the population of the world transitioned from a rural to an urban demographic majority with more than half living in urban areas.1 Modern urban environments are complex 3- dimensional (3D) landscapes with 4-dimensional patterns of activity that challenge various traditional 1-dimensional and 2-dimensional sensors to accurately sample these man-made terrains. Depending on geographic location, data resulting from LIDAR, multi-spectral, electro-optical, thermal, ground-based static and mobile sensors may be available with multiple collects along with more traditional 2D GIS features. Reconciling differing data sources over time to correctly portray the dynamic urban landscape raises significant fusion and representational challenges particularly as higher levels of spatial resolution are available and expected by users. This paper presents a framework for integrating the imperfect answers of our differing sensors and data sources into a powerful representation of the complex urban environment. A case study is presented involving the integration of temporally diverse 2D, 2.5D and 3D spatial data sources over Kandahar, Afghanistan. In this case study we present a methodology for validating and augmenting 2D/2.5D urban feature and attribute data with LIDAR to produce validated 3D objects. We demonstrate that nearly 15% of buildings in Kandahar require understanding nearby vegetation before 3-D validation can be successful. We also address urban temporal change detection at the object level. Finally we address issues involved with increased sampling resolution since urban features are rarely simple cubes but in the case of Kandahar involve balconies, TV dishes, rooftop walls, small rooms, and domes among other things.

  12. Reconstruction of an atmospheric tracer source in Fusion Field Trials: Analyzing resolution features

    Science.gov (United States)

    Singh, Sarvesh Kumar; Turbelin, Gregory; Issartel, Jean-Pierre; Kumar, Pramod; Feiz, Amir Ali

    2015-06-01

    Reconstruction of unknown atmospheric releases using measured concentrations is an ill-posed inverse problem. Due to insufficient measurements and dispersion model uncertainties, reliable interpretation of a retrieved source is limited by lack of resolution, nonuniqueness, and instability in the inverse solution. The study presents an optimality analysis, in terms of resolution, stability, and reliability, of an inverse solution given by a recently proposed inversion technique, called as renormalization. The inversion technique is based on an adjoint source-receptor framework and construction of a weight function which interprets a priori information about the unknown release apparent to the monitoring network. The properties of weight function provide a perfect data resolution, maximum model resolution, and minimum variance (or stability) for the retrieved source. The reliability of the retrieved source is interpreted in view of the information derived from the geometry of the monitoring network. The inversion technique and resolution features are evaluated for a point source reconstruction using measurements from a recent dispersion experiment (Fusion Field Trials 2007) conducted at Dugway Proving Ground, Utah. With the real measurements, the point release is reconstructed within an average distance of 23 m from the true release where the average distance of the nearest receptor from the true source was 32 m. In all the trials, the point release is retrieved within 3-60 m Euclidean distance from their true location. The source strength is retrieved within a factor of 1.5 to the true release mass. The posterior uncertainty in the release parameters is observed to be within 20% of their mean value. The source localization features are resolved to its maximum extent feasible with the design of the monitoring network. The sensitivity studies are conducted to highlight the importance of receptors reporting zero concentration measurements and variations in the

  13. Automatic building extraction from LiDAR data fusion of point and grid-based features

    Science.gov (United States)

    Du, Shouji; Zhang, Yunsheng; Zou, Zhengrong; Xu, Shenghua; He, Xue; Chen, Siyang

    2017-08-01

    This paper proposes a method for extracting buildings from LiDAR point cloud data by combining point-based and grid-based features. To accurately discriminate buildings from vegetation, a point feature based on the variance of normal vectors is proposed. For a robust building extraction, a graph cuts algorithm is employed to combine the used features and consider the neighbor contexture information. As grid feature computing and a graph cuts algorithm are performed on a grid structure, a feature-retained DSM interpolation method is proposed in this paper. The proposed method is validated by the benchmark ISPRS Test Project on Urban Classification and 3D Building Reconstruction and compared to the state-art-of-the methods. The evaluation shows that the proposed method can obtain a promising result both at area-level and at object-level. The method is further applied to the entire ISPRS dataset and to a real dataset of the Wuhan City. The results show a completeness of 94.9% and a correctness of 92.2% at the per-area level for the former dataset and a completeness of 94.4% and a correctness of 95.8% for the latter one. The proposed method has a good potential for large-size LiDAR data.

  14. 基于传感器特征可信度的多信息融合模态研究%Study on multi-information fusion modal based on feature credibility of sensor

    Institute of Scientific and Technical Information of China (English)

    杨剑锋; 周宇; 侯涛; 陈小强

    2013-01-01

    The key of information fusion is how to control amount of information, process relationship between various information and priority levels. A method for information fusion based on information feature credibility which is applied to mode construction of information fusion is presented. First, through pre-optimizing the credibility of information features information for one fusion, then through feature association in multiple information mode, the second information fusion is realized. Find the best multi-information modal construction method,and improve quality and credibility of information fusion%信息融合关键在于如何控制信息的数量,处理各种信息之间的关系以及优先级别.提出一种基于信息特征可信度的信息融合方法运用于信息融合的模态构建之中.通过预先优化信息特征的可信度进行信息的一次融合,再通过多信息模态中的特征关联进行信息的二次融合.找到最佳的多信息的模态构建方法,提高信息融合的质量和可信度.

  15. High resolution multisensor fusion of SAR, optical and LiDAR data based on crisp vs. fuzzy and feature vs. decision ensemble systems

    Science.gov (United States)

    Bigdeli, Behnaz; Pahlavani, Parham

    2016-10-01

    Synthetic Aperture Radar (SAR) data are of high interest for different applications in remote sensing specially land cover classification. SAR imaging is independent of solar illumination and weather conditions. It can even penetrate some of the Earth's surface materials to return information about subsurface features. However, the response of radar is more a function of geometry and structure than a surface reflection occurs in optical images. In addition, the backscatter of objects in the microwave range depends on the frequency of the band used, and the grey values in SAR images are different from the usual assumption of the spectral reflectance of the Earth's surface. Consequently, SAR imaging is often used as a complementary technique to traditional optical remote sensing. This study presents different ensemble systems for multisensor fusion of SAR, multispectral and LiDAR data. First, in decision ensemble system, after extraction and selection of proper features from each data, crisp SVM (Support Vector Machine) and Fuzzy KNN (K Nearest Neighbor) are utilized on each feature space. Finally Bayesian Theory is applied to fuse SVMs when Decision Template (DT) and Dempster Shafer (DS) are applied as fuzzy decision fusion methods on KNNs. Second, in feature ensemble system, features from all data are applied on a cube. Then classifications were performed by SVM and FKNN as crisp and fuzzy decision making system respectively. A co-registered TerrraSAR-X, WorldView-2 and LiDAR data set form San Francisco of USA was available to examine the effectiveness of the proposed method. The results show that combinations of SAR data with different sensor improves classification results for most of the classes.

  16. Fusion programs in applied plasma physics. Final report, fiscal years 1989--1991

    Energy Technology Data Exchange (ETDEWEB)

    1992-02-01

    The objectives of the theoretical science program are: To support the interpretation of present experiments and predict the outcome of future planned experiments; to improve on existing models and codes and validate against experimental results; and to conduct theoretical physics development of advanced concepts with applications for DIII-D and future devices. Major accomplishments in FY91 include the corroboration between theory and experiment on MHD behavior in the second stable regime of operation on DIII-D, and the frequency and mode structure of toroidal Alfven eigenmodes in high beta, shaped plasmas. We have made significant advances in the development of the gyro-Landau fluid approach to turbulence simulation which more accurately models kinetic drive and damping mechanisms. Several theoretical models to explain the bifurcation phenomenon in L- to H-mode transition were proposed providing the theoretical basis for future experimental verification. The capabilities of new rf codes have been upgraded in response to the expanding needs of the rf experiments. Codes are being employed to plan for a fully non-inductive current drive experiment in a high beta, enhanced confinement regime. GA`s experimental effort in Applied Physics encompasses two advanced diagnostics essential for the operation of future fusion experiments: Alpha particle diagnostic, and current and density profile diagnostics. This paper discusses research in all these topics.

  17. An Investigation for Ground State Features of Some Structural Fusion Materials

    Science.gov (United States)

    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.

  18. Feature Fusion Based Road Extraction for HJ-1-C SAR Image

    Directory of Open Access Journals (Sweden)

    Lu Ping-ping

    2014-06-01

    Full Text Available Road network extraction in SAR images is one of the key tasks of military and civilian technologies. To solve the issues of road extraction of HJ-1-C SAR images, a road extraction algorithm is proposed based on the integration of ratio and directional information. Due to the characteristic narrow dynamic range and low signal to noise ratio of HJ-1-C SAR images, a nonlinear quantization and an image filtering method based on a multi-scale autoregressive model are proposed here. A road extraction algorithm based on information fusion, which considers ratio and direction information, is also proposed. By processing Radon transformation, main road directions can be extracted. Cross interferences can be suppressed, and the road continuity can then be improved by the main direction alignment and secondary road extraction. The HJ-1-C SAR image acquired in Wuhan, China was used to evaluate the proposed method. The experimental results show good performance with correctness (80.5% and quality (70.1% when applied to a SAR image with complex content.

  19. Identification of Image Emotional Semantic based on Feature Fusion%基于特征融合的图像情感语义识别研究

    Institute of Scientific and Technical Information of China (English)

    刘增荣; 余雪丽; 李志

    2012-01-01

    针对图像情感语义识别中特征提取的问题,提出了一种加权值的图像特征融合算法,并应用于图像情感语义识别.该方法根据不同特征对情感语义的影响不同,在提取出颜色、纹理和形状特征后通过加权融合为新的特征输入量,并用SVM来实现情感语义的识别.实验结果表明,这种算法比单独使用某种图像特征有更高的准确率.%Because of the semantic gap, we can only extract the image feature to identify indirectly the image emotional semantic. In view of the feature extraction problem of image emotional semantic identification, the image feature fusion algorithm with weights was proposed and applied to the identification of image emotional semantic. According to the effects of the extracted color, texture and shape features of image on emotional semantic, the features were weighted and fused into new feature input. SVM was used to achieve emotional semantic identification. This algorithm was more accurate than the method that used only one kind of image features in experiments.

  20. Optical high-performance computing: introduction to the JOSA A and Applied Optics feature.

    Science.gov (United States)

    Caulfield, H John; Dolev, Shlomi; Green, William M J

    2009-08-01

    The feature issues in both Applied Optics and the Journal of the Optical Society of America A focus on topics of immediate relevance to the community working in the area of optical high-performance computing.

  1. Applying feature reduction analysis to a PPRLM-multiple Gaussian language identification system

    OpenAIRE

    Lucas Cuesta, Juan Manuel; Córdoba Herralde, Ricardo de; D'haro Enríquez, Luis Fernando

    2008-01-01

    This paper presents the application of a feature selection technique such as LDA to a language identification (LID) system. The baseline system consists of a PPRLM module followed by a multiple-Gaussian classifier. This classifier makes use of acoustic scores and duration features of each input utterance. We applied a dimension reduction of the feature space in order to achieve a faster and easier-trainable system. We imputed missing values of our vectors before projecting them on the new spa...

  2. TFG-MET fusion in an infantile spindle cell sarcoma with neural features

    NARCIS (Netherlands)

    Flucke, Uta; van Noesel, Max M.; Wijnen, Marc; Zhang, Lei; Chen, Chun Liang; Sung, Yun Shao; Antonescu, Cristina R.

    2017-01-01

    An increasing number of congenital and infantile sarcomas displaying a primitive, monomorphic spindle cell phenotype have been characterized to harbor recurrent gene fusions, including infantile fibrosarcoma and congenital spindle cell rhabdomyosarcoma. Here, we report an unusual spindle cell

  3. Content-Based High-Resolution Remote Sensing Image Retrieval via Unsupervised Feature Learning and Collaborative Affinity Metric Fusion

    Directory of Open Access Journals (Sweden)

    Yansheng Li

    2016-08-01

    Full Text Available With the urgent demand for automatic management of large numbers of high-resolution remote sensing images, content-based high-resolution remote sensing image retrieval (CB-HRRS-IR has attracted much research interest. Accordingly, this paper proposes a novel high-resolution remote sensing image retrieval approach via multiple feature representation and collaborative affinity metric fusion (IRMFRCAMF. In IRMFRCAMF, we design four unsupervised convolutional neural networks with different layers to generate four types of unsupervised features from the fine level to the coarse level. In addition to these four types of unsupervised features, we also implement four traditional feature descriptors, including local binary pattern (LBP, gray level co-occurrence (GLCM, maximal response 8 (MR8, and scale-invariant feature transform (SIFT. In order to fully incorporate the complementary information among multiple features of one image and the mutual information across auxiliary images in the image dataset, this paper advocates collaborative affinity metric fusion to measure the similarity between images. The performance evaluation of high-resolution remote sensing image retrieval is implemented on two public datasets, the UC Merced (UCM dataset and the Wuhan University (WH dataset. Large numbers of experiments show that our proposed IRMFRCAMF can significantly outperform the state-of-the-art approaches.

  4. A Fault-Tolerant Multiple Sensor Fusion Approach Applied to UAV Attitude Estimation

    Directory of Open Access Journals (Sweden)

    Yu Gu

    2016-01-01

    Full Text Available A novel sensor fusion design framework is presented with the objective of improving the overall multisensor measurement system performance and achieving graceful degradation following individual sensor failures. The Unscented Information Filter (UIF is used to provide a useful tool for combining information from multiple sources. A two-step off-line and on-line calibration procedure refines sensor error models and improves the measurement performance. A Fault Detection and Identification (FDI scheme crosschecks sensor measurements and simultaneously monitors sensor biases. Low-quality or faulty sensor readings are then rejected from the final sensor fusion process. The attitude estimation problem is used as a case study for the multiple sensor fusion algorithm design, with information provided by a set of low-cost rate gyroscopes, accelerometers, magnetometers, and a single-frequency GPS receiver’s position and velocity solution. Flight data collected with an Unmanned Aerial Vehicle (UAV research test bed verifies the sensor fusion, adaptation, and fault-tolerance capabilities of the designed sensor fusion algorithm.

  5. Joint Applied Optics and Chinese Optics Letters Feature Introduction: Digital Holography and 3D Imaging

    Institute of Scientific and Technical Information of China (English)

    Ting-Chung Poon; Changhe Zhou; Toyohiko Yatagai; Byoungho Lee; Hongchen Zhai

    2011-01-01

    This feature issue is the fifth installment on digital holography since its inception four years ago.The last four issues have been published after the conclusion of each Topical Meeting "Digital Holography and 3D imaging (DH)." However,this feature issue includes a new key feature-Joint Applied Optics and Chinese Optics Letters Feature Issue.The DH Topical Meeting is the world's premier forum for disseminating the science and technology geared towards digital holography and 3D information processing.Since the meeting's inception in 2007,it has steadily and healthily grown to 130 presentations this year,held in Tokyo,Japan,May 2011.

  6. Fusion of Pixel-based and Object-based Features for Road Centerline Extraction from High-resolution Satellite Imagery

    Directory of Open Access Journals (Sweden)

    CAO Yungang

    2016-10-01

    Full Text Available A novel approach for road centerline extraction from high spatial resolution satellite imagery is proposed by fusing both pixel-based and object-based features. Firstly, texture and shape features are extracted at the pixel level, and spectral features are extracted at the object level based on multi-scale image segmentation maps. Then, extracted multiple features are utilized in the fusion framework of Dempster-Shafer evidence theory to roughly identify the road network regions. Finally, an automatic noise removing algorithm combined with the tensor voting strategy is presented to accurately extract the road centerline. Experimental results using high-resolution satellite imageries with different scenes and spatial resolutions showed that the proposed approach compared favorably with the traditional methods, particularly in the aspect of eliminating the salt noise and conglutination phenomenon.

  7. Features of a spatially constrained cystine loop in the p10 FAST protein ectodomain define a new class of viral fusion peptides.

    Science.gov (United States)

    Barry, Christopher; Key, Tim; Haddad, Rami; Duncan, Roy

    2010-05-28

    The reovirus fusion-associated small transmembrane (FAST) proteins are the smallest known viral membrane fusion proteins. With ectodomains of only approximately 20-40 residues, it is unclear how such diminutive fusion proteins can mediate cell-cell fusion and syncytium formation. Contained within the 40-residue ectodomain of the p10 FAST protein resides an 11-residue sequence of moderately apolar residues, termed the hydrophobic patch (HP). Previous studies indicate the p10 HP shares operational features with the fusion peptide motifs found within the enveloped virus membrane fusion proteins. Using biotinylation assays, we now report that two highly conserved cysteine residues flanking the p10 HP form an essential intramolecular disulfide bond to create a cystine loop. Mutagenic analyses revealed that both formation of the cystine loop and p10 membrane fusion activity are highly sensitive to changes in the size and spatial arrangement of amino acids within the loop. The p10 cystine loop may therefore function as a cystine noose, where fusion peptide activity is dependent on structural constraints within the noose that force solvent exposure of key hydrophobic residues. Moreover, inhibitors of cell surface thioreductase activity indicate that disruption of the disulfide bridge is important for p10-mediated membrane fusion. This is the first example of a viral fusion peptide composed of a small, spatially constrained cystine loop whose function is dependent on altered loop formation, and it suggests the p10 cystine loop represents a new class of viral fusion peptides.

  8. Sensors Fusion based Online Mapping and Features Extraction of Mobile Robot in the Road Following and Roundabout

    Science.gov (United States)

    Ali, Mohammed A. H.; Mailah, Musa; Yussof, Wan Azhar B.; Hamedon, Zamzuri B.; Yussof, Zulkifli B.; Majeed, Anwar P. P.

    2016-02-01

    A road feature extraction based mapping system using a sensor fusion technique for mobile robot navigation in road environments is presented in this paper. The online mapping of mobile robot is performed continuously in the road environments to find the road properties that enable the robot to move from a certain start position to pre-determined goal while discovering and detecting the roundabout. The sensors fusion involving laser range finder, camera and odometry which are installed in a new platform, are used to find the path of the robot and localize it within its environments. The local maps are developed using camera and laser range finder to recognize the roads borders parameters such as road width, curbs and roundabout. Results show the capability of the robot with the proposed algorithms to effectively identify the road environments and build a local mapping for road following and roundabout.

  9. Non-contact method for the measurement of the enthalpy of fusion applied to binary Zr alloys

    Energy Technology Data Exchange (ETDEWEB)

    Wunderlich, R.K.; Fecht, H.-J. [Ulm Univ. (Germany). Abt. Werkstoffe der Elektrotechnik

    2000-07-01

    A new method for noncontact measurement of the heat of fusion of metallic alloys has been developed. It was applied to reactive binary Zr alloys in an electromagnetic containerless processing device under reduced gravity conditions. The method is based on the evaluation of the power balance between induction heating and radiative heat loss during the melting transition. Input power was obtained from measurement of the inductive coupling between the specimen and the currents in the oscillating circuits of a heating and positioning generator. Output power was obtained by evaluation of the total hemispherical emissivity from measurement of the external relaxation time, and of the heat capacity by noncontact ac-calorimetry. The enthalpy and entropy of fusion of several binary metallic glass-forming Zr alloys such obtained exhibit a pronounced correlation with the specific heat capacity at the liquidus temperature suggesting a reduced ideal glass transition temperature almost independent of composition for these alloys. (orig.)

  10. Fast neutron spectrometry with organic scintillators applied to magnetic fusion experiments

    CERN Document Server

    Kaschuck, Y A; Trykov, L A; Semenov, V P

    2002-01-01

    Neutron spectrometry with NE213 liquid scintillators is commonly used in thermonuclear fusion experiments to measure the 2.45 and 14.1 MeV neutron flux. We present the unfolded neutron spectrum, which was accumulated during several ohmic deuterium plasma discharges in the Frascati Tokamak Upgrade using a 2''x2'' NE213 scintillator. In this paper, we review the application of organic scintillator neutron spectrometers to tokamaks, focusing in particular on the comparison between NE213 and stilbene scintillators. Various aspects of the calibration technique and neutron spectra unfolding procedure are considered in the context of their application for fusion neutron spectrometry. Testing and calibration measurements have been carried out using D-D and D-T neutron generator facilities with both NE213 and stilbene scintillators. The main result from these measurements is that stilbene scintillator has better neutron energy resolution than NE213. Our stilbene detector could be used for the determination of the ion ...

  11. Lessons Learned from ASCI applied to the Fusion Simulation Project (FSP)

    Science.gov (United States)

    Post, Douglass

    2003-10-01

    The magnetic fusion program has proposed a 20M dollar per year project to develop a computational predictive capability for magnetic fusion experiments. The DOE NNSA launched a program in 1996, the Accelerated Strategic Computing Initiative (ASCI) to achieve the same goal for nuclear weapons to allow certification of the stockpile without testing. We present a "lessons learned" analysis of the 3B dollary 7 year ASCI program with the goal of improving the FSP to maximize the likelihood of success. The major lessons from ASCI are: 1. Build on your institution's successful history; 2.Teams are the key element; 3. Sound Software Project Management is essential: 4. Requirements, schedule and resources must be consistent; 5. Practices, not processes, are important; 6. Minimize and mitigate risks; 7. Minimize the computer science research aspect and maximize the physics elements; and 8. Verification and Validation are essential. We map this experience and recommendations into the FSP.

  12. Pulsed eddy current and ultrasonic data fusion applied to stress measurement

    Science.gov (United States)

    Habibalahi, A.; Safizadeh, M. S.

    2014-05-01

    Stress measurement and its variation are key problems in the operating performance of materials. Stress can affect the material properties and the life of components. There are several destructive and nondestructive techniques that are used to measure stress. However, no single nondestructive testing (NDT) technique or method is satisfactory to fully assess stress. This paper presents an NDT data fusion method to improve stress measurement. An aluminum alloy 2024 specimen subjected to stress simulation is nondestructively inspected using pulsed eddy current and ultrasonic techniques. Following these nondestructive examinations, the information gathered from these two NDT methods has been fused using a suitable fuzzy combination operator. The results obtained with these processes are presented in this paper and their efficiency is discussed. It is shown that the fusion of NDT data with a suitable fuzzy operator can be adequate to improve the reliability of stress measurements.

  13. Multiple local feature representations and their fusion based on an SVR model for iris recognition using optimized Gabor filters

    Science.gov (United States)

    He, Fei; Liu, Yuanning; Zhu, Xiaodong; Huang, Chun; Han, Ye; Dong, Hongxing

    2014-12-01

    Gabor descriptors have been widely used in iris texture representations. However, fixed basic Gabor functions cannot match the changing nature of diverse iris datasets. Furthermore, a single form of iris feature cannot overcome difficulties in iris recognition, such as illumination variations, environmental conditions, and device variations. This paper provides multiple local feature representations and their fusion scheme based on a support vector regression (SVR) model for iris recognition using optimized Gabor filters. In our iris system, a particle swarm optimization (PSO)- and a Boolean particle swarm optimization (BPSO)-based algorithm is proposed to provide suitable Gabor filters for each involved test dataset without predefinition or manual modulation. Several comparative experiments on JLUBR-IRIS, CASIA-I, and CASIA-V4-Interval iris datasets are conducted, and the results show that our work can generate improved local Gabor features by using optimized Gabor filters for each dataset. In addition, our SVR fusion strategy may make full use of their discriminative ability to improve accuracy and reliability. Other comparative experiments show that our approach may outperform other popular iris systems.

  14. General fusion approaches for the age determination of latent fingerprint traces: results for 2D and 3D binary pixel feature fusion

    Science.gov (United States)

    Merkel, Ronny; Gruhn, Stefan; Dittmann, Jana; Vielhauer, Claus; Bräutigam, Anja

    2012-03-01

    Determining the age of latent fingerprint traces found at crime scenes is an unresolved research issue since decades. Solving this issue could provide criminal investigators with the specific time a fingerprint trace was left on a surface, and therefore would enable them to link potential suspects to the time a crime took place as well as to reconstruct the sequence of events or eliminate irrelevant fingerprints to ensure privacy constraints. Transferring imaging techniques from different application areas, such as 3D image acquisition, surface measurement and chemical analysis to the domain of lifting latent biometric fingerprint traces is an upcoming trend in forensics. Such non-destructive sensor devices might help to solve the challenge of determining the age of a latent fingerprint trace, since it provides the opportunity to create time series and process them using pattern recognition techniques and statistical methods on digitized 2D, 3D and chemical data, rather than classical, contact-based capturing techniques, which alter the fingerprint trace and therefore make continuous scans impossible. In prior work, we have suggested to use a feature called binary pixel, which is a novel approach in the working field of fingerprint age determination. The feature uses a Chromatic White Light (CWL) image sensor to continuously scan a fingerprint trace over time and retrieves a characteristic logarithmic aging tendency for 2D-intensity as well as 3D-topographic images from the sensor. In this paper, we propose to combine such two characteristic aging features with other 2D and 3D features from the domains of surface measurement, microscopy, photography and spectroscopy, to achieve an increase in accuracy and reliability of a potential future age determination scheme. Discussing the feasibility of such variety of sensor devices and possible aging features, we propose a general fusion approach, which might combine promising features to a joint age determination scheme

  15. Study of safety features and accident scenarios in a fusion DEMO reactor

    Energy Technology Data Exchange (ETDEWEB)

    Nakamura, M., E-mail: nakamura.makoto@jaea.go.jp [Japan Atomic Energy Agency, Rokkasho, Aomori 039-3212 (Japan); Tobita, K. [Japan Atomic Energy Agency, Rokkasho, Aomori 039-3212 (Japan); Gulden, W. [Fusion for Energy, c/o EFDA Garching and Max-Plank-Institut fuer Plasmaphysik, Garching D-85748 (Germany); Watanabe, K. [Japan Atomic Energy Agency, Rokkasho, Aomori 039-3212 (Japan); Toshiba Corporation, Yokohama, Kanagawa 235-8523 (Japan); Someya, Y. [Japan Atomic Energy Agency, Rokkasho, Aomori 039-3212 (Japan); Tanigawa, H. [Japan Atomic Energy Agency, Naka, Ibaraki 311-0193 (Japan); Sakamoto, Y. [Japan Atomic Energy Agency, Rokkasho, Aomori 039-3212 (Japan); Araki, T.; Matsumiya, H.; Ishii, K. [Toshiba Corporation, Yokohama, Kanagawa 235-8523 (Japan); Utoh, H. [Japan Atomic Energy Agency, Rokkasho, Aomori 039-3212 (Japan); Takase, H. [IFERC Project Team, Rokkasho, Aomori 039-3212 (Japan); Hayashi, T. [Japan Atomic Energy Agency, Naka, Ibaraki 311-0193 (Japan); Satou, A.; Yonomoto, T. [Japan Atomic Energy Agency, Tokai, Ibaraki 319-1195 (Japan); Federici, G. [Fusion for Energy, c/o EFDA Garching and Max-Plank-Institut fuer Plasmaphysik, Garching D-85748 (Germany); Okano, K. [IFERC Project Team, Rokkasho, Aomori 039-3212 (Japan)

    2014-10-15

    Highlights: This paper reports progress in the fusion DEMO safety research conducted under the Broader Approach DEMO Design Activities; Hazards of a reference DEMO concept have been assessed; Reference accident event sequences in the reference DEMO in this study have been analyzed based on the master logic diagram (MLD) and the functional failure mode and effect analysis (FFMEA) techniques; Accident events of particular concern in the DEMO have been selected based on the MLD and FFMEA analysis. Abstract: After the Fukushima Dai-ichi nuclear accident, a need for assuring safety of fusion energy has grown in the Japanese (JA) fusion research community. DEMO safety research has been launched as a part of Broader Approach DEMO Design Activities (BA-DDA). This paper reports progress in the fusion DEMO safety research conducted under BA-DDA. Safety requirements and evaluation guidelines have been, first of all, established based on those established in the Japanese ITER site invitation activities. The radioactive source terms and energies that can mobilize such source terms have been assessed for a reference DEMO concept. This concept employs in-vessel components that are cooled by pressurized water and built of a low activation ferritic steel (F82H), contains solid pebble beds made of lithium-titanate (Li{sub 2}TiO{sub 3}) and beryllium–titanium (Be{sub 12}Ti) for tritium breeding and neutron multiplication, respectively. It is shown that unlike the energies expected in ITER, the enthalpy in the first wall/blanket cooling loops is large compared to the other energies expected in the reference DEMO concept. Reference accident event sequences in the reference DEMO in this study have been analyzed based on the Master Logic Diagram and Functional Failure Mode and Effect Analysis techniques. Accident events of particular concern in the DEMO have been selected based on the event sequence analysis and the hazard assessment.

  16. A multi-biometric feature-fusion framework for improved uni-modal and multi-modal human identification

    CSIR Research Space (South Africa)

    Brown, K

    2016-05-01

    Full Text Available provide important guidelines that enable the sys- tematic implementation of multi-modal biometric systems for future research and applications. Feature-level fusion is in particular need of these guidelines because of the ”curse of dimensionality” problem.... The training samples were sequentially chosen from one to five and the rest were used for testing. To the best of our knowledge there are no studies that fuse face and fingerprint data acquired from the SDUMLA multi-modal database. B. Pre-processing Pixel...

  17. Applying a Locally Linear Embedding Algorithm for Feature Extraction and Visualization of MI-EEG

    Directory of Open Access Journals (Sweden)

    Mingai Li

    2016-01-01

    Full Text Available Robotic-assisted rehabilitation system based on Brain-Computer Interface (BCI is an applicable solution for stroke survivors with a poorly functioning hemiparetic arm. The key technique for rehabilitation system is the feature extraction of Motor Imagery Electroencephalography (MI-EEG, which is a nonlinear time-varying and nonstationary signal with remarkable time-frequency characteristic. Though a few people have made efforts to explore the nonlinear nature from the perspective of manifold learning, they hardly take into full account both time-frequency feature and nonlinear nature. In this paper, a novel feature extraction method is proposed based on the Locally Linear Embedding (LLE algorithm and DWT. The multiscale multiresolution analysis is implemented for MI-EEG by DWT. LLE is applied to the approximation components to extract the nonlinear features, and the statistics of the detail components are calculated to obtain the time-frequency features. Then, the two features are combined serially. A backpropagation neural network is optimized by genetic algorithm and employed as a classifier to evaluate the effectiveness of the proposed method. The experiment results of 10-fold cross validation on a public BCI Competition dataset show that the nonlinear features visually display obvious clustering distribution and the fused features improve the classification accuracy and stability. This paper successfully achieves application of manifold learning in BCI.

  18. Joint Applied Optics and Chinese Optics Letters feature introduction: digital holography and three-dimensional imaging.

    Science.gov (United States)

    Poon, Ting-Chung

    2011-12-01

    This feature issue serves as a pilot issue promoting the joint issue of Applied Optics and Chinese Optics Letters. It focuses upon topics of current relevance to the community working in the area of digital holography and 3-D imaging. © 2011 Optical Society of America

  19. Joint Applied Optics and Chinese Optics Letters feature introduction: digital holography and three-dimensional imaging

    OpenAIRE

    Poon, Ting-Chung

    2011-01-01

    This feature issue serves as a pilot issue promoting the joint issue of Applied Optics and Chinese Optics Letters. It focuses upon topics of current relevance to the community working in the area of digital holography and 3-D imaging. (C) 2011 Optical Society of America

  20. RET Fusion Lung Carcinoma: Response to Therapy and Clinical Features in a Case Series of 14 Patients.

    Science.gov (United States)

    Sarfaty, Michal; Moore, Assaf; Neiman, Victoria; Dudnik, Elizabeth; Ilouze, Maya; Gottfried, Maya; Katznelson, Rivka; Nechushtan, Hovav; Sorotsky, Hadas Gantz; Paz, Keren; Katz, Amanda; Saute, Milton; Wolner, Mira; Moskovitz, Mor; Miller, Vincent; Elvin, Julia; Lipson, Doron; Ali, Siraj; Gutman, Lior Soussan; Dvir, Addie; Gordon, Noa; Peled, Nir

    2017-07-01

    RET (rearranged during transfection) fusions have been reported in 1% to 2% of lung adenocarcinoma (LADC) cases. In contrast, KIF5B-RET and CCDC6-RET fusion genes have been identified in 70% to 90% and 10% to 25% of tumors, respectively. The natural history and management of RET-rearranged LADC are still being delineated. We present a series of 14 patients with RET-rearranged LADC. The response to therapy was assessed by the clinical response and an avatar model in 2 cases. Patients underwent chemotherapy, targeted therapy, and immunotherapy. A total of 14 patients (8 women; 10 never smokers; 4 light smokers; mean age, 57 years) were included. KIF5B-RET and CCDC6-RET variants were diagnosed in 10 and 4 cases, respectively. Eight patients had an early disseminated manifestation, seven with KIF5B-RET rearranged tumor. The features of this subset included bilateral miliary lung metastases, bone metastases, and unusual early visceral abdominal involvement. One such patient demonstrated an early and durable complete response to cabozantinib for 7 months. Another 2 patients treated with cabozantinib experienced a partial response, with rapid significant clinical improvement. Four patients with tumors harboring CCDC6-RET and KIF5B-RET fusions showed pronounced and durable responses to platinum-based chemotherapy that lasted for 8 to 15 months. Two patients' tumors showed programmed cell death ligand 1-positive staining but did not respond to pembrolizumab. The median overall survival was 22.8 months. RET-rearranged LADC in our series tended to occur as bilateral disease with early visceral involvement, especially with KIF5B fusion. Treatment with cabozantinib achieved responses, including 1 complete response. However, further studies are required in this group of patients. Copyright © 2016 Elsevier Inc. All rights reserved.

  1. Feature Level Fusion of Biometrics Cues: Human Identification with Doddingtons Caricature

    CERN Document Server

    Kisku, Dakshina Ranjan; Sing, Jamuna Kanta

    2010-01-01

    This paper presents a multimodal biometric system of fingerprint and ear biometrics. Scale Invariant Feature Transform (SIFT) descriptor based feature sets extracted from fingerprint and ear are fused. The fused set is encoded by K-medoids partitioning approach with less number of feature points in the set. K-medoids partition the whole dataset into clusters to minimize the error between data points belonging to the clusters and its center. Reduced feature set is used to match between two biometric sets. Matching scores are generated using wolf-lamb user-dependent feature weighting scheme introduced by Doddington. The technique is tested to exhibit its robust performance.

  2. Applying machine learning and image feature extraction techniques to the problem of cerebral aneurysm rupture

    Directory of Open Access Journals (Sweden)

    Steren Chabert

    2017-01-01

    Full Text Available Cerebral aneurysm is a cerebrovascular disorder characterized by a bulging in a weak area in the wall of an artery that supplies blood to the brain. It is relevant to understand the mechanisms leading to the apparition of aneurysms, their growth and, more important, leading to their rupture. The purpose of this study is to study the impact on aneurysm rupture of the combination of different parameters, instead of focusing on only one factor at a time as is frequently found in the literature, using machine learning and feature extraction techniques. This discussion takes relevance in the context of the complex decision that the physicians have to take to decide which therapy to apply, as each intervention bares its own risks, and implies to use a complex ensemble of resources (human resources, OR, etc. in hospitals always under very high work load. This project has been raised in our actual working team, composed of interventional neuroradiologist, radiologic technologist, informatics engineers and biomedical engineers, from Valparaiso public Hospital, Hospital Carlos van Buren, and from Universidad de Valparaíso – Facultad de Ingeniería and Facultad de Medicina. This team has been working together in the last few years, and is now participating in the implementation of an “interdisciplinary platform for innovation in health”, as part of a bigger project leaded by Universidad de Valparaiso (PMI UVA1402. It is relevant to emphasize that this project is made feasible by the existence of this network between physicians and engineers, and by the existence of data already registered in an orderly manner, structured and recorded in digital format. The present proposal arises from the description in nowadays literature that the actual indicators, whether based on morphological description of the aneurysm, or based on characterization of biomechanical factor or others, these indicators were shown not to provide sufficient information in order

  3. 基于多特征融合的织物瑕疵检测研究%Fabric defect detection based on multi-feature fusion

    Institute of Scientific and Technical Information of China (English)

    马强; 陈亮; 崔雷涛

    2015-01-01

    织物瑕疵纹理特征复杂,单一特征不能很好地反映纹理信息。为此,本文提出一种基于局部二进制模式( Local Binary Pattern , LBP )算子和灰度共生矩阵( Gray Level Co-occurrence Matrix , GLCM )的多特征融合算法。首先,对 LBP 算子进行了改进,提出一种基于邻域像素中值的中心对称LBP 算子;然后,将其提取出的纹理特征和灰度共生矩阵提取的纹理特征进行融合;最后,通过极速学习机和支持向量机做分类实验,验证融合特征描述织物瑕疵纹理特征的能力。实验表明,本文方法提高了织物物疵点检测率,并且具有很好的抗干扰能力。%In order to solve the problem that single feature dose not well reflect fabric defects texture which more complexity than general, this paper presents a feature fusion algorithm which fuses Local Binary Pattern feature (LBP)and Gray level co-occurrence feature matrix (GLCM). Fristly, a new algorithm named MCS_LBP will be put forward based on LBP. Secondly, the texture features extracted by MCS_LBP will mix features which are extracted by GLCM. Finally, the Extreme Learning Machine (ELM)and Support Vector Machine (SVM) are applied to do classification experiments so that we can test the ability of fusion characterization texture features. The results show that the tactics in this paper can improve methods herein woven material defect detection rate, and they have good robustness.

  4. Automatic lumbar vertebrae detection based on feature fusion deep learning for partial occluded C-arm X-ray images.

    Science.gov (United States)

    Li, Yang; Liang, Wei; Zhang, Yinlong; An, Haibo; Tan, Jindong; Yang Li; Wei Liang; Yinlong Zhang; Haibo An; Jindong Tan; Li, Yang; Liang, Wei; Tan, Jindong; Zhang, Yinlong; An, Haibo

    2016-08-01

    Automatic and accurate lumbar vertebrae detection is an essential step of image-guided minimally invasive spine surgery (IG-MISS). However, traditional methods still require human intervention due to the similarity of vertebrae, abnormal pathological conditions and uncertain imaging angle. In this paper, we present a novel convolutional neural network (CNN) model to automatically detect lumbar vertebrae for C-arm X-ray images. Training data is augmented by DRR and automatic segmentation of ROI is able to reduce the computational complexity. Furthermore, a feature fusion deep learning (FFDL) model is introduced to combine two types of features of lumbar vertebrae X-ray images, which uses sobel kernel and Gabor kernel to obtain the contour and texture of lumbar vertebrae, respectively. Comprehensive qualitative and quantitative experiments demonstrate that our proposed model performs more accurate in abnormal cases with pathologies and surgical implants in multi-angle views.

  5. GENIE TRECVID2011 Multimedia Event Detection: Late Fusion Approaches to Combine Multiple Audio Visual features

    Science.gov (United States)

    2012-03-01

    27, May 2011. [2] Sheng Gao, De- Hong Wang , and Chin-Hui Lee. Automatic image annotation through multi-topic text categorization. In ICASSP, 2006. [3...International Journal of Computer Vision, 42(3):145175, 2001. [9] De- Hong Wang , Sheng Gao, Qi Tian, and Wing-Kin Sung. Discriminative fusion approach for automatic image annotation. In MMSP, 2005. ...Government. References [1] Chih -Chung Chang and Chih -Jen Lin. Libsvm: A library for support vector machines. ACM Trans. Intell. Syst. Technol., 2:27:127

  6. Multiple kernel based feature and decision level fusion of iECO individuals for explosive hazard detection in FLIR imagery

    Science.gov (United States)

    Price, Stanton R.; Murray, Bryce; Hu, Lequn; Anderson, Derek T.; Havens, Timothy C.; Luke, Robert H.; Keller, James M.

    2016-05-01

    A serious threat to civilians and soldiers is buried and above ground explosive hazards. The automatic detection of such threats is highly desired. Many methods exist for explosive hazard detection, e.g., hand-held based sensors, downward and forward looking vehicle mounted platforms, etc. In addition, multiple sensors are used to tackle this extreme problem, such as radar and infrared (IR) imagery. In this article, we explore the utility of feature and decision level fusion of learned features for forward looking explosive hazard detection in IR imagery. Specifically, we investigate different ways to fuse learned iECO features pre and post multiple kernel (MK) support vector machine (SVM) based classification. Three MK strategies are explored; fixed rule, heuristics and optimization-based. Performance is assessed in the context of receiver operating characteristic (ROC) curves on data from a U.S. Army test site that contains multiple target and clutter types, burial depths and times of day. Specifically, the results reveal two interesting things. First, the different MK strategies appear to indicate that the different iECO individuals are all more-or-less important and there is not a dominant feature. This is reinforcing as our hypothesis was that iECO provides different ways to approach target detection. Last, we observe that while optimization-based MK is mathematically appealing, i.e., it connects the learning of the fusion to the underlying classification problem we are trying to solve, it appears to be highly susceptible to over fitting and simpler, e.g., fixed rule and heuristics approaches help us realize more generalizable iECO solutions.

  7. a Detection Method of Artificial Area from High Resolution Remote Sensing Images Based on Multi Scale and Multi Feature Fusion

    Science.gov (United States)

    Li, P.; Hu, X.; Hu, Y.; Ding, Y.; Wang, L.; Li, L.

    2017-05-01

    In order to solve the problem of automatic detection of artificial objects in high resolution remote sensing images, a method for detection of artificial areas in high resolution remote sensing images based on multi-scale and multi feature fusion is proposed. Firstly, the geometric features such as corner, straight line and right angle are extracted from the original resolution, and the pseudo corner points, pseudo linear features and pseudo orthogonal angles are filtered out by the self-constraint and mutual restraint between them. Then the radiation intensity map of the image with high geometric characteristics is obtained by the linear inverse distance weighted method. Secondly, the original image is reduced to multiple scales and the visual saliency image of each scale is obtained by adaptive weighting of the orthogonal saliency, the local brightness and contrast which are calculated at the corresponding scale. Then the final visual saliency image is obtained by fusing all scales' visual saliency images. Thirdly, the visual saliency images of artificial areas based on multi scales and multi features are obtained by fusing the geometric feature energy intensity map and visual saliency image obtained in previous decision level. Finally, the artificial areas can be segmented based on the method called OTSU. Experiments show that the method in this paper not only can detect large artificial areas such as urban city, residential district, but also detect the single family house in the countryside correctly. The detection rate of artificial areas reached 92 %.

  8. Uncertainty and Climate Change and its effect on Generalization and Prediction abilities by creating Diverse Classifiers and Feature Section Methods using Information Fusion

    Directory of Open Access Journals (Sweden)

    Y. P. Kosta

    2010-11-01

    Full Text Available The model forecast suggests a deterministic approach. Forecasting was traditionally done by a singlemodel - deterministic prediction, recent years has witnessed drastic changes. Today, with InformationFusion (Ensemble technique it is possible to improve the generalization ability of classifiers with highlevels of reliability. Through Information Fusion it is easily possible to combine diverse & independentoutcomes for decision-making. This approach adopts the idea of combining the results of multiplemethods (two-way interactions between them using appropriate model on the testset. Althoughuncertainties are often very significant, for the purpose of single prediction, especially at the initialstage, one dose not consider uncertainties in the model, the initial conditions, or the very nature of theclimate (environment or atmosphere itself using single model. If we make small changes in the initialparameter setting, it will result in change in predictive accuracy of the model. Similarly, uncertainty inmodel physics can result in large forecast differences and errors. So, instead of running one prediction,run a collection/package/bundle (ensemble of predictions, each one kick starting from a different initialstate or with different conditions and sequentially executing the next. The variations resulting due toexecution of different prediction package/model could be then used (independently combining oraggregating to estimate the uncertainty of the prediction, giving us better accuracy and reliability. Inthis paper the authors propose to use Information fusion technique that will provide insight of probablekey parameters that is necessary to purposefully evaluate the successes of new generation of productsand services, improving forecasting. Ensembles can be creatively applied to provide insight against thenew generation products yielding higher probabilities of success. Ensemble will yield critical features ofthe products and also provide insight to

  9. Nanofluid Applied Numerical Analysis of Subchannel in Square Rod Bundle for Fusion-Fission Hybrid System

    Energy Technology Data Exchange (ETDEWEB)

    Shamim, Jubair Ahmed; Bhowmik, Palash Kumar; Suh, Kune Y. [Seoul National Univ., Seoul (Korea, Republic of)

    2014-05-15

    Most of the traditional ways available in the literature to enhance heat transfer are mainly based on variation of structures like addition of heat surface area such as fins, vibration of heated surface, injection or suction of fluids, applying electrical or magnetic fields, and so forth. Application of these mechanical techniques to a fuel rod bundle will involve not only designing complex geometries but also using many additional mechanisms inside a nuclear reactor core which in turn will certainly increase the manufacturing cost as well as may hamper various safety features essential for sound and uninterrupted operation of a nuclear power reactor. On the other hand, traditional heat transfer fluids such as water, ethylene glycol and oils have inherently low thermal conductivity relative to metals and even metal oxides. In this study the coolant with suspended nano-sized particles in the base fluid is proposed as an alternative to increase heat transfer but minimize flow resistance inside a nuclear reactor core. Due to technical complexities most of the previous studies carried out on heat transfer of suspension of metal oxides in fluids were limited to suspensions with millimeter or micron-sized particles. Such outsized particles may lead to severe problems in heat transfer equipment including increased pressure drop and corrosion and erosion of components and pipe lines. Dramatic advancement in modern science has made it possible to produce ultrafine metallic or nonmetallic particles of nanometer dimension, which has brought a revolutionary change in the research of heat transfer enhancement methods. Due to very tiny particle size and their small volume fraction, problems such as clogging and increased pressure drop are insignificant for nanofluids. Moreover, the relatively large surface area of nanoparticles augments the stability of nanofluid solution and prevents the sedimentation of nanoparticles. Xuan and Roetzel considered two approaches to illustrate

  10. Ensemble Classifier Strategy Based on Transient Feature Fusion in Electronic Nose

    Science.gov (United States)

    Bagheri, Mohammad Ali; Montazer, Gholam Ali

    2011-09-01

    In this paper, we test the performance of several ensembles of classifiers and each base learner has been trained on different types of extracted features. Experimental results show the potential benefits introduced by the usage of simple ensemble classification systems for the integration of different types of transient features.

  11. New image fusion method applied in two-wavelength detection of biochip spots

    Science.gov (United States)

    Chang, Rang-Seng; Sheu, Jin-Yi; Lin, Ching-Huang

    2001-09-01

    In the biological systems genetic information is read, stored, modified, transcribed and translated using the rule of molecular recognition. Every nucleic acid strand carries the capacity to recognize complementary sequences through base paring. Molecular biologists commonly use the DNA probes with known sequence to identify the unknown sequence through hybridization. There are many different detection methods for the hybridization results on a genechip. Fluorescent detection is a conventional method. The data analysis based on the fluorescent images and database establishment is necessary for treatment of such a large-amount obtained from a genechip. The unknown sequence has labeled with fluorescent material. Since the excitation and emission band is not a theoretical narrow band. There is a different in emission windows for different microscope. Therefore the data reading is different for different microscope. We combine two narrow band emission data and take it as two wavelengths from one fluorescence. Which by corresponding UV light excitation after we read the fluorescent intensity distribution of two microscope wavelengths for same hybridization DNA sequence spot, we will use image fusion technology to get best resultsDWe introduce a contrast and aberration correction image fusion method by using discrete wavelet transform to two wavelengths identification microarray biochip. This method includes two parts. First, the multiresolution analysis of the two input images are obtained by the discrete wavelet transform, from the ratio of high frequencies to the low frequency on the corresponding spatial resolution level, the directive contrast can be estimated by selecting the suitable subband signals of each input image. The fused image is reconstructed using the inverse wavelet transform.

  12. Built-up Areas Extraction in High Resolution SAR Imagery based on the method of Multiple Feature Weighted Fusion

    Science.gov (United States)

    Liu, X.; Zhang, J. X.; Zhao, Z.; Ma, A. D.

    2015-06-01

    Synthetic aperture radar in the application of remote sensing technology is becoming more and more widely because of its all-time and all-weather operation, feature extraction research in high resolution SAR image has become a hot topic of concern. In particular, with the continuous improvement of airborne SAR image resolution, image texture information become more abundant. It's of great significance to classification and extraction. In this paper, a novel method for built-up areas extraction using both statistical and structural features is proposed according to the built-up texture features. First of all, statistical texture features and structural features are respectively extracted by classical method of gray level co-occurrence matrix and method of variogram function, and the direction information is considered in this process. Next, feature weights are calculated innovatively according to the Bhattacharyya distance. Then, all features are weighted fusion. At last, the fused image is classified with K-means classification method and the built-up areas are extracted after post classification process. The proposed method has been tested by domestic airborne P band polarization SAR images, at the same time, two groups of experiments based on the method of statistical texture and the method of structural texture were carried out respectively. On the basis of qualitative analysis, quantitative analysis based on the built-up area selected artificially is enforced, in the relatively simple experimentation area, detection rate is more than 90%, in the relatively complex experimentation area, detection rate is also higher than the other two methods. In the study-area, the results show that this method can effectively and accurately extract built-up areas in high resolution airborne SAR imagery.

  13. Applied behavior analysis as intervention for autism: definition, features and philosophical concepts

    Directory of Open Access Journals (Sweden)

    Síglia Pimentel Höher Camargo

    2013-11-01

    Full Text Available Autism spectrum disorder (ASD is a lifelong pervasive developmental disorder with no known causes and cure. However, educational and behavioral interventions with a foundation in applied behavior analysis (ABA have been shown to improve a variety of skill areas such as communication, social, academic, and adaptive behaviors of individuals with ASD. The goal of this work is to present the definition, features and philosophical concepts that underlie ABA and make this science an effective intervention method for people with autism.

  14. Examining applying high performance genetic data feature selection and classification algorithms for colon cancer diagnosis.

    Science.gov (United States)

    Al-Rajab, Murad; Lu, Joan; Xu, Qiang

    2017-07-01

    This paper examines the accuracy and efficiency (time complexity) of high performance genetic data feature selection and classification algorithms for colon cancer diagnosis. The need for this research derives from the urgent and increasing need for accurate and efficient algorithms. Colon cancer is a leading cause of death worldwide, hence it is vitally important for the cancer tissues to be expertly identified and classified in a rapid and timely manner, to assure both a fast detection of the disease and to expedite the drug discovery process. In this research, a three-phase approach was proposed and implemented: Phases One and Two examined the feature selection algorithms and classification algorithms employed separately, and Phase Three examined the performance of the combination of these. It was found from Phase One that the Particle Swarm Optimization (PSO) algorithm performed best with the colon dataset as a feature selection (29 genes selected) and from Phase Two that the Support Vector Machine (SVM) algorithm outperformed other classifications, with an accuracy of almost 86%. It was also found from Phase Three that the combined use of PSO and SVM surpassed other algorithms in accuracy and performance, and was faster in terms of time analysis (94%). It is concluded that applying feature selection algorithms prior to classification algorithms results in better accuracy than when the latter are applied alone. This conclusion is important and significant to industry and society. Copyright © 2017 Elsevier B.V. All rights reserved.

  15. Image Fusion Based on the Self-Organizing Feature Map Neural Networks

    Institute of Scientific and Technical Information of China (English)

    ZHANG Zhaoli; SUN Shenghe

    2001-01-01

    This paper presents a new image datafusion scheme based on the self-organizing featuremap (SOFM) neural networks.The scheme consists ofthree steps:(1) pre-processing of the images,whereweighted median filtering removes part of the noisecomponents corrupting the image,(2) pixel clusteringfor each image using two-dimensional self-organizingfeature map neural networks,and (3) fusion of the im-ages obtained in Step (2) utilizing fuzzy logic,whichsuppresses the residual noise components and thusfurther improves the image quality.It proves thatsuch a three-step combination offers an impressive ef-fectiveness and performance improvement,which isconfirmed by simulations involving three image sen-sors (each of which has a different noise structure).

  16. Multibiometrics Belief Fusion

    CERN Document Server

    Kisku, Dakshina Ranjan; Gupta, Phalguni

    2010-01-01

    This paper proposes a multimodal biometric system through Gaussian Mixture Model (GMM) for face and ear biometrics with belief fusion of the estimated scores characterized by Gabor responses and the proposed fusion is accomplished by Dempster-Shafer (DS) decision theory. Face and ear images are convolved with Gabor wavelet filters to extracts spatially enhanced Gabor facial features and Gabor ear features. Further, GMM is applied to the high-dimensional Gabor face and Gabor ear responses separately for quantitive measurements. Expectation Maximization (EM) algorithm is used to estimate density parameters in GMM. This produces two sets of feature vectors which are then fused using Dempster-Shafer theory. Experiments are conducted on multimodal database containing face and ear images of 400 individuals. It is found that use of Gabor wavelet filters along with GMM and DS theory can provide robust and efficient multimodal fusion strategy.

  17. Secured Cryptographic Key Generation From Multimodal Biometrics Feature Level Fusion Of Fingerprint And Iris

    CERN Document Server

    Jagadeesan, A

    2010-01-01

    Human users have a tough time remembering long cryptographic keys. Hence, researchers, for so long, have been examining ways to utilize biometric features of the user instead of a memorable password or passphrase, in an effort to generate strong and repeatable cryptographic keys. Our objective is to incorporate the volatility of the users biometric features into the generated key, so as to make the key unguessable to an attacker lacking significant knowledge of the users biometrics. We go one step further trying to incorporate multiple biometric modalities into cryptographic key generation so as to provide better security. In this article, we propose an efficient approach based on multimodal biometrics (Iris and fingerprint) for generation of secure cryptographic key. The proposed approach is composed of three modules namely, 1) Feature extraction, 2) Multimodal biometric template generation and 3) Cryptographic key generation. Initially, the features, minutiae points and texture properties are extracted from...

  18. Secured Cryptographic Key Generation From Multimodal Biometrics: Feature Level Fusion of Fingerprint and Iris

    CERN Document Server

    Jagadeesan, A

    2010-01-01

    Human users have a tough time remembering long cryptographic keys. Hence, researchers, for so long, have been examining ways to utilize biometric features of the user instead of a memorable password or passphrase, in an effort to generate strong and repeatable cryptographic keys. Our objective is to incorporate the volatility of the user's biometric features into the generated key, so as to make the key unguessable to an attacker lacking significant knowledge of the user's biometrics. We go one step further trying to incorporate multiple biometric modalities into cryptographic key generation so as to provide better security. In this article, we propose an efficient approach based on multimodal biometrics (Iris and fingerprint) for generation of secure cryptographic key. The proposed approach is composed of three modules namely, 1) Feature extraction, 2) Multimodal biometric template generation and 3) Cryptographic key generation. Initially, the features, minutiae points and texture properties are extracted fr...

  19. Selection of clinical features for pattern recognition applied to gait analysis.

    Science.gov (United States)

    Altilio, Rosa; Paoloni, Marco; Panella, Massimo

    2017-04-01

    This paper deals with the opportunity of extracting useful information from medical data retrieved directly from a stereophotogrammetric system applied to gait analysis. A feature selection method to exhaustively evaluate all the possible combinations of the gait parameters is presented, in order to find the best subset able to classify among diseased and healthy subjects. This procedure will be used for estimating the performance of widely used classification algorithms, whose performance has been ascertained in many real-world problems with respect to well-known classification benchmarks, both in terms of number of selected features and classification accuracy. Precisely, support vector machine, Naive Bayes and K nearest neighbor classifiers can obtain the lowest classification error, with an accuracy greater than 97 %. For the considered classification problem, the whole set of features will be proved to be redundant and it can be significantly pruned. Namely, groups of 3 or 5 features only are able to preserve high accuracy when the aim is to check the anomaly of a gait. The step length and the swing speed are the most informative features for the gait analysis, but also cadence and stride may add useful information for the movement evaluation.

  20. Context-dependent feature selection using unsupervised contexts applied to GPR-based landmine detection

    Science.gov (United States)

    Ratto, Christopher R.; Torrione, Peter A.; Collins, Leslie M.

    2010-04-01

    Context-dependent classification techniques applied to landmine detection with ground-penetrating radar (GPR) have demonstrated substantial performance improvements over conventional classification algorithms. Context-dependent algorithms compute a decision statistic by integrating over uncertainty in the unknown, but probabilistically inferable, context of the observation. When applied to GPR, contexts may be defined by differences in electromagnetic properties of the subsurface environment, which are due to discrepancies in soil composition, moisture levels, and surface texture. Context-dependent Feature Selection (CDFS) is a technique developed for selecting a unique subset of features for classifying landmines from clutter in different environmental contexts. In past work, context definitions were assumed to be soil moisture conditions which were known during training. However, knowledge of environmental conditions could be difficult to obtain in the field. In this paper, we utilize an unsupervised learning algorithm for defining contexts which are unknown a priori. Our method performs unsupervised context identification based on similarities in physics-based and statistical features that characterize the subsurface environment of the raw GPR data. Results indicate that utilizing this contextual information improves classification performance, and provides performance improvements over non-context-dependent approaches. Implications for on-line context identification will be suggested as a possible avenue for future work.

  1. MRI and PET Image Fusion Using Fuzzy Logic and Image Local Features

    Directory of Open Access Journals (Sweden)

    Umer Javed

    2014-01-01

    to maximally combine useful information present in MRI and PET images. Image local features are extracted and combined with fuzzy logic to compute weights for each pixel. Simulation results show that the proposed scheme produces significantly better results compared to state-of-art schemes.

  2. Web News Extraction via Tag Path Feature Fusion Using DS Theory

    Institute of Scientific and Technical Information of China (English)

    Gong-Qing Wu; Lei Li; Li Li; Xindong Wu

    2016-01-01

    Contents, layout styles, and parse structures of web news pages differ greatly from one page to another. In addition, the layout style and the parse structure of a web news page may change from time to time. For these reasons, how to design features with excellent extraction performances for massive and heterogeneous web news pages is a challenging issue. Our extensive case studies indicate that there is potential relevancy between web content layouts and their tag paths. Inspired by the observation, we design a series of tag path extraction features to extract web news. Because each feature has its own strength, we fuse all those features with the DS (Dempster-Shafer) evidence theory, and then design a content extraction method CEDS. Experimental results on both CleanEval datasets and web news pages selected randomly from well-known websites show that the F1-score with CEDS is 8.08%and 3.08%higher than existing popular content extraction methods CETR and CEPR-TPR respectively.

  3. Analysis of Image Fusion Techniques for fingerprint Palmprint Multimodal Biometric System

    Directory of Open Access Journals (Sweden)

    S. Anu H Naira

    2015-01-01

    Full Text Available The multimodal Biometric System using multiple sources of information has been widely recognized. However computational models for multimodal biometrics recognition have only recently received attention. In this paper the fingerprint and palmprint images are chosen and fused together using image fusion methods. The biometric features are subjected to modality extraction. Different fusion methods like average fusion, minimum fusion, maximum fusion, discrete wavelet transform fusion and stationary wavelet transformfusion are implemented for the fusion of extracting modalities. The best fused template is analyzed by applying various fusion metrics. Here the DWT fused image provided better results.

  4. Extended feature-fusion guidelines to improve image-based multi-modal biometrics

    CSIR Research Space (South Africa)

    Brown, Dane

    2016-09-01

    Full Text Available and rotation invariant tex- ture classification compared with Eigen and Fisher [2]. Training the advanced histogram model is also signifi- cantly faster than the former two methods. Furthermore, the training time is independent of the image resolution... at the feature-level compared to the matching score-level. Other face, fingerprint and palmprint studies include [13] and [23], which both use a Curvelet transform followed by SVM classification. However, these studies were tested using datasets...

  5. Effect of particle pinch on the fusion performance and profile features of an international thermonuclear experimental reactor-like fusion reactor

    Science.gov (United States)

    Wang, Shijia; Wang, Shaojie

    2015-04-01

    The evolution of the plasma temperature and density in an international thermonuclear experimental reactor (ITER)-like fusion device has been studied by numerically solving the energy transport equation coupled with the particle transport equation. The effect of particle pinch, which depends on the magnetic curvature and the safety factor, has been taken into account. The plasma is primarily heated by the alpha particles which are produced by the deuterium-tritium fusion reactions. A semi-empirical method, which adopts the ITERH-98P(y,2) scaling law, has been used to evaluate the transport coefficients. The fusion performances (the fusion energy gain factor, Q) similar to the ITER inductive scenario and non-inductive scenario (with reversed magnetic shear) are obtained. It is shown that the particle pinch has significant effects on the fusion performance and profiles of a fusion reactor. When the volume-averaged density is fixed, particle pinch can lower the pedestal density by ˜30 % , with the Q value and the central pressure almost unchanged. When the particle source or the pedestal density is fixed, the particle pinch can significantly enhance the Q value by 60 % , with the central pressure also significantly raised.

  6. Fusion programs in applied plasma physics. Technical progress report, July 11, 1992--May 31, 1993

    Energy Technology Data Exchange (ETDEWEB)

    1993-07-01

    This report summarizes the progress made in theoretical and experimental research funded by US Department of Energy Grant No. DE-FG03-92ER54150, during the period July 11, 1992 through May 31, 1993. Four main tasks are reported: applied plasma physics theory, alpha particle diagnostic, edge and current density diagnostic, and plasma rotation drive. The report also discusses the research plans for the theory and experimental programs for the next grant year. Reports and publications supported by the grant during this period are listed in the final section.

  7. Fusion neutronics

    CERN Document Server

    Wu, Yican

    2017-01-01

    This book provides a systematic and comprehensive introduction to fusion neutronics, covering all key topics from the fundamental theories and methodologies, as well as a wide range of fusion system designs and experiments. It is the first-ever book focusing on the subject of fusion neutronics research. Compared with other nuclear devices such as fission reactors and accelerators, fusion systems are normally characterized by their complex geometry and nuclear physics, which entail new challenges for neutronics such as complicated modeling, deep penetration, low simulation efficiency, multi-physics coupling, etc. The book focuses on the neutronics characteristics of fusion systems and introduces a series of theories and methodologies that were developed to address the challenges of fusion neutronics, and which have since been widely applied all over the world. Further, it introduces readers to neutronics design’s unique principles and procedures, experimental methodologies and technologies for fusion systems...

  8. Sensor Data Fusion

    DEFF Research Database (Denmark)

    Plascencia, Alfredo; Stepán, Petr

    2006-01-01

    The main contribution of this paper is to present a sensor fusion approach to scene environment mapping as part of a Sensor Data Fusion (SDF) architecture. This approach involves combined sonar array with stereo vision readings.  Sonar readings are interpreted using probability density functions...... to the occupied and empty regions. Scale Invariant Feature Transform (SIFT) feature descriptors are interpreted using gaussian probabilistic error models. The use of occupancy grids is proposed for representing the sensor readings. The Bayesian estimation approach is applied to update the sonar array......  and the SIFT descriptors' uncertainty grids. The sensor fusion yields a significant reduction in the uncertainty of the occupancy grid compared to the individual sensor readings....

  9. Applying Improved Multiscale Fuzzy Entropy for Feature Extraction of MI-EEG

    Directory of Open Access Journals (Sweden)

    Ming-ai Li

    2017-01-01

    Full Text Available Electroencephalography (EEG is considered the output of a brain and it is a bioelectrical signal with multiscale and nonlinear properties. Motor Imagery EEG (MI-EEG not only has a close correlation with the human imagination and movement intention but also contains a large amount of physiological or disease information. As a result, it has been fully studied in the field of rehabilitation. To correctly interpret and accurately extract the features of MI-EEG signals, many nonlinear dynamic methods based on entropy, such as Approximate Entropy (ApEn, Sample Entropy (SampEn, Fuzzy Entropy (FE, and Permutation Entropy (PE, have been proposed and exploited continuously in recent years. However, these entropy-based methods can only measure the complexity of MI-EEG based on a single scale and therefore fail to account for the multiscale property inherent in MI-EEG. To solve this problem, Multiscale Sample Entropy (MSE, Multiscale Permutation Entropy (MPE, and Multiscale Fuzzy Entropy (MFE are developed by introducing scale factor. However, MFE has not been widely used in analysis of MI-EEG, and the same parameter values are employed when the MFE method is used to calculate the fuzzy entropy values on multiple scales. Actually, each coarse-grained MI-EEG carries the characteristic information of the original signal on different scale factors. It is necessary to optimize MFE parameters to discover more feature information. In this paper, the parameters of MFE are optimized independently for each scale factor, and the improved MFE (IMFE is applied to the feature extraction of MI-EEG. Based on the event-related desynchronization (ERD/event-related synchronization (ERS phenomenon, IMFE features from multi channels are fused organically to construct the feature vector. Experiments are conducted on a public dataset by using Support Vector Machine (SVM as a classifier. The experiment results of 10-fold cross-validation show that the proposed method yields

  10. 基于多尺度特征融合的SAR图像分割%SAR image segmentation based on multi-scale feature fusion

    Institute of Scientific and Technical Information of China (English)

    宁慧君; 李映; 胡杰

    2011-01-01

    SAR image segmentation is complicated due to the multiplicative nature of the speckle noise in SAR images.An SAR image segmentation method based on the multi-scale feature fusion is proposed in this paper. The fast discrete curvelet transform is applied to extract the image texture features,and the stationary wavelet transform is applied to extract the image statistical features. These two multi-scale features are fused to obtain a high dimensional feature vector. The fuzzy C-means clustering is used to segment the image. Experiments are carried out using typical noise-free image corrupted with simulated speckle noise as well as real SAR images,and the results show that the proposed method performs favorably in comparison to the methods based on the wavelet transform only. The proposed segmentation method can delete lots of small fragments in the homogeneous regions and obtain more accurate and smooth boundaries.%由于存在相干斑噪声的影响,给SAR图像分割造成很大的困难,提出一种基于多尺度特征融合的SAR图像分割方法.该方法利用快速离散curvelet变换提取图像的纹理特征,利用平稳小波变换提取图像的统计特征,将两种多尺度特征融合成高维的特征向量,采用模糊C均值聚类的方法进行分割.在仿真SAR图像和真实SAR图像的分割实验结果表明,提出的方法优于单独采用小波变换进行SAR图像分割的方法,在消除均质区内碎块的同时,使得边界更为精准和平滑.

  11. Ziyuan-3 Multi-Spectral and Panchromatic Images Fusion Quality Assessment: Applied to Jiangsu Coastal Area, China

    Science.gov (United States)

    Wu, Ruijuan; He, Xiufeng

    2014-11-01

    A comprehensive fusion quality assessment was proposed, which based on cross entropy and structure similarity with weighted value, it was used to evaluate the fusion effort of Chinese Ziyuan-3 multi-spectral and panchromatic images from coastal areas, Jiangsu province, China. Fusion algorithms were used, Hue-Intensity-Saturation (HIS), àtrous Wavelet Transformation (AWT), NonsubSampled Contourlet Transform (NSCT), and combined NSCT with HIS. According to visual interpretation, the quality of fused imaged based on combined NSCT with HIS is better than another fusion methods, fusion quality results exploring our proposed image fusion quality assessment also illustrated that fused image of combined NSCT with HIS is the best, which is consistent with human- being subjective interpretation.

  12. Ziyuan-2 Multi-Spectral and Panchromatic Images Fusion Quality Assessment: Applied to Jiangsu Coastal Area, China

    Science.gov (United States)

    Wu, Ruijuan; He, Xiufeng

    2014-11-01

    A comprehensive fusion quality assessment was proposed, which based on cross entropy and structure similarity with weighted value, it was used to evaluate the fusion effort of Chinese Ziyuan-3 multi-spectral and panchromatic images from coastal areas, Jiangsu province, China. Fusion algorithms were used, Hue-Intensity-Saturation (HIS), à trous Wavelet Transformation (AWT), Nonsub Sampled Contourlet Transform (NSCT), and combined NSCT with HIS. According to visual interpretation, the quality of fused imaged based on combined NSCT with HIS is better than another fusion methods, fusion quality results exploring our proposed image fusion quality assessment also illustrated that fused image of combined NSCT with HIS is the best, which is consistent with human-being subjective interpretation.

  13. Data-driven technology for engineering systems health management design approach, feature construction, fault diagnosis, prognosis, fusion and decisions

    CERN Document Server

    Niu, Gang

    2017-01-01

    This book introduces condition-based maintenance (CBM)/data-driven prognostics and health management (PHM) in detail, first explaining the PHM design approach from a systems engineering perspective, then summarizing and elaborating on the data-driven methodology for feature construction, as well as feature-based fault diagnosis and prognosis. The book includes a wealth of illustrations and tables to help explain the algorithms, as well as practical examples showing how to use this tool to solve situations for which analytic solutions are poorly suited. It equips readers to apply the concepts discussed in order to analyze and solve a variety of problems in PHM system design, feature construction, fault diagnosis and prognosis.

  14. Automated EEG artifact elimination by applying machine learning algorithms to ICA-based features

    Science.gov (United States)

    Radüntz, Thea; Scouten, Jon; Hochmuth, Olaf; Meffert, Beate

    2017-08-01

    Objective. Biological and non-biological artifacts cause severe problems when dealing with electroencephalogram (EEG) recordings. Independent component analysis (ICA) is a widely used method for eliminating various artifacts from recordings. However, evaluating and classifying the calculated independent components (IC) as artifact or EEG is not fully automated at present. Approach. In this study, we propose a new approach for automated artifact elimination, which applies machine learning algorithms to ICA-based features. Main results. We compared the performance of our classifiers with the visual classification results given by experts. The best result with an accuracy rate of 95% was achieved using features obtained by range filtering of the topoplots and IC power spectra combined with an artificial neural network. Significance. Compared with the existing automated solutions, our proposed method is not limited to specific types of artifacts, electrode configurations, or number of EEG channels. The main advantages of the proposed method is that it provides an automatic, reliable, real-time capable, and practical tool, which avoids the need for the time-consuming manual selection of ICs during artifact removal.

  15. Weighted Attribute Fusion Model for Face Recognition

    CERN Document Server

    Sakthivel, S

    2010-01-01

    Recognizing a face based on its attributes is an easy task for a human to perform as it is a cognitive process. In recent years, Face Recognition is achieved with different kinds of facial features which were used separately or in a combined manner. Currently, Feature fusion methods and parallel methods are the facial features used and performed by integrating multiple feature sets at different levels. However, this integration and the combinational methods do not guarantee better result. Hence to achieve better results, the feature fusion model with multiple weighted facial attribute set is selected. For this feature model, face images from predefined data set has been taken from Olivetti Research Laboratory (ORL) and applied on different methods like Principal Component Analysis (PCA) based Eigen feature extraction technique, Discrete Cosine Transformation (DCT) based feature extraction technique, Histogram Based Feature Extraction technique and Simple Intensity based features. The extracted feature set obt...

  16. A new feature extraction method for signal classification applied to cord dorsum potentials detection

    Science.gov (United States)

    Vidaurre, D.; Rodríguez, E. E.; Bielza, C.; Larrañaga, P.; Rudomin, P.

    2012-01-01

    In the spinal cord of the anesthetized cat, spontaneous cord dorsum potentials (CDPs) appear synchronously along the lumbo-sacral segments. These CDPs have different shapes and magnitudes. Previous work has indicated that some CDPs appear to be specially associated with the activation of spinal pathways that lead to primary afferent depolarization and presynaptic inhibition. Visual detection and classification of these CDPs provides relevant information on the functional organization of the neural networks involved in the control of sensory information and allows the characterization of the changes produced by acute nerve and spinal lesions. We now present a novel feature extraction approach for signal classification, applied to CDP detection. The method is based on an intuitive procedure. We first remove by convolution the noise from the CDPs recorded in each given spinal segment. Then, we assign a coefficient for each main local maximum of the signal using its amplitude and distance to the most important maximum of the signal. These coefficients will be the input for the subsequent classification algorithm. In particular, we employ gradient boosting classification trees. This combination of approaches allows a faster and more accurate discrimination of CDPs than is obtained by other methods. PMID:22929924

  17. A new feature extraction method for signal classification applied to cord dorsum potential detection

    Science.gov (United States)

    Vidaurre, D.; Rodríguez, E. E.; Bielza, C.; Larrañaga, P.; Rudomin, P.

    2012-10-01

    In the spinal cord of the anesthetized cat, spontaneous cord dorsum potentials (CDPs) appear synchronously along the lumbo-sacral segments. These CDPs have different shapes and magnitudes. Previous work has indicated that some CDPs appear to be specially associated with the activation of spinal pathways that lead to primary afferent depolarization and presynaptic inhibition. Visual detection and classification of these CDPs provides relevant information on the functional organization of the neural networks involved in the control of sensory information and allows the characterization of the changes produced by acute nerve and spinal lesions. We now present a novel feature extraction approach for signal classification, applied to CDP detection. The method is based on an intuitive procedure. We first remove by convolution the noise from the CDPs recorded in each given spinal segment. Then, we assign a coefficient for each main local maximum of the signal using its amplitude and distance to the most important maximum of the signal. These coefficients will be the input for the subsequent classification algorithm. In particular, we employ gradient boosting classification trees. This combination of approaches allows a faster and more accurate discrimination of CDPs than is obtained by other methods.

  18. Medical Image Fusion

    Directory of Open Access Journals (Sweden)

    Mitra Rafizadeh

    2007-08-01

    Full Text Available Technological advances in medical imaging in the past two decades have enable radiologists to create images of the human body with unprecedented resolution. MRI, PET,... imaging devices can quickly acquire 3D images. Image fusion establishes an anatomical correlation between corresponding images derived from different examination. This fusion is applied either to combine images of different modalities (CT, MRI or single modality (PET-PET."nImage fusion is performed in two steps:"n1 Registration: spatial modification (eg. translation of model image relative to reference image in order to arrive at an ideal matching of both images. Registration methods are feature-based and intensity-based approaches."n2 Visualization: the goal of it is to depict the spatial relationship between the model image and refer-ence image. We can point out its clinical application in nuclear medicine (PET/CT.

  19. 一种基于CLMF的深度卷积神经网络模型%Convolutional Neural Networks with Candidate Location and Multi-feature Fusion

    Institute of Scientific and Technical Information of China (English)

    随婷婷; 王晓峰

    2016-01-01

    针对传统人工特征提取模型难以满足复杂场景下目标识别的需求,提出了一种基于CLMF 的深度卷积神经网络(Convolutional neural networks with candidate location and multi-feature fusion, CLMF-CNN)。该模型结合视觉显著性、多特征融合和CNN模型实现目标对象的识别。首先,利用加权Itti模型获取目标候选区;然后,利用CNN模型从颜色、亮度多特征角度提取目标对象的特征,经过加权融合供目标识别;最后,与单一特征以及目前的流行算法进行对比实验,结果表明本文模型不仅在同等条件下正确识别率得到了提高,同时,达到实时性要求。%To solve the problem that the traditional manual feature extraction models are unable to satisfy object recognition in complex environment, an object recognition model based on convolutional neural networks with candidate location and multi-feature fusion (CLMF-CNN) model is proposed. The model combines the visual saliency, multi-feature fusion and CNN model to realize the object recognition. Firstly, the candidate objects are conformed via weighted Itti model. Consequently, color and intensity features are obtained via CNN model respectively. After the multi-feature fusion method, the features can be used for object recognition. Finally, the model is tested and compared with the single feature method and current popular algorithms. Experimental result in this paper proves that our method can not only get good performance in improving the accuracy of object recognition, but also satisfy real-time requirements.

  20. Hyperspectral remote sensing image classification based on decision level fusion

    Institute of Scientific and Technical Information of China (English)

    Peijun Du; Wei Zhang; Junshi Xia

    2011-01-01

    @@ To apply decision level fusion to hyperspectral remote sensing (HRS) image classification, three decision level fusion strategies are experimented on and compared, namely, linear consensus algorithm, improved evidence theory, and the proposed support vector machine (SVM) combiner.To evaluate the effects of the input features on classification performance, four schemes are used to organize input features for member classifiers.In the experiment, by using the operational modular imaging spectrometer (OMIS) II HRS image, the decision level fusion is shown as an effective way for improving the classification accuracy of the HRS image, and the proposed SVM combiner is especially suitable for decision level fusion.The results also indicate that the optimization of input features can improve the classification performance.%To apply decision level fusion to hyperspectral remote sensing (HRS) image classification, three decision level fusion strategies are experimented on and compared, namely, linear consensus algorithm, improved evidence theory, and the proposed support vector machine (SVM) combiner. To evaluate the effects of the input features on classification performance, four schemes are used to organize input features for member classifiers. In the experiment, by using the operational modular imaging spectrometer (OMIS) Ⅱ HRS image, the decision level fusion is shown as an effective way for improving the classification accuracy of the HRS image, and the proposed SVM combiner is especially suitable for decision level fusion. The results also indicate that the optimization of input features can improve the classification performance.

  1. Method of determining the process applied for feature machining : experimental validation of a slot

    OpenAIRE

    Martin, Patrick; D'ACUNTO, Alain

    2007-01-01

    International audience; In this paper, we will be evaluating the "manufacturability" levels for several machining processes of "slot" feature. Using the STEP standard, we will identify the slot feature characteristics. Then, using the ascendant generation of process method, we will define the associated milling process. The expertise is based on a methodology relative to the experience plans carried out during the formalization and systematic evaluation of the machining process associated wit...

  2. 基于分类性能的掌纹特征有机融合%PALMPRINT FEATURES FUSION IN ORGANIC WAY BASED ON CLASSIFICATION PERFORMANCE

    Institute of Scientific and Technical Information of China (English)

    李云峰; 张亚莉

    2012-01-01

    In order to overcome the limitation of palmprint recognition by using single feature, a method of palmprint multi-feature fusion in an organic way based on classification performance is proposed in this paper. This features fusion method is realised in three steps: the feature selection, the weighting processing and the dimension reduction processing. Based on analysing the clustering performance of each single fea ture component, the features' trade-off is carried out by constructing the criterion and set the corresponding threshold value; the weight value of each feature component is calculated by constructing the function of within-class distance and between-class distance, and the weighting processing is then performed; at last the principal components analysis (PCA) is used to reduce the dimension of the feature. The improved Local Binary Patterns (LBP) and Discrete Wavelet Transform ( DWT) are used to extract the two kinds of palmprint features, and these ex tracted features are used in fusion experiments, the results show the effectiveness of the method.%为了克服利用单一特征进行掌纹识别的局限性,提出一种基于分类性能的掌纹多特征有机融合方法.该特征融合方法通过三步来实现:特征选择、加权处理和降维处理.在分析单一特征分量聚类性能的基础上,通过构造判别准则并设定相应阈值对特征进行取舍;通过构造类内距离与类间距离之比这一函数计算得到每个特征分量的权值,然后进行加权处理;最后利用主分量分析法对特征进行降维处理.以改进的LBP算法和离散小波变换提取掌纹的两种特征,将提取的特征进行融合实验,结果表明了该方法的有效性.

  3. Feature Selection Applying Statistical and Neurofuzzy Methods to EEG-Based BCI.

    Science.gov (United States)

    Martinez-Leon, Juan-Antonio; Cano-Izquierdo, Jose-Manuel; Ibarrola, Julio

    2015-01-01

    This paper presents an investigation aimed at drastically reducing the processing burden required by motor imagery brain-computer interface (BCI) systems based on electroencephalography (EEG). In this research, the focus has moved from the channel to the feature paradigm, and a 96% reduction of the number of features required in the process has been achieved maintaining and even improving the classification success rate. This way, it is possible to build cheaper, quicker, and more portable BCI systems. The data set used was provided within the framework of BCI Competition III, which allows it to compare the presented results with the classification accuracy achieved in the contest. Furthermore, a new three-step methodology has been developed which includes a feature discriminant character calculation stage; a score, order, and selection phase; and a final feature selection step. For the first stage, both statistics method and fuzzy criteria are used. The fuzzy criteria are based on the S-dFasArt classification algorithm which has shown excellent performance in previous papers undertaking the BCI multiclass motor imagery problem. The score, order, and selection stage is used to sort the features according to their discriminant nature. Finally, both order selection and Group Method Data Handling (GMDH) approaches are used to choose the most discriminant ones.

  4. Cold nuclear fusion reactor and nuclear fusion rocket

    Directory of Open Access Journals (Sweden)

    Huang Zhenqiang

    2013-10-01

    Full Text Available "Nuclear restraint inertial guidance directly hit the cold nuclear fusion reactor and ion speed dc transformer" [1], referred to as "cold fusion reactor" invention patents, Chinese Patent Application No. CN: 200910129632.7 [2]. The invention is characterized in that: at room temperature under vacuum conditions, specific combinations of the installation space of the electromagnetic field, based on light nuclei intrinsic magnetic moment and the electric field, the first two strings of the nuclei to be bound fusion on the same line (track of. Re-use nuclear spin angular momentum vector inherent nearly the speed of light to form a super strong spin rotation gyro inertial guidance features, to overcome the Coulomb repulsion strong bias barrier to achieve fusion directly hit. Similar constraints apply nuclear inertial guidance mode for different speeds and energy ion beam mixing speed, the design of ion speed dc transformer is cold fusion reactors, nuclear fusion engines and such nuclear power plants and power delivery systems start important supporting equipment, so apply for a patent merger

  5. Computer Graphics Meets Image Fusion: the Power of Texture Baking to Simultaneously Visualise 3d Surface Features and Colour

    Science.gov (United States)

    Verhoeven, G. J.

    2017-08-01

    Since a few years, structure-from-motion and multi-view stereo pipelines have become omnipresent in the cultural heritage domain. The fact that such Image-Based Modelling (IBM) approaches are capable of providing a photo-realistic texture along the threedimensional (3D) digital surface geometry is often considered a unique selling point, certainly for those cases that aim for a visually pleasing result. However, this texture can very often also obscure the underlying geometrical details of the surface, making it very hard to assess the morphological features of the digitised artefact or scene. Instead of constantly switching between the textured and untextured version of the 3D surface model, this paper presents a new method to generate a morphology-enhanced colour texture for the 3D polymesh. The presented approach tries to overcome this switching between objects visualisations by fusing the original colour texture data with a specific depiction of the surface normals. Whether applied to the original 3D surface model or a lowresolution derivative, this newly generated texture does not solely convey the colours in a proper way but also enhances the smalland large-scale spatial and morphological features that are hard or impossible to perceive in the original textured model. In addition, the technique is very useful for low-end 3D viewers, since no additional memory and computing capacity are needed to convey relief details properly. Apart from simple visualisation purposes, the textured 3D models are now also better suited for on-surface interpretative mapping and the generation of line drawings.

  6. Conditional Variational Autoencoder for Prediction and Feature Recovery Applied to Intrusion Detection in IoT.

    Science.gov (United States)

    Lopez-Martin, Manuel; Carro, Belen; Sanchez-Esguevillas, Antonio; Lloret, Jaime

    2017-08-26

    The purpose of a Network Intrusion Detection System is to detect intrusive, malicious activities or policy violations in a host or host's network. In current networks, such systems are becoming more important as the number and variety of attacks increase along with the volume and sensitiveness of the information exchanged. This is of particular interest to Internet of Things networks, where an intrusion detection system will be critical as its economic importance continues to grow, making it the focus of future intrusion attacks. In this work, we propose a new network intrusion detection method that is appropriate for an Internet of Things network. The proposed method is based on a conditional variational autoencoder with a specific architecture that integrates the intrusion labels inside the decoder layers. The proposed method is less complex than other unsupervised methods based on a variational autoencoder and it provides better classification results than other familiar classifiers. More important, the method can perform feature reconstruction, that is, it is able to recover missing features from incomplete training datasets. We demonstrate that the reconstruction accuracy is very high, even for categorical features with a high number of distinct values. This work is unique in the network intrusion detection field, presenting the first application of a conditional variational autoencoder and providing the first algorithm to perform feature recovery.

  7. Cold nuclear fusion

    National Research Council Canada - National Science Library

    Huang Zhenqiang Huang Yuxiang

    2013-01-01

    ...... And with a magnetic moment of light nuclei controlled cold nuclear collide fusion, belongs to the nuclear energy research and development in the field of applied technology "cold nuclear collide fusion...

  8. A two-step fusion process for multi-criteria decision applied to natural hazards in mountains

    CERN Document Server

    Tacnet, Jean-Marc; Dezert, Jean

    2010-01-01

    Mountain river torrents and snow avalanches gen- erate human and material damages with dramatic consequences. Knowledge about natural phenomenona is often lacking and expertise is required for decision and risk management purposes using multi-disciplinary quantitative or qualitative approaches. Expertise is considered as a decision process based on imperfect information coming from more or less reliable and conflicting sources. A methodology mixing the Analytic Hierarchy Process (AHP), a multi-criteria aid-decision method, and information fusion using Belief Function Theory is described. Fuzzy Sets and Possibilities theories allow to transform quantitative and qualita- tive criteria into a common frame of discernment for decision in Dempster-Shafer Theory (DST ) and Dezert-Smarandache Theory (DSmT) contexts. Main issues consist in basic belief assignments elicitation, conflict identification and management, fusion rule choices, results validation but also in specific needs to make a difference between importa...

  9. Adaptive fusion of infrared and visible images in dynamic scene

    Science.gov (United States)

    Yang, Guang; Yin, Yafeng; Man, Hong; Desai, Sachi

    2011-11-01

    Multiple modalities sensor fusion has been widely employed in various surveillance and military applications. A variety of image fusion techniques including PCA, wavelet, curvelet and HSV has been proposed in recent years to improve human visual perception for object detection. One of the main challenges for visible and infrared image fusion is to automatically determine an optimal fusion strategy for different input scenes along with an acceptable computational cost. This paper, we propose a fast and adaptive feature selection based image fusion method to obtain high a contrast image from visible and infrared sensors for targets detection. At first, fuzzy c-means clustering is applied on the infrared image to highlight possible hotspot regions, which will be considered as potential targets' locations. After that, the region surrounding the target area is segmented as the background regions. Then image fusion is locally applied on the selected target and background regions by computing different linear combination of color components from registered visible and infrared images. After obtaining different fused images, histogram distributions are computed on these local fusion images as the fusion feature set. The variance ratio which is based on Linear Discriminative Analysis (LDA) measure is employed to sort the feature set and the most discriminative one is selected for the whole image fusion. As the feature selection is performed over time, the process will dynamically determine the most suitable feature for the image fusion in different scenes. Experiment is conducted on the OSU Color-Thermal database, and TNO Human Factor dataset. The fusion results indicate that our proposed method achieved a competitive performance compared with other fusion algorithms at a relatively low computational cost.

  10. Better than counting seconds: Identifying fallers among healthy elderly using fusion of accelerometer features and dual-task Timed Up and Go.

    Science.gov (United States)

    Ponti, Moacir; Bet, Patricia; Oliveira, Caroline L; Castro, Paula C

    2017-01-01

    Devices and sensors for identification of fallers can be used to implement actions to prevent falls and to allow the elderly to live an independent life while reducing the long-term care costs. In this study we aimed to investigate the accuracy of Timed Up and Go test, for fallers' identification, using fusion of features extracted from accelerometer data. Single and dual tasks TUG (manual and cognitive) were performed by a final sample (94% power) of 36 community dwelling healthy older persons (18 fallers paired with 18 non-fallers) while they wear a single triaxial accelerometer at waist with sampling rate of 200Hz. The segmentation of the TUG different trials and its comparative analysis allows to better discriminate fallers from non-fallers, while conventional functional tests fail to do so. In addition, we show that the fusion of features improve the discrimination power, achieving AUC of 0.84 (Sensitivity = Specificity = 0.83, 95% CI 0.62-0.91), and demonstrating the clinical relevance of the study. We concluded that features extracted from segmented TUG trials acquired with dual tasks has potential to improve performance when identifying fallers via accelerometer sensors, which can improve TUG accuracy for clinical and epidemiological applications.

  11. Better than counting seconds: Identifying fallers among healthy elderly using fusion of accelerometer features and dual-task Timed Up and Go

    Science.gov (United States)

    Bet, Patricia; Oliveira, Caroline L.; Castro, Paula C.

    2017-01-01

    Devices and sensors for identification of fallers can be used to implement actions to prevent falls and to allow the elderly to live an independent life while reducing the long-term care costs. In this study we aimed to investigate the accuracy of Timed Up and Go test, for fallers’ identification, using fusion of features extracted from accelerometer data. Single and dual tasks TUG (manual and cognitive) were performed by a final sample (94% power) of 36 community dwelling healthy older persons (18 fallers paired with 18 non-fallers) while they wear a single triaxial accelerometer at waist with sampling rate of 200Hz. The segmentation of the TUG different trials and its comparative analysis allows to better discriminate fallers from non-fallers, while conventional functional tests fail to do so. In addition, we show that the fusion of features improve the discrimination power, achieving AUC of 0.84 (Sensitivity = Specificity = 0.83, 95% CI 0.62-0.91), and demonstrating the clinical relevance of the study. We concluded that features extracted from segmented TUG trials acquired with dual tasks has potential to improve performance when identifying fallers via accelerometer sensors, which can improve TUG accuracy for clinical and epidemiological applications. PMID:28448509

  12. Quality assessment of ZiYuan-3 multispectral and panchromatic images fusion: applied in Jiangsu coastal wetland area, China

    Science.gov (United States)

    Wu, Ruijuan; He, Xiufeng; Wang, Jing

    2015-01-01

    The new launched ZiYuan-3 (ZY-3) satellite with multispectral (MS) bands and a panchromatic (PAN) band has presented a new opportunity to assess image fusion methods for coastal wetland mapping. This study focuses on image fusion quality assessment through both quantitative spectral and spatial quality analysis and object-oriented classification comparison. Various methods for pan-sharpening ZY-3 MS and PAN bands are tested, including generalized intensity-hue-saturation transform (GIHS), à trous wavelet transform (AWT), nonsubsampled contourlet transform (NSCT), and a combination of NSCT with GIHS (NSCT_GIHS). Spectral fidelity and spatial preservation of fused bands are compared with the original MS bands as reference, and spatial information injections of fused bands are compared with the resampled PAN band as reference. The fusion results demonstrate that, on average, the NSCT_GIHS method has the best performance on spectral fidelity and spatial preservation as well as spatial information injection. The near-infrared (NIR) band has the best spatial information injection in terms of entropy and cross-entropy indices, whereas the NIR band has the best spatial preservation in terms of entropy and structure similarity indices. The classification results show that NSCT_GIHS method also obtains the highest overall accuracy (96%) and Kappa coefficient (0.9425); this is in agreement with the quantitative analysis.

  13. FUSION OF WAVELET AND CURVELET COEFFICIENTS FOR GRAY TEXTURE CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    M. Santhanalakshmi

    2014-05-01

    Full Text Available This study presents a framework for gray texture classification based on the fusion of wavelet and curvelet features. The two main frequency domain transformations Discrete Wavelet Transform (DWT and Discrete Curvelet Transform (DCT are analyzed. The features are extracted from the DWT and DCT decomposed image separately and their performance is evaluated independently. Then feature fusion technique is applied to increase the classification accuracy of the proposed approach. Brodatz texture images are used for this study. The results show that, only two texture images D105 and D106 are misclassified by the fusion approach and 99.74% classification accuracy is obtained.

  14. Continuous wavelet transform-based feature selection applied to near-infrared spectral diagnosis of cancer.

    Science.gov (United States)

    Chen, Hui; Lin, Zan; Mo, Lin; Wu, Hegang; Wu, Tong; Tan, Chao

    2015-01-01

    Spectrum is inherently local in nature since it can be thought of as a signal being composed of various frequency components. Wavelet transform (WT) is a powerful tool that partitions a signal into components with different frequency. The property of multi-resolution enables WT a very effective and natural tool for analyzing spectrum-like signal. In this study, a continuous wavelet transform (CWT)-based variable selection procedure was proposed to search for a set of informative wavelet coefficients for constructing a near-infrared (NIR) spectral diagnosis model of cancer. The CWT provided a fine multi-resolution feature space for selecting best predictors. A measure of discriminating power (DP) was defined to evaluate the coefficients. Partial least squares-discriminant analysis (PLS-DA) was used as the classification algorithm. A NIR spectral dataset associated to cancer diagnosis was used for experiment. The optimal results obtained correspond to the wavelet of db2. It revealed that on condition of having better performance on the training set, the optimal PLS-DA model using only 40 wavelet coefficients in 10 scales achieved the same performance as the one using all the variables in the original space on the test set: an overall accuracy of 93.8%, sensitivity of 92.5% and specificity of 96.3%. It confirms that the CWT-based feature selection coupled with PLS-DA is feasible and effective for constructing models of diagnostic cancer by NIR spectroscopy.

  15. Methods of economic analysis applied to fusion research: discount rate determination and the fossil fuel price effect

    Energy Technology Data Exchange (ETDEWEB)

    1978-09-25

    In current and previous efforts, ECON has provided a preliminary economic assessment of a fusion research program. Part of this effort was the demonstration of a methodology for the estimation of reactor system costs and risk and for the treatment of program alternatives as a series of steps (tests) to buy information, thereby controlling program risk and providing a sound economic rationale for properly constructed research programs. The first phase of work also identified two areas which greatly affect the overall economic evaluation of fusion research and which warranted further study in the second phase. This led to the two tasks of the second phase reported herein: (1) discount rate determination and (2) evaluation of the effect of the expectation of the introduction of fusion power on current fossil fuel prices. In the first task, various conceptual measures of the social rate of discount were reviewed and critiqued. In the second task, a benefit area that had been called out by ECON was further examined. Long-range R and D yields short-term benefits in the form of lower nonrenewable energy resource prices because the R and D provides an expectation of future competition for the remaining reserves at the time of technology availability. ECON developed a model of optimal OPEC petroleum pricing as a function of the expectation of future competing technologies. It was shown that the existence of this expectation lowers the optimal OPEC export price and that accelerated technology R and D programs should provide further price decreases. These price reductions translate into benefits to the U.S. of at least a billion dollars.

  16. Selective Remote Sensing Image Fusion Method Based on the Local Feature of Contourlet Coefficients%基于Contourlet系数局部特征的选择性遥感图像融合算法

    Institute of Scientific and Technical Information of China (English)

    朱康; 贺新光

    2012-01-01

    为了使融合后的多光谱图像在显著提高空间分辨率的同时,尽可能多地保持原始多光谱特性,提出了一种基于Contourlet变换系数局部特征的选择性遥感图像融合方法.根据多光谱和全色图像融合过程中Contourlet变换后的低频和高频部分融合目的的不同,对得到的近似和各层各方向的细节分量分别运用窗口邻域移动模板逐一计算相应区域Contourlet系数阵的不同局部特征量,然后选择适当的准则,对图像的近似和细节分量分别应用不同的策略在Contourlet系数域内进行选择性融合,通过Contourlet和亮度-色调-饱和度(IHS)逆变换得到融合的高分辨率多光谱图像.采用Landsat TM多光谱和SPOT全色图像进行的融合实验结果表明:提出的算法在显著提高空间分辨率的同时,又能很好地保持原始图像的光谱特征,并优于传统的融合方法.%In order to remarkably improve the spatial resolution of the fused multispectral images and preserve the original multispectral characteristics as much as possible, a selective remote sensing image fusion method is proposed based on the local feature of contourlet coefficients. Firstly, a window neighborhood mobile template is used to calculate the different local features of corresponding contourlet coefficient matrix one by one for the approximate components and the detail components of each direction of each layer resulting from contourlet transform according to the different fusion purposes of low and high frequency parts in the fusion process of multi-spectral and panchromatic images. Then the approximate images and detail images are fused selectively in contourlet coefficients domain by applying different fusion rules based on proper criterion. The resultant image with high resolution and multi-spectral characteristics is obtained by inverse contourlet transform and inverse intensity-hue-saturation (HIS) transform. Landsat TM and SPOT images are used to

  17. Features of applying systems approach for evaluating the reliability of cryogenic systems for special purposes

    Directory of Open Access Journals (Sweden)

    E. D. Chertov

    2016-01-01

    Full Text Available Summary. The analysis of cryogenic installations confirms objective regularity of increase in amount of the tasks solved by systems of a special purpose. One of the most important directions of development of a cryogenics is creation of installations for air separation product receipt, namely oxygen and nitrogen. Modern aviation complexes require use of these gases in large numbers as in gaseous, and in the liquid state. The onboard gas systems applied in aircraft of the Russian Federation are subdivided on: oxygen system; air (nitric system; system of neutral gas; fire-proof system. Technological schemes ADI are in many respects determined by pressure of compressed air or, in a general sense, a refrigerating cycle. For the majority ADI a working body of a refrigerating cycle the divided air is, that is technological and refrigerating cycles in installation are integrated. By this principle differentiate installations: low pressure; average and high pressure; with detander; with preliminary chilling. There is also insignificant number of the ADI types in which refrigerating and technological cycles are separated. These are installations with external chilling. For the solution of tasks of control of technical condition of the BRV hardware in real time and estimates of indicators of reliability it is offered to use multi-agent technologies. Multi-agent approach is the most acceptable for creation of SPPR for reliability assessment as allows: to redistribute processing of information on elements of system that leads to increase in overall performance; to solve a problem of accumulating, storage and recycling of knowledge that will allow to increase significantly efficiency of the solution of tasks of an assessment of reliability; to considerably reduce intervention of the person in process of functioning of system that will save time of the person of the making decision (PMD and will not demand from it special skills of work with it.

  18. Remote Sensing Image Fusion Algorithm Based on Multi-Feature%基于多特征的遥感图像融合算法

    Institute of Scientific and Technical Information of China (English)

    王峰; 程咏梅; 李松; 牟宏磊; 李路东

    2015-01-01

    The remote sensing image fusion algorithm based on multiscale transform can not extract details from source images effectively; so a new remote sensing image fusion algorithm based on non⁃subsampled contourlet transform ( NSCT) domain is proposed. Firstly, the multi⁃spectral image was transformed into HSI ( Hue⁃Saturation⁃Intensity) color space, and the NSCT transform was employed to decompose the Intensity component and panchro⁃matic image into multiresolution representation;Secondly, the fusion rule of selecting maximum absolute pixel val⁃ues was used for the low frequency sub⁃band coefficients, while for the high frequency subband coefficients, the multi⁃feature fusion rule was designed; the fused image was reconstructed by inverse NSCT transform and inverse HSI transform. Experiments and their analysis show preliminarily that the fusion method proposed can improve spa⁃tial resolution and keep spectral information simultaneously and that there are improvements both in visual effects and quantitative analysis compared with the traditional HSI tansform method, the contourlet transform based fusion method, and the NSCT transform based fusion method.%针对基于多尺度几何变换的遥感图像融合算法细节表现能力不足的缺陷,提出了一种新的基于多特征的遥感图像融合算法。首先,对多光谱图像进行HSI变换,将得到的亮度分量和全色图像分别进行非下采样的Contourlet变换( NSCT),得到低频和高频子带系数;然后,对低频子带系数采用像素绝对值选大的规则进行融合,对于高频子带系数的选择,考虑到不同的因素如(方差、能量、平均梯度)对图像质量的影响不同,提出了一种基于多特征的融合规则;最后,对融合后的低频和高频系数分别进行了逆NSCT变换和逆HSI变换得到融合图像。实验结果证明,该方法可以有效将全色图像的空间信息注入到多光谱图像中,

  19. Research on Finger Crease Recognition Algorithm Based on Feature Fusion%基于特征融合的指节折痕识别算法研究

    Institute of Scientific and Technical Information of China (English)

    徐娟; 罗荣芳

    2015-01-01

    手指指节折痕同指纹和掌纹一样,具有唯一性、稳定性及可区分性的特点,可作为一种用于人体身份识别的生物特征。针对手指指节折痕的分布特征和形状特征,研究一种基于特征融合的指节折痕识别算法。首先利用Radon变换对指节折痕子图像进行变换,形成投影矩阵;其次利用奇异值分解方法对投影矩阵进行奇异值分解,从而形成指节折痕特征矢量;更进一步,考虑指节折痕特征比较简单的特点,重点研究了指节折痕的特征融合策略,用以描述指节折痕特征以达到最大的可区分性;此外定义了一种城区距离来衡量不同指节折痕特征之间的相似度,进行指节折痕特征匹配。最后在自建图像数据库中进行了测试,验证了算法的可行性及有效性。%As well as fingerprints and palmprint,finger crease has characteristics of uniqueness,stability and differentiation,it can be used as a biometric for human identification. According to the distribution and shape feature of finger crease, an algorithm for finger crease recognition based on feature fusion is researched. Firstly, using Radon Transform to transform finger crease sub image, the projection matrix is obtained. Secondly,using the Singular Value Decomposition method to decompose the projection matrix,the feature vector of finger crease is obtained. Furthermore,considering the simplicity of the finger crease,the feature fusion strategy is emphatically researched, which enable combined-feature to have the bigger distinctiveness. In addition, a city distance is defined to measure the similarity between different finger crease feature and the finger crease is matched by the City Block Distance. Finally, the test is performed with the self-built image database and the experimental results demonstrate that the algorithm proposed is feasible and effective.

  20. Canonical Correlation Analysis for Feature-Based Fusion of Biomedical Imaging Modalities and Its Application to Detection of Associative Networks in Schizophrenia.

    Science.gov (United States)

    Correa, Nicolle M; Li, Yi-Ou; Adalı, Tülay; Calhoun, Vince D

    2008-12-01

    Typically data acquired through imaging techniques such as functional magnetic resonance imaging (fMRI), structural MRI (sMRI), and electroencephalography (EEG) are analyzed separately. However, fusing information from such complementary modalities promises to provide additional insight into connectivity across brain networks and changes due to disease. We propose a data fusion scheme at the feature level using canonical correlation analysis (CCA) to determine inter-subject covariations across modalities. As we show both with simulation results and application to real data, multimodal CCA (mCCA) proves to be a flexible and powerful method for discovering associations among various data types. We demonstrate the versatility of the method with application to two datasets, an fMRI and EEG, and an fMRI and sMRI dataset, both collected from patients diagnosed with schizophrenia and healthy controls. CCA results for fMRI and EEG data collected for an auditory oddball task reveal associations of the temporal and motor areas with the N2 and P3 peaks. For the application to fMRI and sMRI data collected for an auditory sensorimotor task, CCA results show an interesting joint relationship between fMRI and gray matter, with patients with schizophrenia showing more functional activity in motor areas and less activity in temporal areas associated with less gray matter as compared to healthy controls. Additionally, we compare our scheme with an independent component analysis based fusion method, joint-ICA that has proven useful for such a study and note that the two methods provide complementary perspectives on data fusion.

  1. Group dynamics and landscape features constrain the exploration of herds in fusion-fission societies: the case of European roe deer.

    Directory of Open Access Journals (Sweden)

    Olivier Pays

    Full Text Available Despite the large number of movement studies, the constraints that grouping imposes on movement decisions remain essentially unexplored, even for highly social species. Such constraints could be key, however, to understanding the dynamics and spatial organisation of species living in group fusion-fission systems. We investigated the winter movements (speed and diffusion coefficient of groups of free-ranging roe deer (Capreolus capreolus, in an agricultural landscape characterised by a mosaic of food and foodless patches. Most groups were short-lived units that merged and split up frequently during the course of a day. Deer groups decreased their speed and diffusion rate in areas where food patches were abundant, as well as when travelling close to main roads and crest lines and far from forests. While accounting for these behavioural adjustments to habitat features, our study revealed some constraints imposed by group foraging: large groups reached the limit of their diffusion rate faster than small groups. The ability of individuals to move rapidly to new foraging locations following patch depression thus decreases with group size. Our results highlight the importance of considering both habitat heterogeneity and group dynamics when predicting the movements of individuals in group fusion-fission societies. Further, we provide empirical evidence that group cohesion can restrain movement and, therefore, the speed at which group members can explore their environment. When maintaining cohesion reduces foraging gains because of movement constraints, leaving the group may become a fitness-rewarding decision, especially when individuals can join other groups located nearby, which would tend to maintain highly dynamical group fusion-fission systems. Our findings also provide the basis for new hypotheses explaining a broad range of ecological patterns, such as the broader diet and longer residency time reported for larger herbivore groups.

  2. A method based on IHS cylindrical transform model for quality assessment of image fusion

    Science.gov (United States)

    Zhu, Xiaokun; Jia, Yonghong

    2005-10-01

    Image fusion technique has been widely applied to remote sensing image analysis and processing, and methods for quality assessment of image fusion in remote sensing have also become the research issues at home and abroad. Traditional assessment methods combine calculation of quantitative indexes and visual interpretation to compare fused images quantificationally and qualitatively. However, in the existing assessment methods, there are two defects: on one hand, most imdexes lack the theoretic support to compare different fusion methods. On the hand, there is not a uniform preference for most of the quantitative assessment indexes when they are applied to estimate the fusion effects. That is, the spatial resolution and spectral feature could not be analyzed synchronously by these indexes and there is not a general method to unify the spatial and spectral feature assessment. So in this paper, on the basis of the approximate general model of four traditional fusion methods, including Intensity Hue Saturation(IHS) triangle transform fusion, High Pass Filter(HPF) fusion, Principal Component Analysis(PCA) fusion, Wavelet Transform(WT) fusion, a correlation coefficient assessment method based on IHS cylindrical transform is proposed. By experiments, this method can not only get the evaluation results of spatial and spectral features on the basis of uniform preference, but also can acquire the comparison between fusion image sources and fused images, and acquire differences among fusion methods. Compared with the traditional assessment methods, the new methods is more intuitionistic, and in accord with subjective estimation.

  3. Features, events, processes, and safety factor analysis applied to a near-surface low-level radioactive waste disposal facility

    Energy Technology Data Exchange (ETDEWEB)

    Stephens, M.E.; Dolinar, G.M.; Lange, B.A. [Atomic Energy of Canada Limited, Ontario (Canada)] [and others

    1995-12-31

    An analysis of features, events, processes (FEPs) and other safety factors was applied to AECL`s proposed IRUS (Intrusion Resistant Underground Structure) near-surface LLRW disposal facility. The FEP analysis process which had been developed for and applied to high-level and transuranic disposal concepts was adapted for application to a low-level facility for which significant efforts in developing a safety case had already been made. The starting point for this process was a series of meetings of the project team to identify and briefly describe FEPs or safety factors which they thought should be considered. At this early stage participants were specifically asked not to screen ideas. This initial list was supplemented by selecting FEPs documented in other programs and comments received from an initial regulatory review. The entire list was then sorted by topic and common issues were grouped, and issues were classified in three priority categories and assigned to individuals for resolution. In this paper, the issue identification and resolution process will be described, from the initial description of an issue to its resolution and inclusion in the various levels of the safety case documentation.

  4. Multiple Feature Fusion Based on Co-Training Approach and Time Regularization for Place Classification in Wearable Video

    Directory of Open Access Journals (Sweden)

    Vladislavs Dovgalecs

    2013-01-01

    Full Text Available The analysis of video acquired with a wearable camera is a challenge that multimedia community is facing with the proliferation of such sensors in various applications. In this paper, we focus on the problem of automatic visual place recognition in a weakly constrained environment, targeting the indexing of video streams by topological place recognition. We propose to combine several machine learning approaches in a time regularized framework for image-based place recognition indoors. The framework combines the power of multiple visual cues and integrates the temporal continuity information of video. We extend it with computationally efficient semisupervised method leveraging unlabeled video sequences for an improved indexing performance. The proposed approach was applied on challenging video corpora. Experiments on a public and a real-world video sequence databases show the gain brought by the different stages of the method.

  5. Study of the feasibility of applying laser-induced breakdown spectroscopy for in-situ characterization of deposited layers in fusion devices

    Science.gov (United States)

    Huber, A.; Schweer, B.; Philipps, V.; Leyte-Gonzales, R.; Gierse, N.; Zlobinski, M.; Brezinsek, S.; Kotov, V.; Mertens, P.; Samm, U.; Sergienko, G.

    2011-12-01

    This paper presents a feasibility study of laser-induced breakdown spectroscopy (LIBS) for the development of an in-situ diagnostic for the characterization of deposition layers on plasma-facing components in fusion devices. Preferentially, LIBS would be applied in the presence of a toroidal magnetic field and under high vacuum conditions. The impact of the laser-energy densities on the laser-induced plasma parameters and correspondingly on the number of emitted photons and on the reproducibility of the LIBS method has been studied in laboratory experiments and in TEXTOR on fine-grain graphite (EK98) as well as on bulk W samples coated with carbon and metallic-containing deposits. The effect of magnetic fields and of ambient pressures in the range from 2×10-4 Pa to 10 Pa on the carbon plasma plume produced by the LIBS technique has been studied on TEXTOR between plasma pulses. The possibility of applying this method to ITER is discussed.

  6. User Emotion Recognition Based on Multidimensional Data Feature Fusion%多维数据特征融合的用户情绪识别

    Institute of Scientific and Technical Information of China (English)

    陈茜; 史殿习; 杨若松

    2016-01-01

    This paper studies the problem how to recognize the user emotion based on smartphone data more really. With single data used in the previous research, it cannot make a comprehensive response of user behavior patterns. So this paper collects fine-grained sensing data which can reflect user daily behavior fully from multiple dimensions based on smartphone, and then uses multidimensional data feature fusion method and six classification methods such as support vector machine (SVM) and random forest. Finally, this paper carries out contrast experiments with twelve volunteers’hybrid data and personal data respectively to recognize user emotion based on discrete emotion model and circumplex emotion model. The results show that the multidimensional data feature fusion method can reflect user be-havior comprehensively and presents high accuracy. After personal data training, the accuracy rate of emotion recogni-tion can reach 79.78%. In the experiments of different emotion models, the circumplex emotion model is better than discrete emotion model.%针对目前基于智能手机的情绪识别研究中所用数据较为单一,不能全面反应用户行为模式,进而不能真实反应用户情绪这一问题展开研究,基于智能手机从多个维度全面收集反应用户日常行为的细粒度感知数据,采用多维数据特征融合方法,利用支持向量机(support vector machine,SVM)、随机森林(random forest)等6种分类方法,基于离散情绪模型和环状情绪模型两种情绪分类模型,对12名志愿者的混合数据和个人数据分别进行情绪识别,并进行了对比实验。实验结果表明,该全面反应用户行为的多维数据特征融合方法能够很好地对用户的情绪进行识别,其中使用个人数据进行情绪识别的准确率最高可达到79.78%,而且环状情感模型分类结果明显优于离散分类模型。

  7. An Infrared Object Tracking Algorithm of Multi-feature Fusion%一种多特征融合的红外目标跟踪算法

    Institute of Scientific and Technical Information of China (English)

    卞志国; 姚源源

    2012-01-01

    针对红外序列图像中各类目标及背景特征动态变化的特性,提出一种基于二值分类技术的多特征融合目标跟踪算法.分别根据灰度、纹理及梯度方向特征将图像分为背景与目标区域,并根据各类特征分类性能的差异,融合特征图像,通过重采样粒子滤波估计目标状态.实验结果表明,该算法对环境光照变化、局部遮挡等均具有较好的鲁棒性.%Due to the various types of dynamic changes of background and foreground characteristics during object tracking in infrared image sequences, this paper proposes an object tracking algorithm of multi-feature fusion based on binary classification. The scene is classified into object and background region based on characteristics such as intensity, texture and grad orientation. The likelihood map is combined with the weights corresponding to classification performance respectively. A re-sampling particle filter is employed to estimate the object state. Experimental results show that the proposed algorithm is robust to environmental illumination and partial occlusions.

  8. Economics of fusion research

    Energy Technology Data Exchange (ETDEWEB)

    None, None

    1977-10-15

    This report provides the results of a study of methods of economic analysis applied to the evaluation of fusion research. The study recognizes that a hierarchy of economic analyses of research programs exists: standard benefit-cost analysis, expected value of R and D information, and expected utility analysis. It is shown that standard benefit-cost analysis, as commonly applied to research programs, is inadequate for the evaluation of a high technology research effort such as fusion research. A methodology for performing an expected value analysis is developed and demonstrated and an overview of an approach to perform an expected utility analysis of fusion research is presented. In addition, a potential benefit of fusion research, not previously identified, is discussed and rough estimates of its magnitude are presented. This benefit deals with the effect of a fusion research program on optimal fossil fuel consumption patterns. The results of this study indicate that it is both appropriate and possible to perform an expected value analysis of fusion research in order to assess the economics of a fusion research program. The results indicate further that the major area of benefits of fusion research is likely due to the impact of a fusion research program on optimal fossil fuel consumption patterns and it is recommended that this benefit be included in future assessments of fusion research economics.

  9. JPEG BLIND STEGANALYSIS BASED ON FEATURE FUSION AND CLUSTERING%基于特征融合聚类的JPEG盲隐写分析

    Institute of Scientific and Technical Information of China (English)

    周楠; 赵险峰; 黄炜; 盛任农

    2013-01-01

    The prior knowledge for traditional steganalysis, such as steganography algorithms, embedding rates and sources of images, etc. , is difficult to be satisfied in practice. In the scenario of blind steganalysis that the above conditions are unknown, analysis using clustering can effectively distinguish between the actor who performs steganography and the others. We propose a method for fusion which is suitable for the selected features, and is to improve the accuracy of JPEG' s steganalysis via clustering. It fuses the principal components of the feature based on partially ordered Markov models with the feature based on calibration, and makes full use of complementarity between features as well as reduces the redundancy, identifies out of the guilty actor better and improves the accuracy of identifying actors who perform steganography. Experimental results show that by different steganography approaches and in different embedding rate conditions, using our scheme can obtain a general increase in the accuracy of JPEG steganalysis by about 2% compared to the existing methods, and get a highest accuracy up to 16%.%传统隐写分析所需的隐写算法、嵌入率和图像来源等先验知识在实用中很难满足,上述条件未知的盲隐写分析场景下,使用聚类分析方法可以有效区分隐写者与非隐写者.设计一种适合所选特征的融合方案,用以提高JPEG聚类隐写分析的准确率,将偏序Markov模型特征的主成分与校准特征融合,充分利用特征互补并降低冗余,可以在参与者中更好地识别出隐写者,从而提高识别准确率.实验结果表明,在不同隐写算法和嵌入率条件下,采用该方法比现有方法准确率平均提高约2%,最高提高约16%.

  10. Cigarette recognition system of feature fusion based on HALCON and SURF%基于HALCON与SURF的多特征融合条烟识别系统

    Institute of Scientific and Technical Information of China (English)

    刘镇; 张敏

    2015-01-01

    烟草物流中心工作量大,枯燥单一,导致分拣过程中经常出现多拿、少拿以及错拿等错误分拣现象,这极大的影响了分拣的效率,甚至导致一些不必要的损失。针对此现象,设计了一种基于HALCON与SURF的多特征融合条烟识别系统。不但提出了新的条烟图像特征描述方法,同时针对分拣生产线的特点,对识别策略进行了相应的改进设计。实验表明,此方案具有较好的应用前景。%Heavy and boring work in tobacco logistics center always makes workers make mistakes such as taking more or less, wrong sorting during their work, which not only adversely affect the efficiency of sorting work, and even cause losses which is evitable sometimes. Aiming at this phenomenon, a new system named cigarette recognition of feature fusion based on HALCON and SURF has been designed. In this article, some new methods to describe image features are put forward, meanwhile, recognition strategy has also been improved according to the characteristics of the sorting production line. Experimental results show that this scheme has a good application prospect.

  11. Sensor Fusion for Autonomous Mobile Robot Navigation

    DEFF Research Database (Denmark)

    Plascencia, Alfredo

    Multi-sensor data fusion is a broad area of constant research which is applied to a wide variety of fields such as the field of mobile robots. Mobile robots are complex systems where the design and implementation of sensor fusion is a complex task. But research applications are explored constantly....... The scope of the thesis is limited to building a map for a laboratory robot by fusing range readings from a sonar array with landmarks extracted from stereo vision images using the (Scale Invariant Feature Transform) SIFT algorithm....

  12. Materials research for fusion

    Science.gov (United States)

    Knaster, J.; Moeslang, A.; Muroga, T.

    2016-05-01

    Fusion materials research started in the early 1970s following the observation of the degradation of irradiated materials used in the first commercial fission reactors. The technological challenges of fusion energy are intimately linked with the availability of suitable materials capable of reliably withstanding the extremely severe operational conditions of fusion reactors. Although fission and fusion materials exhibit common features, fusion materials research is broader. The harder mono-energetic spectrum associated with the deuterium-tritium fusion neutrons (14.1 MeV compared to hydrogen and helium as transmutation products that might lead to a (at present undetermined) degradation of structural materials after a few years of operation. Overcoming the historical lack of a fusion-relevant neutron source for materials testing is an essential pending step in fusion roadmaps. Structural materials development, together with research on functional materials capable of sustaining unprecedented power densities during plasma operation in a fusion reactor, have been the subject of decades of worldwide research efforts underpinning the present maturity of the fusion materials research programme.

  13. Fusion of biological membranes

    Indian Academy of Sciences (India)

    K Katsov; M Müller; M Schick

    2005-06-01

    The process of membrane fusion has been examined by Monte Carlo simulation, and is found to be very different than the conventional picture. The differences in mechanism lead to several predictions, in particular that fusion is accompanied by transient leakage. This prediction has recently been verified. Self-consistent field theory is applied to examine the free energy barriers in the different scenarios.

  14. 指纹与指静脉的特征层动态加权融合识别%Feature level fusion of fingerprint and finger vein biometrics based on dynamic weighting

    Institute of Scientific and Technical Information of China (English)

    杨永明; 林坤明; 韩凤玲; 张祖泷

    2012-01-01

    To study the fusion at feature extraction level for fingerprint and finger vein biometrics, a dynamic weighting matching algorithm based on predictive quality evaluation of interest features is proposed. The proposed approach is based on the fusion of the two traits by extracting independent feature point-sets from the two modalities, and making the two point-sets compatible for concatenation. According to the results of features evaluation, dynamic weighting strategy is introduction for the fusion biometrics. The weight of excellent features in fusion is improved, aiming to weaken the influence of low quality and false features so that better effects of fusion can be achieved. Experimental results based on FVC2000 and self-constructed databases of finger vein show that our scheme achieves 98.9% recognition rate, compared with fingerprint recognition and finger vein recognition increased by 6. 6% and 9. 6% respectively, compared with fusion recognition at matching level increased by 5.4 %.%结合指纹与指静脉两种生物特征的优点进行多模态特征识别,提出一种特征层动态加权融合匹配算法。在图像预处理的基础上分别提取两模式源的有效特征矢量,根据近邻消除和特殊区域保留原则对特征矢量进行降维;从待识别特征角度对特征点集的相对质量进行评价,根据对双模态特征优和差的分类引入动态加权策略,提高质量较好特征所占权重,削弱低质量及伪特征对识别结果的影响,实现了特征层特征自适应优化融合。在FVC2000公开指纹库和指静脉自建数据库上的测试取得了98.9%的识别率,较指纹、指静脉单模态识别分别提高了6.6%和9.6%,较匹配层加权平均融合识别提高了5.4%。

  15. The effects of combined technics training on some physical strength and technical features that is applied to basketball players

    Directory of Open Access Journals (Sweden)

    Fatih Kılınç

    2011-01-01

    Full Text Available Normal 0 21 false false false TR X-NONE X-NONE MicrosoftInternetExplorer4 Aim, it is the research about the effects of  combined technics traınıng on some physical, strength and technical features  that is applied to basketball players who are in basic  technich  development . Method, twenty-five (n:25 male volunteers  attended to this research who are the students of primary school.Two group was formed. The  first group went into combined technics training (KTA n.13, age 9.7+/-0.4 year, height 142.7+/-5.8cm, body weight 34+/-5.2 kg, the second group went into normal technics training (NTA n.12, age 10.5+/-0.5 year, height 147.7+/-0.5 cm, body weight 38.1+/-0.7 kg it is organised like this. Measurement of the physical environment, vertical jump test, right-left hand gripping strength, back strength, the basic technich tests (dribbling,changing hands from behind, reverse,  right–left  tourniquet were done. Training was programmed to be in eight weeks, five days in a week and 1.5 hour. Two  tests were applied to the children before and after the training. Descriptive statistics and t-test  were performed from the data that was obtained through the research. Findings, among the test measurment results after training  important  differences were found between combined technical training group (KTA and normal technical training group (NTA in arm, double-leg vertical jump, left-right one foot vertical jump as well as  the technical tests such as (dribbling, changing hands behind, reverse, right-left tourniquet (p<0.05. Results, in terms of  technical development in basketball, combined technical group (KTA had a very important degree of development. Basketball players have also developed the technical testing of computer-aided analysis program can be a practical field conditions can be reported.

  16. GEodesy Tools for Societal Issues (GETSI): Undergraduate curricular modules that feature geodetic data applied to critical social topics

    Science.gov (United States)

    Douglas, B. J.; Pratt-Sitaula, B.; Walker, B.; Miller, M. S.; Charlevoix, D.

    2014-12-01

    The GETSI project is a three-year NSF funded project to develop and disseminate teaching and learning materials that feature geodesy data applied to critical societal issues such as climate change, water resource management, and natural hazards (http://serc.carleton.edu/getsi). GETSI was born out of requests from geoscience faculty for more resources with which to educate future citizens and future geoscience professionals on the power and breadth of geodetic methods to address societally relevant topics. Development of the first two modules started at a February 2014 workshop and initial classroom testing begins in fall 2014. The Year 1 introductory module "Changing Ice and Sea Level" includes geodetic data such as gravity, satellite altimetry, and GPS time series. The majors-level Year 1 module is "Imaging Active Tectonics" and it has students analyzing InSAR and LiDAR data to assess infrastructure vulnerability to demonstratively active faults. Additional resources such as animations and interactive data tools are also being developed. The full modules will take about two weeks of class time; module design will permit portions of the material to be used as individual projects or assignments of shorter duration. Ultimately a total of four modules will be created and disseminated, two each at the introductory and majors-levels. GETSI is working in tight partnership with the Science Education Resource Center's (SERC) InTeGrate project on the module development, assessment, and dissemination to ensure compatibility with the growing number of resources for geoscience education. This will allow for an optimized module development process based on successful practices defined by these earlier efforts.

  17. 基于多特征量贝叶斯融合的驾驶疲劳识别%Recognition of driver fatigue using multi-feature fusion by Bayesian network

    Institute of Scientific and Technical Information of China (English)

    张伟; 黄炜; 罗大庸

    2012-01-01

    In order to surmount the limitations of Locality Preserving Projections method(LPP), Orthogonal Manifold Preserving Projections (OMPP) method is proposed, which preserves the local and global structure invariance of the samples in the low-dimensional space by integrated non-adjacent constraint information on the objective function of LPP. The orthogonalization process is applied to solving the projection matrix for further reducing the characteristics dimensions after projections, and all of these improve the accuracy of driver fatigue recognition by the expression. In order to further reduce the false alarm rate of recognition, the Bayesian net is applied to detecting the fatigue states by the fusion of multiple features such as fatigue expression, frequency of yawn, and the degree of eye closure. The superiority of the above process has been verified by experiments.%针对保局投影的局限提出了正交流形保持投影方法,通过在LPP目标函数中引入非临近约束,保持了样本在低维空间中的局部和全局结构,采用正交化过程重新求解了投影矩阵,使得投影后的特征维数进一步降低,提高了通过表情进行驾驶疲劳识别的准确性;为了进一步降低识别的误警率,通过贝叶斯网络实现了基于疲劳表情、哈欠频率、眼睛闭合度等特征融合的疲劳检测,通过实验验证了以上过程的优越性.

  18. A Quantitative Feasibility Study on Potential Safety Improvement Effects of Advanced Safety Features in APR-1400 when Applied to OPR-1000

    Energy Technology Data Exchange (ETDEWEB)

    Ualikhan Zhiyenbayev [KAIST, Daejeon (Korea, Republic of); Chung, Dae Wook [Korea Institute of Nuclear Safety, Daejeon (Korea, Republic of)

    2015-10-15

    This study aims to test the feasibility of the applications using Probabilistic Safety Assessment (PSA). Particularly, three of those advanced safety features are selected as follows: 1. Providing an additional Emergency Diesel Generator (EDG); 2. Increasing the capacity of Class 1E batteries; 3. Placing a Refueling Water Storage Tank (RWST) inside containment, i.e., change from RWST to IRWST. The Advanced Power Reactor 1400 (APR-1400) adopts several advanced safety features compared to its predecessor, the Optimized Power Reactor 1000 (OPR-1000), which includes an additional Emergency Diesel Generator, increase in battery capacity, in-containment refueling water storage tank (IRWST), and so on. Considering the remarkable advantages of these safety features in safety improvement and the design similarities between APR-1400 and OPR-1000, it is feasible to apply key advanced safety features of APR-1400 to OPR-1000 to enhance the safety. The selected safety features are incorporated into OPR-1000 PSA model using the Advanced Information Management System (AIMS) for PSA and CDFs are re-evaluated for each application and combination of three applications. Based on current results, it is concluded that three of key advanced safety features of APR-1400 can be effectively applied to OPR-1000, resulting in considerable safety improvement. In aggregate, three advanced safety features, which are an additional EDG, increased battery capacity and IRWST, can reduce the CDF of OPR-1000 by more than 15% when applied altogether.

  19. Applying prosodic speech features in mental health care: An exploratory study in a life-review intervention for depression

    NARCIS (Netherlands)

    Lamers, S.M.A.; Truong, Khiet Phuong; Steunenberg, B.; Steunenberg, B.; de Jong, Franciska M.G.; Westerhof, Gerben Johan

    2014-01-01

    The present study aims to investigate the application of prosodic speech features in a psychological intervention based on lifereview. Several studies have shown that speech features can be used as indicators of depression severity, but these studies are mainly based on controlled speech recording

  20. Applying prosodic speech features in mental health care: An exploratory study in a life-review intervention for depression

    NARCIS (Netherlands)

    Lamers, S.M.A.; Truong, K.P.; Steunenberg, B.; Jong, de F.M.G.; Westerhof, G.J.

    2014-01-01

    The present study aims to investigate the application of prosodic speech features in a psychological intervention based on lifereview. Several studies have shown that speech features can be used as indicators of depression severity, but these studies are mainly based on controlled speech recording t

  1. A Method of Fault Diagnosis Based on Multi-source Information Fusion Applied in the Distillation Column%基于精馏塔多源信息融合的故障诊断方法

    Institute of Scientific and Technical Information of China (English)

    杨帆; 吴迅; 陈茂林; 江星

    2012-01-01

    研究了一种应用于精馏塔的多源信息融合的故障诊断方法.选择影响精馏塔系统生产质量的主要参数底温、顶温等作为融合对象.首先对参数进行归一化处理,并利用主元分析法对提取的底温、顶温等特征数据进行处理,这样既降低了输入的维数,同时又提高了输入参量特征的相互独立性.然后通过神经网络对主元分析法处理后的特征矢量进行推理分类,得到精馏塔的故障诊断结果.以在一定压力下,间接反映氯乙烯精馏塔产品浓度的塔板温度为诊断对象,仿真结果表明该方法具有很好的诊断效果.%A method of fault diagnosis basing on multi-source information fusion is applied in the distillation column . Extracting the main parameters that affects the production quality of the distillation column system such as temperature at the end, the top temperature and so on as a fusion of object and data preprocessing and feature extraction by using principal component analysis, through linearly associating the points in higher dimension space and projecting them to lower dimension space, not only reducing the input dimension, but also enhancing the mutual independence of the characteristics of the input parameters. Then, we can classify the data by neural network. Under a certain pressure, plate temperature that indirectly reflect the concentration of vinyl chloride distillation column as a diagnostic object , the simulation results show that the method is a good diagnostic result.

  2. 基于HHT和CSSD的多域融合自适应脑电特征提取方法%An Adaptive Multi-Domain Fusion Feature Extraction with Method HHT and CSSD

    Institute of Scientific and Technical Information of China (English)

    李明爱; 崔燕; 杨金福; 郝冬梅

    2013-01-01

    The adaptivity and real-time performance of feature extraction method are crucial in brain-computer interface . Based on Hilbert-Huang transform (HHT ) and common spatial subspace decomposition (CSSD ) algorithm ,a novel feature extrac-tion method ,denoted as HCSSD ,was proposed .Firstly ,the motor imagery electroencephalography (EEG )/ electrocorticography (ECoG ) was preprocessed ,and a relative distance criterion was defined to select the optimal combination of channels .Secondly , Hilbert instantaneous energy spectrum and marginal energy spectrum of EEG/ECoG were calculated to extract time feature and fre-quency feature respectively .Then CSSD was applied to extract spatial feature .Furthermore ,serial feature fusion strategy was adopted to obtain time-frequency-spatial feature .Finally ,learning vector quantization neural network was designed to classify the EEG/ECoG data .The average recognition accuracy was 92% for the left small finger and tongue motor imagery ECoG tasks .Experiment results show that HCSSD can enhance the adaptivity and real-time performance of feature extraction ,with the recognition accuracy im-proved .This method provides a new idea for the application of portable BCI system in rehabilitation field .%为改善运动想象脑电信号特征提取的自适应性和实时性,提出一种基于希尔伯特-黄变换(HHT)与共空域子空间分解算法(CSSD )的特征提取方法(HCSSD )。在对脑电信号进行预处理的基础上,定义一种相对距离准则优选脑电极组合;计算脑电的Hilbert瞬时能量谱和边际能量谱,以获取脑电的时-频特征,并基于CSSD提取其空域特征,采用串行特征融合策略得到脑电的时-频-空特征;设计学习矢量量化神经网络分类器,实现脑电数据分类。在训练集与测试集间隔一周且减少导联数量的情况下,基于HCSSD对左手小指和舌头的运动想象ECoG脑电数据的平均识别率为92%。实验

  3. Undergraduate teaching modules featuring geodesy data applied to critical social topics (GETSI: GEodetic Tools for Societal Issues)

    Science.gov (United States)

    Pratt-Sitaula, B. A.; Walker, B.; Douglas, B. J.; Charlevoix, D. J.; Miller, M. M.

    2015-12-01

    The GETSI project, funded by NSF TUES, is developing and disseminating teaching and learning materials that feature geodesy data applied to critical societal issues such as climate change, water resource management, and natural hazards (serc.carleton.edu/getsi). It is collaborative between UNAVCO (NSF's geodetic facility), Mt San Antonio College, and Indiana University. GETSI was initiated after requests by geoscience faculty for geodetic teaching resources for introductory and majors-level students. Full modules take two weeks but module subsets can also be used. Modules are developed and tested by two co-authors and also tested in a third classroom. GETSI is working in partnership with the Science Education Resource Center's (SERC) InTeGrate project on the development, assessment, and dissemination to ensure compatibility with the growing number of resources for geoscience education. Two GETSI modules are being published in October 2015. "Ice mass and sea level changes" includes geodetic data from GRACE, satellite altimetry, and GPS time series. "Imaging Active Tectonics" has students analyzing InSAR and LiDAR data to assess infrastructure earthquake vulnerability. Another three modules are in testing during fall 2015 and will be published in 2016. "Surface process hazards" investigates mass wasting hazard and risk using LiDAR data. "Water resources and geodesy" uses GRACE, vertical GPS, and reflection GPS data to have students investigating droughts in California and the High Great Plains. "GPS, strain, and earthquakes" helps students learn about infinitesimal and coseismic strain through analysis of horizontal GPS data and includes an extension module on the Napa 2014 earthquake. In addition to teaching resources, the GETSI project is compiling recommendations on successful development of geodesy curricula. The chief recommendations so far are the critical importance of including scientific experts in the authorship team and investing significant resources in

  4. 基于UDCT和三角形测量特征融合的手背静脉识别%Dorsal Hand Vein Recognition Based on the Feature Fusion of UDCT Phase Feature and Triangulation

    Institute of Scientific and Technical Information of China (English)

    魏上清; 顾晓东

    2013-01-01

    A new approach to palm-dorsal vein recognition based on the feature fusion is presented in this paper.After palm-dorsal image preprocessing and ROI (Region Of Interest) extraction,we use UDCT (Uniform Discrete Curvelet Transform) of the Curvelet Transform on ROI,and encode the Curvelet coefficients phase variance,and evaluate the Chi-square distance of coding histogram for vein recognition.When the distance between and threshold is large,we get the recognition result.Otherwise,this paper detects the skeleton of the hand vein,and uses the ending point and the crossing point of the extracted vein skeleton as the feature point,then measure the triangle side by the Triangulation algorithm.At last,this paper calculates the matching distance by the weighted average method.This approach improves recognition ratio and avoids the cost time noise problem increase sharply.%提出了一种基于特征融合的手背静脉识别算法,首先对手背静脉图像感兴趣区域进行预处理,然后采用均衡离散曲率波变换对感兴趣区域进行变换,接着对变换系数进行相位编码,并计算编码统计直方图的卡方距离,当此距离与阈值相差较大时,得到识别结果;否则,对预处理后的图像提取静脉骨架,确定相关的特征点,通过三角测量法来计算匹配距离,对和采用加权平均法来获得最终的识别结果.该方法在识别时间没有明显增加的情况下,而识别的效果却得到了提高.

  5. Audio-visual Feature Fusion Person Identification Based on SVM and Score Normalization%基于SVM和归一化技术的音视频特征融合身份识别

    Institute of Scientific and Technical Information of China (English)

    丁辉; 安今朝

    2012-01-01

    In order to solve the problem of low recognition rate of face recognition and speech recognition under the wicked noise conditions. Based on the studies of feature level fusion theory and combined with Normalization and SVM theory, a novel model for face features and speech features fusion recognition is presented in this paper. First, we extract the face features and speech features correspondingly, then we fuse the two features on the feature level in order to obtain the fusion feature, after the calculation of the distance between the test people and template people we normalize the matching distance so as to reduce the computational and to improve the recognition accuracy. Al the last, we put the normalization matching distance into SVM can we obtain the recognition result. Trie experiment show that the fusion system performs well both in response time and system accuracy especially in noisy background.%针对噪声环境下人脸识别率和说话人识别率低的问题,在研究特征层融合的基础上,结合归一化技术和SVM理论,提出了一种融合人脸和语音的多生物特征识别模型.首先采用离散余弦变换和局部保持投影算法提取人脸特征及SVM方法提取语音特征,在特征层进行融合得到融合特征后,计算测试身份与模板问的距离,为了减少计算量和提高识别性能,对匹配距离进行归一化处理,最后输入到SVM进行识别.仿真结果表明,在噪声环境下,当信噪比降低时,融合识别率要明显高于单个系统的识别率,达到了身份识别的目的.

  6. 一种特征加权融合人脸识别方法%Face recognition by weighted fusion of facial features

    Institute of Scientific and Technical Information of China (English)

    孙劲光; 孟凡宇

    2015-01-01

    针对传统人脸识别算法在非限制条件下识别准确率不高的问题,提出了一种特征加权融合人脸识别方法( DLWF+). 根据人脸面部左眼、右眼、鼻子、嘴、下巴等5个器官位置,将人脸图像划分成5个局部采样区域;将得到的5个局部采样区域和整幅人脸图像分别输入到对应的神经网络中进行网络权值调整,完成子网络的构建;利用softmax回归求出6个相似度向量并组成相似度矩阵与权向量相乘得出最终的识别结果. 经ORL和WFL人脸库上进行实验验证,识别准确率分别达到97%和91.63%. 实验结果表明:该算法能够有效提高人脸识别能力,与传统识别算法相比在限制条件和非限制条件下都具有较高的识别准确率.%The accuracy of face recognition is low under unconstrained conditions. To solve this problem, we pro-pose a new method based on deep learning and the weighted fusion of facial features. First, we divide facial feature points into five regions using an active shape model and then sample different facial components corresponding to those facial feature points. A corresponding deep belief network ( DBN) was then trained based on these regional samples to obtain optimal network parameters. The five regional sampling regions and entire facial image obtained were then inputted into a corresponding neural network to adjust the network weight and complete the construction of sub-networks. Finally, using softmax regression, we obtained six similarity vectors of different components. These six similarity vectors comprise a similarity matrix, which is then multiplied by the weight vector to derive the final recognition result. Recognition accuracy was 97% and 91.63% on the ORL and WFL face databases, respectively. Compared with traditional recognition algorithms such as SVM, DBN, PCA, and FIP+LDA, recognition rates for both databases were improved in both constrained and unconstrained conditions. On the basis of

  7. Face Recognition: An Approach Based on Feature Fusion and Neural Network%人脸识别:一种基于特征融合及神经网络的方法

    Institute of Scientific and Technical Information of China (English)

    於东军; 赵海涛; 杨静宇

    2005-01-01

    基于特征融合和神经网络构建了一个完整的人脸识别系统.首先使用广义K-L变换对人脸的自组织特征和形状特征进行融合;然后使用UDT(Uncorrelated Discriminant Transform)对融合后的特征进行变换,以获得最优鉴别矢量;最后使用多层感知器作为分类器.仿真结果证明了该方法的有效性.%A complete face recognition system based on feature fusion and neural network is proposed in this paper. The new face coding technology based on the fusion of SOM and Shape features is utilized. The dimensionality of the fused feature space is reduced using generalized K-L transform. The corresponding reduced feature is then processed by the Uncorrelated Discriminant Transform (UDT), which has better classification capability than that of the classical Foley-Sammon Discriminant Transform (FSDT), to obtain optimal discriminant feature. Finally, a Multi-Layer Perceptron (MLP), the output of which consists of class membership values, is utilized as the face recognizer. Experimental results on the face database NUST603 of 960 face images corresponding to 96 subjects show the effectiveness and robustness of the proposed approach.

  8. 基于证据支持矩阵的特征权重融合的风电机组故障诊断%Fault Diagnosis of Wind Turbine Based on Feature Weight Fusion Method with Evidence Support Matrix

    Institute of Scientific and Technical Information of China (English)

    陈国初; 苗锐; 徐余法

    2012-01-01

    In view of uncertainty, complexity and diversity in the fault characteristics of the wind power unit's gearbox, a method of feature weight fusion based on evidence support matrix is proposed to construct the model. Two factors, the conflict coefficient and evidence distance, are analyzed, which affect the evidence conflict. An evidence support matrix is constructed. The char- acteristic vector related to the maximum eigenvalue of the matrix is calculated as an evidence weight. The evidence weights are fused using the evidence combination formula. The method is applied to fault diagnosis of a wind turbine gearbox. The results show that the proposed method can enhance efficiency and accuracy of the fault diagnosis of wind turbine gearbox.%针对风电机组齿轮箱故障特征的不确定性、复杂性和多元性的特点,提出基于证据支持矩阵特征权重的融合新方法,建立故障诊断模型。分析了影响证据冲突的冲突因子和证据距离,利用这两个因子构造证据支持度矩阵;求解了该证据支持度矩阵最大特征值对应的特征向量,并将此作为证据的权重,利用证据组合公式进行融合;最后将其用于风电机组齿轮箱故障诊断。实验结果表明,该方法可较好提高风电机组齿轮箱故障诊断的效率和准确率。

  9. 属性内-融合与数据融合挖掘%Attribute inner fusion and data fusion mining

    Institute of Scientific and Technical Information of China (English)

    邱育锋; 汤积华

    2014-01-01

    属性融合是潜藏在 P-集合内的一个重要的应用特性,P-集合的动态特性来自 P-集合的属性融合。利用内 P-集合的结构与动态特性,给出属性内-融合概念、结构和定理,最后给出在属性内-融合条件下的数据融合挖掘和数据融合挖掘准则与数据融合挖掘-筛选的应用。%Attribute fusion is an important applied characteristic hidden in packet sets, whose dynamic features come from its attribute fusion.By using internal packet sets structure and their dynamic features, the concept and structure of attribute inner fusion are proposed, and attribute inner fusion theorem is given.Then data fusion mining under the con-dition of attribute inner fusion is put forward.Moreover, the application of mining criterion with mining-screening of data fusion is shown.

  10. Video hash learning based on feature fusion and Manhattan quantization%基于特征融合和曼哈顿量化的视频哈希学习方法

    Institute of Scientific and Technical Information of China (English)

    聂秀山; 王舒婷; 尹义龙

    2016-01-01

    With the development of computer and multimedia technologies,video storage,transmission and retrieval are facing a huge challenge in the Internet especially the mobile Internet,due to the complex structure and high dimension of the video.Video hash learning is one of the important ways to solve the challenge,and it becomes one of the hot topics in the field of multimedia processing.As known,the existing methods generate video hashes using different types of features.In fact,there are potential relationships among different types of video features. Therefore,to make full use of the relationships among different video features and overcome the limitations of traditional video hashing methods,we proposed a video hash learning method based on feature fusion and Manhattan quantization in this paper.In the proposed method,the global,local and temporal features are firstly extracted from the video content,and the video clip is considered as a third-order tensor.Then,the tensor decomposition,which is popularly applied in multi-dimensional data processing,is used to fuse the global,local and temporal features.The three low-order tensors are obtained after tensor decomposition,and we concatenate them as the fusion representation of video content.Subsequently,the fused video feature is quantified by Manhattan quantization to get the video hash codes,which are used to construct the final video hash.Compared with the traditional video hashing methods,the proposed method not only makes full use the relationship among different video features,but also achieves the goal of coding with different dimensions respectively,which can well preserve the structural similarity among different video features.Two kinds of experiments are conducted to evaluate the performance of the proposed method,and the results show that the proposed method has a good performance compared with the existing methods.%当前信息时代,随着计算机和多媒体技术的发展,在互联网尤其是移

  11. Different bone graft fusion materials applied in lumbar interbody fusion%不同植骨融合材料在腰椎椎体间脊柱融合中的应用

    Institute of Scientific and Technical Information of China (English)

    覃建朴; 王翀; 张朋云; 曹广如; 蔡玉强; 廖文波

    2016-01-01

    背景:脊柱融合治疗时选择合适的替代移植骨具有重要的意义,能够解决自体骨移植及其他移植材料带来的弊端。目的:观察不同植骨融合材料性能,探讨不同植骨融合材料在犬腰椎椎体间脊柱融合中的应用效果。方法:选取45只中华田园犬建立腰椎椎体间脊柱融合模型,建模后随机分3组,分别植入自体髂骨、重组人骨形态发生蛋白2复合材料和同种异体髂骨,分析不同植骨融合材料在犬腰椎椎体间脊柱融合中的效果。结果与结论:①融合率:重组人骨形态发生蛋白2复合材料组犬融合率显著高于其他组(P <0.05);②Oswestry 功能障碍指数:重组人骨形态发生蛋白2复合材料组术后 Oswestry 功能障碍指数显著低于其他2组(P <0.05);②组织学形态:苏木精-伊红染色显示,术后12周,与其他2组相比,重组人骨形态发生蛋白2犬完全骨性融合,且形成了连续骨小梁,植入骨与犬上下椎体完全粘连;④结果提示:重组人骨形态发生蛋白2复合材料更能够促更好地促进脊柱愈合,效果优于自体和同种异体骨移植。%BACKGROUND: The choice of suitable bone graft substitute is vital for spinal fusion treatment, which can solve some limitations caused by autogenous bone graft and other materials. OBJECTIVE: To investigate properties of different bone graft fusion materials, and to explore their application in dog spinal fusion of lumbar vertebral body. METHODS: Forty-five Chinese rural dogs were enrol ed to prepare lumbar interbody fusion models, and then were randomized into three groups transplanted with autogenous ilium, recombinant human bone morphogenetic protein-2 composite or al ograft ilium, respectively. Afterwards, effects of different materials in the lumbar interbody fusion were analyzed. RESULTS AND CONCLUSION: The fusion rate of the composite group was significantly higher than those of the other

  12. Multi-sensor and multi-temporal data fusion for measurement of depositional features at Augustine Volcano, south-central Alaska

    Science.gov (United States)

    McAlpin, D. B.; Meyer, F. J.

    2012-12-01

    In this paper, optical, SAR, and InSAR data from the 2006 eruption of Augustine Volcano, are used to demonstrate how fusion of photogrammatically derived, high resolution DEMs can be used to quantify extent and volume of eruption-related depositional features; to improve the sensitivity and accuracy of differential InSAR (d-InSAR) for volcano deformation monitoring; and how coherence maps of lava, pyroclastic flow deposits, and lahars provide information on deposition history and coherence recovery time of areas disrupted by lahars. Augustine Volcano's most recent eruption occurred in December 2005 through March 2006. Post 2006-eruption data from the ALOS-PRISM satellite is available from image acquisitions on 21 September 2007, 25 May 2008, and 26 September 2009. The ALOS-PRISM instrument consists of three independent panchromatic radiometers for simultaneous imaging in nadir, forward, and backward directions. This results in along-track stereoscopy in overlapping images (triplets), with horizontal resolution at nadir of 2.5-meters. DEMs produced from these high resolution triplets are compared to pre-eruption DEMs from the Shuttle Radar Topography Mission (SRTM) to delineate depositional features and quantify their volumes. Multi-temporal DEMs are also beneficial for the generation of topography-free d-InSAR images Separate d-InSAR analyses based on DEMs from PRISM triplets and the SRTM demonstrate the improvement in deformation-estimate precision that is achieved by using high-resolution DEM information. Augustine's 2006 eruption produced significant lava flows, pyroclastic flows, and lahars, which were previously mapped in detail. Coherence mapping from pre- and post-eruption Envisat data are validated by comparison to the available detail maps, and analyzed to determine the extent to which coherence mapping can resolve the time sequence of deposition during the 2006 eruption. Additional radar data sets are available from the Phased Array type L-band Synthetic

  13. 基于HOG和颜色特征融合的人体姿态估计%Human Pose Estimation Based on Fusion of HOG and Color Feature

    Institute of Scientific and Technical Information of China (English)

    韩贵金; 朱虹

    2014-01-01

    Appearance model plays an important role in the human pose estimation. To improve the estimation accuracy, how to set up the appearance model by using the histogram of oriented gradient (HOG) and color features is studied. The sub-classifier for each cell unit of the body part is built by using the support vector data description ( SVDD ) algorithm, and then the HOG-based appearance model is constructed by the linear combination of sub-classifiers with different weights. The specific location probability is learned by using those states, which has higher similarity with the HOG-based appearance model, and the corresponding color histogram is calculated, which is the color-based appearance model. According to the illumination and the color contrast between the clothing and background in the static image to be proceeded, the weights of two appearance models are determined, and then two appearance models are combined linearly to construct appearance model based on the fusion of the HOG and color features. The proposed appearance model is used for human pose estimation, and the experimental results show it is more effectively and gets higher pose estimation accuracy.%部位外观模型在人体姿态估计中起着关键作用。为提高人体姿态估计的准确度,对如何利用梯度方向直方图( HOG)与颜色特征建立外观模型进行研究。利用支持向量数据描述算法( SVDD)对部位的所有细胞单元构造子分类器,将所有子分类器按照不同权值进行线性组合,建立基于HOG特征的外观模型;利用与基于HOG特征的外观模型之间似然度较高的部位状态学习定位概率,根据定位概率求得的颜色直方图即为基于颜色特征的外观模型;根据待处理静态图像的光照条件和人体着装及背景的颜色对比度可确定分别基于HOG和颜色特征的外观模型的权值;根据相应权值对两种外观模型进行线性组合,建立基于HOG和颜色特征融合

  14. Evaluating score- and feature-based likelihood ratio models for multivariate continuous data: applied to forensic MDMA comparison

    NARCIS (Netherlands)

    A. Bolck; H. Ni; M. Lopatka

    2015-01-01

    Likelihood ratio (LR) models are moving into the forefront of forensic evidence evaluation as these methods are adopted by a diverse range of application areas in forensic science. We examine the fundamentally different results that can be achieved when feature- and score-based methodologies are emp

  15. Osteoclast Fusion

    DEFF Research Database (Denmark)

    Marie Julie Møller, Anaïs; Delaissé, Jean-Marie; Søe, Kent

    2017-01-01

    suggesting that fusion partners may specifically select each other and that heterogeneity between the partners seems to play a role. Therefore, we set out to directly test the hypothesis that fusion factors have a heterogenic involvement at different stages of nuclearity. Therefore, we have analyzed...... on the nuclearity of fusion partners. While CD47 promotes cell fusions involving mono-nucleated pre-osteoclasts, syncytin-1 promotes fusion of two multi-nucleated osteoclasts, but also reduces the number of fusions between mono-nucleated pre-osteoclasts. Furthermore, CD47 seems to mediate fusion mostly through......Investigations addressing the molecular keys of osteoclast fusion are primarily based on end-point analyses. No matter if investigations are performed in vivo or in vitro the impact of a given factor is predominantly analyzed by counting the number of multi-nucleated cells, the number of nuclei per...

  16. Satellite cloud image fusion based on regional feature with nonsubsampled contourlet transform%基于区域特征的非下采样Contourlet变换卫星云图融合

    Institute of Scientific and Technical Information of China (English)

    汪大; 毕硕本; 王必强; 颜坚

    2012-01-01

    对不同的卫星云图进行融合处理,可为灾害性天气的监测和预警提供更为全面的信息,提出一种基于区域特征的非下采样Contourlet变换(NSCT)卫星云图融合新方法.首先,采用NSCT对卫星云图进行多尺度和多方向分解,得到低通子带系数和各带通方向子带系数;然后,对低通子带系数采用基于图像区域相关系数和区域能量的自适应融合规则,对各带通方向子带系数采用加权和区域方差相结合的融合规则;最后,对融合系数进行NSCT逆变换得到融合云图.实验结果表明,该算法在增强融合云图的纹理及边缘等细节信息的同时,能更好地保留源红外云图的红外信息,融合效果更好.%The fusion of different satellite cloud images can provide more comprehensive information for surveillance and early warning of disastrous weather. A satellite cloud image fusion algorithm based on regional feature with NonSubsampled Contourlet Transform (NSCT) was proposed. Firstly, the source images were decomposed at multi-scale and multi-direction by NSCT. Then the self-adaptive fusion rule based on regional correlation coefficient and regional energy was used to fuse the low frequency coefficients, and the fusion rule of regional variance in combination with weighting was used for the fusion of the high frequency coefficients. Finally, the fused image was obtained by performing the inverse NSCT on the fused coefficients. The experimental results illustrate that while the texture and edge feature of the fused cloud image are enriched, the infrared information are preserved as much as possible and the proposed algorithm acquires better fusion result.

  17. Movement Feature of Adjacent Segments After Cervical Three-Segment Fusion%颈椎三节段融合术后相邻节段运动变化规律研究

    Institute of Scientific and Technical Information of China (English)

    薛清华; 刘伟强

    2011-01-01

    This article aims at investigating the rules of the motion of human cervical after 3 - segment fusion,with the help of a study 3D motion information collecting system. The motion information of 6 porcine cervical specimens in intact and fusion condition was collected ,and the motion range and angle of each segment were calculated. Through analyzing the movement feature ,we concluded that the quality of three-level fusion was slightly worse than that of two-level fusion, and the movement range was about to 30% of the intact state. In comparison of the two kinds of three-level fusion and three kinds of two-level fusion,we found that the motion compensation range was bigger in the former ones at each level. The quantitative reference and theory evidence raised from this study will give a great support to the operation of multi-level fusion of the human cervical.%为研究人体颈椎三节段融合后的运动规律,本文利用三维运动信息采集系统,获取了6具猪颈椎C2-T1标本在未损伤及两种三节段融合状态下的各个节段的运动信息,计算并得到各节段运动转角;再通过分析三节段融合的相关运动规律和特点,得出三节段融合质量略差于双节段融合效果,融合后的运动幅度可降低至融合前的30%左右;通过定量比较得出两种三节段融合相对于三种双节段融合,前、后相邻节段与其它节段融合状态的运动补偿幅度均有不同程度的增加.本研究为人体多节段融合临床手术提供了定量参考和理论依据.

  18. Applying quantitative adiposity feature analysis models to predict benefit of bevacizumab-based chemotherapy in ovarian cancer patients

    Science.gov (United States)

    Wang, Yunzhi; Qiu, Yuchen; Thai, Theresa; More, Kathleen; Ding, Kai; Liu, Hong; Zheng, Bin

    2016-03-01

    How to rationally identify epithelial ovarian cancer (EOC) patients who will benefit from bevacizumab or other antiangiogenic therapies is a critical issue in EOC treatments. The motivation of this study is to quantitatively measure adiposity features from CT images and investigate the feasibility of predicting potential benefit of EOC patients with or without receiving bevacizumab-based chemotherapy treatment using multivariate statistical models built based on quantitative adiposity image features. A dataset involving CT images from 59 advanced EOC patients were included. Among them, 32 patients received maintenance bevacizumab after primary chemotherapy and the remaining 27 patients did not. We developed a computer-aided detection (CAD) scheme to automatically segment subcutaneous fat areas (VFA) and visceral fat areas (SFA) and then extracted 7 adiposity-related quantitative features. Three multivariate data analysis models (linear regression, logistic regression and Cox proportional hazards regression) were performed respectively to investigate the potential association between the model-generated prediction results and the patients' progression-free survival (PFS) and overall survival (OS). The results show that using all 3 statistical models, a statistically significant association was detected between the model-generated results and both of the two clinical outcomes in the group of patients receiving maintenance bevacizumab (pchemotherapy.

  19. Membrane fusion

    DEFF Research Database (Denmark)

    Bendix, Pól Martin

    2015-01-01

    At Stanford University, Boxer lab, I worked on membrane fusion of small unilamellar lipid vesicles to flat membranes tethered to glass surfaces. This geometry closely resembles biological systems in which liposomes fuse to plasma membranes. The fusion mechanism was studied using DNA zippering...... between complementary strands linked to the two apposing membranes closely mimicking the zippering mechanism of SNARE fusion complexes....

  20. Cold nuclear fusion

    Directory of Open Access Journals (Sweden)

    Huang Zhenqiang Huang Yuxiang

    2013-10-01

    Full Text Available In normal temperature condition, the nuclear force constraint inertial guidance method, realize the combination of deuterium and tritium, helium and lithium... And with a magnetic moment of light nuclei controlled cold nuclear collide fusion, belongs to the nuclear energy research and development in the field of applied technology "cold nuclear collide fusion". According to the similarity of the nuclear force constraint inertial guidance system, the different velocity and energy of the ion beam mixing control, developed ion speed dc transformer, it is cold nuclear fusion collide, issue of motivation and the nuclear power plant start-up fusion and power transfer system of the important equipment, so the merger to apply for a patent

  1. Fusion Studies in Japan

    Science.gov (United States)

    Ogawa, Yuichi

    2016-05-01

    A new strategic energy plan decided by the Japanese Cabinet in 2014 strongly supports the steady promotion of nuclear fusion development activities, including the ITER project and the Broader Approach activities from the long-term viewpoint. Atomic Energy Commission (AEC) in Japan formulated the Third Phase Basic Program so as to promote an experimental fusion reactor project. In 2005 AEC has reviewed this Program, and discussed on selection and concentration among many projects of fusion reactor development. In addition to the promotion of ITER project, advanced tokamak research by JT-60SA, helical plasma experiment by LHD, FIREX project in laser fusion research and fusion engineering by IFMIF were highly prioritized. Although the basic concept is quite different between tokamak, helical and laser fusion researches, there exist a lot of common features such as plasma physics on 3-D magnetic geometry, high power heat load on plasma facing component and so on. Therefore, a synergetic scenario on fusion reactor development among various plasma confinement concepts would be important.

  2. Fusion rings and fusion ideals

    DEFF Research Database (Denmark)

    Andersen, Troels Bak

    by the so-called fusion ideals. The fusion rings of Wess-Zumino-Witten models have been widely studied and are well understood in terms of precise combinatorial descriptions and explicit generating sets of the fusion ideals. They also appear in another, more general, setting via tilting modules for quantum...

  3. Cell fusion and nuclear fusion in plants.

    Science.gov (United States)

    Maruyama, Daisuke; Ohtsu, Mina; Higashiyama, Tetsuya

    2016-12-01

    Eukaryotic cells are surrounded by a plasma membrane and have a large nucleus containing the genomic DNA, which is enclosed by a nuclear envelope consisting of the outer and inner nuclear membranes. Although these membranes maintain the identity of cells, they sometimes fuse to each other, such as to produce a zygote during sexual reproduction or to give rise to other characteristically polyploid tissues. Recent studies have demonstrated that the mechanisms of plasma membrane or nuclear membrane fusion in plants are shared to some extent with those of yeasts and animals, despite the unique features of plant cells including thick cell walls and intercellular connections. Here, we summarize the key factors in the fusion of these membranes during plant reproduction, and also focus on "non-gametic cell fusion," which was thought to be rare in plant tissue, in which each cell is separated by a cell wall.

  4. Hierarchical Spatio-Temporal Probabilistic Graphical Model with Multiple Feature Fusion for Binary Facial Attribute Classification in Real-World Face Videos.

    Science.gov (United States)

    Demirkus, Meltem; Precup, Doina; Clark, James J; Arbel, Tal

    2016-06-01

    Recent literature shows that facial attributes, i.e., contextual facial information, can be beneficial for improving the performance of real-world applications, such as face verification, face recognition, and image search. Examples of face attributes include gender, skin color, facial hair, etc. How to robustly obtain these facial attributes (traits) is still an open problem, especially in the presence of the challenges of real-world environments: non-uniform illumination conditions, arbitrary occlusions, motion blur and background clutter. What makes this problem even more difficult is the enormous variability presented by the same subject, due to arbitrary face scales, head poses, and facial expressions. In this paper, we focus on the problem of facial trait classification in real-world face videos. We have developed a fully automatic hierarchical and probabilistic framework that models the collective set of frame class distributions and feature spatial information over a video sequence. The experiments are conducted on a large real-world face video database that we have collected, labelled and made publicly available. The proposed method is flexible enough to be applied to any facial classification problem. Experiments on a large, real-world video database McGillFaces [1] of 18,000 video frames reveal that the proposed framework outperforms alternative approaches, by up to 16.96 and 10.13%, for the facial attributes of gender and facial hair, respectively.

  5. Linguistic features of literary theme: some halliday-type principles applied to 'surfacing' (margareth atwood 1972 Linguistic features of literary theme: some halliday-type principles applied to 'surfacing' (margareth atwood 1972

    Directory of Open Access Journals (Sweden)

    M. Nélia Scott

    2008-04-01

    Full Text Available Halliday divides the functions of language into three 'macro-functions' which he calls: Ideational function, expressing content, or the propositional content of the speaker's experiences of the real and inner world; Interpersonal function, which is the means whereby we achieve communication, taking on speech roles viz-a-viz other people,00mplaining, narrating, enquiring, encouraging, etc.; and Textual function, which serves to connect discourse, weaving it together. Under this latter function comes the notion of cohesion. Phoric' elements are parts of the reference system needed for a text to be cohesive. We elucidate and refer to 'phoric' elements in more detail below. It is important to note that all these three macro-functions are present at the same time in a text. Halliday describes the choice of (sets of different options the speaker makes in the language system, to express his experiences. 'All options are embedded in the language system: the system is a network of options, deriving from all the various functions of language' (1973:111 Thus a certain choice of (one set of different options rather than another can be said to have been motivated by what the speaker (or writer wanted to mean -- to convey or emphasize. Prominence of certain features in a text, then, stands out in a particular Way, suggesting or pressing the reader to take notice of it, this recognition contributing towards a more complete understanding of the writer's work. This is Halliday's intention in his study of The Inheritors (Halliday 1973:103-43. Halliday divides the functions of language into three 'macro-functions' which he calls: Ideational function, expressing content, or the propositional content of the speaker's experiences of the real and inner world; Interpersonal function, which is the means whereby we achieve communication, taking on speech roles viz-a-viz other people,00mplaining, narrating, enquiring, encouraging, etc.; and Textual function

  6. Digital Holography and 3D Imaging: introduction to the joint feature issue in Applied Optics and Journal of the Optical Society of America B.

    Science.gov (United States)

    Banerjee, Partha P; Osten, Wolfgang; Picart, Pascal; Cao, Liangcai; Nehmetallah, George

    2017-05-01

    The OSA Topical Meeting on Digital Holography and 3D Imaging (DH) was held 25-28 July 2016 in Heidelberg, Germany, as part of the Imaging Congress. Feature issues based on the DH meeting series have been released by Applied Optics (AO) since 2007. This year, AO and the Journal of the Optical Society of America B (JOSA B) jointly decided to have one such feature issue in each journal. This feature issue includes 31 papers in AO and 11 in JOSA B, and covers a large range of topics, reflecting the rapidly expanding techniques and applications of digital holography and 3D imaging. The upcoming DH meeting (DH 2017) will be held from 29 May to 1 June in Jeju Island, South Korea.

  7. A comparison between a steady state and a pulsed fusion power plant

    Energy Technology Data Exchange (ETDEWEB)

    Zollino, G., E-mail: giuseppe.zollino@igi.cnr.it [Consorzio RFX, Associazione EURATOM-ENEA sulla Fusione Corso Stati Uniti 4, 35127 Padova (Italy); Casini, G.; Pierobon, D.; Antoni, V.; Bolzonella, T.; Piovan, R. [Consorzio RFX, Associazione EURATOM-ENEA sulla Fusione Corso Stati Uniti 4, 35127 Padova (Italy)

    2011-10-15

    In the paper the first results of a simplified code (FRESCO) for the evaluation of capital cost and cost of electricity of a D-T Tokamak fusion power plant are reported. For the scope of this paper, only the main assumptions and features of the code are described and its validation against the figures of the European PPCS plant models are presented. The code is here applied to compare the costs of a steady state and a pulsed fusion power plant.

  8. Multiview fusion for activity recognition using deep neural networks

    Science.gov (United States)

    Kavi, Rahul; Kulathumani, Vinod; Rohit, Fnu; Kecojevic, Vlad

    2016-07-01

    Convolutional neural networks (ConvNets) coupled with long short term memory (LSTM) networks have been recently shown to be effective for video classification as they combine the automatic feature extraction capabilities of a neural network with additional memory in the temporal domain. This paper shows how multiview fusion can be applied to such a ConvNet LSTM architecture. Two different fusion techniques are presented. The system is first evaluated in the context of a driver activity recognition system using data collected in a multicamera driving simulator. These results show significant improvement in accuracy with multiview fusion and also show that deep learning performs better than a traditional approach using spatiotemporal features even without requiring any background subtraction. The system is also validated on another publicly available multiview action recognition dataset that has 12 action classes and 8 camera views.

  9. Sociodemographic features and diagnoses as predictors of severe disability in a sample of adults applying for disability certification.

    Science.gov (United States)

    Raggi, Alberto; Covelli, Venusia; Pagani, Marco; Meucci, Paolo; Martinuzzi, Andrea; Buffoni, Mara; Russo, Emanuela; Leonardi, Matilde

    2014-06-01

    To assess the association between sociodemographic factors and factors related to number and type of comorbidities, and presence of severe disability in a population of adults applying for disability certification. Data have been collected using a protocol based on the ICF Classification. Hierarchical logistic regression was performed to assess the association between severe disability and sex, age, marital status, education, living situation, number, and type of diagnosis. In total, 552 individuals were enrolled (46.2% men, mean age 62.3 years), with an average of three diagnoses, mostly mental, neurological, and cardiovascular. Being married/cohabitating and higher education levels were associated with reduced odds of severe disability; living with other individuals, such as in an institution, was associated with increased odds. Our results show that age and education level were associated with severe disability, and that no association with number of diseases was found: in our opinion, this is specific to the population of individuals with disability.

  10. RELATIONSHIPS BETWEEN ANATOMICAL FEATURES AND INTRA-RING WOOD DENSITY PROFILES IN Gmelina arborea APPLYING X-RAY DENSITOMETRY

    Directory of Open Access Journals (Sweden)

    Mario Tomazelo-Filho

    2007-12-01

    Full Text Available Four annual tree-rings (2 of juvenile wood and 2 of mature wood were sampled from fast-growth plantations ofGmelina arborea in two climatic conditions (dry and wet tropical in Costa Rica. Each annual tree-ring was divided in equal parts ina radial direction. For each part, X-ray density as well as vessel percentage, length and width fiber, cell wall thickness and lumendiameter were measured. Wood density and profile patterns of cell dimension demonstrated inconsistency between juvenile andmature wood and climatic conditions. The Pearson correlation matrix showed that intra-ring wood density was positively correlatedwith the cell wall thickness and negatively correlated with vessel percentage, fiber length, lumen diameter and width. The forwardstepwise regressions determined that: (i intra-ring wood density variation could be predicted from 76 to 96% for anatomicalvariation; (ii cell wall thickness was the most important anatomical feature to produce intra-ring wood density variation and (iii thevessel percentage, fiber length, lumen diameter and width were the second most statically significant characteristics to intra-ring wooddensity, however, with low participation of the determination coefficient of stepwise regressions.

  11. Numerical analysis of applied magnetic field dependence in Malmberg-Penning Trap for compact simulator of energy driver in heavy ion fusion

    Science.gov (United States)

    Sato, T.; Park, Y.; Soga, Y.; Takahashi, K.; Sasaki, T.; Kikuchi, T.; Harada, Nob

    2016-05-01

    To simulate a pulse compression process of space charge dominated beams in heavy ion fusion, we have demonstrated a multi-particle numerical simulation as an equivalent beam using the Malmberg-Penning trap device. The results show that both transverse and longitudinal velocities as a function of external magnetic field strength are increasing during the longitudinal compression. The influence of space-charge effect, which is related to the external magnetic field, was observed as the increase of high velocity particles at the weak external magnetic field.

  12. A Plan for the Development of Fusion Energy. Final Report to Fusion Energy Sciences Advisory Committee, Fusion Development Path Panel

    Energy Technology Data Exchange (ETDEWEB)

    None, None

    2003-03-05

    This report presents a plan for the deployment of a fusion demonstration power plant within 35 years, leading to commercial application of fusion energy by mid-century. The plan is derived from the necessary features of a demonstration fusion power plant and from the time scale defined by President Bush. It identifies critical milestones, key decision points, needed major facilities and required budgets.

  13. Optical Fiber Fusion Splicing

    CERN Document Server

    Yablon, Andrew D

    2005-01-01

    This book is an up-to-date treatment of optical fiber fusion splicing incorporating all the recent innovations in the field. It provides a toolbox of general strategies and specific techniques that the reader can apply when optimizing fusion splices between novel fibers. It specifically addresses considerations important for fusion splicing of contemporary specialty fibers including dispersion compensating fiber, erbium-doped gain fiber, polarization maintaining fiber, and microstructured fiber. Finally, it discusses the future of optical fiber fusion splicing including silica and non-silica based optical fibers as well as the trend toward increasing automation. Whilst serving as a self-contained reference work, abundant citations from the technical literature will enable readers to readily locate primary sources.

  14. 基于AdaBoost的多特征融合指纹检索方法%Fingerprint Retrieval Method of Multi-feature Fusion Based on AdaBoost

    Institute of Scientific and Technical Information of China (English)

    王富丽; 欧阳建权

    2012-01-01

    为提高视频内容检索方法的鲁棒性,提出一种基于AdaBoost的多特征融合指纹检索方法.通过对样本数据的训练,自适应地获得尺度不变特征变换特征、运动特征以及音频特征的权重,利用得到的权重融合音视频特征,以产生视频指纹.实验结果表明,该方法的准确性较高,在尺度变化、亮度变化、音频噪音攻击下具有较好的鲁棒性.%This paper proposes a fingerprint retrieval method of multi-feature fusion based on AdaBoost to improve the robust of video fingerprint. The proposed method can gain the weight of Scale Invariant Feature Transform(SIFT), temporal and audio feature adaptively by training the sample data, then fuse audio-video feature to produce video fingerprint according to the weights of the three features. Experimental results show that this method can gain higher accuracy, and have good robustness under various geometric, brightness modification and audio noise.

  15. Enhanced Face Recognition using Data Fusion

    Directory of Open Access Journals (Sweden)

    Alaa Eleyan

    2012-12-01

    Full Text Available In this paper we scrutinize the influence of fusion on the face recognition performance. In pattern recognition task, benefiting from different uncorrelated observations and performing fusion at feature and/or decision levels improves the overall performance. In features fusion approach, we fuse (concatenate the feature vectors obtained using different feature extractors for the same image. Classification is then performed using different similarity measures. In decisions fusion approach, the fusion is performed at decisions level, where decisions from different algorithms are fused using majority voting. The proposed method was tested using face images having different facial expressions and conditions obtained from ORL and FRAV2D databases. Simulations results show that the performance of both feature and decision fusion approaches outperforms the single performances of the fused algorithms significantly.

  16. EDITORIAL: Safety aspects of fusion power plants

    Science.gov (United States)

    Kolbasov, B. N.

    2007-07-01

    importance for the fusion power plant research programmes. The objective of this Technical Meeting was to examine in an integrated way all the safety aspects anticipated to be relevant to the first fusion power plant prototype expected to become operational by the middle of the century, leading to the first generation of economically viable fusion power plants with attractive S&E features. After screening by guest editors and consideration by referees, 13 (out of 28) papers were accepted for publication. They are devoted to the following safety topics: power plant safety; fusion specific operational safety approaches; test blanket modules; accident analysis; tritium safety and inventories; decommissioning and waste. The paper `Main safety issues at the transition from ITER to fusion power plants' by W. Gulden et al (EU) highlights the differences between ITER and future fusion power plants with magnetic confinement (off-site dose acceptance criteria, consequences of accidents inside and outside the design basis, occupational radiation exposure, and waste management, including recycling and/or final disposal in repositories) on the basis of the most recent European fusion power plant conceptual study. Ongoing S&E studies within the US inertial fusion energy (IFE) community are focusing on two design concepts. These are the high average power laser (HAPL) programme for development of a dry-wall, laser-driven IFE power plant, and the Z-pinch IFE programme for the production of an economically-attractive power plant using high-yield Z-pinch-driven targets. The main safety issues related to these programmes are reviewed in the paper `Status of IFE safety and environmental activities in the US' by S. Reyes et al (USA). The authors propose future directions of research in the IFE S&E area. In the paper `Recent accomplishments and future directions in the US Fusion Safety & Environmental Program' D. Petti et al (USA) state that the US fusion programme has long recognized that the S

  17. 支持向量机的全局局部特征融合目标识别%Target Recognition Based on Support Vector Machine(SVM) Features Fusion

    Institute of Scientific and Technical Information of China (English)

    易晓柯

    2011-01-01

    This paper proposes a target recognition method based on support vector machine features fusion. The method uses nonlinear discrimination analysis and local retain mapping to extract the global and local features and then makes features fusion in order to extract more comprehensive samples and obtain more accurate identification results. Then the support vector machine is used for classification. Since its power to deal with nonlinear and small samples, the identification accuracy is further improved. The simulation results of three plane targets show the effectiveness.%提出一种基于支持向量机的全局局部特征融合目标识别方法,并将其运用到雷达一维距离像目标识别.该方法采用非线性辨别方法与局部保留映射方法分别提取样本的非线性全局特征与局部特征,并进行特征融合,以便提取更全面的样本特征,得到更加准确的识别结果,随后采用支持向量机进行分类识别,利用其对于非线性小样本问题的强大处理能力,进一步改善识别结果.对三种飞机目标的实测雷达一维距离像进行了仿真实验,结果表明了方法的有效性.

  18. Decision time horizon for music genre classification using short time features

    DEFF Research Database (Denmark)

    Ahrendt, Peter; Meng, Anders; Larsen, Jan

    2004-01-01

    In this paper music genre classification has been explored with special emphasis on the decision time horizon and ranking of tapped-delay-line short-time features. Late information fusion as e.g. majority voting is compared with techniques of early information fusion such as dynamic PCA (DPCA......). The most frequently suggested features in the literature were employed including mel-frequency cepstral coefficients (MFCC), linear prediction coefficients (LPC), zero-crossing rate (ZCR), and MPEG-7 features. To rank the importance of the short time features consensus sensitivity analysis is applied...

  19. Feature extraction and fusion for thruster faults of AUV with random disturbance%随机干扰下 AUV 推进器故障特征提取与融合

    Institute of Scientific and Technical Information of China (English)

    张铭钧; 殷宝吉; 刘维新; 王玉甲

    2015-01-01

    The correctness of fault diagnosis results for thrusters of AUV (autonomous underwater vehicle) was frequently influenced by random disturbance ,which was caused by the internal noise of underwater sensors .To decrease the influence ,two feature extraction methods that extracting fault feature from the wavelet approximate component of longitudinal velocity and from the changing rate of control voltage ,and a feature fusion method with normalization were proposed .After the wavelet re‐construction of scale coefficients for wavelet decomposition of longitudinal velocity ,the wavelet ap‐proximate component was obtained .After the derivation of control voltage ,the changing rate was ac‐quired .Two kinds of fault feature were extracted from the wavelet approximate component and the changing rate based on modified Bayes′classification algorithm separately .Following the feature fu‐sion of the two kinds of fault feature based on evidence theory ,the fusion result were normalized .The effectiveness of the proposed methods was verified by the experiments of AUV ,which were carried out in the pool .%针对水下传感器自身噪声等随机干扰影响水下机器人推进器故障诊断结果的准确性问题,为降低随机干扰影响,提出了基于小波近似分量提取故障特征、基于控制信号变化率提取故障特征以及带有归一化处理的特征融合方法。将速度信号进行小波分解,对分解后的尺度系数进行小波重构得到小波近似分量;对控制信号进行求导,得到控制信号变化率。基于修正贝叶斯算法,分别从小波近似分量和控制信号变化率中提取故障特征。基于证据理论对提取到的两个单一特征进行融合,并将融合结果进行归一化处理。水下机器人实验样机的水池实验结果验证了所提方法的有效性。

  20. 基于子模式的Gabor特征融合的单样本人脸识别%A Sub-Pattern Gabor Features Fusion Method for Single Sample Face Recognition

    Institute of Scientific and Technical Information of China (English)

    王科俊; 邹国锋

    2013-01-01

    To overcome the limitations of traditional face recognition methods for single sample face recognition, a sub-pattern Gabor features fusion method for single sample face recognition is proposed. Firstly, facial local features are extracted by Gabor wavelet transformation. Then, the Gabor face images are blocked to take full advantage of the spatial location information of facial organs, and the minimum distance classifiers are used for each sub-pattern. Finally, the recognition result is achieved by the fusion of the sub-pattern classifiers' results at the decision level. According to the difference of sub-pattern construction and fusion method, two kinds of sub-pattern Gabor features integration programs are proposed. The experimental results and comparative analysis on ORL face database and CAS-PEAL-R1 face database show that the proposed method achieves better classification rate and improves the performance of single sample face recognition system.%针对传统人脸识别方法在单训练样本条件下效果不佳的缺点,提出基于子模式的Gabor特征融合方法并用于单样本人脸识别.首先采用Gabor变换抽取人脸局部信息,为有效利用面部器官的空间位置信息,将Gabor人脸图像分块构成子模式,采用最小距离分类器对各子模式分类.最后对各子模式分类结果做决策级融合得出分类结果.根据子模式构成原则和决策级融合策略不同,提出两种子模式Gabor特征融合方法.利用ORL人脸库和CAS-PEAL-R1人脸库进行实验和比较分析,实验结果表明文中方法有效提高单样本人脸识别的正确率,改善单样本人脸识别系统的性能.

  1. Cold fusion

    Energy Technology Data Exchange (ETDEWEB)

    Suh, Suk Yong; Sung, Ki Woong; Kang, Joo Sang; Lee, Jong Jik [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

    1995-02-01

    So called `cold fusion phenomena` are not confirmed yet. Excess heat generation is very delicate one. Neutron generation is most reliable results, however, the records are erratic and the same results could not be repeated. So there is no reason to exclude the malfunction of testing instruments. The same arguments arise in recording {sup 4}He, {sup 3}He, {sup 3}H, which are not rich in quantity basically. An experiment where plenty of {sup 4}He were recorded is attached in appendix. The problem is that we are trying to search cold fusion which is permitted by nature or not. The famous tunneling effect in quantum mechanics will answer it, however, the most fusion rate is known to be negligible. The focus of this project is on the theme that how to increase that negligible fusion rate. 6 figs, 4 tabs, 1512 refs. (Author).

  2. Spinal Fusion

    Science.gov (United States)

    ... results in predictable healing. Autograft is currently the “gold standard” source of bone for a fusion. The ... pump. With this technique, the patient presses a button that delivers a predetermined amount of narcotic pain ...

  3. Peptides and membrane fusion : Towards an understanding of the molecular mechanism of protein-induced fusion

    NARCIS (Netherlands)

    Pecheur, EI; Sainte-Marie, J; Bienvenue, A; Hoekstra, D

    1999-01-01

    Processes such as endo- or exocytosis, membrane recycling, fertilization and enveloped viruses infection require one or more critical membrane fusion reactions. A key feature in viral and cellular fusion phenomena is the involvement of specific fusion proteins. Among the few well-characterized fusio

  4. 基于人眼视觉特性的NSCT医学图像自适应融合%Adaptive MedicaI Image Fusion Based on Human VisuaI Features

    Institute of Scientific and Technical Information of China (English)

    戴文战; 姜晓丽; 李俊峰

    2016-01-01

    医学图像融合对于临床诊断具有重要的应用价值。针对多模态医学图像特性,本文提出一种基于人类视觉特性的医学图像自适应融合方法。首先,对经配准的源图像进行非间隔采样轮廓变换((Nonsubsampled Coutour-let,NSCT)多尺度分解,得到低频子带和若干高频方向子带;其次,根据低频子带集中了大部分源图像能量和决定图像轮廓的特点,采用区域能量与平均梯度相结合的方法进行融合;根据人眼对图像对比度及边缘、纹理的高敏感度,在高频子带系数的选取时提出区域拉普拉斯能量、方向对比度与脉冲耦合神经网络(Pulse Coupled Neural Network,PCNN)相结合的融合策略;进而,提出了把与人类视觉高度一致的加权结构相似度(Weighted Structure Similarity,WSSIM)作为图像融合目标函数,自适应地获取各子带的最优权值;最后,对灰度图像和彩色图像进行了大量融合比较实验,并对不同融合方法进行分析对比。实验结果表明:本文算法不仅可以有效保留源图像的信息,而且可以使融合图像灰度级更分散,更好地保留了图像边缘信息,具有更好的视觉效果。%Medical image fusion has very important application value for medical image analysis and diseases diagno-sis.According to the characteristics of multi modality medical image and human visual features,a new medical image fusion algorithm in NSCT (nonsubsampled coutourlet,NSCT)domain is proposed.Firstly,source images after registration are de-composed into low and high frequency sub-bands using NSCT.According to the low frequency subbands concentrating the majority energy of the source image and determining the image coutour,a fusion rule based on weighted region average ener-gy combined with average gradient is adopted in low frequency subband coefficients.Moreover,according to human visual system which is more sensitive to

  5. Intense fusion neutron sources

    Science.gov (United States)

    Kuteev, B. V.; Goncharov, P. R.; Sergeev, V. Yu.; Khripunov, V. I.

    2010-04-01

    The review describes physical principles underlying efficient production of free neutrons, up-to-date possibilities and prospects of creating fission and fusion neutron sources with intensities of 1015-1021 neutrons/s, and schemes of production and application of neutrons in fusion-fission hybrid systems. The physical processes and parameters of high-temperature plasmas are considered at which optimal conditions for producing the largest number of fusion neutrons in systems with magnetic and inertial plasma confinement are achieved. The proposed plasma methods for neutron production are compared with other methods based on fusion reactions in nonplasma media, fission reactions, spallation, and muon catalysis. At present, intense neutron fluxes are mainly used in nanotechnology, biotechnology, material science, and military and fundamental research. In the near future (10-20 years), it will be possible to apply high-power neutron sources in fusion-fission hybrid systems for producing hydrogen, electric power, and technological heat, as well as for manufacturing synthetic nuclear fuel and closing the nuclear fuel cycle. Neutron sources with intensities approaching 1020 neutrons/s may radically change the structure of power industry and considerably influence the fundamental and applied science and innovation technologies. Along with utilizing the energy produced in fusion reactions, the achievement of such high neutron intensities may stimulate wide application of subcritical fast nuclear reactors controlled by neutron sources. Superpower neutron sources will allow one to solve many problems of neutron diagnostics, monitor nano-and biological objects, and carry out radiation testing and modification of volumetric properties of materials at the industrial level. Such sources will considerably (up to 100 times) improve the accuracy of neutron physics experiments and will provide a better understanding of the structure of matter, including that of the neutron itself.

  6. Information fusion for palmprint authentication

    Science.gov (United States)

    Wu, Xiangqian; Wang, Kuanquan; Zhang, David

    2006-04-01

    A palmprint can be represented using different features and the different representations reflect the different characteristic of a palmprint. Fusion of multiple palmprint features may enhance the performance of a palmprint authentication system. This paper investigates the fusion of two types of palmprint information: the phase (called PalmCode) and the orientation (called OrientationCode). The PalmCode is extracted using the 2-D Gabor filters based algorithm and the OrientationCode is computed using several directional templates. Then several fusion strategies are investigated and compared. The experimental results show that the fusion of the PalmCode and OrientationCode using the Product, Sum and Weighted Sum strategies can greatly improve the accuracy of palmprint authentication, which is up to 99.6%.

  7. Applied anatomy of presacral approach for axial lumbar interbody fusion%轴向腰椎椎间融合术入路的应用解剖

    Institute of Scientific and Technical Information of China (English)

    李向明; 张玉松; 侯致典; 吴涛; 丁自海

    2011-01-01

    Objective The aim of this study was to evaluate the safety of the presacral approach for axial lumbar interbody fusion.Methods (1) The pelvic region of 12 adult cadavers was dissected and analyzed.All specimens were divided in the median sagittal plane.The main goal of these dissection was to understand the fascial structures of the presacral space and measure some data correlated with the rectosacral fascia and pelvic splanchnic nerves.(2) The blunt guide pin was inserted using the technique described by Marotta into 24 pelvic-halves, the distance from the trocar to important structures in the presacral space was measured.Results (1) The fascial structures of the presacral space was multilaminar, it could be divided into five levels.(2) The rectosacral fascia was found in 11 out of 12 specimens (91.7%),it originated from the parietal presacral fascia at the level of S2 in 16.7% ,S3 in 41.7% and S4 in 33.3%.The presacral space was divided into superior and inferior portions by the rectosacral fascia.(3) Pelvic splanchnic nerves confined the dissection of the lower rectum, its length which could be used as a measure of the'sagittal safe zone' for presacral space was (22.9±3.2)mm.(4) In this study, the shortest distance from the guide pin to pelvic splanchnic nerves was (7.8 ±l.9)mm, the vertical distance to the S3/4 junction was (15.0 ±3.6)mm.Conclusion It is risky to perform the presacral approach for axial lumbar interbody fusion because of the presence of the rectosacral fascia, presacral venous plexus and the vascular variations.%目的 探讨经骶前间隙轴向腰椎椎间融合术入路的安全性.方法 (1) 12具(24侧)防腐固定成人骨盆段标本,解剖骶前间隙,观察骶前的筋膜层次,骶直肠筋膜,盆内脏神经等,测量骶直肠筋膜和盆内脏神经的相关解剖数据.(2)参照Marotta方法,模拟手术置入导针,测量导针在骶前间隙中的相关解剖学数据.结果 (1)骶前的筋膜可分为5层;(2)

  8. 基于特征融合的多模态身份识别方法研究%Research on multimodal biometric authentication using feature level fusion

    Institute of Scientific and Technical Information of China (English)

    林玲; 周新民; 商琳; 高阳

    2011-01-01

    Multimodal biometric authentication method is proposed, which combines the features of human faces and palmprints. Biometrics features are extracted using Gabor wavelet and two dimensional principal component analysis (2DPCA) techniques, and identification is carried out by the nearest neighbor classifier according to the combined biometric features of two modals and a new weighting strategy. The AMP, ORL and Poly-U databases are used as the test data in the experiments. Experimental results show that combination of two different modals can provide more authentication information, which generates higher security and more accuracy than the single model authentication.%研究了多模态身份识别问题,结合人脸和掌纹两种不同生理特征,提出了基于特征融合的多模态身份识别方法.对人脸和掌纹图像分别进行Gabor小波、二维主元变换(2DPCA)提取图像特征,根据新的权重算法,结合两种模态的特征,利用最邻近分类器进行分类识别.在AMP、ORL人脸库和Poly-U掌纹图像库中的实验结果表明,两种模态的融合能更多地给出决策分析所需的特征信息相比传统的单一模态的人脸或掌纹识别具有较高的识别率,更具安全性和准确性.

  9. PredPPCrys: accurate prediction of sequence cloning, protein production, purification and crystallization propensity from protein sequences using multi-step heterogeneous feature fusion and selection.

    Directory of Open Access Journals (Sweden)

    Huilin Wang

    Full Text Available X-ray crystallography is the primary approach to solve the three-dimensional structure of a protein. However, a major bottleneck of this method is the failure of multi-step experimental procedures to yield diffraction-quality crystals, including sequence cloning, protein material production, purification, crystallization and ultimately, structural determination. Accordingly, prediction of the propensity of a protein to successfully undergo these experimental procedures based on the protein sequence may help narrow down laborious experimental efforts and facilitate target selection. A number of bioinformatics methods based on protein sequence information have been developed for this purpose. However, our knowledge on the important determinants of propensity for a protein sequence to produce high diffraction-quality crystals remains largely incomplete. In practice, most of the existing methods display poorer performance when evaluated on larger and updated datasets. To address this problem, we constructed an up-to-date dataset as the benchmark, and subsequently developed a new approach termed 'PredPPCrys' using the support vector machine (SVM. Using a comprehensive set of multifaceted sequence-derived features in combination with a novel multi-step feature selection strategy, we identified and characterized the relative importance and contribution of each feature type to the prediction performance of five individual experimental steps required for successful crystallization. The resulting optimal candidate features were used as inputs to build the first-level SVM predictor (PredPPCrys I. Next, prediction outputs of PredPPCrys I were used as the input to build second-level SVM classifiers (PredPPCrys II, which led to significantly enhanced prediction performance. Benchmarking experiments indicated that our PredPPCrys method outperforms most existing procedures on both up-to-date and previous datasets. In addition, the predicted crystallization

  10. Trophoblast fusion.

    Science.gov (United States)

    Huppertz, Berthold; Gauster, Martin

    2011-01-01

    The villous trophoblast of the human placenta is the epithelial cover of the fetal chorionic villi floating in maternal blood. This epithelial cover is organized in two distinct layers, the multinucleated syncytiotrophoblast directly facing maternal blood and a second layer of mononucleated cytotrophoblasts. During pregnancy single cytotrophoblasts continuously fuse with the overlying syncytiotrophoblast to preserve this end-differentiated layer until delivery. Syncytial fusion continuously supplies the syncytiotrophoblast with compounds of fusing cytotrophoblasts such as proteins, nucleic acids and lipids as well as organelles. At the same time the input of cytotrophoblastic components is counterbalanced by a continuous release of apoptotic material from the syncytiotrophoblast into maternal blood. Fusion is an essential step in maintaining the syncytiotrophoblast. Trophoblast fusion was shown to be dependant on and regulated by multiple factors such as fusion proteins, proteases and cytoskeletal proteins as well as cytokines, hormones and transcription factors. In this chapter we focus on factors that may be involved in the fusion process of trophoblast directly or that may prepare the cytotrophoblast to fuse.

  11. 多特征双重匹配验证的驾驶员脸部融合检测%Face Fusion Detection of Multi-feature and Double Matching Verification for Driver

    Institute of Scientific and Technical Information of China (English)

    孙伟; 张为公; 张小瑞; 陈刚; 吕成绪

    2009-01-01

    Referring to the limitation of driver face detection algorithm based on single feature in detection precision and reliability, a novel fusion algorithm of driver face detection is proposed. Firstly, an improved face detection algorithm based on Haar-like feature is used to detect the possibly existing face region in the whole image. Then, the detected region is extended adaptively and a face detection algorithm based on skin color feature in YCbCr space is used to detect the face again in the extended area. Finally, double matching verification is made by the defined area coincidence degree and geometric prior knowledge of human face and fusion detection of driver face region is achieved by establishing relevant location rules. Experiment results in various complicated road conditions show the effectiveness of the proposed algorithm.%针对基于单一特征驾驶员脸部检测算法在检测精度和可靠性方面的局限性,提出了一种新颖的驾驶员脸部检测融合算法.首先采用改进的基于Haar-like特征的人脸检测算法在整幅图像上检测出可能存在的初始人脸区域,然后自适应地扩大初始人脸区域范围,并在此基础上利用基于肤色特征的方法在YCbCr空间上进行脸部的二次检测,最后根据定义的脸部区域重合度和人脸几何先验知识对驾驶员脸部区域进行双重匹配验证进而制定相应的定位规则对脸部进行融合检测.各种复杂路况下的实验结果证明了该算法的有效性.

  12. 多路数据融合在光伏电池组件监控系统中的应用研究%Research on Applying Multi-Sensor Data Fusion in Photovoltaic Array Monitoring System

    Institute of Scientific and Technical Information of China (English)

    胡涛; 谭建军; 黄勇; 孙先波; 易金桥

    2012-01-01

    为了提高光伏电站的使用效率,根据光伏电站的特点,本文设计了一种基于无线传感器网络和多路数据融合技术的光伏电池组件监控系统.通过传感器节点采集单块电池组件的瞬间电压、电流和温度,并对这三类数据实现初级数据融合;然后将初级数据融合数据包通过由ZigBee协议实现的无线传感器网络传输到中心节点;中线节点对所有初级数据融合数据包实现二级数据融合并通过串口传输至服务器;服务器通过基于残差值的数据包解析算法分析各块电池组件的运行数据,以判断电池组件是否正常工作,为光伏电站的维护和管理提供有效的信息.%According to the features of photovoltaic power station,we design a photovoltaic array monitoring system based on wireless sensor network and multi-sensor data fusion in order to improve the u-tilization efficiency of photovoltaic power station. Sensor nodes capture the instantaneous voltage, current and temperature of each photovoltaic array. Then the system is responsible for junior fusion of those data and transmitting junior data packets to the central node through wireless sensor network based on ZigBee. The central node is in charge of senior fusion of all junior data packets and transmitting senior data packets to the server through serial port. Through the data packet residual value parsing algorithm, the server analyzes each photovoltaic array state to determine whether photovoltaic array work correctly or not,providing the useful information for managing and maintaining photovoltaic power station.

  13. 自适应融合目标和背景的图像特征提取方法%An Image Feature Extraction Method Based on Adaptive Fusion of Object and Background

    Institute of Scientific and Technical Information of China (English)

    于来行; 冯林; 张晶; 刘胜蓝

    2016-01-01

    针对现有基于结构元描述的图像特征提取算法缺少连续像素或结构元的相关性描述,对图像特征的区分能力不足的问题。通过定义新的结构元和自适应向量融合模型,并引入连通粒概念,提出一种加权量化方法对图像目标和背景进行自适应融合。首先根据视觉选择特性定义9种新的结构元,并且构建了连通粒属性及分层统计模型;然后通过颜色转换和结构元匹配生成相应的映射子图,从中提取统计结构元和连通性特征向量;最后利用自适应向量融合模型把各分量合并为一组特征向量用于图像检索。在3个 Corel 数据集上的实验结果表明,与其他算法相比,文中方法性能更稳定,能达到更高的检索精度;该方法既能描述图像的全局特征,又能反映图像的局部细节信息。%Existing algorithms based on structural descriptor are not accurate enough to discriminate the image features, because they lack the correlation description of continuous pixels or structural elements. To address this problem, this paper presents a novel weighted quantization method, which can adaptively integrate images object features and background features into one image histogram. The proposed method includes the new structure elements definition, adaptive vector fusion model and connected granule concept. Firstly, based on the visual se-lection characteristics, nine kinds of new structure elements are defined. The connected granule' attributes are given and the hierarchical statistical model is constructed. Secondly, the corresponding mapping sub-graphs are generated by color transformation and structure elements matching. Meanwhile, the feature vectors of statistical structure elements and connectivity are extracted. Finally, a set of feature vectors are obtained by utilizing adap-tive vector fusion model for image retrieval. Extensive experiments on three Corel-datasets demonstrate that

  14. Ablation-erosion analyses of various fusion material surfaces and developments of surface erosion monitors for notification of fusion chamber maintenance times, as an example: Visible light transparent SiC and up-conversion phosphors applied to plasma facing surface structures, useful for versatile purposes to protect and diagnose fusion chambers and so on

    Science.gov (United States)

    Kasuya, K.; Motokoshi, S.; Taniguchi, S.; Nakai, M.; Tokunaga, K.; Kolacek, K.; Schmidt, J.; Frolov, O.; Straus, J.; Matejicek, J.; Choukourov, A.

    2017-01-01

    Two kinds of pulsed lasers in Japan and Czech Republic were used to irradiate various sample materials to investigate the surface erosion thresholds under very hazardous environments including nuclear fusion chambers. The first was ArF laser in ILT and the second was XUV laser in IPP. These data were in-cooperated with our former data to build up our material strength data for our succeeding applications of various materials to a variety of fields. As an example, we proposed surface erosion monitors to notice the fusion chamber maintenance times with which the facilities can be protected from the collapses under very severe operation conditions. These kinds of monitors are expected to be useful for future different kinds of mechanical structures not only for the fusion chambers but also various chambers for many purposes. Special upconversion phosphors are also newly proposed to be used as the candidate materials to measure the thermal inputs onto the front surfaces of the armor structures. Optical transparent SiC was also newly tested to enrich our data base for our future diagnostic and protection possibilities.

  15. Iterative guided image fusion

    Directory of Open Access Journals (Sweden)

    Alexander Toet

    2016-08-01

    Full Text Available We propose a multi-scale image fusion scheme based on guided filtering. Guided filtering can effectively reduce noise while preserving detail boundaries. When applied in an iterative mode, guided filtering selectively eliminates small scale details while restoring larger scale edges. The proposed multi-scale image fusion scheme achieves spatial consistency by using guided filtering both at the decomposition and at the recombination stage of the multi-scale fusion process. First, size-selective iterative guided filtering is applied to decompose the source images into approximation and residual layers at multiple spatial scales. Then, frequency-tuned filtering is used to compute saliency maps at successive spatial scales. Next, at each spatial scale binary weighting maps are obtained as the pixelwise maximum of corresponding source saliency maps. Guided filtering of the binary weighting maps with their corresponding source images as guidance images serves to reduce noise and to restore spatial consistency. The final fused image is obtained as the weighted recombination of the individual residual layers and the mean of the approximation layers at the coarsest spatial scale. Application to multiband visual (intensified and thermal infrared imagery demonstrates that the proposed method obtains state-of-the-art performance for the fusion of multispectral nightvision images. The method has a simple implementation and is computationally efficient.

  16. Adjoint affine fusion and tadpoles

    Science.gov (United States)

    Urichuk, Andrew; Walton, Mark A.

    2016-06-01

    We study affine fusion with the adjoint representation. For simple Lie algebras, elementary and universal formulas determine the decomposition of a tensor product of an integrable highest-weight representation with the adjoint representation. Using the (refined) affine depth rule, we prove that equally striking results apply to adjoint affine fusion. For diagonal fusion, a coefficient equals the number of nonzero Dynkin labels of the relevant affine highest weight, minus 1. A nice lattice-polytope interpretation follows and allows the straightforward calculation of the genus-1 1-point adjoint Verlinde dimension, the adjoint affine fusion tadpole. Explicit formulas, (piecewise) polynomial in the level, are written for the adjoint tadpoles of all classical Lie algebras. We show that off-diagonal adjoint affine fusion is obtained from the corresponding tensor product by simply dropping non-dominant representations.

  17. Adjoint affine fusion and tadpoles

    CERN Document Server

    Urichuk, Andrew

    2016-01-01

    We study affine fusion with the adjoint representation. For simple Lie algebras, elementary and universal formulas determine the decomposition of a tensor product of an integrable highest-weight representation with the adjoint representation. Using the (refined) affine depth rule, we prove that equally striking results apply to adjoint affine fusion. For diagonal fusion, a coefficient equals the number of nonzero Dynkin labels of the relevant affine highest weight, minus 1. A nice lattice-polytope interpretation follows, and allows the straightforward calculation of the genus-1 1-point adjoint Verlinde dimension, the adjoint affine fusion tadpole. Explicit formulas, (piecewise) polynomial in the level, are written for the adjoint tadpoles of all classical Lie algebras. We show that off-diagonal adjoint affine fusion is obtained from the corresponding tensor product by simply dropping non-dominant representations.

  18. Adjoint affine fusion and tadpoles

    Energy Technology Data Exchange (ETDEWEB)

    Urichuk, Andrew, E-mail: andrew.urichuk@uleth.ca [Physics and Astronomy Department, University of Lethbridge, Lethbridge, Alberta T1K 3M4 (Canada); Walton, Mark A., E-mail: walton@uleth.ca [Physics and Astronomy Department, University of Lethbridge, Lethbridge, Alberta T1K 3M4 (Canada); International School for Advanced Studies (SISSA), via Bonomea 265, 34136 Trieste (Italy)

    2016-06-15

    We study affine fusion with the adjoint representation. For simple Lie algebras, elementary and universal formulas determine the decomposition of a tensor product of an integrable highest-weight representation with the adjoint representation. Using the (refined) affine depth rule, we prove that equally striking results apply to adjoint affine fusion. For diagonal fusion, a coefficient equals the number of nonzero Dynkin labels of the relevant affine highest weight, minus 1. A nice lattice-polytope interpretation follows and allows the straightforward calculation of the genus-1 1-point adjoint Verlinde dimension, the adjoint affine fusion tadpole. Explicit formulas, (piecewise) polynomial in the level, are written for the adjoint tadpoles of all classical Lie algebras. We show that off-diagonal adjoint affine fusion is obtained from the corresponding tensor product by simply dropping non-dominant representations.

  19. Fusion Machinery

    DEFF Research Database (Denmark)

    Sørensen, Jakob Balslev; Milosevic, Ira

    2015-01-01

    the vesicular SNARE VAMP2/synaptobrevin-2 and the target (plasma membrane) SNAREs SNAP25 and syntaxin-1 results in fusion and release of neurotransmitter, synchronized to the electrical activity of the cell by calcium influx and binding to synaptotagmin. Formation of the SNARE complex is tightly regulated...... and appears to start with syntaxin-1 bound to an SM (Sec1/Munc18-like) protein. Proteins of the Munc13-family are responsible for opening up syntaxin and allowing sequential binding of SNAP-25 and VAMP2/synaptobrevin-2. N- to C-terminal “zippering” of the SNARE domains leads to membrane fusion...

  20. 基于Gabor幅值特征和相位特征相融合的ISAR像目标识别%ISAR Image Recognition with Fusion of Gabor Magnitude and Phase Feature

    Institute of Scientific and Technical Information of China (English)

    王芳; 盛卫星; 马晓峰; 王昊

    2013-01-01

    A new Inverse Synthetic Aperture Radar (ISAR) target recognition method with the fusion of Gabor magnitude and phase feature is proposed. Firstly, the corresponding Gabor Magnitude Maps (GMMs) and Gabor phase information are obtained by convolving the ISAR image with multi-scale and multi-orientation Gabor filters. Secondly, each GMM is divided into several non-overlapping rectangular units, and the histogram of unit is computed and combined as the magnitude histogram feature. Thirdly, the local Gabor phase pattern is obtained by combining quadrant bit coding with local XOR pattern, and the block histogram feature is extracted from the local Gabor phase pattern. Then, the fusion of the Gabor magnitude and phase feature is used as the feature of ISAR image. Finally, five-type aircraft models are classified by using a nearest neighbor classifier with 2c as a dissimilarity measure in the computed feature space. The recognition method is tested on ISAR data simulated from Greco electromagnetic soft ware. Compared with other recognition methods, the numerical results show that the proposed method is effective and has higher recognition performance.%  该文提出一种基于 Gabor 小波变换幅值特征和相位特征相融合的 ISAR 像目标识别算法。首先将 ISAR像进行Gabor多尺度分析,对不同尺度、不同方向的Gabor幅值图像划分为若干矩形不重叠的子块,分别计算每个子块的直方图分布,将其联合起来作为Gabor的幅值特征;然后结合象限二进制编码和局部异或算子提取Gabor相位信息的局部相位模式,对得到的局部相位模式同样提取分块直方图特征;再把提取的幅值特征和相位特征相融合作为ISAR像最终的Gabor特征;最后在2c统计量作为不相似度量计算的特征空间里,采用最近邻分类器完成5类目标的分类识别。通过使用Greco电磁软件仿真的5类目标的ISAR数据对该方法进行目标识别的验证,并

  1. 双树复小波特征融合的板材压缩感知协同检测与分选%Dual-tree complex wavelet feature fusion and wood board collaborative detection by compressed sensing

    Institute of Scientific and Technical Information of China (English)

    李超; 张怡卓; 于慧伶; 曹军

    2015-01-01

    提出一种对板材表面缺陷和纹理进行协同快速准确检测的算法. 根据双树复小波所特有的方向性和时移不变性,研究了板材表面图像的双树复小波特征提取及融合算法,对板材表面图像进行3级双树复小波分解得到40个特征向量,并通过遗传算法优选出23个关键特征,优选后的特征能够较为完整地表达板材图像的复杂信息并减小数据冗余. 最后采用压缩感知理论,将优选后的特征向量作为样本矩阵列,构造出训练样本数据字典,通过最小残差完成对板材表面信息的分类识别. 实验对木材表面存在的弦切纹、径切纹、活结和死结等4类柞木样本进行了检测,正确率分别为91. 8%、100%、96. 4%和91. 8%,该算法能够以95%的平均识别率完成板材表面缺陷、纹理的协同检测.%A quick and accurate collaborative classification method for wood defects and texture was pro-posed. As dual-tree complex wavelet has the advantages of approximate shift invariance and good direc-tional selectivity, dual-tree complex wavelet feature was extracted from wood board image and the fusion method was discussed. Three-level dual-tree complex wavelet decomposition was carried out to the surface image and 40 features were got, then genetic algorithm ( GA) was used for feature selection and 23 fea-tures were chosen. Feature fusion can better express the surface information and meanwhile heavily re-duce the data redundancy. Finally, wood surface classification was completed by using compressed sens-ing ( CS) , optimized dimensional feature vector was used as sample matrix and data dictionary of training samples was constructed, then, wood surface classification was completed by using least residual at last. Four types of Xylosma samples:radial texture, tangential texture, live knot and dead knot were used for experiment , the classification accuracy of the above four types were 91. 8%, 100%, 96. 4% and 91. 8%respectively

  2. GPU Parallel Particle Filter Object Tracking Algorithm Based on Multiple Feature Fusion%GPU 并行实现多特征融合粒子滤波目标跟踪算法

    Institute of Scientific and Technical Information of China (English)

    赵嵩; 徐彦; 曹海旺; 杨恒

    2015-01-01

    提出了一种多特征融合粒子滤波跟踪算法,并利用 GPU (Graphic Processing Unit)技术对算法进行了并行优化。针对单一特征描述目标模型的缺陷,此算法采用了具有互补性的灰度与梯度直方图特征建立目标模型,从而提高粒子滤波算法跟踪的稳定性和精度。同时,针对粒子滤波计算量大的缺点,此算法对粒子滤波进行了基于GPU 的并行优化设计和实现,从而提升跟踪算法的计算速度。可以满足算法的实时性应用。%A parallel particle filter object tracking algorithm is given out,which is based on multiple feature fusion with the help of GPU (Graphic Processing Unit)technology.Due to the limitation of the model representation based on single visual feature,two complementary visual features,which are gray histogram and gradient histogram,are used in the algorithm to improve the tracking stability and accuracy.Moreover,to handle the large amount computation cost of the particle filter,a GPU parallel optimized scheme is designed to improve the algorithm speed. and can meet the real-time application requirement.

  3. Social tag refinement model based on feature fusion and multi-correlation consistency%基于特征融合与多元关系一致性的社会标签精化模型

    Institute of Scientific and Technical Information of China (English)

    李云毅; 苗夺谦; 卫志华

    2016-01-01

    User-provided tags are accessible on photo sharing websites which facilitate further tag-based multimedia applications,such as image ranking,image retrieval and tag recommendation.However,user-supplied tags for web images are often irrelevant,imprecise and incomplete,which will lower the performances of image management tasks.And many efforts have been made to solve this problem.Image,user tags and author are three basic elements of web images.However,only one or two basic elements and few correlation consistency among them are considered in many image tag refinement algorithms.In this paper,an optimization model based on feature fusion and multi-cor-relation consistency is proposed for social tag refinement.Image visual features,user-supplied tags,and authors’in-formation are all considered in the proposed model.And multi-correlation consistency such as visual content-semantics consistency between image-pair,tag-tag correlation consistency and the user-user correlation consistency are put to use in our framework.Which will gain bettter refinement performance than those works that only consider one or two elements and few correlation consistency between web images.Traditionally,people often connect some visual features into a long vector or only choose one feature for image tag refinement task.The former will suffer from the problem of “Curse of Dimensionality”and the latter can not obtain sufficient image visual information for the task.Therefore,a feature fusion idea is put forward in our framework.Multiple image visual features are considered and weights for each feature can be calculated automatically to estimate the importance of different features by an iteraitve process.F-score macro is used as evaluation criterion like many other works.And comparative experiment results on MIR-Flickr dataset show that our performances are comparable with works of state-of-the-art.And the advantages of feature fusion and multi-correlation consistency are also proved by

  4. IRDO: Iris Recognition by fusion of DTCWT and OLBP

    Directory of Open Access Journals (Sweden)

    Arunalatha J S

    2015-03-01

    Full Text Available Iris Biometric is a physiological trait of human beings. In this paper, we propose Iris an Recognition using Fusion of Dual Tree Complex Wavelet Transform (DTCWT and Over Lapping Local Binary Pattern (OLBP Features. An eye is preprocessed to extract the iris part and obtain the Region of Interest (ROI area from an iris. The complex wavelet features are extracted for region from the Iris DTCWT. OLBP is further applied on ROI to generate features of magnitude coefficients. The resultant features are generated by fusing DTCWT and OLBP using arithmetic addition. The Euclidean Distance (ED is used to compare test iris with database iris features to identify a person. It is observed that the values of Total Success Rate (TSR and Equal Error Rate (EER are better in the case of proposed IRDO compared to the state-of-the art techniques.

  5. Magnetic fusion; La fusion magnetique

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2002-07-01

    This document is a detailed lecture on thermonuclear fusion. The basic physics principles are recalled and the technological choices that have led to tokamaks or stellarators are exposed. Different aspects concerning thermonuclear reactors such as safety, economy and feasibility are discussed. Tore-supra is described in details as well as the ITER project.

  6. Alternate laser fusion drivers

    Energy Technology Data Exchange (ETDEWEB)

    Pleasance, L.D.

    1979-11-01

    Over the past few years, several laser systems have been considered as possible laser fusion drivers. Recently, there has been an increasing effort to evaluate these systems in terms of a reactor driver application. The specifications for such a system have become firmer and generally more restrictive. Several of the promising candidates such as the group VI laser, the metal vapor excimers and some solid state lasers can be eliminated on the basis of inefficiency. New solid state systems may impact the long range development of a fusion driver. Of the short wavelength gas lasers, the KrF laser used in conjunction with Raman compression and pulse stacking techniques is the most promising approach. Efficiencies approaching 10% may be possible with this system. While technically feasible, these approaches are complex and costly and are unsatisfying in an aethetic sense. A search for new lasers with more compelling features is still needed.

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

    Science.gov (United States)

    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.

  8. Physiological Sensor Signals Classification for Healthcare Using Sensor Data Fusion and Case-Based Reasoning

    Directory of Open Access Journals (Sweden)

    Shahina Begum

    2014-07-01

    Full Text Available 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.

  9. Tame Fusion

    Institute of Scientific and Technical Information of China (English)

    S.D. Scott

    2003-01-01

    The first section of this paper covers preliminaries. Essentially, the next four cover units. It is shown that a compatible nearring with DCCR is Nnilpotent if and only if every maximal right N-subgroup is a right ideal. The last five sections relate to fusion (I.e., N-groups minimal for being generated by Nsubgroups, where each is N-isomorphic to a given N-group). Right N-subgroups of a tame nearring N with DCCR, minimal for not annihilating a minimal ideal from the left, are self monogenic and N-isomorphic. That this holds for any collection of minimal ideals is significant. Here, the right N-subgroup involved is a 'fusion product' of the 'components'.

  10. Carpal Fusion

    OpenAIRE

    2012-01-01

    Carpal fusion may be seen in hereditary and nonhereditary conditions such as acrocallosal syndrome,acromegaly, Apert syndrome, arthrogryposis, Carpenter syndrome, chromosomal abnormalities, ectrodactyly-ectodermal dysplasia-cleft (EEC) syndrome, the F form of acropectorovertebral dysgenesis or the F syndrome, fetal alcohol syndrome, Holt-Oram syndrome, Leopard syndrome, multiple synostosis syndrome, oligosyndactyly syndrome, Pfeiffer-like syndrome, scleroderma, split hand and foot malformatio...

  11. Fusion rules of equivariantizations of fusion categories

    OpenAIRE

    2012-01-01

    We determine the fusion rules of the equivariantization of a fusion category $\\mathcal{C}$ under the action of a finite group $G$ in terms of the fusion rules of $\\mathcal{C}$ and group-theoretical data associated to the group action. As an application we obtain a formula for the fusion rules in an equivariantization of a pointed fusion category in terms of group-theoretical data. This entails a description of the fusion rules in any braided group-theoretical fusion category.

  12. Fusion rules of equivariantizations of fusion categories

    OpenAIRE

    Burciu, Sebastian; Natale, Sonia

    2012-01-01

    We determine the fusion rules of the equivariantization of a fusion category $\\mathcal{C}$ under the action of a finite group $G$ in terms of the fusion rules of $\\mathcal{C}$ and group-theoretical data associated to the group action. As an application we obtain a formula for the fusion rules in an equivariantization of a pointed fusion category in terms of group-theoretical data. This entails a description of the fusion rules in any braided group-theoretical fusion category.

  13. Arts Fusion 2004 showcases local talents

    OpenAIRE

    Elliott, Jean

    2004-01-01

    The Virginia Tech School of the Arts (SOTA) announces Arts Fusion 2004, the inaugural weeklong celebration of the arts on campus and in the Blacksburg community, April 19-25. Arts Fusion 2004 will feature a variety of events in music, art, theater, dance, film, and poetry.

  14. Research and Application of Bi-spectrum Features Fusion Based on Batch Drilling Monitoring Signals%批量钻削监测信号双谱特征融合研究及应用

    Institute of Scientific and Technical Information of China (English)

    周友行; 张俏; 田茂; 喻思亮

    2014-01-01

    for every feature, these step quality classification is performed using feature weighted fuzzy cluster algorithm and to be contrast with the manual detection result. The results show that there are organic connections between the bi-spectrum feature of monitoring signals and drilling step quality, and the consistency quality testing of batch drilling step is realized by fusion of clustering bi-spectrum features.

  15. Feature Selection by Applying Feature Resolution and Correlation Matrix of Equivalence Classes%采用特征分辨率和等价类相关矩阵的特征选择

    Institute of Scientific and Technical Information of China (English)

    符红霞; 黄成兵

    2012-01-01

    特征选择是文本分类的关键步骤之一,所选特征子集的优劣直接影响文本分类的结果.首先分析了词频和文档频并在此基础上对文档频进行优化.然后又以此为基础提出了特征分辨率并先用它初选文本特征.紧接着又把粗糙集引入进来并给出了一个基于等价类相关矩阵的属性约简算法,以此来进一步消除冗余特征.仿真结果表明上述方法无论是在精确度和召回率方面,还是时间性能及平均分类精度方面,都具有一定的优势.%Feature selection is one of the key steps in text categorization, selected feature subset directly influences results of text categorization. Firstly, word frequency and document frequency were analyzed, and an improved document frequency was improved. And then, feature resolution was presented based on the improved document frequency. Subsequently, rough sets were introduced into feature selection and a new attribute reduction algorithm based on correlation matrix of equivalence classes was provided. Finally, combining feature resolution with the provided attribute reduction algorithm, a new feature selection method was proposed. The new feature selection method firstly uses feature resolution to select text features and filter out some terms to reduce the sparsity of text feature spaces, and then employs the provided attribute reduction algorithm to eliminate redundancy. The simulation results show that the proposed feature selection method to a certain extent has advantages in precision rate, recall rate, time performance and average classification accuracy.

  16. Fourier domain image fusion for differential X-ray phase-contrast breast imaging.

    Science.gov (United States)

    Coello, Eduardo; Sperl, Jonathan I; Bequé, Dirk; Benz, Tobias; Scherer, Kai; Herzen, Julia; Sztrókay-Gaul, Anikó; Hellerhoff, Karin; Pfeiffer, Franz; Cozzini, Cristina; Grandl, Susanne

    2017-04-01

    X-Ray Phase-Contrast (XPC) imaging is a novel technology with a great potential for applications in clinical practice, with breast imaging being of special interest. This work introduces an intuitive methodology to combine and visualize relevant diagnostic features, present in the X-ray attenuation, phase shift and scattering information retrieved in XPC imaging, using a Fourier domain fusion algorithm. The method allows to present complementary information from the three acquired signals in one single image, minimizing the noise component and maintaining visual similarity to a conventional X-ray image, but with noticeable enhancement in diagnostic features, details and resolution. Radiologists experienced in mammography applied the image fusion method to XPC measurements of mastectomy samples and evaluated the feature content of each input and the fused image. This assessment validated that the combination of all the relevant diagnostic features, contained in the XPC images, was present in the fused image as well.

  17. sEMG Pattern Recognition Based on Multi Feature Fusion of Wavelet Transform%基于小波变换的多特征融合sEMG模式识别

    Institute of Scientific and Technical Information of China (English)

    于亚萍; 孙立宁; 张峰峰; 张建法

    2016-01-01

    In view of the poor characterization of single feature value,multi feature fusion based on different wavelet basis was adopted to extract the surface EMG signal according to multi resolution analysis of wavelet transform. The experiment was conducted on ten testers and collected signals for four basic lower limb movements in daily life. First of all,discrete wavelet transform was used to decompose the surface EMG signals in multi-scale with DB, Dmey and Bior wavelet basis respectively. After that,it was founded that the characterization effects of different muscle vary by different extraction way. In order to combine the characteristics of different features ,features were fused to analyze and compare. At last,the feature values were input to the Elman neural network and BP neural net⁃work for pattern recognition and comparison analysis. Experimental results showed that the recognition rate ob⁃tained by fusing the eigenvalues is higher than single feature with the accuracy up to 98.7%,and the BP neural net⁃work is better than the Elman neural network.%针对单一特征值表征能力差的情况,根据小波变换的多分辨分析思想,采用基于多种母小波的多特征融合的特征提取方法对表面肌电信号进行特征提取。本实验对十名测试人员进行肌电信号的采集,对日常生活中的四个基本下肢动作进行测试。首先,分别基于DB、Dmey和Bior三种不同的母小波,采用离散小波变换通过不同的分析方法对表面肌电信号进行多尺度分解。然后,通过分析发现,不同肌肉在不同特征提取方式下表征效果存在差异,为了结合不同特征方式的特点对基于不同小波基的特征值进行融合分析并比较。最后,将特征值分别输入到Elman神经网络和BP神经网络进行模式识别并比较分析。实验结果表明:通过对不同特征值进行识别比较,融合处理的特征值可以达到98.7%的识别率,并且,BP

  18. Epidemiologic Features and Prognosis of Patients Who Was Diagnosed Having Type 2 Diabetes Mellitus and Applied to a Community Health Center

    Directory of Open Access Journals (Sweden)

    Sevilay Hindistan

    2009-08-01

    Full Text Available AIM: The study was designed to investigate the prognosis and the epidemiologic features of people who was diagnosed having type 2 DM and Applied to the Community Health Center. METHOD: This study which was carried out at Catak Health Branch of Trabzon Erdogdu Health Center in April, May, and June in 2008 is a descriptive and cross-sectional field study. All of the patients with Type 2 DM diagnosis who came to the Health Center for routine control (55 people were involved in the study. The aim of the study was explained to each participant in the study and their oral consent was taken. As the data collection instrument, diabetes surveillance form which includes of socio-demographic features, risk factors, blood sugar diagnosis criteria, body mass index, chronic complications and foot examination was used. Diabetes surveillance form was shaped by modifying the diabetes diagnosis form which was structured by Erdogan and Nahcivan (1999. The data obtained were evaluated through number and percentage distribution, mean, chi square test, correlation and variant analyses techniques. RESULTS: Age mean of the patients was 59.4±10.7 and 85.5% of them was female. Average diagnosis age was 53.2±12.5, average diabetes year was 6,6±6,6. 45.5% of the patients were obese, 12.7% of them morbid obese and diabetes history in the family was about 54.5%. It was found that 56.3% patients had blood glucose level was 140 mg/dl and 54.5% of the patients’ HbA1c level were higher than 7%. When lipid parameter levels of the patients were examined, it was seen that HDL cholesterol level was (E<35,K<45 for 52.7% of the patients and that was lower than the target treatment level; LDL cholesterol level was 100mg/dl for 76.4%; and total cholesterol level was higher than 200 mg/dl 49.1% of the patients. A statistically significant positive correlation was found between diabetes year of the patients and HbA1c level (r=0.291, p=0.031. 8.6 had % neuropathy, 1.7% of them had

  19. Prediction of HPLC retention times of tebipenem pivoxyl and its degradation products in solid state by applying adaptive artificial neural network with recursive features elimination.

    Science.gov (United States)

    Mizera, Mikołaj; Talaczyńska, Alicja; Zalewski, Przemysław; Skibiński, Robert; Cielecka-Piontek, Judyta

    2015-05-01

    A sensitive and fast HPLC method using ultraviolet diode-array detector (DAD)/electrospray ionization tandem mass spectrometry (Q-TOF-MS/MS) was developed for the determination of tebipenem pivoxyl and in the presence of degradation products formed during thermolysis. The chromatographic separations were performed on stationary phases produced in core-shell technology with particle diameter of 5.0 µm. The mobile phases consisted of formic acid (0.1%) and acetonitrile at different ratios. The flow rate was 0.8 mL/min while the wavelength was set at 331 nm. The stability characteristics of tebipenem pivoxyl were studied by performing stress tests in the solid state in dry air (RH=0%) and at an increased relative air humidity (RH=90%). The validation parameters such as selectivity, accuracy, precision and sensitivity were found to be satisfying. The satisfied selectivity and precision of determination were obtained for the separation of tebipenem pivoxyl from its degradation products using a stationary phase with 5.0 µm particles. The evaluation of the chemical structure of the 9 degradation products of tebipenem pivoxyl was conducted following separation based on the stationary phase with a 5.0 µm particle size by applying a Q-TOF-MS/MS detector. The main degradation products of tebipenem pivoxyl were identified: a product resulting from the condensation of the substituents of 1-(4,5-dihydro-1,3-thiazol-2-yl)-3-azetidinyl]sulfanyl and acid and ester forms of tebipenem with an open β-lactam ring in dry air at an increased temperature (RH=0%, T=393 K) as well as acid and ester forms of tebipenem with an open β-lactam ring at an increased relative air humidity and an elevated temperature (RH=90%, T=333 K). Retention times of tebipenem pivoxyl and its degradation products were used as training data set for predictive model of quantitative structure-retention relationship. An artificial neural network with adaptation protocol and extensive feature selection process

  20. Region-based fusion of infrared and visible images using nonsubsampled contourlet transform

    Institute of Scientific and Technical Information of China (English)

    Baolong Guo; Qiang Zhang; Ye Hou

    2008-01-01

    With the nonsubsampled contourlet transform (NSCT), a novel region-segmentation-based fusion algorithm for infrared (IR) and visible images is presented.The IR image is segmented according to the physical features of the target.The source images are decomposed by the NSCT, and then, different fusion rules for the target regions and the background regions are employed to merge the NSCT coefficients respectively.Finally, the fused image is obtained by applying the inverse NSCT.Experimental results show that the proposed algorithm outperforms the pixel-based methods, including the traditional wavelet-based method and NSCT-based method.

  1. FUSION WORLD

    Institute of Scientific and Technical Information of China (English)

    Caroline; 黄颖(翻译)

    2009-01-01

    Fusion World”科技展示体验中心是英国设计公司MET Studio为新加坡科技研究局(A*Star)的科学工程委员会(SERC)所设计的,位于启汇城的办公地点,用于展示该委员会的精选技术作品,以吸引潜在的客户和启汇城内的学生购买群体。

  2. DECISION LEVEL FUSION OF LIDAR DATA AND AERIAL COLOR IMAGERY BASED ON BAYESIAN THEORY FOR URBAN AREA CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    H. Rastiveis

    2015-12-01

    Full Text Available Airborne Light Detection and Ranging (LiDAR generates high-density 3D point clouds to provide a comprehensive information from object surfaces. Combining this data with aerial/satellite imagery is quite promising for improving land cover classification. In this study, fusion of LiDAR data and aerial imagery based on Bayesian theory in a three-level fusion algorithm is presented. In the first level, pixel-level fusion, the proper descriptors for both LiDAR and image data are extracted. In the next level of fusion, feature-level, using extracted features the area are classified into six classes of “Buildings”, “Trees”, “Asphalt Roads”, “Concrete roads”, “Grass” and “Cars” using Naïve Bayes classification algorithm. This classification is performed in three different strategies: (1 using merely LiDAR data, (2 using merely image data, and (3 using all extracted features from LiDAR and image. The results of three classifiers are integrated in the last phase, decision level fusion, based on Naïve Bayes algorithm. To evaluate the proposed algorithm, a high resolution color orthophoto and LiDAR data over the urban areas of Zeebruges, Belgium were applied. Obtained results from the decision level fusion phase revealed an improvement in overall accuracy and kappa coefficient.

  3. The Dark Side of Cell Fusion

    Directory of Open Access Journals (Sweden)

    Daniel Bastida-Ruiz

    2016-04-01

    Full Text Available Cell fusion is a physiological cellular process essential for fertilization, viral entry, muscle differentiation and placental development, among others. In this review, we will highlight the different cancer cell-cell fusions and the advantages obtained by these fusions. We will specially focus on the acquisition of metastatic features by cancer cells after fusion with bone marrow-derived cells. The mechanism by which cancer cells fuse with other cells has been poorly studied thus far, but the presence in several cancer cells of syncytin, a trophoblastic fusogen, leads us to a cancer cell fusion mechanism similar to the one used by the trophoblasts. The mechanism by which cancer cells perform the cell fusion could be an interesting target for cancer therapy.

  4. Traversable Region Detection Based on One-class SVM and Multi-visual Features Fusion%基于one-class SVM与融合多可视化特征的可通行区域检测

    Institute of Scientific and Technical Information of China (English)

    高华; 赵春霞; 韩光

    2011-01-01

    For the difficulty in obtaining the complete non-traversable region samples, a traversable region detection method based on one-class SVM (support vector machine) is proposed to improve the adaptability of algorithms in different scenes. This article formulates traversability detection as a one-class classification problem for the first time. An improved feature extraction method is proposed with the fusion of color and texture. Image data of every color channels are transformed by discrete cosine transform (DCT), then the DCT coefficients are decomposed using pyramid decomposition. Mean and variance in each decomposition are used to describe characteristic window. Traversable region pattern is generated by training the traversable samples using one-class SVM. Experiments show that the algorithm recognizes new data well, and performs with high detection accuracy and low abused detection rate.%针对难以获取完备的非可通行区域样本问题,为提高算法在不同场景的适应性,首次把可通行性检测看作单类分类问题,提出了基于one-class SVM的可通行区域检测算法.提出一种改进的融合颜色和纹理的特征提取方法,对各颜色分量进行离散余弦变换(DCT)变换,对DCT系数进行金字塔分解,用每个分解的均值和方差描述特征窗口.利用one-class SVM进行训练生成可通行区域的模式.实验表明,方法对新数据具有很好的识别能力,具有较高的检测精度和较低的误检率.

  5. Carpal Fusion

    Directory of Open Access Journals (Sweden)

    Jalal Jalalshokouhi*

    2012-05-01

    Full Text Available Carpal fusion may be seen in hereditary and nonhereditary conditions such as acrocallosal syndrome,acromegaly, Apert syndrome, arthrogryposis, Carpenter syndrome, chromosomal abnormalities, ectrodactyly-ectodermal dysplasia-cleft (EEC syndrome, the F form of acropectorovertebral dysgenesis or the F syndrome, fetal alcohol syndrome, Holt-Oram syndrome, Leopard syndrome, multiple synostosis syndrome, oligosyndactyly syndrome, Pfeiffer-like syndrome, scleroderma, split hand and foot malformation, Stickler syndrome, thalidomide embryopathy, Turner syndrome and many other conditions as mentioned in Rubinstein-Taybi's book. Sometimes there is no known causative disease.Diagnosis is usually made by plain X-ray during studying a syndrome or congenital disease or could be an incidental finding like our patients. Hand bone anomalies are more common in syndromes or other congenital or non-hereditary conditions, but polydactyly, syndactyly or oligodactyly and carpal fusions are interesting. X-ray is the modality of choice, but MRI and X-ray CT with multiplanar reconstructions may be used for diagnosis.

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

    Science.gov (United States)

    Fan, Lei

    ., 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.

  7. Gradient-based compressive image fusion

    Institute of Scientific and Technical Information of China (English)

    Yang CHEN‡; Zheng QIN

    2015-01-01

    We present a novel image fusion scheme based on gradient and scrambled block Hadamard ensemble (SBHE) sam-pling for compressive sensing imaging. First, source images are compressed by compressive sensing, to facilitate the transmission of the sensor. In the fusion phase, the image gradient is calculated to reflect the abundance of its contour information. By com-positing the gradient of each image, gradient-based weights are obtained, with which compressive sensing coefficients are achieved. Finally, inverse transformation is applied to the coefficients derived from fusion, and the fused image is obtained. Information entropy (IE), Xydeas’s and Piella’s metrics are applied as non-reference objective metrics to evaluate the fusion quality in line with different fusion schemes. In addition, different image fusion application scenarios are applied to explore the scenario adaptability of the proposed scheme. Simulation results demonstrate that the gradient-based scheme has the best per-formance, in terms of both subjective judgment and objective metrics. Furthermore, the gradient-based fusion scheme proposed in this paper can be applied in different fusion scenarios.

  8. 分布场的多特征融合目标跟踪方法%Study of multi-feature fusion methods for distribution fields in object tracking

    Institute of Scientific and Technical Information of China (English)

    宋长贺; 李云松; 宁纪锋; 牟永强

    2015-01-01

    针对分布场目标跟踪算法中使用分布场的目标模型估计鲁棒性较弱的问题,提出一种将分布场与其他特征有效融合的方法,来提高分布场特征表示的有效性。在对每个像素点进行分布场估计时,原始算法仅通过该点的灰度直方图来估计其在灰度空间上的分布,并没有考虑该点的位置与结构信息。为了实现在分布场中对目标结构信息的有效表示,通过对目标中包含结构信息的特殊点进行特殊编码以实现结构信息的融合。实验表明,对于一些复杂环境下的挑战视频序列,融合了结构信息的分布场比原始分布场在目标跟踪的成功率上具有显著优势,且优于当前流行的4种目标跟踪方法。%In order to improve the robustness of the distribution fields ( DF) as an object model in object tracking , we propose a mutli‐feature fusion framework for the distribution fields . In the original DF‐based method , the density histogram was used to estimate the DF of a pixel , but the structural information was ignored . For effective representation of the structural information in the DFs , a special type of coding for the featured points which contain structural information is merged into the DFs . Experiments show that the new method outperforms the original method and four other state‐of‐the‐art tracking algorithms for some challenging video clips .

  9. Fusion as a future energy source

    Science.gov (United States)

    Ward, D. J.

    2016-11-01

    Fusion remains the main source of energy generation in the Universe and is indirectly the origin of nearly all terrestrial energy (including fossil fuels) but it is the only fundamental energy source not used directly on Earth. Here we look at the characteristics of Earth-based fusion power, how it might contribute to future energy supply and what that tells us about the future direction of the R&D programme. The focus here is Magnetic Confinement Fusion although many of the points apply equally to inertial confinement fusion.

  10. Simultaneous Channel and Feature Selection of Fused EEG Features Based on Sparse Group Lasso

    Directory of Open Access Journals (Sweden)

    Jin-Jia Wang

    2015-01-01

    Full Text Available Feature extraction and classification of EEG signals are core parts of brain computer interfaces (BCIs. Due to the high dimension of the EEG feature vector, an effective feature selection algorithm has become an integral part of research studies. In this paper, we present a new method based on a wrapped Sparse Group Lasso for channel and feature selection of fused EEG signals. The high-dimensional fused features are firstly obtained, which include the power spectrum, time-domain statistics, AR model, and the wavelet coefficient features extracted from the preprocessed EEG signals. The wrapped channel and feature selection method is then applied, which uses the logistical regression model with Sparse Group Lasso penalized function. The model is fitted on the training data, and parameter estimation is obtained by modified blockwise coordinate descent and coordinate gradient descent method. The best parameters and feature subset are selected by using a 10-fold cross-validation. Finally, the test data is classified using the trained model. Compared with existing channel and feature selection methods, results show that the proposed method is more suitable, more stable, and faster for high-dimensional feature fusion. It can simultaneously achieve channel and feature selection with a lower error rate. The test accuracy on the data used from international BCI Competition IV reached 84.72%.

  11. Simultaneous channel and feature selection of fused EEG features based on Sparse Group Lasso.

    Science.gov (United States)

    Wang, Jin-Jia; Xue, Fang; Li, Hui

    2015-01-01

    Feature extraction and classification of EEG signals are core parts of brain computer interfaces (BCIs). Due to the high dimension of the EEG feature vector, an effective feature selection algorithm has become an integral part of research studies. In this paper, we present a new method based on a wrapped Sparse Group Lasso for channel and feature selection of fused EEG signals. The high-dimensional fused features are firstly obtained, which include the power spectrum, time-domain statistics, AR model, and the wavelet coefficient features extracted from the preprocessed EEG signals. The wrapped channel and feature selection method is then applied, which uses the logistical regression model with Sparse Group Lasso penalized function. The model is fitted on the training data, and parameter estimation is obtained by modified blockwise coordinate descent and coordinate gradient descent method. The best parameters and feature subset are selected by using a 10-fold cross-validation. Finally, the test data is classified using the trained model. Compared with existing channel and feature selection methods, results show that the proposed method is more suitable, more stable, and faster for high-dimensional feature fusion. It can simultaneously achieve channel and feature selection with a lower error rate. The test accuracy on the data used from international BCI Competition IV reached 84.72%.

  12. Sensor Fusion of Monocular Cameras and Laser Rangefinders for Line-Based Simultaneous Localization and Mapping (SLAM Tasks in Autonomous Mobile Robots

    Directory of Open Access Journals (Sweden)

    Xinzheng Zhang

    2012-01-01

    Full Text Available 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.

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

    Science.gov (United States)

    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.

  14. Catalysed fusion

    CERN Document Server

    Farley, Francis

    2012-01-01

    A sizzling romance and a romp with subatomic particles at CERN. Love, discovery and adventure in the city where nations meet and beams collide. Life in a large laboratory. As always, the challenges are the same. Who leads? Who follows? Who succeeds? Who gets the credit? Who gets the women or the men? Young Jeremy arrives in CERN and joins the quest for green energy. Coping with baffling jargon and manifold dangers, he is distracted by radioactive rats, lovely ladies and an unscrupulous rival. Full of doubts and hesitations, he falls for a dazzling Danish girl, who leads him astray. His brilliant idea leads to a discovery and a new route to cold fusion. But his personal life is scrambled. Does it bring fame or failure? Tragedy or triumph?

  15. Conceptual exploration package for data fusion

    Science.gov (United States)

    Jousselme, Anne-Laure; Grenier, Dominic; Bosse, Eloi

    2000-04-01

    In this paper, we present a software package designed to explore data fusion area applied to different contexts. This tool, called CEPfuse (Conceptual Exploration Package for Data Fusion) provides a good support to become familiar with all concepts and vocabulary linked to data fusion. Developed with Matlab 5.2, it's also a good tool to test, compare and analyze algorithms. Although the core of this package is evidential reasoning and identity information fusion, it has been conceived to develop all the interesting part of the Multi-Sensor Data Fusion system. Actually, because we concentrate our research work on identity information fusion, the principal included algorithms are Dempster- Shafer rules of combination, Shafer-Logan algorithms for hierarchical structures, and several decision rules.

  16. Non-Trivial Feature Derivation for Intensifying Feature Detection Using LIDAR Datasets Through Allometric Aggregation Data Analysis Applying Diffused Hierarchical Clustering for Discriminating Agricultural Land Cover in Portions of Northern Mindanao, Philippines

    Science.gov (United States)

    Villar, Ricardo G.; Pelayo, Jigg L.; Mozo, Ray Mari N.; Salig, James B., Jr.; Bantugan, Jojemar

    2016-06-01

    Leaning on the derived results conducted by Central Mindanao University Phil-LiDAR 2.B.11 Image Processing Component, the paper attempts to provides the application of the Light Detection and Ranging (LiDAR) derived products in arriving quality Landcover classification considering the theoretical approach of data analysis principles to minimize the common problems in image classification. These are misclassification of objects and the non-distinguishable interpretation of pixelated features that results to confusion of class objects due to their closely-related spectral resemblance, unbalance saturation of RGB information is a challenged at the same time. Only low density LiDAR point cloud data is exploited in the research denotes as 2 pts/m2 of accuracy which bring forth essential derived information such as textures and matrices (number of returns, intensity textures, nDSM, etc.) in the intention of pursuing the conditions for selection characteristic. A novel approach that takes gain of the idea of object-based image analysis and the principle of allometric relation of two or more observables which are aggregated for each acquisition of datasets for establishing a proportionality function for data-partioning. In separating two or more data sets in distinct regions in a feature space of distributions, non-trivial computations for fitting distribution were employed to formulate the ideal hyperplane. Achieving the distribution computations, allometric relations were evaluated and match with the necessary rotation, scaling and transformation techniques to find applicable border conditions. Thus, a customized hybrid feature was developed and embedded in every object class feature to be used as classifier with employed hierarchical clustering strategy for cross-examining and filtering features. This features are boost using machine learning algorithms as trainable sets of information for a more competent feature detection. The product classification in this

  17. Fusion of colour and monochromatic images with edge emphasis

    Directory of Open Access Journals (Sweden)

    Rade M. Pavlović

    2014-02-01

    colours and an improvement in visibility of structures from the monochrome can be achieved when they are used to encode a single HVS colour dimension consistently. The lαβ colour system effectively decorrelates the colour opponency and intensity channels and manipulating one causes no visible changes in the others. Colour fusion can be achieved by fusing one of the colour opponency channels with the monochrome image. We use the Laplacian pyramid fusion known to be one of the most robust monochrome fusion methods available. The Laplacian, also known as the DOLP (difference of low-pass pyramid is a reversible multiresolution representation that expresses the image through a series of sub-band images of decreasing resolution, increasing scale, whose coefficients broadly express fine detail contrast at that location and scale. A simple fusion strategy creates a new fused pyramid by copying the largest absolute input coefficient at each location. The β channel of the lαβ space represents the red-green opponency and we base our fusion on encoding this channel of the colour input with the monochrome image. This causes warmer objects (lighter in IR to appear redder in the fused image. The fusion proceeds in several steps. Initially we transform the colour input RGB image into the lαβ image. Monochrome fusion is then performed by decomposing the β image and the normalised monochrome into their Laplacian pyramid representations. We use the select max strategy to construct the fused pyramid but we only apply this to a small number of higher resolution pyramid sub-bands. Larger scale features in lower resolution sub-band images that constitute the natural context of the scene are sourced entirely from the colour image (β. This ensures that well defined smaller objects from the IR image are transferred robustly into the fused image as well as the broad scene context from the colour input. Reconstructing the fused pyramid produces the fused β image which is combined with the

  18. Massachusetts Institute of Technology, Plasma Fusion Center, Technical Research Programs

    Energy Technology Data Exchange (ETDEWEB)

    Davidson, Ronald C.

    1980-08-01

    A review is given of the technical programs carried out by the Plasma Fusion Center. The major divisions of work areas are applied plasma research, confinement experiments, fusion technology and engineering, and fusion systems. Some objectives and results of each program are described. (MOW)

  19. APPLYING PRINCIPAL CURVES IN COMPLEX FINGERPRINT IMAGE FEATURE EXTRACTION%主曲线在复杂指纹图像特征提取中的应用

    Institute of Scientific and Technical Information of China (English)

    高迎; 张红云

    2013-01-01

    在自动指纹识别系统中,特征抽取是关键步骤之一。主曲线具有自相合特性,对模式特征能够进行很好的描述,并能够有效维持结构信息。因此,选用推广的多边形主曲线算法并加以改进来提取指纹主曲线,并在此基础上进一步实现指纹特征提取和伪特征检测。实验结果表明,该算法能够在短时间内获得更好的指纹骨架,指纹特征提取的准确率也较高。%In automated fingerprint recognition system , feature extraction is one of the key procedures .Principal curve has the property of self-consistency , can well depict the pattern feature and can effectively keep the structure information .Therefore , we choose the promoted polygonal principal curve algorithm and improve it to extract the principal curve of the fingerprint , and further implement on this basis the fingerprint extraction and pseudo feature inspection .Experimental results demonstrate that the algorithm in this paper can get better fingerprint skeleton in short time period , the accuracy rate of fingerprint feature extraction is higher as well .

  20. In-Process modeling method of applying blend feature simplification%应用过渡特征简化的工序几何建模方法

    Institute of Scientific and Technical Information of China (English)

    唐健钧; 田锡天; 耿俊浩

    2013-01-01

    To build In-Process model rapidly,an In-Process modeling method was proposed by combining blend feature simplification with boundary extraction of machining feature.Boundary of the machining feature was obtained by simplifying blend features in machining feature,and it was selected to build processing volume characteristic by rotation,sweep,or stretching.Boolean subtraction between the former In-Process model and the processing volume characteristics was operated to obtain In-Process model.Edge blends and vertex blends were distinguish,and the situation of support surface lose was analyzed when blend features simplified.A process of typical shaft parts turning In-Process modeling was provided to analyze the In-Process model's dimension change rule which was built by different boundary of machining feature.The effectiveness of proposed method was verified by examples.%为了快速建立工序几何模型,提出一种将过渡特征简化和加工特征边界提取相结合的工序几何模型建立方法.首先对加工特征中的过渡特征进行简化,获得加工特征边界;然后选择加工特征边界,利用旋转、扫掠或拉伸方法建立加工体积特征;用前一道工序的几何模型与该加工体积特征做布尔差运算,求得本工序的工序几何模型.在简化过渡特征时区分边过渡和点过渡,并综合考虑支持面丢失等情况.以典型轴类零件的车削加工工序几何建模为例,分析了选择不同加工特征边界建立的工序几何模型的尺寸变化规律,验证了该方法的有效性.

  1. 聚变堆第一壁连续W/Cu梯度材料的热工性能优化%Thermo-technical performance optimization on first wall in fusion reactor applied with continuous W/Cu functionally graded material

    Institute of Scientific and Technical Information of China (English)

    赵永强; 黄生洪; 汪卫华

    2016-01-01

    , there is a more prominent advantage for composition continuous W/Cu graded material applied in first wall design of fusion reactor due to its continuous variation of thermal physical properties and mechanical properties.

  2. Fault diagnosis of power networks applying CE-SVM and fuzzy integral fusion%采用交叉熵支持向量机和模糊积分的电网故障诊断

    Institute of Scientific and Technical Information of China (English)

    边莉; 边晨源

    2016-01-01

    为了解决分布式电网故障诊断中局部电网内部故障和相邻区域联络线故障的诊断问题,采用交叉熵支持向量机( cross entropy support vector machine,CE-SVM)的改进方法,提出一种基于后验概率输出的CE-SVM和模糊积分动态融合的大电网故障诊断策略。首先通过网络分区算法将电网分割成连通且计算负担平衡的子区域;采用历史数据离线训练各局部CE-SVM模块,根据故障报警信息选择性触发局部CE-SVM实现局部电网内部的故障诊断;利用模糊密度动态调节算法构建模糊积分环节,关联融合相连区域CE-SVM模块关于联络线故障的后验概率输出,实现联络线故障的综合决策。该方法不仅可以应对局部网络内部的故障诊断,也可以有效处理相邻区域间联络线的故障诊断问题。仿真结果看出:所得到的诊断结论正确,并且对于处理保护器和断路器报警信息丢失或不正确动作的情况具有较好的容错性。%A fault diagnosis method for power networks based on posterior probability CE-SVM and fuzzy integral dynamic fusion was proposed. The aim was to solve the problem of division fault diagnosis inside the local network and for the tie lines connecting local network. Firstly, a graph partitioning method was used to the large power network into connected sub-networks with balanced working burdens. Historical data was applied to train local CE-SVMs and local CE-SVM modules were selectively triggered according to local alarm information. Fuzzy integral fusion department constructed by fuzzy densities dynamic adjus-ted algorithm was used to fuse posterior probability of the tie lines fault that outputted by local CE-SVM modules for tie line fault identification. The method can not merely diagnose the faults inside local net-work, but also solve the fault diagnosis problem of tie lines. The simulation results indicate that the pro-posed method is effective and have good fault

  3. Fusion Plasma Theory project summaries

    Energy Technology Data Exchange (ETDEWEB)

    1993-10-01

    This Project Summary book is a published compilation consisting of short descriptions of each project supported by the Fusion Plasma Theory and Computing Group of the Advanced Physics and Technology Division of the Department of Energy, Office of Fusion Energy. The summaries contained in this volume were written by the individual contractors with minimal editing by the Office of Fusion Energy. Previous summaries were published in February of 1982 and December of 1987. The Plasma Theory program is responsible for the development of concepts and models that describe and predict the behavior of a magnetically confined plasma. Emphasis is given to the modelling and understanding of the processes controlling transport of energy and particles in a toroidal plasma and supporting the design of the International Thermonuclear Experimental Reactor (ITER). A tokamak transport initiative was begun in 1989 to improve understanding of how energy and particles are lost from the plasma by mechanisms that transport them across field lines. The Plasma Theory program has actively-participated in this initiative. Recently, increased attention has been given to issues of importance to the proposed Tokamak Physics Experiment (TPX). Particular attention has been paid to containment and thermalization of fast alpha particles produced in a burning fusion plasma as well as control of sawteeth, current drive, impurity control, and design of improved auxiliary heating. In addition, general models of plasma behavior are developed from physics features common to different confinement geometries. This work uses both analytical and numerical techniques. The Fusion Theory program supports research projects at US government laboratories, universities and industrial contractors. Its support of theoretical work at universities contributes to the office of Fusion Energy mission of training scientific manpower for the US Fusion Energy Program.

  4. 采用多特征融合的自动适配区选择方法%Automatic suitable-matching area selection method based on multi-feature fusion

    Institute of Scientific and Technical Information of China (English)

    罗海波; 常铮; 余新荣; 丁庆海

    2011-01-01

    Target tracking with local non-texture is a difficult point and hot topic in the field of ground imaging guidance. Since the automatic suitable-matching area selection is an effective method to solve this problem, an algorithm of automatic suitable-matching area selection based on multi-feature fusion was proposed. Firstly, the edge density, the average edge strength, the edge direction dispersion degree andthe space distance were integrated to form a suitable-matching measure function. Then, the credibility of suitable-matching of each point in the image was calculated by this function. Lastly, through developing adaptive selection strategy to the suitable-matching area, three suitable-matching areas with high credibility were segmented as target template for matching tracking. Experimental results show that the segmented suitable-matching area with proposed algorithm can achieve more tracking precision compared with the results judged by the human experience. This proposed algorithm can be widely used in the applications of the ground imaging-guided target tracking with local non-texture target and the scene matching task planning.%局部无纹理目标跟踪是当今空地成像制导领域的一个难点和热点问题,而自动适配区选择是解决该难题的一种有效方法.介绍了一种基于多特征融合的自动适配区选择方法.首先,构造一个融合边缘密度、平均边缘强度、边缘方向离散度以及空间距离的适配性度量函数;然后,采用该函数计算图像中每一点的适配置信度;通过制定适当的适配区选择策略,分割出3个置信度相对较高的适配区,用作匹配跟踪的目标模板.实验结果表明,采用该方法分割出的适配区与通过人工经验判断的结果相近,获得了较好的结果.该方法可广泛用于空地成像制导的局部无纹理目标跟踪以及景象匹配任务规划等应用中.

  5. 基于点扩散函数特征优化融合的水下目标识别%Point spread function based feature optimization and fusion for underwater objet recognition

    Institute of Scientific and Technical Information of China (English)

    王慧斌; 张荣; 陈哲; 徐立中; 沈洁

    2012-01-01

    人类对水下世界探索的热情推动了水下成像及监测系统研究的发展.然而由于水介质光学属性及复杂水下环境的影响,常用的陆地成像及配套算法很难实现理想的效果.因而可以采用设备更新或算法优化两条策略使水下成像监测系统能够适应水下的光学环境.考虑到设备更新在水下场景中实施的困难和较高的资源消耗,沿用传统陆地的光学成像设备进行水下图像数据采集,并利用点扩散函数优化及多信息融合的策略来优化水下成像监测系统所用的目标识别算法,解决水下光学成像中由于散焦、目标移动、前后向散射噪声等所造成的图像目标细节模糊、对比度差等问题,提高水下自主航行器对水下目标的识别能力.%Our interest to explore the underwater world promotes the scientific development of underwater imaging and monitoring systems.However, due to the optical properties of the aqueous medium and complex underwater environment, the desired results are hard to achieve if the ground-based imaging technologies and algorithms are reused without any optimization.To adapt the underwater imaging monitoring systems to the underwater environments, both updating and the algorithm optimizing can be employed.Considering the high resources and energy consumption and the difficulties in the equipment deployment for hardware updating, the ground-based optical imaging equipment is employed while the point spread function and multiple information fusion method are introduced for the feature optimizing.A noval underwater object recognition algorithm, which is loaded in the underwater imaging monitoring systems, is proposed.The traditional problems caused by the imaging defocusing and the scattering, such as the details blurring and the color decaying, are handled.The experiments conducted in the natural water prove the robust capability of the proposed algorithm for underwater object recognition.

  6. Improving Music Genre Classification by Short Time Feature Integration

    DEFF Research Database (Denmark)

    Meng, Anders; Ahrendt, Peter; Larsen, Jan

    . The problem of making new features on the larger time scale from the short-time features (feature integration) has only received little attention. This paper investigates different methods for feature integration (early information fusion) and late information fusion (assembling of probabilistic outputs...

  7. Appearance-based human gesture recognition using multimodal features for human computer interaction

    Science.gov (United States)

    Luo, Dan; Gao, Hua; Ekenel, Hazim Kemal; Ohya, Jun

    2011-03-01

    The use of gesture as a natural interface plays an utmost important role for achieving intelligent Human Computer Interaction (HCI). Human gestures include different components of visual actions such as motion of hands, facial expression, and torso, to convey meaning. So far, in the field of gesture recognition, most previous works have focused on the manual component of gestures. In this paper, we present an appearance-based multimodal gesture recognition framework, which combines the different groups of features such as facial expression features and hand motion features which are extracted from image frames captured by a single web camera. We refer 12 classes of human gestures with facial expression including neutral, negative and positive meanings from American Sign Languages (ASL). We combine the features in two levels by employing two fusion strategies. At the feature level, an early feature combination can be performed by concatenating and weighting different feature groups, and LDA is used to choose the most discriminative elements by projecting the feature on a discriminative expression space. The second strategy is applied on decision level. Weighted decisions from single modalities are fused in a later stage. A condensation-based algorithm is adopted for classification. We collected a data set with three to seven recording sessions and conducted experiments with the combination techniques. Experimental results showed that facial analysis improve hand gesture recognition, decision level fusion performs better than feature level fusion.

  8. Application of data fusion in computer facial recognition

    Directory of Open Access Journals (Sweden)

    Wang Ai Qiang

    2013-11-01

    Full Text Available The recognition rate of single recognition method is inefficiency in computer facial recognition. We proposed a new confluent facial recognition method using data fusion technology, a variety of recognition algorithm are combined to form the fusion-based face recognition system to improve the recognition rate in many ways. Data fusion considers three levels of data fusion, feature level fusion and decision level fusion. And the data layer uses a simple weighted average algorithm, which is easy to implement. Artificial neural network algorithm was selected in feature layer and fuzzy reasoning algorithm was used in decision layer. Finally, we compared with the BP neural network algorithm in the MATLAB experimental platform. The result shows that the recognition rate has been greatly improved after adopting data fusion technology in computer facial recognition.

  9. Multimodal Medical Image Fusion Framework Based on Simplified PCNN in Nonsubsampled Contourlet Transform Domain

    Directory of Open Access Journals (Sweden)

    Nianyi Wang

    2013-06-01

    Full Text Available In this paper, we present a new medical image fusion algorithm based on nonsubsampled contourlet transform (NSCT and spiking cortical model (SCM. The flexible multi-resolution, anisotropy, and directional expansion characteristics of NSCT are associated with global coupling and pulse synchronization features of SCM. Considering the human visual system characteristics, two different fusion rules are used to fuse the low and high frequency sub-bands respectively. Firstly, maximum selection rule (MSR is used to fuse low frequency coefficients. Secondly, spatial frequency (SF is applied to motivate SCM network rather than using coefficients value directly, and then the time matrix of SCM is set as criteria to select coefficients of high frequency subband. The effectiveness of the proposed algorithm is achieved by the comparison with existing fusion methods.

  10. Novel Hydrophobin Fusion Tags for Plant-Produced Fusion Proteins

    Science.gov (United States)

    Ritala, Anneli; Linder, Markus; Joensuu, Jussi

    2016-01-01

    Hydrophobin fusion technology has been applied in the expression of several recombinant proteins in plants. Until now, the technology has relied exclusively on the Trichoderma reesei hydrophobin HFBI. We screened eight novel hydrophobin tags, T. reesei HFBII, HFBIII, HFBIV, HFBV, HFBVI and Fusarium verticillioides derived HYD3, HYD4 and HYD5, for production of fusion proteins in plants and purification by two-phase separation. To study the properties of the hydrophobins, we used N-terminal and C-terminal GFP as a fusion partner. Transient expression of the hydrophobin fusions in Nicotiana benthamiana revealed large variability in accumulation levels, which was also reflected in formation of protein bodies. In two-phase separations, only HFBII and HFBIV were able to concentrate GFP into the surfactant phase from a plant extract. The separation efficiency of both tags was comparable to HFBI. When the accumulation was tested side by side, HFBII-GFP gave a better yield than HFBI-GFP, while the yield of HFBIV-GFP remained lower. Thus we present here two alternatives for HFBI as functional fusion tags for plant-based protein production and first step purification. PMID:27706254

  11. Multisensor Data Fusion for Automotive Engine Fault Diagnosis

    Institute of Scientific and Technical Information of China (English)

    王赟松; 褚福磊; 何永勇; 郭丹

    2004-01-01

    This paper describes mainly a decision-level data fusion technique for fault diagnosis for electronically controlled engines.Experiments on a SANTANA AJR engine show that the data fusion method provides good engine fault diagnosis.In data fusion methods, the data level fusion has small data preprocessing loads and high accuracy, but requires commensurate sensor data and has poor operational performance.The decision-level fusion based on Dempster-Shafer evidence theory can process noncommensurate data and has robust operational performance, reduces ambiguity, increases confidence, and improves system reliability, but has low fusion accuracy and high data preprocessing cost.The feature-level fusion provides good compromise between the above two methods, which becomes gradually mature.In addition, acquiring raw data is a precondition to perform data fusion, so the system for signal acquisition and processing for an automotive engine test is also designed by the virtual instrument technology.

  12. Laser-fusion rocket for interplanetary propulsion

    Energy Technology Data Exchange (ETDEWEB)

    Hyde, R.A.

    1983-09-27

    A rocket powered by fusion microexplosions is well suited for quick interplanetary travel. Fusion pellets are sequentially injected into a magnetic thrust chamber. There, focused energy from a fusion Driver is used to implode and ignite them. Upon exploding, the plasma debris expands into the surrounding magnetic field and is redirected by it, producing thrust. This paper discusses the desired features and operation of the fusion pellet, its Driver, and magnetic thrust chamber. A rocket design is presented which uses slightly tritium-enriched deuterium as the fusion fuel, a high temperature KrF laser as the Driver, and a thrust chamber consisting of a single superconducting current loop protected from the pellet by a radiation shield. This rocket can be operated with a power-to-mass ratio of 110 W gm/sup -1/, which permits missions ranging from occasional 9 day VIP service to Mars, to routine 1 year, 1500 ton, Plutonian cargo runs.

  13. Multi-Scale Analysis Based Curve Feature Extraction in Reverse Engineering

    Institute of Scientific and Technical Information of China (English)

    YANG Hongjuan; ZHOU Yiqi; CHEN Chengjun; ZHAO Zhengxu

    2006-01-01

    A sectional curve feature extraction algorithm based on multi-scale analysis is proposed for reverse engineering. The algorithm consists of two parts: feature segmentation and feature classification. In the first part, curvature scale space is applied to multi-scale analysis and original feature detection. To obtain the primary and secondary curve primitives, feature fusion is realized by multi-scale feature detection information transmission. In the second part: projection height function is presented based on the area of quadrilateral, which improved criterions of sectional curve feature classification. Results of synthetic curves and practical scanned sectional curves are given to illustrate the efficiency of the proposed algorithm on feature extraction. The consistence between feature extraction based on multi-scale curvature analysis and curve primitives is verified.

  14. 基于图像多特征融合和支持向量机的气液两相流流型识别%Identification Method of Gas-Liquid Two-phase Flow Regime Based on Image Multi-feature Fusion and Support Vector Machine

    Institute of Scientific and Technical Information of China (English)

    周云龙; 陈飞; 孙斌

    2008-01-01

    The knowledge of flow regime is very important for quantifying the pressure drop, the stability and safety of two-phase flow systems. Based on image multi-feature fusion and support vector machine, a new method to identify flow regime in two-phase flow was presented. Firstly, gas-liquid two-phase flow images including bubbly flow, plug flow, slug flow, stratified flow, wavy flow, annular flow and mist flow were captured by digital high speed video systems in the horizontal tube. The image moment invariants and gray level co-occurrence matrix texture features were extracted using image processing techniques. To improve the performance of a multiple classifier system, the rough sets theory was used for reducing the inessential factors. Furthermore, the support vector machine was trained by using these eigenvectors to reduce the dimension as flow regime samples, and the flow regime intelligent identification was realized. The test results showed that image features which were reduced with the rough sets theory could excellently reflect the difference between seven typical flow regimes, and successful training the support vector machine could quickly and accurately identify seven typical flow regimes of gas-liquid two-phase flow in the horizontal tube. Image multi-feature fusion method provided a new way to identify the gas-liquid two-phase flow, and achieved higher identification ability than that of single characteristic. The overall identification accuracy was 100%, and an estimate of the image processing time was 8 ms for online flow regime identification.

  15. Dempster-Shafer Multifeature Fusion for Pedestrian Detection

    Directory of Open Access Journals (Sweden)

    Hua Cui

    2015-01-01

    Full Text Available Pedestrian detection is of great importance for ensuring traffic safety. In recent years, many works employing image-based shape features to recognize pedestrians have been reported. However, previous pedestrian detectors were in many cases not sufficient to achieve satisfactory results under complex weather conditions and complex scenarios. As a solution this paper exploits two video-based motion feature descriptors and applies such motion features to the detection task in addition to four classical shape features with the aim of significantly improving the detection performance. Our motion features are defined as the trajectory smoothness degree and motion vector field, which are derived from our proposed point tracking strategy beyond tough target segmentation. And then the appealing Dempster-Shafer theory of evidence (D-S theory is applied to fuse these features, due to the fact that D-S theory is better than the classical Bayesian approach in handling the information with lack of prior probabilities. The proposed automatic pedestrian detection algorithm is evaluated on real data and in real traffic scenes under various weather conditions. Theoretical analysis and experiment results consistently show that the proposed method outperforms SVM-based multifeature fusion approach for pedestrian detection in terms of recognition ability and robustness in various real traffic scenes.

  16. A Model for Membrane Fusion

    Science.gov (United States)

    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.

  17. Nuclear Fusion prize laudation Nuclear Fusion prize laudation

    Science.gov (United States)

    Burkart, W.

    2011-01-01

    Clean energy in abundance will be of critical importance to the pursuit of world peace and development. As part of the IAEA's activities to facilitate the dissemination of fusion related science and technology, the journal Nuclear Fusion is intended to contribute to the realization of such energy from fusion. In 2010, we celebrated the 50th anniversary of the IAEA journal. The excellence of research published in the journal is attested to by its high citation index. The IAEA recognizes excellence by means of an annual prize awarded to the authors of papers judged to have made the greatest impact. On the occasion of the 2010 IAEA Fusion Energy Conference in Daejeon, Republic of Korea at the welcome dinner hosted by the city of Daejeon, we celebrated the achievements of the 2009 and 2010 Nuclear Fusion prize winners. Steve Sabbagh, from the Department of Applied Physics and Applied Mathematics, Columbia University, New York is the winner of the 2009 award for his paper: 'Resistive wall stabilized operation in rotating high beta NSTX plasmas' [1]. This is a landmark paper which reports record parameters of beta in a large spherical torus plasma and presents a thorough investigation of the physics of resistive wall mode (RWM) instability. The paper makes a significant contribution to the critical topic of RWM stabilization. John Rice, from the Plasma Science and Fusion Center, MIT, Cambridge is the winner of the 2010 award for his paper: 'Inter-machine comparison of intrinsic toroidal rotation in tokamaks' [2]. The 2010 award is for a seminal paper that analyzes results across a range of machines in order to develop a universal scaling that can be used to predict intrinsic rotation. This paper has already triggered a wealth of experimental and theoretical work. I congratulate both authors and their colleagues on these exceptional papers. W. Burkart Deputy Director General Department of Nuclear Sciences and Applications International Atomic Energy Agency, Vienna

  18. Fusion Utility in the Knudsen Layer

    Energy Technology Data Exchange (ETDEWEB)

    Davidovits, Seth [Princeton Plasma Physics Lab. (PPPL), Princeton, NJ (United States); Fisch, Nathaniel J. [Princeton Plasma Physics Lab. (PPPL), Princeton, NJ (United States)

    2014-08-01

    In inertial confi nement fusion, the loss of fast ions from the edge of the fusing hot-spot region reduces the reactivity below its Maxwellian value. The loss of fast ions may be pronounced because of the long mean free paths of fast ions, compared to those of thermal ions. We introduce a fusion utility function to demonstrate essential features of this Knudsen layer e ffect, in both magnetized and unmagnetized cases. The fusion utility concept is also used to evaluate restoring the reactivity in the Knudsen layer by manipulating fast ions in phase space using waves.

  19. Design of Fusion Safety Data Base

    Science.gov (United States)

    Aoki, Isao; Seki, Yasushi

    1994-03-01

    This report presents a data base architecture with its circumstance which is designed to be used for safety design and analysis studies. Design of Fusion Safety Data Base has been carried out to take into account a great number of published references on operation and control of fusion energy and engineering features to secure safety of fusion devices. Data Base of Fiscal Year 1993 - which has been established over an extended year - realized on PC (Personal Computer) peripherals is reported. The concept of data base architecture with its attributive issues and a manipulating way for users are also shown.

  20. Seismic data fusion anomaly detection

    Science.gov (United States)

    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.

  1. JENDL fusion file 99

    Energy Technology Data Exchange (ETDEWEB)

    Chiba, Satoshi; Fukahori, Tokio; Shibata, Keiichi [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment; Yu Baosheng [China Institute of Atomic Energy, Beijing (China); Kosako, Kazuaki [Sumitomo Atomic Industries, Tokyo (Japan); Yamamuro, Nobuhiro [Data Engineering Co. Ltd., Yokohama, Kanagawa (Japan)

    2002-02-01

    The double-differential cross sections (DDXs) of secondary neutrons have been evaluated for 79 isotopes and 13 natural elements ranging from H to Bi to improve the accuracy of predictions for the neutronics calculations in the D-T thermonuclear fusion applications. The data given in JENDL-3.1, which was the newest version of JENDL general purpose file when this project was initiated, was combined with new calculations based on the optical model, DWBA, pre-equilibrium and multi-step statistical models, and the DDX data were generated based on various kinds of systematics for medium-mass nuclei. Different methods were employed for light nuclei to which the above method could not be applied. In addition, the DDXs for emission of charged particles (p, d, t, {sup 3}He and {alpha}-particle) were given for {sup 2}H, {sup 9}Be and elements heavier or equal to F. The present results give an overall good description of the measured DDX data of both the neutron and charged particles emission channels. The data were compiled in ENDF-6 format, and released in 1999 as a special purpose file of JENDL family, namely, JENDL Fusion File 99. (author)

  2. Next Level of Data Fusion for Human Face Recognition

    CERN Document Server

    Bhowmik, Mrinal Kanti; Bhattacharjee, Debotosh; Basu, Dipak Kumar; Nasipuri, Mita

    2011-01-01

    This paper demonstrates two different fusion techniques at two different levels of a human face recognition process. The first one is called data fusion at lower level and the second one is the decision fusion towards the end of the recognition process. At first a data fusion is applied on visual and corresponding thermal images to generate fused image. Data fusion is implemented in the wavelet domain after decomposing the images through Daubechies wavelet coefficients (db2). During the data fusion maximum of approximate and other three details coefficients are merged together. After that Principle Component Analysis (PCA) is applied over the fused coefficients and finally two different artificial neural networks namely Multilayer Perceptron(MLP) and Radial Basis Function(RBF) networks have been used separately to classify the images. After that, for decision fusion based decisions from both the classifiers are combined together using Bayesian formulation. For experiments, IRIS thermal/visible Face Database h...

  3. How to analyse the typological features of stone terrace walls. A methodology applied to the rural landscape of the Tuscan Region (Central Italy)

    Science.gov (United States)

    Agnoletti, Mauro; Conti, Leonardo; Frezza, Lorenza; Santoro, Antonio

    2015-04-01

    Terraced systems currently represent an indubitable added value for Tuscany, as for other regions. This value goes beyond their original function of hosting new areas for cultivation. Indeed, the hydrological functions performed by such systems within the historic and modern agricultural matrix, including control of erosion, stabilisation of the slopes, prolongation of run-off times and the possible reduction of the volumes of surface runoff, are well-known. In addition they also play a strategic role in the conservation of biodiversity and in maintaining local identity value. These systems are evidence of the laborious knowledge built up by many generations of farmers in making the most of the territorial resources in terms of quality production through agronomic operations for the management of the crops. Within the framework of policies for the conservation and valorisation of the rural landscape, this recognised economic, environmental and historic-cultural value has engendered a growing awareness and sensitivity towards the safeguarding of such structural characteristics. Indeed, at national level the terraced agricultural systems come within the scope of actions scheduled in the National Strategic Plan for Rural Development 2007-2013, and the Cross-Compliance Decree envisages that they be maintained through the granting of economic aid as laid down in the Regional Development Plans, to be pursued through appropriate agronomic and environmental conditions in adherence to the obligatory management criteria for the protection of the soil. 18 sample areas, previously selected on the basis of the terracing intensity index (> 400 m/ha), were subjected to on-site surveys to determine the geo-typological features through the identification and measurement of the main technical-construction parameters of the dry stone walls. In view of the complexity of carrying out a census of the entire regional territory, it was essential to restrict the analysis to a limited

  4. Cold fusion research

    Energy Technology Data Exchange (ETDEWEB)

    None

    1989-11-01

    I am pleased to forward to you the Final Report of the Cold Fusion Panel. This report reviews the current status of cold fusion and includes major chapters on Calorimetry and Excess Heat, Fusion Products and Materials Characterization. In addition, the report makes a number of conclusions and recommendations, as requested by the Secretary of Energy.

  5. An Algorithm for Multimodal Biometrics Feature Level Fusion Recognition Based on the Second-Generation Curvelet and 2D Log-Gabor Filter%一种基于二代Curvelet和2D Log—Gabor滤波器的多模特征层融合识别方法

    Institute of Scientific and Technical Information of China (English)

    晏国淇; 张新曼; 王栋; 刘杨; 许学斌; 田中民

    2012-01-01

    针对单模生物特征识别在实际应用中易受干扰、识别率低且无法达到零错误识别的问题,提出一种基于二代Curvelet和2DLog-Gabor滤波器的人脸与虹膜特征层融合识别算法.该方法利用二代曲波变换提取人脸特征,用2DLog-Gabor幅值法提取虹膜特征,通过PCA降维单模特征向量,在特征层进行融合,通过SVM分类识别融合特征向量.在ORL人脸库和CISIA虹膜库构成的多模生物特征库上进行测试.实验结果表明:该算法正确识别率能达到100%,较单模人脸、单模虹膜识别方法的识别率均提高3.33%,为多模生物特征识别提供了一种有效模型.%For single-modal biometric system is susceptible to interference in appliacation, with low recognition rate, and not able to achieve zero error identification, a new fusion recognition approach in feature level of face and iris is proposed, based on the second-generation Curvelet and 2D Log-Gabor filtering. In the proposed approach, the second generation Curvelet is employed to extract face information, and amplitudes of 2D Log-Gabor are used to extract iris information. Then we use PCA to reduce the dimention of single-modal feature vectors, combine them in feature level, and distinguish fusion feature vectors by SVM. Experimental results on ORL face database and CASIA iris database show that: the correct fusion recognition rate can reach 100%, improved both 3. 33% compared with single face feature and single iris feature, and the proposed algorithm is an effective model for multimodal biometric recognition.

  6. Qualitative Reliability Issues for Solid and Liquid Wall Fusion Designs

    Energy Technology Data Exchange (ETDEWEB)

    Cadwallader, L.C.

    2001-01-31

    This report is an initial effort to identify issues affecting reliability and availability of solid and liquid wall designs for magnetic fusion power plant designs. A qualitative approach has been used to identify the possible failure modes of major system components and their effects on the systems. A general set of design attributes known to affect the service reliability has been examined for the overview solid and liquid wall designs, and some specific features of good first wall design have been discussed and applied to these designs as well. The two generalized designs compare well in regard to these design attributes. The strengths and weaknesses of each design approach are seen in the comparison of specific features.

  7. Qualitative Reliability Issues for Solid and Liquid Wall Fusion Design

    Energy Technology Data Exchange (ETDEWEB)

    Cadwallader, Lee Charles

    2001-01-01

    This report is an initial effort to identify issues affecting reliability and availability of solid and liquid wall designs for magnetic fusion power plant designs. A qualitative approach has been used to identify the possible failure modes of major system components and their effects on the systems. A general set of design attributes known to affect the service reliability has been examined for the overview solid and liquid wall designs, and some specific features of good first wall design have been discussed and applied to these designs as well. The two generalized designs compare well in regard to these design attributes. The strengths and weaknesses of each design approach are seen in the comparison of specific features.

  8. Qualitative Reliability Issues for Solid and Liquid Wall Fusion Designs

    Energy Technology Data Exchange (ETDEWEB)

    Cadwallader, L.C.

    2001-01-31

    This report is an initial effort to identify issues affecting reliability and availability of solid and liquid wall designs for magnetic fusion power plant designs. A qualitative approach has been used to identify the possible failure modes of major system components and their effects on the systems. A general set of design attributes known to affect the service reliability has been examined for the overview solid and liquid wall designs, and some specific features of good first wall design have been discussed and applied to these designs as well. The two generalized designs compare well in regard to these design attributes. The strengths and weaknesses of each design approach are seen in the comparison of specific features.

  9. Qualitative Reliability Issues for Solid and Liquid Wall Fusion Design

    Energy Technology Data Exchange (ETDEWEB)

    Cadwallader, Lee Charles

    2001-01-01

    This report is an initial effort to identify issues affecting reliability and availability of solid and liquid wall designs for magnetic fusion power plant designs. A qualitative approach has been used to identify the possible failure modes of major system components and their effects on the systems. A general set of design attributes known to affect the service reliability has been examined for the overview solid and liquid wall designs, and some specific features of good first wall design have been discussed and applied to these designs as well. The two generalized designs compare well in regard to these design attributes. The strengths and weaknesses of each design approach are seen in the comparison of specific features.

  10. Fusion of classifiers for REIS-based detection of suspicious breast lesions

    Science.gov (United States)

    Lederman, Dror; Wang, Xingwei; Zheng, Bin; Sumkin, Jules H.; Tublin, Mitchell; Gur, David

    2011-03-01

    After developing a multi-probe resonance-frequency electrical impedance spectroscopy (REIS) system aimed at detecting women with breast abnormalities that may indicate a developing breast cancer, we have been conducting a prospective clinical study to explore the feasibility of applying this REIS system to classify younger women (biopsy due to findings of a highly suspicious breast lesion ("positives"), and 108 were determined as negative during imaging based procedures ("negatives"). A set of REIS-based features, extracted using a mirror-matched approach, was computed and fed into five machine learning classifiers. A genetic algorithm was used to select an optimal subset of features for each of the five classifiers. Three fusion rules, namely sum rule, weighted sum rule and weighted median rule, were used to combine the results of the classifiers. Performance evaluation was performed using a leave-one-case-out cross-validation method. The results indicated that REIS may provide a new technology to identify younger women with higher than average risk of having or developing breast cancer. Furthermore, it was shown that fusion rule, such as a weighted median fusion rule and a weighted sum fusion rule may improve performance as compared with the highest performing single classifier.

  11. Understanding fuel magnetization and mix using secondary nuclear reactions in magneto-inertial fusion.

    Science.gov (United States)

    Schmit, P F; Knapp, 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; Chandler, G A; Cooper, G W; Cuneo, M E; Geissel, M; Harvey-Thompson, A J; Herrmann, M C; Hess, M H; Johns, O; Lamppa, D C; Martin, M R; McBride, R D; Porter, J L; Robertson, G K; Rochau, G A; Rovang, D C; Ruiz, C L; Savage, M E; Smith, I C; Stygar, W A; Vesey, R A

    2014-10-10

    Magnetizing the fuel in inertial confinement fusion relaxes ignition requirements by reducing thermal conductivity and changing the physics of burn product confinement. Diagnosing the level of fuel magnetization during burn is critical to understanding target performance in magneto-inertial fusion (MIF) implosions. In pure deuterium fusion plasma, 1.01 MeV tritons are emitted during deuterium-deuterium fusion and can undergo secondary deuterium-tritium reactions before exiting the fuel. Increasing the fuel magnetization elongates the path lengths through the fuel of some of the tritons, enhancing their probability of reaction. Based on this feature, a method to diagnose fuel magnetization using the ratio of overall deuterium-tritium to deuterium-deuterium neutron yields is developed. Analysis of anisotropies in the secondary neutron energy spectra further constrain the measurement. Secondary reactions also are shown to provide an upper bound for the volumetric fuel-pusher mix in MIF. The analysis is applied to recent MIF experiments [M. R. Gomez et al., Phys. Rev. Lett. 113, 155003 (2014)] on the Z Pulsed Power Facility, indicating that significant magnetic confinement of charged burn products was achieved and suggesting a relatively low-mix environment. Both of these are essential features of future ignition-scale MIF designs.

  12. Study on the performance of data fusion system for sonar signal detection

    Institute of Scientific and Technical Information of China (English)

    XIANG Ming; WANG Zhao; LI Hong; ZHAO Junwei; GONG Xianyi

    2000-01-01

    The mathematical model and fusion algorithm for multisensor data fusion are presented, and applied to integrate the decisions obtained by multiple sonars in a distributed detection system. Assuming that all the sonars and the fusion system operate at the same false alarm probability, the expression for the detection probability of the fusion system is obtained.Computer simulations reveals that the detection probability and detection range of the fusion system are significantly improved compared to the original distributed detection system.

  13. Forecasting Chronic Diseases Using Data Fusion.

    Science.gov (United States)

    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.

  14. Virtual experiment of pyroelectric fusion

    Energy Technology Data Exchange (ETDEWEB)

    Nasseri, Mohammad Mehdi, E-mail: mnasseri@aeoi.org.ir

    2015-11-01

    The virtual experiment of pyroelectric fusion was conducted by Geant4 simulator. Despite the limitations of the code for simulating the pyroelectric fusion experiment precisely, the following interesting results were obtained. Two crystals were separated by a certain distance. A constant electric field with varying intensities was applied between the crystals. As initial particles, deuterium ions were emitted to deuterated polypropylene (CD{sub 2}). This virtual experiment showed that the number of ions that hit the target, for different distances between the crystals, increases with the increase of the intensity of the electric field; however, further increase of the electric field results in the reduction of the number of hit ions, which attains a constant value of about 57% of the initial number of ions. For a (D, D) fusion reaction to occur, the distance between the two crystals should be <1.5 cm and for a (D, T) fusion reaction to occur, this distance could be up to 2 cm. The energy spectra of ions for low and high electric fields were narrow and long and wide and short, respectively.

  15. Prospects for bubble fusion

    Energy Technology Data Exchange (ETDEWEB)

    Nigmatulin, R.I. [Tyumen Institute of Mechanics of Multiphase Systems (TIMMS), Marx (Russian Federation); Lahey, R.T. Jr. [Rensselaer Polytechnic Institute, Troy, NY (United States)

    1995-09-01

    In this paper a new method for the realization of fusion energy is presented. This method is based on the superhigh compression of a gas bubble (deuterium or deuterium/thritium) in heavy water or another liquid. The superhigh compression of a gas bubble in a liquid is achieved through forced non-linear, non-periodic resonance oscillations using moderate amplitudes of forcing pressure. The key feature of this new method is a coordination of the forced liquid pressure change with the change of bubble volume. The corresponding regime of the bubble oscillation has been called {open_quotes}basketball dribbling (BD) regime{close_quotes}. The analytical solution describing this process for spherically symmetric bubble oscillations, neglecting dissipation and compressibility of the liquid, has been obtained. This solution shown no limitation on the supercompression of the bubble and the corresponding maximum temperature. The various dissipation mechanisms, including viscous, conductive and radiation heat losses have been considered. It is shown that in spite of these losses it is possible to achieve very high gas bubble temperatures. This because the time duration of the gas bubble supercompression becomes very short when increasing the intensity of compression, thus limiting the energy losses. Significantly, the calculated maximum gas temperatures have shown that nuclear fusion may be possible. First estimations of the affect of liquid compressibility have been made to determine possible limitations on gas bubble compression. The next step will be to investigate the role of interfacial instability and breaking down of the bubble, shock wave phenomena around and in the bubble and mutual diffusion of the gas and the liquid.

  16. Soldier systems sensor fusion

    Science.gov (United States)

    Brubaker, Kathryne M.

    1998-08-01

    This paper addresses sensor fusion and its applications in emerging Soldier Systems integration and the unique challenges associated with the human platform. Technology that,provides the highest operational payoff in a lightweight warrior system must not only have enhanced capabilities, but have low power components resulting in order of magnitude reductions coupled with significant cost reductions. These reductions in power and cost will be achieved through partnership with industry and leveraging of commercial state of the art advancements in microelectronics and power sources. As new generation of full solution fire control systems (to include temperature, wind and range sensors) and target acquisition systems will accompany a new generation of individual combat weapons and upgrade existing weapon systems. Advanced lightweight thermal, IR, laser and video senors will be used for surveillance, target acquisition, imaging and combat identification applications. Multifunctional sensors will provide embedded training features in combat configurations allowing the soldier to 'train as he fights' without the traditional cost and weight penalties associated with separate systems. Personal status monitors (detecting pulse, respiration rate, muscle fatigue, core temperature, etc.) will provide commanders and highest echelons instantaneous medical data. Seamless integration of GPS and dead reckoning (compass and pedometer) and/or inertial sensors will aid navigation and increase position accuracy. Improved sensors and processing capability will provide earlier detection of battlefield hazards such as mines, enemy lasers and NBC (nuclear, biological, chemical) agents. Via the digitized network the situational awareness database will automatically be updated with weapon, medical, position and battlefield hazard data. Soldier Systems Sensor Fusion will ultimately establish each individual soldier as an individual sensor on the battlefield.

  17. Viral membrane fusion

    Energy Technology Data Exchange (ETDEWEB)

    Harrison, Stephen C., E-mail: harrison@crystal.harvard.edu

    2015-05-15

    Membrane fusion is an essential step when enveloped viruses enter cells. Lipid bilayer fusion requires catalysis to overcome a high kinetic barrier; viral fusion proteins are the agents that fulfill this catalytic function. Despite a variety of molecular architectures, these proteins facilitate fusion by essentially the same generic mechanism. Stimulated by a signal associated with arrival at the cell to be infected (e.g., receptor or co-receptor binding, proton binding in an endosome), they undergo a series of conformational changes. A hydrophobic segment (a “fusion loop” or “fusion peptide”) engages the target-cell membrane and collapse of the bridging intermediate thus formed draws the two membranes (virus and cell) together. We know of three structural classes for viral fusion proteins. Structures for both pre- and postfusion conformations of illustrate the beginning and end points of a process that can be probed by single-virion measurements of fusion kinetics. - Highlights: • Viral fusion proteins overcome the high energy barrier to lipid bilayer merger. • Different molecular structures but the same catalytic mechanism. • Review describes properties of three known fusion-protein structural classes. • Single-virion fusion experiments elucidate mechanism.

  18. 保角特征结合改进差分进化算法的三维人脸识别%3D face recognition based on fusion of conformal features and improved differential evolution algorithm

    Institute of Scientific and Technical Information of China (English)

    刘述木; 杨建; 陈跃

    2016-01-01

    As the problem of the high complexity of 3D face recognition and 2D face recognition not providing granular clues, this paper proposed a fully automatic 3D facial expression recognition algorithm.It provided more clues than that of 2D face recognition and reduced the computational complexity at the same time.Firstly,it transformed 3D face into a 2D plane by con-formal mapping,retaining the changing of facial clues.Secondly,it proposed an optimization algorithm based on differential e-volution (DE)algorithm to improve the recognition efficiency,while extracting the best facial feature set and classification pa-rameters,and speed up robust features (SURF)described all the expected facial feature points.Experimental results on the data sets of Bosphorus,FRGC v2 and gathered face data sets show that the proposed algorithm solves high computational com-plexity of 3D face recognition and low clues of 2D face recognition.This algorithm greatly reduces the cost without lowering the recognition performance,compared to several more advanced 3D face recognition algorithm,the algorithm achieves better reco-gnition results,expecting to be applied to commercial face recognition systems.%针对三维人脸识别的高复杂度和二维人脸识别无法提供粒状线索的问题,提出一种全自动3D 人脸表情识别算法,该算法主要是提供比2D 人脸识别更多的线索,同时降低计算复杂度。通过保角映射将3D 人脸转换到2D 平面,保留了面部变化的线索,提出了基于优化算法的差分进化(DE)算法用于提高识别效率,同时提取最优人脸特征集和分类器参数,加速鲁棒特征池描述了所有预期的人脸特征点。在博斯普鲁斯、FRGC v2及笔者搜集的人脸数据集上的实验结果表明,算法解决了三维人脸识别的高计算复杂度和二维人脸识别的线索低的问题,并在不降低识别性能的前提下大大地节约了成本,相比几种较为先进的三

  19. Fusion between Satellite and Geophysical images in the study of Archaeological Sites

    Science.gov (United States)

    Karamitrou, A. A.; Tsokas, G. N.; Petrou, M.; Maggidis, C.

    2012-12-01

    In this work various image fusion techniques are used between one satellite (Quickbird) and one geophysical (electric resistivity) image to create various combinations with higher information content than the two original images independently. The resultant images provide more information about possible buried archaeological relics. The examined archaeological area is located in mainland Greece near the city of Boetia at the acropolis of Gla. The acropolis was built on a flat-topped bedrock outcrop at the north-eastern edge of the Kopais basin. When Kopais was filled with water, Glas was emerging as an island. At the end of 14th century the two palaces of Thebes and Orchomenos jointly utilized a large scale engineering project in order to transform the Kopais basin into a fertile plain. They used the acropolis to monitor the project, and as a warehouse to storage the harvest. To examine the Acropolis for potential archaeological remnants we use one Quickbird satellite image that covers the surrounding area of Gla. The satellite image includes one panchromatic (8532x8528 pixels) and one multispectral (2133x2132 pixels) image, collected on 30th of August 2011, covering an area of 20 square kilometers. On the other hand, geophysical measurements were performed using the electric resistivity method to the south west part of the Acropolis. To combine these images we investigate mean-value fusion, wavelets fusion, and curvelet fusion. In the cases of wavelet and curvelet fusion we apply as the fusion criterion the maximum frequency rule. Furthermore, the two original images, and excavations near the area suggest that the dominant orientations of the buried features are north-south and east-west. Therefore, in curvelet fusion method, in curvelet domain we enhance the image details along these specific orientations, additionally to the fusion. The resultant fused images succeed to map linear and rectangular features that were not easily visible in the original images

  20. Remote sensing of shorelines using data fusion of hyperspectral and multispectral imagery acquired from mobile and fixed platforms

    Science.gov (United States)

    Bostater, Charles R.; Frystacky, Heather

    2012-06-01

    areas". The data fusion "synthetic imagery" forms a basis for spectral-spatial resolution enhancement for optimal band selection and remote sensing algorithm development within "spectral anomaly areas". The methods are applied to imagery intended to support Deepwater Horizon oil spill remediation and recovery efforts. Sensitivity analysis demonstrates the data fusion methodology is most sensitive to (a) the pixels and features used in the SVD model building process and (b) the 2-D Butterworth cutoff frequency optimized by application of K-S nonparametric test. The optimized image fusion approach is transferable to sensor data acquired from other platforms, including autonomous underwater vehicles using near real time processing.

  1. Review of the safety concept for fusion reactor concepts and transferability of the nuclear fission regulation to potential fusion power plants

    Energy Technology Data Exchange (ETDEWEB)

    Raeder, Juergen; Weller, Arthur; Wolf, Robert [Max-Planck-Institut fuer Plasmaphysik (IPP), Garching (Germany); Jin, Xue Zhou; Boccaccini, Lorenzo V.; Stieglitz, Robert; Carloni, Dario [Karlsruher Institute fuer Technologie (KIT), Eggenstein-Leopoldshafen (Germany); Pistner, Christoph [Oeko-Institut e.V., Darmstadt (Germany); Herb, Joachim [Gesellschaft fuer Anlagen- und Reaktorsicherheit, Koeln (Germany)

    2016-01-15

    process residual heat is produced by the activated materials. Correspondingly, the fundamental safety function ''cooling'' is also applicable to fusion. The analyses performed so far have shown that in the case of an adequate design of a FPP the residual heat can be removed by passive heat transport. For a fission power plant the fundamental safety function ''reactivity control'' should prevent power excursion, guarantee that the fission process can be stopped and re-criticality is prevented. The first aspect is not transferable to fusion, because such power excursions are excluded due to the physical nature of the fusion process. The requirement for the ability to terminate the power production can be applied in principle to a fusion power plant. It is fulfilled by the inherent features. In a FPP it is by physical nature not necessary to consider re-criticality. As in the safety concept of fission, postulated single initiating and multiple failure events, as well as severe plant states of a fusion power plant are assigned to different levels of defence, covering the range from normal operation to very rare events. The assignment is based on probabilistic criteria and the possible radiological consequences. In a fusion power plant measures and installations are foreseen to guarantee the compliance with radiological criteria. The measures and installations are based on inherent physical principles, and passive and active safety systems. For a fusion power plant, the criteria for the measures and installations on the different levels of defence are not yet as detailed as for a fission power plant. The safety analyses for fusion performed so far have focused on plant-internal events. For these events in an adequately designed fusion power plant, only relying on inher-ent and passive safety features, the analyses showed that there will be no need for an evacuation outside the plant. Together with the development of more detailed plant

  2. Review of the safety concept for fusion reactor concepts and transferability of the nuclear fission regulation to potential fusion power plants

    Energy Technology Data Exchange (ETDEWEB)

    Raeder, Juergen; Weller, Arthur; Wolf, Robert [Max-Planck-Institut fuer Plasmaphysik (IPP), Garching (Germany); Jin, Xue Zhou; Boccaccini, Lorenzo V.; Stieglitz, Robert; Carloni, Dario [Karlsruher Institute fuer Technologie (KIT), Eggenstein-Leopoldshafen (Germany); Pistner, Christoph [Oeko-Institut e.V., Darmstadt (Germany); Herb, Joachim [Gesellschaft fuer Anlagen- und Reaktorsicherheit, Koeln (Germany)

    2016-01-15

    process residual heat is produced by the activated materials. Correspondingly, the fundamental safety function ''cooling'' is also applicable to fusion. The analyses performed so far have shown that in the case of an adequate design of a FPP the residual heat can be removed by passive heat transport. For a fission power plant the fundamental safety function ''reactivity control'' should prevent power excursion, guarantee that the fission process can be stopped and re-criticality is prevented. The first aspect is not transferable to fusion, because such power excursions are excluded due to the physical nature of the fusion process. The requirement for the ability to terminate the power production can be applied in principle to a fusion power plant. It is fulfilled by the inherent features. In a FPP it is by physical nature not necessary to consider re-criticality. As in the safety concept of fission, postulated single initiating and multiple failure events, as well as severe plant states of a fusion power plant are assigned to different levels of defence, covering the range from normal operation to very rare events. The assignment is based on probabilistic criteria and the possible radiological consequences. In a fusion power plant measures and installations are foreseen to guarantee the compliance with radiological criteria. The measures and installations are based on inherent physical principles, and passive and active safety systems. For a fusion power plant, the criteria for the measures and installations on the different levels of defence are not yet as detailed as for a fission power plant. The safety analyses for fusion performed so far have focused on plant-internal events. For these events in an adequately designed fusion power plant, only relying on inher-ent and passive safety features, the analyses showed that there will be no need for an evacuation outside the plant. Together with the development of more detailed plant

  3. Region-based multisensor image fusion method

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    Image fusion should consider the priori knowledge of the source images to be fused, such as the characteristics of the images and the goal of image fusion, that is to say, the knowledge about the input data and the application plays a crucial role. This paper is concerned on multiresolution (MR) image fusion. Considering the characteristics of the multisensor (SAR and FLIR etc) and the goal of fusion, which is to achieve one image in possession of the contours feature and the target region feature. It seems more meaningful to combine features rather than pixels. A multisensor image fusion scheme based on K-means cluster and steerable pyramid is presented. K-means cluster is used to segment out objects in FLIR images. The steerable pyramid is a multiresolution analysis method, which has a good property to extract contours information at different scales. Comparisons are made with the relevant existing techniques in the literature. The paper concludes with some examples to illustrate the efficiency of the proposed scheme.

  4. AI/Simulation Fusion Project at Lawrence Livermore National Laboratory

    Energy Technology Data Exchange (ETDEWEB)

    Erickson, S.A.

    1984-04-25

    This presentation first discusses the motivation for the AI Simulation Fusion project. After discussing very briefly what expert systems are in general, what object oriented languages are in general, and some observed features of typical combat simulations, it discusses why putting together artificial intelligence and combat simulation makes sense. We then talk about the first demonstration goal for this fusion project.

  5. Analysis on the Fusion and Sustainable Developmental of Landscape Sculpture

    Institute of Scientific and Technical Information of China (English)

    LlU Jinmin[1,2; GE Li[1,2

    2015-01-01

    Landscape sculpture, as part of landscape environment, features fusion that is not possessed by other art forms. Therefore, it will lose its existence value and meaning once it is without fusion. Along with the development of the times, landscape sculpture can attain a sustainable development, and this is a highlight in the development of the modem landscape sculpture design.

  6. Molecular detection of EWS-Ets fusion transcripts and their clinicopathologic significance in Ewing's sarcoma/peripheral primitive neuroectodermal tumor

    Institute of Scientific and Technical Information of China (English)

    WANG Hua; ZHENG Jie; WANG Yu-ping; YANG Yu; YOU Jiang-feng

    2005-01-01

    Background Ewing's sarcoma/peripheral primitive neuroectodermal tumor (ES/pPNET) is often difficult to distinguish from other small round cell tumors. The EWS-Ets gene fusions that result from chromosomal translocations in this tumor provide potential molecular diagnostic markers. To apply these molecular markers to commonly available archival materials, we evaluated the feasibility of detecting EWS-Ets including EWS-Fli1 and EWS-ERG fusion transcripts in paraffin-embedded tissues and its diagnostic value for detecting ES/pPNET.Methods Thirteen paraffin-embedded samples of ES/pPNETs were retrieved from archives. Thirteen cases of other tumors with small round cell features (including rhabdomyosarcoma, neuroblastoma, lymphoma, small cell carcinoma, and desmoplastic small round cell tumor) were used as negative controls. Β-actin and β2-microglobulin were used as internal controls. A nested reverse transcriptase-polymerase chain reaction (RT-PCR)-based assay was performed to detect the EWS-Fli1 and EWS-ERG fusion transcripts.Results β-actin and β2-microglobulin were detected in 10/13 and 13/13 ES/pPNETs, respectively. EWS-Fli1 fusion transcripts were detected in 11 of 13 (85%) ES/pPNETs. Three chimeric transcripts, all EWS-Fli1, were detected in ES/pPNET samples. Among 11 EWS-Fli1-positive cases, 7 cases had a typeⅠfusion transcript involving fusion of EWS exon 7 with Fli1 exon 6, 2 cases had a typeⅡfusion transcript involving EWS exon 7 with Fli1 exon 5, and 2 cases expressed fusion transcripts involving EWS exon 7 and Fli1 exon 8. Type Ⅰ EWS-Fli1 fusion predominated over other types. Fusion types could not be distinguished in the remaining 2 cases. Thirteen negative controls did not show detectable chimeric messages. There was a significant relationship between EWS-Fli1 fusion transcripts and CD99 expression. Conclusions Molecular detection of EWS-Fli1 fusion transcripts in formalin-fixed paraffin-embedded material by nested RT-PCR is feasible and is

  7. 标签时态特征分析及其在标签预测中的应用%Applying Temporal Features of Social Tags to Tag Predication

    Institute of Scientific and Technical Information of China (English)

    袁柳; 张龙波

    2012-01-01

    标签作为用户生成的对资源的描述,反映了资源的语义和用户的兴趣.由于Web资源的动态性,标签数据相应地表现出较为明显的时态特征,已有相关研究中标签的时态特征却很少受到关注.针对这方面的不足,对标签数据的时态特征以及基于时态特征的标签间语义关联进行分析,并提出发现标签时态特征的时间段划分准则;为了评价标签时态特征的价值,以经典的统计主题模型为基础,提出新的模型用于分析数据时态特征对所生成主题的影响,并将其用于标签预测.在多个数据集上的测试验证了标签数据的时态特性及其对提高标签预测性能的影响.%Tag is a kind of description of Web resources generated by users,and it represents the semantics of resources and interests of users. Because the Web resources are dynamic, tags show some temporal features. However, few researches are concentrated on temporal features of tags. The temporal features represented by tags dataset were analyzed in this paper, and the semantic relations between tags based temporal features were discussed. The principle of time segmentation for discovering temporal features was proposed,and the effect of tags temporal on topics was analyzed by statistical topic model. The discovered temporal features were used in tags predication. The experiments based on different datasets shows that applying tags temporal feature to tags predication can improve the predication performance.

  8. Muon Catalyzed Fusion

    Science.gov (United States)

    Armour, Edward A.G.

    2007-01-01

    Muon catalyzed fusion is a process in which a negatively charged muon combines with two nuclei of isotopes of hydrogen, e.g, a proton and a deuteron or a deuteron and a triton, to form a muonic molecular ion in which the binding is so tight that nuclear fusion occurs. The muon is normally released after fusion has taken place and so can catalyze further fusions. As the muon has a mean lifetime of 2.2 microseconds, this is the maximum period over which a muon can participate in this process. This article gives an outline of the history of muon catalyzed fusion from 1947, when it was first realised that such a process might occur, to the present day. It includes a description of the contribution that Drachrnan has made to the theory of muon catalyzed fusion and the influence this has had on the author's research.

  9. Nonsubsampled rotated complex wavelet transform (NSRCxWT) for medical image fusion related to clinical aspects in neurocysticercosis.

    Science.gov (United States)

    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

  10. Magnetic fusion technology

    CERN Document Server

    Dolan, Thomas J

    2014-01-01

    Magnetic Fusion Technology describes the technologies that are required for successful development of nuclear fusion power plants using strong magnetic fields. These technologies include: ? magnet systems, ? plasma heating systems, ? control systems, ? energy conversion systems, ? advanced materials development, ? vacuum systems, ? cryogenic systems, ? plasma diagnostics, ? safety systems, and ? power plant design studies. Magnetic Fusion Technology will be useful to students and to specialists working in energy research.

  11. Fusion research principles

    CERN Document Server

    Dolan, Thomas James

    2013-01-01

    Fusion Research, Volume I: Principles provides a general description of the methods and problems of fusion research. The book contains three main parts: Principles, Experiments, and Technology. The Principles part describes the conditions necessary for a fusion reaction, as well as the fundamentals of plasma confinement, heating, and diagnostics. The Experiments part details about forty plasma confinement schemes and experiments. The last part explores various engineering problems associated with reactor design, vacuum and magnet systems, materials, plasma purity, fueling, blankets, neutronics

  12. Multilevel depth and image fusion for human activity detection.

    Science.gov (United States)

    Ni, Bingbing; Pei, Yong; Moulin, Pierre; Yan, Shuicheng

    2013-10-01

    Recognizing complex human activities usually requires the detection and modeling of individual visual features and the interactions between them. Current methods only rely on the visual features extracted from 2-D images, and therefore often lead to unreliable salient visual feature detection and inaccurate modeling of the interaction context between individual features. In this paper, we show that these problems can be addressed by combining data from a conventional camera and a depth sensor (e.g., Microsoft Kinect). We propose a novel complex activity recognition and localization framework that effectively fuses information from both grayscale and depth image channels at multiple levels of the video processing pipeline. In the individual visual feature detection level, depth-based filters are applied to the detected human/object rectangles to remove false detections. In the next level of interaction modeling, 3-D spatial and temporal contexts among human subjects or objects are extracted by integrating information from both grayscale and depth images. Depth information is also utilized to distinguish different types of indoor scenes. Finally, a latent structural model is developed to integrate the information from multiple levels of video processing for an activity detection. Extensive experiments on two activity recognition benchmarks (one with depth information) and a challenging grayscale + depth human activity database that contains complex interactions between human-human, human-object, and human-surroundings demonstrate the effectiveness of the proposed multilevel grayscale + depth fusion scheme. Higher recognition and localization accuracies are obtained relative to the previous methods.

  13. Linker engineering for fusion protein construction: Improvement and characterization of a GLP-1 fusion protein.

    Science.gov (United States)

    Kong, Yuelin; Tong, Yue; Gao, Mingming; Chen, Chen; Gao, Xiangdong; Yao, Wenbing

    2016-01-01

    Protein engineering has been successfully applied in protein drug discovery. Using this technology, we previously have constructed a fusion protein by linking the globular domain of adiponectin to the C-terminus of a glucagon-like peptide-1 (GLP-1) analog. Herein, to further improve its bioactivity, we reconstructed this fusion protein by introducing linker peptides of different length and flexibility. The reconstructed fusion proteins were overexpressed in Escherichia coli and purified using nickel affinity chromatography. Their agonist activity towards receptors of GLP-1 and adiponectin were assessed in vitro by using luciferase assay and AMP-activated protein kinase (AMPK) immunoblotting, respectively. The effects of the selected fusion protein on glucose and lipid metabolism were evaluated in mice. The fusion protein reconstructed using a linker peptide of AMGPSSGAPGGGGS showed high potency in activating GLP-1 receptor and triggering AMPK phosphorylation via activating the adiponectin receptor. Remarkably, the optimized fusion protein was highly effective in lowering blood glucose and lipids in mice. Collectively, these findings demonstrate that the bioactivity of this GLP-1 fusion protein can be significantly promoted by linker engineering, and indicate that the optimized GLP-1 fusion protein is a promising lead structure for anti-diabetic drug discovery.

  14. Magnetic fusion reactor economics

    Energy Technology Data Exchange (ETDEWEB)

    Krakowski, R.A.

    1995-12-01

    An almost primordial trend in the conversion and use of energy is an increased complexity and cost of conversion systems designed to utilize cheaper and more-abundant fuels; this trend is exemplified by the progression fossil fission {yields} fusion. The present projections of the latter indicate that capital costs of the fusion ``burner`` far exceed any commensurate savings associated with the cheapest and most-abundant of fuels. These projections suggest competitive fusion power only if internal costs associate with the use of fossil or fission fuels emerge to make them either uneconomic, unacceptable, or both with respect to expensive fusion systems. This ``implementation-by-default`` plan for fusion is re-examined by identifying in general terms fusion power-plant embodiments that might compete favorably under conditions where internal costs (both economic and environmental) of fossil and/or fission are not as great as is needed to justify the contemporary vision for fusion power. Competitive fusion power in this context will require a significant broadening of an overly focused program to explore the physics and simbiotic technologies leading to more compact, simplified, and efficient plasma-confinement configurations that reside at the heart of an attractive fusion power plant.

  15. Frontiers in fusion research

    CERN Document Server

    Kikuchi, Mitsuru

    2011-01-01

    Frontiers in Fusion Research provides a systematic overview of the latest physical principles of fusion and plasma confinement. It is primarily devoted to the principle of magnetic plasma confinement, that has been systematized through 50 years of fusion research. Frontiers in Fusion Research begins with an introduction to the study of plasma, discussing the astronomical birth of hydrogen energy and the beginnings of human attempts to harness the Sun's energy for use on Earth. It moves on to chapters that cover a variety of topics such as: * charged particle motion, * plasma kinetic theory, *

  16. Magnetic-confinement fusion

    Science.gov (United States)

    Ongena, J.; Koch, R.; Wolf, R.; Zohm, H.

    2016-05-01

    Our modern society requires environmentally friendly solutions for energy production. Energy can be released not only from the fission of heavy nuclei but also from the fusion of light nuclei. Nuclear fusion is an important option for a clean and safe solution for our long-term energy needs. The extremely high temperatures required for the fusion reaction are routinely realized in several magnetic-fusion machines. Since the early 1990s, up to 16 MW of fusion power has been released in pulses of a few seconds, corresponding to a power multiplication close to break-even. Our understanding of the very complex behaviour of a magnetized plasma at temperatures between 150 and 200 million °C surrounded by cold walls has also advanced substantially. This steady progress has resulted in the construction of ITER, a fusion device with a planned fusion power output of 500 MW in pulses of 400 s. ITER should provide answers to remaining important questions on the integration of physics and technology, through a full-size demonstration of a tenfold power multiplication, and on nuclear safety aspects. Here we review the basic physics underlying magnetic fusion: past achievements, present efforts and the prospects for future production of electrical energy. We also discuss questions related to the safety, waste management and decommissioning of a future fusion power plant.

  17. Fusion of Nonionic Vesicles

    DEFF Research Database (Denmark)

    Bulut, Sanja; Oskolkova, M. Z.; Schweins, R.

    2010-01-01

    We present an experimental study of vesicle fusion using light and neutron scattering to monitor fusion events. Vesicles are reproducibly formed with an extrusion procedure using an single amphiphile triethylene glycol mono-n-decyl ether in water. They show long-term stability for temperatures...... around 20 C, but at temperatures above 26 C we observe an increase in the scattered intensity due to fusion. The system is unusually well suited for the study of basic mechanisms of vesicle fusion. The vesicles are flexible with a bending rigidity of only a few k(H)T. The monolayer spontaneous curvature...

  18. Environmental Perception and Sensor Data Fusion for Unmanned Ground Vehicle

    Directory of Open Access Journals (Sweden)

    Yibing Zhao

    2013-01-01

    Full Text Available Unmanned Ground Vehicles (UGVs that can drive autonomously in cross-country environment have received a good deal of attention in recent years. They must have the ability to determine whether the current terrain is traversable or not by using onboard sensors. This paper explores new methods related to environment perception based on computer image processing, pattern recognition, multisensors data fusion, and multidisciplinary theory. Kalman filter is used for low-level fusion of physical level, thus using the D-S evidence theory for high-level data fusion. Probability Test and Gaussian Mixture Model are proposed to obtain the traversable region in the forward-facing camera view for UGV. One feature set including color and texture information is extracted from areas of interest and combined with a classifier approach to resolve two types of terrain (traversable or not. Also, three-dimension data are employed; the feature set contains components such as distance contrast of three-dimension data, edge chain-code curvature of camera image, and covariance matrix based on the principal component method. This paper puts forward one new method that is suitable for distributing basic probability assignment (BPA, based on which D-S theory of evidence is employed to integrate sensors information and recognize the obstacle. The subordination obtained by using the fuzzy interpolation is applied to calculate the basic probability assignment. It is supposed that the subordination is equal to correlation coefficient in the formula. More accurate results of object identification are achieved by using the D-S theory of evidence. Control on motion behavior or autonomous navigation for UGV is based on the method, which is necessary for UGV high speed driving in cross-country environment. The experiment results have demonstrated the viability of the new method.

  19. Feature-Aware Verification

    CERN Document Server

    Apel, Sven; Wendler, Philipp; von Rhein, Alexander; Beyer, Dirk

    2011-01-01

    A software product line is a set of software products that are distinguished in terms of features (i.e., end-user--visible units of behavior). Feature interactions ---situations in which the combination of features leads to emergent and possibly critical behavior--- are a major source of failures in software product lines. We explore how feature-aware verification can improve the automatic detection of feature interactions in software product lines. Feature-aware verification uses product-line verification techniques and supports the specification of feature properties along with the features in separate and composable units. It integrates the technique of variability encoding to verify a product line without generating and checking a possibly exponential number of feature combinations. We developed the tool suite SPLverifier for feature-aware verification, which is based on standard model-checking technology. We applied it to an e-mail system that incorporates domain knowledge of AT&T. We found that feat...

  20. Optimization of the fission--fusion hybrid concept

    Energy Technology Data Exchange (ETDEWEB)

    Saltmarsh, M.J.; Grimes, W.R.; Santoro, R.T.

    1979-04-01

    One of the potentially attractive applications of controlled thermonuclear fusion is the fission--fusion hybrid concept. In this report we examine the possible role of the hybrid as a fissile fuel producer. We parameterize the advantages of the concept in terms of the performance of the fusion device and the breeding blanket and discuss some of the more troublesome features of existing design studies. The analysis suggests that hybrids based on deuterium--tritium (D--T) fusion devices are unlikely to be economically attractive and that they present formidable blanket technology problems. We suggest an alternative approach based on a semicatalyzed deuterium--deuterium (D--D) fusion reactor and a molten salt blanket. This concept is shown to emphasize the desirable features of the hybrid, to have considerably greater economic potential, and to mitigate many of the disadvantages of D--T-based systems.

  1. Multi-atlas segmentation with augmented features for cardiac MR images.

    Science.gov (United States)

    Bai, Wenjia; Shi, Wenzhe; Ledig, Christian; Rueckert, Daniel

    2015-01-01

    Multi-atlas segmentation infers the target image segmentation by combining prior anatomical knowledge encoded in multiple atlases. It has been quite successfully applied to medical image segmentation in the recent years, resulting in highly accurate and robust segmentation for many anatomical structures. However, to guide the label fusion process, most existing multi-atlas segmentation methods only utilise the intensity information within a small patch during the label fusion process and may neglect other useful information such as gradient and contextual information (the appearance of surrounding regions). This paper proposes to combine the intensity, gradient and contextual information into an augmented feature vector and incorporate it into multi-atlas segmentation. Also, it explores the alternative to the K nearest neighbour (KNN) classifier in performing multi-atlas label fusion, by using the support vector machine (SVM) for label fusion instead. Experimental results on a short-axis cardiac MR data set of 83 subjects have demonstrated that the accuracy of multi-atlas segmentation can be significantly improved by using the augmented feature vector. The mean Dice metric of the proposed segmentation framework is 0.81 for the left ventricular myocardium on this data set, compared to 0.79 given by the conventional multi-atlas patch-based segmentation (Coupé et al., 2011; Rousseau et al., 2011). A major contribution of this paper is that it demonstrates that the performance of non-local patch-based segmentation can be improved by using augmented features.

  2. Geodata fusion study by the Open Geospatial Consortium

    Science.gov (United States)

    Percivall, George

    2013-05-01

    Making new connections in existing data is a powerful method to gain understanding of the world. Data fusion is not a new topic, but new approaches provide opportunities to enhance this ubiquitous process. Interoperability based on open standards is radically changing the classical domains of data fusion while inventing entirely new ways to discern relationships in data with little structure. Associations based on locations and times are of the most primary type. The Open Geospatial Consortium (OGC) conducted a Fusion Standards study with recommendations implemented in testbeds. In the context of this study, Data Fusion was defined as: "the act or process of combining or associating data or information regarding one or more entities considered in an explicit or implicit knowledge framework to improve one's capability (or provide a new capability) for detection, identification, or characterization of that entity". Three categories were used to organize this study: Observation Fusion, Feature fusion, and Decision fusion. The study considered classical fusion as exemplified by the JDL and OODA models as well as how fusion is achieved by new technology such as web-based mash-ups and mobile Internet. The study considers both OGC standards as well open standards from other standards organizations. These technologies and standards aid in bringing structure to unstructured data as well as enabling a major new thrust in Decision Fusion.

  3. Nuclear fusion inside condense matters

    Institute of Scientific and Technical Information of China (English)

    HE Jing-tang

    2007-01-01

    This article describes in detail the nuclear fusion inside condense matters--the Fleischmann-Pons effect, the reproducibility of cold fusions, self-consistentcy of cold fusions and the possible applications.

  4. Applying micromorphological features of quartz to measure the age of active fault%应用石英微形貌特征测定断层活动年龄

    Institute of Scientific and Technical Information of China (English)

    陈艳

    2012-01-01

    对石英微形貌学测定断层活动年龄这一方法的基本原理、发展情况、存在的问题三方面进行了总结,在此基础上提出了值得深入研究的方向,以进一步完善该测年方法。%This paper outlines basic principles,development condition,and existing problems of applying micromorphological features of quartz to measure the age of active fault,and puts forward further research direction,so as to improve the age-measuring method.

  5. Fusion in computer vision understanding complex visual content

    CERN Document Server

    Ionescu, Bogdan; Piatrik, Tomas

    2014-01-01

    This book presents a thorough overview of fusion in computer vision, from an interdisciplinary and multi-application viewpoint, describing successful approaches, evaluated in the context of international benchmarks that model realistic use cases. Features: examines late fusion approaches for concept recognition in images and videos; describes the interpretation of visual content by incorporating models of the human visual system with content understanding methods; investigates the fusion of multi-modal features of different semantic levels, as well as results of semantic concept detections, fo

  6. Sensor Data Fusion

    DEFF Research Database (Denmark)

    Plascencia, Alfredo; Stepán, Petr

    2006-01-01

    The main contribution of this paper is to present a sensor fusion approach to scene environment mapping as part of a Sensor Data Fusion (SDF) architecture. This approach involves combined sonar array with stereo vision readings.  Sonar readings are interpreted using probability density functions...

  7. Complementary Advanced Fusion Exploration

    Science.gov (United States)

    2005-08-01

    homographic computer vision image fusion, out-of-sequence measurement and track data handling, Nash bargaining approaches to sensor management... homographic fusion notions are identified together with the Nash approach, the pursuit-evasion approach to threat situation outcome determination, and the

  8. Controlled Nuclear Fusion.

    Science.gov (United States)

    Glasstone, Samuel

    This publication is one of a series of information booklets for the general public published by The United States Atomic Energy Commission. Among the topics discussed are: Importance of Fusion Energy; Conditions for Nuclear Fusion; Thermonuclear Reactions in Plasmas; Plasma Confinement by Magnetic Fields; Experiments With Plasmas; High-Temperature…

  9. Controlled thermonuclear fusion

    CERN Document Server

    Bobin, Jean Louis

    2014-01-01

    The book is a presentation of the basic principles and main achievements in the field of nuclear fusion. It encompasses both magnetic and inertial confinements plus a few exotic mechanisms for nuclear fusion. The state-of-the-art regarding thermonuclear reactions, hot plasmas, tokamaks, laser-driven compression and future reactors is given.

  10. Cell fusions in mammals

    DEFF Research Database (Denmark)

    Larsson, Lars-Inge; Bjerregaard, Bolette; Talts, Jan Fredrik

    2008-01-01

    Cell fusions are important to fertilization, placentation, development of skeletal muscle and bone, calcium homeostasis and the immune defense system. Additionally, cell fusions participate in tissue repair and may be important to cancer development and progression. A large number of factors appe...

  11. Incorporating protein transduction domains (PTD) within intracellular proteins associated with the 'stemness' phenotype. Novel use of such recombinant 'fusion' proteins to overcome current limitations of applying autologous adult stem cells in regenerative medicine?

    Science.gov (United States)

    Heng, Boon Chin; Cao, Tong

    2005-01-01

    Adult stem cells originating from post-natal tissues hold tremendous promise in regenerative medicine. Nevertheless, there are several deficiencies of adult stem cells that would limit their application in transplantation therapy, in particular their relative scarcity, restricted multi-potency and limited proliferative capacity in vitro. A possible approach to overcome these limitations would be to genetically modulate adult stem cells to strongly express genes that are closely associated with the 'stemness' phenotype. Overwhelming safety concerns would preclude the direct application of recombinant DNA technology in genetic modulation. Moreover, constitutive expression of 'stemness' genes would prevent adult stem cells from participating in tissue/organ regeneration upon transplantation. A novel alternative would be to incorporate protein transduction domains within intracellular proteins (i.e. transcription factors) that are associated with the 'stemness' phenotype. Such recombinant fusion proteins would then have the ability to translocate across the cell membrane and be internalized within the cytosol, thereby enabling them to exert a gene-modulatory effect on the cell, without any permanent genetic alteration. This would be particularly useful for maintaining the 'stemness' of adult stem cell populations during extensive ex vivo proliferation, to generate adequate cell numbers for transplantation therapy.

  12. Degradation feature extraction of hydraulic pump based on morphological undecimated decomposition fusion and DCT high order singular entropy%基于形态非抽样融合与DCT高阶奇异熵的液压泵退化特征提取

    Institute of Scientific and Technical Information of China (English)

    孙健; 李洪儒; 王卫国; 许葆华

    2015-01-01

    针对轴向柱塞式液压泵性能退化中振动信号非线性强、退化特征提取困难等问题,提出基于形态非抽样融合与DCT(Discrete Cosine Transform)高阶奇异熵的退化特征提取方法。在一般框架下提出形态非抽样小波融合方法,通过构建特征能量因子筛选各分解层近似信号,据融合规则实现双通道振动信号融合重构、改善重构信号的特征信息;并利用DCT高阶谱分析法对融合信号进一步处理,通过奇异值分解分别计算Shannon、Tsallis奇异熵作为液压泵性能退化特征向量;用仿真信号及液压泵实测振动信号验证该方法的有效性。%Tosolvetheproblemthatvibrationsignalsofahydraulicpumpasusualarestronglynonlinearandits degradation features are difficult to extract,a degradation feature extraction method based upon morphological undecimated wavelet decomposition fusion (MUWDF)and DCT high order singular entropy was proposed.The MUWDF algorithm was presented under the general framework of morphological undecimated decomposition.The approximate signals of all decomposition layers were selected by using the feature energy factor and dual-channel vibration signals were fused according to the presented fusion rules so as to increase the proportion of feature information.On this basis,a high order spectrum analysis algorithm modified by DCT was proposed for further dealing with the fused signal.Shannon and Tsallis singular entropies,which were considered as fault degradation features of hydraulic pump,were respectively achieved by singular value decomposition.Finally,the proposed method was verified by using simulation signals and real pump vibration signals in various working conditions.

  13. Compact fusion reactors

    CERN Document Server

    CERN. Geneva

    2015-01-01

    Fusion research is currently to a large extent focused on tokamak (ITER) and inertial confinement (NIF) research. In addition to these large international or national efforts there are private companies performing fusion research using much smaller devices than ITER or NIF. The attempt to achieve fusion energy production through relatively small and compact devices compared to tokamaks decreases the costs and building time of the reactors and this has allowed some private companies to enter the field, like EMC2, General Fusion, Helion Energy, Lawrenceville Plasma Physics and Lockheed Martin. Some of these companies are trying to demonstrate net energy production within the next few years. If they are successful their next step is to attempt to commercialize their technology. In this presentation an overview of compact fusion reactor concepts is given.

  14. Fusion categories and homotopy theory

    CERN Document Server

    Etingof, Pavel; Ostrik, Victor

    2009-01-01

    We apply the yoga of classical homotopy theory to classification problems of G-extensions of fusion and braided fusion categories, where G is a finite group. Namely, we reduce such problems to classification (up to homotopy) of maps from BG to classifiying spaces of certain higher groupoids. In particular, to every fusion category C we attach the 3-groupoid BrPic(C) of invertible C-bimodule categories, called the Brauer-Picard groupoid of C, such that equivalence classes of G-extensions of C are in bijection with homotopy classes of maps from BG to the classifying space of BrPic(C). This gives rise to an explicit description of both the obstructions to existence of extensions and the data parametrizing them; we work these out both topologically and algebraically. One of the central results of the paper is that the 2-truncation of BrPic(C) is canonically the 2-groupoid of braided autoequivalences of the Drinfeld center Z(C) of C. In particular, this implies that the Brauer-Picard group BrPic(C) (i.e., the grou...

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

    Science.gov (United States)

    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.

  16. Safety of magnetic fusion facilities: Guidance

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1996-05-01

    This document provides guidance for the implementation of the requirements identified in DOE-STD-6002-96, Safety of Magnetic Fusion Facilities: Requirements. This guidance is intended for the managers, designers, operators, and other personnel with safety responsibilities for facilities designated as magnetic fusion facilities. While the requirements in DOE-STD-6002-96 are generally applicable to a wide range of fusion facilities, this Standard, DOE-STD-6003-96, is concerned mainly with the implementation of those requirements in large facilities such as the International Thermonuclear Experimental Reactor (ITER). Using a risk-based prioritization, the concepts presented here may also be applied to other magnetic fusion facilities. This Standard is oriented toward regulation in the Department of Energy (DOE) environment as opposed to regulation by other regulatory agencies. As the need for guidance involving other types of fusion facilities or other regulatory environments emerges, additional guidance volumes should be prepared. The concepts, processes, and recommendations set forth here are for guidance only. They will contribute to safety at magnetic fusion facilities.

  17. 基于关键帧多特征融合的视频拷贝检测%Video Copy Detection Based on Key Frame Multi-feature Fusion

    Institute of Scientific and Technical Information of China (English)

    张兴忠; 李皓; 张三义

    2015-01-01

    Retrieval speed is an important issue in video copy detection .This paper proposed a fast video copy detection method ,w hich uses a local sensitive hashing index to achive fast retriev‐al by mapping videos with similar clips into the same buckets ,and combines multi‐features of key frames to achieve high accuracy .To improve retrieval accuracy ,the method extracts key frames by using shot segmentation techniques ,and then obtains the Hilbert feature based on key points , ordinal measure feature and ORB (Oriented FAST and Rotated BRIEF ) feature from key frames . This allows the method make full use of both local features and global features .The hash index is built by hash the combined features .Experimental results show that this proposed method not only achieves high precision and recall rate ,but also has high spead .%针对视频拷贝检测中检索速度问题,提出一种基于关键帧多特征融合的类局部敏感哈希索引方法,将存在拷贝片段的视频映射到同一个哈希桶中,减少检索的范围,达到提高检索速度的目的。该算法首先对视频进行镜头分割提取关键帧,为了提高检测精度,分别提取了灰度序全局特征、基于关键点的希尔伯特特征、ORB(Oriented FAST and Rotated BRIEF )局部特征,综合利用全局特征和局部特征两者各自的优势;然后根据视频关键帧序列建立了类局部敏感哈希索引,利用建立好的索引获得拷贝检测结果。实验结果表明,该方法在保证检测精度的同时,速度上也有很大提升,具有重要的应用价值。

  18. Enhanced Singular Value Decomposition based Fusion for Super Resolution Image Reconstruction

    Directory of Open Access Journals (Sweden)

    K. Joseph Abraham Sundar

    2015-11-01

    Full Text Available The singular value decomposition (SVD plays a very important role in the field of image processing for applications such as feature extraction, image compression, etc. The main objective is to enhance the resolution of the image based on Singular Value Decomposition. The original image and the subsequent sub-pixel shifted image, subjected to image registration is transferred to SVD domain. An enhanced method of choosing the singular values from the SVD domain images to reconstruct a high resolution image using fusion techniques is proposesed. This technique is called as enhanced SVD based fusion. Significant improvement in the performance is observed by applying enhanced SVD method preceding the various interpolation methods which are incorporated. The technique has high advantage and computationally fast which is most needed for satellite imaging, high definition television broadcasting, medical imaging diagnosis, military surveillance, remote sensing etc.

  19. Data-Acquisition Systems for Fusion Devices

    NARCIS (Netherlands)

    van Haren, P. C.; Oomens, N. A.

    1993-01-01

    During the last two decades, computerized data acquisition systems (DASs) have been applied at magnetic confinement fusion devices. Present-day data acquisition is done by means of distributed computer systems and transient recorders in CAMAC systems. The development of DASs has been technology driv

  20. Fusion of Multiple Pyroelectric Characteristics for Human Body Identification

    Directory of Open Access Journals (Sweden)

    Wanchun Zhou

    2014-12-01

    Full Text Available Due to instability and poor identification ability of single pyroelectric infrared (PIR detector for human target identification, this paper proposes a new approach to fuse the information collected from multiple PIR sensors for human identification. Firstly, Fast Fourier Transform (FFT, Short Time Fourier Transform (STFT, Wavelet Transform (WT and Wavelet Packet Transform (WPT are adopted to extract features of the human body, which can be achieved by single PIR sensor. Then, we apply Principal Component Analysis (PCA and Support Vector Machine (SVM to reduce the characteristic dimensions and to classify the human targets, respectively. Finally, Fuzzy Comprehensive Evaluation (FCE is utilized to fuse recognition results from multiple PIR sensors to finalize human identification. The pyroelectric characteristics under scenarios with different people and/or different paths are analyzed by various experiments, and the recognition results with/without fusion procedure are also shown and compared. The experimental results demonstrate our scheme has improved efficiency for human identification.

  1. Community Clustering Algorithm in Complex Networks Based on Microcommunity Fusion

    Directory of Open Access Journals (Sweden)

    Jin Qi

    2015-01-01

    Full Text Available With the further research on physical meaning and digital features of the community structure in complex networks in recent years, the improvement of effectiveness and efficiency of the community mining algorithms in complex networks has become an important subject in this area. This paper puts forward a concept of the microcommunity and gets final mining results of communities through fusing different microcommunities. This paper starts with the basic definition of the network community and applies Expansion to the microcommunity clustering which provides prerequisites for the microcommunity fusion. The proposed algorithm is more efficient and has higher solution quality compared with other similar algorithms through the analysis of test results based on network data set.

  2. Structured and Sparse Canonical Correlation Analysis as a Brain-Wide Multi-Modal Data Fusion Approach.

    Science.gov (United States)

    Mohammadi-Nejad, Ali-Reza; Hossein-Zadeh, Gholam-Ali; Soltanian-Zadeh, Hamid

    2017-07-01

    Multi-modal data fusion has recently emerged as a comprehensive neuroimaging analysis approach, which usually uses canonical correlation analysis (CCA). However, the current CCA-based fusion approaches face problems like high-dimensionality, multi-collinearity, unimodal feature selection, asymmetry, and loss of spatial information in reshaping the imaging data into vectors. This paper proposes a structured and sparse CCA (ssCCA) technique as a novel CCA method to overcome the above problems. To investigate the performance of the proposed algorithm, we have compared three data fusion techniques: standard CCA, regularized CCA, and ssCCA, and evaluated their ability to detect multi-modal data associations. We have used simulations to compare the performance of these approaches and probe the effects of non-negativity constraint, the dimensionality of features, sample size, and noise power. The results demonstrate that ssCCA outperforms the existing standard and regularized CCA-based fusion approaches. We have also applied the methods to real functional magnetic resonance imaging (fMRI) and structural MRI data of Alzheimer's disease (AD) patients (n = 34) and healthy control (HC) subjects (n = 42) from the ADNI database. The results illustrate that the proposed unsupervised technique differentiates the transition pattern between the subject-course of AD patients and HC subjects with a p-value of less than 1×10(-6) . Furthermore, we have depicted the brain mapping of functional areas that are most correlated with the anatomical changes in AD patients relative to HC subjects.

  3. 基于语义矩阵反馈的多特征融合三维模型检索方法%3D model retrieval method with multi-feature fusion based on semantic matrix feedback

    Institute of Scientific and Technical Information of China (English)

    胡敏; 罗珣; 马韵洁

    2012-01-01

    为解决相关反馈三维模型检索方法存在用户不能确定模型是否相似的问题,提出了一种基于语义矩阵反馈的多特征融合三维模型检索方法.首先,采用形状分布和球面调和两种特征提取算法进行多特征提取.然后,对每种特征进行检索计算,将得到的相似度进行基于语义的反馈,根据反馈结果对不同特征分配不同的权值.最后,对迭代反馈结果的权求和得到检索模型的相似度.实验结果表明,本方法的检索结果比用单一的特征提取方法得到的结果准确.%When the relevance feedback method is used to retrieve the 3D model, it has the problem that the user unclear whether the models are similar or not similar. In order to solve this problem, an integrated method of 3D model retrieval is proposed which based on the combination of semantic matrix feedback and feature. Firstly, 3D model features are extracted by using shape distributions and spherical harmonics methods. Then these features similarity of the 3D mod-els are involved to calculate the assessment weights. These assessment weights are combined with semantic matrix feed-back in the 3D model retrieval. Finally, the similarity of the 3D models is calculated based on the iterative feedback result. The experiment results show that this method is more accurate than the single feature extraction method.

  4. Fusion of Local and Global Features Using Multiple Kernel Learning for Face Recognition%多核学习融合局部和全局特征的人脸识别算法

    Institute of Scientific and Technical Information of China (English)

    杨赛; 赵春霞; 刘凡

    2016-01-01

    A new face recognition algorithm via bag-of-words(BoW)is proposed.In specific,it uses BoW and the global pattern of BoW respectively as the local feature and global feature of face images.Multiple kernel learning is adopted to fuse the local and global features.Extensive experiments were carried out on four face databases,i.e.AR,FERET,CMU PIE and LFW.The results show that our method can effectively solve the small training size problem and is more robust to expression changes,position variations and occlusion.%提出一种基于词袋模型的新的人脸识别算法.该方法将词袋模型和词袋模型的全局模式分别作为人脸图像的局部特征和全局特征描述,最后使用多核学习方法将二者进行融合.AR、FERET、CMU PIE以及LFW公开人脸数据库上的实验结果表明,本文方法能够更好的解决小样本问题,并且对人脸的表情变化、姿态变化以及面部遮挡具有更优良的鲁棒性.

  5. Control of Fusion and Solubility in Fusion Systems

    CERN Document Server

    Craven, David A

    2009-01-01

    In this article, we consider the control of fusion in fusion systems, proving three previously known, non-trivial results in a new, largely elementary way. We then reprove a result of Aschbacher, that the product of two strongly closed subgroups is strongly closed; to do this, we consolidate the theory of quotients of fusion systems into a consistent theory. We move on considering p-soluble fusion systems, and prove that they are constrained, allowing us to effectively characterize fusion systems of p-soluble groups. This leads us to recast Thompson Factorization for Qd(p)-free fusion systems, and consider Thompson Factorization for more general fusion systems.

  6. Current fusion power plant design concepts

    Energy Technology Data Exchange (ETDEWEB)

    Gore, B.F.; Murphy, E.S.

    1976-09-01

    Nine current U.S. designs for fusion power plants are described in this document. Summary tabulations include a tenth concept, for which the design document was unavailable during preparation of the descriptions. The information contained in the descriptions was used to define an envelope of fusion power plant characteristics which formed the basis for definition of reference first commercial fusion power plant design. A brief prose summary of primary plant features introduces each of the descriptions contained in the body of this document. In addition, summary tables are presented. These tables summarize in side-by-side fashion, plant parameters, processes, combinations of materials used, requirements for construction materials, requirements for replacement materials during operation, and production of wastes.

  7. Remote sensing image fusion

    CERN Document Server

    Alparone, Luciano; Baronti, Stefano; Garzelli, Andrea

    2015-01-01

    A synthesis of more than ten years of experience, Remote Sensing Image Fusion covers methods specifically designed for remote sensing imagery. The authors supply a comprehensive classification system and rigorous mathematical description of advanced and state-of-the-art methods for pansharpening of multispectral images, fusion of hyperspectral and panchromatic images, and fusion of data from heterogeneous sensors such as optical and synthetic aperture radar (SAR) images and integration of thermal and visible/near-infrared images. They also explore new trends of signal/image processing, such as

  8. Fusion Materials Research at Oak Ridge National Laboratory in Fiscal Year 2014

    Energy Technology Data Exchange (ETDEWEB)

    Wiffen, Frederick W. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Noe, Susan P. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Snead, Lance Lewis [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2014-10-01

    The realization of fusion energy is a formidable challenge with significant achievements resulting from close integration of the plasma physics and applied technology disciplines. Presently, the most significant technological challenge for the near-term experiments such as ITER, and next generation fusion power systems, is the inability of current materials and components to withstand the harsh fusion nuclear environment. The overarching goal of the ORNL fusion materials program is to provide the applied materials science support and understanding to underpin the ongoing DOE Office of Science fusion energy program while developing materials for fusion power systems. In doing so the program continues to be integrated both with the larger U.S. and international fusion materials communities, and with the international fusion design and technology communities.

  9. Fusion Reactivity in the Case of Ion Cyclotron Resonant Heating

    Institute of Scientific and Technical Information of China (English)

    俞国扬; 常永斌; 沈林芳

    2003-01-01

    By applying the integral-variable-change technique,an explicit expression of deuterium-tritium fusion reactivity in the case of second harmonic ion cyclotron resonant heating on deuterium is obtained.

  10. Researches on a reactor core in heavy ion inertial fusion

    CERN Document Server

    Kondo, S; Iinuma, T; Kubo, K; Kato, H; Kawata, S; Ogoyski, A I

    2016-01-01

    In this paper a study on a fusion reactor core is presented in heavy ion inertial fusion (HIF), including the heavy ion beam (HIB) transport in a fusion reactor, a HIB interaction with a background gas, reactor cavity gas dynamics, the reactor gas backflow to the beam lines, and a HIB fusion reactor design. The HIB has remarkable preferable features to release the fusion energy in inertial fusion: in particle accelerators HIBs are generated with a high driver efficiency of ~30-40%, and the HIB ions deposit their energy inside of materials. Therefore, a requirement for the fusion target energy gain is relatively low, that would be ~50 to operate a HIF fusion reactor with a standard energy output of 1GW of electricity. In a fusion reactor the HIB charge neutralization is needed for a ballistic HIB transport. Multiple mechanical shutters would be installed at each HIB port at the reactor wall to stop the blast waves and the chamber gas backflow, so that the accelerator final elements would be protected from the ...

  11. Determination of feature generation methods for PTZ camera object tracking

    Science.gov (United States)

    Doyle, Daniel D.; Black, Jonathan T.

    2012-06-01

    Object detection and tracking using computer vision (CV) techniques have been widely applied to sensor fusion applications. Many papers continue to be written that speed up performance and increase learning of artificially intelligent systems through improved algorithms, workload distribution, and information fusion. Military application of real-time tracking systems is becoming more and more complex with an ever increasing need of fusion and CV techniques to actively track and control dynamic systems. Examples include the use of metrology systems for tracking and measuring micro air vehicles (MAVs) and autonomous navigation systems for controlling MAVs. This paper seeks to contribute to the determination of select tracking algorithms that best track a moving object using a pan/tilt/zoom (PTZ) camera applicable to both of the examples presented. The select feature generation algorithms compared in this paper are the trained Scale-Invariant Feature Transform (SIFT) and Speeded Up Robust Features (SURF), the Mixture of Gaussians (MoG) background subtraction method, the Lucas- Kanade optical flow method (2000) and the Farneback optical flow method (2003). The matching algorithm used in this paper for the trained feature generation algorithms is the Fast Library for Approximate Nearest Neighbors (FLANN). The BSD licensed OpenCV library is used extensively to demonstrate the viability of each algorithm and its performance. Initial testing is performed on a sequence of images using a stationary camera. Further testing is performed on a sequence of images such that the PTZ camera is moving in order to capture the moving object. Comparisons are made based upon accuracy, speed and memory.

  12. Wireless distributed computing for cyclostationary feature detection

    Directory of Open Access Journals (Sweden)

    Mohammed I.M. Alfaqawi

    2016-02-01

    Full Text Available Recently, wireless distributed computing (WDC concept has emerged promising manifolds improvements to current wireless technologies. Despite the various expected benefits of this concept, significant drawbacks were addressed in the open literature. One of WDC key challenges is the impact of wireless channel quality on the load of distributed computations. Therefore, this research investigates the wireless channel impact on WDC performance when the latter is applied to spectrum sensing in cognitive radio (CR technology. However, a trade-off is found between accuracy and computational complexity in spectrum sensing approaches. Increasing these approaches accuracy is accompanied by an increase in computational complexity. This results in greater power consumption and processing time. A novel WDC scheme for cyclostationary feature detection spectrum sensing approach is proposed in this paper and thoroughly investigated. The benefits of the proposed scheme are firstly presented. Then, the impact of the wireless channel of the proposed scheme is addressed considering two scenarios. In the first scenario, workload matrices are distributed over the wireless channel. Then, a fusion center combines these matrices in order to make a decision. Meanwhile, in the second scenario, local decisions are made by CRs, then, only a binary flag is sent to the fusion center.

  13. The involvement of naturalists: Introduction to the Special Feature "Applying ecology" La participación de los naturalistas: Introducción al Tema Especial "Aplicando la ecología"

    Directory of Open Access Journals (Sweden)

    PATRICIO A CAMUS

    2011-06-01

    Full Text Available This article firstly introduces the Special Feature "Applying Ecology", addressing the use of ecological information for dealing with conservation and environmental problems in Chile. This is part of a series of special features in Revista Chilena de Historia Natural, intended for exploring the contribution of naturalists in making sound decisions in social-environmental planning. However, the low involvement of Chilean biologists has become a factor potentially affecting the quality of environmental decisions and policies, and increasing the chance of unwanted results, which raises some open questions about ethics. In such a context, the second part of the article analyzes the issue of involvement from different perspectives, considering its causes and consequences at individual and collective levels.Este artículo presenta en primer lugar el Tema Especial "Aplicando la Ecología", que aborda el uso de información ecológica para enfrentar problemas ambientales y de conservación en Chile. Este es parte de una serie de temas especiales en la Revista Chilena de Historia Natural, destinados a explorar la contribución de los naturalistas en la toma de decisiones bien fundamentadas en planificación socio-ambiental. Sin embargo, la baja participación de los biólogos chilenos se ha convertido en un factor que potencialmente afecta la calidad de las decisiones y políticas ambientales, y aumenta la probabilidad de los resultados no deseados, lo cual plantea algunas preguntas abiertas sobre ética. En este contexto, la segunda parte del artículo analiza el problema de la participación desde distintas perspectivas, considerando sus causas y consecuencias a nivel individual y colectivo.

  14. Radiographic properties and applied anatomy of presacral space in percutaneous axial lumbosacral interbody fusion%经皮前路腰骶轴向融合的骶前影像学及解剖学研究

    Institute of Scientific and Technical Information of China (English)

    靳松; 彭建强; 徐宏光; 刘平; 陈学武; 李怀斌

    2012-01-01

    Objective:To examine the radiologir and neurovascular ana-tomic data of the presacral area in Chinese population for safe procedure in percutaneous axial lumbosacral interbody fusion(AxiaLIF). Methods : ①Radiographic data were reviewed in 68 outpatients with low back pain undergone enhanced CT scanning. Measurements included bilateral iliac vessels to the S1,2 , the midpoint of the 2 clearance distance as well as lumbosacral MRI midsagittal chip measurement of the lumbosacral inter-vertebral space and each vertebral body point by the minimum distance of mesorectum. ② Anatomical aspects: 25 adult cadaveric specimens were included by measurement of internal / external iliac vessels, median sacral vein to S1,2 spaces at the midpoint of the distance and S1 distance between and nerve to determine coronal "safe zone" for operation. Results ATT images displayed the minimum distance of S1,2 space midline by the closest vessels with bilateral internal iliac vein. The reach within the bilateral internal iliac veins was(57. 7 ±4. 9)mm for men and(70.10 ± 9. 0) mm for women(P<0.05). MRI measurement exhibited the minimum distance between mesorectum and individual sacral anterior boder margin with median measurement of 10(3 -23)mm in males and 6(3 - 18)mm in females(P<0.01). Anatomical data revealed the "safe zone" for operation by(57. 60 ± 5. 11) mm in men and (70.01 ± 8. 99) mm in women,respectively. The distance between inner margin of bilateral ante-rior sacral foramina at the level of SI was(34. 95 ± 3. 50) mm for males and(31. 98 ± 2.99) mm for females. No difference was seen in the median sacral artery, whereas the median sacral veins varied a lot with thinner wall and existence rate of 48% . Conclusion : The measurement data for "safe zone" operation are in relative match in radiographic findings with anatomic measurement, which can be served as reference parameter for development of instrumentation and fusion device for bone surgery in Chinese population

  15. Fusion calculations for 40Ca+40Ca, 48Ca+48Ca, 40Ca+48Ca and p+208Pb systems

    Science.gov (United States)

    Gao, Jie; Zhang, Haifei; Bao, Xiaojun; Li, Junqing; Zhang, Hongfei

    2014-09-01

    The fusion cross sections of calcium isotopes and proton induced fusion have been calculated in terms of a coupled-channels formulation. Results indicated that there are big differences between the two fusion types. In the calculations of calcium isotopes fusion, the pair-transfer coupling has been applied in addition to the vibrational coupling, the combined effects showed that pair-transfer has played a significant role in the fusion process for the asymmetric 40Ca+48Ca system. The result of proton induced fusion for p+208Pb system successfully presents the fusion oscillation, which agrees with the experimental data rather well.

  16. Slantlet Transform for Multispectral Image Fusion

    Directory of Open Access Journals (Sweden)

    Adnan H.M. Al-Helali

    2009-01-01

    Full Text Available Problem statement: Image fusion is a process by which multispectral and panchromatic images, or some of their features, are combined together to form a high spatial/high spectral resolutions image. The successful fusion of images acquired from different modalities or instruments is a great importance issue in remote sensing applications. Approach: A new method of image fusion was introduced. It was based on a hybrid transform, which is an extension of Ridgelet transform. It used the slantlet transform instead of wavelet transform in the final steps of Ridgelet transform. The slantlet transform was an orthogonal discrete wavelet transform with two zero moments and with improved time localization. Results: Since edges and noise played fundamental role in image understanding, this hybrid transform was proved to be good way to enhance the edges and reduce the noise. Conclusion: The proposed method of fusion presented richer information in spatial and spectral domains simultaneously as well as it had reached an optimum fusion result.

  17. Sampling Based Average Classifier Fusion

    Directory of Open Access Journals (Sweden)

    Jian Hou

    2014-01-01

    fusion algorithms have been proposed in literature, average fusion is almost always selected as the baseline for comparison. Little is done on exploring the potential of average fusion and proposing a better baseline. In this paper we empirically investigate the behavior of soft labels and classifiers in average fusion. As a result, we find that; by proper sampling of soft labels and classifiers, the average fusion performance can be evidently improved. This result presents sampling based average fusion as a better baseline; that is, a newly proposed classifier fusion algorithm should at least perform better than this baseline in order to demonstrate its effectiveness.

  18. Fusion plasma physics

    CERN Document Server

    Stacey, Weston M

    2012-01-01

    This revised and enlarged second edition of the popular textbook and reference contains comprehensive treatments of both the established foundations of magnetic fusion plasma physics and of the newly developing areas of active research. It concludes with a look ahead to fusion power reactors of the future. The well-established topics of fusion plasma physics -- basic plasma phenomena, Coulomb scattering, drifts of charged particles in magnetic and electric fields, plasma confinement by magnetic fields, kinetic and fluid collective plasma theories, plasma equilibria and flux surface geometry, plasma waves and instabilities, classical and neoclassical transport, plasma-materials interactions, radiation, etc. -- are fully developed from first principles through to the computational models employed in modern plasma physics. The new and emerging topics of fusion plasma physics research -- fluctuation-driven plasma transport and gyrokinetic/gyrofluid computational methodology, the physics of the divertor, neutral ...

  19. Laser-Driven Fusion.

    Science.gov (United States)

    Gibson, A. F.

    1980-01-01

    Discusses the present status and future prospects of laser-driven fusion. Current research (which is classified under three main headings: laser-matter interaction processes, compression, and laser development) is also presented. (HM)

  20. Fusion Revisits CERN

    CERN Multimedia

    2001-01-01

    It's going to be a hot summer at CERN. At least in the Main Building, where from 13 July to 20 August an exhibition is being hosted on nuclear fusion, the energy of the Stars. Nuclear fusion is the engine driving the stars but also a potential source of energy for mankind. The exhibition shows the different nuclear fusion techniques and research carried out on the subject in Europe. Inaugurated at CERN in 1993, following collaboration between Lausanne's CRPP-EPFL and CERN, with input from Alessandro Pascolini of Italy's INFN, this exhibition has travelled round Europe before being revamped and returning to CERN. 'Fusion, Energy of the Stars', from 13 July onwards, Main Building

  1. Economically competitive fusion

    Directory of Open Access Journals (Sweden)

    David J. Ward

    2008-12-01

    Full Text Available Not since the oil crisis of the 1970s has the perception that energy is a crucial and precious resource been as strong as it is today. The need for a new approach to world energy supply, driven by concerns over resources, pollution, and security, is leading to a reappraisal of fusion. Fusion has enormous potential and major safety and environmental advantages, and hence could make a large difference to energy supplies.

  2. Fusion ignition research experiment

    Energy Technology Data Exchange (ETDEWEB)

    Dale Meade

    2000-07-18

    Understanding the properties of high gain (alpha-dominated) fusion plasmas in an advanced toroidal configuration is the largest remaining open issue that must be addressed to provide the scientific foundation for an attractive magnetic fusion reactor. The critical parts of this science can be obtained in a compact high field tokamak which is also likely to provide the fastest and least expensive path to understanding alpha-dominated plasmas in advanced toroidal systems.

  3. Use of the Nanofitin Alternative Scaffold as a GFP-Ready Fusion Tag.

    Directory of Open Access Journals (Sweden)

    Simon Huet

    Full Text Available With the continuous diversification of recombinant DNA technologies, the possibilities for new tailor-made protein engineering have extended on an on-going basis. Among these strategies, the use of the green fluorescent protein (GFP as a fusion domain has been widely adopted for cellular imaging and protein localization. Following the lead of the direct head-to-tail fusion of GFP, we proposed to provide additional features to recombinant proteins by genetic fusion of artificially derived binders. Thus, we reported a GFP-ready fusion tag consisting of a small and robust fusion-friendly anti-GFP Nanofitin binding domain as a proof-of-concept. While limiting steric effects on the carrier, the GFP-ready tag allows the capture of GFP or its blue (BFP, cyan (CFP and yellow (YFP alternatives. Here, we described the generation of the GFP-ready tag from the selection of a Nanofitin variant binding to the GFP and its spectral variants with a nanomolar affinity, while displaying a remarkable folding stability, as demonstrated by its full resistance upon thermal sterilization process or the full chemical synthesis of Nanofitins. To illustrate the potential of the Nanofitin-based tag as a fusion partner, we compared the expression level in Escherichia coli and activity profile of recombinant human tumor necrosis factor alpha (TNFα constructs, fused to a SUMO or GFP-ready tag. Very similar expression levels were found with the two fusion technologies. Both domains of the GFP-ready tagged TNFα were proved fully active in ELISA and interferometry binding assays, allowing the simultaneous capture by an anti-TNFα antibody and binding to the GFP, and its spectral mutants. The GFP-ready tag was also shown inert in a L929 cell based assay, demonstrating the potent TNFα mediated apoptosis induction by the GFP-ready tagged TNFα. Eventually, we proposed the GFP-ready tag as a versatile capture and labeling system in addition to expected applications of anti

  4. Safety of magnetic fusion facilities: Volume 2, Guidance

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1995-07-01

    This document provides guidance for the implementation of the requirements identified in Vol. 1 of this Standard. This guidance is intended for the managers, designers, operators, and other personnel with safety responsibilities for facilities designated as magnetic fusion facilities. While Vol. 1 is generally applicable in that requirements there apply to a wide range of fusion facilities, this volume is concerned mainly with large facilities such as the International Thermonuclear Experimental Reactor (ITER). Using a risk-based prioritization, the concepts presented here may also be applied to other magnetic fusion facilities. This volume is oriented toward regulation in the Department of Energy (DOE) environment.

  5. Fusion, cold fusion, and space policy

    Energy Technology Data Exchange (ETDEWEB)

    Rotegard, D. (CST Ltd. (United States))

    1991-01-01

    This paper critiques Americal science policy through a consideration of two examples-cold fusion and asteroid mining. It points out that the failure of central planning in science and technology policy is just as marked as in more mundane activities. It highlights the current low level of debate and points out some technical issues that need to be addressed. It concludes with evidence that the alliance of flawed policy options is further lowering the level of debate. (author).

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

    Science.gov (United States)

    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.

  7. APPLYING RANDOM FOREST CLASSIFIER COMBINED WITH TIME-FREQUENCY TEXTURE FEATURES TO BIRD SOUNDS RECOGNITION%结合时-频纹理特征的随机森林分类器应用于鸟声识别

    Institute of Scientific and Technical Information of China (English)

    陈莎莎; 李应

    2014-01-01

    An anti-noise bird sounds recognition system based on time-frequency texture features and random forest classifier is studied in this paper.As various unpredictable noises existing in the practical environment can make the performance of the recognition system degrade seriously,an audio frequency enhancement algorithm based on noise-estimation is firstly applied for front-end processing of the noisy bird sounds.Then the enhanced signal power spectrum is outputted in the form of time-frequency graph,and the texture features extraction is con-ducted using texture analysis method based on gray level co-occurrence matrix (GLCM)according to the texture information contained in time-frequency graph.Finally,an ensemble classifier based on decision tree-random forest is used for the classification and recognition of bird sounds.Experimental results show that the proposed method can recognise the bird sounds quickly and accurately,and has better anti-noise property as well.%研究一个基于时频纹理特征和随机森林分类器的抗噪鸟声识别系统。首先,针对实际环境中,各种不可预料的噪音会使得系统识别性能严重下降的问题,使用一种基于噪声估计的音频增强算法对带噪鸟声信号进行前端处理。然后将增强后的信号功率谱以时频图形式输出,并根据时频图中所包含的纹理信息,利用基于灰度共生矩阵的纹理分析法进行纹理特征提取。最后使用基于决策树的组合分类器-随机森林进行分类和识别。实验结果表明,该方法不仅能对鸟类声音进行快速准确地识别而且具有良好的抗噪性。

  8. The cytoplasmic domain of the gamete membrane fusion protein HAP2 targets the protein to the fusion site in Chlamydomonas and regulates the fusion reaction

    Science.gov (United States)

    Liu, Yanjie; Pei, Jimin; Grishin, Nick; Snell, William J.

    2015-01-01

    Cell-cell fusion between gametes is a defining step during development of eukaryotes, yet we know little about the cellular and molecular mechanisms of the gamete membrane fusion reaction. HAP2 is the sole gamete-specific protein in any system that is broadly conserved and shown by gene disruption to be essential for gamete fusion. The wide evolutionary distribution of HAP2 (also known as GCS1) indicates it was present in the last eukaryotic common ancestor and, therefore, dissecting its molecular properties should provide new insights into fundamental features of fertilization. HAP2 acts at a step after membrane adhesion, presumably directly in the merger of the lipid bilayers. Here, we use the unicellular alga Chlamydomonas to characterize contributions of key regions of HAP2 to protein location and function. We report that mutation of three strongly conserved residues in the ectodomain has no effect on targeting or fusion, although short deletions that include those residues block surface expression and fusion. Furthermore, HAP2 lacking a 237-residue segment of the cytoplasmic region is expressed at the cell surface, but fails to localize at the apical membrane patch specialized for fusion and fails to rescue fusion. Finally, we provide evidence that the ancient HAP2 contained a juxta-membrane, multi-cysteine motif in its cytoplasmic region, and that mutation of a cysteine dyad in this motif preserves protein localization, but substantially impairs HAP2 fusion activity. Thus, the ectodomain of HAP2 is essential for its surface expression, and the cytoplasmic region targets HAP2 to the site of fusion and regulates the fusion reaction. PMID:25655701

  9. Geoinformatics and Data Fusion in the Southwestern Utah Mineral Belt

    Science.gov (United States)

    Kiesel, T.; Enright, R.

    2012-12-01

    Data Fusion is a technique in remote sensing that combines separate geophysical data sets from different platforms to yield the maximum information of each set. Data fusion was employed on multiple sources of data for the purposes of investigating an area of the Utah Mineral Belt known as the San Francisco Mining District. In the past many mineral deposits were expressed in or on the immediate surface and therefore relatively easy to locate. More modern methods of investigation look for evidence beyond the visible spectrum to find patterns that predict the presence of deeply buried mineral deposits. The methods used in this study employed measurements of reflectivity or emissivity features in the infrared portion of the electromagnetic spectrum for different materials, elevation data collected from the Shuttle Radar Topography Mission and indirect measurement of the magnetic or mass properties of deposits. The measurements were collected by various spaceborne remote sensing instruments like Landsat TM, ASTER and Hyperion and ground-based statewide geophysical surveys. ASTER's shortwave infrared bands, that have been calibrated to surface reflectance using the atmospheric correction tool FLAASH, can be used to identify products of hydrothermal alteration like kaolinite, alunite, limonite and pyrophyllite using image spectroscopy. The thermal infrared bands once calibrated to emissivity can be used to differentiate between felsic, mafic and carbonate rock units for the purposes of lithologic mapping. To validate results from the extracted spectral profiles existing geological reports were used for ground truth data. Measurements of electromagnetic spectra can only reveal the composition of surface features. Gravimetric and magnetic information were utilized to reveal subsurface features. Using Bouguer anomaly data provided by the USGS an interpreted geological cross section can be created that indicates the shape of local igneous intrusions and the depth of

  10. Multimodal Sensor Fusion for Personnel Detection

    Science.gov (United States)

    2011-07-01

    Multimodal Sensor Fusion for Personnel Detection Xin Jin Shalabh Gupta Asok Ray Department of Mechanical Engineering The Pennsylvania State...have con- sidered relations taken only two at a time, but we propose to explore relations between higher order cliques as future work. D. Feature...detection,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 23, no. 6, pp. 577–589, 2001. [11] A. Ray , “Symbolic dynamic analysis

  11. A sensitive HIV-1 envelope induced fusion assay identifies fusion enhancement of thrombin

    Energy Technology Data Exchange (ETDEWEB)

    Cheng, De-Chun; Zhong, Guo-Cai; Su, Ju-Xiang [Department of Microbiology, Harbin Medical University, 194 Xuefu Road, Harbin, Heilongjiang 150081 (China); Liu, Yan-Hong [Second Affiliated Hospital of Harbin Medical University, 246 Xuefu Road, Harbin, Heilongjiang 150081 (China); Li, Yan; Wang, Jia-Ye [Department of Microbiology, Harbin Medical University, 194 Xuefu Road, Harbin, Heilongjiang 150081 (China); Hattori, Toshio [Department of Emerging Infectious Diseases, Division of Internal Medicine, Graduate School of Medicine, Tohoku University, Sendai 9808574 (Japan); Ling, Hong, E-mail: lingh@ems.hrbmu.edu.cn [Department of Microbiology, Harbin Medical University, 194 Xuefu Road, Harbin, Heilongjiang 150081 (China); Department of Parasitology, Harbin Medical University, 194 Xuefu Road, Harbin, Heilongjiang 150081 (China); Key Lab of Heilongjiang Province for Infection and Immunity, Key Lab of Heilongjiang Province Education Bureau for Etiology, Harbin, Heilongjiang 150081 (China); Zhang, Feng-Min, E-mail: fengminzhang@yahoo.com.cn [Department of Microbiology, Harbin Medical University, 194 Xuefu Road, Harbin, Heilongjiang 150081 (China); Key Lab of Heilongjiang Province for Infection and Immunity, Key Lab of Heilongjiang Province Education Bureau for Etiology, Harbin, Heilongjiang 150081 (China)

    2010-01-22

    To evaluate the interaction between HIV-1 envelope glycoprotein (Env) and target cell receptors, various cell-cell-fusion assays have been developed. In the present study, we established a novel fusion system. In this system, the expression of the sensitive reporter gene, firefly luciferase (FL) gene, in the target cells was used to evaluate cell fusion event. Simultaneously, constitutively expressed Renilla luciferase (RL) gene was used to monitor effector cell number and viability. FL gave a wider dynamic range than other known reporters and the introduction of RL made the assay accurate and reproducible. This system is especially beneficial for investigation of potential entry-influencing agents, for its power of ruling out the false inhibition or enhancement caused by the artificial cell-number variation. As a case study, we applied this fusion system to observe the effect of a serine protease, thrombin, on HIV Env-mediated cell-cell fusion and have found the fusion enhancement activity of thrombin over two R5-tropic HIV strains.

  12. Fusion transcriptome profiling provides insights into alveolar rhabdomyosarcoma.

    Science.gov (United States)

    Xie, Zhongqiu; Babiceanu, Mihaela; Kumar, Shailesh; Jia, Yuemeng; Qin, Fujun; Barr, Frederic G; Li, Hui

    2016-11-15

    Gene fusions and fusion products were thought to be unique features of neoplasia. However, more and more studies have identified fusion RNAs in normal physiology. Through RNA sequencing of 27 human noncancer tissues, a large number of fusion RNAs were found. By analyzing fusion transcriptome, we observed close clusterings between samples of same or similar tissues, supporting the feasibility of using fusion RNA profiling to reveal connections between biological samples. To put the concept into use, we selected alveolar rhabdomyosarcoma (ARMS), a myogenic pediatric cancer whose exact cell of origin is not clear. PAX3-FOXO1 (paired box gene 3 fused with forkhead box O1) fusion RNA, which is considered a hallmark of ARMS, was recently found during normal muscle cell differentiation. We performed and analyzed RNA sequencing from various time points during myogenesis and uncovered many chimeric fusion RNAs. Interestingly, we found that the fusion RNA profile of RH30, an ARMS cell line, is most similar to the myogenesis time point when PAX3-FOXO1 is expressed. In contrast, full transcriptome clustering analysis failed to uncover this connection. Strikingly, all of the 18 chimeric RNAs in RH30 cells could be detected at the same myogenic time point(s). In addition, the seven chimeric RNAs that follow the exact transient expression pattern as PAX3-FOXO1 are specific to rhabdomyosarcoma cells. Further testing with clinical samples also confirmed their specificity to rhabdomyosarcoma. These results provide further support for the link between at least some ARMSs and the PAX3-FOXO1-expressing myogenic cells and demonstrate that fusion RNA profiling can be used to investigate the etiology of fusion-gene-associated cancers.

  13. Image Fusion Techniques for Multispectral Palm Image Enhancement

    OpenAIRE

    Rajashree Bhokare; Deepali Sale; Dr. (Mrs. ) M. A. Joshi; Dr. M. S. Gaikwad

    2013-01-01

    We proposed the multispectral image enhancement through image fusion by combining the data from the multiple spectrum to address the problem of accuracy and make the system robust against spoofing and to improve the accuracy of recognition, using more discriminating of palm images. Palm line features are clearer in the blue and green bands while red band can reveal some palm vein structure. The NIR band can show the palm vein structure as well as partial line information. Image fusion improve...

  14. Myoblast fusion in Drosophila

    Energy Technology Data Exchange (ETDEWEB)

    Haralalka, Shruti [Stowers Institute for Medical Research, Kansas City, MO 64110 (United States); Abmayr, Susan M., E-mail: sma@stowers.org [Stowers Institute for Medical Research, Kansas City, MO 64110 (United States); Department of Anatomy and Cell Biology, University of Kansas Medical Center, Kansas City, MO 66160 (United States)

    2010-11-01

    The body wall musculature of a Drosophila larva is composed of an intricate pattern of 30 segmentally repeated muscle fibers in each abdominal hemisegment. Each muscle fiber has unique spatial and behavioral characteristics that include its location, orientation, epidermal attachment, size and pattern of innervation. Many, if not all, of these properties are dictated by founder cells, which determine the muscle pattern and seed the fusion process. Myofibers are then derived from fusion between a specific founder cell and several fusion competent myoblasts (FCMs) fusing with as few as 3-5 FCMs in the small muscles on the most ventral side of the embryo and as many as 30 FCMs in the larger muscles on the dorsal side of the embryo. The focus of the present review is the formation of the larval muscles in the developing embryo, summarizing the major issues and players in this process. We have attempted to emphasize experimentally-validated details of the mechanism of myoblast fusion and distinguish these from the theoretically possible details that have not yet been confirmed experimentally. We also direct the interested reader to other recent reviews that discuss myoblast fusion in Drosophila, each with their own perspective on the process . With apologies, we use gene nomenclature as specified by Flybase (http://flybase.org) but provide Table 1 with alternative names and references.

  15. Lateral Lumbar Interbody Fusion

    Science.gov (United States)

    Hughes, Alexander; Girardi, Federico; Sama, Andrew; Lebl, Darren; Cammisa, Frank

    2015-01-01

    The lateral lumbar interbody fusion (LLIF) is a relatively new technique that allows the surgeon to access the intervertebral space from a direct lateral approach either anterior to or through the psoas muscle. This approach provides an alternative to anterior lumbar interbody fusion with instrumentation, posterior lumbar interbody fusion, and transforaminal lumbar interbody fusion for anterior column support. LLIF is minimally invasive, safe, better structural support from the apophyseal ring, potential for coronal plane deformity correction, and indirect decompression, which have has made this technique popular. LLIF is currently being utilized for a variety of pathologies including but not limited to adult de novo lumbar scoliosis, central and foraminal stenosis, spondylolisthesis, and adjacent segment degeneration. Although early clinical outcomes have been good, the potential for significant neurological and vascular vertebral endplate complications exists. Nevertheless, LLIF is a promising technique with the potential to more effectively treat complex adult de novo scoliosis and achieve predictable fusion while avoiding the complications of traditional anterior surgery and posterior interbody techniques. PMID:26713134

  16. Polar Fusion Technique Analysis for Evaluating the Performances of Image Fusion of Thermal and Visual Images for Human Face Recognition

    CERN Document Server

    Bhowmik, Mrinal Kanti; Basu, Dipak Kumar; Nasipuri, Mita

    2011-01-01

    This paper presents a comparative study of two different methods, which are based on fusion and polar transformation of visual and thermal images. Here, investigation is done to handle the challenges of face recognition, which include pose variations, changes in facial expression, partial occlusions, variations in illumination, rotation through different angles, change in scale etc. To overcome these obstacles we have implemented and thoroughly examined two different fusion techniques through rigorous experimentation. In the first method log-polar transformation is applied to the fused images obtained after fusion of visual and thermal images whereas in second method fusion is applied on log-polar transformed individual visual and thermal images. After this step, which is thus obtained in one form or another, Principal Component Analysis (PCA) is applied to reduce dimension of the fused images. Log-polar transformed images are capable of handling complicacies introduced by scaling and rotation. The main objec...

  17. 彩色CCD比色测温的灰度值融合处理方法研究%An Intensity Fusion Method Applied To Color CCD-based Colorimetric Temperature Measurement

    Institute of Scientific and Technical Information of China (English)

    李进军

    2012-01-01

    设计了基于两个彩色CCD通道的比色测温系统,提出了用于比色测温时彩色CCD的R、G、B亮度(灰度)值融合处理方法,解决了在不同快门下利用两个通道的灰度值进行比色测温计算的问题;黑体炉实验结果表明,与常用的基于面阵CCD的简化比色测温方法相比较,基于两个彩色CCD通道的比色测温方法系统虽稍显复杂,但由于采用了经融合处理后的亮度值进行比色测量计算使得测温精度较高.%This paper designs a colorimetric temperature measurement method based on two color CCD. And presents an effective method applied to Colorimetric Temperature Measurement, which uses the intensity of the tuo CCD Camera images under different shutter. The experiment demonstrates that compared with the traditional methods, the simplified Dichromatic method , the proposed method obtained higher accuracy in the Temprature Measurement.

  18. 结合多特征的单幅图像超分辨率重建算法%Single image super-resolution reconstruction based on multi-feature fusion

    Institute of Scientific and Technical Information of China (English)

    黄剑华; 王丹丹; 金野

    2016-01-01

    为提高直接捕获的图像质量,针对梯度特征只能提取水平、垂直方向信息及非下采样轮廓波变换( NSCT)提取细节信息不足的缺陷,提出一种结合Gabor变换及NSCT的超分辨率重建算法。该算法充分利用Gabor变换和NSCT的互补性,针对输入图像块的特点,采用Gabor变换来提取纹理特征,NSCT来提取轮廓特征,然后分别利用稀疏模型进行重建,最后合并成一幅高分辨率图像。由于输入图像或多或少存在模糊,在重建过程中,加入了去模糊的正则项,以消除输入模糊的影响。实验结果表明,结合两种特征的超分辨率效果与单一特征相比,能够恢复更多的细节信息,去模糊正则项也有一定的作用。本文方法与Kim提出的核岭回归及Yang提出的稀疏表示算法( SCSR)相比,主观上视觉效果更加清晰,客观上PSNR值平均提高了近2dB,说明了该算法能够有效地提高图像的质量。%The gradients extract the information only along the horizontal and vertical directions and the non⁃subsampled contourlet transform ( NSCT) is poor relatively to capture the detailed information. To overcome the drawback, a novel super⁃resolution approach combined Gabor with NSCT is proposed to improve the quality of image captured directly. The algorithm makes full use of the complementary of the Gabor transform and NSCT, to extract the texture feature using the Gabor transform and to extract the contour feature using the NSCT according to the characteristics of input image pieces. After that the sparse coding reconstruction is performed, and finally merge the pieces into a initial high⁃resolution image. Since the input image is blurred more or less, the approach revises the initial high⁃resolution image through the deblurred regularization to eliminate the influence of blurred input. Experiment results show that combining the Gabor and NSCT can recover more details and

  19. Sensor fusion for airborne landmine detection

    Science.gov (United States)

    Schatten, Miranda A.; Gader, Paul D.; Bolton, Jeremy; Zare, Alina; Mendez-Vasquez, Andres

    2006-05-01

    Sensor fusion has become a vital research area for mine detection because of the countermine community's conclusion that no single sensor is capable of detecting mines at the necessary detection and false alarm rates over a wide variety of operating conditions. The U. S. Army Night Vision and Electronic Sensors Directorate (NVESD) evaluates sensors and algorithms for use in a multi-sensor multi-platform airborne detection modality. A large dataset of hyperspectral and radar imagery exists from the four major data collections performed at U. S. Army temperate and arid testing facilities in Autumn 2002, Spring 2003, Summer 2004, and Summer 2005. There are a number of algorithm developers working on single-sensor algorithms in order to optimize feature and classifier selection for that sensor type. However, a given sensor/algorithm system has an absolute limitation based on the physical phenomena that system is capable of sensing. Therefore, we perform decision-level fusion of the outputs from single-channel algorithms and we choose to combine systems whose information is complementary across operating conditions. That way, the final fused system will be robust to a variety of conditions, which is a critical property of a countermine detection system. In this paper, we present the analysis of fusion algorithms on data from a sensor suite consisting of high frequency radar imagery combined with hyperspectral long-wave infrared sensor imagery. The main type of fusion being considered is Choquet integral fusion. We evaluate performance achieved using the Choquet integral method for sensor fusion versus Boolean and soft "and," "or," mean, or majority voting.

  20. Applying ligands profiling using multiple extended electron distribution based field templates and feature trees similarity searching in the discovery of new generation of urea-based antineoplastic kinase inhibitors.

    Directory of Open Access Journals (Sweden)

    Eman M Dokla

    Full Text Available This study provides a comprehensive computational procedure for the discovery of novel urea-based antineoplastic kinase inhibitors while focusing on diversification of both chemotype and selectivity pattern. It presents a systematic structural analysis of the different binding motifs of urea-based kinase inhibitors and the corresponding configurations of the kinase enzymes. The computational model depends on simultaneous application of two protocols. The first protocol applies multiple consecutive validated virtual screening filters including SMARTS, support vector-machine model (ROC = 0.98, Bayesian model (ROC = 0.86 and structure-based pharmacophore filters based on urea-based kinase inhibitors complexes retrieved from literature. This is followed by hits profiling against different extended electron distribution (XED based field templates representing different kinase targets. The second protocol enables cancericidal activity verification by using the algorithm of feature trees (Ftrees similarity searching against NCI database. Being a proof-of-concept study, this combined procedure was experimentally validated by its utilization in developing a novel series of urea-based derivatives of strong anticancer activity. This new series is based on 3-benzylbenzo[d]thiazol-2(3H-one scaffold which has interesting chemical feasibility and wide diversification capability. Antineoplastic activity of this series was assayed in vitro against NCI 60 tumor-cell lines showing very strong inhibition of GI(50 as low as 0.9 uM. Additionally, its mechanism was unleashed using KINEX™ protein kinase microarray-based small molecule inhibitor profiling platform and cell cycle analysis showing a peculiar selectivity pattern against Zap70, c-src, Mink1, csk and MeKK2 kinases. Interestingly, it showed activity on syk kinase confirming the recent studies finding of the high activity of diphenyl urea containing compounds against this kinase. Allover, the new series

  1. Applying ligands profiling using multiple extended electron distribution based field templates and feature trees similarity searching in the discovery of new generation of urea-based antineoplastic kinase inhibitors.

    Science.gov (United States)

    Dokla, Eman M; Mahmoud, Amr H; Elsayed, Mohamed S A; El-Khatib, Ahmed H; Linscheid, Michael W; Abouzid, Khaled A

    2012-01-01

    This study provides a comprehensive computational procedure for the discovery of novel urea-based antineoplastic kinase inhibitors while focusing on diversification of both chemotype and selectivity pattern. It presents a systematic structural analysis of the different binding motifs of urea-based kinase inhibitors and the corresponding configurations of the kinase enzymes. The computational model depends on simultaneous application of two protocols. The first protocol applies multiple consecutive validated virtual screening filters including SMARTS, support vector-machine model (ROC = 0.98), Bayesian model (ROC = 0.86) and structure-based pharmacophore filters based on urea-based kinase inhibitors complexes retrieved from literature. This is followed by hits profiling against different extended electron distribution (XED) based field templates representing different kinase targets. The second protocol enables cancericidal activity verification by using the algorithm of feature trees (Ftrees) similarity searching against NCI database. Being a proof-of-concept study, this combined procedure was experimentally validated by its utilization in developing a novel series of urea-based derivatives of strong anticancer activity. This new series is based on 3-benzylbenzo[d]thiazol-2(3H)-one scaffold which has interesting chemical feasibility and wide diversification capability. Antineoplastic activity of this series was assayed in vitro against NCI 60 tumor-cell lines showing very strong inhibition of GI(50) as low as 0.9 uM. Additionally, its mechanism was unleashed using KINEX™ protein kinase microarray-based small molecule inhibitor profiling platform and cell cycle analysis showing a peculiar selectivity pattern against Zap70, c-src, Mink1, csk and MeKK2 kinases. Interestingly, it showed activity on syk kinase confirming the recent studies finding of the high activity of diphenyl urea containing compounds against this kinase. Allover, the new series, which is based on

  2. Fusion Reactor Materials

    Energy Technology Data Exchange (ETDEWEB)

    Decreton, M

    2002-04-01

    The objective of SCK-CEN's programme on fusion reactor materials is to contribute to the knowledge on the radiation-induced behaviour of fusion reactor materials and components as well as to help the international community in building the scientific and technical basis needed for the construction of the future reactor. Ongoing projects include: the study of the mechanical and chemical (corrosion) behaviour of structural materials under neutron irradiation and water coolant environment; the investigation of the characteristics of irradiated first wall material such as beryllium; investigations on the management of materials resulting from the dismantling of fusion reactors including waste disposal. Progress and achievements in these areas in 2001 are discussed.

  3. Fusion research at ORNL

    Energy Technology Data Exchange (ETDEWEB)

    1982-03-01

    The ORNL Fusion Program includes the experimental and theoretical study of two different classes of magnetic confinement schemes - systems with helical magnetic fields, such as the tokamak and stellarator, and the ELMO Bumpy Torus (EBT) class of toroidally linked mirror systems; the development of technologies, including superconducting magnets, neutral atomic beam and radio frequency (rf) heating systems, fueling systems, materials, and diagnostics; the development of databases for atomic physics and radiation effects; the assessment of the environmental impact of magnetic fusion; and the design of advanced demonstration fusion devices. The program involves wide collaboration, both within ORNL and with other institutions. The elements of this program are shown. This document illustrates the program's scope; and aims by reviewing recent progress.

  4. Peaceful Uses of Fusion

    Science.gov (United States)

    Teller, E.

    1958-07-03

    Applications of thermonuclear energy for peaceful and constructive purposes are surveyed. Developments and problems in the release and control of fusion energy are reviewed. It is pointed out that the future of thermonuclear power reactors will depend upon the construction of a machine that produces more electric energy than it consumes. The fuel for thermonuclear reactors is cheap and practically inexhaustible. Thermonuclear reactors produce less dangerous radioactive materials than fission reactors and, when once brought under control, are not as likely to be subject to dangerous excursions. The interaction of the hot plasma with magnetic fields opens the way for the direct production of electricity. It is possible that explosive fusion energy released underground may be harnessed for the production of electricity before the same feat is accomplished in controlled fusion processes. Applications of underground detonations of fission devices in mining and for the enhancement of oil flow in large low-specific-yield formations are also suggested.

  5. Infrared and Visual Image Fusion through Fuzzy Measure and Alternating Operators

    Science.gov (United States)

    Bai, Xiangzhi

    2015-01-01

    The crucial problem of infrared and visual image fusion is how to effectively extract the image features, including the image regions and details and combine these features into the final fusion result to produce a clear fused image. To obtain an effective fusion result with clear image details, an algorithm for infrared and visual image fusion through the fuzzy measure and alternating operators is proposed in this paper. Firstly, the alternating operators constructed using the opening and closing based toggle operator are analyzed. Secondly, two types of the constructed alternating operators are used to extract the multi-scale features of the original infrared and visual images for fusion. Thirdly, the extracted multi-scale features are combined through the fuzzy measure-based weight strategy to form the final fusion features. Finally, the final fusion features are incorporated with the original infrared and visual images using the contrast enlargement strategy. All the experimental results indicate that the proposed algorithm is effective for infrared and visual image fusion. PMID:26184229

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

    Directory of Open Access Journals (Sweden)

    Matteo Carrara

    2013-01-01

    Full Text Available 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.

  7. Multi-focus image fusion using a guided-filter-based difference image.

    Science.gov (United States)

    Yan, Xiang; Qin, Hanlin; Li, Jia; Zhou, Huixin; Yang, Tingwu

    2016-03-20

    The aim of multi-focus image fusion technology is to integrate different partially focused images into one all-focused image. To realize this goal, a new multi-focus image fusion method based on a guided filter is proposed and an efficient salient feature extraction method is presented in this paper. Furthermore, feature extraction is primarily the main objective of the present work. Based on salient feature extraction, the guided filter is first used to acquire the smoothing image containing the most sharpness regions. To obtain the initial fusion map, we compose a mixed focus measure by combining the variance of image intensities and the energy of the image gradient together. Then, the initial fusion map is further processed by a morphological filter to obtain a good reprocessed fusion map. Lastly, the final fusion map is determined via the reprocessed fusion map and is optimized by a guided filter. Experimental results demonstrate that the proposed method does markedly improve the fusion performance compared to previous fusion methods and can be competitive with or even outperform state-of-the-art fusion methods in terms of both subjective visual effects and objective quality metrics.

  8. Atomic data for fusion

    Energy Technology Data Exchange (ETDEWEB)

    Hunter, H.T.; Kirkpatrick, M.I.; Alvarez, I.; Cisneros, C.; Phaneuf, R.A. (eds.); Barnett, C.F.

    1990-07-01

    This report provides a handbook of recommended cross-section and rate-coefficient data for inelastic collisions between hydrogen, helium and lithium atoms, molecules and ions, and encompasses more than 400 different reactions of primary interest in fusion research. Published experimental and theoretical data have been collected and evaluated, and the recommended data are presented in tabular, graphical and parametrized form. Processes include excitation and spectral line emission, charge exchange, ionization, stripping, dissociation and particle interchange reactions. The range of collision energies is appropriate to applications in fusion-energy research.

  9. Fusion Welding Research.

    Science.gov (United States)

    2014-09-26

    RD-AlSO 253 FUSION WELDING RESEARCH(U) MASSACHUSETTS INST OF TECH L/I CAMBRIDGE DEPT OF MATERIALS SCIENCE AND ENGINEERING T W EAGAR ET AL. 30 RPR 85...NUMBER 12. GOV’ ACCESSION NO. 3. RECICIE-S CATALOG NUMBER 4. T TL V nd Subtitle) S. P OFRPR PERIOD COVERED 5t h A~nnual Technical Report Fusion Welding ...research S on welding processes. Studies include metal vapors in the arc, development of a high speed infrared temperature monitor, digital signal

  10. Quantum controlled fusion

    Science.gov (United States)

    Berrios, Eduardo; Gruebele, Martin; Wolynes, Peter G.

    2017-09-01

    Quantum-controlled motion of nuclei, starting from the nanometer-size ground state of a molecule, can potentially overcome some of the difficulties of thermonuclear fusion by compression of a fuel pellet or in a bulk plasma. Coherent laser control can manipulate nuclear motion precisely, achieving large phase space densities for the colliding nuclei. We combine quantum wavepacket propagation of D and T nuclei in a field-bound molecule with coherent control by a shaped laser pulse to demonstrate enhancement of nuclear collision rates. Atom-smashers powered by coherent control may become laboratory sources of particle bursts, and even assist muonic fusion.

  11. Fusion Propulsion Study

    Science.gov (United States)

    1989-07-01

    of propellant can be millions of times greater than the fuel, only a tiny fraction can completely push out the fuel. If the plasma is moving at a... push -plate for various explosive yields. It appears that the maximum specific impulse for such a system is -4000 to 5000 sec and increasing the base...Energy Agency, 1977, p. 507. Bourque, R.F., "OHTE as a Fusion Reactor," Proc. 4th Topl. Mt,. Tecnology of Controlled NV?4clear Fusion, King of Prussia

  12. Fusion Reactor Materials

    Energy Technology Data Exchange (ETDEWEB)

    Decreton, M

    2000-07-01

    SCK-CEN's research and development programme on fusion reactor materials includes: (1) the study of the mechanical behaviour of structural materials under neutron irradiation (including steels, inconel, molybdenum, chromium); (2) the determination and modelling of the characteristics of irradiated first wall materials such as beryllium; (3) the detection of abrupt electrical degradation of insulating ceramics under high temperature and neutron irradiation; (4) the study of the dismantling and waste disposal strategy for fusion reactors.; (5) a feasibility study for the testing of blanket modules under neutron radiation. Main achievements in these topical areas in the year 1999 are summarised.

  13. Improving Music Genre Classification by Short-Time Feature Integration

    DEFF Research Database (Denmark)

    Meng, Anders; Ahrendt, Peter; Larsen, Jan

    2005-01-01

    of seconds instead of milliseconds. The problem of making new features on the larger time scale from the short-time features (feature integration) has only received little attention. This paper investigates different methods for feature integration and late information fusion for music genre classification....... A new feature integration technique, the AR model, is proposed and seemingly outperforms the commonly used mean-variance features....

  14. Classification of weld defect based on information fusion technology for radiographic testing system

    Science.gov (United States)

    Jiang, Hongquan; Liang, Zeming; Gao, Jianmin; Dang, Changying

    2016-03-01

    Improving the efficiency and accuracy of weld defect classification is an important technical problem in developing the radiographic testing system. This paper proposes a novel weld defect classification method based on information fusion technology, Dempster-Shafer evidence theory. First, to characterize weld defects and improve the accuracy of their classification, 11 weld defect features were defined based on the sub-pixel level edges of radiographic images, four of which are presented for the first time in this paper. Second, we applied information fusion technology to combine different features for weld defect classification, including a mass function defined based on the weld defect feature information and the quartile-method-based calculation of standard weld defect class which is to solve a sample problem involving a limited number of training samples. A steam turbine weld defect classification case study is also presented herein to illustrate our technique. The results show that the proposed method can increase the correct classification rate with limited training samples and address the uncertainties associated with weld defect classification.

  15. Classification of weld defect based on information fusion technology for radiographic testing system.

    Science.gov (United States)

    Jiang, Hongquan; Liang, Zeming; Gao, Jianmin; Dang, Changying

    2016-03-01

    Improving the efficiency and accuracy of weld defect classification is an important technical problem in developing the radiographic testing system. This paper proposes a novel weld defect classification method based on information fusion technology, Dempster-Shafer evidence theory. First, to characterize weld defects and improve the accuracy of their classification, 11 weld defect features were defined based on the sub-pixel level edges of radiographic images, four of which are presented for the first time in this paper. Second, we applied information fusion technology to combine different features for weld defect classification, including a mass function defined based on the weld defect feature information and the quartile-method-based calculation of standard weld defect class which is to solve a sample problem involving a limited number of training samples. A steam turbine weld defect classification case study is also presented herein to illustrate our technique. The results show that the proposed method can increase the correct classification rate with limited training samples and address the uncertainties associated with weld defect classification.

  16. Improving iris recognition performance using segmentation, quality enhancement, match score fusion, and indexing.

    Science.gov (United States)

    Vatsa, Mayank; Singh, Richa; Noore, Afzel

    2008-08-01

    This paper proposes algorithms for iris segmentation, quality enhancement, match score fusion, and indexing to improve both the accuracy and the speed of iris recognition. A curve evolution approach is proposed to effectively segment a nonideal iris image using the modified Mumford-Shah functional. Different enhancement algorithms are concurrently applied on the segmented iris image to produce multiple enhanced versions of the iris image. A support-vector-machine-based learning algorithm selects locally enhanced regions from each globally enhanced image and combines these good-quality regions to create a single high-quality iris image. Two distinct features are extracted from the high-quality iris image. The global textural feature is extracted using the 1-D log polar Gabor transform, and the local topological feature is extracted using Euler numbers. An intelligent fusion algorithm combines the textural and topological matching scores to further improve the iris recognition performance and reduce the false rejection rate, whereas an indexing algorithm enables fast and accurate iris identification. The verification and identification performance of the proposed algorithms is validated and compared with other algorithms using the CASIA Version 3, ICE 2005, and UBIRIS iris databases.

  17. Fusion engineering device design description

    Energy Technology Data Exchange (ETDEWEB)

    Flanagan, C.A.; Steiner, D.; Smith, G.E.

    1981-12-01

    The US Magnetic Fusion Engineering Act of 1980 calls for the operation of a Fusion Engineering Device (FED) by 1990. It is the intent of the Act that the FED, in combination with other testing facilities, will establish the engineering feasibility of magnetic fusion energy. During 1981, the Fusion Engineering Design Center (FEDC), under the guidance of a Technical Management Board (TMB), developed a baseline design for the FED. This design is summarized herein.

  18. Fusion Engineering Device design description

    Energy Technology Data Exchange (ETDEWEB)

    Flanagan, C.A.; Steiner, D.; Smith, G.E.

    1981-12-01

    The US Magnetic Fusion Engineering Act of 1980 calls for the operation of a Fusion Engineering Device (FED) by 1990. It is the intent of the Act that the FED, in combination with other testing facilities, will establish the engineering feasibility of magnetic fusion energy. During 1981, the Fusion Engineering Design Center (FEDC), under the guidance of a Technical Management Board (TMB), developed a baseline design for the FED. This design is summarized herein.

  19. Application of the JDL data fusion process model for cyber security

    Science.gov (United States)

    Giacobe, Nicklaus A.

    2010-04-01

    A number of cyber security technologies have proposed the use of data fusion to enhance the defensive capabilities of the network and aid in the development of situational awareness for the security analyst. While there have been advances in fusion technologies and the application of fusion in intrusion detection systems (IDSs), in particular, additional progress can be made by gaining a better understanding of a variety of data fusion processes and applying them to the cyber security application domain. This research explores the underlying processes identified in the Joint Directors of Laboratories (JDL) data fusion process model and further describes them in a cyber security context.

  20. Burnside Rings of Fusion Systems

    DEFF Research Database (Denmark)

    Reeh, Sune Precht

    , and we produce a basis for the Burnside ring that shares properties with the transitive sets for a finite group. We construct a transfer map from the p-local Burnside ring of the underlying p-group S to the p-local Burnside ring of F. Using such transfer maps, we give a new explicit construction...... of Burnside rings given by multiplication with the characteristic idempotent, and we show that this map is the transfer map previously constructed. Applying these results, we show that for every saturated fusion system the ring generated by all (non-idempotent) characteristic elements in the p-local double...... of the characteristic idempotent of F { the unique idempotent in the p-local double Burnside ring of S satisfying properties of Linckelmann and Webb. We describe this idempotent both in terms of fixed points and as a linear combination of transitive bisets. Additionally, using fixed points we determine the map...

  1. International fusion og spaltning

    DEFF Research Database (Denmark)

    Hansen, Lone L.

    Bogen analyserer de nye muligheder fra 2007 i europæisk ret med hensyn til fusion eller spaltning mellem aktieselskaber og anpartsselskaber med hjemsted i forskellige europæiske lande. Bogen gennemgår de nye muligheder for strukturændringer, der herved er opstået mulighed for, og den sætter fokus...

  2. Fusion reactor materials

    Energy Technology Data Exchange (ETDEWEB)

    none,

    1989-01-01

    This paper discuses the following topics on fusion reactor materials: irradiation, facilities, test matrices, and experimental methods; dosimetry, damage parameters, and activation calculations; materials engineering and design requirements; fundamental mechanical behavior; radiation effects; development of structural alloys; solid breeding materials; and ceramics.

  3. International fusion og spaltning

    DEFF Research Database (Denmark)

    Hansen, Lone L.

    Bogen analyserer de nye muligheder fra 2007 i europæisk ret med hensyn til fusion eller spaltning mellem aktieselskaber og anpartsselskaber med hjemsted i forskellige europæiske lande. Bogen gennemgår de nye muligheder for strukturændringer, der herved er opstået mulighed for, og den sætter fokus...

  4. Synergetic Multisensor Fusion

    Science.gov (United States)

    1990-11-30

    technology have led to increased interest in using DEMs for navigation and other applications. In particular, DEMs are attractive for use in aircraft...Multisensor Fusion for Computer Vision [67]. 30 6. POSI!IONAL zSTIM&TION TECEnIQUzs FOR AN OUTDOOR MOBLE ROBOT The autonomous navigation of mobile robots is

  5. Muon catalyzed fusion

    Energy Technology Data Exchange (ETDEWEB)

    Ishida, K. [Advanced Meson Science Laboratory, RIKEN, 2-1 Hirosawa, Wako, Saitama 351-0198 (Japan); Nagamine, K. [Muon Science Laboratory, IMSS-KEK, 1-1 Oho, Tsukuba, Ibaraki 305-0801 (Japan); Matsuzaki, T. [Advanced Meson Science Laboratory, RIKEN, 2-1 Hirosawa, Wako, Saitama 351-0198 (Japan); Kawamura, N. [Muon Science Laboratory, IMSS-KEK, 1-1 Oho, Tsukuba, Ibaraki 305-0801 (Japan)

    2005-12-15

    The latest progress of muon catalyzed fusion study at the RIKEN-RAL muon facility (and partly at TRIUMF) is reported. The topics covered are magnetic field effect, muon transfer to {sup 3}He in solid D/T and ortho-para effect in dd{mu} formation.

  6. Bouillabaisse sushi fusion power

    CERN Multimedia

    2004-01-01

    "If avant-garde cuisine is any guide, Japanese-French fusion does not work all that well. And the interminable discussions over the International Thermonuclear Experimental Reactor (ITER) suggest that what is true of cooking is true of physics" (1 page)

  7. Hugging fusion and related topics

    Energy Technology Data Exchange (ETDEWEB)

    Iwamoto, Akira [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment

    1997-07-01

    An important problem related to the synthesis of very heavy nuclides by fusion of two heavy-ions is the extra push effect. To avoid it, we propose a hugging fusion, which is the fusion of two well-deformed heavy-ions. (author)

  8. A multifocus image fusion in nonsubsampled contourlet domain with variational fusion strategy

    Science.gov (United States)

    Ma, Ning; Luo, Limin; Zhou, Zeming; Liang, Miaoyuan

    2011-11-01

    Based on the variational idea, we propose a new fusion strategy for nonsubsampled contourlet transform (NSCT). For NSCT bandpass subband coefficients of input images, we take the main component of coefficients as the target and then build an extremum problem for energy functional to find the closest to the target one as the fused coefficient. We apply the gradient descent flow to minimize the functional and give the numerical scheme. The experimental results show that the proposed strategy outperforms state-of-the-art image fusion strategies for NSCT in terms of both visual quality and objective evaluation criteria.

  9. Histology image search using multimodal fusion.

    Science.gov (United States)

    Caicedo, Juan C; Vanegas, Jorge A; Páez, Fabian; González, Fabio A

    2014-10-01

    This work proposes a histology image indexing strategy based on multimodal representations obtained from the combination of visual features and associated semantic annotations. Both data modalities are complementary information sources for an image retrieval system, since visual features lack explicit semantic information and semantic terms do not usually describe the visual appearance of images. The paper proposes a novel strategy to build a fused image representation using matrix factorization algorithms and data reconstruction principles to generate a set of multimodal features. The methodology can seamlessly recover the multimodal representation of images without semantic annotations, allowing us to index new images using visual features only, and also accepting single example images as queries. Experimental evaluations on three different histology image data sets show that our strategy is a simple, yet effective approach to building multimodal representations for histology image search, and outperforms the response of the popular late fusion approach to combine information.

  10. CBFS: high performance feature selection algorithm based on feature clearness.

    Directory of Open Access Journals (Sweden)

    Minseok Seo

    Full Text Available BACKGROUND: The goal of feature selection is to select useful features and simultaneously exclude garbage features from a given dataset for classification purposes. This is expected to bring reduction of processing time and improvement of classification accuracy. METHODOLOGY: In this study, we devised a new feature selection algorithm (CBFS based on clearness of features. Feature clearness expresses separability among classes in a feature. Highly clear features contribute towards obtaining high classification accuracy. CScore is a measure to score clearness of each feature and is based on clustered samples to centroid of classes in a feature. We also suggest combining CBFS and other algorithms to improve classification accuracy. CONCLUSIONS/SIGNIFICANCE: From the experiment we confirm that CBFS is more excellent than up-to-date feature selection algorithms including FeaLect. CBFS can be applied to microarray gene selection, text categorization, and image classification.

  11. Applied longitudinal analysis

    CERN Document Server

    Fitzmaurice, Garrett M; Ware, James H

    2012-01-01

    Praise for the First Edition "". . . [this book] should be on the shelf of everyone interested in . . . longitudinal data analysis.""-Journal of the American Statistical Association   Features newly developed topics and applications of the analysis of longitudinal data Applied Longitudinal Analysis, Second Edition presents modern methods for analyzing data from longitudinal studies and now features the latest state-of-the-art techniques. The book emphasizes practical, rather than theoretical, aspects of methods for the analysis of diverse types of lo

  12. Handling Data Uncertainty and Inconsistency Using Multisensor Data Fusion

    Directory of Open Access Journals (Sweden)

    Waleed A. Abdulhafiz

    2013-01-01

    paper presents an approach to multisensor data fusion in order to decrease data uncertainty with ability to identify and handle inconsistency. The proposed approach relies on combining a modified Bayesian fusion algorithm with Kalman filtering. Three different approaches, namely, prefiltering, postfiltering and pre-postfiltering are described based on how filtering is applied to the sensor data, to the fused data or both. A case study to find the position of a mobile robot by estimating its x and y coordinates using four sensors is presented. The simulations show that combining fusion with filtering helps in handling the problem of uncertainty and inconsistency of the data.

  13. A framework of region-based dynamic image fusion

    Institute of Scientific and Technical Information of China (English)

    WANG Zhong-hua; QIN Zheng; LIU Yu

    2007-01-01

    A new framework of region-based dynamic image fusion is proposed. First, the technique of target detection is applied to dynamic images (image sequences) to segment images into different targets and background regions. Then different fusion rules are employed in different regions so that the target information is preserved as much as possible. In addition, steerable non-separable wavelet frame transform is used in the process of multi-resolution analysis, so the system achieves favorable characters of orientation and invariant shift. Compared with other image fusion methods, experimental results showed that the proposed method has better capabilities of target recognition and preserves clear background information.

  14. Distributed Fusion Receding Horizon Filtering in Linear Stochastic Systems

    Directory of Open Access Journals (Sweden)

    Il Young Song

    2009-01-01

    Full Text Available This paper presents a distributed receding horizon filtering algorithm for multisensor continuous-time linear stochastic systems. Distributed fusion with a weighted sum structure is applied to local receding horizon Kalman filters having different horizon lengths. The fusion estimate of the state of a dynamic system represents the optimal linear fusion by weighting matrices under the minimum mean square error criterion. The key contribution of this paper lies in the derivation of the differential equations for determining the error cross-covariances between the local receding horizon Kalman filters. The subsequent application of the proposed distributed filter to a linear dynamic system within a multisensor environment demonstrates its effectiveness.

  15. Computer-aided breast MR image feature analysis for prediction of tumor response to chemotherapy

    Energy Technology Data Exchange (ETDEWEB)

    Aghaei, Faranak; Tan, Maxine; Liu, Hong; Zheng, Bin, E-mail: Bin.Zheng-1@ou.edu [School of Electrical and Computer Engineering, University of Oklahoma, Norman, Oklahoma 73019 (United States); Hollingsworth, Alan B. [Mercy Women’s Center, Mercy Health Center, Oklahoma City, Oklahoma 73120 (United States); Qian, Wei [Department of Electrical and Computer Engineering, University of Texas, El Paso, Texas 79968 (United States)

    2015-11-15

    Purpose: To identify a new clinical marker based on quantitative kinetic image features analysis and assess its feasibility to predict tumor response to neoadjuvant chemotherapy. Methods: The authors assembled a dataset involving breast MR images acquired from 68 cancer patients before undergoing neoadjuvant chemotherapy. Among them, 25 patients had complete response (CR) and 43 had partial and nonresponse (NR) to chemotherapy based on the response evaluation criteria in solid tumors. The authors developed a computer-aided detection scheme to segment breast areas and tumors depicted on the breast MR images and computed a total of 39 kinetic image features from both tumor and background parenchymal enhancement regions. The authors then applied and tested two approaches to classify between CR and NR cases. The first one analyzed each individual feature and applied a simple feature fusion method that combines classification results from multiple features. The second approach tested an attribute selected classifier that integrates an artificial neural network (ANN) with a wrapper subset evaluator, which was optimized using a leave-one-case-out validation method. Results: In the pool of 39 features, 10 yielded relatively higher classification performance with the areas under receiver operating characteristic curves (AUCs) ranging from 0.61 to 0.78 to classify between CR and NR cases. Using a feature fusion method, the maximum AUC = 0.85 ± 0.05. Using the ANN-based classifier, AUC value significantly increased to 0.96 ± 0.03 (p < 0.01). Conclusions: This study demonstrated that quantitative analysis of kinetic image features computed from breast MR images acquired prechemotherapy has potential to generate a useful clinical marker in predicting tumor response to chemotherapy.

  16. Supersymmetry search via gauge boson fusion

    Indian Academy of Sciences (India)

    Anindya Datta

    2003-02-01

    We propose a novel method for the search of supersymmetry, especially for the electroweak gauginos at the large hadron collider (LHC). Gauge boson fusion technique was shown to be useful for heavy and intermediate mass Higgs bosons. In this article, we have shown that this method can also be applied to find the signals of EW gauginos in supersymmetric theories where the canonical search strategies for these particles fail.

  17. Safety studies on Korean fusion DEMO plant using integrated safety assessment methodology

    Energy Technology Data Exchange (ETDEWEB)

    Oh, Kyemin; Kang, Myoung-suk [Kyung Hee University, Youngin-si, Gyeonggi-do 446-701 (Korea, Republic of); Heo, Gyunyoung, E-mail: gheo@khu.ac.kr [Kyung Hee University, Youngin-si, Gyeonggi-do 446-701 (Korea, Republic of); Kim, Hyoung-chan [National Fusion Research Institute, Daejeon-si 305-333 (Korea, Republic of)

    2014-10-15

    Highlights: •The purpose of this paper is to suggest methodology that can investigate safety issues and provides a case study for Korean fusion DEMO plant. •The concepts of integrated safety assessment methodology (ISAM) that can be applied in addressing regulatory requirements and recognizing safety issues for K-DEMO were emphasized. •Phenomena identification and ranking table (PIRT) was proposed. It can recognize vulnerabilities of systems and identify the gaps in technical areas requiring additional researches. •This work is expected to contribute on the conceptual design of safety features for K-DEMO to design engineers and the guidance for regulatory requirements to licensers. -- Abstract: The purpose of this paper is to suggest methodology that can investigate safety issues and provides a case study for Korean fusion DEMO plant (K-DEMO) as a part of R and D program through the National Fusion Research Institute of Korea. Even though nuclear regulation and licensing framework is well setup due to the operating and design experience of Pressurized Water Reactors (PWRs) since 1970s, the regulatory authority of South Korea has concerns on the challenge of facing new nuclear facilities including K-DEMO due to the differences in systems, materials, and inherent safety feature from conventional PWRs. Even though the follow-up of the ITER license process facilitates to deal with significant safety issues of fusion facilities, a licensee as well as a licenser should identify the gaps between ITER and DEMO in terms of safety issues. First we reviewed the methods of conducting safety analysis for unprecedented nuclear facilities such as Generation IV reactors, particularly very high temperature reactor (VHTR), which is called as integrated safety assessment methodology (ISAM). Second, the analysis for the conceptual design of K-DEMO on the basis of ISAM was conducted. The ISAM consists of five analytical tools to develop the safety requirements from licensee

  18. CLASSIFICATION OF DIGITAL IMAGES USING FUSION ELEVATED ORDER CLASSIFIER IN WAVELET NEURAL NETWORK

    Directory of Open Access Journals (Sweden)

    R. Arulmurugan

    2014-01-01

    Full Text Available The revival of wavelet neural networks obtained an extensive use in digital image processing. The shape representation, classification and detection play a very important role in the image analysis. Boosted Greedy Sparse Linear Discriminate Analysis (BGSLDA trains the cascade level of detection in an efficient manner. With the application of reweighting concept and deployment of class-reparability criterion, lesser search was made on more efficient weak classifiers. At the same time, Multi-Scale Histogram of Oriented Gradients (MS-HOG method removes the confined portions of images. MS-HOG algorithm includes the advanced recognition scenarios such as rotations transportations on multiple objects but does not perform effective feature classification. To overcome the drawbacks in classification of higher order units, Fusion Elevated Order Classifier (FEOC method is introduced. FEOC contains a different fusion of high order units to deal with diverse datasets by making changes in the order of units with parametric considerations. FEOC uses a prominent value of input neurons for better fitting properties resulting in a higher level of learning parameters (i.e., weights. FEOC method features are reduced using feature subset collection method. However, elevation mechanisms are significantly applied to the neuron, neuron activation function type and finally in the higher order types of neural network with the functions of adaptive in nature. FEOC have evaluated sigma-pi network representing both the Elevated order Processing Unit (EPU and pi-sigma network. The experimental performance of Fusion Elevated Order Classifier in the wavelet neural network is evaluated against BGSLDA and MS-HOG using Statlog (Landsat Satellite Data Set from UCI repository. FEOC performed in MATLAB with factors such as classification accuracy rate, false positive error, computational cost, memory consumption, response time and higher order classifier rate.

  19. SIFT applied to CBIR

    Directory of Open Access Journals (Sweden)

    ALMEIDA, J.

    2009-12-01

    Full Text Available Content-Based Image Retrieval (CBIR is a challenging task. Common approaches use only low-level features. Notwithstanding, such CBIR solutions fail on capturing some local features representing the details and nuances of scenes. Many techniques in image processing and computer vision can capture these scene semantics. Among them, the Scale Invariant Features Transform~(SIFT has been widely used in a lot of applications. This approach relies on the choice of several parameters which directly impact its effectiveness when applied to retrieve images. In this paper, we discuss the results obtained in several experiments proposed to evaluate the application of the SIFT in CBIR tasks.

  20. Controlled fusion and plasma physics

    CERN Document Server

    Miyamoto, Kenro

    2006-01-01

    Resulting from ongoing, international research into fusion processes, the International Tokamak Experimental Reactor (ITER) is a major step in the quest for a new energy source.The first graduate-level text to cover the details of ITER, Controlled Fusion and Plasma Physics introduces various aspects and issues of recent fusion research activities through the shortest access path. The distinguished author breaks down the topic by first dealing with fusion and then concentrating on the more complex subject of plasma physics. The book begins with the basics of controlled fusion research, foll

  1. An evaluation of fusion gain in the compact helical fusion reactor FFHR-c1

    Science.gov (United States)

    Miyazawa, J.; Goto, T.; Sakamoto, R.; Sagara, A.; the FFHR Design Group

    2014-01-01

    A new procedure to predict achievable fusion gain in a sub-ignition fusion reactor is proposed. This procedure uses the direct profile extrapolation (DPE) method based on the gyro-Bohm model. The DPE method has been developed to predict the radial profiles in a fusion reactor sustained without auxiliary heating (i.e., in the self-ignition state) from the experimental data. To evaluate the fusion gain in a fusion reactor sustained with auxiliary heating (i.e., in the sub-ignition state), the DPE method is modified to include the influence of the auxiliary heating. The beta scale factor from experiment to reactor is assumed to be 1. Under this assumption, it becomes reasonable to apply the magnetohydrodynamic (MHD) equilibrium (which is calculated to reproduce the experimental data) to the reactor. At the same time, the MHD stability of the reactor plasma is also guaranteed to a certain extent since that beta was already proven in the experiment. The fusion gain in the helical type nuclear test machine FFHR-c1 has been evaluated using this modified DPE method. FFHR-c1 is basically a large duplication of the Large Helical Device (LHD) with a scale factor of 10/3, which corresponds to the major radius of the helical coils of 13.0 m and the plasma volume of ∼1000 m3. Two options with different magnetic field strengths are considered. The fusion gain in FFHR-c1 extrapolated from a set of radial profile data obtained in LHD ranges from 1 to 7, depending on the profiles used together with the assumptions of the magnetic field strength and the alpha heating efficiency.

  2. FGFR-TACC gene fusions in human glioma.

    Science.gov (United States)

    Lasorella, Anna; Sanson, Marc; Iavarone, Antonio

    2016-11-16

    Chromosomal translocations joining in-frame members of the fibroblast growth factor receptor-transforming acidic coiled-coil gene families (the FGFR-TACC gene fusions) were first discovered in human glioblastoma multiforme (GBM) and later in many other cancer types. Here, we review this rapidly expanding field of research and discuss the unique biological and clinical features conferred to isocitrate dehydrogenase wild-type glioma cells by FGFR-TACC fusions. FGFR-TACC fusions generate powerful oncogenes that combine growth-promoting effects with aneuploidy through the activation of as yet unclear intracellular signaling mechanisms. FGFR-TACC fusions appear to be clonal tumor-initiating events that confer strong sensitivity to FGFR tyrosine kinase inhibitors. Screening assays have recently been reported for the accurate identification of FGFR-TACC fusion variants in human cancer, and early clinical data have shown promising effects in cancer patients harboring FGFR-TACC fusions and treated with FGFR inhibitors. Thus, FGFR-TACC gene fusions provide a "low-hanging fruit" model for the validation of precision medicine paradigms in human GBM.

  3. Review of Heavy-Ion Inertial Fusion Physics

    CERN Document Server

    Kawata1, S; Ogoyski, A I

    2015-01-01

    In this review paper on heavy ion inertial fusion (HIF), the state-of-the-art scientific results are presented and discussed on the HIF physics, including physics of the heavy ion beam (HIB) transport in a fusion reactor, the HIBs-ion illumination on a direct-drive fuel target, the fuel target physics, the uniformity of the HIF target implosion, the smoothing mechanisms of the target implosion non- uniformity and the robust target implosion. The HIB has remarkable preferable features to release the fusion energy in inertial fusion: in particle accelerators HIBs are generated with a high driver efficiency of ~ 30-40%, and the HIB ions deposit their energy inside of materials. Therefore, a requirement for the fusion target energy gain is relatively low, that would be ~50-70 to operate a HIF fusion reactor with the standard energy output of 1GW of electricity. The HIF reactor operation frequency would be ~10~15 Hz or so. Several- MJ HIBs illuminate a fusion fuel target, and the fuel target is imploded to about a...

  4. Molecular pathways: targeting ETS gene fusions in cancer.

    Science.gov (United States)

    Feng, Felix Y; Brenner, J Chad; Hussain, Maha; Chinnaiyan, Arul M

    2014-09-01

    Rearrangements, or gene fusions, involving the ETS family of transcription factors are common driving events in both prostate cancer and Ewing sarcoma. These rearrangements result in pathogenic expression of the ETS genes and trigger activation of transcriptional programs enriched for invasion and other oncogenic features. Although ETS gene fusions represent intriguing therapeutic targets, transcription factors, such as those comprising the ETS family, have been notoriously difficult to target. Recently, preclinical studies have demonstrated an association between ETS gene fusions and components of the DNA damage response pathway, such as PARP1, the catalytic subunit of DNA protein kinase (DNAPK), and histone deactylase 1 (HDAC1), and have suggested that ETS fusions may confer sensitivity to inhibitors of these DNA repair proteins. In this review, we discuss the role of ETS fusions in cancer, the preclinical rationale for targeting ETS fusions with inhibitors of PARP1, DNAPK, and HDAC1, as well as ongoing clinical trials targeting ETS gene fusions. ©2014 American Association for Cancer Research.

  5. Simultaneous Segmentation and Statistical Label Fusion.

    Science.gov (United States)

    Asman, Andrew J; Landmana, Bennett A

    2012-02-23

    Labeling or segmentation of structures of interest in medical imaging plays an essential role in both clinical and scientific understanding. Two of the common techniques to obtain these labels are through either fully automated segmentation or through multi-atlas based segmentation and label fusion. Fully automated techniques often result in highly accurate segmentations but lack the robustness to be viable in many cases. On the other hand, label fusion techniques are often extremely robust, but lack the accuracy of automated algorithms for specific classes of problems. Herein, we propose to perform simultaneous automated segmentation and statistical label fusion through the reformulation of a generative model to include a linkage structure that explicitly estimates the complex global relationships between labels and intensities. These relationships are inferred from the atlas labels and intensities and applied to the target using a non-parametric approach. The novelty of this approach lies in the combination of previously exclusive techniques and attempts to combine the accuracy benefits of automated segmentation with the robustness of a multi-atlas based approach. The accuracy benefits of this simultaneous approach are assessed using a multi-label multi- atlas whole-brain segmentation experiment and the segmentation of the highly variable thyroid on computed tomography images. The results demonstrate that this technique has major benefits for certain types of problems and has the potential to provide a paradigm shift in which the lines between statistical label fusion and automated segmentation are dramatically blurred.

  6. Understanding Legacy Features with Featureous

    DEFF Research Database (Denmark)

    Olszak, Andrzej; Jørgensen, Bo Nørregaard

    2011-01-01

    Feature-centric comprehension of source code is essential during software evolution. However, such comprehension is oftentimes difficult to achieve due the discrepancies between structural and functional units of object-oriented programs. We present a tool for feature-centric analysis of legacy...

  7. Fusion Energy Division progress report, 1 January 1990--31 December 1991

    Energy Technology Data Exchange (ETDEWEB)

    Sheffield, J.; Baker, C.C.; Saltmarsh, M.J.

    1994-03-01

    The Fusion Program of the Oak Ridge National Laboratory (ORNL), a major part of the national fusion program, encompasses nearly all areas of magnetic fusion research. The program is directed toward the development of fusion as an economical and environmentally attractive energy source for the future. The program involves staff from ORNL, Martin Marietta Energy systems, Inc., private industry, the academic community, and other fusion laboratories, in the US and abroad. Achievements resulting from this collaboration are documented in this report, which is issued as the progress report of the ORNL Fusion Energy Division; it also contains information from components for the Fusion Program that are external to the division (about 15% of the program effort). The areas addressed by the Fusion Program include the following: experimental and theoretical research on magnetic confinement concepts; engineering and physics of existing and planned devices, including remote handling; development and testing of diagnostic tools and techniques in support of experiments; assembly and distribution to the fusion community of databases on atomic physics and radiation effects; development and testing of technologies for heating and fueling fusion plasmas; development and testing of superconducting magnets for containing fusion plasmas; development and testing of materials for fusion devices; and exploration of opportunities to apply the unique skills, technology, and techniques developed in the course of this work to other areas (about 15% of the Division`s activities). Highlights from program activities during 1990 and 1991 are presented.

  8. Fusion Energy Division annual progress report, period ending December 31, 1989

    Energy Technology Data Exchange (ETDEWEB)

    Sheffield, J.; Baker, C.C.; Saltmarsh, M.J.

    1991-07-01

    The Fusion Program of Oak Ridge National Laboratory (ORNL) carries out research in most areas of magnetic confinement fusion. The program is directed toward the development of fusion as an energy source and is a strong and vital component of both the US fusion program and the international fusion community. Issued as the annual progress report of the ORNL Fusion Energy Division, this report also contains information from components of the Fusion Program that are carried out by other ORNL organizations (about 15% of the program effort). The areas addressed by the Fusion Program and discussed in this report include the following: Experimental and theoretical research on magnetic confinement concepts, engineering and physics of existing and planned devices, including remote handling, development and testing of diagnostic tools and techniques in support of experiments, assembly and distribution to the fusion community of databases on atomic physics and radiation effects, development and testing of technologies for heating and fueling fusion plasmas, development and testing of superconducting magnets for containing fusion plasmas, development and testing of materials for fusion devices, and exploration of opportunities to apply the unique skills, technology, and techniques developed in the course of this work to other areas. Highlights from program activities are included in this report.

  9. European Nuclear Features

    Energy Technology Data Exchange (ETDEWEB)

    Barre, B.; Gonzalez, E.; Diaz Diaz, J.L.; Jimenez, J.L.; Velarde, G.; Navarro, J.M.; Hittner, D.; Dominguez, M.T.; Bollini, G.; Martin, A.; Suarez, J.; Traini, E.; Lang-Lenton, J.

    2004-09-01

    ''European Nuclear Features - ENF'' is a joint publication of the three specialized technical journals, Nuclear Espana (Spain), Revue General Nucleaire (France), and atw - International Journal of Nuclear Power (Germany). The ENF support the international Europeen exchange of information and news about energy and nuclear power. News items, comments, and scientific and technical contributions will cover important aspects of the field. The second issue of ENF contains contributions about theses topics, among others: Institutional and Political Changes in the EU. - CIEMAT Department of Nuclear Fission: A General Overview. - Inertial Fusion Energy at DENIM. - High Temperature Reactors. European Research Programme. - On Site Assistance to Khmelnitsky NPP 1 and 2 (Ukraine). - Dismantling and Decommissioning of Vandellos I. (orig.)

  10. Alphavirus Entry and Membrane Fusion

    Directory of Open Access Journals (Sweden)

    Margaret Kielian

    2010-03-01

    Full Text Available The study of enveloped animal viruses has greatly advanced our understanding of the general properties of membrane fusion and of the specific pathways that viruses use to infect the host cell. The membrane fusion proteins of the alphaviruses and flaviviruses have many similarities in structure and function. As reviewed here, alphaviruses use receptor-mediated endocytic uptake and low pH-triggered membrane fusion to deliver their RNA genomes into the cytoplasm. Recent advances in understanding the biochemistry and structure of the alphavirus membrane fusion protein provide a clearer picture of this fusion reaction, including the protein’s conformational changes during fusion and the identification of key domains. These insights into the alphavirus fusion mechanism suggest new areas for experimental investigation and potential inhibitor strategies for anti-viral therapy.

  11. Refractory metals fabrication technology as applied to fusion reactors

    Energy Technology Data Exchange (ETDEWEB)

    1976-07-01

    Activities are reported in research programs on inspection and fabricion of refractory metals and alloys including those of Mo, Nb, Ta, and V. Progress is summarized in sections on blanking, edge preparation, machining, forming, joining, cleaning, thermal processing, and coating. (JRD)

  12. Site Features

    Data.gov (United States)

    U.S. Environmental Protection Agency — This dataset consists of various site features from multiple Superfund sites in U.S. EPA Region 8. These data were acquired from multiple sources at different times...

  13. Feature Extraction

    CERN Document Server

    CERN. Geneva

    2015-01-01

    Feature selection and reduction are key to robust multivariate analyses. In this talk I will focus on pros and cons of various variable selection methods and focus on those that are most relevant in the context of HEP.

  14. Solar Features

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Collection includes a variety of solar feature datasets contributed by a number of national and private solar observatories located worldwide.

  15. New Characterizations of Fusion Bases and Riesz Fusion Bases in Hilbert Spaces

    OpenAIRE

    Asgari, Mohammad Sadegh

    2012-01-01

    In this paper we investigate a new notion of bases in Hilbert spaces and similar to fusion frame theory we introduce fusion bases theory in Hilbert spaces. We also introduce a new definition of fusion dual sequence associated with a fusion basis and show that the operators of a fusion dual sequence are continuous projections. Next we define the fusion biorthogonal sequence, Bessel fusion basis, Hilbert fusion basis and obtain some characterizations of them. we study orthonormal fusion systems...

  16. Infrared and visible images fusion based on RPCA and NSCT

    Science.gov (United States)

    Fu, Zhizhong; Wang, Xue; Xu, Jin; Zhou, Ning; Zhao, Yufei

    2016-07-01

    Current infrared and visible images fusion algorithms cannot efficiently extract the object information in the infrared image while retaining the background information in visible image. To address this issue, we propose a new infrared and visible image fusion algorithm by taking advantage of robust principal component analysis (RPCA) and non-subsampled Contourlet transform (NSCT). Firstly, RPCA decomposition is performed on the infrared and visible images respectively to obtain their corresponding sparse matrixes, which can well represent the sparse feature of images. Secondly, the infrared and visible images are decomposed into low frequency sub-band and high-frequency sub-band coefficients by using NSCT. Subsequently, the sparse matrixes are used to guide the fusion rule of low frequency sub-band coefficients and high frequency sub-band coefficients. Experimental results demonstrate that our fusion algorithm can highlight the infrared objects as well as retain the background information in visible image.

  17. Joint Multi-Focus Fusion and Bayer ImageRestoration

    Institute of Scientific and Technical Information of China (English)

    2015-01-01

    In this paper, a joint multifocus image fusion and Bayer pattern image restoration algorithm for raw images of single-sensor colorimaging devices is proposed. Different from traditional fusion schemes, the raw Bayer pattern images are fused before colorrestoration. Therefore, the Bayer image restoration operation is only performed one time. Thus, the proposed algorithm is moreefficient than traditional fusion schemes. In detail, a clarity measurement of Bayer pattern image is defined for raw Bayer patternimages, and the fusion operator is performed on superpixels which provide powerful grouping cues of local image feature. Theraw images are merged with refined weight map to get the fused Bayer pattern image, which is restored by the demosaicingalgorithm to get the full resolution color image. Experimental results demonstrate that the proposed algorithm can obtain betterfused results with more natural appearance and fewer artifacts than the traditional algorithms.

  18. Herpesvirus glycoproteins undergo multiple antigenic changes before membrane fusion.

    Directory of Open Access Journals (Sweden)

    Daniel L Glauser

    Full Text Available Herpesvirus entry is a complicated process involving multiple virion glycoproteins and culminating in membrane fusion. Glycoprotein conformation changes are likely to play key roles. Studies of recombinant glycoproteins have revealed some structural features of the virion fusion machinery. However, how the virion glycoproteins change during infection remains unclear. Here using conformation-specific monoclonal antibodies we show in situ that each component of the Murid Herpesvirus-4 (MuHV-4 entry machinery--gB, gH/gL and gp150--changes in antigenicity before tegument protein release begins. Further changes then occurred upon actual membrane fusion. Thus virions revealed their final fusogenic form only in late endosomes. The substantial antigenic differences between this form and that of extracellular virions suggested that antibodies have only a limited opportunity to block virion membrane fusion.

  19. A MEDICAL MULTI-MODALITY IMAGE FUSION OF CT/PET WITH PCA, DWT METHODS

    Directory of Open Access Journals (Sweden)

    S. Guruprasad

    2013-11-01

    Full Text Available This paper gives a view on the fusion of different modality images like PET and CT (Positron Emission Tomography & Computed Tomography by two domain methods PCA and DWT methods. The spatial domain is PCA method, and another transformation domain method (DWT. In dwt decomposed coefficients of DWT (discrete wavelet transformation are applied with the IDWT to get fused image information. Before that, choose a detailed part of decomposed coefficients by maximum selection and averaging the approximated part of DWT coefficients. In applying the PCA using eigen values and eigen vector of larger values as principal components and after to reconstruct using addition to these to get the fussed image of two modalities CT & PET. So that adds complimentary features of both anatomic, physiological and metabolic information in one image, provides better visual information in single image of patients in medical field. The analytic parameters like, MSE, PSNR, ENTROPY results are better enough to prove the methods each other.

  20. Examplers based image fusion features for face recognition

    CERN Document Server

    James, Alex Pappachen

    2012-01-01

    Examplers of a face are formed from multiple gallery images of a person and are used in the process of classification of a test image. We incorporate such examplers in forming a biologically inspired local binary decisions on similarity based face recognition method. As opposed to single model approaches such as face averages the exampler based approach results in higher recognition accu- racies and stability. Using multiple training samples per person, the method shows the following recognition accuracies: 99.0% on AR, 99.5% on FERET, 99.5% on ORL, 99.3% on EYALE, 100.0% on YALE and 100.0% on CALTECH face databases. In addition to face recognition, the method also detects the natural variability in the face images which can find application in automatic tagging of face images.