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Fusion Method (fusion + method)
Selected AbstractsLow-Temperature Fusion of Polymeric Nanostructures Using Carbon Dioxide,ADVANCED MATERIALS, Issue 2 2007Y. Yang A low-temperature fusion method for preparing polymeric nanostructures based on low-pressure CO2 -enhanced chain mobility at the nanoscale is presented. Characterization of the structures reveals a pressure-tunable rubbery layer on the surface. The successful fusion of polymeric nanostructures (see figure) at temperatures below the bulk glass-transition temperature of the polymer is demonstrated. The technique has potential for the assembly of 3D micro/nanoscale polymeric devices for biomedical applications. [source] MAP fusion method for superresolution of images with locally varying pixel qualityINTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY, Issue 4 2008Kio Kim Abstract Superresolution is a procedure that produces a high-resolution image from a set of low-resolution images. Many of superresolution techniques are designed for optical cameras, which produce pixel values of well-defined uncertainty, while there are still various imaging modalities for which the uncertainty of the images is difficult to control. To construct a superresolution image from low-resolution images with varying uncertainty, one needs to keep track of the uncertainty values in addition to the pixel values. In this paper, we develop a probabilistic approach to superresolution to address the problem of varying uncertainty. As direct computation of the analytic solution for the superresolution problem is difficult, we suggest a novel algorithm for computing the approximate solution. As this algorithm is a noniterative method based on Kalman filter-like recursion relations, there is a potential for real-time implementation of the algorithm. To show the efficiency of our method, we apply this algorithm to a video sequence acquired by a forward looking sonar system. © 2008 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 18, 242,250, 2008; Published online in Wiley InterScience (www.interscience.wiley.com). [source] LIDAR and vision-based pedestrian detection systemJOURNAL OF FIELD ROBOTICS (FORMERLY JOURNAL OF ROBOTIC SYSTEMS), Issue 9 2009Cristiano Premebida A perception system for pedestrian detection in urban scenarios using information from a LIDAR and a single camera is presented. Two sensor fusion architectures are described, a centralized and a decentralized one. In the former, the fusion process occurs at the feature level, i.e., features from LIDAR and vision spaces are combined in a single vector for posterior classification using a single classifier. In the latter, two classifiers are employed, one per sensor-feature space, which were offline selected based on information theory and fused by a trainable fusion method applied over the likelihoods provided by the component classifiers. The proposed schemes for sensor combination, and more specifically the trainable fusion method, lead to enhanced detection performance and, in addition, maintenance of false-alarms under tolerable values in comparison with single-based classifiers. Experimental results highlight the performance and effectiveness of the proposed pedestrian detection system and the related sensor data combination strategies. © 2009 Wiley Periodicals, Inc. [source] A new space and time sensor fusion method for mobile robot navigationJOURNAL OF FIELD ROBOTICS (FORMERLY JOURNAL OF ROBOTIC SYSTEMS), Issue 7 2004TaeSeok Jin To fully utilize the information from the sensors of mobile robot, this paper proposes a new sensor-fusion technique where the sample data set obtained at a previous instant is properly transformed and fused with the current data sets to produce a reliable estimate for navigation control. Exploration of an unknown environment is an important task for the new generation of mobile service robots. The mobile robots may navigate by means of a number of monitoring systems such as the sonar-sensing system or the visual-sensing system. Notice that in the conventional fusion schemes, the measurement is dependent on the current data sets only. Therefore, more sensors are required to measure a given physical parameter or to improve the reliability of the measurement. However, in this approach, instead of adding more sensors to the system, the temporal sequences of the data sets are stored and utilized for the purpose. The basic principle is illustrated by examples and the effectiveness is proved through simulations and experiments. The newly proposed STSF (space and time sensor fusion) scheme is applied to the navigation of a mobile robot in an environment using landmarks, and the experimental results demonstrate the effective performance of the system. © 2004 Wiley Periodicals, Inc. [source] Preparation of monoclonal antibody bank against whole water-soluble proteins from rapid-growing bamboo shootsPROTEINS: STRUCTURE, FUNCTION AND BIOINFORMATICS, Issue 22 2006Yu-Jen Wu Abstract An antibody bank against the whole proteins in a proteome is a useful tool for biological research. Using the standard cell fusion method, and a modified screening protocol, we produced an mAb bank against the total water-soluble proteins extracted from the rapid-growing green bamboo shoots. An improved two-stage strategy was employed to enrich those poor immunogenic or lower expressed proteins. Totally, we obtained a bank of 192 mAb which were identified as distinctive to each other by 2-DE and immunostaining. [source] Aberrant processing of deviant stimuli in schizophrenia revealed by fusion of fMRI and EEG dataACTA NEUROPSYCHIATRICA, Issue 3 2010Vince D. Calhoun Calhoun VD, Wu L, Kiehl KA, Eichele T, Pearlson GD. Aberrant processing of deviant stimuli in schizophrenia revealed by fusion of fMRI and EEG data. Background: Aberrant electrophysiological and haemodynamic processing of auditory oddball stimuli is among the most robustly documented findings in patients with schizophrenia. However, no study to date has directly examined linked patterns of electrical and haemodynamic differences in patients and controls. Methods: In a recent paper we demonstrated a data-driven approach, joint independent component analysis (jICA) to fuse together functional magnetic resonance imaging (fMRI) and event-related potential (ERP) data and elucidated the chronometry of auditory oddball target detection in healthy control subjects. In this paper we extend our fusion method to identify specific differences in the neuronal chronometry of target detection for chronic schizophrenia patients compared to healthy controls. Results: We found one linked source, consistent with the N2 response, known to be related to cognitive processing of deviant stimuli, spatially localized to bilateral fronto-temporal regions. This source showed significant between-group differences both in amplitude response and in the fMRI/ERP distribution pattern. These findings are consistent with previous work showing N2 amplitude and latency abnormalities in schizophrenia, and provide new information about the linkage between the two. Conclusions: In summary, we use a novel approach to isolate and identify a linked fMRI/ERP component which shows marked differences in chronic schizophrenia patients. We also show that jointly using both fMRI and ERP measures provides a fully picture of the underlying haemodynamic and electrical changes which are present in patients. Our approach also has broad applicability to other diseases such as autism, Alzheimer's disease, or bipolar disorder. [source] | ||||||||||