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  • Institute of Electrical and Electronics Engineers (IEEE)  (1,121)
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  • 1
    Publication Date: 2015-08-21
    Description: Objective: To develop a pipeline for realistic head models of nonhuman primates (NHPs) for simulations of noninvasive brain stimulation, and use these models together with empirical threshold measurements to demonstrate that the models capture individual anatomical variability. Methods: Based on structural MRI data, we created models of the electric field (E-field) induced by right unilateral (RUL) electroconvulsive therapy (ECT) in four rhesus macaques. Individual motor threshold (MT) was measured with transcranial electric stimulation (TES) administered through the RUL electrodes in the same subjects. Results: The interindividual anatomical differences resulted in 57% variation in median E-field strength in the brain at fixed stimulus current amplitude. Individualization of the stimulus current by MT reduced the E-field variation in the target motor area by 27%. There was significant correlation between the measured MT and the ratio of simulated electrode current and E-field strength ( $r^{2} = 0.95$ , $p = 0.026$ ). Exploratory analysis revealed significant correlations of this ratio with anatomical parameters including of the superior electrode-to-cortex distance, vertex-to-cortex distance, and brain volume ( $r^{2} > 0.96$ , $p 〈 0.02$ ). The neural activation threshold was estimated to be $0.45 pm 0.07$ V/cm for 0.2-ms stimulus pulse width. Conclusion: These results suggest that our individual-specific NHP E-field models appropriately capture individual anatomical variability relevant to the dosing of TES/ECT. These findings are exploratory due to the small number of subjects. Sign- ficance: This study can contribute insight in NHP studies of ECT and other brain stimulation interventions, help link the results to clinical studies, and ultimately lead to more rational brain stimulation dosing paradigms.
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  • 2
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    Publication Date: 2015-08-21
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  • 3
    Publication Date: 2015-08-21
    Description: Ectopic electrical activity that originates in the peri-infarct region can give rise to potentially lethal re-entrant arrhythmias. The spatial variation in electrotonic loading that results from structural remodelling in the infarct border zone may increase the probability that focal activity will trigger electrical capture, but this has not previously been investigated systematically. This study uses in-silico experiments to examine the structural modulation of effective refractory period on ectopic beat capture. Informed by 3-D reconstructions of myocyte organization in the infarct border zone, a region of rapid tissue expansion is abstracted to an idealized representation. A novel metric is introduced that defines the local electrotonic loading as a function of passive tissue properties and boundary conditions. The effective refractory period correlates closely with local electrotonic loading, while the action potential duration, conduction, and upstroke velocity reduce in regions of increasing electrotonic load. In the presence of focal ectopic stimuli, spatial variation in effective refractory period can cause unidirectional conduction block providing a substrate for reentrant arrhythmias. Consequently, based on the observed results, a possible novel mechanism for arrhythmogenesis in the infarct border zone is proposed.
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  • 4
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    Publication Date: 2015-08-22
    Description: Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.
    Print ISSN: 1521-9615
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    Topics: Computer Science , Natural Sciences in General , Technology
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  • 5
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    Publication Date: 2015-08-22
    Description: Kalyani Nair reviews "Multiscale Modeling in Biomechanics and Mechanobiology", edited by S. De, W. Hwang, and E. Kuhl, declaring it useful for anyone looking to get a quick overview of the field over a broad spectrum of areas.
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  • 6
    Publication Date: 2015-08-21
    Description: Automatic processing and accurate diagnosis of pathological electrocardiogram (ECG) signals remains a challenge. As long-term ECG recordings continue to increase in prevalence, driven partly by the ease of remote monitoring technology usage, the need to automate ECG analysis continues to grow. In previous studies, a model-based ECG filtering approach to ECG data from healthy subjects has been applied to facilitate accurate online filtering and analysis of physiological signals. We propose an extension of this approach, which models not only normal and ventricular heartbeats, but also morphologies not previously encountered. A switching Kalman filter approach is introduced to enable the automatic selection of the most likely mode (beat type), while simultaneously filtering the signal using appropriate prior knowledge. Novelty detection is also made possible by incorporating a third mode for the detection of unknown (not previously observed) morphologies, and denoted as X-factor. This new approach is compared to state-of-the-art techniques for the ventricular heartbeat classification in the MIT-BIH arrhythmia and Incart databases. $F_1$ scores of $mathbf {98.3%}$ and $mathbf {99.5%}$ were found on each database, respectively, which are superior to other published algorithms’ results reported on the same databases. Only $mathbf {3%}$ of all the beats were discarded as X-factor, and the majority of these beats contained high levels of noise. The proposed technique demonstrates accurate beat classification in the presence of previously unseen (and unlearned) morphologies and noise, and provides an automated method for morphological analysis of arbitrary (unknown) ECG leads.
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  • 7
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    Publication Date: 2015-08-21
    Description: Objective : A hybrid imaging technique, ultrasound-modulated luminescence tomography, that uses ultrasound to modulate diffusely propagating light has been shown to improve the spatial resolution of optical images. This paper investigates the underlying modulation mechanisms and the feasibility of applying this technique to improve spatial resolution in bioluminescence tomography. Methods : Ultrasound-modulated bioluminescence tomography was studied numerically to identify the effects of four factors (reduced optical scattering coefficient, optical absorption coefficient, refractive index, and luciferase concentration) on the depth of light modulation. In practice, an open source finite-element method tool for simulation of diffusely propagating light, near infrared fluorescence and spectral tomography, was modified to incorporate the effects of ultrasound modulation. The signal-to-noise ratios of detected modulated bioluminescent emissions are calculated using the optical and physical properties of a mouse model. Results : The modulation depth of the bioluminescent emission affected by the US induced variation of local concentration of the light emitting enzyme luciferase was at least two orders of magnitude greater than that caused by variations in the other factors. For surface radiances above approximately $10^7$ $hbox{photons}$ / $hbox{s}$ / $hbox{cm}^{2}$ / $hbox{sr,}$ the corresponding SNRs are detectable with the currently available detector technologies. Conclusion : The dominant effect in generation of ultrasound-modulated bioluminescence is ultrasound induced variation in luciferase concentration. The SNR analysis confirms the- feasibility of applying ultrasound-modulated bioluminescence tomography in preclinical imaging of mice. Significance : The simulation model developed suggests ultrasound-modulated bioluminescence tomography is a potential technique to improve the spatial resolution of bioluminescence tomography.
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  • 8
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    Publication Date: 2015-08-21
    Description: Mechanical ventilation of patients with acute respiratory distress syndrome (ARDS) is a necessary life support measure which may lead to ventilator-induced lung injury, a complication that can be reduced or ameliorated by using appropriate tidal volumes and positive end-expiratory pressures. However, the optimal mechanical ventilation parameters are almost certainly different for each patient, and will vary with time as the injury status of the lung changes. In order to optimize mechanical ventilation in an individual ARDS patient, therefore, it is necessary to track the manner in which injury status is reflected in the mechanical properties of the lungs. Accordingly, we developed an algorithm for assessing the time-dependent manner in which different lung regions open (recruit) and close (derecruit) as a function of the pressure waveform that is applied to the airways during mechanical ventilation. We used this algorithm to test the notion that variable ventilation provides the dynamic perturbations in lung volume necessary to accurately identify recruitment/derecruitment dynamics in the injured lung. We performed this test on synthetic pressure and flow data generated with established numerical models of lung function corresponding to both healthy mice and mice with lung injury. The data were generated by subjecting the models to a variety of mechanical ventilation regimens including variable ventilation. Our results support the hypothesis that variable ventilation can be used as a diagnostic tool to identify the injury status of the lung in ARDS.
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  • 9
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-08-21
    Description: Goal: Many brain–computer interface (BCI) classification techniques rely on a large number of labeled brain responses to create efficient classifiers. A large database representing all of the possible variability in the signal is impossible to obtain in a short period of time, and prolonged calibration times prevent efficient BCI use. We propose to improve BCIs based on the detection of event-related potentials (ERPs) in two ways. Methods: First, we increase the size of the training database by considering additional deformed trials. The creation of the additional deformed trials is based on the addition of Gaussian noise, and on the variability of the ERP latencies. Second, we exploit the variability of the ERP latencies by combining decisions across multiple deformed trials. These new methods are evaluated on data from 16 healthy subjects participating in a rapid serial visual presentation task. Results: The results show a significant increase in the performance of single-trial detection with the addition of artificial trials, and the combination of decisions obtained from altered trials. When the number of trials to train a classifier is low, the proposed approach allows us improve performance from an AUC of $0.533pm 0.080$ to $0.905pm 0.053$ . This improvement represents approximately an 80% reduction in classification error. Conclusion: These results demonstrate that artificially increasing the training dataset leads to improved single-trial detection. Significance: Calibration sessions can be shortened for BCIs based on ERP detection.
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  • 10
    Publication Date: 2015-08-21
    Description: Goal: The existing ISFET-based DNA sequencing detects hydrogen ions released during the polymerization of DNA strands on microbeads, which are scattered into microwell array above the ISFET sensor with unknown distribution. However, false pH detection happens at empty microwells due to crosstalk from neighboring microbeads. In this paper, a dual-mode CMOS ISFET sensor is proposed to have accurate pH detection toward DNA sequencing. Methods: Dual-mode sensing, optical and chemical modes, is realized by integrating a CMOS image sensor (CIS) with ISFET pH sensor, and is fabricated in a standard 0.18-μm CIS process. With accurate determination of microbead physical locations with CIS pixel by contact imaging, the dual-mode sensor can correlate local pH for one DNA slice at one location-determined microbead, which can result in improved pH detection accuracy. Moreover, toward a high-throughput DNA sequencing, a correlated-double-sampling readout that supports large array for both modes is deployed to reduce pixel-to-pixel nonuniformity such as threshold voltage mismatch. Results: The proposed CMOS dual-mode sensor is experimentally examined to show a well correlated pH map and optical image for microbeads with a pH sensitivity of 26.2 mV/pH, a fixed pattern noise (FPN) reduction from 4% to 0.3%, and a readout speed of 1200 frames/s. Conclusion: A dual-mode CMOS ISFET sensor with suppressed FPN for accurate large-arrayed pH sensing is proposed and demonstrated with state-of-the-art measured results toward accurate and high-throughput DNA sequencing. Significance: The developed dual-mode CMOS ISFET sensor has great potential for future personal genome diagnostics with high accuracy and low cost.
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  • 11
    Publication Date: 2015-08-21
    Description: Goal : Visual feedback can be used during gait rehabilitation to improve the efficacy of training. We presented a paradigm called visual feedback distortion; the visual representation of step length was manipulated during treadmill walking. Our prior work demonstrated that an implicit distortion of visual feedback of step length entails an unintentional adaptive process in the subjects’ spatial gait pattern. Here, we investigated whether the implicit visual feedback distortion, versus conscious correction, promotes efficient locomotor adaptation that relates to greater retention of a task. Methods: Thirteen healthy subjects were studied under two conditions: (1) we implicitly distorted the visual representation of their gait symmetry over 14 min, and (2) with help of visual feedback, subjects were told to walk on the treadmill with the intent of attaining the gait asymmetry observed during the first implicit trial. After adaptation, the visual feedback was removed while subjects continued walking normally. Over this 6-min period, retention of preserved asymmetric pattern was assessed. Results: We found that there was a greater retention rate during the implicit distortion trial than that of the visually guided conscious modulation trial. Conclusion: This study highlights the important role of implicit learning in the context of gait rehabilitation by demonstrating that training with implicit visual feedback distortion may produce longer lasting effects. Significance: This suggests that using visual feedback distortion could improve the effectiveness of treadmill rehabilitation processes by influencing the retention of motor skills.
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  • 12
    Publication Date: 2015-08-21
    Description: This paper explores the development of biomechanical models for evaluating a new class of passive mechanical implants for orthopedic surgery. The proposed implants take the form of passive engineered mechanisms, and will be used to improve the functional attachment of muscles to tendons and bone by modifying the transmission of forces and movement inside the body. Specifically, we present how two types of implantable mechanisms may be modeled in the open-source biomechanical software OpenSim. The first implant, which is proposed for hand tendon-transfer surgery, differentially distributes the forces and movement from one muscle across multiple tendons. The second implant, which is proposed for knee-replacement surgery, scales up the forces applied to the knee joint by the quadriceps muscle. This paper's key innovation is that such mechanisms have never been considered before in biomechanical simulation modeling and in surgery. When compared with joint function enabled by the current surgical practice of using sutures to make the attachment, biomechanical simulations show that the surgery with 1) the differential mechanism (tendon network) implant improves the fingers’ ability to passively adapt to an object's shape significantly during grasping tasks (2.74× as measured by the extent of finger flexion) for the same muscle force, and 2) the force-scaling implant increases knee-joint torque by 84% for the same muscle force. The critical significance of this study is to provide a methodology for the design and inclusion of the implants into biomechanical models and validating the improvement in joint function they enable when compared with current surgical practice.
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  • 13
    Publication Date: 2015-08-21
    Description: The impact of pulse repetition rate (PRR) in modulating electroporation (EP) induced by nanosecond pulsed electric fields (nsPEFs) in mammalian cells was approached here by performing both biological and numerical analysis. Plasma membrane permeabilization and viability of Jurkat cells were analyzed after exposure to 500, 1.3 MV/m, 40 ns PEFs with variable PRR (2–30 Hz). A finite-element model was used to investigate EP dynamics in a single cell under the same pulsing conditions, by looking at the time course of transmembrane voltage and pore density on the ns time scale. The biological observations showed an increased EP and reduced viability of the exposed cells at lower PRR in the considered range. The numerical analysis resulted in different dynamics of plasma membrane response when ns pulses were delivered with different PRR, consistently with a phenomenon of electrodesensitization recently hypothesized by another research group.
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  • 14
    Publication Date: 2015-08-21
    Description: Gastroscopy plays an important role in the diagnosis of gastric disease. In this paper, we develop an image panoramic system to assist endoscopists in improving lesion surveillance and reducing many of the tedious operations associated with gastroscopy. The constructed panoramic view has two categories: 1) the local view broadens the endoscopist's field of view in real time. Combining with the original gastroscopic video, this mosaicking view enables the endoscopist to diagnose the lesion comprehensively; 2) the global view constructs a large-area panoramic scene of the internal gastric surface, which can be used for intraoperative surgical navigation and postoperative scene review. Due to the irregular texture and inconsistent reflection of the gastric internal surface, common registration methods cannot accurately stitch this surface. Thereby, a six degree of freedom position tracking endoscope is devised to accommodate for the accumulated mosaicking error and provide efficient mosaicking results. For the global view, a dual-cube constraint model and a Bundle Adjustment algorithm are incorporated to deal with the mosaicking error caused by the irregular inflation and nonrigid deformation of the stomach. Moreover, texture blending and frame selection schemes are developed to make the mosaicking results feasible in real-clinical applications. The experimental results demonstrate that our system performs with a speed of 7.12 frames/s in a standard computer environment, and the mosaicking mean error is 0.43 mm for local panoramic view and 3.71 mm for global panoramic view.
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  • 15
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    Publication Date: 2015-08-21
    Description: In this paper, we present a smart capsule for location-specific drug release in the gastrointestinal tract. Once activated through a magnetic proximity fuse, the capsule opens up and releases its powdered payload in a location specified by an implanted miniature magnetic marker or an externally worn larger magnet. The capsule (9 mm × 26 mm) comprises of two compartments: one contains a charged capacitor and a reed switch, while the second one houses the drug reservoir capped by a taut nylon thread intertwined with a nichrome wire. The nichrome wire is connected to the capacitor through the reed switch. The capacitor is charged to 2.7 V before ingestion and once within the proximity of the permanent magnet; the reed switch closes, discharging the capacitor through the nichrome wire, melting the nylon thread, detaching the cap, and emptying the drug reservoir.
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  • 16
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    Publication Date: 2015-08-21
    Description: Goal: The purpose of this paper was to evaluate a nitinol tine fixation design for a transcatheter pacemaker in order to determine if the tines could be easily deployed and safely removed from the myocardium, enable low, stable pacing thresholds, and minimize the potential for dislodgment. Methods: The penetration properties of 13 human hearts were compared to the deployment and fixation energy of the tines to determine if the tines could be easily deployed and removed from the myocardium. The safety factor for dislodgement was calculated by comparing the kinetic energy of the device to the fixation energy of the tines. The fixation stability was tested in 113 chronic implants across 89 animals via pacing threshold measurements or evidence of dislodgement at necropsy. Results: Based on the tine fixation and tissue energy analysis, the tines can easily penetrate the heart. The tines can be safely removed from the myocardium based on the increased tine surface area during retraction. There were no dislodgements observed in the animals and the mean pacing threshold at implant was 0.59 +/− 0.21 V and at termination was 0.65 +/− 0.36 V. The safety factor for dislodgement was determined to be 15X during simulated exercise conditions. Conclusion: The nitinol tine fixation design enabled the implant of a self-contained pacemaker within the right ventricle and was effective in meeting the design requirements. Significance: This fixation technology provides a novel solution to enable the attachment of a transcatheter pacemaker directly within the heart.
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  • 17
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    Publication Date: 2015-06-03
    Description: Accurately recovering the hippocampal shapes against rough and noisy segmentations is as challenging as achieving good anatomical correspondence between the individual shapes. To address these issues, we propose a mesh-to-volume registration approach, characterized by a progressive model deformation. Our model implements flexible weighting scheme for model rigidity under a multi-level neighborhood for vertex connectivity. This method induces a large-to-small scale deformation of a template surface to build the pairwise correspondence by minimizing geometric distortion while robustly restoring the individuals' shape characteristics. We evaluated the proposed method's 1) accuracy and robustness in smooth surface reconstruction, 2) sensitivity in detecting significant shape differences between healthy control and disease groups (mild cognitive impairment and Alzheimer's disease), 3) robustness in constructing the anatomical correspondence between individual shape models, and 4) applicability in identifying subtle shape changes in relation to cognitive abilities in a healthy population. We compared the performance of the proposed method with other well-known methods—SPHARM-PDM, ShapeWorks and LDDMM volume registration with template injection—using various metrics of shape similarity, surface roughness, volume, and shape deformity. The experimental results showed that the proposed method generated smooth surfaces with less volume differences and better shape similarity to input volumes than others. The statistical analyses with clinical variables also showed that it was sensitive in detecting subtle shape changes of hippocampus.
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  • 18
    Publication Date: 2015-06-03
    Description: We propose a conditional random field (CRF) based classifier for segmentation of small enhanced pathologies. Specifically, we develop a temporal hierarchical adaptive texture CRF (THAT-CRF) and apply it to the challenging problem of gad enhancing lesion segmentation in brain MRI of patients with multiple sclerosis. In this context, the presence of many nonlesion enhancements (such as blood vessels) renders the problem more difficult. In addition to voxel-wise features, the framework exploits multiple higher order textures to discriminate the true lesional enhancements from the pool of other enhancements. Since lesional enhancements show more variation over time as compared to the nonlesional ones, we incorporate temporal texture analysis in order to study the textures of enhanced candidates over time. The parameters of the THAT-CRF model are learned based on 2380 scans from a multi-center clinical trial. The effect of different components of the model is extensively evaluated on 120 scans from a separate multi-center clinical trial. The incorporation of the temporal textures results in a general decrease of the false discovery rate. Specifically, THAT-CRF achieves overall sensitivity of 95% along with false discovery rate of 20% and average false positive count of 0.5 lesions per scan. The sensitivity of the temporal method to the trained time interval is further investigated on five different intervals of 69 patients. Moreover, superior performance is achieved by the reviewed labelings of our model compared to the fully manual labeling when applied to the context of separating different treatment arms in a real clinical trial.
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  • 19
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    Publication Date: 2015-06-03
    Description: We present a novel general-purpose compression method for tomographic images, termed 3D adaptive sparse representation based compression (3D-ASRC). In this paper, we focus on applications of 3D-ASRC for the compression of ophthalmic 3D optical coherence tomography (OCT) images. The 3D-ASRC algorithm exploits correlations among adjacent OCT images to improve compression performance, yet is sensitive to preserving their differences. Due to the inherent denoising mechanism of the sparsity based 3D-ASRC, the quality of the compressed images are often better than the raw images they are based on. Experiments on clinical-grade retinal OCT images demonstrate the superiority of the proposed 3D-ASRC over other well-known compression methods.
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  • 20
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    Publication Date: 2015-06-03
    Description: Accurate segmentation is usually crucial in transrectal ultrasound (TRUS) image based prostate diagnosis; however, it is always hampered by heavy speckles. Contrary to the traditional view that speckles are adverse to segmentation, we exploit intrinsic properties induced by speckles to facilitate the task, based on the observations that sizes and orientations of speckles provide salient cues to determine the prostate boundary. Since the speckle orientation changes in accordance with a statistical prior rule, rotation-invariant texture feature is extracted along the orientations revealed by the rule. To address the problem of feature changes due to different speckle sizes, TRUS images are split into several arc-like strips. In each strip, every individual feature vector is sparsely represented, and representation residuals are obtained. The residuals, along with the spatial coherence inherited from biological tissues, are combined to segment the prostate preliminarily via graph cuts. After that, the segmentation is fine-tuned by a novel level sets model, which integrates 1) the prostate shape prior, 2) dark-to-light intensity transition near the prostate boundary, and 3) the texture feature just obtained. The proposed method is validated on two 2-D image datasets obtained from two different sonographic imaging systems, with the mean absolute distance on the mid gland images only $1.06pm 0.53~{hbox {mm}}$ and $1.25pm 0.77~{hbox {mm}}$ , respectively. The method is also extended to segment apex and base images, producing competitive results over the state of the art.
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  • 21
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-18
    Description: Presents a listing of the handling editors for this issue of the publication.
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  • 22
    Publication Date: 2015-09-18
    Description: Presents corrections to the article, ???Learning to detect vocal hyperfunction from ambulatory neck-surface acceleration features: Initial results for vocal fold nodules,??? (Ghassemi, M., et al), IEEE Trans. Biomed. Eng., vol. 61, no. 6, pp. 1668???1675, Jun. 2014.
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  • 23
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    Publication Date: 2015-09-29
    Description: This paper considers the problem of emitter location in the presence of an adversary able to inject false information, where both the viewpoints of the adversary and locating network are considered. We begin by developing adversary strategies, which focus on degrading and redirecting the locating network. The locating network uses the time difference of arrival (TDOA) method and estimates the emitter location using both nonlinear least squares (LS) and the robust least median squares (LMS). Specifically, we determine the false sensor position the adversary should inject that maximally impacts the locating network by 1) minimizing the network???s accuracy, and 2) redirecting the network???s emitter location estimate. Similarly, we formulate a network???s strategy for detecting the adversary???s injection and develop a detector able to determine its presence under both adversary strategies. We present both theoretical and numerical results illustrating the effectiveness of the developed strategies.
    Print ISSN: 0018-9251
    Electronic ISSN: 1557-9603
    Topics: Electrical Engineering, Measurement and Control Technology , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
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  • 24
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    Publication Date: 2015-09-29
    Description: Delay/disruption tolerant networking (DTN) offers a solution to communications in ???challenged??? networks. Some work has been seen in evaluating the performance of DTN protocols based on simulated or emulated file transfer experiments. However, there is a need for a model of the performance of the DTN Licklider transmission protocol (LTP), which particularly targets reliable data transmission in deep space. In this paper, we present a performance model of LTP-based DTN data transmission in challenging communications characterized by extremely long signal propagation delay, lengthy link disruptions, and highly lossy channels that are typical of deep-space links. The model is verified by file-transfer experiments using a PC-based testbed.
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  • 25
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    Publication Date: 2015-09-29
    Description: Modeling of the dynamics and disturbances and designing of the precise formation controller are two major problems for the inner-formation flying system (IFFS). This paper introduces a nonlinear, nonautonomous formation dynamics model for IFFS in a general elliptic orbit. This model integrates the newly developed formation dynamics and the detailed disturbance models, including atmospheric drag, solar radiation pressure, and J2 effects. Furthermore, this paper establishes a coupled self-gravitational attraction model for IFFS. After considering such a comprehensive dynamics model, the precise formation control problem of IFFS is researched in detail. By referring to the averaging system, Hurwitz matrix, Lyapunov stability theorem, Matrosov???s theory, and Barbalat???s lemma as preliminaries, four possible controllers are designed, i.e., feedback-linearization plus proportional-derivative (PD) controller, Lyapunov-based controller, virtual potential-based controller, and velocity-free virtual potential-based controller. These controllers are all analyzed by the corresponding stability theories. Some simulations are carried out to testify these controllers, and the results show the effectiveness. By comparing the convergence time and fuel consumption, the velocity-free virtual potential-based controller is proven to be a more advantageous controller.
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  • 26
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-29
    Description: The fuel-optimal control problem of soft landing becomes a significant challenge due to the highly irregular gravitational field of an asteroid. An indirect method is used to deal with this fuel-optimal control problem. The difficult bang-bang control problem caused by the indirect method is solved through an improved fast homotopic approach. To validate the advanced homotopic method, the landing site is selected in a region where the gravitational field is especially irregular. The results show that this method is effective for the fuel-optimal control problem in an irregular gravitational field. Moreover, the trajectory designed with the fuel-optimal control is taken as a nominal descent trajectory for a sliding mode control. Monte Carlo simulations show that the desired soft landing can be achieved by tracking the fuel-optimal trajectory.
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  • 27
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-29
    Description: In this paper, a novel framework of sparse kernel learning for support vector data description (SVDD) based anomaly detection is presented. By introducing 0-1 control variables to original features in the input space, sparse feature selection for anomaly detection is modeled as a mixed integer programming problem. Due to the prohibitively high computational complexity, it is relaxed into a quadratically constrained linear programming (QCLP) problem. The QCLP problem can then be practically solved by using an iterative optimization method, in which multiple subsets of features are iteratively found as opposed to a single subset. However, when a nonlinear kernel such as Gaussian radial basis function kernel, associated with an infinite-dimensional reproducing kernel Hilbert space (RKHS) is used in the QCLP-based iterative optimization, it is impractical to find optimal subsets of features due to a large number of possible combinations of the original features. To tackle this issue, a feature map called the empirical kernel map, which maps data points in the input space into a finite space called the empirical kernel feature space (EKFS), is used in the proposed work. The QCLP-based iterative optimization problem is solved in the EKFS instead of in the input space or the RKHS. This is possible because the geometrical properties of the EKFS and the corresponding RKHS remain the same. Now, an explicit nonlinear exploitation of the data in a finite EKFS is achievable, which results in optimal feature ranking. Comprehensive experimental results on three hyperspectral images and several machine learning datasets show that our proposed method can provide improved performance over the current state-of-the-art techniques.
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  • 28
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-29
    Description: This paper deals with the swath acquisition planning problem for multisatellite Earth observation missions. Given a set of satellites and a mission time frame, the problem we solve consists of selecting a set of acquisitions from the satellites in order to cover a given region of interest during the requested time frame, optimizing a certain objective function.We show that the planning problem can be modeled as a set covering problem, using basic tools of mathematical programming. The formulation of the model requires the solution of a complex computational geometry problem, and therefore the use of heuristics and metaheuristics applies. In this paper, we discuss the efficiency of the constructive phase of a greedy randomized adaptive search procedure algorithm. Computational results comparing the heuristic algorithms with the exact approach are presented.
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  • 29
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-29
    Description: This paper proposes an efficient method to classify inverse synthetic aperture radar (ISAR) images. The proposed method achieves invariance to translation and rotation of ISAR images by using two-dimensional (2D) Fourier transform (FT) of ISAR images, polar mapping of the 2D FT image, and a simple nearest-neighbor classifier. In simulations using ISAR images measured in a compact range, the proposed method yielded high classification ratios with small-sized data regardless of the location of the rotation center, whereas the existing method was very sensitive to the location of it.
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  • 30
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-29
    Description: A method for fusing synthetic aperture radar (SAR) images with optical aerial images is presented. This is done in a navigation framework, in which the absolute position and orientation of the flying platform, as computed from the inertial navigation system, is corrected based on the aerial image coordinates taken as ground truth. The method is suitable for new low-price SAR systems for small unmanned vehicles. The primary application is surveillance, and to some extent it can be applied to remote sensing, where the SAR image provides complementary information by revealing reflectivity to microwave frequencies. The method is based on first applying an edge detection algorithm to the images and then optimising the most important navigation states by matching the two binary images. To get a measure of the estimation uncertainty, we embed the optimisation in a least squares framework, in which an explicit method to estimate the (relative) size of the errors is presented. The performance is demonstrated on real SAR and aerial images, leading to an error of only a few pixels (around 4 m in our case), which is a quite satisfactory performance for applications like surveillance and navigation.
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  • 31
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-29
    Description: This paper presents a sensor-control method for choosing the best next state of the sensors that provide accurate estimation results in a multitarget tracking application. The proposed solution is formulated for a multi-Bernoulli filter and works via minimization of a new estimation-error-based cost function. Simulation results demonstrate that the proposed method can outperform the state-of-the-art methods in terms of computation time and robustness to clutter while delivering similar accuracy.
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  • 32
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-29
    Description: The Kalman filter has always been applied to enhance the estimation of inertial measurement unit errors and to improve estimation accuracy of navigation states under practical conditions. Therefore, understanding the behaviors and limitations of optimal estimation of the navigation states is instructive and of great importance. In order to provide comprehensive information about the observability and convergence rapidity of the navigation states when implementing a Kalman filter, the basic properties of intuitive linear-algebraic characterizations of stochastic observability will be intensively investigated in this study. We have extended the utilization of the analytic stochastic observability approach for analytic optimization of strapdown inertial navigation systems multiposition stationary alignment. The advantage of analytic explicit formulation of convergence rapidity of the implemented Kalman filter by stochastic observability approach is demonstrated. Compared to numerical simulation methods, the proposed stochastic observability approach can provide analysts with much more analytic information.
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  • 33
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-29
    Description: Localization of persons that are hidden behind a corner is important in various security situations when the first responders should not be exposed to any threat. This article demonstrates the feasibility of an ultrawideband multipath-exploitation radar for localization in such scenarios. The approach utilizes multibounce echoes of electromagnetic waves that are scattered by the closest person situated behind a corner. We assume that the person does not carry any tag and does not cooperate with the localization system. The multibounce echoes are reflected and diffracted by the surroundings and make the hidden person visible to an operator that is behind the corner. The location estimation relies only on single-channel time-of-arrival data. Measured data are first processed by a background subtraction algorithm, which reveals the multipath evoked by the person. The multipath echoes are detected by a parallel threshold-based detector. A simple global nearest-neighbor algorithm is used for tracking detected echoes and improving their range estimates. The obtained range estimates are assigned to different physical propagation paths of the electromagnetic waves. The location of the person is estimated by fusing the information of the antenna location with respect to its surroundings and the assigned range estimates. The proposed approach is experimentally verified in a scenario where data are measured in real time by an ultrawideband sensor. Experimental results demonstrate that, depending on the scenario geometry, a walking or calmly standing person can be localized up to several meters behind the corner.
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  • 34
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-29
    Description: Inverse synthetic aperture radar (ISAR) images can be obtained using digital video broadcasting???terrestrial (DVB-T)???based passive radars. However, television broadcast???transmitted signals offer poor range resolution for imaging purposes, because they have a narrower bandwidth with respect to those transmitted by a dedicated ISAR system. To reach finer range resolutions, signals composed of multiple DVB-T channels are required. Problems arise, however, because DVB-T channels are typically widely separated in the frequency domain. The gaps between channels produce high grating lobes in the image domain when Fourier-based algorithms are used to form the ISAR image. In this paper, compressive sensing theory is investigated to address this problem because of its ability to reconstruct sparse signals by using incomplete measures. By solving an optimization problem under the constraint of signal sparsity, passive ISAR images can be obtained with strongly reduced grating lobes. Both simulation and experimental results are shown to demonstrate the validity of the proposed approach.
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  • 35
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-29
    Description: Mechanically steered scanning radars receive measurements continuously while sweeping the surveillance region. However, most target tracking algorithms, like the multiple hypothesis tracker (MHT) and the joint probabilistic data association (JPDA) techniques, wait for the end of a scan in order to process the measurements and to estimate targets states. This is due to the fundamental assumption of one-to-one association between tracks and measurements and the 360° physical limit of a scan. Associating measurements to initialized tracks and filtering at the end of a complete scan may cause significant delays in target state update. In addition, association may become imperfect due to longer intervals between updates. This issue becomes significant when tracking high-speed targets with low scan rate sensors as in the airborne early warning (AEW) system. In this paper, we present a new dynamic sector processing algorithm using two-dimensional (2-D) assignment for scanning radars that report measurements within the duration of a scan. The full scan is dynamically and adaptively divided into sectors, which could be as small as a single detection, depending on the scanning rate, sparsity of targets, and required target state update speed. Measurement-to-track association, filtering, and target state update are done dynamically while sweeping from one region to another, i.e., continuous track update, limited only by the intermeasurement interval, becomes possible. The proposed algorithm offers low latency while maintaining estimation accuracy in track updates as well as efficient utilization of computational resources compared with standard frame-based tracking algorithms. Experimental results based on rotating radars demonstrate the advantages of the proposed technique.
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  • 36
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-29
    Description: An iterative ESPRIT-like algorithm is devised for direction-of-departure (DOD) and direction-of-arrival (DOA) estimation in multiple-input multiple-output radar. Our proposal can handle identical DODs and DOAs, and provides autopairing of the angle parameters. Furthermore, it is proved that the multiple signal classification methodology cannot identify (MN ??? 1) targets, where M and N are the element numbers in the transmit and receive antennas, respectively. Simulation results are included to evaluate the performance of the proposed algorithm.
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  • 37
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-29
    Description: Multiple-input multiple-output (MIMO) radar imaging suffers from performance degradation under carrier offsets across transmitters and receivers. This paper analyzes the impact of carrier offsets on imaging a sparse target, from the perspective of the MIMO point spread function (PSF). Conditions are established for successful support recovery using orthogonal matching pursuit (OMP), and the performance loss is characterized in terms of l2 distance. A sparse imaging algorithm taking into account the perturbation due to carrier offsets is also proposed, which improves upon the OMP algorithm. Numerical experiments corroborate this analysis.
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  • 38
    Publication Date: 2015-09-29
    Description: Ambiguity functions (AFs) are obtained for a radar using matched illumination (MI) transmit signals for the detection of range-spread targets in the presence of clutter. The transmit signals are adapted to target and interference spectra and are filtered optimally in the receiver; they are designed to maximize signal-to-interference-and-noise ratio (SINR) power ratios at receiver output. In this paper, expressions for processing gains, spread AFs, and Cramer-Rao bounds on range and Doppler estimates are derived based on likelihood functions. Here, for extended targets, AFs resulting from using optimal MI constant envelope waveforms obtained via phase retrieval techniques demonstrate superior resolution characteristics compared with classic linear frequency-modulated (LFM) signals employing optimal pulse compression. For various target and clutter spectral models, simulation results show that optimally filtered MI signals provide significantly enhanced SINR behavior compared with LFM radar signals. Hopefully, these results set the stage for the induction of MI signaling and receive techniques into conventional radar signal processing and pave the way for realization of one methodology for achieving cognition in radar systems.
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  • 39
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-29
    Description: In an effort to improve the channel utilization of a warship combat system (WCS), it is necessary to control and manage the large volume of video traffic by considering a strong self-similarity characteristic. We propose a new video traffic management method for the WCS that smooths the traffic of the closed-circuit television surveillance system (CSS) video and encodes the electro-optical tracking system (EOTS) video with low complexity in real time. First, to achieve global and local traffic smoothing for the CSS video traffic, a proper bandwidth allocation interval and a minimum bandwidth for the CSS video traffic must be determined. Second, due to the increased available bandwidth after traffic smoothing, more elaborate low-delay encoding is accomplished by selecting encoding modes adaptively to compress the EOTS video efficiently with high visual quality. The experimental results demonstrate that the proposed method is able to control the WCS traffic to be as flat as possible and to encode the EOTS video with low delay, even in combat and emergency scenarios. Hence, we show that to migrate to network-centric warfare successfully, the proposed method is much more suitable for the WCS than conventional video traffic management.
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  • 40
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-29
    Description: In this paper, we propose multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) radar with sufficient cyclic prefix (CP), where all OFDM pulses transmitted from different transmitters share the same frequency band and are orthogonal to each other for every subcarrier in the discrete frequency domain. The orthogonality is not affected by time delays from transmitters. Thus, our proposed MIMO OFDM radar has the same range resolution as single transmitter radar and achieves full spatial diversity. Orthogonal designs are used to achieve this orthogonality across the transmitters, with which it is only needed to design OFDM pulses for the first transmitter. We also propose a joint pulse compression and pulse coherent integration for range reconstruction. In order to achieve the optimal signal-to-noise ratio (SNR) for the range reconstruction, we apply the paraunitary filterbank theory to design the OFDM pulses. We then propose a modified iterative clipping and filtering (MICF) algorithm for the designs of OFDM pulses jointly, when other important factors, such as peak-to-average power ratio (PAPR) in time domain, are also considered.With our proposed MIMO OFDM radar, there is no interference for the range reconstruction not only across the transmitters but also across the range cells in a swath called inter-range-cell interference (IRCI) free that is similar to our previously proposed CP-based OFDM radar for single transmitter. Simulations are presented to illustrate our proposed theory and show that the CP-based MIMO OFDM radar outperforms the existing frequency-band shared MIMO radar with polyphase codes and also frequency division MIMO radar.
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  • 41
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-29
    Description: The minimum-variance filter and smoother are generalized to include Poisson-distributed measurement noise components. It is shown that the resulting filtered and smoothed estimates are unbiased. The use of the filter and smoother within expectation-maximization algorithms are described for joint estimation of the signal and Poisson noise intensity. Conditions for the monotonicity and asymptotic convergence of the Poisson intensity iterates are also established. An image restoration example is presented that demonstrates improved estimation performance at low signal-to-noise ratios.
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  • 42
    Publication Date: 2015-09-29
    Description: This paper proposes a new radar/sonar processing architecture that enables a low-rate time-sampling rate while still producing a high-resolution range profile over a narrow range-window. This new architecture generalizes the conventional ???stretch processing??? architecture (which employs linear frequency modulated (LFM) waveforms that suffer from high range-sidelobes), to nonlinear frequency modulated (NLFM) waveforms, which can lower the range-sidelobes without tapering. Computational results demonstrate both the estimation efficacy and the time-sampling efficiency of the proposed scheme.
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  • 43
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-29
    Description: Free-floating manipulators are subject to dynamic singularities that complicate their Cartesian motions and restrict their workspace. In this work, the Cartesian trajectory planning of free-floating manipulators is studied. A methodology is developed in which, for given end-effector trajectories, appropriate initial system configurations are found that result in singularity avoidance during end-effector motion. The method applies to both planar and spatial systems, with and without initial angular momentum, and to any desired end-effector position and attitude trajectories.
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-29
    Description: This paper investigates the problem of fusion filtering for a class of networked multisensor fusion systems with multiple uncertainties, including sensor failures, stochastic parameter uncertainties, random observation delays, and packet dropouts. A novel model is proposed to describe the random observation delays and packet dropouts, and a robust optimal fusion filter for the addressed networked multisensor fusion systems is designed using the innovation analysis method. The dimension of the designed filter is the same as that of the original system, which helps to reduce computation cost compared with the augmentation method. Moreover, robust reduced-dimension observation-fusion Kalman filters are proposed to further reduce the computation burden. Note that the designed fusion filter gain matrices can be computed off-line, as they depend only on the upper bounds of random delays and on the occurrence probabilities of delays and sensor failures. Some sufficient conditions are presented for stability and optimality of the designed fusion filters, and a steady-state fusion filter is also given for the networked multisensor fusion systems. Simulations show the effectiveness of the proposed fusion filters.
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  • 45
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-10-27
    Description: Fabricated vessel-mimetic microtubes are essential for delivering sufficient nutrient to engineered composite tissues. In this paper, vascular-like microtubes are engineered by automated assembly of donut-shaped micromodules that embed fibroblast cells. A microrobotic system is set up with dual manipulators of 30-nm positioning resolution under an optical microscope. The system assembles the micromodules by repeated single-step pick-up motions. This process is specifically designed to avoid human interference and ensure high reproducibility for automation. We optimized the single-step motion by calibrating the key parameters (the micromodule dimensions) in a force analysis. The optimal motion achieved a 98% pick-up success rate. The automated repetitive single-step assembly is achieved by an algorithm that acquires the 3-D location and tracks the micromanipulator without being affected by low contrast. The accuracy of the acquired 3-D location was experimentally determined as approximately 1 pixel (2 μm under 4× magnification), and the tracking under different observation conditions is proved effective. Finally, we automatically assembled microtubes at 6 micromodules/min, sufficiently fast for fabricating macroscopic vessel-mimetic substitutes in biological applications.
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    Topics: Medicine , Technology
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  • 46
    Publication Date: 2015-10-27
    Description: Goal: This study tests and validates a new method to remove power line interference from monopolar EMGs detected by multichannel systems: the filtered virtual reference (FVR). FVR is an adaptation of the virtual reference (VR) method, which consists in referencing signals detected by each electrode in a grid to their spatial average. Signals may however be distorted with the VR approach, in particular when the skin region where the detection system is positioned does not cover the entire muscle. Methods: Simulated and experimental EMGs were used to compare the performance of FVR and VR in terms of interference reduction and distortion of monopolar signals referred to a remote reference. Results : Simulated data revealed the monopolar EMG signals processed with FVR were significantly less distorted than those filtered by VR. These results were similarly observed for experimental signals. Moreover, FVR method outperformed VR in removing power line interference when it was distributed unevenly across the signals of the grid. Conclusion: Key results demonstrated that FVR improves the VR method as it reduces interference while preserving the information content of monopolar signals. Significance: Although the actual distribution of motor unit action potential is represented in monopolar EMGs, collecting high quality monopolar signals is challenging. This study presents a possible solution to this issue; FVR provides undistorted monopolar signals with negligible interference and is insensitive to muscle architecture. It is therefore relevant for EMG applications benefiting from a clean monopolar detection (e.g., decomposition, control of prosthetic devices, motor unit number estimation).
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  • 47
    Publication Date: 2015-10-27
    Description: This study concentrates on finite-element-method (FEM)-based electroencephalography (EEG) forward simulation in which the electric potential evoked by neural activity in the brain is to be calculated at the surface of the head. The main advantage of the FEM is that it allows realistic modeling of tissue conductivity inhomogeneity. However, it is not straightforward to apply the classical model of a dipolar source with the FEM, due to its strong singularity and the resulting irregularity. The focus of this study is on comparing different methods to cope with this problem. In particular, we evaluate the accuracy of Whitney (Raviart–Thomas)-type dipole-like source currents compared to two reference dipole modeling methods: the St. Venant and partial integration approach. Common to all these methods is that they enable direct approximation of the potential field utilizing linear basis functions. In the present context, Whitney elements are particularly interesting, as they provide a simple means to model a divergence-conforming primary current vector field satisfying the square integrability condition. Our results show that a Whitney-type source model can provide simulation accuracy comparable to the present reference methods. It can lead to superior accuracy under optimized conditions with respect to both source location and orientation in a tetrahedral mesh. For random source orientations, the St. Venant approach turns out to be the method of choice over the interpolated version of the Whitney model. The overall moderate differences obtained suggest that practical aspects, such as the focality, should be prioritized when choosing a source model.
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  • 48
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-10-27
    Description: This paper presents a wearable vital signs monitor at the ear. The monitor measures the electrocardiogram (ECG), ballistocardiogram (BCG), and photoplethysmogram (PPG) to obtain pre-ejection period (PEP), stroke volume (SV), cardiac output (CO), and pulse transit time (PTT). The ear is demonstrated as a natural anchoring point for the integrated sensing of physiological signals. All three signals measured can be used to obtain heart rate (HR). Combining the ECG and BCG allows for the estimation of the PEP, while combining the BCG and PPG allows for the measurement of PTT. Additionally, the J-wave amplitude of the BCG is correlated with the SV and, when combined with HR, yields CO. Results from a clinical human study on 13 subjects demonstrate this proof-of-concept device.
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  • 49
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-06-13
    Description: Presents the back cover of this issue of the periodical.
    Print ISSN: 0885-8985
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  • 50
    Publication Date: 2015-06-13
    Description: Nonmilitary applications of unmanned air vehicles (UAVs), especially as rescue vehicles to obtain information have increased in recent years. Small UAVs (SUAV) were used in nonmilitary projects, where the focus was on autonomous vehicles; however, microaerial vehicles (MAVs), such as Samarai, make use of radio control, and they were not autonomous vehicles [1]. Autonomous UAVs need sophisticated guidance, control, and navigation systems with conventional aircraft flying processes. Most of current UAVs use ground-station commands for guidance purposes, although autonomous UAVs tend to reduce dependency on ground-station command via autonomous algorithms, such as intelligent methods. Therefore, ground-based air control may not suffice to cover every flying mission. Thus, self-contained, onboard guidance via intelligent methods, such as fuzzy logic, has been considered to achieve this goal. Lockheed Martin???s Intelligent Robotics Laboratory has spent the last 5 years developing an unmanned craft to replicate the air vehicle motion. The idea was based on the motion of maple seed, which whirls softly to the ground after dropping from maple tree. This motion, which is similar to a one-winged helicopter, inspired Lockheed Martin to design a new type of flying vehicles, beneficial in military and nonmilitary surveillance. Maple seeds disperse themselves by auto-rotating passively by using a single wing as they descend from trees, thereby ensuring they are widely scattered. Inspired by these flight concepts, Lockheed Martin Advanced Technology Laboratories developed the Samarai MAV, a 30-cm-radius maple seedlike aircraft that can take off and land vertically and fly laterally, like a helicopter, due to the intrinsic stability of the maple seeds??? nature [2] (Figure 1).
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-06-13
    Description: Presents the message from the Associate Editor-in-Chief.
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-05-02
    Description: Provides a listing of the editors, board members, and current staff for this issue of the publication.
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    Publication Date: 2015-05-02
    Description: Electron and light microscopy imaging can now deliver high-quality image stacks of neural structures. However, the amount of human annotation effort required to analyze them remains a major bottleneck. While machine learning algorithms can be used to help automate this process, they require training data, which is time-consuming to obtain manually, especially in image stacks. Furthermore, due to changing experimental conditions, successive stacks often exhibit differences that are severe enough to make it difficult to use a classifier trained for a specific one on another. This means that this tedious annotation process has to be repeated for each new stack. In this paper, we present a domain adaptation algorithm that addresses this issue by effectively leveraging labeled examples across different acquisitions and significantly reducing the annotation requirements. Our approach can handle complex, nonlinear image feature transformations and scales to large microscopy datasets that often involve high-dimensional feature spaces and large 3D data volumes. We evaluate our approach on four challenging electron and light microscopy applications that exhibit very different image modalities and where annotation is very costly. Across all applications we achieve a significant improvement over the state-of-the-art machine learning methods and demonstrate our ability to greatly reduce human annotation effort.
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    Publication Date: 2015-05-02
    Description: Efficient and accurate segmentation of cellular structures in microscopic data is an essential task in medical imaging. Many state-of-the-art approaches to image segmentation use structured models whose parameters must be carefully chosen for optimal performance. A popular choice is to learn them using a large-margin framework and more specifically structured support vector machines (SSVM). Although SSVMs are appealing, they suffer from certain limitations. First, they are restricted in practice to linear kernels because the more powerful nonlinear kernels cause the learning to become prohibitively expensive. Second, they require iteratively finding the most violated constraints, which is often intractable for the loopy graphical models used in image segmentation. This requires approximation that can lead to reduced quality of learning. In this paper, we propose three novel techniques to overcome these limitations. We first introduce a method to “kernelize” the features so that a linear SSVM framework can leverage the power of nonlinear kernels without incurring much additional computational cost. Moreover, we employ a working set of constraints to increase the reliability of approximate subgradient methods and introduce a new way to select a suitable step size at each iteration. We demonstrate the strength of our approach on both 2-D and 3-D electron microscopic (EM) image data and show consistent performance improvement over state-of-the-art approaches.
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    Publication Date: 2015-05-02
    Description: In this study, we proposed an efficient nonrigid magnetic resonance (MR) to transrectal ultrasound (TRUS) deformable registration method in order to improve the accuracy of targeting suspicious regions during a three dimensional (3-D) TRUS guided prostate biopsy. The proposed deformable registration approach employs the multi-channel modality independent neighborhood descriptor (MIND) as the local similarity feature across the two modalities of MR and TRUS, and a novel and efficient duality-based convex optimization-based algorithmic scheme was introduced to extract the deformations and align the two MIND descriptors. The registration accuracy was evaluated using 20 patient images by calculating the TRE using manually identified corresponding intrinsic fiducials in the whole gland and peripheral zone. Additional performance metrics [Dice similarity coefficient (DSC), mean absolute surface distance (MAD), and maximum absolute surface distance (MAXD)] were also calculated by comparing the MR and TRUS manually segmented prostate surfaces in the registered images. Experimental results showed that the proposed method yielded an overall median TRE of 1.76 mm. The results obtained in terms of DSC showed an average of $80.8pm7.8hbox{%}$ for the apex of the prostate, $92.0pm3.4hbox{%}$ for the mid-gland, $81.7pm6.4hbox{%}$ for the base and $85.7pm4.7hbox{%}$ for the whole gland. The surface distance calculations showed an overall average of $1.84pm0.52$ mm for MAD and $6.90pm2.07$ mm for MAXD.
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  • 56
    Publication Date: 2015-05-02
    Description: In this work we present a framework for reliably detecting significant differences in quantitative magnetic resonance imaging and evaluate it with diffusion tensor imaging (DTI) experiments. As part of this framework we propose a new spatially regularized maximum likelihood estimator that simultaneously estimates the quantitative parameters and the spatially-smoothly-varying noise level from the acquisitions. The noise level estimation method does not require repeated acquisitions. We show that the amount of regularization in this method can be set a priori to achieve a desired coefficient of variation of the estimated noise level. The noise level estimate allows the construction of a Cramér-Rao-lower-bound based test statistic that reliably assesses the significance of differences between voxels within a scan or across different scans. We show that the regularized noise level estimate improves upon existing methods and results in a substantially increased precision of the uncertainty estimates of the DTI parameters. It enables correct specification of the null distribution of the test statistic and with it the test statistic obtains the highest sensitivity and specificity. The source code of the estimation framework, test statistic and experiment scripts are made available to the community.
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    Publication Date: 2015-05-02
    Description: Magnetic particle imaging (MPI) shows promise for medical imaging, particularly in angiography of patients with chronic kidney disease. As the first biomedical imaging technique that truly depends on nanoscale materials properties, MPI requires highly optimized magnetic nanoparticle tracers to generate quality images. Until now, researchers have relied on tracers optimized for MRI ${rm T}2^ {ast} $ -weighted imaging that are sub-optimal for MPI. Here, we describe new tracers tailored to MPI's unique physics, synthesized using an organic-phase process and functionalized to ensure biocompatibility and adequate in vivo circulation time. Tailored tracers showed up to 3 $,times$ greater signal-to-noise ratio and better spatial resolution than existing commercial tracers in MPI images of phantoms.
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    Publication Date: 2015-05-02
    Description: Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.
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    Publication Date: 2015-05-02
    Description: Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.
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    Publication Date: 2015-05-02
    Description: These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal.
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    Publication Date: 2015-05-02
    Description: A promising, recently explored, alternative to ultra-high $b$ -value diffusion weighted imaging (UHB-DWI) is apparent ultra-high $b$ -value diffusion-weighted image reconstruction (AUHB-DWR), where a computational model is used to assist in the reconstruction of apparent DW images at ultra-high $b$ -values. Firstly, we present a novel approach to AUHB-DWR that aims to improve image quality. We formulate the reconstruction of an apparent DW image as a hidden conditional random field (HCRF) in which tissue model diffusion parameters act as hidden states in this random field. The second contribution of this paper is a new generation of fully connected conditional random fields, called the hidden stochastically fully connected conditional random fields (HSFCRF) that allows for efficient inference with significantly reduced computational complexity via stochastic clique structures. The proposed AUHB-DWR algorithms, HCRF and HSFCRF, are evaluated quantitatively in nine different patient cases using Fisher's criteria, probability of error, and coefficient of variation metrics to validate its effectiveness for the purpose of improving intensity delineation between expert identified suspected cancerous and healthy tissue within the prostate gland. The proposed methods are also examined using a prostate phantom, where the apparent ultra-high $b$ -value DW images reconstructed using the tested AUHB-DWR methods are compared with real captured UHB-DWI. The results illustrate that the proposed AUHB-DWR methods has improved reconstruction quality and improved intensity delineation compared with existing AUHB-DWR approaches.
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    Publication Date: 2015-05-02
    Description: A numerical method is shown for calculating the noise correlation coefficient in arrays of magnetic resonance imaging (MRI) coils loaded with capacitively-loaded ring metamaterial lenses, and in the presence of a conducting half-space resembling a sample. This numerical method is validated by comparison with experimental results obtained in two different experimental procedures for double check: noise resistance measurements with a network analyzer and noise correlation measurements in an MRI system. It is found that, for practical array configurations such as overlapping coils or capacitively-decoupled coils, the noise correlation coefficient turns negative for coils loaded with metamaterial lenses. In particular, the analysis is carried out with metamaterial structures known as magnetoinductive lenses, which have been demonstrated in previous works to improve the signal-to-noise ratio of MRI coils. Results are also shown to demonstrate that negative noise correlations have as an effect the improvement of the g-factor in coil arrays for parallel MRI.
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    Publication Date: 2015-05-02
    Description: Functional magnetic resonance imaging (fMRI) is an indirect measure of neural activity which is modeled as a convolution of the latent neuronal response and the hemodynamic response function (HRF). Since the sources of HRF variability can be nonneural in nature, the measured fMRI signal does not faithfully represent underlying neural activity. Therefore, it is advantageous to deconvolve the HRF from the fMRI signal. However, since both latent neural activity and the voxel-specific HRF is unknown, the deconvolution must be blind. Existing blind deconvolution approaches employ highly parameterized models, and it is unclear whether these models have an over fitting problem. In order to address these issues, we 1) present a nonparametric deconvolution method based on homomorphic filtering to obtain the latent neuronal response from the fMRI signal and, 2) compare our approach to the best performing existing parametric model based on the estimation of the biophysical hemodynamic model using the Cubature Kalman Filter/Smoother. We hypothesized that if the results from nonparametric deconvolution closely resembled that obtained from parametric deconvolution, then the problem of over fitting during estimation in highly parameterized deconvolution models of fMRI could possibly be over stated. Both simulations and experimental results demonstrate support for our hypothesis since the estimated latent neural response from both parametric and nonparametric methods were highly correlated in the visual cortex. Further, simulations showed that both methods were effective in recovering the simulated ground truth of the latent neural response.
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    Publication Date: 2015-05-02
    Description: Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.
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  • 66
    Publication Date: 2015-05-02
    Description: In this work, we demonstrated that an optimized detector angular configuration based on the anisotropic energy distribution of background scattered X-rays improves X-ray fluorescence computed tomography (XFCT) detection sensitivity. We built an XFCT imaging system composed of a bench-top fluoroscopy X-ray source, a CdTe X-ray detector, and a phantom motion stage. We imaged a 6.4-cm-diameter phantom containing different concentrations of gold solution and investigated the effect of detector angular configuration on XFCT image quality. Based on our previous theoretical study, three detector angles were considered. The X-ray fluorescence detector was first placed at 145 $^{circ}$ (approximating back-scatter) to minimize scatter X-rays. XFCT image quality was compared to images acquired with the detector at 60 $^{circ}$ (forward-scatter) and 90 $^{circ}$ (side-scatter). The datasets for the three different detector positions were also combined to approximate an isotropically arranged detector. The sensitivity was optimized with detector in the 145 $^{circ}$ back-scatter configuration counting the 78-keV gold ${rm K}beta 1$ X-rays. The improvement arose from the reduced energy of scattered X-ray at the 145 $^{circ}$ position and the large energy separation from gold ${rm K} beta 1$ X-rays. The lowest detected concentration in this configuration was 2.5 mgAu/mL (or 0.25% Au with SNR $ = 4.3$ ). This concentration could not be detected with the 60- formula formulatype="inline"〉 $^{circ}$ , 90 $^{circ}$ , or isotropic configurations (SNRs $ = 1.3$ , 0, 2.3, respectively). XFCT imaging dose of 14 mGy was in the range of typical clinical X-ray CT imaging doses. To our knowledge, the sensitivity achieved in this experiment is the highest in any XFCT experiment using an ordinary bench-top X-ray source in a phantom larger than a mouse ( ${〉} 3$ cm).
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    Publication Date: 2015-05-02
    Description: We have developed a method for the simultaneous estimation of local diffusion and the global fiber tracts based upon the information entropy flow that computes the maximum entropy trajectories between locations and depends upon the global structure of the multi-dimensional and multi-modal diffusion field. Computation of the entropy spectrum pathways requires only solving a simple eigenvector problem for the probability distribution for which efficient numerical routines exist, and a straight forward integration of the probability conservation through ray tracing of the convective modes guided by a global structure of the entropy spectrum coupled with a small scale local diffusion. The intervoxel diffusion is sampled by multi b-shell multi q-angle diffusion weighted imaging data expanded in spherical waves. This novel approach to fiber tracking incorporates global information about multiple fiber crossings in every individual voxel and ranks it in the most scientifically rigorous way. This method has potential significance for a wide range of applications, including studies of brain connectivity.
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    Publication Date: 2015-05-13
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    Publication Date: 2015-05-13
    Description: The rapid growth in the use of software in airborne systems and equipment in the early 1980s resulted in a need for industry-accepted guidance for satisfying airworthiness requirements [1]. To assure the reliability of the software and to ultimately ensure the safety of passengers, the U.S. Federal Aviation Administration (FAA) has imposed software certifcation suited to the development of safety-critical systems. The FAA has accepted guidelines developed by the Radio Technical Commission for Aeronautics (RTCA) that respond to the necessity of reliability and safety, which are vital in this feld: DO-178B/EUROCAE ED-12B (DO-178B), titled Software Considerations in Airborne Systems and Equipment Certifcation [1]. DO-178B prescribes design assurance guidance for airborne software. The aim of DO-178B is to assure that software developed for avionics systems is reliable and safe to use in fight [2].
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    Publication Date: 2015-05-02
    Description: The variation between images obtained with different scanners or different imaging protocols presents a major challenge in automatic segmentation of biomedical images. This variation especially hampers the application of otherwise successful supervised-learning techniques which, in order to perform well, often require a large amount of labeled training data that is exactly representative of the target data. We therefore propose to use transfer learning for image segmentation. Transfer-learning techniques can cope with differences in distributions between training and target data, and therefore may improve performance over supervised learning for segmentation across scanners and scan protocols. We present four transfer classifiers that can train a classification scheme with only a small amount of representative training data, in addition to a larger amount of other training data with slightly different characteristics. The performance of the four transfer classifiers was compared to that of standard supervised classification on two magnetic resonance imaging brain-segmentation tasks with multi-site data: white matter, gray matter, and cerebrospinal fluid segmentation; and white-matter-/MS-lesion segmentation. The experiments showed that when there is only a small amount of representative training data available, transfer learning can greatly outperform common supervised-learning approaches, minimizing classification errors by up to 60%.
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    Publication Date: 2015-05-02
    Description: We present a graph-based framework for airway tree reconstruction from computerized tomography (CT) scans and evaluate the performance of different feature categories and their combinations on five lung cohorts. The approach consists of two main processing steps. First, potential airway branch and connection candidates are identified and represented by a graph structure with weighted nodes and edges, respectively. Second, an optimization algorithm is utilized for generating an airway detection result by selecting a subset of airway branches and connections based on graph weights derived from image features. The performance of the algorithm with different feature categories and their combinations was assessed on a set of 50 lung CT scans from five different cohorts, including normal and diseased lungs. Results show trade-offs between feature categories/combinations in terms of correctly (true positive) and incorrectly (false positive) identified airways. Also, the performance of features in dependence of lung cohort was analyzed. Across all cohorts, a good trade-off with high true positive rate (TPR) and low false positive rate (FPR) was achieved by a combination of gray-value, local shape, and structural features. This combination enabled extracting 91.80% of reference airways (TPR) in combination with a low FPR of 1.00%. In addition, this variant was evaluated on the public EXACT'09 test set, and a comparison with other airway detection approaches is provided. One of the main advantages of the presented method is that it is robust against local disturbances/artifacts or other ambiguities that are frequently occurring in lung CT scans.
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    Publication Date: 2015-05-02
    Description: In this paper, we discuss about applications of different methods for decomposing a signal over elementary waveforms chosen in a family called a dictionary (atomic representations) in optical coherence tomography (OCT). If the representation is learned from the data, a nonparametric dictionary is defined with three fundamental properties of being data-driven, applicability on 3D, and working in multi-scale, which make it appropriate for processing of OCT images. We discuss about application of such representations including complex wavelet based K-SVD, and diffusion wavelets on OCT data. We introduce complex wavelet based K-SVD to take advantage of adaptability in dictionary learning methods to improve the performance of simple dual tree complex wavelets in speckle reduction of OCT datasets in 2D and 3D. The algorithm is evaluated on 144 randomly selected slices from twelve 3D OCTs taken by Topcon 3D OCT-1000 and Cirrus Zeiss Meditec. Improvement of contrast to noise ratio (CNR) (from 0.9 to 11.91 and from 3.09 to 88.9, respectively) is achieved. Furthermore, two approaches are proposed for image segmentation using diffusion. The first method is designing a competition between extended basis functions at each level and the second approach is defining a new distance for each level and clustering based on such distances. A combined algorithm, based on these two methods is then proposed for segmentation of retinal OCTs, which is able to localize 12 boundaries with unsigned border positioning error of $9.22 pm 3.05 mu {hbox {m}}$ , on a test set of 20 slices selected from 13 3D OCTs.
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    Publication Date: 2015-05-02
    Description: The spectral graph wavelet transform (SGWT) has recently been developed to compute wavelet transforms of functions defined on non-Euclidean spaces such as graphs. By capitalizing on the established framework of the SGWT, we adopt a fast and efficient computation of a discretized Laplace-Beltrami (LB) operator that allows its extension from arbitrary graphs to differentiable and closed 2-D manifolds (smooth surfaces embedded in the 3-D Euclidean space). This particular class of manifolds are widely used in bioimaging to characterize the morphology of cells, tissues, and organs. They are often discretized into triangular meshes, providing additional geometric information apart from simple nodes and weighted connections in graphs. In comparison with the SGWT, the wavelet bases constructed with the LB operator are spatially localized with a more uniform “spread” with respect to underlying curvature of the surface. In our experiments, we first use synthetic data to show that traditional applications of wavelets in smoothing and edge detectio can be done using the wavelet bases constructed with the LB operator. Second, we show that multi-resolutional capabilities of the proposed framework are applicable in the classification of Alzheimer's patients with normal subjects using hippocampal shapes. Wavelet transforms of the hippocampal shape deformations at finer resolutions registered higher sensitivity (96%) and specificity (90%) than the classification results obtained from the direct usage of hippocampal shape deformations. In addition, the Laplace-Beltrami method requires consistently a smaller number of principal components (to retain a fixed variance) at higher resolution as compared to the binary and weighted graph Laplacians, demonstrating the potential of the wavelet bases in adapting to the geometry of the underlying manifold.
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    Publication Date: 2015-05-02
    Description: Linear predictive models are applied to functional MRI (fMRI) data to estimate boundaries that predict experimental task states for scans. These boundaries are visualized as statistical parametric maps (SPMs) and range from low to high spatial reproducibility across subjects (e.g., Strother , 2004; LaConte , 2003). Such inter-subject pattern reproducibility is an essential characteristic of interpretable SPMs that generalize across subjects. Therefore, we introduce a flexible hybrid model that optimizes reproducibility by simultaneously enhancing the prediction power and reproducibility. This hybrid model is formed by a weighted summation of the optimization functions of a linear discriminate analysis (LDA) model and a generalized canonical correlation (gCCA) model (Afshin-Pour , 2012). LDA preserves the model’s ability to discriminate the fMRI scans of multiple brain states while gCCA finds a linear combination for each subject’s scans such that the estimated boundary map is reproducible. The hybrid model is implemented in a split-half resampling framework (Strother , 2010) which provides reproducibility (r) and prediction (p) quality metrics. Then the model was compared with LDA, and Gaussian Naive Bayes (GNB). For simulated fMRI data, the hybrid model outperforms the other two techniques in terms of receiver operating characteristic (ROC) curves, particularly for detecting less predictable but spatially reproducible networks. These techniques were applied to real fMRI data to estimate the maps for two task contrasts. Our results indicate that compared to LDA and GNB, the hybrid model can provide maps with large increases in reproducibility for small reductions in prediction, which are jointly closer to the ideal performance point of (p=1, r=1).
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    Publication Date: 2015-05-13
    Description: Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.
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    Publication Date: 2015-05-13
    Description: Over-the-horizon radar (OTHR) systems, or skywave propagation systems, use the high frequency (HF) band (3 to 30 MHz) to ???bounce??? or ???refract??? a signal off the ionosphere to detect tracks of interest (TOIs) between 500 and 2000 nautical miles from the transmitter/receiver pair. This range is ???an order of magnitude greater than is possible with conventional line-of-sight radars??? [1]. Since their initial employment, OTHR systems have significantly improved in abilities to detect and track TOIs such as aircraft, ballistic and cruise missiles, and ships [2].
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  • 80
    Publication Date: 2015-05-13
    Description: As discussed in Partitioning in Avionics Architectures: Requirements, Mechanisms, and Assurance by Rush by, J. [1], integrated modular avionics (IMA) is an embedded version of a centralized time-shared ???mainframe,??? which provides the hosted applications with the common computing resources and the airborne data network. The features of various IMA systems can be summarized in the following points: 1. high performance shared common computing resources 2. high speed communication network 3. open architecture for both software and hardware.
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-05-13
    Print ISSN: 0885-8985
    Electronic ISSN: 1557-959X
    Topics: Electrical Engineering, Measurement and Control Technology , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
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  • 84
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-05-13
    Description: The ionosphere consists of plasma trapped by Earth's magnetic feld. The plasma consists of heterogeneous structures, which are susceptible to perturbation caused by solar winds. Radio waves passing through the ionosphere experience scintillation due to irregularities in the plasma. This is a problem for satellite-based systems used for communication and navigation because the signals received by ground-based terminals experience reduced signal quality. This effect is greater around the Equator and near the polar cusps. During periods with high solar activity it can cause satellite communication outage. To understand radio wave disturbance in the ionosphere and develop more accurate space weather models, one must measure and quantify the plasma structures and perturbation by using in-situ instruments.
    Print ISSN: 0885-8985
    Electronic ISSN: 1557-959X
    Topics: Electrical Engineering, Measurement and Control Technology , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
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  • 85
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-05-13
    Print ISSN: 0885-8985
    Electronic ISSN: 1557-959X
    Topics: Electrical Engineering, Measurement and Control Technology , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
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  • 86
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    Unknown
    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-05-13
    Print ISSN: 0885-8985
    Electronic ISSN: 1557-959X
    Topics: Electrical Engineering, Measurement and Control Technology , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
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  • 87
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-05-13
    Description: Presents a call for nominations for the IEEE AESS Judith A. Resnik space award.
    Print ISSN: 0885-8985
    Electronic ISSN: 1557-959X
    Topics: Electrical Engineering, Measurement and Control Technology , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
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  • 88
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-01-24
    Description: This paper investigates a vertically differentiated product (VDP) line design problem in both a centralized and decentralized supply chain setting with one manufacturer and one retailer. We study how the product variety decision making in the decentralized setting affects the number of VDPs developed and produced by the manufacturer, as well as the number of products that the retailer will accept from the manufacturer. We show the value of flexibility, timeliness of information, and product development lead time reduction in three market scenarios where the retailer will elect to carry a product only if the product meets a specified target profit. Our results reveal that if the manufacturer faces a long design lead time and designs only one product line, he may be better off not lowering wholesale prices to accommodate the retailer's profit restriction. If design lead time is short, negotiation between manufacturer and retailer along with a side payment could possibly lead to a profit improving solution for both parties. Optimization models and computational results are presented.
    Print ISSN: 0018-9391
    Electronic ISSN: 1558-0040
    Topics: Technology
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  • 89
    Publication Date: 2015-01-24
    Description: This study empirically investigates the merger and acquisition (M&A) strategies of focal firms by considering their market and technology position at the industry level. The results obtained using patents, firm M&A agreements, and the financial data of U.S. technology firms from 1997 through 2008 demonstrate how industry leaders, challengers, and niche players differ in their M&A strategic logic. Three industry environmental factors and two technology positioning factors exhibit different effects on firms’ M&A strategies for varied market positions. The overall patterns reveal that niche players are more aggressive in leveraging their technology positions to adopt M&As for the purpose of acquiring access to external knowledge resources, while leaders tend to leverage their market positions and use M&As to further strengthen their market power. Challengers are more likely to engage in M&As when locating in unfavorable environmental markets, but they are less likely to engage in M&As when locating in technologically crowded areas.
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  • 90
    Publication Date: 2015-01-24
    Description: Due to the characteristics of cross-functional teams, trust is crucial for cross-functional teams to enhance performance. However, as a significant factor, trust had been neglected in previous team performance models. In this paper, we investigate whether trust can be used as a predictor of cross-functional team performance by proposing a prediction model. The inputs of the model are both team structural and contextual (SC) factors, and project process (PP) factors, which are two major sources that form team trust. The output of the model is different levels of team performance, which consists of internal performance and external performance. The support vector machine techniques are used to establish the model. Results show that prediction accuracy is high (84.95%) when using both SC and PP factors as inputs, while PP factors have better prediction accuracy than SC factors on team performance and internal performance. It is suggested that team trust can be used as a good predictor of cross-functional team performance. In practice, this paper presents a better understanding of the relationship between trust and performance in cross-functional teams, and thus, enhances practitioners’ managerial skills. It also gives reference for managers to dynamically control and predict team performance during project period.
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  • 91
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-01-24
    Description: Virtual communities have become ubiquitous and vital in nearly all professions. These communities typically involve voluntary participation, and given that these communities are not organization specific, community members’ motivations for participation vary. In this study, we investigate the motivations of the members of a professional virtual community to engage in knowledge exchange. We synthesize social exchange theory and the theory of reasoned action to identify critical determinants of attitudes toward knowledge exchange in virtual communities, namely, trust among participants, anticipated reciprocal relationships, and the relevance of the community to participants’ jobs. Additionally, we posit that attitudes will influence the intention to use the virtual community and that this relationship will be moderated by the perceived quality of the information exchanged within the community. We test our research model using data compiled from a community of research scientists in South Korea. Our findings indicate that trust among participants has a positive influence on attitudes toward both sharing and acquiring knowledge. The anticipation of a reciprocal relationship has a positive effect on attitudes toward knowledge acquisition, and job relevance has a positive effect on attitudes toward knowledge sharing. Furthermore, attitudes toward knowledge acquisition affect attitudes toward knowledge sharing, and attitudes toward knowledge sharing positively influence intentions to use a virtual community. We also find that perceived information quality negatively moderates the relationship between attitudes toward knowledge sharing and user intentions to use a virtual community. We interpret and discuss these findings, and their implications for research and practice.
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  • 92
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    Unknown
    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-01-24
    Print ISSN: 0018-9391
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  • 93
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-01-24
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  • 94
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    Unknown
    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-01-24
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  • 95
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-01-24
    Print ISSN: 0018-9391
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  • 96
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-04-22
    Description: Provides a listing of the editors, board members, and current staff for this issue of the publication.
    Print ISSN: 0018-9294
    Electronic ISSN: 1558-2531
    Topics: Medicine , Technology
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  • 97
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-04-22
    Description: In some biomedical applications such as wireless capsule endoscopy, the localization of an in-body radio-frequency (RF) source is important for the positioning of any abnormality inside the gastrointestinal tract. With knowledge of the location, therapeutic operations can be performed precisely at the position of the abnormality. Electrical properties (relative permittivity and conductivity) of the tissues and their distribution are utilized to estimate the position. This paper presents a method for the localization of an in-body RF source based on microwave imaging. The electrical properties of the tissues and their distribution at 403.5 MHz are found from microwave imaging and the position of an RF source is then estimated based on the image. The method is applied on synthetic noisy data, obtained after the addition of white Gaussian noise to simulated data of a simple circular phantom, and a realistic phantom in a 2-D case. The root-mean-square of the error distance between the actual and the estimated position is found to be within 10 and 4 mm for the circular and the realistic phantom, respectively, showing the capability of the proposed algorithm to work with a good accuracy even in the presence of noise for the localization of the in-body RF source.
    Print ISSN: 0018-9294
    Electronic ISSN: 1558-2531
    Topics: Medicine , Technology
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  • 98
    Publication Date: 2015-04-22
    Description: Recent advances in high-density surface electromyogram (EMG) decomposition have made it a feasible task to discriminate single motor unit activity from surface EMG interference patterns, thus providing a noninvasive approach for examination of motor unit control properties. In the current study, we applied high-density surface EMG recording and decomposition techniques to assess motor unit firing behavior alterations poststroke. Surface EMG signals were collected using a 64-channel 2-D electrode array from the paretic and contralateral first dorsal interosseous (FDI) muscles of nine hemiparetic stroke subjects at different isometric discrete contraction levels between 2 to 10 N with a 2 N increment step. Motor unit firing rates were extracted through decomposition of the high-density surface EMG signals and compared between paretic and contralateral muscles. Across the nine tested subjects, paretic FDI muscles showed decreased motor unit firing rates compared with contralateral muscles at different contraction levels. Regression analysis indicated a linear relation between the mean motor unit firing rate and the muscle contraction level for both paretic and contralateral muscles (p 〈 0.001), with the former demonstrating a lower increment rate (0.32 pulses per second (pps)/N) compared with the latter (0.67 pps/N). The coefficient of variation (averaged over the contraction levels) of the motor unit firing rates for the paretic muscles (0.21 ± 0.012) was significantly higher than for the contralateral muscles (0.17 ± 0.014) (p 〈 0.05). This study provides direct evidence of motor unit firing behavior alterations poststroke using surface EMG, which can be an important factor contributing to hemiparetic muscle weakness.
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  • 99
    Publication Date: 2015-04-22
    Description: A new adaptive beamforming algorithm for imaging via small-aperture 1-D ultrasonic-phased arrays through composite layered structures is reported. Such structures cause acoustic phase aberration and wave refraction at undulating interfaces and can lead to significant distortion of an ultrasonic field pattern produced by conventional beamforming techniques. This distortion takes the form of defocusing the ultrasonic field transmitted through the barrier and causes loss of resolution and overall degradation of image quality. To compensate for the phase aberration and the refractional effects, we developed and examined an adaptive beamforming algorithm for small-aperture linear-phased arrays. After accurately assessing the barrier's local geometry and sound speed, the method calculates a new timing scheme to refocus the distorted beam at its original location. As a tentative application, implementation of this method for trans-skull imaging of certain types of head injuries through human skull is discussed. Simulation and laboratory results of applying the method on skull-mimicking phantoms are presented. Correction of up to 2.5 cm focal point displacement at up to 10 cm depth under our skull phantom is demonstrated. Quantitative assessment of the method in a variety of temporal focusing scenarios is also reported. Overall temporal deviation on the order of a few nanoseconds was observed between the simulated and experimental results. The single-point adaptive focusing results demonstrate strong potential of our approach for diagnostic imaging through intact human skull. The algorithms were implemented on an ultrasound advanced open-platform controlling 64 active elements on a 128-element phased array.
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    Topics: Medicine , Technology
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  • 100
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-04-22
    Description: RNA secondary structures are vital in determining the 3-D structures of noncoding RNA molecules, which in turn affect their functions. Computational RNA secondary structure alignment and analysis are biologically significant, because they help identify numerous functionally important motifs. Unfortunately, many analysis methods suffer from computational intractability in the presence of pseudoknots. The conversion of knotted to knot-free secondary structures is an essential preprocessing step, and is regarded as pseudoknot removal. Although exact methods have been proposed for this task, their computational complexities are undetermined, and so their efficiencies in processing complex pseudoknots are currently unknown. We transformed the pseudoknot removal problem into a circle graph maximum weight independent set (MWIS) problem, in which each MWIS represents a unique optimal deknotted structure. An existing circle graph MWIS algorithm was extended to report either single or all solutions. Its time complexity depends on the number of MWISs, and is guaranteed to report one solution in polynomial time. Experimental results suggest that our extended algorithm is much more efficient than the state-of-the-art tool. We also devised a novel concept called the structural scoring function, and investigated its effectiveness in more accurate solution candidate selection for a certain criteria.
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    Topics: Medicine , Technology
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