In this work we present a new fabrication technique to print thin dielectric elastomer actuators (DEAs), reducing the driving voltage below 300 V while keeping good actuation performance. With operation voltages in th...
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ISBN:
(纸本)9781510600393
In this work we present a new fabrication technique to print thin dielectric elastomer actuators (DEAs), reducing the driving voltage below 300 V while keeping good actuation performance. With operation voltages in the kV-range, standard DEAs are limited in terms of potential applications. Using thinner membranes is one of the few existing methods to achieve lower operation voltages. Typical DEAs have membranes in the 20-100 mu m range, values below which membrane fabrication becomes challenging and the membrane quality and uniformity degrade. Using pad printing we produced thin silicone elastomer membranes, on which we pad-printed compliant electrodes. We then fabricated DEAs by assembling two membranes back to back. We obtain an actuation strain of 7.5% at only 245 V on a 3 mu m thick DEA. In order to investigate the stiffening impact of the electrodes we developed a simple DEA model that includes their mechanical properties. We also developed a strain-mapping algorithm based on optical correlation. The simulation results and the strain-mapping measurements confirm that the stiffening impact of the electrodes increases for thinner membranes. Electrodes are an important element that cannot be neglected in the design and optimization of ultra-thin DEAs.
We present a new algorithm that allows for raw data-based automated cardiac and respiratory intrinsic gating in cone-beam CT scans. It can be summarized in three steps: First, a median filter is applied to an initiall...
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ISBN:
(纸本)9781510600188
We present a new algorithm that allows for raw data-based automated cardiac and respiratory intrinsic gating in cone-beam CT scans. It can be summarized in three steps: First, a median filter is applied to an initially reconstructed volume. The forward projection of this volume contains less motion information and is subtracted from the original projections. This results in new raw data that, contain only moving and not static anatomy like bones, that would otherwise impede the cardiac or respiratory signal acquisition. All further steps are applied to these modified raw data. Second, the raw data are cropped to a region of interest (ROI). The ROI in the raw data is determined by the forward projection of a binary volume of interest (VOI) that includes the diaphragm for respiratory gating and most of the edge of the heart for cardiac gating. Third, the mean gray value in this ROI is calculated for every projection and the respiratory/cardiac signal is acquired using a bandpass filter. Steps two and three are carried out simultaneously for 64 or 1440 overlapping VOI inside the body for the respiratory or cardiac signal respectively. The signals acquired from each ROI are compared and the most consistent one is chosen as the desired cardiac or respiratory motion signal. Consistency is assessed by the standard deviation of the time between two maxima. The robustness and efficiency of the method is evaluated using simulated and measured patient data by computing the standard deviation of the mean signal difference between the ground truth and the intrinsic signal.
This article is about one of the alternative forms of energy - the algorithm for the development of a sea wave energy converter, which is based on reflection, refraction, diffraction and interference analysis between ...
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ISBN:
(纸本)9781509037315
This article is about one of the alternative forms of energy - the algorithm for the development of a sea wave energy converter, which is based on reflection, refraction, diffraction and interference analysis between waves and their energy transformers. This article provides information to the placement of a wave energy converter receiver, specially calculated parallel to the surface, thereby allowing obtaining wave energy step by step. It provides an insight into wave power plant optimization principles.
Multispectral and hyperspectral imaging can facilitate vehicle tracking across a series of images by gathering spectral information that distinguishes the vehicle of interest from confusers. Developing effective algor...
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ISBN:
(数字)9781510603448
ISBN:
(纸本)9781510603431;9781510603448
Multispectral and hyperspectral imaging can facilitate vehicle tracking across a series of images by gathering spectral information that distinguishes the vehicle of interest from confusers. Developing effective algorithms for utilizing this information requires an understanding of the sources and nature of both the common and unique components in vehicle spectra, as well as the variations associated with lighting, view angle, and part of the vehicle being observed. In this study, focusing on the VNIR-SWIR spectral region, we analyze hyperspectral data from a recent field experiment at the Rochester Institute of Technology. We describe the spectra of painted vehicle surfaces in general terms, and demonstrate effective classification of automobiles based on spectra from upward facing surfaces (the roof, hood or trunk) using a method that combines the Support Vector Machine with data pre-conditioning.
Understanding the mechanisms behind the proliferation of Mesenchymal Stem cells (MSCs) can offer a greater insight into the behaviour of these cells throughout their life cycles. Traditional methods of determining the...
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ISBN:
(纸本)9781628419450
Understanding the mechanisms behind the proliferation of Mesenchymal Stem cells (MSCs) can offer a greater insight into the behaviour of these cells throughout their life cycles. Traditional methods of determining the rate of MSC differentiation rely on population based studies over an extended time period. However, such methods can be inadequate as they are unable to track cells as they interact;for example, in autologous cell therapies for osteoarthritis, the development of biological assays that could predict in vivo functional activity and biological action are particularly challenging. Here further research is required to determine non-histochemical biomarkers which provide correlations between cell survival and predictive functional outcome. This paper proposes using a (previously developed) advanced texture-based analysis algorithm to facilitate in vitro cells tracking using time lapsed microscopy. The technique was adopted to monitor stem cells in the context of unlabelled, phase contrast imaging, with the goal of examining the cell to cell interactions in both monoculture and co-culture systems. The results obtained are analysed using established exploratory procedures developed for time series data and compared with the typical fluorescent-based approach of cell labelling. A review of the progress and the lessons learned are also presented.
The overall goal of this work is to develop a rapid, accurate and fully automated software tool to estimate patient-specific organ doses from computed tomography (CT) scans using a deterministic Boltzmann Transport Eq...
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ISBN:
(纸本)9781510600188
The overall goal of this work is to develop a rapid, accurate and fully automated software tool to estimate patient-specific organ doses from computed tomography (CT) scans using a deterministic Boltzmann Transport Equation solver and automated CT segmentation algorithms. This work quantified the accuracy of organ dose estimates obtained by an automated segmentation algorithm. The investigated algorithm uses a combination of feature-based and atlas-based methods. A multi atlas approach was also investigated. We hypothesize that the autosegmentation algorithm is sufficiently accurate to provide organ dose estimates since random errors at the organ boundaries will average out when computing the total organ dose. To test this hypothesis, twenty head-neck CT scans were expertly segmented into nine regions. A leave-one-out validation study was performed, where every case was automatically segmented with each of the remaining cases used as the expert atlas, resulting in nineteen automated segmentations for each of the twenty datasets. The segmented regions were applied to gold-standard Monte Carlo dose maps to estimate mean and peak organ doses. The results demonstrated that the fully automated segmentation algorithm estimated the mean organ dose to within 10% of the expert segmentation for regions other than the spinal canal, with median error for each organ region below 2%. In the spinal canal region, the median error was 7% across all data sets and atlases, with a maximum error of 20%. The error in peak organ dose was below 10% for all regions, with a median error below 4% for all organ regions. The multiple-case atlas reduced the variation in the dose estimates and additional improvements may be possible with more robust multi-atlas approaches. Overall, the results support potential feasibility of an automated segmentation algorithm to provide accurate organ dose estimates.
While object detection is a relatively well-developed field with respect to visible light photographs, there are significantly fewer algorithms designed to work with other imaging modalities. X-ray radiographs have ma...
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ISBN:
(数字)9781510603301
ISBN:
(纸本)9781510603295;9781510603301
While object detection is a relatively well-developed field with respect to visible light photographs, there are significantly fewer algorithms designed to work with other imaging modalities. X-ray radiographs have many unique characteristics that introduce additional challenges that can cause common image processing and object detection algorithms to begin to fail. Examples of these problematic attributes include the fact that radiographs are only represented in gray scale with similar textures and that transmission overlap occurs when multiple objects are overlaid on top of each other. In this paper we not only analyze the effectiveness of common object detection techniques as applied to our specific database, but also outline how we combined various techniques to improve overall performance. While significant strides have been made towards developing a robust object detection algorithm for use with the given database, it is still a work in progress. Further research will be needed in order to deal with the specific obstacles posed by radiographs and X-ray imaging systems. Success in this project would have disruptive repercussions in fields ranging from medical imaging to manufacturing quality assurance and national security.
Hyperspectral Imager Suite (HISUI)[1] is a Japanese future spaceborne hyperspectral instrument being developed by Ministry of Economy, Trade, and Industry (METI) and will be delivered to ISS in 2018. In HISUI project,...
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ISBN:
(数字)9781510604056
ISBN:
(纸本)9781510604049;9781510604056
Hyperspectral Imager Suite (HISUI)[1] is a Japanese future spaceborne hyperspectral instrument being developed by Ministry of Economy, Trade, and Industry (METI) and will be delivered to ISS in 2018. In HISUI project, observation strategy is important especially for hyperspectral sensor, and relationship between the limitations of sensor operation and the planned observation scenarios have to be studied. We have developed concept of multiple algorithms approach. The concept is to use two (or more) algorithm models (Long Strip Model and Score Downfall Model) for selecting observing scenes from complex data acquisition requests with satisfactory of sensor constrains. We have tested the algorithm, and found that the performance of two models depends on remaining data acquisition requests, i.e. distribution score along with orbits. We conclude that the multiple algorithms approach will be make better collection plans for HISUI comparing with single fixed approach.
The Durham AO Real-time Controller has been used on-sky with the CANARY AO demonstrator instrument since 2010, and is also used to provide control for several AO test-benches, including DRAGON. Over this period, many ...
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ISBN:
(纸本)9781510601987
The Durham AO Real-time Controller has been used on-sky with the CANARY AO demonstrator instrument since 2010, and is also used to provide control for several AO test-benches, including DRAGON. Over this period, many new real-time algorithms have been developed, implemented and demonstrated, leading to performance improvements for CANARY. Additionally, the computational performance of this real-time system has continued to improve. Here, we provide details about recent updates and changes made to DARC, and the relevance of these updates, including new algorithms, to forthcoming AO systems. We present the computational performance of DARC when used on different hardware platforms, including hardware accelerators, and determine the relevance and potential for ELT scale systems. Recent updates to DARC have included algorithms to handle elongated laser guide star images, including correlation wavefront sensing, with options to automatically update references during AO loop operation. Additionally, sub-aperture masking options have been developed to increase signal to noise ratio when operating with non-symmetrical wavefront sensor images. The development of end-user tools has progressed with new options for configuration and control of the system. New wavefront sensor camera models and DM models have been integrated with the system, increasing the number of possible hardware configurations available, and a fully open-source AO system is now a reality, including drivers necessary for commercial cameras and DMs. The computational performance of DARC makes it suitable for ELT scale systems when implemented on suitable hardware. We present tests made on different hardware platforms, along with the strategies taken to optimise DARC for these systems.
An intelligent video surveillance system is able to detect and identify abnormal and alarming situations by analyzing object movement. The Smart Sensing Surveillance Video ((SV)-V-3) System is proposed to minimize vid...
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ISBN:
(纸本)9781510601123
An intelligent video surveillance system is able to detect and identify abnormal and alarming situations by analyzing object movement. The Smart Sensing Surveillance Video ((SV)-V-3) System is proposed to minimize video processing and transmission, thus allowing a fixed number of cameras to be connected on the system, and making it suitable for its applications in remote battlefield, tactical, and civilian applications including border surveillance, special force operations, airfield protection, perimeter and building protection, and etc. The (SV)-V-3 System would be more effective if equipped with visual understanding capabilities to detect, analyze, and recognize objects, track motions, and predict intentions. In addition, alarm detection is performed on the basis of parameters of the moving objects and their trajectories, and is performed using semantic reasoning and ontologies. The (SV)-V-3 System capabilities and technologies have great potential for both military and civilian applications, enabling highly effective security support tools for improving surveillance activities in densely crowded environments. It would be directly applicable to solutions for emergency response personnel, law enforcement, and other homeland security missions, as well as in applications requiring the interoperation of sensor networks with handheld or body-worn interface devices.
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