To improve the accuracy and interactivity of soft tissue delormatlon simulation, a new plate spring model based on physics is proposed. The model is parameterized and thus can be adapted to simulate different organs. ...
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To improve the accuracy and interactivity of soft tissue delormatlon simulation, a new plate spring model based on physics is proposed. The model is parameterized and thus can be adapted to simulate different organs. Different soft tissues are modeled by changing the width, number of pieces, thickness, and length of a single plate spring. In this paper, the structural design, calcula- tion of soft tissue deformation and real-time feedback operations of our system are also introduced. To evaluate the feasibility of the system and validate the model, an experimental system of haptic in- teraction, in which users can use virtual hands to pull virtual brain tissues, is built using PHANTOM OMNI devices. Experimental results show that the proposed system is stable, accurate and promising for modeling instantaneous soft tissue deformation.
WHOIS service allows people to ask the current registrant some Internet resources. WHOIS service has become an indispensable information service in the DNS. Unfortunately, WHOIS information is often available by the m...
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A conditional privacy-protection remote user authentication scheme based on a certificateless group signature was proposed, which can accomplish the anonymous mutual authentication between the user and the remote doct...
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Vector orthogonal frequency division multiplexing (V-OFDM) for single transmit antenna systems is a generalization of OFDM where single-carrier frequency domain equalization (SC-FDE) and OFDM are just two special case...
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Multi-threshold segmentation is a basic and widely used technique in image segmentation. The key step of accomplishing this task is to find the optimal multi-threshold value, which in essence can be reduced to multi-o...
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The OraCDP disaster recovery system uses CDP disaster recovery technology based on the combination of block level, combining with the communication coupling between the underlying I/O and Oracle database. The experime...
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There have two effective ways to improve the overall efficiency of the object-based distributed storage system, one is network caching technology and the other is metadata server cluster load balancing strategy. Under...
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Cluster analysis is important in scientific and industrial fields. In this study, we proposed a novel chaotic biogeography-based optimization(CBBO) method, and applied it in centroid-based clustering methods. The resu...
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Cluster analysis is important in scientific and industrial fields. In this study, we proposed a novel chaotic biogeography-based optimization(CBBO) method, and applied it in centroid-based clustering methods. The results over three types of simulation data showed that this proposed CBBO method gave better performance than chaotic particle swarm optimization, genetic algorithm, firefly algorithm, and quantum-behaved particle swarm optimization. In all, our CBBO method is effective in centroid-based clustering.
Protein residue-residue contacts dictate the topology of protein structure and play an important role in structural biology, especially in de novo protein structure prediction. Accurate prediction of residue contacts ...
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ISBN:
(纸本)9781509016129
Protein residue-residue contacts dictate the topology of protein structure and play an important role in structural biology, especially in de novo protein structure prediction. Accurate prediction of residue contacts could improve the performance of de novo protein structure prediction methods. In this study, a novel method based on learning-to-rank (RRCRank) has been presented to predict protein residue-residue contacts. The proposed method formulates the contacts prediction problem as a ranking problem. Firstly, the contact probabilities of residue pairs are predicted by ensemble machine-learning classifiers and correlated mutations approaches. And then, the proposed method integrates the complementary outputs of machine-learning and correlated mutations approaches and uses the learning-to-rank algorithm to rank residue pairs based on their probabilities to be contacts. Benchmarked on the CASP11 dataset, the proposed method achieves an improved performance for all three categories of contacts (short-range, medium-range and long-range contacts), which shows the proposed method based on learning-to-rank could take advantage of machine-learning and correlated mutations approaches and could provide the state-of-the-art performance.
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