Hidden Naive Bayes (HNB) has demonstrated remarkable progress in classification accuracy, accurate class probability estimation and ranking. Since HNB is based on one-dependence estimators to get the approximate value...
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We present an improved RRT*to blend lane information and avoid obstacles in this *** most of other improved RRT*,this paper attach great importance to the convergent goal of RRT*.We consider the condition that there e...
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We present an improved RRT*to blend lane information and avoid obstacles in this *** most of other improved RRT*,this paper attach great importance to the convergent goal of RRT*.We consider the condition that there exists a reference path,maybe not the shortest path,but the environment requires the vehicle to follow,such as a lane *** with standard RRT*applied to differential situation,we first add a T estto Goal procedure to improve the convergent speed and also make sure the path can reach the goal pose but not the goal region to promise the safety of autonomous *** of the key characteristic of our improved algorithm is to employ a fast clothoid fitting method into RRT*to enable us to control the *** important modification is the heuristic sampling method that makes our algorithm can converge to lane *** evaluate our algorithm with a real lane to demonstrate the effect of our modifications.
XML documents cluster analysis is a hot research topic. Researchers proposed a number of methods to cluster XML document collections. Boosting is successful well-known methods for improving the quality of clustering. ...
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BACKGROUND:To facilitate advances in personalized medicine, it is important to detect predictive, stable and interpretable biomarkers related with different clinical characteristics. These clinical characteristics may...
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BACKGROUND:To facilitate advances in personalized medicine, it is important to detect predictive, stable and interpretable biomarkers related with different clinical characteristics. These clinical characteristics may be heterogeneous with respect to underlying interactions between genes. Usually, traditional methods just focus on detection of differentially expressed genes without taking the interactions between genes into account. Moreover, due to the typical low reproducibility of the selected biomarkers, it is difficult to give a clear biological interpretation for a specific disease. Therefore, it is necessary to design a robust biomarker identification method that can predict disease-associated interactions with high reproducibility.
RESULTS:In this article, we propose a regularized logistic regression model. Different from previous methods which focus on individual genes or modules, our model takes gene pairs, which are connected in a protein-protein interaction network, into account. A line graph is constructed to represent the adjacencies between pairwise interactions. Based on this line graph, we incorporate the degree information in the model via an adaptive elastic net, which makes our model less dependent on the expression data. Experimental results on six publicly available breast cancer datasets show that our method can not only achieve competitive performance in classification, but also retain great stability in variable selection. Therefore, our model is able to identify the diagnostic and prognostic biomarkers in a more robust way. Moreover, most of the biomarkers discovered by our model have been verified in biochemical or biomedical researches.
CONCLUSIONS:The proposed method shows promise in the diagnosis of disease pathogenesis with different clinical characteristics. These advances lead to more accurate and stable biomarker discovery, which can monitor the functional changes that are perturbed by diseases. Based on these predictions, researche
We present an improved RRT* to blend lane information and avoid obstacles in this paper. Unlike most of other improved RRT*, this paper attach great importance to the convergent goal of RRT*. We consider the condition...
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ISBN:
(纸本)9781479960798
We present an improved RRT* to blend lane information and avoid obstacles in this paper. Unlike most of other improved RRT*, this paper attach great importance to the convergent goal of RRT*. We consider the condition that there exists a reference path, maybe not the shortest path, but the environment requires the vehicle to follow, such as a lane center. Compared with standard RRT* applied to differential situation, we first add a TesttoGoal procedure to improve the convergent speed and also make sure the path can reach the goal pose but not the goal region to promise the safety of autonomous vehicle. One of the key characteristic of our improved algorithm is to employ a fast clothoid fitting method into RRT* to enable us to control the curvature. Another important modification is the heuristic sampling method that makes our algorithm can converge to lane center. We evaluate our algorithm with a real lane to demonstrate the effect of our modifications.
The cloud platform provides abundant resources and services for users. More and more mobile users began to use the cloud services. They have higher real-time demands on service. The size of traditional virtual machine...
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The cloud platform provides abundant resources and services for users. More and more mobile users began to use the cloud services. They have higher real-time demands on service. The size of traditional virtual machine (VM) operating system is basically large. It will take many resources in deployment and communication process, and always affect the real-time performance of system. To reduce communication overhead and improve deployment speed of VMs, this paper proposes an approach of customized VM image with LFS. LFS can reduce the size of VM image efficiently and enable flexible customization of the VM image by incremental customization. The experimental results show us that the size of VM image generated by the proposed method is smaller than the one generated by kernel tailoring technology in system overhead. Meanwhile it is also faster in running speed.
In this paper, a modified particle swarm optimization(MPSO) algorithm is proposed to solve the reliability redundancy optimization problem. This algorithm modifies the strategy of generating new position of particles....
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In this paper, a modified particle swarm optimization(MPSO) algorithm is proposed to solve the reliability redundancy optimization problem. This algorithm modifies the strategy of generating new position of particles. For each generation solution, the flight velocity of particles is removed. Whereas the new position of each particle is generated by using difference strategy. Moreover, an adaptive parameter is used to ensure diversity of feasible solutions. Experimental results on four benchmark problems demonstrate that the proposed MPSO has better robustness, effectiveness and efficiency than other algorithms reported in literatures for solving the reliability redundancy optimization problem.
Recent years have witnessed the explosive growth of online social networks (OSNs), which provide a perfect platform for observing the information propagation. Based on the theory of complex network analysis, consideri...
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