2445646
Modeling and Robustness Analysis of Biochemical Networks of Glycerol Metabolism by Klebsiella Pneumoniae
Glycerol bioconversion to 1,3-propanediol (1,3-PD) by Klebsiella pneumoniae (K. pneumoniae) can be characterized by an intricate network of interactions among biochemical fluxes, metabolic compounds, key enzymes and genetic regulatory. To date, there still exist some uncertain factors in this complex network because of the limitation in bio-techniques, especially in measuring techniques for intracellular substances. In this paper, among these uncertain factors, we aim to infer the transport mechanisms of glycerol and 1,3-PD across the cell membrane, which have received intensive interest in recent years. On the basis of different inferences of the transport mechanisms, we reconstruct various metabolic networks correspondingly and subsequently develop their dynamical systems (S-systems). To determine the most reasonable metabolic network from all possible ones, we establish a quantitative definition of biological robustness and undertake parameter identification and robustness analysis for each system. Numerical results show that it is most possible that both glycerol and 1,3-PD pass the cell membrane by active transport and passive diffusion.
119668212
Impulsive optimal control model for the trajectory of horizontal wells
This paper presents an impulsive optimal control model for solving the optimal designing problem of the trajectory of horizontal wells. We take fully into account the effect of unknown disturbances in drilling. The optimal control problem can be converted into a nonlinear parametric optimization by integrating the state equation. We discuss here that the locally optimal solution depends in a continuous way on the parameters (disturbances) and utilize this property to propose a revised Hooke-Jeeves algorithm. The uniform design technique is incorporated into the revised Hooke-Jeeves algorithm to handle the multimodal objective function. The numerical simulation is in accordance with theoretical results. The numerical results illustrate the validity of the model and efficiency of the algorithm.
18513431
Modeling and Properties of Nonlinear Stochastic Dynamical System of Continuous Culture
The stochastic counterpart to the deterministic description of continuous fermentation with ordinary differential equation is investigated in the process of glycerol bio-dissimilation to 1,3-propanediol by Klebsiella pneumoniae. We briefly discuss the continuous fermentation process driven by three-dimensional Brownian motion and Lipschitz coefficients, which is suitable for the factual fermentation. Subsequently, we study the existence and uniqueness of solutions for the stochastic system as well as the boundedness of the Two-order Moment and the Markov property of the solution. Finally stochastic simulation is carried out under the Stochastic Euler-Maruyama method.
5641652
Image orientation detection with integrated human perception cues (or which way is up)
In this paper, we propose a set of human perceptual cues used jointly to automatically detect image orientation. The cues used are: orientation of faces, position of the sky, brighter regions, and textured objects, and symmetry. We combine these cues in a Bayesian framework, and the photo acquiring model has been considered carefully as the prior knowledge of the image orientation. Results on more than a thousand different images provide a compelling argument that our approach is a viable one.
33446676
Voronoi Tessellation Based Rapid Coverage Decision Algorithm for Wireless Sensor Networks
The coverage problem is a fundamental issue in the research of sensor network. A novel Voronoi tessellation based rapid coverage decision algorithm is proposed, in which the region of interest is partitioned into some square grids firstly, and then the complex area coverage problem is transformed into simple vertices coverage problem, on the basis of the good characteristics of Voronoi tessellation such as being able to divide the planner area into a set of simple geometric simplexes. Theoretical analysis and simulation results show that, the new algorithm can decrease the computation complexity of networks, especially for sensor networks with n different sensors, it can solve the coverage problem correctly for any given region of interest with time costs of O(nlogn) only.
17047961
Image annotations by combining multiple evidence & wordNet
The development of technology generates huge amounts of non-textual information, such as images. An efficient image annotation and retrieval system is highly desired. Clustering algorithms make it possible to represent visual features of images with finite symbols. Based on this, many statistical models, which analyze correspondence between visual features and words and discover hidden semantics, have been published. These models improve the annotation and retrieval of large image databases. However, current state of the art including our previous work produces too many irrelevant keywords for images during annotation. In this paper, we propose a novel approach that augments the classical model with generic knowledge-based, WordNet. Our novel approach strives to prune irrelevant keywords by the usage of WordNet. To identify irrelevant keywords, we investigate various semantic similarity measures between keywords and finally fuse outcomes of all these measures together to make a final decision using Dempster-Shafer evidence combination. We have implemented various models to link visual tokens with keywords based on knowledge-based, WordNet and evaluated performance using precision, and recall using benchmark dataset. The results show that by augmenting knowledge-based with classical model we can improve annotation accuracy by removing irrelevant keywords.
120181133
Face recognition based on discriminative manifold learning
In this paper, a discriminative manifold learning method for face recognition is proposed which achieved the discriminative embedding the high dimensional face data into a low dimensional hidden manifold. Unlike the recently proposed LLE, Isomap and Eigenmap algorithms, which are based on reconstruction purpose, our method uses the RCA algorithm to achieve nonlinear embedding and data discrimination at the same time. Also, the LLE and Isomap algorithms are crucially depends on the appropriateness of the neighborhood construction rule, in this paper, a CK-nearest neighborhood rule is proposed to achieve better neighborhood construction. Experimental results indicate the promising performance of the proposed method.
17681650
Cross-Layer Optimized Data Gathering in Wireless Multimedia Sensor Networks
Using multimedia sensor nodes can enhance the capability of wireless sensor networks (WSNs) for event description. In some scenarios, e.g., an erupting volcano, the WSNs are not deployed to work for long time. Instead, the WSNs aim to deliver continuous and reliable multimedia data as much as possible within an expected lifetime. In this paper, we focus on the efficient multimedia data gathering in WSNs within an expected lifetime. A distributed transmission Radius and data generation Rate Adjustment (RRA) scheme is proposed based on a cross-layer design, considering the interaction among physical, network and transport layers. Simulation results show that the proposed RRA strategy can effectively enhance the data gathering performance in wireless multimedia sensor networks (WMSNs) by dynamically adjusting the transmission radius of sensor nodes and the data generation rate of source nodes.