15661895
Robust Distributed Localization with Data Inference for Wireless Sensor Networks
We consider the range-based localization with highly insufficient inter-node distance measurements in Wireless Sensor Networks (WSNs). With an error model established, a novel distributed probabilistic localization approach which exploits the network constraints through statistical inference on missing distances is proposed. The advantage of the new approach over traditional methods is proved analytically and further confirmed by extensive simulations.
34552917
A new dynamic Bayesian network for integrating multiple data in estimating gene networks
We propose a novel method for estimating a gene regulatory network from both gene expression data and transcription factor binding location data. Based on dynamic Bayesian network (DBN) models, our method has two advantages. First, structural expectation maximization algorithm is embedded into a DBN framework, allowing it to learn the network with unknown structure and incomplete data, which cannot be tackled by expectation maximization algorithm. Second, since learning only from gene expression data is not enough to accurately estimate a gene network, we incorporate transcription factor binding location data through a structure prior. We demonstrate the effectiveness of the proposed method by the analysis of Saccharomyces Cerevisiae cell cycle data. The experimental results show that this new approach suits for dealing with missing values. Furthermore, combination of heterogeneous data from multiple sources ensures that our results are more accurate than those recovered from gene expression data alone.
39739560
Optimal Motion Generation of Flexible Macro-micro Manipulator Systems Using Estimation of Distribution Algorithm
In this paper, a new approach for motion generation and optimization of the flexible macro-micro manipulator system is proposed based on Estimation of Distribution Algorithm (EDA). The macro-micro manipulator system is a redundant system, of which inverse kinematics remains challenging, with no generic solution to date. Here, the manipulator system configurations, or the optimal joint motions, are generated using the EDA algorithm base on Gaussian probability model. Compared with simple genetic algorithms (SGA), this approach uses fewer parameters and the time for motion optimization is remarkably reduced. The proposed approach shows excellent performance on motion generation and optimization of a flexible macro-micro manipulator system, as demonstrated by the simulation results.
5444016
Arbitrary warped document image restoration based on segmentation and Thin-Plate Splines
Warping is a common appearance in camera captured document images. It is the primary factor that makes such kind of document images hard to be recognized. Therefore it is necessary to restore warped document image before recognition. In this paper, a novel restore method is presented. The method takes a rough line segmentation and character segmentation firstly in order to estimate the warping direction. Then several pairs of key points mapping between the original image and the restored image are determined and thin-plate splines (TPS), which is an interpolation algorithm, is introduced to restore the image. Such process can effectively describe the warping direction of the document and successfully restore the image. Some experimental results show the effect of the image restoration and compare the recognition rate before and after the restoration based on a same OCR application.
41660705
Fault Diagnosis on Satellite Attitude Control with Dynamic Neural Network
With increasing demands on higher performance, more safety and reliability of dynamic systems, especially on safety-critical systems, fault diagnosis became a research interests in recent years. In this paper, a systematic approach to design fault diagnosis and accommodation with compound approach such as applying improved robust observer to fault diagnosis on linearized system aided by dynamic neural network, which is trained to bridge the gap between simulated system and real system on nonlinear attributes and modeling errors. Using an instance of fault diagnosis on attitude control system of satellite attitude, advantages of new scheme are tested to be effective.
2479481
Gene Regulatory Network Construction Using Dynamic Bayesian Network (DBN) with Structure Expectation Maximization (SEM)
Discovering gene relationship from gene expression data is a hot topic in the post-genomic era. In recent years, Bayesian network has become a popular method to reconstruct the gene regulatory network due to the statistical nature. However, it is not suitable for analyzing the time-series data and cannot deal with cycles in the gene regulatory network. In this paper we apply the dynamic Bayesian network to model the gene relationship in order to overcome these difficulties. By incorporating the structural expectation maximization algorithm into the dynamic Bayesian network model, we develop a new method to learn the regulatory network from the S. Cerevisiae cell cycle gene expression data. The experimental results demonstrate that. the accuracy of our method outperforms the previous work.
16732097
Modeling Role-Based Agent Team
The problem of ensuring agents work as an effective team in dynamic distributed environments still remains a challenging issue. In this paper we proposed a role-based team model. In our model, the role characterizes the responsibilities and provides logic patterns to achieve certain goals and cooperate with others. The agent is an autonomous execution unit and follows the logic patterns that the role provides. We also developed algorithms and mechanisms to evolve the plan of a role to the plan of an agent. Our role-based team model allows the split of roles (who define the plans) and agents (who execute the plans) in team plans, and dynamic role-agent assignment. It also achieves a certain level of plan reusability. We present two experiments which show plan reusability and its flexibility in supporting simultaneously plan invocation.
8166991
On Destination Set in IP-Level Topology Measurement
We present a thorough investigation of four issues with the destination set in IP-level topology measurement. (1) To evaluate the completeness of the destination set, we measured by brute force and found that a half of edges will be missed by the uniform random selection (URS) method which was adopted by well-known CAIDA' skitter. (2) Two potential reasons for edge missing, the short-term routing dynamics and the subnetting technique, were investigated with the last-hop selection method and the bisection selection method respectively. And the results showed that the subnetting technique is the main reason. (3) To select destinations efficiently, we presented the minimum cover selection (MCS) method which performed better than the URS method on 75% of networks over three months. (4) Finally, to investigate the bias of topology characterization, we measured a destination set larger than before and discovered a Chinese topology whose size is 5 times as large as that discovered by skitter. The comparison between characteristics of skitter's topology and ours indicated that the small destination set trends to miss the information on marginal networks.
29942985
Poisson approximation for significance in genome-wide ChIP-chip tiling arrays
MOTIVATION
A genome-wide ChIP-chip tiling array study requires millions of simultaneous comparisons of hybridization for significance. Controlling the false positive rate in genome-wide tiling array studies is very important, because the number of computationally identified regions can easily go beyond the capability of experimental verification. No accurate and efficient method exists for evaluating statistical significance in tiling arrays. The Bonferroni method is overly conservative and the permutation test is time consuming for genome-wide studies.


RESULT
Motivated by the Poisson clumping heuristic, we propose an accurate and efficient method for evaluating statistical significance in genome-wide ChIP-chip tiling arrays. The method works accurately for any large number of multiple comparisons, and the computational cost for evaluating P-values does not increase with the total number of tests. Based on a moving window approach, we demonstrate how to combine results using various window sizes to increase the detection power while maintaining a specified type I error rate. We further introduce a new false discovery rate control that is more appropriate in measuring the false proportion of binding intervals in tiling array analysis. Our method is general and can be applied to many large-scale genomic and genetic studies.


AVAILABILITY
http://www.stat.psu.edu/~yuzhang/pass.tar
5397904
Modeling and Throughput Analysis for Wireless Ad Hoc Networks
This paper presents a novel analytical model for wireless ad hoc networks. Based on the strong points in the literature, an accurate performance model for IEEE 802.11 MAC protocol is proposed. Moreover, by introducing the properties of spatial reuse, we extend the proposed model to support the throughput analysis of wireless ad hoc networks with directional antenna. An extensive set of simulations and numerical calculations validate our model by showing high accurate results.
17429523
A Novel Trust-based Cooperative Node Selection Scheme in Wireless Sensor Networks
For communication between the cluster head node (CHN) and the distant data fusion center (DFC) with the cooperation of intra-cluster nodes in wireless sensor networks (WSNs), reliable handling of packets by the cooperative node (CN) is difficult to ensure. In this paper, we propose a novel CN selection scheme based on trust for WSNs. This scheme can choose one of high trust nodes to assist in the transmission of CHN, which aims to improve the transmission performance over cooperative communication in the presence of potential malicious nodes. First, we establish a trust model to improve the reliability of transmission by CN in WSNs, which is based on both the direct trust and the indirect trust of nodes. Then the CHN selects a node based on the proposed trust model to aid the CHN in transmission. Simulation results show that the proposed scheme can mitigate the impact of the potential malicious nodes on transmission performance and the simulation results also demonstrate the efficiency of the proposed scheme.