作者机构：
[Wu, Libing; Cao, Shuqin] Wuhan Univ, Sch Comp Sci, Wuhan 430072, Peoples R China.;[Wu, Libing; Cao, Shuqin] Guangdong Lab Artificial Intelligence & Digital Ec, Wuhan 518132, Peoples R China.;[Chen, Yanjiao] Zhejiang Univ, Coll Elect Engn, Hangzhou 310007, Peoples R China.;[Li, Jianxin] Deakin Univ, Sch Informat Technol, Burwood, Vic 3217, Australia.;[Cui, Jianqun; Chang, Yanan] Cent China Normal Univ, Sch Comp Sci, Wuhan 430079, Peoples R China.
通讯机构：
[Wu, L.] S;[Chen, Y.] C;School of Computer Science, Wuhan University, Wuhan, 430072, China<&wdkj&>Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Wuhan, 518132, China
摘要：
A mobility model is a basis of constructing the simulation environment for vehicular ad hoc network (VANET) research. Most existing models mainly focus on the geographical movement of individual mobile communication devices. However, few works focus on the cooperative movement of multiple autonomous vehicles. In this paper, we propose a cooperative mobility model for multiple autonomous vehicles, making vehicles run as a swarm in an orderly manner. Specifically, inspired by artificial fish swarm algorithms, we draw on the cooperative behaviors of the fish swarm to model the collaboration and self-organization in multi-vehicle formation. Then we design several force functions to express the interactions between vehicles and the influence of the driving environment based on the artificial potential field. Under Newtonian dynamics, the proposed mobility model determines the coordinated movement of multiple autonomous vehicles by force functions. Furthermore, we introduce a parallel orientation area in the interaction area division to improve vehicle stability. Following existing works, we assume that the road is straight and of infinite length. This is, the considered environment is suitable for intersection-free double-lane roads. To comprehensively verify the effectiveness of our proposed approach, we conduct extensive simulations under different traffic scenarios. Simulation results confirm that using our mobility model, multiple vehicles are able to keep driving in the center of the lane at the allowed speed limit, form an ordered collision-free motorcade, and collaboratively avoid collisions with obstacles. Particularly, our proposed mobility model has better stability.
作者机构：
[Wu, Libing; Cao, Shuqin; Chen, Yanjiao] Wuhan Univ, Sch Comp Sci, Wuhan 430072, Peoples R China.;[Wu, Libing] Wuhan Univ, Sch Cyber Sci & Engn, Wuhan, Peoples R China.;[Wu, Libing] Wuhan Univ, Shenzhen Res Inst, Wuhan, Peoples R China.;[Cui, Jianqun; Chang, Yanan] Cent China Normal Univ, Sch Comp, Wuhan, Peoples R China.
通讯机构：
[Libing Wu] S;School of Computer Science, Wuhan University, Wuhan, 430072, China<&wdkj&>School of Cyber Science and Engineering, Wuhan University, China<&wdkj&>Shenzhen Research Institute of Wuhan University, China
关键词：
improved brainstorm optimization;Vehicle routing problem with soft time window
摘要：
In this paper, we propose a novel ant colony optimization algorithm based on improved brainstorm optimization (IBSO-ACO) to solve the vehicle routing problem with soft time windows. Compared with the traditional ant colony algorithm, the proposed IBSO-ACO can better address the local optimum problem, since we have carefully designed an improved brainstorming optimization algorithm to update the solutions obtained by the ant colony algorithm, which enhance the solution diversity and the global search ability. Furthermore, we use the classification method to accelerate the convergence of the proposed algorithm. The extensive experimental results have confirmed that the proposed IBSO-ACO algorithm can achieve a lower routing cost at a high convergence rate than the traditional ant colony algorithm and the simulated annealing ant colony algorithm.
关键词：
Spatial keyword query;Internet of industrial vehicles;Wireless data broadcast;Air index
摘要：
With the development of the Internet of Things (IoT), the industrial vehicle ad hoc networks are revolving into the Internet of Industrial Vehicles (IoIV). Due to the popularity of the geographical devices used on the Industrial vehicle, location-based information is extensively available in IoIV. This development calls for spatial keyword queries (SKQ), which takes into account both the locations and textual descriptions of objects. This paper addresses the issue of processing SKQ in IoIV environment, which focuses on two types of SKQ queries, namely Boolean kNN Queries and Top-k Queries. A general air index called Extended Spatial Keyword query index in IoIV environment (ESKIV) is proposed, which supports both network space pruning and textual pruning simultaneously. Based on ESKIV, efficient algorithms are designed to deal with these two types of SKQ respectively. The proposed ESKIV also can be used to deal with other kinds of queries, such as range SKQ. Finally, extensive simulations are conducted to demonstrate the efficiency of our ESKIV index and the corresponding query processing algorithms.
摘要：
According to the growth of reality demand of digital media, the 5.1 surround is widely used and researched. To further improve the listening experience of the 5.1 channel audio, the primary-ambient extraction (PAE) is introduced to facilitate flexible rendering in spatial audio reproduction. The common multichannel PAE approach is principle component analysis (PCA), which suffers from high extraction errors and long computation time. In this letter, we proposed a novel approach based on channel pair for 5.1 channel audio, which considers the five channels as a set of channel pairs. Then a linear estimation framework is applied at any one time to only one pair, which converts the problem of PAE into the estimation of weight matrix, thus the weight of each component can be computed by using the Least Square. The experimental results indicate that the novel approach significantly outperforms the existing approach PCA.
摘要：
Emerging multimedia Multiview video systems consist of a dense deployment of multiple partial-overlapped wireless cameras, as well as some access points (Aps) and many wireless distributed relay nodes. Correlated views are captured by cameras followed being transmitted to destination by different Aps and networks links. Packet expiration of one camera flow may harm the whole task. To effectively integrate multiple viewpoints into a whole image, the correlated data rate and deadline of flows from multiple cameras are meaningful. There is a trade-off between data redundancy and time deadline among correlated multi-views subjecting to the constraints of limited buffer length. However, most researches in this field have not considered packet expiration suffering from varieties of delays after multipath. In this paper, we conduct this problem to optimally adjust multiple flows of viewpoints by exploiting spatial and temporal correlations among cameras to reduce delay variances. A global optimization algorithm based on joint rate-distortion and delay-distortion model is proposed. Simulation results show that quality of service for Multiview streaming can be improved by allocating suitable transmission rates among correlated cameras as well as appropriate playout deadline. The PSNR quality shows that better performance can be achieved compared with baseline policies.
作者机构：
[Jiang, Xingpeng; Yang, Jincai; He, Tingting; Shen, Xianjun; Hu, Xiaohua; Chen, Yao] Cent China Normal Univ, Sch Comp, Wuhan 430079, Hubei, Peoples R China.
通讯机构：
[Shen, Xianjun] C;Cent China Normal Univ, Sch Comp, Wuhan 430079, Hubei, Peoples R China.
关键词：
*Disease network;*Heterogeneous network;*Microbe network;*Random walk
摘要：
As we all know, the microbiota show remarkable variability within individuals. At the same time, those microorganisms living in the human body play a very important role in our health and disease, so the identification of the relationships between microbes and diseases will contribute to better understanding of microbes interactions, mechanism of functions. However, the microbial data which are obtained through the related technical sequencing is too much, but the known associations between the diseases and microbes are very less. In bioinformatics, many researchers choose the network topology analysis to solve these problems. Inspired by this idea, we proposed a new method for prioritization of candidate microbes to predict potential disease-microbe association. First of all, we connected the disease network and microbe network based on the known disease-microbe relationships information to construct a heterogeneous network, then we extended the random walk to the heterogeneous network, and used leave-one-out cross-validation and ROC curve to evaluate the method. In conclusion, the algorithm could be effective to disclose some potential associations between diseases and microbes that cannot be found by microbe network or disease network only. Furthermore, we studied three representative diseases, Type 2 diabetes, Asthma and Psoriasis, and finally presented the potential microbes associated with these diseases by ranking candidate disease-causing microbes, respectively. We confirmed that the discovery of the new associations will be a good clinical solution for disease mechanism understanding, diagnosis and therapy.
期刊：
International Journal of Wireless and Mobile Computing,2016年11(1):18-23 ISSN：1741-1084
通讯作者：
Shen, Xianjun(xjshen@mail.ccnu.edu.cn)
作者机构：
[Hu, Wenjie] College of Information Engineering, Xianning Vocational Technical College, Xianning, Hubei, China;[Yang, Jincai; Chen, Yao; Shen, Xianjun] School of Computer, Central China Normal University, Wuhan, Hubei, China;Collaborative & Innovative Center for Educational Technology, Central China Normal University, Wuhan, Hubei, China;[Shen, Xianjun] Collaborative and Innovative Center for Educational Technology, Central China Normal University, Wuhan, Hubei, China
通讯机构：
School of Computer, Central China Normal University, Wuhan, Hubei, China
摘要：
Aiming at the critical drawbacks of low sampling rate and less accuracy in Monte Carlo Localisation (MCL) algorithm, a novel mobile nodes localisation algorithm based on the hill climbing optimisation strategy is proposed, namely HCPSO-MCL (Hill Climbing Particle Swarm Optimisation-MCL). The HCPSO-MCL algorithm combines the hill climbing strategy and particle swarm optimisation to correct the location estimated by the MCL algorithm, which results in effective implementation and accurate positioning of the mobile nodes. The experimental results indicate that the HCPSO-MCL algorithm improves the positioning accuracy greatly compared to the MCL algorithm and that it has a faster position velocity than the PSO-MCL algorithm.
