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Synergetic neural network (SNN) is a top-down network to explain the phase transition and self-organization in non-equilibrium system. The network parameters have a crucial impact on the recognition performance of synergetic neural network. At present, there is no good way to control and adjust the network parameters. To solve these problems, an improved parameters optimization algorithm based on differential evolution algorithm is proposed and implemented in this paper. There are two main works in this paper. Firstly, a semantic analysis model based on synergetic neural network is presented. Secondly, differential evolution algorithm is used to search the global optimum of network parameters in the corresponding parameter space. The experiments showed that the optimization algorithm can improve the synergetic recognition performance.
Network virtualization provides a promising tool to allow multiple heterogeneous virtual networks to run on a shared substrate network simultaneously. A long-standing challenge in network virtualization is the Virtual Network Embedding (VNE) problem: how to embed virtual networks onto specific physical nodes and links in the substrate network effectively. Recent research presents several heuristic algorithms that only consider single topological attribute of networks, which may lead to decreased utilization of resources. In this paper, we introduce six complementary characteristics that reflect different topological attributes, and propose three topology-aware VNE algorithms by leveraging the respective advantages of different characteristics. In addition, a new KS-core decomposition algorithm based on two characteristics is devised to better disentangle the hierarchical topological structure of virtual networks. Due to the overall consideration of topological attributes of substrate and virtual networks by using multiple characteristics, our study better coordinates node and link embedding. Extensive simulations demonstrate that our proposed algorithms improve the long-term average revenue, acceptance ratio, and revenue/cost ratio compared to previous algorithms.
Osmanthus fragrans Lour. is a popular aromatic ornamental plant and its fl owers are used to enhance the color and fragrance of food. In this study, we analyzed the volatiles of 29 cultivars from all four groups of O. fragrans using a solid-phase microextraction (SPME) technique and gas chromatography–mass spectrometry (GC–MS). We identifi ed 41 volatile organic components that were distributed over fi ve diff erent compound classes, with the majority of the volatile components being dominated by alcohols, ketones, and terpenes, which accounted for 56.6–95.06% of the total volatiles in all tested materials except ‘Zao Yingui'. In ‘Zao Yingui', alcohols, ketones, and terpenes accounted for only 48.19% of the total volatiles. The diversity of the volatile compounds and their relative contents varied among the four groups and cultivars within each group. The major volatile compounds were α-ionone, β-ionone, 2H-β-ionone, linalool, trans -linalool oxide, cis -linalool oxide, epoxy linalool, geraniol ( Z )-ocimene, and γ-decalactone in all tested cultivars, while nerol and ( Z )-3-hexenyl butanoic acid ester were abundant in several cultivars. The 29 cultivars were classifi ed into fi ve clusters in a hierarchical cluster analysis based on their fl oral volatile compounds. The cultivars of diff erent sexes (male vs. hermaphrodite) had no signifi cant diff erences in the relative contents of the major volatile compounds. This study provides valuable information for understanding the chemical composition of the volatile compounds of O. fragrans fl owers as well as a theoretical basis for the origin, development, and application of modern cultivars of O. fragrans.
Overlay networks have been widely deployed upon the Internet by Service Providers (SPs) to provide improved network services. However, the interaction between each overlay and traffic engineering (TE) as well as the interaction among co-existing overlays may occur. In this paper, we adopt both non-cooperative and cooperative game theory to analyze these interactions, which are collectively called hybrid interaction. Firstly, we model a situation of the hybrid interaction as an n+1-player non-cooperative game, in which overlays and TE are of equal status, and prove the existence of Nash equilibrium (NE) for this game. Secondly, we model another situation of the hybrid interaction as a 1-leader-n-follower Stackelberg-Nash game, in which TE is the leader and co-existing overlays are followers, and prove that the cost at Stackelberg-Nash equilibrium (SNE) is at least as good as that at NE for TE. Thirdly, we propose a cooperative coalition mechanism based on Shapley value to overcome the inherent inefficiency of NE and SNE, in which players can improve their performance and form stable coalitions. Finally, we apply distinct genetic algorithms (GA) to calculate the values for NE, SNE and the assigned cost for each player in each coalition, respectively. Analytical results are confirmed by the simulation on complex network topologies.
Wireless wearable sensor networks have emerged as a promising technique for human motion tracking due to the flexibility and scalability. In such system several wireless sensor nodes being attached to human limb construct a wearable sensor network, where each sensor node including MEMS sensors (such as 3-axis accelerometer, 3-axis magnetometer and 3-axis gyroscope) monitors the limb orientation and transmits these information to the base station for reconstruction via low-power wireless communication technique. Due to the energy constraint, the high fidelity requirement for real time rendering of human motion and tiny operating system embedded in each sensor node adds more challenges for the system implementation. In this paper, we discuss such challenges and experiences in detail during the implementation of such system with wireless wearable sensor network which includes COTS wireless sensor nodes (Imote 2) and uses TinyOS 1.x in each sensor node. Since our system uses the COTS sensor nodes and popular tiny operating system, it might be helpful for further exploration in such field.
Service oriented architecture (SOA) lends itself to model the application components to coarse-grained services in such a way that the composition of different services could be feasible. Service composition fulfills numerous service requirements by constructing composite applications with various services. As it is the case in many real-world applications, different users have diverse QoS demands issuing for composite applications. In this paper, we present a service composition framework for a typical service overlay network (SON) considering both multiple QoS constraints and load balancing factors. Moreover, a service selection algorithm based on niching technique and particle swarm optimization (PSO) is proposed for the service composition problem. It supports optimization problems with multiple constraints and objective functions, whether linear or nonlinear. Simulation results show that the proposed algorithm results in an acceptable level of efficiency regarding the service composition objective under different circumstances.
In this paper, we use a quadrotor-based mobile sink to gather sensor data from the terrestrial deployed wireless sensor network. By analyzing the flight features of the mobile sink node, we theoretically study the flight constraints of height, velocity, and trajectory of the mobile sink node so as to communicate with the terrestrial wireless sensor network. Moreover, we analyze the data amount which the mobile sink can send when it satisfies these flight constraints. Based on these analysis results, we propose a data acquisition approach for the mobile sink node, which is discussed detailed in terms of network performance such as the transmission delay, packet loss rate, sojourning time and mobile trajectory when given the flying speed and height of the mobile sink node. Extensive simulation results validate the efficiency of the proposed scheme.
In practical wireless systems, the erroneous channel state information (CSI) sometimes deteriorates the performance drastically. This paper focuses on robust design of coordinated set planning of coordinated multi-point (CoMP) transmission, with respect to the feedback delay and link error. The non-ideal channel models involving various uncertainty conditions are given. After defining a penalty factor, the robust net ergodic capacity optimization problem is derived, whose variables to be optimized are the number of coordinated base stations (BSs) and the divided area`s radius. By the maximum minimum criterion, upper and lower bounds of the robust capacity are investigated. A practical scheme is proposed to determine the optimal number of cooperative BSs. The simulation results indicate that the robust design based on maxmin principle is better than other precoding schemes. The gap between two bounds gets smaller as transmission power increases. Besides, as the large scale fading is higher or the channel is less reliable, the number of the cooperated BSs shall be greater.
Normal and the spontaneous spirally rolled leaves of Cymbidium goeringii var. longibracteatum were used for RNA sequencing analyses using the Illumina paired-end sequencing technique to figure out the differently- expressed genes in two samples. About 5.65 and 4.82 Gb sequencing data of raw reads were obtained from 2 cDNA libraries of normal and the spirally rolled leaves respectively. After data filtering, quality checks and de novo assembly, a total of 48,935 unigenes with an average sequence length of 820 nt were generated. In addition, the transcriptome change in normal and the spirally rolled leaves was investigated. With non-redundant annotation, 219 differentially expressed genes (DEGs) are identified, with 147 up-regulated genes and 72 down-regulated genes. Out of these DEGs, 21 DEGs (9.59 %) were involved in cell wall modeling enzymes, such as expansin, xyloglucan endo-transglycosylase, pectate lyase, cell wall-associated hydrolase. Besides, other DEGs were predominantly classified as genes involved in transcription factor and signal sense and transduction signaling. This study presents the first comprehensive characterization of the leave transcriptomes of Cymbidium goeringii var. longibracteatum. This study not only gave us valuable sequence resources of this species, but also provided theoretical foundation for cultivar breeding of leaf mutation in C. goeringii var. longibracteatum.