Communication Mechanism and Algorithm of Composite Location Analysis of Emergency Communication based on Rail

The emergency communication system based on rail is an unconventional emergency communication mode,it is a complement equipment for that conventional communication system can’t work while tunnel mine accident occurs.Medium of transmission channel is the widely existing rail in the tunnel.In this paper we analyzed the characteristics of the rail transmission channel,verified the feasibility that information is transmitted by vibration signal in rail,we proposed the realization plan of the system.Communication protocol and processing mechanism suitable for rail transmission are designed according to the characteristics of channel bandwidth and low data transmission.Information communication with low bit rate and low bit error is realized in the communication simulation model.In the simplified model,we realized to transmit recognition speech information,and the error rate of the key text information is low to accept.The most concerned problem of personnel location in the mine disaster rescue is proposed,the composite algorithm is based on the model of signal amplitude attenuation,key node information and data frame transmission delay.Location information of hitting point can be achieved within the simplified model of the experiment.Furthermore,we discuss the characteristics of vibration signals passing through different channels.

A Multiple-Neighborhood-Based Parallel Composite Local Search Algorithm for Timetable Problem

This paper presents a parallel composite local search algorithm based on multiple search neighborhoods to solve a special kind of timetable problem. The new algorithm can also effectively solve those problems that can be solved by general local search algorithms. Experimental results show that the new algorithm can generate better solutions than general local search algorithms.

Design Optimization of CFRP Stacking Sequence Using a Multi-Island Genetic Algorithms Under Low-velocity Impact Loads

A method to improve the low-velocity impact performance of composite laminate is proposed, and a multi-island genetic algorithm is used for the optimization of composite laminate stacking sequence under low-velocity impact loads based on a 2D dynamic impact finite element analysis. Low-velocity impact tests and compression-after impact（CAI） tests have been conducted to verify the effectiveness of optimization method. Experimental results show that the impact damage areas of the optimized laminate have been reduced by 42.1% compared to the baseline specimen, and the residual compression strength has been increased by 10.79%, from baseline specimen 156.97 MPa to optimized 173.91 MPa. The tests result shows that optimization method can effectively enhance the impact performances of the laminate.

Mathematical Foundation of Basic Algorithms of Fuzzy Reasoning

Algorithm of fuzzy reasoning has been successful applied in fuzzy control,but its theoretical foundation of algorithms has not been thoroughly investigated. In this paper,structure of basic algorithms of fuzzy reasoning was studied, its rationality was discussed from the viewpoint of logic and mathematics, and three theorems were proved. These theorems shows that there always exists a mathe-~matical relation (that is, a bounded real function) between the premises and the conclusion for fuzzy reasoning, and in fact various algorithms of fuzzy reasoning are specific forms of this function. Thus these results show that algorithms of fuzzy reasoning are theoretically reliable.

STACKING SEQUENCE OPTIMIZA-TION OF LAMINATED COMPOSITE CYLINDER SHELL FOR MAXIMAL BUCKLING LOAD

A new optimization method for the optimization of stacking of composite glass fiber laminates is developed. The fiber orientation and angle of the layers of the cylindrical shells are sought considering the buckling load. The proposed optimization algorithm applies both finite element analysis and the mode-pursuing sampling （MPS）method. The algorithms suggest the optimal stacking sequence for achieving the maximal buckling load. The procedure is implemented by integrating ANSYS and MATLAB. The stacking sequence designing for the symmetric angle-ply three-layered and five-layered composite cylinder shells is presented to illustrate the optimization process, respectively. Compared with the genetic algorithms, the proposed optimization method is much faster and efficient for composite staking sequence plan.

Multi-style Chord Music Generation Based on Artificial Neural Network

With the continuous development of deep learning and artificial neural networks(ANNs), algorithmic composition has gradually become a hot research field. In order to solve the music-style problem in generating chord music, a multi-style chord music generation(MSCMG) network is proposed based on the previous ANN for creation. A music-style extraction module and a style extractor are added by the network on the original basis;the music-style extraction module divides the entire music content into two parts, namely the music-style information Mstyleand the music content information Mcontent. The style extractor removes the music-style information entangled in the music content information. The similarity of music generated by different models is compared in this paper. It is also evaluated whether the model can learn music composition rules from the database. Through experiments, it is found that the model proposed in this paper can generate music works in the expected style. Compared with the long short term memory(LSTM) network, the MSCMG network has a certain improvement in the performance of music styles.

Performance of global look-up table strategy in digital image correlation with cubic B-spline interpolation and bicubic interpolation

Global look-up table strategy proposed recently has been proven to be an efficient method to accelerate the interpolation, which is the most time-consuming part in the iterative sub-pixel digital image correlation （DIC） algorithms. In this paper, a global look-up table strategy with cubic B-spline interpolation is developed for the DIC method based on the inverse compositional Gauss-Newton （IC-GN） algorithm. The performance of this strategy, including accuracy, precision, and computation efficiency, is evaluated through a theoretical and experimental study, using the one with widely employed bicubic interpolation as a benchmark. The global look-up table strategy with cubic B-spline interpolation improves significantly the accuracy of the IC-GN algorithm-based DIC method compared with the one using the bicubic interpolation, at a trivial price of computation efficiency.

Auto Composition System for Two Voice Part Inventions Based on Soft Computational Methods

Algorithmic composition is a very popular research field today. Bach's "two voice part invention" is the research object in this paper. The grammar and compositional rules of "invention" are introduced first. Then two soft computational methods,genetic algorithms and back propagation (BP) neural network technology,are combined to the experiment on assisting in composing "two voice part inventions". The system presented in this paper is quite effective and satisfactory.

Efficient model building in active appearance model for rotated face

This paper proposes the efficient model building in active appearance model(AAM) for the rotated face.Finding an exact region of the face is generally difficult due to different shapes and viewpoints.Unlike many papers about the fitting method of AAM,this paper treats how images are chosen for fitting of the rotated face in modelling process.To solve this problem,databases of facial rotation and expression are selected and models are built using Procrustes method and principal component analysis(PCA).These models are applied in fitting methods like basic AAM fitting,inverse compositional alignment(ICA),project-out ICA,normalization ICA,robust normalization inverse compositional algorithm(RNIC)and efficient robust normalization algorithm(ERN).RNIC and ERN can fit the rotated face in images efficiently.The efficiency of model building is checked using sequence images made by ourselves.

Auto-Harmonizing Chinese Folk Song with Piano Accompaniment

This paper approaches melody harmonization with piano accompaniment as a machine learning task, in a probabilistic framework. An existing Sample score set of Chinese folk song with piano accompaniment is used to build a model of piano accomimniment process. The mcdel can then be used to harmonize new mclody with piano accompaniment.

Two Dimensional Spatial Independent Component Analysis and Its Application in fMRI Data Process

One important application of independent component analysis （ICA） is in image processing. A two dimensional （2-D） composite ICA algorithm framework for 2-D image independent component analysis （2-D ICA） is proposed. The 2-D nature of the algorithm provides it an advantage of circumventing the roundabout transforming procedures between two dimensional （2-D） image deta and one-dimensional （l-D） signal. Moreover the combination of the Newton （fixed-point algorithm） and natural gradient algorithms in this composite algorithm increases its efficiency and robustness. The convincing results of a successful example in functional magnetic resonance imaging （fMRI） show the potential application of composite 2-D ICA in the brain activity detection.

A single-level composite structure optimization method based on a blending tapered model

In order to decrease the number of design variables and improve the efficiency of com- posite structure optimal design, a single-level composite structure optimization method based on a tapered model is presented. Compared with the conventional multi-level composite structure opti- mization method, this single-level method has many advantages. First, by using a distance variable and a ply group variable, the number of design variables is decreased evidently and independent with the density of sub-regions, which makes the single-level method very suitable for large-scale composite structures. Second, it is very convenient to optimize laminate thickness and stacking sequence in the same level, which probably improves the quality of optimal result. Third, ply con-tinuity can be guaranteed between sub-regions in the single-level method, which could reduce stress concentration and manufacturing difficulty. An example of a composite wing is used to demonstrate the advantages and competence of the single-level method proposed.

An Optimization Algorithm for Service Composition Based on an Improved FOA

Large-scale service composition has become an important research topic in Service-Oriented Computing（SOC）. Quality of Service（Qo S） has been mostly applied to represent nonfunctional properties of web services and to differentiate those with the same functionality. Many studies for measuring service composition in terms of Qo S have been completed. Among current popular optimization methods for service composition, the exhaustion method has some disadvantages such as requiring a large number of calculations and poor scalability. Similarly,the traditional evolutionary computation method has defects such as exhibiting slow convergence speed and falling easily into the local optimum. In order to solve these problems, an improved optimization algorithm, WS FOA（Web Service composition based on Fruit Fly Optimization Algorithm） for service composition, was proposed, on the basis of the modeling of service composition and the FOA. Simulated experiments demonstrated that the algorithm is effective, feasible, stable, and possesses good global searching ability.

Distributed Algorithms for Event Reporting in Mobile-Sink WSNs for Internet of Things

Wireless Sensor Networks（WSNs） have many applications, such as climate monitoring systems, fire detection, smart homes, and smart cities. It is expected that WSNs will be integrated into the Internet of Things（IoT）and participate in various tasks. WSNs play an important role monitoring and reporting environment information and collecting surrounding context. In this paper we consider a WSN deployed for an application such as environment monitoring, and a mobile sink which acts as the gateway between the Internet and the WSN. Data gathering is a challenging problem in WSNs and in the IoT because the information has to be available quickly and effectively without delays and redundancies. In this paper we propose several distributed algorithms for composite event detection and reporting to a mobile sink. Once data is collected by the sink, it can be shared using the IoT infrastructure. We analyze the performance of our algorithms using WSNet simulator, which is specially designed for event-based WSNs. We measure various metrics such as average residual energy, percentage of composite events processed successfully at the sink, and the average number of hops to reach the sink.

一种用于位移场分析的应变模式频域数字图像相关方法

本文提出了一种在频域中考虑应变对位移影响的频域数字图像相关方法.研究并建立了一个在频域中评价参考图像子区与目标图像子区之间匹配的评价标准,并在此基础之上,提出了可用于位移和应变计算的频域迭代算法,其中,Hessian矩阵在迭代过程中保持不变.在Hessian矩阵的形成过程中,参考图像子区中灰度的梯度可以通过快速傅里叶变换进行计算,具有很高的计算效率和精度.同时,一种离散傅里叶变换重采样技术被用于代替传统的插值方法对变形图像子区中亚像素位置的灰度进行重建和更新.为了验证所提方法的有效性和准确性,使用了国际DIC挑战委员会(IDCC)提供的系列图像(2D-Challenge 1.0,样本6)进行位移分析.分析的误差结果表明,在子区大小为41×41像素的条件下,对变形为50%的模拟实验进行了计算,位移分析结果的精度约为0.0032像素(最大绝对值误差),在精度上优于已发表的文献.最后,对硅橡胶试件进行了14.85%的单轴拉伸试验,通过相关系数分布检验了本文所提方法在实际应用中的有效性,并给出了分析的位移和应变分布.

Heterogeneous parallel computing accelerated iterative subpixel digital image correlation

Parallel computing techniques have been introduced into digital image correlation(DIC) in recent years and leads to a surge in computation speed. The graphics processing unit(GPU)-based parallel computing demonstrated a surprising effect on accelerating the iterative subpixel DIC, compared with CPU-based parallel computing. In this paper, the performances of the two kinds of parallel computing techniques are compared for the previously proposed path-independent DIC method, in which the initial guess for the inverse compositional Gauss-Newton(IC-GN) algorithm at each point of interest(POI) is estimated through the fast Fourier transform-based cross-correlation(FFT-CC) algorithm. Based on the performance evaluation, a heterogeneous parallel computing(HPC) model is proposed with hybrid mode of parallelisms in order to combine the computing power of GPU and multicore CPU. A scheme of trial computation test is developed to optimize the configuration of the HPC model on a specific computer. The proposed HPC model shows excellent performance on a middle-end desktop computer for real-time subpixel DIC with high resolution of more than 10000 POIs per frame.

Harmonizing Melody with Meta-Structure of Piano Accompaniment Figure

In this paper, a meta-structure of piano accompaniment figure （meta-structure for short） is proposed to harmonize a melodic piece of music so as to construct a multi-voice music. Here we approach melody harmonization with piano accompaniment as a machine learning task in a probabilistic framework. A series of piano accompaniment figures are collected from the massive existing sample scores and converted into a set of meta-structure. After the procedure of samples training, a model is formulated to generate a proper piano accompaniment figure for a harmonizing unit in the context. This model is flexible in harmonizing a melody with piano accompaniment. The experimental results are evaluated and discussed.