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To improve the distributed system performance which is affected by load unbalance, this paper proposes and implements an impulsive and switching load balancing model with time delay based on control theory. The model constructs the corresponding sub-system according to the dynamics of node resources. The overloading is migrated by the load migrate rule, of which the migrate proportion is calculated by real-time running states of nodes. Only on this moment, the node broadcasts its message to others. Thus, the communication cost among nodes decreases, and the efficiency of dynamic load balancing increases. This paper provides the corresponding load balancing algorithm and conducts the evaluation on a real platform. Experimental results demonstrate that compared with other load balancing algorithms, the load balancing time of the proposed model is reduced by 29.82% on average. [ABSTRACT FROM AUTHOR]

Since the self-structure of the DAG(directed acyclic graph)task is not considered， the schedulability analysis of the DAG parallel task model based on G-EDF(global earliest deadline first)is very pessimistic. The response time analysis of the DAG task set under the G-EDF scheduling strategy in multiprocessor systems was studied in this paper. First， a more accurate carry-in workload estimation method was proposed for the execution of the carry-in task instance. Then a method for estimating the problem window workload of completion time was put forward based on the carry-in workload estimation method. Based on the two proposed methods， this paper proposed a response time analyzing method to derive a response time upper bound of each task. The experiments show that the proposed method outperforms the state-of-the-art method by at least 15% and at most 25%. [ABSTRACT FROM AUTHOR]

There are a lot of spatio-temporal data in the real world. The management of spatio-temporal data has proposed higher requirements for spatio-temporal modeling， which has become a hotspot in many fields. UML is a widely used unified modeling language， and the spatio-temporal extension model based on UML has become an important spatio-temporal modeling approach of many fields. This paper presents a spatio-temporal UML model， which can deal with a variety of spatio-temporal topology relationships (including RCC-8 spatial topology and Allen-13 temporal topology relationships) and the complex semantic relations among the spatio-temporal objects. In addition， this paper provides a formal definition and semantic interpretation of spatio-temporal UML model. Finally， an example of cadastral change is provided to demonstrate the feasibility and practicability of the proposed model. [ABSTRACT FROM AUTHOR]

The accuracy of the known wave-speed acoustic emission positioning algorithm is highly restricted by the accuracy of the initial wave speed test， an acoustic emission location algorithm was developed based on the particle swarm optimization (PSO) algorithm no need to pretesting wave velocity. The fitness function was constructed based on the time difference received by the sensor， and the function was solved by the algorithm to obtain the acoustic emission source position and wave velocity. The influence of the difference of different wave speed assignment ranges and the difference ratio (φ) between the upper and lower bounds of different wave speed assignment ranges and the real wave speed value on the accuracy of the algorithm was studied. Then， a lead-off test was carried out to compare and analyze the location accuracy of the PSO algorithm and the simplex algorithm. The results show that the PSO algorithm location error is less than 10% under different wave velocity ranges and different φ values. When the wave velocity assignment range difference is 2000m/s and φ is 1， the algorithm accuracy is the highest. The positioning accuracy of the algorithm in this paper is significantly better than the traditional simplex positioning algorithm. [ABSTRACT FROM AUTHOR]

In order to solve the problem that there are many restrictions on the source domain and the target domain in the process of Bayesian network parameter transfer， a unified framework based on Bayesian network parameter transfer learning was proposed under the condition of considering multiple information forms of source domain and target domain. The method considers the role of source domain structure and data volume in the migration. On the basis of structural similarity， the influence of alternative source domain data volume on parameter migration was discussed. The balance coefficient related to the target domain data was introduced in the migration process. According to the balance coefficient， the target domain data was linked with the migration process to realize the automatic adjustment of the balance coefficient. The Asia network verifies the accuracy of the method in this paper. [ABSTRACT FROM AUTHOR]

Compared with other regions, Northeast China has its unique characteristics of non-road mobile source emission inventories due to its long and cold winter. In this paper, the analysis was divided into Liaoning Province and Harbin-Changchun Megalopolis. Firstly, the emission inventory of non-road mobile sources was established based on technical guide for preparation of air pollutant emission list of non-road mobile sources (trial), and its emission and spatial-temporal distribution characteristics were analyzed. Secondly， the emissions in 2030 were forecasted based on the scenario analysis, taking into account of the relevant policy objectives. Finally， reasonable emission reduction recommendations were made. The results show that: 1) the emissions of PM10， PM2.5, NO.x, THC, and CO were 13.0×10³, 12.5×10³， 205.6×10³, 37.0×10³ and 101.1×10³ t, respectively; 2) construction machinery accounts for the largest share of emissions in the two urban agglomerations with 44.5%and 44.8% respectively; 3) the overall emission reduction can be improved by more than 50% under both the baseline scenario and the enhanced control scenario. [ABSTRACT FROM AUTHOR]

With high-rise buildings emerging, objective fear of heights detection is a key step in the standardization of the aerial work industry. Taking into account virtual reality, this paper designs an aerial exposure experiment, which studies the brain neural mechanism of fear of heights reaction, and proposes the functional brain network (FBN) to detect the fear of heights .By comparing the basic topological characteristics of FBNs, the brain regions closely related to fear of heights are found through thresholding. By dividing the community structures according to the brain regions, the recognition model of fear of heights is established . The results show that the more severe the fear of heights, the more complicated the FBN. The main brain regions involved in fear of heights include frontal lobe, central area, and occipital lobe. Using these brain regions to divide the community structures, the calculation accuracy of connection strengths on fear of heights can reach (97.37±0.58)%. [ABSTRACT FROM AUTHOR]

The flammability limit is an important parameter of combustion characteristics. In this paper, a flammability limit experimental device was set up based on the 5L cylindrical reactor. The flammability limits of ethane under CO2/O2 atmosphere were studied and compared with those in air atmosphere. The results showed that high concentration of CO2 reduces the upper flammability limit and increases the lower flammability limit of gas mixture. The influence of high concentration of CO2 on flammability limit was analyzed. The formula of calculation of flammability limit for CO2/O2was deduced according to the thermal theory. The average absolute deviation between the experimental values and calculated values is within 2.2%. The values of calculation are in agreement with the experimental data. [ABSTRACT FROM AUTHOR]

The neural network with piecewise linear activation function ( PLNN) is extensively applied in machine learning. This paper gives a measure of the expressive power of PLNN model, i. e., the number of linear regions, with the mathematical representation of linear regions presented. The relationship between linear regions is analyzed and the number of combined linear regions is calculated. A method for calculating the number of linear regions based on Z curve is developed. A case is given to calculate the number of linear regions of different network structures and the number of linear regions after merging, and the correlation between the number of linear regions and the accuracy of different network structures is analyzed. The results show that the number of linear regions can reflect the expressive power of PLNN model, which has great research significance for selecting network hyperparameters and explaining model boundaries. [ABSTRACT FROM AUTHOR]

A CW laser was used to perform laser polishing experiments on the 304 stainless steel based on the ablation principle， and a good polishing effect is obtained. A two-dimensional transient numerical model was developed by coupling the heat transfer and material vaporization in laser polishing. The evolution of the workpiece surface in laser polishing was simulated. The surface morphology and surface roughness of the workpiece after laser polishing were predicted. The simulation results are close to the experimental ones， and the error is only 8.17%. In addition， this paper studied the distribution of the surface moving velocity of the workpiece in laser polishing， and determined the relationship between the surface moving velocity and the initial surface morphology: the surface moving velocity at the peak position of the surface morphology is larger， while the surface moving velocity at the valley position is smaller， which reveals the mechanism of laser polishing based on ablation principle to reduce the surface roughness of the workpiece. [ABSTRACT FROM AUTHOR]

The modeling of complex mine roadways， such as curved roadways， intersection roadways， and variable cross-section roadways， is the key and difficult point when building the 3D models of roadway network. Deficiencies exists in the existing method when reconstructing complex roadway networks based on traverse data， especially for the curved intersection roadways which are common in mines. This paper proposed a basic component assembly method (BCAM) for the modeling of the 3D roadway network by using the underground survey data of coal mine roadway. By applying three steps of BCAM， namely the modeling of roadway centerlines， the modeling of roadway sidelines， and the modeling of the basic component of roadway (BCR)， 3D models of complex roadway network can be automatically constructed. The experimental results show that the proposed method is robust， and the modeling time increases linearly and steadily with the increase of data volume. The established 3D model of the roadway network can support various analyses on space， geometry， and mechanics for smart mines. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to realize the evaluation of the level of low-carbon economy by the low-carbon economy evaluation model， and find the effecting factors which influence the development of low-carbon economy. The evaluation results of low-carbon economy can provide theoretical guidance for the low-carbon economic development. The paper first developed the low-carbon economy evaluation index system， and then determined the weights of indicators by Gini and G1， establishing the comprehensive evaluation model of low-carbon economy based on Gini revised G1. At last， the paper did empirical analysis on the level of low-carbon economy development of Qinhuangdao between 2005~2015， determining its status and influence factors. In the meantime， the paper provides theoretical references for the development of low-carbon economy in Qinhuangdao. [ABSTRACT FROM AUTHOR]

When a node in the network fails， in order to study how the node load is distributed to the connected nodes to maintain the normal operation of the network， in this paper， a load re-allocation strategy based on the maximum residual capacity of neighbor nodes was proposed. When the fault node distributes the load， the residual capacity of the receiving node was taken into account， so as to avoid the propagation of the fault caused by full load and overload after the node received the additional load. Considering the energy consumption in the process of load propagation， the influence of path length on load distribution was analyzed. Through the simulation of the model network， the influence of tolerance parameters， load distribution parameters and path length on the load distribution effect was analyzed. The results showed that the network could achieve the desired effect by adjusting the path adjustable parameters， and the propagation of cascade failure could be effectively prevented. [ABSTRACT FROM AUTHOR]

The structural plane spacing is an important parameter in rock mass stability and mechanical properties analysis. It is widely used in the numerical computation of rock mechanics， mining engineering， slope monitoring and other fields. Based on the three-dimensional rock mass slope point cloud data acquired by non-contacting surveying method， this paper proposes a structural surface refinement classification method using density clustering. Projection transformation and scattered point fitting are used after a previous step of general discontinuity classification. The refinement classification is used to compute the structural plane spacing and the rock mass joint number. A prototype system for parameter calculation and analysis of structural surface refinement classification and spacing was designed and developed. The real case experiment and analysis show that the proposed method performs effectively in realizing the automatic refinement classification of structural planes， and in calculating the related parameters such as structural surface spacing， which may provide further support for rock mass quality classification and rock mass stability analysis. [ABSTRACT FROM AUTHOR]

The existing spam website detection methods are mainly aimed at self-built spam websites， and not suitable for injected spam websites because of the low efficiency of link detection. This paper proposes a new detection method， in which a detection framework is based on multi-dimensional features of webpage structure and text. The framework divides the webpage into blocks. Then content features are extracted by calculating odd ratio and structural features based on tags， attribute keys and attribute values are extracted by using the one-hot rate. The detection model is generated by proper machine learning and used to detect spam links. The detection accuracy of this framework is increased by up to 13%， compared with the algorithms based on content detection and on blacklist matching. [ABSTRACT FROM AUTHOR]

Reversible data hiding,as a special information hiding technology,is very useful in many fields,such as medicine,military and law. This paper proposes a reversible data hiding algorithm based on adaptive histogram modification for 3 D mesh models. At first,the local similarity of model shapes is used to predict vertex positions in order to obtain the prediction error sequence with a steep histogram. Then,according to the distribution characteristics of the prediction error histogram,two groups of prediction errors are specified in embedding region for data embedding,which reduce the auxiliary date transfer. In addition,to reduce the model distortion,proper embedding regions are selected based on the payload size to avoid moving more prediction errors. The experimental results demonstrate that the proposed algorithm maintains high visual quality after data embedding and is applicable to low-capacity reversible data hiding. [ABSTRACT FROM AUTHOR]

The orthogonal frequency division multiplexing( OFDM), widely applied in underwater acoustic( UWA) communication,is an efficiently multicarrier modulation technique.But OFDM requires the subcarriers to be orthogonal and is very sensitive to frequency offset. The Doppler compensation or adding the subcarrier filter is mainly used to combat Doppler shift in UWA communication,but the implementation is complicated. This paper investigates the method of reducing intercarrier interference( ICI) from a new perspective,that is,increasing the spacing between subcarriers. The combined frequency division multiplexing( C-FDM) is proposed and several OFDM subcarrier blocks are combined into one new C-FDM subcarrier block,and the same frequency subcarrier near each other to construct new C-FDM subcarriers is arranged.Assuming the symbol lengths of C-FDM and OFDM are equal and the subcarrier spacing of C-FDM is larger, the anti-Doppler shifting capability is effectively improved without complex compensation algorithms. The simulation results showed that C-FDM technology has better BER performance in UWA channel. [ABSTRACT FROM AUTHOR]

The moth-flame optimization( MFO) algorithm may show shortcomings such as the local optimum and convergence stagnation when solving the practical optimization problem.Therefore,aiming at the problem that MRI( magnetic resonance imaging) images are difficult to segment,this paper proposes a chaotic moth-flame optimization( CMFO) algorithm. In order to help doctors read the MRI films and improve the efficiency and accuracy of diagnosis,the knee MRI images are selected as research objects during the experiments. Then,CMFO algorithm and maximum threshold entropy are combined and applied into multi-threshold segmentation. In order to present the advantages of the CMFO algorithm proposed,SOA,BFOA and MFO algorithms are introduced under the same condition for comparative experiments. The experimental results show that CMFO can effectively improve the optimal performance of MFO,and has better applicability and advantages for knee MRI image segmentation. [ABSTRACT FROM AUTHOR]

In order to improve the tracking efficiency of manipulator tracking dynamic target,this paper proposed a fast tracking strategy of uncalibrated visual servo systems. On the one hand,by predicting the joint angle of the manipulator motion,the controller’s calculating behavior can be carried out in parallel with the manipulator’s moving behavior. On the other hand,the strategy uses the latest image information to calculate the joint angle,which improves the real-time performance of the system. In the simulation and physical experiments,two uncalibrated visual servo systems with different tracking strategy algorithms are constructed to track dynamic target.Finally,the fast, real-time and anti-jamming performance of the strategy are verified by comparing tracking time and tracking path. [ABSTRACT FROM AUTHOR]

Ａｍｏｎｇ ｔｈｅ ｍｅｔｈｏｄｓ ｆｏｒ ｍｏｄｅｌｉｎｇ ｇｅｎｅ ｒｅｇｕｌａｔｉｏｎ ｎｅｔｗｏｒｋｓꎬ Ｂａｙｅｓｉａｎ ｎｅｔｗｏｒｋ ｍｏｄｅｌ ｃａｎ ｉｎｔｕｉｔｉｖｅｌｙ ｅｘｐｒｅｓｓ ｔｈｅ ｒｅｇｕｌａｔｏｒｙ ｒｅｌａｔｉｏｎｓｈｉｐ ｂｅｔｗｅｅｎ ｇｅｎｅｓ. Ｈｏｗｅｖｅｒꎬ ｄｕｅ ｔｏ ｔｈｅ ｈｉｇｈ ｃｏｍｐｌｅｘｉｔｙ ｏｆ Ｂａｙｅｓｉａｎ ｎｅｔｗｏｒｋ ｍｏｄｅｌ ｉｎ ｔｈｅ ｓｔｒｕｃｔｕｒｅ ｌｅａｒｎｉｎｇꎬ ｔｈｅ ｅｆｆｉｃｉｅｎｃｙ ｏｆ ｔｈｅ ｇｅｎｅ ｒｅｇｕｌａｔｉｏｎ ｎｅｔｗｏｒｋｓ ｍｏｄｅｌｉｎｇ ｉｓ ｌｏｗ ａｎｄ ｔｈｅ ｓｃａｌｅ ｏｆ ｔｈｅ ｒｅｃｏｎｓｔｒｕｃｔｅｄ ｎｅｔｗｏｒｋ ｉｓ ｌｉｍｉｔｅｄ. Ｔｈｅｒｅｆｏｒｅꎬ ｔｈｉｓ ｐａｐｅｒ ｐｒｏｐｏｓｅｄ ａ ｍｅｔｈｏｄ ｗｈｉｃｈ ｉｓ ｃａｌｌｅｄ ｔｈｅ ｐａｒｅｎｔ ｎｏｄｅ ｓｃｒｅｅｎｉｎｇ￣ｂａｓｅｄ Ｂａｙｅｓｉａｎ ｎｅｔｗｏｒｋ(ＰＳ￣ＢＮ). Ｔｈｅ ＰＳ￣ＢＮ ｍｅｔｈｏｄ ｃｏｍｂｉｎｅｓ ｔｈｅ ｃｏｒｒｅｌａｔｉｏｎ ｍｏｄｅｌ ｗｉｔｈ Ｂａｙｅｓｉａｎ ｎｅｔｗｏｒｋ ｍｏｄｅｌ. Ｕｎｄｅｒ ｔｈｅ ｐｒｅｍｉｓｅ ｏｆ ｍａｋｉｎｇ ｆｕｌｌ ｕｓｅ ｏｆ ｔｈｅ ｓｅａｒｃｈ ｓｔｒａｔｅｇｙ ｏｆ ｓｔｒｕｃｔｕｒｅ ｌｅａｒｎｉｎｇ ｉｎ Ｂａｙｅｓｉａｎ ｎｅｔｗｏｒｋ ｍｏｄｅｌꎬ ｔｈｅ ｐａｒｅｎｔ ｎｏｄｅ ｓｃｒｅｅｎｉｎｇ ｍｅｔｈｏｄ ｉｓ ｕｓｅｄ ｔｏ ｒｅｍｏｖｅ ｓｏｍｅ ｒｅｄｕｎｄａｎｔ ｎｏｄｅｓꎬ ｔｈｕｓ ｒｅｄｕｃｉｎｇ ｔｈｅ ｓｅａｒｃｈ ｓｐａｃｅ. Ｔｈｅ ｅｘｐｅｒｉｍｅｎｔａｌ ｒｅｓｕｌｔｓ ｓｈｏｗ ｔｈａｔ ｃｏｍｐａｒｅｄ ｗｉｔｈ ｔｈｅ Ｂａｙｅｓｉａｎ ｎｅｔｗｏｒｋ ｍｏｄｅｌꎬ ｔｈｅ ＰＳ￣ＢＮ ｍｅｔｈｏｄ ｇｒｅａｔｌｙ ｉｍｐｒｏｖｅｓ ｔｈｅ ｅｆｆｉｃｉｅｎｃｙ ｏｆ ｍｏｄｅｌｉｎｇ ｇｅｎｅ ｒｅｇｕｌａｔｏｒｙ ｎｅｔｗｏｒｋｓ ｗｈｉｌｅ ｉｍｐｒｏｖｉｎｇ ｔｈｅ ａｃｃｕｒａｃｙ. [ABSTRACT FROM AUTHOR]

Ｔｈｅ ｃｏｒａｌ ｒｅｅｆ ａｌｇｏｒｉｔｈｍ ｈａｓ ｔｈｅ ｄｉｓａｄｖａｎｔａｇｅｓ ｏｆ ｂｅｉｎｇ ｅａｓｙ ｔｏ ｆａｌｌ ｉｎｔｏ ｌｏｃａｌ ｏｐｔｉｍｕｍ ａｎｄ ｌｏｗ ｐｒｅｃｉｓｉｏｎ. Ｉｎ ｖｉｅｗ ｏｆ ｔｈｅ ｓｈｏｒｔｃｏｍｉｎｇｓ ｏｆ ｃｏｒａｌ ｒｅｅｆ ａｌｇｏｒｉｔｈｍꎬ ｔｈｉｓ ｐａｐｅｒ ｐｒｏｐｏｓｅｓ ａｎ ｉｍｐｒｏｖｅｄ ｃｏｒａｌ ｒｅｅｆ ａｌｇｏｒｉｔｈｍ. Ｂｙ ｒｅｆｅｒｒｉｎｇ ｔｏ ｐａｒｔｉｃｌｅ ｓｗａｒｍ ｏｐｔｉｍｉｚａｔｉｏｎꎬ Ｇａｕｓｓｉａｎ ｍｕｔａｔｉｏｎ ａｎｄ ｓｉｍｕｌａｔｅｄ ａｎｎｅａｌｉｎｇ ａｌｇｏｒｉｔｈｍꎬ ｔｈｉｓ ａｌｇｏｒｉｔｈｍ ｉｍｐｒｏｖｅｓ ｔｈｅ ｂｒｏａｄｃａｓｔ ｓｐａｗｎｉｎｇꎬ ａｓｅｘｕａｌ ｒｅｐｒｏｄｕｃｔｉｏｎ ａｎｄ ｓｅｔｔｉｎｇ(ｒｅｐｌａｃｅｍｅｎｔ)ｍｅｃｈａｎｉｓｍｓ ｏｆ ｃｏｒａｌ ｒｅｅｆ ａｌｇｏｒｉｔｈｍꎬ ｗｈｉｃｈ ｇｒｅａｔｌｙ ｉｍｐｒｏｖｅｓ ｔｈｅ ｏｐｔｉｍｉｚａｔｉｏｎ ｐｒｅｃｉｓｉｏｎ ｏｆ ｔｈｅ ａｌｇｏｒｉｔｈｍ ａｎｄ ｃａｎ ｊｕｍｐ ｏｕｔ ｏｆ ｔｈｅ ｌｏｃａｌ ｏｐｔｉｍｕｍ. Ｉｎ ｔｈｅ ｓｉｍｕｌａｔｉｏｎ ｅｘｐｅｒｉｍｅｎｔꎬ ｔｈｅ ｉｍｐｒｏｖｅｄ ｃｏｒａｌ ｒｅｅｆ ａｌｇｏｒｉｔｈｍ ｉｓ ｒｅｓｐｅｃｔｉｖｅｌｙ ｃｏｍｐａｒｅｄ ｗｉｔｈ ｔｅｎ ａｌｇｏｒｉｔｈｍｓ ｓｕｃｈ ａｓ ｂａｓｉｃ ｃｏｒａｌ ｒｅｅｆ ａｌｇｏｒｉｔｈｍ ａｎｄ ｐａｒｔｉｃｌｅ ｓｗａｒｍ ａｌｇｏｒｉｔｈｍ ｉｎ ｈｉｇｈ￣ｄｉｍｅｎｓｉｏｎａｌ ａｎｄ ｌｏｗ￣ｄｉｍｅｎｓｉｏｎａｌ ｔｅｓｔ ｆｕｎｃｔｉｏｎｓ. Ｔｈｅ ｅｘｐｅｒｉｍｅｎｔａｌ ｒｅｓｕｌｔｓ ｓｈｏｗ ｔｈａｔ ｔｈｅ ｉｍｐｒｏｖｅｄ ｃｏｒａｌ ｒｅｅｆ ａｌｇｏｒｉｔｈｍ ｈａｓ ｂｅｔｔｅｒ ｃｏｎｖｅｒｇｅｎｃｅ ｒａｔｅ ａｎｄ ａｃｃｕｒａｃｙ ｔｈａｎ ｏｔｈｅｒ ａｌｇｏｒｉｔｈｍｓꎬ ｗｈｉｃｈ ｃａｎ ｓｔｉｌｌ ｂｅ ｍａｉｎｔａｉｎｅｄ ｉｎ ｔｈｅ ｈｉｇｈ￣ｄｉｍｅｎｓｉｏｎａｌ ｔｅｓｔ ｆｕｎｃｔｉｏｎｓ. [ABSTRACT FROM AUTHOR]

Ｃｅｎｔｒａｌ ａｏｒｔｉｃ ｐｒｅｓｓｕｒｅ ｗａｖｅ(ＣＡＰＷ)ｃａｎ ｂｅ ｒｅｃｏｎｓｔｒｕｃｔｅｄ ｂｙ ｄｉｆｆｅｒｅｎｔ ｐｅｒｉｐｈｅｒａｌ ａｒｔｅｒｙ ｐｒｅｓｓｕｒｅ ｗａｖｅｓ ( ＰＡＰＷ ) ｎｏｎ￣ｉｎｖａｓｉｖｅｌｙ ｕｓｉｎｇ ｂｌｉｎｄ ｓｙｓｔｅｍ ｉｄｅｎｔｉｆｉｃａｔｉｏｎ ｔｅｃｈｎｏｌｏｇｙꎬ ｂｕｔ ｔｈｅ ｓｅｌｅｃｔｉｏｎ ｏｆ ｐｅｒｉｐｈｅｒａｌ ａｒｔｅｒｉｅｓ ｒｅｍａｉｎｓ ａ ｓｅｒｉｏｕｓ ｐｒｏｂｌｅｍ. Ｉｎ ｔｈｉｓ ｐａｐｅｒꎬ ａｎ ａｏｒｔｉｃ ｐｒｅｓｓｕｒｅ ｗａｖｅ ｒｅｃｏｎｓｔｒｕｃｔｉｏｎ ａｌｇｏｒｉｔｈｍ ｂａｓｅｄ ｏｎ ｓｕｂｓｐａｃｅ ｍｅｔｈｏｄ ｈａｓ ｂｅｅｎ ｕｓｅｄ. Ｒａｄｉａｌ ｐｒｅｓｓｕｒｅ ｗａｖｅｓ ａｎｄ ｄｏｒｓａｌ ｐｅｄａｌ ａｒｔｅｒｙ ｐｒｅｓｓｕｒｅ ｗａｖｅｓ ａｒｅ ｃｏｌｌｅｃｔｅｄ ｆｏｒ ｒｅｃｏｎｓｔｒｕｃｔｉｏｎ. Ｔｈｅ ａｏｒｔｉｃ ｐｒｅｓｓｕｒｅ ｗａｖｅ ｉｓ ｒｅｃｏｎｓｔｒｕｃｔｅｄ ｄｙｎａｍｉｃａｌｌｙ ｔｈｒｏｕｇｈ ｆｏｕｒ ｄｉｆｆｅｒｅｎｔ ｃｏｍｂｉｎａｔｉｏｎｓꎬ ａｎｄ ｔｈｅ ｒｅｓｕｌｔｓ ａｒｅ ａｓｓｅｓｓｅｄ ｂｙ ｄｙｎａｍｉｃ ｔｉｍｅ ｗａｒｐｉｎｇ. Ｔｈｅ ｏｐｔｉｍａｌ ｃｏｍｂｉｎａｔｉｏｎ ｏｆ ｐｅｒｉｐｈｅｒａｌ ａｒｔｅｒｉａｌ ｗａｖｅｓ ｉｓ ａｌｓｏ ｄｅｔｅｒｍｉｎｅｄ. Ｔｈｅ ｒｅｓｕｌｔｓ ｓｈｏｗ ｔｈａｔ ａｎｙ ｃｏｍｂｉｎａｔｉｏｎ ｏｆ ｔｈｅ ｄｏｒｓａｌ ａｎｄ ｒａｄｉａｌ ａｒｔｅｒｉｅｓ ｐｒｅｓｓｕｒｅ ｗａｖｅ ｈａｓ ｎｏ ｓｉｇｎｉｆｉｃａｎｔ ｅｆｆｅｃｔ ｏｎ ｔｈｅ ｒｅｃｏｎｓｔｒｕｃｔｉｏｎ ｏｆ ａｏｒｔｉｃ ｐｒｅｓｓｕｒｅ ｗａｖｅ ( Ｐ > ０􀆰 ５ ). Ｈｏｗｅｖｅｒꎬ ｔｈｅ ｒｅｃｏｎｓｔｒｕｃｔｉｏｎ ｃａｎｎｏｔ ｂｅ ａｃｈｉｅｖｅｄ ｂｙ ｏｎｌｙ ｕｓｉｎｇ ｔｈｅ ｒａｄｉａｌ ｐｒｅｓｓｕｒｅ ｗａｖｅｓ ｏｒ ｔｈｅ ｄｏｒｓａｌ ｐｅｄａｌ ｐｒｅｓｓｕｒｅ ｗａｖｅｓ. [ABSTRACT FROM AUTHOR]

Tｈｉｓ ｐａｐｅｒ ｐｒｏｐｏｓｅｓ ａｎ ａｌｇｏｒｉｔｈｍ ｂａｓｅｄ ｏｎ ｏｒｉｅｎｔａｔｉｏｎ ｓｃｏｒｅｓ ｃｏｍｂｉｎｅｄ ｗｉｔｈ Ｆｒａｎｇｉ ｆｉｌｔｅｒ ｔｏ ｆｉｘ ｔｈｅ ｄｉｆｆｉｃｕｌｔｉｅｓ ｃａｕｓｅｄ ｂｙ ｂｉｆｕｒｃａｔｉｏｎ ａｎｄ ｃｒｏｓｓｉｎｇｓ ｏｆ ｒｅｔｉｎａｌ ｖｅｓｓｅｌｓ. Ｔｈｅ Ｆｒａｎｇｉ ｆｉｌｔｅｒꎬ ｗｈｉｃｈ ｉｓ ｃｏｎｓｔｒｕｃｔｅｄ ｂｙ Ｈｅｓｓｉａｎ ｍａｔｒｉｘ ａｎｄ ｓｕｉｔａｂｌｅ ｆｏｒ ｆｉｌｔｅｒｉｎｇ ｔｈｅ ｌｉｎｅａｒ ｏｂｊｅｃｔꎬ ｉｓ ｕｓｅｄ ｔｏ ｅｎｈａｎｃｅ ｔｈｅ ｃｏｎｔｒａｓｔ ｏｆ ｔｈｅ ｂｌｏｏｄ ｖｅｓｓｅｌｓ. Ｔｈｅ ａｎｉｓｏｔｒｏｐｙ ａｎｄ ｏｒｔｈｏｇｏｎａｌｉｔｙ ｏｆ ｔｈｅ ｃａｋｅ ｗａｖｅｌｅｔ ｉｎ ｔｈｅ ｏｒｉｅｎｔａｔｉｏｎ ｓｃｏｒｅｓ ａｒｅ ｕｓｅｄ ｔｏ ｆｉｌｔｅｒ ｔｈｅ ｂｌｏｏｄ ｖｅｓｓｅｌｓ ｉｎ ｍｕｌｔｉｐｌｅ ａｎｇｌｅｓ ａｎｄ ｄｉｒｅｃｔｉｏｎｓꎬ ｗｈｉｃｈ ｉｓ ｂｅｎｅｆｉｃｉａｌ ｔｏ ｔｈｅ ｐｒｏｃｅｓｓｉｎｇ ｏｆ ｄｅｔａｉｌｓ ａｎｄ ｔｈｅ ｃｏｍｐｌｅｔｅ ｓｅｇｍｅｎｔａｔｉｏｎ ｏｆ ｔｈｅ ｒｅｔｉｎａｌ ｖａｓｃｕｌａｒ ｎｅｔｗｏｒｋ. Ｔｈｅ ｃｏｍｐａｒｉｓｏｎ ｏｆ ｔｈｅ ｍｅｔｈｏｄ ｐｒｏｐｏｓｅｄ ｗｉｔｈ ｏｔｈｅｒ ｅｘｉｓｔｉｎｇ ｍｅｔｈｏｄｓ ｓｈｏｗｓ ｔｈａｔ ｔｈｅ ａｌｇｏｒｉｔｈｍ ｉｓ ｂｅｔｔｅｒ ｔｈａｎ ｏｔｈｅｒ ａｌｇｏｒｉｔｈｍｓ ｉｎ ｐｒｏｃｅｓｓｉｎｇ ｔｈｅ ｂｉｆｕｒｃａｔｉｏｎ ａｎｄ ｃｒｏｓｓｉｎｇｓꎬ ａｎｄ ｔｈｅ ｍｅａｓｕｒｅｍｅｎｔｓ ｏｆ ａｃｃｕｒａｃｙꎬ ｓｅｎｓｉｔｉｖｉｔｙ ａｎｄ ｓｐｅｃｉｆｉｃｉｔｙ ａｒｅ ｓｕｐｅｒｉｏｒ ｔｏ ｅｘｉｓｔｉｎｇ ａｌｇｏｒｉｔｈｍｓ. [ABSTRACT FROM AUTHOR]

To investigate the grinding surface quality of unidirection carbon fiber-reinforced ceramic matrix composites(Cf/SiC)， the orthogonal experiments were carried out by using resin-bonded diamond grinding wheel. In order to achieve the influence order of grinding wheel linear speed， grinding depth and feed speed on grinding surface quality， range analysis was adopted in this paper. The results indicate that: the grinding depth has maximum impact on the machining surface roughness; as the raises of grinding depth， the grinding surface roughness increases; as the raises of grinding wheel linear speed， the grinding surface roughness decreases; as the raises of feed speed， the grinding surface roughness increases. According to the result of orthogonal experiments， the best combination of grinding parameters was achieved. Based on the experiment results and surface topography， the grinding mechanisms of unidirection Cf/SiC were further analyzed， which supplies some useful technical reference for revaling the grinding mechanisms of unidirection Cf/SiC. [ABSTRACT FROM AUTHOR]

The ball screw feed drive system of CNC(computerized numerical control)machine tools is characterized as multi-heat sources with strong time-varying heat rate. But the past work was scarely focused on the time-varying of the heat sources. This fact results in inaccuracy of predicting temperature rise and thermal error of the screw. In this paper， the heat rates of the multi-heat sources were captured by virtue of the FEM integrated with Monte Carlo method. Consequently， relationship of the ratio of each heat source to the total heat rate of the system with the running time was obtained. Then， based on heat ratios of the heat sources， the heat rates of the heat sources were determined using torque current of the servo motor in the ball screw feed drive system. Finally， numeric prediction model of temperature rise and thermal error of the screw was put forward based on finite difference method of one-dimension heat conduction equation， and the accuracy of the prediction method was verified by experimental results. [ABSTRACT FROM AUTHOR]

Appearance and scale change are the difficulties of pedestrian tracking. To solve the problem of multi-scale pedestrian tracking is the key factor to enhance the practicability of the algorithm. On the basis of KCF(kernel correlation filter) algorithm，this paper uses multiple correlation filters(such as head and hip)to assist the tracking of the body trunk filter. The distance change rate which is obtained by comparing the distance between the pedestrian’s head and hip of every image frame(except the first frame)with the initial frame is used to zoom the search area， so as to avoid inaccurate target location and time waste. By adjusting the size of the target’s bounding box， the problem of target’s template shift caused by gradual change of the target template including background features or local features is solved. The experiment is conducted on eighteen pedestrian scene video sequences with obvious scale changes in VOT2016 dataset， and the experimental results show that the algorithm proposed has higher tracking accuracy. [ABSTRACT FROM AUTHOR]

In view of the crowd evacuation exit selection strategy question of complex buildings， this paper focuses on the cognitive difference of pedestrians in the synthetic shortest distance. The mixed distance strategy is established by introducing the distance factor and density factor， and combined with the modified background field modeling rules. The exit selection strategy is integrated into the particle swarm updating mechanism， and the exit selection strategy based on particle swarm optimization with background field is established. The evacuation performance of exit selection strategy is simulated by numerical experiments. The experimental results reveal the mechanism of group movement in multi-exit buildings， and reflect the dynamic adjustment performance of the evacuation strategy. The simulated evacuation process verifies the rationality and effectiveness of the multi-exit selection of the mixed distance strategy in group evacuation. [ABSTRACT FROM AUTHOR]

Sunshine has played a critical role in trajectory analysis. It is of great significance to design an algorithm that could not only estimate the sunshine information of the trajectory effectively, but also remove the redundant points and keep the necessary sunshine-based information. This paper proposes a sunshine based trajectory simplification algorithm, which considers the urban trajectory character, to solve the challenges of trajectory analyzing in various sunshine related scenarios. On the one hand, an orientation model is established to abstract the relationship between trajectory and sunlight. On the other hand, a sunshine related trajectory simplification model is proposed, and the genetic algorithm is applied to find the points that need to be reserved. Finally, the real-world data of Minneapolis, US, is used for experiment. The results demonstrate that the proposed algorithm can effectively reduce the number of turning points in the trajectories under the control of bound Tmax. [ABSTRACT FROM AUTHOR]

This paper proposed a synchronous processing method using random noise suppression and high-frequency compensation for GPR data in curvelet domain. First, the GPR data were transformed into curvelet domain in order to use its multi-angle and multi-scale sparsity. The random noise thus could be suppressed by the adaptive threshold function changed with angle and scale. Second, according to the propagation laws of electromagnetic waves in elastic medium and the curvelet multi-scale feature, the time-varying compensation factor could be calculated so as to inverse weighting the corresponding scale and angle for compensation of the high-frequency absorption. Finally, inverse curvelet transformation was conducted thus the GPR data after random noise suppression and high-frequency compensation could be obtained. This method is totally a data-driven method thus can overcome the influence from artificial factors in traditional method. [ABSTRACT FROM AUTHOR]

In order to solve the problem of peak-to-average power ratio of optical orthogonal frequency division multiplexing system, a partial transmission sequence algorithm based on correlation analysis is proposed. By analyzing the correlation among the alternative signals, the algorithm classifies the strong correlation signal and the weak correlation signal, and searches the strong correlation signal selectively and the weak correlation signal completely, thus reducing the searching times on the whole. In addition, this paper optimizes the phase factor weighting process by analyzing the relationship between alternative phase factor sequences. The simulation results show that the peak-to-average power ratio of the system can be improved effectively under the three segmentation states. Especially in the interleaved segmentation state, the proposed algorithm is compared with the traditional partial transmission sequence algorithm. The proposed algorithm is with no-performance loss of peak-to-average power ratio, and the computational complexity is greatly reduced. [ABSTRACT FROM AUTHOR]

To resist the influence of the malicious attacks and the malfunctions of fault nodes in wireless sensor networks (WSNs) on data aggregation, this paper proposes an algorithm of trust-based secure data aggregation for WSNs. The algorithm is based on multi-layer non-uniform clustering network topology to achieve secure data aggregation, which can effectively balance the network energy consumption. The trust evaluation model is established based on the communication behavior and data correlation among the nodes. The dynamic trust integration mechanism and update mechanism are introduced to realize the trust evaluation intra-cluster and inter-cluster. Based on the trust value, a trusted aggregation node is chosen in the cluster to complete data fusion of trusted nodes. Simulation results show that the algorithm can achieve accurate and effective trust evaluation, identify internal malicious nodes, and obtain the data aggregation results with high accuracy. [ABSTRACT FROM AUTHOR]

This paper establishes an intelligent big data storage system IHDFS, based on the existing open source distributed file storage system HDFS. The system proposes and implements big data de-duplication module, big data placement module, big data intelligent migration module, and big data encoding module, which improves the efficiency of user visits and saves the storage space of the cluster. Experimental results show that the data de-duplication module can save the storage space. The data placement module provides a reasonable distribution of file upload storage layer, which twice the uploading speed; the data intelligent migration module improves the hit rate of files on the upper storage layer, which improves the efficiency of obtaining data; the data encoding module saves the storage space of the cluster about one third of the original. [ABSTRACT FROM AUTHOR]

Due to its good particles trapping properties， filter screen is widely used in industrial or civil fields. However， the research on its micro-capture mechanism is still limited. In this paper， a set of microscopic observation system was set up to record the whole process of filter screen trapping particles. The microscopic performance of the process of particles trapping was studied. The influencing factors that affect single fiber filtration and mesh bridging blockage were analyzed. The results show that with the increase of filtration velocity， the ratio of unblocked pore area to total pore area gradually decreases， and eventually a stable state will appear. With the increase of mesh number， the ratio gradually decreases. In the actual application， the filtration velocity and filter screen pore size should be properly selected according to the specific conditions of use. The filter screen should be cleaned in time to avoid secondary pollution. [ABSTRACT FROM AUTHOR]

Using the high voltage industrial frequency current to heat oil shale， the plasma channels can be formed in oil shale. The in-situ cracking of oil shale is realized by heating the oil shale with the generated plasma and the carbonized inner surface of the conductive channel. In this paper， a three-dimensional coupled model of oil shale was established by finite element analysis software， and the distribution of temperature field during the high frequency oil shale pyrolysis was obtained by numerical calculation. When the voltage is 1000V and the current is 5A， the temperature at the center of electrode， after 6 minutes heating， reached 597℃， and the temperature at the areas around the electrode 30mm away reached 347℃， meeting the pyrolysis demand of oil shale. With the increase of current， the increased temperature of oil shale during the same heating time showed a steady rise， and the range of effective pyrolysis also went up. According to the results of numerical simulation， using the high voltage industrial frequency to heat oil shale can gain a fast heating rate and high energy efficiency. [ABSTRACT FROM AUTHOR]

The wheel-workpiece contact zone is changed due to point grinding inclining angle α and novel grinding wheel with coarse grinding area angle θ. It changes from line contact into point contact in theory and the grinding zone temperature is also changed. In this paper，the grinding zone temperature is simulated by the finite element method. The orthogonal experiments L16(45)was designed and thermocouple measurement was used for grinding experiments. Through range analysis， primary and secondary factors affecting grinding temperature is that coarse grinding area angle θ>cutting depth a○p>inclining angle α>axial feeding speed vf>grinding wheel speed vs. The optimum parameters combination of reducing the grinding zone temperature is that θ(20°)， ap(0.01mm)，α(1°)，vf(0.6mm/min)，vs(35m/s). Finally，by means of single factor experiments， the correctness of the simulation was verified and the influence of each parameter on grinding zone temperature was deeply analyzed. [ABSTRACT FROM AUTHOR]

The braking performance of MRB(magneto-rheological brake)based on braking controller was mainly explored in this paper. The main research contents included design and structural optimization to obtain the optimum MRB. In order to study its braking performance，the MRB controller was designed based on the Arduino board and the L9349 power driver IC. Deceleration experiment and braking torque following experiment with different step signals and sine signal were carried out for exploring braking performance. The results indicate that the MRB′s response time is about 40ms，the delay time is about 70ms，and the lag braking time is about 20ms in the following process that was faster than that of the hydraulic braking system. This study may has great significance with laying a foundation for the development and application of MRB. [ABSTRACT FROM AUTHOR]

Lightweight of driving axle housing is of great importance to enhance load capacity and reduce production cost. In this paper， multi-objective optimal model was built on the basis of finite element and fatigue analysis of driving axle housing. The orthogonal test table was established as parametric design of driving axle housing. The fatigue robustness and lightweight of the driving axle housing were optimized by Taguchi method and comprehensive evaluation method. The optimization result shows that this method can be applied to the multi-objective optimization of driving axle housing. The optimized driving axle housing has a better performance in fatigue robustness with light weight. The material of driving axle housing is saved， the production and operating cost is reduced， and the design level is thus improved. [ABSTRACT FROM AUTHOR]

Considering that the industrial process of reheating furnace is with the characteristics of complexity， non-linearity and time delay， and the prediction of billet temperature is difficult to achieve， an improved principal component regression(PCR)and prediction method based on data features is proposed in this paper. The time-delay among different variables is solved at first by synchronization of the original data. Then statistic and entropy features are extracted from each billet of reheating furnace and these data features consist of a data feature vector orderly. Lastly， the prediction model between billet outlet temperature and data features of process variable is established by PCR. The proposed method is applied in the reheating furnace of a real steel factory， and the model parameter is reckoned based on actual operational data. The experiment results and error analysis indicate that this model is able to predict the billet steel outlet temperature， and the prediction error can satisfy the demands of industrial application. [ABSTRACT FROM AUTHOR]

Induced caving is a new underground mining method， which contributes to the smooth connection of ore production during the transition from open pit to underground. However， large scale of slope failure can be triggered when mining hanging-wall ores by this method， which would pose a threat to the open-pit mining， the open-pit transportation system and the surface infrastructure. The discontinuous geological structure of the rock mass is a key factor for slope stability. In this paper， the discontinuous deformation analysis(DDA)was used to study the slope failure process caused by hanging-wall-ore mining excavated by the induced caving method in different rock mass structures. Three slope failure modes， namely， sliding， toppling and complex failures， were concluded based on seven models with different rock mass structures， leading to different failure modes. A case of slope failure was analyzed based on Hainan iron mine. This study provides some technical supports for mining design of induced caving， as well as risk prediction and prevention of slope failure. [ABSTRACT FROM AUTHOR]

Most of the traditional community detection algorithms cannot balance partitioning effect and complexity well. So， this paper presents a new evaluation standard of single community called group density. Based on the group density， a community detection algorithm based on agglomeration is proposed. The algorithm continues to integrate small communities， and makes the community structure of the network develop in the direction of maximizing average group density. Modularity is employed to detect the partitioning effect of the algorithm. Experimental results demonstrate that the new algorithm outperforms the traditional GN， Fast Newman， LPA algorithms in multiple data sets， which shows that the algorithm proposed has better partitioning effect and lower time complexity. [ABSTRACT FROM AUTHOR]

Based on convolutional neural networks， this paper proposes innovative ideas for diagnosing intracranial tissue and organ diseases. The images of Parkinson’s disease patients were preprocessed by gray mapping， histogram equalization， improved wavelet denoising and image enhancement. A convolutional neural network is designed and built on the basis of VGG-Net network model. Regularization strategy is adopted to avoid over-fitting problem. Then the ten-fold cross-validation of the network model is carried out five times with MRI image set of patients. And feature visualization is performed by deconvolution network to dig out latent features of diseases. The result and objective evaluation show that the network can make a good diagnosis of MRI image for Parkinson’s disease. [ABSTRACT FROM AUTHOR]

Interactive data exploration(IDE) is a key technique in a diverse set of discovery-based applications, which focuses on interaction, exploration and discovery and has a wide range of applications in many scenes and areas. The feature adaptive technology of interactive data exploration was studied in this paper with the background of massive academic literature data exploration. Firstly, a framework of interactive data exploration was presented, namely FA-IDE(feature-adaptive interactive data exploration) framework, which can dynamically adjust the subset of features during each iteration to meet the needs of the user’ s interest diversity. Secondly, according to this framework, the evaluation criteria of the balance of feature subsets(BFS) were proposed in the stage of exploration and a sequence forward feature selection algorithm based on BFS was also given. Besides, for the phases of related sample discovery, a division level establishment method was proposed. According to the decision tree model which can divide the user interest area, a strategy of result set sorting based on similarity was proposed. The results of experiments showthat the accuracy and efficiency of the proposed method have been effectively improved. [ABSTRACT FROM AUTHOR]

Random noise contained in the mine micro-seismic signal has serious interference to the micro-seismic monitoring and the accurate positioning of the micro-seismic source. According to the previous research and the actual application effects， the paper proposed a new denoising method with the hierarchical adaptive threshold based on the characteristics of mine micro-seismic signals. It adds the layered adaptive factors to the hierarchical threshold. According to the low frequency characteristic of the mine micro-seismic effective signal， the noise signal of the high frequency part is removed greatly by using the layered adaptive factor to improve the signal to noise ratio of the mine micro-seismic signal. And the signal of the low frequency part is maximally kept. The validity and superiority of the method are illustrated by comparing the hierarchical threshold with the real-field micro-seismic data. [ABSTRACT FROM AUTHOR]

Aiming to solve the problem of “hot lower part and cool upper part” in blast furnace with oxygen enrichment blowing， this work has developed a model considering necessary conditions in practice to calculate the heat balances of both the high- and low-temperature zones respectively. The model is expected to study the variation of thermal state of blast furnace and the possible corresponding countermeasures in oxygen enrichment blowing operation. This paper describes the process of model development and validation through comparing with practical production data. The result under conditions of the base case shows that， when oxygen enrichment ratio increases by 1%， the top gas temperature decreases by 14℃. For the operation with an oxygen enrichment rate of 1.7%， the heat balances of both high-and low-temperature zones can be ensured with no additional countermeasures. Besides， the difference between the theoretical minimum direct reduction degree calculated by this model and the reduction degree acquired in practice proves that there is still some room to further reduce the fuel rate in blast furnace ironmaking. [ABSTRACT FROM AUTHOR]

The paper mainly researches how to improve sound source localization effects in indoor environments with complex noise and serious reverberation. Firstly， the signal model of the indoor microphone array is analyzed and a suitable array topology is established. Secondly， a lot of parameters of the filter in the cepstral domain are determined optimally by simulation. Then， the generalized cross-power spectrum phase is proposed to make the peak value more obvious. In addition， many weight functions are simulated and compared in Matlab to further improve the accuracy of sound source localization. Finally， the proposed algorithm is verified. The result shows that the localization success rate is up to 80% when the angle error and distance error of the improved algorithm are ±10°and ±15cm， respectively. [ABSTRACT FROM AUTHOR]

This paper proposes a searchable encryption model for graph data to address the problem that most of the current searchable encryption schemes cannot deal with complex data structures. The algorithms and security models of the scheme are described. Taking the encryption index of matrix structure into account， the detailed description of the searchable encryption scheme for graph data that supports adjacency queries is presented. The scheme utilizes pseudo-random functions and pseudo-random permutations to protect the privacy of the graph data and the encrypted index. Real models and ideal models test the security of the scheme. Compared with traditional searchable encryption schemes， the proposed scheme has more flexible searching ability and higher efficiency， which promotes broader application under big data environment. [ABSTRACT FROM AUTHOR]

The efficiency of traditional user-based collaborative filtering (user-based CF) recommendation algorithm is reduced with data increasing. This paper proposes a recommendation algorithm based on community detection (RACD) in bipartite networks by introducing bipartite network community detection theory into user-based CF recommendation algorithm. Firstly， the user-item rating matrix is mapped into user-item bipartite network. Then， the community information of each user is obtained by using RACD to divide the user-item network. Finally， the items are recommended to the target user according to other users in the same community. Experiments on real-world classic network datasets show that the RACD can effectively improve real-time recommendation efficiency of the recommendation system. [ABSTRACT FROM AUTHOR]

Aiming at the problems of data confidentiality and user’s privacy leakage in cloud， this paper proposes an efficient and secure cloud storage scheme with hidden access patterns. Firstly， the files are divided into data blocks with fixed sizes， and encrypted by pseudo-random functions and collision-resistant Hash functions. Then， in order to construct the secure cloud storage structure， the blocks are uploaded into pseudo-random collection superset in the cloud server. Meanwhile， a two-round access strategy that hides the access patterns， reduces the storage cost and access interaction is designed. Security analysis shows that the proposed scheme achieves L1L2-dynamic adaptive security. Experimental results show that the proposed scheme can not only protect data confidentiality， but also be more suitable for the actual cloud storage. [ABSTRACT FROM AUTHOR]

Aiming at the existing shortcomings of outsourced database schemes including heavy temporal and spatial cost， low efficiency for query and update， and lack of the support for the complete verification of multiple SQL query results， this paper proposes a publicly verifiable outsourced database model supporting full operations. The formal definition and security definition are presented. On the basis of the model， a publicly verifiable outsourced database scheme， composed of three entities， is constructed using bilinear mapping accumulator and authenticated skip list. Also， the implement and the communication are described in detail. Finally， the security and efficiency are analyzed， respectively， which shows that the proposed scheme is with unforgeability and high efficiency. [ABSTRACT FROM AUTHOR]

In order to eliminate the vibration of the rotor system， a tension string-permanent magnet dynamic vibration absorber is designed for the rotating machinery. The frequency adjustability of the vibration absorber is realized by using the adjustable tension-stiffness feature of the tension string， and the structure of the vibration absorber is separated from the rotor system by a stiffness institution which is made with permanent magnets. In this paper， the dynamical model and the simulation analysis of the rotor-dynamic vibration absorber is built，the operating characteristic of the vibration absorber is studied， and the correctness of the theoretical research is proved by the experimental study. The results proved that the vibration absorber has good effect on eliminating the vibration of the rotor system， and the absorbing function becomes better and more stable as the inter-distance of the magnets is set closer. [ABSTRACT FROM AUTHOR]